371 lines
17 KiB
Python
371 lines
17 KiB
Python
|
#!/usr/bin/env python3
|
|||
|
|
|
|||
|
|
import argparse, re, random, string
|
|||
|
|
import subprocess
|
|||
|
|
from scipy.constants import hbar, e as eV, pi, c
|
|||
|
|
|
|||
|
|
unitcell_size = 1 # rectangular lattice
|
|||
|
|
unitcell_indices = tuple(range(unitcell_size))
|
|||
|
|
|
|||
|
|
def make_action_sharedlist(opname, listname):
|
|||
|
|
class opAction(argparse.Action):
|
|||
|
|
def __call__(self, parser, args, values, option_string=None):
|
|||
|
|
if (not hasattr(args, listname)) or getattr(args, listname) is None:
|
|||
|
|
setattr(args, listname, list())
|
|||
|
|
getattr(args,listname).append((opname, values))
|
|||
|
|
return opAction
|
|||
|
|
|
|||
|
|
parser = argparse.ArgumentParser()
|
|||
|
|
#TODO? použít type=argparse.FileType('r') ?
|
|||
|
|
parser.add_argument('--TMatrix', action='store', required=True, help='Path to TMatrix file')
|
|||
|
|
#parser.add_argument('--griddir', action='store', required=True, help='Path to the directory with precalculated translation operators')
|
|||
|
|
parser.add_argument('--output_prefix', '-p', '-o', action='store', required=True, help='Prefix to the npz output (will be appended frequency, hexside and chunkno)')
|
|||
|
|
parser.add_argument('--nosuffix', action='store_true', help='Do not add dimension metadata to the output filenames')
|
|||
|
|
#sizepar = parser.add_mutually_exclusive_group(required=True)
|
|||
|
|
#parser.add_argument('--hexside', action='store', type=float, required=True, help='Lattice hexagon size length')
|
|||
|
|
parser.add_argument('--dx', action='store', type=float, required=True, help='x-direction lattice constant')
|
|||
|
|
parser.add_argument('--dy', action='store', type=float, required=True, help='y-direction lattice constant')
|
|||
|
|
|
|||
|
|
parser.add_argument('--Nx', '--nx', action='store', type=int, required=True, help='Lattice points in the x-direction')
|
|||
|
|
parser.add_argument('--Ny', '--ny', action='store', type=int, required=True, help='Lattice points in the y-direction')
|
|||
|
|
|
|||
|
|
# In these default settings, the area is 2x2 times larger than first BZ
|
|||
|
|
parser.add_argument('--kxmin', action='store', type=float, default=-1., help='TODO')
|
|||
|
|
parser.add_argument('--kxmax', action='store', type=float, default=1., help='TODO')
|
|||
|
|
parser.add_argument('--kymin', action='store', type=float, default=-1., help='TODO')
|
|||
|
|
parser.add_argument('--kymax', action='store', type=float, default=1., help='TODO')
|
|||
|
|
|
|||
|
|
#parser.add_argument('--kdensity', action='store', type=int, default=33, help='Number of k-points per x-axis segment')
|
|||
|
|
parser.add_argument('--kxdensity', action='store', type=int, default=51, help='k-space resolution in the x-direction')
|
|||
|
|
parser.add_argument('--kydensity', action='store', type=int, default=51, help='k-space resolution in the y-direction')
|
|||
|
|
|
|||
|
|
partgrp = parser.add_mutually_exclusive_group()
|
|||
|
|
partgrp.add_argument('--only_TE', action='store_true', help='Calculate only the projection on the E⟂z modes')
|
|||
|
|
partgrp.add_argument('--only_TM', action='store_true', help='Calculate only the projection on the E∥z modes')
|
|||
|
|
partgrp.add_argument('--serial', action='store_true', help='Calculate the TE and TM parts separately to save memory')
|
|||
|
|
|
|||
|
|
