def test_good_case(self):
# hypothetical data for two atoms
good_powder = {"a_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]],
[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])},
"b_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]],
[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])}}
good_tester = PowderData(num_atoms=2)
good_tester.set(items=good_powder)
extracted_data = good_tester.extract()
for key in good_powder:
for k_point in good_powder[key]:
self.assertEqual(True, np.allclose(good_powder[key][k_point], extracted_data[key][k_point]))
def test_good_case(self):
# hypothetical data for two atoms
good_powder = {"a_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]],
[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])},
"b_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]],
[[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])}}
good_tester = PowderData(num_atoms=2)
good_tester.set(items=good_powder)
extracted_data = good_tester.extract()
for key in good_powder:
for k_point in good_powder[key]:
self.assertEqual(True, np.allclose(good_powder[key][k_point], extracted_data[key][k_point]))
def test_set(self):
poor_tester = PowderData(num_atoms=2)
# wrong items: list instead of numpy array
bad_items = {"a_tensors": [[0.002, 0.001]], "b_tensors": [[0.002, 0.001]]}
with self.assertRaises(ValueError):
poor_tester.set(items=bad_items)
# wrong size of items: data only for one atom ; should be for two atoms
bad_items = {"a_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03], [0.01, 0.02, 0.03], [0.01, 0.02, 0.03]]])},
"b_tensors": {"0": np.asarray([[[0.01, 0.02, 0.03], [0.01, 0.02, 0.03], [0.01, 0.02, 0.03]]])}}
with self.assertRaises(ValueError):
poor_tester.set(items=bad_items)
def test_set(self):
poor_tester = PowderData(num_atoms=2)
# wrong items: list instead of numpy array
bad_items = {
"a_tensors": [[0.002, 0.001]],
"b_tensors": [[0.002, 0.001]]
}
with self.assertRaises(ValueError):
poor_tester.set(items=bad_items)
# wrong size of items: data only for one atom ; should be for two atoms
bad_items = {
"a_tensors": {
"0":
np.asarray([[[0.01, 0.02, 0.03], [0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])
},
"b_tensors": {
"0":
np.asarray([[[0.01, 0.02, 0.03], [0.01, 0.02, 0.03],
[0.01, 0.02, 0.03]]])
}
}
with self.assertRaises(ValueError):
poor_tester.set(items=bad_items)
def test_input(self):
# wrong number of atoms
with self.assertRaises(ValueError):
# noinspection PyUnusedLocal
poor_tester = PowderData(num_atoms=-2)