/
solver.py
1346 lines (1030 loc) · 45 KB
/
solver.py
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# -*- coding: utf-8 -*-
from __future__ import division, print_function
import functools
import math
import os
import numbers
import re
import sys
import time
import h5py
import numpy as np
import meep as mp
from . import mode_solver, with_hermitian_epsilon, verbosity
from meep.geom import init_do_averaging
from meep.simulation import get_num_args
try:
basestring
except NameError:
basestring = str
U_MIN = 0
U_PROD = 1
U_MEAN = 2
class MPBArray(np.ndarray):
def __new__(cls, input_array, lattice, kpoint=None, bloch_phase=False):
# Input array is an already formed ndarray instance
# We first cast to be our class type
obj = np.asarray(input_array).view(cls)
# add the new properties to the created instance
obj.lattice = lattice
obj.kpoint = kpoint
obj.bloch_phase = bloch_phase
# Finally, we must return the newly created object:
return obj
def __array_finalize__(self, obj):
# ``self`` is a new object resulting from
# ndarray.__new__(MPBArray, ...), therefore it only has
# attributes that the ndarray.__new__ constructor gave it -
# i.e. those of a standard ndarray.
# We could have got to the ndarray.__new__ call in 3 ways:
# From an explicit constructor - e.g. MPBArray(lattice):
# obj is None
# (we're in the middle of the MPBArray.__new__
# constructor, and self.lattice will be set when we return to
# MPBArray.__new__)
if obj is None:
return
# From view casting - e.g arr.view(MPBArray):
# obj is arr
# (type(obj) can be MPBArray)
# From new-from-template - e.g mpbarr[:3]
# type(obj) is MPBArray
#
# Note that it is here, rather than in the __new__ method,
# that we set the default value for 'lattice', because this
# method sees all creation of default objects - with the
# MPBArray.__new__ constructor, but also with
# arr.view(MPBArray).
self.lattice = getattr(obj, 'lattice', None)
self.kpoint = getattr(obj, 'kpoint', None)
self.bloch_phase = getattr(obj, 'bloch_phase', False)
class ModeSolver(object):
def __init__(self,
resolution=10,
is_negative_epsilon_ok=False,
eigensolver_flops=0,
eigensolver_flags=68,
use_simple_preconditioner=False,
force_mu=False,
mu_input_file='',
epsilon_input_file='',
mesh_size=3,
target_freq=0.0,
tolerance=1.0e-7,
num_bands=1,
k_points=[],
ensure_periodicity=True,
geometry=[],
geometry_lattice=mp.Lattice(),
geometry_center=mp.Vector3(0, 0, 0),
default_material=mp.Medium(epsilon=1),
dimensions=3,
random_fields=False,
filename_prefix='',
deterministic=False,
verbose=False,
optimize_grid_size=True,
eigensolver_nwork=3,
eigensolver_block_size=-11):
self.mode_solver = None
self.resolution = resolution
self.eigensolver_flags = eigensolver_flags
self.k_points = k_points
self.geometry = geometry
self.geometry_lattice = geometry_lattice
self.geometry_center = mp.Vector3(*geometry_center)
self.default_material = default_material
self.random_fields = random_fields
self.filename_prefix = filename_prefix
self.optimize_grid_size = optimize_grid_size
self.parity = ''
self.iterations = 0
self.all_freqs = None
self.freqs = []
self.band_range_data = []
self.total_run_time = 0
self.current_k = mp.Vector3()
self.k_split_num = 1
self.k_split_index = 0
self.eigensolver_iters = []
grid_size = self._adjust_grid_size()
if type(self.default_material) is not mp.Medium and callable(self.default_material):
init_do_averaging(self.default_material)
self.default_material.eps = False
self.mode_solver = mode_solver(
num_bands,
self.resolution,
self.geometry_lattice,
tolerance,
mesh_size,
self.default_material,