parser.add_argument('--nocentre', action='store_true', help='Place the coordinate origin to the left bottom corner rather that to the centre of the array')
|
|||
|
|
|
|||
|
|
parser.add_argument('--plot_TMatrix', action='store_true', help='Visualise TMatrix on the first page of the output')
|
|||
|
|
#parser.add_argument('--SVD_output', action='store', help='Path to output singular value decomposition result')
|
|||
|
|
parser.add_argument('--maxlayer', action='store', type=int, default=100, help='How far to sum the lattice points to obtain the dispersion')
|
|||
|
|
parser.add_argument('--scp_to', action='store', metavar='N', type=str, help='SCP the output files to a given destination')
|
|||
|
|
parser.add_argument('--background_permittivity', action='store', type=float, default=1., help='Background medium relative permittivity (default 1)')
|
|||
|
|
parser.add_argument('--eVfreq', action='store', required=True, type=float, help='Frequency in eV')
|
|||
|
|
|
|||
|
|
parser.add_argument('--chunklen', action='store', type=int, default=3000, help='Number of k-points per output file (default 3000)')
|
|||
|
|
parser.add_argument('--lMax', action='store', type=int, help='Override lMax from the TMatrix file')
|
|||
|
|
#TODO some more sophisticated x axis definitions
|
|||
|
|
#parser.add_argument('--gaussian', action='store', type=float, metavar='σ', help='Use a gaussian envelope for weighting the interaction matrix contributions (depending on the distance), measured in unit cell lengths (?) FIxME).')
|
|||
|
|
parser.add_argument('--verbose', '-v', action='count', help='Be verbose (about computation times, mostly)')
|
|||
|
|
popgrp=parser.add_argument_group(title='Operations')
|
|||
|
|
popgrp.add_argument('--tr', dest='ops', action=make_action_sharedlist('tr', 'ops'), default=list()) # the default value for dest can be set once
|
|||
|
|
for i in unitcell_indices:
|
|||
|
|
popgrp.add_argument('--tr%d'%i, dest='ops', action=make_action_sharedlist('tr%d'%i, 'ops'))
|
|||
|
|
popgrp.add_argument('--sym', dest='ops', action=make_action_sharedlist('sym', 'ops'))
|
|||
|
|
for i in unitcell_indices:
|
|||
|
|
popgrp.add_argument('--sym%d'%i, dest='ops', action=make_action_sharedlist('sym%d'%i, 'ops'))
|
|||
|
|
#popgrp.add_argument('--mult', dest='ops', nargs=3, metavar=('INCSPEC', 'SCATSPEC', 'MULTIPLIER'), action=make_action_sharedlist('mult', 'ops'))
|
|||
|
|
#popgrp.add_argument('--mult0', dest='ops', nargs=3, metavar=('INCSPEC', 'SCATSPEC', 'MULTIPLIER'), action=make_action_sharedlist('mult0', 'ops'))
|
|||
|
|
#popgrp.add_argument('--mult1', dest='ops', nargs=3, metavar=('INCSPEC', 'SCATSPEC', 'MULTIPLIER'), action=make_action_sharedlist('mult1', 'ops'))
|
|||
|
|
popgrp.add_argument('--multl', dest='ops', nargs=3, metavar=('INCL[,INCL,...]', 'SCATL[,SCATL,...]', 'MULTIPLIER'), action=make_action_sharedlist('multl', 'ops'))
|
|||
|
|
for i in unitcell_indices:
|
|||
|
|
popgrp.add_argument('--multl%d'%i, dest='ops', nargs=3, metavar=('INCL[,INCL,...]', 'SCATL[,SCATL,...]', 'MULTIPLIER'), action=make_action_sharedlist('multl%d'%i, 'ops'))
|
|||
|
|
#popgrp.add_argument('--multl1', dest='ops', nargs=3, metavar=('INCL[,INCL,...]', 'SCATL[,SCATL,...]', 'MULTIPLIER'), action=make_action_sharedlist('multl1', 'ops'))
|
|||
|
|
parser.add_argument('--frequency_multiplier', action='store', type=float, default=1., help='Multiplies the frequencies in the TMatrix file by a given factor.')
