Basic plotting of the dispersion_chunks.py generated data
Former-commit-id: 852034a558b1a8b09937d60687bb9c1a3e994946
This commit is contained in:
Marek Nečada
parent
1fa2e70d93
commit
22771ef507
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@ -1,6 +1,5 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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import argparse, re, random, string
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import argparse, re, random, string
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import subprocess
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import subprocess
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from scipy.constants import hbar, e as eV, pi, c
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from scipy.constants import hbar, e as eV, pi, c
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@ -200,9 +199,11 @@ if verbose:
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sys.stderr.flush()
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sys.stderr.flush()
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metadata = np.array({
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metadata = np.array({
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'lMax' : lMax,
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'maxlayer' : maxlayer,
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'maxlayer' : maxlayer,
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'gaussianSigma' : gaussianSigma,
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'gaussianSigma' : gaussianSigma,
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'epsilon_b' : epsilon_b,
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'epsilon_b' : epsilon_b,
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'hexside' : hexside,
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'chunkn' : chunkn,
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'chunkn' : chunkn,
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'TMatrix_file' : TMatrix_file,
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'TMatrix_file' : TMatrix_file,
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'ops' : ops,
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'ops' : ops,
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#!/usr/bin/env python3
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import argparse, re, random, string
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from scipy.constants import hbar, e as eV, pi, c
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parser = argparse.ArgumentParser()
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#TODO? použít type=argparse.FileType('r') ?
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parser.add_argument('--output', '-o', action='store', help='Path to output PDF')
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parser.add_argument('--nSV', action='store', metavar='N', type=int, default=1, help='Draw N minimum singular values')
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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('inputfile', nargs='+', help='Npz file(s) generated by dispersion_chunks.py or other script')
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pargs=parser.parse_args()
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print(pargs)
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#freq = eVfreq*eV/hbar
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pdfout = pargs.output if pargs.output else '%s.pdf' % pargs.inputfile[-1]
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print(pdfout)
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svn = pargs.nSV
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# -----------------finished basic CLI parsing (except for op arguments) ------------------
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import time
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begtime=time.time()
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import qpms
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from matplotlib.path import Path
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import matplotlib.patches as patches
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import matplotlib.pyplot as plt
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import numpy as np
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import os, sys, warnings, math
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from matplotlib import pyplot as plt
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from matplotlib.backends.backend_pdf import PdfPages
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from scipy import interpolate
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# We do not want to import whole qpms, so copy and modify this only fun needed
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def nelem2lMax(nelem):
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lMax = round(math.sqrt(1+nelem) - 1)
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if ((lMax < 1) or ((lMax + 2) * lMax != nelem)):
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raise
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else:
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return lMax
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nx = None
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s3 = math.sqrt(3)
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# read data from files
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lMax = None
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epsilon_b = None
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hexside = None
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karrlist = list()
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svTElist = list()
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svTMlist = list()
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omegalist = list()
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records = 0
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for filename in pargs.inputfile:
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npz = np.load(filename)
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lMaxRead = npz['metadata'][()]['lMax'] if 'lMax' in npz['metadata'][()] else nelem2lMax(npz['sTE'].shape[1] / 2)
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if lMax is None: lMax = lMaxRead
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elif lMax != lMaxRead: raise
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if epsilon_b is None: epsilon_b = npz['metadata'][()]['epsilon_b']
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elif epsilon_b != npz['metadata'][()]['epsilon_b'] : raise
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if hexside is None: hexside = npz['metadata'][()]['hexside']
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elif hexside != npz['metadata'][()]['hexside'] : raise
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omegalist.append(npz['omega'][()])
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karrlist.append(np.array(npz['klist']))
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svTElist.append(np.array(npz['sTE'][:,-svn:]))
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svTMlist.append(np.array(npz['sTM'][:,-svn:]))
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records += 1
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npz.close()
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# sort by frequencies
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omegas = set(omegalist)
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print(omegas)
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k = dict()
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svTE = dict()
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svTM = dict()
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for omega in omegas:
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k[omega] = list()
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svTE[omega] = list()
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svTM[omega] = list()
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for i in range(records):
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omega = omegalist[i]
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k[omega].append(karrlist[i])
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svTE[omega].append(svTElist[i])
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svTM[omega].append(svTMlist[i])
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# concatenate arrays for each frequency
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for omega in omegas:
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k[omega] = np.concatenate(k[omega])
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svTE[omega] = np.concatenate(svTE[omega])
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svTM[omega] = np.concatenate(svTM[omega])
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# ... that was for the slices. TODO fill also the righternmost plot with the calculated (which?) modes.
