From 013813e994f566dc605cba3b402ef65d8943e6aa Mon Sep 17 00:00:00 2001 From: arno756 Date: Fri, 29 Sep 2023 09:11:49 -0700 Subject: [PATCH 01/24] Create readme --- notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme | 1 + 1 file changed, 1 insertion(+) create mode 100644 notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme new file mode 100644 index 00000000..8b137891 --- /dev/null +++ b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme @@ -0,0 +1 @@ + From 997eb08da9cb64cdb6ad93a5371922878e907c7e Mon Sep 17 00:00:00 2001 From: arno756 Date: Fri, 29 Sep 2023 09:12:14 -0700 Subject: [PATCH 02/24] Add files via upload --- ...ild-LLM-Apps-that-can-See-Hear-Speak.ipynb | 669 ++++++++++++++++++ .../meta.toml | 8 + 2 files changed, 677 insertions(+) create mode 100644 notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb create mode 100644 notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb new file mode 100644 index 00000000..a8636d78 --- /dev/null +++ b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb @@ -0,0 +1,669 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "215c4617-6ebd-43fc-aa25-904fec4bdf5e", + "metadata": { + "language": "python" + }, + "source": "# How to Build LLM Apps that can See, Hear, Speak" + }, + { + "cell_type": "markdown", + "id": "a2a7fa17-ff2a-4abf-922d-af00514ab87e", + "metadata": { + "execution": { + "iopub.execute_input": "2023-09-28T12:52:11.717083Z", + "iopub.status.busy": "2023-09-28T12:52:11.716833Z", + "iopub.status.idle": "2023-09-28T12:52:11.719792Z", + "shell.execute_reply": "2023-09-28T12:52:11.719167Z", + "shell.execute_reply.started": "2023-09-28T12:52:11.717067Z" + }, + "language": "python" + }, + "source": "\n- [Back to Contents](#contents)\n# Demo Architecture\n![Image Alt Text](https://drive.google.com/uc?id=14LYlMDIroDDXHel4hCaOR1EFg_BuYb9P)" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f035321e-d2b9-4576-9219-fe2f89e7cbe2", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "!python --version" + }, + { + "cell_type": "markdown", + "id": "c9938d9e-5f18-4c25-9dbe-207dc8c6f91b", + "metadata": { + "execution": { + "iopub.execute_input": "2023-09-28T13:01:44.430458Z", + "iopub.status.busy": "2023-09-28T13:01:44.430181Z", + "iopub.status.idle": "2023-09-28T13:01:44.434484Z", + "shell.execute_reply": "2023-09-28T13:01:44.433724Z", + "shell.execute_reply.started": "2023-09-28T13:01:44.430442Z" + }, + "language": "python" + }, + "source": "\n# Contents: \n- [Demo Architecture](#architecture)\n- [Step 1: SingleStore DDLs](#ddl)\n- [Step 2: Packages and imports](#imports)\n- [Step 3: Ingest from data sources](#ingest)\n- [Step 4: Connect SingleStore to Open AI's LLM with Langchain](#connect_s2)\n- [Step 5: Add Voice Recognition and Speech](#speech)\n- [Step 6: Tying it together with Image data](#image)\n- [Conclusion](#conclusion)" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "96d5cbe6-59c0-4cbf-bb7d-75683e24c51a", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "markdown", + "id": "72d63784-9e1b-47fb-a962-70da21b7128c", + "metadata": { + "language": "python" + }, + "source": "\n- [Back to Contents](#contents)\n- # Setup SingleStore DDLs" + }, + { + "cell_type": "markdown", + "id": "5cdc0633-6480-478d-a9fd-9af7ee2b2c24", + "metadata": { + "language": "python" + }, + "source": "Create and use the database llm_webinar" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35d1dd68-4280-481d-aefd-954c609b184d", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nCREATE DATABASE llm_webinar;" + }, + { + "cell_type": "markdown", + "id": "a846eff5-74e7-410a-a51a-2a58da119e81", + "metadata": { + "execution": { + "iopub.execute_input": "2023-09-27T17:12:51.870607Z", + "iopub.status.busy": "2023-09-27T17:12:51.870412Z", + "iopub.status.idle": "2023-09-27T17:12:51.874780Z", + "shell.execute_reply": "2023-09-27T17:12:51.873989Z", + "shell.execute_reply.started": "2023-09-27T17:12:51.870588Z" + }, + "language": "python" + }, + "source": "Create tables" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "728002a2-663e-48fd-8153-9c1a50b03bbb", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nCREATE TABLE `stockTable` (\n`ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n`created_at` datetime DEFAULT NULL,\n`open` float DEFAULT NULL,\n`high` float DEFAULT NULL,\n`low` float DEFAULT NULL,\n`close` float DEFAULT NULL,\n`volume` int(11) DEFAULT NULL,\nSORT KEY (ticker, created_at desc),\nSHARD KEY (ticker)\n);\n\nCREATE TABLE newsSentiment (\n title TEXT CHARACTER SET utf8mb4,\n url TEXT,\n time_published DATETIME,\n authors TEXT,\n summary TEXT CHARACTER SET utf8mb4,\n banner_image TEXT,\n source TEXT,\n category_within_source TEXT,\n source_domain TEXT,\n topic TEXT,\n topic_relevance_score TEXT,\n overall_sentiment_score REAL,\n overall_sentiment_label TEXT,\n `ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n ticker_relevance_score DECIMAL(10, 6),\n ticker_sentiment_score DECIMAL(10, 6),\n ticker_sentiment_label TEXT,\n SORT KEY (`ticker`,`time_published` DESC),\n SHARD KEY `__SHARDKEY` (`ticker`,`time_published` DESC),\n KEY(ticker) USING HASH,\n KEY(authors) USING HASH,\n KEY(source) USING HASH,\n KEY(overall_sentiment_label) USING HASH,\n KEY(ticker_sentiment_label) USING HASH \n);\n\nCREATE ROWSTORE REFERENCE TABLE companyInfo (\n ticker VARCHAR(10) PRIMARY KEY,\n AssetType VARCHAR(50),\n Name VARCHAR(100),\n Description TEXT,\n CIK VARCHAR(10),\n Exchange VARCHAR(10),\n Currency VARCHAR(10),\n Country VARCHAR(50),\n Sector VARCHAR(50),\n Industry VARCHAR(250),\n Address VARCHAR(100),\n FiscalYearEnd VARCHAR(20),\n LatestQuarter DATE,\n MarketCapitalization BIGINT,\n EBITDA BIGINT,\n PERatio DECIMAL(10, 2),\n PEGRatio DECIMAL(10, 3),\n BookValue DECIMAL(10, 2),\n DividendPerShare DECIMAL(10, 2),\n DividendYield DECIMAL(10, 4),\n EPS DECIMAL(10, 2),\n RevenuePerShareTTM DECIMAL(10, 2),\n ProfitMargin DECIMAL(10, 4),\n OperatingMarginTTM DECIMAL(10, 4),\n ReturnOnAssetsTTM DECIMAL(10, 4),\n ReturnOnEquityTTM DECIMAL(10, 4),\n RevenueTTM BIGINT,\n GrossProfitTTM BIGINT,\n DilutedEPSTTM DECIMAL(10, 2),\n QuarterlyEarningsGrowthYOY DECIMAL(10, 3),\n QuarterlyRevenueGrowthYOY DECIMAL(10, 3),\n AnalystTargetPrice DECIMAL(10, 2),\n TrailingPE DECIMAL(10, 2),\n ForwardPE DECIMAL(10, 2),\n PriceToSalesRatioTTM DECIMAL(10, 3),\n PriceToBookRatio DECIMAL(10, 2),\n EVToRevenue DECIMAL(10, 3),\n EVToEBITDA DECIMAL(10, 2),\n Beta DECIMAL(10, 3),\n 52WeekHigh DECIMAL(10, 2),\n 52WeekLow DECIMAL(10, 2),\n 50DayMovingAverage DECIMAL(10, 2),\n 200DayMovingAverage DECIMAL(10, 2),\n SharesOutstanding BIGINT,\n DividendDate DATE,\n ExDividendDate DATE\n);\n\nCREATE TABLE `embeddings` (\n`id` bigint(11) NOT NULL AUTO_INCREMENT,\n`category` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n`question` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n`question_embedding` longblob,\n`answer` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n`answer_embedding` longblob,\n`created_at` datetime DEFAULT NULL,\nUNIQUE KEY `PRIMARY` (`id`) USING HASH,\nSHARD KEY `__SHARDKEY` (`id`),\nKEY `category` (`category`) USING HASH,\nSORT KEY `__UNORDERED` (`created_at` DESC)\n);" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58f31787-6d9a-42cb-8bec-548e429f39de", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nSHOW TABLES;" + }, + { + "cell_type": "markdown", + "id": "4fb79318-199c-4d33-97d9-3b8d381dcaba", + "metadata": { + "language": "python" + }, + "source": "\n- [Back to Contents](#contents)\n# Install packages and imports" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "986a23fe-91d6-40cf-8ccf-8ff37f639014", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "!pip install elevenlabs --quiet\n!pip install openai --quiet\n!pip install matplotlib --quiet\n!pip install scipy --quiet\n!pip install scikit-learn --quiet\n!pip install singlestoredb --quiet\n!pip install langchain --quiet" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "819b9d83-28f6-49de-be48-82d29b315ab0", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "import requests\nimport time\nfrom datetime import datetime, timedelta\nfrom datetime import datetime\nimport datetime\nfrom dateutil.relativedelta import relativedelta\nimport singlestoredb as s2\nimport getpass\nimport openai\nfrom langchain.sql_database import SQLDatabase\nfrom langchain.llms.openai import OpenAI\nfrom langchain.agents.agent_toolkits import SQLDatabaseToolkit\nfrom langchain.agents import create_sql_agent\nfrom openai.embeddings_utils import get_embeddings\nimport numpy as np" + }, + { + "cell_type": "markdown", + "id": "27b4b29e-b0c9-401e-a969-9fc770f7f6bd", + "metadata": { + "language": "python" + }, + "source": "### Set API keys" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce7134f0-4ba9-4a8c-b53d-1e42cfaf8d98", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "alpha_vantage_apikey = getpass.getpass(\"enter alphavantage apikey here\")\nopenai_apikey = getpass.getpass(\"enter openai apikey here\")\nelevenlabs_apikey = getpass.getpass(\"enter elevenlabs apikey here\")" + }, + { + "cell_type": "markdown", + "id": "105bdb05-3cb5-4c1e-9cd1-b741bd3ab87a", + "metadata": { + "language": "python" + }, + "source": "\n- [Back to Contents](#contents)\n# Ingest from data sources" + }, + { + "cell_type": "markdown", + "id": "9c43af07-1bd3-43e8-9911-355966072ebe", + "metadata": { + "language": "python" + }, + "source": "### Bring past two months of stock data" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9595c3a-8b00-4d44-a6ab-32d2848459ad", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "# set up connection to SingleStore and the ticker list\ns2_conn = s2.connect(connection_url)\nticker_list = ['TSLA', 'AMZN', 'PLTR']" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2f2c5126-d102-4904-83f6-3a30bc4906b5", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "from datetime import datetime\n\ndef get_past_months(num_months):\n today = datetime.today()\n months = []\n\n for months_ago in range(0, num_months):\n target_date = today - relativedelta(months=months_ago)\n months.append(target_date.strftime('%Y-%m'))\n\n return months\n\nnum_months = 2 # Number of months \nyear_month_list = get_past_months(num_months)\nprint(year_month_list)\n\n# pull intraday data for each stock and write to SingleStore\nfor ticker in ticker_list:\n print(ticker)\n data_list = []\n for year_month in year_month_list:\n print(year_month)\n\n intraday_price_url = \"https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={}&interval=5min&month={}&outputsize=full&apikey={}\".format(ticker, year_month, alpha_vantage_apikey)\n r = requests.get(intraday_price_url)\n\n try: \n data = r.json()['Time Series (5min)']\n except:\n time.sleep(1) # required to not hit API limits\n continue\n \n for key in data:\n document = data[key]\n document['datetime'] = key\n document['ticker'] = ticker\n\n document['open'] = document['1. open']\n document['high'] = document['2. high']\n document['low'] = document['3. low']\n document['close'] = document['4. close']\n document['volume'] = document['5. volume']\n\n document['open'] = float(document['open'])\n document['high'] = float(document['high'])\n document['low'] = float(document['low'])\n document['close'] = float(document['close'])\n document['volume'] = int(document['volume'])\n\n \n del document['1. open']\n del document['2. high']\n del document['3. low']\n del document['4. close']\n del document['5. volume']\n\n data_list += [document]\n \n # Inside your loop, create the params dictionary with the correct values\n params = {\n 'datetime': document['datetime'],\n 'ticker': ticker,\n 'open': document['open'],\n 'high': document['high'],\n 'low': document['low'],\n 'close': document['close'],\n 'volume': document['volume']\n }\n\n # Construct and execute the SQL statement\n table_name = 'stockTable'\n stmt = f\"INSERT INTO {table_name} (created_at, ticker, open, high, low, close, volume) VALUES (%(datetime)s, %(ticker)s, %(open)s, %(high)s, %(low)s, %(close)s, %(volume)s)\"\n\n with s2_conn.cursor() as cur:\n cur.execute(stmt, params)\n # time.sleep(1) # required to not hit API limits" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb534c0e-bfd9-47f6-a2be-7bd160ab9ab2", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nselect count(*) from stockTable" + }, + { + "cell_type": "markdown", + "id": "5e142437-c49b-4484-9475-35105cde45b2", + "metadata": { + "language": "python" + }, + "source": "# Bring in Company data" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4c9d7e8-5cd7-47d4-a188-cb660bd9c798", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "# pull intraday data for each stock and write to SingleStore\nfor ticker in ticker_list:\n print(ticker)\n data_list = []\n # for year_month in year_month_list:\n\n company_overview = \"https://www.alphavantage.co/query?function=OVERVIEW&symbol={}&outputsize=full&apikey={}\".format(ticker, alpha_vantage_apikey)\n r = requests.get(company_overview)\n\n try: \n data = r.json()\n except:\n time.sleep(3) # required to not hit API limits\n continue\n \n data['CIK'] = int(data['CIK'])\n data['MarketCapitalization']= float(data['MarketCapitalization'])\n # Assuming data['EBITDA'] is a string containing 'None'\n ebitda_str = data['EBITDA']\n if ebitda_str.lower() == 'none':\n # Handle the case where EBITDA is 'None', for example, you can set it to 0\n data['EBITDA'] = 0.0\n else:\n # Convert the EBITDA string to a float\n data['EBITDA'] = float(ebitda_str)\n \n PERatio_flt = data['PERatio']\n if PERatio_flt.lower() == 'none':\n # Handle the case where EVToRevenue is '-'\n data['PERatio'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['PERatio'] = float(PERatio_flt)\n \n data['PEGRatio']= float(data['PEGRatio'])\n data['BookValue']= float(data['BookValue'])\n data['DividendPerShare']= float(data['DividendPerShare'])\n data['DividendYield']= float(data['DividendYield'])\n data['EPS']= float(data['EPS'])\n data['RevenuePerShareTTM']= float(data['RevenuePerShareTTM'])\n data['ProfitMargin']= float(data['ProfitMargin'])\n data['OperatingMarginTTM']= float(data['OperatingMarginTTM'])\n data['ReturnOnAssetsTTM']= float(data['ReturnOnAssetsTTM'])\n data['ReturnOnEquityTTM']= float(data['ReturnOnEquityTTM'])\n data['RevenueTTM']= int(data['RevenueTTM'])\n data['GrossProfitTTM']= int(data['GrossProfitTTM'])\n data['DilutedEPSTTM']= float(data['DilutedEPSTTM'])\n data['QuarterlyEarningsGrowthYOY']= float(data['QuarterlyEarningsGrowthYOY'])\n data['QuarterlyRevenueGrowthYOY']= float(data['QuarterlyRevenueGrowthYOY'])\n data['AnalystTargetPrice']= float(data['AnalystTargetPrice'])\n # Assuming data['TrailingPE'] is a string containing '-'\n trailing_pe_str = data['TrailingPE']\n if trailing_pe_str == '-':\n # Handle the case where TrailingPE is '-'\n data['TrailingPE'] = 0.0 # You can use any default value that makes sense\n else:\n try:\n # Attempt to convert the TrailingPE string to a float\n data['TrailingPE'] = float(trailing_pe_str)\n except ValueError:\n # Handle the case where the conversion fails (e.g., if it contains invalid characters)\n data['TrailingPE'] = 0.0 # Set to a default value or handle as needed\n\n\n \n data['ForwardPE']= float(data['ForwardPE'])\n data['PriceToSalesRatioTTM']= float(data['PriceToSalesRatioTTM'])\n # Assuming data['EVToRevenue'] is a string containing '-'\n PriceToBookRatio_flt = data['PriceToBookRatio']\n if PriceToBookRatio_flt == '-':\n # Handle the case where EVToRevenue is '-'\n data['PriceToBookRatio'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['PriceToBookRatio'] = float(PriceToBookRatio_flt)\n\n \n # Assuming data['EVToRevenue'] is a string containing '-'\n ev_to_revenue_str = data['EVToRevenue']\n if ev_to_revenue_str == '-':\n # Handle the case where EVToRevenue is '-'\n data['EVToRevenue'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['EVToRevenue'] = float(ev_to_revenue_str)\n \n # data['EVToEBITDA']= float(data['EVToEBITDA'])\n # Assuming data['EVToRevenue'] is a string containing '-'\n ev_to_EBITDA_str = data['EVToEBITDA']\n if ev_to_revenue_str == '-':\n # Handle the case where EVToRevenue is '-'\n data['EVToEBITDA'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['EVToEBITDA'] = float(ev_to_EBITDA_str)\n\n \n data['Beta']= float(data['Beta'])\n data['52WeekHigh']= float(data['52WeekHigh'])\n data['52WeekLow']= float(data['52WeekLow'])\n data['50DayMovingAverage']= float(data['50DayMovingAverage'])\n data['200DayMovingAverage']= float(data['200DayMovingAverage'])\n data['SharesOutstanding']= int(data['SharesOutstanding'])\n # description_embedding = [np.array(x, '\n- [Back to Demo Architecture](#architecture)\n# Connect SingleStore to Open AI's LLM with Langchain" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1dd25cf2-bd39-4f25-b3a5-fe128c372e97", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "os.environ[\"OPENAI_API_KEY\"] = openai_apikey\nembedding_model = 'text-embedding-ada-002'\ngpt_model = 'gpt-3.5-turbo-16k'\n\n# Create the agent executor\ndb = SQLDatabase.from_uri(connection_url, include_tables=['embeddings', 'companyInfo', 'newsSentiment', 'stockTable'], sample_rows_in_table_info=2)\nllm = OpenAI(openai_api_key=os.environ[\"OPENAI_API_KEY\"], temperature=0, verbose=True)\ntoolkit = SQLDatabaseToolkit(db=db, llm=llm)\n\nagent_executor = create_sql_agent(\n llm=OpenAI(temperature=0),\n toolkit=toolkit,\n verbose=True,\n prefix= '''\n You are an agent designed to interact with a SQL database called SingleStore. This sometimes has Shard and Sort keys in the table schemas, which you can ignore. \n \\nGiven an input question, create a syntactically correct MySQL query to run, then look at the results of the query and return the answer. \n \\n If you are asked about similarity questions, you should use the DOT_PRODUCT function.\n \n \\nHere are a few examples of how to use the DOT_PRODUCT function:\n \\nExample 1:\n Q: how similar are the questions and answers?\n A: The query used to find this is:\n \n select question, answer, dot_product(question_embedding, answer_embedding) as similarity from embeddings;\n \n \\nExample 2:\n Q: What are the most similar questions in the embeddings table, not including itself?\n A: The query used to find this answer is:\n \n SELECT q1.question as question1, q2.question as question2, DOT_PRODUCT(q1.question_embedding, q2.question_embedding) :> float as score\n FROM embeddings q1, embeddings q2 \n WHERE question1 != question2 \n ORDER BY score DESC LIMIT 5;\n \n \\nExample 3:\n Q: In the embeddings table, which rows are from the chatbot?\n A: The query used to find this answer is:\n \n SELECT category, question, answer FROM embeddings\n WHERE category = 'chatbot';\n\n \\nIf you are asked to describe the database, you should run the query SHOW TABLES \n \\nUnless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n \\n The question embeddings and answer embeddings are very long, so do not show them unless specifically asked to.\n \\nYou can order the results by a relevant column to return the most interesting examples in the database.\n \\nNever query for all the columns from a specific table, only ask for the relevant columns given the question.\n \\nYou have access to tools for interacting with the database.\\nOnly use the below tools. \n Only use the information returned by the below tools to construct your final answer.\n \\nYou MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again up to 3 times.\n \\n\\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n \\n\\nIf the question does not seem related to the database, just return \"I don\\'t know\" as the answer.\\n,\n \n ''',\n format_instructions='''Use the following format:\\n\n \\nQuestion: the input question you must answer\n \\nThought: you should always think about what to do\n \\nAction: the action to take, should be one of [{tool_names}]\n \\nAction Input: the input to the action\n \\nObservation: the result of the action\n \\nThought: I now know the final answer\n \\nFinal Answer: the final answer to the original input question\n \\nSQL Query used to get the Answer: the final sql query used for the final answer'\n ''',\n top_k=3,\n max_iterations=5\n)" + }, + { + "cell_type": "markdown", + "id": "a993b299-200e-48e0-886a-6eba2daafe35", + "metadata": { + "language": "python" + }, + "source": "### Create function that processes user question with a check in Semantic Cache Layer" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be7f7f12-13ee-42bc-a6c7-c5743642bd62", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "table_name = 'embeddings'\nsimilarity_threshold = .97\n\ndef process_user_question(question):\n print(f'\\nQuestion asked: {question}')\n category = 'chatbot'\n \n # Get vector embedding from the original question and calculate the elapsed time\n start_time = time.time()\n question_embedding= [np.array(x, ' float as score from embeddings where category=\"chatbot\" order by score desc limit 1;'\n \n\n with s2_conn.cursor() as cur:\n start_time = time.time()\n cur.execute(stmt, params)\n row = cur.fetchone()\n elapsed_time = (time.time() - start_time) * 1000\n print(f\"Execution time for checking existing questions: {elapsed_time:.2f} milliseconds\")\n \n try:\n question2, answer, score = row\n print(f\"\\nClosest Matching row:\\nQuestion: {question2}\\nAnswer: {answer}\\nSimilarity Score: {score}\")\n\n if score > similarity_threshold:\n print('Action to take: Using existing answer')\n return answer\n\n else:\n print('Action to take: Running agent_executor')\n start_time = time.time()\n answer2 = agent_executor.run(question)\n elapsed_time = (time.time() - start_time) * 1000\n print(f\"agent_executor execution time: {elapsed_time:.2f} milliseconds\")\n\n # Get current time\n created_at = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n\n # Get the answer embedding and calculate the elapsed time\n start_time = time.time()\n answer_embedding = [np.array(x, '\n- [Back to Contents](#contents)\n# Add Voice Recognition and Speech" + }, + { + "cell_type": "markdown", + "id": "f4ad3d62-554d-43b9-af75-862efee6e001", + "metadata": { + "language": "python" + }, + "source": "### Select a voice" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc2390de-f4e3-4d33-9593-f829a7d40d85", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "from elevenlabs import generate, stream, voices\nfrom elevenlabs import set_api_key\nfrom IPython.display import Audio\nfrom IPython.display import display\nimport requests" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9b098298-ce68-46ba-b962-bc08226ca955", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "voices = voices()\nvoices[0]" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2001b20-6d6b-4a34-8716-7f295b7abc53", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "CHUNK_SIZE = 1024\nurl = \"https://api.elevenlabs.io/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM/stream\"\n\nheaders = {\n \"Accept\": \"audio/mpeg\",\n \"Content-Type\": \"application/json\",\n \"xi-api-key\": elevenlabs_apikey\n}\n\ndata = {\n \"text\": answer,\n \"model_id\": \"eleven_monolingual_v1\",\n \"voice_settings\": {\n \"stability\": 0.5,\n \"similarity_boost\": 0.5\n }\n}\n\nresponse = requests.post(url, json=data, headers=headers, stream=True)\n\n# create an audio file\nwith open('output.mp3', 'wb') as f:\n for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n if chunk:\n f.write(chunk)\n" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3ba4d543-6df1-4089-b054-7c149d9a3324", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "!ls" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8bbffa96-ed40-40ea-b424-a32b5f1b9a9f", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "audio_file = 'output.mp3'\n\naudio = Audio(filename=audio_file, autoplay =True)\ndisplay(audio)" + }, + { + "cell_type": "markdown", + "id": "6d904504-c20b-4ca9-bc36-8c9288c4c4f4", + "metadata": { + "language": "python" + }, + "source": "### Transcribe the audio file" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f991542-c92a-498c-ba7e-c37af7bbc491", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "openai.api_key = openai_apikey\naudio_file= open(\"output.mp3\", \"rb\")\ntranscript = openai.Audio.transcribe(\"whisper-1\", audio_file)\nprint(transcript[\"text\"])" + }, + { + "cell_type": "markdown", + "id": "c6d005ea-9979-4c62-b09b-0888ec17da12", + "metadata": { + "language": "python" + }, + "source": "\n- [Back to Demo Architecture](#architecture)\n# Tying it together with Image data" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "290da6ad-3ea5-426e-8d6c-3b226f00cad4", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "# Most recent news article for TSLA\nquestion_3 = \"\"\"What is the most recent news article for Amazon where the topic_relevance_score is greater than 90%? \nInclude the url, time published and banner image.\"\"\"\nanswer = process_user_question(question_3)\nprint(f'The answer is: {answer}')" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c18a63c-13c4-40e8-b235-55bc6f04fd28", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nSELECT title, url, time_published, banner_image FROM newsSentiment WHERE ticker = 'AMZN' AND topic_relevance_score > 0.9 ORDER BY time_published DESC LIMIT 3" + }, + { + "cell_type": "markdown", + "id": "a3076d45-a48e-4a90-811f-e4fb9e01c7e6", + "metadata": { + "language": "python" + }, + "source": "### Load the image" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "672be099-e988-4739-9932-0a6f23bcc844", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "import matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nfrom io import BytesIO\nbanner_image_url = \"https://staticx-tuner.zacks.com/images/default_article_images/default341.jpg\"\nresponse = requests.get(banner_image_url)\n\nif response.status_code == 200:\n img = mpimg.imread(BytesIO(response.content), format='JPG')\n imgplot = plt.imshow(img)\n plt.show()\nelse:\n print(f\"Failed to retrieve the image. Status code: {response.status_code}\")" + }, + { + "cell_type": "markdown", + "id": "7b4528e9-4545-41d0-9a36-b84141e9850c", + "metadata": { + "language": "python" + }, + "source": "### Set up the huggingface transformer" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6848e943-4cd8-445e-840d-f9d13b4391f6", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "transformers_version = \"v4.29.0\" #@param [\"main\", \"v4.29.0\"] {allow-input: true}\n\nprint(f\"Setting up everything with transformers version {transformers_version}\")\n\n!pip install huggingface_hub>=0.14.1 git+https://github.com/huggingface/transformers@$transformers_version -q diffusers accelerate datasets torch soundfile sentencepiece opencv-python openai\n" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b77f62b-3f57-4335-bae4-27f5f74abf70", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "import IPython\nimport soundfile as sf\n\ndef play_audio(audio):\n sf.write(\"speech_converted.wav\", audio.numpy(), samplerate=16000)\n return IPython.display.Audio(\"speech_converted.wav\")\n\nfrom huggingface_hub import notebook_login\nnotebook_login()" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6b2ceeee-6d95-4aa5-83fd-9651be326e59", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "agent_name = \"OpenAI (API Key)\" #@param [\"StarCoder (HF Token)\", \"OpenAssistant (HF Token)\", \"OpenAI (API Key)\"]\n\nif agent_name == \"StarCoder (HF Token)\":\n from transformers.tools import HfAgent\n agent = HfAgent(\"https://api-inference.huggingface.co/models/bigcode/starcoder\")\n print(\"StarCoder is initialized 💪\")\nelif agent_name == \"OpenAssistant (HF Token)\":\n from transformers.tools import HfAgent\n agent = HfAgent(url_endpoint=\"https://api-inference.huggingface.co/models/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5\")\n print(\"OpenAssistant is initialized 💪\")\nif agent_name == \"OpenAI (API Key)\":\n from transformers.tools import OpenAiAgent\n pswd = openai_apikey\n agent = OpenAiAgent(model=\"text-davinci-003\", api_key=pswd)\n print(\"OpenAI is initialized 💪\")" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eed4814a-8a7e-41f6-956b-51c7debc1fff", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "caption = agent.run(\"Can you caption the `image`?\", image=img)" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "71e8f5dd-ab27-415e-a0b6-423c497232ef", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "data = {\n \"text\": caption,\n \"model_id\": \"eleven_monolingual_v1\",\n \"voice_settings\": {\n \"stability\": 0.5,\n \"similarity_boost\": 0.5\n }\n}\n\nresponse = requests.post(url, json=data, headers=headers)\nwith open('output.mp3', 'wb') as f:\n for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n if chunk:\n f.write(chunk)\n\naudio_file = 'output.mp3'\n\naudio = Audio(filename=audio_file, autoplay =True)\ndisplay(audio)" + }, + { + "cell_type": "markdown", + "id": "de4c4db5-d068-41ef-aa85-0657c6c450a9", + "metadata": { + "language": "python" + }, + "source": "\n- [Back to Contents](#contents)\n# Conclusion" + }, + { + "cell_type": "markdown", + "id": "faff70cf-728f-4bb3-b744-ba7efb195e10", + "metadata": { + "language": "python" + }, + "source": "- Handle transactional and analytical queries with your vector data\n- no need to export data out of SingleStore to another vector db\n- Scan vectors fast with exact nearest neighbor. (DOT_PRODUCT, EUCLIDEAN_DISTANCE, and VECTOR_SUB are high-perf functions using single-instruction-multiple-data (SIMD) processor instructions)\n- Ability to stream data directly into SingleStore\n- Use SingleStore as Semantic Cache Layer leveraging the Plancache. No need for a cache layer.\n- Easily scale the workspace for your workload\n- handle reads and writes in parallel\n- Use of external functions. \n" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "13bff7c9-a7c5-4807-84df-e9f7490f4627", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21e59bb1-bf4f-4aa7-bf7a-92f8e4f19dd7", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b07e2d81-473d-4035-9cbf-fe66007362bf", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "808e304b-2515-449a-8cec-8f3a3a38ed4b", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93e4e0da-a887-4cd7-b70c-475710ece772", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + }, + { + "cell_type": "markdown", + "id": "17b69461-5ceb-42ff-9986-2092b5670f58", + "metadata": { + "language": "python" + }, + "source": "# Reset Demo" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4ae2913a-ee2b-40f0-94b3-cb75c9891aea", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "%%sql\nDROP DATABASE llm_webinar;" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eeb7d04b-df99-457b-96c3-9b0967f00c6c", + "metadata": { + "language": "python" + }, + "outputs": [], + "source": "" + } + ], + "metadata": { + "jupyterlab": { + "notebooks": { + "version_major": 6, + "version_minor": 4 + } + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimeType": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + }, + "singlestore_cell_default_language": "python", + "singlestore_connection": { + "connectionID": "ee66326b-0803-4fdb-8b7f-d6415f18d4c8", + "defaultDatabase": "llm_webinar" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml new file mode 100644 index 00000000..dec289e9 --- /dev/null +++ b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml @@ -0,0 +1,8 @@ +[meta] +title="How to Build LLM Apps that can See Hear Speak" +description="""\ + Using OpenAI to build a an app that can take images, audio, and text data to generate output + """ +icon="chart-network" +tags=["Advanced", "OpenAI", "genAI"] +destinations=["spaces"] From 021b6b03a88a9933ecf29341392aa57185328198 Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Fri, 29 Sep 2023 11:20:17 -0500 Subject: [PATCH 03/24] Fix style issues --- ...ild-LLM-Apps-that-can-See-Hear-Speak.ipynb | 669 -------- .../readme | 1 - .../meta.toml | 2 +- .../notebook.ipynb | 1431 +++++++++++++++++ 4 files changed, 1432 insertions(+), 671 deletions(-) delete mode 100644 notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb delete mode 100644 notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme rename notebooks/{How-to-Build-LLM-Apps-that-can-See-Hear-Speak => how-to-build-llm-apps-that-can-see-hear-speak}/meta.toml (86%) create mode 100644 notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb deleted file mode 100644 index a8636d78..00000000 --- a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/How-to-Build-LLM-Apps-that-can-See-Hear-Speak.ipynb +++ /dev/null @@ -1,669 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "215c4617-6ebd-43fc-aa25-904fec4bdf5e", - "metadata": { - "language": "python" - }, - "source": "# How to Build LLM Apps that can See, Hear, Speak" - }, - { - "cell_type": "markdown", - "id": "a2a7fa17-ff2a-4abf-922d-af00514ab87e", - "metadata": { - "execution": { - "iopub.execute_input": "2023-09-28T12:52:11.717083Z", - "iopub.status.busy": "2023-09-28T12:52:11.716833Z", - "iopub.status.idle": "2023-09-28T12:52:11.719792Z", - "shell.execute_reply": "2023-09-28T12:52:11.719167Z", - "shell.execute_reply.started": "2023-09-28T12:52:11.717067Z" - }, - "language": "python" - }, - "source": "\n- [Back to Contents](#contents)\n# Demo Architecture\n![Image Alt Text](https://drive.google.com/uc?id=14LYlMDIroDDXHel4hCaOR1EFg_BuYb9P)" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f035321e-d2b9-4576-9219-fe2f89e7cbe2", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "!python --version" - }, - { - "cell_type": "markdown", - "id": "c9938d9e-5f18-4c25-9dbe-207dc8c6f91b", - "metadata": { - "execution": { - "iopub.execute_input": "2023-09-28T13:01:44.430458Z", - "iopub.status.busy": "2023-09-28T13:01:44.430181Z", - "iopub.status.idle": "2023-09-28T13:01:44.434484Z", - "shell.execute_reply": "2023-09-28T13:01:44.433724Z", - "shell.execute_reply.started": "2023-09-28T13:01:44.430442Z" - }, - "language": "python" - }, - "source": "\n# Contents: \n- [Demo Architecture](#architecture)\n- [Step 1: SingleStore DDLs](#ddl)\n- [Step 2: Packages and imports](#imports)\n- [Step 3: Ingest from data sources](#ingest)\n- [Step 4: Connect SingleStore to Open AI's LLM with Langchain](#connect_s2)\n- [Step 5: Add Voice Recognition and Speech](#speech)\n- [Step 6: Tying it together with Image data](#image)\n- [Conclusion](#conclusion)" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "96d5cbe6-59c0-4cbf-bb7d-75683e24c51a", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "markdown", - "id": "72d63784-9e1b-47fb-a962-70da21b7128c", - "metadata": { - "language": "python" - }, - "source": "\n- [Back to Contents](#contents)\n- # Setup SingleStore DDLs" - }, - { - "cell_type": "markdown", - "id": "5cdc0633-6480-478d-a9fd-9af7ee2b2c24", - "metadata": { - "language": "python" - }, - "source": "Create and use the database llm_webinar" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "35d1dd68-4280-481d-aefd-954c609b184d", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nCREATE DATABASE llm_webinar;" - }, - { - "cell_type": "markdown", - "id": "a846eff5-74e7-410a-a51a-2a58da119e81", - "metadata": { - "execution": { - "iopub.execute_input": "2023-09-27T17:12:51.870607Z", - "iopub.status.busy": "2023-09-27T17:12:51.870412Z", - "iopub.status.idle": "2023-09-27T17:12:51.874780Z", - "shell.execute_reply": "2023-09-27T17:12:51.873989Z", - "shell.execute_reply.started": "2023-09-27T17:12:51.870588Z" - }, - "language": "python" - }, - "source": "Create tables" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "728002a2-663e-48fd-8153-9c1a50b03bbb", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nCREATE TABLE `stockTable` (\n`ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n`created_at` datetime DEFAULT NULL,\n`open` float DEFAULT NULL,\n`high` float DEFAULT NULL,\n`low` float DEFAULT NULL,\n`close` float DEFAULT NULL,\n`volume` int(11) DEFAULT NULL,\nSORT KEY (ticker, created_at desc),\nSHARD KEY (ticker)\n);\n\nCREATE TABLE newsSentiment (\n title TEXT CHARACTER SET utf8mb4,\n url TEXT,\n time_published DATETIME,\n authors TEXT,\n summary TEXT CHARACTER SET utf8mb4,\n banner_image TEXT,\n source TEXT,\n category_within_source TEXT,\n source_domain TEXT,\n topic TEXT,\n topic_relevance_score TEXT,\n overall_sentiment_score REAL,\n overall_sentiment_label TEXT,\n `ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n ticker_relevance_score DECIMAL(10, 6),\n ticker_sentiment_score DECIMAL(10, 6),\n ticker_sentiment_label TEXT,\n SORT KEY (`ticker`,`time_published` DESC),\n SHARD KEY `__SHARDKEY` (`ticker`,`time_published` DESC),\n KEY(ticker) USING HASH,\n KEY(authors) USING HASH,\n KEY(source) USING HASH,\n KEY(overall_sentiment_label) USING HASH,\n KEY(ticker_sentiment_label) USING HASH \n);\n\nCREATE ROWSTORE REFERENCE TABLE companyInfo (\n ticker VARCHAR(10) PRIMARY KEY,\n AssetType VARCHAR(50),\n Name VARCHAR(100),\n Description TEXT,\n CIK VARCHAR(10),\n Exchange VARCHAR(10),\n Currency VARCHAR(10),\n Country VARCHAR(50),\n Sector VARCHAR(50),\n Industry VARCHAR(250),\n Address VARCHAR(100),\n FiscalYearEnd VARCHAR(20),\n LatestQuarter DATE,\n MarketCapitalization BIGINT,\n EBITDA BIGINT,\n PERatio DECIMAL(10, 2),\n PEGRatio DECIMAL(10, 3),\n BookValue DECIMAL(10, 2),\n DividendPerShare DECIMAL(10, 2),\n DividendYield DECIMAL(10, 4),\n EPS DECIMAL(10, 2),\n RevenuePerShareTTM DECIMAL(10, 2),\n ProfitMargin DECIMAL(10, 4),\n OperatingMarginTTM DECIMAL(10, 4),\n ReturnOnAssetsTTM DECIMAL(10, 4),\n ReturnOnEquityTTM DECIMAL(10, 4),\n RevenueTTM BIGINT,\n GrossProfitTTM BIGINT,\n DilutedEPSTTM DECIMAL(10, 2),\n QuarterlyEarningsGrowthYOY DECIMAL(10, 3),\n QuarterlyRevenueGrowthYOY DECIMAL(10, 3),\n AnalystTargetPrice DECIMAL(10, 2),\n TrailingPE DECIMAL(10, 2),\n ForwardPE DECIMAL(10, 2),\n PriceToSalesRatioTTM DECIMAL(10, 3),\n PriceToBookRatio DECIMAL(10, 2),\n EVToRevenue DECIMAL(10, 3),\n EVToEBITDA DECIMAL(10, 2),\n Beta DECIMAL(10, 3),\n 52WeekHigh DECIMAL(10, 2),\n 52WeekLow DECIMAL(10, 2),\n 50DayMovingAverage DECIMAL(10, 2),\n 200DayMovingAverage DECIMAL(10, 2),\n SharesOutstanding BIGINT,\n DividendDate DATE,\n ExDividendDate DATE\n);\n\nCREATE TABLE `embeddings` (\n`id` bigint(11) NOT NULL AUTO_INCREMENT,\n`category` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n`question` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n`question_embedding` longblob,\n`answer` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n`answer_embedding` longblob,\n`created_at` datetime DEFAULT NULL,\nUNIQUE KEY `PRIMARY` (`id`) USING HASH,\nSHARD KEY `__SHARDKEY` (`id`),\nKEY `category` (`category`) USING HASH,\nSORT KEY `__UNORDERED` (`created_at` DESC)\n);" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "58f31787-6d9a-42cb-8bec-548e429f39de", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nSHOW TABLES;" - }, - { - "cell_type": "markdown", - "id": "4fb79318-199c-4d33-97d9-3b8d381dcaba", - "metadata": { - "language": "python" - }, - "source": "\n- [Back to Contents](#contents)\n# Install packages and imports" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "986a23fe-91d6-40cf-8ccf-8ff37f639014", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "!pip install elevenlabs --quiet\n!pip install openai --quiet\n!pip install matplotlib --quiet\n!pip install scipy --quiet\n!pip install scikit-learn --quiet\n!pip install singlestoredb --quiet\n!pip install langchain --quiet" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "819b9d83-28f6-49de-be48-82d29b315ab0", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "import requests\nimport time\nfrom datetime import datetime, timedelta\nfrom datetime import datetime\nimport datetime\nfrom dateutil.relativedelta import relativedelta\nimport singlestoredb as s2\nimport getpass\nimport openai\nfrom langchain.sql_database import SQLDatabase\nfrom langchain.llms.openai import OpenAI\nfrom langchain.agents.agent_toolkits import SQLDatabaseToolkit\nfrom langchain.agents import create_sql_agent\nfrom openai.embeddings_utils import get_embeddings\nimport numpy as np" - }, - { - "cell_type": "markdown", - "id": "27b4b29e-b0c9-401e-a969-9fc770f7f6bd", - "metadata": { - "language": "python" - }, - "source": "### Set API keys" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ce7134f0-4ba9-4a8c-b53d-1e42cfaf8d98", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "alpha_vantage_apikey = getpass.getpass(\"enter alphavantage apikey here\")\nopenai_apikey = getpass.getpass(\"enter openai apikey here\")\nelevenlabs_apikey = getpass.getpass(\"enter elevenlabs apikey here\")" - }, - { - "cell_type": "markdown", - "id": "105bdb05-3cb5-4c1e-9cd1-b741bd3ab87a", - "metadata": { - "language": "python" - }, - "source": "\n- [Back to Contents](#contents)\n# Ingest from data sources" - }, - { - "cell_type": "markdown", - "id": "9c43af07-1bd3-43e8-9911-355966072ebe", - "metadata": { - "language": "python" - }, - "source": "### Bring past two months of stock data" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9595c3a-8b00-4d44-a6ab-32d2848459ad", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "# set up connection to SingleStore and the ticker list\ns2_conn = s2.connect(connection_url)\nticker_list = ['TSLA', 'AMZN', 'PLTR']" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2f2c5126-d102-4904-83f6-3a30bc4906b5", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "from datetime import datetime\n\ndef get_past_months(num_months):\n today = datetime.today()\n months = []\n\n for months_ago in range(0, num_months):\n target_date = today - relativedelta(months=months_ago)\n months.append(target_date.strftime('%Y-%m'))\n\n return months\n\nnum_months = 2 # Number of months \nyear_month_list = get_past_months(num_months)\nprint(year_month_list)\n\n# pull intraday data for each stock and write to SingleStore\nfor ticker in ticker_list:\n print(ticker)\n data_list = []\n for year_month in year_month_list:\n print(year_month)\n\n intraday_price_url = \"https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={}&interval=5min&month={}&outputsize=full&apikey={}\".format(ticker, year_month, alpha_vantage_apikey)\n r = requests.get(intraday_price_url)\n\n try: \n data = r.json()['Time Series (5min)']\n except:\n time.sleep(1) # required to not hit API limits\n continue\n \n for key in data:\n document = data[key]\n document['datetime'] = key\n document['ticker'] = ticker\n\n document['open'] = document['1. open']\n document['high'] = document['2. high']\n document['low'] = document['3. low']\n document['close'] = document['4. close']\n document['volume'] = document['5. volume']\n\n document['open'] = float(document['open'])\n document['high'] = float(document['high'])\n document['low'] = float(document['low'])\n document['close'] = float(document['close'])\n document['volume'] = int(document['volume'])\n\n \n del document['1. open']\n del document['2. high']\n del document['3. low']\n del document['4. close']\n del document['5. volume']\n\n data_list += [document]\n \n # Inside your loop, create the params dictionary with the correct values\n params = {\n 'datetime': document['datetime'],\n 'ticker': ticker,\n 'open': document['open'],\n 'high': document['high'],\n 'low': document['low'],\n 'close': document['close'],\n 'volume': document['volume']\n }\n\n # Construct and execute the SQL statement\n table_name = 'stockTable'\n stmt = f\"INSERT INTO {table_name} (created_at, ticker, open, high, low, close, volume) VALUES (%(datetime)s, %(ticker)s, %(open)s, %(high)s, %(low)s, %(close)s, %(volume)s)\"\n\n with s2_conn.cursor() as cur:\n cur.execute(stmt, params)\n # time.sleep(1) # required to not hit API limits" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fb534c0e-bfd9-47f6-a2be-7bd160ab9ab2", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nselect count(*) from stockTable" - }, - { - "cell_type": "markdown", - "id": "5e142437-c49b-4484-9475-35105cde45b2", - "metadata": { - "language": "python" - }, - "source": "# Bring in Company data" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a4c9d7e8-5cd7-47d4-a188-cb660bd9c798", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "# pull intraday data for each stock and write to SingleStore\nfor ticker in ticker_list:\n print(ticker)\n data_list = []\n # for year_month in year_month_list:\n\n company_overview = \"https://www.alphavantage.co/query?function=OVERVIEW&symbol={}&outputsize=full&apikey={}\".format(ticker, alpha_vantage_apikey)\n r = requests.get(company_overview)\n\n try: \n data = r.json()\n except:\n time.sleep(3) # required to not hit API limits\n continue\n \n data['CIK'] = int(data['CIK'])\n data['MarketCapitalization']= float(data['MarketCapitalization'])\n # Assuming data['EBITDA'] is a string containing 'None'\n ebitda_str = data['EBITDA']\n if ebitda_str.lower() == 'none':\n # Handle the case where EBITDA is 'None', for example, you can set it to 0\n data['EBITDA'] = 0.0\n else:\n # Convert the EBITDA string to a float\n data['EBITDA'] = float(ebitda_str)\n \n PERatio_flt = data['PERatio']\n if PERatio_flt.lower() == 'none':\n # Handle the case where EVToRevenue is '-'\n data['PERatio'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['PERatio'] = float(PERatio_flt)\n \n data['PEGRatio']= float(data['PEGRatio'])\n data['BookValue']= float(data['BookValue'])\n data['DividendPerShare']= float(data['DividendPerShare'])\n data['DividendYield']= float(data['DividendYield'])\n data['EPS']= float(data['EPS'])\n data['RevenuePerShareTTM']= float(data['RevenuePerShareTTM'])\n data['ProfitMargin']= float(data['ProfitMargin'])\n data['OperatingMarginTTM']= float(data['OperatingMarginTTM'])\n data['ReturnOnAssetsTTM']= float(data['ReturnOnAssetsTTM'])\n data['ReturnOnEquityTTM']= float(data['ReturnOnEquityTTM'])\n data['RevenueTTM']= int(data['RevenueTTM'])\n data['GrossProfitTTM']= int(data['GrossProfitTTM'])\n data['DilutedEPSTTM']= float(data['DilutedEPSTTM'])\n data['QuarterlyEarningsGrowthYOY']= float(data['QuarterlyEarningsGrowthYOY'])\n data['QuarterlyRevenueGrowthYOY']= float(data['QuarterlyRevenueGrowthYOY'])\n data['AnalystTargetPrice']= float(data['AnalystTargetPrice'])\n # Assuming data['TrailingPE'] is a string containing '-'\n trailing_pe_str = data['TrailingPE']\n if trailing_pe_str == '-':\n # Handle the case where TrailingPE is '-'\n data['TrailingPE'] = 0.0 # You can use any default value that makes sense\n else:\n try:\n # Attempt to convert the TrailingPE string to a float\n data['TrailingPE'] = float(trailing_pe_str)\n except ValueError:\n # Handle the case where the conversion fails (e.g., if it contains invalid characters)\n data['TrailingPE'] = 0.0 # Set to a default value or handle as needed\n\n\n \n data['ForwardPE']= float(data['ForwardPE'])\n data['PriceToSalesRatioTTM']= float(data['PriceToSalesRatioTTM'])\n # Assuming data['EVToRevenue'] is a string containing '-'\n PriceToBookRatio_flt = data['PriceToBookRatio']\n if PriceToBookRatio_flt == '-':\n # Handle the case where EVToRevenue is '-'\n data['PriceToBookRatio'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['PriceToBookRatio'] = float(PriceToBookRatio_flt)\n\n \n # Assuming data['EVToRevenue'] is a string containing '-'\n ev_to_revenue_str = data['EVToRevenue']\n if ev_to_revenue_str == '-':\n # Handle the case where EVToRevenue is '-'\n data['EVToRevenue'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['EVToRevenue'] = float(ev_to_revenue_str)\n \n # data['EVToEBITDA']= float(data['EVToEBITDA'])\n # Assuming data['EVToRevenue'] is a string containing '-'\n ev_to_EBITDA_str = data['EVToEBITDA']\n if ev_to_revenue_str == '-':\n # Handle the case where EVToRevenue is '-'\n data['EVToEBITDA'] = 0.0 # You can use any default value that makes sense\n else:\n # Convert the EVToRevenue string to a float\n data['EVToEBITDA'] = float(ev_to_EBITDA_str)\n\n \n data['Beta']= float(data['Beta'])\n data['52WeekHigh']= float(data['52WeekHigh'])\n data['52WeekLow']= float(data['52WeekLow'])\n data['50DayMovingAverage']= float(data['50DayMovingAverage'])\n data['200DayMovingAverage']= float(data['200DayMovingAverage'])\n data['SharesOutstanding']= int(data['SharesOutstanding'])\n # description_embedding = [np.array(x, '\n- [Back to Demo Architecture](#architecture)\n# Connect SingleStore to Open AI's LLM with Langchain" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1dd25cf2-bd39-4f25-b3a5-fe128c372e97", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "os.environ[\"OPENAI_API_KEY\"] = openai_apikey\nembedding_model = 'text-embedding-ada-002'\ngpt_model = 'gpt-3.5-turbo-16k'\n\n# Create the agent executor\ndb = SQLDatabase.from_uri(connection_url, include_tables=['embeddings', 'companyInfo', 'newsSentiment', 'stockTable'], sample_rows_in_table_info=2)\nllm = OpenAI(openai_api_key=os.environ[\"OPENAI_API_KEY\"], temperature=0, verbose=True)\ntoolkit = SQLDatabaseToolkit(db=db, llm=llm)\n\nagent_executor = create_sql_agent(\n llm=OpenAI(temperature=0),\n toolkit=toolkit,\n verbose=True,\n prefix= '''\n You are an agent designed to interact with a SQL database called SingleStore. This sometimes has Shard and Sort keys in the table schemas, which you can ignore. \n \\nGiven an input question, create a syntactically correct MySQL query to run, then look at the results of the query and return the answer. \n \\n If you are asked about similarity questions, you should use the DOT_PRODUCT function.\n \n \\nHere are a few examples of how to use the DOT_PRODUCT function:\n \\nExample 1:\n Q: how similar are the questions and answers?\n A: The query used to find this is:\n \n select question, answer, dot_product(question_embedding, answer_embedding) as similarity from embeddings;\n \n \\nExample 2:\n Q: What are the most similar questions in the embeddings table, not including itself?\n A: The query used to find this answer is:\n \n SELECT q1.question as question1, q2.question as question2, DOT_PRODUCT(q1.question_embedding, q2.question_embedding) :> float as score\n FROM embeddings q1, embeddings q2 \n WHERE question1 != question2 \n ORDER BY score DESC LIMIT 5;\n \n \\nExample 3:\n Q: In the embeddings table, which rows are from the chatbot?\n A: The query used to find this answer is:\n \n SELECT category, question, answer FROM embeddings\n WHERE category = 'chatbot';\n\n \\nIf you are asked to describe the database, you should run the query SHOW TABLES \n \\nUnless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n \\n The question embeddings and answer embeddings are very long, so do not show them unless specifically asked to.\n \\nYou can order the results by a relevant column to return the most interesting examples in the database.\n \\nNever query for all the columns from a specific table, only ask for the relevant columns given the question.\n \\nYou have access to tools for interacting with the database.\\nOnly use the below tools. \n Only use the information returned by the below tools to construct your final answer.\n \\nYou MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again up to 3 times.\n \\n\\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n \\n\\nIf the question does not seem related to the database, just return \"I don\\'t know\" as the answer.\\n,\n \n ''',\n format_instructions='''Use the following format:\\n\n \\nQuestion: the input question you must answer\n \\nThought: you should always think about what to do\n \\nAction: the action to take, should be one of [{tool_names}]\n \\nAction Input: the input to the action\n \\nObservation: the result of the action\n \\nThought: I now know the final answer\n \\nFinal Answer: the final answer to the original input question\n \\nSQL Query used to get the Answer: the final sql query used for the final answer'\n ''',\n top_k=3,\n max_iterations=5\n)" - }, - { - "cell_type": "markdown", - "id": "a993b299-200e-48e0-886a-6eba2daafe35", - "metadata": { - "language": "python" - }, - "source": "### Create function that processes user question with a check in Semantic Cache Layer" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "be7f7f12-13ee-42bc-a6c7-c5743642bd62", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "table_name = 'embeddings'\nsimilarity_threshold = .97\n\ndef process_user_question(question):\n print(f'\\nQuestion asked: {question}')\n category = 'chatbot'\n \n # Get vector embedding from the original question and calculate the elapsed time\n start_time = time.time()\n question_embedding= [np.array(x, ' float as score from embeddings where category=\"chatbot\" order by score desc limit 1;'\n \n\n with s2_conn.cursor() as cur:\n start_time = time.time()\n cur.execute(stmt, params)\n row = cur.fetchone()\n elapsed_time = (time.time() - start_time) * 1000\n print(f\"Execution time for checking existing questions: {elapsed_time:.2f} milliseconds\")\n \n try:\n question2, answer, score = row\n print(f\"\\nClosest Matching row:\\nQuestion: {question2}\\nAnswer: {answer}\\nSimilarity Score: {score}\")\n\n if score > similarity_threshold:\n print('Action to take: Using existing answer')\n return answer\n\n else:\n print('Action to take: Running agent_executor')\n start_time = time.time()\n answer2 = agent_executor.run(question)\n elapsed_time = (time.time() - start_time) * 1000\n print(f\"agent_executor execution time: {elapsed_time:.2f} milliseconds\")\n\n # Get current time\n created_at = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n\n # Get the answer embedding and calculate the elapsed time\n start_time = time.time()\n answer_embedding = [np.array(x, '\n- [Back to Contents](#contents)\n# Add Voice Recognition and Speech" - }, - { - "cell_type": "markdown", - "id": "f4ad3d62-554d-43b9-af75-862efee6e001", - "metadata": { - "language": "python" - }, - "source": "### Select a voice" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cc2390de-f4e3-4d33-9593-f829a7d40d85", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "from elevenlabs import generate, stream, voices\nfrom elevenlabs import set_api_key\nfrom IPython.display import Audio\nfrom IPython.display import display\nimport requests" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9b098298-ce68-46ba-b962-bc08226ca955", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "voices = voices()\nvoices[0]" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c2001b20-6d6b-4a34-8716-7f295b7abc53", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "CHUNK_SIZE = 1024\nurl = \"https://api.elevenlabs.io/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM/stream\"\n\nheaders = {\n \"Accept\": \"audio/mpeg\",\n \"Content-Type\": \"application/json\",\n \"xi-api-key\": elevenlabs_apikey\n}\n\ndata = {\n \"text\": answer,\n \"model_id\": \"eleven_monolingual_v1\",\n \"voice_settings\": {\n \"stability\": 0.5,\n \"similarity_boost\": 0.5\n }\n}\n\nresponse = requests.post(url, json=data, headers=headers, stream=True)\n\n# create an audio file\nwith open('output.mp3', 'wb') as f:\n for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n if chunk:\n f.write(chunk)\n" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3ba4d543-6df1-4089-b054-7c149d9a3324", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "!ls" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8bbffa96-ed40-40ea-b424-a32b5f1b9a9f", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "audio_file = 'output.mp3'\n\naudio = Audio(filename=audio_file, autoplay =True)\ndisplay(audio)" - }, - { - "cell_type": "markdown", - "id": "6d904504-c20b-4ca9-bc36-8c9288c4c4f4", - "metadata": { - "language": "python" - }, - "source": "### Transcribe the audio file" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f991542-c92a-498c-ba7e-c37af7bbc491", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "openai.api_key = openai_apikey\naudio_file= open(\"output.mp3\", \"rb\")\ntranscript = openai.Audio.transcribe(\"whisper-1\", audio_file)\nprint(transcript[\"text\"])" - }, - { - "cell_type": "markdown", - "id": "c6d005ea-9979-4c62-b09b-0888ec17da12", - "metadata": { - "language": "python" - }, - "source": "\n- [Back to Demo Architecture](#architecture)\n# Tying it together with Image data" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "290da6ad-3ea5-426e-8d6c-3b226f00cad4", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "# Most recent news article for TSLA\nquestion_3 = \"\"\"What is the most recent news article for Amazon where the topic_relevance_score is greater than 90%? \nInclude the url, time published and banner image.\"\"\"\nanswer = process_user_question(question_3)\nprint(f'The answer is: {answer}')" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7c18a63c-13c4-40e8-b235-55bc6f04fd28", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nSELECT title, url, time_published, banner_image FROM newsSentiment WHERE ticker = 'AMZN' AND topic_relevance_score > 0.9 ORDER BY time_published DESC LIMIT 3" - }, - { - "cell_type": "markdown", - "id": "a3076d45-a48e-4a90-811f-e4fb9e01c7e6", - "metadata": { - "language": "python" - }, - "source": "### Load the image" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "672be099-e988-4739-9932-0a6f23bcc844", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "import matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nfrom io import BytesIO\nbanner_image_url = \"https://staticx-tuner.zacks.com/images/default_article_images/default341.jpg\"\nresponse = requests.get(banner_image_url)\n\nif response.status_code == 200:\n img = mpimg.imread(BytesIO(response.content), format='JPG')\n imgplot = plt.imshow(img)\n plt.show()\nelse:\n print(f\"Failed to retrieve the image. Status code: {response.status_code}\")" - }, - { - "cell_type": "markdown", - "id": "7b4528e9-4545-41d0-9a36-b84141e9850c", - "metadata": { - "language": "python" - }, - "source": "### Set up the huggingface transformer" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6848e943-4cd8-445e-840d-f9d13b4391f6", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "transformers_version = \"v4.29.0\" #@param [\"main\", \"v4.29.0\"] {allow-input: true}\n\nprint(f\"Setting up everything with transformers version {transformers_version}\")\n\n!pip install huggingface_hub>=0.14.1 git+https://github.com/huggingface/transformers@$transformers_version -q diffusers accelerate datasets torch soundfile sentencepiece opencv-python openai\n" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7b77f62b-3f57-4335-bae4-27f5f74abf70", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "import IPython\nimport soundfile as sf\n\ndef play_audio(audio):\n sf.write(\"speech_converted.wav\", audio.numpy(), samplerate=16000)\n return IPython.display.Audio(\"speech_converted.wav\")\n\nfrom huggingface_hub import notebook_login\nnotebook_login()" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6b2ceeee-6d95-4aa5-83fd-9651be326e59", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "agent_name = \"OpenAI (API Key)\" #@param [\"StarCoder (HF Token)\", \"OpenAssistant (HF Token)\", \"OpenAI (API Key)\"]\n\nif agent_name == \"StarCoder (HF Token)\":\n from transformers.tools import HfAgent\n agent = HfAgent(\"https://api-inference.huggingface.co/models/bigcode/starcoder\")\n print(\"StarCoder is initialized 💪\")\nelif agent_name == \"OpenAssistant (HF Token)\":\n from transformers.tools import HfAgent\n agent = HfAgent(url_endpoint=\"https://api-inference.huggingface.co/models/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5\")\n print(\"OpenAssistant is initialized 💪\")\nif agent_name == \"OpenAI (API Key)\":\n from transformers.tools import OpenAiAgent\n pswd = openai_apikey\n agent = OpenAiAgent(model=\"text-davinci-003\", api_key=pswd)\n print(\"OpenAI is initialized 💪\")" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eed4814a-8a7e-41f6-956b-51c7debc1fff", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "caption = agent.run(\"Can you caption the `image`?\", image=img)" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "71e8f5dd-ab27-415e-a0b6-423c497232ef", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "data = {\n \"text\": caption,\n \"model_id\": \"eleven_monolingual_v1\",\n \"voice_settings\": {\n \"stability\": 0.5,\n \"similarity_boost\": 0.5\n }\n}\n\nresponse = requests.post(url, json=data, headers=headers)\nwith open('output.mp3', 'wb') as f:\n for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n if chunk:\n f.write(chunk)\n\naudio_file = 'output.mp3'\n\naudio = Audio(filename=audio_file, autoplay =True)\ndisplay(audio)" - }, - { - "cell_type": "markdown", - "id": "de4c4db5-d068-41ef-aa85-0657c6c450a9", - "metadata": { - "language": "python" - }, - "source": "\n- [Back to Contents](#contents)\n# Conclusion" - }, - { - "cell_type": "markdown", - "id": "faff70cf-728f-4bb3-b744-ba7efb195e10", - "metadata": { - "language": "python" - }, - "source": "- Handle transactional and analytical queries with your vector data\n- no need to export data out of SingleStore to another vector db\n- Scan vectors fast with exact nearest neighbor. (DOT_PRODUCT, EUCLIDEAN_DISTANCE, and VECTOR_SUB are high-perf functions using single-instruction-multiple-data (SIMD) processor instructions)\n- Ability to stream data directly into SingleStore\n- Use SingleStore as Semantic Cache Layer leveraging the Plancache. No need for a cache layer.\n- Easily scale the workspace for your workload\n- handle reads and writes in parallel\n- Use of external functions. \n" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "13bff7c9-a7c5-4807-84df-e9f7490f4627", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "21e59bb1-bf4f-4aa7-bf7a-92f8e4f19dd7", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b07e2d81-473d-4035-9cbf-fe66007362bf", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "808e304b-2515-449a-8cec-8f3a3a38ed4b", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "93e4e0da-a887-4cd7-b70c-475710ece772", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - }, - { - "cell_type": "markdown", - "id": "17b69461-5ceb-42ff-9986-2092b5670f58", - "metadata": { - "language": "python" - }, - "source": "# Reset Demo" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4ae2913a-ee2b-40f0-94b3-cb75c9891aea", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "%%sql\nDROP DATABASE llm_webinar;" - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eeb7d04b-df99-457b-96c3-9b0967f00c6c", - "metadata": { - "language": "python" - }, - "outputs": [], - "source": "" - } - ], - "metadata": { - "jupyterlab": { - "notebooks": { - "version_major": 6, - "version_minor": 4 - } - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimeType": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.4" - }, - "singlestore_cell_default_language": "python", - "singlestore_connection": { - "connectionID": "ee66326b-0803-4fdb-8b7f-d6415f18d4c8", - "defaultDatabase": "llm_webinar" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme b/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme deleted file mode 100644 index 8b137891..00000000 --- a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/readme +++ /dev/null @@ -1 +0,0 @@ - diff --git a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/meta.toml similarity index 86% rename from notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml rename to notebooks/how-to-build-llm-apps-that-can-see-hear-speak/meta.toml index dec289e9..6dc766ac 100644 --- a/notebooks/How-to-Build-LLM-Apps-that-can-See-Hear-Speak/meta.toml +++ b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/meta.toml @@ -4,5 +4,5 @@ description="""\ Using OpenAI to build a an app that can take images, audio, and text data to generate output """ icon="chart-network" -tags=["Advanced", "OpenAI", "genAI"] +tags=["advanced", "openai", "genai"] destinations=["spaces"] diff --git a/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb new file mode 100644 index 00000000..4b40b1ae --- /dev/null +++ b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb @@ -0,0 +1,1431 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "4bded9c9-d911-4f57-830c-9aec92b7f505", + "metadata": {}, + "source": [ + "
\n", + "
\n", + " \n", + "
\n", + "
\n", + "
SingleStore Notebooks
\n", + "