|
|||
|
|
# TODO enable more flexible per-sublattice specification
|
|||
|
|
pargs=parser.parse_args()
|
|||
|
|
print(pargs)
|
|||
|
|
|
|||
|
|
maxlayer=pargs.maxlayer
|
|||
|
|
eVfreq = pargs.eVfreq
|
|||
|
|
freq = eVfreq*eV/hbar
|
|||
|
|
verbose=pargs.verbose
|
|||
|
|
dy = pargs.dy
|
|||
|
|
dx = pargs.dx
|
|||
|
|
Ny = pargs.Ny
|
|||
|
|
Nx = pargs.Nx
|
|||
|
|
|
|||
|
|
TMatrix_file = pargs.TMatrix
|
|||
|
|
|
|||
|
|
epsilon_b = pargs.background_permittivity #2.3104
|
|||
|
|
#gaussianSigma = pargs.gaussian if pargs.gaussian else None # hexside * 222 / 7
|
|||
|
|
interpfreqfactor = pargs.frequency_multiplier
|
|||
|
|
scp_dest = pargs.scp_to if pargs.scp_to else None
|
|||
|
|
kxdensity = pargs.kxdensity
|
|||
|
|
kydensity = pargs.kydensity
|
|||
|
|
chunklen = pargs.chunklen
|
|||
|
|
|
|||
|
|
ops = list()
|
|||
|
|
opre = re.compile('(tr|sym|copy|multl|mult)(\d*)')
|
|||
|
|
for oparg in pargs.ops:
|
|||
|
|
opm = opre.match(oparg[0])
|
|||
|
|
if opm:
|
|||
|
|
ops.append(((opm.group(2),) if opm.group(2) else unitcell_indices, opm.group(1), oparg[1]))
|
|||
|
|
else:
|
|||
|
|
raise # should not happen
|
|||
|
|
print(ops)
|
|||
|
|
|
|||
|
|
|
|||
|
|
# -----------------finished basic CLI parsing (except for op arguments) ------------------
|
|||
|
|
from qpms.timetrack import _time_b, _time_e
|
|||
|
|
btime=_time_b(verbose)
|
|||
|
|
|
|||
|
|
import qpms
|
|||
|
|
import numpy as np
|
|||
|
|
import os, sys, warnings, math
|
|||
|
|
from scipy import interpolate
|
|||
|
|
nx = None
|
|||
|
|
s3 = math.sqrt(3)
|
|||
|
|
|
|||
|
|
|
|||
|
|
# specifikace T-matice zde
|
|||
|
|
refind = math.sqrt(epsilon_b)
|
|||
|
|
cdn = c / refind
|
|||
|
|
k_0 = freq * refind / c # = freq / cdn
|
|||
|
|
TMatrices_orig, freqs_orig, freqs_weirdunits_orig, lMaxTM = qpms.loadScuffTMatrices(TMatrix_file)
|
|||
|
|
lMax = lMaxTM
|
|||
|
|
if pargs.lMax:
|
|||
|
|
lMax = pargs.lMax if pargs.lMax else lMaxTM
|
|||
|
|
my, ny = qpms.get_mn_y(lMax)
|
|||
|
|
nelem = len(my)
|
|||
|
|
if pargs.lMax: #force commandline specified lMax
|
|||
|
|
TMatrices_orig = TMatrices_orig[...,0:nelem,:,0:nelem]
|
|||
|
|
|
|||
|
|
TMatrices = np.array(np.broadcast_to(TMatrices_orig[:,nx,:,:,:,:],(len(freqs_orig),2,2,nelem,2,nelem)) )
|
|||
|
|
|
|||
|
|
xfl = qpms.xflip_tyty(lMax)
|
|||
|
|
yfl = qpms.yflip_tyty(lMax)
|
|||
|
|
zfl = qpms.zflip_tyty(lMax)
|
|||
|
|
c2rot = qpms.apply_matrix_left(qpms.yflip_yy(3),qpms.xflip_yy(3),-1)
|
|||
|
|
|
|||
|
|
reCN = re.compile('(\d*)C(\d+)')
|
|||
|
|
#TODO C nekonečno
|
|||
|
