def __init__(
self,
energies: Dict[Spin, np.ndarray],
kpoints: np.ndarray,
ir_kpoints_idx: np.ndarray,
ir_kpoint_mapping: np.ndarray,
ir_kpoint_weights: np.ndarray,
tetrahedra: Dict[Spin, np.ndarray],
ir_tetrahedra: Dict[Spin, np.ndarray],
ir_tetrahedra_energies: Dict[Spin, np.ndarray],
ir_tetrahedra_idx: np.ndarray,
ir_tetrahedra_to_full_idx: np.ndarray,
ir_tetrahedra_weights: np.ndarray,
e21: Dict[Spin, np.ndarray],
e31: Dict[Spin, np.ndarray],
e41: Dict[Spin, np.ndarray],
e32: Dict[Spin, np.ndarray],
e42: Dict[Spin, np.ndarray],
e43: Dict[Spin, np.ndarray],
max_tetrahedra_energies: Dict[Spin, np.ndarray],
min_tetrahedra_energies: Dict[Spin, np.ndarray],
cross_section_weights: Dict[Spin, np.ndarray],
tetrahedron_volume: float,
weights_cache: Optional[Dict[Spin, np.ndarray]] = None,
weights_mask_cache: Optional[Dict[Spin, np.ndarray]] = None,
energies_cache: Optional[Dict[Spin, np.ndarray]] = None,
):
self.energies = energies
self.kpoints = kpoints
self.ir_kpoints_idx = ir_kpoints_idx
self.ir_kpoint_mapping = ir_kpoint_mapping
self.ir_kpoint_weights = ir_kpoint_weights
self.tetrahedra = tetrahedra
self.ir_tetrahedra = ir_tetrahedra
self.ir_tetrahedra_energies = ir_tetrahedra_energies
self.ir_tetrahedra_idx = ir_tetrahedra_idx
self.ir_tetrahedra_to_full_idx = ir_tetrahedra_to_full_idx
self.ir_tetrahedra_weights = ir_tetrahedra_weights
self.e21 = e21
self.e31 = e31
self.e41 = e41
self.e32 = e32
self.e42 = e42
self.e43 = e43
self.max_tetrahedra_energies = max_tetrahedra_energies
self.min_tetrahedra_energies = min_tetrahedra_energies
self.cross_section_weights = cross_section_weights
self._tetrahedron_volume = tetrahedron_volume
self._weights_cache = {} if weights_cache is None else weights_cache
self._weights_mask_cache = ({} if weights_mask_cache is None else
weights_mask_cache)
self._energies_cache = {} if energies_cache is None else energies_cache
self.grouped_ir_to_full = groupby(
np.arange(len(ir_tetrahedra_to_full_idx)),
ir_tetrahedra_to_full_idx)
self._ir_weights_shape = {
s: (len(energies[s]), len(ir_kpoints_idx))
for s in energies
}
def test_groupby(elements, groups, expected):
elements = ["a", "b", "1", "2", "c", "d"]
groups = [2, 0, 1, 2, 0, 0]
expected_output = [["b", "c", "d"], ["1"], ["a", "2"]]
output = groupby(elements, groups)
output = [x.tolist() for x in output]
assert output == expected_output
def __init__(
self,
structure: Structure,
energies: Dict[Spin, np.ndarray],
vvelocities_product: Dict[Spin, np.ndarray],
velocities: Dict[Spin, np.ndarray],
kpoint_mesh: np.ndarray,
kpoints: np.ndarray,
ir_kpoints_idx: np.ndarray,
ir_to_full_kpoint_mapping: np.ndarray,
tetrahedra: np.ndarray,
ir_tetrahedra_info: np.ndarray,
efermi: float,
num_electrons: float,
is_metal: bool,
soc: bool,
vb_idx: Optional[Dict[Spin, int]] = None,
):
self.structure = structure
self.velocities_product = vvelocities_product
self.kpoint_mesh = kpoint_mesh
self.intrinsic_fermi_level = efermi
self.ir_to_full_kpoint_mapping = ir_to_full_kpoint_mapping
self._soc = soc
self.num_electrons = num_electrons
self.is_metal = is_metal
self.vb_idx = vb_idx
self.spins = list(energies.keys())
self.velocities = {
s: v.transpose((0, 2, 1))
for s, v in velocities.items()
}
self.dos = None
self.scattering_rates = None
self.scattering_labels = None
self.doping = None
self.temperatures = None
self.fermi_levels = None
self.electron_conc = None
self.hole_conc = None
self.conductivity = None
self.seebeck = None
self.electronic_thermal_conductivity = None
self.mobility = None
self.overlap_calculator = None
self.mrta_calculator = None
self.fd_cutoffs = None
self.grouped_ir_to_full = groupby(np.arange(len(kpoints)),
ir_to_full_kpoint_mapping)
self.tetrahedral_band_structure = TetrahedralBandStructure.from_data(
energies, kpoints, tetrahedra, structure, ir_kpoints_idx,
ir_to_full_kpoint_mapping, *ir_tetrahedra_info)
logger.info("Initializing momentum relaxation time factor calculator")
self.mrta_calculator = MRTACalculator.from_data(
kpoints, self.velocities)
def __init__(
self,
structure: Structure,
energies: Dict[Spin, np.ndarray],
vvelocities_product: Dict[Spin, np.ndarray],
effective_mass: Dict[Spin, np.ndarray],
projections: Dict[Spin, Dict[str, np.ndarray]],