How to Build LLM Apps that can See Hear Speak

\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "215c4617-6ebd-43fc-aa25-904fec4bdf5e", + "metadata": {}, + "source": [ + "# How to Build LLM Apps that can See, Hear, Speak" + ] + }, + { + "cell_type": "markdown", + "id": "a2a7fa17-ff2a-4abf-922d-af00514ab87e", + "metadata": {}, + "source": [ + "\n", + "- [Back to Contents](#contents)\n", + "# Demo Architecture\n", + "![Image Alt Text](https://drive.google.com/uc?id=14LYlMDIroDDXHel4hCaOR1EFg_BuYb9P)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f035321e-d2b9-4576-9219-fe2f89e7cbe2", + "metadata": {}, + "outputs": [], + "source": [ + "!python --version" + ] + }, + { + "cell_type": "markdown", + "id": "c9938d9e-5f18-4c25-9dbe-207dc8c6f91b", + "metadata": {}, + "source": [ + "\n", + "# Contents:\n", + "- [Demo Architecture](#architecture)\n", + "- [Step 1: SingleStore DDLs](#ddl)\n", + "- [Step 2: Packages and imports](#imports)\n", + "- [Step 3: Ingest from data sources](#ingest)\n", + "- [Step 4: Connect SingleStore to Open AI's LLM with Langchain](#connect_s2)\n", + "- [Step 5: Add Voice Recognition and Speech](#speech)\n", + "- [Step 6: Tying it together with Image data](#image)\n", + "- [Conclusion](#conclusion)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "96d5cbe6-59c0-4cbf-bb7d-75683e24c51a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "72d63784-9e1b-47fb-a962-70da21b7128c", + "metadata": {}, + "source": [ + "\n", + "- [Back to Contents](#contents)\n", + "- # Setup SingleStore DDLs" + ] + }, + { + "cell_type": "markdown", + "id": "5cdc0633-6480-478d-a9fd-9af7ee2b2c24", + "metadata": {}, + "source": [ + "Create and use the database llm_webinar" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "35d1dd68-4280-481d-aefd-954c609b184d", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE DATABASE llm_webinar;" + ] + }, + { + "cell_type": "markdown", + "id": "a846eff5-74e7-410a-a51a-2a58da119e81", + "metadata": {}, + "source": [ + "Create tables" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "728002a2-663e-48fd-8153-9c1a50b03bbb", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE TABLE `stockTable` (\n", + "`ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n", + "`created_at` datetime DEFAULT NULL,\n", + "`open` float DEFAULT NULL,\n", + "`high` float DEFAULT NULL,\n", + "`low` float DEFAULT NULL,\n", + "`close` float DEFAULT NULL,\n", + "`volume` int(11) DEFAULT NULL,\n", + "SORT KEY (ticker, created_at desc),\n", + "SHARD KEY (ticker)\n", + ");\n", + "\n", + "CREATE TABLE newsSentiment (\n", + " title TEXT CHARACTER SET utf8mb4,\n", + " url TEXT,\n", + " time_published DATETIME,\n", + " authors TEXT,\n", + " summary TEXT CHARACTER SET utf8mb4,\n", + " banner_image TEXT,\n", + " source TEXT,\n", + " category_within_source TEXT,\n", + " source_domain TEXT,\n", + " topic TEXT,\n", + " topic_relevance_score TEXT,\n", + " overall_sentiment_score REAL,\n", + " overall_sentiment_label TEXT,\n", + " `ticker` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n", + " ticker_relevance_score DECIMAL(10, 6),\n", + " ticker_sentiment_score DECIMAL(10, 6),\n", + " ticker_sentiment_label TEXT,\n", + " SORT KEY (`ticker`,`time_published` DESC),\n", + " SHARD KEY `__SHARDKEY` (`ticker`,`time_published` DESC),\n", + " KEY(ticker) USING HASH,\n", + " KEY(authors) USING HASH,\n", + " KEY(source) USING HASH,\n", + " KEY(overall_sentiment_label) USING HASH,\n", + " KEY(ticker_sentiment_label) USING HASH\n", + ");\n", + "\n", + "CREATE ROWSTORE REFERENCE TABLE companyInfo (\n", + " ticker VARCHAR(10) PRIMARY KEY,\n", + " AssetType VARCHAR(50),\n", + " Name VARCHAR(100),\n", + " Description TEXT,\n", + " CIK VARCHAR(10),\n", + " Exchange VARCHAR(10),\n", + " Currency VARCHAR(10),\n", + " Country VARCHAR(50),\n", + " Sector VARCHAR(50),\n", + " Industry VARCHAR(250),\n", + " Address VARCHAR(100),\n", + " FiscalYearEnd VARCHAR(20),\n", + " LatestQuarter DATE,\n", + " MarketCapitalization BIGINT,\n", + " EBITDA BIGINT,\n", + " PERatio DECIMAL(10, 2),\n", + " PEGRatio DECIMAL(10, 3),\n", + " BookValue DECIMAL(10, 2),\n", + " DividendPerShare DECIMAL(10, 2),\n", + " DividendYield DECIMAL(10, 4),\n", + " EPS DECIMAL(10, 2),\n", + " RevenuePerShareTTM DECIMAL(10, 2),\n", + " ProfitMargin DECIMAL(10, 4),\n", + " OperatingMarginTTM DECIMAL(10, 4),\n", + " ReturnOnAssetsTTM DECIMAL(10, 4),\n", + " ReturnOnEquityTTM DECIMAL(10, 4),\n", + " RevenueTTM BIGINT,\n", + " GrossProfitTTM BIGINT,\n", + " DilutedEPSTTM DECIMAL(10, 2),\n", + " QuarterlyEarningsGrowthYOY DECIMAL(10, 3),\n", + " QuarterlyRevenueGrowthYOY DECIMAL(10, 3),\n", + " AnalystTargetPrice DECIMAL(10, 2),\n", + " TrailingPE DECIMAL(10, 2),\n", + " ForwardPE DECIMAL(10, 2),\n", + " PriceToSalesRatioTTM DECIMAL(10, 3),\n", + " PriceToBookRatio DECIMAL(10, 2),\n", + " EVToRevenue DECIMAL(10, 3),\n", + " EVToEBITDA DECIMAL(10, 2),\n", + " Beta DECIMAL(10, 3),\n", + " 52WeekHigh DECIMAL(10, 2),\n", + " 52WeekLow DECIMAL(10, 2),\n", + " 50DayMovingAverage DECIMAL(10, 2),\n", + " 200DayMovingAverage DECIMAL(10, 2),\n", + " SharesOutstanding BIGINT,\n", + " DividendDate DATE,\n", + " ExDividendDate DATE\n", + ");\n", + "\n", + "CREATE TABLE `embeddings` (\n", + "`id` bigint(11) NOT NULL AUTO_INCREMENT,\n", + "`category` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci DEFAULT NULL,\n", + "`question` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n", + "`question_embedding` longblob,\n", + "`answer` longtext CHARACTER SET utf8 COLLATE utf8_general_ci,\n", + "`answer_embedding` longblob,\n", + "`created_at` datetime DEFAULT NULL,\n", + "UNIQUE KEY `PRIMARY` (`id`) USING HASH,\n", + "SHARD KEY `__SHARDKEY` (`id`),\n", + "KEY `category` (`category`) USING HASH,\n", + "SORT KEY `__UNORDERED` (`created_at` DESC)\n", + ");" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "58f31787-6d9a-42cb-8bec-548e429f39de", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "SHOW TABLES;" + ] + }, + { + "cell_type": "markdown", + "id": "4fb79318-199c-4d33-97d9-3b8d381dcaba", + "metadata": {}, + "source": [ + "\n", + "- [Back to Contents](#contents)\n", + "# Install packages and imports" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "986a23fe-91d6-40cf-8ccf-8ff37f639014", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install elevenlabs --quiet\n", + "!pip install openai --quiet\n", + "!pip install matplotlib --quiet\n", + "!pip install scipy --quiet\n", + "!pip install scikit-learn --quiet\n", + "!pip install singlestoredb --quiet\n", + "!pip install langchain --quiet" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "819b9d83-28f6-49de-be48-82d29b315ab0", + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "import time\n", + "from datetime import datetime, timedelta\n", + "from datetime import datetime\n", + "import datetime\n", + "from dateutil.relativedelta import relativedelta\n", + "import singlestoredb as s2\n", + "import getpass\n", + "import openai\n", + "from langchain.sql_database import SQLDatabase\n", + "from langchain.llms.openai import OpenAI\n", + "from langchain.agents.agent_toolkits import SQLDatabaseToolkit\n", + "from langchain.agents import create_sql_agent\n", + "from openai.embeddings_utils import get_embeddings\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "id": "27b4b29e-b0c9-401e-a969-9fc770f7f6bd", + "metadata": {}, + "source": [ + "### Set API keys" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ce7134f0-4ba9-4a8c-b53d-1e42cfaf8d98", + "metadata": {}, + "outputs": [], + "source": [ + "alpha_vantage_apikey = getpass.getpass(\"enter alphavantage apikey here\")\n", + "openai_apikey = getpass.getpass(\"enter openai apikey here\")\n", + "elevenlabs_apikey = getpass.getpass(\"enter elevenlabs apikey here\")" + ] + }, + { + "cell_type": "markdown", + "id": "105bdb05-3cb5-4c1e-9cd1-b741bd3ab87a", + "metadata": {}, + "source": [ + "\n", + "- [Back to Contents](#contents)\n", + "# Ingest from data sources" + ] + }, + { + "cell_type": "markdown", + "id": "9c43af07-1bd3-43e8-9911-355966072ebe", + "metadata": {}, + "source": [ + "### Bring past two months of stock data" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c9595c3a-8b00-4d44-a6ab-32d2848459ad", + "metadata": {}, + "outputs": [], + "source": [ + "# set up connection to SingleStore and the ticker list\n", + "s2_conn = s2.connect(connection_url)\n", + "ticker_list = ['TSLA', 'AMZN', 'PLTR']" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2f2c5126-d102-4904-83f6-3a30bc4906b5", + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime\n", + "\n", + "def get_past_months(num_months):\n", + " today = datetime.today()\n", + " months = []\n", + "\n", + " for months_ago in range(0, num_months):\n", + " target_date = today - relativedelta(months=months_ago)\n", + " months.append(target_date.strftime('%Y-%m'))\n", + "\n", + " return months\n", + "\n", + "num_months = 2 # Number of months\n", + "year_month_list = get_past_months(num_months)\n", + "print(year_month_list)\n", + "\n", + "# pull intraday data for each stock and write to SingleStore\n", + "for ticker in ticker_list:\n", + " print(ticker)\n", + " data_list = []\n", + " for year_month in year_month_list:\n", + " print(year_month)\n", + "\n", + " intraday_price_url = \"https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={}&interval=5min&month={}&outputsize=full&apikey={}\".format(ticker, year_month, alpha_vantage_apikey)\n", + " r = requests.get(intraday_price_url)\n", + "\n", + " try:\n", + " data = r.json()['Time Series (5min)']\n", + " except:\n", + " time.sleep(1) # required to not hit API limits\n", + " continue\n", + "\n", + " for key in data:\n", + " document = data[key]\n", + " document['datetime'] = key\n", + " document['ticker'] = ticker\n", + "\n", + " document['open'] = document['1. open']\n", + " document['high'] = document['2. high']\n", + " document['low'] = document['3. low']\n", + " document['close'] = document['4. close']\n", + " document['volume'] = document['5. volume']\n", + "\n", + " document['open'] = float(document['open'])\n", + " document['high'] = float(document['high'])\n", + " document['low'] = float(document['low'])\n", + " document['close'] = float(document['close'])\n", + " document['volume'] = int(document['volume'])\n", + "\n", + "\n", + " del document['1. open']\n", + " del document['2. high']\n", + " del document['3. low']\n", + " del document['4. close']\n", + " del document['5. volume']\n", + "\n", + " data_list += [document]\n", + "\n", + " # Inside your loop, create the params dictionary with the correct values\n", + " params = {\n", + " 'datetime': document['datetime'],\n", + " 'ticker': ticker,\n", + " 'open': document['open'],\n", + " 'high': document['high'],\n", + " 'low': document['low'],\n", + " 'close': document['close'],\n", + " 'volume': document['volume']\n", + " }\n", + "\n", + " # Construct and execute the SQL statement\n", + " table_name = 'stockTable'\n", + " stmt = f\"INSERT INTO {table_name} (created_at, ticker, open, high, low, close, volume) VALUES (%(datetime)s, %(ticker)s, %(open)s, %(high)s, %(low)s, %(close)s, %(volume)s)\"\n", + "\n", + " with s2_conn.cursor() as cur:\n", + " cur.execute(stmt, params)\n", + " # time.sleep(1) # required to not hit API limits" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "fb534c0e-bfd9-47f6-a2be-7bd160ab9ab2", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "select count(*) from stockTable" + ] + }, + { + "cell_type": "markdown", + "id": "5e142437-c49b-4484-9475-35105cde45b2", + "metadata": {}, + "source": [ + "# Bring in Company data" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a4c9d7e8-5cd7-47d4-a188-cb660bd9c798", + "metadata": {}, + "outputs": [], + "source": [ + "# pull intraday data for each stock and write to SingleStore\n", + "for ticker in ticker_list:\n", + " print(ticker)\n", + " data_list = []\n", + " # for year_month in year_month_list:\n", + "\n", + " company_overview = \"https://www.alphavantage.co/query?function=OVERVIEW&symbol={}&outputsize=full&apikey={}\".format(ticker, alpha_vantage_apikey)\n", + " r = requests.get(company_overview)\n", + "\n", + " try:\n", + " data = r.json()\n", + " except:\n", + " time.sleep(3) # required to not hit API limits\n", + " continue\n", + "\n", + " data['CIK'] = int(data['CIK'])\n", + " data['MarketCapitalization']= float(data['MarketCapitalization'])\n", + " # Assuming data['EBITDA'] is a string containing 'None'\n", + " ebitda_str = data['EBITDA']\n", + " if ebitda_str.lower() == 'none':\n", + " # Handle the case where EBITDA is 'None', for example, you can set it to 0\n", + " data['EBITDA'] = 0.0\n", + " else:\n", + " # Convert the EBITDA string to a float\n", + " data['EBITDA'] = float(ebitda_str)\n", + "\n", + " PERatio_flt = data['PERatio']\n", + " if PERatio_flt.lower() == 'none':\n", + " # Handle the case where EVToRevenue is '-'\n", + " data['PERatio'] = 0.0 # You can use any default value that makes sense\n", + " else:\n", + " # Convert the EVToRevenue string to a float\n", + " data['PERatio'] = float(PERatio_flt)\n", + "\n", + " data['PEGRatio']= float(data['PEGRatio'])\n", + " data['BookValue']= float(data['BookValue'])\n", + " data['DividendPerShare']= float(data['DividendPerShare'])\n", + " data['DividendYield']= float(data['DividendYield'])\n", + " data['EPS']= float(data['EPS'])\n", + " data['RevenuePerShareTTM']= float(data['RevenuePerShareTTM'])\n", + " data['ProfitMargin']= float(data['ProfitMargin'])\n", + " data['OperatingMarginTTM']= float(data['OperatingMarginTTM'])\n", + " data['ReturnOnAssetsTTM']= float(data['ReturnOnAssetsTTM'])\n", + " data['ReturnOnEquityTTM']= float(data['ReturnOnEquityTTM'])\n", + " data['RevenueTTM']= int(data['RevenueTTM'])\n", + " data['GrossProfitTTM']= int(data['GrossProfitTTM'])\n", + " data['DilutedEPSTTM']= float(data['DilutedEPSTTM'])\n", + " data['QuarterlyEarningsGrowthYOY']= float(data['QuarterlyEarningsGrowthYOY'])\n", + " data['QuarterlyRevenueGrowthYOY']= float(data['QuarterlyRevenueGrowthYOY'])\n", + " data['AnalystTargetPrice']= float(data['AnalystTargetPrice'])\n", + " # Assuming data['TrailingPE'] is a string containing '-'\n", + " trailing_pe_str = data['TrailingPE']\n", + " if trailing_pe_str == '-':\n", + " # Handle the case where TrailingPE is '-'\n", + " data['TrailingPE'] = 0.0 # You can use any default value that makes sense\n", + " else:\n", + " try:\n", + " # Attempt to convert the TrailingPE string to a float\n", + " data['TrailingPE'] = float(trailing_pe_str)\n", + " except ValueError:\n", + " # Handle the case where the conversion fails (e.g., if it contains invalid characters)\n", + " data['TrailingPE'] = 0.0 # Set to a default value or handle as needed\n", + "\n", + "\n", + "\n", + " data['ForwardPE']= float(data['ForwardPE'])\n", + " data['PriceToSalesRatioTTM']= float(data['PriceToSalesRatioTTM'])\n", + " # Assuming data['EVToRevenue'] is a string containing '-'\n", + " PriceToBookRatio_flt = data['PriceToBookRatio']\n", + " if PriceToBookRatio_flt == '-':\n", + " # Handle the case where EVToRevenue is '-'\n", + " data['PriceToBookRatio'] = 0.0 # You can use any default value that makes sense\n", + " else:\n", + " # Convert the EVToRevenue string to a float\n", + " data['PriceToBookRatio'] = float(PriceToBookRatio_flt)\n", + "\n", + "\n", + " # Assuming data['EVToRevenue'] is a string containing '-'\n", + " ev_to_revenue_str = data['EVToRevenue']\n", + " if ev_to_revenue_str == '-':\n", + " # Handle the case where EVToRevenue is '-'\n", + " data['EVToRevenue'] = 0.0 # You can use any default value that makes sense\n", + " else:\n", + " # Convert the EVToRevenue string to a float\n", + " data['EVToRevenue'] = float(ev_to_revenue_str)\n", + "\n", + " # data['EVToEBITDA']= float(data['EVToEBITDA'])\n", + " # Assuming data['EVToRevenue'] is a string containing '-'\n", + " ev_to_EBITDA_str = data['EVToEBITDA']\n", + " if ev_to_revenue_str == '-':\n", + " # Handle the case where EVToRevenue is '-'\n", + " data['EVToEBITDA'] = 0.0 # You can use any default value that makes sense\n", + " else:\n", + " # Convert the EVToRevenue string to a float\n", + " data['EVToEBITDA'] = float(ev_to_EBITDA_str)\n", + "\n", + "\n", + " data['Beta']= float(data['Beta'])\n", + " data['52WeekHigh']= float(data['52WeekHigh'])\n", + " data['52WeekLow']= float(data['52WeekLow'])\n", + " data['50DayMovingAverage']= float(data['50DayMovingAverage'])\n", + " data['200DayMovingAverage']= float(data['200DayMovingAverage'])\n", + " data['SharesOutstanding']= int(data['SharesOutstanding'])\n", + " # description_embedding = [np.array(x, '\n", + "- [Back to Demo Architecture](#architecture)\n", + "# Connect SingleStore to Open AI's LLM with Langchain" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "1dd25cf2-bd39-4f25-b3a5-fe128c372e97", + "metadata": {}, + "outputs": [], + "source": [ + "os.environ[\"OPENAI_API_KEY\"] = openai_apikey\n", + "embedding_model = 'text-embedding-ada-002'\n", + "gpt_model = 'gpt-3.5-turbo-16k'\n", + "\n", + "# Create the agent executor\n", + "db = SQLDatabase.from_uri(connection_url, include_tables=['embeddings', 'companyInfo', 'newsSentiment', 'stockTable'], sample_rows_in_table_info=2)\n", + "llm = OpenAI(openai_api_key=os.environ[\"OPENAI_API_KEY\"], temperature=0, verbose=True)\n", + "toolkit = SQLDatabaseToolkit(db=db, llm=llm)\n", + "\n", + "agent_executor = create_sql_agent(\n", + " llm=OpenAI(temperature=0),\n", + " toolkit=toolkit,\n", + " verbose=True,\n", + " prefix= '''\n", + " You are an agent designed to interact with a SQL database called SingleStore. This sometimes has Shard and Sort keys in the table schemas, which you can ignore.\n", + " \\nGiven an input question, create a syntactically correct MySQL query to run, then look at the results of the query and return the answer.\n", + " \\n If you are asked about similarity questions, you should use the DOT_PRODUCT function.\n", + "\n", + " \\nHere are a few examples of how to use the DOT_PRODUCT function:\n", + " \\nExample 1:\n", + " Q: how similar are the questions and answers?\n", + " A: The query used to find this is:\n", + "\n", + " select question, answer, dot_product(question_embedding, answer_embedding) as similarity from embeddings;\n", + "\n", + " \\nExample 2:\n", + " Q: What are the most similar questions in the embeddings table, not including itself?\n", + " A: The query used to find this answer is:\n", + "\n", + " SELECT q1.question as question1, q2.question as question2, DOT_PRODUCT(q1.question_embedding, q2.question_embedding) :> float as score\n", + " FROM embeddings q1, embeddings q2\n", + " WHERE question1 != question2\n", + " ORDER BY score DESC LIMIT 5;\n", + "\n", + " \\nExample 3:\n", + " Q: In the embeddings table, which rows are from the chatbot?\n", + " A: The query used to find this answer is:\n", + "\n", + " SELECT category, question, answer FROM embeddings\n", + " WHERE category = 'chatbot';\n", + "\n", + " \\nIf you are asked to describe the database, you should run the query SHOW TABLES\n", + " \\nUnless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n", + " \\n The question embeddings and answer embeddings are very long, so do not show them unless specifically asked to.\n", + " \\nYou can order the results by a relevant column to return the most interesting examples in the database.\n", + " \\nNever query for all the columns from a specific table, only ask for the relevant columns given the question.\n", + " \\nYou have access to tools for interacting with the database.\\nOnly use the below tools.\n", + " Only use the information returned by the below tools to construct your final answer.\n", + " \\nYou MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again up to 3 times.\n", + " \\n\\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n", + " \\n\\nIf the question does not seem related to the database, just return \"I don\\'t know\" as the answer.\\n,\n", + "\n", + " ''',\n", + " format_instructions='''Use the following format:\\n\n", + " \\nQuestion: the input question you must answer\n", + " \\nThought: you should always think about what to do\n", + " \\nAction: the action to take, should be one of [{tool_names}]\n", + " \\nAction Input: the input to the action\n", + " \\nObservation: the result of the action\n", + " \\nThought: I now know the final answer\n", + " \\nFinal Answer: the final answer to the original input question\n", + " \\nSQL Query used to get the Answer: the final sql query used for the final answer'\n", + " ''',\n", + " top_k=3,\n", + " max_iterations=5\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a993b299-200e-48e0-886a-6eba2daafe35", + "metadata": {}, + "source": [ + "### Create function that processes user question with a check in Semantic Cache Layer" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "be7f7f12-13ee-42bc-a6c7-c5743642bd62", + "metadata": {}, + "outputs": [], + "source": [ + "table_name = 'embeddings'\n", + "similarity_threshold = .97\n", + "\n", + "def process_user_question(question):\n", + " print(f'\\nQuestion asked: {question}')\n", + " category = 'chatbot'\n", + "\n", + " # Get vector embedding from the original question and calculate the elapsed time\n", + " start_time = time.time()\n", + " question_embedding= [np.array(x, ' float as score from embeddings where category=\"chatbot\" order by score desc limit 1;'\n", + "\n", + "\n", + " with s2_conn.cursor() as cur:\n", + " start_time = time.time()\n", + " cur.execute(stmt, params)\n", + " row = cur.fetchone()\n", + " elapsed_time = (time.time() - start_time) * 1000\n", + " print(f\"Execution time for checking existing questions: {elapsed_time:.2f} milliseconds\")\n", + "\n", + " try:\n", + " question2, answer, score = row\n", + " print(f\"\\nClosest Matching row:\\nQuestion: {question2}\\nAnswer: {answer}\\nSimilarity Score: {score}\")\n", + "\n", + " if score > similarity_threshold:\n", + " print('Action to take: Using existing answer')\n", + " return answer\n", + "\n", + " else:\n", + " print('Action to take: Running agent_executor')\n", + " start_time = time.time()\n", + " answer2 = agent_executor.run(question)\n", + " elapsed_time = (time.time() - start_time) * 1000\n", + " print(f\"agent_executor execution time: {elapsed_time:.2f} milliseconds\")\n", + "\n", + " # Get current time\n", + " created_at = datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", + "\n", + " # Get the answer embedding and calculate the elapsed time\n", + " start_time = time.time()\n", + " answer_embedding = [np.array(x, '\n", + "- [Back to Contents](#contents)\n", + "# Add Voice Recognition and Speech" + ] + }, + { + "cell_type": "markdown", + "id": "f4ad3d62-554d-43b9-af75-862efee6e001", + "metadata": {}, + "source": [ + "### Select a voice" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "cc2390de-f4e3-4d33-9593-f829a7d40d85", + "metadata": {}, + "outputs": [], + "source": [ + "from elevenlabs import generate, stream, voices\n", + "from elevenlabs import set_api_key\n", + "from IPython.display import Audio\n", + "from IPython.display import display\n", + "import requests" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "9b098298-ce68-46ba-b962-bc08226ca955", + "metadata": {}, + "outputs": [], + "source": [ + "voices = voices()\n", + "voices[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "c2001b20-6d6b-4a34-8716-7f295b7abc53", + "metadata": {}, + "outputs": [], + "source": [ + "CHUNK_SIZE = 1024\n", + "url = \"https://api.elevenlabs.io/v1/text-to-speech/21m00Tcm4TlvDq8ikWAM/stream\"\n", + "\n", + "headers = {\n", + " \"Accept\": \"audio/mpeg\",\n", + " \"Content-Type\": \"application/json\",\n", + " \"xi-api-key\": elevenlabs_apikey\n", + "}\n", + "\n", + "data = {\n", + " \"text\": answer,\n", + " \"model_id\": \"eleven_monolingual_v1\",\n", + " \"voice_settings\": {\n", + " \"stability\": 0.5,\n", + " \"similarity_boost\": 0.5\n", + " }\n", + "}\n", + "\n", + "response = requests.post(url, json=data, headers=headers, stream=True)\n", + "\n", + "# create an audio file\n", + "with open('output.mp3', 'wb') as f:\n", + " for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n", + " if chunk:\n", + " f.write(chunk)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "3ba4d543-6df1-4089-b054-7c149d9a3324", + "metadata": {}, + "outputs": [], + "source": [ + "!ls" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "8bbffa96-ed40-40ea-b424-a32b5f1b9a9f", + "metadata": {}, + "outputs": [], + "source": [ + "audio_file = 'output.mp3'\n", + "\n", + "audio = Audio(filename=audio_file, autoplay =True)\n", + "display(audio)" + ] + }, + { + "cell_type": "markdown", + "id": "6d904504-c20b-4ca9-bc36-8c9288c4c4f4", + "metadata": {}, + "source": [ + "### Transcribe the audio file" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "9f991542-c92a-498c-ba7e-c37af7bbc491", + "metadata": {}, + "outputs": [], + "source": [ + "openai.api_key = openai_apikey\n", + "audio_file= open(\"output.mp3\", \"rb\")\n", + "transcript = openai.Audio.transcribe(\"whisper-1\", audio_file)\n", + "print(transcript[\"text\"])" + ] + }, + { + "cell_type": "markdown", + "id": "c6d005ea-9979-4c62-b09b-0888ec17da12", + "metadata": {}, + "source": [ + "\n", + "- [Back to Demo Architecture](#architecture)\n", + "# Tying it together with Image data" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "290da6ad-3ea5-426e-8d6c-3b226f00cad4", + "metadata": {}, + "outputs": [], + "source": [ + "# Most recent news article for TSLA\n", + "question_3 = \"\"\"What is the most recent news article for Amazon where the topic_relevance_score is greater than 90%?\n", + "Include the url, time published and banner image.\"\"\"\n", + "answer = process_user_question(question_3)\n", + "print(f'The answer is: {answer}')" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "7c18a63c-13c4-40e8-b235-55bc6f04fd28", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "SELECT title, url, time_published, banner_image FROM newsSentiment WHERE ticker = 'AMZN' AND topic_relevance_score > 0.9 ORDER BY time_published DESC LIMIT 3" + ] + }, + { + "cell_type": "markdown", + "id": "a3076d45-a48e-4a90-811f-e4fb9e01c7e6", + "metadata": {}, + "source": [ + "### Load the image" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "672be099-e988-4739-9932-0a6f23bcc844", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import matplotlib.image as mpimg\n", + "from io import BytesIO\n", + "banner_image_url = \"https://staticx-tuner.zacks.com/images/default_article_images/default341.jpg\"\n", + "response = requests.get(banner_image_url)\n", + "\n", + "if response.status_code == 200:\n", + " img = mpimg.imread(BytesIO(response.content), format='JPG')\n", + " imgplot = plt.imshow(img)\n", + " plt.show()\n", + "else:\n", + " print(f\"Failed to retrieve the image. Status code: {response.status_code}\")" + ] + }, + { + "cell_type": "markdown", + "id": "7b4528e9-4545-41d0-9a36-b84141e9850c", + "metadata": {}, + "source": [ + "### Set up the huggingface transformer" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "6848e943-4cd8-445e-840d-f9d13b4391f6", + "metadata": {}, + "outputs": [], + "source": [ + "transformers_version = \"v4.29.0\" #@param [\"main\", \"v4.29.0\"] {allow-input: true}\n", + "\n", + "print(f\"Setting up everything with transformers version {transformers_version}\")\n", + "\n", + "!pip install huggingface_hub>=0.14.1 git+https://github.com/huggingface/transformers@$transformers_version -q diffusers accelerate datasets torch soundfile sentencepiece opencv-python openai" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "7b77f62b-3f57-4335-bae4-27f5f74abf70", + "metadata": {}, + "outputs": [], + "source": [ + "import IPython\n", + "import soundfile as sf\n", + "\n", + "def play_audio(audio):\n", + " sf.write(\"speech_converted.wav\", audio.numpy(), samplerate=16000)\n", + " return IPython.display.Audio(\"speech_converted.wav\")\n", + "\n", + "from huggingface_hub import notebook_login\n", + "notebook_login()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "6b2ceeee-6d95-4aa5-83fd-9651be326e59", + "metadata": {}, + "outputs": [], + "source": [ + "agent_name = \"OpenAI (API Key)\" #@param [\"StarCoder (HF Token)\", \"OpenAssistant (HF Token)\", \"OpenAI (API Key)\"]\n", + "\n", + "if agent_name == \"StarCoder (HF Token)\":\n", + " from transformers.tools import HfAgent\n", + " agent = HfAgent(\"https://api-inference.huggingface.co/models/bigcode/starcoder\")\n", + " print(\"StarCoder is initialized \ud83d\udcaa\")\n", + "elif agent_name == \"OpenAssistant (HF Token)\":\n", + " from transformers.tools import HfAgent\n", + " agent = HfAgent(url_endpoint=\"https://api-inference.huggingface.co/models/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5\")\n", + " print(\"OpenAssistant is initialized \ud83d\udcaa\")\n", + "if agent_name == \"OpenAI (API Key)\":\n", + " from transformers.tools import OpenAiAgent\n", + " pswd = openai_apikey\n", + " agent = OpenAiAgent(model=\"text-davinci-003\", api_key=pswd)\n", + " print(\"OpenAI is initialized \ud83d\udcaa\")" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "eed4814a-8a7e-41f6-956b-51c7debc1fff", + "metadata": {}, + "outputs": [], + "source": [ + "caption = agent.run(\"Can you caption the `image`?\", image=img)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "71e8f5dd-ab27-415e-a0b6-423c497232ef", + "metadata": {}, + "outputs": [], + "source": [ + "data = {\n", + " \"text\": caption,\n", + " \"model_id\": \"eleven_monolingual_v1\",\n", + " \"voice_settings\": {\n", + " \"stability\": 0.5,\n", + " \"similarity_boost\": 0.5\n", + " }\n", + "}\n", + "\n", + "response = requests.post(url, json=data, headers=headers)\n", + "with open('output.mp3', 'wb') as f:\n", + " for chunk in response.iter_content(chunk_size=CHUNK_SIZE):\n", + " if chunk:\n", + " f.write(chunk)\n", + "\n", + "audio_file = 'output.mp3'\n", + "\n", + "audio = Audio(filename=audio_file, autoplay =True)\n", + "display(audio)" + ] + }, + { + "cell_type": "markdown", + "id": "de4c4db5-d068-41ef-aa85-0657c6c450a9", + "metadata": {}, + "source": [ + "\n", + "- [Back to Contents](#contents)\n", + "# Conclusion" + ] + }, + { + "cell_type": "markdown", + "id": "faff70cf-728f-4bb3-b744-ba7efb195e10", + "metadata": {}, + "source": [ + "- Handle transactional and analytical queries with your vector data\n", + "- no need to export data out of SingleStore to another vector db\n", + "- Scan vectors fast with exact nearest neighbor. (DOT_PRODUCT, EUCLIDEAN_DISTANCE, and VECTOR_SUB are high-perf functions using single-instruction-multiple-data (SIMD) processor instructions)\n", + "- Ability to stream data directly into SingleStore\n", + "- Use SingleStore as Semantic Cache Layer leveraging the Plancache. No need for a cache layer.\n", + "- Easily scale the workspace for your workload\n", + "- handle reads and writes in parallel\n", + "- Use of external functions." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "13bff7c9-a7c5-4807-84df-e9f7490f4627", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "21e59bb1-bf4f-4aa7-bf7a-92f8e4f19dd7", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "b07e2d81-473d-4035-9cbf-fe66007362bf", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "808e304b-2515-449a-8cec-8f3a3a38ed4b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "93e4e0da-a887-4cd7-b70c-475710ece772", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "17b69461-5ceb-42ff-9986-2092b5670f58", + "metadata": {}, + "source": [ + "# Reset Demo" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "4ae2913a-ee2b-40f0-94b3-cb75c9891aea", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "DROP DATABASE llm_webinar;" + ] + }, + { + "cell_type": "markdown", + "id": "b7292fcf-cb0d-454c-aec6-a883cb6816ff", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + } + ], + "metadata": { + "jupyterlab": { + "notebooks": { + "version_major": 6, + "version_minor": 4 + } + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimeType": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From ad753b2130ce750ceea7844cdecc146e39d6a07c Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Fri, 29 Sep 2023 11:21:26 -0500 Subject: [PATCH 04/24] Remove extra header --- notebooks/getting-started-with-dataframes/notebook.ipynb | 6 +++--- notebooks/getting-started-with-notebooks/notebook.ipynb | 2 +- .../notebook.ipynb | 8 -------- notebooks/hybrid-search/notebook.ipynb | 8 ++++++++ notebooks/integrating-with-pandas/notebook.ipynb | 2 +- 5 files changed, 13 insertions(+), 13 deletions(-) diff --git a/notebooks/getting-started-with-dataframes/notebook.ipynb b/notebooks/getting-started-with-dataframes/notebook.ipynb index 6a7a50f5..2e5cf573 100644 --- a/notebooks/getting-started-with-dataframes/notebook.ipynb +++ b/notebooks/getting-started-with-dataframes/notebook.ipynb @@ -212,7 +212,7 @@ "metadata": {}, "source": [ "The code below will create the table in the server from the given `DataFrame`. The data types for the database table will be inferred from\n", - "the `DataFrame` data types. The `force=True` is merely used here in case you run the notebook code multiple times against the same\n", + "the `DataFrame` data types. The `overwrite=True` is merely used here in case you run the notebook code multiple times against the same\n", "database. It will cause an existing `phones` table to be overwritten if it already exists." ] }, @@ -223,7 +223,7 @@ "metadata": {}, "outputs": [], "source": [ - "phones_tbl = conn.create_table('phones', phones_df, force=True)\n", + "phones_tbl = conn.create_table('phones', phones_df, overwrite=True)\n", "phones_tbl.head(3)" ] }, @@ -432,7 +432,7 @@ "metadata": {}, "outputs": [], "source": [ - "tbl_2 = conn.create_table('phones2', phones_tbl, force=True)\n", + "tbl_2 = conn.create_table('phones2', phones_tbl, overwrite=True)\n", "tbl_2" ] }, diff --git a/notebooks/getting-started-with-notebooks/notebook.ipynb b/notebooks/getting-started-with-notebooks/notebook.ipynb index 4bc7ecbf..63050e30 100644 --- a/notebooks/getting-started-with-notebooks/notebook.ipynb +++ b/notebooks/getting-started-with-notebooks/notebook.ipynb @@ -116,6 +116,7 @@ "df = pd.read_csv(url, index_col=0,\n", " # Use parse_date=, dtype=, and converters= to specify explicit data types\n", " parse_dates=['inspection_date'],\n", + " date_format='%m/%d/%Y %H:%M:%S %p',\n", " dtype=dict(business_id=int, business_phone_number=str, business_postal_code=str, inspection_score=float),\n", " converters=dict(business_location=str_to_shapely))\n", "df" @@ -194,7 +195,6 @@ "source": [ "%%sql\n", "DROP DATABASE IF EXISTS {{database_name}};\n", - "\n", "CREATE DATABASE {{database_name}};" ] }, diff --git a/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb index 4b40b1ae..2e38a0b7 100644 --- a/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb +++ b/notebooks/how-to-build-llm-apps-that-can-see-hear-speak/notebook.ipynb @@ -16,14 +16,6 @@ "" ] }, - { - "cell_type": "markdown", - "id": "215c4617-6ebd-43fc-aa25-904fec4bdf5e", - "metadata": {}, - "source": [ - "# How to Build LLM Apps that can See, Hear, Speak" - ] - }, { "cell_type": "markdown", "id": "a2a7fa17-ff2a-4abf-922d-af00514ab87e", diff --git a/notebooks/hybrid-search/notebook.ipynb b/notebooks/hybrid-search/notebook.ipynb index 2cf6ea1c..12c81643 100644 --- a/notebooks/hybrid-search/notebook.ipynb +++ b/notebooks/hybrid-search/notebook.ipynb @@ -211,6 +211,14 @@ "all_embeddings.shape" ] }, + { + "cell_type": "markdown", + "id": "d74c544f-feea-4d48-84be-c62bf5cb4ea3", + "metadata": {}, + "source": [ + "Merge embedding values into `data` rows." + ] + }, { "cell_type": "code", "execution_count": 10, diff --git a/notebooks/integrating-with-pandas/notebook.ipynb b/notebooks/integrating-with-pandas/notebook.ipynb index 1c107ae7..2e08b8f8 100644 --- a/notebooks/integrating-with-pandas/notebook.ipynb +++ b/notebooks/integrating-with-pandas/notebook.ipynb @@ -546,7 +546,7 @@ "metadata": {}, "outputs": [], "source": [ - "ibis_iris = ibis_conn.create_table('iris', iris, force=True)\n", + "ibis_iris = ibis_conn.create_table('iris', iris, overwrite=True)\n", "ibis_iris.limit(10).execute()" ] }, From 64d1101aaa8802635afe42a6278182936c3681ad Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Wed, 4 Oct 2023 12:05:16 -0500 Subject: [PATCH 05/24] Minor fixes --- notebooks/pipelines-query-tuning/meta.toml | 2 +- .../pipelines-query-tuning/notebook.ipynb | 92 ++++++++++++------- 2 files changed, 58 insertions(+), 36 deletions(-) diff --git a/notebooks/pipelines-query-tuning/meta.toml b/notebooks/pipelines-query-tuning/meta.toml index a8674aff..fdd7e933 100644 --- a/notebooks/pipelines-query-tuning/meta.toml +++ b/notebooks/pipelines-query-tuning/meta.toml @@ -3,6 +3,6 @@ title="Kafka Pipelines and Query Tuning" description="""\ Create a SingleStore pipeline to track the International Space Station and adjust queries & schema to optimize performance. """ -tags=["beginner", "kafka", "pipeline","querytuning"] +tags=["beginner", "kafka", "pipeline", "querytuning"] icon="database" destinations=["spaces"] diff --git a/notebooks/pipelines-query-tuning/notebook.ipynb b/notebooks/pipelines-query-tuning/notebook.ipynb index f4da0d13..7976f58a 100644 --- a/notebooks/pipelines-query-tuning/notebook.ipynb +++ b/notebooks/pipelines-query-tuning/notebook.ipynb @@ -41,11 +41,41 @@ { "cell_type": "code", "execution_count": 1, + "id": "854b5ad5-f2f7-434d-9d17-ea916516327f", + "metadata": {}, + "outputs": [], + "source": [ + "email_address = \"<< enter your email address >>\"" + ] + }, + { + "cell_type": "markdown", + "id": "f55ddc3c-00ec-4b28-8df6-edfbf0d66aba", + "metadata": {}, + "source": [ + "Remove characters that can't be used in a datbase name." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "3e6687cf-414f-490d-89fa-5c0f13814393", + "metadata": {}, + "outputs": [], + "source": [ + "import re\n", + "\n", + "modified_email_address = re.sub(r'[^A-Za-z0-9]', '_', email_address)\n", + "modified_email_address" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "id": "b3daf7fc-c60e-4c3b-a811-3338b94015ca", "metadata": {}, "outputs": [], "source": [ - "modified_email_address = \"insert your email\"\n", "%%sql\n", "DROP DATABASE IF EXISTS {{ modified_email_address }};\n", "CREATE DATABASE {{ modified_email_address }};\n", @@ -77,7 +107,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "id": "6af2f20a-8d80-4ff4-b56a-07db593157a5", "metadata": {}, "outputs": [], @@ -100,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "49316e8f-03b1-4dcc-a747-170135ccf7a0", "metadata": {}, "outputs": [], @@ -120,7 +150,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "6f36c4ff-a153-4acf-ba20-0b28a0ba75e4", "metadata": {}, "outputs": [], @@ -135,12 +165,12 @@ "id": "908c7e4c-fa9c-42b1-a164-6f410efb4f05", "metadata": {}, "source": [ - "### 5. Get the count of records. Run this a few time to see the number of records ingested." + "### 5. Get the count of records. Run this a few times to see the number of records ingested." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "e97f6065-9f42-4a32-9a15-fa06c4a1dda7", "metadata": {}, "outputs": [], @@ -160,7 +190,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "46a63ec2-bb8b-4887-b41a-42612e64c756", "metadata": {}, "outputs": [], @@ -183,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "bc4a122a-e86e-405d-a0ed-fb82dcc21816", "metadata": {}, "outputs": [], @@ -204,7 +234,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "id": "7efb3adb-bc12-4ca4-8eae-28703020af18", "metadata": {}, "outputs": [], @@ -226,7 +256,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "id": "94e46f4b-597e-4c71-b329-c4a3c3b8fff9", "metadata": {}, "outputs": [], @@ -246,7 +276,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "id": "196f0285-0c8f-4e71-8a7d-8237fcdc891e", "metadata": {}, "outputs": [], @@ -266,7 +296,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "id": "ddf2a7d5-050a-4146-b965-68a2aa6ce92c", "metadata": {}, "outputs": [], @@ -291,12 +321,12 @@ "source": [ "### 1. Restore the 'employees' database that has been backed up into a public S3 bucket\n", "\n", - "For the database name we'll prepend employee_ to the modified email address again." + "For the database name we'll prepend employees_ to the modified email address again." ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "id": "cb27d520-2141-450d-b0cf-925c12c32f3c", "metadata": {}, "outputs": [], @@ -318,13 +348,13 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "id": "bafa5dbc-f149-4465-ab16-83339e515abb", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "USE employees_<>;" + "USE employees_{{ modified_email_address }};" ] }, { @@ -337,12 +367,11 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "id": "41fb7c5b-e007-4d2c-a271-f91bc40a8405", "metadata": {}, "outputs": [], "source": [ - "%%sql\n", "%%sql\n", "\n", "SELECT e.first_name, e.last_name, d.dept_name, t.title, t.from_date, t.to_date\n", @@ -364,12 +393,11 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "id": "d58506b8-f97f-462c-a0e5-a15a93c8a7a5", "metadata": {}, "outputs": [], "source": [ - "%%sql\n", "%%sql\n", "\n", "EXPLAIN SELECT e.first_name, e.last_name, d.dept_name, t.title, t.from_date, t.to_date\n", @@ -391,12 +419,11 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "id": "0c35c2fd-67b2-4ddd-be8f-4e25f0e851b0", "metadata": {}, "outputs": [], "source": [ - "%%sql\n", "%%sql\n", "PROFILE SELECT e.first_name, e.last_name, d.dept_name, t.title, t.from_date, t.to_date\n", " FROM employees e\n", @@ -417,12 +444,11 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "id": "a45226d3-4a3e-442e-9800-90654ef8d045", "metadata": {}, "outputs": [], "source": [ - "%%sql\n", "%%sql\n", "SHOW PROFILE;" ] @@ -449,7 +475,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "id": "60599ab6-5c8e-4a49-a2cd-a4b201ff2f84", "metadata": {}, "outputs": [], @@ -475,13 +501,11 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, "id": "fdba3687-6430-4c30-8b50-177c528e54be", "metadata": {}, "outputs": [], "source": [ - "%%sql\n", - "%%sql\n", "%%sql\n", "-- CONTROL. Here is the original query. We can use this as our control in our experiment.\n", "SELECT e.first_name, e.last_name, d.dept_name, t.title, t.from_date, t.to_date\n", @@ -492,8 +516,6 @@ " ORDER BY e.first_name, e.last_name, d.dept_name, t.from_date\n", " LIMIT 10;\n", "\n", - "\n", - "\n", "-- IMPROVED. Here is the slightly more improved query with the departments_ref table\n", "SELECT e.first_name, e.last_name, d.dept_name, t.title, t.from_date, t.to_date\n", " FROM employees e\n", @@ -516,7 +538,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, "id": "8494132a-38cd-40e7-bcff-3d6a32eb25fb", "metadata": {}, "outputs": [], @@ -544,7 +566,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 23, "id": "40327756-cb80-444c-8745-f0646385d8da", "metadata": {}, "outputs": [], @@ -565,7 +587,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 24, "id": "7066ff30-e4f1-4105-aaa4-0369af08658d", "metadata": {}, "outputs": [], @@ -590,7 +612,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "id": "9b05ca85-78f7-4a4b-b4d9-779af58d8501", "metadata": {}, "outputs": [], @@ -611,7 +633,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, "id": "431ee5a9-9953-4891-9db5-effd0ec04320", "metadata": {}, "outputs": [], From 9a8edf02cfa9cd8461f157248cd4dc6855a5b02c Mon Sep 17 00:00:00 2001 From: arno756 Date: Wed, 4 Oct 2023 22:10:04 -0700 Subject: [PATCH 06/24] Update meta.toml --- notebooks/launch-open-source-apps-with-langchain/meta.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/launch-open-source-apps-with-langchain/meta.toml b/notebooks/launch-open-source-apps-with-langchain/meta.toml index d470014a..f0eb18d9 100644 --- a/notebooks/launch-open-source-apps-with-langchain/meta.toml +++ b/notebooks/launch-open-source-apps-with-langchain/meta.toml @@ -5,4 +5,4 @@ description="""\ """ icon="vector-circle" tags=["vectordb", "genai", "langchain"] -destinations=[] +destinations=[spaces] From 798f66cfcb8a46b4f2c8b6d03c12cf69e9404e00 Mon Sep 17 00:00:00 2001 From: arno756 Date: Wed, 4 Oct 2023 22:12:42 -0700 Subject: [PATCH 07/24] Adding a new notebook --- .../optimize-performance-with-tpch-100/meta.toml | 12 ++++++++++++ .../notebook.ipynb | 1 + 2 files changed, 13 insertions(+) create mode 100644 notebooks/optimize-performance-with-tpch-100/meta.toml create mode 100644 notebooks/optimize-performance-with-tpch-100/notebook.ipynb diff --git a/notebooks/optimize-performance-with-tpch-100/meta.toml b/notebooks/optimize-performance-with-tpch-100/meta.toml new file mode 100644 index 00000000..7562ad1c --- /dev/null +++ b/notebooks/optimize-performance-with-tpch-100/meta.toml @@ -0,0 +1,12 @@ +[meta] +title="Learn how to Optimize Performance with TPCH 100" +description="This notebook will help you understand how you can take advantage of SingleStoreDB distributed capability using TPCH-100. We recommend using a S2 or S4 workspace to see the difference in performance. +If you come from single node database, this is an important step to follow to scale your performance linearly as your data grows. + +You will see two areas: +*) Ingesting data using pipeline at a super fast speed (You will use a real-time embedded dashboard) +*) Compare query performance with an unoptimized database and an optimized database +" +icon="database" +tags=["performance", "benchmark", "tpch", "benchmark", "shardkey", "ingest"] +destinations=["spaces"] \ No newline at end of file diff --git a/notebooks/optimize-performance-with-tpch-100/notebook.ipynb b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb new file mode 100644 index 00000000..84137758 --- /dev/null +++ b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"attachments":null,"cell_type":"markdown","id":"8e67bcbe-6ace-4ca9-b28c-927b4b5a85b2","metadata":{"language":"sql"},"source":"
\n
\n \n
\n
\n
SingleStore Notebooks
\n

Learn How to Optimize Table Data Structures with TPCH Benchmark

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\n
"},{"attachments":null,"cell_type":"markdown","id":"5d93af8b-eb1d-4207-a060-1a45c46d8b41","metadata":{"language":"sql"},"source":"### Context\n\nThis notebook will help you with four core key principles for getting performance out of SingleStoreDB using TPCH Benchmark. SingleStoreDB is a distributed database, so you should think of using shard keys, database partitions, primary keys and indexes for getting the best performance out of it. \n\n##### About database partitions\nThe generalized recommendation for most clusters is to have 4 CPU cores per database partition on each leaf. This means if you had a cluster with 16 cores on each of 4 leaves (64 CPU cores total across all leaf hosts), you would want to have 4 partitions on each leaf (16 partitions throughout the cluster). If you are using a S00 workspace, you will have 2 partitions per database. ***Note*** *that increasing partitions will have additional memory and caching overheads, which can be expensive if you have thousands of tables*\n\n##### About shard keys\nData is distributed across the SingleStoreDB Cloud workspace into a number of partitions on the leaf nodes. The shard key is a collection of the columns in a table that are used to control how the rows of that table are distributed. To determine the partition responsible for a given row, SingleStoreDB Cloud computes a hash from all the columns in the shard key to the partition ID. Therefore, rows with the same shard key will reside on the same partition.\n\n##### About hash indexes\nThey are highly efficient for exact-match lookups (point-reads). Because hash indexes store rows in a sparse array of buckets indexed through a hash function on the relevant columns, queries can quickly retrieve data by examining only the corresponding bucket rather than searching the entire dataset. This enables significant reduction in lookup time and hence, increased performance for specific query types.\n\n**For that tutorial, we recommend using a workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.**"},{"attachments":null,"cell_type":"markdown","id":"67f041ef-5605-43ef-8ca0-5db3194b4cad","metadata":{"language":"sql"},"source":"
\n \n
\n

Note

\n

For that tutorial, we recommend using workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.

\n
\n
"},{"attachments":null,"cell_type":"markdown","id":"6052728d-7828-4fb2-bb53-b960a7ad43af","metadata":{"language":"sql"},"source":"### Let's first create the unoptimized database"},{"cell_type":"code","execution_count":null,"id":"7301a602-48cf-4f3b-9cbc-2e7184d97ae0","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\ncreate database if not exists s2_tpch_unoptimized\n\n# To create a database with custom partitions use the following syntax: CREATE DATABASE YourDatabaseName PARTITIONS=X;\n# You cannot change after creation the number of partitions"},{"attachments":null,"cell_type":"markdown","id":"94c8bb6f-658d-4434-9074-4847f1c7d721","metadata":{"language":"sql"},"source":"If using a S00, the database will have 2 partitions, if using S1, it will have 8 partitions"},{"cell_type":"code","execution_count":null,"id":"b36585b9-4d52-4301-ac68-60fa49425751","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nSELECT num_partitions FROM information_schema.DISTRIBUTED_DATABASES WHERE database_name = 's2_tpch_unoptimized';"},{"attachments":null,"cell_type":"markdown","id":"b576e31c-6a67-4126-86ab-480fd96805d3","metadata":{"language":"sql"},"source":"##### Let's create all the tables in that database with no index, shard key or primary key"},{"attachments":null,"cell_type":"markdown","id":"4587c575-9b5a-4535-bebe-70779064e9dc","metadata":{"execution":{"iopub.execute_input":"2023-10-02T05:17:36.998748Z","iopub.status.busy":"2023-10-02T05:17:36.998493Z","iopub.status.idle":"2023-10-02T05:17:37.009703Z","shell.execute_reply":"2023-10-02T05:17:37.009283Z","shell.execute_reply.started":"2023-10-02T05:17:36.998731Z"},"language":"sql"},"source":"
\n \n
\n

Action Required

\n

Make sure to select the s2_tpch_unoptimized database from the drop-down menu at the top of this notebook.\n It updates the connection_url to connect to that database.

\n
\n
"},{"cell_type":"code","execution_count":null,"id":"afde1362-2d38-4732-94ed-6d4ed05a6806","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE TABLE IF NOT EXISTS `customer` (\n `c_custkey` int(11) NOT NULL,\n `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_nationkey` int(11) NOT NULL,\n `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_acctbal` decimal(15,2) NOT NULL,\n `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `lineitem` (\n `l_orderkey` bigint(11) NOT NULL,\n `l_partkey` int(11) NOT NULL,\n `l_suppkey` int(11) NOT NULL,\n `l_linenumber` int(11) NOT NULL,\n `l_quantity` decimal(15,2) NOT NULL,\n `l_extendedprice` decimal(15,2) NOT NULL,\n `l_discount` decimal(15,2) NOT NULL,\n `l_tax` decimal(15,2) NOT NULL,\n `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipdate` date NOT NULL,\n `l_commitdate` date NOT NULL,\n `l_receiptdate` date NOT NULL,\n `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `nation` (\n `n_nationkey` int(11) NOT NULL,\n `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `n_regionkey` int(11) NOT NULL,\n `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `orders` (\n `o_orderkey` bigint(11) NOT NULL,\n `o_custkey` int(11) NOT NULL,\n `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_totalprice` decimal(15,2) NOT NULL,\n `o_orderdate` date NOT NULL,\n `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_shippriority` int(11) NOT NULL,\n `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `part` (\n `p_partkey` int(11) NOT NULL,\n `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_size` int(11) NOT NULL,\n `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_retailprice` decimal(15,2) NOT NULL,\n `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `partsupp` (\n `ps_partkey` int(11) NOT NULL,\n `ps_suppkey` int(11) NOT NULL,\n `ps_availqty` int(11) NOT NULL,\n `ps_supplycost` decimal(15,2) NOT NULL,\n `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `region` (\n `r_regionkey` int(11) NOT NULL,\n `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `supplier` (\n `s_suppkey` int(11) NOT NULL,\n `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_nationkey` int(11) NOT NULL,\n `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_acctbal` decimal(15,2) NOT NULL,\n `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);"},{"attachments":null,"cell_type":"markdown","id":"09711e8c-fb01-4e10-862b-ee5350be6076","metadata":{"language":"sql"},"source":"### Now let's create the pipelines and run them to ingest data"},{"cell_type":"code","execution_count":null,"id":"4e8ca124-ac4b-49de-b0ee-d9441d43bedd","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `customer_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/customer'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `customer`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"ce739af4-6839-4751-8a81-019fb26cad72","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `lineitem_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/lineitem/lineitem.'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `lineitem`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"bfdd5bbc-702a-4f77-b771-cd38189040e0","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `nation_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/nation'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `nation`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"1b040083-f864-4e64-9bd2-00b1ff7d1e2b","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `orders_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/orders'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `orders`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"b5e06dfe-f679-4fe2-bd47-802a0b127270","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `partsupp_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/partsupp'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `partsupp`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"8b2726ea-9d0c-4809-bf35-b851821cf336","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `part_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/part'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `part`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"06114a70-d7f9-4c1f-b6a6-4554b33bb5c6","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `region_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/region'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `region`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"bfc2e19d-f32c-4b9e-8fa7-1e68711f834e","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `supplier_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/supplier'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `supplier`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"e19cb045-bebc-4aa6-92d7-ae06778d8af8","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nSTART PIPELINE customer_pipeline;\nSTART PIPELINE lineitem_pipeline;\nSTART PIPELINE nation_pipeline;\nSTART PIPELINE orders_pipeline;\nSTART PIPELINE partsupp_pipeline;\nSTART PIPELINE part_pipeline;\nSTART PIPELINE region_pipeline;\nSTART PIPELINE supplier_pipeline;"},{"attachments":null,"cell_type":"markdown","id":"3eacdd09-9b27-4995-a3df-9514cd733a57","metadata":{"language":"sql"},"source":"#### [Optional Step] Check data ingestion in real-time with Perspective"},{"cell_type":"code","execution_count":null,"id":"e5c3fa1a-af9b-4fdb-98bc-9c73a1fa7f33","metadata":{"language":"python"},"outputs":[],"source":"pip install perspective-python --quiet"},{"cell_type":"code","execution_count":null,"id":"b61f205f-5d1d-4af2-8369-e31057c76f66","metadata":{"language":"python"},"outputs":[],"source":"import perspective\nimport threading\nimport random\nimport time\nfrom datetime import datetime, date\nfrom perspective import Table, PerspectiveWidget\nimport warnings\nwarnings.filterwarnings('ignore')"},{"cell_type":"code","execution_count":null,"id":"ac376696-0b7e-4182-bc04-ddef400b7fca","metadata":{"language":"python"},"outputs":[],"source":"def loop():\n while mode != 'stop':\n while mode == 'run':\n table.update(data_source())\n time.sleep(1)"},{"cell_type":"code","execution_count":null,"id":"5e2ce253-576d-49c9-a92b-f165ffcc4ae7","metadata":{"language":"python"},"outputs":[],"source":"def data_source():\n result = %sql select sum(rows_streamed) as rows_streamed from information_schema.pipelines_batches_summary where database_name = 's2_tpch_unoptimized';\n result2 = list(result.dicts()) \n return result2\n\nSCHEMA = {\n \"rows_streamed\": int\n}"},{"cell_type":"code","execution_count":null,"id":"d388a00d-23ec-45d2-a94c-5e747da707c0","metadata":{"language":"python"},"outputs":[],"source":"mode = 'run'\ntable = perspective.Table(SCHEMA, limit=100)\nthreading.Thread(target=loop).start()"},{"cell_type":"code","execution_count":null,"id":"9e88e523-63b1-48e3-bde5-a2840490199c","metadata":{"language":"python"},"outputs":[],"source":"perspective.PerspectiveWidget(table,title = \"Track Row Ingestion\",plugin=\"Y Line\",columns=[\"count_rows\"])"},{"cell_type":"code","execution_count":null,"id":"debbed63-11dc-43dc-9f12-a0e80a5b7703","metadata":{"language":"python"},"outputs":[],"source":"mode = 'stop'"},{"attachments":null,"cell_type":"markdown","id":"442281db-7fd2-4bba-9104-84f3b0537a9a","metadata":{"language":"sql"},"source":"### Now, let's see the performance of a few queries"},{"cell_type":"code","execution_count":null,"id":"97e9050b-3b8e-40e3-b871-2b0bb73eb5ae","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 1: Pricing Summary Report \nselect \n l_returnflag,\n l_linestatus,\n sum(l_quantity) as sum_qty,\n sum(l_extendedprice) as sum_base_price,\n sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n avg(l_discount) as avg_disc,\n count(*) as count_order \nfrom s2_tpch_unoptimized.lineitem\nwhere l_shipdate <= date('1998-12-01') - interval '90' day \ngroup by l_returnflag, l_linestatus \norder by l_returnflag, l_linestatus;"},{"cell_type":"code","execution_count":null,"id":"71669c07-d06e-41f4-bd63-5046add22afb","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 4: Order Priority Checking \nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_unoptimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_unoptimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;"},{"cell_type":"code","execution_count":null,"id":"654f872b-4a35-4897-86d2-c51b548919b8","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n-- TPC-H Query 21: Suppliers Who Kept Orders Waiting \n\nselect\n s_name,\n count(*) as numwait\nfrom\n s2_tpch_unoptimized.supplier,\n s2_tpch_unoptimized.lineitem l1,\n s2_tpch_unoptimized.orders,\n s2_tpch_unoptimized.nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n s2_tpch_unoptimized.lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n s2_tpch_unoptimized.lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;"},{"attachments":null,"cell_type":"markdown","id":"0ad2d768-cb53-4e0b-8353-6178c8f9508c","metadata":{"language":"sql"},"source":"### Now, let's first focus on optimizing the performance"},{"cell_type":"code","execution_count":null,"id":"d1844926-ae73-4fec-b5ba-802c8173e846","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\ncreate database if not exists s2_tpch_optimized"},{"attachments":null,"cell_type":"markdown","id":"a163696a-0507-4b05-9146-6cbfa1ba1e29","metadata":{"language":"sql"},"source":"
\n \n
\n

Action Required

\n

Make sure to select the s2_tpch_optimized database from the drop-down menu at the top of this notebook.\n It updates the connection_url to connect to that database.

\n
\n
"},{"attachments":null,"cell_type":"markdown","id":"bafd1114-f88c-409c-8281-b32ac27f1222","metadata":{"language":"sql"},"source":"##### Now, let's create each table with optimized data structure:\n* We create a unique key through primary key. For example **lineitem** table needs both the orderkey and linenumber to identify rows by uniqueness\n* We create a shard key which will distribute data in an efficient way to perform fast join and filtering. For **lineitem** table since we perform joins and calculation based on the orderkey we create a shardkey with orderkey"},{"cell_type":"code","execution_count":null,"id":"ff6aea3d-a965-475d-becd-3910965f5c8f","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE TABLE IF NOT EXISTS `lineitem` (\n `l_orderkey` bigint(11) NOT NULL,\n `l_partkey` int(11) NOT NULL,\n `l_suppkey` int(11) NOT NULL,\n `l_linenumber` int(11) NOT NULL,\n `l_quantity` decimal(15,2) NOT NULL,\n `l_extendedprice` decimal(15,2) NOT NULL,\n `l_discount` decimal(15,2) NOT NULL,\n `l_tax` decimal(15,2) NOT NULL,\n `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipdate` date NOT NULL,\n `l_commitdate` date NOT NULL,\n `l_receiptdate` date NOT NULL,\n `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`l_orderkey`,`l_linenumber`) USING HASH,\n SHARD KEY `__SHARDKEY` (`l_orderkey`),\n KEY `l_orderkey` (`l_orderkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `customer` (\n `c_custkey` int(11) NOT NULL,\n `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_nationkey` int(11) NOT NULL,\n `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_acctbal` decimal(15,2) NOT NULL,\n `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`c_custkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`c_custkey`),\n KEY `c_custkey` (`c_custkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `nation` (\n `n_nationkey` int(11) NOT NULL,\n `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `n_regionkey` int(11) NOT NULL,\n `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`n_nationkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`n_nationkey`),\n KEY `n_nationkey` (`n_nationkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `orders` (\n `o_orderkey` bigint(11) NOT NULL,\n `o_custkey` int(11) NOT NULL,\n `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_totalprice` decimal(15,2) NOT NULL,\n `o_orderdate` date NOT NULL,\n `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_shippriority` int(11) NOT NULL,\n `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`o_orderkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`o_orderkey`),\n KEY `o_orderkey` (`o_orderkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `part` (\n `p_partkey` int(11) NOT NULL,\n `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_size` int(11) NOT NULL,\n `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_retailprice` decimal(15,2) NOT NULL,\n `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`p_partkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`p_partkey`),\n KEY `p_partkey` (`p_partkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `partsupp` (\n `ps_partkey` int(11) NOT NULL,\n `ps_suppkey` int(11) NOT NULL,\n `ps_availqty` int(11) NOT NULL,\n `ps_supplycost` decimal(15,2) NOT NULL,\n `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`ps_partkey`,`ps_suppkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`ps_partkey`),\n KEY `ps_partkey` (`ps_partkey`,`ps_suppkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `region` (\n `r_regionkey` int(11) NOT NULL,\n `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`r_regionkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`r_regionkey`),\n KEY `r_regionkey` (`r_regionkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `supplier` (\n `s_suppkey` int(11) NOT NULL,\n `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_nationkey` int(11) NOT NULL,\n `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_acctbal` decimal(15,2) NOT NULL,\n `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`s_suppkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`s_suppkey`),\n KEY `s_suppkey` (`s_suppkey`) USING CLUSTERED COLUMNSTORE\n);"},{"cell_type":"code","execution_count":null,"id":"6ed484a7-8ed8-479d-9ebe-5716749369bc","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nINSERT INTO s2_tpch_optimized.nation SELECT * FROM s2_tpch_unoptimized.nation;\nINSERT INTO s2_tpch_optimized.lineitem SELECT * FROM s2_tpch_unoptimized.lineitem;\nINSERT INTO s2_tpch_optimized.customer SELECT * FROM s2_tpch_unoptimized.customer;\nINSERT INTO s2_tpch_optimized.orders SELECT * FROM s2_tpch_unoptimized.orders;\nINSERT INTO s2_tpch_optimized.part SELECT * FROM s2_tpch_unoptimized.part;\nINSERT INTO s2_tpch_optimized.partsupp SELECT * FROM s2_tpch_unoptimized.partsupp;\nINSERT INTO s2_tpch_optimized.region SELECT * FROM s2_tpch_unoptimized.region;\nINSERT INTO s2_tpch_optimized.supplier SELECT * FROM s2_tpch_unoptimized.supplier;"},{"cell_type":"code","execution_count":null,"id":"9c79d8a5-c626-4f14-85e2-1f00afbceb8f","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 1: Pricing Summary Report \nselect \n l_returnflag,\n l_linestatus,\n sum(l_quantity) as sum_qty,\n sum(l_extendedprice) as sum_base_price,\n sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n avg(l_discount) as avg_disc,\n count(*) as count_order \nfrom lineitem\nwhere l_shipdate <= date('1998-12-01') - interval '90' day \ngroup by l_returnflag, l_linestatus \norder by l_returnflag, l_linestatus;"},{"cell_type":"code","execution_count":null,"id":"e9b21e9b-1869-4a1e-8998-a209c3dc6ffd","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 4: Order Priority Checking \nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_optimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_optimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;"},{"cell_type":"code","execution_count":null,"id":"c8b63c2a-b1fb-4cd1-90bb-62e8b56922f5","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n-- TPC-H Query 21: Suppliers Who Kept Orders Waiting \n\nselect\n s_name,\n count(*) as numwait\nfrom\n s2_tpch_optimized.supplier,\n s2_tpch_optimized.lineitem l1,\n s2_tpch_optimized.orders,\n s2_tpch_optimized.nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n s2_tpch_optimized.lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n s2_tpch_optimized.lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;"},{"attachments":null,"cell_type":"markdown","id":"54a6902d-bc3b-455d-8f47-3450d5928de8","metadata":{"language":"sql"},"source":"### Finally, let's do a side by side comparison between the optimized and unoptimized database"},{"cell_type":"code","execution_count":null,"id":"2f23e742-d9fe-467a-a299-a09a20d2af1e","metadata":{"language":"python"},"outputs":[],"source":"from singlestoredb import create_engine\nimport sqlalchemy as sa\nconnection_url_unoptimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_unoptimized?ssl_cipher=HIGH\"\ndb_connection_unoptimized = create_engine(connection_url_unoptimized).connect()\nconnection_url_optimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_optimized?ssl_cipher=HIGH\"\ndb_connection_optimized = create_engine(connection_url_optimized).connect()"},{"attachments":null,"cell_type":"markdown","id":"7f84ed59-9d2c-4e3e-92eb-63603645d953","metadata":{"language":"sql"},"source":"Here are a few queries that you can test side by side against. Overall you will notice an average of 4x improvement in performance"},{"cell_type":"code","execution_count":null,"id":"f3d86d62-ffe2-40ad-b59a-7c77cae98ca0","metadata":{"language":"python"},"outputs":[],"source":"sql_query4 = sa.text('''\nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_unoptimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_unoptimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;\n''')"},{"cell_type":"code","execution_count":null,"id":"7d947658-6dec-4efa-97f6-863977b2003b","metadata":{"language":"python"},"outputs":[],"source":"sql_query21 = sa.text('''\n select\n s_name,\n count(*) as numwait\nfrom\n supplier,\n lineitem l1,\n orders,\n nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;\n''')"},{"cell_type":"code","execution_count":null,"id":"6e4da6ac-52ff-4506-8826-3a46bf350656","metadata":{"language":"python"},"outputs":[],"source":"result = db_connection_optimized.execute(sql_query21)"},{"cell_type":"code","execution_count":null,"id":"b699bc42-e9bd-4b8f-81c0-48311b7fd14e","metadata":{"language":"python"},"outputs":[],"source":"import time\nimport pandas as pd\nimport plotly.graph_objs as go\nnum_iterations = 10\nopt_times = []\n\nfor i in range(num_iterations):\n opt_start_time = time.time()\n opt_result = db_connection_optimized.execute(sql_query21)\n opt_stop_time = time.time()\n opt_times.append(opt_stop_time - opt_start_time)\n\nunopt_times = []\nfor i in range(num_iterations):\n unopt_start_time = time.time()\n unopt_result = db_connection_unoptimized.execute(sql_query21)\n unopt_stop_time = time.time()\n unopt_times.append(unopt_stop_time - unopt_start_time)\n\nx_axis = list(range(1, num_iterations + 1))\ndata = {\n 'iteration': x_axis,\n 'opt_times': opt_times,\n 'unopt_times': unopt_times,\n}\ndf = pd.DataFrame.from_dict(data)\n\nfig = go.Figure()\n\n# Adding optimized times to the plot\nfig.add_trace(go.Scatter(x=df['iteration'], y=df['opt_times'], mode='lines+markers', name='Optimized Database'))\n\n# Adding unoptimized times to the plot\nfig.add_trace(go.Scatter(x=df['iteration'], y=df['unopt_times'], mode='lines+markers', name='Unoptimized Database'))\n\n# Update y-axis and x-axis properties\nfig.update_layout(\n title=\"Execution Time Comparison\",\n xaxis_title=\"Iteration\",\n yaxis_title=\"Time in Seconds\",\n xaxis=dict(tickmode='array', tickvals=list(range(1, num_iterations + 1)))\n)\n\n# Show the plot\nfig.show()"},{"attachments":null,"cell_type":"markdown","id":"4708ffe5-ea88-48a8-a4ac-9eaa5f801f79","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimeType":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"s2_tpch_optimized"}},"nbformat":4,"nbformat_minor":5} \ No newline at end of file From 4010bb9f512e7c0d7195aae4777b5c4058056f16 Mon Sep 17 00:00:00 2001 From: arno756 Date: Wed, 4 Oct 2023 22:14:39 -0700 Subject: [PATCH 08/24] Update meta.toml --- notebooks/launch-open-source-apps-with-langchain/meta.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/launch-open-source-apps-with-langchain/meta.toml b/notebooks/launch-open-source-apps-with-langchain/meta.toml index f0eb18d9..b25f69c6 100644 --- a/notebooks/launch-open-source-apps-with-langchain/meta.toml +++ b/notebooks/launch-open-source-apps-with-langchain/meta.toml @@ -5,4 +5,4 @@ description="""\ """ icon="vector-circle" tags=["vectordb", "genai", "langchain"] -destinations=[spaces] +destinations=["spaces"] From e05d4c288c57ca4239c0c1b656645c20c494a5ed Mon Sep 17 00:00:00 2001 From: arno756 Date: Wed, 4 Oct 2023 22:23:20 -0700 Subject: [PATCH 09/24] Add files via upload --- .../load-json-files-s3/loading-json-pipeline-s3.ipynb | 1 + notebooks/load-json-files-s3/meta.toml | 9 +++++++++ 2 files changed, 10 insertions(+) create mode 100644 notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb create mode 100644 notebooks/load-json-files-s3/meta.toml diff --git a/notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb b/notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb new file mode 100644 index 00000000..ed4b39a2 --- /dev/null +++ b/notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","id":"deb8dbf4-2368-41b4-9f09-b14c96ccb344","metadata":{"language":"sql"},"source":"
\n
\n \n
\n
\n
SingleStore Notebooks
\n

Learn How to ingest JSON files in S3 into SingleStoreDB

\n
\n
"},{"cell_type":"markdown","id":"50093846-9ea3-441d-89f0-fbe0576f78bf","metadata":{},"source":"This notebook helps you navigate through different scenarios data ingestion of JSON files from an AWS S3 location:\n* Ingest JSON files in AWS S3 using wildcards with pre-defined schema\n* Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"b2ed410a-87b8-452a-b906-431fb0e949b3","metadata":{},"source":"## Create a Pipeline from JSON files in AWS S3 using wildcards"},{"cell_type":"markdown","id":"9996b479-586d-4af3-b0ee-b61eead39ebc","metadata":{},"source":"In this example, we want to create a pipeline from two JSON files called **actors1.json** and **actors2.json** stored in an AWS S3 bucket called singlestoredb and a folder called **actors**. This bucket is located in **us-east-1**."},{"cell_type":"markdown","id":"9a4caf68-0610-41a6-bfd1-59612b8e959a","metadata":{},"source":"Each file has the following shape with nested objects and arrays:\n```json\n{\n \"Actors\": [\n {\n \"name\": \"Tom Cruise\",\n \"age\": 56,\n \"Born At\": \"Syracuse, NY\",\n \"Birthdate\": \"July 3, 1962\",\n \"photo\": \"https://jsonformatter.org/img/tom-cruise.jpg\",\n \"wife\": null,\n \"weight\": 67.5,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Suri\",\n \"Isabella Jane\",\n \"Connor\"\n ]\n },\n {\n \"name\": \"Robert Downey Jr.\",\n \"age\": 53,\n \"Born At\": \"New York City, NY\",\n \"Birthdate\": \"April 4, 1965\",\n \"photo\": \"https://jsonformatter.org/img/Robert-Downey-Jr.jpg\",\n \"wife\": \"Susan Downey\",\n \"weight\": 77.1,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Indio Falconer\",\n \"Avri Roel\",\n \"Exton Elias\"\n ]\n }\n ]\n}\n```"},{"cell_type":"markdown","id":"98a8e14f-808e-43ff-b670-b6656091b81a","metadata":{},"source":"### Create a Table"},{"cell_type":"markdown","id":"a70e168d-de32-4988-90c4-651089ac25a0","metadata":{},"source":"We first create a table called **actors** in the database **demo_database**"},{"cell_type":"code","execution_count":11,"id":"b703aab8-7449-43db-af04-9d65520239a5","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:21.090281Z","iopub.status.busy":"2023-09-29T16:16:21.089700Z","iopub.status.idle":"2023-09-29T16:16:23.607632Z","shell.execute_reply":"2023-09-29T16:16:23.607074Z","shell.execute_reply.started":"2023-09-29T16:16:21.090258Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors (\nname text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nage int NOT NULL,\nborn_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nBirthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nphoto text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nwife text CHARACTER SET utf8 COLLATE utf8_general_ci,\nweight float NOT NULL,\nhaschildren boolean,\nhasGreyHair boolean,\nchildren JSON COLLATE utf8_bin NOT NULL,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"e4c15a63-eb17-432d-b0b5-d7485bcf028d","metadata":{},"source":"### Create a pipeline"},{"cell_type":"markdown","id":"5e09146a-74cb-4e0d-bd0a-3502c2d15a00","metadata":{},"source":"We then create a pipeline called **actors** in the database **demo_database**. Since those files are small, batch_interval is not as important and the maximum partitions per batch is only 1. For faster performance, we recommend increasing the maximum partitions per batch. \nNote, that since the bucket is publcly accessible, you do not need to provide access key and secret."},{"cell_type":"code","execution_count":13,"id":"92df7943-e68d-4509-b7f5-4a93697f6578","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:32.661374Z","iopub.status.busy":"2023-09-29T16:16:32.661156Z","iopub.status.idle":"2023-09-29T16:16:32.799913Z","shell.execute_reply":"2023-09-29T16:16:32.799326Z","shell.execute_reply.started":"2023-09-29T16:16:32.661355Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors`\nFORMAT JSON\n(\n actors.name <- name,\n actors.age <- age,\n actors.born_at <- `Born At`,\n actors.Birthdate <- Birthdate,\n actors.photo <- photo,\n actors.wife <- wife,\n actors.weight <- weight,\n actors.haschildren <- hasChildren,\n actors.hasGreyHair <- hasGreyHair,\n actors.children <- children\n);"},{"cell_type":"markdown","id":"5410c1b9-573f-4326-ba4c-b7af71e069ad","metadata":{},"source":"### Start and monitor the pipeline"},{"cell_type":"code","execution_count":15,"id":"eeddd12e-e28c-4000-859b-6d1291c4a137","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:46.866565Z","iopub.status.busy":"2023-09-29T16:16:46.866099Z","iopub.status.idle":"2023-09-29T16:16:46.884560Z","shell.execute_reply":"2023-09-29T16:16:46.884032Z","shell.execute_reply.started":"2023-09-29T16:16:46.866544Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors;"},{"cell_type":"markdown","id":"a555997d-38dc-4b69-821b-390e52bb4d00","metadata":{},"source":"If there is no error or warning, you should see no error message."},{"cell_type":"code","execution_count":17,"id":"f48de155-af85-4c40-ad56-955573a434f8","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:53.215976Z","iopub.status.busy":"2023-09-29T16:16:53.215653Z","iopub.status.idle":"2023-09-29T16:16:53.330859Z","shell.execute_reply":"2023-09-29T16:16:53.330370Z","shell.execute_reply.started":"2023-09-29T16:16:53.215958Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors' ;"},{"cell_type":"markdown","id":"c18ac453-63de-424a-b9bf-ae6846817ea6","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":18,"id":"09a739cb-4925-4699-ab61-71016a04bfb6","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:58.182000Z","iopub.status.busy":"2023-09-29T16:16:58.181746Z","iopub.status.idle":"2023-09-29T16:16:58.247687Z","shell.execute_reply":"2023-09-29T16:16:58.247115Z","shell.execute_reply.started":"2023-09-29T16:16:58.181983Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
nameageborn_atBirthdatephotowifeweighthaschildrenhasGreyHairchildren
Robert Downey Jr.53New York City, NYApril 4, 1965https://jsonformatter.org/img/Robert-Downey-Jr.jpgSusan Downey77.110['Indio Falconer', 'Avri Roel', 'Exton Elias']
Tom Cruise56Syracuse, NYJuly 3, 1962https://jsonformatter.org/img/tom-cruise.jpgNone67.510['Suri', 'Isabella Jane', 'Connor']
","text/plain":"+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| name | age | born_at | Birthdate | photo | wife | weight | haschildren | hasGreyHair | children |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| Robert Downey Jr. | 53 | New York City, NY | April 4, 1965 | https://jsonformatter.org/img/Robert-Downey-Jr.jpg | Susan Downey | 77.1 | 1 | 0 | ['Indio Falconer', 'Avri Roel', 'Exton Elias'] |\n| Tom Cruise | 56 | Syracuse, NY | July 3, 1962 | https://jsonformatter.org/img/tom-cruise.jpg | None | 67.5 | 1 | 0 | ['Suri', 'Isabella Jane', 'Connor'] |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors;"},{"cell_type":"markdown","id":"c4815572-10d8-4c31-a246-05ad6e7e6e99","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":20,"id":"6a6dfc1d-c758-4287-a797-6cc3e4fff934","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:17:03.196969Z","iopub.status.busy":"2023-09-29T16:17:03.196725Z","iopub.status.idle":"2023-09-29T16:17:03.232536Z","shell.execute_reply":"2023-09-29T16:17:03.231955Z","shell.execute_reply.started":"2023-09-29T16:17:03.196954Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nDrop pipeline if exists demo_database.actors;\nDrop table if exists demo_database.actors;"},{"cell_type":"markdown","id":"09fbffac-9a0a-45fd-ad07-ede4e11b3691","metadata":{},"source":"## Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"d3e8ff65-1b2d-47c5-8754-28fa4c254edd","metadata":{},"source":"As the schema of your files might change, you might want to keep flexibility in ingesting the data into one JSON column that we name **json_data**. the table we create is named **actors_json**."},{"cell_type":"markdown","id":"d761f324-0d28-4713-a866-3f96673d8317","metadata":{},"source":"### Create Table"},{"cell_type":"code","execution_count":14,"id":"bcb14814-7b79-4df2-ab47-7def7ae03ce3","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:17:30.337597Z","iopub.status.busy":"2023-10-05T05:17:30.337247Z","iopub.status.idle":"2023-10-05T05:17:33.420875Z","shell.execute_reply":"2023-10-05T05:17:33.420319Z","shell.execute_reply.started":"2023-10-05T05:17:30.337580Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors_json (\njson_data JSON NOT NULL ,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"429fce4b-c529-4acf-af7e-5d802f79eda6","metadata":{},"source":"### Create a pipeline"},{"cell_type":"code","execution_count":21,"id":"a1d60130-095e-45da-b55d-b427a0af3d26","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:03.678851Z","iopub.status.busy":"2023-10-05T05:18:03.678450Z","iopub.status.idle":"2023-10-05T05:18:03.839061Z","shell.execute_reply":"2023-10-05T05:18:03.838442Z","shell.execute_reply.started":"2023-10-05T05:18:03.678826Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors_json\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors_json`\nFORMAT JSON\n(json_data <- %);"},{"cell_type":"markdown","id":"bd296bf5-db20-4028-a1d7-b5c9da0a6cb2","metadata":{},"source":"### Start and monitor pipeline"},{"cell_type":"code","execution_count":22,"id":"b374598a-f9cb-43c4-a2a4-ebcd298108c4","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:05.818171Z","iopub.status.busy":"2023-10-05T05:18:05.817819Z","iopub.status.idle":"2023-10-05T05:18:05.837111Z","shell.execute_reply":"2023-10-05T05:18:05.836663Z","shell.execute_reply.started":"2023-10-05T05:18:05.818153Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors_json;"},{"cell_type":"code","execution_count":23,"id":"ca06781b-61fa-4fea-97de-cd0dbacd86e8","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:07.571689Z","iopub.status.busy":"2023-10-05T05:18:07.571335Z","iopub.status.idle":"2023-10-05T05:18:07.690209Z","shell.execute_reply":"2023-10-05T05:18:07.688498Z","shell.execute_reply.started":"2023-10-05T05:18:07.571671Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":23,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n# Monitor and see if there is any error or warning\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors_json' ;"},{"cell_type":"markdown","id":"7419ccdd-0f85-414e-bd05-fbe8d9656305","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":25,"id":"e34c5b49-0e97-4b07-9026-38bb6c370f73","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:10.653949Z","iopub.status.busy":"2023-10-05T05:18:10.653693Z","iopub.status.idle":"2023-10-05T05:18:11.007955Z","shell.execute_reply":"2023-10-05T05:18:11.007444Z","shell.execute_reply.started":"2023-10-05T05:18:10.653929Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
json_data
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
","text/plain":"+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| json_data |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":25,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors_json"},{"cell_type":"markdown","id":"c4c155e5-a4a5-4b01-a8a7-e7e626e5fac8","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":27,"id":"6f0bd356-8a11-4cd9-b774-569d8f5e2520","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:29.840296Z","iopub.status.busy":"2023-10-05T05:18:29.840026Z","iopub.status.idle":"2023-10-05T05:18:29.881582Z","shell.execute_reply":"2023-10-05T05:18:29.880978Z","shell.execute_reply.started":"2023-10-05T05:18:29.840279Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n\nDrop pipeline if exists demo_database.actors_json;\nDrop table if exists demo_database.actors_json;"},{"cell_type":"markdown","id":"c572193e-7f5b-4637-af5d-2f33f5ba5d86","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"demo_database"},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file diff --git a/notebooks/load-json-files-s3/meta.toml b/notebooks/load-json-files-s3/meta.toml new file mode 100644 index 00000000..7f3a525c --- /dev/null +++ b/notebooks/load-json-files-s3/meta.toml @@ -0,0 +1,9 @@ +[meta] +title="Load JSON files with Pipeline from S3" +description="This notebook will help you load JSON files from a public open AWS S3 bucket. You will see two modes: +*) where you map the JSON elements to columns in a relational table +*) where you just ingest all documents ito a JSON column. In that mode we also show how you can use persisted computed column for extracting JSON fields +" +icon="chart-network" +tags=["pipeline", "json", "s3"] +destinations=["spaces"] \ No newline at end of file From 63b6685b606b4af7f4a1b377f2a7f3a302e9111f Mon Sep 17 00:00:00 2001 From: arno756 Date: Wed, 4 Oct 2023 22:23:58 -0700 Subject: [PATCH 10/24] Rename loading-json-pipeline-s3.ipynb to notebook.ipynb --- .../{loading-json-pipeline-s3.ipynb => notebook.ipynb} | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename notebooks/load-json-files-s3/{loading-json-pipeline-s3.ipynb => notebook.ipynb} (99%) diff --git a/notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb b/notebooks/load-json-files-s3/notebook.ipynb similarity index 99% rename from notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb rename to notebooks/load-json-files-s3/notebook.ipynb index ed4b39a2..a8067ff3 100644 --- a/notebooks/load-json-files-s3/loading-json-pipeline-s3.ipynb +++ b/notebooks/load-json-files-s3/notebook.ipynb @@ -1 +1 @@ -{"cells":[{"cell_type":"markdown","id":"deb8dbf4-2368-41b4-9f09-b14c96ccb344","metadata":{"language":"sql"},"source":"
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SingleStore Notebooks
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Learn How to ingest JSON files in S3 into SingleStoreDB

