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AI_Diplomacy/support_explanation_ablations_csa.ipynb
AlxAI eeeb312d40 hold reduction
2025-07-17 14:22:07 -04:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"id": "3d56e2ca",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Analysis Report\n",
"==================================================\n",
"sam-exp096-csa baseline (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.358 [0.330, 0.386]\n",
" support_success/unit= 0.141 [0.110, 0.173]\n",
" move+support/unit = 0.498 [0.466, 0.531]\n",
"\n",
"sam-exp096-csa-r baseline (repeat) (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.377 [0.343, 0.411]\n",
" support_success/unit= 0.144 [0.114, 0.175]\n",
" move+support/unit = 0.521 [0.485, 0.556]\n",
"\n",
"sam-exp096-csa2 supports explained v2 nshot3 (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.316 [0.282, 0.350]\n",
" support_success/unit= 0.167 [0.137, 0.198]\n",
" move+support/unit = 0.482 [0.445, 0.520]\n",
"\n",
"sam-exp096-csa3 supports explained v2 nshot3 + condensed possible moves (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.339 [0.317, 0.361]\n",
" support_success/unit= 0.169 [0.143, 0.197]\n",
" move+support/unit = 0.508 [0.472, 0.544]\n",
"\n",
"sam-exp096-csa4 condensed possible moves (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.359 [0.334, 0.384]\n",
" support_success/unit= 0.092 [0.068, 0.116]\n",
" move+support/unit = 0.451 [0.418, 0.484]\n",
"\n",
"sam-exp096-csa5 supports explained v2 nshot6 (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.367 [0.336, 0.399]\n",
" support_success/unit= 0.132 [0.105, 0.160]\n",
" move+support/unit = 0.499 [0.463, 0.536]\n",
"\n",
"sam-exp096-csa6 supports explained v2 nshot12 (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.413 [0.383, 0.443]\n",
" support_success/unit= 0.103 [0.080, 0.128]\n",
" move+support/unit = 0.516 [0.483, 0.549]\n",
"\n",
"sam-exp096-csa7 supports explained v2 nshot6 + condensed possible moves (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.345 [0.321, 0.370]\n",
" support_success/unit= 0.168 [0.142, 0.194]\n",
" move+support/unit = 0.513 [0.478, 0.548]\n",
"\n",
"sam-exp096-csa8 supports explained v2 nshot12 + condensed possible moves (n=120 games)\n",
" Analysis Target: Power 'FRANCE' in Phase 'S1912M'\n",
" move_success/unit = 0.367 [0.341, 0.394]\n",
" support_success/unit= 0.075 [0.053, 0.098]\n",
" move+support/unit = 0.442 [0.408, 0.477]\n",
"\n"
]
},
{
"data": {
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",
"text/plain": [
"<Figure size 1000x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# --- config ---------------------------------------------------------------\n",
"# Define each analysis run here. Each dictionary groups all the information\n",
"# for a single bar group in the final plot.\n",
"\n",
"\n",
"\n",
"# csa moment 1, order history NOT included in order generation prompt\n",
"RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa\",\n",
" \"label\": \"sam-exp087-csa baseline\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa-r\",\n",
" \"label\": \"sam-exp087-csa-r baseline (repeat)\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa2\",\n",
" \"label\": \"sam-exp087-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa3\",\n",
" \"label\": \"sam-exp087-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa4\",\n",
" \"label\": \"sam-exp087-csa4 condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa5\",\n",
" \"label\": \"sam-exp087-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa6\",\n",
" \"label\": \"sam-exp087-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa7\",\n",
" \"label\": \"sam-exp087-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp087-csa8\",\n",
" \"label\": \"sam-exp087-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
"]\n",
"\n",
"# csa moment 1, order history IS included in order generation prompt\n",
"RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa\",\n",
" \"label\": \"sam-exp094-csa baseline\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa-r\",\n",
" \"label\": \"sam-exp094-csa-r baseline (repeat)\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa2\",\n",
" \"label\": \"sam-exp094-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa3\",\n",
" \"label\": \"sam-exp094-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa4\",\n",
" \"label\": \"sam-exp094-csa4 condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa5\",\n",
" \"label\": \"sam-exp094-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa6\",\n",
" \"label\": \"sam-exp094-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa7\",\n",
" \"label\": \"sam-exp094-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp094-csa8\",\n",
" \"label\": \"sam-exp094-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"F1907M\",\n",
" \"power\": \"GERMANY\",\n",
" },\n",
"]\n",
"\n",
"# csa moment 2, order history IS included in order generation prompt\n",
"_RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa\",\n",
