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Multiple minimum singular value support 

Former-commit-id: c8351b2b509d5887bcde06fadcfb21c3f79a0054
This commit is contained in:
Marek Nečada 2017-02-16 00:49:53 +00:00
parent a3dec16ee3
commit 2ff17ba650
1 changed files with 76 additions and 70 deletions
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146
misc/dispersion-SVD.py
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@ -19,6 +19,7 @@ parser.add_argument('--griddir', action='store', required=True, help='Path to th
#sizepar = parser.add_mutually_exclusive_group(required=True) #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('--hexside', action='store', type=float, required=True, help='Lattice hexagon size length')
parser.add_argument('--output', action='store', help='Path to output PDF') parser.add_argument('--output', action='store', help='Path to output PDF')
parser.add_argument('--nSV', action='store', metavar='N', type=int, default=1, help='Store and draw N minimun singular values')
parser.add_argument('--background_permittivity', action='store', type=float, default=1., help='Background medium relative permittivity (default 1)') parser.add_argument('--background_permittivity', action='store', type=float, default=1., help='Background medium relative permittivity (default 1)')
parser.add_argument('--sparse', action='store', type=int, help='Skip frequencies for preview') parser.add_argument('--sparse', action='store', type=int, help='Skip frequencies for preview')
parser.add_argument('--eVmax', action='store', help='Skip frequencies above this value') parser.add_argument('--eVmax', action='store', help='Skip frequencies above this value')
@ -58,6 +59,7 @@ kdensity = pargs.kdensity
minfreq = pargs.eVmin*eV/hbar if pargs.eVmin else None minfreq = pargs.eVmin*eV/hbar if pargs.eVmin else None
maxfreq = pargs.eVmax*eV/hbar if pargs.eVmax else None maxfreq = pargs.eVmax*eV/hbar if pargs.eVmax else None
skipfreq = pargs.sparse if pargs.sparse else None skipfreq = pargs.sparse if pargs.sparse else None
svn = pargs.nSV
# TODO multiplier operation definitions and parsing # TODO multiplier operation definitions and parsing
#factor13inc = 10 #factor13inc = 10
@ -92,6 +94,9 @@ print(ops)
import time import time
begtime=time.time() begtime=time.time()
from matplotlib.path import Path
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import qpms import qpms
import numpy as np import numpy as np
import os, sys, warnings, math import os, sys, warnings, math
@ -324,8 +329,8 @@ for trfile in os.scandir(translations_dir):
TMatrices_om = TMatrices_interp(omega) TMatrices_om = TMatrices_interp(omega)
minsvTElist = np.full((klist.shape[0]),np.nan) minsvTElist = np.full((klist.shape[0], svn),np.nan)
minsvTMlist = np.full((klist.shape[0]),np.nan) minsvTMlist = np.full((klist.shape[0], svn),np.nan)
leftmatrixlist = np.full((klist.shape[0],2,2,nelem,2,2,nelem),np.nan,dtype=complex) leftmatrixlist = np.full((klist.shape[0],2,2,nelem,2,2,nelem),np.nan,dtype=complex)
isNaNlist = np.zeros((klist.shape[0]), dtype=bool) isNaNlist = np.zeros((klist.shape[0]), dtype=bool)
@ -373,8 +378,14 @@ for trfile in os.scandir(translations_dir):
leftmatrixlist_s = np.reshape(leftmatrixlist,(klist.shape[0], 2*2*nelem,2*2*nelem))[nnlist] leftmatrixlist_s = np.reshape(leftmatrixlist,(klist.shape[0], 2*2*nelem,2*2*nelem))[nnlist]