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\n
"},{"cell_type":"markdown","id":"50093846-9ea3-441d-89f0-fbe0576f78bf","metadata":{},"source":"This notebook helps you navigate through different scenarios data ingestion of JSON files from an AWS S3 location:\n* Ingest JSON files in AWS S3 using wildcards with pre-defined schema\n* Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"b2ed410a-87b8-452a-b906-431fb0e949b3","metadata":{},"source":"## Create a Pipeline from JSON files in AWS S3 using wildcards"},{"cell_type":"markdown","id":"9996b479-586d-4af3-b0ee-b61eead39ebc","metadata":{},"source":"In this example, we want to create a pipeline from two JSON files called **actors1.json** and **actors2.json** stored in an AWS S3 bucket called singlestoredb and a folder called **actors**. This bucket is located in **us-east-1**."},{"cell_type":"markdown","id":"9a4caf68-0610-41a6-bfd1-59612b8e959a","metadata":{},"source":"Each file has the following shape with nested objects and arrays:\n```json\n{\n \"Actors\": [\n {\n \"name\": \"Tom Cruise\",\n \"age\": 56,\n \"Born At\": \"Syracuse, NY\",\n \"Birthdate\": \"July 3, 1962\",\n \"photo\": \"https://jsonformatter.org/img/tom-cruise.jpg\",\n \"wife\": null,\n \"weight\": 67.5,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Suri\",\n \"Isabella Jane\",\n \"Connor\"\n ]\n },\n {\n \"name\": \"Robert Downey Jr.\",\n \"age\": 53,\n \"Born At\": \"New York City, NY\",\n \"Birthdate\": \"April 4, 1965\",\n \"photo\": \"https://jsonformatter.org/img/Robert-Downey-Jr.jpg\",\n \"wife\": \"Susan Downey\",\n \"weight\": 77.1,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Indio Falconer\",\n \"Avri Roel\",\n \"Exton Elias\"\n ]\n }\n ]\n}\n```"},{"cell_type":"markdown","id":"98a8e14f-808e-43ff-b670-b6656091b81a","metadata":{},"source":"### Create a Table"},{"cell_type":"markdown","id":"a70e168d-de32-4988-90c4-651089ac25a0","metadata":{},"source":"We first create a table called **actors** in the database **demo_database**"},{"cell_type":"code","execution_count":11,"id":"b703aab8-7449-43db-af04-9d65520239a5","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:21.090281Z","iopub.status.busy":"2023-09-29T16:16:21.089700Z","iopub.status.idle":"2023-09-29T16:16:23.607632Z","shell.execute_reply":"2023-09-29T16:16:23.607074Z","shell.execute_reply.started":"2023-09-29T16:16:21.090258Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors (\nname text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nage int NOT NULL,\nborn_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nBirthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nphoto text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nwife text CHARACTER SET utf8 COLLATE utf8_general_ci,\nweight float NOT NULL,\nhaschildren boolean,\nhasGreyHair boolean,\nchildren JSON COLLATE utf8_bin NOT NULL,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"e4c15a63-eb17-432d-b0b5-d7485bcf028d","metadata":{},"source":"### Create a pipeline"},{"cell_type":"markdown","id":"5e09146a-74cb-4e0d-bd0a-3502c2d15a00","metadata":{},"source":"We then create a pipeline called **actors** in the database **demo_database**. Since those files are small, batch_interval is not as important and the maximum partitions per batch is only 1. For faster performance, we recommend increasing the maximum partitions per batch. \nNote, that since the bucket is publcly accessible, you do not need to provide access key and secret."},{"cell_type":"code","execution_count":13,"id":"92df7943-e68d-4509-b7f5-4a93697f6578","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:32.661374Z","iopub.status.busy":"2023-09-29T16:16:32.661156Z","iopub.status.idle":"2023-09-29T16:16:32.799913Z","shell.execute_reply":"2023-09-29T16:16:32.799326Z","shell.execute_reply.started":"2023-09-29T16:16:32.661355Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors`\nFORMAT JSON\n(\n actors.name <- name,\n actors.age <- age,\n actors.born_at <- `Born At`,\n actors.Birthdate <- Birthdate,\n actors.photo <- photo,\n actors.wife <- wife,\n actors.weight <- weight,\n actors.haschildren <- hasChildren,\n actors.hasGreyHair <- hasGreyHair,\n actors.children <- children\n);"},{"cell_type":"markdown","id":"5410c1b9-573f-4326-ba4c-b7af71e069ad","metadata":{},"source":"### Start and monitor the pipeline"},{"cell_type":"code","execution_count":15,"id":"eeddd12e-e28c-4000-859b-6d1291c4a137","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:46.866565Z","iopub.status.busy":"2023-09-29T16:16:46.866099Z","iopub.status.idle":"2023-09-29T16:16:46.884560Z","shell.execute_reply":"2023-09-29T16:16:46.884032Z","shell.execute_reply.started":"2023-09-29T16:16:46.866544Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors;"},{"cell_type":"markdown","id":"a555997d-38dc-4b69-821b-390e52bb4d00","metadata":{},"source":"If there is no error or warning, you should see no error message."},{"cell_type":"code","execution_count":17,"id":"f48de155-af85-4c40-ad56-955573a434f8","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:53.215976Z","iopub.status.busy":"2023-09-29T16:16:53.215653Z","iopub.status.idle":"2023-09-29T16:16:53.330859Z","shell.execute_reply":"2023-09-29T16:16:53.330370Z","shell.execute_reply.started":"2023-09-29T16:16:53.215958Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors' ;"},{"cell_type":"markdown","id":"c18ac453-63de-424a-b9bf-ae6846817ea6","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":18,"id":"09a739cb-4925-4699-ab61-71016a04bfb6","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:58.182000Z","iopub.status.busy":"2023-09-29T16:16:58.181746Z","iopub.status.idle":"2023-09-29T16:16:58.247687Z","shell.execute_reply":"2023-09-29T16:16:58.247115Z","shell.execute_reply.started":"2023-09-29T16:16:58.181983Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
nameageborn_atBirthdatephotowifeweighthaschildrenhasGreyHairchildren
Robert Downey Jr.53New York City, NYApril 4, 1965https://jsonformatter.org/img/Robert-Downey-Jr.jpgSusan Downey77.110['Indio Falconer', 'Avri Roel', 'Exton Elias']
Tom Cruise56Syracuse, NYJuly 3, 1962https://jsonformatter.org/img/tom-cruise.jpgNone67.510['Suri', 'Isabella Jane', 'Connor']
","text/plain":"+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| name | age | born_at | Birthdate | photo | wife | weight | haschildren | hasGreyHair | children |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| Robert Downey Jr. | 53 | New York City, NY | April 4, 1965 | https://jsonformatter.org/img/Robert-Downey-Jr.jpg | Susan Downey | 77.1 | 1 | 0 | ['Indio Falconer', 'Avri Roel', 'Exton Elias'] |\n| Tom Cruise | 56 | Syracuse, NY | July 3, 1962 | https://jsonformatter.org/img/tom-cruise.jpg | None | 67.5 | 1 | 0 | ['Suri', 'Isabella Jane', 'Connor'] |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors;"},{"cell_type":"markdown","id":"c4815572-10d8-4c31-a246-05ad6e7e6e99","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":20,"id":"6a6dfc1d-c758-4287-a797-6cc3e4fff934","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:17:03.196969Z","iopub.status.busy":"2023-09-29T16:17:03.196725Z","iopub.status.idle":"2023-09-29T16:17:03.232536Z","shell.execute_reply":"2023-09-29T16:17:03.231955Z","shell.execute_reply.started":"2023-09-29T16:17:03.196954Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nDrop pipeline if exists demo_database.actors;\nDrop table if exists demo_database.actors;"},{"cell_type":"markdown","id":"09fbffac-9a0a-45fd-ad07-ede4e11b3691","metadata":{},"source":"## Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"d3e8ff65-1b2d-47c5-8754-28fa4c254edd","metadata":{},"source":"As the schema of your files might change, you might want to keep flexibility in ingesting the data into one JSON column that we name **json_data**. the table we create is named **actors_json**."},{"cell_type":"markdown","id":"d761f324-0d28-4713-a866-3f96673d8317","metadata":{},"source":"### Create Table"},{"cell_type":"code","execution_count":14,"id":"bcb14814-7b79-4df2-ab47-7def7ae03ce3","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:17:30.337597Z","iopub.status.busy":"2023-10-05T05:17:30.337247Z","iopub.status.idle":"2023-10-05T05:17:33.420875Z","shell.execute_reply":"2023-10-05T05:17:33.420319Z","shell.execute_reply.started":"2023-10-05T05:17:30.337580Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors_json (\njson_data JSON NOT NULL ,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"429fce4b-c529-4acf-af7e-5d802f79eda6","metadata":{},"source":"### Create a pipeline"},{"cell_type":"code","execution_count":21,"id":"a1d60130-095e-45da-b55d-b427a0af3d26","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:03.678851Z","iopub.status.busy":"2023-10-05T05:18:03.678450Z","iopub.status.idle":"2023-10-05T05:18:03.839061Z","shell.execute_reply":"2023-10-05T05:18:03.838442Z","shell.execute_reply.started":"2023-10-05T05:18:03.678826Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors_json\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors_json`\nFORMAT JSON\n(json_data <- %);"},{"cell_type":"markdown","id":"bd296bf5-db20-4028-a1d7-b5c9da0a6cb2","metadata":{},"source":"### Start and monitor pipeline"},{"cell_type":"code","execution_count":22,"id":"b374598a-f9cb-43c4-a2a4-ebcd298108c4","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:05.818171Z","iopub.status.busy":"2023-10-05T05:18:05.817819Z","iopub.status.idle":"2023-10-05T05:18:05.837111Z","shell.execute_reply":"2023-10-05T05:18:05.836663Z","shell.execute_reply.started":"2023-10-05T05:18:05.818153Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors_json;"},{"cell_type":"code","execution_count":23,"id":"ca06781b-61fa-4fea-97de-cd0dbacd86e8","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:07.571689Z","iopub.status.busy":"2023-10-05T05:18:07.571335Z","iopub.status.idle":"2023-10-05T05:18:07.690209Z","shell.execute_reply":"2023-10-05T05:18:07.688498Z","shell.execute_reply.started":"2023-10-05T05:18:07.571671Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":23,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n# Monitor and see if there is any error or warning\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors_json' ;"},{"cell_type":"markdown","id":"7419ccdd-0f85-414e-bd05-fbe8d9656305","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":25,"id":"e34c5b49-0e97-4b07-9026-38bb6c370f73","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:10.653949Z","iopub.status.busy":"2023-10-05T05:18:10.653693Z","iopub.status.idle":"2023-10-05T05:18:11.007955Z","shell.execute_reply":"2023-10-05T05:18:11.007444Z","shell.execute_reply.started":"2023-10-05T05:18:10.653929Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
json_data
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
","text/plain":"+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| json_data |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":25,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors_json"},{"cell_type":"markdown","id":"c4c155e5-a4a5-4b01-a8a7-e7e626e5fac8","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":27,"id":"6f0bd356-8a11-4cd9-b774-569d8f5e2520","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:29.840296Z","iopub.status.busy":"2023-10-05T05:18:29.840026Z","iopub.status.idle":"2023-10-05T05:18:29.881582Z","shell.execute_reply":"2023-10-05T05:18:29.880978Z","shell.execute_reply.started":"2023-10-05T05:18:29.840279Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n\nDrop pipeline if exists demo_database.actors_json;\nDrop table if exists demo_database.actors_json;"},{"cell_type":"markdown","id":"c572193e-7f5b-4637-af5d-2f33f5ba5d86","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"demo_database"},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file +{"cells":[{"cell_type":"markdown","id":"deb8dbf4-2368-41b4-9f09-b14c96ccb344","metadata":{"language":"sql"},"source":"
\n
\n \n
\n
\n
SingleStore Notebooks
\n

Learn How to ingest JSON files in S3 into SingleStoreDB

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\n
"},{"cell_type":"markdown","id":"50093846-9ea3-441d-89f0-fbe0576f78bf","metadata":{},"source":"This notebook helps you navigate through different scenarios data ingestion of JSON files from an AWS S3 location:\n* Ingest JSON files in AWS S3 using wildcards with pre-defined schema\n* Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"b2ed410a-87b8-452a-b906-431fb0e949b3","metadata":{},"source":"## Create a Pipeline from JSON files in AWS S3 using wildcards"},{"cell_type":"markdown","id":"9996b479-586d-4af3-b0ee-b61eead39ebc","metadata":{},"source":"In this example, we want to create a pipeline from two JSON files called **actors1.json** and **actors2.json** stored in an AWS S3 bucket called singlestoredb and a folder called **actors**. This bucket is located in **us-east-1**."},{"cell_type":"markdown","id":"9a4caf68-0610-41a6-bfd1-59612b8e959a","metadata":{},"source":"Each file has the following shape with nested objects and arrays:\n```json\n{\n \"Actors\": [\n {\n \"name\": \"Tom Cruise\",\n \"age\": 56,\n \"Born At\": \"Syracuse, NY\",\n \"Birthdate\": \"July 3, 1962\",\n \"photo\": \"https://jsonformatter.org/img/tom-cruise.jpg\",\n \"wife\": null,\n \"weight\": 67.5,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Suri\",\n \"Isabella Jane\",\n \"Connor\"\n ]\n },\n {\n \"name\": \"Robert Downey Jr.\",\n \"age\": 53,\n \"Born At\": \"New York City, NY\",\n \"Birthdate\": \"April 4, 1965\",\n \"photo\": \"https://jsonformatter.org/img/Robert-Downey-Jr.jpg\",\n \"wife\": \"Susan Downey\",\n \"weight\": 77.1,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Indio Falconer\",\n \"Avri Roel\",\n \"Exton Elias\"\n ]\n }\n ]\n}\n```"},{"cell_type":"markdown","id":"98a8e14f-808e-43ff-b670-b6656091b81a","metadata":{},"source":"### Create a Table"},{"cell_type":"markdown","id":"a70e168d-de32-4988-90c4-651089ac25a0","metadata":{},"source":"We first create a table called **actors** in the database **demo_database**"},{"cell_type":"code","execution_count":11,"id":"b703aab8-7449-43db-af04-9d65520239a5","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:21.090281Z","iopub.status.busy":"2023-09-29T16:16:21.089700Z","iopub.status.idle":"2023-09-29T16:16:23.607632Z","shell.execute_reply":"2023-09-29T16:16:23.607074Z","shell.execute_reply.started":"2023-09-29T16:16:21.090258Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors (\nname text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nage int NOT NULL,\nborn_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nBirthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nphoto text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nwife text CHARACTER SET utf8 COLLATE utf8_general_ci,\nweight float NOT NULL,\nhaschildren boolean,\nhasGreyHair boolean,\nchildren JSON COLLATE utf8_bin NOT NULL,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"e4c15a63-eb17-432d-b0b5-d7485bcf028d","metadata":{},"source":"### Create a pipeline"},{"cell_type":"markdown","id":"5e09146a-74cb-4e0d-bd0a-3502c2d15a00","metadata":{},"source":"We then create a pipeline called **actors** in the database **demo_database**. Since those files are small, batch_interval is not as important and the maximum partitions per batch is only 1. For faster performance, we recommend increasing the maximum partitions per batch. \nNote, that since the bucket is publcly accessible, you do not need to provide access key and secret."},{"cell_type":"code","execution_count":13,"id":"92df7943-e68d-4509-b7f5-4a93697f6578","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:32.661374Z","iopub.status.busy":"2023-09-29T16:16:32.661156Z","iopub.status.idle":"2023-09-29T16:16:32.799913Z","shell.execute_reply":"2023-09-29T16:16:32.799326Z","shell.execute_reply.started":"2023-09-29T16:16:32.661355Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors`\nFORMAT JSON\n(\n actors.name <- name,\n actors.age <- age,\n actors.born_at <- `Born At`,\n actors.Birthdate <- Birthdate,\n actors.photo <- photo,\n actors.wife <- wife,\n actors.weight <- weight,\n actors.haschildren <- hasChildren,\n actors.hasGreyHair <- hasGreyHair,\n actors.children <- children\n);"},{"cell_type":"markdown","id":"5410c1b9-573f-4326-ba4c-b7af71e069ad","metadata":{},"source":"### Start and monitor the pipeline"},{"cell_type":"code","execution_count":15,"id":"eeddd12e-e28c-4000-859b-6d1291c4a137","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:46.866565Z","iopub.status.busy":"2023-09-29T16:16:46.866099Z","iopub.status.idle":"2023-09-29T16:16:46.884560Z","shell.execute_reply":"2023-09-29T16:16:46.884032Z","shell.execute_reply.started":"2023-09-29T16:16:46.866544Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors;"},{"cell_type":"markdown","id":"a555997d-38dc-4b69-821b-390e52bb4d00","metadata":{},"source":"If there is no error or warning, you should see no error message."},{"cell_type":"code","execution_count":17,"id":"f48de155-af85-4c40-ad56-955573a434f8","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:53.215976Z","iopub.status.busy":"2023-09-29T16:16:53.215653Z","iopub.status.idle":"2023-09-29T16:16:53.330859Z","shell.execute_reply":"2023-09-29T16:16:53.330370Z","shell.execute_reply.started":"2023-09-29T16:16:53.215958Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors' ;"},{"cell_type":"markdown","id":"c18ac453-63de-424a-b9bf-ae6846817ea6","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":18,"id":"09a739cb-4925-4699-ab61-71016a04bfb6","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:58.182000Z","iopub.status.busy":"2023-09-29T16:16:58.181746Z","iopub.status.idle":"2023-09-29T16:16:58.247687Z","shell.execute_reply":"2023-09-29T16:16:58.247115Z","shell.execute_reply.started":"2023-09-29T16:16:58.181983Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
nameageborn_atBirthdatephotowifeweighthaschildrenhasGreyHairchildren
Robert Downey Jr.53New York City, NYApril 4, 1965https://jsonformatter.org/img/Robert-Downey-Jr.jpgSusan Downey77.110['Indio Falconer', 'Avri Roel', 'Exton Elias']
Tom Cruise56Syracuse, NYJuly 3, 1962https://jsonformatter.org/img/tom-cruise.jpgNone67.510['Suri', 'Isabella Jane', 'Connor']
","text/plain":"+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| name | age | born_at | Birthdate | photo | wife | weight | haschildren | hasGreyHair | children |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| Robert Downey Jr. | 53 | New York City, NY | April 4, 1965 | https://jsonformatter.org/img/Robert-Downey-Jr.jpg | Susan Downey | 77.1 | 1 | 0 | ['Indio Falconer', 'Avri Roel', 'Exton Elias'] |\n| Tom Cruise | 56 | Syracuse, NY | July 3, 1962 | https://jsonformatter.org/img/tom-cruise.jpg | None | 67.5 | 1 | 0 | ['Suri', 'Isabella Jane', 'Connor'] |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors;"},{"cell_type":"markdown","id":"c4815572-10d8-4c31-a246-05ad6e7e6e99","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":20,"id":"6a6dfc1d-c758-4287-a797-6cc3e4fff934","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:17:03.196969Z","iopub.status.busy":"2023-09-29T16:17:03.196725Z","iopub.status.idle":"2023-09-29T16:17:03.232536Z","shell.execute_reply":"2023-09-29T16:17:03.231955Z","shell.execute_reply.started":"2023-09-29T16:17:03.196954Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nDrop pipeline if exists demo_database.actors;\nDrop table if exists demo_database.actors;"},{"cell_type":"markdown","id":"09fbffac-9a0a-45fd-ad07-ede4e11b3691","metadata":{},"source":"## Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"d3e8ff65-1b2d-47c5-8754-28fa4c254edd","metadata":{},"source":"As the schema of your files might change, you might want to keep flexibility in ingesting the data into one JSON column that we name **json_data**. the table we create is named **actors_json**."},{"cell_type":"markdown","id":"d761f324-0d28-4713-a866-3f96673d8317","metadata":{},"source":"### Create Table"},{"cell_type":"code","execution_count":14,"id":"bcb14814-7b79-4df2-ab47-7def7ae03ce3","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:17:30.337597Z","iopub.status.busy":"2023-10-05T05:17:30.337247Z","iopub.status.idle":"2023-10-05T05:17:33.420875Z","shell.execute_reply":"2023-10-05T05:17:33.420319Z","shell.execute_reply.started":"2023-10-05T05:17:30.337580Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors_json (\njson_data JSON NOT NULL ,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"429fce4b-c529-4acf-af7e-5d802f79eda6","metadata":{},"source":"### Create a pipeline"},{"cell_type":"code","execution_count":21,"id":"a1d60130-095e-45da-b55d-b427a0af3d26","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:03.678851Z","iopub.status.busy":"2023-10-05T05:18:03.678450Z","iopub.status.idle":"2023-10-05T05:18:03.839061Z","shell.execute_reply":"2023-10-05T05:18:03.838442Z","shell.execute_reply.started":"2023-10-05T05:18:03.678826Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors_json\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors_json`\nFORMAT JSON\n(json_data <- %);"},{"cell_type":"markdown","id":"bd296bf5-db20-4028-a1d7-b5c9da0a6cb2","metadata":{},"source":"### Start and monitor pipeline"},{"cell_type":"code","execution_count":22,"id":"b374598a-f9cb-43c4-a2a4-ebcd298108c4","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:05.818171Z","iopub.status.busy":"2023-10-05T05:18:05.817819Z","iopub.status.idle":"2023-10-05T05:18:05.837111Z","shell.execute_reply":"2023-10-05T05:18:05.836663Z","shell.execute_reply.started":"2023-10-05T05:18:05.818153Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors_json;"},{"cell_type":"code","execution_count":23,"id":"ca06781b-61fa-4fea-97de-cd0dbacd86e8","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:07.571689Z","iopub.status.busy":"2023-10-05T05:18:07.571335Z","iopub.status.idle":"2023-10-05T05:18:07.690209Z","shell.execute_reply":"2023-10-05T05:18:07.688498Z","shell.execute_reply.started":"2023-10-05T05:18:07.571671Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":23,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n# Monitor and see if there is any error or warning\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors_json' ;"},{"cell_type":"markdown","id":"7419ccdd-0f85-414e-bd05-fbe8d9656305","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":25,"id":"e34c5b49-0e97-4b07-9026-38bb6c370f73","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:10.653949Z","iopub.status.busy":"2023-10-05T05:18:10.653693Z","iopub.status.idle":"2023-10-05T05:18:11.007955Z","shell.execute_reply":"2023-10-05T05:18:11.007444Z","shell.execute_reply.started":"2023-10-05T05:18:10.653929Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
json_data
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
","text/plain":"+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| json_data |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":25,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors_json"},{"cell_type":"markdown","id":"c4c155e5-a4a5-4b01-a8a7-e7e626e5fac8","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":27,"id":"6f0bd356-8a11-4cd9-b774-569d8f5e2520","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:29.840296Z","iopub.status.busy":"2023-10-05T05:18:29.840026Z","iopub.status.idle":"2023-10-05T05:18:29.881582Z","shell.execute_reply":"2023-10-05T05:18:29.880978Z","shell.execute_reply.started":"2023-10-05T05:18:29.840279Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n\nDrop pipeline if exists demo_database.actors_json;\nDrop table if exists demo_database.actors_json;"},{"cell_type":"markdown","id":"c572193e-7f5b-4637-af5d-2f33f5ba5d86","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"demo_database"},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} From 6516b8b27616799132ccff9720d122a17f0ea5f2 Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Thu, 5 Oct 2023 08:54:02 -0500 Subject: [PATCH 11/24] Fix notebooks; add check for attachments=null --- notebooks/load-json-files-s3/meta.toml | 12 +- notebooks/load-json-files-s3/notebook.ipynb | 446 ++++++- .../meta.toml | 19 +- .../notebook.ipynb | 1114 ++++++++++++++++- resources/nb-check.py | 7 +- resources/toml-check.py | 4 +- 6 files changed, 1585 insertions(+), 17 deletions(-) diff --git a/notebooks/load-json-files-s3/meta.toml b/notebooks/load-json-files-s3/meta.toml index 7f3a525c..c82e5c0d 100644 --- a/notebooks/load-json-files-s3/meta.toml +++ b/notebooks/load-json-files-s3/meta.toml @@ -1,9 +1,11 @@ [meta] title="Load JSON files with Pipeline from S3" -description="This notebook will help you load JSON files from a public open AWS S3 bucket. You will see two modes: -*) where you map the JSON elements to columns in a relational table -*) where you just ingest all documents ito a JSON column. In that mode we also show how you can use persisted computed column for extracting JSON fields -" +description="""\ + This notebook will help you load JSON files from a public open + AWS S3 bucket. You will see two modes: + *) where you map the JSON elements to columns in a relational table + *) where you just ingest all documents ito a JSON column. In that mode we also show how you can use persisted computed column for extracting JSON fields +""" icon="chart-network" tags=["pipeline", "json", "s3"] -destinations=["spaces"] \ No newline at end of file +destinations=["spaces"] diff --git a/notebooks/load-json-files-s3/notebook.ipynb b/notebooks/load-json-files-s3/notebook.ipynb index a8067ff3..9f0ad7ff 100644 --- a/notebooks/load-json-files-s3/notebook.ipynb +++ b/notebooks/load-json-files-s3/notebook.ipynb @@ -1 +1,445 @@ -{"cells":[{"cell_type":"markdown","id":"deb8dbf4-2368-41b4-9f09-b14c96ccb344","metadata":{"language":"sql"},"source":"
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SingleStore Notebooks
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Learn How to ingest JSON files in S3 into SingleStoreDB

\n
\n
"},{"cell_type":"markdown","id":"50093846-9ea3-441d-89f0-fbe0576f78bf","metadata":{},"source":"This notebook helps you navigate through different scenarios data ingestion of JSON files from an AWS S3 location:\n* Ingest JSON files in AWS S3 using wildcards with pre-defined schema\n* Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"b2ed410a-87b8-452a-b906-431fb0e949b3","metadata":{},"source":"## Create a Pipeline from JSON files in AWS S3 using wildcards"},{"cell_type":"markdown","id":"9996b479-586d-4af3-b0ee-b61eead39ebc","metadata":{},"source":"In this example, we want to create a pipeline from two JSON files called **actors1.json** and **actors2.json** stored in an AWS S3 bucket called singlestoredb and a folder called **actors**. This bucket is located in **us-east-1**."},{"cell_type":"markdown","id":"9a4caf68-0610-41a6-bfd1-59612b8e959a","metadata":{},"source":"Each file has the following shape with nested objects and arrays:\n```json\n{\n \"Actors\": [\n {\n \"name\": \"Tom Cruise\",\n \"age\": 56,\n \"Born At\": \"Syracuse, NY\",\n \"Birthdate\": \"July 3, 1962\",\n \"photo\": \"https://jsonformatter.org/img/tom-cruise.jpg\",\n \"wife\": null,\n \"weight\": 67.5,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Suri\",\n \"Isabella Jane\",\n \"Connor\"\n ]\n },\n {\n \"name\": \"Robert Downey Jr.\",\n \"age\": 53,\n \"Born At\": \"New York City, NY\",\n \"Birthdate\": \"April 4, 1965\",\n \"photo\": \"https://jsonformatter.org/img/Robert-Downey-Jr.jpg\",\n \"wife\": \"Susan Downey\",\n \"weight\": 77.1,\n \"hasChildren\": true,\n \"hasGreyHair\": false,\n \"children\": [\n \"Indio Falconer\",\n \"Avri Roel\",\n \"Exton Elias\"\n ]\n }\n ]\n}\n```"},{"cell_type":"markdown","id":"98a8e14f-808e-43ff-b670-b6656091b81a","metadata":{},"source":"### Create a Table"},{"cell_type":"markdown","id":"a70e168d-de32-4988-90c4-651089ac25a0","metadata":{},"source":"We first create a table called **actors** in the database **demo_database**"},{"cell_type":"code","execution_count":11,"id":"b703aab8-7449-43db-af04-9d65520239a5","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:21.090281Z","iopub.status.busy":"2023-09-29T16:16:21.089700Z","iopub.status.idle":"2023-09-29T16:16:23.607632Z","shell.execute_reply":"2023-09-29T16:16:23.607074Z","shell.execute_reply.started":"2023-09-29T16:16:21.090258Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors (\nname text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nage int NOT NULL,\nborn_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nBirthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nphoto text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\nwife text CHARACTER SET utf8 COLLATE utf8_general_ci,\nweight float NOT NULL,\nhaschildren boolean,\nhasGreyHair boolean,\nchildren JSON COLLATE utf8_bin NOT NULL,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"e4c15a63-eb17-432d-b0b5-d7485bcf028d","metadata":{},"source":"### Create a pipeline"},{"cell_type":"markdown","id":"5e09146a-74cb-4e0d-bd0a-3502c2d15a00","metadata":{},"source":"We then create a pipeline called **actors** in the database **demo_database**. Since those files are small, batch_interval is not as important and the maximum partitions per batch is only 1. For faster performance, we recommend increasing the maximum partitions per batch. \nNote, that since the bucket is publcly accessible, you do not need to provide access key and secret."},{"cell_type":"code","execution_count":13,"id":"92df7943-e68d-4509-b7f5-4a93697f6578","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:32.661374Z","iopub.status.busy":"2023-09-29T16:16:32.661156Z","iopub.status.idle":"2023-09-29T16:16:32.799913Z","shell.execute_reply":"2023-09-29T16:16:32.799326Z","shell.execute_reply.started":"2023-09-29T16:16:32.661355Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors`\nFORMAT JSON\n(\n actors.name <- name,\n actors.age <- age,\n actors.born_at <- `Born At`,\n actors.Birthdate <- Birthdate,\n actors.photo <- photo,\n actors.wife <- wife,\n actors.weight <- weight,\n actors.haschildren <- hasChildren,\n actors.hasGreyHair <- hasGreyHair,\n actors.children <- children\n);"},{"cell_type":"markdown","id":"5410c1b9-573f-4326-ba4c-b7af71e069ad","metadata":{},"source":"### Start and monitor the pipeline"},{"cell_type":"code","execution_count":15,"id":"eeddd12e-e28c-4000-859b-6d1291c4a137","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:46.866565Z","iopub.status.busy":"2023-09-29T16:16:46.866099Z","iopub.status.idle":"2023-09-29T16:16:46.884560Z","shell.execute_reply":"2023-09-29T16:16:46.884032Z","shell.execute_reply.started":"2023-09-29T16:16:46.866544Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors;"},{"cell_type":"markdown","id":"a555997d-38dc-4b69-821b-390e52bb4d00","metadata":{},"source":"If there is no error or warning, you should see no error message."},{"cell_type":"code","execution_count":17,"id":"f48de155-af85-4c40-ad56-955573a434f8","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:53.215976Z","iopub.status.busy":"2023-09-29T16:16:53.215653Z","iopub.status.idle":"2023-09-29T16:16:53.330859Z","shell.execute_reply":"2023-09-29T16:16:53.330370Z","shell.execute_reply.started":"2023-09-29T16:16:53.215958Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors' ;"},{"cell_type":"markdown","id":"c18ac453-63de-424a-b9bf-ae6846817ea6","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":18,"id":"09a739cb-4925-4699-ab61-71016a04bfb6","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:16:58.182000Z","iopub.status.busy":"2023-09-29T16:16:58.181746Z","iopub.status.idle":"2023-09-29T16:16:58.247687Z","shell.execute_reply":"2023-09-29T16:16:58.247115Z","shell.execute_reply.started":"2023-09-29T16:16:58.181983Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
nameageborn_atBirthdatephotowifeweighthaschildrenhasGreyHairchildren
Robert Downey Jr.53New York City, NYApril 4, 1965https://jsonformatter.org/img/Robert-Downey-Jr.jpgSusan Downey77.110['Indio Falconer', 'Avri Roel', 'Exton Elias']
Tom Cruise56Syracuse, NYJuly 3, 1962https://jsonformatter.org/img/tom-cruise.jpgNone67.510['Suri', 'Isabella Jane', 'Connor']
","text/plain":"+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| name | age | born_at | Birthdate | photo | wife | weight | haschildren | hasGreyHair | children |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+\n| Robert Downey Jr. | 53 | New York City, NY | April 4, 1965 | https://jsonformatter.org/img/Robert-Downey-Jr.jpg | Susan Downey | 77.1 | 1 | 0 | ['Indio Falconer', 'Avri Roel', 'Exton Elias'] |\n| Tom Cruise | 56 | Syracuse, NY | July 3, 1962 | https://jsonformatter.org/img/tom-cruise.jpg | None | 67.5 | 1 | 0 | ['Suri', 'Isabella Jane', 'Connor'] |\n+-------------------+-----+-------------------+---------------+-------------------------------------------------------------------------------------------------------------------+--------------+--------+-------------+-------------+------------------------------------------------+"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors;"},{"cell_type":"markdown","id":"c4815572-10d8-4c31-a246-05ad6e7e6e99","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":20,"id":"6a6dfc1d-c758-4287-a797-6cc3e4fff934","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:17:03.196969Z","iopub.status.busy":"2023-09-29T16:17:03.196725Z","iopub.status.idle":"2023-09-29T16:17:03.232536Z","shell.execute_reply":"2023-09-29T16:17:03.231955Z","shell.execute_reply.started":"2023-09-29T16:17:03.196954Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":""},"execution_count":20,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nDrop pipeline if exists demo_database.actors;\nDrop table if exists demo_database.actors;"},{"cell_type":"markdown","id":"09fbffac-9a0a-45fd-ad07-ede4e11b3691","metadata":{},"source":"## Ingest JSON files in AWS S3 using wildcards into a JSON column"},{"cell_type":"markdown","id":"d3e8ff65-1b2d-47c5-8754-28fa4c254edd","metadata":{},"source":"As the schema of your files might change, you might want to keep flexibility in ingesting the data into one JSON column that we name **json_data**. the table we create is named **actors_json**."},{"cell_type":"markdown","id":"d761f324-0d28-4713-a866-3f96673d8317","metadata":{},"source":"### Create Table"},{"cell_type":"code","execution_count":14,"id":"bcb14814-7b79-4df2-ab47-7def7ae03ce3","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:17:30.337597Z","iopub.status.busy":"2023-10-05T05:17:30.337247Z","iopub.status.idle":"2023-10-05T05:17:33.420875Z","shell.execute_reply":"2023-10-05T05:17:33.420319Z","shell.execute_reply.started":"2023-10-05T05:17:30.337580Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCreate database if not exists demo_database;\nUse demo_database;\nCREATE TABLE if not exists demo_database.actors_json (\njson_data JSON NOT NULL ,\nSHARD KEY ()\n);"},{"cell_type":"markdown","id":"429fce4b-c529-4acf-af7e-5d802f79eda6","metadata":{},"source":"### Create a pipeline"},{"cell_type":"code","execution_count":21,"id":"a1d60130-095e-45da-b55d-b427a0af3d26","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:03.678851Z","iopub.status.busy":"2023-10-05T05:18:03.678450Z","iopub.status.idle":"2023-10-05T05:18:03.839061Z","shell.execute_reply":"2023-10-05T05:18:03.838442Z","shell.execute_reply.started":"2023-10-05T05:18:03.678826Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nCREATE PIPELINE if not exists demo_database.actors_json\nAS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\nCONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n/*\nCREDENTIALS '{\"aws_access_key_id\": \"\", \n \"aws_secret_access_key\": \"\"}'\n*/\nBATCH_INTERVAL 2500\nMAX_PARTITIONS_PER_BATCH 1\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `actors_json`\nFORMAT JSON\n(json_data <- %);"},{"cell_type":"markdown","id":"bd296bf5-db20-4028-a1d7-b5c9da0a6cb2","metadata":{},"source":"### Start and monitor pipeline"},{"cell_type":"code","execution_count":22,"id":"b374598a-f9cb-43c4-a2a4-ebcd298108c4","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:05.818171Z","iopub.status.busy":"2023-10-05T05:18:05.817819Z","iopub.status.idle":"2023-10-05T05:18:05.837111Z","shell.execute_reply":"2023-10-05T05:18:05.836663Z","shell.execute_reply.started":"2023-10-05T05:18:05.818153Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":22,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nStart pipeline demo_database.actors_json;"},{"cell_type":"code","execution_count":23,"id":"ca06781b-61fa-4fea-97de-cd0dbacd86e8","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:07.571689Z","iopub.status.busy":"2023-10-05T05:18:07.571335Z","iopub.status.idle":"2023-10-05T05:18:07.690209Z","shell.execute_reply":"2023-10-05T05:18:07.688498Z","shell.execute_reply.started":"2023-10-05T05:18:07.571671Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
DATABASE_NAMEPIPELINE_NAMEERROR_UNIX_TIMESTAMPERROR_TYPEERROR_CODEERROR_MESSAGEERROR_KINDSTD_ERRORLOAD_DATA_LINELOAD_DATA_LINE_NUMBERBATCH_IDERROR_IDBATCH_SOURCE_PARTITION_IDBATCH_EARLIEST_OFFSETBATCH_LATEST_OFFSETHOSTPORTPARTITION
","text/plain":"+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n| DATABASE_NAME | PIPELINE_NAME | ERROR_UNIX_TIMESTAMP | ERROR_TYPE | ERROR_CODE | ERROR_MESSAGE | ERROR_KIND | STD_ERROR | LOAD_DATA_LINE | LOAD_DATA_LINE_NUMBER | BATCH_ID | ERROR_ID | BATCH_SOURCE_PARTITION_ID | BATCH_EARLIEST_OFFSET | BATCH_LATEST_OFFSET | HOST | PORT | PARTITION |\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+\n+---------------+---------------+----------------------+------------+------------+---------------+------------+-----------+----------------+-----------------------+----------+----------+---------------------------+-----------------------+---------------------+------+------+-----------+"},"execution_count":23,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n# Monitor and see if there is any error or warning\nselect * from information_schema.pipelines_errors\nwhere pipeline_name = 'actors_json' ;"},{"cell_type":"markdown","id":"7419ccdd-0f85-414e-bd05-fbe8d9656305","metadata":{},"source":"### Query the table"},{"cell_type":"code","execution_count":25,"id":"e34c5b49-0e97-4b07-9026-38bb6c370f73","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:10.653949Z","iopub.status.busy":"2023-10-05T05:18:10.653693Z","iopub.status.idle":"2023-10-05T05:18:11.007955Z","shell.execute_reply":"2023-10-05T05:18:11.007444Z","shell.execute_reply.started":"2023-10-05T05:18:10.653929Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
json_data
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'}
{'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None}
","text/plain":"+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| json_data |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'April 4, 1965', 'Born At': 'New York City, NY', 'age': 53, 'children': ['Indio Falconer', 'Avri Roel', 'Exton Elias'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Robert Downey Jr.', 'photo': 'https://jsonformatter.org/img/Robert-Downey-Jr.jpg', 'weight': 77.1, 'wife': 'Susan Downey'} |\n| {'Birthdate': 'July 3, 1962', 'Born At': 'Syracuse, NY', 'age': 56, 'children': ['Suri', 'Isabella Jane', 'Connor'], 'hasChildren': True, 'hasGreyHair': False, 'name': 'Tom Cruise', 'photo': 'https://jsonformatter.org/img/tom-cruise.jpg', 'weight': 67.5, 'wife': None} |\n+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":25,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\nselect * from demo_database.actors_json"},{"cell_type":"markdown","id":"c4c155e5-a4a5-4b01-a8a7-e7e626e5fac8","metadata":{},"source":"### Cleanup ressources"},{"cell_type":"code","execution_count":27,"id":"6f0bd356-8a11-4cd9-b774-569d8f5e2520","metadata":{"execution":{"iopub.execute_input":"2023-10-05T05:18:29.840296Z","iopub.status.busy":"2023-10-05T05:18:29.840026Z","iopub.status.idle":"2023-10-05T05:18:29.881582Z","shell.execute_reply":"2023-10-05T05:18:29.880978Z","shell.execute_reply.started":"2023-10-05T05:18:29.840279Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":27,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n\nDrop pipeline if exists demo_database.actors_json;\nDrop table if exists demo_database.actors_json;"},{"cell_type":"markdown","id":"c572193e-7f5b-4637-af5d-2f33f5ba5d86","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"demo_database"},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} +{ + "cells": [ + { + "cell_type": "markdown", + "id": "deb8dbf4-2368-41b4-9f09-b14c96ccb344", + "metadata": {}, + "source": [ + "
\n", + "
\n", + " \n", + "
\n", + "
\n", + "
SingleStore Notebooks
\n", + "

Load JSON files with Pipeline from S3

\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "50093846-9ea3-441d-89f0-fbe0576f78bf", + "metadata": {}, + "source": [ + "This notebook helps you navigate through different scenarios data ingestion of JSON files from an AWS S3 location:\n", + "* Ingest JSON files in AWS S3 using wildcards with pre-defined schema\n", + "* Ingest JSON files in AWS S3 using wildcards into a JSON column" + ] + }, + { + "cell_type": "markdown", + "id": "b2ed410a-87b8-452a-b906-431fb0e949b3", + "metadata": {}, + "source": [ + "## Create a Pipeline from JSON files in AWS S3 using wildcards" + ] + }, + { + "cell_type": "markdown", + "id": "9996b479-586d-4af3-b0ee-b61eead39ebc", + "metadata": {}, + "source": [ + "In this example, we want to create a pipeline from two JSON files called **actors1.json** and **actors2.json** stored in an AWS S3 bucket called singlestoredb and a folder called **actors**. This bucket is located in **us-east-1**." + ] + }, + { + "cell_type": "markdown", + "id": "9a4caf68-0610-41a6-bfd1-59612b8e959a", + "metadata": {}, + "source": [ + "Each file has the following shape with nested objects and arrays:\n", + "```json\n", + "{\n", + " \"Actors\": [\n", + " {\n", + " \"name\": \"Tom Cruise\",\n", + " \"age\": 56,\n", + " \"Born At\": \"Syracuse, NY\",\n", + " \"Birthdate\": \"July 3, 1962\",\n", + " \"photo\": \"https://jsonformatter.org/img/tom-cruise.jpg\",\n", + " \"wife\": null,\n", + " \"weight\": 67.5,\n", + " \"hasChildren\": true,\n", + " \"hasGreyHair\": false,\n", + " \"children\": [\n", + " \"Suri\",\n", + " \"Isabella Jane\",\n", + " \"Connor\"\n", + " ]\n", + " },\n", + " {\n", + " \"name\": \"Robert Downey Jr.\",\n", + " \"age\": 53,\n", + " \"Born At\": \"New York City, NY\",\n", + " \"Birthdate\": \"April 4, 1965\",\n", + " \"photo\": \"https://jsonformatter.org/img/Robert-Downey-Jr.jpg\",\n", + " \"wife\": \"Susan Downey\",\n", + " \"weight\": 77.1,\n", + " \"hasChildren\": true,\n", + " \"hasGreyHair\": false,\n", + " \"children\": [\n", + " \"Indio Falconer\",\n", + " \"Avri Roel\",\n", + " \"Exton Elias\"\n", + " ]\n", + " }\n", + " ]\n", + "}\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "98a8e14f-808e-43ff-b670-b6656091b81a", + "metadata": {}, + "source": [ + "### Create a Table" + ] + }, + { + "cell_type": "markdown", + "id": "a70e168d-de32-4988-90c4-651089ac25a0", + "metadata": {}, + "source": [ + "We first create a table called **actors** in the database **demo_database**" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "b703aab8-7449-43db-af04-9d65520239a5", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "Create database if not exists demo_database;\n", + "Use demo_database;\n", + "CREATE TABLE if not exists demo_database.actors (\n", + "name text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + "age int NOT NULL,\n", + "born_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + "Birthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + "photo text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + "wife text CHARACTER SET utf8 COLLATE utf8_general_ci,\n", + "weight float NOT NULL,\n", + "haschildren boolean,\n", + "hasGreyHair boolean,\n", + "children JSON COLLATE utf8_bin NOT NULL,\n", + "SHARD KEY ()\n", + ");" + ] + }, + { + "cell_type": "markdown", + "id": "e4c15a63-eb17-432d-b0b5-d7485bcf028d", + "metadata": {}, + "source": [ + "### Create a pipeline" + ] + }, + { + "cell_type": "markdown", + "id": "5e09146a-74cb-4e0d-bd0a-3502c2d15a00", + "metadata": {}, + "source": [ + "We then create a pipeline called **actors** in the database **demo_database**. Since those files are small, batch_interval is not as important and the maximum partitions per batch is only 1. For faster performance, we recommend increasing the maximum partitions per batch.\n", + "Note, that since the bucket is publcly accessible, you do not need to provide access key and secret." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "92df7943-e68d-4509-b7f5-4a93697f6578", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE if not exists demo_database.actors\n", + "AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", + "CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", + "/*\n", + "CREDENTIALS '{\"aws_access_key_id\": \"\",\n", + " \"aws_secret_access_key\": \"\"}'\n", + "*/\n", + "BATCH_INTERVAL 2500\n", + "MAX_PARTITIONS_PER_BATCH 1\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `actors`\n", + "FORMAT JSON\n", + "(\n", + " actors.name <- name,\n", + " actors.age <- age,\n", + " actors.born_at <- `Born At`,\n", + " actors.Birthdate <- Birthdate,\n", + " actors.photo <- photo,\n", + " actors.wife <- wife,\n", + " actors.weight <- weight,\n", + " actors.haschildren <- hasChildren,\n", + " actors.hasGreyHair <- hasGreyHair,\n", + " actors.children <- children\n", + ");" + ] + }, + { + "cell_type": "markdown", + "id": "5410c1b9-573f-4326-ba4c-b7af71e069ad", + "metadata": {}, + "source": [ + "### Start and monitor the pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eeddd12e-e28c-4000-859b-6d1291c4a137", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "Start pipeline demo_database.actors;" + ] + }, + { + "cell_type": "markdown", + "id": "a555997d-38dc-4b69-821b-390e52bb4d00", + "metadata": {}, + "source": [ + "If there is no error or warning, you should see no error message." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "f48de155-af85-4c40-ad56-955573a434f8", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "select * from information_schema.pipelines_errors\n", + "where pipeline_name = 'actors' ;" + ] + }, + { + "cell_type": "markdown", + "id": "c18ac453-63de-424a-b9bf-ae6846817ea6", + "metadata": {}, + "source": [ + "### Query the table" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "09a739cb-4925-4699-ab61-71016a04bfb6", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "select * from demo_database.actors;" + ] + }, + { + "cell_type": "markdown", + "id": "c4815572-10d8-4c31-a246-05ad6e7e6e99", + "metadata": {}, + "source": [ + "### Cleanup ressources" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6a6dfc1d-c758-4287-a797-6cc3e4fff934", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "Drop pipeline if exists demo_database.actors;\n", + "Drop table if exists demo_database.actors;" + ] + }, + { + "cell_type": "markdown", + "id": "09fbffac-9a0a-45fd-ad07-ede4e11b3691", + "metadata": {}, + "source": [ + "## Ingest JSON files in AWS S3 using wildcards into a JSON column" + ] + }, + { + "cell_type": "markdown", + "id": "d3e8ff65-1b2d-47c5-8754-28fa4c254edd", + "metadata": {}, + "source": [ + "As the schema of your files might change, you might want to keep flexibility in ingesting the data into one JSON column that we name **json_data**. the table we create is named **actors_json**." + ] + }, + { + "cell_type": "markdown", + "id": "d761f324-0d28-4713-a866-3f96673d8317", + "metadata": {}, + "source": [ + "### Create Table" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "bcb14814-7b79-4df2-ab47-7def7ae03ce3", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "Create database if not exists demo_database;\n", + "Use demo_database;\n", + "CREATE TABLE if not exists demo_database.actors_json (\n", + "json_data JSON NOT NULL ,\n", + "SHARD KEY ()\n", + ");" + ] + }, + { + "cell_type": "markdown", + "id": "429fce4b-c529-4acf-af7e-5d802f79eda6", + "metadata": {}, + "source": [ + "### Create a pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a1d60130-095e-45da-b55d-b427a0af3d26", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE if not exists demo_database.actors_json\n", + "AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", + "CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", + "/*\n", + "CREDENTIALS '{\"aws_access_key_id\": \"\",\n", + " \"aws_secret_access_key\": \"\"}'\n", + "*/\n", + "BATCH_INTERVAL 2500\n", + "MAX_PARTITIONS_PER_BATCH 1\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `actors_json`\n", + "FORMAT JSON\n", + "(json_data <- %);" + ] + }, + { + "cell_type": "markdown", + "id": "bd296bf5-db20-4028-a1d7-b5c9da0a6cb2", + "metadata": {}, + "source": [ + "### Start and monitor pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "b374598a-f9cb-43c4-a2a4-ebcd298108c4", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "Start pipeline demo_database.actors_json;" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "ca06781b-61fa-4fea-97de-cd0dbacd86e8", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "# Monitor and see if there is any error or warning\n", + "select * from information_schema.pipelines_errors\n", + "where pipeline_name = 'actors_json' ;" + ] + }, + { + "cell_type": "markdown", + "id": "7419ccdd-0f85-414e-bd05-fbe8d9656305", + "metadata": {}, + "source": [ + "### Query the table" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e34c5b49-0e97-4b07-9026-38bb6c370f73", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "select * from demo_database.actors_json" + ] + }, + { + "cell_type": "markdown", + "id": "c4c155e5-a4a5-4b01-a8a7-e7e626e5fac8", + "metadata": {}, + "source": [ + "### Cleanup ressources" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "6f0bd356-8a11-4cd9-b774-569d8f5e2520", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "\n", + "Drop pipeline if exists demo_database.actors_json;\n", + "Drop table if exists demo_database.actors_json;" + ] + }, + { + "cell_type": "markdown", + "id": "c572193e-7f5b-4637-af5d-2f33f5ba5d86", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + } + ], + "metadata": { + "jupyterlab": { + "notebooks": { + "version_major": 6, + "version_minor": 4 + } + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/optimize-performance-with-tpch-100/meta.toml b/notebooks/optimize-performance-with-tpch-100/meta.toml index 7562ad1c..330d242e 100644 --- a/notebooks/optimize-performance-with-tpch-100/meta.toml +++ b/notebooks/optimize-performance-with-tpch-100/meta.toml @@ -1,12 +1,17 @@ [meta] title="Learn how to Optimize Performance with TPCH 100" -description="This notebook will help you understand how you can take advantage of SingleStoreDB distributed capability using TPCH-100. We recommend using a S2 or S4 workspace to see the difference in performance. -If you come from single node database, this is an important step to follow to scale your performance linearly as your data grows. +description="""\ + This notebook will help you understand how you can take advantage of + SingleStoreDB distributed capability using TPCH-100. We recommend using + a S2 or S4 workspace to see the difference in performance. -You will see two areas: -*) Ingesting data using pipeline at a super fast speed (You will use a real-time embedded dashboard) -*) Compare query performance with an unoptimized database and an optimized database -" + If you come from single node database, this is an important step to follow + to scale your performance linearly as your data grows. + + You will see two areas: + *) Ingesting data using pipeline at a super fast speed (You will use a real-time embedded dashboard) + *) Compare query performance with an unoptimized database and an optimized database +""" icon="database" tags=["performance", "benchmark", "tpch", "benchmark", "shardkey", "ingest"] -destinations=["spaces"] \ No newline at end of file +destinations=["spaces"] diff --git a/notebooks/optimize-performance-with-tpch-100/notebook.ipynb b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb index 84137758..cc9a0713 100644 --- a/notebooks/optimize-performance-with-tpch-100/notebook.ipynb +++ b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb @@ -1 +1,1113 @@ -{"cells":[{"attachments":null,"cell_type":"markdown","id":"8e67bcbe-6ace-4ca9-b28c-927b4b5a85b2","metadata":{"language":"sql"},"source":"
\n
\n \n
\n
\n
SingleStore Notebooks
\n

Learn How to Optimize Table Data Structures with TPCH Benchmark

\n
\n
"},{"attachments":null,"cell_type":"markdown","id":"5d93af8b-eb1d-4207-a060-1a45c46d8b41","metadata":{"language":"sql"},"source":"### Context\n\nThis notebook will help you with four core key principles for getting performance out of SingleStoreDB using TPCH Benchmark. SingleStoreDB is a distributed database, so you should think of using shard keys, database partitions, primary keys and indexes for getting the best performance out of it. \n\n##### About database partitions\nThe generalized recommendation for most clusters is to have 4 CPU cores per database partition on each leaf. This means if you had a cluster with 16 cores on each of 4 leaves (64 CPU cores total across all leaf hosts), you would want to have 4 partitions on each leaf (16 partitions throughout the cluster). If you are using a S00 workspace, you will have 2 partitions per database. ***Note*** *that increasing partitions will have additional memory and caching overheads, which can be expensive if you have thousands of tables*\n\n##### About shard keys\nData is distributed across the SingleStoreDB Cloud workspace into a number of partitions on the leaf nodes. The shard key is a collection of the columns in a table that are used to control how the rows of that table are distributed. To determine the partition responsible for a given row, SingleStoreDB Cloud computes a hash from all the columns in the shard key to the partition ID. Therefore, rows with the same shard key will reside on the same partition.\n\n##### About hash indexes\nThey are highly efficient for exact-match lookups (point-reads). Because hash indexes store rows in a sparse array of buckets indexed through a hash function on the relevant columns, queries can quickly retrieve data by examining only the corresponding bucket rather than searching the entire dataset. This enables significant reduction in lookup time and hence, increased performance for specific query types.\n\n**For that tutorial, we recommend using a workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.**"},{"attachments":null,"cell_type":"markdown","id":"67f041ef-5605-43ef-8ca0-5db3194b4cad","metadata":{"language":"sql"},"source":"
\n \n
\n

Note

\n

For that tutorial, we recommend using workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.

\n
\n
"},{"attachments":null,"cell_type":"markdown","id":"6052728d-7828-4fb2-bb53-b960a7ad43af","metadata":{"language":"sql"},"source":"### Let's first create the unoptimized database"},{"cell_type":"code","execution_count":null,"id":"7301a602-48cf-4f3b-9cbc-2e7184d97ae0","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\ncreate database if not exists s2_tpch_unoptimized\n\n# To create a database with custom partitions use the following syntax: CREATE DATABASE YourDatabaseName PARTITIONS=X;\n# You cannot change after creation the number of partitions"},{"attachments":null,"cell_type":"markdown","id":"94c8bb6f-658d-4434-9074-4847f1c7d721","metadata":{"language":"sql"},"source":"If using a S00, the database will have 2 partitions, if using S1, it will have 8 partitions"},{"cell_type":"code","execution_count":null,"id":"b36585b9-4d52-4301-ac68-60fa49425751","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nSELECT num_partitions FROM information_schema.DISTRIBUTED_DATABASES WHERE database_name = 's2_tpch_unoptimized';"},{"attachments":null,"cell_type":"markdown","id":"b576e31c-6a67-4126-86ab-480fd96805d3","metadata":{"language":"sql"},"source":"##### Let's create all the tables in that database with no index, shard key or primary key"},{"attachments":null,"cell_type":"markdown","id":"4587c575-9b5a-4535-bebe-70779064e9dc","metadata":{"execution":{"iopub.execute_input":"2023-10-02T05:17:36.998748Z","iopub.status.busy":"2023-10-02T05:17:36.998493Z","iopub.status.idle":"2023-10-02T05:17:37.009703Z","shell.execute_reply":"2023-10-02T05:17:37.009283Z","shell.execute_reply.started":"2023-10-02T05:17:36.998731Z"},"language":"sql"},"source":"
\n \n
\n

Action Required

\n

Make sure to select the s2_tpch_unoptimized database from the drop-down menu at the top of this notebook.\n It updates the connection_url to connect to that database.

\n
\n
"},{"cell_type":"code","execution_count":null,"id":"afde1362-2d38-4732-94ed-6d4ed05a6806","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE TABLE IF NOT EXISTS `customer` (\n `c_custkey` int(11) NOT NULL,\n `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_nationkey` int(11) NOT NULL,\n `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_acctbal` decimal(15,2) NOT NULL,\n `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `lineitem` (\n `l_orderkey` bigint(11) NOT NULL,\n `l_partkey` int(11) NOT NULL,\n `l_suppkey` int(11) NOT NULL,\n `l_linenumber` int(11) NOT NULL,\n `l_quantity` decimal(15,2) NOT NULL,\n `l_extendedprice` decimal(15,2) NOT NULL,\n `l_discount` decimal(15,2) NOT NULL,\n `l_tax` decimal(15,2) NOT NULL,\n `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipdate` date NOT NULL,\n `l_commitdate` date NOT NULL,\n `l_receiptdate` date NOT NULL,\n `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `nation` (\n `n_nationkey` int(11) NOT NULL,\n `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `n_regionkey` int(11) NOT NULL,\n `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `orders` (\n `o_orderkey` bigint(11) NOT NULL,\n `o_custkey` int(11) NOT NULL,\n `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_totalprice` decimal(15,2) NOT NULL,\n `o_orderdate` date NOT NULL,\n `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_shippriority` int(11) NOT NULL,\n `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `part` (\n `p_partkey` int(11) NOT NULL,\n `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_size` int(11) NOT NULL,\n `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_retailprice` decimal(15,2) NOT NULL,\n `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `partsupp` (\n `ps_partkey` int(11) NOT NULL,\n `ps_suppkey` int(11) NOT NULL,\n `ps_availqty` int(11) NOT NULL,\n `ps_supplycost` decimal(15,2) NOT NULL,\n `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `region` (\n `r_regionkey` int(11) NOT NULL,\n `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS `supplier` (\n `s_suppkey` int(11) NOT NULL,\n `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_nationkey` int(11) NOT NULL,\n `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_acctbal` decimal(15,2) NOT NULL,\n `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n);"},{"attachments":null,"cell_type":"markdown","id":"09711e8c-fb01-4e10-862b-ee5350be6076","metadata":{"language":"sql"},"source":"### Now let's create the pipelines and run them to ingest data"},{"cell_type":"code","execution_count":null,"id":"4e8ca124-ac4b-49de-b0ee-d9441d43bedd","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `customer_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/customer'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `customer`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"ce739af4-6839-4751-8a81-019fb26cad72","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `lineitem_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/lineitem/lineitem.'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `lineitem`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"bfdd5bbc-702a-4f77-b771-cd38189040e0","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `nation_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/nation'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `nation`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"1b040083-f864-4e64-9bd2-00b1ff7d1e2b","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `orders_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/orders'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `orders`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"b5e06dfe-f679-4fe2-bd47-802a0b127270","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `partsupp_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/partsupp'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `partsupp`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"8b2726ea-9d0c-4809-bf35-b851821cf336","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `part_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/part'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `part`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"06114a70-d7f9-4c1f-b6a6-4554b33bb5c6","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `region_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/region'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `region`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"bfc2e19d-f32c-4b9e-8fa7-1e68711f834e","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE PIPELINE IF NOT EXISTS `supplier_pipeline`\nAS LOAD DATA S3 'memsql-tpch-dataset/sf_100/supplier'\nCONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\nBATCH_INTERVAL 2500\nDISABLE OUT_OF_ORDER OPTIMIZATION\nDISABLE OFFSETS METADATA GC\nSKIP DUPLICATE KEY ERRORS\nINTO TABLE `supplier`\nFIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\nLINES TERMINATED BY '|\\n' STARTING BY '';"},{"cell_type":"code","execution_count":null,"id":"e19cb045-bebc-4aa6-92d7-ae06778d8af8","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nSTART PIPELINE customer_pipeline;\nSTART PIPELINE lineitem_pipeline;\nSTART PIPELINE nation_pipeline;\nSTART PIPELINE orders_pipeline;\nSTART PIPELINE partsupp_pipeline;\nSTART PIPELINE part_pipeline;\nSTART PIPELINE region_pipeline;\nSTART PIPELINE supplier_pipeline;"},{"attachments":null,"cell_type":"markdown","id":"3eacdd09-9b27-4995-a3df-9514cd733a57","metadata":{"language":"sql"},"source":"#### [Optional Step] Check data ingestion in real-time with Perspective"},{"cell_type":"code","execution_count":null,"id":"e5c3fa1a-af9b-4fdb-98bc-9c73a1fa7f33","metadata":{"language":"python"},"outputs":[],"source":"pip install perspective-python --quiet"},{"cell_type":"code","execution_count":null,"id":"b61f205f-5d1d-4af2-8369-e31057c76f66","metadata":{"language":"python"},"outputs":[],"source":"import perspective\nimport threading\nimport random\nimport time\nfrom datetime import datetime, date\nfrom perspective import Table, PerspectiveWidget\nimport warnings\nwarnings.filterwarnings('ignore')"},{"cell_type":"code","execution_count":null,"id":"ac376696-0b7e-4182-bc04-ddef400b7fca","metadata":{"language":"python"},"outputs":[],"source":"def loop():\n while mode != 'stop':\n while mode == 'run':\n table.update(data_source())\n time.sleep(1)"},{"cell_type":"code","execution_count":null,"id":"5e2ce253-576d-49c9-a92b-f165ffcc4ae7","metadata":{"language":"python"},"outputs":[],"source":"def data_source():\n result = %sql select sum(rows_streamed) as rows_streamed from information_schema.pipelines_batches_summary where database_name = 's2_tpch_unoptimized';\n result2 = list(result.dicts()) \n return result2\n\nSCHEMA = {\n \"rows_streamed\": int\n}"},{"cell_type":"code","execution_count":null,"id":"d388a00d-23ec-45d2-a94c-5e747da707c0","metadata":{"language":"python"},"outputs":[],"source":"mode = 'run'\ntable = perspective.Table(SCHEMA, limit=100)\nthreading.Thread(target=loop).start()"},{"cell_type":"code","execution_count":null,"id":"9e88e523-63b1-48e3-bde5-a2840490199c","metadata":{"language":"python"},"outputs":[],"source":"perspective.PerspectiveWidget(table,title = \"Track Row Ingestion\",plugin=\"Y Line\",columns=[\"count_rows\"])"},{"cell_type":"code","execution_count":null,"id":"debbed63-11dc-43dc-9f12-a0e80a5b7703","metadata":{"language":"python"},"outputs":[],"source":"mode = 'stop'"},{"attachments":null,"cell_type":"markdown","id":"442281db-7fd2-4bba-9104-84f3b0537a9a","metadata":{"language":"sql"},"source":"### Now, let's see the performance of a few queries"},{"cell_type":"code","execution_count":null,"id":"97e9050b-3b8e-40e3-b871-2b0bb73eb5ae","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 1: Pricing Summary Report \nselect \n l_returnflag,\n l_linestatus,\n sum(l_quantity) as sum_qty,\n sum(l_extendedprice) as sum_base_price,\n sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n avg(l_discount) as avg_disc,\n count(*) as count_order \nfrom s2_tpch_unoptimized.lineitem\nwhere l_shipdate <= date('1998-12-01') - interval '90' day \ngroup by l_returnflag, l_linestatus \norder by l_returnflag, l_linestatus;"},{"cell_type":"code","execution_count":null,"id":"71669c07-d06e-41f4-bd63-5046add22afb","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 4: Order Priority Checking \nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_unoptimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_unoptimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;"},{"cell_type":"code","execution_count":null,"id":"654f872b-4a35-4897-86d2-c51b548919b8","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n-- TPC-H Query 21: Suppliers Who Kept Orders Waiting \n\nselect\n s_name,\n count(*) as numwait\nfrom\n s2_tpch_unoptimized.supplier,\n s2_tpch_unoptimized.lineitem l1,\n s2_tpch_unoptimized.orders,\n s2_tpch_unoptimized.nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n s2_tpch_unoptimized.lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n s2_tpch_unoptimized.lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;"},{"attachments":null,"cell_type":"markdown","id":"0ad2d768-cb53-4e0b-8353-6178c8f9508c","metadata":{"language":"sql"},"source":"### Now, let's first focus on optimizing the performance"},{"cell_type":"code","execution_count":null,"id":"d1844926-ae73-4fec-b5ba-802c8173e846","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\ncreate database if not exists s2_tpch_optimized"},{"attachments":null,"cell_type":"markdown","id":"a163696a-0507-4b05-9146-6cbfa1ba1e29","metadata":{"language":"sql"},"source":"
\n \n
\n

Action Required

\n

Make sure to select the s2_tpch_optimized database from the drop-down menu at the top of this notebook.\n It updates the connection_url to connect to that database.

\n
\n
"},{"attachments":null,"cell_type":"markdown","id":"bafd1114-f88c-409c-8281-b32ac27f1222","metadata":{"language":"sql"},"source":"##### Now, let's create each table with optimized data structure:\n* We create a unique key through primary key. For example **lineitem** table needs both the orderkey and linenumber to identify rows by uniqueness\n* We create a shard key which will distribute data in an efficient way to perform fast join and filtering. For **lineitem** table since we perform joins and calculation based on the orderkey we create a shardkey with orderkey"},{"cell_type":"code","execution_count":null,"id":"ff6aea3d-a965-475d-becd-3910965f5c8f","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nCREATE TABLE IF NOT EXISTS `lineitem` (\n `l_orderkey` bigint(11) NOT NULL,\n `l_partkey` int(11) NOT NULL,\n `l_suppkey` int(11) NOT NULL,\n `l_linenumber` int(11) NOT NULL,\n `l_quantity` decimal(15,2) NOT NULL,\n `l_extendedprice` decimal(15,2) NOT NULL,\n `l_discount` decimal(15,2) NOT NULL,\n `l_tax` decimal(15,2) NOT NULL,\n `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipdate` date NOT NULL,\n `l_commitdate` date NOT NULL,\n `l_receiptdate` date NOT NULL,\n `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`l_orderkey`,`l_linenumber`) USING HASH,\n SHARD KEY `__SHARDKEY` (`l_orderkey`),\n KEY `l_orderkey` (`l_orderkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `customer` (\n `c_custkey` int(11) NOT NULL,\n `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_nationkey` int(11) NOT NULL,\n `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_acctbal` decimal(15,2) NOT NULL,\n `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`c_custkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`c_custkey`),\n KEY `c_custkey` (`c_custkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `nation` (\n `n_nationkey` int(11) NOT NULL,\n `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `n_regionkey` int(11) NOT NULL,\n `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`n_nationkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`n_nationkey`),\n KEY `n_nationkey` (`n_nationkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `orders` (\n `o_orderkey` bigint(11) NOT NULL,\n `o_custkey` int(11) NOT NULL,\n `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_totalprice` decimal(15,2) NOT NULL,\n `o_orderdate` date NOT NULL,\n `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `o_shippriority` int(11) NOT NULL,\n `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`o_orderkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`o_orderkey`),\n KEY `o_orderkey` (`o_orderkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `part` (\n `p_partkey` int(11) NOT NULL,\n `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_size` int(11) NOT NULL,\n `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `p_retailprice` decimal(15,2) NOT NULL,\n `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`p_partkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`p_partkey`),\n KEY `p_partkey` (`p_partkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `partsupp` (\n `ps_partkey` int(11) NOT NULL,\n `ps_suppkey` int(11) NOT NULL,\n `ps_availqty` int(11) NOT NULL,\n `ps_supplycost` decimal(15,2) NOT NULL,\n `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`ps_partkey`,`ps_suppkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`ps_partkey`),\n KEY `ps_partkey` (`ps_partkey`,`ps_suppkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `region` (\n `r_regionkey` int(11) NOT NULL,\n `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`r_regionkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`r_regionkey`),\n KEY `r_regionkey` (`r_regionkey`) USING CLUSTERED COLUMNSTORE\n);\n\nCREATE TABLE IF NOT EXISTS `supplier` (\n `s_suppkey` int(11) NOT NULL,\n `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_nationkey` int(11) NOT NULL,\n `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n `s_acctbal` decimal(15,2) NOT NULL,\n `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n UNIQUE KEY `pk` (`s_suppkey`) USING HASH,\n SHARD KEY `__SHARDKEY` (`s_suppkey`),\n KEY `s_suppkey` (`s_suppkey`) USING CLUSTERED COLUMNSTORE\n);"},{"cell_type":"code","execution_count":null,"id":"6ed484a7-8ed8-479d-9ebe-5716749369bc","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\nINSERT INTO s2_tpch_optimized.nation SELECT * FROM s2_tpch_unoptimized.nation;\nINSERT INTO s2_tpch_optimized.lineitem SELECT * FROM s2_tpch_unoptimized.lineitem;\nINSERT INTO s2_tpch_optimized.customer SELECT * FROM s2_tpch_unoptimized.customer;\nINSERT INTO s2_tpch_optimized.orders SELECT * FROM s2_tpch_unoptimized.orders;\nINSERT INTO s2_tpch_optimized.part SELECT * FROM s2_tpch_unoptimized.part;\nINSERT INTO s2_tpch_optimized.partsupp SELECT * FROM s2_tpch_unoptimized.partsupp;\nINSERT INTO s2_tpch_optimized.region SELECT * FROM s2_tpch_unoptimized.region;\nINSERT INTO s2_tpch_optimized.supplier SELECT * FROM s2_tpch_unoptimized.supplier;"},{"cell_type":"code","execution_count":null,"id":"9c79d8a5-c626-4f14-85e2-1f00afbceb8f","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 1: Pricing Summary Report \nselect \n l_returnflag,\n l_linestatus,\n sum(l_quantity) as sum_qty,\n sum(l_extendedprice) as sum_base_price,\n sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n avg(l_discount) as avg_disc,\n count(*) as count_order \nfrom lineitem\nwhere l_shipdate <= date('1998-12-01') - interval '90' day \ngroup by l_returnflag, l_linestatus \norder by l_returnflag, l_linestatus;"},{"cell_type":"code","execution_count":null,"id":"e9b21e9b-1869-4a1e-8998-a209c3dc6ffd","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n# TPC-H Query 4: Order Priority Checking \nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_optimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_optimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;"},{"cell_type":"code","execution_count":null,"id":"c8b63c2a-b1fb-4cd1-90bb-62e8b56922f5","metadata":{"language":"sql"},"outputs":[],"source":"%%sql\n-- TPC-H Query 21: Suppliers Who Kept Orders Waiting \n\nselect\n s_name,\n count(*) as numwait\nfrom\n s2_tpch_optimized.supplier,\n s2_tpch_optimized.lineitem l1,\n s2_tpch_optimized.orders,\n s2_tpch_optimized.nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n s2_tpch_optimized.lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n s2_tpch_optimized.lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;"},{"attachments":null,"cell_type":"markdown","id":"54a6902d-bc3b-455d-8f47-3450d5928de8","metadata":{"language":"sql"},"source":"### Finally, let's do a side by side comparison between the optimized and unoptimized database"},{"cell_type":"code","execution_count":null,"id":"2f23e742-d9fe-467a-a299-a09a20d2af1e","metadata":{"language":"python"},"outputs":[],"source":"from singlestoredb import create_engine\nimport sqlalchemy as sa\nconnection_url_unoptimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_unoptimized?ssl_cipher=HIGH\"\ndb_connection_unoptimized = create_engine(connection_url_unoptimized).connect()\nconnection_url_optimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_optimized?ssl_cipher=HIGH\"\ndb_connection_optimized = create_engine(connection_url_optimized).connect()"},{"attachments":null,"cell_type":"markdown","id":"7f84ed59-9d2c-4e3e-92eb-63603645d953","metadata":{"language":"sql"},"source":"Here are a few queries that you can test side by side against. Overall you will notice an average of 4x improvement in performance"},{"cell_type":"code","execution_count":null,"id":"f3d86d62-ffe2-40ad-b59a-7c77cae98ca0","metadata":{"language":"python"},"outputs":[],"source":"sql_query4 = sa.text('''\nselect\n o_orderpriority,\n count(*) as order_count\nfrom\n s2_tpch_unoptimized.orders\nwhere\n o_orderdate >= date('1993-07-01')\n and o_orderdate < date('1993-10-01')\n and exists (\n select *\n from s2_tpch_unoptimized.lineitem\n where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n )\ngroup by o_orderpriority\norder by o_orderpriority;\n''')"},{"cell_type":"code","execution_count":null,"id":"7d947658-6dec-4efa-97f6-863977b2003b","metadata":{"language":"python"},"outputs":[],"source":"sql_query21 = sa.text('''\n select\n s_name,\n count(*) as numwait\nfrom\n supplier,\n lineitem l1,\n orders,\n nation\nwhere\n s_suppkey = l1.l_suppkey\n and o_orderkey = l1.l_orderkey\n and o_orderstatus = 'F'\n and l1.l_receiptdate > l1.l_commitdate\n and exists (\n select\n *\n from\n lineitem l2\n where\n l2.l_orderkey = l1.l_orderkey\n and l2.l_suppkey <> l1.l_suppkey\n )\n and not exists (\n select\n *\n from\n lineitem l3\n where\n l3.l_orderkey = l1.l_orderkey\n and l3.l_suppkey <> l1.l_suppkey\n and l3.l_receiptdate > l3.l_commitdate\n )\n and s_nationkey = n_nationkey\n and n_name = 'EGYPT'\ngroup by\n s_name\norder by\n numwait desc,\n s_name\nlimit 100;\n''')"},{"cell_type":"code","execution_count":null,"id":"6e4da6ac-52ff-4506-8826-3a46bf350656","metadata":{"language":"python"},"outputs":[],"source":"result = db_connection_optimized.execute(sql_query21)"},{"cell_type":"code","execution_count":null,"id":"b699bc42-e9bd-4b8f-81c0-48311b7fd14e","metadata":{"language":"python"},"outputs":[],"source":"import time\nimport pandas as pd\nimport plotly.graph_objs as go\nnum_iterations = 10\nopt_times = []\n\nfor i in range(num_iterations):\n opt_start_time = time.time()\n opt_result = db_connection_optimized.execute(sql_query21)\n opt_stop_time = time.time()\n opt_times.append(opt_stop_time - opt_start_time)\n\nunopt_times = []\nfor i in range(num_iterations):\n unopt_start_time = time.time()\n unopt_result = db_connection_unoptimized.execute(sql_query21)\n unopt_stop_time = time.time()\n unopt_times.append(unopt_stop_time - unopt_start_time)\n\nx_axis = list(range(1, num_iterations + 1))\ndata = {\n 'iteration': x_axis,\n 'opt_times': opt_times,\n 'unopt_times': unopt_times,\n}\ndf = pd.DataFrame.from_dict(data)\n\nfig = go.Figure()\n\n# Adding optimized times to the plot\nfig.add_trace(go.Scatter(x=df['iteration'], y=df['opt_times'], mode='lines+markers', name='Optimized Database'))\n\n# Adding unoptimized times to the plot\nfig.add_trace(go.Scatter(x=df['iteration'], y=df['unopt_times'], mode='lines+markers', name='Unoptimized Database'))\n\n# Update y-axis and x-axis properties\nfig.update_layout(\n title=\"Execution Time Comparison\",\n xaxis_title=\"Iteration\",\n yaxis_title=\"Time in Seconds\",\n xaxis=dict(tickmode='array', tickvals=list(range(1, num_iterations + 1)))\n)\n\n# Show the plot\nfig.show()"},{"attachments":null,"cell_type":"markdown","id":"4708ffe5-ea88-48a8-a4ac-9eaa5f801f79","metadata":{"language":"sql"},"source":"
\n
\n"}],"metadata":{"jupyterlab":{"notebooks":{"version_major":6,"version_minor":4}},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimeType":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_cell_default_language":"sql","singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"s2_tpch_optimized"}},"nbformat":4,"nbformat_minor":5} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8e67bcbe-6ace-4ca9-b28c-927b4b5a85b2", + "metadata": {}, + "source": [ + "
\n", + "
\n", + " \n", + "
\n", + "
\n", + "
SingleStore Notebooks
\n", + "

Learn how to Optimize Performance with TPCH 100

\n", + "
\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "5d93af8b-eb1d-4207-a060-1a45c46d8b41", + "metadata": {}, + "source": [ + "### Context\n", + "\n", + "This notebook will help you with four core key principles for getting performance out of SingleStoreDB using TPCH Benchmark. SingleStoreDB is a distributed database, so you should think of using shard keys, database partitions, primary keys and indexes for getting the best performance out of it.\n", + "\n", + "##### About database partitions\n", + "The generalized recommendation for most clusters is to have 4 CPU cores per database partition on each leaf. This means if you had a cluster with 16 cores on each of 4 leaves (64 CPU cores total across all leaf hosts), you would want to have 4 partitions on each leaf (16 partitions throughout the cluster). If you are using a S00 workspace, you will have 2 partitions per database. ***Note*** *that increasing partitions will have additional memory and caching overheads, which can be expensive if you have thousands of tables*\n", + "\n", + "##### About shard keys\n", + "Data is distributed across the SingleStoreDB Cloud workspace into a number of partitions on the leaf nodes. The shard key is a collection of the columns in a table that are used to control how the rows of that table are distributed. To determine the partition responsible for a given row, SingleStoreDB Cloud computes a hash from all the columns in the shard key to the partition ID. Therefore, rows with the same shard key will reside on the same partition.\n", + "\n", + "##### About hash indexes\n", + "They are highly efficient for exact-match lookups (point-reads). Because hash indexes store rows in a sparse array of buckets indexed through a hash function on the relevant columns, queries can quickly retrieve data by examining only the corresponding bucket rather than searching the entire dataset. This enables significant reduction in lookup time and hence, increased performance for specific query types.\n", + "\n", + "**For that tutorial, we recommend using a workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.**" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "67f041ef-5605-43ef-8ca0-5db3194b4cad", + "metadata": {}, + "source": [ + "
\n", + " \n", + "
\n", + "

Note

\n", + "

For that tutorial, we recommend using workspace of size S4 to ingest data faster and also see the difference and gain you can get from a distributed architecture.

\n", + "
\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "6052728d-7828-4fb2-bb53-b960a7ad43af", + "metadata": {}, + "source": [ + "### Let's first create the unoptimized database" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "7301a602-48cf-4f3b-9cbc-2e7184d97ae0", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "create database if not exists s2_tpch_unoptimized\n", + "\n", + "# To create a database with custom partitions use the following syntax: CREATE DATABASE YourDatabaseName PARTITIONS=X;\n", + "# You cannot change after creation the number of partitions" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "94c8bb6f-658d-4434-9074-4847f1c7d721", + "metadata": {}, + "source": [ + "If using a S00, the database will have 2 partitions, if using S1, it will have 8 partitions" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "b36585b9-4d52-4301-ac68-60fa49425751", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "SELECT num_partitions FROM information_schema.DISTRIBUTED_DATABASES WHERE database_name = 's2_tpch_unoptimized';" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "b576e31c-6a67-4126-86ab-480fd96805d3", + "metadata": {}, + "source": [ + "##### Let's create all the tables in that database with no index, shard key or primary key" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "4587c575-9b5a-4535-bebe-70779064e9dc", + "metadata": {}, + "source": [ + "
\n", + " \n", + "
\n", + "

Action Required

\n", + "

Make sure to select the s2_tpch_unoptimized database from the drop-down menu at the top of this notebook.\n", + " It updates the connection_url to connect to that database.