deterministic,
target_freq,
dimensions,
verbose,
ensure_periodicity,
eigensolver_flops,
is_negative_epsilon_ok,
epsilon_input_file,
mu_input_file,
force_mu,
use_simple_preconditioner,
grid_size,
eigensolver_nwork,
eigensolver_block_size,
)
@property
def num_bands(self):
return self.mode_solver.num_bands
@num_bands.setter
def num_bands(self, val):
self.mode_solver.set_num_bands(val)
@property
def resolution(self):
return self._resolution
@resolution.setter
def resolution(self, val):
if isinstance(val, numbers.Number):
self._resolution = [val, val, val]
elif isinstance(val, mp.Vector3):
self._resolution = [val.x, val.y, val.z]
else:
t = type(val)
raise TypeError("resolution must be a number or a Vector3: Got {}".format(t))
if self.mode_solver:
self.mode_solver.resolution = self._resolution
grid_size = self._adjust_grid_size()
self.mode_solver.set_grid_size(grid_size)
@property
def geometry_lattice(self):
return self._geometry_lattice
@geometry_lattice.setter
def geometry_lattice(self, val):
self._geometry_lattice = val
if self.mode_solver:
self.mode_solver.set_libctl_geometry_lattice(val)
grid_size = self._adjust_grid_size()
self.mode_solver.set_grid_size(grid_size)
@property
def tolerance(self):
return self.mode_solver.tolerance
@tolerance.setter
def tolerance(self, val):
self.mode_solver.tolerance = val
@property
def mesh_size(self):
return self.mode_solver.mesh_size
@mesh_size.setter
def mesh_size(self, val):
self.mode_solver.mesh_size = val
@property
def deterministic(self):
return self.mode_solver.deterministic
@deterministic.setter
def deterministic(self, val):
self.mode_solver.deterministic = val
@property
def target_freq(self):
return self.mode_solver.target_freq
@target_freq.setter
def target_freq(self, val):
self.mode_solver.target_freq = val
@property
def dimensions(self):
return self.mode_solver.get_libctl_dimensions()
@dimensions.setter
def dimensions(self, val):
self.mode_solver.set_libctl_dimensions(val)
@property
def verbose(self):
return self.mode_solver.verbose
@verbose.setter
def verbose(self, val):
self.mode_solver.verbose = val
@property
def ensure_periodicity(self):
return self.mode_solver.get_libctl_ensure_periodicity()
@ensure_periodicity.setter
def ensure_periodicity(self, val):
self.mode_solver.set_libctl_ensure_periodicity(val)
@property
def eigensolver_flops(self):
return self.mode_solver.eigensolver_flops
@eigensolver_flops.setter
def eigensolver_flops(self, val):
self.mode_solver.eigensolver_flops = val
@property
def is_negative_epsilon_ok(self):
return self.mode_solver.negative_epsilon_ok
@is_negative_epsilon_ok.setter
def is_negative_epsilon_ok(self, val):
self.mode_solver.negative_epsilon_ok = val
@property
def epsilon_input_file(self):
return self.mode_solver.epsilon_input_file
@epsilon_input_file.setter
def epsilon_input_file(self, val):
self.mode_solver.epsilon_input_file = val
@property
def mu_input_file(self):
return self.mode_solver.mu_input_file
@mu_input_file.setter
def mu_input_file(self, val):
self.mode_solver.mu_input_file = val
@property
def force_mu(self):
return self.mode_solver.force_mu
@force_mu.setter
def force_mu(self, val):
self.mode_solver.force_mu = val
@property
def use_simple_preconditioner(self):
return self.mode_solver.use_simple_preconditioner
@use_simple_preconditioner.setter
def use_simple_preconditioner(self, val):
self.mode_solver.use_simple_preconditioner = val
@property
def eigensolver_nwork(self):
return self.mode_solver.eigensolver_nwork
@eigensolver_nwork.setter
def eigensolver_nwork(self, val):
self.mode_solver.eigensolver_nwork = val
@property
