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Alternative analysis of What Could Be Bowling Green consultation https://report.whatcouldbgbe.com/
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "view-in-github", | |
"colab_type": "text" | |
}, | |
"source": [ | |
"<a href=\"https://colab.research.google.com/gist/patcon/069ab5de2402b63c5ffe83d19077d3de/2025-05-01-bowling-green-algo-compare.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "kEyVHx6y7zpu", | |
"outputId": "ad7cbeee-bef7-4956-ce10-5b04a99c1847" | |
}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", | |
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", | |
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", | |
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"\u001b[?25h Building wheel for red-dwarf (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", | |
"Collecting pacmap\n", | |
" Downloading pacmap-0.8.0-py3-none-any.whl.metadata (14 kB)\n", | |
"Requirement already satisfied: scikit-learn>=0.20 in /usr/local/lib/python3.11/dist-packages (from pacmap) (1.6.1)\n", | |
"Requirement already satisfied: numba>=0.57 in /usr/local/lib/python3.11/dist-packages (from pacmap) (0.60.0)\n", | |
"Collecting annoy>=1.11 (from pacmap)\n", | |
" Downloading annoy-1.17.3.tar.gz (647 kB)\n", | |
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m647.5/647.5 kB\u001b[0m \u001b[31m9.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", | |
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", | |
"Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.11/dist-packages (from pacmap) (2.0.2)\n", | |
"Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in /usr/local/lib/python3.11/dist-packages (from numba>=0.57->pacmap) (0.43.0)\n", | |
"Requirement already satisfied: scipy>=1.6.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn>=0.20->pacmap) (1.15.2)\n", | |
"Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn>=0.20->pacmap) (1.4.2)\n", | |
"Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn>=0.20->pacmap) (3.6.0)\n", | |
"Downloading pacmap-0.8.0-py3-none-any.whl (21 kB)\n", | |
"Building wheels for collected packages: annoy\n", | |
" Building wheel for annoy (setup.py) ... \u001b[?25l\u001b[?25hdone\n", | |
" Created wheel for annoy: filename=annoy-1.17.3-cp311-cp311-linux_x86_64.whl size=553321 sha256=3722374440306d56ad17dfce6b2ffc0c97c4efc75b9718d6ebea2e4a9482ed0b\n", | |
" Stored in directory: /root/.cache/pip/wheels/33/e5/58/0a3e34b92bedf09b4c57e37a63ff395ade6f6c1099ba59877c\n", | |
"Successfully built annoy\n", | |
"Installing collected packages: annoy, pacmap\n", | |
"Successfully installed annoy-1.17.3 pacmap-0.8.0\n" | |
] | |
} | |
], | |
"source": [ | |
"%pip install --quiet --no-cache-dir git+https://github.com/polis-community/red-dwarf.git@main\n", | |
"%pip install pacmap" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"from reddwarf.data_loader import Loader\n", | |
"from reddwarf.utils.matrix import generate_raw_matrix, get_clusterable_participant_ids, simple_filter_matrix\n", | |
"from reddwarf.utils.polismath import extract_data_from_polismath\n", | |
"from reddwarf.utils.statements import process_statements\n", | |
"\n", | |
"REPORT_ID, CONVO_ID = None, None\n", | |
"# REPORT_ID, CONVO_ID = \"r7aybmkd3nce56sbry55t\", \"6mdwcmn7jh\" # DemDis: Slovakia state of democracy\n", | |
"# REPORT_ID, CONVO_ID = \"r9cnkypdddkmnefz8k2bn\", \"2ku7arccjt\" # DemDis: Hoaxes\n", | |
"# REPORT_ID, CONVO_ID = \"r8bzudrhs8j6petppicrj\", \"2upmdmyrbv\" # DemDis: Debating with fascists\n", | |
"# REPORT_ID=\"r64ajcsmp9butzxhzj44c\"\n", | |
"# REPORT_ID, CONVO_ID = \"r7kfpvrhdpyykbhnirtcd\", \"3nemnipcrc\" # Bowling Green\n", | |
"CONVO_ID = \"9hhbck2kda\"\n", | |
"# REPORT_ID, CONVO_ID = \"r3rwrinr5udrzwkvxtdkj\", \"3akt5cdsfk\"\n", | |