\n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "afde1362-2d38-4732-94ed-6d4ed05a6806", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE TABLE IF NOT EXISTS `customer` (\n", + " `c_custkey` int(11) NOT NULL,\n", + " `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_nationkey` int(11) NOT NULL,\n", + " `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_acctbal` decimal(15,2) NOT NULL,\n", + " `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `lineitem` (\n", + " `l_orderkey` bigint(11) NOT NULL,\n", + " `l_partkey` int(11) NOT NULL,\n", + " `l_suppkey` int(11) NOT NULL,\n", + " `l_linenumber` int(11) NOT NULL,\n", + " `l_quantity` decimal(15,2) NOT NULL,\n", + " `l_extendedprice` decimal(15,2) NOT NULL,\n", + " `l_discount` decimal(15,2) NOT NULL,\n", + " `l_tax` decimal(15,2) NOT NULL,\n", + " `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_shipdate` date NOT NULL,\n", + " `l_commitdate` date NOT NULL,\n", + " `l_receiptdate` date NOT NULL,\n", + " `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `nation` (\n", + " `n_nationkey` int(11) NOT NULL,\n", + " `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `n_regionkey` int(11) NOT NULL,\n", + " `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `orders` (\n", + " `o_orderkey` bigint(11) NOT NULL,\n", + " `o_custkey` int(11) NOT NULL,\n", + " `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_totalprice` decimal(15,2) NOT NULL,\n", + " `o_orderdate` date NOT NULL,\n", + " `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_shippriority` int(11) NOT NULL,\n", + " `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `part` (\n", + " `p_partkey` int(11) NOT NULL,\n", + " `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_size` int(11) NOT NULL,\n", + " `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_retailprice` decimal(15,2) NOT NULL,\n", + " `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `partsupp` (\n", + " `ps_partkey` int(11) NOT NULL,\n", + " `ps_suppkey` int(11) NOT NULL,\n", + " `ps_availqty` int(11) NOT NULL,\n", + " `ps_supplycost` decimal(15,2) NOT NULL,\n", + " `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `region` (\n", + " `r_regionkey` int(11) NOT NULL,\n", + " `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `supplier` (\n", + " `s_suppkey` int(11) NOT NULL,\n", + " `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_nationkey` int(11) NOT NULL,\n", + " `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_acctbal` decimal(15,2) NOT NULL,\n", + " `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL\n", + ");" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "09711e8c-fb01-4e10-862b-ee5350be6076", + "metadata": {}, + "source": [ + "### Now let's create the pipelines and run them to ingest data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4e8ca124-ac4b-49de-b0ee-d9441d43bedd", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `customer_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/customer'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `customer`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ce739af4-6839-4751-8a81-019fb26cad72", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `lineitem_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/lineitem/lineitem.'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `lineitem`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "bfdd5bbc-702a-4f77-b771-cd38189040e0", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `nation_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/nation'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `nation`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1b040083-f864-4e64-9bd2-00b1ff7d1e2b", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `orders_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/orders'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `orders`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b5e06dfe-f679-4fe2-bd47-802a0b127270", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `partsupp_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/partsupp'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `partsupp`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "8b2726ea-9d0c-4809-bf35-b851821cf336", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `part_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/part'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `part`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "06114a70-d7f9-4c1f-b6a6-4554b33bb5c6", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `region_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/region'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `region`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "bfc2e19d-f32c-4b9e-8fa7-1e68711f834e", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE PIPELINE IF NOT EXISTS `supplier_pipeline`\n", + "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/supplier'\n", + "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + "BATCH_INTERVAL 2500\n", + "DISABLE OUT_OF_ORDER OPTIMIZATION\n", + "DISABLE OFFSETS METADATA GC\n", + "SKIP DUPLICATE KEY ERRORS\n", + "INTO TABLE `supplier`\n", + "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + "LINES TERMINATED BY '|\\n' STARTING BY '';" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e19cb045-bebc-4aa6-92d7-ae06778d8af8", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "START PIPELINE customer_pipeline;\n", + "START PIPELINE lineitem_pipeline;\n", + "START PIPELINE nation_pipeline;\n", + "START PIPELINE orders_pipeline;\n", + "START PIPELINE partsupp_pipeline;\n", + "START PIPELINE part_pipeline;\n", + "START PIPELINE region_pipeline;\n", + "START PIPELINE supplier_pipeline;" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "3eacdd09-9b27-4995-a3df-9514cd733a57", + "metadata": {}, + "source": [ + "#### [Optional Step] Check data ingestion in real-time with Perspective" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "e5c3fa1a-af9b-4fdb-98bc-9c73a1fa7f33", + "metadata": {}, + "outputs": [], + "source": [ + "pip install perspective-python --quiet" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "b61f205f-5d1d-4af2-8369-e31057c76f66", + "metadata": {}, + "outputs": [], + "source": [ + "import perspective\n", + "import threading\n", + "import random\n", + "import time\n", + "from datetime import datetime, date\n", + "from perspective import Table, PerspectiveWidget\n", + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ac376696-0b7e-4182-bc04-ddef400b7fca", + "metadata": {}, + "outputs": [], + "source": [ + "def loop():\n", + " while mode != 'stop':\n", + " while mode == 'run':\n", + " table.update(data_source())\n", + " time.sleep(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "5e2ce253-576d-49c9-a92b-f165ffcc4ae7", + "metadata": {}, + "outputs": [], + "source": [ + "def data_source():\n", + " result = %sql select sum(rows_streamed) as rows_streamed from information_schema.pipelines_batches_summary where database_name = 's2_tpch_unoptimized';\n", + " result2 = list(result.dicts())\n", + " return result2\n", + "\n", + "SCHEMA = {\n", + " \"rows_streamed\": int\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d388a00d-23ec-45d2-a94c-5e747da707c0", + "metadata": {}, + "outputs": [], + "source": [ + "mode = 'run'\n", + "table = perspective.Table(SCHEMA, limit=100)\n", + "threading.Thread(target=loop).start()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "9e88e523-63b1-48e3-bde5-a2840490199c", + "metadata": {}, + "outputs": [], + "source": [ + "perspective.PerspectiveWidget(table,title = \"Track Row Ingestion\",plugin=\"Y Line\",columns=[\"count_rows\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "debbed63-11dc-43dc-9f12-a0e80a5b7703", + "metadata": {}, + "outputs": [], + "source": [ + "mode = 'stop'" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "442281db-7fd2-4bba-9104-84f3b0537a9a", + "metadata": {}, + "source": [ + "### Now, let's see the performance of a few queries" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "97e9050b-3b8e-40e3-b871-2b0bb73eb5ae", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "# TPC-H Query 1: Pricing Summary Report\n", + "select\n", + " l_returnflag,\n", + " l_linestatus,\n", + " sum(l_quantity) as sum_qty,\n", + " sum(l_extendedprice) as sum_base_price,\n", + " sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n", + " sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n", + " avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n", + " avg(l_discount) as avg_disc,\n", + " count(*) as count_order\n", + "from s2_tpch_unoptimized.lineitem\n", + "where l_shipdate <= date('1998-12-01') - interval '90' day\n", + "group by l_returnflag, l_linestatus\n", + "order by l_returnflag, l_linestatus;" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "71669c07-d06e-41f4-bd63-5046add22afb", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "# TPC-H Query 4: Order Priority Checking\n", + "select\n", + " o_orderpriority,\n", + " count(*) as order_count\n", + "from\n", + " s2_tpch_unoptimized.orders\n", + "where\n", + " o_orderdate >= date('1993-07-01')\n", + " and o_orderdate < date('1993-10-01')\n", + " and exists (\n", + " select *\n", + " from s2_tpch_unoptimized.lineitem\n", + " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + " )\n", + "group by o_orderpriority\n", + "order by o_orderpriority;" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "654f872b-4a35-4897-86d2-c51b548919b8", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "-- TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", + "\n", + "select\n", + " s_name,\n", + " count(*) as numwait\n", + "from\n", + " s2_tpch_unoptimized.supplier,\n", + " s2_tpch_unoptimized.lineitem l1,\n", + " s2_tpch_unoptimized.orders,\n", + " s2_tpch_unoptimized.nation\n", + "where\n", + " s_suppkey = l1.l_suppkey\n", + " and o_orderkey = l1.l_orderkey\n", + " and o_orderstatus = 'F'\n", + " and l1.l_receiptdate > l1.l_commitdate\n", + " and exists (\n", + " select\n", + " *\n", + " from\n", + " s2_tpch_unoptimized.lineitem l2\n", + " where\n", + " l2.l_orderkey = l1.l_orderkey\n", + " and l2.l_suppkey <> l1.l_suppkey\n", + " )\n", + " and not exists (\n", + " select\n", + " *\n", + " from\n", + " s2_tpch_unoptimized.lineitem l3\n", + " where\n", + " l3.l_orderkey = l1.l_orderkey\n", + " and l3.l_suppkey <> l1.l_suppkey\n", + " and l3.l_receiptdate > l3.l_commitdate\n", + " )\n", + " and s_nationkey = n_nationkey\n", + " and n_name = 'EGYPT'\n", + "group by\n", + " s_name\n", + "order by\n", + " numwait desc,\n", + " s_name\n", + "limit 100;" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "0ad2d768-cb53-4e0b-8353-6178c8f9508c", + "metadata": {}, + "source": [ + "### Now, let's first focus on optimizing the performance" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "d1844926-ae73-4fec-b5ba-802c8173e846", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "create database if not exists s2_tpch_optimized" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "a163696a-0507-4b05-9146-6cbfa1ba1e29", + "metadata": {}, + "source": [ + "
\n", + " \n", + "
\n", + "

Action Required

\n", + "

Make sure to select the s2_tpch_optimized database from the drop-down menu at the top of this notebook.\n", + " It updates the connection_url to connect to that database.

\n", + "
\n", + "
" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "bafd1114-f88c-409c-8281-b32ac27f1222", + "metadata": {}, + "source": [ + "##### Now, let's create each table with optimized data structure:\n", + "* We create a unique key through primary key. For example **lineitem** table needs both the orderkey and linenumber to identify rows by uniqueness\n", + "* We create a shard key which will distribute data in an efficient way to perform fast join and filtering. For **lineitem** table since we perform joins and calculation based on the orderkey we create a shardkey with orderkey" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "ff6aea3d-a965-475d-becd-3910965f5c8f", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE TABLE IF NOT EXISTS `lineitem` (\n", + " `l_orderkey` bigint(11) NOT NULL,\n", + " `l_partkey` int(11) NOT NULL,\n", + " `l_suppkey` int(11) NOT NULL,\n", + " `l_linenumber` int(11) NOT NULL,\n", + " `l_quantity` decimal(15,2) NOT NULL,\n", + " `l_extendedprice` decimal(15,2) NOT NULL,\n", + " `l_discount` decimal(15,2) NOT NULL,\n", + " `l_tax` decimal(15,2) NOT NULL,\n", + " `l_returnflag` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_linestatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_shipdate` date NOT NULL,\n", + " `l_commitdate` date NOT NULL,\n", + " `l_receiptdate` date NOT NULL,\n", + " `l_shipinstruct` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_shipmode` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `l_comment` varchar(44) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`l_orderkey`,`l_linenumber`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`l_orderkey`),\n", + " KEY `l_orderkey` (`l_orderkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `customer` (\n", + " `c_custkey` int(11) NOT NULL,\n", + " `c_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_nationkey` int(11) NOT NULL,\n", + " `c_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_acctbal` decimal(15,2) NOT NULL,\n", + " `c_mktsegment` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `c_comment` varchar(117) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`c_custkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`c_custkey`),\n", + " KEY `c_custkey` (`c_custkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `nation` (\n", + " `n_nationkey` int(11) NOT NULL,\n", + " `n_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `n_regionkey` int(11) NOT NULL,\n", + " `n_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`n_nationkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`n_nationkey`),\n", + " KEY `n_nationkey` (`n_nationkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `orders` (\n", + " `o_orderkey` bigint(11) NOT NULL,\n", + " `o_custkey` int(11) NOT NULL,\n", + " `o_orderstatus` char(1) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_totalprice` decimal(15,2) NOT NULL,\n", + " `o_orderdate` date NOT NULL,\n", + " `o_orderpriority` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_clerk` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `o_shippriority` int(11) NOT NULL,\n", + " `o_comment` varchar(79) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`o_orderkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`o_orderkey`),\n", + " KEY `o_orderkey` (`o_orderkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `part` (\n", + " `p_partkey` int(11) NOT NULL,\n", + " `p_name` varchar(55) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_mfgr` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_brand` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_type` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_size` int(11) NOT NULL,\n", + " `p_container` varchar(10) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `p_retailprice` decimal(15,2) NOT NULL,\n", + " `p_comment` varchar(23) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`p_partkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`p_partkey`),\n", + " KEY `p_partkey` (`p_partkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `partsupp` (\n", + " `ps_partkey` int(11) NOT NULL,\n", + " `ps_suppkey` int(11) NOT NULL,\n", + " `ps_availqty` int(11) NOT NULL,\n", + " `ps_supplycost` decimal(15,2) NOT NULL,\n", + " `ps_comment` varchar(199) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`ps_partkey`,`ps_suppkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`ps_partkey`),\n", + " KEY `ps_partkey` (`ps_partkey`,`ps_suppkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `region` (\n", + " `r_regionkey` int(11) NOT NULL,\n", + " `r_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `r_comment` varchar(152) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`r_regionkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`r_regionkey`),\n", + " KEY `r_regionkey` (`r_regionkey`) USING CLUSTERED COLUMNSTORE\n", + ");\n", + "\n", + "CREATE TABLE IF NOT EXISTS `supplier` (\n", + " `s_suppkey` int(11) NOT NULL,\n", + " `s_name` varchar(25) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_address` varchar(40) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_nationkey` int(11) NOT NULL,\n", + " `s_phone` varchar(15) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " `s_acctbal` decimal(15,2) NOT NULL,\n", + " `s_comment` varchar(101) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,\n", + " UNIQUE KEY `pk` (`s_suppkey`) USING HASH,\n", + " SHARD KEY `__SHARDKEY` (`s_suppkey`),\n", + " KEY `s_suppkey` (`s_suppkey`) USING CLUSTERED COLUMNSTORE\n", + ");" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "6ed484a7-8ed8-479d-9ebe-5716749369bc", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "INSERT INTO s2_tpch_optimized.nation SELECT * FROM s2_tpch_unoptimized.nation;\n", + "INSERT INTO s2_tpch_optimized.lineitem SELECT * FROM s2_tpch_unoptimized.lineitem;\n", + "INSERT INTO s2_tpch_optimized.customer SELECT * FROM s2_tpch_unoptimized.customer;\n", + "INSERT INTO s2_tpch_optimized.orders SELECT * FROM s2_tpch_unoptimized.orders;\n", + "INSERT INTO s2_tpch_optimized.part SELECT * FROM s2_tpch_unoptimized.part;\n", + "INSERT INTO s2_tpch_optimized.partsupp SELECT * FROM s2_tpch_unoptimized.partsupp;\n", + "INSERT INTO s2_tpch_optimized.region SELECT * FROM s2_tpch_unoptimized.region;\n", + "INSERT INTO s2_tpch_optimized.supplier SELECT * FROM s2_tpch_unoptimized.supplier;" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "9c79d8a5-c626-4f14-85e2-1f00afbceb8f", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "# TPC-H Query 1: Pricing Summary Report\n", + "select\n", + " l_returnflag,\n", + " l_linestatus,\n", + " sum(l_quantity) as sum_qty,\n", + " sum(l_extendedprice) as sum_base_price,\n", + " sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n", + " sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n", + " avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n", + " avg(l_discount) as avg_disc,\n", + " count(*) as count_order\n", + "from lineitem\n", + "where l_shipdate <= date('1998-12-01') - interval '90' day\n", + "group by l_returnflag, l_linestatus\n", + "order by l_returnflag, l_linestatus;" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "e9b21e9b-1869-4a1e-8998-a209c3dc6ffd", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "# TPC-H Query 4: Order Priority Checking\n", + "select\n", + " o_orderpriority,\n", + " count(*) as order_count\n", + "from\n", + " s2_tpch_optimized.orders\n", + "where\n", + " o_orderdate >= date('1993-07-01')\n", + " and o_orderdate < date('1993-10-01')\n", + " and exists (\n", + " select *\n", + " from s2_tpch_optimized.lineitem\n", + " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + " )\n", + "group by o_orderpriority\n", + "order by o_orderpriority;" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "c8b63c2a-b1fb-4cd1-90bb-62e8b56922f5", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "-- TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", + "\n", + "select\n", + " s_name,\n", + " count(*) as numwait\n", + "from\n", + " s2_tpch_optimized.supplier,\n", + " s2_tpch_optimized.lineitem l1,\n", + " s2_tpch_optimized.orders,\n", + " s2_tpch_optimized.nation\n", + "where\n", + " s_suppkey = l1.l_suppkey\n", + " and o_orderkey = l1.l_orderkey\n", + " and o_orderstatus = 'F'\n", + " and l1.l_receiptdate > l1.l_commitdate\n", + " and exists (\n", + " select\n", + " *\n", + " from\n", + " s2_tpch_optimized.lineitem l2\n", + " where\n", + " l2.l_orderkey = l1.l_orderkey\n", + " and l2.l_suppkey <> l1.l_suppkey\n", + " )\n", + " and not exists (\n", + " select\n", + " *\n", + " from\n", + " s2_tpch_optimized.lineitem l3\n", + " where\n", + " l3.l_orderkey = l1.l_orderkey\n", + " and l3.l_suppkey <> l1.l_suppkey\n", + " and l3.l_receiptdate > l3.l_commitdate\n", + " )\n", + " and s_nationkey = n_nationkey\n", + " and n_name = 'EGYPT'\n", + "group by\n", + " s_name\n", + "order by\n", + " numwait desc,\n", + " s_name\n", + "limit 100;" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "54a6902d-bc3b-455d-8f47-3450d5928de8", + "metadata": {}, + "source": [ + "### Finally, let's do a side by side comparison between the optimized and unoptimized database" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "2f23e742-d9fe-467a-a299-a09a20d2af1e", + "metadata": {}, + "outputs": [], + "source": [ + "from singlestoredb import create_engine\n", + "import sqlalchemy as sa\n", + "connection_url_unoptimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_unoptimized?ssl_cipher=HIGH\"\n", + "db_connection_unoptimized = create_engine(connection_url_unoptimized).connect()\n", + "connection_url_optimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_optimized?ssl_cipher=HIGH\"\n", + "db_connection_optimized = create_engine(connection_url_optimized).connect()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "7f84ed59-9d2c-4e3e-92eb-63603645d953", + "metadata": {}, + "source": [ + "Here are a few queries that you can test side by side against. Overall you will notice an average of 4x improvement in performance" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "f3d86d62-ffe2-40ad-b59a-7c77cae98ca0", + "metadata": {}, + "outputs": [], + "source": [ + "sql_query4 = sa.text('''\n", + "select\n", + " o_orderpriority,\n", + " count(*) as order_count\n", + "from\n", + " s2_tpch_unoptimized.orders\n", + "where\n", + " o_orderdate >= date('1993-07-01')\n", + " and o_orderdate < date('1993-10-01')\n", + " and exists (\n", + " select *\n", + " from s2_tpch_unoptimized.lineitem\n", + " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + " )\n", + "group by o_orderpriority\n", + "order by o_orderpriority;\n", + "''')" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "7d947658-6dec-4efa-97f6-863977b2003b", + "metadata": {}, + "outputs": [], + "source": [ + "sql_query21 = sa.text('''\n", + " select\n", + " s_name,\n", + " count(*) as numwait\n", + "from\n", + " supplier,\n", + " lineitem l1,\n", + " orders,\n", + " nation\n", + "where\n", + " s_suppkey = l1.l_suppkey\n", + " and o_orderkey = l1.l_orderkey\n", + " and o_orderstatus = 'F'\n", + " and l1.l_receiptdate > l1.l_commitdate\n", + " and exists (\n", + " select\n", + " *\n", + " from\n", + " lineitem l2\n", + " where\n", + " l2.l_orderkey = l1.l_orderkey\n", + " and l2.l_suppkey <> l1.l_suppkey\n", + " )\n", + " and not exists (\n", + " select\n", + " *\n", + " from\n", + " lineitem l3\n", + " where\n", + " l3.l_orderkey = l1.l_orderkey\n", + " and l3.l_suppkey <> l1.l_suppkey\n", + " and l3.l_receiptdate > l3.l_commitdate\n", + " )\n", + " and s_nationkey = n_nationkey\n", + " and n_name = 'EGYPT'\n", + "group by\n", + " s_name\n", + "order by\n", + " numwait desc,\n", + " s_name\n", + "limit 100;\n", + "''')" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "6e4da6ac-52ff-4506-8826-3a46bf350656", + "metadata": {}, + "outputs": [], + "source": [ + "result = db_connection_optimized.execute(sql_query21)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "b699bc42-e9bd-4b8f-81c0-48311b7fd14e", + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "import pandas as pd\n", + "import plotly.graph_objs as go\n", + "num_iterations = 10\n", + "opt_times = []\n", + "\n", + "for i in range(num_iterations):\n", + " opt_start_time = time.time()\n", + " opt_result = db_connection_optimized.execute(sql_query21)\n", + " opt_stop_time = time.time()\n", + " opt_times.append(opt_stop_time - opt_start_time)\n", + "\n", + "unopt_times = []\n", + "for i in range(num_iterations):\n", + " unopt_start_time = time.time()\n", + " unopt_result = db_connection_unoptimized.execute(sql_query21)\n", + " unopt_stop_time = time.time()\n", + " unopt_times.append(unopt_stop_time - unopt_start_time)\n", + "\n", + "x_axis = list(range(1, num_iterations + 1))\n", + "data = {\n", + " 'iteration': x_axis,\n", + " 'opt_times': opt_times,\n", + " 'unopt_times': unopt_times,\n", + "}\n", + "df = pd.DataFrame.from_dict(data)\n", + "\n", + "fig = go.Figure()\n", + "\n", + "# Adding optimized times to the plot\n", + "fig.add_trace(go.Scatter(x=df['iteration'], y=df['opt_times'], mode='lines+markers', name='Optimized Database'))\n", + "\n", + "# Adding unoptimized times to the plot\n", + "fig.add_trace(go.Scatter(x=df['iteration'], y=df['unopt_times'], mode='lines+markers', name='Unoptimized Database'))\n", + "\n", + "# Update y-axis and x-axis properties\n", + "fig.update_layout(\n", + " title=\"Execution Time Comparison\",\n", + " xaxis_title=\"Iteration\",\n", + " yaxis_title=\"Time in Seconds\",\n", + " xaxis=dict(tickmode='array', tickvals=list(range(1, num_iterations + 1)))\n", + ")\n", + "\n", + "# Show the plot\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "4708ffe5-ea88-48a8-a4ac-9eaa5f801f79", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + } + ], + "metadata": { + "jupyterlab": { + "notebooks": { + "version_major": 6, + "version_minor": 4 + } + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimeType": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/resources/nb-check.py b/resources/nb-check.py index ab4cb007..7a1414b0 100755 --- a/resources/nb-check.py +++ b/resources/nb-check.py @@ -167,8 +167,9 @@ def new_markdown_cell(cell_id: str, content: list[str]) -> dict[str, Any]: footer_cell = cells.pop(-1) footer_id = footer_cell.get('id', footer_id) - # Convert source lists to a string for cell in cells: + + # Convert source lists to a string source = cell.get('source', []) if isinstance(source, list): source = ''.join(source) @@ -178,6 +179,10 @@ def new_markdown_cell(cell_id: str, content: list[str]) -> dict[str, Any]: source = [] cell['source'] = source + # Remove "attachments": null (not sure how they get in there) + if 'attachments' in cell and cell['attachments'] is None: + cell['attachments'] = {} + # Prepare parameter substitutions for header try: icon_name = toml_info['meta']['icon'] diff --git a/resources/toml-check.py b/resources/toml-check.py index ff6da45d..5927c2cd 100755 --- a/resources/toml-check.py +++ b/resources/toml-check.py @@ -35,8 +35,8 @@ def error(msg): if [x.lower() for x in tags] != tags: error(f'Tags must be in all lower-case ({tags}) in {f}') - if [re.sub(r'[^a-z]', r'', x) for x in tags] != tags: - error(f'Tags can only contain letters ({tags}) in {f}') + if [re.sub(r'[^a-z0-9]', r'', x) for x in tags] != tags: + error(f'Tags can only contain letters and numbers ({tags}) in {f}') # Currently only "spaces" is allowed in destinations destinations = meta.get('destinations', []) From a50d5032200ef49827fde7d247cb8a3458fce967 Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Thu, 5 Oct 2023 09:40:55 -0500 Subject: [PATCH 12/24] Clean up formatting --- .../notebook.ipynb | 476 +++++++++--------- 1 file changed, 232 insertions(+), 244 deletions(-) diff --git a/notebooks/optimize-performance-with-tpch-100/notebook.ipynb b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb index cc9a0713..5d954cc4 100644 --- a/notebooks/optimize-performance-with-tpch-100/notebook.ipynb +++ b/notebooks/optimize-performance-with-tpch-100/notebook.ipynb @@ -70,7 +70,7 @@ "outputs": [], "source": [ "%%sql\n", - "create database if not exists s2_tpch_unoptimized\n", + "CREATE DATABASE IF NOT EXISTS s2_tpch_unoptimized\n", "\n", "# To create a database with custom partitions use the following syntax: CREATE DATABASE YourDatabaseName PARTITIONS=X;\n", "# You cannot change after creation the number of partitions" @@ -233,15 +233,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `customer_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/customer'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `customer`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/customer'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `customer`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -253,15 +253,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `lineitem_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/lineitem/lineitem.'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `lineitem`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/lineitem/lineitem.'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `lineitem`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -273,15 +273,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `nation_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/nation'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `nation`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/nation'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `nation`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -293,15 +293,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `orders_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/orders'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `orders`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/orders'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `orders`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -313,15 +313,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `partsupp_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/partsupp'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `partsupp`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/partsupp'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `partsupp`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -333,15 +333,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `part_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/part'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `part`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/part'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `part`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -353,15 +353,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `region_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/region'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `region`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/region'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `region`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -373,15 +373,15 @@ "source": [ "%%sql\n", "CREATE PIPELINE IF NOT EXISTS `supplier_pipeline`\n", - "AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/supplier'\n", - "CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", - "BATCH_INTERVAL 2500\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `supplier`\n", - "FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", - "LINES TERMINATED BY '|\\n' STARTING BY '';" + " AS LOAD DATA S3 'memsql-tpch-dataset/sf_100/supplier'\n", + " CONFIG '{\\\"region\\\":\\\"us-east-1\\\", \\\"disable_gunzip\\\": false}'\n", + " BATCH_INTERVAL 2500\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `supplier`\n", + " FIELDS TERMINATED BY '|' ENCLOSED BY '' ESCAPED BY '\\\\'\n", + " LINES TERMINATED BY '|\\n' STARTING BY '';" ] }, { @@ -414,16 +414,6 @@ { "cell_type": "code", "execution_count": 13, - "id": "e5c3fa1a-af9b-4fdb-98bc-9c73a1fa7f33", - "metadata": {}, - "outputs": [], - "source": [ - "pip install perspective-python --quiet" - ] - }, - { - "cell_type": "code", - "execution_count": 14, "id": "b61f205f-5d1d-4af2-8369-e31057c76f66", "metadata": {}, "outputs": [], @@ -432,15 +422,15 @@ "import threading\n", "import random\n", "import time\n", + "import warnings\n", "from datetime import datetime, date\n", "from perspective import Table, PerspectiveWidget\n", - "import warnings\n", "warnings.filterwarnings('ignore')" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "id": "ac376696-0b7e-4182-bc04-ddef400b7fca", "metadata": {}, "outputs": [], @@ -454,13 +444,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "id": "5e2ce253-576d-49c9-a92b-f165ffcc4ae7", "metadata": {}, "outputs": [], "source": [ "def data_source():\n", - " result = %sql select sum(rows_streamed) as rows_streamed from information_schema.pipelines_batches_summary where database_name = 's2_tpch_unoptimized';\n", + " result = %sql SELECT sum(rows_streamed) AS rows_streamed FROM information_schema.pipelines_batches_summary WHERE database_name = 's2_tpch_unoptimized';\n", " result2 = list(result.dicts())\n", " return result2\n", "\n", @@ -471,7 +461,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "d388a00d-23ec-45d2-a94c-5e747da707c0", "metadata": {}, "outputs": [], @@ -483,7 +473,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "9e88e523-63b1-48e3-bde5-a2840490199c", "metadata": {}, "outputs": [], @@ -493,7 +483,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "debbed63-11dc-43dc-9f12-a0e80a5b7703", "metadata": {}, "outputs": [], @@ -512,105 +502,104 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "97e9050b-3b8e-40e3-b871-2b0bb73eb5ae", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "# TPC-H Query 1: Pricing Summary Report\n", - "select\n", + "SELECT\n", " l_returnflag,\n", " l_linestatus,\n", - " sum(l_quantity) as sum_qty,\n", - " sum(l_extendedprice) as sum_base_price,\n", - " sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n", - " sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n", - " avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n", - " avg(l_discount) as avg_disc,\n", - " count(*) as count_order\n", - "from s2_tpch_unoptimized.lineitem\n", - "where l_shipdate <= date('1998-12-01') - interval '90' day\n", - "group by l_returnflag, l_linestatus\n", - "order by l_returnflag, l_linestatus;" + " SUM(l_quantity) AS sum_qty,\n", + " SUM(l_extendedprice) AS sum_base_price,\n", + " SUM(l_extendedprice * (1 - l_discount)) AS sum_disc_price,\n", + " SUM(l_extendedprice * (1 - l_discount) * (1 + l_tax)) AS sum_charge,\n", + " AVG(l_quantity) AS avg_qty, AVG(l_extendedprice) AS avg_price,\n", + " AVG(l_discount) AS avg_disc,\n", + " COUNT(*) AS count_order\n", + "FROM s2_tpch_unoptimized.lineitem\n", + "WHERE l_shipdate <= DATE('1998-12-01') - INTERVAL '90' DAY\n", + "GROUP BY l_returnflag, l_linestatus\n", + "ORDER BY l_returnflag, l_linestatus;" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "id": "71669c07-d06e-41f4-bd63-5046add22afb", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "# TPC-H Query 4: Order Priority Checking\n", - "select\n", + "SELECT\n", " o_orderpriority,\n", - " count(*) as order_count\n", - "from\n", + " COUNT(*) AS order_count\n", + "FROM\n", " s2_tpch_unoptimized.orders\n", - "where\n", - " o_orderdate >= date('1993-07-01')\n", - " and o_orderdate < date('1993-10-01')\n", - " and exists (\n", - " select *\n", - " from s2_tpch_unoptimized.lineitem\n", - " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + "WHERE\n", + " o_orderdate >= DATE('1993-07-01')\n", + " AND o_orderdate < DATE('1993-10-01')\n", + " AND EXISTS (\n", + " SELECT *\n", + " FROM s2_tpch_unoptimized.lineitem\n", + " WHERE l_orderkey = o_orderkey AND l_commitdate < l_receiptdate\n", " )\n", - "group by o_orderpriority\n", - "order by o_orderpriority;" + "GROUP BY o_orderpriority\n", + "ORDER BY o_orderpriority;" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "654f872b-4a35-4897-86d2-c51b548919b8", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "-- TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", - "\n", - "select\n", + "# TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", + "SELECT\n", " s_name,\n", - " count(*) as numwait\n", - "from\n", + " COUNT(*) AS numwait\n", + "FROM\n", " s2_tpch_unoptimized.supplier,\n", " s2_tpch_unoptimized.lineitem l1,\n", " s2_tpch_unoptimized.orders,\n", " s2_tpch_unoptimized.nation\n", - "where\n", + "WHERE\n", " s_suppkey = l1.l_suppkey\n", - " and o_orderkey = l1.l_orderkey\n", - " and o_orderstatus = 'F'\n", - " and l1.l_receiptdate > l1.l_commitdate\n", - " and exists (\n", - " select\n", + " AND o_orderkey = l1.l_orderkey\n", + " AND o_orderstatus = 'F'\n", + " AND l1.l_receiptdate > l1.l_commitdate\n", + " AND EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " s2_tpch_unoptimized.lineitem l2\n", - " where\n", + " WHERE\n", " l2.l_orderkey = l1.l_orderkey\n", - " and l2.l_suppkey <> l1.l_suppkey\n", + " AND l2.l_suppkey <> l1.l_suppkey\n", " )\n", - " and not exists (\n", - " select\n", + " AND NOT EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " s2_tpch_unoptimized.lineitem l3\n", - " where\n", + " WHERE\n", " l3.l_orderkey = l1.l_orderkey\n", - " and l3.l_suppkey <> l1.l_suppkey\n", - " and l3.l_receiptdate > l3.l_commitdate\n", + " AND l3.l_suppkey <> l1.l_suppkey\n", + " AND l3.l_receiptdate > l3.l_commitdate\n", " )\n", - " and s_nationkey = n_nationkey\n", - " and n_name = 'EGYPT'\n", - "group by\n", + " AND s_nationkey = n_nationkey\n", + " AND n_name = 'EGYPT'\n", + "GROUP BY\n", " s_name\n", - "order by\n", - " numwait desc,\n", + "ORDER BY\n", + " numwait DESC,\n", " s_name\n", - "limit 100;" + "LIMIT 100;" ] }, { @@ -624,13 +613,13 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "id": "d1844926-ae73-4fec-b5ba-802c8173e846", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "create database if not exists s2_tpch_optimized" + "CREATE DATABASE IF NOT EXISTS s2_tpch_optimized" ] }, { @@ -662,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "id": "ff6aea3d-a965-475d-becd-3910965f5c8f", "metadata": {}, "outputs": [], @@ -780,7 +769,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "id": "6ed484a7-8ed8-479d-9ebe-5716749369bc", "metadata": {}, "outputs": [], @@ -798,105 +787,104 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "id": "9c79d8a5-c626-4f14-85e2-1f00afbceb8f", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "# TPC-H Query 1: Pricing Summary Report\n", - "select\n", + "SELECT\n", " l_returnflag,\n", " l_linestatus,\n", - " sum(l_quantity) as sum_qty,\n", - " sum(l_extendedprice) as sum_base_price,\n", - " sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,\n", - " sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,\n", - " avg(l_quantity) as avg_qty, avg(l_extendedprice) as avg_price,\n", - " avg(l_discount) as avg_disc,\n", - " count(*) as count_order\n", - "from lineitem\n", - "where l_shipdate <= date('1998-12-01') - interval '90' day\n", - "group by l_returnflag, l_linestatus\n", - "order by l_returnflag, l_linestatus;" + " SUM(l_quantity) AS sum_qty,\n", + " SUM(l_extendedprice) AS sum_base_price,\n", + " SUM(l_extendedprice * (1 - l_discount)) AS sum_disc_price,\n", + " SUM(l_extendedprice * (1 - l_discount) * (1 + l_tax)) AS sum_charge,\n", + " AVG(l_quantity) AS avg_qty, AVG(l_extendedprice) AS avg_price,\n", + " AVG(l_discount) AS avg_disc,\n", + " COUNT(*) AS count_order\n", + "FROM lineitem\n", + "WHERE l_shipdate <= DATE('1998-12-01') - INTERVAL '90' DAY\n", + "GROUP BY l_returnflag, l_linestatus\n", + "ORDER BY l_returnflag, l_linestatus;" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "id": "e9b21e9b-1869-4a1e-8998-a209c3dc6ffd", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "# TPC-H Query 4: Order Priority Checking\n", - "select\n", + "SELECT\n", " o_orderpriority,\n", - " count(*) as order_count\n", - "from\n", + " COUNT(*) AS order_count\n", + "FROM\n", " s2_tpch_optimized.orders\n", - "where\n", - " o_orderdate >= date('1993-07-01')\n", - " and o_orderdate < date('1993-10-01')\n", - " and exists (\n", - " select *\n", - " from s2_tpch_optimized.lineitem\n", - " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + "WHERE\n", + " o_orderdate >= DATE('1993-07-01')\n", + " AND o_orderdate < DATE('1993-10-01')\n", + " AND EXISTS (\n", + " SELECT *\n", + " FROM s2_tpch_optimized.lineitem\n", + " WHERE l_orderkey = o_orderkey AND l_commitdate < l_receiptdate\n", " )\n", - "group by o_orderpriority\n", - "order by o_orderpriority;" + "GROUP BY o_orderpriority\n", + "ORDER BY o_orderpriority;" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "id": "c8b63c2a-b1fb-4cd1-90bb-62e8b56922f5", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "-- TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", - "\n", - "select\n", + "# TPC-H Query 21: Suppliers Who Kept Orders Waiting\n", + "SELECT\n", " s_name,\n", - " count(*) as numwait\n", - "from\n", + " COUNT(*) AS numwait\n", + "FROM\n", " s2_tpch_optimized.supplier,\n", " s2_tpch_optimized.lineitem l1,\n", " s2_tpch_optimized.orders,\n", " s2_tpch_optimized.nation\n", - "where\n", + "WHERE\n", " s_suppkey = l1.l_suppkey\n", - " and o_orderkey = l1.l_orderkey\n", - " and o_orderstatus = 'F'\n", - " and l1.l_receiptdate > l1.l_commitdate\n", - " and exists (\n", - " select\n", + " AND o_orderkey = l1.l_orderkey\n", + " AND o_orderstatus = 'F'\n", + " AND l1.l_receiptdate > l1.l_commitdate\n", + " AND EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " s2_tpch_optimized.lineitem l2\n", - " where\n", + " WHERE\n", " l2.l_orderkey = l1.l_orderkey\n", - " and l2.l_suppkey <> l1.l_suppkey\n", + " AND l2.l_suppkey <> l1.l_suppkey\n", " )\n", - " and not exists (\n", - " select\n", + " AND NOT EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " s2_tpch_optimized.lineitem l3\n", - " where\n", + " WHERE\n", " l3.l_orderkey = l1.l_orderkey\n", - " and l3.l_suppkey <> l1.l_suppkey\n", - " and l3.l_receiptdate > l3.l_commitdate\n", + " AND l3.l_suppkey <> l1.l_suppkey\n", + " AND l3.l_receiptdate > l3.l_commitdate\n", " )\n", - " and s_nationkey = n_nationkey\n", - " and n_name = 'EGYPT'\n", - "group by\n", + " AND s_nationkey = n_nationkey\n", + " AND n_name = 'EGYPT'\n", + "GROUP BY\n", " s_name\n", - "order by\n", + "ORDER BY\n", " numwait desc,\n", " s_name\n", - "limit 100;" + "LIMIT 100;" ] }, { @@ -910,17 +898,16 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "id": "2f23e742-d9fe-467a-a299-a09a20d2af1e", "metadata": {}, "outputs": [], "source": [ "from singlestoredb import create_engine\n", "import sqlalchemy as sa\n", - "connection_url_unoptimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_unoptimized?ssl_cipher=HIGH\"\n", - "db_connection_unoptimized = create_engine(connection_url_unoptimized).connect()\n", - "connection_url_optimized = \"singlestoredb://\"+connection_user+\":\"+connection_password+\"@\"+connection_host+\":\"+connection_port+\"/s2_tpch_optimized?ssl_cipher=HIGH\"\n", - "db_connection_optimized = create_engine(connection_url_optimized).connect()" + "\n", + "db_connection_unoptimized = create_engine(database='s2_tpch_unoptimized').connect()\n", + "db_connection_optimized = create_engine(database='s2_tpch_optimized').connect()" ] }, { @@ -934,84 +921,84 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "id": "f3d86d62-ffe2-40ad-b59a-7c77cae98ca0", "metadata": {}, "outputs": [], "source": [ "sql_query4 = sa.text('''\n", - "select\n", + "SELECT\n", " o_orderpriority,\n", - " count(*) as order_count\n", - "from\n", + " COUNT(*) AS order_count\n", + "FROM\n", " s2_tpch_unoptimized.orders\n", - "where\n", - " o_orderdate >= date('1993-07-01')\n", - " and o_orderdate < date('1993-10-01')\n", - " and exists (\n", - " select *\n", - " from s2_tpch_unoptimized.lineitem\n", - " where l_orderkey = o_orderkey and l_commitdate < l_receiptdate\n", + "WHERE\n", + " o_orderdate >= DATE('1993-07-01')\n", + " AND o_orderdate < DATE('1993-10-01')\n", + " AND EXISTS (\n", + " SELECT *\n", + " FROM s2_tpch_unoptimized.lineitem\n", + " WHERE l_orderkey = o_orderkey AND l_commitdate < l_receiptdate\n", " )\n", - "group by o_orderpriority\n", - "order by o_orderpriority;\n", + "GROUP BY o_orderpriority\n", + "ORDER BY o_orderpriority;\n", "''')" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "id": "7d947658-6dec-4efa-97f6-863977b2003b", "metadata": {}, "outputs": [], "source": [ "sql_query21 = sa.text('''\n", - " select\n", + "SELECT\n", " s_name,\n", - " count(*) as numwait\n", - "from\n", + " COUNT(*) AS numwait\n", + "FROM\n", " supplier,\n", " lineitem l1,\n", " orders,\n", " nation\n", - "where\n", + "WHERE\n", " s_suppkey = l1.l_suppkey\n", - " and o_orderkey = l1.l_orderkey\n", - " and o_orderstatus = 'F'\n", - " and l1.l_receiptdate > l1.l_commitdate\n", - " and exists (\n", - " select\n", + " AND o_orderkey = l1.l_orderkey\n", + " AND o_orderstatus = 'F'\n", + " AND l1.l_receiptdate > l1.l_commitdate\n", + " AND EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " lineitem l2\n", - " where\n", + " WHERE\n", " l2.l_orderkey = l1.l_orderkey\n", - " and l2.l_suppkey <> l1.l_suppkey\n", + " AND l2.l_suppkey <> l1.l_suppkey\n", " )\n", - " and not exists (\n", - " select\n", + " AND NOT EXISTS (\n", + " SELECT\n", " *\n", - " from\n", + " FROM\n", " lineitem l3\n", - " where\n", + " WHERE\n", " l3.l_orderkey = l1.l_orderkey\n", - " and l3.l_suppkey <> l1.l_suppkey\n", - " and l3.l_receiptdate > l3.l_commitdate\n", + " AND l3.l_suppkey <> l1.l_suppkey\n", + " AND l3.l_receiptdate > l3.l_commitdate\n", " )\n", - " and s_nationkey = n_nationkey\n", - " and n_name = 'EGYPT'\n", - "group by\n", + " AND s_nationkey = n_nationkey\n", + " AND n_name = 'EGYPT'\n", + "GROUP BY\n", " s_name\n", - "order by\n", + "ORDER BY\n", " numwait desc,\n", " s_name\n", - "limit 100;\n", + "LIMIT 100;\n", "''')" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "id": "6e4da6ac-52ff-4506-8826-3a46bf350656", "metadata": {}, "outputs": [], @@ -1021,7 +1008,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "id": "b699bc42-e9bd-4b8f-81c0-48311b7fd14e", "metadata": {}, "outputs": [], @@ -1029,6 +1016,7 @@ "import time\n", "import pandas as pd\n", "import plotly.graph_objs as go\n", + "\n", "num_iterations = 10\n", "opt_times = []\n", "\n", @@ -1101,7 +1089,7 @@ "version": 3 }, "file_extension": ".py", - "mimeType": "text/x-python", + "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", From 0b8cbb0b0987481233d92fd5a425dbb86f31a3a4 Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Thu, 5 Oct 2023 09:50:24 -0500 Subject: [PATCH 13/24] Clean up formatting --- notebooks/load-json-files-s3/notebook.ipynb | 185 +++++++++++--------- 1 file changed, 102 insertions(+), 83 deletions(-) diff --git a/notebooks/load-json-files-s3/notebook.ipynb b/notebooks/load-json-files-s3/notebook.ipynb index 9f0ad7ff..4a548acf 100644 --- a/notebooks/load-json-files-s3/notebook.ipynb +++ b/notebooks/load-json-files-s3/notebook.ipynb @@ -112,20 +112,43 @@ "outputs": [], "source": [ "%%sql\n", - "Create database if not exists demo_database;\n", - "Use demo_database;\n", - "CREATE TABLE if not exists demo_database.actors (\n", - "name text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", - "age int NOT NULL,\n", - "born_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", - "Birthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", - "photo text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", - "wife text CHARACTER SET utf8 COLLATE utf8_general_ci,\n", - "weight float NOT NULL,\n", - "haschildren boolean,\n", - "hasGreyHair boolean,\n", - "children JSON COLLATE utf8_bin NOT NULL,\n", - "SHARD KEY ()\n", + "CREATE DATABASE IF NOT EXISTS demo_database;" + ] + }, + { + "cell_type": "markdown", + "id": "6dfc5b0b-9308-46c9-8cc8-be08fb07c1b6", + "metadata": {}, + "source": [ + "
\n", + " \n", + "
\n", + "

Action Required

\n", + "

Make sure to select the demo_database database from the drop-down menu at the top of this notebook. It updates the connection_url to connect to that database.

\n", + "
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "b09528cf-0beb-4fe0-9e60-6edefb72f8b1", + "metadata": {}, + "outputs": [], + "source": [ + "%%sql\n", + "CREATE TABLE IF NOT EXISTS demo_database.actors (\n", + " name text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + " age int NOT NULL,\n", + " born_at text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + " Birthdate text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + " photo text CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL,\n", + " wife text CHARACTER SET utf8 COLLATE utf8_general_ci,\n", + " weight float NOT NULL,\n", + " haschildren boolean,\n", + " hasGreyHair boolean,\n", + " children JSON COLLATE utf8_bin NOT NULL,\n", + " SHARD KEY ()\n", ");" ] }, @@ -148,38 +171,38 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "92df7943-e68d-4509-b7f5-4a93697f6578", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "CREATE PIPELINE if not exists demo_database.actors\n", - "AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", - "CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", - "/*\n", - "CREDENTIALS '{\"aws_access_key_id\": \"\",\n", - " \"aws_secret_access_key\": \"\"}'\n", - "*/\n", - "BATCH_INTERVAL 2500\n", - "MAX_PARTITIONS_PER_BATCH 1\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `actors`\n", - "FORMAT JSON\n", - "(\n", - " actors.name <- name,\n", - " actors.age <- age,\n", - " actors.born_at <- `Born At`,\n", - " actors.Birthdate <- Birthdate,\n", - " actors.photo <- photo,\n", - " actors.wife <- wife,\n", - " actors.weight <- weight,\n", - " actors.haschildren <- hasChildren,\n", - " actors.hasGreyHair <- hasGreyHair,\n", - " actors.children <- children\n", - ");" + " AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", + " CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", + " /*\n", + " CREDENTIALS '{\"aws_access_key_id\": \"\",\n", + " \"aws_secret_access_key\": \"\"}'\n", + " */\n", + " BATCH_INTERVAL 2500\n", + " MAX_PARTITIONS_PER_BATCH 1\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `actors`\n", + " FORMAT JSON\n", + " (\n", + " actors.name <- name,\n", + " actors.age <- age,\n", + " actors.born_at <- `Born At`,\n", + " actors.Birthdate <- Birthdate,\n", + " actors.photo <- photo,\n", + " actors.wife <- wife,\n", + " actors.weight <- weight,\n", + " actors.haschildren <- hasChildren,\n", + " actors.hasGreyHair <- hasGreyHair,\n", + " actors.children <- children\n", + " );" ] }, { @@ -192,13 +215,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "eeddd12e-e28c-4000-859b-6d1291c4a137", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "Start pipeline demo_database.actors;" + "START PIPELINE demo_database.actors;" ] }, { @@ -211,14 +234,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "f48de155-af85-4c40-ad56-955573a434f8", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "select * from information_schema.pipelines_errors\n", - "where pipeline_name = 'actors' ;" + "SELECT * FROM information_schema.pipelines_errors\n", + " WHERE pipeline_name = 'actors' ;" ] }, { @@ -231,13 +254,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "09a739cb-4925-4699-ab61-71016a04bfb6", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "select * from demo_database.actors;" + "SELECT * FROM demo_database.actors;" ] }, { @@ -250,14 +273,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "6a6dfc1d-c758-4287-a797-6cc3e4fff934", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "Drop pipeline if exists demo_database.actors;\n", - "Drop table if exists demo_database.actors;" + "DROP PIPELINE IF EXISTS demo_database.actors;\n", + "DROP TABLE IF EXISTS demo_database.actors;" ] }, { @@ -286,17 +309,15 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "bcb14814-7b79-4df2-ab47-7def7ae03ce3", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "Create database if not exists demo_database;\n", - "Use demo_database;\n", - "CREATE TABLE if not exists demo_database.actors_json (\n", - "json_data JSON NOT NULL ,\n", - "SHARD KEY ()\n", + "CREATE TABLE IF NOT EXISTS demo_database.actors_json (\n", + " json_data JSON NOT NULL,\n", + " SHARD KEY ()\n", ");" ] }, @@ -310,27 +331,27 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "id": "a1d60130-095e-45da-b55d-b427a0af3d26", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "CREATE PIPELINE if not exists demo_database.actors_json\n", - "AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", - "CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", - "/*\n", - "CREDENTIALS '{\"aws_access_key_id\": \"\",\n", - " \"aws_secret_access_key\": \"\"}'\n", - "*/\n", - "BATCH_INTERVAL 2500\n", - "MAX_PARTITIONS_PER_BATCH 1\n", - "DISABLE OUT_OF_ORDER OPTIMIZATION\n", - "DISABLE OFFSETS METADATA GC\n", - "SKIP DUPLICATE KEY ERRORS\n", - "INTO TABLE `actors_json`\n", - "FORMAT JSON\n", - "(json_data <- %);" + "CREATE PIPELINE IF NOT EXISTS demo_database.actors_json\n", + " AS LOAD DATA S3 'studiotutorials/sample_dataset/json_files/wildcard_demo/*.json'\n", + " CONFIG '{ \\\"region\\\": \\\"us-east-1\\\" }'\n", + " /*\n", + " CREDENTIALS '{\"aws_access_key_id\": \"\",\n", + " \"aws_secret_access_key\": \"\"}'\n", + " */\n", + " BATCH_INTERVAL 2500\n", + " MAX_PARTITIONS_PER_BATCH 1\n", + " DISABLE OUT_OF_ORDER OPTIMIZATION\n", + " DISABLE OFFSETS METADATA GC\n", + " SKIP DUPLICATE KEY ERRORS\n", + " INTO TABLE `actors_json`\n", + " FORMAT JSON\n", + " (json_data <- %);" ] }, { @@ -343,26 +364,26 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "id": "b374598a-f9cb-43c4-a2a4-ebcd298108c4", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "Start pipeline demo_database.actors_json;" + "START PIPELINE demo_database.actors_json;" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "id": "ca06781b-61fa-4fea-97de-cd0dbacd86e8", "metadata": {}, "outputs": [], "source": [ "%%sql\n", "# Monitor and see if there is any error or warning\n", - "select * from information_schema.pipelines_errors\n", - "where pipeline_name = 'actors_json' ;" + "SELECT * FROM information_schema.pipelines_errors\n", + " WHERE pipeline_name = 'actors_json' ;" ] }, { @@ -375,13 +396,13 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "id": "e34c5b49-0e97-4b07-9026-38bb6c370f73", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "select * from demo_database.actors_json" + "SELECT * FROM demo_database.actors_json" ] }, { @@ -394,15 +415,13 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "id": "6f0bd356-8a11-4cd9-b774-569d8f5e2520", "metadata": {}, "outputs": [], "source": [ "%%sql\n", - "\n", - "Drop pipeline if exists demo_database.actors_json;\n", - "Drop table if exists demo_database.actors_json;" + "DROP DATABASE IF EXISTS demo_database;" ] }, { From ce94ec781c4089618e03d9184a99227890498132 Mon Sep 17 00:00:00 2001 From: arno756 Date: Thu, 5 Oct 2023 11:04:53 -0700 Subject: [PATCH 14/24] Update meta.toml --- notebooks/load-json-files-s3/meta.toml | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/notebooks/load-json-files-s3/meta.toml b/notebooks/load-json-files-s3/meta.toml index c82e5c0d..b037410d 100644 --- a/notebooks/load-json-files-s3/meta.toml +++ b/notebooks/load-json-files-s3/meta.toml @@ -1,10 +1,6 @@ [meta] title="Load JSON files with Pipeline from S3" -description="""\ - This notebook will help you load JSON files from a public open - AWS S3 bucket. You will see two modes: - *) where you map the JSON elements to columns in a relational table - *) where you just ingest all documents ito a JSON column. In that mode we also show how you can use persisted computed column for extracting JSON fields +description="""\This notebook will help you load JSON files from a public open AWS S3 bucket. You will see two modes: """ icon="chart-network" tags=["pipeline", "json", "s3"] From b2c7a43fc0c111d4a3a56d9777d61815520d9dfd Mon Sep 17 00:00:00 2001 From: arno756 Date: Thu, 5 Oct 2023 11:09:16 -0700 Subject: [PATCH 15/24] Update meta.toml --- .../optimize-performance-with-tpch-100/meta.toml | 11 +---------- 1 file changed, 1 insertion(+), 10 deletions(-) diff --git a/notebooks/optimize-performance-with-tpch-100/meta.toml b/notebooks/optimize-performance-with-tpch-100/meta.toml index 330d242e..a58e04a9 100644 --- a/notebooks/optimize-performance-with-tpch-100/meta.toml +++ b/notebooks/optimize-performance-with-tpch-100/meta.toml @@ -1,16 +1,7 @@ [meta] title="Learn how to Optimize Performance with TPCH 100" description="""\ - This notebook will help you understand how you can take advantage of - SingleStoreDB distributed capability using TPCH-100. We recommend using - a S2 or S4 workspace to see the difference in performance. - - If you come from single node database, this is an important step to follow - to scale your performance linearly as your data grows. - - You will see two areas: - *) Ingesting data using pipeline at a super fast speed (You will use a real-time embedded dashboard) - *) Compare query performance with an unoptimized database and an optimized database + This notebook will help you understand how you can take advantage of SingleStoreDB distributed capability using TPCH-100. """ icon="database" tags=["performance", "benchmark", "tpch", "benchmark", "shardkey", "ingest"] From 6544a4c3bb4a5bbcac07b6137060a9ba207d7fe5 Mon Sep 17 00:00:00 2001 From: Kevin Smith Date: Thu, 5 Oct 2023 13:19:03 -0500 Subject: [PATCH 16/24] Fix description --- notebooks/load-json-files-s3/meta.toml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/notebooks/load-json-files-s3/meta.toml b/notebooks/load-json-files-s3/meta.toml index b037410d..eee8644d 100644 --- a/notebooks/load-json-files-s3/meta.toml +++ b/notebooks/load-json-files-s3/meta.toml @@ -1,7 +1,8 @@ [meta] title="Load JSON files with Pipeline from S3" -description="""\This notebook will help you load JSON files from a public open AWS S3 bucket. You will see two modes: -""" +description="""\ + This notebook will help you load JSON files from a public open AWS S3 bucket. + """ icon="chart-network" tags=["pipeline", "json", "s3"] destinations=["spaces"] From 70f48538581bcb7fd0f1c4e2f89efad217385fb3 Mon Sep 17 00:00:00 2001 From: mivasconcelos Date: Wed, 11 Oct 2023 11:03:56 +0100 Subject: [PATCH 17/24] Remove duplicated benchmark tag --- notebooks/optimize-performance-with-tpch-100/meta.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/optimize-performance-with-tpch-100/meta.toml b/notebooks/optimize-performance-with-tpch-100/meta.toml index a58e04a9..cbc31580 100644 --- a/notebooks/optimize-performance-with-tpch-100/meta.toml +++ b/notebooks/optimize-performance-with-tpch-100/meta.toml @@ -4,5 +4,5 @@ description="""\ This notebook will help you understand how you can take advantage of SingleStoreDB distributed capability using TPCH-100. """ icon="database" -tags=["performance", "benchmark", "tpch", "benchmark", "shardkey", "ingest"] +tags=["performance", "benchmark", "tpch", "shardkey", "ingest"] destinations=["spaces"] From 89a7d6fc801cb768607bf6e7276e40a42cc3b365 Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 12:58:40 -0700 Subject: [PATCH 18/24] Add files via upload --- network-intrusion-detection-part-1/meta.toml | 8 ++++++++ network-intrusion-detection-part-1/notebook.ipynb | 1 + 2 files changed, 9 insertions(+) create mode 100644 network-intrusion-detection-part-1/meta.toml create mode 100644 network-intrusion-detection-part-1/notebook.ipynb diff --git a/network-intrusion-detection-part-1/meta.toml b/network-intrusion-detection-part-1/meta.toml new file mode 100644 index 00000000..d5acf21c --- /dev/null +++ b/network-intrusion-detection-part-1/meta.toml @@ -0,0 +1,8 @@ +[meta] +title="Part 1 or Real-time threat Detection - This notebook demonstrates the application of SingleStoreDB's similarity search to create a system +for identifying infrequent occurrences, a common requirement in fields such as cybersecurity +and fraud detection where only a small percentage of events are potentially malicious. +" +icon="browser" +tags=["iot", "cybersecurity", "training", "vectordb"] +destinations=["spaces"] \ No newline at end of file diff --git a/network-intrusion-detection-part-1/notebook.ipynb b/network-intrusion-detection-part-1/notebook.ipynb new file mode 100644 index 00000000..b403636a --- /dev/null +++ b/network-intrusion-detection-part-1/notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","id":"93ad2bda-e101-4aad-a83b-45f84560597c","metadata":{"language":"python"},"source":"
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SingleStore Notebooks
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IT Threat Detection, Part 1

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"},{"cell_type":"markdown","id":"4d343fe9-0c6f-4cf7-bf04-02524cdb5879","metadata":{"language":"python"},"source":"This notebook demonstrates the application of SingleStoreDB's similarity search to create a system for identifying infrequent occurrences, a common requirement in fields such as cybersecurity and fraud detection where only a small percentage of events are potentially malicious.\n\nIn this instance, we aim to construct a network intrusion detection system. These systems continuously monitor incoming and outgoing network traffic, generating alerts when potential threats are detected. We'll utilize a combination of a deep learning model and similarity search to identify and classify network intrusion traffic.\n\nOur initial step involves a dataset of labeled traffic events, distinguishing between benign and malicious events, by transforming them into vector embeddings. These vector embeddings serve as comprehensive mathematical representations of network traffic events. SingleStoreDB's built-in similarity-search algorithms allow us to measure the similarity between different network events. To generate these embeddings, we'll leverage a deep learning model based on recent academic research.\n\nSubsequently, we'll apply this dataset to search for the most similar matches when presented with new, unseen network events. We'll retrieve these matches along with their corresponding labels. This process enables us to classify the unseen events as either **benign** or **malicious** by propagating the labels of the matched events. It's essential to note that intrusion detection is a complex classification task, primarily because malicious events occur infrequently. The similarity search service plays a crucial role in identifying relevant historical labeled events, thus enabling the identification of these rare events while maintaining a low rate of false alarms.\n\n## Install Dependencies"},{"cell_type":"code","execution_count":4,"id":"c649045f-0a53-4c49-88cb-0351e872d68c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:11:32.025758Z","iopub.status.busy":"2023-10-04T15:11:32.025506Z","iopub.status.idle":"2023-10-04T15:12:02.177962Z","shell.execute_reply":"2023-10-04T15:12:02.177338Z","shell.execute_reply.started":"2023-10-04T15:11:32.025741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!pip3 install tensorflow keras pandas --upgrade --quiet"},{"cell_type":"code","execution_count":5,"id":"f3bb35f9-67ea-4a23-b713-888746494baf","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:06.378457Z","iopub.status.busy":"2023-10-04T15:12:06.378188Z","iopub.status.idle":"2023-10-04T15:12:07.773000Z","shell.execute_reply":"2023-10-04T15:12:07.772488Z","shell.execute_reply.started":"2023-10-04T15:12:06.378438Z"},"language":"python","scrolled":true,"tags":[],"trusted":true},"outputs":[],"source":"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\nimport pandas as pd\nimport tensorflow.keras.backend as K\nfrom tensorflow import keras\nfrom tensorflow.keras.models import Model"},{"cell_type":"markdown","id":"01fa2a0b-0213-4399-8481-adc1734cecf0","metadata":{"language":"python"},"source":"We'll define a Python context manager called `clear_memory()` using the **contextlib** module. This context manager will be used to clear memory by running Python's garbage collector (`gc.collect()`) after a block of code is executed."},{"cell_type":"code","execution_count":6,"id":"b7b5a0c6-aef9-4fea-91d9-8777e75d5c1f","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:13.931036Z","iopub.status.busy":"2023-10-04T15:12:13.930471Z","iopub.status.idle":"2023-10-04T15:12:13.934758Z","shell.execute_reply":"2023-10-04T15:12:13.933574Z","shell.execute_reply.started":"2023-10-04T15:12:13.931013Z"},"language":"python","trusted":true},"outputs":[],"source":"import contextlib\nimport gc\n\n@contextlib.contextmanager\ndef clear_memory():\n try:\n yield\n finally:\n gc.collect()"},{"cell_type":"markdown","id":"6eaabcc0-3bfa-4c67-86cd-8b3a42150a6f","metadata":{"language":"python"},"source":"We'll will incorporate portions of code from [research work](https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS). To begin, we'll clone the repository required for data preparation."},{"cell_type":"code","execution_count":7,"id":"1d06bd7a-f3ad-4c3a-a085-d8583d20e2bc","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:20.727187Z","iopub.status.busy":"2023-10-04T15:12:20.726917Z","iopub.status.idle":"2023-10-04T15:12:23.906216Z","shell.execute_reply":"2023-10-04T15:12:23.905573Z","shell.execute_reply.started":"2023-10-04T15:12:20.727172Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!git clone -q https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS.git"},{"cell_type":"markdown","id":"8c323aab-899d-4156-8cfe-98f0fdbb2147","metadata":{"language":"python"},"source":"## Data Preparation\n\nThe datasets we'll utilize comprise two types of network traffic:\n\n1. Benign (normal)\n2. Malicious (attack)\n\nstemming from various network attacks. Our focus will be solely on web-based attacks. These web attacks fall into three common categories:\n\n1. Cross-site scripting (BruteForce-XSS)\n2. SQL-Injection (SQL-Injection)\n3. Brute force attempts on administrative and user passwords (BruteForce-Web)\n\nThe original data was collected over a span of two days.\n\n### Download Data\n\nWe'll proceed by downloading data for two specific dates:\n\n1. February 22, 2018\n2. February 23, 2018\n\nThese files will be retrieved and saved to the current directory. Our intention is to use one of these dates for training and generating vectors, while the other will be reserved for testing purposes."},{"cell_type":"code","execution_count":8,"id":"47a639f2-1f03-4972-8212-316887cc1c73","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:32.057896Z","iopub.status.busy":"2023-10-04T15:12:32.057596Z","iopub.status.idle":"2023-10-04T15:12:43.448204Z","shell.execute_reply":"2023-10-04T15:12:43.447571Z","shell.execute_reply.started":"2023-10-04T15:12:32.057874Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Thursday-22-02-2018 100%[===================>] 364.91M 57.0MB/s in 5.8s \nFriday-23-02-2018_T 100%[===================>] 365.10M 78.5MB/s in 4.7s \n"}],"source":"!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress\n!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress"},{"cell_type":"markdown","id":"21103ba6-036d-4525-9e5a-073ec515aba9","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:17:45.604442Z","iopub.status.busy":"2023-09-27T15:17:45.604182Z","iopub.status.idle":"2023-09-27T15:17:45.607166Z","shell.execute_reply":"2023-09-27T15:17:45.606518Z","shell.execute_reply.started":"2023-09-27T15:17:45.604422Z"},"language":"python"},"source":"### Review Data"},{"cell_type":"code","execution_count":14,"id":"c17e283b-8629-483a-9631-69392b3b872e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:49.959451Z","iopub.status.busy":"2023-10-04T15:12:49.959246Z","iopub.status.idle":"2023-10-04T15:12:55.095007Z","shell.execute_reply":"2023-10-04T15:12:55.094492Z","shell.execute_reply.started":"2023-10-04T15:12:49.959434Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1048009\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data = pd.read_csv('Friday-23-02-2018_TrafficForML_CICFlowMeter.csv')\n\ndata.Label.value_counts()"},{"cell_type":"markdown","id":"176bc1e1-822e-4e22-a5fa-0dd03d6ecf04","metadata":{"language":"python"},"source":"### Clean Data\n\nWe'll run a cleanup script from the previously downloaded GitHub repo."},{"cell_type":"code","execution_count":17,"id":"af4f1d28-cba5-4547-a2bd-a34b200fc261","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:01.860976Z","iopub.status.busy":"2023-10-04T15:13:01.860721Z","iopub.status.idle":"2023-10-04T15:13:47.515247Z","shell.execute_reply":"2023-10-04T15:13:47.514670Z","shell.execute_reply.started":"2023-10-04T15:13:01.860959Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"cleaning Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\ntotal rows read = 1048576\nall done writing 1042868 rows; dropped 5708 rows\n"}],"source":"!python DeepLearning-IDS/data_cleanup.py \"Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" \"result23022018\""},{"cell_type":"markdown","id":"15fd1f07-d8a1-4ab5-a36c-5a08f1f043e9","metadata":{"language":"python"},"source":"We'll now review the cleaned data from the previous step."},{"cell_type":"code","execution_count":18,"id":"d893178a-6bcc-4a16-89ef-f3559adad14c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:58.399760Z","iopub.status.busy":"2023-10-04T15:13:58.399474Z","iopub.status.idle":"2023-10-04T15:14:03.115597Z","shell.execute_reply":"2023-10-04T15:14:03.115048Z","shell.execute_reply.started":"2023-10-04T15:13:58.399739Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
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5 rows × 80 columns

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","text/plain":" Dst Port Protocol Timestamp Flow Duration Tot Fwd Pkts \\\n0 22 6 1.519374e+09 1532698 11 \n1 500 17 1.519374e+09 117573855 3 \n2 500 17 1.519374e+09 117573848 3 \n3 22 6 1.519374e+09 1745392 11 \n4 500 17 1.519374e+09 89483474 6 \n\n Tot Bwd Pkts TotLen Fwd Pkts TotLen Bwd Pkts Fwd Pkt Len Max \\\n0 11 1179 1969 648 \n1 0 1500 0 500 \n2 0 1500 0 500 \n3 11 1179 1969 648 \n4 0 3000 0 500 \n\n Fwd Pkt Len Min ... Fwd Seg Size Min Active Mean Active Std \\\n0 0 ... 32 0.0 0.0 \n1 500 ... 8 0.0 0.0 \n2 500 ... 8 0.0 0.0 \n3 0 ... 32 0.0 0.0 \n4 500 ... 8 4000364.0 0.0 \n\n Active Max Active Min Idle Mean Idle Std Idle Max Idle Min \\\n0 0 0 0.0 0.000000e+00 0 0 \n1 0 0 58786927.5 2.375324e+07 75583006 41990849 \n2 0 0 58786924.0 2.375325e+07 75583007 41990841 \n3 0 0 0.0 0.000000e+00 0 0 \n4 4000364 4000364 21370777.5 1.528092e+07 41989576 7200485 \n\n Label \n0 Benign \n1 Benign \n2 Benign \n3 Benign \n4 Benign \n\n[5 rows x 80 columns]"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data_23_cleaned = pd.read_csv('result23022018.csv')\n\ndata_23_cleaned.head()"},{"cell_type":"code","execution_count":19,"id":"d98eee6b-6a68-4fb6-b418-1599daa9e4ff","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:09.241483Z","iopub.status.busy":"2023-10-04T15:14:09.241237Z","iopub.status.idle":"2023-10-04T15:14:09.283891Z","shell.execute_reply":"2023-10-04T15:14:09.283370Z","shell.execute_reply.started":"2023-10-04T15:14:09.241467Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1042301\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":"data_23_cleaned.Label.value_counts()"},{"cell_type":"markdown","id":"1b466f2f-ee4f-43ba-b1e6-0cb3380c9125","metadata":{"language":"python"},"source":"## Load Model\n\nIn this section, we'll load a pre-trained model that has been trained on data collected from the same date.\n\nThere are slight modifications to the original model, specifically, altering the number of classes. Initially, the model was designed to classify into four categories:\n\n1. Benign\n2. BruteForce-Web\n3. BruteForce-XSS\n4. SQL-Injection\n\nOur modified model has been adjusted to classify into just two categories:\n\n1. Benign\n2. Attack\n\n
\n \n
\n

Action Required

\n

The ZIP file is hosted on a Google Drive.

\n

Using the Edit Firewall button in the top right, add the following to the SingleStoreDB Cloud notebook firewall, one-by-one:\n

    \n
  • drive.google.com
    • \n
  • *.googleapis.com
    • \n
  • *.googleusercontent.com
    • \n
\n

\n
\n
"},{"cell_type":"code","execution_count":20,"id":"4074a769-b16b-4543-b0db-518c7f95f205","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:18.247758Z","iopub.status.busy":"2023-10-04T15:14:18.247504Z","iopub.status.idle":"2023-10-04T15:14:20.107308Z","shell.execute_reply":"2023-10-04T15:14:20.106660Z","shell.execute_reply.started":"2023-10-04T15:14:18.247741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!wget -q -O it_threat_model.zip \"https://drive.google.com/uc?export=download&id=1ahr5dYlhuxS56M6helUFI0yIxxIoFk9o\" \n!unzip -q it_threat_model.zip"},{"cell_type":"code","execution_count":21,"id":"7c77cf96-e3f7-4bed-9f7e-913f851367d8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:26.353287Z","iopub.status.busy":"2023-10-04T15:14:26.352961Z","iopub.status.idle":"2023-10-04T15:14:26.688942Z","shell.execute_reply":"2023-10-04T15:14:26.688380Z","shell.execute_reply.started":"2023-10-04T15:14:26.353263Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Model: \"sequential\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n dense (Dense) (None, 128) 10240 \n \n dense_1 (Dense) (None, 64) 8256 \n \n dense_2 (Dense) (None, 1) 65 \n \n=================================================================\nTotal params: 18561 (72.50 KB)\nTrainable params: 18561 (72.50 KB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n"}],"source":"with clear_memory():\n model = keras.models.load_model('it_threat_model')\n\nmodel.summary()"},{"cell_type":"code","execution_count":22,"id":"ed66c137-1023-4dce-b9ea-5e742099302e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:34.082125Z","iopub.status.busy":"2023-10-04T15:14:34.081856Z","iopub.status.idle":"2023-10-04T15:14:34.224177Z","shell.execute_reply":"2023-10-04T15:14:34.223680Z","shell.execute_reply.started":"2023-10-04T15:14:34.082108Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"with clear_memory():\n # Use the first layer\n layer_name = 'dense'\n intermediate_layer_model = Model(\n inputs = model.input,\n outputs = model.get_layer(layer_name).output\n )"},{"cell_type":"markdown","id":"24d3bfbb-78ee-4a8b-a429-84f988915b6d","metadata":{"language":"python"},"source":"## Upload Data to SingleStoreDB\n\n### Prepare Data\nWe'll use a method for defining item IDs that aligns with the event's label."},{"cell_type":"code","execution_count":23,"id":"ae1fc38e-f532-430a-99cd-f3e154343bd4","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:41.159100Z","iopub.status.busy":"2023-10-04T15:14:41.158708Z","iopub.status.idle":"2023-10-04T15:16:14.701123Z","shell.execute_reply":"2023-10-04T15:16:14.700506Z","shell.execute_reply.started":"2023-10-04T15:14:41.159081Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"32590/32590 [==============================] - 26s 797us/step\n"},{"name":"stderr","output_type":"stream","text":"100%|██████████| 1042867/1042867 [00:50<00:00, 20810.99it/s]\n"}],"source":"from tqdm import tqdm\nitems_to_upload = []\n\nwith clear_memory():\n model_res = intermediate_layer_model.predict(K.constant(data_23_cleaned.iloc[:,:-1]))\n \n for i, res in tqdm(zip(data_23_cleaned.iterrows(), model_res), total = len(model_res)):\n benign_or_attack = i[1]['Label'][:3]\n items_to_upload.append((benign_or_attack + '_' + str(i[0]), res.tolist()))"},{"cell_type":"markdown","id":"e4b3f74e-efea-499e-b25a-74316fcf2395","metadata":{"language":"python"},"source":"We'll store the data in a Pandas DataFrame."},{"cell_type":"code","execution_count":29,"id":"0177714c-62b7-4d3e-a93b-2fd467ff1352","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:45.778441Z","iopub.status.busy":"2023-10-04T15:17:45.778183Z","iopub.status.idle":"2023-10-04T15:17:47.525268Z","shell.execute_reply":"2023-10-04T15:17:47.524802Z","shell.execute_reply.started":"2023-10-04T15:17:45.778425Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
0Ben_0[0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...
1Ben_1[0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...
2Ben_2[0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...
3Ben_3[0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...
4Ben_4[0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ...
\n
","text/plain":" ID Model_Results\n0 Ben_0 [0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...\n1 Ben_1 [0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...\n2 Ben_2 [0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...\n3 Ben_3 [0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...\n4 Ben_4 [0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ..."},"execution_count":29,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n df = pd.DataFrame(items_to_upload, columns=['ID', 'Model_Results'])\n\ndf.head()"},{"cell_type":"markdown","id":"f52639f6-82c8-427f-aa7b-9859d6580eae","metadata":{"language":"python"},"source":"Now we'll convert the vectors to a binary format, ready to store in SingleStoreDB."},{"cell_type":"code","execution_count":30,"id":"ec8a2d26-98cf-4f1a-9e13-e197cd65040c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:53.975325Z","iopub.status.busy":"2023-10-04T15:17:53.975066Z","iopub.status.idle":"2023-10-04T15:17:57.811281Z","shell.execute_reply":"2023-10-04T15:17:57.810738Z","shell.execute_reply.started":"2023-10-04T15:17:53.975308Z"},"language":"python","trusted":true},"outputs":[],"source":"import struct\n\ndef data_to_binary(data: list[float]):\n format_string = 'f' * len(data)\n return struct.pack(format_string, *data)\n\nwith clear_memory():\n df['Model_Results'] = df['Model_Results'].apply(data_to_binary)"},{"cell_type":"markdown","id":"e267e6a4-3e70-4411-96cd-94da3f1f6011","metadata":{"language":"python"},"source":"We'll check the DataFrame."},{"cell_type":"code","execution_count":31,"id":"770cfe1e-4d55-43a8-a5e0-36da2525ca25","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:02.459555Z","iopub.status.busy":"2023-10-04T15:18:02.459286Z","iopub.status.idle":"2023-10-04T15:18:02.466500Z","shell.execute_reply":"2023-10-04T15:18:02.465962Z","shell.execute_reply.started":"2023-10-04T15:18:02.459538Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
0Ben_0b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
1Ben_1b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
2Ben_2b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
3Ben_3b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
4Ben_4b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
\n
","text/plain":" ID Model_Results\n0 Ben_0 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n1 Ben_1 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n2 Ben_2 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n3 Ben_3 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n4 Ben_4 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00..."},"execution_count":31,"metadata":{},"output_type":"execute_result"}],"source":"df.head()"},{"cell_type":"markdown","id":"8131ad6c-6d50-49db-845c-457e9957ddb9","metadata":{"language":"python"},"source":"### Create Database and Table"},{"cell_type":"code","execution_count":34,"id":"8940168f-072f-42cd-8855-4c6b6829421d","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:54.107461Z","iopub.status.busy":"2023-10-04T15:18:54.107206Z","iopub.status.idle":"2023-10-04T15:19:02.426902Z","shell.execute_reply":"2023-10-04T15:19:02.426343Z","shell.execute_reply.started":"2023-10-04T15:18:54.107444Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":34,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nDROP DATABASE IF EXISTS siem_log_kafka_demo;\n\nCREATE DATABASE IF NOT EXISTS siem_log_kafka_demo;\n\nUSE siem_log_kafka_demo;\n\nDROP TABLE IF EXISTS model_results_demo;\n\nCREATE TABLE IF NOT EXISTS model_results (\n id TEXT,\n Model_Results BLOB\n);"},{"cell_type":"markdown","id":"b6390a0c-d60a-4876-85bd-56e17deabeeb","metadata":{"language":"python"},"source":"### Get Connection Details\n\n
\n \n
\n

Action Required

\n

Select the database from the drop-down menu at the top of this notebook. It updates the connection_url which is used by SQLAlchemy to make connections to the selected database.

