def _pinv_multithread(self, matrices):
inv_matrices = []
try:
import anharmonic._forcefit as forcefit
multi = len(matrices)
row_nums = np.array([m.shape[0] for m in matrices], dtype='intc')
info = np.zeros(len(row_nums), dtype='intc')
max_row_num = max(row_nums)
column_num = matrices[0].shape[1]
mats_in = np.zeros((multi, max_row_num * column_num),
dtype='double')
for i in range(multi):
mats_in[i, :row_nums[i] * column_num] = matrices[i].flatten()
mats_out = np.zeros_like(mats_in)
forcefit.pinv_mt(mats_in, mats_out, row_nums, max_row_num,
column_num, self._pinv_cutoff, info)
inv_matrices = [
mats_out[i, :row_nums[i] * column_num].reshape(column_num, -1)
for i in range(multi)
]
except ImportError:
for mat in matrices:
inv_mat = np.linalg.pinv(mat)
inv_matrices.append(inv_mat)
return inv_matrices
def _invert_displacements(self, rot_disps_set):
try:
import anharmonic._forcefit as forcefit
row_nums = np.array([x.shape[0] for x in rot_disps_set],
dtype='intc')
info = np.zeros(len(row_nums), dtype='intc')
max_row_num = max(row_nums)
column_num = rot_disps_set[0].shape[1]
rot_disps = np.zeros((self._num_atom, max_row_num * column_num),
dtype='double')
for i in range(self._num_atom):
rot_disps[i, :row_nums[i] *
column_num] = rot_disps_set[i].flatten()
inv_disps = np.zeros_like(rot_disps)
forcefit.pinv_mt(rot_disps, inv_disps, row_nums, max_row_num,
column_num, 1e-13, info)
inv_disps_set = [
inv_disps[i, :row_nums[i] * column_num].reshape(
column_num, -1) for i in range(self._num_atom)
]
except ImportError:
inv_disps_set = [np.linalg.pinv(d) for d in rot_disps_set]
return inv_disps_set
def _pinv_multithread(self, matrices):
inv_matrices = []
try:
import anharmonic._forcefit as forcefit
multi = len(matrices)
row_nums = np.intc([m.shape[0] for m in matrices])
info = np.zeros(len(row_nums), dtype='intc')
max_row_num = max(row_nums)
column_num = matrices[0].shape[1]
mats_in = np.zeros((multi, max_row_num * column_num),
dtype='double')
for i in range(multi):
mats_in[i, :row_nums[i] * column_num] = matrices[i].flatten()
mats_out = np.zeros_like(mats_in)
forcefit.pinv_mt(mats_in,
mats_out,
row_nums,
max_row_num,
column_num,
self._pinv_cutoff,
info)
inv_matrices = [
mats_out[i, :row_nums[i] * column_num].reshape(column_num, -1)
for i in range(multi)]
except ImportError:
for mat in matrices:
inv_mat = np.linalg.pinv(mat)
inv_matrices.append(inv_mat)
return inv_matrices
def _invert_displacements(self, rot_disps_set):
try:
import anharmonic._forcefit as forcefit
row_nums = np.array([x.shape[0] for x in rot_disps_set],
dtype='intc')
info = np.zeros(len(row_nums), dtype='intc')
max_row_num = max(row_nums)
column_num = rot_disps_set[0].shape[1]
rot_disps = np.zeros((self._num_atom, max_row_num * column_num),
dtype='double')
for i in range(self._num_atom):
rot_disps[
i, :row_nums[i] * column_num] = rot_disps_set[i].flatten()
inv_disps = np.zeros_like(rot_disps)
forcefit.pinv_mt(rot_disps,
inv_disps,
row_nums,
max_row_num,
column_num,
1e-13,
info)
inv_disps_set = [
inv_disps[i, :row_nums[i] * column_num].reshape(column_num, -1)
for i in range(self._num_atom)]
except ImportError:
inv_disps_set = [np.linalg.pinv(d) for d in rot_disps_set]
return inv_disps_set