"# REPORT_ID, CONVO_ID = \"r2xcn2cdbmrzjmmuuytdk\", \"9wtchdmmun\" # Bowling Green #1\n", | |
"# REPORT_ID, CONVO_ID = \"r263pyffyjvsurzs9dc6h\", \"7yhactmdme\" # vTaiwan drunk driving\n", | |
"# REPORT_ID, CONVO_ID = \"r6xd526vyjyjrj9navxrj\", \"4uf4hkunf3\" # Germans never had it better (33,000)\n", | |
"# REPORT_ID, CONVO_ID = \"r8nssrnnnf2bewvtd5f5h\", \"2vkxcncppn\" # Austria Klimarat: Energy (7000 ppl)\n", | |
"# REPORT_ID, CONVO_ID = \"r7jjamzvde5iv96scfhdr\", \"3ufjbm7hfb\" # DemDis: NGOs (400 ppl)\n", | |
"# CONVO_ID = \"7eahucmmjc\" # NDP Nakba ban\n", | |
"# REPORT_ID, CONVO_ID = \"r4z6d6mjj6mykyazj87tr\", \"48ntjepisf\" # Tax Bill (250)\n", | |
"# REPORT_ID, CONVO_ID = \"r98y2p9easajrxhpvhsrr\", \"4cacski7ha\" # French AI\n", | |
"# CONVO_ID = \"9zcd4ktce5\" nishio Japan (250)\n", | |
"# CONVO_ID = \"6mhvipxs2z\" # Akron OH, candidates (300)\n", | |
"\n", | |
"# Load polis data is the speediest way possible\n", | |
"if REPORT_ID and CONVO_ID:\n", | |
" loader = Loader(polis_id=REPORT_ID, data_source=\"csv_export\", polis_instance_url=\"https://preprod.pol.is/\")\n", | |
" loader.conversation_id = CONVO_ID\n", | |
" loader.load_api_data_math()\n", | |
"else:\n", | |
" loader = Loader(polis_id=REPORT_ID or CONVO_ID)\n", | |
"\n", | |
"_, _, mod_out_statement_ids, _ = process_statements(loader.comments_data)\n", | |
"\n", | |
"raw_vote_matrix = generate_raw_matrix(votes=loader.votes_data)\n", | |
"\n", | |
"filtered_vote_matrix = simple_filter_matrix(\n", | |
" vote_matrix=raw_vote_matrix,\n", | |
" mod_out_statement_ids=mod_out_statement_ids,\n", | |
")\n", | |
"\n", | |
"print(filtered_vote_matrix)" | |
], | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "Ea8YprXESDAd", | |
"outputId": "b396b324-fa32-4908-87db-a3dff9dcd23a" | |
}, | |
"execution_count": 2, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"statement_id 0 1 2 3 4 5 8 9 10 11 \\\n", | |
"participant_id \n", | |
"1 0.0 0.0 NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"2 -1.0 1.0 -1.0 NaN NaN NaN NaN NaN NaN NaN \n", | |
"3 1.0 1.0 NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"4 1.0 -1.0 -1.0 NaN NaN NaN NaN NaN NaN NaN \n", | |
"5 1.0 1.0 1.0 NaN NaN NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... ... ... ... ... ... \n", | |
"5743 NaN -1.0 NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5744 NaN 1.0 NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5745 NaN 0.0 0.0 NaN NaN 0.0 1.0 1.0 NaN NaN \n", | |
"5746 NaN 1.0 1.0 NaN NaN NaN NaN NaN 0.0 NaN \n", | |
"5747 NaN -1.0 1.0 NaN NaN NaN NaN 1.0 NaN NaN \n", | |
"\n", | |
"statement_id ... 7741 7742 7743 7744 7745 7747 7748 7749 7750 \\\n", | |
"participant_id ... \n", | |
"1 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"2 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"3 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"4 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... ... ... ... ... ... \n", | |
"5743 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5744 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5745 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5746 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"5747 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", | |
"\n", | |
"statement_id 7752 \n", | |
"participant_id \n", | |
"1 NaN \n", | |
"2 NaN \n", | |
"3 NaN \n", | |
"4 NaN \n", | |
"5 NaN \n", | |
"... ... \n", | |
"5743 NaN \n", | |
"5744 NaN \n", | |
"5745 NaN \n", | |
"5746 NaN \n", | |
"5747 NaN \n", | |
"\n", | |
"[5743 rows x 7730 columns]\n" | |
] | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"import numpy as np\n", | |
"from sklearn.pipeline import Pipeline\n", | |
"from sklearn.impute import SimpleImputer\n", | |
"from pacmap import PaCMAP, LocalMAP\n", | |
"from sklearn.decomposition import PCA\n", | |
