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Move the polarized ptycho dataset class back to loading data from the actual stored motor positions, and fix the test for the gaussian probe

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This commit is contained in:
Abe Levitan
2021-08-04 19:43:20 -04:00
parent 7421c8527c
commit b3e45af06e
3 changed files with 10 additions and 24 deletions
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CDTools/datasets/polarized_ptycho_2d_dataset.py
+5 -22
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@@ -62,18 +62,10 @@ class PolarizedPtycho2DDataset(Ptycho2DDataset):
*args, **kwargs)
# self.polarizer = t.tensor(polarizer_angles, dtype=t.float32)
# self.analyzer = t.tensor(analyzer_angles, dtype=t.float32)
self.polarizer = t.tensor(polarizer_angles, dtype=t.float32)
self.analyzer = t.tensor(analyzer_angles, dtype=t.float32)
polarizer = []
analyzer = []
for k in range(t.tensor(translations).shape[0]):
polarizer.append((k//3)%3 * 45)
analyzer.append((k%3 * 45))
self.polarizer = t.tensor(polarizer)
self.analyzer = t.tensor(analyzer)
def _load(self, index):
""" Internal function to load data
@@ -157,17 +149,8 @@ class PolarizedPtycho2DDataset(Ptycho2DDataset):
dataset.__class__ = cls
# Now, we save out the polarizer and analyzer states
# polarizer = cdtdata.get_shot_to_shot_info(cxi_file, 'polarizer_angle')
# analyzer = cdtdata.get_shot_to_shot_info(cxi_file, 'analyzer_angle')
polarizer = []
analyzer = []
for k in range(dataset.translations.shape[0]):
polarizer.append((k//3)%3)
analyzer.append((k%3))
dataset.polarizer = t.tensor(polarizer)
dataset.analyzer = t.tensor(analyzer)
polarizer = cdtdata.get_shot_to_shot_info(cxi_file, 'polarizer_angle')
analyzer = cdtdata.get_shot_to_shot_info(cxi_file, 'analyzer_angle')
dataset.analyzer = t.tensor(analyzer, dtype=t.float32)
dataset.polarizer = t.tensor(polarizer, dtype=t.float32)
tests/test_datasets.py
+2
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@@ -308,6 +308,8 @@ def test_PolarizedPtycho2DDataset_init():
detector_geometry=detector_geometry,
mask=mask)
print(analyzer.dtype)
print(dataset.analyzer.dtype)
assert t.all(t.eq(dataset.mask,t.BoolTensor(mask)))
assert dataset.entry_info == entry_info
assert dataset.sample_info == sample_info
tests/tools/test_initializers.py
+3 -2
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@@ -145,9 +145,10 @@ def test_gaussian_probe(ptycho_cxi_1):
normalization += np.sum(im.cpu().numpy())
normalization /= len(dataset)
normalization_1 = normalization / np.sum(np.abs(np_probe)**2)
normalization_1 = np.sqrt(normalization / np.sum(np.abs(np_probe)**2))
probe = initializers.gaussian_probe(dataset, basis, shape, sigma).numpy()
assert np.allclose(probe, normalization_1*np_probe)
# And then a propagated probe
@@ -159,7 +160,7 @@ def test_gaussian_probe(ptycho_cxi_1):
Rz = z * (1 + (zr / z)**2)
np_probe = np.exp(-Rs**2 / wz**2) * np.exp(-1j * k * Rs**2 / (2 * Rz))
normalization_2 = normalization / np.sum(np.abs(np_probe)**2)
normalization_2 = np.sqrt(normalization / np.sum(np.abs(np_probe)**2))
probe = initializers.gaussian_probe(dataset, basis, shape, sigma,
propagation_distance=z).numpy()