|
|
|||
|
|
for op in ops:
|
|||
|
|
if op[0] == 'all':
|
|||
|
|
#targets = (0,1)
|
|||
|
|
targets = unitcell_indices
|
|||
|
|
elif isinstance(op[0],int):
|
|||
|
|
targets = (op[0],)
|
|||
|
|
else:
|
|||
|
|
targets = op[0]
|
|||
|
|
|
|||
|
|
if op[1] == 'sym':
|
|||
|
|
mCN = reCN.match(op[2]) # Fuck van Rossum for not having assignments inside expressions
|
|||
|
|
if op[2] == 'σ_z':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = (TMatrices[:,t] + qpms.apply_ndmatrix_left(zfl,qpms.apply_ndmatrix_left(zfl, TMatrices[:,t], (-4,-3)),(-2,-1)))/2
|
|||
|
|
elif op[2] == 'σ_y':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = (TMatrices[:,t] + qpms.apply_ndmatrix_left(yfl,qpms.apply_ndmatrix_left(yfl, TMatrices[:,t], (-4,-3)),(-2,-1)))/2
|
|||
|
|
elif op[2] == 'σ_x':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = (TMatrices[:,t] + qpms.apply_ndmatrix_left(xfl,qpms.apply_ndmatrix_left(xfl, TMatrices[:,t], (-4,-3)),(-2,-1)))/2
|
|||
|
|
elif op[2] == 'C2': # special case of the latter
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = (TMatrices[:,t] + qpms.apply_matrix_left(c2rot,qpms.apply_matrix_left(c2rot, TMatrices[:,t], -3),-1))/2
|
|||
|
|
elif mCN:
|
|||
|
|
rotN = int(mCN.group(2))
|
|||
|
|
TMatrix_contribs = np.empty((rotN,TMatrices.shape[0],2,nelem,2,nelem), dtype=np.complex_)
|
|||
|
|
for t in targets:
|
|||
|
|
for i in range(rotN):
|
|||
|
|
rotangle = 2*np.pi*i / rotN
|
|||
|
|
rot = qpms.WignerD_yy_fromvector(lMax,np.array([0,0,rotangle]))
|
|||
|
|
rotinv = qpms.WignerD_yy_fromvector(lMax,np.array([0,0,-rotangle]))
|
|||
|
|
TMatrix_contribs[i] = qpms.apply_matrix_left(rot,qpms.apply_matrix_left(rotinv, TMatrices[:,t], -3),-1)
|
|||
|
|
TMatrices[:,t] = np.sum(TMatrix_contribs, axis=0) / rotN
|
|||
|
|
else:
|
|||
|
|
raise
|
|||
|
|
elif op[1] == 'tr':
|
|||
|
|
mCN = reCN.match(op[2]) # Fuck van Rossum for not having assignments inside expressions
|
|||
|
|
if op[2] == 'σ_z':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = qpms.apply_ndmatrix_left(zfl,qpms.apply_ndmatrix_left(zfl, TMatrices[:,t], (-4,-3)),(-2,-1))
|
|||
|
|
elif op[2] == 'σ_y':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = qpms.apply_ndmatrix_left(yfl,qpms.apply_ndmatrix_left(yfl, TMatrices[:,t], (-4,-3)),(-2,-1))
|
|||
|
|
elif op[2] == 'σ_x':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = qpms.apply_ndmatrix_left(xfl,qpms.apply_ndmatrix_left(xfl, TMatrices[:,t], (-4,-3)),(-2,-1))
|
|||
|
|
elif op[2] == 'C2':