leftmatrixlist_TE = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TEč,TEč)] leftmatrixlist_TE = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TEč,TEč)]
leftmatrixlist_TM = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TMč,TMč)] leftmatrixlist_TM = leftmatrixlist_s[np.ix_(np.arange(leftmatrixlist_s.shape[0]),TMč,TMč)]
minsvTElist[nnlist] = np.amin(np.linalg.svd(leftmatrixlist_TE, compute_uv=False), axis=-1) svarr = np.linalg.svd(leftmatrixlist_TE, compute_uv=False)
minsvTMlist[nnlist] = np.amin(np.linalg.svd(leftmatrixlist_TM, compute_uv=False), axis=-1) argsortlist = np.argsort(svarr, axis=-1)[...,:svn]
minsvTElist[nnlist] = svarr[argsortlist]
#minsvTElist[nnlist] = np.amin(np.linalg.svd(leftmatrixlist_TE, compute_uv=False), axis=-1)
svarr = np.linalg.svd(leftmatrixlist_TM, compute_uv=False)
argsortlist = np.argsort(svarr, axis=-1)[...,:svn]
minsvTMlist[nnlist] = svarr[argsortlist]
#minsvTMlist[nnlist] = np.amin(np.linalg.svd(leftmatrixlist_TM, compute_uv=False), axis=-1)
minsvTMlistlist.append(minsvTMlist) minsvTMlistlist.append(minsvTMlist)
minsvTElistlist.append(minsvTElist) minsvTElistlist.append(minsvTElist)
@ -393,76 +404,71 @@ omegalist = omegalist[omegaorder]
minsvTElistarr = minsvTElistarr[omegaorder] minsvTElistarr = minsvTElistarr[omegaorder]
minsvTMlistarr = minsvTMlistarr[omegaorder] minsvTMlistarr = minsvTMlistarr[omegaorder]
omlist = np.broadcast_to(omegalist[:,nx], minsvTElistarr.shape) omlist = np.broadcast_to(omegalist[:,nx], minsvTElistarr[...,0].shape)
kxmlarr = np.broadcast_to(kxmaplist[nx,:], minsvTElistarr.shape) kxmlarr = np.broadcast_to(kxmaplist[nx,:], minsvTElistarr[...,0].shape)
klist = np.concatenate((k0Mlist,kMK1list,kK10list,k0K2list,kK2Mlist), axis=0) klist = np.concatenate((k0Mlist,kMK1list,kK10list,k0K2list,kK2Mlist), axis=0)
# In[ ]: # In[ ]:
for minN in range(svn):
from matplotlib.path import Path f, ax = plt.subplots(1, figsize=(20,15))
import matplotlib.patches as patches sc = ax.scatter(kxmlarr, omlist/eV*hbar, c = np.sqrt(minsvTMlistarr[...,minN]), s =40, lw=0)
f, ax = plt.subplots(1, figsize=(20,15)) ax.plot(kxmaplist, np.linalg.norm(klist,axis=-1)*cdn/eV*hbar, '-',
sc = ax.scatter(kxmlarr, omlist/eV*hbar, c = np.sqrt(minsvTMlistarr), s =40, lw=0) kxmaplist, np.linalg.norm(klist+B1, axis=-1)*cdn/eV*hbar, '-',
ax.plot(kxmaplist, np.linalg.norm(klist,axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist+B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist+B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B2+B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist+B2+B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-2*B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-2*B2, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1-B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-2*B2-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1-2*B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-2*B1-B2, axis=-1)*cdn/eV*hbar, '-', # kxmaplist, np.linalg.norm(klist+2*B2-B1, axis=-1)*cdn, '-',
kxmaplist, np.linalg.norm(klist-2*B1-2*B2, axis=-1)*cdn/eV*hbar, '-', # kxmaplist, np.linalg.norm(klist+2*B1-B2, axis=-1)*cdn, '-',
# kxmaplist, np.linalg.norm(klist+2*B2-B1, axis=-1)*cdn, '-', )
# kxmaplist, np.linalg.norm(klist+2*B1-B2, axis=-1)*cdn, '-', ax.set_xlim([np.min(kxmlarr),np.max(kxmlarr)])
) #ax.set_ylim([2.15,2.30])
ax.set_xlim([np.min(kxmlarr),np.max(kxmlarr)]) ax.set_ylim([np.min(omlist/eV*hbar),np.max(omlist/eV*hbar)])