def eigensolver_block_size(self):
return self.mode_solver.eigensolver_block_size
@eigensolver_block_size.setter
def eigensolver_block_size(self, val):
self.mode_solver.eigensolver_block_size = val
def _adjust_grid_size(self):
grid_size = self._get_grid_size()
if self.optimize_grid_size:
grid_size = self._optimize_grid_size(grid_size)
return grid_size
def allow_negative_epsilon(self):
self.is_negative_epsilon_ok = True
self.target_freq = 1 / mp.inf
def get_filename_prefix(self):
if self.filename_prefix:
return self.filename_prefix + '-'
else:
_, filename = os.path.split(sys.argv[0])
if filename == 'ipykernel_launcher.py' or filename == '__main__.py':
return ''
else:
return re.sub(r'\.py$', '', filename) + '-'
def get_freqs(self):
return self.mode_solver.get_freqs()
def multiply_bloch_phase(self, arr):
dims = arr.shape
arr = arr.ravel()
self.mode_solver.multiply_bloch_phase(arr)
return np.reshape(arr, dims)
def get_poynting(self, which_band):
e = self.get_efield(which_band, False)
dims = e.shape
e = e.ravel()
h = self.get_hfield(which_band, False).ravel()
# Reshape into rows of vector3s
e = e.reshape((int(e.shape[0] / 3), 3))
h = h.reshape((int(h.shape[0] / 3), 3))
res = np.zeros(e.shape, dtype=np.complex128)
def ExH(e, h):
ev = mp.Vector3(e[0], e[1], e[2])
hv = mp.Vector3(h[0], h[1], h[2])
return ev.conj().cross(hv)
for i in range(e.shape[0]):
res[i] = np.array(ExH(e[i], h[i]))
flat_res = res.ravel()
self.mode_solver.set_curfield_cmplx(flat_res)
self.mode_solver.set_curfield_type('v')
arr = np.reshape(res, dims)
return MPBArray(arr, self.get_lattice(), self.current_k)
def get_epsilon(self):
self.mode_solver.get_epsilon()
return self.get_curfield_as_array(False)
def get_mu(self):
self.mode_solver.get_mu()
return self.get_curfield_as_array(False)
def get_bfield(self, which_band, bloch_phase=True):
return self._get_field('b', which_band, bloch_phase)
def get_efield(self, which_band, bloch_phase=True):
return self._get_field('e', which_band, bloch_phase)
def get_dfield(self, which_band, bloch_phase=True):
return self._get_field('d', which_band, bloch_phase)
def get_hfield(self, which_band, bloch_phase=True):
return self._get_field('h', which_band, bloch_phase)
def get_charge_density(self, which_band, bloch_phase=True):
self.get_efield(which_band, bloch_phase)
self.mode_solver.compute_field_divergence()
def _get_field(self, f, band, bloch_phase):
if self.mode_solver is None:
raise ValueError("Must call a run function before attempting to get a field")
if f == 'b':
self.mode_solver.get_bfield(band)
elif f == 'd':
self.mode_solver.get_dfield(band)
elif f == 'e':
self.mode_solver.get_efield(band)
elif f == 'h':
self.mode_solver.get_hfield(band)
dims = self.mode_solver.get_dims()
while len(dims) < 3:
dims += [1]
dims += [3]
arr = np.zeros(np.prod(dims), np.complex128)
if bloch_phase:
self.mode_solver.multiply_bloch_phase()
self.mode_solver.get_curfield_cmplx(arr)
arr = np.reshape(arr, dims)
res = MPBArray(arr, self.get_lattice(), self.current_k, bloch_phase=bloch_phase)
return res
def get_curfield_as_array(self, bloch_phase=True):
dims = self.mode_solver.get_dims()
arr = np.zeros(np.prod(dims))
self.mode_solver.get_curfield(arr)
arr = np.reshape(arr, dims)
return MPBArray(arr, self.get_lattice(), self.current_k, bloch_phase=bloch_phase)
def get_dpwr(self, band):
self.get_dfield(band, False)
self.compute_field_energy()
return self.get_curfield_as_array(False)
def get_bpwr(self, band):
self.get_bfield(band, False)
self.compute_field_energy()
return self.get_curfield_as_array(False)
def fix_field_phase(self):
