initial commit FESurrogateModelTutorial

2026-05-21 17:03:51 +09:00
parent 93665d9ee6
commit 43b86669fa
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "741ede83",
+   "metadata": {},
+   "source": [
+    "# 06 Compare Surrogate Models\n",
+    "\n",
+    "? notebook? ?? model notebook?? ??? metrics JSON? ?? ??? ????. ??? ?? ???? ???."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "10f43a71",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "from pathlib import Path\n",
+    "\n",
+    "import pandas as pd\n",
+    "\n",
+    "from femsurrogate.plotting.comparison import plot_metric_comparison\n",
+    "\n",
+    "ROOT = Path.cwd().resolve()\n",
+    "if not (ROOT / \"pyproject.toml\").exists():\n",
+    "    ROOT = ROOT.parent\n",
+    "assert (ROOT / \"pyproject.toml\").exists(), ROOT\n",
+    "RESULTS_DIR = ROOT / \"reports\" / \"results\"\n",
+    "FIGURES_DIR = ROOT / \"reports\" / \"figures\"\n",
+    "FIGURES_DIR.mkdir(parents=True, exist_ok=True)\n",
+    "MODEL_NAMES = [\"rsm\", \"gpr\", \"random_forest\", \"gradient_boosting\", \"mlp\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9798e3bb",
+   "metadata": {},
+   "source": [
+    "## Metrics ??"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "55d2447d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "records = []\n",
+    "for model_name in MODEL_NAMES:\n",
+    "    metrics_path = RESULTS_DIR / f\"{model_name}_metrics.json\"\n",
+    "    assert metrics_path.exists(), metrics_path\n",
+    "    records.append(json.loads(metrics_path.read_text(encoding=\"utf-8\")))\n",
+    "\n",
+    "comparison = pd.DataFrame(records).sort_values(\"rmse\").reset_index(drop=True)\n",
+    "comparison_path = RESULTS_DIR / \"model_comparison.csv\"\n",
+    "comparison.to_csv(comparison_path, index=False)\n",
+    "comparison"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "731bb2f7",
+   "metadata": {},
+   "source": [
+    "## Metric ?? plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64657b84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "figures = {}\n",
+    "for metric in [\"rmse\", \"mae\", \"r2\", \"fit_time_s\", \"predict_time_s\"]:\n",
+    "    figure = plot_metric_comparison(comparison, metric=metric, title=f\"Surrogate {metric}\")\n",
+    "    figure.savefig(FIGURES_DIR / f\"comparison_{metric}.png\", dpi=150, bbox_inches=\"tight\")\n",
+    "    figures[metric] = figure\n",
+    "\n",
+    "figures[\"rmse\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63cb5b8d",
+   "metadata": {},
+   "source": [
+    "## ?? ???\n",
+    "\n",
+    "- `rmse`? `mae`? ?? ??? ?? ????.\n",
+    "- `r2`? ??? residual plot?? ?? ?? ??? bias? ??? ????? ????.\n",
+    "- `fit_time_s`, `predict_time_s`? ?? ??? ??? loop?? ????.\n",
+    "- GPR? ?? dataset?? ???? sample ?? ??? ?? ??? ??? ?? ? ??."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "pygments_lexer": "ipython3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}