qpms/examples/rectangular/modes/04_collect_modes.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import re\n",
"import numpy as np\n",
"import matplotlib\n",
"from matplotlib import pyplot as plt\n",
"from scipy.constants import hbar, e as eV, c\n",
"eh = eV/hbar\n",
"import glob\n",
"def ri(z): return (z.real, z.imag)\n",
"#m = re.compile(r\"([^_]+)_r([0-9.]+)nm_\")\n",
"#removek = re.compile(r\"(k\\([^)]+\\)um-1_)\")\n",
"#remover = re.compile(r\"r[0-9.]+nm_\")"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"allfiles=glob.glob('*cyl*k(0_0)*.npz')\n",
"allgraphs=dict()\n",
"for f in allfiles:\n",
" base = remover.sub('', f)\n",
" if base in allgraphs.keys():\n",
" allgraphs[base] += 1\n",
" else:\n",
" allgraphs[base] = 1\n",
"for k in sorted(allgraphs.keys()):\n",
" print(k, allgraphs[k])"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"filenames=glob.glob('modes_basis*.npz')\n",
"projectors = np.load('projectors_D4h_lMax3.npz')\n",
"irlabels = sorted(projectors.keys())\n",
"projectors = {f: projectors[f] for f in irlabels}\n",
"projectors_list = [projectors[irlabels[i]] for i in range(len(projectors))]"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"plotdata = []\n",
"for file in filenames:\n",
" dat = np.load(file, allow_pickle=True)\n",
" kx = dat['meta'][()]['k'][0]\n",
" b = dat['meta'][()]['band_index']\n",
" eigvals = dat['eigval']\n",
" lMax = dat['meta'][()]['lMax'][None]\n",
" residuals = dat['residuals']\n",
" #print(kx, residuals)\n",
" ef =dat['empty_freqs']\n",
" eigvecs = dat['eigvec']\n",
" if(kx==0): \n",
" irweights = np.array([np.linalg.norm(np.tensordot(proj, eigvecs, axes=(-1, -1)), axis=0,ord=2) for proj in projectors_list]).T\n",
" irclass = np.argmax(irweights, axis=-1)\n",
" else:\n",
" irweights = None\n",
" irclass = [None] * len(eigvals)\n",
" plotdata.append((kx, eigvals, residuals, b, ef, irclass))\n"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [],
"source": [
"markerdict = {\n",
" 4: \"3\",\n",
" -4: \"4\",\n",
" 3: \"^\",\n",
" -3: \"v\",\n",
" -2: 'x',\n",
" 2: '+',\n",
" 1: 's',\n",
" -1: 'd',\n",
"}\n",
"\n",
"prop_cycle = plt.rcParams['axes.prop_cycle']\n",
"colors = prop_cycle.by_key()['color']\n",
"colordict = {i: colors[(i+1)] for i in range(-4,8)}\n",
"\n",
"def markerfun(b):\n",
" if b in markerdict.keys():\n",
" return markerdict[b]\n",
" else: return 'X'\n",
"\n",
"def colorfun(b):\n",
" if (b+1) in colordict.keys():\n",
" return colordict[b+1]\n",
" else: return colordict[0]\n",
" \n",
"labeldict = {\n",
" \"E'\" : \"$E'$\",\n",
" \"A2''\" : \"$A_2''$\",\n",
"}\n",
"def label2latex(label):\n",
" return labeldict[label] if label in labeldict.keys() else label\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, None}\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 432x576 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(6,8))\n",
"ax = fig.add_subplot(211)\n",
"\n",
"res_thr = 0.1\n",
"xlim = [40,200]\n",
"plot_irreps = None #{\"E''\"}\n",
"\n",
"\n",
"plot_iris=set(range(len(irlabels))) if plot_irreps is None else {iri for iri in range(len(irlabels)) if irlabels[iri] in plot_irreps}\n",
"plot_iris |= {None}\n",
"print(plot_iris)\n",
"\n",
"ir_labeled=set()\n",
"for (kx, eigvals, residuals, b, ef, irclass) in plotdata:\n",
" for i, (e, res, iri) in enumerate(zip(eigvals, residuals, irclass)):\n",