"from reddwarf.sklearn.transformers import SparsityAwareScaler\n", | |
"import matplotlib.pyplot as plt\n", | |
"\n", | |
"n_components = 2\n", | |
"\n", | |
"# Setup participant mask (we won't derive our own list of active participant IDs this time)\n", | |
"# participant_ids_to_cluster = get_clusterable_participant_ids(raw_vote_matrix, vote_threshold=7)\n", | |
"# cluster_mask = [pid in participant_ids_to_cluster for pid in raw_vote_matrix.index]\n", | |
"\n", | |
"# Set up participant mask and cluster labels from polismath, for comparison with default Polis.\n", | |
"all_clustered_participant_ids, cluster_labels = extract_data_from_polismath(loader.math_data)\n", | |
"cluster_mask = [pid in all_clustered_participant_ids for pid in raw_vote_matrix.index]\n", | |
"\n", | |
"RANDOM_STATE = None\n", | |
"# RANDOM_STATE = 12345\n", | |
"\n", | |
"# Configure pipelines\n", | |
"pipelines = {\n", | |
" \"PCA\": Pipeline([\n", | |
" (\"impute\", SimpleImputer(missing_values=np.nan, strategy=\"mean\")),\n", | |
" (\"pca\", PCA(n_components=n_components, random_state=RANDOM_STATE)),\n", | |
" (\"scale\", SparsityAwareScaler(X_sparse=raw_vote_matrix.values)),\n", | |
" ]),\n", | |
" \"PaCMAP\": Pipeline([\n", | |
" (\"impute\", SimpleImputer(missing_values=np.nan, strategy=\"mean\")),\n", | |
" (\"pacmap\", PaCMAP(n_components=n_components, random_state=RANDOM_STATE)),\n", | |
" ]),\n", | |
" \"LocalMAP\": Pipeline([\n", | |
" (\"impute\", SimpleImputer(missing_values=np.nan, strategy=\"mean\")),\n", | |
" (\"localmap\", LocalMAP(n_components=n_components, random_state=RANDOM_STATE)),\n", | |
" ]),\n", | |
" # Add more here easily\n", | |
"}\n", | |
"\n", | |
"# Run pipelines\n", | |
"embeddings = {}\n", | |
"for name, pipe in pipelines.items():\n", | |
" X_transformed = pipe.fit_transform(filtered_vote_matrix.values)\n", | |
" embeddings[name] = {\n", | |
" \"X\": X_transformed,\n", | |
" \"kmeans\": None,\n", | |
" }" | |
], | |
"metadata": { | |
"id": "DwoS4OvOSJqG" | |
}, | |
"execution_count": 3, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"source": [ | |
"from reddwarf.utils.clustering import find_optimal_k\n", | |
"\n", | |
"# [Re-]generate clusters\n", | |
"for name, data in embeddings.items():\n", | |
" _, _, kmeans = find_optimal_k(\n", | |
" projected_data=data[\"X\"][cluster_mask],\n", | |
" k_bounds=(2,6),\n", | |
" init=\"k-means++\",\n", | |
" # random_state=RANDOM_STATE,\n", | |
" )\n", | |
" embeddings[name][\"kmeans\"] = kmeans" | |
], | |
"metadata": { | |
"id": "nhgO-6vCFpBY" | |
}, | |
"execution_count": 4, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 703 | |
}, | |
"id": "NkGdoHCy8RdA", | |
"outputId": "50f8ce63-de5d-486f-9880-51ae1818fe26" | |
}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"name": "stdout", | |
"text": [ | |
"{0: 2249, 1: 333, 2: 1252, 3: 813}\n", | |
"{0: 2842, 1: 1805}\n", | |
"{0: 545, 1: 1607, 2: 1163, 3: 1332}\n" | |
] | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": [ | |
"<Figure size 1500x500 with 4 Axes>" | |
], | |
"image/png": 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\n" | |
}, | |
"metadata": {} | |
}, | |
{ | |
"output_type": "error", | |
"ename": "KeyError", | |
"evalue": "'[5748, 5749, 5750, 5751] not in index'", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", | |