\n
\n
"},{"cell_type":"code","execution_count":36,"id":"8208b373-1973-4925-8d8a-cd43ba13e7d7","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:22.359227Z","iopub.status.busy":"2023-10-04T15:19:22.358972Z","iopub.status.idle":"2023-10-04T15:19:22.363216Z","shell.execute_reply":"2023-10-04T15:19:22.362608Z","shell.execute_reply.started":"2023-10-04T15:19:22.359211Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"from sqlalchemy import *\n\ndb_connection = create_engine(connection_url)"},{"cell_type":"markdown","id":"d97c6886-0ea9-47b5-938b-03ada717b394","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:37:17.351200Z","iopub.status.busy":"2023-09-27T15:37:17.350962Z","iopub.status.idle":"2023-09-27T15:37:17.354770Z","shell.execute_reply":"2023-09-27T15:37:17.353988Z","shell.execute_reply.started":"2023-09-27T15:37:17.351170Z"},"language":"python"},"source":"### Store DataFrame"},{"cell_type":"code","execution_count":37,"id":"e70b91a0-fdb9-46da-8c0d-5acc947799be","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:28.729452Z","iopub.status.busy":"2023-10-04T15:19:28.729169Z","iopub.status.idle":"2023-10-04T15:22:34.401289Z","shell.execute_reply":"2023-10-04T15:22:34.400783Z","shell.execute_reply.started":"2023-10-04T15:19:28.729435Z"},"language":"python","trusted":true},"outputs":[],"source":"with clear_memory():\n df.to_sql(\n 'model_results',\n con = db_connection,\n if_exists = 'append',\n index = False,\n chunksize = 1000\n )"},{"cell_type":"markdown","id":"559928bd-10a0-4880-805a-23444d7d72a3","metadata":{"language":"python"},"source":"### Check Stored Data"},{"cell_type":"code","execution_count":47,"id":"f4cb8e7f-362f-4477-8600-e5f39ec197b8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:22:52.838607Z","iopub.status.busy":"2023-10-04T15:22:52.838359Z","iopub.status.idle":"2023-10-04T15:22:53.253409Z","shell.execute_reply":"2023-10-04T15:22:53.252952Z","shell.execute_reply.started":"2023-10-04T15:22:52.838591Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
Ben_764632[0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0]
","text/plain":"+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| ID | Model_Results |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| Ben_764632 | [0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0] |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":47,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nUSE siem_log_kafka_demo;\n\nSELECT ID, JSON_ARRAY_UNPACK(Model_Results) AS Model_Results\nFROM model_results\nLIMIT 1;"}],"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":""},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file From 870a1b07c80bdb2de22c09dac5b788e00f2273cc Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 12:59:41 -0700 Subject: [PATCH 19/24] Add files via upload --- notebooks/network-intrusion-detection-part-1/meta.toml | 8 ++++++++ .../network-intrusion-detection-part-1/notebook.ipynb | 1 + 2 files changed, 9 insertions(+) create mode 100644 notebooks/network-intrusion-detection-part-1/meta.toml create mode 100644 notebooks/network-intrusion-detection-part-1/notebook.ipynb diff --git a/notebooks/network-intrusion-detection-part-1/meta.toml b/notebooks/network-intrusion-detection-part-1/meta.toml new file mode 100644 index 00000000..d5acf21c --- /dev/null +++ b/notebooks/network-intrusion-detection-part-1/meta.toml @@ -0,0 +1,8 @@ +[meta] +title="Part 1 or Real-time threat Detection - This notebook demonstrates the application of SingleStoreDB's similarity search to create a system +for identifying infrequent occurrences, a common requirement in fields such as cybersecurity +and fraud detection where only a small percentage of events are potentially malicious. +" +icon="browser" +tags=["iot", "cybersecurity", "training", "vectordb"] +destinations=["spaces"] \ No newline at end of file diff --git a/notebooks/network-intrusion-detection-part-1/notebook.ipynb b/notebooks/network-intrusion-detection-part-1/notebook.ipynb new file mode 100644 index 00000000..b403636a --- /dev/null +++ b/notebooks/network-intrusion-detection-part-1/notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","id":"93ad2bda-e101-4aad-a83b-45f84560597c","metadata":{"language":"python"},"source":"
\n
\n \n
\n
\n
SingleStore Notebooks
\n

IT Threat Detection, Part 1

\n
\n
"},{"cell_type":"markdown","id":"4d343fe9-0c6f-4cf7-bf04-02524cdb5879","metadata":{"language":"python"},"source":"This notebook demonstrates the application of SingleStoreDB's similarity search to create a system for identifying infrequent occurrences, a common requirement in fields such as cybersecurity and fraud detection where only a small percentage of events are potentially malicious.\n\nIn this instance, we aim to construct a network intrusion detection system. These systems continuously monitor incoming and outgoing network traffic, generating alerts when potential threats are detected. We'll utilize a combination of a deep learning model and similarity search to identify and classify network intrusion traffic.\n\nOur initial step involves a dataset of labeled traffic events, distinguishing between benign and malicious events, by transforming them into vector embeddings. These vector embeddings serve as comprehensive mathematical representations of network traffic events. SingleStoreDB's built-in similarity-search algorithms allow us to measure the similarity between different network events. To generate these embeddings, we'll leverage a deep learning model based on recent academic research.\n\nSubsequently, we'll apply this dataset to search for the most similar matches when presented with new, unseen network events. We'll retrieve these matches along with their corresponding labels. This process enables us to classify the unseen events as either **benign** or **malicious** by propagating the labels of the matched events. It's essential to note that intrusion detection is a complex classification task, primarily because malicious events occur infrequently. The similarity search service plays a crucial role in identifying relevant historical labeled events, thus enabling the identification of these rare events while maintaining a low rate of false alarms.\n\n## Install Dependencies"},{"cell_type":"code","execution_count":4,"id":"c649045f-0a53-4c49-88cb-0351e872d68c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:11:32.025758Z","iopub.status.busy":"2023-10-04T15:11:32.025506Z","iopub.status.idle":"2023-10-04T15:12:02.177962Z","shell.execute_reply":"2023-10-04T15:12:02.177338Z","shell.execute_reply.started":"2023-10-04T15:11:32.025741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!pip3 install tensorflow keras pandas --upgrade --quiet"},{"cell_type":"code","execution_count":5,"id":"f3bb35f9-67ea-4a23-b713-888746494baf","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:06.378457Z","iopub.status.busy":"2023-10-04T15:12:06.378188Z","iopub.status.idle":"2023-10-04T15:12:07.773000Z","shell.execute_reply":"2023-10-04T15:12:07.772488Z","shell.execute_reply.started":"2023-10-04T15:12:06.378438Z"},"language":"python","scrolled":true,"tags":[],"trusted":true},"outputs":[],"source":"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\nimport pandas as pd\nimport tensorflow.keras.backend as K\nfrom tensorflow import keras\nfrom tensorflow.keras.models import Model"},{"cell_type":"markdown","id":"01fa2a0b-0213-4399-8481-adc1734cecf0","metadata":{"language":"python"},"source":"We'll define a Python context manager called `clear_memory()` using the **contextlib** module. This context manager will be used to clear memory by running Python's garbage collector (`gc.collect()`) after a block of code is executed."},{"cell_type":"code","execution_count":6,"id":"b7b5a0c6-aef9-4fea-91d9-8777e75d5c1f","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:13.931036Z","iopub.status.busy":"2023-10-04T15:12:13.930471Z","iopub.status.idle":"2023-10-04T15:12:13.934758Z","shell.execute_reply":"2023-10-04T15:12:13.933574Z","shell.execute_reply.started":"2023-10-04T15:12:13.931013Z"},"language":"python","trusted":true},"outputs":[],"source":"import contextlib\nimport gc\n\n@contextlib.contextmanager\ndef clear_memory():\n try:\n yield\n finally:\n gc.collect()"},{"cell_type":"markdown","id":"6eaabcc0-3bfa-4c67-86cd-8b3a42150a6f","metadata":{"language":"python"},"source":"We'll will incorporate portions of code from [research work](https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS). To begin, we'll clone the repository required for data preparation."},{"cell_type":"code","execution_count":7,"id":"1d06bd7a-f3ad-4c3a-a085-d8583d20e2bc","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:20.727187Z","iopub.status.busy":"2023-10-04T15:12:20.726917Z","iopub.status.idle":"2023-10-04T15:12:23.906216Z","shell.execute_reply":"2023-10-04T15:12:23.905573Z","shell.execute_reply.started":"2023-10-04T15:12:20.727172Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!git clone -q https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS.git"},{"cell_type":"markdown","id":"8c323aab-899d-4156-8cfe-98f0fdbb2147","metadata":{"language":"python"},"source":"## Data Preparation\n\nThe datasets we'll utilize comprise two types of network traffic:\n\n1. Benign (normal)\n2. Malicious (attack)\n\nstemming from various network attacks. Our focus will be solely on web-based attacks. These web attacks fall into three common categories:\n\n1. Cross-site scripting (BruteForce-XSS)\n2. SQL-Injection (SQL-Injection)\n3. Brute force attempts on administrative and user passwords (BruteForce-Web)\n\nThe original data was collected over a span of two days.\n\n### Download Data\n\nWe'll proceed by downloading data for two specific dates:\n\n1. February 22, 2018\n2. February 23, 2018\n\nThese files will be retrieved and saved to the current directory. Our intention is to use one of these dates for training and generating vectors, while the other will be reserved for testing purposes."},{"cell_type":"code","execution_count":8,"id":"47a639f2-1f03-4972-8212-316887cc1c73","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:32.057896Z","iopub.status.busy":"2023-10-04T15:12:32.057596Z","iopub.status.idle":"2023-10-04T15:12:43.448204Z","shell.execute_reply":"2023-10-04T15:12:43.447571Z","shell.execute_reply.started":"2023-10-04T15:12:32.057874Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Thursday-22-02-2018 100%[===================>] 364.91M 57.0MB/s in 5.8s \nFriday-23-02-2018_T 100%[===================>] 365.10M 78.5MB/s in 4.7s \n"}],"source":"!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress\n!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress"},{"cell_type":"markdown","id":"21103ba6-036d-4525-9e5a-073ec515aba9","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:17:45.604442Z","iopub.status.busy":"2023-09-27T15:17:45.604182Z","iopub.status.idle":"2023-09-27T15:17:45.607166Z","shell.execute_reply":"2023-09-27T15:17:45.606518Z","shell.execute_reply.started":"2023-09-27T15:17:45.604422Z"},"language":"python"},"source":"### Review Data"},{"cell_type":"code","execution_count":14,"id":"c17e283b-8629-483a-9631-69392b3b872e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:49.959451Z","iopub.status.busy":"2023-10-04T15:12:49.959246Z","iopub.status.idle":"2023-10-04T15:12:55.095007Z","shell.execute_reply":"2023-10-04T15:12:55.094492Z","shell.execute_reply.started":"2023-10-04T15:12:49.959434Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1048009\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data = pd.read_csv('Friday-23-02-2018_TrafficForML_CICFlowMeter.csv')\n\ndata.Label.value_counts()"},{"cell_type":"markdown","id":"176bc1e1-822e-4e22-a5fa-0dd03d6ecf04","metadata":{"language":"python"},"source":"### Clean Data\n\nWe'll run a cleanup script from the previously downloaded GitHub repo."},{"cell_type":"code","execution_count":17,"id":"af4f1d28-cba5-4547-a2bd-a34b200fc261","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:01.860976Z","iopub.status.busy":"2023-10-04T15:13:01.860721Z","iopub.status.idle":"2023-10-04T15:13:47.515247Z","shell.execute_reply":"2023-10-04T15:13:47.514670Z","shell.execute_reply.started":"2023-10-04T15:13:01.860959Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"cleaning Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\ntotal rows read = 1048576\nall done writing 1042868 rows; dropped 5708 rows\n"}],"source":"!python DeepLearning-IDS/data_cleanup.py \"Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" \"result23022018\""},{"cell_type":"markdown","id":"15fd1f07-d8a1-4ab5-a36c-5a08f1f043e9","metadata":{"language":"python"},"source":"We'll now review the cleaned data from the previous step."},{"cell_type":"code","execution_count":18,"id":"d893178a-6bcc-4a16-89ef-f3559adad14c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:58.399760Z","iopub.status.busy":"2023-10-04T15:13:58.399474Z","iopub.status.idle":"2023-10-04T15:14:03.115597Z","shell.execute_reply":"2023-10-04T15:14:03.115048Z","shell.execute_reply.started":"2023-10-04T15:13:58.399739Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Dst PortProtocolTimestampFlow DurationTot Fwd PktsTot Bwd PktsTotLen Fwd PktsTotLen Bwd PktsFwd Pkt Len MaxFwd Pkt Len Min...Fwd Seg Size MinActive MeanActive StdActive MaxActive MinIdle MeanIdle StdIdle MaxIdle MinLabel
02261.519374e+0915326981111117919696480...320.00.0000.00.000000e+0000Benign
1500171.519374e+091175738553015000500500...80.00.00058786927.52.375324e+077558300641990849Benign
2500171.519374e+091175738483015000500500...80.00.00058786924.02.375325e+077558300741990841Benign
32261.519374e+0917453921111117919696480...320.00.0000.00.000000e+0000Benign
4500171.519374e+09894834746030000500500...84000364.00.04000364400036421370777.51.528092e+07419895767200485Benign
\n

5 rows × 80 columns

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","text/plain":" Dst Port Protocol Timestamp Flow Duration Tot Fwd Pkts \\\n0 22 6 1.519374e+09 1532698 11 \n1 500 17 1.519374e+09 117573855 3 \n2 500 17 1.519374e+09 117573848 3 \n3 22 6 1.519374e+09 1745392 11 \n4 500 17 1.519374e+09 89483474 6 \n\n Tot Bwd Pkts TotLen Fwd Pkts TotLen Bwd Pkts Fwd Pkt Len Max \\\n0 11 1179 1969 648 \n1 0 1500 0 500 \n2 0 1500 0 500 \n3 11 1179 1969 648 \n4 0 3000 0 500 \n\n Fwd Pkt Len Min ... Fwd Seg Size Min Active Mean Active Std \\\n0 0 ... 32 0.0 0.0 \n1 500 ... 8 0.0 0.0 \n2 500 ... 8 0.0 0.0 \n3 0 ... 32 0.0 0.0 \n4 500 ... 8 4000364.0 0.0 \n\n Active Max Active Min Idle Mean Idle Std Idle Max Idle Min \\\n0 0 0 0.0 0.000000e+00 0 0 \n1 0 0 58786927.5 2.375324e+07 75583006 41990849 \n2 0 0 58786924.0 2.375325e+07 75583007 41990841 \n3 0 0 0.0 0.000000e+00 0 0 \n4 4000364 4000364 21370777.5 1.528092e+07 41989576 7200485 \n\n Label \n0 Benign \n1 Benign \n2 Benign \n3 Benign \n4 Benign \n\n[5 rows x 80 columns]"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data_23_cleaned = pd.read_csv('result23022018.csv')\n\ndata_23_cleaned.head()"},{"cell_type":"code","execution_count":19,"id":"d98eee6b-6a68-4fb6-b418-1599daa9e4ff","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:09.241483Z","iopub.status.busy":"2023-10-04T15:14:09.241237Z","iopub.status.idle":"2023-10-04T15:14:09.283891Z","shell.execute_reply":"2023-10-04T15:14:09.283370Z","shell.execute_reply.started":"2023-10-04T15:14:09.241467Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1042301\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":"data_23_cleaned.Label.value_counts()"},{"cell_type":"markdown","id":"1b466f2f-ee4f-43ba-b1e6-0cb3380c9125","metadata":{"language":"python"},"source":"## Load Model\n\nIn this section, we'll load a pre-trained model that has been trained on data collected from the same date.\n\nThere are slight modifications to the original model, specifically, altering the number of classes. Initially, the model was designed to classify into four categories:\n\n1. Benign\n2. BruteForce-Web\n3. BruteForce-XSS\n4. SQL-Injection\n\nOur modified model has been adjusted to classify into just two categories:\n\n1. Benign\n2. Attack\n\n
\n \n
\n

Action Required

\n

The ZIP file is hosted on a Google Drive.

\n

Using the Edit Firewall button in the top right, add the following to the SingleStoreDB Cloud notebook firewall, one-by-one:\n

    \n
  • drive.google.com
    • \n
  • *.googleapis.com
    • \n
  • *.googleusercontent.com
    • \n
\n

\n
\n
"},{"cell_type":"code","execution_count":20,"id":"4074a769-b16b-4543-b0db-518c7f95f205","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:18.247758Z","iopub.status.busy":"2023-10-04T15:14:18.247504Z","iopub.status.idle":"2023-10-04T15:14:20.107308Z","shell.execute_reply":"2023-10-04T15:14:20.106660Z","shell.execute_reply.started":"2023-10-04T15:14:18.247741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!wget -q -O it_threat_model.zip \"https://drive.google.com/uc?export=download&id=1ahr5dYlhuxS56M6helUFI0yIxxIoFk9o\" \n!unzip -q it_threat_model.zip"},{"cell_type":"code","execution_count":21,"id":"7c77cf96-e3f7-4bed-9f7e-913f851367d8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:26.353287Z","iopub.status.busy":"2023-10-04T15:14:26.352961Z","iopub.status.idle":"2023-10-04T15:14:26.688942Z","shell.execute_reply":"2023-10-04T15:14:26.688380Z","shell.execute_reply.started":"2023-10-04T15:14:26.353263Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Model: \"sequential\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n dense (Dense) (None, 128) 10240 \n \n dense_1 (Dense) (None, 64) 8256 \n \n dense_2 (Dense) (None, 1) 65 \n \n=================================================================\nTotal params: 18561 (72.50 KB)\nTrainable params: 18561 (72.50 KB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n"}],"source":"with clear_memory():\n model = keras.models.load_model('it_threat_model')\n\nmodel.summary()"},{"cell_type":"code","execution_count":22,"id":"ed66c137-1023-4dce-b9ea-5e742099302e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:34.082125Z","iopub.status.busy":"2023-10-04T15:14:34.081856Z","iopub.status.idle":"2023-10-04T15:14:34.224177Z","shell.execute_reply":"2023-10-04T15:14:34.223680Z","shell.execute_reply.started":"2023-10-04T15:14:34.082108Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"with clear_memory():\n # Use the first layer\n layer_name = 'dense'\n intermediate_layer_model = Model(\n inputs = model.input,\n outputs = model.get_layer(layer_name).output\n )"},{"cell_type":"markdown","id":"24d3bfbb-78ee-4a8b-a429-84f988915b6d","metadata":{"language":"python"},"source":"## Upload Data to SingleStoreDB\n\n### Prepare Data\nWe'll use a method for defining item IDs that aligns with the event's label."},{"cell_type":"code","execution_count":23,"id":"ae1fc38e-f532-430a-99cd-f3e154343bd4","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:41.159100Z","iopub.status.busy":"2023-10-04T15:14:41.158708Z","iopub.status.idle":"2023-10-04T15:16:14.701123Z","shell.execute_reply":"2023-10-04T15:16:14.700506Z","shell.execute_reply.started":"2023-10-04T15:14:41.159081Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"32590/32590 [==============================] - 26s 797us/step\n"},{"name":"stderr","output_type":"stream","text":"100%|██████████| 1042867/1042867 [00:50<00:00, 20810.99it/s]\n"}],"source":"from tqdm import tqdm\nitems_to_upload = []\n\nwith clear_memory():\n model_res = intermediate_layer_model.predict(K.constant(data_23_cleaned.iloc[:,:-1]))\n \n for i, res in tqdm(zip(data_23_cleaned.iterrows(), model_res), total = len(model_res)):\n benign_or_attack = i[1]['Label'][:3]\n items_to_upload.append((benign_or_attack + '_' + str(i[0]), res.tolist()))"},{"cell_type":"markdown","id":"e4b3f74e-efea-499e-b25a-74316fcf2395","metadata":{"language":"python"},"source":"We'll store the data in a Pandas DataFrame."},{"cell_type":"code","execution_count":29,"id":"0177714c-62b7-4d3e-a93b-2fd467ff1352","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:45.778441Z","iopub.status.busy":"2023-10-04T15:17:45.778183Z","iopub.status.idle":"2023-10-04T15:17:47.525268Z","shell.execute_reply":"2023-10-04T15:17:47.524802Z","shell.execute_reply.started":"2023-10-04T15:17:45.778425Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
0Ben_0[0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...
1Ben_1[0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...
2Ben_2[0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...
3Ben_3[0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...
4Ben_4[0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ...
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","text/plain":" ID Model_Results\n0 Ben_0 [0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...\n1 Ben_1 [0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...\n2 Ben_2 [0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...\n3 Ben_3 [0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...\n4 Ben_4 [0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ..."},"execution_count":29,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n df = pd.DataFrame(items_to_upload, columns=['ID', 'Model_Results'])\n\ndf.head()"},{"cell_type":"markdown","id":"f52639f6-82c8-427f-aa7b-9859d6580eae","metadata":{"language":"python"},"source":"Now we'll convert the vectors to a binary format, ready to store in SingleStoreDB."},{"cell_type":"code","execution_count":30,"id":"ec8a2d26-98cf-4f1a-9e13-e197cd65040c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:53.975325Z","iopub.status.busy":"2023-10-04T15:17:53.975066Z","iopub.status.idle":"2023-10-04T15:17:57.811281Z","shell.execute_reply":"2023-10-04T15:17:57.810738Z","shell.execute_reply.started":"2023-10-04T15:17:53.975308Z"},"language":"python","trusted":true},"outputs":[],"source":"import struct\n\ndef data_to_binary(data: list[float]):\n format_string = 'f' * len(data)\n return struct.pack(format_string, *data)\n\nwith clear_memory():\n df['Model_Results'] = df['Model_Results'].apply(data_to_binary)"},{"cell_type":"markdown","id":"e267e6a4-3e70-4411-96cd-94da3f1f6011","metadata":{"language":"python"},"source":"We'll check the DataFrame."},{"cell_type":"code","execution_count":31,"id":"770cfe1e-4d55-43a8-a5e0-36da2525ca25","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:02.459555Z","iopub.status.busy":"2023-10-04T15:18:02.459286Z","iopub.status.idle":"2023-10-04T15:18:02.466500Z","shell.execute_reply":"2023-10-04T15:18:02.465962Z","shell.execute_reply.started":"2023-10-04T15:18:02.459538Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
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IDModel_Results
0Ben_0b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
1Ben_1b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
2Ben_2b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
3Ben_3b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
4Ben_4b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
\n
","text/plain":" ID Model_Results\n0 Ben_0 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n1 Ben_1 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n2 Ben_2 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n3 Ben_3 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n4 Ben_4 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00..."},"execution_count":31,"metadata":{},"output_type":"execute_result"}],"source":"df.head()"},{"cell_type":"markdown","id":"8131ad6c-6d50-49db-845c-457e9957ddb9","metadata":{"language":"python"},"source":"### Create Database and Table"},{"cell_type":"code","execution_count":34,"id":"8940168f-072f-42cd-8855-4c6b6829421d","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:54.107461Z","iopub.status.busy":"2023-10-04T15:18:54.107206Z","iopub.status.idle":"2023-10-04T15:19:02.426902Z","shell.execute_reply":"2023-10-04T15:19:02.426343Z","shell.execute_reply.started":"2023-10-04T15:18:54.107444Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":34,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nDROP DATABASE IF EXISTS siem_log_kafka_demo;\n\nCREATE DATABASE IF NOT EXISTS siem_log_kafka_demo;\n\nUSE siem_log_kafka_demo;\n\nDROP TABLE IF EXISTS model_results_demo;\n\nCREATE TABLE IF NOT EXISTS model_results (\n id TEXT,\n Model_Results BLOB\n);"},{"cell_type":"markdown","id":"b6390a0c-d60a-4876-85bd-56e17deabeeb","metadata":{"language":"python"},"source":"### Get Connection Details\n\n
\n \n
\n

Action Required

\n

Select the database from the drop-down menu at the top of this notebook. It updates the connection_url which is used by SQLAlchemy to make connections to the selected database.

\n
\n
"},{"cell_type":"code","execution_count":36,"id":"8208b373-1973-4925-8d8a-cd43ba13e7d7","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:22.359227Z","iopub.status.busy":"2023-10-04T15:19:22.358972Z","iopub.status.idle":"2023-10-04T15:19:22.363216Z","shell.execute_reply":"2023-10-04T15:19:22.362608Z","shell.execute_reply.started":"2023-10-04T15:19:22.359211Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"from sqlalchemy import *\n\ndb_connection = create_engine(connection_url)"},{"cell_type":"markdown","id":"d97c6886-0ea9-47b5-938b-03ada717b394","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:37:17.351200Z","iopub.status.busy":"2023-09-27T15:37:17.350962Z","iopub.status.idle":"2023-09-27T15:37:17.354770Z","shell.execute_reply":"2023-09-27T15:37:17.353988Z","shell.execute_reply.started":"2023-09-27T15:37:17.351170Z"},"language":"python"},"source":"### Store DataFrame"},{"cell_type":"code","execution_count":37,"id":"e70b91a0-fdb9-46da-8c0d-5acc947799be","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:28.729452Z","iopub.status.busy":"2023-10-04T15:19:28.729169Z","iopub.status.idle":"2023-10-04T15:22:34.401289Z","shell.execute_reply":"2023-10-04T15:22:34.400783Z","shell.execute_reply.started":"2023-10-04T15:19:28.729435Z"},"language":"python","trusted":true},"outputs":[],"source":"with clear_memory():\n df.to_sql(\n 'model_results',\n con = db_connection,\n if_exists = 'append',\n index = False,\n chunksize = 1000\n )"},{"cell_type":"markdown","id":"559928bd-10a0-4880-805a-23444d7d72a3","metadata":{"language":"python"},"source":"### Check Stored Data"},{"cell_type":"code","execution_count":47,"id":"f4cb8e7f-362f-4477-8600-e5f39ec197b8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:22:52.838607Z","iopub.status.busy":"2023-10-04T15:22:52.838359Z","iopub.status.idle":"2023-10-04T15:22:53.253409Z","shell.execute_reply":"2023-10-04T15:22:53.252952Z","shell.execute_reply.started":"2023-10-04T15:22:52.838591Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
Ben_764632[0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0]
","text/plain":"+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| ID | Model_Results |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| Ben_764632 | [0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0] |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":47,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nUSE siem_log_kafka_demo;\n\nSELECT ID, JSON_ARRAY_UNPACK(Model_Results) AS Model_Results\nFROM model_results\nLIMIT 1;"}],"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":""},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file From fbe99b92bc65c3b0faaf22b16f557debac8fd304 Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 13:00:08 -0700 Subject: [PATCH 20/24] Delete network-intrusion-detection-part-1 directory --- network-intrusion-detection-part-1/meta.toml | 8 -------- network-intrusion-detection-part-1/notebook.ipynb | 1 - 2 files changed, 9 deletions(-) delete mode 100644 network-intrusion-detection-part-1/meta.toml delete mode 100644 network-intrusion-detection-part-1/notebook.ipynb diff --git a/network-intrusion-detection-part-1/meta.toml b/network-intrusion-detection-part-1/meta.toml deleted file mode 100644 index d5acf21c..00000000 --- a/network-intrusion-detection-part-1/meta.toml +++ /dev/null @@ -1,8 +0,0 @@ -[meta] -title="Part 1 or Real-time threat Detection - This notebook demonstrates the application of SingleStoreDB's similarity search to create a system -for identifying infrequent occurrences, a common requirement in fields such as cybersecurity -and fraud detection where only a small percentage of events are potentially malicious. -" -icon="browser" -tags=["iot", "cybersecurity", "training", "vectordb"] -destinations=["spaces"] \ No newline at end of file diff --git a/network-intrusion-detection-part-1/notebook.ipynb b/network-intrusion-detection-part-1/notebook.ipynb deleted file mode 100644 index b403636a..00000000 --- a/network-intrusion-detection-part-1/notebook.ipynb +++ /dev/null @@ -1 +0,0 @@ -{"cells":[{"cell_type":"markdown","id":"93ad2bda-e101-4aad-a83b-45f84560597c","metadata":{"language":"python"},"source":"
\n
\n \n
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SingleStore Notebooks
\n

IT Threat Detection, Part 1

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"},{"cell_type":"markdown","id":"4d343fe9-0c6f-4cf7-bf04-02524cdb5879","metadata":{"language":"python"},"source":"This notebook demonstrates the application of SingleStoreDB's similarity search to create a system for identifying infrequent occurrences, a common requirement in fields such as cybersecurity and fraud detection where only a small percentage of events are potentially malicious.\n\nIn this instance, we aim to construct a network intrusion detection system. These systems continuously monitor incoming and outgoing network traffic, generating alerts when potential threats are detected. We'll utilize a combination of a deep learning model and similarity search to identify and classify network intrusion traffic.\n\nOur initial step involves a dataset of labeled traffic events, distinguishing between benign and malicious events, by transforming them into vector embeddings. These vector embeddings serve as comprehensive mathematical representations of network traffic events. SingleStoreDB's built-in similarity-search algorithms allow us to measure the similarity between different network events. To generate these embeddings, we'll leverage a deep learning model based on recent academic research.\n\nSubsequently, we'll apply this dataset to search for the most similar matches when presented with new, unseen network events. We'll retrieve these matches along with their corresponding labels. This process enables us to classify the unseen events as either **benign** or **malicious** by propagating the labels of the matched events. It's essential to note that intrusion detection is a complex classification task, primarily because malicious events occur infrequently. The similarity search service plays a crucial role in identifying relevant historical labeled events, thus enabling the identification of these rare events while maintaining a low rate of false alarms.\n\n## Install Dependencies"},{"cell_type":"code","execution_count":4,"id":"c649045f-0a53-4c49-88cb-0351e872d68c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:11:32.025758Z","iopub.status.busy":"2023-10-04T15:11:32.025506Z","iopub.status.idle":"2023-10-04T15:12:02.177962Z","shell.execute_reply":"2023-10-04T15:12:02.177338Z","shell.execute_reply.started":"2023-10-04T15:11:32.025741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!pip3 install tensorflow keras pandas --upgrade --quiet"},{"cell_type":"code","execution_count":5,"id":"f3bb35f9-67ea-4a23-b713-888746494baf","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:06.378457Z","iopub.status.busy":"2023-10-04T15:12:06.378188Z","iopub.status.idle":"2023-10-04T15:12:07.773000Z","shell.execute_reply":"2023-10-04T15:12:07.772488Z","shell.execute_reply.started":"2023-10-04T15:12:06.378438Z"},"language":"python","scrolled":true,"tags":[],"trusted":true},"outputs":[],"source":"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\nimport pandas as pd\nimport tensorflow.keras.backend as K\nfrom tensorflow import keras\nfrom tensorflow.keras.models import Model"},{"cell_type":"markdown","id":"01fa2a0b-0213-4399-8481-adc1734cecf0","metadata":{"language":"python"},"source":"We'll define a Python context manager called `clear_memory()` using the **contextlib** module. This context manager will be used to clear memory by running Python's garbage collector (`gc.collect()`) after a block of code is executed."},{"cell_type":"code","execution_count":6,"id":"b7b5a0c6-aef9-4fea-91d9-8777e75d5c1f","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:13.931036Z","iopub.status.busy":"2023-10-04T15:12:13.930471Z","iopub.status.idle":"2023-10-04T15:12:13.934758Z","shell.execute_reply":"2023-10-04T15:12:13.933574Z","shell.execute_reply.started":"2023-10-04T15:12:13.931013Z"},"language":"python","trusted":true},"outputs":[],"source":"import contextlib\nimport gc\n\n@contextlib.contextmanager\ndef clear_memory():\n try:\n yield\n finally:\n gc.collect()"},{"cell_type":"markdown","id":"6eaabcc0-3bfa-4c67-86cd-8b3a42150a6f","metadata":{"language":"python"},"source":"We'll will incorporate portions of code from [research work](https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS). To begin, we'll clone the repository required for data preparation."},{"cell_type":"code","execution_count":7,"id":"1d06bd7a-f3ad-4c3a-a085-d8583d20e2bc","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:20.727187Z","iopub.status.busy":"2023-10-04T15:12:20.726917Z","iopub.status.idle":"2023-10-04T15:12:23.906216Z","shell.execute_reply":"2023-10-04T15:12:23.905573Z","shell.execute_reply.started":"2023-10-04T15:12:20.727172Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!git clone -q https://github.com/Colorado-Mesa-University-Cybersecurity/DeepLearning-IDS.git"},{"cell_type":"markdown","id":"8c323aab-899d-4156-8cfe-98f0fdbb2147","metadata":{"language":"python"},"source":"## Data Preparation\n\nThe datasets we'll utilize comprise two types of network traffic:\n\n1. Benign (normal)\n2. Malicious (attack)\n\nstemming from various network attacks. Our focus will be solely on web-based attacks. These web attacks fall into three common categories:\n\n1. Cross-site scripting (BruteForce-XSS)\n2. SQL-Injection (SQL-Injection)\n3. Brute force attempts on administrative and user passwords (BruteForce-Web)\n\nThe original data was collected over a span of two days.\n\n### Download Data\n\nWe'll proceed by downloading data for two specific dates:\n\n1. February 22, 2018\n2. February 23, 2018\n\nThese files will be retrieved and saved to the current directory. Our intention is to use one of these dates for training and generating vectors, while the other will be reserved for testing purposes."},{"cell_type":"code","execution_count":8,"id":"47a639f2-1f03-4972-8212-316887cc1c73","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:32.057896Z","iopub.status.busy":"2023-10-04T15:12:32.057596Z","iopub.status.idle":"2023-10-04T15:12:43.448204Z","shell.execute_reply":"2023-10-04T15:12:43.447571Z","shell.execute_reply.started":"2023-10-04T15:12:32.057874Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Thursday-22-02-2018 100%[===================>] 364.91M 57.0MB/s in 5.8s \nFriday-23-02-2018_T 100%[===================>] 365.10M 78.5MB/s in 4.7s \n"}],"source":"!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress\n!wget \"https://cse-cic-ids2018.s3.ca-central-1.amazonaws.com/Processed%20Traffic%20Data%20for%20ML%20Algorithms/Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" -q --show-progress"},{"cell_type":"markdown","id":"21103ba6-036d-4525-9e5a-073ec515aba9","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:17:45.604442Z","iopub.status.busy":"2023-09-27T15:17:45.604182Z","iopub.status.idle":"2023-09-27T15:17:45.607166Z","shell.execute_reply":"2023-09-27T15:17:45.606518Z","shell.execute_reply.started":"2023-09-27T15:17:45.604422Z"},"language":"python"},"source":"### Review Data"},{"cell_type":"code","execution_count":14,"id":"c17e283b-8629-483a-9631-69392b3b872e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:12:49.959451Z","iopub.status.busy":"2023-10-04T15:12:49.959246Z","iopub.status.idle":"2023-10-04T15:12:55.095007Z","shell.execute_reply":"2023-10-04T15:12:55.094492Z","shell.execute_reply.started":"2023-10-04T15:12:49.959434Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1048009\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data = pd.read_csv('Friday-23-02-2018_TrafficForML_CICFlowMeter.csv')\n\ndata.Label.value_counts()"},{"cell_type":"markdown","id":"176bc1e1-822e-4e22-a5fa-0dd03d6ecf04","metadata":{"language":"python"},"source":"### Clean Data\n\nWe'll run a cleanup script from the previously downloaded GitHub repo."},{"cell_type":"code","execution_count":17,"id":"af4f1d28-cba5-4547-a2bd-a34b200fc261","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:01.860976Z","iopub.status.busy":"2023-10-04T15:13:01.860721Z","iopub.status.idle":"2023-10-04T15:13:47.515247Z","shell.execute_reply":"2023-10-04T15:13:47.514670Z","shell.execute_reply.started":"2023-10-04T15:13:01.860959Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"cleaning Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\ntotal rows read = 1048576\nall done writing 1042868 rows; dropped 5708 rows\n"}],"source":"!python DeepLearning-IDS/data_cleanup.py \"Friday-23-02-2018_TrafficForML_CICFlowMeter.csv\" \"result23022018\""},{"cell_type":"markdown","id":"15fd1f07-d8a1-4ab5-a36c-5a08f1f043e9","metadata":{"language":"python"},"source":"We'll now review the cleaned data from the previous step."},{"cell_type":"code","execution_count":18,"id":"d893178a-6bcc-4a16-89ef-f3559adad14c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:13:58.399760Z","iopub.status.busy":"2023-10-04T15:13:58.399474Z","iopub.status.idle":"2023-10-04T15:14:03.115597Z","shell.execute_reply":"2023-10-04T15:14:03.115048Z","shell.execute_reply.started":"2023-10-04T15:13:58.399739Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Dst PortProtocolTimestampFlow DurationTot Fwd PktsTot Bwd PktsTotLen Fwd PktsTotLen Bwd PktsFwd Pkt Len MaxFwd Pkt Len Min...Fwd Seg Size MinActive MeanActive StdActive MaxActive MinIdle MeanIdle StdIdle MaxIdle MinLabel
02261.519374e+0915326981111117919696480...320.00.0000.00.000000e+0000Benign
1500171.519374e+091175738553015000500500...80.00.00058786927.52.375324e+077558300641990849Benign
2500171.519374e+091175738483015000500500...80.00.00058786924.02.375325e+077558300741990841Benign
32261.519374e+0917453921111117919696480...320.00.0000.00.000000e+0000Benign
4500171.519374e+09894834746030000500500...84000364.00.04000364400036421370777.51.528092e+07419895767200485Benign
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5 rows × 80 columns

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","text/plain":" Dst Port Protocol Timestamp Flow Duration Tot Fwd Pkts \\\n0 22 6 1.519374e+09 1532698 11 \n1 500 17 1.519374e+09 117573855 3 \n2 500 17 1.519374e+09 117573848 3 \n3 22 6 1.519374e+09 1745392 11 \n4 500 17 1.519374e+09 89483474 6 \n\n Tot Bwd Pkts TotLen Fwd Pkts TotLen Bwd Pkts Fwd Pkt Len Max \\\n0 11 1179 1969 648 \n1 0 1500 0 500 \n2 0 1500 0 500 \n3 11 1179 1969 648 \n4 0 3000 0 500 \n\n Fwd Pkt Len Min ... Fwd Seg Size Min Active Mean Active Std \\\n0 0 ... 32 0.0 0.0 \n1 500 ... 8 0.0 0.0 \n2 500 ... 8 0.0 0.0 \n3 0 ... 32 0.0 0.0 \n4 500 ... 8 4000364.0 0.0 \n\n Active Max Active Min Idle Mean Idle Std Idle Max Idle Min \\\n0 0 0 0.0 0.000000e+00 0 0 \n1 0 0 58786927.5 2.375324e+07 75583006 41990849 \n2 0 0 58786924.0 2.375325e+07 75583007 41990841 \n3 0 0 0.0 0.000000e+00 0 0 \n4 4000364 4000364 21370777.5 1.528092e+07 41989576 7200485 \n\n Label \n0 Benign \n1 Benign \n2 Benign \n3 Benign \n4 Benign \n\n[5 rows x 80 columns]"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data_23_cleaned = pd.read_csv('result23022018.csv')\n\ndata_23_cleaned.head()"},{"cell_type":"code","execution_count":19,"id":"d98eee6b-6a68-4fb6-b418-1599daa9e4ff","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:09.241483Z","iopub.status.busy":"2023-10-04T15:14:09.241237Z","iopub.status.idle":"2023-10-04T15:14:09.283891Z","shell.execute_reply":"2023-10-04T15:14:09.283370Z","shell.execute_reply.started":"2023-10-04T15:14:09.241467Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1042301\nBrute Force -Web 362\nBrute Force -XSS 151\nSQL Injection 53\nName: count, dtype: int64"},"execution_count":19,"metadata":{},"output_type":"execute_result"}],"source":"data_23_cleaned.Label.value_counts()"},{"cell_type":"markdown","id":"1b466f2f-ee4f-43ba-b1e6-0cb3380c9125","metadata":{"language":"python"},"source":"## Load Model\n\nIn this section, we'll load a pre-trained model that has been trained on data collected from the same date.\n\nThere are slight modifications to the original model, specifically, altering the number of classes. Initially, the model was designed to classify into four categories:\n\n1. Benign\n2. BruteForce-Web\n3. BruteForce-XSS\n4. SQL-Injection\n\nOur modified model has been adjusted to classify into just two categories:\n\n1. Benign\n2. Attack\n\n
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Action Required

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The ZIP file is hosted on a Google Drive.

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Using the Edit Firewall button in the top right, add the following to the SingleStoreDB Cloud notebook firewall, one-by-one:\n

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  • drive.google.com
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  • *.googleapis.com
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  • *.googleusercontent.com
    • \n
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"},{"cell_type":"code","execution_count":20,"id":"4074a769-b16b-4543-b0db-518c7f95f205","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:18.247758Z","iopub.status.busy":"2023-10-04T15:14:18.247504Z","iopub.status.idle":"2023-10-04T15:14:20.107308Z","shell.execute_reply":"2023-10-04T15:14:20.106660Z","shell.execute_reply.started":"2023-10-04T15:14:18.247741Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"!wget -q -O it_threat_model.zip \"https://drive.google.com/uc?export=download&id=1ahr5dYlhuxS56M6helUFI0yIxxIoFk9o\" \n!unzip -q it_threat_model.zip"},{"cell_type":"code","execution_count":21,"id":"7c77cf96-e3f7-4bed-9f7e-913f851367d8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:26.353287Z","iopub.status.busy":"2023-10-04T15:14:26.352961Z","iopub.status.idle":"2023-10-04T15:14:26.688942Z","shell.execute_reply":"2023-10-04T15:14:26.688380Z","shell.execute_reply.started":"2023-10-04T15:14:26.353263Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Model: \"sequential\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n dense (Dense) (None, 128) 10240 \n \n dense_1 (Dense) (None, 64) 8256 \n \n dense_2 (Dense) (None, 1) 65 \n \n=================================================================\nTotal params: 18561 (72.50 KB)\nTrainable params: 18561 (72.50 KB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n"}],"source":"with clear_memory():\n model = keras.models.load_model('it_threat_model')\n\nmodel.summary()"},{"cell_type":"code","execution_count":22,"id":"ed66c137-1023-4dce-b9ea-5e742099302e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:34.082125Z","iopub.status.busy":"2023-10-04T15:14:34.081856Z","iopub.status.idle":"2023-10-04T15:14:34.224177Z","shell.execute_reply":"2023-10-04T15:14:34.223680Z","shell.execute_reply.started":"2023-10-04T15:14:34.082108Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"with clear_memory():\n # Use the first layer\n layer_name = 'dense'\n intermediate_layer_model = Model(\n inputs = model.input,\n outputs = model.get_layer(layer_name).output\n )"},{"cell_type":"markdown","id":"24d3bfbb-78ee-4a8b-a429-84f988915b6d","metadata":{"language":"python"},"source":"## Upload Data to SingleStoreDB\n\n### Prepare Data\nWe'll use a method for defining item IDs that aligns with the event's label."},{"cell_type":"code","execution_count":23,"id":"ae1fc38e-f532-430a-99cd-f3e154343bd4","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:14:41.159100Z","iopub.status.busy":"2023-10-04T15:14:41.158708Z","iopub.status.idle":"2023-10-04T15:16:14.701123Z","shell.execute_reply":"2023-10-04T15:16:14.700506Z","shell.execute_reply.started":"2023-10-04T15:14:41.159081Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"32590/32590 [==============================] - 26s 797us/step\n"},{"name":"stderr","output_type":"stream","text":"100%|██████████| 1042867/1042867 [00:50<00:00, 20810.99it/s]\n"}],"source":"from tqdm import tqdm\nitems_to_upload = []\n\nwith clear_memory():\n model_res = intermediate_layer_model.predict(K.constant(data_23_cleaned.iloc[:,:-1]))\n \n for i, res in tqdm(zip(data_23_cleaned.iterrows(), model_res), total = len(model_res)):\n benign_or_attack = i[1]['Label'][:3]\n items_to_upload.append((benign_or_attack + '_' + str(i[0]), res.tolist()))"},{"cell_type":"markdown","id":"e4b3f74e-efea-499e-b25a-74316fcf2395","metadata":{"language":"python"},"source":"We'll store the data in a Pandas DataFrame."},{"cell_type":"code","execution_count":29,"id":"0177714c-62b7-4d3e-a93b-2fd467ff1352","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:45.778441Z","iopub.status.busy":"2023-10-04T15:17:45.778183Z","iopub.status.idle":"2023-10-04T15:17:47.525268Z","shell.execute_reply":"2023-10-04T15:17:47.524802Z","shell.execute_reply.started":"2023-10-04T15:17:45.778425Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
0Ben_0[0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...
1Ben_1[0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...
2Ben_2[0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...
3Ben_3[0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...
4Ben_4[0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ...
\n
","text/plain":" ID Model_Results\n0 Ben_0 [0.0, 0.0, 0.0, 125628656.0, 0.0, 0.0, 5421442...\n1 Ben_1 [0.0, 0.0, 0.0, 356751744.0, 1190461440.0, 0.0...\n2 Ben_2 [0.0, 0.0, 0.0, 356751680.0, 1190461440.0, 0.0...\n3 Ben_3 [0.0, 0.0, 0.0, 125515856.0, 0.0, 0.0, 5432884...\n4 Ben_4 [0.0, 0.0, 0.0, 26214912.0, 698683840.0, 0.0, ..."},"execution_count":29,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n df = pd.DataFrame(items_to_upload, columns=['ID', 'Model_Results'])\n\ndf.head()"},{"cell_type":"markdown","id":"f52639f6-82c8-427f-aa7b-9859d6580eae","metadata":{"language":"python"},"source":"Now we'll convert the vectors to a binary format, ready to store in SingleStoreDB."},{"cell_type":"code","execution_count":30,"id":"ec8a2d26-98cf-4f1a-9e13-e197cd65040c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:17:53.975325Z","iopub.status.busy":"2023-10-04T15:17:53.975066Z","iopub.status.idle":"2023-10-04T15:17:57.811281Z","shell.execute_reply":"2023-10-04T15:17:57.810738Z","shell.execute_reply.started":"2023-10-04T15:17:53.975308Z"},"language":"python","trusted":true},"outputs":[],"source":"import struct\n\ndef data_to_binary(data: list[float]):\n format_string = 'f' * len(data)\n return struct.pack(format_string, *data)\n\nwith clear_memory():\n df['Model_Results'] = df['Model_Results'].apply(data_to_binary)"},{"cell_type":"markdown","id":"e267e6a4-3e70-4411-96cd-94da3f1f6011","metadata":{"language":"python"},"source":"We'll check the DataFrame."},{"cell_type":"code","execution_count":31,"id":"770cfe1e-4d55-43a8-a5e0-36da2525ca25","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:02.459555Z","iopub.status.busy":"2023-10-04T15:18:02.459286Z","iopub.status.idle":"2023-10-04T15:18:02.466500Z","shell.execute_reply":"2023-10-04T15:18:02.465962Z","shell.execute_reply.started":"2023-10-04T15:18:02.459538Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
0Ben_0b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
1Ben_1b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
2Ben_2b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
3Ben_3b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
4Ben_4b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...
\n
","text/plain":" ID Model_Results\n0 Ben_0 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n1 Ben_1 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n2 Ben_2 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n3 Ben_3 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...\n4 Ben_4 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00..."},"execution_count":31,"metadata":{},"output_type":"execute_result"}],"source":"df.head()"},{"cell_type":"markdown","id":"8131ad6c-6d50-49db-845c-457e9957ddb9","metadata":{"language":"python"},"source":"### Create Database and Table"},{"cell_type":"code","execution_count":34,"id":"8940168f-072f-42cd-8855-4c6b6829421d","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:18:54.107461Z","iopub.status.busy":"2023-10-04T15:18:54.107206Z","iopub.status.idle":"2023-10-04T15:19:02.426902Z","shell.execute_reply":"2023-10-04T15:19:02.426343Z","shell.execute_reply.started":"2023-10-04T15:18:54.107444Z"},"language":"sql","tags":[],"trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n
","text/plain":"++\n||\n++\n++"},"execution_count":34,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nDROP DATABASE IF EXISTS siem_log_kafka_demo;\n\nCREATE DATABASE IF NOT EXISTS siem_log_kafka_demo;\n\nUSE siem_log_kafka_demo;\n\nDROP TABLE IF EXISTS model_results_demo;\n\nCREATE TABLE IF NOT EXISTS model_results (\n id TEXT,\n Model_Results BLOB\n);"},{"cell_type":"markdown","id":"b6390a0c-d60a-4876-85bd-56e17deabeeb","metadata":{"language":"python"},"source":"### Get Connection Details\n\n
\n \n
\n

Action Required

\n

Select the database from the drop-down menu at the top of this notebook. It updates the connection_url which is used by SQLAlchemy to make connections to the selected database.

\n
\n
"},{"cell_type":"code","execution_count":36,"id":"8208b373-1973-4925-8d8a-cd43ba13e7d7","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:22.359227Z","iopub.status.busy":"2023-10-04T15:19:22.358972Z","iopub.status.idle":"2023-10-04T15:19:22.363216Z","shell.execute_reply":"2023-10-04T15:19:22.362608Z","shell.execute_reply.started":"2023-10-04T15:19:22.359211Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":"from sqlalchemy import *\n\ndb_connection = create_engine(connection_url)"},{"cell_type":"markdown","id":"d97c6886-0ea9-47b5-938b-03ada717b394","metadata":{"execution":{"iopub.execute_input":"2023-09-27T15:37:17.351200Z","iopub.status.busy":"2023-09-27T15:37:17.350962Z","iopub.status.idle":"2023-09-27T15:37:17.354770Z","shell.execute_reply":"2023-09-27T15:37:17.353988Z","shell.execute_reply.started":"2023-09-27T15:37:17.351170Z"},"language":"python"},"source":"### Store DataFrame"},{"cell_type":"code","execution_count":37,"id":"e70b91a0-fdb9-46da-8c0d-5acc947799be","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:19:28.729452Z","iopub.status.busy":"2023-10-04T15:19:28.729169Z","iopub.status.idle":"2023-10-04T15:22:34.401289Z","shell.execute_reply":"2023-10-04T15:22:34.400783Z","shell.execute_reply.started":"2023-10-04T15:19:28.729435Z"},"language":"python","trusted":true},"outputs":[],"source":"with clear_memory():\n df.to_sql(\n 'model_results',\n con = db_connection,\n if_exists = 'append',\n index = False,\n chunksize = 1000\n )"},{"cell_type":"markdown","id":"559928bd-10a0-4880-805a-23444d7d72a3","metadata":{"language":"python"},"source":"### Check Stored Data"},{"cell_type":"code","execution_count":47,"id":"f4cb8e7f-362f-4477-8600-e5f39ec197b8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:22:52.838607Z","iopub.status.busy":"2023-10-04T15:22:52.838359Z","iopub.status.idle":"2023-10-04T15:22:53.253409Z","shell.execute_reply":"2023-10-04T15:22:53.252952Z","shell.execute_reply.started":"2023-10-04T15:22:52.838591Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/html":"\n \n \n \n \n \n \n \n \n \n \n \n \n
IDModel_Results
Ben_764632[0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0]
","text/plain":"+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| ID | Model_Results |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+\n| Ben_764632 | [0, 0, 0, 161398336, 0, 0, 91465440, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 186428320, 0, 0, 0, 167306864, 0, 0, 277207904, 0, 92328576, 73124928, 0, 0, 0, 95751136, 0, 0, 0, 0, 0, 0, 0, 0, 230162768, 273622432, 511405120, 0, 0, 0, 0, 0, 0, 0, 0, 0, 145775152, 106490400, 373456928, 0, 0, 0, 211604256, 30848250, 0, 0, 0, 0, 326004800, 0, 0, 0, 0, 13625428, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 248507264, 0, 121489904, 196521904, 0, 2331058, 0, 0, 234076784, 247954704, 0, 0, 16321682, 0, 0, 0, 343808992, 0, 0, 0, 74993352, 0, 0, 59710728, 0, 0, 89274704, 0, 174431776, 107296112, 0, 0, 134864096, 0, 0] |\n+------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+"},"execution_count":47,"metadata":{},"output_type":"execute_result"}],"source":"%%sql\n%%sql\nUSE siem_log_kafka_demo;\n\nSELECT ID, JSON_ARRAY_UNPACK(Model_Results) AS Model_Results\nFROM model_results\nLIMIT 1;"}],"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":""},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file From dc6e4aa7ccbf3d1a6f05f110e676c4d89f12dc23 Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 13:02:02 -0700 Subject: [PATCH 21/24] Create readme --- notebooks/network-intrusion-detection-part-2/readme | 1 + 1 file changed, 1 insertion(+) create mode 100644 notebooks/network-intrusion-detection-part-2/readme diff --git a/notebooks/network-intrusion-detection-part-2/readme b/notebooks/network-intrusion-detection-part-2/readme new file mode 100644 index 00000000..8b137891 --- /dev/null +++ b/notebooks/network-intrusion-detection-part-2/readme @@ -0,0 +1 @@ + From 785ba7fb3faa981608419d63c39e66ce0b07682b Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 13:02:20 -0700 Subject: [PATCH 22/24] Add files via upload --- notebooks/network-intrusion-detection-part-2/meta.toml | 6 ++++++ notebooks/network-intrusion-detection-part-2/notebook.ipynb | 1 + 2 files changed, 7 insertions(+) create mode 100644 notebooks/network-intrusion-detection-part-2/meta.toml create mode 100644 notebooks/network-intrusion-detection-part-2/notebook.ipynb diff --git a/notebooks/network-intrusion-detection-part-2/meta.toml b/notebooks/network-intrusion-detection-part-2/meta.toml new file mode 100644 index 00000000..9a202b7a --- /dev/null +++ b/notebooks/network-intrusion-detection-part-2/meta.toml @@ -0,0 +1,6 @@ +[meta] +title="Part 2 or Real-time threat Detection - Validate the accuracy of the threat detection model with a test dataset +" +icon="browser" +tags=["iot", "cybersecurity", "training", "vectordb"] +destinations=["spaces"] \ No newline at end of file diff --git a/notebooks/network-intrusion-detection-part-2/notebook.ipynb b/notebooks/network-intrusion-detection-part-2/notebook.ipynb new file mode 100644 index 00000000..015a8906 --- /dev/null +++ b/notebooks/network-intrusion-detection-part-2/notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","id":"d62916d4-c174-4708-92b1-b6940fa5a861","metadata":{"language":"python"},"source":"
\n
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\n
SingleStore Notebooks
\n

IT Threat Detection, Part 2

\n
\n
"},{"cell_type":"markdown","id":"59521b37-8c16-4713-b341-dcf4d020ef88","metadata":{"language":"python"},"source":"## Install Dependencies"},{"cell_type":"code","execution_count":7,"id":"c649045f-0a53-4c49-88cb-0351e872d68c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:25:39.154518Z","iopub.status.busy":"2023-10-04T15:25:39.154237Z","iopub.status.idle":"2023-10-04T15:25:46.672297Z","shell.execute_reply":"2023-10-04T15:25:46.671674Z","shell.execute_reply.started":"2023-10-04T15:25:39.154501Z"},"language":"python","trusted":true},"outputs":[],"source":"!pip3 install tensorflow keras scikit-learn pandas --upgrade --quiet"},{"cell_type":"code","execution_count":8,"id":"f3bb35f9-67ea-4a23-b713-888746494baf","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:25:50.440874Z","iopub.status.busy":"2023-10-04T15:25:50.440598Z","iopub.status.idle":"2023-10-04T15:25:53.802416Z","shell.execute_reply":"2023-10-04T15:25:53.801316Z","shell.execute_reply.started":"2023-10-04T15:25:50.440853Z"},"language":"python","trusted":true},"outputs":[],"source":"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n\nimport pandas as pd\nimport tensorflow.keras.backend as K\nfrom collections import Counter\nfrom sklearn.metrics import accuracy_score, precision_score, recall_score\nfrom sklearn.metrics import confusion_matrix\nfrom tensorflow import keras\nfrom tensorflow.keras.models import Model"},{"cell_type":"markdown","id":"7f949377-d93b-43d3-b9e1-2fb910f843fd","metadata":{"language":"python"},"source":"We'll define a Python context manager called `clear_memory()` using the **contextlib** module. This context manager will be used to clear memory by running Python's garbage collector (`gc.collect()`) after a block of code is executed."},{"cell_type":"code","execution_count":9,"id":"00eccb20-5b95-4383-88c4-2dff1b494a1f","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:25:58.943482Z","iopub.status.busy":"2023-10-04T15:25:58.943033Z","iopub.status.idle":"2023-10-04T15:25:58.946633Z","shell.execute_reply":"2023-10-04T15:25:58.946046Z","shell.execute_reply.started":"2023-10-04T15:25:58.943463Z"},"language":"python","trusted":true},"outputs":[],"source":"import contextlib\nimport gc\n\n@contextlib.contextmanager\ndef clear_memory():\n try:\n yield\n finally:\n gc.collect()"},{"cell_type":"markdown","id":"b06e5a33-bf7f-41ea-85fd-1b13871c40e9","metadata":{"language":"python"},"source":"## Load Model"},{"cell_type":"code","execution_count":10,"id":"7c77cf96-e3f7-4bed-9f7e-913f851367d8","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:26:03.750305Z","iopub.status.busy":"2023-10-04T15:26:03.749964Z","iopub.status.idle":"2023-10-04T15:26:04.138631Z","shell.execute_reply":"2023-10-04T15:26:04.138055Z","shell.execute_reply.started":"2023-10-04T15:26:03.750282Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Model: \"sequential\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n dense (Dense) (None, 128) 10240 \n \n dense_1 (Dense) (None, 64) 8256 \n \n dense_2 (Dense) (None, 1) 65 \n \n=================================================================\nTotal params: 18561 (72.50 KB)\nTrainable params: 18561 (72.50 KB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n"}],"source":"with clear_memory():\n model = keras.models.load_model('it_threat_model')\n\nmodel.summary()"},{"cell_type":"code","execution_count":11,"id":"ed66c137-1023-4dce-b9ea-5e742099302e","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:26:10.193366Z","iopub.status.busy":"2023-10-04T15:26:10.193090Z","iopub.status.idle":"2023-10-04T15:26:10.343918Z","shell.execute_reply":"2023-10-04T15:26:10.343428Z","shell.execute_reply.started":"2023-10-04T15:26:10.193347Z"},"language":"python","trusted":true},"outputs":[],"source":"with clear_memory():\n # Select the first layer\n layer_name = 'dense'\n intermediate_layer_model = Model(\n inputs = model.input,\n outputs = model.get_layer(layer_name).output\n )"},{"cell_type":"markdown","id":"f3756497-a5a8-453a-9257-13ac0122a6ff","metadata":{"language":"python"},"source":"## Data Preparation\n\nWe'll use the second file we downloaded earlier for testing purposes.\n\n### Review Data"},{"cell_type":"code","execution_count":12,"id":"bc2325d6-a298-4916-bf33-7416b3b4ab25","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:26:15.812577Z","iopub.status.busy":"2023-10-04T15:26:15.812299Z","iopub.status.idle":"2023-10-04T15:26:24.090195Z","shell.execute_reply":"2023-10-04T15:26:24.089485Z","shell.execute_reply.started":"2023-10-04T15:26:15.812559Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1048213\nBrute Force -Web 249\nBrute Force -XSS 79\nSQL Injection 34\nName: count, dtype: int64"},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data = pd.read_csv('Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv')\n\ndata.Label.value_counts()"},{"cell_type":"markdown","id":"3c515eb7-1e06-4be3-993b-cc4483cb7bf6","metadata":{"language":"python"},"source":"### Clean Data\n\nWe'll run a cleanup script from the previously downloaded GitHub repo."},{"cell_type":"code","execution_count":13,"id":"73e53251-5fd9-4fbd-856e-2bbc560a2924","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:26:33.808949Z","iopub.status.busy":"2023-10-04T15:26:33.808685Z","iopub.status.idle":"2023-10-04T15:27:21.029619Z","shell.execute_reply":"2023-10-04T15:27:21.029028Z","shell.execute_reply.started":"2023-10-04T15:26:33.808932Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"cleaning Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv\ntotal rows read = 1048576\nall done writing 1042966 rows; dropped 5610 rows\n"}],"source":"!python DeepLearning-IDS/data_cleanup.py \"Thursday-22-02-2018_TrafficForML_CICFlowMeter.csv\" \"result22022018\""},{"cell_type":"markdown","id":"67c1125c-bb62-40b8-b885-d5d9187b5f81","metadata":{"language":"python"},"source":"We'll now review the cleaned data from the previous step."},{"cell_type":"code","execution_count":16,"id":"326a320a-9388-4108-a0f0-10520d25c2a4","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:27:26.141735Z","iopub.status.busy":"2023-10-04T15:27:26.141481Z","iopub.status.idle":"2023-10-04T15:27:30.942932Z","shell.execute_reply":"2023-10-04T15:27:30.942374Z","shell.execute_reply.started":"2023-10-04T15:27:26.141718Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Dst PortProtocolTimestampFlow DurationTot Fwd PktsTot Bwd PktsTotLen Fwd PktsTotLen Bwd PktsFwd Pkt Len MaxFwd Pkt Len Min...Fwd Seg Size MinActive MeanActive StdActive MaxActive MinIdle MeanIdle StdIdle MaxIdle MinLabel
02261.519288e+0920553406107106312977440...201027304.00.0102730410273041.952608e+070.000000e+001952608019526080Benign
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5 rows × 80 columns

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","text/plain":" Dst Port Protocol Timestamp Flow Duration Tot Fwd Pkts \\\n0 22 6 1.519288e+09 20553406 10 \n1 34989 6 1.519288e+09 790 2 \n2 500 17 1.519288e+09 99745913 5 \n3 500 17 1.519288e+09 99745913 5 \n4 500 17 1.519288e+09 89481361 6 \n\n Tot Bwd Pkts TotLen Fwd Pkts TotLen Bwd Pkts Fwd Pkt Len Max \\\n0 7 1063 1297 744 \n1 0 848 0 848 \n2 0 2500 0 500 \n3 0 2500 0 500 \n4 0 3000 0 500 \n\n Fwd Pkt Len Min ... Fwd Seg Size Min Active Mean Active Std \\\n0 0 ... 20 1027304.0 0.0 \n1 0 ... 20 0.0 0.0 \n2 500 ... 8 4000203.0 0.0 \n3 500 ... 8 4000189.0 0.0 \n4 500 ... 8 4000554.0 0.0 \n\n Active Max Active Min Idle Mean Idle Std Idle Max Idle Min \\\n0 1027304 1027304 1.952608e+07 0.000000e+00 19526080 19526080 \n1 0 0 0.000000e+00 0.000000e+00 0 0 \n2 4000203 4000203 3.191524e+07 3.792787e+07 75584115 7200679 \n3 4000189 4000189 3.191524e+07 3.792788e+07 75584130 7200693 \n4 4000554 4000554 2.137020e+07 1.528109e+07 41990741 7200848 \n\n Label \n0 Benign \n1 Benign \n2 Benign \n3 Benign \n4 Benign \n\n[5 rows x 80 columns]"},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data_22_cleaned = pd.read_csv('result22022018.csv')\n\ndata_22_cleaned.head()"},{"cell_type":"code","execution_count":17,"id":"66a13b5c-07b2-413b-9b77-ce490fa8507b","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:27:36.208801Z","iopub.status.busy":"2023-10-04T15:27:36.208532Z","iopub.status.idle":"2023-10-04T15:27:36.251908Z","shell.execute_reply":"2023-10-04T15:27:36.251354Z","shell.execute_reply.started":"2023-10-04T15:27:36.208784Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1042603\nBrute Force -Web 249\nBrute Force -XSS 79\nSQL Injection 34\nName: count, dtype: int64"},"execution_count":17,"metadata":{},"output_type":"execute_result"}],"source":"data_22_cleaned.Label.value_counts()"},{"cell_type":"markdown","id":"df41d065-924e-4de5-834c-967846688e13","metadata":{"language":"python"},"source":"We'll create a sample that encompasses all the distinct types of web attacks observed on this particular date."},{"cell_type":"code","execution_count":18,"id":"9f669747-2c58-4113-a099-070c5a08a492","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:28:01.776887Z","iopub.status.busy":"2023-10-04T15:28:01.776616Z","iopub.status.idle":"2023-10-04T15:28:01.920002Z","shell.execute_reply":"2023-10-04T15:28:01.919505Z","shell.execute_reply.started":"2023-10-04T15:28:01.776870Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/plain":"Label\nBenign 1638\nBrute Force -Web 249\nBrute Force -XSS 79\nSQL Injection 34\nName: count, dtype: int64"},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":"with clear_memory():\n data_sample = data_22_cleaned[-2000:]\n\ndata_sample.Label.value_counts()"},{"cell_type":"markdown","id":"722010dd-2a2e-41a8-848f-bad78d0fa79f","metadata":{"language":"python"},"source":"## Get Connection Details\n\n
\n \n
\n

Action Required

\n

Select the database from the drop-down menu at the top of this notebook. It updates the connection_url which is used by SQLAlchemy to make connections to the selected database.

