def test_vector_indexation_generator_init():
vectors = DiffractionVectors([[1], [2]])
vectors.cartesian = [[1], [2]]
vector_library = DiffractionVectorLibrary()
vector_indexation_generator = VectorIndexationGenerator(
vectors, vector_library)
assert isinstance(vector_indexation_generator, VectorIndexationGenerator)
assert vector_indexation_generator.vectors == vectors
assert vector_indexation_generator.library == vector_library
def test_vector_indexation_generator_index_vectors(vector_match_peaks,
vector_library):
# vectors not used directly
vectors = DiffractionVectors(np.array(vector_match_peaks[:, :2]))
vectors.cartesian = DiffractionVectors(np.array(vector_match_peaks))
gen = VectorIndexationGenerator(vectors, vector_library)
indexation = gen.index_vectors(mag_tol=0.1,
angle_tol=6,
index_error_tol=0.3,
n_peaks_to_index=2,
n_best=5)
# Values are tested directly on the match_vector in the util tests
assert isinstance(indexation.vectors, DiffractionVectors)
# (n_best=1, 5 result values from each)
np.testing.assert_equal(indexation.data.shape, (5, ))
# n_best=1, 3 peaks with hkl)
np.testing.assert_equal(indexation.hkls.shape, (1, 3, 3))
refined1 = gen.refine_n_best_orientations(indexation, 1.0, 1.0, n_best=0)
assert isinstance(refined1.vectors, DiffractionVectors)
np.testing.assert_equal(refined1.data.shape, (5, ))
refined2 = gen.refine_best_orientation(indexation, 1.0, 1.0)
assert isinstance(refined2.vectors, DiffractionVectors)
np.testing.assert_equal(refined2.data.shape, (1, ))
assert isinstance(refined2.data[0], OrientationResult)
assert refined2.data[0].phase_index == indexation.data[0].phase_index
assert refined2.data[0].match_rate == indexation.data[0].match_rate
# Must use a large tolerance here, because there are only 3 vectors
np.testing.assert_almost_equal(
np.diag(refined1.data[0].rotation_matrix),
np.diag(indexation.data[0].rotation_matrix),
1,
)
np.testing.assert_almost_equal(
np.diag(refined2.data[0].rotation_matrix),
np.diag(indexation.data[0].rotation_matrix),
1,
)