" #if i == 0:\n",
" if iri in plot_iris and res < res_thr:# and e.real < 2.14e15:\n",
" if iri in ir_labeled: \n",
" label=None\n",
" else:\n",
" ir_labeled.add(iri)\n",
" label=irlabels[iri] if iri is not None else None\n",
" ax.plot(kx/1e6, e.real/eh,\n",
" marker=markerfun(b) if iri is None else \"D\",\n",
" ms=4, #c=colorfun(b)\n",
" c=matplotlib.cm.hsv(iri/9 if iri is not None else 0),\n",
" #c = colorfun(iri),\n",
" label=label2latex(label),\n",
" )\n",
" #print(kx, abs(e.imag/e.real), res, b)\n",
"#for eff in ef:\n",
"# ax.axhline(y= eff/eh)\n",
"ax.set_xlabel(\"$k_x/\\mathrm{\\mu m^{-1}}$\")\n",
"ax.set_ylabel('$\\hbar \\Re \\omega / \\mathrm{eV}$')\n",
"ax.legend(title=\"Irrep at $\\\\Gamma$\")\n",
"#ax.set_ylim([2.075e15,2.085e15])\n",
"#ax.set_ylim([1.30, 1.42])\n",
"#ax.set_xlim(xlim)\n",
"\n",
"#ax.set_xlim([40,100])\n",
"#ax.legend()\n",
"\n",
"ax = fig.add_subplot(212)\n",
"ir_labeled=set()\n",
"for (kx, eigvals, residuals, b, ef, irclass) in plotdata:\n",
" for i, (e, res, iri) in enumerate(zip(eigvals, residuals, irclass)):\n",
" #if i==0:\n",
" if iri in plot_iris and res < res_thr:# and e.real < 2.14e15:\n",
" if iri in ir_labeled: \n",
" label=None\n",
" else:\n",
" ir_labeled.add(iri)\n",
" label=irlabels[iri] if iri is not None else None,\n",
" ax.plot(kx/1e6, e.imag/eh*1000, \n",
" #marker='x', \n",
" #c=colorfun(b), \n",
" c=matplotlib.cm.hsv(iri/9 if iri is not None else 0),#colorfun(iri),\n",
" marker=markerfun(b) if iri is None else \"D\", ms=4,\n",
" label=label2latex(label)\n",
" )\n",
" #print(kx, abs(e.imag/e.real), res, b)\n",
"#ax.set_ylim([-15,0])\n",
"#ax.set_xlim(xlim)\n",
"ax.set_xlabel(\"$k_x/\\mathrm{\\mu m^{-1}}$\")\n",
"ax.set_ylabel('$\\hbar \\Im \\omega / \\mathrm{meV}$')\n",
"#fig.suptitle('$l_\\mathrm{max}=%d$, residual threshold = %g' % (lMax, res_thr) )\n",
"#fig.savefig(plotfilename)\n",
"#fig.savefig(plotfilename.replace('pdf', 'png'))\n",
"fig.savefig(\"sqlat_beyn_dispersion.pdf\")"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[(-266666.6666666667, array([3.35664512e+15-8.70857302e+11j]), array([0.00326631]), -4, array([5.25951681e+13, 3.25205670e+15, 3.30507039e+15, 3.35724704e+15,\n",
" 4.63644226e+15, 4.71082070e+15, 6.55670858e+15, 6.60951301e+15,\n",
" 6.66189891e+15, 7.34242136e+15, 7.36605517e+15, 7.41309677e+15,\n",
" 7.43650598e+15, 9.30985088e+15, 9.38423109e+15, 9.86136045e+15,\n",
" 9.91409513e+15, 9.96655079e+15, 1.04003439e+16, 1.04337140e+16,\n",
" 1.04669778e+16, 1.05001361e+16, 1.31660123e+16, 1.32187121e+16,\n",
" 1.32712027e+16]), [None]), (400000.0, array([3.30014096e+15-2.51999947e+12j]), array([5.91025308e-05]), -3, array([7.88927521e+13, 3.22575912e+15, 3.30559345e+15, 3.38354462e+15,\n",
" 4.61803485e+15, 4.72959810e+15, 6.53041099e+15, 6.60977458e+15,\n",
" 6.68819650e+15, 7.31894745e+15, 7.35448284e+15, 7.42504345e+15,\n",
" 7.46007348e+15, 9.29134886e+15, 9.40291808e+15, 9.83506287e+15,\n",
" 9.91426952e+15, 9.99284837e+15, 1.03754125e+16, 1.04255474e+16,\n",
" 1.04754422e+16, 1.05251006e+16, 1.31397147e+16, 1.32188429e+16]), [None]), (373333.3333333333, array([3.23102785e+15-4.80112733e+09j]), array([0.12782094]), 2, array([7.36332353e+13, 3.23101864e+15, 3.30547211e+15, 3.37828511e+15,\n",
" 4.62171023e+15, 4.72583689e+15, 6.53567051e+15, 6.60971390e+15,\n",