\n
\n
"},{"cell_type":"code","execution_count":19,"id":"806149fa-bba9-42fd-b804-3b5964bceca5","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:28:15.383580Z","iopub.status.busy":"2023-10-04T15:28:15.383328Z","iopub.status.idle":"2023-10-04T15:28:15.387539Z","shell.execute_reply":"2023-10-04T15:28:15.386869Z","shell.execute_reply.started":"2023-10-04T15:28:15.383564Z"},"language":"python","trusted":true},"outputs":[],"source":"from sqlalchemy import *\n\ndb_connection = create_engine(connection_url)"},{"cell_type":"markdown","id":"0f5e79af-3991-45e1-845e-a24390437d56","metadata":{"language":"python"},"source":"## Queries\n\nNext, we'll perform queries on the test dataset and store the predicted and expected results, enabling us to construct a confusion matrix."},{"cell_type":"code","execution_count":20,"id":"ddcd73cd-0d87-4aaf-82be-5d7bd0e73566","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:28:28.581591Z","iopub.status.busy":"2023-10-04T15:28:28.581340Z","iopub.status.idle":"2023-10-04T15:43:39.914364Z","shell.execute_reply":"2023-10-04T15:43:39.913753Z","shell.execute_reply.started":"2023-10-04T15:28:28.581575Z"},"language":"python","trusted":true},"outputs":[{"name":"stderr","output_type":"stream","text":" 0%| | 0/20 [00:00\n window.PlotlyConfig = {MathJaxConfig: 'local'};\n if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n if (typeof require !== 'undefined') {\n require.undef(\"plotly\");\n define('plotly', function(require, exports, module) {\n /**\n* plotly.js v2.25.2\n* Copyright 2012-2023, Plotly, Inc.\n* All rights reserved.\n* Licensed under the MIT license\n*/\n/*! 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e?e.xpx:_[0]._length/2,lt=\"ypx\"in e?e.ypx:w[0]._length/2;if(e.pointerX=st+_[0]._offset,e.pointerY=lt+w[0]._offset,q=\"xval\"in e?y.flat(l,e.xval):y.p2c(_,st),G=\"yval\"in e?y.flat(l,e.yval):y.p2c(w,lt),!i(q[0])||!i(G[0]))return o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ft=1/0;function ht(t,r){for(Y=0;Yrt&&(nt.splice(0,rt),ft=nt[0].distance),m&&0!==H&&0===nt.length){et.distance=H,et.index=!1;var f=X._module.hoverPoints(et,Q,tt,\"closest\",{hoverLayer:c._hoverlayer});if(f&&(f=f.filter((function(t){return t.spikeDistance<=H}))),f&&f.length){var h,d=f.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(d.length){var v=d[0];i(v.x0)&&i(v.y0)&&(h=dt(v),(!at.vLinePoint||at.vLinePoint.spikeDistance>h.spikeDistance)&&(at.vLinePoint=h))}var g=f.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(g.length){var x=g[0];i(x.x0)&&i(x.y0)&&(h=dt(x),(!at.hLinePoint||at.hLinePoint.spikeDistance>h.spikeDistance)&&(at.hLinePoint=h))}}}}}function pt(t,e,r){for(var n,i=null,a=1/0,o=0;o0&&Math.abs(t.distance)At-1;Mt--)Ct(nt[Mt]);nt=St,mt()}var Pt=t._hoverdata,Ot=[],It=U(t),Dt=V(t);for(Z=0;Z1||nt.length>1)||\"closest\"===I&&ot&&nt.length>1,Yt=p.combine(c.plot_bgcolor||p.background,c.paper_bgcolor),Wt=O(nt,{gd:t,hovermode:I,rotateLabels:Zt,bgColor:Yt,container:c._hoverlayer,outerContainer:c._paper.node(),commonLabelOpts:c.hoverlabel,hoverdistance:c.hoverdistance}),Xt=Wt.hoverLabels;if(y.isUnifiedHover(I)||(function(t,e,r,n){var i,a,o,s,l,u,c,f=e?\"xa\":\"ya\",h=e?\"ya\":\"xa\",p=0,d=1,v=t.size(),g=new Array(v),y=0,m=n.minX,x=n.maxX,b=n.minY,_=n.maxY,w=function(t){return t*r._invScaleX},k=function(t){return t*r._invScaleY};function A(t){var e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,o=r.pos+r.dp+r.size-e.pmax,a>.01){for(l=t.length-1;l>=0;l--)t[l].dp+=a;i=!1}if(!(o<.01)){if(a<-.01){for(l=t.length-1;l>=0;l--)t[l].dp-=o;i=!1}if(i){var n=0;for(s=0;se.pmax&&n++;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos>e.pmax-1&&(u.del=!0,n--);for(s=0;s=0;l--)t[l].dp-=o;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos+u.dp+u.size>e.pmax&&(u.del=!0,n--)}}}for(t.each((function(t){var n=t[f],i=t[h],a=\"x\"===n._id.charAt(0),o=n.range;0===y&&o&&o[0]>o[1]!==a&&(d=-1);var s=0,l=a?r.width:r.height;if(\"x\"===r.hovermode||\"y\"===r.hovermode){var u,c,p=D(t,e),v=t.anchor,A=\"end\"===v?-1:1;if(\"middle\"===v)c=(u=t.crossPos+(a?k(p.y-t.by/2):w(t.bx/2+t.tx2width/2)))+(a?k(t.by):w(t.bx));else if(a)c=(u=t.crossPos+k(M+p.y)-k(t.by/2-M))+k(t.by);else{var S=w(A*M+p.x),E=S+w(A*t.bx);u=t.crossPos+Math.min(S,E),c=t.crossPos+Math.max(S,E)}a?void 0!==b&&void 0!==_&&Math.min(c,_)-Math.max(u,b)>1&&(\"left\"===i.side?(s=i._mainLinePosition,l=r.width):l=i._mainLinePosition):void 0!==m&&void 0!==x&&Math.min(c,x)-Math.max(u,m)>1&&(\"top\"===i.side?(s=i._mainLinePosition,l=r.height):l=i._mainLinePosition)}g[y++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(a?T:1)/2,pmin:s,pmax:l}]})),g.sort((function(t,e){return t[0].posref-e[0].posref||d*(e[0].traceIndex-t[0].traceIndex)}));!i&&p<=v;){for(p++,i=!0,s=0;s.01&&L.pmin===C.pmin&&L.pmax===C.pmax){for(l=E.length-1;l>=0;l--)E[l].dp+=a;for(S.push.apply(S,E),g.splice(s+1,1),c=0,l=S.length-1;l>=0;l--)c+=S[l].dp;for(o=c/S.length,l=S.length-1;l>=0;l--)S[l].dp-=o;i=!1}else s++}g.forEach(A)}for(s=g.length-1;s>=0;s--){var P=g[s];for(l=P.length-1;l>=0;l--){var O=P[l],I=O.datum;I.offset=O.dp,I.del=O.del}}}(Xt,Zt,c,Wt.commonLabelBoundingBox),z(Xt,Zt,c._invScaleX,c._invScaleY)),s&&s.tagName){var Jt=g.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,Ot);f(n.select(s),Jt?\"pointer\":\"\")}s&&!a&&function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt)&&(Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt}),t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:_,yaxes:w,xvals:q,yvals:G}))}(t,e,r,a,s)}))},e.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=U(i),o=V(i),s=O(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,u=t.eventData;if(u){var c=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),v=t.trace;if(g.traceIs(v,\"gl3d\")){var y=i._fullLayout[v.scene]._scene.container,m=y.offsetLeft,x=y.offsetTop;c+=m,f+=m,h+=x,d+=x}u.bbox={x0:c+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(u.bbox)}else u=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:u}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}).hoverLabels,l=0,u=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5([\\s\\S]*)<\\/extra>/;function O(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,u=e.rotateLabels,f=e.bgColor,d=e.container,v=e.outerContainer,w=e.commonLabelOpts||{};if(0===t.length)return[[]];var T=e.fontFamily||m.HOVERFONT,k=e.fontSize||m.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),O=P+\"Label\",D=A[O];if(void 0===D&&\"multicategory\"===E.type)for(var z=0;zi.width-b?(g=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+m.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+b+\"v\"+x+(2*S+m.height)+\"H-\"+b+\"V\"+x+M+\"H-\"+M+\"Z\"),Y.minX=g-b,Y.maxX=g+b,\"top\"===E.side?(Y.minY=y-(2*S+m.height),Y.maxY=y-S):(Y.minY=y+S,Y.maxY=y+(2*S+m.height))}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",g=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",g=E._offset),y=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+m.height/2)+\"h\"+P+(2*S+m.width)+\"V-\"+(S+m.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\"),Y.minY=y-(S+m.height/2),Y.maxY=y+(S+m.height/2),\"right\"===L.side?(Y.minX=g+M,Y.maxX=g+M+(2*S+m.width)):(Y.minX=g-M-(2*S+m.width),Y.maxX=g-M);var O,I=m.height/2,z=F-m.top-I,R=\"clip\"+i._uid+\"commonlabel\"+L._id;if(g=0?lt:ut+ht=0?ut:bt+ht=0?ot:st+pt=0?st:_t+pt=0,\"top\"!==t.idealAlign&&G||!Z?G?(O+=R/2,t.anchor=\"start\"):t.anchor=\"middle\":(O-=R/2,t.anchor=\"end\"),t.crossPos=O;else{if(t.pos=O,G=P+z/2+Y<=B,Z=P-z/2-Y>=0,\"left\"!==t.idealAlign&&G||!Z)if(G)P+=z/2,t.anchor=\"start\";else{t.anchor=\"middle\";var W=Y/2,X=P+W-B,J=P-W;X>0&&(P-=X),J<0&&(P+=-J)}else P-=z/2,t.anchor=\"end\";t.crossPos=P}w.attr(\"text-anchor\",t.anchor),E&&A.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",s(P,O)+(u?l(_):\"\"))})),{hoverLabels:wt,commonLabelBoundingBox:Y}}function I(t,e,r,n,i,a){var s=\"\",l=\"\";void 0!==t.nameOverride&&(t.name=t.nameOverride),t.name&&(t.trace._meta&&(t.name=o.templateString(t.name,t.trace._meta)),s=N(t.name,t.nameLength));var u=r.charAt(0),c=\"x\"===u?\"y\":\"x\";void 0!==t.zLabel?(void 0!==t.xLabel&&(l+=\"x: \"+t.xLabel+\"
\"),void 0!==t.yLabel&&(l+=\"y: \"+t.yLabel+\"
\"),\"choropleth\"!==t.trace.type&&\"choroplethmapbox\"!==t.trace.type&&(l+=(l?\"z: \":\"\")+t.zLabel)):e&&t[u+\"Label\"]===i?l=t[c+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&\"scattercarpet\"!==t.trace.type&&(l=t.yLabel):l=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",!t.text&&0!==t.text||Array.isArray(t.text)||(l+=(l?\"
\":\"\")+t.text),void 0!==t.extraText&&(l+=(l?\"
\":\"\")+t.extraText),a&&\"\"===l&&!t.hovertemplate&&(\"\"===s&&a.remove(),l=s);var f=t.hovertemplate||!1;if(f){var h=t.hovertemplateLabels||t;t[u+\"Label\"]!==i&&(h[u+\"other\"]=h[u+\"Val\"],h[u+\"otherLabel\"]=h[u+\"Label\"]),l=(l=o.hovertemplateString(f,h,n._d3locale,t.eventData[0]||{},t.trace._meta)).replace(P,(function(e,r){return s=N(r,t.nameLength),\"\"}))}return[l,s]}function D(t,e){var r=0,n=t.offset;return e&&(n*=-A,r=t.offset*k),{x:r,y:n}}function z(t,e,r,i){var a=function(t){return t*r},o=function(t){return t*i};t.each((function(t){var r=n.select(this);if(t.del)return r.remove();var i,s,l,u,f=r.select(\"text.nums\"),p=t.anchor,d=\"end\"===p?-1:1,v=(u=(l=(s={start:1,end:-1,middle:0}[(i=t).anchor])*(M+S))+s*(i.txwidth+S),\"middle\"===i.anchor&&(l-=i.tx2width/2,u+=i.txwidth/2+S),{alignShift:s,textShiftX:l,text2ShiftX:u}),g=D(t,e),y=g.x,m=g.y,x=\"middle\"===p;r.select(\"path\").attr(\"d\",x?\"M-\"+a(t.bx/2+t.tx2width/2)+\",\"+o(m-t.by/2)+\"h\"+a(t.bx)+\"v\"+o(t.by)+\"h-\"+a(t.bx)+\"Z\":\"M0,0L\"+a(d*M+y)+\",\"+o(M+m)+\"v\"+o(t.by/2-M)+\"h\"+a(d*t.bx)+\"v-\"+o(t.by)+\"H\"+a(d*M+y)+\"V\"+o(m-M)+\"Z\");var b=y+v.textShiftX,_=m+t.ty0-t.by/2+S,w=t.textAlign||\"auto\";\"auto\"!==w&&(\"left\"===w&&\"start\"!==p?(f.attr(\"text-anchor\",\"start\"),b=x?-t.bx/2-t.tx2width/2+S:-t.bx-S):\"right\"===w&&\"end\"!==p&&(f.attr(\"text-anchor\",\"end\"),b=x?t.bx/2-t.tx2width/2-S:t.bx+S)),f.call(c.positionText,a(b),o(_)),t.tx2width&&(r.select(\"text.name\").call(c.positionText,a(v.text2ShiftX+v.alignShift*S+y),o(m+t.ty0-t.by/2+S)),r.select(\"rect\").call(h.setRect,a(v.text2ShiftX+(v.alignShift-1)*t.tx2width/2+y),o(m-t.by/2-1),a(t.tx2width),o(t.by+2)))}))}function R(t,e){var r=t.index,n=t.trace||{},a=t.cd[0],s=t.cd[r]||{};function l(t){return t||i(t)&&0===t}var u=Array.isArray(r)?function(t,e){var i=o.castOption(a,r,t);return l(i)?i:o.extractOption({},n,\"\",e)}:function(t,e){return o.extractOption(s,n,t,e)};function c(e,r,n){var i=u(r,n);l(i)&&(t[e]=i)}if(c(\"hoverinfo\",\"hi\",\"hoverinfo\"),c(\"bgcolor\",\"hbg\",\"hoverlabel.bgcolor\"),c(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),c(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),c(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),c(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),c(\"nameLength\",\"hnl\",\"hoverlabel.namelength\"),c(\"textAlign\",\"hta\",\"hoverlabel.align\"),t.posref=\"y\"===e||\"closest\"===e&&\"h\"===n.orientation?t.xa._offset+(t.x0+t.x1)/2:t.ya._offset+(t.y0+t.y1)/2,t.x0=o.constrain(t.x0,0,t.xa._length),t.x1=o.constrain(t.x1,0,t.xa._length),t.y0=o.constrain(t.y0,0,t.ya._length),t.y1=o.constrain(t.y1,0,t.ya._length),void 0!==t.xLabelVal&&(t.xLabel=\"xLabel\"in t?t.xLabel:v.hoverLabelText(t.xa,t.xLabelVal,n.xhoverformat),t.xVal=t.xa.c2d(t.xLabelVal)),void 0!==t.yLabelVal&&(t.yLabel=\"yLabel\"in t?t.yLabel:v.hoverLabelText(t.ya,t.yLabelVal,n.yhoverformat),t.yVal=t.ya.c2d(t.yLabelVal)),void 0!==t.zLabelVal&&void 0===t.zLabel&&(t.zLabel=String(t.zLabelVal)),!(isNaN(t.xerr)||\"log\"===t.xa.type&&t.xerr<=0)){var f=v.tickText(t.xa,t.xa.c2l(t.xerr),\"hover\").text;void 0!==t.xerrneg?t.xLabel+=\" +\"+f+\" / -\"+v.tickText(t.xa,t.xa.c2l(t.xerrneg),\"hover\").text:t.xLabel+=\" ± \"+f,\"x\"===e&&(t.distance+=1)}if(!(isNaN(t.yerr)||\"log\"===t.ya.type&&t.yerr<=0)){var h=v.tickText(t.ya,t.ya.c2l(t.yerr),\"hover\").text;void 0!==t.yerrneg?t.yLabel+=\" +\"+h+\" / -\"+v.tickText(t.ya,t.ya.c2l(t.yerrneg),\"hover\").text:t.yLabel+=\" ± \"+h,\"y\"===e&&(t.distance+=1)}var p=t.hoverinfo||t.trace.hoverinfo;return p&&\"all\"!==p&&(-1===(p=Array.isArray(p)?p:p.split(\"+\")).indexOf(\"x\")&&(t.xLabel=void 0),-1===p.indexOf(\"y\")&&(t.yLabel=void 0),-1===p.indexOf(\"z\")&&(t.zLabel=void 0),-1===p.indexOf(\"text\")&&(t.text=void 0),-1===p.indexOf(\"name\")&&(t.name=void 0)),t}function F(t,e,r){var n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var d=p.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var g,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(g=u.pointerX,y=u.pointerY):(g=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,d)<1.5?p.contrast(d):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=v.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=g),-1!==w.indexOf(\"across\")){var M=i._counterDomainMin,S=i._counterDomainMax;\"free\"===i.anchor&&(M=Math.min(M,i.position),S=Math.max(S,i.position)),x=l.l+M*l.w,b=l.l+S*l.w}o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:y,y2:y,\"stroke-width\":T,stroke:k,\"stroke-dasharray\":h.dashStyle(i.spikedash,T)}).classed(\"spikeline\",!0).classed(\"crisp\",!0),o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:y,y2:y,\"stroke-width\":T+2,stroke:d}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}-1!==w.indexOf(\"marker\")&&o.insert(\"circle\",\":first-child\").attr({cx:A+(\"right\"!==i.side?T:-T),cy:y,r:T,fill:k}).classed(\"spikeline\",!0)}if(f){var E,L,C=e.vLinePoint;n=C&&C.xa,i=C&&C.ya,\"cursor\"===n.spikesnap?(E=u.pointerX,L=u.pointerY):(E=n._offset+C.x,L=i._offset+C.y);var 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n=r(64505).selectMode,i=r(51873).clearOutline,a=r(60165),o=a.readPaths,s=a.writePaths,l=a.fixDatesForPaths;t.exports=function(t,e){if(t.length){var r=t[0][0];if(r){var a=r.getAttribute(\"d\"),u=e.gd,c=u._fullLayout.newselection,f=e.plotinfo,h=f.xaxis,p=f.yaxis,d=e.isActiveSelection,v=e.dragmode,g=(u.layout||{}).selections||[];if(!n(v)&&void 0!==d){var y=u._fullLayout._activeSelectionIndex;if(y-1,b=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(y)){Z(t,e,a);var _=function(t,e){var r,n,i=t[0],a=-1,o=[];for(n=0;n0?function(t,e){var r,n,i,a=[];for(i=0;i0&&a.push(r);if(1===a.length&&a[0]===e.searchInfo&&(n=e.searchInfo.cd[0].trace).selectedpoints.length===e.pointNumbers.length){for(i=0;i1)return!1;if((n+=e.selectedpoints.length)>1)return!1}return 1===n}(s)&&(h=K(_))){for(o&&o.remove(),g=0;g=0})(i)&&i._fullLayout._deactivateShape(i),function(t){return t._fullLayout._activeSelectionIndex>=0}(i)&&i._fullLayout._deactivateSelection(i);var 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n=r(50215),i=r(41940),a=r(82196).line,o=r(79952).P,s=r(1426).extendFlat,l=r(44467).templatedArray,u=(r(24695),r(9012)),c=r(5386).R,f=r(37281);t.exports=l(\"shape\",{visible:s({},u.visible,{editType:\"calc+arraydraw\"}),showlegend:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},legend:s({},u.legend,{editType:\"calc+arraydraw\"}),legendgroup:s({},u.legendgroup,{editType:\"calc+arraydraw\"}),legendgrouptitle:{text:s({},u.legendgrouptitle.text,{editType:\"calc+arraydraw\"}),font:i({editType:\"calc+arraydraw\"}),editType:\"calc+arraydraw\"},legendrank:s({},u.legendrank,{editType:\"calc+arraydraw\"}),legendwidth:s({},u.legendwidth,{editType:\"calc+arraydraw\"}),type:{valType:\"enumerated\",values:[\"circle\",\"rect\",\"path\",\"line\"],editType:\"calc+arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},xref:s({},n.xref,{}),xsizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},xanchor:{valType:\"any\",editType:\"calc+arraydraw\"},x0:{valType:\"any\",editType:\"calc+arraydraw\"},x1:{valType:\"any\",editType:\"calc+arraydraw\"},yref:s({},n.yref,{}),ysizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},yanchor:{valType:\"any\",editType:\"calc+arraydraw\"},y0:{valType:\"any\",editType:\"calc+arraydraw\"},y1:{valType:\"any\",editType:\"calc+arraydraw\"},path:{valType:\"string\",editType:\"calc+arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},line:{color:s({},a.color,{editType:\"arraydraw\"}),width:s({},a.width,{editType:\"calc+arraydraw\"}),dash:s({},o,{editType:\"arraydraw\"}),editType:\"calc+arraydraw\"},fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},fillrule:{valType:\"enumerated\",values:[\"evenodd\",\"nonzero\"],dflt:\"evenodd\",editType:\"arraydraw\"},editable:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},label:{text:{valType:\"string\",dflt:\"\",editType:\"arraydraw\"},texttemplate:c({},{keys:Object.keys(f)}),font:i({editType:\"calc+arraydraw\",colorEditType:\"arraydraw\"}),textposition:{valType:\"enumerated\",values:[\"top 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e?e.d2l(t):t}function r(t,e){return e?e.l2d(t):t}function n(t,r){return e(t.x1,r)-e(t.x0,r)}function i(t,r,n){return e(t.y1,n)-e(t.y0,n)}t.exports={x0:function(t){return t.x0},x1:function(t){return t.x1},y0:function(t){return t.y0},y1:function(t){return t.y1},slope:function(t,e,r){return\"line\"!==t.type?void 0:i(t,0,r)/n(t,e)},dx:n,dy:i,width:function(t,e){return Math.abs(n(t,e))},height:function(t,e,r){return Math.abs(i(t,0,r))},length:function(t,e,r){return\"line\"!==t.type?void 0:Math.sqrt(Math.pow(n(t,e),2)+Math.pow(i(t,0,r),2))},xcenter:function(t,n){return r((e(t.x1,n)+e(t.x0,n))/2,n)},ycenter:function(t,n,i){return r((e(t.y1,i)+e(t.y0,i))/2,i)}}},75067:function(t,e,r){\"use strict\";var n=r(41940),i=r(35025),a=r(1426).extendDeepAll,o=r(30962).overrideAll,s=r(85594),l=r(44467).templatedArray,u=r(98292),c=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:c,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:u.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:u.railBgColor},bordercolor:{valType:\"color\",dflt:u.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:u.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:u.tickLength},tickcolor:{valType:\"color\",dflt:u.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:u.minorTickLength}}),\"arraydraw\",\"from-root\")},98292:function(t){\"use strict\";t.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},12343:function(t,e,r){\"use 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r=e._dims,n=r.inputAreaLength-2*f.railInset,i=s.ensureSingle(t,\"rect\",f.railRectClass);i.attr({width:n,height:f.railWidth,rx:f.railRadius,ry:f.railRadius,\"shape-rendering\":\"crispEdges\"}).call(a.stroke,e.bordercolor).call(a.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\"),o.setTranslate(i,f.railInset,.5*(r.inputAreaWidth-f.railWidth)+r.currentValueTotalHeight)}t.exports=function(t){var e=t._context.staticPlot,r=t._fullLayout,a=function(t,e){for(var r=t[f.name],n=[],i=0;i0?[0]:[]);function l(e){e._commandObserver&&(e._commandObserver.remove(),delete e._commandObserver),i.autoMargin(t,g(e))}if(s.enter().append(\"g\").classed(f.containerClassName,!0).style(\"cursor\",e?null:\"ew-resize\"),s.exit().each((function(){n.select(this).selectAll(\"g.\"+f.groupClassName).each(l)})).remove(),0!==a.length){var u=s.selectAll(\"g.\"+f.groupClassName).data(a,y);u.enter().append(\"g\").classed(f.groupClassName,!0),u.exit().each(l).remove();for(var c=0;c0||_<0){var M={left:[-w,0],right:[w,0],top:[0,-w],bottom:[0,w]}[b.side];r.attr(\"transform\",l(M[0],M[1]))}}}return R.call(F),I&&(E?R.on(\".opacity\",null):(A=0,M=!0,R.text(m).on(\"mouseover.opacity\",(function(){n.select(this).transition().duration(h.SHOW_PLACEHOLDER).style(\"opacity\",1)})).on(\"mouseout.opacity\",(function(){n.select(this).transition().duration(h.HIDE_PLACEHOLDER).style(\"opacity\",0)}))),R.call(f.makeEditable,{gd:t}).on(\"edit\",(function(e){void 0!==x?o.call(\"_guiRestyle\",t,y,e,x):o.call(\"_guiRelayout\",t,y,e)})).on(\"cancel\",(function(){this.text(this.attr(\"data-unformatted\")).call(F)})).on(\"input\",(function(t){this.text(t||\" \").call(f.positionText,_.x,_.y)}))),R.classed(\"js-placeholder\",M),T}}},7163:function(t,e,r){\"use strict\";var n=r(41940),i=r(22399),a=r(1426).extendFlat,o=r(30962).overrideAll,s=r(35025),l=r(44467).templatedArray,u=l(\"button\",{visible:{valType:\"boolean\"},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},args2:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\",dflt:\"\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"updatemenu\",{_arrayAttrRegexps:[/^updatemenus\\[(0|[1-9][0-9]+)\\]\\.buttons/],visible:{valType:\"boolean\"},type:{valType:\"enumerated\",values:[\"dropdown\",\"buttons\"],dflt:\"dropdown\"},direction:{valType:\"enumerated\",values:[\"left\",\"right\",\"up\",\"down\"],dflt:\"down\"},active:{valType:\"integer\",min:-1,dflt:0},showactive:{valType:\"boolean\",dflt:!0},buttons:u,x:{valType:\"number\",min:-2,max:3,dflt:-.05},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"right\"},y:{valType:\"number\",min:-2,max:3,dflt:1},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},pad:a(s({editType:\"arraydraw\"}),{}),font:n({}),bgcolor:{valType:\"color\"},bordercolor:{valType:\"color\",dflt:i.borderLine},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"arraydraw\"}}),\"arraydraw\",\"from-root\")},75909:function(t){\"use strict\";t.exports={name:\"updatemenus\",containerClassName:\"updatemenu-container\",headerGroupClassName:\"updatemenu-header-group\",headerClassName:\"updatemenu-header\",headerArrowClassName:\"updatemenu-header-arrow\",dropdownButtonGroupClassName:\"updatemenu-dropdown-button-group\",dropdownButtonClassName:\"updatemenu-dropdown-button\",buttonClassName:\"updatemenu-button\",itemRectClassName:\"updatemenu-item-rect\",itemTextClassName:\"updatemenu-item-text\",menuIndexAttrName:\"updatemenu-active-index\",autoMarginIdRoot:\"updatemenu-\",blankHeaderOpts:{label:\" \"},minWidth:30,minHeight:30,textPadX:24,arrowPadX:16,rx:2,ry:2,textOffsetX:12,textOffsetY:3,arrowOffsetX:4,gapButtonHeader:5,gapButton:2,activeColor:\"#F4FAFF\",hoverColor:\"#F4FAFF\",arrowSymbol:{left:\"◄\",right:\"►\",up:\"▲\",down:\"▼\"}}},64897:function(t,e,r){\"use strict\";var n=r(71828),i=r(85501),a=r(7163),o=r(75909).name,s=a.buttons;function l(t,e,r){function o(r,i){return n.coerce(t,e,a,r,i)}o(\"visible\",i(t,e,{name:\"buttons\",handleItemDefaults:u}).length>0)&&(o(\"active\"),o(\"direction\"),o(\"type\"),o(\"showactive\"),o(\"x\"),o(\"y\"),n.noneOrAll(t,e,[\"x\",\"y\"]),o(\"xanchor\"),o(\"yanchor\"),o(\"pad.t\"),o(\"pad.r\"),o(\"pad.b\"),o(\"pad.l\"),n.coerceFont(o,\"font\",r.font),o(\"bgcolor\",r.paper_bgcolor),o(\"bordercolor\"),o(\"borderwidth\"))}function u(t,e){function r(r,i){return n.coerce(t,e,s,r,i)}r(\"visible\",\"skip\"===t.method||Array.isArray(t.args))&&(r(\"method\"),r(\"args\"),r(\"args2\"),r(\"label\"),r(\"execute\"))}t.exports=function(t,e){i(t,e,{name:o,handleItemDefaults:l})}},13689:function(t,e,r){\"use strict\";var n=r(39898),i=r(74875),a=r(7901),o=r(91424),s=r(71828),l=r(63893),u=r(44467).arrayEditor,c=r(18783).LINE_SPACING,f=r(75909),h=r(25849);function p(t){return t._index}function d(t,e){return+t.attr(f.menuIndexAttrName)===e._index}function v(t,e,r,n,i,a,o,s){e.active=o,u(t.layout,f.name,e).applyUpdate(\"active\",o),\"buttons\"===e.type?y(t,n,null,null,e):\"dropdown\"===e.type&&(i.attr(f.menuIndexAttrName,\"-1\"),g(t,n,i,a,e),s||y(t,n,i,a,e))}function g(t,e,r,n,i){var a=s.ensureSingle(e,\"g\",f.headerClassName,(function(t){t.style(\"pointer-events\",\"all\")})),l=i._dims,u=i.active,c=i.buttons[u]||f.blankHeaderOpts,h={y:i.pad.t,yPad:0,x:i.pad.l,xPad:0,index:0},p={width:l.headerWidth,height:l.headerHeight};a.call(m,i,c,t).call(M,i,h,p),s.ensureSingle(e,\"text\",f.headerArrowClassName,(function(t){t.attr(\"text-anchor\",\"end\").call(o.font,i.font).text(f.arrowSymbol[i.direction])})).attr({x:l.headerWidth-f.arrowOffsetX+i.pad.l,y:l.headerHeight/2+f.textOffsetY+i.pad.t}),a.on(\"click\",(function(){r.call(S,String(d(r,i)?-1:i._index)),y(t,e,r,n,i)})),a.on(\"mouseover\",(function(){a.call(w)})),a.on(\"mouseout\",(function(){a.call(T,i)})),o.setTranslate(e,l.lx,l.ly)}function y(t,e,r,a,o){r||(r=e).attr(\"pointer-events\",\"all\");var l=function(t){return-1==+t.attr(f.menuIndexAttrName)}(r)&&\"buttons\"!==o.type?[]:o.buttons,u=\"dropdown\"===o.type?f.dropdownButtonClassName:f.buttonClassName,c=r.selectAll(\"g.\"+u).data(s.filterVisible(l)),h=c.enter().append(\"g\").classed(u,!0),p=c.exit();\"dropdown\"===o.type?(h.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),p.transition().attr(\"opacity\",\"0\").remove()):p.remove();var d=0,g=0,y=o._dims,x=-1!==[\"up\",\"down\"].indexOf(o.direction);\"dropdown\"===o.type&&(x?g=y.headerHeight+f.gapButtonHeader:d=y.headerWidth+f.gapButtonHeader),\"dropdown\"===o.type&&\"up\"===o.direction&&(g=-f.gapButtonHeader+f.gapButton-y.openHeight),\"dropdown\"===o.type&&\"left\"===o.direction&&(d=-f.gapButtonHeader+f.gapButton-y.openWidth);var b={x:y.lx+d+o.pad.l,y:y.ly+g+o.pad.t,yPad:f.gapButton,xPad:f.gapButton,index:0},k={l:b.x+o.borderwidth,t:b.y+o.borderwidth};c.each((function(s,l){var u=n.select(this);u.call(m,o,s,t).call(M,o,b),u.on(\"click\",(function(){n.event.defaultPrevented||(s.execute&&(s.args2&&o.active===l?(v(t,o,0,e,r,a,-1),i.executeAPICommand(t,s.method,s.args2)):(v(t,o,0,e,r,a,l),i.executeAPICommand(t,s.method,s.args))),t.emit(\"plotly_buttonclicked\",{menu:o,button:s,active:o.active}))})),u.on(\"mouseover\",(function(){u.call(w)})),u.on(\"mouseout\",(function(){u.call(T,o),c.call(_,o)}))})),c.call(_,o),x?(k.w=Math.max(y.openWidth,y.headerWidth),k.h=b.y-k.t):(k.w=b.x-k.l,k.h=Math.max(y.openHeight,y.headerHeight)),k.direction=o.direction,a&&(c.size()?function(t,e,r,n,i,a){var o,s,l,u=i.direction,c=\"up\"===u||\"down\"===u,h=i._dims,p=i.active;if(c)for(s=0,l=0;l0?[0]:[]);if(o.enter().append(\"g\").classed(f.containerClassName,!0).style(\"cursor\",\"pointer\"),o.exit().each((function(){n.select(this).selectAll(\"g.\"+f.headerGroupClassName).each(a)})).remove(),0!==r.length){var l=o.selectAll(\"g.\"+f.headerGroupClassName).data(r,p);l.enter().append(\"g\").classed(f.headerGroupClassName,!0);for(var u=s.ensureSingle(o,\"g\",f.dropdownButtonGroupClassName,(function(t){t.style(\"pointer-events\",\"all\")})),c=0;cw,A=s.barLength+2*s.barPad,M=s.barWidth+2*s.barPad,S=d,E=g+y;E+M>u&&(E=u-M);var L=this.container.selectAll(\"rect.scrollbar-horizontal\").data(k?[0]:[]);L.exit().on(\".drag\",null).remove(),L.enter().append(\"rect\").classed(\"scrollbar-horizontal\",!0).call(i.fill,s.barColor),k?(this.hbar=L.attr({rx:s.barRadius,ry:s.barRadius,x:S,y:E,width:A,height:M}),this._hbarXMin=S+A/2,this._hbarTranslateMax=w-A):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var C=y>T,P=s.barWidth+2*s.barPad,O=s.barLength+2*s.barPad,I=d+v,D=g;I+P>l&&(I=l-P);var z=this.container.selectAll(\"rect.scrollbar-vertical\").data(C?[0]:[]);z.exit().on(\".drag\",null).remove(),z.enter().append(\"rect\").classed(\"scrollbar-vertical\",!0).call(i.fill,s.barColor),C?(this.vbar=z.attr({rx:s.barRadius,ry:s.barRadius,x:I,y:D,width:P,height:O}),this._vbarYMin=D+O/2,this._vbarTranslateMax=T-O):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var R=this.id,F=c-.5,B=C?f+P+.5:f+.5,N=h-.5,j=k?p+M+.5:p+.5,U=o._topdefs.selectAll(\"#\"+R).data(k||C?[0]:[]);if(U.exit().remove(),U.enter().append(\"clipPath\").attr(\"id\",R).append(\"rect\"),k||C?(this._clipRect=U.select(\"rect\").attr({x:Math.floor(F),y:Math.floor(N),width:Math.ceil(B)-Math.floor(F),height:Math.ceil(j)-Math.floor(N)}),this.container.call(a.setClipUrl,R,this.gd),this.bg.attr({x:d,y:g,width:v,height:y})):(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),k||C){var 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c=s.simpleMap(t.range,t.r2l);if(t._isMinor&&(e*=1.5),e>.7)t.dtick=Math.ceil(e);else if(Math.abs(c[1]-c[0])<1){var f=1.5*Math.abs((c[1]-c[0])/e);e=Math.abs(Math.pow(10,c[1])-Math.pow(10,c[0]))/f,n=a(10),t.dtick=\"L\"+dt(e,n,st)}else t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):Dt(t)?(t.tick0=0,n=1,t.dtick=dt(e,n,pt)):(t.tick0=0,n=a(10),t.dtick=dt(e,n,st));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var h=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(h)}},q.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),u=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,u,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+u)/Math.LN10;if(\"D\"===l){var c=\"D2\"===e?ht:ft,f=t+.01*o,h=s.roundUp(s.mod(f,1),c,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick 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u=t.side,c=l?(t.tickwidth||0)/2:0,f=3,h=t.tickfont?t.tickfont.size:12;return(o||n)&&(c+=h*U,f+=(t.linewidth||0)/2),(i||a)&&(c+=(t.linewidth||0)/2,f+=3),s&&\"top\"===u&&(f-=h*(1-U)),(i||n)&&(c=-c),\"bottom\"!==u&&\"right\"!==u||(f=-f),[l?c:0,s?f:0]}(t),r=e[0],n=e[1];return\"x\"===t._id.charAt(0)?function(e){return l(r+t._offset+t.l2p(Tt(e)),n)}:function(e){return l(n,r+t._offset+t.l2p(Tt(e)))}},q.makeTickPath=function(t,e,r,n){n||(n={});var i=n.minor;if(i&&!t.minor)return\"\";var a=void 0!==n.len?n.len:i?t.minor.ticklen:t.ticklen,o=t._id.charAt(0),s=(t.linewidth||1)/2;return\"x\"===o?\"M0,\"+(e+s*r)+\"v\"+a*r:\"M\"+(e+s*r)+\",0h\"+a*r},q.makeLabelFns=function(t,e,r){var n=t.ticklabelposition||\"\",a=function(t){return-1!==n.indexOf(t)},o=a(\"top\"),l=a(\"left\"),u=a(\"right\"),c=a(\"bottom\")||l||o||u,f=a(\"inside\"),h=\"inside\"===n&&\"inside\"===t.ticks||!f&&\"outside\"===t.ticks&&\"boundaries\"!==t.tickson,p=0,d=0,v=h?t.ticklen:0;if(f?v*=-1:c&&(v=0),h&&(p+=v,r)){var 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e.projection.rotation.lon))}t.exports=function(t,e,r){i(t,e,r,{type:\"geo\",attributes:s,handleDefaults:u,fullData:r,partition:\"y\"})}},74455:function(t,e,r){\"use strict\";var n=r(39898),i=r(71828),a=r(73972),o=Math.PI/180,s=180/Math.PI,l={cursor:\"pointer\"},u={cursor:\"auto\"};function c(t,e){return n.behavior.zoom().translate(e.translate()).scale(e.scale())}function f(t,e,r){var n=t.id,o=t.graphDiv,s=o.layout,l=s[n],u=o._fullLayout,c=u[n],f={},h={};function p(t,e){f[n+\".\"+t]=i.nestedProperty(l,t).get(),a.call(\"_storeDirectGUIEdit\",s,u._preGUI,f);var r=i.nestedProperty(c,t);r.get()!==e&&(r.set(e),i.nestedProperty(l,t).set(e),h[n+\".\"+t]=e)}r(p),p(\"projection.scale\",e.scale()/t.fitScale),p(\"fitbounds\",!1),o.emit(\"plotly_relayout\",h)}function h(t,e){var r=c(0,e);function i(r){var n=e.invert(t.midPt);r(\"center.lon\",n[0]),r(\"center.lat\",n[1])}return r.on(\"zoomstart\",(function(){n.select(this).style(l)})).on(\"zoom\",(function(){e.scale(n.event.scale).translate(n.event.translate),t.render(!0);var r=e.invert(t.midPt);t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.center.lon\":r[0],\"geo.center.lat\":r[1]})})).on(\"zoomend\",(function(){n.select(this).style(u),f(t,e,i)})),r}function p(t,e){var r,i,a,o,s,h,p,d,v,g=c(0,e);function y(t){return e.invert(t)}function m(r){var n=e.rotate(),i=e.invert(t.midPt);r(\"projection.rotation.lon\",-n[0]),r(\"center.lon\",i[0]),r(\"center.lat\",i[1])}return g.on(\"zoomstart\",(function(){n.select(this).style(l),r=n.mouse(this),i=e.rotate(),a=e.translate(),o=i,s=y(r)})).on(\"zoom\",(function(){if(h=n.mouse(this),function(t){var r=y(t);if(!r)return!0;var n=e(r);return Math.abs(n[0]-t[0])>2||Math.abs(n[1]-t[1])>2}(r))return g.scale(e.scale()),void g.translate(e.translate());e.scale(n.event.scale),e.translate([a[0],n.event.translate[1]]),s?y(h)&&(d=y(h),p=[o[0]+(d[0]-s[0]),i[1],i[2]],e.rotate(p),o=p):s=y(r=h),v=!0,t.render(!0);var l=e.rotate(),u=e.invert(t.midPt);t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.center.lon\":u[0],\"geo.center.lat\":u[1],\"geo.projection.rotation.lon\":-l[0]})})).on(\"zoomend\",(function(){n.select(this).style(u),v&&f(t,e,m)})),g}function d(t,e){var r,i={r:e.rotate(),k:e.scale()},a=c(0,e),h=function(t){for(var e=0,r=arguments.length,i=[];++ed?(a=(f>0?90:-90)-p,i=0):(a=Math.asin(f/d)*s-p,i=Math.sqrt(d*d-f*f));var v=180-a-2*p,y=(Math.atan2(h,c)-Math.atan2(u,i))*s,x=(Math.atan2(h,c)-Math.atan2(u,-i))*s;return g(r[0],r[1],a,y)<=g(r[0],r[1],v,x)?[a,y,r[2]]:[v,x,r[2]]}(T,r,E);isFinite(k[0])&&isFinite(k[1])&&isFinite(k[2])||(k=E),e.rotate(k),E=k}}else r=v(e,M=b);h.of(this,arguments)({type:\"zoom\"})})),A=h.of(this,arguments),p++||A({type:\"zoomstart\"})})).on(\"zoomend\",(function(){var r;n.select(this).style(u),d.call(a,\"zoom\",null),r=h.of(this,arguments),--p||r({type:\"zoomend\"}),f(t,e,y)})).on(\"zoom.redraw\",(function(){t.render(!0);var r=e.rotate();t.graphDiv.emit(\"plotly_relayouting\",{\"geo.projection.scale\":e.scale()/t.fitScale,\"geo.projection.rotation.lon\":-r[0],\"geo.projection.rotation.lat\":-r[1]})})),n.rebind(a,h,\"on\")}function v(t,e){var r=t.invert(e);return r&&isFinite(r[0])&&isFinite(r[1])&&function(t){var e=t[0]*o,r=t[1]*o,n=Math.cos(r);return[n*Math.cos(e),n*Math.sin(e),Math.sin(r)]}(r)}function g(t,e,r,n){var i=y(r-t),a=y(n-e);return Math.sqrt(i*i+a*a)}function y(t){return(t%360+540)%360-180}function m(t,e,r){var n=r*o,i=t.slice(),a=0===e?1:0,s=2===e?1:2,l=Math.cos(n),u=Math.sin(n);return i[a]=t[a]*l-t[s]*u,i[s]=t[s]*l+t[a]*u,i}function x(t,e){for(var r=0,n=0,i=t.length;nMath.abs(s)?(u.boxEnd[1]=u.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),u.boxEnd[1]l[3]&&(u.boxEnd[1]=l[3],u.boxEnd[0]=u.boxStart[0]+(l[3]-u.boxStart[1])/Math.abs(_))):(u.boxEnd[0]=u.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),u.boxEnd[0]l[2]&&(u.boxEnd[0]=l[2],u.boxEnd[1]=u.boxStart[1]+(l[2]-u.boxStart[0])*Math.abs(_)))}}else u.boxEnabled?(a=u.boxStart[0]!==u.boxEnd[0],s=u.boxStart[1]!==u.boxEnd[1],a||s?(a&&(g(0,u.boxStart[0],u.boxEnd[0]),t.xaxis.autorange=!1),s&&(g(1,u.boxStart[1],u.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),u.boxEnabled=!1,u.boxInited=!1):u.boxInited&&(u.boxInited=!1);break;case\"pan\":u.boxEnabled=!1,u.boxInited=!1,e?(u.panning||(u.dragStart[0]=n,u.dragStart[1]=i),Math.abs(u.dragStart[0]-n).999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},65500:function(t,e,r){\"use strict\";var n=r(77894),i=r(27670).Y,a=r(1426).extendFlat,o=r(71828).counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}t.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 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r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},96085:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d/g,\" 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a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,h=e.glplot.selection,v=0;v\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),h.textLabel&&E.push(h.textLabel),x=E.join(\"
\")):x=h.textLabel;var L={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(L,w,T),t._module.eventData&&(L=w._module.eventData(L,h,w,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:w,x:(.5+.5*m[0]/m[3])*s,y:(.5-.5*m[1]/m[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:x,name:c.name,color:d.castHoverOption(w,T,\"bgcolor\")||c.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}h.distance<5&&(h.buttons||_)?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),this.oldEventData=C}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},T.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var A=[\"xaxis\",\"yaxis\",\"zaxis\"];function M(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=A[i],o=a.charAt(0),s=n[a],l=e[o],u=e[o+\"calendar\"],c=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(c||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;dy[1][o])y[0][o]=-1,y[1][o]=1;else{var C=y[1][o]-y[0][o];y[0][o]-=C/32,y[1][o]+=C/32}if(\"reversed\"===l.autorange){var P=y[0][o];y[0][o]=y[1][o],y[1][o]=P}}else{var O=l.range;y[0][o]=l.r2l(O[0]),y[1][o]=l.r2l(O[1])}y[0][o]===y[1][o]&&(y[0][o]-=1,y[1][o]+=1),m[o]=y[1][o]-y[0][o],n.glplot.setBounds(o,{min:y[0][o]*p[o],max:y[1][o]*p[o]})}var I=c.aspectmode;if(\"cube\"===I)g=[1,1,1];else if(\"manual\"===I){var D=c.aspectratio;g=[D.x,D.y,D.z]}else{if(\"auto\"!==I&&\"data\"!==I)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var z=[1,1,1];for(o=0;o<3;++o){var R=x[u=(l=c[A[o]]).type];z[o]=Math.pow(R.acc,1/R.count)/p[o]}g=\"data\"===I||Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1]}c.aspectratio.x=f.aspectratio.x=g[0],c.aspectratio.y=f.aspectratio.y=g[1],c.aspectratio.z=f.aspectratio.z=g[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var F=c.domain||null,B=e._size||null;if(F&&B){var N=n.container.style;N.position=\"absolute\",N.left=B.l+F.x[0]*B.w+\"px\",N.top=B.t+(1-F.y[1])*B.h+\"px\",N.width=B.w*(F.x[1]-F.x[0])+\"px\",N.height=B.h*(F.y[1]-F.y[0])+\"px\"}n.glplot.redraw()}},T.destroy=function(){var t=this;t.glplot&&(t.camera.mouseListener.enabled=!1,t.container.removeEventListener(\"wheel\",t.camera.wheelListener),t.camera=null,t.glplot.dispose(),t.container.parentNode.removeChild(t.container),t.glplot=null)},T.getCamera=function(){var t,e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),{up:{x:(t=e.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},T.setViewport=function(t){var e,r=this,n=t.camera;r.camera.lookAt.apply(this,[[(e=n).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),r.glplot.setAspectratio(t.aspectratio),\"orthographic\"===n.projection.type!==r.camera._ortho&&(r.glplot.redraw(),r.glplot.clearRGBA(),r.glplot.dispose(),r.initializeGLPlot())},T.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},T.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},T.saveLayout=function(t){var e,r,n,i,a,o,s=this,l=s.fullLayout,u=s.isCameraChanged(t),h=s.isAspectChanged(t),p=u||h;if(p){var d={};u&&(e=s.getCamera(),n=(r=f.nestedProperty(t,s.id+\".camera\")).get(),d[s.id+\".camera\"]=n),h&&(i=s.glplot.getAspectratio(),o=(a=f.nestedProperty(t,s.id+\".aspectratio\")).get(),d[s.id+\".aspectratio\"]=o),c.call(\"_storeDirectGUIEdit\",t,l._preGUI,d),u&&(r.set(e),f.nestedProperty(l,s.id+\".camera\").set(e)),h&&(a.set(i),f.nestedProperty(l,s.id+\".aspectratio\").set(i),s.glplot.redraw())}return p},T.updateFx=function(t,e){var r=this,n=r.camera;if(n)if(\"orbit\"===t)n.mode=\"orbit\",n.keyBindingMode=\"rotate\";else if(\"turntable\"===t){n.up=[0,0,1],n.mode=\"turntable\",n.keyBindingMode=\"rotate\";var i=r.graphDiv,a=i._fullLayout,o=r.fullSceneLayout.camera,s=o.up.x,l=o.up.y,u=o.up.z;if(u/Math.sqrt(s*s+l*l+u*u)<.999){var h=r.id+\".camera.up\",p={x:0,y:0,z:1},d={};d[h]=p;var v=i.layout;c.call(\"_storeDirectGUIEdit\",v,a._preGUI,d),o.up=p,f.nestedProperty(v,h).set(p)}}else n.keyBindingMode=t;r.fullSceneLayout.hovermode=e},T.toImage=function(t){var e=this;t||(t=\"png\"),e.staticMode&&e.container.appendChild(n),e.glplot.redraw();var r=e.glplot.gl,i=r.drawingBufferWidth,a=r.drawingBufferHeight;r.bindFramebuffer(r.FRAMEBUFFER,null);var o=new Uint8Array(i*a*4);r.readPixels(0,0,i,a,r.RGBA,r.UNSIGNED_BYTE,o),function(t,e,r){for(var n=0,i=r-1;n0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(o,i,a);var s=document.createElement(\"canvas\");s.width=i,s.height=a;var l,u=s.getContext(\"2d\",{willReadFrequently:!0}),c=u.createImageData(i,a);switch(c.data.set(o),u.putImageData(c,0,0),t){case\"jpeg\":l=s.toDataURL(\"image/jpeg\");break;case\"webp\":l=s.toDataURL(\"image/webp\");break;default:l=s.toDataURL(\"image/png\")}return e.staticMode&&e.container.removeChild(n),l},T.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[A[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},T.make4thDimension=function(){var t=this,e=t.graphDiv._fullLayout;t._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(t._mockAxis,e)},t.exports=w},90060:function(t){\"use strict\";t.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;aOpenStreetMap contributors',o=['© Carto',a].join(\" \"),s=['Map tiles by Stamen Design','under CC BY 3.0',\"|\",'Data by OpenStreetMap contributors','under ODbL'].join(\" 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n=r(44517),i=r(71828),a=i.strTranslate,o=i.strScale,s=r(27659).AU,l=r(77922),u=r(39898),c=r(91424),f=r(63893),h=r(10481),p=\"mapbox\",d=e.constants=r(77734);function v(t){return\"string\"==typeof t&&(-1!==d.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}e.name=p,e.attr=\"subplot\",e.idRoot=p,e.idRegex=e.attrRegex=i.counterRegex(p),e.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},e.layoutAttributes=r(23585),e.supplyLayoutDefaults=r(77882),e.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots[p];if(n.version!==d.requiredVersion)throw new Error(d.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l1&&i.warn(d.multipleTokensErrorMsg),n[0]):(a.length&&i.log([\"Listed mapbox access token(s)\",a.join(\",\"),\"but did not use a Mapbox map style, ignoring token(s).\"].join(\" \")),\"\")}(t,a);n.accessToken=o;for(var l=0;lw/2){var T=m.split(\"|\").join(\"
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i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=u(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,u(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};return\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates),a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution)),a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r1)for(r=0;r-1&&g(e.originalEvent,n,[r.xaxis],[r.yaxis],r.id,t),i.indexOf(\"event\")>-1&&u.click(n,e.originalEvent)}}},b.updateFx=function(t){var e=this,r=e.map,n=e.gd;if(!e.isStatic){var a,o=t.dragmode;a=function(t,r){r.isRect?(t.range={})[e.id]=[u([r.xmin,r.ymin]),u([r.xmax,r.ymax])]:(t.lassoPoints={})[e.id]=r.map(u)};var s=e.dragOptions;e.dragOptions=i.extendDeep(s||{},{dragmode:t.dragmode,element:e.div,gd:n,plotinfo:{id:e.id,domain:t[e.id].domain,xaxis:e.xaxis,yaxis:e.yaxis,fillRangeItems:a},xaxes:[e.xaxis],yaxes:[e.yaxis],subplot:e.id}),r.off(\"click\",e.onClickInPanHandler),h(o)||f(o)?(r.dragPan.disable(),r.on(\"zoomstart\",e.clearOutline),e.dragOptions.prepFn=function(t,r,n){p(t,r,n,e.dragOptions,o)},l.init(e.dragOptions)):(r.dragPan.enable(),r.off(\"zoomstart\",e.clearOutline),e.div.onmousedown=null,e.div.ontouchstart=null,e.div.removeEventListener(\"touchstart\",e.div._ontouchstart),e.onClickInPanHandler=e.onClickInPanFn(e.dragOptions),r.on(\"click\",e.onClickInPanHandler))}function u(t){var r=e.map.unproject(t);return[r.lng,r.lat]}},b.updateFramework=function(t){var 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e,r,s=this,u=s.isSmith,c=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,v=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,O=E.clampTiny,I=E.findXYatLength,D=E.findEnclosingVertexAngles,z=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){m.hover(c,t,s.id),c._fullLayout._lasthover=F,c._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){c._dragging||y.unhover(c,t)};var B,N,j,U,V,H,q,G,Z,Y={element:F,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function W(t,e){return Math.sqrt(t*t+e*e)}function X(t,e){return W(t-A,e-M)}function J(t,e){return Math.atan2(M-e,t-A)}function K(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function $(t,e){if(0===t)return s.pathSector(2*z);var r=R/t,n=e-r,i=e+r,a=Math.max(0,Math.min(t,v)),o=a-z,l=a+z;return\"M\"+K(o,n)+\"A\"+[o,o]+\" 0,0,0 \"+K(o,i)+\"L\"+K(l,i)+\"A\"+[l,l]+\" 0,0,1 \"+K(l,n)+\"Z\"}function Q(t,e,r){if(0===t)return s.pathSector(2*z);var n,i,a=K(t,e),o=K(t,r),l=O((a[0]+o[0])/2),u=O((a[1]+o[1])/2);if(l&&u){var c=u/l,f=-1/c,h=I(z,c,l,u);n=I(R,f,h[0][0],h[0][1]),i=I(R,f,h[1][0],h[1][1])}else{var p,d;u?(p=R,d=z):(p=z,d=R),n=[[l-p,u-d],[l+p,u-d]],i=[[l-p,u+d],[l+p,u+d]]}return\"M\"+n.join(\"L\")+\"L\"+i.reverse().join(\"L\")+\"Z\"}function tt(t,e){return e=Math.max(Math.min(e,v),x),tp?(t-1&&1===t&&_(e,c,[s.xaxis],[s.yaxis],s.id,Y),r.indexOf(\"event\")>-1&&m.click(c,e,s.id)}Y.prepFn=function(t,n,a){var l=c._fullLayout.dragmode,f=F.getBoundingClientRect();c._fullLayout._calcInverseTransform(c);var p=c._fullLayout._invTransform;e=c._fullLayout._invScaleX,r=c._fullLayout._invScaleY;var d=o.apply3DTransform(p)(n-f.left,a-f.top);if(B=d[0],N=d[1],C){var y=E.findPolygonOffset(v,L[0],L[1],C);B+=A+y[0],N+=M+y[1]}switch(l){case\"zoom\":Y.clickFn=st,u||(Y.moveFn=C?it:rt,Y.doneFn=at,function(){j=null,U=null,V=s.pathSubplot(),H=!1;var t=c._fullLayout[s.id];q=i(t.bgcolor).getLuminance(),(G=g.makeZoombox(h,q,T,k,V)).attr(\"fill-rule\",\"evenodd\"),Z=g.makeCorners(h,T,k),w(c)}());break;case\"select\":case\"lasso\":b(t,n,a,Y,l)}},y.init(Y)},N.updateRadialDrag=function(t,e,r){var i=this,u=i.gd,c=i.layers,f=i.radius,h=i.innerRadius,p=i.cx,d=i.cy,v=i.radialAxis,m=S.radialDragBoxSize,x=m/2;if(v.visible){var b,_,T,M=R(i.radialAxisAngle),E=v._rl,L=E[0],C=E[1],P=E[r],O=.75*(E[1]-E[0])/(1-i.getHole(e))/f;r?(b=p+(f+x)*Math.cos(M),_=d-(f+x)*Math.sin(M),T=\"radialdrag\"):(b=p+(h-x)*Math.cos(M),_=d-(h-x)*Math.sin(M),T=\"radialdrag-inner\");var I,D,z,B=g.makeRectDragger(c,T,\"crosshair\",-x,-x,m,m),N={element:B,gd:u};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),v.visible&&h0==(r?z>L:zn?function(t){return t<=0}:function(t){return t>=0};t.c2g=function(r){var n=t.c2l(r)-e;return(s(n)?n:0)+o},t.g2c=function(r){return t.l2c(r+e-o)},t.g2p=function(t){return t*a},t.c2p=function(e){return t.g2p(t.c2g(e))}}}(t,e);break;case\"angularaxis\":!function(t,e){var r=t.type;if(\"linear\"===r){var i=t.d2c,s=t.c2d;t.d2c=function(t,e){return function(t,e){return\"degrees\"===e?a(t):t}(i(t),e)},t.c2d=function(t,e){return s(function(t,e){return\"degrees\"===e?o(t):t}(t,e))}}t.makeCalcdata=function(e,i){var a,o,s=e[i],l=e._length,u=function(r){return t.d2c(r,e.thetaunit)};if(s){if(n.isTypedArray(s)&&\"linear\"===r){if(l===s.length)return s;if(s.subarray)return s.subarray(0,l)}for(a=new Array(l),o=0;o0?1:0}function r(t){var e=t[0],r=t[1];if(!isFinite(e)||!isFinite(r))return[1,0];var n=(e+1)*(e+1)+r*r;return[(e*e+r*r-1)/n,2*r/n]}function n(t,e){var r=e[0],n=e[1];return[r*t.radius+t.cx,-n*t.radius+t.cy]}function i(t,e){return e*t.radius}t.exports={smith:r,reactanceArc:function(t,e,a,o){var s=n(t,r([a,e])),l=s[0],u=s[1],c=n(t,r([o,e])),f=c[0],h=c[1];if(0===e)return[\"M\"+l+\",\"+u,\"L\"+f+\",\"+h].join(\" \");var p=i(t,1/Math.abs(e));return[\"M\"+l+\",\"+u,\"A\"+p+\",\"+p+\" 0 0,\"+(e<0?1:0)+\" \"+f+\",\"+h].join(\" \")},resistanceArc:function(t,a,o,s){var l=i(t,1/(a+1)),u=n(t,r([a,o])),c=u[0],f=u[1],h=n(t,r([a,s])),p=h[0],d=h[1];if(e(o)!==e(s)){var v=n(t,r([a,0]));return[\"M\"+c+\",\"+f,\"A\"+l+\",\"+l+\" 0 0,\"+(00){for(var n=[],i=0;i=c&&(h.min=0,d.min=0,g.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}function v(t,e,r,n){var i=h[e._name];function o(r,n){return a.coerce(t,e,i,r,n)}o(\"uirevision\",n.uirevision),e.type=\"linear\";var p=o(\"color\"),d=p!==i.color.dflt?p:r.font.color,v=e._name.charAt(0).toUpperCase(),g=\"Component 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n=r(39898),i=r(84267),a=r(73972),o=r(71828),s=o.strTranslate,l=o._,u=r(7901),c=r(91424),f=r(21994),h=r(1426).extendFlat,p=r(74875),d=r(89298),v=r(28569),g=r(30211),y=r(64505),m=y.freeMode,x=y.rectMode,b=r(92998),_=r(47322).prepSelect,w=r(47322).selectOnClick,T=r(47322).clearOutline,k=r(47322).clearSelectionsCache,A=r(85555);function M(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}t.exports=M;var S=M.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=this,n=e[r.id],i=e._size;r._hasClipOnAxisFalse=!1;for(var a=0;aE*b?i=(a=b)*E:a=(i=x)/E,o=y*i/x,l=m*a/b,r=e.l+e.w*v-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[v-o/2,v+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var L=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(L,p.graphDiv._fullLayout),L.setScale();var C=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",C),p.layers.plotbg.select(\"path\").attr(\"d\",C);var P=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",P);var O=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",O),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var I=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",I),p.layers.bgrid.attr(\"transform\",I);var D=s(r+i/2,n)+\"rotate(30)\"+s(0,-M._offset);p.layers.aaxis.attr(\"transform\",D),p.layers.agrid.attr(\"transform\",D);var z=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",z),p.layers.cgrid.attr(\"transform\",z),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(u.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(u.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(u.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),c.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var e=this,r=e.graphDiv,n=e.id.substr(7)+\"title\",i=e.layers,a=e.aaxis,o=e.baxis,s=e.caxis;if(e.drawAx(a),e.drawAx(o),e.drawAx(s),t){var u=Math.max(a.showticklabels?a.tickfont.size/2:0,(s.showticklabels?.75*s.tickfont.size:0)+(\"outside\"===s.ticks?.87*s.ticklen:0)),c=(o.showticklabels?o.tickfont.size:0)+(\"outside\"===o.ticks?o.ticklen:0)+3;i[\"a-title\"]=b.draw(r,\"a\"+n,{propContainer:a,propName:e.id+\".aaxis.title\",placeholder:l(r,\"Click to enter Component A title\"),attributes:{x:e.x0+e.w/2,y:e.y0-a.title.font.size/3-u,\"text-anchor\":\"middle\"}}),i[\"b-title\"]=b.draw(r,\"b\"+n,{propContainer:o,propName:e.id+\".baxis.title\",placeholder:l(r,\"Click to enter Component B title\"),attributes:{x:e.x0-c,y:e.y0+e.h+.83*o.title.font.size+c,\"text-anchor\":\"middle\"}}),i[\"c-title\"]=b.draw(r,\"c\"+n,{propContainer:s,propName:e.id+\".caxis.title\",placeholder:l(r,\"Click to enter Component C title\"),attributes:{x:e.x0+e.w+c,y:e.y0+e.h+.83*s.title.font.size+c,\"text-anchor\":\"middle\"}})}},S.drawAx=function(t){var e,r=this,n=r.graphDiv,i=t._name,a=i.charAt(0),s=t._id,l=r.layers[i],u=a+\"tickLayout\",c=(e=t).ticks+String(e.ticklen)+String(e.showticklabels);r[u]!==c&&(l.selectAll(\".\"+s+\"tick\").remove(),r[u]=c),t.setScale();var f=d.calcTicks(t),h=d.clipEnds(t,f),p=d.makeTransTickFn(t),v=d.getTickSigns(t)[2],g=o.deg2rad(30),y=v*(t.linewidth||1)/2,m=v*t.ticklen,x=r.w,b=r.h,_=\"b\"===a?\"M0,\"+y+\"l\"+Math.sin(g)*m+\",\"+Math.cos(g)*m:\"M\"+y+\",0l\"+Math.cos(g)*m+\",\"+-Math.sin(g)*m,w={a:\"M0,0l\"+b+\",-\"+x/2,b:\"M0,0l-\"+x/2+\",-\"+b,c:\"M0,0l-\"+b+\",\"+x/2}[a];d.drawTicks(n,t,{vals:\"inside\"===t.ticks?h:f,layer:l,path:_,transFn:p,crisp:!1}),d.drawGrid(n,t,{vals:h,layer:r.layers[a+\"grid\"],path:w,transFn:p,crisp:!1}),d.drawLabels(n,t,{vals:f,layer:l,transFn:p,labelFns:d.makeLabelFns(t,0,30)})};var L=A.MINZOOM/2+.87,C=\"m-0.87,.5h\"+L+\"v3h-\"+(L+5.2)+\"l\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l2.6,1.5l-\"+L/2+\",\"+.87*L+\"Z\",P=\"m0.87,.5h-\"+L+\"v3h\"+(L+5.2)+\"l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-2.6,1.5l\"+L/2+\",\"+.87*L+\"Z\",O=\"m0,1l\"+L/2+\",\"+.87*L+\"l2.6,-1.5l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-\"+(L/2+2.6)+\",\"+(.87*L+4.5)+\"l2.6,1.5l\"+L/2+\",-\"+.87*L+\"Z\",I=!0;function D(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}S.clearOutline=function(){k(this.dragOptions),T(this.dragOptions.gd)},S.initInteractions=function(){var t,e,r,n,f,h,p,d,y,b,T,k,M=this,S=M.layers.plotbg.select(\"path\").node(),L=M.graphDiv,z=L._fullLayout._zoomlayer;function R(t){var e={};return e[M.id+\".aaxis.min\"]=t.a,e[M.id+\".baxis.min\"]=t.b,e[M.id+\".caxis.min\"]=t.c,e}function F(t,e){var r=L._fullLayout.clickmode;D(L),2===t&&(L.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",L,R({a:0,b:0,c:0}))),r.indexOf(\"select\")>-1&&1===t&&w(e,L,[M.xaxis],[M.yaxis],M.id,M.dragOptions),r.indexOf(\"event\")>-1&&g.click(L,e,M.id)}function B(t,e){return 1-e/M.h}function N(t,e){return 1-(t+(M.h-e)/Math.sqrt(3))/M.w}function j(t,e){return(t-(M.h-e)/Math.sqrt(3))/M.w}function U(i,a){var o=r+i*t,s=n+a*e,l=Math.max(0,Math.min(1,B(0,n),B(0,s))),u=Math.max(0,Math.min(1,N(r,n),N(o,s))),c=Math.max(0,Math.min(1,j(r,n),j(o,s))),v=(l/2+c)*M.w,g=(1-l/2-u)*M.w,m=(v+g)/2,x=g-v,_=(1-l)*M.h,w=_-x/E;x.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),k.transition().style(\"opacity\",1).duration(200),b=!0),L.emit(\"plotly_relayouting\",R(p))}function V(){D(L),p!==f&&(a.call(\"_guiRelayout\",L,R(p)),I&&L.data&&L._context.showTips&&(o.notifier(l(L,\"Double-click to zoom back out\"),\"long\"),I=!1))}function H(t,e){var r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),u=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[u]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(c.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function 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o=e.yaxis,s=e.xaxis,l=!!s.rangebreaks;i.makeTraceGroups(a,r,\"trace ohlc\").each((function(t){var e=n.select(this),r=t[0],a=r.t;if(!0!==r.trace.visible||a.empty)e.remove();else{var u=a.tickLen,c=e.selectAll(\"path\").data(i.identity);c.enter().append(\"path\"),c.exit().remove(),c.attr(\"d\",(function(t){if(t.empty)return\"M0,0Z\";var e=s.c2p(t.pos-u,!0),r=s.c2p(t.pos+u,!0),n=l?(e+r)/2:s.c2p(t.pos,!0);return\"M\"+e+\",\"+o.c2p(t.o,!0)+\"H\"+n+\"M\"+n+\",\"+o.c2p(t.h,!0)+\"V\"+o.c2p(t.l,!0)+\"M\"+r+\",\"+o.c2p(t.c,!0)+\"H\"+n}))}}))}},67324:function(t){\"use strict\";t.exports=function(t,e){var r,n=t.cd,i=t.xaxis,a=t.yaxis,o=[],s=n[0].t.bPos||0;if(!1===e)for(r=0;r=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(r))for(e=0;e0;u&&(o=\"array\");var c=r(\"categoryorder\",o);\"array\"===c?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),u||\"array\"!==c||(e.categoryorder=\"trace\")}}t.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,l,r,i)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:c}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,f,h);o(e,f,h),Array.isArray(p)&&p.length||(e.visible=!1),u(e,p,\"values\",d),h(\"hoveron\"),h(\"hovertemplate\"),h(\"arrangement\"),h(\"bundlecolors\"),h(\"sortpaths\"),h(\"counts\");var v={family:f.font.family,size:Math.round(f.font.size),color:f.font.color};n.coerceFont(h,\"labelfont\",v);var g={family:f.font.family,size:Math.round(f.font.size/1.2),color:f.font.color};n.coerceFont(h,\"tickfont\",g)}},94873:function(t,e,r){\"use 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w=x.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);_(w),x.attr(\"d\",(function(t){return t.svgD})),w.empty()||x.sort(v),x.exit().remove(),x.on(\"mouseover\",g).on(\"mouseout\",y).on(\"click\",b),m.append(\"g\").attr(\"class\",\"dimensions\");var A=h.select(\"g.dimensions\").selectAll(\"g.dimension\").data((function(t){return t.dimensions}),p);A.enter().append(\"g\").attr(\"class\",\"dimension\"),A.attr(\"transform\",(function(t){return l(t.x,0)})),A.exit().remove();var M=A.selectAll(\"g.category\").data((function(t){return t.categories}),p),S=M.enter().append(\"g\").attr(\"class\",\"category\");M.attr(\"transform\",(function(t){return l(0,t.y)})),S.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),M.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})),T(S);var E=M.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p);E.each((function(){s.raiseToTop(this)})),E.attr(\"fill\",(function(t){return t.color}));var D=E.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);E.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(D),E.exit().remove(),S.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){u.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),S.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){u.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),M.exit().remove(),A.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",O).on(\"dragend\",I)),h.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),h.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function v(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+v.left,y:_-d.top+v.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L1&&h.displayInd===f.dimensions.length-1?(i=u.left,a=\"left\"):(i=u.left+u.width,a=\"right\");var v=c.model.count,g=c.model.categoryLabel,y=v/c.parcatsViewModel.model.count,m={countLabel:v,categoryLabel:g,probabilityLabel:y.toFixed(3)},x=[];-1!==c.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",m.countLabel].join(\" \")),-1!==c.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+m.categoryLabel+\"):\",m.probabilityLabel].join(\" \"));var b=x.join(\"
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e=t.parcatsViewModel;e.dragDimension||(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(v),-1!==e.hoverinfoItems.indexOf(\"skip\"))||(\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event))}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.yf.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragXp.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),z(t.parcatsViewModel)}}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=D(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var u=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),c=u.map((function(t){return t.categoryValue})),f=u.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[c],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd&&(t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null),t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function D(t){for(var e,r=t.graphDiv._fullData,n=0;n=0;s--)c+=\"C\"+u[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),c+=\"l-\"+r[s]+\",0 \";return c+\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),u=[];for(var c in r.paths)r.paths.hasOwnProperty(c)&&u.push(r.paths[c]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}u.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),ni?1:0}));for(var h=new Array(u.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),v=0;v0?d*(y.count/p):0;for(var m,x=new Array(n.length),b=0;b1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,u,c=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),v=8*(f-h)/2,g=e.categories.map((function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}}));for(g.sort((function(t,e){return t.displayInd-e.displayInd})),u=0;u0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:v,bands:[],parcatsViewModel:t},v=v+a+8,c.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:c,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}t.exports=function(t,e,r,n){h(r,t,n,e)}},45784:function(t,e,r){\"use strict\";var n=r(45460);t.exports=function(t,e,r,i){var a=t._fullLayout,o=a._paper,s=a._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,i)}},73362:function(t,e,r){\"use strict\";var n=r(50693),i=r(13838),a=r(41940),o=r(27670).Y,s=r(1426).extendFlat,l=r(44467).templatedArray;t.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"})),unselected:{line:{color:{valType:\"color\",dflt:\"#7f7f7f\",editType:\"plot\"},opacity:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"plot\"},editType:\"plot\"},editType:\"plot\"}}},57920:function(t,e,r){\"use strict\";var n=r(25706),i=r(39898),a=r(28984).keyFun,o=r(28984).repeat,s=r(71828).sorterAsc,l=r(71828).strTranslate,u=n.bar.snapRatio;function c(t,e){return t*(1-u)+e*u}var f=n.bar.snapClose;function h(t,e){return t*(1-f)+e*f}function p(t,e,r,n){if(function(t,e){for(var r=0;r=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var i=t?-1:1,a=0,o=e.length-1;if(i<0){var s=a;a=o,o=s}for(var l=e[a],u=l,f=a;i*fe){h=r;break}}if(a=c,isNaN(a)&&(a=isNaN(f)||isNaN(h)?isNaN(f)?h:f:e-u[f][1]t[1]+r||e=.9*t[1]+.1*t[0]?\"n\":e<=.9*t[0]+.1*t[1]?\"s\":\"ns\"}(d,e);v&&(o.interval=l[a],o.intervalPix=d,o.region=v)}}if(t.ordinal&&!o.region){var g=t.unitTickvals,m=t.unitToPaddedPx.invert(e);for(r=0;r=x[0]&&m<=x[1]){o.clickableOrdinalRange=x;break}}}return o}function w(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.brush.svgBrush;a.wasDragged=!0,a._dragging=!0,a.grabbingBar?a.newExtent=[r-a.grabPoint,r+a.barLength-a.grabPoint].map(e.unitToPaddedPx.invert):a.newExtent=[a.startExtent,e.unitToPaddedPx.invert(r)].sort(s),e.brush.filterSpecified=!0,a.extent=a.stayingIntervals.concat([a.newExtent]),a.brushCallback(e),b(t.parentNode)}function T(t,e){var r=_(e,e.height-i.mouse(t)[1]-2*n.verticalPadding),a=\"crosshair\";r.clickableOrdinalRange?a=\"pointer\":r.region&&(a=r.region+\"-resize\"),i.select(document.body).style(\"cursor\",a)}function k(t){t.on(\"mousemove\",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on(\"mouseleave\",(function(t){t.parent.inBrushDrag||m()})).call(i.behavior.drag().on(\"dragstart\",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,u=o.svgBrush;if(u.wasDragged=!1,u.grabbingBar=\"ns\"===s.region,u.grabbingBar){var c=l.map(e.unitToPaddedPx);u.grabPoint=r-c[0]-n.verticalPadding,u.barLength=c[1]-c[0]}u.clickableOrdinalRange=s.clickableOrdinalRange,u.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(u.stayingIntervals=u.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),u.startExtent=s.region?l[\"s\"===s.region?1:0]:a,e.parent.inBrushDrag=!0,u.brushStartCallback()}(this,t)})).on(\"drag\",(function(t){w(this,t)})).on(\"dragend\",(function(t){!function(t,e){var r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,m(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]a.newExtent[0];a.extent=a.stayingIntervals.concat(u?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),u?b(t.parentNode,s):(s(),b(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function A(t,e){return t[0]-e[0]}function M(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}t.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(A)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=S(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e),n=r.slice();e.filter.set(n),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t,e,r){var i=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);i.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t,e,r){var i=r._context.staticPlot,a=t.selectAll(\".background\").data(o);a.enter().append(\"rect\").classed(\"background\",!0).call(d).call(v).style(\"pointer-events\",i?\"none\":\"auto\").attr(\"transform\",l(0,n.verticalPadding)),a.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var s=t.selectAll(\".highlight-shadow\").data(o);s.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",e).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),s.attr(\"y1\",(function(t){return t.height})).call(x);var u=t.selectAll(\".highlight\").data(o);u.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),u.attr(\"y1\",(function(t){return t.height})).call(x)}(i,e,r)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},71791:function(t,e,r){\"use strict\";t.exports={attributes:r(73362),supplyDefaults:r(3633),calc:r(24639),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:r(49351),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},49351:function(t,e,r){\"use strict\";var n=r(39898),i=r(27659).a0,a=r(21341),o=r(77922);e.name=\"parcoords\",e.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},e.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},e.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this,r=t.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":r,preserveAspectRatio:\"none\",x:0,y:0,width:t.style.width,height:t.style.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},24639:function(t,e,r){\"use strict\";var n=r(71828).isArrayOrTypedArray,i=r(21081),a=r(28984).wrap;t.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;rf&&(n.log(\"parcoords traces support up to \"+f+\" dimensions at the moment\"),d.splice(f));var v=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),g=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,c);o(e,l,c),Array.isArray(v)&&v.length||(e.visible=!1),h(e,v,\"values\",g);var y={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(c,\"labelfont\",y),n.coerceFont(c,\"tickfont\",y),n.coerceFont(c,\"rangefont\",y),c(\"labelangle\"),c(\"labelside\"),c(\"unselected.line.color\"),c(\"unselected.line.opacity\")}},1602:function(t,e,r){\"use strict\";var n=r(71828).isTypedArray;e.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},e.isOrdinal=function(t){return!!t.tickvals},e.isVisible=function(t){return t.visible||!(\"visible\"in t)}},67618:function(t,e,r){\"use strict\";var n=r(71791);n.plot=r(21341),t.exports=n},83398:function(t,e,r){\"use strict\";var n=r(56068),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n p17_20, p21_24, p25_28, p29_32,\\n p33_36, p37_40, p41_44, p45_48,\\n p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n return (\\n fOutside(p[0], lo[0], hi[0]) ||\\n fOutside(p[1], lo[1], hi[1]) ||\\n fOutside(p[2], lo[2], hi[2]) ||\\n fOutside(p[3], lo[3], hi[3])\\n );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n return (\\n vOutside(p[0], lo[0], hi[0]) ||\\n vOutside(p[1], lo[1], hi[1]) ||\\n vOutside(p[2], lo[2], hi[2]) ||\\n vOutside(p[3], lo[3], hi[3])\\n );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n return mOutside(A, loA, hiA) ||\\n mOutside(B, loB, hiB) ||\\n mOutside(C, loC, hiC) ||\\n mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n mat4 pnts[4];\\n pnts[0] = A;\\n pnts[1] = B;\\n pnts[2] = C;\\n pnts[3] = D;\\n\\n for(int i = 0; i < 4; ++i) {\\n for(int j = 0; j < 4; ++j) {\\n for(int k = 0; k < 4; ++k) {\\n if(0 == iMod(\\n int(255.0 * texture2D(maskTexture,\\n vec2(\\n (float(i * 2 + j / 2) + 0.5) / 8.0,\\n (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n ))[3]\\n ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n 2\\n )) return true;\\n }\\n }\\n }\\n return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n float x = 0.5 * sign(v) + 0.5;\\n float y = axisY(x, A, B, C, D);\\n float z = 1.0 - abs(v);\\n\\n z += isContext ? 0.0 : 2.0 * float(\\n outsideBoundingBox(A, B, C, D) ||\\n outsideRasterMask(A, B, C, D)\\n );\\n\\n return vec4(\\n 2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n z,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n mat4 B = 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r=[],n=0;n1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var 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n=r(82196);t.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},42743:function(t,e,r){\"use strict\";var n=r(9330).gl_pointcloud2d,i=r(78614),a=r(71739).findExtremes,o=r(34603);function 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v=i(t.marker.color),g=i(t.marker.border.color),y=t.opacity*t.marker.opacity;v[3]*=y,this.pointcloudOptions.color=v;var m=t.marker.blend;null===m&&(m=u.length<100||c.length<100),this.pointcloudOptions.blend=m,g[3]*=y,this.pointcloudOptions.borderColor=g;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,T=b/2||.5;t._extremes[_._id]=a(_,[d[0],d[2]],{ppad:T}),t._extremes[w._id]=a(w,[d[1],d[3]],{ppad:T})},l.dispose=function(){this.pointcloud.dispose()},t.exports=function(t,e){var r=new s(t,e.uid);return r.update(e),r}},33876:function(t,e,r){\"use strict\";var n=r(71828),i=r(10959);t.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof 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n=r(32663),i=r(89298),a=r(91424);t.exports=function(t,e,r,o){var s,l,u,c=r[0][0].carpet,f=i.getFromId(t,c.xaxis||\"x\"),h=i.getFromId(t,c.yaxis||\"y\"),p={xaxis:f,yaxis:h,plot:e.plot};for(s=0;s\")}function p(t){return t+\"°\"}}(u,v,t,l[0].t.labels),t.hovertemplate=u.hovertemplate,[t]}}},17988:function(t,e,r){\"use strict\";t.exports={attributes:r(19316),supplyDefaults:r(10659),colorbar:r(4898),formatLabels:r(82719),calc:r(84622),calcGeoJSON:r(89171).calcGeoJSON,plot:r(89171).plot,style:r(33095),styleOnSelect:r(16296).styleOnSelect,hoverPoints:r(14977),eventData:r(84084),selectPoints:r(20548),moduleType:\"trace\",name:\"scattergeo\",basePlotModule:r(44622),categories:[\"geo\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},89171:function(t,e,r){\"use strict\";var n=r(39898),i=r(71828),a=r(90973).getTopojsonFeatures,o=r(18214),s=r(41327),l=r(71739).findExtremes,u=r(50606).BADNUM,c=r(47761).calcMarkerSize,f=r(34098),h=r(33095);t.exports={calcGeoJSON:function(t,e){var 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h=n[0],p=n[1];for(i=0;i1?l[i]:l[0]:l,d=Array.isArray(u)?u.length>1?u[i]:u[0]:u,v=g[p],y=g[d],m=c?c/.8+1:0,x=-y*m-.5*y;o.offset[i]=[v*m/h,x/h]}}return o}}},47148:function(t,e,r){\"use strict\";var n=r(71828),i=r(73972),a=r(68645),o=r(42341),s=r(47581),l=r(34098),u=r(67513),c=r(73927),f=r(49508),h=r(11058),p=r(28908),d=r(82410);t.exports=function(t,e,r,v){function g(r,i){return n.coerce(t,e,o,r,i)}var y=!!t.marker&&a.isOpenSymbol(t.marker.symbol),m=l.isBubble(t),x=u(t,e,v,g);if(x){c(t,e,v,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x100},e.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},20794:function(t,e,r){\"use strict\";var n=r(73972),i=r(71828),a=r(34603);function o(t,e,r,o){var s=t.xa,l=t.ya,u=t.distance,c=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.ma=i.isArrayOrTypedArray(d.angle)?d.angle[f]:d.angle,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var v=d&&d.line;v&&(h.mlc=Array.isArray(v.color)?v.color[f]:v.color,h.mlw=i.isArrayOrTypedArray(v.width)?v.width[f]:v.width);var 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R=m.selectBatch[O]=s.selIndices2selPoints(C),F={};for(g=0;g\")}function c(t){return t+\"°\"}}t.exports={hoverPoints:function(t,e,r){var o=t.cd,c=o[0].trace,f=t.xa,h=t.ya,p=t.subplot,d=[],v=l+c.uid+\"-circle\",g=c.cluster&&c.cluster.enabled;if(g){var y=p.map.queryRenderedFeatures(null,{layers:[v]});d=y.map((function(t){return t.id}))}var m=360*(e>=0?Math.floor((e+180)/360):Math.ceil((e-180)/360)),x=e-m;if(n.getClosest(o,(function(t){var e=t.lonlat;if(e[0]===s)return 1/0;if(g&&-1===d.indexOf(t.i+1))return 1/0;var n=i.modHalf(e[0],360),a=e[1],o=p.project([n,a]),l=o.x-f.c2p([x,a]),u=o.y-h.c2p([n,r]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(l*l+u*u)-c,1-3/c)}),t),!1!==t.index){var b=o[t.index],_=b.lonlat,w=[i.modHalf(_[0],360)+m,_[1]],T=f.c2p(w),k=h.c2p(w),A=b.mrc||1;t.x0=T-A,t.x1=T+A,t.y0=k-A,t.y1=k+A;var M={};M[c.subplot]={_subplot:p};var S=c._module.formatLabels(b,c,M);return t.lonLabel=S.lonLabel,t.latLabel=S.latLabel,t.color=a(c,b),t.extraText=u(c,b,o[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}},getExtraText:u}},20467:function(t,e,r){\"use strict\";t.exports={attributes:r(99181),supplyDefaults:r(76645),colorbar:r(4898),formatLabels:r(15636),calc:r(84622),plot:r(86951),hoverPoints:r(28178).hoverPoints,eventData:r(53353),selectPoints:r(86387),styleOnSelect:function(t,e){e&&e[0].trace._glTrace.update(e)},moduleType:\"trace\",name:\"scattermapbox\",basePlotModule:r(50101),categories:[\"mapbox\",\"gl\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},86951:function(t,e,r){\"use strict\";var n=r(71828),i=r(15790),a=r(77734).traceLayerPrefix,o={cluster:[\"cluster\",\"clusterCount\",\"circle\"],nonCluster:[\"fill\",\"line\",\"circle\",\"symbol\"]};function s(t,e,r,n){this.type=\"scattermapbox\",this.subplot=t,this.uid=e,this.clusterEnabled=r,this.isHidden=n,this.sourceIds={fill:\"source-\"+e+\"-fill\",line:\"source-\"+e+\"-line\",circle:\"source-\"+e+\"-circle\",symbol:\"source-\"+e+\"-symbol\",cluster:\"source-\"+e+\"-circle\",clusterCount:\"source-\"+e+\"-circle\"},this.layerIds={fill:a+e+\"-fill\",line:a+e+\"-line\",circle:a+e+\"-circle\",symbol:a+e+\"-symbol\",cluster:a+e+\"-cluster\",clusterCount:a+e+\"-cluster-count\"},this.below=null}var l=s.prototype;l.addSource=function(t,e,r){var i={type:\"geojson\",data:e.geojson};r&&r.enabled&&n.extendFlat(i,{cluster:!0,clusterMaxZoom:r.maxzoom});var a=this.subplot.map.getSource(this.sourceIds[t]);a?a.setData(e.geojson):this.subplot.map.addSource(this.sourceIds[t],i)},l.setSourceData=function(t,e){this.subplot.map.getSource(this.sourceIds[t]).setData(e.geojson)},l.addLayer=function(t,e,r){var n={type:e.type,id:this.layerIds[t],source:this.sourceIds[t],layout:e.layout,paint:e.paint};e.filter&&(n.filter=e.filter);for(var i,a=this.layerIds[t],o=this.subplot.getMapLayers(),s=0;s=0;r--){var i=e[r];n.removeLayer(c.layerIds[i])}t||n.removeSource(c.sourceIds.circle)}(t):function(t){for(var e=o.nonCluster,r=e.length-1;r>=0;r--){var i=e[r];n.removeLayer(c.layerIds[i]),t||n.removeSource(c.sourceIds[i])}}(t)}function h(t){l?function(t){t||c.addSource(\"circle\",a.circle,e.cluster);for(var r=o.cluster,n=0;n=0;r--){var n=e[r];t.removeLayer(this.layerIds[n]),t.removeSource(this.sourceIds[n])}},t.exports=function(t,e){var r,n,a,l=e[0].trace,u=l.cluster&&l.cluster.enabled,c=!0!==l.visible,f=new s(t,l.uid,u,c),h=i(t.gd,e),p=f.below=t.belowLookup[\"trace-\"+l.uid];if(u)for(f.addSource(\"circle\",h.circle,l.cluster),r=0;r\")}}t.exports={hoverPoints:function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index)return o;var l=t.subplot,u=s.cd[s.index],c=s.trace;if(l.isPtInside(u))return s.xLabelVal=void 0,s.yLabelVal=void 0,i(u,c,l,s),s.hovertemplate=c.hovertemplate,o}},makeHoverPointText:i}},91271:function(t,e,r){\"use strict\";t.exports={moduleType:\"trace\",name:\"scatterpolar\",basePlotModule:r(23580),categories:[\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:r(81245),supplyDefaults:r(22184).supplyDefaults,colorbar:r(4898),formatLabels:r(98608),calc:r(26442),plot:r(45162),style:r(16296).style,styleOnSelect:r(16296).styleOnSelect,hoverPoints:r(59150).hoverPoints,selectPoints:r(98002),meta:{}}},45162:function(t,e,r){\"use strict\";var n=r(32663),i=r(50606).BADNUM;t.exports=function(t,e,r){for(var 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n=r(78803);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},43768:function(t,e,r){\"use strict\";var n=r(9330).gl_surface3d,i=r(9330).ndarray,a=r(9330).ndarray_linear_interpolate.d2,o=r(824),s=r(43907),l=r(71828).isArrayOrTypedArray,u=r(81697).parseColorScale,c=r(78614),f=r(21081).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 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r=l(e.cells.values),p=function(t){return t.slice(e.header.values.length,t.length)},d=l(e.header.values);d.length&&!d[0].length&&(d[0]=[\"\"],d=l(d));var v=d.concat(p(r).map((function(){return u((d[0]||[\"\"]).length)}))),g=e.domain,y=Math.floor(t._fullLayout._size.w*(g.x[1]-g.x[0])),m=Math.floor(t._fullLayout._size.h*(g.y[1]-g.y[0])),x=e.header.values.length?v[0].map((function(){return e.header.height})):[n.emptyHeaderHeight],b=r.length?r[0].map((function(){return e.cells.height})):[],_=x.reduce(s,0),w=h(b,m-_+n.uplift),T=f(h(x,_),[]),k=f(w,T),A={},M=e._fullInput.columnorder.concat(p(r.map((function(t,e){return e})))),S=v.map((function(t,r){var n=Array.isArray(e.columnwidth)?e.columnwidth[Math.min(r,e.columnwidth.length-1)]:e.columnwidth;return a(n)?Number(n):1})),E=S.reduce(s,0);S=S.map((function(t){return t/E*y}));var 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f,h,p=c?\"\":T(t.calcdata.cells.prefix,e,r)||\"\",d=c?\"\":T(t.calcdata.cells.suffix,e,r)||\"\",v=c?null:T(t.calcdata.cells.format,e,r)||null,g=p+(v?a(v)(t.value):t.value)+d;if(t.wrappingNeeded=!t.wrapped&&!l&&!c&&(f=w(g)),t.cellHeightMayIncrease=s||c||t.mayHaveMarkup||(void 0===f?w(g):f),t.needsConvertToTspans=t.mayHaveMarkup||t.wrappingNeeded||t.latex,t.wrappingNeeded){var y=(\" \"===n.wrapSplitCharacter?g.replace(/i&&n.push(a),i+=l}return n}(i,l,s);1===u.length&&(u[0]===i.length-1?u.unshift(u[0]-1):u.push(u[0]+1)),u[0]%2&&u.reverse(),e.each((function(t,e){t.page=u[e],t.scrollY=l})),e.attr(\"transform\",(function(t){var e=z(t.rowBlocks,t.page)-t.scrollY;return c(0,e)})),t&&(C(t,r,e,u,n.prevPages,n,0),C(t,r,e,u,n.prevPages,n,1),x(r,t))}}function L(t,e,r,a){return function(o){var s=o.calcdata?o.calcdata:o,l=e.filter((function(t){return s.key===t.key})),u=r||s.scrollbarState.dragMultiplier,c=s.scrollY;s.scrollY=void 0===a?s.scrollY+u*i.event.dy:a;var 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t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a>>26;for(;0!==i&&a>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;at.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o>26,this.words[o]=67108863&e;for(;0!==a&&o>26,this.words[o]=67108863&e;if(0===a&&o>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,D=0|o[8],z=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Z=0|s[2],Y=8191&Z,W=Z>>>13,X=0|s[3],J=8191&X,K=X>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,q)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,W)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,W)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,q)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,W)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,W)|0;var xt=(u+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;u=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,W)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,W)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(v,J)|0,a=a+Math.imul(v,K)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,W)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,W)|0,n=n+Math.imul(y,J)|0,i=(i=i+Math.imul(y,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,W)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,W)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,W)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,W)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(z,U),i=(i=Math.imul(z,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,W)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,W)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(z,q)|0,i=(i=i+Math.imul(z,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,W)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,W)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(z,Y)|0,i=(i=i+Math.imul(z,W)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,W)|0,n=n+Math.imul(O,J)|0,i=(i=i+Math.imul(O,K)|0)+Math.imul(I,J)|0,a=a+Math.imul(I,K)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,W))+Math.imul(N,Y)|0,a=Math.imul(N,W),n=n+Math.imul(z,J)|0,i=(i=i+Math.imul(z,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(z,Q)|0,i=(i=i+Math.imul(z,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(z,rt)|0,i=(i=i+Math.imul(z,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(z,at)|0,i=(i=i+Math.imul(z,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(z,lt)|0,i=(i=i+Math.imul(z,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(z,ft)|0,i=(i=i+Math.imul(z,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(z,dt)|0)|0)+((8191&(i=(i=i+Math.imul(z,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o>>=1)i++;return 1<>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<o)for(this.length-=o,u=0;u=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:it.length)return 1;if(this.length=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){ni&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with 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e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return 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v=l(\"labels\");l(\"labelFont\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\"),this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,D=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,D,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,D=(A+1+(1^O))%3,this.zeroEnable[D]&&Math.min(a[0][D],a[1][D])<=0&&Math.max(a[0][D],a[1][D])>=0&&this._lines.drawZero(I,D,this.bounds,P,this.zeroLineColor[D],this.zeroLineWidth[D]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];z[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(H[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)H[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)H[O]+=k*U[O]*this.labelPad[O]/r[5*O];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},1011:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(5827),i=r(2944),a=r(1943).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},2864:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]E&&(w|=1<E&&(w|=1<u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===z?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1< HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);e.f=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},9557:function(t,e,r){\"use strict\";t.exports=function(t,e,r,i,o,l){var u=n(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,i,o,l),p};var n=r(5827),a=r(2944),o=r(875),s=r(1943).f,l=window||i.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=u[r];l||(l=u[r]={});var c=l[e];c||(c=l[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=c.positions,p=c.cells,d=0,v=p.length;d=0;--y){var m=h[g[y]];a.push(f*m[0],-f*m[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;nr)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},1140:function(t,e,r){\"use strict\";var n=r(2858);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=0;mo&&(o=n.length(b)),m){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),y=!1):y=!0}y||(p=x,d=b),v.push(b)}var w=[s,u,f],T=[l,c,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A,m=0;for(var M=0;m=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},7234:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},1950:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},6603:function(t,e,r){var 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n=r(8931);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;ac||r<0||r>c)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var f=1;if(\"color\"in(n=n||{})){if((f=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(f>1){if(!u)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(f>t.getParameter(u.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+f+\" draw buffers\")}}var h=t.UNSIGNED_BYTE,p=t.getExtension(\"OES_texture_float\");if(n.float&&f>0){if(!p)throw new Error(\"gl-fbo: Context does not support floating point textures\");h=t.FLOAT}else 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x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;yi||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n float e = floor(log2(av));\\n float m = av * pow(2.0, -e) - 1.0;\\n\\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n\\n //Unpack exponent\\n float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0;\\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},6086:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(5827),i=r(2944),a=r(8931),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(5070),u=r(5050),c=r(248),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,c=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],v=t.lineWidth||1,g=!1;t:for(e=1;e0){for(var w=0;w<24;++w)i.push(i[i.length-12]);c+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(y=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],m=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):y=m=p,3===y.length&&(y=[y[0],y[1],y[2],1]),3===m.length&&(m=[m[0],m[1],m[2],1]),!this.hasAlpha&&y[3]<1&&(this.hasAlpha=!0),x=Array.isArray(v)?v.length>e-1?v[e-1]:v.length>0?v[v.length-1]:[0,0,0,1]:v;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3]);c+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,m[0],m[1],m[2],m[3]),c+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=c,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},2056:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},8116:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(115),l=r(104),u=r(7437),c=r(5050),f=r(9156),h=r(7212),p=r(5306),d=r(2056),v=r(4340),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;ai[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],ki[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;rMath.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(8161),i=r(1152),a=r(6145),o=r(6475),s=r(2565),l=r(5233)},8245:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},1059:function(t,e,r){\"use strict\";var n=r(4296),i=r(7453),a=r(2771),o=r(6496),s=r(2611),l=r(4234),u=r(8126),c=r(6145),f=r(1120),h=r(5268),p=r(8245),d=r(2321)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,D={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},z=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:z,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:D,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;tx.distance)continue;for(var u=0;u 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},8271:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(5306),o=r(8023);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e>>1;for(r=0;r=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},6093:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},8240:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},4123:function(t,e,r){\"use strict\";var n=r(875);t.exports=function(t,e,r){var a=i[e];if(a||(a=i[e]={}),t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,u,c=n(t,o);if(r&&1!==r){for(l=0;l max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},2182:function(t,e,r){\"use strict\";var n=r(3596),i=r(5827),a=r(2944),o=r(5306),s=r(104),l=r(9282),u=r(4123),c=r(8240),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var D=p(0,0,0,S(_,O)),z=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(z[1])){var R=D;D=z,z=R,R=O,O=I,I=R;var F=C;C=P,P=F}D[0]<0&&(O[C]=-1),z[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n0){var I=0,D=x,z=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(y)&&Array.isArray(y[0]);t:for(n=0;n<_;++n){for(m+=1,w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n0?1-M[0][0]:Z<0?1+M[1][0]:1,Y*=Y>0?1-M[0][1]:Y<0?1+M[1][1]:1],X=k.cells||[],J=k.positions||[];for(T=0;T0){var y=r*c;o.drawBox(f-y,h-y,p+y,h+y,a),o.drawBox(f-y,d-y,p+y,d+y,a),o.drawBox(f-y,h-y,f+y,d+y,a),o.drawBox(p-y,h-y,p+y,d+y,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},2611:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=e[0],a=e[1];return new l(t,n(t,r,a,{}),i.mallocUint8(r*a*4))};var n=r(4234),i=r(5306),a=r(5050),o=r(2288).nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var u=l.prototype;Object.defineProperty(u,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){i.free(this.buffer);for(var n=this.buffer=i.mallocUint8(o(r*e*4)),a=0;ar)for(t=r;te)for(t=e;t=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A=0;)M+=1;_[m]=M}var S=new Array(r.length);function E(){h.program=o.program(p,h._vref,h._fref,b,_);for(var t=0;t=0){if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": \"+h);s(t,e,p[0],i,d,a,f)}else{if(!(h.indexOf(\"mat\")>=0))throw new n(\"\",\"Unknown data type for attribute \"+f+\": \"+h);var d;if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": 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a||(a[s[0]]=[]),a=a[s[0]];for(var l=1;l1)for(var l=0;l 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 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e=t[0],r=t[1],n=t[2];return!(eb||r_||nw)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;uS&&(S=F),z.push(F),g.push({points:P,velocities:O,divergences:z});for(var B=0;B<100*u&&P.lengthA&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(D,N)-A>-1e-4*A&&(P.push(N),D=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),z.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n 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dataCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n vec4 clipPosition = projection * view * worldPosition;\\n clipPosition.z += zOffset;\\n\\n gl_Position = clipPosition;\\n value = f + objectOffset.z;\\n kill = -1.0;\\n planeCoordinate = uv.zw;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Don't do lighting for contours\\n surfaceNormal = vec3(1,0,0);\\n eyeDirection = vec3(0,1,0);\\n lightDirection = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n float vh = 255.0 * v;\\n float upper = floor(vh);\\n float lower = fract(vh);\\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},3754:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(2288),i=r(5827),a=r(2944),o=r(8931),s=r(5306),l=r(9156),u=r(7498),c=r(7382),f=r(5050),h=r(4162),p=r(104),d=r(7437),v=r(5070),g=r(9144),y=r(9054),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),z=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;es||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return 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e>t==t>0?o===a?(r+=1,o=0):o+=1:0===o?(o=a,r-=1):o-=1,n.pack(o,r)}},115:function(t,e){e.vertexNormals=function(t,e,r){for(var n=e.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;oa){var b=i[u],_=1/Math.sqrt(g*m);for(x=0;x<3;++x){var w=(x+1)%3,T=(x+2)%3;b[x]+=_*(y[w]*v[T]-y[T]*v[w])}}}for(o=0;oa)for(_=1/Math.sqrt(k),x=0;x<3;++x)b[x]*=_;else for(x=0;x<3;++x)b[x]=0}return i},e.faceNormals=function(t,e,r){for(var n=t.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;oa?1/Math.sqrt(p):0,u=0;u<3;++u)h[u]*=p;i[o]=h}return i}},567:function(t){\"use strict\";t.exports=function(t,e,r,n,i,a,o,s,l,u){var c=e+a+u;if(f>0){var f=Math.sqrt(c+1);t[0]=.5*(o-l)/f,t[1]=.5*(s-n)/f,t[2]=.5*(r-a)/f,t[3]=.5*f}else{var h=Math.max(e,a,u);f=Math.sqrt(2*h-c+1),e>=h?(t[0]=.5*f,t[1]=.5*(i+r)/f,t[2]=.5*(s+n)/f,t[3]=.5*(o-l)/f):a>=h?(t[0]=.5*(r+i)/f,t[1]=.5*f,t[2]=.5*(l+o)/f,t[3]=.5*(s-n)/f):(t[0]=.5*(n+s)/f,t[1]=.5*(o+l)/f,t[2]=.5*f,t[3]=.5*(r-i)/f)}return t}},7774:function(t,e,r){\"use strict\";t.exports=function(t){var e=(t=t||{}).center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),c(r=[].slice.call(r,0,4),r);var i=new f(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i};var n=r(8444),i=r(3012),a=r(5950),o=r(7437),s=r(567);function l(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function u(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function c(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=u(r,n,i,a);o>1e-6?(t[0]=r/o,t[1]=n/o,t[2]=i/o,t[3]=a/o):(t[0]=t[1]=t[2]=0,t[3]=1)}function f(t,e,r){this.radius=n([r]),this.center=n(e),this.rotation=n(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}var h=f.prototype;h.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},h.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;c(e,e);var r=this.computedMatrix;a(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;l<3;++l){for(var u=0,f=0;f<3;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},h.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r},h.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},h.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},h.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=i[1],o=i[5],s=i[9],u=l(a,o,s);a/=u,o/=u,s/=u;var 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r,n,o,s,l,u,c,f,h,p=1,d=t.length,v=\"\";for(n=0;n=0),s.type){case\"b\":r=parseInt(r,10).toString(2);break;case\"c\":r=String.fromCharCode(parseInt(r,10));break;case\"d\":case\"i\":r=parseInt(r,10);break;case\"j\":r=JSON.stringify(r,null,s.width?parseInt(s.width):0);break;case\"e\":r=s.precision?parseFloat(r).toExponential(s.precision):parseFloat(r).toExponential();break;case\"f\":r=s.precision?parseFloat(r).toFixed(s.precision):parseFloat(r);break;case\"g\":r=s.precision?String(Number(r.toPrecision(s.precision))):parseFloat(r);break;case\"o\":r=(parseInt(r,10)>>>0).toString(8);break;case\"s\":r=String(r),r=s.precision?r.substring(0,s.precision):r;break;case\"t\":r=String(!!r),r=s.precision?r.substring(0,s.precision):r;break;case\"T\":r=Object.prototype.toString.call(r).slice(8,-1).toLowerCase(),r=s.precision?r.substring(0,s.precision):r;break;case\"u\":r=parseInt(r,10)>>>0;break;case\"v\":r=r.valueOf(),r=s.precision?r.substring(0,s.precision):r;break;case\"x\":r=(parseInt(r,10)>>>0).toString(16);break;case\"X\":r=(parseInt(r,10)>>>0).toString(16).toUpperCase()}i.json.test(s.type)?v+=r:(!i.number.test(s.type)||f&&!s.sign?h=\"\":(h=f?\"+\":\"-\",r=r.toString().replace(i.sign,\"\")),u=s.pad_char?\"0\"===s.pad_char?\"0\":s.pad_char.charAt(1):\" 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s[t]=n}(t),arguments)}function o(t,e){return a.apply(null,[t].concat(e||[]))}var s=Object.create(null);e.sprintf=a,e.vsprintf=o,\"undefined\"!=typeof window&&(window.sprintf=a,window.vsprintf=o,void 0===(n=function(){return{sprintf:a,vsprintf:o}}.call(e,r,e,t))||(t.exports=n))}()},4162:function(t,e,r){\"use strict\";t.exports=function(t,e){if(t.dimension<=0)return{positions:[],cells:[]};if(1===t.dimension)return function(t,e){for(var r=i(t,e),n=r.length,a=new Array(n),o=new Array(n),s=0;sn|0},vertex:function(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=(o<<0)+(s<<1)+(l<<2)+(u<<3)|0;if(0!==p&&15!==p)switch(p){case 0:case 15:c.push([t-.5,e-.5]);break;case 1:c.push([t-.25-.25*(n+r-2*h)/(r-n),e-.25-.25*(i+r-2*h)/(r-i)]);break;case 2:c.push([t-.75-.25*(-n-r+2*h)/(n-r),e-.25-.25*(a+n-2*h)/(n-a)]);break;case 3:c.push([t-.5,e-.5-.5*(i+r+a+n-4*h)/(r-i+n-a)]);break;case 4:c.push([t-.25-.25*(a+i-2*h)/(i-a),e-.75-.25*(-i-r+2*h)/(i-r)]);break;case 5:c.push([t-.5-.5*(n+r+a+i-4*h)/(r-n+i-a),e-.5]);break;case 6:c.push([t-.5-.25*(-n-r+a+i)/(n-r+i-a),e-.5-.25*(-i-r+a+n)/(i-r+n-a)]);break;case 7:c.push([t-.75-.25*(a+i-2*h)/(i-a),e-.75-.25*(a+n-2*h)/(n-a)]);break;case 8:c.push([t-.75-.25*(-a-i+2*h)/(a-i),e-.75-.25*(-a-n+2*h)/(a-n)]);break;case 9:c.push([t-.5-.25*(n+r+-a-i)/(r-n+a-i),e-.5-.25*(i+r+-a-n)/(r-i+a-n)]);break;case 10:c.push([t-.5-.5*(-n-r-a-i+4*h)/(n-r+a-i),e-.5]);break;case 11:c.push([t-.25-.25*(-a-i+2*h)/(a-i),e-.75-.25*(i+r-2*h)/(r-i)]);break;case 12:c.push([t-.5,e-.5-.5*(-i-r-a-n+4*h)/(i-r+a-n)]);break;case 13:c.push([t-.75-.25*(n+r-2*h)/(r-n),e-.25-.25*(-a-n+2*h)/(a-n)]);break;case 14:c.push([t-.25-.25*(-n-r+2*h)/(n-r),e-.25-.25*(-i-r+2*h)/(i-r)])}},cell:function(t,e,r,n,i,a,o,s,l){i?s.push([t,e]):s.push([e,t])}});return function(t,e){var r=[],i=[];return n(t,r,i,e),{positions:r,cells:i}}}},o={}},6946:function(t,e,r){\"use strict\";t.exports=function t(e,r,i){i=i||{};var a=o[e];a||(a=o[e]={\" \":{data:new Float32Array(0),shape:.2}});var s=a[r];if(!s)if(r.length<=1||!/\\d/.test(r))s=a[r]=function(t){for(var e=t.cells,r=t.positions,n=new Float32Array(6*e.length),i=0,a=0,o=0;o0&&(f+=.02);var p=new Float32Array(c),d=0,v=-.5*f;for(h=0;hMath.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,l=0;l<3;++l)a+=t[l]*t[l],o+=i[l]*t[l];for(l=0;l<3;++l)i[l]-=o/a*t[l];return s(i,i),i}function h(t,e,r,i,a,o,s,l){this.center=n(r),this.up=n(i),this.right=n(a),this.radius=n([o]),this.angle=n([s,l]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;u<16;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}var p=h.prototype;p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),c=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,c+=r[a]*r[a],e[a]/=l;var f=Math.sqrt(c);for(a=0;a<3;++a)r[a]/=f;var h=this.computedToward;o(h,e,r),s(h,h);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],v=this.computedAngle[1],g=Math.cos(d),y=Math.sin(d),m=Math.cos(v),x=Math.sin(v),b=this.computedCenter,_=g*m,w=y*m,T=x,k=-g*x,A=-y*x,M=m,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var L=_*r[a]+w*h[a]+T*e[a];E[4*a+1]=k*r[a]+A*h[a]+M*e[a],E[4*a+2]=L,E[4*a+3]=0}var C=E[1],P=E[5],O=E[9],I=E[2],D=E[6],z=E[10],R=P*z-O*D,F=O*I-C*z,B=C*D-P*I,N=u(R,F,B);for(R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B,a=0;a<3;++a)S[a]=b[a]+E[2+4*a]*p;for(a=0;a<3;++a){c=0;for(var j=0;j<3;++j)c+=E[a+4*j]*S[j];E[12+a]=-c}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,u=0;u<3;++u)i[4*u]=o[u],i[4*u+1]=s[u],i[4*u+2]=l[u];for(a(i,i,n,d),u=0;u<3;++u)o[u]=i[4*u],s[u]=i[4*u+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=u(a,o,s);a/=l,o/=l,s/=l;var c=i[0],f=i[4],h=i[8],p=c*a+f*o+h*s,d=u(c-=a*p,f-=o*p,h-=s*p),v=(c/=d)*e+a*r,g=(f/=d)*e+o*r,y=(h/=d)*e+s*r;this.center.move(t,v,g,y);var m=Math.exp(this.computedRadius[0]);m=Math.max(1e-4,m+n),this.radius.set(t,Math.log(m))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),v=Math.max(h,p,d);h===v?(s=s<0?-1:1,l=f=0):d===v?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=u(s,l,f);s/=g,l/=g,f/=g}var y,m,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=u(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=u(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,q,G,Z),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,O=E*k+L*A+C*M;y=R<0?-Math.PI/2:Math.PI/2,m=Math.atan2(O,P)}else{var I=e[2],D=e[6],z=e[10],R=I*s+D*l+z*f,F=I*x+D*b+z*_,B=I*k+D*A+z*M;y=Math.asin(c(R)),m=Math.atan2(B,F)}this.angle.jump(t,m,y),this.recalcMatrix(t);var N=e[2],j=e[6],U=e[10],V=this.computedMatrix;i(V,e);var H=V[15],q=V[12]/H,G=V[13]/H,Z=V[14]/H,Y=Math.exp(this.computedRadius[0]);this.center.jump(t,q-N*Y,G-j*Y,Z-U*Y)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},p.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter;var i=(n=n||this.computedUp)[0],a=n[1],o=n[2],s=u(i,a,o);if(!(s<1e-6)){i/=s,a/=s,o/=s;var l=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=u(l,f,h);if(!(p<1e-6)){l/=p,f/=p,h/=p;var d=this.computedRight,v=d[0],g=d[1],y=d[2],m=i*v+a*g+o*y,x=u(v-=m*i,g-=m*a,y-=m*o);if(!(x<.01&&(x=u(v=a*h-o*f,g=o*l-i*h,y=i*f-a*l))<1e-6)){v/=x,g/=x,y/=x,this.up.set(t,i,a,o),this.right.set(t,v,g,y),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var b=a*y-o*g,_=o*v-i*y,w=i*g-a*v,T=u(b,_,w),k=i*l+a*f+o*h,A=v*l+g*f+y*h,M=(b/=T)*l+(_/=T)*f+(w/=T)*h,S=Math.asin(c(k)),E=Math.atan2(M,A),L=this.angle._state,C=L[L.length-1],P=L[L.length-2];C%=2*Math.PI;var O=Math.abs(C+2*Math.PI-E),I=Math.abs(C-E),D=Math.abs(C-2*Math.PI-E);O0?r.pop():new ArrayBuffer(t)}function d(t){return new Uint8Array(p(t),0,t)}function v(t){return new Uint16Array(p(2*t),0,t)}function g(t){return new Uint32Array(p(4*t),0,t)}function y(t){return new Int8Array(p(t),0,t)}function m(t){return new Int16Array(p(2*t),0,t)}function x(t){return new 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n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},15692:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],f=e[6],h=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},10789:function(t){t.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},6726:function(t){t.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", 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t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},42505:function(t,e,r){\"use strict\";var n=r(72791),i=r(71299),a=r(98580),o=r(12018),s=r(83522),l=r(25075),u=r(68016),c=r(58404),f=r(18863),h=r(10973),p=r(25677),d=r(75686),v=r(53545),g=r(56131),y=r(32879),m=r(30120),x=r(13547).nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign 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t.offset&&(t.offset=[t.offset,0]),this.positionOffset=m(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var u=t.family.join(\", \"),c=[t.style];t.style!=t.variant&&c.push(t.variant),t.variant!=t.weight&&c.push(t.weight),_&&t.weight!=t.stretch&&c.push(t.stretch),e.font[r]={baseString:i,family:u,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:y(u,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:c.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h2){for(var w=!t.position[0].length,k=c.mallocFloat(2*this.count),A=0,M=0;A1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,-1*(i+=\"number\"==typeof t?t-n.baseline:-n[t])}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var q;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;q=c.mallocUint8(G);for(var Z=(t.color.subarray||t.color.slice).bind(t.color),Y=0;Y4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},t.exports=T},12018:function(t,e,r){\"use strict\";var n=r(71299);function i(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*r.g.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*r.g.innerHeight);else{var e=t.container.getBoundingClientRect();t.canvas.width=t.width||e.right-e.left,t.canvas.height=t.height||e.bottom-e.top}}function a(t){return\"function\"==typeof t.getContext&&\"width\"in t&&\"height\"in t}function o(){var t=document.createElement(\"canvas\");return t.style.position=\"absolute\",t.style.top=0,t.style.left=0,t}t.exports=function(t){var e;if(t?