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"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1182\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1183\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtakeable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_takeable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1184\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1185\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1375\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_multi_take\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1376\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1377\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple_same_dim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1378\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1379\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAxisInt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple_same_dim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 1018\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1019\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1020\u001b[0;31m \u001b[0mretval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mretval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1021\u001b[0m \u001b[0;31m# We should never have retval.ndim < self.ndim, as that should\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1022\u001b[0m \u001b[0;31m# be handled by the _getitem_lowerdim call above.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1418\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Cannot index with multidimensional key\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1419\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1420\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_iterable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1421\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1422\u001b[0m \u001b[0;31m# nested tuple slicing\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_iterable\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1358\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1359\u001b[0m \u001b[0;31m# A collection of keys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1360\u001b[0;31m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1361\u001b[0m return self.obj._reindex_with_indexers(\n\u001b[1;32m 1362\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_dups\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m 1556\u001b[0m \u001b[0maxis_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1557\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1558\u001b[0;31m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_indexer_strict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1559\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1560\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m_get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m 6198\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6199\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6200\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_raise_if_missing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6201\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6202\u001b[0m \u001b[0mkeyarr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36m_raise_if_missing\u001b[0;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[1;32m 6250\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6251\u001b[0m \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6252\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{not_found} not in index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 6253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6254\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0moverload\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;31mKeyError\u001b[0m: '[5748, 5749, 5750, 5751] not in index'" | |
] | |
} | |
], | |
"source": [ | |
"%pip install --quiet tabulate\n", | |
"\n", | |
"import math\n", | |
"from reddwarf.utils.stats import calculate_comment_statistics_dataframes, select_representative_statements\n", | |
"import pandas as pd\n", | |
"\n", | |
"from tabulate import tabulate\n", | |
"from reddwarf.data_presenter import print_repness\n", | |
"\n", | |
