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