self.mode_solver.fix_field_phase()
def get_epsilon_point(self, p):
return self.mode_solver.get_epsilon_point(p)
def get_epsilon_inverse_tensor_point(self, p):
return self.mode_solver.get_epsilon_inverse_tensor_point(p)
def get_energy_point(self, p):
return self.mode_solver.get_energy_point(p)
def get_field_point(self, p):
return self.mode_solver.get_field_point(p)
def get_bloch_field_point(self, p):
return self.mode_solver.get_bloch_field_point(p)
def get_tot_pwr(self, which_band):
epwr = self.get_dpwr(which_band)
hpwr = self.get_bpwr(which_band)
tot_pwr = epwr + hpwr
self.mode_solver.set_curfield(tot_pwr.ravel())
self.mode_solver.set_curfield_type('R')
return MPBArray(tot_pwr, self.get_lattice(), self.current_k, bloch_phase=False)
def get_eigenvectors(self, first_band, num_bands):
dims = self.mode_solver.get_eigenvectors_slice_dims(num_bands)
ev = np.zeros(np.prod(dims), dtype=np.complex128)
self.mode_solver.get_eigenvectors(first_band - 1, num_bands, ev)
return MPBArray(ev.reshape(dims), self.get_lattice(), self.current_k)
def set_eigenvectors(self, ev, first_band):
self.mode_solver.set_eigenvectors(first_band - 1, ev.flatten())
def save_eigenvectors(self, filename):
with h5py.File(filename, 'w') as f:
ev = self.get_eigenvectors(1, self.num_bands)
f['rawdata'] = ev
def load_eigenvectors(self, filename):
with h5py.File(filename, 'r') as f:
ev = f['rawdata'][()]
self.set_eigenvectors(ev, 1)
self.mode_solver.curfield_reset()
# The band-range-data is a list of tuples, each consisting of a (min, k-point)
# tuple and a (max, k-point) tuple, with each min/max pair describing the
# frequency range of a band and the k-points where it achieves its minimum/maximum.
# Here, we update this data with a new list of band frequencies, and return the new
# data. If band-range-data is null or too short, the needed entries will be created.
def update_band_range_data(self, brd, freqs, kpoint):
def update_brd(brd, freqs, br_start):
if not freqs:
return br_start + brd
else:
br = ((mp.inf, -1), (-mp.inf, -1)) if not brd else brd[0]
br_rest = [] if not brd else brd[1:]
newmin = (freqs[0], kpoint) if freqs[0] < br[0][0] else br[0]
newmax = (freqs[0], kpoint) if freqs[0] > br[1][0] else br[1]
new_start = br_start + [(newmin, newmax)]
return update_brd(br_rest, freqs[1:], new_start)
return update_brd(brd, freqs, [])
def output_band_range_data(self, br_data):
if verbosity.mpb >= 1:
for tup, band in zip(br_data, range(1, len(br_data) + 1)):
fmt = "Band {} range: {} at {} to {} at {}"
min_band, max_band = tup
min_freq, min_kpoint = min_band
max_freq, max_kpoint = max_band
print(fmt.format(band, min_freq, min_kpoint, max_freq, max_kpoint))
# Output any gaps in the given band ranges, and return a list of the gaps as
# a list of (percent, freq-min, freq-max) tuples.
def output_gaps(self, br_data):
def ogaps(br_cur, br_rest, i, gaps):
if not br_rest:
ordered_gaps = []
gaps = list(reversed(gaps))
for i in range(0, len(gaps), 3):
ordered_gaps.append((gaps[i + 2], gaps[i + 1], gaps[i]))
return ordered_gaps
else:
br_rest_min_f = br_rest[0][0][0]
br_cur_max_f = br_cur[1][0]
if br_cur_max_f >= br_rest_min_f:
return ogaps(br_rest[0], br_rest[1:], i + 1, gaps)
else:
gap_size = ((200 * (br_rest_min_f - br_cur_max_f)) /
(br_rest_min_f + br_cur_max_f))
if verbosity.mpb >= 1:
fmt = "Gap from band {} ({}) to band {} ({}), {}%"
print(fmt.format(i, br_cur_max_f, i + 1, br_rest_min_f, gap_size))
return ogaps(br_rest[0], br_rest[1:], i + 1,
[gap_size, br_cur_max_f, br_rest_min_f] + gaps)
if not br_data:
return []
else:
return ogaps(br_data[0], br_data[1:], 1, [])