#ax.set_ylim([2.15,2.30]) ax.set_xticks([0, kxmaplist[len(k0Mlist)-1], kxmaplist[len(k0Mlist)+len(kMK1list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)+len(kK2Mlist)-1]])
ax.set_ylim([np.min(omlist/eV*hbar),np.max(omlist/eV*hbar)]) ax.set_xticklabels(['Γ', 'M', 'K', 'Γ', 'K\'','M'])
ax.set_xticks([0, kxmaplist[len(k0Mlist)-1], kxmaplist[len(k0Mlist)+len(kMK1list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)+len(kK2Mlist)-1]]) f.colorbar(sc)
ax.set_xticklabels(['Γ', 'M', 'K', 'Γ', 'K\'','M'])
f.colorbar(sc) pdf.savefig(f)
pdf.savefig(f)
# In[ ]:
# In[ ]: f, ax = plt.subplots(1, figsize=(20,15))
sc = ax.scatter(kxmlarr, omlist/eV*hbar, c = np.sqrt(minsvTElistarr[...,minN]), s =40, lw=0)
import matplotlib.pyplot as plt ax.plot(kxmaplist, np.linalg.norm(klist,axis=-1)*cdn/eV*hbar, '-',
from matplotlib.path import Path kxmaplist, np.linalg.norm(klist+B1, axis=-1)*cdn/eV*hbar, '-',
import matplotlib.patches as patches kxmaplist, np.linalg.norm(klist+B2, axis=-1)*cdn/eV*hbar, '-',
f, ax = plt.subplots(1, figsize=(20,15)) kxmaplist, np.linalg.norm(klist-B2, axis=-1)*cdn/eV*hbar, '-',
sc = ax.scatter(kxmlarr, omlist/eV*hbar, c = np.sqrt(minsvTElistarr), s =40, lw=0) kxmaplist, np.linalg.norm(klist-B1, axis=-1)*cdn/eV*hbar, '-',
ax.plot(kxmaplist, np.linalg.norm(klist,axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist+B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B2+B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist+B2+B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B2-B1, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-B2-B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1-B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist+B2+B1, axis=-1)*cdn/eV*hbar, '-', kxmaplist, np.linalg.norm(klist-2*B1-2*B2, axis=-1)*cdn/eV*hbar, '-',
kxmaplist, np.linalg.norm(klist-2*B1, axis=-1)*cdn/eV*hbar, '-', # kxmaplist, np.linalg.norm(klist+2*B2-B1, axis=-1)*cdn, '-',
kxmaplist, np.linalg.norm(klist-2*B2, axis=-1)*cdn/eV*hbar, '-', # kxmaplist, np.linalg.norm(klist+2*B1-B2, axis=-1)*cdn, '-',
kxmaplist, np.linalg.norm(klist-2*B2-B1, axis=-1)*cdn/eV*hbar, '-', )
kxmaplist, np.linalg.norm(klist-2*B1-B2, axis=-1)*cdn/eV*hbar, '-', ax.set_xlim([np.min(kxmlarr),np.max(kxmlarr)])
kxmaplist, np.linalg.norm(klist-2*B1-2*B2, axis=-1)*cdn/eV*hbar, '-', #ax.set_ylim([2.15,2.30])
# kxmaplist, np.linalg.norm(klist+2*B2-B1, axis=-1)*cdn, '-', ax.set_ylim([np.min(omlist/eV*hbar),np.max(omlist/eV*hbar)])
# kxmaplist, np.linalg.norm(klist+2*B1-B2, axis=-1)*cdn, '-', ax.set_xticks([0, kxmaplist[len(k0Mlist)-1], kxmaplist[len(k0Mlist)+len(kMK1list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)+len(kK2Mlist)-1]])
) ax.set_xticklabels(['Γ', 'M', 'K', 'Γ', 'K\'','M'])
ax.set_xlim([np.min(kxmlarr),np.max(kxmlarr)]) f.colorbar(sc)
#ax.set_ylim([2.15,2.30])
ax.set_ylim([np.min(omlist/eV*hbar),np.max(omlist/eV*hbar)]) pdf.savefig(f)
ax.set_xticks([0, kxmaplist[len(k0Mlist)-1], kxmaplist[len(k0Mlist)+len(kMK1list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)-1], kxmaplist[len(k0Mlist)+len(kMK1list)+len(kK10list)+len(k0K2list)+len(kK2Mlist)-1]])
ax.set_xticklabels(['Γ', 'M', 'K', 'Γ', 'K\'','M'])
f.colorbar(sc)
pdf.savefig(f)
pdf.close() pdf.close()
print(time.strftime("%H.%M:%S",time.gmtime(time.time()-begtime))) print(time.strftime("%H.%M:%S",time.gmtime(time.time()-begtime)))