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| import os | |
| import sys | |
| import numpy as np | |
| PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | |
| if PROJECT_ROOT not in sys.path: | |
| sys.path.insert(0, PROJECT_ROOT) | |
| from data_preparation.prepare_dataset import ( | |
| SELECTED_FEATURES, | |
| _generate_synthetic_data, | |
| get_numpy_splits, | |
| ) | |
| def test_generate_synthetic_data_shape(): | |
| X, y = _generate_synthetic_data("face_orientation") | |
| assert X.shape[0] == 500 | |
| assert y.shape[0] == 500 | |
| assert X.shape[1] == len(SELECTED_FEATURES["face_orientation"]) | |
| def test_get_numpy_splits_consistency(): | |
| splits, num_features, num_classes, scaler = get_numpy_splits("face_orientation") | |
| # train/val/test each have samples | |
| n_train = len(splits["y_train"]) | |
| n_val = len(splits["y_val"]) | |
| n_test = len(splits["y_test"]) | |
| assert n_train > 0 | |
| assert n_val > 0 | |
| assert n_test > 0 | |
| # feature dim should same as num_features | |
| assert splits["X_train"].shape[1] == num_features | |
| assert num_classes >= 2 | |