# Return the frequency gap from the band #lower-band to the band
# #(lower-band+1), as a percentage of mid-gap frequency. The "gap"
# may be negative if the maximum of the lower band is higher than the
# minimum of the upper band. (The gap is computed from the
# band-range-data of the previous run.)
def retrieve_gap(self, lower_band):
if lower_band + 1 > len(self.band_range_data):
raise ValueError("retrieve-gap called for higher band than was calculated")
f1 = self.band_range_data[lower_band - 1][1][0]
f2 = self.band_range_data[lower_band][0][0]
return (f2 - f1) / (0.005 * (f1 + f2))
# Split a list L into num more-or-less equal pieces, returning the piece
# given by index (in 0..num-1), along with the index in L of the first
# element of the piece, as a list: [first-index, piece-of-L]
def list_split(self, l, num, index):
def list_sub(l, start, length, index, rest):
if not l:
return list(reversed(rest))
if index >= start and index < (start + length):
return list_sub(l[1:], start, length, index + 1, [l[0]] + rest)
else:
return list_sub(l[1:], start, length, index + 1, rest)
if index >= num or index < 0:
return (len(l), [])
else:
block_size = (len(l) + num - 1) // num
start = index * block_size
length = min(block_size, (len(l) - index * block_size))
return (start, list_sub(l, start, length, 0, []))
def get_lattice(self):
if self.mode_solver is None:
raise RuntimeError("Must call ModeSolver.run before getting the lattice.")
lattice = np.zeros((3, 3))
self.mode_solver.get_lattice(lattice)
return lattice
def output_field(self):
self.output_field_to_file(mp.ALL, self.get_filename_prefix())
def output_field_x(self):
self.output_field_to_file(0, self.get_filename_prefix())
def output_field_y(self):
self.output_field_to_file(1, self.get_filename_prefix())
def output_field_z(self):
self.output_field_to_file(2, self.get_filename_prefix())
def output_epsilon(self):
self.mode_solver.get_epsilon()
self.output_field_to_file(mp.ALL, self.get_filename_prefix())
def output_mu(self):
self.mode_solver.get_mu()
self.output_field_to_file(mp.ALL, self.get_filename_prefix())
def output_field_to_file(self, component, fname_prefix):
curfield_type = self.mode_solver.get_curfield_type()
output_k = self.mode_solver.get_output_k()
if curfield_type in 'Rv':
# Generic scalar/vector field. Don't know k
output_k = [0, 0, 0]
if curfield_type in 'dhbecv':
self._output_vector_field(curfield_type, fname_prefix, output_k, component)
elif curfield_type == 'C':
self._output_complex_scalar_field(fname_prefix, output_k)
elif curfield_type in 'DHBnmR':
self._output_scalar_field(curfield_type, fname_prefix)
else:
raise ValueError("Unkown field type: {}".format(curfield_type))
self.mode_solver.curfield_reset()
def _output_complex_scalar_field(self, fname_prefix, output_k):
curfield_type = 'C'
kpoint_index = self.mode_solver.get_kpoint_index()
curfield_band = self.mode_solver.curfield_band
fname = "{}.k{:02d}.b{:02d}".format(curfield_type, kpoint_index, curfield_band)
description = "{} field, kpoint {}, band {}, freq={:.6g}".format(
curfield_type,
kpoint_index,
curfield_band,
self.freqs[curfield_band - 1]
)
fname = self._create_fname(fname, fname_prefix, True)
if verbosity.mpb >= 1:
print("Outputting complex scalar field to {}...".format(fname))
with h5py.File(fname, 'w') as f:
f['description'] = description.encode()
f['Bloch wavevector'] = np.array(output_k)
self._write_lattice_vectors(f)
dims = self.mode_solver.get_dims()
field = np.empty(np.prod(dims), np.complex128)
