def set_integration_weights(self, scattering_event_class=None):
if self._frequency_points is None:
bi = self._pp.band_indices
f_points = self._frequencies[self._grid_point][bi]
else:
f_points = self._frequency_points
self._g, _g_zero = get_triplets_integration_weights(
self._pp,
np.array(f_points, dtype='double'),
self._sigma,
self._sigma_cutoff,
is_collision_matrix=self._is_collision_matrix)
if self._frequency_points is None:
self._g_zero = _g_zero
else:
# g_zero feature can not be used in frequency sampling mode.
# zero values of the following array shape is used in C-routine.
# shape = [num_triplets, num_band0, num_band, num_band]
shape = list(self._g.shape[1:])
shape[1] = len(self._pp.band_indices)
self._g_zero_zeros = np.zeros(shape=shape, dtype='byte', order='C')
self._g_zero_frequency_points = _g_zero
if scattering_event_class == 1 or scattering_event_class == 2:
self._g[scattering_event_class - 1] = 0
def run_integration_weights(self, lang="C"):
"""Compute triplets integration weights."""
self._g, self._g_zero = get_triplets_integration_weights(
self,
self._frequency_points,
self._sigma,
sigma_cutoff=self._sigma_cutoff,
is_collision_matrix=(self._temperature is None),
lang=lang,
)
def _run_c_with_g(self):
self.run_phonon_solver(self._triplets_at_q.ravel())
max_phonon_freq = np.max(self._frequencies)
self._frequency_points = get_frequency_points(
max_phonon_freq=max_phonon_freq,
sigmas=[
self._sigma,
],
frequency_points=None,
frequency_step=self._frequency_step,
num_frequency_points=self._num_frequency_points)
num_freq_points = len(self._frequency_points)
num_mesh = np.prod(self._mesh)
if self._temperatures is None:
jdos = np.zeros((num_freq_points, 2), dtype='double')
else:
num_temps = len(self._temperatures)
jdos = np.zeros((num_temps, num_freq_points, 2), dtype='double')
occ_phonons = []
for t in self._temperatures:
freqs = self._frequencies[self._triplets_at_q[:, 1:]]
occ_phonons.append(
np.where(freqs > self._cutoff_frequency,
bose_einstein(freqs, t), 0))
for i, freq_point in enumerate(self._frequency_points):
g, _ = get_triplets_integration_weights(
self,
np.array([freq_point], dtype='double'),
self._sigma,
is_collision_matrix=True,
neighboring_phonons=(i == 0))
if self._temperatures is None:
jdos[i, 1] = np.sum(
np.tensordot(g[0, :, 0], self._weights_at_q, axes=(0, 0)))
gx = g[2] - g[0]
jdos[i, 0] = np.sum(
np.tensordot(gx[:, 0], self._weights_at_q, axes=(0, 0)))
else:
for j, n in enumerate(occ_phonons):
for k, l in list(np.ndindex(g.shape[3:])):
jdos[j, i, 1] += np.dot(
(n[:, 0, k] + n[:, 1, l] + 1) * g[0, :, 0, k, l],
self._weights_at_q)
jdos[j, i, 0] += np.dot(
(n[:, 0, k] - n[:, 1, l]) * g[1, :, 0, k, l],
self._weights_at_q)
self._joint_dos = jdos / num_mesh
def set_integration_weights(self, scattering_event_class=None):
if self._frequency_points is None:
f_points = self._frequencies[self._grid_point][self._band_indices]
else:
f_points = self._frequency_points
self._g, _g_zero = get_triplets_integration_weights(
self._pp,
np.array(f_points, dtype='double'),
self._sigma,
is_collision_matrix=self._is_collision_matrix)
if self._frequency_points is None:
self._g_zero = _g_zero
if scattering_event_class == 1 or scattering_event_class == 2:
self._g[scattering_event_class - 1] = 0