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[:,t] = qpms.apply_matrix_left(c2rot,qpms.apply_matrix_left(c2rot, TMatrices[:,t], -3),-1)
|
|||
|
|
elif mCN:
|
|||
|
|
rotN = int(mCN.group(2))
|
|||
|
|
power = int(mCN.group(1)) if mCN.group(1) else 1
|
|||
|
|
TMatrix_contribs = np.empty((rotN,TMatrices.shape[0],2,nelem,2,nelem), dtype=np.complex_)
|
|||
|
|
for t in targets:
|
|||
|
|
rotangle = 2*np.pi*power/rotN
|
|||
|
|
rot = qpms.WignerD_yy_fromvector(lMax, np.array([0,0,rotangle]))
|
|||
|
|
rotinv = qpms.WignerD_yy_fromvector(lMax, np.array([0,0,-rotangle]))
|
|||
|
|
TMatrices[:,t] = qpms.apply_matrix_left(rot, qpms.apply_matrix_left(rotinv, TMatrices[:,t], -3),-1)
|
|||
|
|
else:
|
|||
|
|
raise
|
|||
|
|
elif op[1] == 'copy':
|
|||
|
|
raise # not implemented
|
|||
|
|
elif op[1] == 'mult':
|
|||
|
|
raise # not implemented
|
|||
|
|
elif op[1] == 'multl':
|
|||
|
|
incy = np.full((nelem,), False, dtype=bool)
|
|||
|
|
for incl in op[2][0].split(','):
|
|||
|
|
l = int(incl)
|
|||
|
|
incy += (l == ny)
|
|||
|
|
scaty = np.full((nelem,), False, dtype=bool)
|
|||
|
|
for scatl in op[2][1].split(','):
|
|||
|
|
l = int(scatl)
|
|||
|
|
scaty += (l == ny)
|
|||
|
|
for t in targets:
|
|||
|
|
TMatrices[np.ix_(np.arange(TMatrices.shape[0]),np.array([t]),np.array([0,1]),scaty,np.array([0,1]),incy)] *= float(op[2][2])
|
|||
|
|
else:
|
|||
|
|
raise #unknown operation; should not happen
|
|||
|
|
|
|||
|
|
TMatrices_interp = interpolate.interp1d(freqs_orig*interpfreqfactor, TMatrices, axis=0, kind='linear',fill_value="extrapolate")
|
|||
|
|
|
|||
|
|
|
|||
|
|
xpositions = np.arange(Nx) * dx
|
|||
|
|
ypositions = np.arange(Ny) * dy
|
|||
|
|
if not pargs.nocentre:
|
|||
|
|
xpositions -= Nx * dx / 2
|
|||
|
|
ypositions -= Ny * dy / 2
|
|||
|
|
xpositions, ypositions = np.meshgrid(xpositions, ypositions, indexing='ij', copy=False)
|
|||
|
|
positions=np.stack((xpositions.ravel(),ypositions.ravel()), axis=-1)
|
|||
|
|
N = positions.shape[0]
|
|||
|
|
|
|||
|
|
kx = np.linspace(pargs.kxmin, pargs.kxmax, num=pargs.kxdensity, endpoint=True) * 2*np.pi / dx
|
|||
|
|
ky = np.linspace(pargs.kymin, pargs.kymax, num=pargs.kydensity, endpoint=True) * 2*np.pi / dy
|
|||
|
|
kx, ky = np.meshgrid(kx, ky, indexing='ij', copy=False)
|
|||
|
|
kz = np.sqrt(k_0 - (kx ** 2 + ky ** 2))
|
|||
|
|
|
|||
|
|
klist_full = np.stack((kx,ky,kz), axis=-1).reshape((-1,3))
|
|||
|
|
TMatrices_om = TMatrices_interp(freq)
|
|||
|
|
|
|||
|
|
chunkn = math.ceil(klist_full.size / 3 / chunklen)
|
|||
|
|
|
|||
|
|
if verbose:
|
|||
|
|