self.mode_solver.get_curfield_cmplx(field)
reshaped_field = field.reshape(dims)
f['c.r'] = np.real(reshaped_field)
f['c.i'] = np.imag(reshaped_field)
def _output_vector_field(self, curfield_type, fname_prefix, output_k, component):
components = ['x', 'y', 'z']
kpoint_index = self.mode_solver.get_kpoint_index()
curfield_band = self.mode_solver.curfield_band
fname = "{}.k{:02d}.b{:02d}".format(curfield_type, kpoint_index, curfield_band)
if component >= 0:
fname += ".{}".format(components[component])
description = "{} field, kpoint {}, band {}, freq={:.6g}".format(
curfield_type,
kpoint_index,
curfield_band,
self.freqs[curfield_band - 1]
)
fname = self._create_fname(fname, fname_prefix, True)
if verbosity.mpb >= 1:
print("Outputting fields to {}...".format(fname))
with h5py.File(fname, 'w') as f:
f['description'] = description.encode()
f['Bloch wavevector'] = np.array(output_k)
self._write_lattice_vectors(f)
if curfield_type != 'v':
self.mode_solver.multiply_bloch_phase()
for c_idx, c in enumerate(components):
if component >= 0 and c_idx != component:
continue
dims = self.mode_solver.get_dims()
field = np.empty(np.prod(dims) * 3, np.complex128)
self.mode_solver.get_curfield_cmplx(field)
component_field = field[c_idx::3].reshape(dims)
name = "{}.r".format(c)
f[name] = np.real(component_field)
name = "{}.i".format(c)
f[name] = np.imag(component_field)
def _output_scalar_field(self, curfield_type, fname_prefix):
components = ['x', 'y', 'z']
if curfield_type == 'n':
fname = 'epsilon'
description = 'dielectric function, epsilon'
elif curfield_type == 'm':
fname = 'mu'
description = 'permeability mu'
else:
kpoint_index = self.mode_solver.get_kpoint_index()
curfield_band = self.mode_solver.curfield_band
fname = "{}pwr.k{:02d}.b{:02d}".format(curfield_type.lower(),
kpoint_index, curfield_band)
descr_fmt = "{} field energy density, kpoint {}, band {}, freq={:.6g}"
description = descr_fmt.format(curfield_type, kpoint_index, curfield_band,
self.freqs[curfield_band - 1])
parity_suffix = False if curfield_type in 'mn' else True
fname = self._create_fname(fname, fname_prefix, parity_suffix)
if verbosity.mpb >= 1:
print("Outputting {}...".format(fname))
with h5py.File(fname, 'w') as f:
f['description'] = description.encode()
self._create_h5_dataset(f, 'data')
self._write_lattice_vectors(f)
if curfield_type == 'n':
for inv in [False, True]:
inv_str = 'epsilon_inverse' if inv else 'epsilon'
for c1 in range(3):
for c2 in range(c1, 3):
self.mode_solver.get_epsilon_tensor(c1, c2, 0, inv)
dataname = "{}.{}{}".format(inv_str, components[c1],
components[c2])
self._create_h5_dataset(f, dataname)
if with_hermitian_epsilon() and c1 != c2:
self.mode_solver.get_epsilon_tensor(c1, c2, 1, inv)
dataname += '.i'
self._create_h5_dataset(f, dataname)
def _write_lattice_vectors(self, h5file):
lattice = np.zeros((3, 3))
self.mode_solver.get_lattice(lattice)
h5file['lattice vectors'] = lattice
def _create_h5_dataset(self, h5file, key):
h5file[key] = self.get_curfield_as_array(False)
def _create_fname(self, fname, prefix, parity_suffix):
parity_str = self.mode_solver.get_parity_string()
if parity_suffix and parity_str:
suffix = ".{}".format(parity_str)
else:
suffix = ''
return prefix + fname + suffix + '.h5'
def compute_field_energy(self):
return self.mode_solver.compute_field_energy()
def compute_field_divergence(self):
return self.mode_solver.compute_field_divergence()
def compute_energy_in_objects(self, objs):