" 6.68293698e+15, 7.32364069e+15, 7.35679125e+15, 7.42264820e+15,\n",
" 7.45535852e+15, 9.29504626e+15, 9.39917777e+15, 9.84032238e+15,\n",
" 9.91422906e+15]), [None]), (-346666.6666666667, array([3.30537911e+15-5.34095064e+08j]), array([0.15775551]), 3, array([6.83737185e+13, 3.23627815e+15, 3.30535913e+15, 3.37302559e+15,\n",
" 4.62538866e+15, 4.72207853e+15, 6.54093003e+15, 6.60965740e+15,\n",
" 6.67767746e+15, 7.32833471e+15, 7.35910268e+15, 7.42025590e+15,\n",
" 7.45064429e+15, 9.29874516e+15, 9.39543891e+15, 9.84558190e+15,\n",
" 9.91419139e+15, 9.98232934e+15, 1.03853843e+16, 1.04288068e+16,\n",
" 1.04720494e+16, 1.05151140e+16, 1.31502338e+16, 1.32187843e+16]), [None]), (400000.0, array([3.2257785e+15-5.7760227e+09j]), array([0.08601028]), 2, array([7.88927521e+13, 3.22575912e+15, 3.30559345e+15, 3.38354462e+15,\n",
" 4.61803485e+15, 4.72959810e+15, 6.53041099e+15, 6.60977458e+15,\n",
" 6.68819650e+15, 7.31894745e+15, 7.35448284e+15, 7.42504345e+15,\n",
" 7.46007348e+15, 9.29134886e+15, 9.40291808e+15, 9.83506287e+15,\n",
" 9.91426952e+15]), [None]), (453333.3333333333, array([3.39321239e+15-9.16449782e+11j, 3.39405872e+15-4.72031291e+08j]), array([0.00243872, 0.49750472]), -4, array([8.94117857e+13, 3.21524009e+15, 3.30586123e+15, 3.39406366e+15,\n",
" 4.61069331e+15, 4.73712910e+15, 6.51989196e+15, 6.60990851e+15,\n",
" 6.69871553e+15, 7.30956327e+15, 7.34987516e+15, 7.42984281e+15,\n",
" 7.46950559e+15, 9.28395859e+15, 9.41040306e+15, 9.82454383e+15,\n",
" 9.91435880e+15, 1.00033674e+16, 1.03654419e+16, 1.04222975e+16,\n",
" 1.04788446e+16, 1.05350882e+16, 1.31291957e+16, 1.32189099e+16,\n",
" 1.33080193e+16]), [None, None]), (293333.3333333333, array([3.24681795e+15-3.84676983e+09j]), array([0.04389545]), 2, array([5.78546849e+13, 3.24679719e+15, 3.30515827e+15, 3.36250656e+15,\n",
" 4.63275469e+15, 4.71457043e+15, 6.55144906e+15, 6.60955696e+15,\n",
" 6.66715843e+15, 7.33772504e+15, 7.36373465e+15, 7.41548018e+15,\n",
" 7.44121801e+15, 9.30614747e+15, 9.38796557e+15, 9.85610093e+15,\n",
" 9.91412443e+15]), [None]), (-79999.99999999999, array([], dtype=complex128), array([], dtype=float64), 4, array([1.57785504e+13, 3.28887332e+15, 3.30468954e+15, 3.32043042e+15,\n",
" 4.66233973e+15, 4.68465390e+15, 6.59352519e+15, 6.60932258e+15,\n",
" 6.62508230e+15, 7.37531684e+15, 7.38238334e+15, 7.39649607e+15,\n",
" 7.40354236e+15, 9.33581654e+15, 9.35813076e+15, 9.89817707e+15,\n",
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" 1.04552271e+16, 1.04651968e+16, 1.32028289e+16, 1.32186169e+16,\n",
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" 3.30558398e+15-1.05276663e+09j, 3.30558718e+15-6.75635783e+08j]), array([1.90722989e-04, 3.75869771e-01, 2.69595069e-01, 4.59556196e-01]), -3, array([7.88927521e+13, 3.22575912e+15, 3.30559345e+15, 3.38354462e+15,\n",
" 4.61803485e+15, 4.72959810e+15, 6.53041099e+15, 6.60977458e+15,\n",
" 6.68819650e+15, 7.31894745e+15, 7.35448284e+15, 7.42504345e+15,\n",
" 7.46007348e+15, 9.29134886e+15, 9.40291808e+15, 9.83506287e+15,\n",
" 9.91426952e+15, 9.99284837e+15, 1.03754125e+16, 1.04255474e+16,\n",
" 1.04754422e+16, 1.05251006e+16, 1.31397147e+16, 1.32188429e+16]), [None, None, None, None]), (-426666.6666666667, array([], dtype=complex128), array([], dtype=float64), 1, array([8.41522689e+13, 3.22049960e+15, 3.30572316e+15, 3.38880414e+15,\n",
