feat: add read-only training dataset loader

2026-09-11 10:08:15 +08:00
parent 7bdd705cef
commit 272542bad5
4 changed files with 302 additions and 0 deletions
@@ -0,0 +1,152 @@
+import sqlite3
+
+import pytest
+
+from lmpm.training.dataset import (
+    TrainingDataError,
+    load_sqlite_training_dataset,
+)
+
+MATERIAL_SCHEMA = """
+CREATE TABLE material_records (
+    id INTEGER PRIMARY KEY,
+    entry_batch_id INTEGER NOT NULL,
+    experiment_id VARCHAR(100) NOT NULL UNIQUE,
+    test_date DATE NOT NULL,
+    material_category VARCHAR(100) NOT NULL,
+    material_name VARCHAR(200) NOT NULL,
+    apparent_density FLOAT,
+    uv_absorption_355nm FLOAT,
+    material_thickness FLOAT NOT NULL,
+    moisture_content FLOAT,
+    thermal_conductivity FLOAT,
+    initial_decomposition_temp FLOAT,
+    melting_vaporization_temp FLOAT,
+    specific_heat_capacity FLOAT,
+    carbon_residue_rate FLOAT,
+    surface_roughness FLOAT,
+    hardness FLOAT,
+    actual_output_power FLOAT NOT NULL,
+    display_current FLOAT NOT NULL,
+    scanning_speed FLOAT NOT NULL,
+    pulse_frequency FLOAT NOT NULL,
+    pulse_width FLOAT NOT NULL,
+    defocus_amount FLOAT NOT NULL,
+    scan_line_spacing FLOAT NOT NULL,
+    filling_method VARCHAR(100) NOT NULL,
+    processing_size VARCHAR(100) NOT NULL,
+    is_cut_through BOOLEAN NOT NULL,
+    carbonized_edge_width FLOAT NOT NULL,
+    etching_depth FLOAT NOT NULL,
+    is_fire_smolder BOOLEAN NOT NULL,
+    pattern_clarity_score FLOAT NOT NULL,
+    presentation_balance_score FLOAT NOT NULL,
+    finished_image_filename VARCHAR(255) NOT NULL,
+    remarks TEXT NOT NULL,
+    created_at DATETIME NOT NULL
+);
+"""
+
+
+def make_record(number: int) -> tuple:
+    return (
+        number,
+        1,
+        f"LAS-2026-{number:04d}",
+        "2026-09-11",
+        "polymer",
+        f"Acrylic {number}",
+        1.18 if number == 1 else None,
+        0.92,
+        3.0,
+        None,
+        0.19,
+        None,
+        None,
+        1.5,
+        None,
+        1.2,
+        None,
+        8.5 + number,
+        2.0,
+        80.0,
+        20.0,
+        5.0,
+        0.0,
+        0.1,
+        "双向填充",
+        "20x20",
+        number == 1,
+        0.2,
+        30.0,
+        False,
+        9.0,
+        8.0,
+        f"image-{number}.jpg",
+        "stable",
+        "2026-09-11T08:00:00+00:00",
+    )
+
+
+def create_database(tmp_path, *, with_table: bool = True) -> object:
+    database_path = tmp_path / f"platform-{int(with_table)}.db"
+    connection = sqlite3.connect(database_path)
+    if with_table:
+        connection.execute(MATERIAL_SCHEMA)
+        connection.executemany(
+            """
+            INSERT INTO material_records VALUES (
+                ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,
+                ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?
+            )
+            """,
+            [make_record(1), make_record(2)],
+        )
+    connection.commit()
+    connection.close()
+    return database_path
+
+
+def test_sqlite_dataset_maps_features_and_targets(tmp_path):
+    dataset = load_sqlite_training_dataset(create_database(tmp_path))
+
+    assert dataset.experiment_ids == ["LAS-2026-0001", "LAS-2026-0002"]
+    assert dataset.feature_names[:5] == [
+        "apparent_density",
+        "uv_absorption_355nm",
+        "material_thickness",
+        "moisture_content",
+        "thermal_conductivity",
+    ]
+    assert dataset.feature_names[-1] == "processing_size"
+    assert dataset.target_names == [
+        "is_cut_through",
+        "carbonized_edge_width",
+        "etching_depth",
+        "is_fire_smolder",
+        "pattern_clarity_score",
+        "presentation_balance_score",
+    ]
+    assert dataset.records[0].metadata == {
+        "experiment_id": "LAS-2026-0001",
+        "test_date": "2026-09-11",
+        "material_category": "polymer",
+        "material_name": "Acrylic 1",
+    }
+    assert dataset.records[0].features["actual_output_power"] == pytest.approx(9.5)
+    assert dataset.records[0].targets["is_cut_through"] is True
+    assert dataset.records[1].targets["is_cut_through"] is False
+
+
+def test_missing_database_raises_expected_error(tmp_path):
+    missing_path = tmp_path / "missing.db"
+
+    with pytest.raises(FileNotFoundError):
+        load_sqlite_training_dataset(missing_path)
+
+
+def test_database_without_material_table_raises_expected_error(tmp_path):
+    database_path = create_database(tmp_path, with_table=False)
+
+    with pytest.raises(TrainingDataError, match="material_records"):
+        load_sqlite_training_dataset(database_path)