318 lines
16 KiB
Python
Executable File
318 lines
16 KiB
Python
Executable File
#!/usr/bin/env python3
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'''
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Bulk SVD mode computation for compact scatterer 2D lattices
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'''
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__TODOs__ = '''
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BIG TODO: Use more efficient way to calculate the interaction sums: perhaps some customized Ewald-type summation?
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Small TODOs:
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- Implement a more user-friendly way to define the lattice base vectors and positions of the particles.
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cf. https://stackoverflow.com/questions/2371436/evaluating-a-mathematical-expression-in-a-string/2371789
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- low priority: allow to perform some more custom operations on T-Matrix, using some kind of parsing from the previous point
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- Autodetect symmetries
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'''
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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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import warnings
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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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#TODO create some user-friendlier way to define lattice vectors, cf. https://stackoverflow.com/questions/2371436/evaluating-a-mathematical-expression-in-a-string/2371789
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parser.add_argument('--lattice_base', nargs=4, action='store', type=float, required=True, help='Lattice basis vectors x1, y1, x2, y2')
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parser.add_argument('--particle', '-p', nargs='+', action=make_action_sharedlist('particle', 'particlespec'), help='Particle label, coordinates x,y, and (optionally) path to the T-Matrix.')
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parser.add_argument('--TMatrix', '-t', nargs='+', action=make_action_sharedlist('TMatrix_path', 'particlespec'), 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', action='store', required=True, help='Prefix to the npz output (will be appended frequency, hexside and chunkno)')
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#sizepar = parser.add_mutually_exclusive_group(required=True)
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#DEL parser.add_argument('--hexside', action='store', type=float, required=True, help='Lattice hexagon size length')
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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('--kdensity', '--k_density', action='store', type=int, default=33, help='Number of k-points per x-axis segment FIXME DESCRIPTION')
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parser.add_argument('--bz_coverage', action='store', type=float, default=1., help='Brillouin zone coverage in relative length (default 1 for whole 1. BZ)')
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parser.add_argument('--bz_edge_width', action='store', type=float, default=0., help='Width of the more densely covered belt along the 1. BZ edge in relative lengths')
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parser.add_argument('--bz_edge_factor', action='store', type=float, default=8., help='Relative density of the belt along the 1. BZ edge w.r.t. k_density (default==8)')
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parser.add_argument('--bz_edge_twoside', action='store_true', help='Compute also the parts of the densely covered edge belt outside the 1. BZ')
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parser.add_argument('--bz_corner_width', action='store', type=float, default=0., help='Size of the more densely covered subcell along the 1. BZ corners in relative lengths')
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parser.add_argument('--bz_corner_factor', action='store', type=float, default=16., help='Relative density of the subcell along the 1. BZ corner w.r.t. k_density (default==16)')
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parser.add_argument('--bz_corner_twoside', action='store_true', help='Compute also the parts of the densely covered subcell outside the 1. BZ')
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parser.add_argument('--chunklen', action='store', type=int, default=1000, help='Number of k-points per output file (default 1000)')
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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', nargs='+', action=make_action_sharedlist('tr', 'ops'), default=list()) # the default value for dest can be set once
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popgrp.add_argument('--sym', dest='ops', nargs='+', action=make_action_sharedlist('sym', '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('--multl', dest='ops', nargs=3, metavar=('INCL[,INCL,...]', 'SCATL[,SCATL,...]', 'MULTIPLIER'), action=make_action_sharedlist('multl', '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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pargs=parser.parse_args()
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print(pargs)
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exit(0) ###
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maxlayer=pargs.maxlayer
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#DEL hexside=pargs.hexside
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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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#DEL 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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kdensity = pargs.kdensity
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chunklen = pargs.chunklen
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#### Nanoparticle position and T-matrix path parsing ####
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TMatrix_paths = dict()
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default_TMatrix_path = None
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if not any((arg_type == 'particle') in (arg_type, arg_content) for in pargs.particlespec):
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# no particles positions given: suppose only one per unit cell, in the cell origin
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positions = {None: (0.0)}
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else:
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positions = dict()
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for arg_type, arg_content in pargs.particlespec:
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if arg_type == 'particle' # --particle option
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if 3 <= len(arg_content) <= 4:
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try:
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positions[arg_content[0]] = (float(arg_content[1]), float(arg_content[2]))
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except ValueError as e:
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e.args += ("second and third argument of --particle must be valid floats, given: ", arg_content)
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raise
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if len(arg_content == 4):
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if arg_content[0] in TMatrix_paths:
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % arg_content[0], SyntaxWarning)
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TMatrix_paths[arg_content[0]] = arg_content[3]
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else:
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raise ValueError("--particle expects 3 or 4 arguments, %d given: " % len(arg_content), arg_content)
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elif arg_type == 'TMatrix_path': # --TMatrix option
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if len(arg_content) == 1: # --TMatrix default_path
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if default_TMatrix_path is not None:
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warnings.warn('Default T-matrix path already specified. Overriding with the last value.', SyntaxWarning)
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default_TMatrix_path = arg_content[0]
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elif len(arg_content) > 1: # --TMatrix label [label2 [...]] path
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for label in arg_content[:-1]:
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if label in TMatrix_paths:
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % label, SyntaxWarning)
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TMatrix_paths[label] = arg_content[-1]
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else: assert False, 'unknown option type'
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# Check the info from positions and TMatrix_paths
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if not set(TMatrix_paths.keys()) <= set(positions.keys()):
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raise ValueError("T-Matrix path(s) for particle(s) labeled %s was given, but not their positions"
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% str(set(TMatrix_paths.keys()) - set(positions.keys())))
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if (set(TMatrix_paths.keys()) != set(positions.keys())) and default_TMatrix_path is None:
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raise ValueError("Position(s) of particles(s) labeled %s was given without their T-matrix"
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" and no default T-matrix was specified"
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% str(set(positions.keys()) - set(TMatrix_paths_keys())))
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for path in TMatrix_paths.values():
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if not os.path.exists(path):
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raise ValueError("Cannot access T-matrix file %s. Does it exist?" % path)
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# Assign (pre-parse) the T-matrix operations to individual particles
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ops = dict()
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for label in positions.keys(): ops[label] = list()
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for optype, arg_content in pargs.ops:
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# if, no label given, apply to all, otherwise on the specifield particles
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for label in (positions.keys() if len(arg_content) == 1 else arg_content[:-1]):
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try:
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ops[label].append((optype, arg_content[-1]))
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except KeyError as e:
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e.args += 'Specified operation on undefined particle labeled \'%s\'' % label
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raise
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print(sys.stderr, "ops: ", ops) #DEBUG
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#### Collect all the info about the particles / their T-matrices ####
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# Enumerate and assign all the _different_ T-matrices (without any intelligent group-theory checking, though)
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TMatrix_specs = dict((spec, number)
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for (number, spec) in enumerate(set(
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(TMatrix_paths[label], tuple(ops[label])) for label in positions.keys()
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)))
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# particles_specs contains (label, (xpos, ypos), tmspec_index per element)
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particles_specs = [(label, positions(label), TMatrix_specs[(TMatrix_paths[label], tuple(ops[label]))]) for label in positions.keys()]
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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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cdn = c/ math.sqrt(epsilon_b)
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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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if pargs.lMax: #force commandline specified lMax
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TMatrices_orig = TMatrices_orig[...,0:nelem,:,0:nelem]
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TMatrices = np.array(np.broadcast_to(TMatrices_orig[:,nx,:,:,:,:],(len(freqs_orig),2,2,nelem,2,nelem)) )
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#TMatrices[:,:,:,:,:,ny==3] *= factor13inc
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#TMatrices[:,:,:,ny==3,:,:] *= factor13scat
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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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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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TMatrices_interp = interpolate.interp1d(freqs_orig*interpfreqfactor, TMatrices, axis=0, kind='linear',fill_value="extrapolate")
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klist_full = qpms.generate_trianglepoints(kdensity, v3d=True, include_origin=True)*3*math.pi/(3*kdensity*hexside)
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TMatrices_om = TMatrices_interp(freq)
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chunkn = math.ceil(klist_full.shape[0] / chunklen)
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if verbose:
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print('Evaluating %d k-points in %d chunks' % (klist_full.shape[0], chunkn), file = sys.stderr)
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sys.stderr.flush()
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metadata = np.array({
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'lMax' : lMax,
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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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'TMatrix_file' : TMatrix_file,
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'ops' : ops,
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})
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for chunki in range(chunkn):
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svdout = '%s_%dnm_%.4f_c%03d.npz' % (pargs.output_prefix, hexside/1e-9, eVfreq, chunki)
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klist = klist_full[chunki * chunklen : (chunki + 1) * chunklen]
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svdres = qpms.hexlattice_zsym_getSVD(lMax=lMax, TMatrices_om=TMatrices_om, epsilon_b=epsilon_b, hexside=hexside, maxlayer=maxlayer,
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omega=freq, klist=klist, gaussianSigma=gaussianSigma, onlyNmin=False, verbose=verbose)
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#((svUfullTElist, svSfullTElist, svVfullTElist), (svUfullTMlist, svSfullTMlist, svVfullTMlist)) = svdres
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np.savez(svdout, omega = freq, klist = klist,
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metadata=metadata,
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uTE = svdres[0][0],
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vTE = svdres[0][2],
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sTE = svdres[0][1],
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uTM = svdres[1][0],
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vTM = svdres[1][2],
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sTM = svdres[1][1],
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)
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svdres=None
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if scp_dest:
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if svdout:
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subprocess.run(['scp', svdout, scp_dest])
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_time_e(btime, verbose)
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#print(time.strftime("%H.%M:%S",time.gmtime(time.time()-begtime)))
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