\"string\"==typeof t&&(t={container:t}):t={},(t=a(t)||\"string\"==typeof(e=t).nodeName&&\"function\"==typeof e.appendChild&&\"function\"==typeof e.getBoundingClientRect?{container:t}:function(t){return\"function\"==typeof t.drawArrays||\"function\"==typeof t.drawElements}(t)?{gl:t}:n(t,{container:\"container target element el canvas holder parent parentNode wrapper use ref root node\",gl:\"gl context webgl 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Intl.NumberFormat(this.locale?this.locale.evaluate(t):[],{style:this.currency?\"currency\":\"decimal\",currency:this.currency?this.currency.evaluate(t):void 0,minimumFractionDigits:this.minFractionDigits?this.minFractionDigits.evaluate(t):void 0,maximumFractionDigits:this.maxFractionDigits?this.maxFractionDigits.evaluate(t):void 0}).format(this.number.evaluate(t))},Br.prototype.eachChild=function(t){t(this.number),this.locale&&t(this.locale),this.currency&&t(this.currency),this.minFractionDigits&&t(this.minFractionDigits),this.maxFractionDigits&&t(this.maxFractionDigits)},Br.prototype.outputDefined=function(){return!1},Br.prototype.serialize=function(){var t={};return this.locale&&(t.locale=this.locale.serialize()),this.currency&&(t.currency=this.currency.serialize()),this.minFractionDigits&&(t[\"min-fraction-digits\"]=this.minFractionDigits.serialize()),this.maxFractionDigits&&(t[\"max-fraction-digits\"]=this.maxFractionDigits.serialize()),[\"number-format\",this.number.serialize(),t]};var Nr=function(t){this.type=Ht,this.input=t};Nr.parse=function(t,e){if(2!==t.length)return e.error(\"Expected 1 argument, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1);return r?\"array\"!==r.type.kind&&\"string\"!==r.type.kind&&\"value\"!==r.type.kind?e.error(\"Expected argument of type string or array, but found \"+Qt(r.type)+\" instead.\"):new Nr(r):null},Nr.prototype.evaluate=function(t){var e=this.input.evaluate(t);if(\"string\"==typeof e)return e.length;if(Array.isArray(e))return e.length;throw new ge(\"Expected value to be of type string or array, but found \"+Qt(pe(e))+\" 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e[0].value.indexOf(t.geometryType())>=0}],\"filter-id-in\":[Gt,[$t(Wt)],function(t,e){return e[0].value.indexOf(t.id())>=0}],\"filter-in-small\":[Gt,[qt,$t(Wt)],function(t,e){var r=e[0];return e[1].value.indexOf(t.properties()[r.value])>=0}],\"filter-in-large\":[Gt,[qt,$t(Wt)],function(t,e){var r=e[0],n=e[1];return function(t,e,r,n){for(;r<=n;){var i=r+n>>1;if(e[i]===t)return!0;e[i]>t?n=i-1:r=i+1}return!1}(t.properties()[r.value],n.value,0,n.value.length-1)}],all:{type:Gt,overloads:[[[Gt,Gt],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)&&n.evaluate(t)}],[qr(Gt),function(t,e){for(var r=0,n=e;r0&&\"string\"==typeof t[0]&&t[0]in jr}function ln(t,e){var r=new We(jr,[],e?function(t){var e={color:Zt,string:qt,number:Ht,enum:qt,boolean:Gt,formatted:Jt,resolvedImage:Kt};return\"array\"===t.type?$t(e[t.value]||Wt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&\"string\"===e.type?{typeAnnotation:\"coerce\"}:void 0);return n?Gr(new on(n,e)):Zr(r.errors)}on.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a,this.expression.evaluate(this._evaluator)},on.prototype.evaluate=function(t,e,r,n,i,a){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a||null;try{var o=this.expression.evaluate(this._evaluator);if(null==o||\"number\"==typeof o&&o!=o)return this._defaultValue;if(this._enumValues&&!(o in this._enumValues))throw new ge(\"Expected value to be one of \"+Object.keys(this._enumValues).map((function(t){return JSON.stringify(t)})).join(\", \")+\", but found \"+JSON.stringify(o)+\" instead.\");return o}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var un=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!Ge(e.expression)};un.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},un.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)};var cn=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!Ge(e.expression),this.interpolationType=n};function fn(t,e){if(\"error\"===(t=ln(t,e)).result)return t;var r=t.value.expression,n=qe(r);if(!n&&!Yr(e))return Zr([new jt(\"\",\"data expressions not supported\")]);var i=Ze(r,[\"zoom\"]);if(!i&&!Wr(e))return Zr([new jt(\"\",\"zoom expressions not supported\")]);var a=pn(r);if(!a&&!i)return Zr([new jt(\"\",'\"zoom\" expression may only be 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e=1;e\"===r||\"<=\"===r||\">=\"===r?Mn(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(An))):\"all\"===r?[\"all\"].concat(t.slice(1).map(An)):\"none\"===r?[\"all\"].concat(t.slice(1).map(An).map(Ln)):\"in\"===r?Sn(t[1],t.slice(2)):\"!in\"===r?Ln(Sn(t[1],t.slice(2))):\"has\"===r?En(t[1]):\"!has\"===r?Ln(En(t[1])):\"within\"!==r||t}function Mn(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Sn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Tn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function En(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function Ln(t){return[\"!\",t]}function Cn(t){return bn(Nt(t.value))?mn(Ft({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):Pn(t)}function Pn(t){var e=t.value,r=t.key;if(\"array\"!==Jr(e))return[new zt(r,e,\"array expected, \"+Jr(e)+\" found\")];var n,i=t.styleSpec,a=[];if(e.length<1)return[new zt(r,e,\"filter array must have at least 1 element\")];switch(a=a.concat(xn({key:r+\"[0]\",value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Bt(e[0])){case\"<\":case\"<=\":case\">\":case\">=\":e.length>=2&&\"$type\"===Bt(e[1])&&a.push(new zt(r,e,'\"$type\" cannot be use with operator \"'+e[0]+'\"'));case\"==\":case\"!=\":3!==e.length&&a.push(new zt(r,e,'filter array for operator \"'+e[0]+'\" must have 3 elements'));case\"in\":case\"!in\":e.length>=2&&\"string\"!==(n=Jr(e[1]))&&a.push(new zt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));for(var o=2;o=c[p+0]&&n>=c[p+1])?(o[h]=!0,a.push(u[h])):o[h]=!1}}},Qn.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),u=this._convertToCellCoord(e),c=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},Qn.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},Qn.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},Qn.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=$n+this.cells.length+1+1,r=0,n=0;n=0)){var f=t[c];u[c]=ri[l].shallow.indexOf(c)>=0?f:si(f,e)}t instanceof Error&&(u.message=t.message)}if(u.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==l&&(u.$name=l),u}throw new Error(\"can't serialize object of type \"+typeof t)}function li(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||ai(t)||oi(t)||ArrayBuffer.isView(t)||t instanceof ti)return t;if(Array.isArray(t))return t.map(li);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=ri[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class \"+e);if(r.deserialize)return r.deserialize(t);for(var n=Object.create(r.prototype),i=0,a=Object.keys(t);i=0?s:li(s)}}return n}throw new Error(\"can't deserialize object of type \"+typeof t)}var ui=function(){this.first=!0};ui.prototype.update=function(t,e){var r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoom=128&&t<=255},Arabic:function(t){return t>=1536&&t<=1791},\"Arabic 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t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description Characters\":function(t){return t>=12272&&t<=12287},\"CJK Symbols and Punctuation\":function(t){return t>=12288&&t<=12351},Hiragana:function(t){return t>=12352&&t<=12447},Katakana:function(t){return t>=12448&&t<=12543},Bopomofo:function(t){return t>=12544&&t<=12591},\"Hangul Compatibility Jamo\":function(t){return t>=12592&&t<=12687},Kanbun:function(t){return t>=12688&&t<=12703},\"Bopomofo Extended\":function(t){return t>=12704&&t<=12735},\"CJK Strokes\":function(t){return t>=12736&&t<=12783},\"Katakana Phonetic Extensions\":function(t){return t>=12784&&t<=12799},\"Enclosed CJK Letters and Months\":function(t){return t>=12800&&t<=13055},\"CJK Compatibility\":function(t){return t>=13056&&t<=13311},\"CJK Unified Ideographs Extension A\":function(t){return t>=13312&&t<=19903},\"Yijing Hexagram 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e=0,r=t;e=65097&&t<=65103)||ci[\"CJK Compatibility Ideographs\"](t)||ci[\"CJK Compatibility\"](t)||ci[\"CJK Radicals Supplement\"](t)||ci[\"CJK Strokes\"](t)||!(!ci[\"CJK Symbols and Punctuation\"](t)||t>=12296&&t<=12305||t>=12308&&t<=12319||12336===t)||ci[\"CJK Unified Ideographs Extension A\"](t)||ci[\"CJK Unified Ideographs\"](t)||ci[\"Enclosed CJK Letters and Months\"](t)||ci[\"Hangul Compatibility Jamo\"](t)||ci[\"Hangul Jamo Extended-A\"](t)||ci[\"Hangul Jamo Extended-B\"](t)||ci[\"Hangul Jamo\"](t)||ci[\"Hangul Syllables\"](t)||ci.Hiragana(t)||ci[\"Ideographic Description Characters\"](t)||ci.Kanbun(t)||ci[\"Kangxi Radicals\"](t)||ci[\"Katakana Phonetic Extensions\"](t)||ci.Katakana(t)&&12540!==t||!(!ci[\"Halfwidth and Fullwidth Forms\"](t)||65288===t||65289===t||65293===t||t>=65306&&t<=65310||65339===t||65341===t||65343===t||t>=65371&&t<=65503||65507===t||t>=65512&&t<=65519)||!(!ci[\"Small Form Variants\"](t)||t>=65112&&t<=65118||t>=65123&&t<=65126)||ci[\"Unified Canadian 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Ri=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ri.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);in.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ui),Hi=function(t){this.specification=t};Hi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new Pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom+1),e)),e)}},Hi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Hi.prototype.interpolate=function(t){return t};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},qi.prototype.interpolate=function(){return!1};var Gi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new Oi(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new Ii(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};ni(\"DataDrivenProperty\",Ui),ni(\"DataConstantProperty\",ji),ni(\"CrossFadedDataDrivenProperty\",Vi),ni(\"CrossFadedProperty\",Hi),ni(\"ColorRampProperty\",qi);var Zi=\"-transition\",Yi=function(t){function 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this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);la.prototype.bytesPerElement=12,ni(\"StructArrayLayout2i2i2i12\",la);var ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Ji);ua.prototype.bytesPerElement=16,ni(\"StructArrayLayout2f1f2i16\",ua);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Ji);ca.prototype.bytesPerElement=12,ni(\"StructArrayLayout2ub2f12\",ca);var fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return 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this.int16[m+0]=e,this.int16[m+1]=r,this.uint16[m+2]=n,this.uint16[m+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[m+10]=l,this.uint16[m+11]=u,this.uint16[m+12]=c,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=v,this.uint32[x+10]=g,this.int16[m+22]=y,t},e}(Ji);ha.prototype.bytesPerElement=48,ni(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",ha);var pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=u,this.uint16[L+9]=c,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=v,this.uint16[L+15]=g,this.uint16[L+16]=y,this.uint16[L+17]=m,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Ji);pa.prototype.bytesPerElement=68,ni(\"StructArrayLayout8i15ui1ul4f68\",pa);var da=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Ji);da.prototype.bytesPerElement=4,ni(\"StructArrayLayout1f4\",da);var va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Ji);va.prototype.bytesPerElement=6,ni(\"StructArrayLayout3i6\",va);var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Ji);ga.prototype.bytesPerElement=8,ni(\"StructArrayLayout1ul2ui8\",ga);var ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new 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t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Ji);xa.prototype.bytesPerElement=8,ni(\"StructArrayLayout2f8\",xa);var ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Ji);ba.prototype.bytesPerElement=16,ni(\"StructArrayLayout4f16\",ba);var _a=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Xi);_a.prototype.size=20;var wa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new _a(this,t)},e}(sa);ni(\"CollisionBoxArray\",wa);var Ta=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var 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S=o.content;x=zu(h,0,S[0]),_=zu(p,0,S[1]),b=zu(h,S[0],S[2]),w=zu(p,S[1],S[3]),T=S[0]-x,A=S[1]-_,k=S[2]-S[0]-b,M=S[3]-S[1]-w}var E=function(n,i,l,u){var h=Fu(n.stretch-x,b,c,t.left),p=Bu(n.fixed-T,k,n.stretch,v),d=Fu(i.stretch-_,w,f,t.top),y=Bu(i.fixed-A,M,i.stretch,g),m=Fu(l.stretch-x,b,c,t.left),S=Bu(l.fixed-T,k,l.stretch,v),E=Fu(u.stretch-_,w,f,t.top),L=Bu(u.fixed-A,M,u.stretch,g),C=new a(h,d),P=new a(m,d),O=new a(m,E),I=new a(h,E),D=new a(p/s,y/s),z=new a(S/s,L/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),N=[B,-F,F,B];C._matMult(N),P._matMult(N),I._matMult(N),O._matMult(N)}var j=n.stretch+n.fixed,U=l.stretch+l.fixed,V=i.stretch+i.fixed,H=u.stretch+u.fixed;return{tl:C,tr:P,bl:I,br:O,tex:{x:o.paddedRect.x+Iu+j,y:o.paddedRect.y+Iu+V,w:U-j,h:H-V},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:D,pixelOffsetBR:z,minFontScaleX:k/s/c,minFontScaleY:M/s/f,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var L=Ru(h,y,v),C=Ru(p,m,g),P=0;P0&&(d=Math.max(10,d),this.circleDiameter=d)}else{var v=o.top*s-l,g=o.bottom*s+l,y=o.left*s-l,m=o.right*s+l,x=o.collisionPadding;if(x&&(y-=x[0]*s,v-=x[1]*s,m+=x[2]*s,g+=x[3]*s),c){var b=new a(y,v),_=new a(m,v),w=new a(y,g),T=new a(m,g),k=c*Math.PI/180;b._rotate(k),_._rotate(k),w._rotate(k),T._rotate(k),y=Math.min(b.x,_.x,w.x,T.x),m=Math.max(b.x,_.x,w.x,T.x),v=Math.min(b.y,_.y,w.y,T.y),g=Math.max(b.y,_.y,w.y,T.y)}t.emplaceBack(e.x,e.y,y,v,m,g,r,n,i)}this.boxEndIndex=t.length},ju=function(t,e){if(void 0===t&&(t=[]),void 0===e&&(e=Uu),this.data=t,this.length=this.data.length,this.compare=e,this.length>0)for(var r=(this.length>>1)-1;r>=0;r--)this._down(r)};function Uu(t,e){return te?1:0}function Vu(t,e,r){void 0===e&&(e=1),void 0===r&&(r=!1);for(var n=1/0,i=1/0,o=-1/0,s=-1/0,l=t[0],u=0;uo)&&(o=c.x),(!u||c.y>s)&&(s=c.y)}var f=o-n,h=s-i,p=Math.min(f,h),d=p/2,v=new ju([],Hu);if(0===p)return new a(n,i);for(var g=n;gm.d||!m.d)&&(m=b,r&&console.log(\"found best %d after %d probes\",Math.round(1e4*b.d)/1e4,x)),b.max-m.d<=e||(d=b.h/2,v.push(new qu(b.p.x-d,b.p.y-d,d,t)),v.push(new qu(b.p.x+d,b.p.y-d,d,t)),v.push(new qu(b.p.x-d,b.p.y+d,d,t)),v.push(new qu(b.p.x+d,b.p.y+d,d,t)),x+=4)}return r&&(console.log(\"num probes: \"+x),console.log(\"best distance: \"+m.d)),m.p}function Hu(t,e){return e.max-t.max}function qu(t,e,r,n){this.p=new a(t,e),this.h=r,this.d=function(t,e){for(var r=!1,n=1/0,i=0;it.y!=c.y>t.y&&t.x<(c.x-u.x)*(t.y-u.y)/(c.y-u.y)+u.x&&(r=!r),n=Math.min(n,ko(t,u,c))}return(r?1:-1)*Math.sqrt(n)}(this.p,n),this.max=this.d+this.h*Math.SQRT2}ju.prototype.push=function(t){this.data.push(t),this.length++,this._up(this.length-1)},ju.prototype.pop=function(){if(0!==this.length){var t=this.data[0],e=this.data.pop();return this.length--,this.length>0&&(this.data[0]=e,this._down(0)),t}},ju.prototype.peek=function(){return this.data[0]},ju.prototype._up=function(t){for(var e=this.data,r=this.compare,n=e[t];t>0;){var i=t-1>>1,a=e[i];if(r(n,a)>=0)break;e[t]=a,t=i}e[t]=n},ju.prototype._down=function(t){for(var e=this.data,r=this.compare,n=this.length>>1,i=e[t];t=0)break;e[t]=o,t=a}e[t]=i};var Gu=7,Zu=Number.POSITIVE_INFINITY;function Yu(t,e){return e[1]!==Zu?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-Gu;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=-r+Gu}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-Gu;break;case\"bottom-right\":case\"bottom-left\":n=-i+Gu;break;case\"bottom\":n=-e+Gu;break;case\"top\":n=e-Gu}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function Wu(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}var Xu=255,Ju=Xu*bu;function Ku(t,e,r,n,i,o,s,l,u,c,f,h,p,d,v){var g=function(t,e,r,n,i,o,s,l){for(var u=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,c=[],f=0,h=e.positionedLines;fJu&&w(t.layerIds[0]+': Value for \"text-size\" is >= '+Xu+'. Reduce your \"text-size\".'):\"composite\"===y.kind&&((m=[bu*d.compositeTextSizes[0].evaluate(s,{},v),bu*d.compositeTextSizes[1].evaluate(s,{},v)])[0]>Ju||m[1]>Ju)&&w(t.layerIds[0]+': Value for \"text-size\" is >= '+Xu+'. Reduce your \"text-size\".'),t.addSymbols(t.text,g,m,l,o,s,c,e,u.lineStartIndex,u.lineLength,p,v);for(var x=0,b=f;x=0;o--)if(n.dist(a[o])0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),u=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get(\"symbol-sort-key\");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new Pi(this.zoom),v=0,g=t;v=0;for(var I=0,D=k.sections;I=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l0},sc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},sc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},sc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},sc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},sc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},ni(\"SymbolBucket\",sc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),sc.MAX_GLYPHS=65535,sc.addDynamicAttributes=nc;var lc=new Gi({\"symbol-placement\":new ji(Dt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new ji(Dt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new ji(Dt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ui(Dt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new ji(Dt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new ji(Dt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new ji(Dt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new ji(Dt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new ji(Dt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ui(Dt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new ji(Dt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new ji(Dt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ui(Dt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ui(Dt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new ji(Dt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new ji(Dt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ui(Dt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ui(Dt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new ji(Dt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new ji(Dt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new ji(Dt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ui(Dt.layout_symbol[\"text-field\"]),\"text-font\":new Ui(Dt.layout_symbol[\"text-font\"]),\"text-size\":new Ui(Dt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ui(Dt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new ji(Dt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ui(Dt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ui(Dt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ui(Dt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new ji(Dt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ui(Dt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new ji(Dt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new ji(Dt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ui(Dt.layout_symbol[\"text-rotate\"]),\"text-padding\":new ji(Dt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new ji(Dt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ui(Dt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ui(Dt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new ji(Dt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new ji(Dt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new ji(Dt.layout_symbol[\"text-optional\"])}),uc={paint:new Gi({\"icon-opacity\":new Ui(Dt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ui(Dt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ui(Dt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ui(Dt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ui(Dt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new ji(Dt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new ji(Dt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ui(Dt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ui(Dt.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ui(Dt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ui(Dt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ui(Dt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new ji(Dt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new ji(Dt.paint_symbol[\"text-translate-anchor\"])}),layout:lc},cc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Vt,this.defaultValue=t};cc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},cc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},cc.prototype.outputDefined=function(){return!1},cc.prototype.serialize=function(){return null},ni(\"FormatSectionOverride\",cc,{omit:[\"defaultValue\"]});var fc=function(t){function e(e){t.call(this,e,uc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a\",targetMapId:n,sourceMapId:a.mapId})}}},Ac.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else A()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Ac.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Ac.prototype.processTask=function(t,e){var r=this;if(\"\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(li(e.error)):n(null,li(e.data)))}else{var i=!1,a=E(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"\",sourceMapId:r.mapId,error:e?si(e):null,data:si(n,a)},a)}:function(t){i=!0},s=null,l=li(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Ac.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Sc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Sc.prototype.setNorthEast=function(t){return this._ne=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.setSouthWest=function(t){return this._sw=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Lc)e=t,r=t;else{if(!(t instanceof Sc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Sc.convert(a))}var o=t;return this.extend(Lc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Lc(e.lng,e.lat),this._ne=new Lc(r.lng,r.lat)),this},Sc.prototype.getCenter=function(){return new Lc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Sc.prototype.getSouthWest=function(){return this._sw},Sc.prototype.getNorthEast=function(){return this._ne},Sc.prototype.getNorthWest=function(){return new Lc(this.getWest(),this.getNorth())},Sc.prototype.getSouthEast=function(){return new Lc(this.getEast(),this.getSouth())},Sc.prototype.getWest=function(){return this._sw.lng},Sc.prototype.getSouth=function(){return this._sw.lat},Sc.prototype.getEast=function(){return this._ne.lng},Sc.prototype.getNorth=function(){return this._ne.lat},Sc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Sc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Sc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Sc.prototype.contains=function(t){var e=Lc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Sc.convert=function(t){return!t||t instanceof Sc?t:new Sc(t)};var Ec=6371008.8,Lc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Lc.prototype.wrap=function(){return new Lc(c(this.lng,-180,180),this.lat)},Lc.prototype.toArray=function(){return[this.lng,this.lat]},Lc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Lc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ec*Math.acos(Math.min(i,1))},Lc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Sc(new Lc(this.lng-r,this.lat-e),new Lc(this.lng+r,this.lat+e))},Lc.convert=function(t){if(t instanceof Lc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Lc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Lc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]\")};var Cc=2*Math.PI*Ec;function Pc(t){return Cc*Math.cos(t*Math.PI/180)}function Oc(t){return(180+t)/360}function Ic(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Dc(t,e){return t/Pc(e)}function zc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Rc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Rc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Lc.convert(t);return new Rc(Oc(r.lng),Ic(r.lat),Dc(e,r.lat))},Rc.prototype.toLngLat=function(){return new Lc(360*this.x-180,zc(this.y))},Rc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Pc(zc(e));var t,e},Rc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Cc*(t=zc(this.y),1/Math.cos(t*Math.PI/180));var t};var Fc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=jc(0,t,t,e,r)};Fc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Fc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Mc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Mc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<this.canonical.z?new Nc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Nc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Nc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?jc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):jc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Nc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ>e&&t.canonical.y===this.canonical.y>>e},Nc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Nc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Nc(e,this.wrap,e,r,n),new Nc(e,this.wrap,e,r+1,n),new Nc(e,this.wrap,e,r,n+1),new Nc(e,this.wrap,e,r+1,n+1)]},Nc.prototype.isLessThan=function(t){return this.wrapt.wrap)&&(this.overscaledZt.overscaledZ)&&(this.canonical.xt.canonical.x)&&this.canonical.y=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Uc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Uc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Uc.prototype.getPixels=function(){return new Wo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Uc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Js.VectorTile(new Sl(this.rawTileData)).layers,this.sourceLayerCoder=new Vc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=co/t.tileSize/t.scale,l=wn(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Wc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Wc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new Pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),v=0;vn)i=!1;else if(e)if(this.expirationTimect&&(t.getActor().send(\"enforceCacheSizeLimit\",ut),yt=0)},t.clamp=u,t.clearTileCache=function(t){var e=self.caches.delete(lt);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Ou,t.clone=function(t){var e=new Io(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=b,t.clone$2=function(t){var e=new Io(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=_l,t.config=B,t.create=function(){var t=new Io(16);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Io(9);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new Io(4);return Io!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=ln,t.createLayout=Ki,t.createStyleLayer=function(t){return\"custom\"===t.type?new gc(t):new yc[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=$e,t.offscreenCanvasSupported=mt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},t.parseGlyphPBF=function(t){return new Sl(t).readFields(Wl,[])},t.pbf=Sl,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=co/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,u=t.layers[0]._unevaluatedLayout._values,c={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;c.compositeTextSizes=[u[\"text-size\"].possiblyEvaluate(new Pi(h),o),u[\"text-size\"].possiblyEvaluate(new Pi(p),o)]}if(\"composite\"===t.iconSizeData.kind){var d=t.iconSizeData,v=d.minZoom,g=d.maxZoom;c.compositeIconSizes=[u[\"icon-size\"].possiblyEvaluate(new Pi(v),o),u[\"icon-size\"].possiblyEvaluate(new Pi(g),o)]}c.layoutTextSize=u[\"text-size\"].possiblyEvaluate(new Pi(t.zoom+1),o),c.layoutIconSize=u[\"icon-size\"].possiblyEvaluate(new Pi(t.zoom+1),o),c.textMaxSize=u[\"text-size\"].possiblyEvaluate(new Pi(18));for(var y=l.get(\"text-line-height\")*kl,m=\"map\"===l.get(\"text-rotation-alignment\")&&\"point\"!==l.get(\"symbol-placement\"),x=l.get(\"text-keep-upright\"),b=l.get(\"text-size\"),_=function(){var a=k[T],s=l.get(\"text-font\").evaluate(a,{},o).join(\",\"),u=b.evaluate(a,{},o),f=c.layoutTextSize.evaluate(a,{},o),h=c.layoutIconSize.evaluate(a,{},o),p={horizontal:{},vertical:void 0},d=a.text,v=[0,0];if(d){var g=d.toString(),_=l.get(\"text-letter-spacing\").evaluate(a,{},o)*kl,A=function(t){for(var e=0,r=t;e=co||f.y<0||f.y>=co||function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A){var M,S,E,L,C,P=t.addToLineVertexArray(e,r),O=0,I=0,D=0,z=0,R=-1,F=-1,B={},N=Fa(\"\"),j=0,U=0;if(void 0===s._unevaluatedLayout.getValue(\"text-radial-offset\")?(j=(M=s.layout.get(\"text-offset\").evaluate(b,{},k).map((function(t){return t*kl})))[0],U=M[1]):(j=s.layout.get(\"text-radial-offset\").evaluate(b,{},k)*kl,U=Zu),t.allowVerticalPlacement&&n.vertical){var V=s.layout.get(\"text-rotate\").evaluate(b,{},k)+90,H=n.vertical;L=new Nu(l,e,u,c,f,H,h,p,d,V),o&&(C=new Nu(l,e,u,c,f,o,g,y,d,V))}if(i){var q=s.layout.get(\"icon-rotate\").evaluate(b,{}),G=\"none\"!==s.layout.get(\"icon-text-fit\"),Z=Du(i,q,T,G),Y=o?Du(o,q,T,G):void 0;E=new Nu(l,e,u,c,f,i,g,y,!1,q),O=4*Z.length;var W=t.iconSizeData,X=null;\"source\"===W.kind?(X=[bu*s.layout.get(\"icon-size\").evaluate(b,{})])[0]>Ju&&w(t.layerIds[0]+': Value for \"icon-size\" is >= '+Xu+'. Reduce your \"icon-size\".'):\"composite\"===W.kind&&((X=[bu*_.compositeIconSizes[0].evaluate(b,{},k),bu*_.compositeIconSizes[1].evaluate(b,{},k)])[0]>Ju||X[1]>Ju)&&w(t.layerIds[0]+': Value for \"icon-size\" is >= '+Xu+'. Reduce your \"icon-size\".'),t.addSymbols(t.icon,Z,X,x,m,b,!1,e,P.lineStartIndex,P.lineLength,-1,k),R=t.icon.placedSymbolArray.length-1,Y&&(I=4*Y.length,t.addSymbols(t.icon,Y,X,x,m,b,nu.vertical,e,P.lineStartIndex,P.lineLength,-1,k),F=t.icon.placedSymbolArray.length-1)}for(var J in n.horizontal){var K=n.horizontal[J];if(!S){N=Fa(K.text);var $=s.layout.get(\"text-rotate\").evaluate(b,{},k);S=new Nu(l,e,u,c,f,K,h,p,d,$)}var Q=1===K.positionedLines.length;if(D+=Ku(t,e,K,a,s,d,b,v,P,n.vertical?nu.horizontal:nu.horizontalOnly,Q?Object.keys(n.horizontal):[J],B,R,_,k),Q)break}n.vertical&&(z+=Ku(t,e,n.vertical,a,s,d,b,v,P,nu.vertical,[\"vertical\"],B,F,_,k));var tt=S?S.boxStartIndex:t.collisionBoxArray.length,et=S?S.boxEndIndex:t.collisionBoxArray.length,rt=L?L.boxStartIndex:t.collisionBoxArray.length,nt=L?L.boxEndIndex:t.collisionBoxArray.length,it=E?E.boxStartIndex:t.collisionBoxArray.length,at=E?E.boxEndIndex:t.collisionBoxArray.length,ot=C?C.boxStartIndex:t.collisionBoxArray.length,st=C?C.boxEndIndex:t.collisionBoxArray.length,lt=-1,ut=function(t,e){return t&&t.circleDiameter?Math.max(t.circleDiameter,e):e};lt=ut(S,lt),lt=ut(L,lt),lt=ut(E,lt);var ct=(lt=ut(C,lt))>-1?1:0;ct&&(lt*=A/kl),t.glyphOffsetArray.length>=sc.MAX_GLYPHS&&w(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),void 0!==b.sortKey&&t.addToSortKeyRanges(t.symbolInstances.length,b.sortKey),t.symbolInstances.emplaceBack(e.x,e.y,B.right>=0?B.right:-1,B.center>=0?B.center:-1,B.left>=0?B.left:-1,B.vertical||-1,R,F,N,tt,et,rt,nt,it,at,ot,st,u,D,z,O,I,ct,0,h,j,U,lt)}(t,f,s,r,n,i,h,t.layers[0],t.collisionBoxArray,e.index,e.sourceLayerIndex,t.index,m,T,M,l,b,k,S,d,e,a,u,c,o)};if(\"line\"===E)for(var O=0,I=Ou(e.geometry,0,0,co,co);O1){var U=Lu(j,A,r.vertical||v,n,g,x);U&&P(j,U)}}else if(\"Polygon\"===e.type)for(var V=0,H=Is(e.geometry,0);V=E.maxzoom||\"none\"!==E.visibility&&(o(S,this.zoom,n),(v[E.id]=E.createBucket({index:c.bucketLayerIDs.length,layers:S,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:b,sourceID:this.source})).populate(_,g,this.tileID.canonical),c.bucketLayerIDs.push(S.map((function(t){return t.id}))))}}}var L=t.mapObject(g.glyphDependencies,(function(t){return Object.keys(t).map(Number)}));Object.keys(L).length?a.send(\"getGlyphs\",{uid:this.uid,stacks:L},(function(t,e){f||(f=t,h=e,O.call(l))})):h={};var C=Object.keys(g.iconDependencies);C.length?a.send(\"getImages\",{icons:C,source:this.source,tileID:this.tileID,type:\"icons\"},(function(t,e){f||(f=t,p=e,O.call(l))})):p={};var P=Object.keys(g.patternDependencies);function O(){if(f)return s(f);if(h&&p&&d){var e=new i(h),r=new t.ImageAtlas(p,d);for(var a in v){var l=v[a];l instanceof t.SymbolBucket?(o(l.layers,this.zoom,n),t.performSymbolLayout(l,h,e.positions,p,r.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):l.hasPattern&&(l instanceof t.LineBucket||l instanceof t.FillBucket||l instanceof t.FillExtrusionBucket)&&(o(l.layers,this.zoom,n),l.addFeatures(g,this.tileID.canonical,r.patternPositions))}this.status=\"done\",s(null,{buckets:t.values(v).filter((function(t){return!t.isEmpty()})),featureIndex:c,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:e.image,imageAtlas:r,glyphMap:this.returnDependencies?h:null,iconMap:this.returnDependencies?p:null,glyphPositions:this.returnDependencies?e.positions:null})}}P.length?a.send(\"getImages\",{icons:P,source:this.source,tileID:this.tileID,type:\"patterns\"},(function(t,e){f||(f=t,d=e,O.call(l))})):d={},O.call(this)};var l=function(t,e,r,n){this.actor=t,this.layerIndex=e,this.availableImages=r,this.loadVectorData=n||s,this.loading={},this.loaded={}};l.prototype.loadTile=function(e,r){var n=this,i=e.uid;this.loading||(this.loading={});var o=!!(e&&e.request&&e.request.collectResourceTiming)&&new t.RequestPerformance(e.request),s=this.loading[i]=new a(e);s.abort=this.loadVectorData(e,(function(e,a){if(delete n.loading[i],e||!a)return s.status=\"done\",n.loaded[i]=s,r(e);var l=a.rawData,u={};a.expires&&(u.expires=a.expires),a.cacheControl&&(u.cacheControl=a.cacheControl);var c={};if(o){var f=o.finish();f&&(c.resourceTiming=JSON.parse(JSON.stringify(f)))}s.vectorTile=a.vectorTile,s.parse(a.vectorTile,n.layerIndex,n.availableImages,n.actor,(function(e,n){if(e||!n)return r(e);r(null,t.extend({rawTileData:l.slice(0)},n,u,c))})),n.loaded=n.loaded||{},n.loaded[i]=s}))},l.prototype.reloadTile=function(t,e){var r=this,n=this.loaded,i=t.uid,a=this;if(n&&n[i]){var o=n[i];o.showCollisionBoxes=t.showCollisionBoxes;var s=function(t,n){var i=o.reloadCallback;i&&(delete o.reloadCallback,o.parse(o.vectorTile,a.layerIndex,r.availableImages,a.actor,i)),e(t,n)};\"parsing\"===o.status?o.reloadCallback=s:\"done\"===o.status&&(o.vectorTile?o.parse(o.vectorTile,this.layerIndex,this.availableImages,this.actor,s):s())}},l.prototype.abortTile=function(t,e){var r=this.loading,n=t.uid;r&&r[n]&&r[n].abort&&(r[n].abort(),delete r[n]),e()},l.prototype.removeTile=function(t,e){var r=this.loaded,n=t.uid;r&&r[n]&&delete r[n],e()};var u=t.window.ImageBitmap,c=function(){this.loaded={}};c.prototype.loadTile=function(e,r){var n=e.uid,i=e.encoding,a=e.rawImageData,o=u&&a instanceof u?this.getImageData(a):a,s=new t.DEMData(n,o,i);this.loaded=this.loaded||{},this.loaded[n]=s,r(null,s)},c.prototype.getImageData=function(e){this.offscreenCanvas&&this.offscreenCanvasContext||(this.offscreenCanvas=new OffscreenCanvas(e.width,e.height),this.offscreenCanvasContext=this.offscreenCanvas.getContext(\"2d\")),this.offscreenCanvas.width=e.width,this.offscreenCanvas.height=e.height,this.offscreenCanvasContext.drawImage(e,0,0,e.width,e.height);var r=this.offscreenCanvasContext.getImageData(-1,-1,e.width+2,e.height+2);return this.offscreenCanvasContext.clearRect(0,0,this.offscreenCanvas.width,this.offscreenCanvas.height),new t.RGBAImage({width:r.width,height:r.height},r.data)},c.prototype.removeTile=function(t){var e=this.loaded,r=t.uid;e&&e[r]&&delete e[r]};var f=function t(e,r){var n,i=e&&e.type;if(\"FeatureCollection\"===i)for(n=0;n=0!=!!e&&t.reverse()}var d=t.vectorTile.VectorTileFeature.prototype.toGeoJSON,v=function(e){this._feature=e,this.extent=t.EXTENT,this.type=e.type,this.properties=e.tags,\"id\"in e&&!isNaN(e.id)&&(this.id=parseInt(e.id,10))};v.prototype.loadGeometry=function(){if(1===this._feature.type){for(var e=[],r=0,n=this._feature.geometry;r>31}function P(t,e){for(var r=t.loadGeometry(),n=t.type,i=0,a=0,o=r.length,s=0;s>1;D(t,e,o,n,i,a%2),I(t,e,r,n,o-1,a+1),I(t,e,r,o+1,i,a+1)}}function D(t,e,r,n,i,a){for(;i>n;){if(i-n>600){var o=i-n+1,s=r-n+1,l=Math.log(o),u=.5*Math.exp(2*l/3),c=.5*Math.sqrt(l*u*(o-u)/o)*(s-o/2<0?-1:1);D(t,e,r,Math.max(n,Math.floor(r-s*u/o+c)),Math.min(i,Math.floor(r+(o-s)*u/o+c)),a)}var f=e[2*r+a],h=n,p=i;for(z(t,e,n,r),e[2*i+a]>f&&z(t,e,n,i);hf;)p--}e[2*n+a]===f?z(t,e,n,p):z(t,e,++p,i),p<=r&&(n=p+1),r<=p&&(i=p-1)}}function z(t,e,r,n){R(t,r,n),R(e,2*r,2*n),R(e,2*r+1,2*n+1)}function R(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function F(t,e,r,n){var i=t-r,a=e-n;return i*i+a*a}_.fromVectorTileJs=w,_.fromGeojsonVt=T,_.GeoJSONWrapper=k;var B=function(t){return t[0]},N=function(t){return t[1]},j=function(t,e,r,n,i){void 0===e&&(e=B),void 0===r&&(r=N),void 0===n&&(n=64),void 0===i&&(i=Float64Array),this.nodeSize=n,this.points=t;for(var a=t.length<65536?Uint16Array:Uint32Array,o=this.ids=new a(t.length),s=this.coords=new i(2*t.length),l=0;l=r&&s<=i&&l>=n&&l<=a&&c.push(t[d]);else{var v=Math.floor((p+h)/2);s=e[2*v],l=e[2*v+1],s>=r&&s<=i&&l>=n&&l<=a&&c.push(t[v]);var g=(f+1)%2;(0===f?r<=s:n<=l)&&(u.push(p),u.push(v-1),u.push(g)),(0===f?i>=s:a>=l)&&(u.push(v+1),u.push(h),u.push(g))}}return c}(this.ids,this.coords,t,e,r,n,this.nodeSize)},j.prototype.within=function(t,e,r){return function(t,e,r,n,i,a){for(var o=[0,t.length-1,0],s=[],l=i*i;o.length;){var u=o.pop(),c=o.pop(),f=o.pop();if(c-f<=a)for(var h=f;h<=c;h++)F(e[2*h],e[2*h+1],r,n)<=l&&s.push(t[h]);else{var p=Math.floor((f+c)/2),d=e[2*p],v=e[2*p+1];F(d,v,r,n)<=l&&s.push(t[p]);var g=(u+1)%2;(0===u?r-i<=d:n-i<=v)&&(o.push(f),o.push(p-1),o.push(g)),(0===u?r+i>=d:n+i>=v)&&(o.push(p+1),o.push(c),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var U={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},V=function(t){this.options=X(Object.create(U),t),this.trees=new Array(this.options.maxZoom+1)};function H(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function q(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function G(t){return{type:\"Feature\",id:t.id,properties:Z(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function Z(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return X(X({},t.properties),{cluster:!0,cluster_id:t.id,point_count:e,point_count_abbreviated:r})}function Y(t){return t/360+.5}function W(t){var e=Math.sin(t*Math.PI/180),r=.5-.25*Math.log((1+e)/(1-e))/Math.PI;return r<0?0:r>1?1:r}function X(t,e){for(var r in e)t[r]=e[r];return t}function J(t){return t.x}function K(t){return t.y}function $(t,e,r,n){for(var i,a=n,o=r-e>>1,s=r-e,l=t[e],u=t[e+1],c=t[r],f=t[r+1],h=e+3;ha)i=h,a=p;else if(p===a){var d=Math.abs(h-o);dn&&(i-e>3&&$(t,e,i,n),t[i+2]=a,r-i>3&&$(t,i,r,n))}function Q(t,e,r,n,i,a){var o=i-r,s=a-n;if(0!==o||0!==s){var l=((t-r)*o+(e-n)*s)/(o*o+s*s);l>1?(r=i,n=a):l>0&&(r+=o*l,n+=s*l)}return(o=t-r)*o+(s=e-n)*s}function tt(t,e,r,n){var i={id:void 0===t?null:t,type:e,geometry:r,tags:n,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return function(t){var e=t.geometry,r=t.type;if(\"Point\"===r||\"MultiPoint\"===r||\"LineString\"===r)et(t,e);else if(\"Polygon\"===r||\"MultiLineString\"===r)for(var n=0;n0&&(o+=n?(i*u-l*a)/2:Math.sqrt(Math.pow(l-i,2)+Math.pow(u-a,2))),i=l,a=u}var c=e.length-3;e[2]=1,$(e,0,c,r),e[c+2]=1,e.size=Math.abs(o),e.start=0,e.end=e.size}function at(t,e,r,n){for(var i=0;i1?1:r}function lt(t,e,r,n,i,a,o,s){if(n/=e,a>=(r/=e)&&o=n)return null;for(var l=[],u=0;u=r&&d=n)){var v=[];if(\"Point\"===h||\"MultiPoint\"===h)ut(f,v,r,n,i);else if(\"LineString\"===h)ct(f,v,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ht(f,v,r,n,i,!1);else if(\"Polygon\"===h)ht(f,v,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function ct(t,e,r,n,i,a,o){for(var s,l,u=ft(t),c=0===i?dt:vt,f=t.start,h=0;hr&&(l=c(u,p,d,g,y,r),o&&(u.start=f+s*l)):m>n?x=r&&(l=c(u,p,d,g,y,r),b=!0),x>n&&m<=n&&(l=c(u,p,d,g,y,n),b=!0),!a&&b&&(o&&(u.end=f+s*l),e.push(u),u=ft(t)),o&&(f+=s)}var _=t.length-3;p=t[_],d=t[_+1],v=t[_+2],(m=0===i?p:d)>=r&&m<=n&&pt(u,p,d,v),_=u.length-3,a&&_>=3&&(u[_]!==u[0]||u[_+1]!==u[1])&&pt(u,u[0],u[1],u[2]),u.length&&e.push(u)}function ft(t){var e=[];return e.size=t.size,e.start=t.start,e.end=t.end,e}function ht(t,e,r,n,i,a){for(var o=0;oo.maxX&&(o.maxX=c),f>o.maxY&&(o.maxY=f)}return o}function _t(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;lo)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n0===e)for(n=0,i=t.length;n24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,J,K,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),W(a),Y(i),W(n));c1?this._map(u,!0):null,g=(l<<5)+(e+1)+this.points.length,y=0,m=f;y>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var Mt=function(e){function r(t,r,n,i){e.call(this,t,r,n,At),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new V(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),u=0,c=l;u=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o=n&&e.x=i&&e.y0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+10&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;or.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];tthis.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Dt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);fthis._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Dt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(na.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;yMath.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.yn.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var D=0,z=v;D0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;yo*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r=1;P--)C.push(E.path[P]);for(var O=1;O0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.xM.x||F.yM.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=z;N=this.screenRightBoundary||nthis.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t=0&&e0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,D=0,z=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Z=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),W=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,Z,l,u,c,n,_,v.predicate,W,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(z=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=X(a.verticalIconBox)).box.length>0:(O=X(a.iconBox)).box.length>0,S=S&&O.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=y||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,D,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,z,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=De(y.text),k=_?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=De(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:ze;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?ze:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var D=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var z=!0;if(u){var R=i.variableOffsets[v];R?(D=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&D._rotate(f?i.transform.angle:-i.transform.angle)):z=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||_,D.x,D.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||w,D.x,D.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?D.x:0,h?D.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?D.x:0,h?D.y:0)}}},g=0;gt},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function De(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var ze=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;nt.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(He(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id] 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var wr=Object.freeze({__proto__:null,prelude:Xe,background:Je,backgroundPattern:Ke,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}kr.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Mr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Sr=function(e,r,n,i,a,o,s){return t.extend(Mr(e,r,n,i),Ar(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Er=function(t){return{u_matrix:t}},Lr=function(e,r,n,i){return t.extend(Er(e),Ar(n,r,i))},Cr=function(t,e){return{u_matrix:t,u_world:e}},Pr=function(e,r,n,i,a){return t.extend(Lr(e,r,n,i),{u_world:a})},Or=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Ir=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},zr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Rr=function(t){return{u_matrix:t}},Fr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Br=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},Nr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},jr=function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}};var Ur=function(e,r,n){var i=e.transform;return{u_matrix:Zr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Vr=function(e,r,n){return t.extend(Ur(e,r,n),{u_image:0})},Hr=function(e,r,n,i){var a=e.transform,o=Gr(r,a);return{u_matrix:Zr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},qr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Gr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Ur(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Gr(t,e){return 1/ge(t,1,e.tileZoom)}function Zr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Yr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Wr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Wr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Xr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},Kr=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},$r=function(e,r,n,i,a,o,s,l,u,c){return t.extend(Kr(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},Qr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},tn=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},en={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function rn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Ir(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var vn=new t.Color(1,0,0,1),gn=new t.Color(0,1,0,1),yn=new t.Color(0,0,1,1),mn=new t.Color(1,0,1,1),xn=new t.Color(0,1,1,1);function bn(t){var e=t.transform.padding;_n(t,t.transform.height-(e.top||0),3,vn),_n(t,e.bottom||0,3,gn),wn(t,e.left||0,3,yn),wn(t,t.transform.width-(e.right||0),3,mn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;Tn(t,e-a/2,r-i/2,a,i,n),Tn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,xn)}function _n(t,e,r,n){Tn(t,0,e+r/2,t.transform.width,r,n)}function wn(t,e,r,n){Tn(t,e-r/2,0,r,t.transform.height,n)}function Tn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function kn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,zr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,zr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var An={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer0?e.pop():null},Mn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Mn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new kr(this.context,wr[t],e,en[t],this._showOverdrawInspector)),this.cache[r]},Mn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Mn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Mn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Mn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Sn=function(t,e){this.points=t,this.planes=e};Sn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new Sn(a,o)};var En=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};En.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;fthis.max[l]-this.min[l])return 0}return 1};var Ln=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Ln.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Ln.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Ln.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Ln.prototype.clone=function(){return new Ln(this.top,this.bottom,this.left,this.right)},Ln.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Cn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ln,this._posMatrixCache={},this._alignedPosMatrixCache={}},Pn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Cn.prototype.clone=function(){var t=new Cn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Pn.minZoom.get=function(){return this._minZoom},Pn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Pn.maxZoom.get=function(){return this._maxZoom},Pn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Pn.minPitch.get=function(){return this._minPitch},Pn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Pn.maxPitch.get=function(){return this._maxPitch},Pn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Pn.renderWorldCopies.get=function(){return this._renderWorldCopies},Pn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Pn.worldSize.get=function(){return this.tileSize*this.scale},Pn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Pn.size.get=function(){return new t.Point(this.width,this.height)},Pn.bearing.get=function(){return-this.angle/Math.PI*180},Pn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Pn.pitch.get=function(){return this._pitch/Math.PI*180},Pn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Pn.fov.get=function(){return this._fov/Math.PI*180},Pn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Pn.zoom.get=function(){return this._zoom},Pn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Pn.center.get=function(){return this._center},Pn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Pn.padding.get=function(){return this._edgeInsets.toJSON()},Pn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Pn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Cn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Cn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Cn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Cn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Cn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&re.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=Sn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new En([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Cn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Pn.unmodified.get=function(){return this._unmodified},Cn.prototype.zoomScale=function(t){return Math.pow(2,t)},Cn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Cn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Cn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Pn.point.get=function(){return this.project(this.center)},Cn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Cn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Cn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Cn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Cn.prototype.coordinateLocation=function(t){return t.toLngLat()},Cn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Cn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Cn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Cn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Cn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Cn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Cn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Cn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-ao&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-ml&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Cn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Cn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Cn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Cn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},On.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var In={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},In),zn=t.extend({deceleration:20,maxSpeed:1400},In),Rn=t.extend({deceleration:1e3,maxSpeed:360},In),Fn=t.extend({deceleration:1e3,maxSpeed:90},In),Bn=function(t){this._map=t,this.clear()};function Nn(t,e){(!t.duration||t.duration0&&r-e[0].time>160;)e.shift()},Bn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n=this._clickTolerance||this._map.fire(new Un(t.type,this._map,t))},qn.prototype.dblclick=function(t){return this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseover=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.mouseout=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.touchstart=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},qn.prototype.touchmove=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchend=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchcancel=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},qn.prototype.isEnabled=function(){return!0},qn.prototype.isActive=function(){return!1},qn.prototype.enable=function(){},qn.prototype.disable=function(){};var Gn=function(t){this._map=t};Gn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Gn.prototype.mousemove=function(t){this._map.fire(new Un(t.type,this._map,t))},Gn.prototype.mousedown=function(){this._delayContextMenu=!0},Gn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Un(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Gn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Un(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Zn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Yn(t,e){for(var r={},n=0;nthis.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n30)&&(this.aborted=!0)}}},Wn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Xn=function(t){this.singleTap=new Wn(t),this.numTaps=t.numTaps,this.reset()};Xn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Xn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Xn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Xn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Xn({numTouches:1,numTaps:2}),this._zoomOut=new Xn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Kn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Kn.prototype._correctButton=function(t,e){return!1},Kn.prototype._move=function(t,e){return{}},Kn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Kn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)0&&(this._active=!0);var i=Yn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(sMath.abs(t.x)}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,li(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return li(t)&&li(e)&&a}},e}(ri),ci={panStep:100,bearingStep:15,pitchStep:10},fi=function(){var t=ci;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function hi(t){return t*(2-t)}fi.prototype.reset=function(){this._active=!1},fi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:hi,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var pi=4.000244140625,di=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};di.prototype.setZoomRate=function(t){this._defaultZoomRate=t},di.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},di.prototype.isEnabled=function(){return!!this._enabled},di.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},di.prototype.isZooming=function(){return!!this._zooming},di.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},di.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},di.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%pi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},di.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},di.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},di.prototype.renderFrame=function(){return this._onScrollFrame()},di.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>pi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},di.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},di.prototype.reset=function(){this._active=!1};var vi=function(t,e){this._clickZoom=t,this._tapZoom=e};vi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},vi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},vi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},vi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var gi=function(){this.reset()};gi.prototype.reset=function(){this._active=!1},gi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},gi.prototype.enable=function(){this._enabled=!0},gi.prototype.disable=function(){this._enabled=!1,this.reset()},gi.prototype.isEnabled=function(){return this._enabled},gi.prototype.isActive=function(){return this._active};var yi=function(){this._tap=new Xn({numTouches:1,numTaps:1}),this.reset()};yi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},yi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},yi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},yi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},yi.prototype.touchcancel=function(){this.reset()},yi.prototype.enable=function(){this._enabled=!0},yi.prototype.disable=function(){this._enabled=!1,this.reset()},yi.prototype.isEnabled=function(){return this._enabled},yi.prototype.isActive=function(){return this._active};var mi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};mi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},mi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},mi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},mi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var xi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};xi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},xi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},xi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},xi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var bi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};bi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},bi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},bi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},bi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var _i=function(t){return t.zoom||t.drag||t.pitch||t.rotate},wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ki=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Bn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;aa?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},D=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var z=Te.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)180?-360:r<-180?360:0}},r}(t.Evented),Mi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Mi.prototype.getDefaultPosition=function(){return\"bottom-right\"},Mi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Mi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Mi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Mi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var Si=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Si.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Si.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Si.prototype.getDefaultPosition=function(){return\"bottom-left\"},Si.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Si.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Si.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ei=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ei.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ei.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;re.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>Ii)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Cn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ei,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Li,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Pi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new ki(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new On(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Mi({customAttribution:e.customAttribution})),this.addControl(new Si,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()Ii)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Un(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Un(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Un(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ni.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ni.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ni.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ni.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ni.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ni.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ni.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ni.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)e.getEast()||r.latitudee.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Yi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new qi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new qi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Zi--,Yi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Zi>1?(e={maximumAge:6e5,timeout:0},Yi=!0):(e=this.options.positionOptions,Yi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Xi={maxWidth:100,unit:\"metric\"},Ji=function(e){this.options=t.extend({},Xi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Ki(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?$i(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):$i(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?$i(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?$i(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):$i(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function $i(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\" \"+n}Ji.prototype.getDefaultPosition=function(){return\"bottom-left\"},Ji.prototype._onMove=function(){Ki(this._map,this._container,this.options)},Ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl 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this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Qi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Qi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Qi.prototype._isFullscreen=function(){return this._fullscreen},Qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ta={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},ea=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ta),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"×\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=ra(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.ythis._map.transform.height-u?[\"bottom\"]:[],i.xthis._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,Ui[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Vi(this._container,a,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function ra(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return ra(new t.Point(0,0))}var na={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:zi,NavigationControl:Bi,GeolocateControl:Wi,AttributionControl:Mi,ScaleControl:Ji,FullscreenControl:Qi,Popup:ea,Marker:qi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var 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n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thalāthā’\",\"Yawm al-Arba‘ā’\",\"Yawm al-Khamīs\",\"Yawm al-Jum‘a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;ar)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;ne);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,u=e-o[r-1]+1;return this.newDate(s,l,u)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=r(56131);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var 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qWK6/57blTNbJv20Y4/zyhbzxLR5gtg8hX21V+DEPJxh7mNsULOyc7/lqA8+dSzMU8Mx71gMVUg09Zj7QE0QfvSBu1S8yE3asWuv717GS+9JNE731+7oeD3XopbzwE2SJEmcdSUkJJqnvhu1e825bD9pRA/dcWthx8Vc9javNIrvk/Du/avDyAgggAACCIS3gGdComE+dfqs80JnsxtoQkbMx1xafKjCHWpY+0EnKJqPCY3dXnvX+f9jPmYX77VurWK9jPtaIdHsAprLrF/NGOa8SsZ8zIMr5oXZE9/sHqvrX36zXh1fecf3M/NOQvMuP3OvnHm1Tadn6unosRPqO9w82LEu1nfNJdzenZv5Xpw98v3ZzkuzZ43v5/x1F/Mxl9HHTJkv87tL12x2Li+9T9G8H9CEzsvvy4u5J/Hydzle7dQ1l87NJfTvvhijlCli/93mmONjdhIv/dvNGzbv0PO9RjhBMeZjAvr70xcqT66svnsSze/M902dMQ+bmGA5uFcb5/2GV6vffGf1d1vV8oXBzrsPze0CMfchtnuqlto2q+mb0/xt6KqNujn/PPeDAbxMO7z/94nVIYAAAgiEUMBTIfFSh2P/nJS55JomdUrnr56YexGv9jE7kOZ1LLlzZXN2rdz6mAD7+76Dzhz/9foVE/jMDqD5u89mRzTmL8TEpy6zU2ZCUNKkSZ2XYwfyb0bHZ/64jjG7e+YSs/mYvxZjno7+r495R6S5NG9eMWR2UfkggAACCCCAgD0Cng2J9hBSKQIIIIAAAgggEH4ChMTw6ykrQgABBBBAAAEE/BYgJPpNyAAIIIAAAggggED4CRASw6+nrAgBBBBAAAEEEPBbgJDoNyEDIIAAAggggAAC4SdASAy/nrIiBBBAAAEEEEDAbwFCot+EDIAAAggggAACCISfACEx/HrKihBAAAEEEEAAAb8FCIl+EzIAAggggAACCCAQfgKExPDrKStCAAEEEEAAAQT8FiAk+k3IAAgggAACCCCAQPgJEBLDr6esCAEEEEAAAQQQ8FuAkOg3IQMggAACCCCAAALhJ0BIDL+esiIEEEAAAQQQQMBvAUKi34QMgAACCCCAAAIIhJ8AITH8esqKEEAAAQQQQAABvwUIiX4TMgACCCCAAAIIIBB+AoTE8OspK0IAAQQQQAABBPwWICT6TcgACCCAAAIIIIBA+AkQEsOvp6wIAQQQQAABBBDwW4CQ6DchAyCAAAIIIIAAAuEnQEgMv56yIgQQQAABBBBAwG8BQqLfhAyAAAIIIIAAAgiEnwAhMfx6yooQQAABBBBAAAG/BQiJfhMyAAIIIIAAAgggEH4ChMTw6ykrQgABBBBAAAEE/BYgJPpNyAAIIIAAAggggED4CRASw6+nrAgBBBBAAAEEEPBbgJDoNyEDIIAAAggggAAC4SdASAy/nrIiBBBAAAEEEEDAbwFCot+EDIAAAggggAACCISfACEx/HrKihBAAAEEEEAAAb8FCIl+EzIAAggggAACCCAQfgKExPDrKStCAAEEEEAAAQT8FiAk+k3IAAgggAACCCCAQPgJEBLDr6esCAEEEEAAAQQQ8FuAkOg3IQMggAACCCCAAALhJ0BIDL+esiIEEEAAAQQQQMBvAUKi34QMgAACCCCAAAIIhJ8AITH8esqKEEAAAQQQQAABvwUIiX4TMgACCCCAAAIIIBB+AoTE8OspK0IAAQQQQAABBPwWICT6TcgACCCAAAIIIIBA+AkQEsOvp6wIAQQQQAABBBDwW4CQ6DchAyCAAAIIIIAAAuEnQEgMv56yIgQQQAABBBBAwG8BQqLfhAyAAAIIIIAAAgiEnwAhMfx6yooQQAABBBBAAAG/BQiJfhMyAAIIIIAAAgggEH4ChMTw6ykr8oLA6ePSmRNeqIQaEijw797tCfwGh4dcIHs+Jc6RP+RlUAAC4SZASAy3jrIebwgQEr3Rh+uogpB4HWih/gohMdQdYP4wFSAkhmljWVaIBQiJIW7A9U9PSLx+u5B9k5AYMnomDm8BQmJ495fVhUqAkBgqeb/nJST6TRj8AQiJwTdnxogQICRGRJtZZNAFCIlBJw/UhITEQEkGcRxCYhCxmSqSBAiJkdRt1ho8AUJi8KwDPBMhMcCgwRiOkBgMZeaIQAFCYgQ2nSUHQYCQGARkd6YgJLrj6uqohERXeRk8cgUIiZHbe1bupgAh0U1dV8cmJLrK687ghER3XBk14gUIiRF/CgDgigAh0RXWYAxKSAyGcoDnICQGGJThELgoQEjkTEDADQFCohuqQRmTkBgU5sBOQkgMrCejIfA/AUIipwICbggQEt1QDcqYhMSgMAd2EkJiYD0ZDQFCIucAAi4KEBJdxHV3aEKiu76ujE5IdIWVQRFgJ5FzAAE3BAiJbqgGZUxCYlCYAzsJITGwnoyGADuJnAMIuChASHQR192hCYnu+royOiHRFVYGRYCdRM4BBNwQICS6oRqUMQmJQWEO7CSExMB6MhoC7CRyDiDgogAh0UVcd4cmJLrr68rohERXWBkUAXYSOQcQcEOAkOiGalDGJCQGhTmwkxASA+vJaAiwk8g5gICLAoREF3HdHZqQ6K6vK6MTEl1hZVAE2EnkHEDADQFCohuqQRmTkBgU5sBOQkgMrCejIcBOIucAAi4KEBJdxHV3aEKiu76ujE5IdIWVQRFgJ5FzAAE3BAiJbqgGZUxCYlCYAzsJITGwnoyGADuJnAMIuChASHQR192hCYnu+royOiHRFVYGRYCdRM4BBNwQICS6oRqUMQmJQWEO7CSExMB6MhoC7CRyDiDgogAh0UVcd4cmJLrr68rohERXWBkUAXYSOQcQcEOAkOiGalDGJCQGhTmwkxASA+vJaAiwk8g5gICLAoREF3HdHZqQ6K6vK6MTEl1hZVAE2EnkHEDADQFCohuqQRmTkBgU5sBOQkgMrCejIcBOIucAAi4KEBJdxHV3aEKiu76ujE5IdIWVQRFgJ5FzAAE3BAiJbqgGZUxCYlCYAzsJITGwnoyGADuJnAMIuChASHQR192hCYnu+royOiHRFVYGRYCdRM4BBNwQICS6oRqUMQmJQWEO7CSExMB6MhoC7CRyDiDgogAh0UVcd4cmJLrr68rohERXWBkUAXYSOQcQcEOAkOiGalDGJCQGhTmwkxASA+vJaAiwk8g5gICLAoREF3HdHZqQ6K6vK6MTEl1hZVAE2EnkHEDADQFCohuqQRmTkBgU5sBOQkgMrCejIcBOIucAAi4KEBJdxHV3aEKiu76ujE5IdIWVQRFgJ5FzAAE3BAiJbqgGZUxCYlCYAzsJITGwnoyGADuJnAMIuChASHQR192hCYnu+royOiHRFVYGRYCdRM4BBNwQICS6oRqUMQmJQWEO7CSExMB6MhoC7CRyDiDgogAh0UVcd4cmJLrr68rohERXWBkUAXYSOQcQcEOAkOiGalDGJCQGhTmwkxASA+vJaAiwk8g5gICLAoREF3HdHZqQ6K6vK6MTEl1hZVAE2EnkHEDADQFCohuqQRmTkBgU5sBOQkgMrCejIcBOIucAAi4KEBJdxHV3aEKiu76ujE5IdIWVQRFgJ5FzAAE3BAiJbqgGZUxCYlCYAzsJITGwnoyGADuJnAMIuChASHQR192hCYnu+royOiHRFVYGRYCdRM4BBNwQICS6oRqUMQmJQWEO7CSExMB6MhoC7CRyDiDgogAh0UVcd4cmJLrr68rohERXWBkUAXYSOQcQcEOAkOiGalDGJCQGhTmwkxASA+vJaAiwkxj/c+Cr5d/ptuIFlC1Lxvh/iSMjW4CQaG3/CYkWto6QaGHTKNkGAat2Es+f/1cV6zyvv44e1+KZw5QzW2afcbf+76lVw0dVKH8e52d79x/SsPdmaHCvNkqaJIlfvShTtY3e7Puc7i1zi1/j8OUIEiAkWttsG0PiqdNndOjvo7oxZ3YlTpz4qva//3lQubNnvebvrW2YKZyQaHX7KN67AlaFxLUbt+mpTgOVOWM6tWz4qJrXr+KTLVGxud4f3l1lSxV1fvbTjt2q+3Rvff/lOCVLltSvDhAS/eKLzC9bHhJ37NylwmXuu6J36dKl1T+7f9ahw0eUvXDJK36/+NMZqlzhyu/ZdBLYFhJrP/+y5iz91iHOnjmTmtV8RAM7tfaRvzXlY73z4Wydi4rSuahoNX+8il7v+Izz+1wVa+vgX39f0Z4fZk1QiYL57WkbIdGeXlGpVQJWhcTeQ9/X2XNRypcnhxYtW6fZE15zsM2O4fhpnytPrmzKmD6talUrr4/nf+0ExWKF8ilJ4sTq8XxjRUVFq++wD7T/4F/O9yrdc7t6dmyiDOnSOP+8YfPPGj7mY237ZY/y5MqqJnUfVu1qFXRpSDzy9z96acAY3VPmllgh1aquU6z7ApaHxKioKP225/dYTqMnTNJnXy7W9rXLdfDQYeUocqsWzJyqAjfl8x2XO1cupU6dyn1fF2ewLST2GfW+6jx0vwremFuL12xQzfY9tGrqKJUtWUzfbd2usg3aaPH44apY5nZt+3WPStRspm+njNRdtxbXrr37ZK7QxHw2/rRDT3btqz1fzlDuHNlcVA7w0ITEAIMyHAIXBawJiafPnFOFWh00rE9bJwxWb/qSExIL35xHO37dq8efelld2z2p4oXyKWf2zFq/abteHjRe44a+qKRJk6hwgRv1+76D2rFrrxMcT585q95D3lfFe25X59b1teePA6raqJsTCmtXK6/ffv9T32/5Ra92ecoXEm8pml/Nn39d+fPmCshlbE7CMBawPCRe3pnjx08o9y2lNWrI62pcv44vJG5b842KFCoYVo20LSRejp/vofpqU7+GXnq6sZau3agHW3XW9vlTVDBvbudQs3s4tMuzalT9oSv6Vr1td+XKnkVj+7xoV08JiXb1i2qtEbAmJH75zXr1eH2cVs59x7l8bC4l31e2pDo+XdfBju/l5kNHjmrD5h06ePhvLfp6vdKnS62RAzrqnQmzNX3uEn0ze4QSJUoUq4FmJ7F/91aaNPMLZc6UTm/0bqdkSS/e53jq7Hlrmk2hwRNIdu6EkkWfCt6ELs/Ub8hwTZk5S1tWLlXSpEl9IbFmtUeUJXMmlSxWTM2erKdMGe1/uMvmkLhj914VfayJ5r7zuh6tcJfOnjunR555Ud9v/0V927XQPydP6pMvv9HSCW86V10u/Xy9/ntVbtFJuxZOU74bcrp8RgV2+OjMeRWd9f93tAM7OqPZLJA6hX/PJNi89kDUbk1I7NBrhDZu3qEHK9zprHvNhq06fuKUln3ylpIkSRyvkLhgyRp16TtapUsWVrFCefXzrr1KmSKZ3h30gsyDL+YzqOf/38sTA2xCohMIT5/RgqmDlDd3Dp/9qTPRgegDY4SZQLKok2ETEg8cPKScRW/T7MkT9PijF+8D/uef4+rZf6BuyJlTx/75R+9/OF05s2fX2q8+U4oUKazupq0h8fjJU6rQrIMypE2jxeOHKcn/HtgbNP5DTZn/pdKkSql1P25Tt5YNncBorrDEfC5cuKC7G7XVvaVK6o0X21rXv+jMNyo6CyHRusYFoeDUKf17JiEIJXp6CitC4tFjJ3RvzefUoGZlZcmU3gGNPn9e702ep4lvdleZ24s6IXH8sK66q3Rx5/fmvsI6rV7RhkVjlSJ5MudnNZr1UJXK5dS2WU3nnyd89LnWbvzJCYlD352ub1Zt0twPBlzRMBMSH3v4Hu0/cES79/6pD0f2UsYMsf8r3NNdprjgC4TR5eZOPXvr2zXrtObLz67YZY+B3b7jFxUtV0GrF81XuTtLB987gDPaGBLNf8DW7fyKfv/zkJa9/6ayZMzgiCxYsUbmEvKRFfOcncNFK9ep/gt9NKhTa7WuX8OnNnvxctXt9Ir+WPKJcmb9/7dGBJDV3aG43OyuL6NHrIAVIdE8hPLWuI99u4Yx3WrecaBzf2Dvzs3UotMglSlVVK0aVtepU2eUPHky3VnlGU0Y3k23Fisg81/Kz7w4VIVuzqPOz9RzXpHTZ+hEZcqY1gmJq7/bqpYvDNYrnZrqsYfv1f6DR7Ry3Y/OwysxD66UuqWQc4z5jH+jq1KnsnvHJGLP+mAsPExC4q7fdqtA6bv15ayP9GDFCteUM/csps9XWEvmzFSl8vcGQ9i1OWwLiUf/OaE6nXrp5Okz+mzUQF9ANEA9R4zT3KXfavPs931ej7fvqbRpUmnKwJedn0VHn1fJWk+pfpVKerXdU665ujowIdFVXgaPXAErQmKT9gNU6paCzgMml35MeBw0cpq+nfO2lq/ZrD5vvO+8Q/EVKiBXAAAgAElEQVTZpjX1XItazn2GoyfNcb5iHmD598IFde//nnNM6lQpVaTAjUqXNrVGD+zkHDNxxkINGfWRb4o2TWuofYvaTkgc0a+97r6zhMyuZsN2/ZQ3d3aNHNDJudTNB4ErBMIkJDZ9toN+/2Ofls79ONYSP1v0lU6dOq0HK5ZXsqTJnEvP5pLz7k1rrb8v0aaQePLUad3VqK0T9Ka/0Vvp01x8U4P53yXzzsTpC5aoYbd+mj9qoKrcW9Z5mrnwo4015IVn1bnZxf89fX/25+o0eKR+/eIjZUqfzs5/mQmJdvaNqj0vYEVIjK+ieZXD38eOO5ekYx4+MU9Fm/eDxbzmxlymNpeNc2bP4nv45NLxzRjmNTcZ06dxdiP5IHBdAmEQEn/YslW3lX9Q3y6co3vKlonFMGve52r+XEeZHUTzyZ4tqz4cM1IP3F/+uri89CWbQuIfBw4p70Ox/+PZ6UfmTNq/bJb+/fdfDRg7RR/M+cJ52ba5X7HJYw+r97PNnQcAz5w9p/yPNFDHJnWdexWt/RASrW0dhXtbIKxCorepqS6iBMIgJMbVr+joaJmHWsznhlw5r3m/YlzjeO33NoXEhNjt3vfnf/5FloSM5bljCYmeawkFhYcAITE8+sgqvCYQASHRa+SBqidcQ2KgfDw5DiHRk22hKPsFCIn295AVeFGAkOjFrsSrJkJivJi8dRAh0Vv9oJqwESAkhk0rWYinBAiJnmpHQoohJCZEyyPHEhI90gjKCDcBQmK4dZT1eEOAkOiNPlxHFYTE60AL9VcIiaHuAPOHqQAhMUwby7JCLEBIDHEDrn96QuL124Xsm4TEkNEzcXgLEBLDu7+sLlQChMRQyfs9LyHRb8LgD0BIDL45M0aEACExItrMIoMuQEgMOnmgJiQkBkoyiOMQEoOIzVSRJEBIjKRus9bgCRASg2cd4JkIiQEGDcZwhMRgKDNHBAoQEiOw6Sw5CAKExCAguzMFIdEdV1dHJSS6ysvgkStASIzc3rNyNwUIiW7qujo2IdFVXncGJyS648qoES9ASIz4UwAAVwQIia6wBmNQQmIwlAM8ByExwKAMh8BFAUIiZwICbggQEt1QDcqYhMSgMAd2EkJiYD0ZDYH/CRASORUQcEOAkOiGalDGJCQGhTmwkxASA+vJaAgQEjkHEHBRgJDoIq67QxMS3fV1ZXRCoiusDIoAO4mcAwi4IUBIdEM1KGMSEoPCHNhJCImB9WQ0BNhJ5BxAwEUBQqKLuO4OTUh019eV0QmJrrAyKALsJHIOIOCGACHRDdWgjElIDApzYCchJAbWk9EQYCeRcwABFwUIiS7iujs0IdFdX1dGJyS6wsqgCLCTyDmAgBsChEQ3VIMyJiExKMyBnYSQGFhPRkOAnUTOAQRcFCAkuojr7tCERHd9XRmdkOgKK4MiwE4i5wACbggQEt1QDcqYhMSgMAd2EkJiYD0ZDQF2EjkHEHBRgJDoIq67QxMS3fV1ZXRCoiusDIoAO4mcAwi4IUBIdEM1KGMSEoPCHNhJCImB9WQ0BNhJ5BxAwEUBQqKLuO4OTUh019eV0QmJrrAyKALsJHIOIOCGACHRDdWgjElIDApzYCchJAbWk9EQYCeRcwABFwUIiS7iujs0IdFdX1dGJyS6wsqgCLCTyDmAgBsChEQ3VIMyJiExKMyBnYSQGFhPRkOAnUTOAQRcFCAkuojr7tCERHd9XRmdkOgKK4MiEGsn8b3J8/TDTzvjpTKkVxulTpUyXsdyEAIRJ0BItLblhEQLW0dItLBplGyDQKyQOGbKPG3+aVe86h70cmtCYrykOCgiBQiJ1radkGhh6wiJFjaNkm0Q4J5EG7pEjfYJEBLt69n/KiYkWtg6QqKFTaNkGwQIiTZ0iRrtEyAk2tczQqK1PRMh0d7eUbmnBa4ZEs+di9KoD+Zo1fotOn7y1BWLmP5ub6VLm9rTi6M4BEImQEgMGb2/E7OT6K9gCL5PSAwBOlNGgsA1Q+LoSXP0zoTZeqjCnfrym/WqX6OS0qROqelzlipfnhya/HZPpUqZPBKMWCMCCRcgJCbczCPfICR6pBEJKYOQmBAtjkUg3gLXDIlPtH5V5UoXU5umNVWmamstmDpIeXPn0Mz5yzRi3Cda+smbSpokSbwn4kAEIkqAkGhtuwmJFraOkGhh0yjZBoFrhsTK9TqpbbPHVbf6/SpRsbnGD+uqu0oX154/Dqhqo276eOyrKlYonw1rpEYEgi9ASAy+eYBmJCQGCDKYwxASg6nNXBEkcM2QWPfp3qp8X2m1bVZTrboMUb7cOdSrU1PnHkXzz7PG91ORAjdGEBVLRSABAoTEBGB561BCorf6Ea9qCInxYuIgBBIqcM2Q2LXfu/p9/yFNG9VL8xatVPcBY1Qg3w3auXufCt+cR7MnvJbQuTgegcgRICRa22tCooWtIyRa2DRKtkHgmiHxxMnTOnsuSlkypXfW8cln32jZyo0qVvgm1alWQTmyZbJhfdSIQGgECImhcQ/ArITEACAGewhCYrDFmS9CBHhPYoQ0mmUGWYCQGGTwwE1HSAycZdBGIiQGjZqJIkvgmiHxi2XrnIdUrvVpWu8RpUieLLK0WC0C8RUgJMZXynPHERI915K4CyIkxm3EEQhch8A1Q6K5B3Hx8g1XDHnq9BnnZ6vmj1J6XqZ9HeR8JSIECInWtpmQaGHrCIkWNo2SbRBI8OVm80BL9Pl/NaxPWxvWR40IhEaAkBga9wDMSkgMAGKwhyAkBluc+SJEIMEhcdPWnWrYtp+WfvymsmfNGCFMLBOBBAoQEhMI5p3DCYne6UW8KyEkxpuKAxFIiECCQ+Ivv/6hmk/1dP4sX+mShRIyF8ciEDkChERre01ItLB1hEQLm0bJNghcMySu/m6r9h88EmsNx0+c0uwFy3X4r2NaMnO4kiVLasMaqRGB4AsQEoNvHqAZCYkBggzmMITEYGozVwQJXDMktu/5lpZ8u/EKikcqltETNSurXKliEcTEUhFIoAAhMYFg3jmckOidXsS7EkJivKk4EIGECFwzJEZFn9f58+djjZU0aRIlTZIkIeNzLAKRKUBItLbvhEQLW0dItLBplGyDwDVD4tqN25QhfZor/j7zoSNHZS5FV32gHIHRhg5TY2gECImhcQ/ArITEACAGewhCYrDFmS9CBP7zcnPxIjfp2aY1Y1Hs+/OwHmrQRfMnva78eXNFCBPLRCBhAvN6D9BnfQcm7Esc7QmBd0/+7ok6KCIBAklTSMlTJuALHIoAAvERSHBI3Przb6r3TB8tmDpIeXPniM8cHINAxAkQEu1tOSHRwt4REi1sGiXbIHBFSDR/aeXoseP67ocdypwxnfLnzelbx7lz0Vqz8ScVK5RPH4991Yb1USMCIREgJIaEPSCTEhIDwhjcQQiJwfVmtogRuCIk9ho8QceOn9DGzTuULm1qFcyf24eRMnlylSlVVPffdTsv0o6YU4SFXo8AIfF61LzxHUKiN/qQoCoIiQni4mAE4itwzcvN5n2IObNl1t13lojvWByHAAL/EyAk2nsqEBIt7B0h0cKmUbINAtcMiYuXb9DoSXM0pFebWA+omL/dnCZNKvXu3MyG9VEjAiERICSGhD0gkxISA8IY3EEIicH1ZraIEfjPB1f+vXBBIwd0jIWxZMUGtX95hFbOHem8IocPAghcKUBItPesICRa2DtCooVNo2QbBK4ZEqs17qYGNSurab1HYq3j72PHdV/N9po5po+KF77JhjVSIwJBFyAkBp08YBMSEgNGGbyBCInBs2amiBK4Zkhs3nGgUqVModEDO8UCWbBkjbr0Ha0vPxqqG3JmjSgsFotAfAUIifGV8t5xhETv9STOigiJcRJxAALXI3DNkPjBzC80eOQ0dW5dX/ffdZuyZs6gNRu36q1xnzjzzJ80UIkTJ7qeOfkOAmEvQEi0t8WERAt7R0i0sGmUbIPANUNi9Pnz6trvPX2xbG2sdZh3J44a2Fkli+a3YX3UiEBIBAiJIWEPyKSExIAwBncQQmJwvZktYgSuGRJjBH7YulPbftmjk6fOKF+eHCpbqpjSpkkVMUAsFIHrESAkXo+aN75DSPRGHxJUBSExQVwcjEB8BeIMiZcOZHYX12/arvlfrtJL7RspTWr+VmZ8oTkusgQIifb2m5BoYe8IiRY2jZJtEIhXSPx51159vni1Pvnsa/119LizrtXzRzl/kYUPAghcKUBItPesICRa2DtCooVNo2QbBK4ZEg8dOapFX6/Tx/O/lgmJ5nNvmVtUt3pFlS93q1KlTG7D+qgRgZAIEBJDwh6QSQmJAWEM7iCExOB6M1vECMQKiWfPRcn8pZW5i1Zo+ZrNDkLpkoVV+d5SGvrudH04qpduK14gYnBYKALXK0BIvF650H+PkBj6HiS4AkJigsn4AgLxEYgVEjds3qEm7fsrR7ZMalznIVWpWNZ5F+Kx4yd1z2PtCInxEeUYBCQREu09DQiJFvaOkGhh0yjZBoFYIXHzT7vU4Nm+Tt2PV7lP1R+8W2VKFXWebCYk2tBOavSKACHRK51IeB2ExISbhfwbhMSQt4ACwlPginsS9+4/JPNXVcy9iOb/Nu9FfOC+OzRz/jJ2EsPzHGBVLggQEl1ADdKQhMQgQQdyGkJiIDUZCwGfwDUfXLlw4YJ+3ParPnOeav5Gp06fUZ5c2VSrank9UrGM8ufNBSMCCFxDgJBo76lBSLSwd4REC5tGyTYIxOsVOFFR0Vq5fovmfPGt7y+wrJw3UhnSpbFhjdSIQNAFCIlBJw/YhITEgFEGbyBCYvCsmSmiBOIVEi8VMQ+xLFmxQVUrl1PKFLwGJ6LOFhYbbwFCYrypPHcgIdFzLYm7IEJi3EYcgcB1CCQ4JF7HHHwFgYgTICTa23JCooW9IyRa2DRKtkGAkGhDl6jROgFConUt8xVMSLSwd4REC5tGyTYIEBJt6BI1WidASLSuZYREe1smERJt7h61e1iAkOjh5lCavQKERHt7x06ihb0jJFrYNEq2QYCQaEOXqNE6AUKidS1jJ9HelrGTaHPvqN3TAoRET7eH4mwVICTa2jmJnUQLe8dOooVNo2QbBAiJNnSJGq0TICRa1zJ2Eu1tGTuJNveO2j0tQEj0dHsozlYBQqKtnWMn0crOsZNoZdso2vsChETv94gKLRQgJFrYtP+VzOVmC3tHSLSwaZRsgwAh0YYuUaN1AoRE61rG5WZ7W8blZpt7R+2eFiAkero9FGerACHR1s5xudnKzrGTaGXbKNr7AoRE7/eICi0UICRa2DQuN9vbNEKivb2jck8LEBI93R6Ks1WAkGhr59hJtLJzhEQr20bR3hcgJHq/R1RooQAh0cKmsZNob9MIifb2jso9LUBI9HR7KM5WAUKirZ1jJ9HKzhESrWwbRXtfgJDo/R5RoYUChEQLm8ZOor1NIyTa2zsq97QAIdHT7aE4WwUIibZ2jp1EKztHSLSybRTtfQFCovd7RIUWChASLWwaO4n2No2QaG/vqNzTAoRET7eH4mwVICTa2jl2Eq3sHCHRyrZRtPcFCIne7xEVWihASLSwaewk2ts0QqK9vaNyTwsQEj3dHoqzVYCQaGvn2Em0snOERCvbRtHeFyAker9HVGihACHRwqaxk2hv0wiJ9vaOyj0tQEj0dHsozlYBQqKtnWMn0crOERKtbBtFe1+AkOj9HlGhhQKERAubxk6ivU0jJNrbOyr3tAAh0dPtoThbBQiJtnaOnUQrO0dItLJtFO19AUKi93tEhRYKEBItbBo7ifY2jZBob++o3NMChERPt4fibBUgJNraOXYSrewcIdHKtlG09wUiMiSeP/+vzp6LUupUKbzfISq0UoCQaGXbnKLfPfm7vcVHauWExEjtPOt2WcCzIXHv/kN65MkXYy2/XKli6v1Cc+XLk8MvllXrt6hVlyH6ds47ypghrV9j8WUEriZgU0hMlCSxEiVOrH+joq/ZzFzFizi/2791u++YpCmSK3fJEkqUJIn2bPj+iu+nzJBeuUsW14nDR3Rg2w5rThRCojWt+v9CCYkWNo2SbRDwfEic/HYP5cqeRX8dPa6+wz5Q9qwZ9Xb/5/2yPXHytHbvPaAiBW9U0iRJ/BqLLyNgc0hMlDiR+mxd7yyhd9E7Yi3FhMf2n3+iYg9WckLkhQsX9GziDM4xLaaOU9mG9X3H/xsdrYlPPau1U6Y7P+v78wZlL1TQ9/sz//yj/ndU0KFfdnn+hAm3kNi5ew8Nf3tULPd7775LK75a6PlexLtAQmK8qTgQgYQIeD4kLvxwsG68Ibuzpv5vTdaBw39rRL8Ozj/v+/OwXn97qlZv+Em3lSigetUr6pGKZZzfPdm2nyrdc7sWfb3eCYQNalZW2+aPK1XK5Nq5e596DBirD0f1UpIkifXrnv3qP2KKzA6j2aXMnjWTnqhRSVUrl9O8RSv19epNypAujeYuWqmiBfPquRa1ZHY1+SBwLQEbdhLrDH1ND3Z6zgmAB7bvuCIkdl+zRPnuLK2Ns+ZqTq9+Spk2rXav33jx369Rw3T0j31aPuZ9JUuVSi9vWCETODtnzuf8/vkv52jl+1P0/afzlb/cner01TxtW7xMbz38uOdPmnALiZ26vaSdu37TG6+/5rNPlSql8uTO7flexLtAQmK8qTgQgYQIeD4ktm1WUxkzpHMC4Yx5y2R2Fk1Qi4o+r5rNe+j2EgXVpO7D+nXPn3qx32gt+miocufMqhIVm6tAvhvUpmlN597DF/u9q2F92qp8uVu1Zftvqt+6jzYtHi9zf2KNZj2c7zzdqLpj13PQOLV88lE1qv2gJk5fqCGjP9JTDarqvrIltWDJGuf7H499NSHOHBthAjaExLTZsihLvrx6ZuYkRZ89Fysk5r61hHptWqVvJ0zW5Jbt4uzegN1blChRIr2Ut/gVx6ZIm0ZvHvtD66bN1ITGT8c5VqgPCMeQeOTI35o07t1Q07o3PyHRPVtGjmgBz4fE8uVKKnWqVDp77pzWbtymu0oX06CX2+iHn3aqZefB+uCtl5QmdUqniX2GTlTNKvepYa0HnJA45Z2eKnVLIed33fq/p6yZMujFtg1ihcTvfvhZLToN0oKpg5U398UdyybtB6hKpbK+kLhi3WaNG3rx/kiz61i96UtaOXekMqRPo1Nnz0f0CcTiry6wsN/rWtR/sBU8vbesVeIkSWKFxMcH9FaVl17Qvh+3KnPePDofHa3vZn6qD9t0jLWmhu++qVsfq6q0WbNoQuNW2jDzU9/vU6ZPpzazpjo7iWeOn9DrZe7X0T/2e94kHEPix7Pn6oGK9ytr1syq+Wg1lb/3Hs/3ISEFRiVKpqjEPIiYELNIOTZ1Cm4p86fXng+Jl15uPnrshB5q0EWvdWupk6dOq9fgCb4QGINQ6d5SavlktStCorlUHX3+X/Xu3CxWSPx88Wr1Gz5Z6xb8/39l/1dIPHj4qCrV7ajFM4cpZ7bMOnXm2jf7+9MYvmu3wMJ+A7VogL0h0ewulq77uLYt+Vq7Vq3VzXeXVdHK92vpO+9pevv/f6Cs68ovdUOJYs4l509efFlL3hrta1yarJmdy9DpcmTXuVOnNOKRWvpt7Xeeb2y4hcQp06br5192KmXKFFq/YaNmz52vGZMnql5t71/6j+/JEiUTEpPH93COiyCB1CmTRtBqA79Uq0KiWX61xt1Uq2p5Fb75RnXpO1qr5o+86sMnl+8kXisk7v79T9Vo3lMr54107juMayfx8pAY+JYwYjgI2HC5Ocb5ajuJJiSaHcLnUmbzteO1XT8oaYoU6p774pPOl37MPYgmRD6bJOMVvzP3Kg499KtOHvlLrxQu7fn2hltIvBy8aas2OnzkiD6fPdPzvYh3gVxujjcVByKQEAHPh0RzD6LZsTt+8rQWL/9OIyd+qo9Gv6K8eXLowfovOIGx49N1nDWv+367oqKj9WD5O+K9k5gkcWJVqNVBJYrcpFpVK2jL9l81ftrn6tGh8VUvNxMSE3J6Re6xtofER3t312N9eqh9mhyKOnXaaaS579CExK45//+p5ZgO1x7cVw+/2FHPpczq3N94+eflTSuVKc8NeiHLTZ4/KcI9JPbo3VcrVq3WN4s+93wv4l0gITHeVByIQEIEPB8SL13MLUXyq02zGqp0Tynnxxt/3KGeA8c5Ty+bT+pUKTWwxzN6oHzpq4bE8/9e0Cudmmrrz7+p3jMXH1wxr8DZsHmHRoz/RAcP/+08nLJi7Wa1aFBNdavfr4kzFmrluh81ZkgXZ45DR46qYp2OWjJzuHJky5QQa46NIAEbQmLiZEmVLEUK9Vj/jczrbvqXuk/nTp/WhfP/KlPePBrw2xb9smKVhj9QXXc3fVJNxo3UdzNmaewTzdV56WdaM+UjbZw1T7mKF1WHhbN0PirKebo5Y+5cav3JFBmDHctXqkyDumoy7p2LTzc/VNPzZ0G4hcSXXnlVTZ58QoUKFtCmzT+qcrUa6tb5efXsevF/08LiQ0gMizayCO8JeDYkJoTq2PGTioqKVpZM6Z0nLBP6iT5/3nfJ+viJU6pcr7NGDuiosqWKJnQojkfAEbAhJLaYMlZlGz0Rq2Mr35+sSS0uPs380IvPq/agvr5/p/7YvMV5+MTsFPbdsVHZCxbwfffM8eN6u1od7VyxWulz5dBrv2xS8tSpfb8/+MtODbjzfp059o/nz5BwC4llK1TWuu82+NybN26oUW++oVSpUnm+F/EukJAYbyoORCAhAmEREhOy4Ksd+2z34TLh0Lyoe93321SkYF6NGdxFiRMnPHD6WwvfDw8BG0JifKTNX1Ux70o0Ie/4gUOxvmKeXjavyvnnz4NXfUm2CYs5ixZ2npA+cehIfKbzxDHhFhIN6rFjx3To8BHdkCunUl8S3j0BHogiCImBUGQMBK4QICRK2vbLHucS9LmoaOfF3XeVLu68ZJsPAtcrEC4h8XrXb/P3wjEk2tyPeNVOSIwXEwchkFABQmJCxTgegXgIEBLjgeTRQwiJHm3Mf5VFSLSwaZRsgwAh0YYuUaN1AoRE61rmK5iQaGHvCIkWNo2SbRAgJNrQJWq0ToCQaF3LCIn2tkwiJNrcPWr3sAAh0cPNoTR7BQiJ9vaOnUQLe0dItLBplGyDACHRhi5Ro3UChETrWsZOor0tYyfR5t5Ru6cFCImebg/F2SpASLS1cxI7iRb2jp1EC5tGyTYIEBJt6BI1WidASLSuZewk2tsydhJt7h21e1qAkOjp9lCcrQKERFs7x06ilZ1jJ9HKtlG09wUIid7vERVaKEBItLBp/yuZy80W9o6QaGHTKNkGAUKiDV2iRusECInWtYzLzfa2jMvNNveO2j0tQEj0dHsozlYBQqKtneNys5WdYyfRyrZRtPcFCIne7xEVWihASLSwaVxutrdphER7e0flnhYgJHq6PRRnqwAh0dbOsZNoZecIiVa2jaK9L0BI9H6PqNBCAUKihU1jJ9HephES7e0dlXtagJDo6fZQnK0ChERbO8dOopWdIyRa2TaK9r4AIdH7PaJCCwUIiRY2jZ1Ee5tGSLS3d1TuaQFCoqfbQ3G2ChASbe0cO4lWdo6QaGXbKNr7AoRE7/eICi0UICRa2DR2Eu1tGiHR3t5RuacFCImebg/F2SpASLS1c+wkWtk5QqKVbaNo7wsQEr3fIyq0UICQaGHT2Em0t2mERHt7R+WeFiAkero9FGerACHR1s6xk2hl5wiJVraNor0vQEj0fo+o0EIBQqKFTWMn0d6mERLt7R2Ve1qAkOjp9lCcrQKERFs7x06ilZ0jJFrZNor2vgAh0fs9okILBQiJFjaNnUR7m0ZItLd3VO5pAUKip9tDcbYKEBJt7Rw7iVZ2jpBoZdso2vsChETv94gKLRQgJFrYNHYS7W0aIdHe3lG5pwUIiZ5uD8XZKkBItLVz7CRa2TlCopVto2jvCxASvd8jKrRQgJBoYdPYSbS3aYREe3tH5Z4WICR6uj0UZ6sAIdHWzrGTaGXnCIlWto2ivS9ASPR+j6jQQgFCooVNYyfR3qYREu3tHZV7WoCQ6On2UJytAoREWzvHTqKVnSMkWtk2iva+ACHR+z2iQgsFCIkWNo2dRHubRki0t3dU7mkBQqKn20NxtgoQEm3tHDuJVnaOkGhl2yja+wKERO/3iAotFCAkWtg0dhLtbRoh0d7eUbmnBQiJnm4PxdkqQEi0tXPsJFrZOUKilW2jaO8LEBK93yMqtFCAkGhh09hJtLdphER7e0flnhYgJHq6PRRnqwAh0dbOsZNoZecIiVa2jaK9L0BI9H6PqNBCAUKihU1jJ9HephES7e0dlXtagJDo6fZQnK0ChERbO8dOopWdIyRa2TaK9r4AIdH7PaJCCwUIiRY2jZ1Ee5tGSLS3d1TuaQFCoqfbQ3G2ChASbe0cO4lWdo6QaGXbKNr7AoRE7/eICi0UICRa2DR2Eu1tGiHR3t5RuacFCImebg/F2SpASLS1c+wkWtk5QqKVbaNo7wsQEr3fIyq0UICQaGHT2Em0t2mERHt7R+WeFiAkero9FGerACHR1s6xk2hl5wiJVraNor0vQEj0fo+o0EIBQqKFTWMn0d6mERLt7R2Ve1qAkOjp9lCcrQKERFs7x06ilZ0jJFrZNor2vgAh0fs9okILBQiJFjaNnUR7m0ZItLd3VO5pAUKip9tDcQgggAACCCCAQGgECImhcWdWBBBAAAEEEEDA0wKERE+3h+IQQAABBBBAAIHQCBASQ+POrAiEhcD58//q7LkopU6VIizWwyJiC+z544D+2H9Yd99ZAhoEEIhAAUJiBDadJUeWwN79h/TIky/GWnS5UsXU+4Xmypcnh18Yq9ZvUasuQ/TtnHeUMUNav8biy/8tMOvzb9Rr8AQ9UbOyXunU1Hfw16s2afNPu/Rci1q+n42f9rny5MqqRyqW9Yt1xtylmr1whQt7SzsAABHDSURBVKaN6uXXOHwZAQTsFCAk2tk3qkYg3gIxIXHy2z2UK3sW/XX0uPoO+0DZs2bU2/2fj/c4VzvwxMnT2r33gIoUvFFJkyTxayy+/N8CTdoP0JG/j+nQkWNaMedtpUiezPnC1FlfaeHStTL9jfl06DVCRQvmU9tmNf1iJST6xceXEbBegJBofQtZAAL/LRATEhd+OFg33pDdObj/W5N14PDfGtGvg/PP+/48rNffnqrVG37SbSUKqF71inqkYhnndwPf+VBJkybRzt/2af2m7ap0z+1q37K2M9bO3fvUY8BYfTiql5IkSaxf9+xX/xFTZHYYzS5l9qyZ9ESNSqpauZzmLVqpr1dvUoZ0aTR30UoVLZjX2f0yu5p8/lvA9OehBl00470+qt+6j95+rYMq31faCeiNn3vNCf63FMnvDNK47kPqO2ySUqZIphtyZFWhm/PotW4t1a3/e1q57kfn2AL5blC7p2r5enz6zDmNmvipFn29TqdOn1GZ24vqpfaNtPTbjbF2EqfPWaIFS9dq8MttnP/I4IMAAuEtQEgM7/6yOgQUExLNrlLGDOmcQDhj3jJn58kEtajo86rZvIduL1FQTeo+rF/3/KkX+43Woo+GKnfOrHq2+3AnHHZ8uo4K5s+jYe/OULnSxdS5dX1t2f6bE1o2LR4vc39ijWY9nO883ai6I99z0Di1fPJRNar9oCZOX6ghoz/SUw2q6r6yJbVgyRrn+x+PfZUuxSEw4aPP9cXSdZr+Xm8n7EVFRWtYn3Y6dfqsho+ZoTUbflKv/12Czp0zm7q+9q7y5s6uWlXLK22aVCpWKJ+mzvrS6V+WjOm1bNX3Gj5mplbOHakM6dM4l7G/XbdZ7VvUdsL9J599owY1K+unHbt9IXH2guV6edB4TXmnp0rdUoieIYBABAgQEiOgySwxsgViQmL5ciWVOlUqnT13Tms3btNdpYtp0Mtt9MNPO9Wy82B98NZLSpM6pYPVZ+hE1axynxrWesAJiaVLFvIFPxMgpnyySLMnvBYrJH73w89q0WmQFkwd7AQU8zGXSKtUKusLiSvWbda4oRfvjzS7jtWbvuQLKpHdpf9efbXG3dSo9kOOo7kHse1Lw7Vy3khnVza+l5tNiN++c4+2/bJHBw8f1dsTZjmhs0C+3LqzyjPObqMJlZd+Yi43N69fRZ37jHTOkTtvK0KrEEAgQgQIiRHSaJYZuQJXu9x89NgJ5/KlCQYnT512dpIu3x2qdG8ptXyy2hUh8YtlazXsvZn6YtqQWCHx88Wr1W/4ZK1b8K4P+79Cogkqlep21OKZw5QzW+bIbVAcKze7eXWf7q3K95ZS1iwZde5clD5duMIX6uITEk+eOqM23YY5AbHyfaWce1PHTp3vPJCSLm1qJ6zPn/S68ufNdUVIfHXYB87PHq9yn/p3b0WfEEAgggQIiRHUbJYamQJXC4lGwuxOmZ2jwjffqC59R2vV/JFXffjk8p3Ea4XE3b//qRrNe/p2uOLaSSQkxu98HPbeDC1b+b2zIxvzWfXdVuce0IlvdteHsxfLBHRzGTjm4zy4UiCv2jZ/3PnR4uUbZH4Ws/toflaiYnMnJOa7Mafueayd3urXXg+Wv+OKkDhk9HS92LaBXn1jovNUtXm6mg8CCESGACExMvrMKiNY4NKnm82O3fGTp7V4+XcaOfFTfTT6FeXNk0MP1n/BCYzmvkPzWff9dkVFRzuhIb4hMUnixKpQq4NKFLlJtapW0Jbtv8q8iqVHh8ZXvdxMSIz7pIw+f16V6nRUp2fqqXa1Cr4vrPt+m5p3HKivpr+h/QePqHXXYVowdZATHDOmT+vsEpr7SM3T62YX8eedv6vlC4M1a3w/Z9f2s8WrnYeXTEi8tXgBNX6uvxIlSqSezzfWTTfm1GdfrdbtJQrI3EIQ8wqcRV+vV6fe7zj3QsY81BT3CjgCAQRsFiAk2tw9akcgHgJXe0+ieRK2TbMaqnRPKWeEjT/uUM+B45ynZc0ndaqUGtjjGT1QvrQTEu+4tbBaNXzU+d0Xy9bJ7G6Zy81bf/5N9Z65+OCKeQXOhs07NGL8Jzp4+G/n4ZQVazerRYNqqlv9fk2csdB5unbMkC7OOIeOHFXFOh21ZOZw5ciWKR4ribxDzL2jT3UaeMV7KM39hRXrPK+WDR9V4zoP6bkeb2r5ms0O0PqFY/TnwSPOPYQ/79rr3EYwaUQP55+//Ga9c4y5dL3k243OfySULHaz9vxxUD1eH+ucB+aTJ1c2jR36olZv2CrzwErMexKnfbpYr705mXsTI+9UZMURKkBIjNDGs2wEriZw7PhJ58nZLJnSOztLCf2Yna+Y9yUeP3FKlet11sgBHVW2VNGEDsXxCRQwvUueLJlSpUzu++aRv/9R+nRplCzpxXdYHv7rmLPbmClDuquObt57eS4qWpkzXv33CSyJwxFAwHIBQqLlDaR8BLwkYHYdTTg079Azl0SLFMyrMYO7KHHihAdOL62LWhBAAIFIFCAkRmLXWTMCLgmYp2fNJWizG2Vetn1X6eLOzhUfBBBAAAH7BAiJ9vWMihFAAAEEEEAAAdcFCImuEzMBAggggAACCCBgnwAh0b6eUTECCCCAAAIIIOC6ACHRdWImQAABBBBAAAEE7BMgJNrXMypGAAEEEEAAAQRcFyAkuk7MBAgggAACCCCAgH0ChET7ekbFCCCAAAIIIICA6wKERNeJmQABBBBAAAEEELBPgJBoX8+oGAEEEEAAAQQQcF2AkOg6MRMggAACCCCAAAL2CRAS7esZFSOAAAIIIIAAAq4LEBJdJ2YCBBBAAAEEEEDAPgFCon09o2IEEEAAAQQQQMB1AUKi68RMgAACCRH4YetOHf7rmPOVxIkTK3vWjCpaMJ8SJ06UkGHideyBQ3+rY+931PP5xrqlSH5t/HGH9u47pMcevide3w/UQe9OmqsDh/9W787NAjUk4yCAAAJ+CxAS/SZkAAQQCKRAh14jtHj5hlhD5suTQ+8O6qy8uXMEcirt+eOAqjbqpvFvdNVddxRXn6ETNXP+Mm1ZNjHOedZs/EktOg3SgqmDlTd39jiP/68Deg4cp917D2jKOz39GocvI4AAAoEUICQGUpOxEEDAbwETEg8dOaZpo3opKipaG3/8Re16vKmb8+bS9Pd6+z3+pQNcHhJPnT6rqOhoZUiXJs55Vn+3VS1fGKwFUwf5HV4JiXFycwACCIRAgJAYAnSmRACBawtcGhJjjho+ZqbGffiZ1i8co7lfrNCajdvUrnlNTZ29WLt271OHlrVVumRhLV+zWe9NnutcNs6TK5tqVrlPTzeqrmRJkzhDHfvnpAaPmqZFX693/rlEkZu07vttvp1Es4u4av0WDevTzleg+eexU+dr87ZflS1LBt19RwnVr1FJnXq/4+z+FSuUTylTJFfBm3KrT5fmOn/+X02Z9aU+mf+1du7ep8I351GbpjX1SMUyvjG/Wv6dRr4/Wz/v2qsC+W7Q2XNRypYlIzuJ/IuBAAKeEiAkeqodFIMAAlcLiX2HT9L0OUu0afF4jRj3icZP+9yBMsEwR7ZMeqJGJZ05e05tug1z7id8sPwdMvc2muNeaFNfLRpU07//XtCTz/bVj9t/Vd3q9+vOW4to9Yat+nThCl9IHDH+E+efl8wc7oz/9apNavvScCfoNahZWcdPntYHMxZq0MtttPTbDfpw9mK1bVZTmTOlV+aM6fRIxbIa9t4MTft0iZ58vLJuLV5AC5eu1YIla/ThqF66rXgBLV/zg1OnuYTepO7Dzm7pxBkLdUOOrIRETn8EEPCUACHRU+2gGAQQMCFx359HnHsQj/1zQt+u+1GDRk5zgt2rXZ7yhTBz/16RAjf6wGq1eNnZjRszpIvvZ537jNQvv/6huR8M8IWzQT1bq/pDdzvHXH65+fKQWKNZD2eX74tpQ3xjnjp9RhcuSJt/2nXF5eYjf/+jCrU6qHPr+mr5ZDXnO9Hnz+vu6u1U59EK6v5cQz3R+lUd/eeEcy9jzMM4XG7mvEcAAS8KEBK92BVqQiCCBa724ErDWg+o0zP1lDpVSickfrFsXazgZnbjbn+olbOblyNbZp+euRxsQp15EMVcrjaXrb+ZPUJZMqWPMySacFj64afVrN4j6truySs6crV7Etdv2q5mz7/uXOpOlza17zs/7ditivfcrrf6tddtD7R0dhBNYIz5EBIj+IRn6Qh4WICQ6OHmUBoCkShgQuJve/7U4F5tlDpVCuXKkdV3T6HxuFpIPHnqjMpWa6N61SvqgfKlL2NLpPLlSurNsR879xZ+/9V433j/tZN44uRplXv0WT3XopaebVozXiHR3BPZptsb6tGh8RVPPGfMkE4F8uVSmaptnMDbquGjhMRIPMFZMwIWCRASLWoWpSIQCQJXuyfx0nVfLSSa35d/vL3K3F5Mw/q0jcV04cIFJUqUSDPmLtWrwz7QzDF9VLzwTXHuJMaMae4VvPypanN/46atv6jxc/316fuvqVD+PP8b76CqNurqvO/QPNxy6SemDhMS7ypdTG/3f9736x6vj9WePw5yT2IknOCsEQGLBAiJFjWLUhGIBIHrDYnmIZL+b0127gU0D6+cOxet77fscB4+Mfcp/nnoLz1Qr7PzNPIzjR+TCW1mZ9FcCo55T+Ll9ySaB19MKDU7lHWq36+zZ885D660alRdxQrmVamHn1aj2g+qbvWKMjuPpUsWUszlcnP/5B23Fpa5T/Gb1ZucF4N3fLquBoyYoqmzvnIepqlw163OPZemjlK3FCIkRsIJzhoRsEiAkGhRsygVgUgQiCskmvsKzRPDlz5MYlzMq2emzvpSb0+Y7dyHGPMxodE8SGI+8xatVPcBY3y/e7zKfRefbh7WVXeVLq63J8zS7AXLfU83R0Wf13uT5mr0pDm+75i/zDL81Xa6IWdWfTDzC42bOl9/HT3uPMls3u147PhJ59K22bmM+Zh7Jc0l6KqVy+nosRNq//IIbdj8s/NrE1qTJE6sZMmSEhIj4QRnjQhYJEBItKhZlIoAAnELmB1C82f9zBPI5gGVJEkSx/qSeVXO/gNHlDtnViVPnizuAf8XQA8e/ltp0qRS+kseSDFfNk8vm/myZs6gpEkuvo8x5ueHDh9VypTJlSlDuivmMX8S0FwGN392kA8CCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFiAkBjiBjA9AggggAACCCDgRQFCohe7Qk0IIIAAAggggECIBQiJIW4A0yOAAAIIIIAAAl4UICR6sSvUhAACCCCAAAIIhFjg/wBnHsExlJTsnQAAAABJRU5ErkJggg==","text/html":"
"},"metadata":{},"output_type":"display_data"}],"source":"import plotly.graph_objs as go\n\n# Calculate the confusion matrix\nconf_matrix = confusion_matrix(y_true, y_pred)\n\n# Create a DataFrame from the confusion matrix\nconf_matrix_df = pd.DataFrame(\n conf_matrix,\n columns = ['Benign', 'Attack'],\n index = ['Benign', 'Attack']\n)\n\n# Create an empty list to store annotations\nannotations = []\n\n# Define a threshold for text color\nthresh = conf_matrix_df.values.max() / 2\n\n# Loop through the confusion matrix and add annotations with text color based on the threshold\nfor i in range(len(conf_matrix_df)):\n for j in range(len(conf_matrix_df)):\n value = conf_matrix_df.iloc[i, j]\n text_color = \"white\" if value > thresh else \"black\"\n annotations.append(\n go.layout.Annotation(\n x = j,\n y = i,\n text = str(value),\n font = dict(color = text_color),\n showarrow = False,\n )\n )\n\n# Create a heatmap trace with showscale set to False\ntrace = go.Heatmap(\n z = conf_matrix_df.values,\n x = ['Benign', 'Attack'],\n y = ['Benign', 'Attack'],\n colorscale = 'Reds',\n showscale = False\n)\n\n# Create the figure with heatmap and annotations\nfig = go.Figure(\n data = [trace],\n layout = {\n \"title\": \"Confusion Matrix\",\n \"xaxis\": {\"title\": \"Predicted\", \"scaleanchor\": \"y\", \"scaleratio\": 1},\n \"yaxis\": {\"title\": \"Actual\"},\n \"annotations\": annotations,\n \"height\": 400,\n \"width\": 400\n }\n)\n\nfig.show()"},{"cell_type":"code","execution_count":39,"id":"abaddb79-c9ea-4331-968e-98cd540f034b","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:44:51.128673Z","iopub.status.busy":"2023-10-04T15:44:51.128457Z","iopub.status.idle":"2023-10-04T15:44:51.135317Z","shell.execute_reply":"2023-10-04T15:44:51.134678Z","shell.execute_reply.started":"2023-10-04T15:44:51.128653Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Confusion Matrix:\nBenign (Actual) -> Benign (Predicted): 1633\nBenign (Actual) -> Attack (Predicted): 5\nAttack (Actual) -> Benign (Predicted): 75\nAttack (Actual) -> Attack (Predicted): 287\n"}],"source":"# Create confusion matrix\nconf_matrix = confusion_matrix(y_true, y_pred)\n\n# Define class labels\nclass_labels = ['Benign', 'Attack']\n\n# Print confusion matrix with labels\nprint(\"Confusion Matrix:\")\nfor i in range(len(class_labels)):\n for j in range(len(class_labels)):\n print(f\"{class_labels[i]} (Actual) -> {class_labels[j]} (Predicted): {conf_matrix[i][j]}\")"},{"cell_type":"markdown","id":"a212b279-edce-4b3b-ad82-3b4933b1b10f","metadata":{"language":"python"},"source":"### Accuracy"},{"cell_type":"code","execution_count":40,"id":"bdb00bdc-4264-4ee5-b953-fed3c7317dd6","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:07.771340Z","iopub.status.busy":"2023-10-04T15:45:07.771044Z","iopub.status.idle":"2023-10-04T15:45:07.783637Z","shell.execute_reply":"2023-10-04T15:45:07.783111Z","shell.execute_reply.started":"2023-10-04T15:45:07.771323Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Accuracy: 0.960\nPrecision: 0.983\nRecall: 0.793\n"}],"source":"# Calculate accuracy\nacc = accuracy_score(y_true, y_pred, normalize = True, sample_weight = None)\nprecision = precision_score(y_true, y_pred)\nrecall = recall_score(y_true, y_pred)\n\nprint(f\"Accuracy: {acc:.3f}\")\nprint(f\"Precision: {precision:.3f}\")\nprint(f\"Recall: {recall:.3f}\")"},{"cell_type":"markdown","id":"30a06f84-7d9c-48d2-9b59-5d0aafb9b328","metadata":{"language":"python"},"source":"### Per Class Accuracy"},{"cell_type":"code","execution_count":42,"id":"46f58998-e5ce-4c31-9612-25669254e98c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:15.565738Z","iopub.status.busy":"2023-10-04T15:45:15.565539Z","iopub.status.idle":"2023-10-04T15:45:15.574517Z","shell.execute_reply":"2023-10-04T15:45:15.573983Z","shell.execute_reply.started":"2023-10-04T15:45:15.565723Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
typeaccuracy
0Benign1.00
1Attack0.79
\n
","text/plain":" type accuracy\n0 Benign 1.00\n1 Attack 0.79"},"metadata":{},"output_type":"display_data"}],"source":"# Calculate per class accuracy\ncmd = confusion_matrix(y_true, y_pred, normalize = \"true\").diagonal()\nper_class_accuracy_df = pd.DataFrame([(index, round(value,4)) for index, value in zip(['Benign', 'Attack'], cmd)], columns = ['type', 'accuracy'])\nper_class_accuracy_df = per_class_accuracy_df.round(2)\ndisplay(per_class_accuracy_df)"},{"cell_type":"markdown","id":"18da66d1-fa5f-4c0a-913f-915fc49c9411","metadata":{"language":"python"},"source":"## Predict Values Directly from Model\n\nWe achieved excellent results with SingleStoreDB. Now, let's explore what happens when we bypass the similarity search step and make predictions directly from the model. In other words, we'll utilize the model responsible for generating the embeddings as a classifier. We can then compare the accuracy of this approach with that of the similarity search method."},{"cell_type":"code","execution_count":43,"id":"1ae8e5cb-c0fe-46e1-950f-3274644d869d","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:23.411073Z","iopub.status.busy":"2023-10-04T15:45:23.410802Z","iopub.status.idle":"2023-10-04T15:45:24.327503Z","shell.execute_reply":"2023-10-04T15:45:24.327028Z","shell.execute_reply.started":"2023-10-04T15:45:23.411055Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"63/63 [==============================] - 0s 869us/step\n"}],"source":"from tensorflow.keras.utils import normalize\nimport numpy as np\n\ndata_sample = normalize(data_22_cleaned.iloc[:, :-1])[-2000:]\ny_pred_model = model.predict(normalize(data_sample)).flatten()\ny_pred_model = np.round(y_pred_model)"},{"cell_type":"markdown","id":"23953237-8c81-4fe3-bead-aacbcc994c05","metadata":{"language":"python"},"source":"## Visualize Results\n\n### Confusion 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","text/html":"
"},"metadata":{},"output_type":"display_data"}],"source":"# Create confusion matrix\nconf_matrix = confusion_matrix(y_true, y_pred_model)\n\n# Create a DataFrame from the confusion matrix\nconf_matrix_df = pd.DataFrame(\n conf_matrix,\n columns = ['Benign', 'Attack'],\n index = ['Benign', 'Attack']\n)\n\n# Create an empty list to store annotations\nannotations = []\n\n# Define a threshold for text color\nthresh = conf_matrix_df.values.max() / 2\n\n# Loop through the confusion matrix and add annotations with text color based on the threshold\nfor i in range(len(conf_matrix_df)):\n for j in range(len(conf_matrix_df)):\n value = conf_matrix_df.iloc[i, j]\n text_color = \"white\" if value > thresh else \"black\"\n annotations.append(\n go.layout.Annotation(\n x = j,\n y = i,\n text = str(value),\n font = dict(color=text_color),\n showarrow = False,\n )\n )\n\n# Create a heatmap trace with showscale set to False\ntrace = go.Heatmap(\n z = conf_matrix_df.values,\n x = ['Benign', 'Attack'],\n y = ['Benign', 'Attack'],\n colorscale = 'Reds',\n showscale = False\n)\n\n# Create the figure with heatmap and annotations\nfig = go.Figure(\n data = [trace],\n layout = {\n \"title\": \"Confusion Matrix\",\n \"xaxis\": {\"title\": \"Predicted\", \"scaleanchor\": \"y\", \"scaleratio\": 1},\n \"yaxis\": {\"title\": \"Actual\"},\n \"annotations\": annotations,\n \"height\": 400,\n \"width\": 400\n }\n)\n\nfig.show()"},{"cell_type":"code","execution_count":45,"id":"c9621933-9b22-4536-bf7a-6c1c78c4ac4d","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:36.827671Z","iopub.status.busy":"2023-10-04T15:45:36.827383Z","iopub.status.idle":"2023-10-04T15:45:36.834072Z","shell.execute_reply":"2023-10-04T15:45:36.833474Z","shell.execute_reply.started":"2023-10-04T15:45:36.827653Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Confusion Matrix:\nBenign (Actual) -> Benign (Predicted): 1638\nBenign (Actual) -> Attack (Predicted): 0\nAttack (Actual) -> Benign (Predicted): 258\nAttack (Actual) -> Attack (Predicted): 104\n"}],"source":"# Create confusion matrix\nconf_matrix = confusion_matrix(y_true, y_pred_model)\n\n# Define class labels\nclass_labels = ['Benign', 'Attack']\n\n# Print confusion matrix with labels\nprint(\"Confusion Matrix:\")\nfor i in range(len(class_labels)):\n for j in range(len(class_labels)):\n print(f\"{class_labels[i]} (Actual) -> {class_labels[j]} (Predicted): {conf_matrix[i][j]}\")"},{"cell_type":"markdown","id":"7168534e-77c1-440f-b55a-7fad84af37aa","metadata":{"language":"python"},"source":"### Accuracy"},{"cell_type":"code","execution_count":46,"id":"9ad16de3-2eb6-4ae3-b269-76c1f131fe63","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:42.382264Z","iopub.status.busy":"2023-10-04T15:45:42.382020Z","iopub.status.idle":"2023-10-04T15:45:42.393023Z","shell.execute_reply":"2023-10-04T15:45:42.392509Z","shell.execute_reply.started":"2023-10-04T15:45:42.382248Z"},"language":"python","trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":"Accuracy: 0.871\nPrecision: 1.000\nRecall: 0.287\n"}],"source":"# Calculate accuracy\nacc = accuracy_score(y_true, y_pred_model, normalize = True, sample_weight = None)\nprecision = precision_score(y_true, y_pred_model)\nrecall = recall_score(y_true, y_pred_model)\n\nprint(f\"Accuracy: {acc:.3f}\")\nprint(f\"Precision: {precision:.3f}\")\nprint(f\"Recall: {recall:.3f}\")"},{"cell_type":"markdown","id":"b80e72e5-814c-4533-9685-b126a0b481e7","metadata":{"language":"python"},"source":"### Per Class Accuracy"},{"cell_type":"code","execution_count":47,"id":"bc88066d-df3b-48be-9ff6-246587e6630c","metadata":{"execution":{"iopub.execute_input":"2023-10-04T15:45:49.034077Z","iopub.status.busy":"2023-10-04T15:45:49.033804Z","iopub.status.idle":"2023-10-04T15:45:49.043624Z","shell.execute_reply":"2023-10-04T15:45:49.043172Z","shell.execute_reply.started":"2023-10-04T15:45:49.034059Z"},"language":"python","trusted":true},"outputs":[{"data":{"text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
typeaccuracy
0Benign1.00
1Attack0.29
\n
","text/plain":" type accuracy\n0 Benign 1.00\n1 Attack 0.29"},"metadata":{},"output_type":"display_data"}],"source":"# Calculate per class accuracy\ncmd = confusion_matrix(y_true, y_pred_model, normalize = \"true\").diagonal()\nper_class_accuracy_df = pd.DataFrame([(index, round(value,4)) for index, value in zip(['Benign', 'Attack'], cmd)], columns = ['type', 'accuracy'])\nper_class_accuracy_df = per_class_accuracy_df.round(2)\ndisplay(per_class_accuracy_df)"},{"cell_type":"markdown","id":"5455ba06-f2ba-4e2e-9494-c65ab2d9d96c","metadata":{"language":"python"},"source":"# Conclusions\n\nUtilizing SingleStoreDB's vector embeddings, we achieved an extremely high detection rate for attacks while maintaining a very small false-positive rate. Furthermore, our example showed that our similarity search methodology surpassed the direct classification approach that relies on the classifier's embedding model."}],"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.4"},"singlestore_connection":{"connectionID":"a98658e6-5e5d-4be9-be2e-9fa993172504","defaultDatabase":"siem_log_kafka_demo"},"singlestore_row_limit":300},"nbformat":4,"nbformat_minor":5} \ No newline at end of file From 349a5a4351edb0103875d4ac16eed25454cfc725 Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 13:02:38 -0700 Subject: [PATCH 23/24] Delete notebooks/network-intrusion-detection-part-2/readme --- notebooks/network-intrusion-detection-part-2/readme | 1 - 1 file changed, 1 deletion(-) delete mode 100644 notebooks/network-intrusion-detection-part-2/readme diff --git a/notebooks/network-intrusion-detection-part-2/readme b/notebooks/network-intrusion-detection-part-2/readme deleted file mode 100644 index 8b137891..00000000 --- a/notebooks/network-intrusion-detection-part-2/readme +++ /dev/null @@ -1 +0,0 @@ - From b3aa9d10cf31b0cd52ee6dda4e4499cf02c87f9c Mon Sep 17 00:00:00 2001 From: arno756 Date: Mon, 16 Oct 2023 13:03:00 -0700 Subject: [PATCH 24/24] Add files via upload --- notebooks/network-intrusion-detection-part-3/meta.toml | 6 ++++++ notebooks/network-intrusion-detection-part-3/notebook.ipynb | 1 + 2 files changed, 7 insertions(+) create mode 100644 notebooks/network-intrusion-detection-part-3/meta.toml create mode 100644 notebooks/network-intrusion-detection-part-3/notebook.ipynb diff --git a/notebooks/network-intrusion-detection-part-3/meta.toml b/notebooks/network-intrusion-detection-part-3/meta.toml new file mode 100644 index 00000000..ec11fa1b --- /dev/null +++ b/notebooks/network-intrusion-detection-part-3/meta.toml @@ -0,0 +1,6 @@ +[meta] +title="Part 3 or Real-time threat Detection - Integrate with Kafka, run and visualize Threat Detection on incoming logs. +This notebook requires adjustments to work out of the box." +icon="browser" +tags=["iot", "cybersecurity", "training", "vectordb", "kafka", "pipeline", "realtime"] +destinations=["spaces"] \ No newline at end of file diff --git a/notebooks/network-intrusion-detection-part-3/notebook.ipynb b/notebooks/network-intrusion-detection-part-3/notebook.ipynb new file mode 100644 index 00000000..d550aeb8 --- /dev/null +++ b/notebooks/network-intrusion-detection-part-3/notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","id":"37793ab8-641c-4596-9e5b-445dd92ba229","metadata":{"language":"python"},"source":["
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SingleStore Notebooks
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IT Threat Detection, Part 3

