def test_misorientation_matrix(self):
for test_euler in self.test_eulers:
o = Orientation.from_euler(test_euler)
g = o.orientation_matrix()
delta = np.dot(g, g.T)
self.assertEqual(
Orientation.misorientation_angle_from_delta(delta), 0.0)
def poll_system(g_list, dis_tol=1.0, verbose=False):
"""
Poll system to sort a series of orientation matrices determined by the indexation procedure.
For each orientation matrix, check if it corresponds to an existing solution, if so: vote for it,
if not add a new solution to the list
:param list g_list: the list of orientation matrices (should be in the fz)
:param float dis_tol: angular tolerance (degrees)
:param bool verbose: activate verbose mode (False by default)
:return: a tuple composed by the most popular orientation matrix, the corresponding vote number and the confidence index
"""
solution_indices = [0]
votes = [0]
vote_index = np.zeros(len(g_list), dtype=int)
dis_tol_rad = dis_tol * pi / 180
from pymicro.crystal.microstructure import Orientation
for i in range(len(g_list)):
g = g_list[i]
# rotations are already in the fundamental zone
for j in range(len(solution_indices)):
index = solution_indices[j]
delta = np.dot(g, g_list[index].T)
# compute misorientation angle in radians
angle = Orientation.misorientation_angle_from_delta(delta)
if verbose:
print('j=%d -- angle=%f' % (j, angle))
if angle <= dis_tol_rad:
votes[j] += 1
vote_index[i] = j
if verbose:
print('angle (deg) is %.2f' % (180 / pi * angle))
print('vote list is now %s' % votes)
print('solution_indices list is now %s' % solution_indices)
break
elif j == len(solution_indices) - 1:
solution_indices.append(i)
votes.append(1)
vote_index[i] = len(votes) - 1
if verbose:
print('vote list is now %s' % votes)
print('solution_indices list is now %s' % solution_indices)
break
index_result = np.argwhere(votes == np.amax(votes)).flatten()
if verbose:
print('Max vote =', np.amax(votes))
print('index result:', index_result)
print('Number of equivalent solutions :', len(index_result))
print(type(index_result))
print(index_result.shape)
final_orientation_matrix = []
for n in range(len(index_result)):
solutions = g_list[solution_indices[index_result[n]]]
if verbose:
print('Solution number {0:d} is'.format(n+1), solutions)
final_orientation_matrix.append(solutions)
result_vote = max(votes)
ci = confidence_index(votes)
vote_field = [votes[i] for i in vote_index]
return final_orientation_matrix, result_vote, ci, vote_field
def test_small_disorientation(self):
o_ref = Orientation(np.array([[-0.03454188, 0.05599919, -0.99783313],
[-0.01223192, -0.99837784, -0.05560633],
[-0.99932839, 0.01028467, 0.03517083]]))
o_12 = Orientation(np.array([[-0.03807341, -0.06932796, -0.99686712],
[-0.0234124, -0.99725469, 0.07024911],
[-0.99900064, 0.02601367, 0.03634576]]))
(angle, axis, axis_xyz) = o_ref.disorientation(o_12, crystal_structure=Symmetry.cubic)
self.assertAlmostEqual(angle * 180 / np.pi, 7.24, 2)
o_ref_fz = o_ref.move_to_FZ(symmetry=Symmetry.cubic, verbose=False)
o_12_fz = o_12.move_to_FZ(symmetry=Symmetry.cubic, verbose=False)
delta = np.dot(o_ref_fz.orientation_matrix(), o_12_fz.orientation_matrix().T)
mis_angle = Orientation.misorientation_angle_from_delta(delta)
self.assertAlmostEqual(mis_angle * 180 / np.pi, 7.24, 2)