kpoint_mesh: np.ndarray,
kpoints: np.ndarray,
ir_kpoints: np.ndarray,
ir_kpoints_idx: np.ndarray,
ir_to_full_kpoint_mapping: np.ndarray,
tetrahedra: np.ndarray,
ir_tetrahedra_info: np.ndarray,
efermi: float,
num_electrons: float,
is_metal: bool,
soc: bool,
vb_idx: Optional[Dict[Spin, int]] = None,
):
self.structure = structure
self.energies = energies
self.velocities_product = vvelocities_product
self.effective_mass = effective_mass
self.kpoint_mesh = kpoint_mesh
self.kpoints = kpoints
self.ir_kpoints = ir_kpoints
self.ir_kpoints_idx = ir_kpoints_idx
self.ir_to_full_kpoint_mapping = ir_to_full_kpoint_mapping
self.intrinsic_fermi_level = efermi
self._soc = soc
self.num_electrons = num_electrons
self.is_metal = is_metal
self.vb_idx = vb_idx
self.spins = self.energies.keys()
self.a_factor, self.c_factor = _calculate_orbital_factors(projections)
self.dos = None
self.scattering_rates = None
self.scattering_labels = None
self.doping = None
self.temperatures = None
self.fermi_levels = None
self.electron_conc = None
self.hole_conc = None
self.conductivity = None
self.seebeck = None
self.electronic_thermal_conductivity = None
self.mobility = None
self.overlap_calculator = None
self.fd_cutoffs = None
self.grouped_ir_to_full = groupby(np.arange(len(kpoints)),
ir_to_full_kpoint_mapping)
self.tetrahedral_band_structure = TetrahedralBandStructure(
energies, kpoints, tetrahedra, structure, ir_kpoints_idx,
ir_to_full_kpoint_mapping, *ir_tetrahedra_info)
def __init__(
self,
energies: Dict[Spin, np.ndarray],
kpoints: np.ndarray,
tetrahedra: np.ndarray,
structure: Structure,
ir_kpoints_idx: np.ndarray,
ir_kpoint_mapping: np.ndarray,
ir_tetrahedra_idx: Optional[np.ndarray] = None,
ir_tetrahedra_to_full_idx: Optional[np.ndarray] = None,
ir_tetrahedra_weights: Optional[np.ndarray] = None,
):
logger.info("Generating tetrahedron mesh")
tparams = (ir_tetrahedra_idx, ir_tetrahedra_to_full_idx,
ir_tetrahedra_weights)
if len(set([x is None for x in tparams])) != 1:
raise ValueError(
"Either all or none of ir_tetrahedra_idx, "
"ir_tetrahedra_to_full_idx and ir_tetrahedra_weights should be set."
)
if ir_tetrahedra_idx is None:
ir_tetrahedra_idx = np.arange(len(kpoints))
ir_tetrahedra_to_full_idx = np.ones_like(ir_tetrahedra_idx)
ir_tetrahedra_weights = np.ones_like(ir_tetrahedra_idx)
self.energies = energies
self.kpoints = kpoints
self.ir_tetrahedra_idx = ir_tetrahedra_idx
self.ir_tetrahedra_to_full_idx = ir_tetrahedra_to_full_idx
self.ir_tetrahedra_weights = ir_tetrahedra_weights
self.ir_kpoints_idx = ir_kpoints_idx
self.ir_kpoint_mapping = ir_kpoint_mapping
_, self.ir_kpoint_weights = np.unique(ir_kpoint_mapping,
return_counts=True)
# need to keep track of full tetrahedra to recover full k-point indices
# when calculating scattering rates (i.e., k-k' is symmetry inequivalent).
self.tetrahedra, _ = process_tetrahedra(tetrahedra, self.energies)
# store irreducible tetrahedra and use energies to calculate diffs and min/maxes
self.ir_tetrahedra, self.ir_tetrahedra_energies = process_tetrahedra(
tetrahedra[self.ir_tetrahedra_idx], self.energies)
# the remaining properties are given for each irreducible tetrahedra
(
self.e21,
self.e31,
self.e41,
self.e32,
self.e42,
self.e43,
) = get_tetrahedra_energy_diffs(self.ir_tetrahedra_energies)
(
self.max_tetrahedra_energies,
self.min_tetrahedra_energies,
) = get_max_min_tetrahedra_energies(self.ir_tetrahedra_energies)
self.cross_section_weights = get_tetrahedra_cross_section_weights(
structure.lattice.reciprocal_lattice.matrix,
self.kpoints,
self.ir_tetrahedra,
self.e21,
self.e31,
self.e41,
)
self._tetrahedron_volume = 1 / len(tetrahedra)
self.grouped_ir_to_full = groupby(
np.arange(len(ir_tetrahedra_to_full_idx)),
ir_tetrahedra_to_full_idx)
self._ir_weights_shape = {
s: (len(self.energies[s]), len(ir_kpoints_idx))
for s in self.energies
}
self._weights_cache = {}
self._weights_mask_cache = {}
self._energies_cache = {}
self._tetrahedra_connections = defaultdict(set)
for tet in tetrahedra:
self._tetrahedra_connections[tet[0]].update(tet)
self._tetrahedra_connections[tet[1]].update(tet)
self._tetrahedra_connections[tet[2]].update(tet)
self._tetrahedra_connections[tet[3]].update(tet)
