initial commit FESurrogateModelTutorial

2026-05-21 17:03:51 +09:00
parent 93665d9ee6
commit 43b86669fa
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7e3ade70",
+   "metadata": {},
+   "source": [
+    "# 00 Beam2D FEM Dataset\n",
+    "\n",
+    "BeamExamples ?? ??? ?? ??? ? LHS sample? ???, repository solver? FEM surrogate ??? dataset? ????."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "71929240",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "from pathlib import Path\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "from femsurrogate.data.bounds import DEFAULT_PARAMETER_BOUNDS\n",
+    "from femsurrogate.data.dataset import build_dataset\n",
+    "from femsurrogate.data.sampling import generate_lhs_samples\n",
+    "from femsurrogate.data.schema import DEFAULT_RANDOM_SEED, TARGET_COLUMNS\n",
+    "from femsurrogate.fea.io import read_beam_example, read_expected_displacements\n",
+    "from femsurrogate.fea.solver import solve_linear_static\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",
+    "REFERENCE_DIR = ROOT / \"data\" / \"reference\"\n",
+    "REFERENCE_DIR.mkdir(parents=True, exist_ok=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df256ebc",
+   "metadata": {},
+   "source": [
+    "## BeamExamples ?? ??\n",
+    "\n",
+    "Fixture? ?? node? ?? `Ux`, `Uy`, `Rz`? ???? ???? ?? ????? ????."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0a8c947c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = read_beam_example(ROOT / \"BeamExamples\" / \"CantileverBeam.txt\")\n",
+    "expected = read_expected_displacements(ROOT / \"BeamExamples\" / \"CantileverBeam_Displacements.txt\")\n",
+    "actual = solve_linear_static(model)\n",
+    "\n",
+    "max_abs_error = 0.0\n",
+    "for node_id, expected_displacement in expected.items():\n",
+    "    actual_displacement = actual[node_id]\n",
+    "    actual_values = np.array(\n",
+    "        [actual_displacement.ux, actual_displacement.uy, actual_displacement.rz]\n",
+    "    )\n",
+    "    expected_values = np.array(\n",
+    "        [expected_displacement.ux, expected_displacement.uy, expected_displacement.rz]\n",
+    "    )\n",
+    "    error = float(np.max(np.abs(actual_values - expected_values)))\n",
+    "    max_abs_error = max(max_abs_error, error)\n",
+    "\n",
+    "assert max_abs_error <= 5e-7\n",
+    "max_abs_error"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6620d0ee",
+   "metadata": {},
+   "source": [
+    "## LHS sampling? FEM batch ??"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9923fd04",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "N_SAMPLES = 300\n",
+    "\n",
+    "samples = generate_lhs_samples(DEFAULT_PARAMETER_BOUNDS, n=N_SAMPLES, seed=DEFAULT_RANDOM_SEED)\n",
+    "dataset = build_dataset(samples)\n",
+    "\n",
+    "assert len(dataset) == N_SAMPLES\n",
+    "assert set(TARGET_COLUMNS).issubset(dataset.columns)\n",
+    "dataset.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0efee15",
+   "metadata": {},
+   "source": [
+    "## Dataset ??\n",
+    "\n",
+    "?? notebook? ?? CSV? metadata? ??? `data/reference/`? ????."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d80890bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset_path = REFERENCE_DIR / \"beam2d_lhs_300.csv\"\n",
+    "metadata_path = REFERENCE_DIR / \"beam2d_lhs_300_metadata.json\"\n",
+    "\n",
+    "dataset.to_csv(dataset_path, index=False)\n",
+    "metadata = {\n",
+    "    \"dataset_name\": \"beam2d_lhs_300\",\n",
+    "    \"sample_count\": N_SAMPLES,\n",
+    "    \"random_seed\": DEFAULT_RANDOM_SEED,\n",
+    "    \"unit_system\": \"SI\",\n",
+    "    \"fea_model\": \"2D Euler-Bernoulli beam/frame, linear static\",\n",
+    "    \"target_columns\": list(TARGET_COLUMNS),\n",
+    "    \"parameter_bounds\": {\n",
+    "        name: {\"lower\": bound.lower, \"upper\": bound.upper}\n",
+    "        for name, bound in DEFAULT_PARAMETER_BOUNDS.items()\n",
+    "    },\n",
+    "    \"notes\": \"Generated by notebooks/00_beam2d_fea_dataset.ipynb using src/femsurrogate.\",\n",
+    "}\n",
+    "metadata_path.write_text(json.dumps(metadata, indent=2), encoding=\"utf-8\")\n",
+    "\n",
+    "{\"dataset_path\": str(dataset_path), \"metadata_path\": str(metadata_path)}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d56bcddb",
+   "metadata": {},
+   "source": [
+    "## ?? sanity check"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e560e50c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset.describe().T.loc[[\"L_m\", \"b_m\", \"h_m\", \"E_pa\", \"P_n\", *TARGET_COLUMNS]]"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "pygments_lexer": "ipython3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}