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pdf = PdfPages(pdfout)
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# In[3]:
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cdn = c/ math.sqrt(epsilon_b)
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#my, ny = qpms.get_mn_y(lMax)
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#nelem = len(my)
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nelem = lMax * (lMax + 2)
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''' The new pretty diffracted order drawing '''
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maxlayer_reciprocal=4
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cdn = c/ math.sqrt(epsilon_b)
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bz_0 = np.array((0,0,))
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bz_K1 = np.array((1.,0))*4*np.pi/3/hexside/s3
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bz_K2 = np.array((1./2.,s3/2))*4*np.pi/3/hexside/s3
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bz_M = np.array((3./4, s3/4))*4*np.pi/3/hexside/s3
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# reciprocal lattice basis
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B1 = 2* bz_K1 - bz_K2
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B2 = 2* bz_K2 - bz_K1
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k2density = 100
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k0Mlist = bz_0 + (bz_M-bz_0) * np.linspace(0,1,k2density)[:,nx]
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kMK1list = bz_M + (bz_K1-bz_M) * np.linspace(0,1,k2density)[:,nx]
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kK10list = bz_K1 + (bz_0-bz_K1) * np.linspace(0,1,k2density)[:,nx]
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k0K2list = bz_0 + (bz_K2-bz_0) * np.linspace(0,1,k2density)[:,nx]
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kK2Mlist = bz_K2 + (bz_M-bz_K2) * np.linspace(0,1,k2density)[:,nx]
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k2list = np.concatenate((k0Mlist,kMK1list,kK10list,k0K2list,kK2Mlist), axis=0)
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kxmaplist = np.concatenate((np.array([0]),np.cumsum(np.linalg.norm(np.diff(k2list, axis=0), axis=-1))))
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centers2=qpms.generate_trianglepoints(maxlayer_reciprocal, v3d = False, include_origin= True)*4*np.pi/3/hexside
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rot90 = np.array([[0,-1],[1,0]])
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centers2=np.dot(centers2,rot90)
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import matplotlib.pyplot as plt
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import matplotlib
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from matplotlib.path import Path
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import matplotlib.patches as patches
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cmap = matplotlib.cm.prism
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colormax = np.amax(np.linalg.norm(centers2,axis=0))
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for omega in sorted(omegas):
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klist = k[omega]
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minsvTElist = svTE[omega]
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minsvTMlist = svTM[omega]
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for minN in reversed(range(svn)):
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f, axes = plt.subplots(1,3, figsize=(20,4.8))
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ax = axes[0]
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sc = ax.scatter(klist[:,0], klist[:,1], c = np.clip(np.abs(minsvTElist[:,minN]),0,1), lw=0)
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for center in centers2:
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circle=plt.Circle((center[0],center[1]),omega/cdn, facecolor='none', edgecolor=cmap(np.linalg.norm(center)/colormax),lw=0.5)
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ax.add_artist(circle)
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verts = [(math.cos(math.pi*i/3)*4*np.pi/3/hexside/s3,math.sin(math.pi*i/3)*4*np.pi/3/hexside/s3) for i in range(6 +1)]
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codes = [Path.MOVETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.CLOSEPOLY,]
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path = Path(verts, codes)
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patch = patches.PathPatch(path, facecolor='none', edgecolor='black', lw=1)
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ax.add_patch(patch)
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ax.set_xticks([])
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ax.set_yticks([])
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ax.title.set_text('E in-plane ("TE"), %d. lowest SV' % minN)
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f.colorbar(sc,ax=ax)
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ax = axes[1]
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sc = ax.scatter(klist[:,0], klist[:,1], c = np.clip(np.abs(minsvTMlist[:,minN]),0,1), lw=0)
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for center in centers2:
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circle=plt.Circle((center[0],center[1]),omega/cdn, facecolor='none', edgecolor=cmap(np.linalg.norm(center)/colormax),lw=0.5)
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ax.add_artist(circle)
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verts = [(math.cos(math.pi*i/3)*4*np.pi/3/hexside/s3,math.sin(math.pi*i/3)*4*np.pi/3/hexside/s3) for i in range(6 +1)]
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codes = [Path.MOVETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.LINETO,Path.CLOSEPOLY,]
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path = Path(verts, codes)
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patch = patches.PathPatch(path, facecolor='none', edgecolor='black', lw=1)
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ax.add_patch(patch)
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ax.set_xticks([])
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ax.set_yticks([])
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ax.title.set_text('E perpendicular ("TM"), %d. lowest SV' % minN)
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f.colorbar(sc,ax=ax)
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ax = axes[2]
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for center in centers2:
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ax.plot(kxmaplist, np.linalg.norm(k2list-center,axis=-1)*cdn, '-', color=cmap(np.linalg.norm(center)/colormax))
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#ax.set_xlim([np.min(kxmlarr),np.max(kxmlarr)])
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#ax.set_ylim([np.min(omegalist),np.max(omegalist)])
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xticklist = [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]]
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ax.set_xticks(xticklist)
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for xt in xticklist:
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ax.axvline(xt, ls='dotted', lw=0.3,c='k')
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ax.set_xticklabels(['Γ', 'M', 'K', 'Γ', 'K\'','M'])
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ax.axhline(omega, c='black')
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ax.set_ylim([0,5e15])
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ax2 = ax.twinx()
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ax2.set_ylim([ax.get_ylim()[0]/eV*hbar,ax.get_ylim()[1]/eV*hbar])
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pdf.savefig(f)
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pdf.close()
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