return self.mode_solver.compute_energy_in_objects(objs)
def compute_energy_in_dielectric(self, eps_low, eps_high):
return self.mode_solver.compute_energy_in_dielectric(eps_low, eps_high)
def compute_energy_integral(self, f):
return self.mode_solver.compute_energy_integral(f)
def compute_field_integral(self, f):
return self.mode_solver.compute_field_integral(f)
def compute_group_velocities(self):
xarg = mp.cartesian_to_reciprocal(mp.Vector3(1), self.geometry_lattice)
vx = self.mode_solver.compute_group_velocity_component(xarg)
yarg = mp.cartesian_to_reciprocal(mp.Vector3(y=1), self.geometry_lattice)
vy = self.mode_solver.compute_group_velocity_component(yarg)
zarg = mp.cartesian_to_reciprocal(mp.Vector3(z=1), self.geometry_lattice)
vz = self.mode_solver.compute_group_velocity_component(zarg)
return [mp.Vector3(x, y, z) for x, y, z in zip(vx, vy, vz)]
def compute_group_velocity_component(self, direction):
return self.mode_solver.compute_group_velocity_component(direction)
def compute_one_group_velocity(self, which_band):
return self.mode_solver.compute_1_group_velocity(which_band)
def compute_one_group_velocity_component(self, direction, which_band):
return self.mode_solver.compute_1_group_velocity_component(direction,
which_band)
def compute_zparities(self):
return self.mode_solver.compute_zparities()
def compute_yparities(self):
return self.mode_solver.compute_yparities()
def randomize_fields(self):
self.mode_solver.randomize_fields()
def display_kpoint_data(self, name, data):
k_index = self.mode_solver.get_kpoint_index()
if verbosity.mpb >= 1:
print("{}{}:, {}".format(self.parity, name, k_index), end='')
for d in data:
print(", {}".format(d), end='')
print()
def display_eigensolver_stats(self):
num_runs = len(self.eigensolver_iters)
if num_runs <= 0:
return
min_iters = min(self.eigensolver_iters)
max_iters = max(self.eigensolver_iters)
mean_iters = np.mean(self.eigensolver_iters)
if verbosity.mpb >= 1:
fmt = "eigensolver iterations for {} kpoints: {}-{}, mean = {}"
print(fmt.format(num_runs, min_iters, max_iters, mean_iters), end='')
sorted_iters = sorted(self.eigensolver_iters)
idx1 = num_runs // 2
idx2 = ((num_runs + 1) // 2) - 1
median_iters = 0.5 * (sorted_iters[idx1] + sorted_iters[idx2])
if verbosity.mpb >= 1:
print(", median = {}".format(median_iters))
mean_flops = self.eigensolver_flops / (num_runs * mean_iters)
if verbosity.mpb >= 1:
print("mean flops per iteration = {}".format(mean_flops))
mean_time = self.total_run_time / (mean_iters * num_runs)
if verbosity.mpb >= 1:
print("mean time per iteration = {} s".format(mean_time))
def _get_grid_size(self):
grid_size = mp.Vector3(self.resolution[0] * self.geometry_lattice.size.x,
self.resolution[1] * self.geometry_lattice.size.y,
self.resolution[2] * self.geometry_lattice.size.z)
grid_size.x = max(math.ceil(grid_size.x), 1)
grid_size.y = max(math.ceil(grid_size.y), 1)
grid_size.z = max(math.ceil(grid_size.z), 1)
return grid_size
def _optimize_grid_size(self, grid_size):
grid_size.x = self.next_factor2357(grid_size.x)
grid_size.y = self.next_factor2357(grid_size.y)
grid_size.z = self.next_factor2357(grid_size.z)
return grid_size
def next_factor2357(self, n):
def is_factor2357(n):
def divby(n, p):
if n % p == 0:
return divby(n // p, p)
return n
return divby(divby(divby(divby(n, 2), 3), 5), 7) == 1
if is_factor2357(n):
return n
return self.next_factor2357(n + 1)
def init_params(self, p, reset_fields):
self.mode_solver.init(p, reset_fields, self.geometry, self.default_material)