" \"label\": \"sam-exp093-csa baseline\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa-r\",\n",
" \"label\": \"sam-exp093-csa-r baseline (repeat)\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa2\",\n",
" \"label\": \"sam-exp093-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa3\",\n",
" \"label\": \"sam-exp093-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa4\",\n",
" \"label\": \"sam-exp093-csa4 condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa5\",\n",
" \"label\": \"sam-exp093-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa6\",\n",
" \"label\": \"sam-exp093-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa7\",\n",
" \"label\": \"sam-exp093-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp093-csa8\",\n",
" \"label\": \"sam-exp093-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
"]\n",
"\n",
"# csa moment 2, order history NOT included in order generation prompt\n",
"_RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa\",\n",
" \"label\": \"sam-exp095-csa baseline\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa-r\",\n",
" \"label\": \"sam-exp095-csa-r baseline (repeat)\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa2\",\n",
" \"label\": \"sam-exp095-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa3\",\n",
" \"label\": \"sam-exp095-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa4\",\n",
" \"label\": \"sam-exp095-csa4 condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa5\",\n",
" \"label\": \"sam-exp095-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa6\",\n",
" \"label\": \"sam-exp095-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa7\",\n",
" \"label\": \"sam-exp095-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp095-csa8\",\n",
" \"label\": \"sam-exp095-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"F1917M\",\n",
" \"power\": \"AUSTRIA\",\n",
" },\n",
"]\n",
"\n",
"\n",
"# csa moment 3, order history NOT included in order generation prompt\n",
"RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa\",\n",
" \"label\": \"sam-exp096-csa baseline\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa-r\",\n",
" \"label\": \"sam-exp096-csa-r baseline (repeat)\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa2\",\n",
" \"label\": \"sam-exp096-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa3\",\n",
" \"label\": \"sam-exp096-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa4\",\n",
" \"label\": \"sam-exp096-csa4 condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa5\",\n",
" \"label\": \"sam-exp096-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa6\",\n",
" \"label\": \"sam-exp096-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa7\",\n",
" \"label\": \"sam-exp096-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp096-csa8\",\n",
" \"label\": \"sam-exp096-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
"]\n",
"\n",
"# csa moment 3, order history IS included in order generation prompt\n",
"_RUN_CONFIGS = [\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa\",\n",
" \"label\": \"sam-exp097-csa baseline\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa-r\",\n",
" \"label\": \"sam-exp097-csa-r baseline (repeat)\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa2\",\n",
" \"label\": \"sam-exp097-csa2 supports explained v2 nshot3\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa3\",\n",
" \"label\": \"sam-exp097-csa3 supports explained v2 nshot3 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa4\",\n",
" \"label\": \"sam-exp097-csa4 condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa5\",\n",
" \"label\": \"sam-exp097-csa5 supports explained v2 nshot6\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa6\",\n",
" \"label\": \"sam-exp097-csa6 supports explained v2 nshot12\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa7\",\n",
" \"label\": \"sam-exp097-csa7 supports explained v2 nshot6 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
" {\n",
" \"dir\": \"/mnt/i/diplo/sam-exp097-csa8\",\n",
" \"label\": \"sam-exp097-csa8 supports explained v2 nshot12 + condensed possible moves\",\n",
" \"phase\": \"S1912M\",\n",
" \"power\": \"FRANCE\",\n",
" },\n",
"]\n",
"\n",
"\n",
"\n",
"# --- imports --------------------------------------------------------------\n",
"from pathlib import Path\n",
"import json, numpy as np, matplotlib.pyplot as plt, textwrap as tw\n",
"\n",
"# --- helpers --------------------------------------------------------------\n",
"def get_stats_for_phase(exp_dir: Path, target_phase: str, target_power: str):\n",
" \"\"\"\n",
" Return arrays of move-success/unit and support-success/unit for a\n",
" specific power in a specific phase, with one data point per game file.\n",
" \"\"\"\n",
" move_ratios, support_ratios = [], []\n",
" for jpath in exp_dir.glob(\"runs/run_*/lmvsgame.json\"):\n",
" with jpath.open(encoding=\"utf-8\") as fh:\n",
" data = json.load(fh)\n",
"\n",
" # Find the specific phase in the game log\n",
" phase_data = next(\n",