print('Evaluating %d k-points in %d chunks' % (klist_full.size / 3, chunkn), file = sys.stderr)
|
|||
|
|
sys.stderr.flush()
|
|||
|
|
|
|||
|
|
try:
|
|||
|
|
version = qpms.__version__
|
|||
|
|
except NameError:
|
|||
|
|
version = None
|
|||
|
|
|
|||
|
|
metadata = np.array({
|
|||
|
|
'script': os.path.basename(__file__),
|
|||
|
|
'version': version,
|
|||
|
|
'type' : 'Plane wave scattering on a finite rectangular lattice',
|
|||
|
|
'lMax' : lMax,
|
|||
|
|
'dx' : dx,
|
|||
|
|
'dy' : dy,
|
|||
|
|
'Nx' : Nx,
|
|||
|
|
'Ny' : Ny,
|
|||
|
|
#'maxlayer' : maxlayer,
|
|||
|
|
#'gaussianSigma' : gaussianSigma,
|
|||
|
|
'epsilon_b' : epsilon_b,
|
|||
|
|
#'hexside' : hexside,
|
|||
|
|
'chunkn' : chunkn,
|
|||
|
|
'chunki' : 0,
|
|||
|
|
'TMatrix_file' : TMatrix_file,
|
|||
|
|
'ops' : ops,
|
|||
|
|
'centred' : not pargs.nocentre
|
|||
|
|
})
|
|||
|
|
|
|||
|
|
|
|||
|
|
scat = qpms.Scattering_2D_zsym(positions, TMatrices_om, k_0, verbose=verbose)
|
|||
|
|
|
|||
|
|
if pargs.only_TE:
|
|||
|
|
actions = (0,)
|
|||
|
|
elif pargs.only_TM:
|
|||
|
|
actions = (1,)
|
|||
|
|
elif pargs.serial:
|
|||
|
|
actions = (0,1)
|
|||
|
|
else:
|
|||
|
|
actions = (None,)
|
|||
|
|
|
|||
|
|
xu = np.array((1,0,0))
|
|||
|
|
yu = np.array((0,1,0))
|
|||
|
|
zu = np.array((0,0,1))
|
|||
|
|
TEč, TMč = qpms.symz_indexarrays(lMax)
|
|||
|
|
|
|||
|
|
klist_full_2D = klist_full[...,:2]
|
|||
|
|
klist_full_dir = klist_full/np.linalg.norm(klist_full, axis=-1, keepdims=True)
|
|||
|
|
for action in actions:
|
|||
|
|
if action is None:
|
|||
|
|
scat.prepare(verbose=verbose)
|
|||
|
|
actionstring = ''
|
|||
|
|
else:
|
|||
|
|
scat.prepare_partial(action, verbose=verbose)
|
|||
|
|
actionstring = '.TM' if action else '.TE'
|
|||
|
|
for chunki in range(chunkn):
|
|||
|
|
if pargs.nosuffix:
|
|||
|
|
outfile = pargs.output_prefix + actionstring + (
|
|||
|
|
('.%03d' % chunki) if chunkn > 1 else '')
|
|||
|
|
else:
|
|||
|
|
outfile = '%s_%dx%d_%.0fnmx%.0fnm_%.4f%s%s.npz' % (
|
|||
|
|
pargs.output_prefix, hexside/1e-9, eVfreq, actionstring,
|
|||
|
|
(".%03d" % cunki) if chunkn > 1 else '')
|
|||
|
|
|
|||
|
|
klist = klist_full[chunki * chunklen : (chunki + 1) * chunklen]
|
|||
|
|
klist2d = klist_full_2D[chunki * chunklen : (chunki + 1) * chunklen]
|
|||
|
|
klistdir = klist_full_dir[chunki * chunklen : (chunki + 1) * chunklen]
|
|||
|
|
|
|||
|
|
'''
|
|||
|
|
The following loop is a fuckup that has its roots in the fact that
|
|||
|
|
the function qpms.get_π̃τ̃_y1 in qpms_p.py is not vectorized
|
|||
|
|
(and consequently, neither is plane_pq_y.)