def set_parity(self, p):
self.mode_solver.set_parity(p)
def solve_kpoint(self, k):
self.mode_solver.solve_kpoint(k)
def run_parity(self, p, reset_fields, *band_functions):
if self.random_fields and self.randomize_fields not in band_functions:
band_functions.append(self.randomize_fields)
start = time.time()
self.all_freqs = np.zeros((len(self.k_points), self.num_bands))
self.band_range_data = []
init_time = time.time()
if verbosity.mpb >= 1:
print("Initializing eigensolver data")
print("Computing {} bands with {} tolerance".format(self.num_bands, self.tolerance))
self.init_params(p, reset_fields)
if isinstance(reset_fields, basestring):
self.load_eigenvectors(reset_fields)
if verbosity.mpb >= 1:
print("{} k-points".format(len(self.k_points)))
for kp in self.k_points:
print(" {}".format(kp))
print("elapsed time for initialization: {}".format(time.time() - init_time))
# TODO: Split over multiple processes
# k_split = list_split(self.k_points, self.k_split_num, self.k_split_index)
k_split = (0, self.k_points)
self.mode_solver.set_kpoint_index(k_split[0])
if self.num_bands > 0:
for i, k in enumerate(k_split[1]):
self.current_k = k
solve_kpoint_time = time.time()
self.mode_solver.solve_kpoint(k)
self.iterations = self.mode_solver.get_iterations()
if verbosity.mpb >= 1:
print("elapsed time for k point: {}".format(time.time() - solve_kpoint_time))
self.freqs = self.get_freqs()
self.all_freqs[i, :] = np.array(self.freqs)
self.band_range_data = self.update_band_range_data(self.band_range_data,
self.freqs, k)
self.eigensolver_iters += [self.iterations / self.num_bands]
for f in band_functions:
num_args = get_num_args(f)
if num_args == 1:
f(self)
elif num_args == 2:
band = 1
while band <= self.num_bands:
f(self, band)
band += 1
else:
raise ValueError("Band function should take 1 or 2 arguments. "
"The first must be a ModeSolver instance")
if len(k_split[1]) > 1:
self.output_band_range_data(self.band_range_data)
self.gap_list = self.output_gaps(self.band_range_data)
else:
self.gap_list = []
end = time.time() - start
if verbosity.mpb >= 1:
print("total elapsed time for run: {}".format(end))
self.total_run_time += end
self.eigensolver_flops = self.mode_solver.get_eigensolver_flops()
self.parity = self.mode_solver.get_parity_string()
if verbosity.mpb >= 1:
print("done")
def run(self, *band_functions):
self.run_parity(mp.NO_PARITY, True, *band_functions)
def run_zeven(self, *band_functions):
self.run_parity(mp.EVEN_Z, True, *band_functions)
def run_zodd(self, *band_functions):
self.run_parity(mp.ODD_Z, True, *band_functions)
def run_yeven(self, *band_functions):
self.run_parity(mp.EVEN_Y, True, *band_functions)
def run_yodd(self, *band_functions):
self.run_parity(mp.ODD_Y, True, *band_functions)
def run_yeven_zeven(self, *band_functions):
self.run_parity(mp.EVEN_Y + mp.EVEN_Z, True, *band_functions)
def run_yeven_zodd(self, *band_functions):
self.run_parity(mp.EVEN_Y + mp.ODD_Z, True, *band_functions)
def run_yodd_zeven(self, *band_functions):
self.run_parity(mp.ODD_Y + mp.EVEN_Z, True, *band_functions)
def run_yodd_zodd(self, *band_functions):
self.run_parity(mp.ODD_Y + mp.ODD_Z, True, *band_functions)
run_te = run_zeven
run_tm = run_zodd
run_te_yeven = run_yeven_zeven
run_te_yodd = run_yodd_zeven
run_tm_yeven = run_yeven_zodd
run_tm_yodd = run_yodd_zodd
def find_k(self, p, omega, band_min, band_max, korig_and_kdir, tol,
kmag_guess, kmag_min, kmag_max, *band_funcs):
num_bands_save = self.num_bands