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Add probability change maze database and other small updates (#17)
* Update to organize probability change mazes into groups * Read Xulu's excel file into a maze database * Add database of good probability change mazes * Add function to check similarity against isomorphic mazes
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Barrier_Sequence_Databases/maze_database_probability_change.csv
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Barrier_Sequence_Databases/probability_change_mazes.csv
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Tutorials/Generate_Probability_Change_Database_part2.ipynb
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{ | ||
"cells": [ | ||
{ | ||
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"execution_count": 10, | ||
"metadata": {}, | ||
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{ | ||
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"text": [ | ||
"{34, 29, 45, 20, 25, 46, 5, 14, 11}\n", | ||
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"b1 = {34, 15, 24, 20, 41, 31, 10, 14, 38}\n", | ||
"\n", | ||
"b2 = {34, 15, 24, 12, 20, 41, 31, 14, 38}\n", | ||
"\n", | ||
"b3 = {34, 40, 15, 12, 20, 41, 31, 14, 38}\n", | ||
"b1 = {43, 23, 35, 45, 12, 9, 21, 10, 32, 18}\n", | ||
"\n", | ||
"b2 = {43, 23, 35, 45, 12, 9, 25, 10, 32, 18}\n", | ||
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"{33, 29, 15, 45, 30, 10, 37, 11, 27}\n", | ||
"{28, 34, 9, 25, 21, 10, 37, 47, 18}\n", | ||
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"\n", | ||
"b2 = {34, 44, 30, 9, 36, 13, 26, 18, 38}\n", | ||
"\n", | ||
"b3 = {34, 44, 24, 30, 9, 36, 13, 26, 38}\n", | ||
"b1 = {34, 19, 45, 12, 25, 21, 32, 6, 18}\n", | ||
"\n", | ||
"b2 = {34, 40, 45, 12, 25, 21, 32, 6, 18}\n", | ||
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"b3 = {34, 40, 45, 12, 25, 13, 21, 32, 6}\n", | ||
"{43, 19, 29, 41, 9, 13, 37, 6, 18}\n", | ||
"{23, 34, 45, 20, 9, 36, 17, 8, 32}\n", | ||
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"\n", | ||
"b2 = {44, 29, 24, 36, 7, 21, 10, 37, 27}\n", | ||
"\n", | ||
"b3 = {44, 29, 24, 7, 21, 10, 17, 37, 27}\n", | ||
"b1 = {39, 44, 45, 12, 20, 36, 7, 5, 26, 11}\n", | ||
"\n", | ||
"b2 = {39, 44, 12, 20, 36, 7, 5, 26, 14, 11}\n", | ||
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"b3 = {39, 44, 29, 20, 36, 7, 5, 26, 14, 11}\n", | ||
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"b1 = {19, 29, 45, 13, 5, 17, 47, 22, 27}\n", | ||
"\n", | ||
"b2 = {19, 45, 13, 31, 5, 17, 47, 22, 27}\n", | ||
"\n", | ||
"b3 = {19, 45, 20, 13, 31, 5, 17, 47, 27}\n", | ||
"{39, 44, 15, 35, 36, 13, 5, 26, 11}\n", | ||
"{43, 15, 24, 35, 46, 31, 10, 17, 11}\n", | ||
"b1 = {28, 35, 45, 30, 9, 10, 17, 37, 27}\n", | ||
"\n", | ||
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"[{36, 5, 39, 7, 11, 12, 44, 45, 20, 26}, {36, 5, 39, 7, 11, 44, 12, 14, 20, 26}, {36, 5, 39, 7, 11, 44, 14, 20, 26, 29}]\n", | ||
"[{32, 43, 45, 16, 17, 23, 26, 27, 29}]\n", | ||
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"[{33, 37, 40, 41, 12, 14, 18, 21, 29}]\n", | ||
"[{5, 45, 13, 47, 17, 19, 22, 27, 29}, {5, 13, 45, 47, 17, 19, 22, 27, 31}, {5, 13, 45, 47, 17, 19, 20, 27, 31}]\n", | ||
"[{35, 36, 5, 39, 11, 44, 13, 15, 26}]\n", | ||
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"[{35, 37, 9, 10, 45, 17, 27, 28, 30}, {35, 37, 9, 10, 45, 17, 27, 28, 31}, {35, 37, 9, 10, 45, 20, 27, 28, 31}]\n", | ||
"[{37, 6, 10, 44, 46, 15, 18, 21, 24}, {37, 6, 10, 44, 46, 15, 18, 21, 30}, {37, 6, 10, 44, 46, 15, 21, 24, 30}]\n", | ||
"[{34, 36, 6, 38, 9, 44, 13, 24, 26, 30}]\n", | ||
"[{33, 37, 5, 45, 13, 15, 17, 22, 29, 30}]\n", | ||
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"[{34, 37, 11, 46, 15, 16, 26, 28, 30}, {34, 37, 11, 13, 46, 16, 26, 28, 30}, {34, 35, 37, 11, 13, 46, 16, 28, 30}]\n", | ||
"[{32, 34, 37, 10, 12, 45, 18, 19, 21, 25}, {32, 34, 37, 40, 10, 12, 45, 18, 21, 25}, {32, 34, 37, 40, 10, 12, 45, 16, 21, 25}]\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"import pandas as pd\n", | ||
"import ast\n", | ||
"import re\n", | ||
"import sys\n", | ||
"sys.path.append(\"..\") # Use sys to add the parent directory (where hex_maze_utils lives) to the path\n", | ||
"\n", | ||
"# Read the excel file into a DataFrame\n", | ||
"excel_file_path = 'BraveLu_experimental_notes.xlsx'\n", | ||
"df = pd.read_excel(excel_file_path, sheet_name='Daily configs and notes_BanditT', skiprows=1) \n", | ||
"\n", | ||
"# will include b1 = , b2 = , b3 = if barrier shift\n", | ||
"\n", | ||
"def extract_sets_from_string(value):\n", | ||
" if isinstance(value, str):\n", | ||
" # Regular expression to find all the sets in the string\n", | ||
" sets = re.findall(r'\\{.*?\\}', value)\n", | ||
" return [ast.literal_eval(s) for s in sets]\n", | ||
" return None\n", | ||
"\n", | ||
"def flatten_sets(nested_list):\n", | ||
" flat_list = []\n", | ||
" for item in nested_list:\n", | ||
" if isinstance(item, list):\n", | ||
" # Flatten sublists of sets (from barrier sequences)\n", | ||
" flat_list.extend(flatten_sets(item)) \n", | ||
" elif isinstance(item, set):\n", | ||
" # Or if the list element is just a set, add it\n", | ||
" flat_list.append(item)\n", | ||
" return flat_list\n", | ||
"\n", | ||
"rows_with_mazes = df[df['barrier location'].notna()]\n", | ||
"\n", | ||
"list_of_sets = rows_with_mazes['barrier location'].apply(extract_sets_from_string).tolist()\n", | ||
"\n", | ||
"for set in list_of_sets:\n", | ||
" print(set)" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "venv", | ||
"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": "3.12.3" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |
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