" 4.61436254e+15, 4.73336218e+15, 6.52515148e+15, 6.60983945e+15]), []), (-480000.0, array([3.2100011e+15-5.31310467e+09j]), array([0.10756916]), 2, array([9.46713025e+13, 3.20998057e+15, 3.30600766e+15, 3.39932317e+15,\n",
" 4.60702716e+15, 4.74089886e+15, 6.51463244e+15, 6.60998174e+15,\n",
" 6.70397505e+15, 7.30487234e+15, 7.34757588e+15, 7.43224690e+15,\n",
" 7.47422273e+15, 9.28026572e+15, 9.41414773e+15, 9.81928431e+15,\n",
" 9.91440763e+15]), [None]), (-533333.3333333334, array([3.18994344e+15-5.57748807e+12j]), array([0.00536213]), -2, array([1.05190336e+14, 3.19946154e+15, 3.30632560e+15, 3.40984221e+15,\n",
" 4.59970413e+15, 4.74844689e+15, 6.50411341e+15, 6.61014077e+15,\n",
" 6.71449408e+15, 7.29549280e+15, 7.34298646e+15, 7.43706393e+15,\n",
" 7.48365918e+15, 9.27288451e+15, 9.42164140e+15, 9.80876528e+15,\n",
" 9.91451365e+15]), [None]), (133333.33333333334, array([3.27835479e+15+7.00997131e+09j]), array([0.16601648]), 2, array([2.62975840e+13, 3.27835429e+15, 3.30475651e+15, 3.33094946e+15,\n",
" 4.65492544e+15, 4.69211554e+15, 6.58300616e+15, 6.60935606e+15,\n",
" 6.63560133e+15, 7.36591434e+15, 7.37770309e+15, 7.40122424e+15,\n",
" 7.41295683e+15, 9.32839033e+15, 9.36558065e+15, 9.88765803e+15,\n",
" 9.91399050e+15]), [None]), (533333.3333333334, array([3.18994344e+15-5.57748807e+12j]), array([0.00536213]), -2, array([1.05190336e+14, 3.19946154e+15, 3.30632560e+15, 3.40984221e+15,\n",
" 4.59970413e+15, 4.74844689e+15, 6.50411341e+15, 6.61014077e+15,\n",
" 6.71449408e+15, 7.29549280e+15, 7.34298646e+15, 7.43706393e+15,\n",
" 7.48365918e+15, 9.27288451e+15, 9.42164140e+15, 9.80876528e+15,\n",
" 9.91451365e+15]), [None]), (-373333.3333333333, array([], dtype=complex128), array([], dtype=float64), 1, array([7.36332353e+13, 3.23101864e+15, 3.30547211e+15, 3.37828511e+15,\n",
" 4.62171023e+15, 4.72583689e+15, 6.53567051e+15, 6.60971390e+15]), []), (133333.33333333334, array([], dtype=complex128), array([], dtype=float64), 1, array([2.62975840e+13, 3.27835429e+15, 3.30475651e+15, 3.33094946e+15,\n",
" 4.65492544e+15, 4.69211554e+15, 6.58300616e+15, 6.60935606e+15]), []), (-293333.3333333333, array([3.30517599e+15-1112660.64916992j]), array([0.14959926]), 3, array([5.78546849e+13, 3.24679719e+15, 3.30515827e+15, 3.36250656e+15,\n",
" 4.63275469e+15, 4.71457043e+15, 6.55144906e+15, 6.60955696e+15,\n",
" 6.66715843e+15, 7.33772504e+15, 7.36373465e+15, 7.41548018e+15,\n",
" 7.44121801e+15, 9.30614747e+15, 9.38796557e+15, 9.85610093e+15,\n",
" 9.91412443e+15, 9.97181030e+15, 1.03953571e+16, 1.04320759e+16,\n",
" 1.04686659e+16, 1.05051285e+16, 1.31607528e+16, 1.32187341e+16]), [None]), (-186666.66666666666, array([3.30485388e+15+4.66629553e+09j, 3.30484930e+15-7.25032353e+08j,\n",
" 3.30485218e+15-5.60888939e+08j]), array([0.37812244, 0.30679969, 0.30683937]), -3, array([3.68166176e+13, 3.26783525e+15, 3.30485695e+15, 3.34146849e+15,\n",
" 4.64752313e+15, 4.69958888e+15, 6.57248713e+15, 6.60940629e+15,\n",
" 6.64612036e+15, 7.35651487e+15, 7.37303487e+15, 7.40596433e+15,\n",
" 7.42237427e+15, 9.32097007e+15, 9.37303643e+15, 9.87713900e+15,\n",
" 9.91402398e+15, 9.95077224e+15, 1.04153060e+16, 1.04386428e+16,\n",
" 1.04619275e+16, 1.04851606e+16, 1.31817909e+16, 1.32186588e+16]), [None, None, None])]\n"
]
}
],
"source": [
"print (plotdata)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}