|
|||
|
|
|
|||
|
|
And Scattering_2D_zsym.scatter_partial is not vectorized, either.
|
|||
|
|
'''
|
|||
|
|
if action == 0 or action is None:
|
|||
|
|
xresult = np.full((klist.shape[0], N, nelem), np.nan, dtype=complex)
|
|||
|
|
yresult = np.full((klist.shape[0], N, nelem), np.nan, dtype=complex)
|
|||
|
|
if action == 1 or action is None:
|
|||
|
|
zresult = np.full((klist.shape[0], N, nelem), np.nan, dtype=complex)
|
|||
|
|
for i in range(klist.shape[0]):
|
|||
|
|
if math.isnan(klist[i,2]):
|
|||
|
|
continue
|
|||
|
|
kdir = klistdir[i]
|
|||
|
|
phases = np.exp(np.sum(klist2d[i] * positions, axis=-1))
|
|||
|
|
if action == 0 or action is None:
|
|||
|
|
pq = np.array(qpms.plane_pq_y(lMax, kdir, xu)).ravel()[TEč] * phases[:, nx]
|
|||
|
|
xresult[i] = scat.scatter_partial(0, pq)
|
|||
|
|
pq = np.array(qpms.plane_pq_y(lMax, kdir, yu)).ravel()[TEč] * phases[:, nx]
|
|||
|
|
yresult[i] = scat.scatter_partial(0, pq)
|
|||
|
|
if action == 1 or action is none:
|
|||
|
|
pq = np.array(qpms.plane_pq_y(lMax, kdir, xu)).ravel()[TMč] * phases[:, nx]
|
|||
|
|
zresult[i] = scat.scatter_partial(1, pq)
|
|||
|
|
svdres = qpms.hexlattice_zsym_getSVD(lMax=lMax, TMatrices_om=TMatrices_om, epsilon_b=epsilon_b, hexside=hexside, maxlayer=maxlayer,
|
|||
|
|
omega=freq, klist=klist, gaussianSigma=gaussianSigma, onlyNmin=False, verbose=verbose)
|
|||
|
|
|
|||
|
|
#((svUfullTElist, svSfullTElist, svVfullTElist), (svUfullTMlist, svSfullTMlist, svVfullTMlist)) = svdres
|
|||
|
|
|
|||
|
|
metadata[()]['chunki'] = chunki
|
|||
|
|
if action is None:
|
|||
|
|
np.savez(outfile, omega = freq, klist = klist,
|
|||
|
|
metadata=metadata,
|
|||
|
|
ab_x=xresult,
|
|||
|
|
ab_y=yresult,
|
|||
|
|
ab_z=zresult
|
|||
|
|
)
|
|||
|
|
elif action == 0:
|
|||
|
|
np.savez(outfile, omega = freq, klist = klist,
|
|||
|
|
metadata=metadata,
|
|||
|
|
ab_x=xresult,
|
|||
|
|
ab_y=yresult,
|
|||
|
|
)
|
|||
|
|
elif action == 1:
|
|||
|
|
np.savez(outfile, omega = freq, klist = klist,
|
|||
|
|
metadata=metadata,
|
|||
|
|
ab_z=zresult
|
|||
|
|
)
|
|||
|
|
else:
|
|||
|
|
raise
|
|||
|
|
|
|||
|
|
if scp_dest:
|
|||
|
|
if outfile:
|
|||
|
|
subprocess.run(['scp', outfile, scp_dest])
|
|||
|
|
scat.forget_matrices() # free memory in case --serial was used
|
|||
|
|
|
|||
|
|
_time_e(btime, verbose)
|