def eigendecompose(self, normalise=False):
"""
Performs and eigendecomposition of the tensor and orders into
descending eigenvalues
"""
self.eigenvalues, self.eigenvectors = utils.eigendecompose(self.tensor,
normalise)
return self.eigenvalues, self.eigenvectors
def get_nodal_planes(self):
"""
Returns the nodal planes by eigendecomposition of the moment tensor
"""
# Convert reference frame to NED
self.tensor, self.tensor_sigma = self._to_ned()
self.ref_frame = 'NED'
# Eigenvalue decomposition
# Tensor
_, evect = utils.eigendecompose(self.tensor)
# Rotation matrix
_, rot_vec = utils.eigendecompose(np.matrix([[0., 0., -1],
[0., 0., 0.],
[-1., 0., 0.]]))
rotation_matrix = (np.matrix(evect * rot_vec.T)).T
if np.linalg.det(rotation_matrix) < 0.:
rotation_matrix *= -1.
flip_dc = np.matrix([[0., 0., -1.],
[0., -1., 0.],
[-1., 0., 0.]])
rotation_matrices = sorted(
[rotation_matrix, flip_dc * rotation_matrix],
cmp=cmp_mat)
nodal_planes = GCMTNodalPlanes()
dip, strike, rake = [(180. / pi) * angle
for angle in utils.matrix_to_euler(rotation_matrices[0])]
# 1st Nodal Plane
nodal_planes.nodal_plane_1 = {'strike': strike % 360,
'dip': dip,
'rake': -rake}
# 2nd Nodal Plane
dip, strike, rake = [(180. / pi) * angle
for angle in utils.matrix_to_euler(rotation_matrices[1])]
nodal_planes.nodal_plane_2 = {'strike': strike % 360.,
'dip': dip,
'rake': -rake}
return nodal_planes
