| """Patch-map plotting uses inference timestamps and tolerates partial outputs.""" |
|
|
| import numpy as np |
| import pandas as pd |
| from matplotlib.axes import Axes |
| from matplotlib.colors import LogNorm |
|
|
| from forecasting.evaluation import FOXESEvaluator |
|
|
|
|
| def test_patch_maps_match_csv_timestamps_with_optional_aia(tmp_path, monkeypatch): |
| patches = tmp_path / 'inference_patch' |
| flux_dir = patches / 'flux' |
| uncertainty_dir = patches / 'patch_uncertainty' |
| aia_dir = tmp_path / 'aia' |
| for directory in (flux_dir, uncertainty_dir, aia_dir): |
| directory.mkdir(parents=True) |
|
|
| first = '2023-08-04T15:30:00' |
| second = '2023-08-06T05:46:00' |
| np.save(flux_dir / f'{first}.npy', np.ones((2, 2)) * 1e-7) |
| np.save(uncertainty_dir / f'{first}.npy', np.ones((2, 2)) * 1e-8) |
| np.save(aia_dir / f'{first}.npy', np.zeros((7, 16, 16))) |
| np.save(flux_dir / f'{second}.npy', np.ones((2, 2)) * 2e-3) |
| np.save(flux_dir / 'unrelated.npy', np.ones((2, 2))) |
|
|
| csv_path = tmp_path / 'predictions.csv' |
| pd.DataFrame({ |
| 'timestamp': [first, second], |
| 'predictions': [4e-7, 8e-7], |
| 'groundtruth': [5e-7, 9e-7], |
| }).to_csv(csv_path, index=False) |
| evaluator = FOXESEvaluator( |
| csv_path, tmp_path / 'evaluation', |
| inference_patch_dir=patches, aia_dir=aia_dir, |
| ) |
| evaluator.load_data() |
|
|
| plotted = [] |
| original_imshow = Axes.imshow |
|
|
| def record_imshow(self, image, *args, **kwargs): |
| plotted.append(kwargs) |
| return original_imshow(self, image, *args, **kwargs) |
|
|
| monkeypatch.setattr(Axes, 'imshow', record_imshow) |
|
|
| assert evaluator.plot_patch_maps() == 2 |
| assert all(call['origin'] == 'lower' for call in plotted) |
| patch_norms = [call['norm'] for call in plotted if 'norm' in call] |
| assert len(patch_norms) == 3 |
| assert all(call['cmap'] == 'inferno' for call in plotted if 'norm' in call) |
| assert all(isinstance(norm, LogNorm) for norm in patch_norms) |
| assert all(np.isclose(norm.vmin, 1e-8, rtol=1e-12, atol=0) |
| and np.isclose(norm.vmax, 2e-3, rtol=1e-12, atol=0) |
| for norm in patch_norms) |
| figures = sorted((tmp_path / 'evaluation' / 'plots' / 'patch_maps').glob('*.png')) |
| assert [path.name for path in figures] == [ |
| '2023-08-04T15_30_00.png', '2023-08-06T05_46_00.png', |
| ] |
| assert all(path.stat().st_size > 0 for path in figures) |
|
|
