added excel functions to dopo __init__

dev/dopo_excel.py

@@ -3,7 +3,9 @@
 
 import re
 import pandas as pd
-
+from dopo import generate_sets_from_filters
+from dopo import compare_activities_multiple_methods
+from dopo import small_inputs_to_other_column
 import openpyxl
 from openpyxl import load_workbook
 from openpyxl.chart import ScatterChart, Reference, Series
@@ -177,7 +179,7 @@ def clean_label(label):
     # Apply the cleaning function to all column names
     df.columns = [clean_label(col) for col in df.columns]
 
-    # Regular expression pattern to match "Number: Name" or "Number Name"
+    # Regular expression pattern to match "Number: Name"
     pattern = r'^\d+:\s*'
 
     for idx, column in enumerate(df.columns):
@@ -207,7 +209,7 @@ def clean_label(label):
     return df
 
 def add_sector_marker(df, sector):
-'''
+    '''
     It is called in the function sector_lca_scores_to_excel_and_column_positions.
 
     It adds information about the sector for titel and labeling in plotting.
@@ -427,7 +429,7 @@ def dot_plots(filepath_workbook, worksheet_dict, index_positions):
 from openpyxl import load_workbook
 from openpyxl.chart import BarChart, Reference
 
-def stacked_bars(filepath_workbook, worksheet_dict, current_row_dot_plot):
+def stacked_bars(filepath_workbook, worksheet_dict, index_positions, current_row_dot_plot):
     # Load the workbook
     wb = load_workbook(filepath_workbook)
 

dev/test_excel_flow.ipynb

@@ -0,0 +1,297 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "0. import dopo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# from functions_v2 import*\n",
+    "# from methods import MethodFinder\n",
+    "import dopo\n",
+    "\n",
+    "import brightway2 as bw\n",
+    "import bw2data as bd\n",
+    "import bw2analyzer as ba"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. Define a bw project, bw setup, get the databases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Biosphere database already present!!! No setup is needed\n"
+     ]
+    }
+   ],
+   "source": [
+    "bd.projects.set_current(\"premise-validation-try1\")\n",
+    "bw.bw2setup()\n",
+    "\n",
+    "bio3=bw.Database('biosphere3')\n",
+    "ei39=bw.Database('ecoinvent 3.9.1 cutoff')\n",
+    "ei39SSP2=bw.Database('ei_cutoff_3.9_image_SSP2-RCP19_2050 2024-06-27')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "2. Define filter files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Cement': {'yaml': 'yamls\\\\cement_small.yaml', 'yaml identifier': 'Cement'},\n",
+       " 'Electricity': {'yaml': 'yamls\\\\electricity_small.yaml',\n",
+       "  'yaml identifier': 'Electricity'}}"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "files_dict={}\n",
+    "files_dict['Cement']={'yaml': 'yamls\\cement_small.yaml',\n",
+    "                      'yaml identifier': 'Cement'}\n",
+    "files_dict['Electricity']= {'yaml':'yamls\\electricity_small.yaml',\n",
+    "                            'yaml identifier': 'Electricity'} #yaml identifier is the name of the filter in the yaml file, in the first line.\n",
+    "files_dict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "3. Get activity lists from filters and store them in a dictionary by sector"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sectors_dict = dopo.dopo_excel.process_yaml_files(files_dict, ei39SSP2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "2. Initiate MethodFinder()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "finder=dopo.methods.MethodFinder()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "3. Define methods and store them in a dictionary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'method_1': {'object': Brightway2 Method: IPCC 2013: climate change: global warming potential (GWP100),\n",
+       "  'method name': ('IPCC 2013',\n",
+       "   'climate change',\n",
+       "   'global warming potential (GWP100)'),\n",
+       "  'short name': 'global warming potential (GWP100)',\n",
+       "  'unit': 'kg CO2-Eq'},\n",
+       " 'method_2': {'object': Brightway2 Method: EN15804: inventory indicators ISO21930: Cumulative Energy Demand - non-renewable energy resources,\n",
+       "  'method name': ('EN15804',\n",
+       "   'inventory indicators ISO21930',\n",
+       "   'Cumulative Energy Demand - non-renewable energy resources'),\n",
+       "  'short name': 'Cumulative Energy Demand - non-renewable energy resources',\n",
+       "  'unit': 'megajoule'},\n",
+       " 'method_3': {'object': Brightway2 Method: selected LCI results: resource: land occupation,\n",
+       "  'method name': ('selected LCI results', 'resource', 'land occupation'),\n",
+       "  'short name': 'land occupation',\n",
+       "  'unit': 'square meter-year'},\n",
+       " 'method_4': {'object': Brightway2 Method: EN15804: inventory indicators ISO21930: use of net fresh water,\n",
+       "  'method name': ('EN15804',\n",
+       "   'inventory indicators ISO21930',\n",
+       "   'use of net fresh water'),\n",
+       "  'short name': 'use of net fresh water',\n",
+       "  'unit': 'cubic meter'}}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "finder.find_and_create_method(criteria=['IPCC', '2013', 'GWP100'], exclude=['no LT'])\n",
+    "finder.find_and_create_method(criteria=['EN15804','Cumulative', 'non-renewable' ])\n",
+    "finder.find_and_create_method(criteria=['land occupation','selected'])\n",
+    "finder.find_and_create_method(criteria=['EN15804','fresh water'])\n",
+    "method_dict=finder.get_all_methods()\n",
+    "method_dict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "4. get LCA score tables and store them in scores_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Omitting activity name common prefix: 'cement production, '\n",
+      "Omitting activity name common prefix: 'cement production, '\n",
+      "Omitting activity name common prefix: 'cement production, '\n",
+      "Omitting activity name common prefix: 'cement production, '\n",
+      "Omitting activity name common prefix: 'electricity production, at biomass-fired IGCC power '\n",
+      "Omitting activity name common prefix: 'electricity production, at biomass-fired IGCC power '\n",
+      "Omitting activity name common prefix: 'electricity production, at biomass-fired IGCC power '\n",
+      "Omitting activity name common prefix: 'electricity production, at biomass-fired IGCC power '\n"
+     ]
+    }
+   ],
+   "source": [
+    "scores_dict = dopo.dopo_excel.sector_lca_scores(sectors_dict, method_dict) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "5. trasnfer lca tables to excel, add some statistics, get positions of columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "index_positions = dopo.dopo_excel.sector_lca_scores_to_excel_and_column_positions(scores_dict, 'test_charts_v1.xlsx')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "6. group sheets by sector"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "worksheet_dict=dopo.dopo_excel.categorize_sheets_by_sector('test_charts_v1.xlsx')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "7. generate dot plot and store row position of last chart in variable for stacked bar inital position"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "current_row_dots=dopo.dopo_excel.dot_plots('test_charts_v1.xlsx', worksheet_dict, index_positions=index_positions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "8. get stacked bars on the same sheet as the dot plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dopo.dopo_excel.stacked_bars('test_charts_v1.xlsx', worksheet_dict, index_positions, current_row_dots)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Et voila"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "premise",
+   "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": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

dopo/__init__.py

@@ -5,6 +5,7 @@
     "__version__",
     'generate_sets_from_filters',
     'MethodFinder',
+    ''
     'compare_activities_multiple_methods',
     'scores_across_activities',
     'inputs_contributions',
@@ -26,3 +27,10 @@
     input_contribution_across_activities,
     activities_across_databases
 )
+from dopo.dopo_excel import (
+    process_yaml_files,
+    sector_lca_scores,
+    sector_lca_scores_to_excel_and_column_positions,
+    dot_plots,
+    stacked_bars
+)