"# Plotting and rendering representative group statements\n", | |
"\n", | |
"pid_labels = raw_vote_matrix.index[cluster_mask].to_list()\n", | |
"\n", | |
"MAX_COLS = 3 # <-- How many plots per row\n", | |
"n_embeddings = len(embeddings)\n", | |
"n_cols = min(MAX_COLS, n_embeddings)\n", | |
"n_rows = math.ceil(n_embeddings / MAX_COLS)\n", | |
"\n", | |
"fig, axes = plt.subplots(n_rows, n_cols, figsize=(5 * n_cols, 5 * n_rows))\n", | |
"\n", | |
"# Various toggles for rendering graph\n", | |
"SHOW_PARTICIPANT_IDS = False\n", | |
"FLIP_X = False\n", | |
"FLIP_Y = True\n", | |
"# Set to name of algo: \"PCA\", \"PaCMAP\", \"LocalMAP\"\n", | |
"# Set to \"polis\" to show originals from API.\n", | |
"LOCK_CLUSTER = \"polis\"\n", | |
"LOCK_CLUSTER = False\n", | |
"LOCK_CLUSTER = \"LocalMAP\"\n", | |
"\n", | |
"# Ensure axes is a flat list, even if 1 row\n", | |
"axes = np.atleast_1d(axes).flatten()\n", | |
"\n", | |
"# Save the last scatterplot to add colorbar\n", | |
"sc = None\n", | |
"\n", | |
"for ax, (name, data) in zip(axes, embeddings.items()):\n", | |
" X = data[\"X\"]\n", | |
" x = X[cluster_mask, 0]\n", | |
" y = X[cluster_mask, 1]\n", | |
"\n", | |
" kmeans = data[\"kmeans\"]\n", | |
"\n", | |
" if not LOCK_CLUSTER:\n", | |
" colors = kmeans.labels_ if kmeans else None\n", | |
" else:\n", | |
" if LOCK_CLUSTER == \"polis\":\n", | |
" colors = cluster_labels\n", | |
" else:\n", | |
" colors = embeddings[LOCK_CLUSTER][\"kmeans\"].labels_\n", | |
"\n", | |
" # Print messy group member counts\n", | |
" print({int(l): list(kmeans.labels_).count(l) for l in set(kmeans.labels_)})\n", | |
"\n", | |
"\n", | |
" sc = ax.scatter(x, y, c=colors, cmap='tab10')\n", | |
" ax.set_title(f\"{name} Projection\")\n", | |
"\n", | |
" # Too crowded for participant ID labels.\n", | |
" if SHOW_PARTICIPANT_IDS:\n", | |
" for xi, yi, label in zip(x, y, pid_labels):\n", | |
" ax.text(xi, yi, label, fontsize=6, color=\"gray\", ha='right', va='bottom')\n", | |
" if FLIP_X:\n", | |
" ax.invert_xaxis()\n", | |
" if FLIP_Y:\n", | |
" ax.invert_yaxis()\n", | |
"\n", | |
"# Add one colorbar\n", | |
"cbar = fig.colorbar(sc, ax=ax)\n", | |
"cbar.set_label('Cluster Label') # Optional label for the colorbar\n", | |
"\n", | |
"# Hide any unused axes (if there are extra empty slots)\n", | |
"for i in range(len(embeddings), len(axes)):\n", | |
" axes[i].axis('off')\n", | |
"\n", | |
"plt.tight_layout()\n", | |
"plt.show()\n", | |
"\n", | |
"import io\n", | |
"import contextlib\n", | |
"import textwrap\n", | |
"\n", | |
"cols = []\n", | |
"# Write the representative group statements below.\n", | |
"for name, data in embeddings.items():\n", | |
" grouped_stats_df, gac_df = calculate_comment_statistics_dataframes(\n", | |
" vote_matrix=raw_vote_matrix.loc[all_clustered_participant_ids, :],\n", | |
" cluster_labels=data[\"kmeans\"].labels_,\n", | |
" )\n", | |
" repness = select_representative_statements(grouped_stats_df=grouped_stats_df)\n", | |
"\n", | |
" string_io = io.StringIO()\n", | |
" with contextlib.redirect_stdout(string_io):\n", | |
" print_repness(repness=repness, statements_data=loader.comments_data)\n", | |
" output = string_io.getvalue()\n", | |
" print(output)\n", | |
" output = textwrap.wrap(output, width=60, replace_whitespace=False)\n", | |
" output = \"\\n\".join(output)\n", | |
" cols.append((name, output))\n", | |
"\n", | |
"headers, data = zip(*cols)\n", | |
"print(tabulate([data], headers=headers))\n" | |
] | |
} | |
], | |
"metadata": { | |
"colab": { | |
"provenance": [], | |
"name": "2025-04-28-polis-algo-comparison.ipynb", | |
"include_colab_link": true | |
}, | |
"kernelspec": { | |
"display_name": "Python 3", | |
"name": "python3" | |
}, | |
"language_info": { | |
"name": "python" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 0 | |
} |
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