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"]},{"cell_type":"markdown","id":"184309fb-7eef-4ae2-bb10-dd431eba6811","metadata":{"language":"python"},"source":["
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Get pipeline data from Confluent (Kafka)

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"}},"cell_type":"markdown","id":"996738fc-01ab-4d72-8acd-a96f2862c476","metadata":{"language":"python"},"source":["![Kafka_SingleStore.png](attachment:e89ae78c-5f57-46a6-82d2-b38fb4b926f5.png)"]},{"cell_type":"markdown","id":"f6100d05-d796-452b-893c-8e9240d9a3f9","metadata":{"language":"python"},"source":["We start creating a simple table to load the logs into a JSON column"]},{"cell_type":"code","execution_count":325,"id":"89c133a9-1765-4f61-a9bb-fce74f4a7c0a","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:33.825700Z","iopub.status.busy":"2023-09-29T05:21:33.825334Z","iopub.status.idle":"2023-09-29T05:21:33.861359Z","shell.execute_reply":"2023-09-29T05:21:33.860889Z","shell.execute_reply.started":"2023-09-29T05:21:33.825680Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":[]},"execution_count":325,"metadata":{},"output_type":"execute_result"}],"source":["%%sql\n","drop PIPELINE `siem_log_real`;\n","drop table `siem_log_real`;"]},{"cell_type":"code","execution_count":326,"id":"f09a053e-3082-422a-af8a-3cc81846b172","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:35.566329Z","iopub.status.busy":"2023-09-29T05:21:35.566082Z","iopub.status.idle":"2023-09-29T05:21:35.655301Z","shell.execute_reply":"2023-09-29T05:21:35.654731Z","shell.execute_reply.started":"2023-09-29T05:21:35.566312Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":[]},"execution_count":326,"metadata":{},"output_type":"execute_result"}],"source":["%%sql\n","CREATE TABLE `siem_log_real` (\n"," `logs` JSON COLLATE utf8_bin\n"," , SHARD KEY () \n",") AUTOSTATS_CARDINALITY_MODE=PERIODIC AUTOSTATS_HISTOGRAM_MODE=CREATE SQL_MODE='STRICT_ALL_TABLES';"]},{"cell_type":"markdown","id":"0f9e5c48-ed62-4354-a311-90672862fcae","metadata":{"language":"python"},"source":["We create a pipeline from the Confluent Cluster with an interval of 20ms"]},{"cell_type":"code","execution_count":327,"id":"2022c2aa-4b29-41b3-894f-1a2e40311ed2","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:37.894987Z","iopub.status.busy":"2023-09-29T05:21:37.894573Z","iopub.status.idle":"2023-09-29T05:21:38.197432Z","shell.execute_reply":"2023-09-29T05:21:38.196849Z","shell.execute_reply.started":"2023-09-29T05:21:37.894968Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":[]},"execution_count":327,"metadata":{},"output_type":"execute_result"}],"source":["%%sql\n","CREATE PIPELINE `siem_log_real`\n","AS LOAD DATA KAFKA 'pkc-XXX.us-east-1.aws.confluent.cloud:9092/connections_siem_logs'\n","CONFIG '{\\\"sasl.username\\\": \\\"YOURKEY\\\",\\n \\\"sasl.mechanism\\\": \\\"PLAIN\\\",\\n \\\"security.protocol\\\": \\\"SASL_SSL\\\",\\n \\\"ssl.ca.location\\\": \\\"/etc/pki/ca-trust/extracted/pem/tls-ca-bundle.pem\\\"}'\n","CREDENTIALS '{\"sasl.password\": \"YOURPASSWORD\"}'\n","BATCH_INTERVAL 20\n","DISABLE OFFSETS METADATA GC\n","INTO TABLE `siem_log_real`\n","FIELDS TERMINATED BY '\\t' ENCLOSED BY '' ESCAPED BY '\\\\'\n","LINES TERMINATED BY '\\n' STARTING BY '';"]},{"cell_type":"markdown","id":"a8511976-97ba-4bc0-8dca-0b41cd6e0c84","metadata":{"language":"python"},"source":["Let's start the pipeline"]},{"cell_type":"code","execution_count":328,"id":"042af566-8b5d-47e1-9626-81c2aad6b4a0","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:40.145374Z","iopub.status.busy":"2023-09-29T05:21:40.145009Z","iopub.status.idle":"2023-09-29T05:21:40.160868Z","shell.execute_reply":"2023-09-29T05:21:40.160427Z","shell.execute_reply.started":"2023-09-29T05:21:40.145355Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":[]},"execution_count":328,"metadata":{},"output_type":"execute_result"}],"source":["%%sql\n","Start pipeline siem_log_real;"]},{"cell_type":"markdown","id":"5a414b17-23a0-465a-81b0-3a62e7f1f4c3","metadata":{"language":"python"},"source":["We extract a few elements from the JSON column such as timestamp, Log_ID, and the vector to be stored in a blob format. Data is extracted as soon as an update is made to the table"]},{"cell_type":"code","execution_count":329,"id":"5d687011-86ab-4acf-9f5e-863284c23793","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:41.691122Z","iopub.status.busy":"2023-09-29T05:21:41.690871Z","iopub.status.idle":"2023-09-29T05:21:44.125391Z","shell.execute_reply":"2023-09-29T05:21:44.124789Z","shell.execute_reply.started":"2023-09-29T05:21:41.691105Z"},"language":"sql","trusted":true},"outputs":[{"data":{"text/plain":[]},"execution_count":329,"metadata":{},"output_type":"execute_result"}],"source":["%%sql\n","ALTER TABLE siem_log_real\n","ADD COLUMN Timestamp as JSON_EXTRACT_STRING(`logs`,'Timestamp') PERSISTED datetime,\n","ADD COLUMN model_res_blob AS JSON_ARRAY_PACK_F32(JSON_EXTRACT_STRING(`logs`, 'model_res')) PERSISTED BLOB,\n","ADD COLUMN Log_ID AS JSON_EXTRACT_BIGINT(`logs`, 'Log_ID') PERSISTED bigint;"]},{"cell_type":"markdown","id":"fdfdaa2b-b3e3-46e0-8bc7-a697d03cb5c0","metadata":{"language":"python"},"source":[""]},{"cell_type":"code","execution_count":331,"id":"7e6d493e-5fd8-47d5-a040-b3c5a629c6d2","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:21:47.029915Z","iopub.status.busy":"2023-09-29T05:21:47.029639Z","iopub.status.idle":"2023-09-29T05:21:51.602313Z","shell.execute_reply":"2023-09-29T05:21:51.601419Z","shell.execute_reply.started":"2023-09-29T05:21:47.029899Z"},"language":"python","tags":[],"trusted":true},"outputs":[{"name":"stdout","output_type":"stream","text":["Note: you may need to restart the kernel to use updated packages.\n"]}],"source":["pip install perspective-python --quiet"]},{"cell_type":"code","execution_count":24,"id":"b4f823ea-8a41-458e-b19c-f65a59a928f7","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:51:45.182704Z","iopub.status.busy":"2023-09-29T16:51:45.182342Z","iopub.status.idle":"2023-09-29T16:51:45.314283Z","shell.execute_reply":"2023-09-29T16:51:45.313787Z","shell.execute_reply.started":"2023-09-29T16:51:45.182687Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":["import perspective\n","import threading\n","import random\n","import time\n","from datetime import datetime, date\n","from perspective import Table, PerspectiveWidget\n","import warnings\n","warnings.filterwarnings('ignore')"]},{"cell_type":"markdown","id":"0bc126ab-971e-4acd-8d93-3507636b6605","metadata":{"language":"python"},"source":["We will set dashboard with a refresh rate of 500ms. We use two modes: stop and run to stop a dashboard retrieving results from the database."]},{"cell_type":"code","execution_count":25,"id":"f866ec95-0c9f-4771-aaee-5e86a05e1939","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:51:47.242323Z","iopub.status.busy":"2023-09-29T16:51:47.241966Z","iopub.status.idle":"2023-09-29T16:51:47.245199Z","shell.execute_reply":"2023-09-29T16:51:47.244659Z","shell.execute_reply.started":"2023-09-29T16:51:47.242304Z"},"language":"python","trusted":true},"outputs":[],"source":["def loop():\n"," while mode != 'stop':\n"," while mode == 'run':\n"," table.update(data_source())\n"," time.sleep(0.5)"]},{"cell_type":"markdown","id":"c65ef6c4-3a1e-48d3-8cf7-b54619fd6e84","metadata":{},"source":["
\n","
\n","

Track Real-Time Connections

\n","
\n","
"]},{"cell_type":"code","execution_count":41,"id":"4d3f67ff-3143-4f55-b371-52898af7aeda","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:53:57.642472Z","iopub.status.busy":"2023-09-29T16:53:57.642225Z","iopub.status.idle":"2023-09-29T16:53:57.646067Z","shell.execute_reply":"2023-09-29T16:53:57.645452Z","shell.execute_reply.started":"2023-09-29T16:53:57.642455Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":["def data_source():\n"," result = %sql select Timestamp, count(*) as count_connections from siem_log_real group by Timestamp order by Timestamp desc limit 100\n"," result2 = list(result.dicts()) \n"," return result2\n","\n","SCHEMA = {\n"," \"Timestamp\": datetime,\n"," \"count_connections\": int\n","}"]},{"cell_type":"code","execution_count":42,"id":"f27cd500-8e90-475a-b991-ecb371212721","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:53:58.941558Z","iopub.status.busy":"2023-09-29T16:53:58.941315Z","iopub.status.idle":"2023-09-29T16:53:58.945510Z","shell.execute_reply":"2023-09-29T16:53:58.944992Z","shell.execute_reply.started":"2023-09-29T16:53:58.941542Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":["mode = 'run'\n","table = perspective.Table(SCHEMA, limit=100)\n","threading.Thread(target=loop).start()"]},{"cell_type":"code","execution_count":43,"id":"77dc7166-9037-483b-8578-d4fd6626af71","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:54:00.422175Z","iopub.status.busy":"2023-09-29T16:54:00.421929Z","iopub.status.idle":"2023-09-29T16:54:00.427761Z","shell.execute_reply":"2023-09-29T16:54:00.427217Z","shell.execute_reply.started":"2023-09-29T16:54:00.422160Z"},"language":"python","trusted":true},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"a6a7a3bfd54749898031c313c161f196","version_major":2,"version_minor":0},"text/plain":["PerspectiveWidget(columns=['count_connections'], group_by=['Timestamp'], plugin='Y Line', theme=None, title='T…"]},"execution_count":43,"metadata":{},"output_type":"execute_result"}],"source":["perspective.PerspectiveWidget(table,title = \"Track Real-Time Connections\", group_by=[\"Timestamp\"],plugin=\"Y Line\",columns=[\"count_connections\"])"]},{"cell_type":"code","execution_count":47,"id":"40296099-a5cf-40b5-8295-b097fd94d630","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:54:15.683496Z","iopub.status.busy":"2023-09-29T16:54:15.683241Z","iopub.status.idle":"2023-09-29T16:54:15.686173Z","shell.execute_reply":"2023-09-29T16:54:15.685515Z","shell.execute_reply.started":"2023-09-29T16:54:15.683460Z"},"language":"python","trusted":true},"outputs":[],"source":["mode = 'stop'"]},{"cell_type":"markdown","id":"2282842a-918c-4937-a602-d2edc41b3825","metadata":{"language":"python"},"source":["
\n","
\n","

Monitor and Infer IT Threats using Semantic Search over Real-Time Data

\n","
\n","
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"}},"cell_type":"markdown","id":"9414c751-1c61-4c01-aa55-f5a6e064df7a","metadata":{"language":"python"},"source":["![Semantic_searches.png](attachment:09fb8fd5-67f5-47d9-9904-a782e51df5dc.png)"]},{"cell_type":"code","execution_count":49,"id":"755d7238-4fe9-4119-ad4b-d4fc2f5bf4b6","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:54:41.934459Z","iopub.status.busy":"2023-09-29T16:54:41.934195Z","iopub.status.idle":"2023-09-29T16:54:41.938678Z","shell.execute_reply":"2023-09-29T16:54:41.938082Z","shell.execute_reply.started":"2023-09-29T16:54:41.934442Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":["def data_source():\n"," result = %sql WITH test_sql AS (SELECT Log_ID, TIMESTAMP, id, EUCLIDEAN_DISTANCE(model_res_blob, Model_Results) AS score,ROW_NUMBER() OVER(PARTITION BY Log_ID ORDER BY EUCLIDEAN_DISTANCE(model_res_blob, Model_Results) ASC) AS rn FROM (SELECT TIMESTAMP, Log_ID, model_res_blob FROM siem_log_real ORDER BY TIMESTAMP DESC LIMIT 20) CROSS JOIN model_results where score IS NOT NULL),label_table AS (SELECT Log_ID, TIMESTAMP,MAX(CASE WHEN id LIKE 'Bru%' OR id LIKE 'SQL%' THEN 'Malicious' ELSE 'Benign' END) as log_status FROM test_sql WHERE rn <= 100 GROUP BY Log_ID,TIMESTAMP order by TIMESTAMP DESC) SELECT log_status, count(Log_ID) as count_connections FROM label_table group by log_status;\n"," result2 = list(result.dicts()) \n"," return result2\n","\n","SCHEMA = {\n"," \"log_status\": str,\n"," \"count_connections\": int\n","}"]},{"cell_type":"code","execution_count":50,"id":"8ea8b1cf-50ec-48c5-94fe-f19977e81f93","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:54:43.997332Z","iopub.status.busy":"2023-09-29T16:54:43.997087Z","iopub.status.idle":"2023-09-29T16:54:44.001199Z","shell.execute_reply":"2023-09-29T16:54:44.000541Z","shell.execute_reply.started":"2023-09-29T16:54:43.997317Z"},"language":"python","tags":[],"trusted":true},"outputs":[],"source":["mode = 'run'\n","table = perspective.Table(SCHEMA, limit=100)\n","threading.Thread(target=loop).start()"]},{"cell_type":"code","execution_count":51,"id":"70d45c26-a29e-4fdb-a42c-fb5bd35e2836","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:54:45.639183Z","iopub.status.busy":"2023-09-29T16:54:45.638827Z","iopub.status.idle":"2023-09-29T16:54:45.647740Z","shell.execute_reply":"2023-09-29T16:54:45.647226Z","shell.execute_reply.started":"2023-09-29T16:54:45.639166Z"},"language":"python","scrolled":true,"tags":[],"trusted":true},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bc6a6f6104724dd6b54964e822a95f92","version_major":2,"version_minor":0},"text/plain":["PerspectiveWidget(columns=['count_connections'], plugin='Y Line', split_by=['log_status'], theme=None, title='…"]},"execution_count":51,"metadata":{},"output_type":"execute_result"}],"source":["perspective.PerspectiveWidget(table,title = \"Monitor Threat Inference\", split_by=[\"log_status\"],plugin=\"Y Line\",columns=[\"count_connections\"])"]},{"cell_type":"code","execution_count":54,"id":"948fa4fb-a55e-4e52-a843-d0dadf47448e","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:55:21.992552Z","iopub.status.busy":"2023-09-29T16:55:21.992288Z","iopub.status.idle":"2023-09-29T16:55:21.995199Z","shell.execute_reply":"2023-09-29T16:55:21.994624Z","shell.execute_reply.started":"2023-09-29T16:55:21.992537Z"},"language":"python","trusted":true},"outputs":[],"source":["mode = 'stop'"]},{"cell_type":"markdown","id":"96a3c621-f5b1-4236-832d-514979b45cef","metadata":{},"source":["
\n","
\n","

Track latest connections with Inferences Threat Inference by Log IDs

\n","
\n","
"]},{"cell_type":"code","execution_count":55,"id":"3d846312-3c0f-47c1-ba13-88b83a20ed7d","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:55:23.393317Z","iopub.status.busy":"2023-09-29T16:55:23.393002Z","iopub.status.idle":"2023-09-29T16:55:23.400967Z","shell.execute_reply":"2023-09-29T16:55:23.400432Z","shell.execute_reply.started":"2023-09-29T16:55:23.393296Z"},"language":"python","trusted":true},"outputs":[],"source":["def data_source():\n"," result = %sql WITH test_sql AS (SELECT Log_ID, TIMESTAMP, id, EUCLIDEAN_DISTANCE(model_res_blob, Model_Results) AS score,ROW_NUMBER() OVER(PARTITION BY Log_ID ORDER BY EUCLIDEAN_DISTANCE(model_res_blob, Model_Results) ASC) AS rn FROM (SELECT TIMESTAMP, Log_ID, model_res_blob FROM siem_log_real ORDER BY TIMESTAMP DESC LIMIT 20) CROSS JOIN model_results where score IS NOT NULL),label_table AS (SELECT Log_ID, TIMESTAMP,MAX(CASE WHEN id LIKE 'Bru%' OR id LIKE 'SQL%' THEN 'Malicious' ELSE 'Benign' END) as log_status FROM test_sql WHERE rn <= 100 GROUP BY Log_ID,TIMESTAMP order by TIMESTAMP DESC) SELECT * FROM label_table;\n"," result2 = list(result.dicts()) \n"," return result2\n","\n","SCHEMA = {\n"," \"Log_ID\": str,\n"," \"TIMESTAMP\": datetime,\n"," \"log_status\": str\n","}"]},{"cell_type":"code","execution_count":56,"id":"a79aa8f9-c4e1-4c4e-a5ec-e1ef5e6b0299","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:55:26.339869Z","iopub.status.busy":"2023-09-29T16:55:26.339576Z","iopub.status.idle":"2023-09-29T16:55:26.348657Z","shell.execute_reply":"2023-09-29T16:55:26.345240Z","shell.execute_reply.started":"2023-09-29T16:55:26.339847Z"},"language":"python","trusted":true},"outputs":[],"source":["mode = 'run'\n","table = perspective.Table(SCHEMA, limit=20)\n","threading.Thread(target=loop).start()"]},{"cell_type":"code","execution_count":57,"id":"3e6db8bb-f609-4e1f-8b5a-5ffd6567e210","metadata":{"execution":{"iopub.execute_input":"2023-09-29T16:55:27.668331Z","iopub.status.busy":"2023-09-29T16:55:27.668086Z","iopub.status.idle":"2023-09-29T16:55:27.673301Z","shell.execute_reply":"2023-09-29T16:55:27.672734Z","shell.execute_reply.started":"2023-09-29T16:55:27.668316Z"},"language":"python","trusted":true},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"663eda02158840c395774ebe90049ddb","version_major":2,"version_minor":0},"text/plain":["PerspectiveWidget(columns=['count_attack'], group_by=['TIMESTAMP'], theme=None, title='Latest Connections')"]},"execution_count":57,"metadata":{},"output_type":"execute_result"}],"source":["perspective.PerspectiveWidget(table,title = \"Latest Connections\", group_by=[\"TIMESTAMP\"],plugin=\"Datagrid\",columns=[\"count_attack\"])"]},{"cell_type":"code","execution_count":377,"id":"e86ad97f-83e2-432c-ac9e-80e0cd1d95c1","metadata":{"execution":{"iopub.execute_input":"2023-09-29T05:26:04.350064Z","iopub.status.busy":"2023-09-29T05:26:04.349808Z","iopub.status.idle":"2023-09-29T05:26:04.352614Z","shell.execute_reply":"2023-09-29T05:26:04.352064Z","shell.execute_reply.started":"2023-09-29T05:26:04.350047Z"},"language":"python","trusted":true},"outputs":[],"source":["mode = 'stop'"]},{"cell_type":"code","execution_count":null,"id":"de5e6255-f29f-4154-8044-4e174ed881b9","metadata":{"language":"python","trusted":true},"outputs":[],"source":[]}],"metadata":{"kernelspec":{"display_name":"Python 3.11.3 64-bit","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.3"},"singlestore_connection":{"connectionID":"59147d7e-ecaa-43cb-8427-fdaf1d83643f","defaultDatabase":""},"singlestore_row_limit":300,"vscode":{"interpreter":{"hash":"b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"}}},"nbformat":4,"nbformat_minor":5}