" (p for p in data.get(\"phases\", [])\n",
" if (p.get(\"name\") or p.get(\"state\", {}).get(\"name\", \"\")) == target_phase),\n",
" None\n",
" )\n",
"\n",
" if not phase_data:\n",
" continue # Target phase not found in this game file\n",
"\n",
" units = phase_data[\"state\"][\"units\"].get(target_power, [])\n",
" n_units = len(units)\n",
" if n_units == 0:\n",
" continue # Target power eliminated or has no units in this phase\n",
"\n",
" orders = phase_data.get(\"order_results\", {}).get(target_power, {})\n",
" succ_moves = sum(1 for o in orders.get(\"move\", []) if o[\"result\"] == \"success\")\n",
" succ_supports = sum(1 for o in orders.get(\"support\", []) if o[\"result\"] == \"success\")\n",
"\n",
" move_ratios.append(succ_moves / n_units)\n",
" support_ratios.append(succ_supports / n_units)\n",
"\n",
" del data\n",
"\n",
" return np.array(move_ratios), np.array(support_ratios)\n",
"\n",
"def bootstrap_ci(samples, iters=10_000, alpha=0.05):\n",
" \"\"\"Return mean, lower-CI, upper-CI for the bootstrap of the mean.\"\"\"\n",
" if samples.size == 0:\n",
" return np.nan, np.nan, np.nan\n",
" rng = np.random.default_rng()\n",
" means = rng.choice(samples, size=(iters, samples.size), replace=True).mean(axis=1)\n",
" lower, upper = np.percentile(means, [100*alpha/2, 100*(1-alpha/2)])\n",
" return samples.mean(), lower, upper\n",
"\n",
"# --- aggregate ------------------------------------------------------------\n",
"summary = {}\n",
"for config in RUN_CONFIGS:\n",
" exp_dir = config[\"dir\"]\n",
" move, sup = get_stats_for_phase(Path(exp_dir), config[\"phase\"], config[\"power\"])\n",
" combined = move + sup\n",
" m_mean, m_low, m_up = bootstrap_ci(move)\n",
" s_mean, s_low, s_up = bootstrap_ci(sup)\n",
" c_mean, c_low, c_up = bootstrap_ci(combined)\n",
" # Use the directory as a unique key for the summary stats\n",
" summary[exp_dir] = dict(\n",
" move_mean=m_mean, move_low=m_low, move_up=m_up,\n",
" support_mean=s_mean, support_low=s_low, support_up=s_up,\n",
" combined_mean=c_mean, combined_low=c_low, combined_up=c_up,\n",
" n_samples=move.size,\n",
" )\n",
"\n",
"# --- textual report -------------------------------------------------------\n",
"print(\"Analysis Report\\n\" + \"=\"*50)\n",
"for config in RUN_CONFIGS:\n",
" stats = summary[config[\"dir\"]]\n",
" print(\n",
" f\"{config['label']} (n={stats['n_samples']} games)\\n\"\n",
" f\" Analysis Target: Power '{config['power']}' in Phase '{config['phase']}'\\n\"\n",
" f\" move_success/unit = {stats['move_mean']:.3f} \"\n",
" f\"[{stats['move_low']:.3f}, {stats['move_up']:.3f}]\\n\"\n",
" f\" support_success/unit= {stats['support_mean']:.3f} \"\n",
" f\"[{stats['support_low']:.3f}, {stats['support_up']:.3f}]\\n\"\n",
" f\" move+support/unit = {stats['combined_mean']:.3f} \"\n",
" f\"[{stats['combined_low']:.3f}, {stats['combined_up']:.3f}]\\n\"\n",
" )\n",
"\n",
"# --- plot -----------------------------------------------------------------\n",
"labels = [tw.fill(c['label'], width=38) for c in RUN_CONFIGS]\n",
"move_means = np.array([summary[c[\"dir\"]][\"move_mean\"] for c in RUN_CONFIGS])\n",
"support_means = np.array([summary[c[\"dir\"]][\"support_mean\"] for c in RUN_CONFIGS])\n",
"combined_means = np.array([summary[c[\"dir\"]][\"combined_mean\"] for c in RUN_CONFIGS])\n",
"\n",
"move_err = np.vstack([\n",
" move_means - np.array([summary[c[\"dir\"]][\"move_low\"] for c in RUN_CONFIGS]),\n",
" np.array([summary[c[\"dir\"]][\"move_up\"] for c in RUN_CONFIGS]) - move_means,\n",
"])\n",
"sup_err = np.vstack([\n",
" support_means - np.array([summary[c[\"dir\"]][\"support_low\"] for c in RUN_CONFIGS]),\n",
" np.array([summary[c[\"dir\"]][\"support_up\"] for c in RUN_CONFIGS]) - support_means,\n",
"])\n",
"comb_err = np.vstack([\n",
" combined_means - np.array([summary[c[\"dir\"]][\"combined_low\"] for c in RUN_CONFIGS]),\n",
" np.array([summary[c[\"dir\"]][\"combined_up\"] for c in RUN_CONFIGS]) - combined_means,\n",
"])\n",
"\n",
"y = np.arange(len(RUN_CONFIGS))\n",
"h = 0.25\n",
"\n",
"fig, ax = plt.subplots(figsize=(10, max(4, len(labels)*0.8)))\n",
"ax.barh(y - h, move_means, h, xerr=move_err, label=\"Move success / unit\")\n",
"ax.barh(y, support_means, h, xerr=sup_err, label=\"Support success / unit\")\n",
"ax.barh(y + h, combined_means, h, xerr=comb_err, label=\"Move+Support success / unit\")\n",
"\n",
"ax.set_xlabel(\"Successes per Unit (for specified power/phase)\")\n",
"ax.set_yticks(y)\n",
"ax.set_yticklabels(labels)\n",
"ax.invert_yaxis()\n",
"ax.set_title(\"Per-phase Success Rates by Experiment (95% CIs)\")\n",
"\n",
"# ── legend outside the axes ───────────────────────────────────────────────\n",
"fig.legend(\n",
" loc=\"upper center\",\n",
" bbox_to_anchor=(0.5, -0.04), # centred, just below the axes\n",
" ncol=3, # three labels side-by-side\n",
" frameon=False,\n",
")\n",
"\n",
"# reserve a little bottom margin for the legend\n",
"plt.tight_layout(rect=[0, 0.05, 1, 1]) # left, bottom, right, top (0-1)\n",
"\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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