456 lines
97 KiB
Plaintext
456 lines
97 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"examples_dir = '/home/mmn/repo/qpms-article/lepaper/figs/examples/' # prefix where the data is located"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 78,
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"metadata": {},
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"outputs": [],
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"source": [
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"from matplotlib import pyplot as plt\n",
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"from scipy.constants import elementary_charge, hbar\n",
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"from scipy.interpolate import griddata\n",
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"eh = elementary_charge/hbar\n",
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"import numpy as np\n",
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"import os\n",
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"import glob\n",
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"import matplotlib\n",
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"matplotlib.use('pdf')\n",
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"\n",
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"D4h_irlabels = {\"B2''\":\"$B_2''$\",\n",
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" \"B2'\":\"$B_2'$\",\n",
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" \"A1''\":\"$A_1''$\",\n",
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" \"A1'\":\"$A_1'$\",\n",
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" \"A2''\":\"$A_2''$\",\n",
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" \"B1''\":\"$B_1''$\",\n",
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" \"A2'\":\"$A_2'$\", \n",
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" \"B1'\":\"$B_1'$\",\n",
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" \"E'\":\"$E'$\",\n",
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" \"E''\":\"$E''$\",}\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.0075_0.0075)π_ψ0π_χ0π_f2.11–2.23eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/inf_big_px.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_50x50_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_40x40_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.075_0.075)π_ψ0π_χ0π_f2.11–2.23eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_70x70_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/40x400.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_50x50_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.0025_0.0025)π_ψ0.5π_χ0π_f2.19eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/40x401.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.0025_0.0025)π_ψ0.5π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/30x30_psi0.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_40x40_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.0025_0.0025)π_ψ0π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.0025_0.0025)π_ψ0π_χ0π_f2.19eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.16eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/30x30_psi1.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_40x40_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/inf.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/40x40_psi1.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.075_0.075)π_ψ0.5π_χ0π_f2.11–2.23eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.0025_0.0025)π_ψ0.5π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.0075_0.0075)π_ψ0.5π_χ0π_f2.11–2.23eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_40x40_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/5x5.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_70x70_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0.5π_χ0π_f2.15eV_L2.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/100x100.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/140x100.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/40x40_psi0.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_mAg_bg1.52_φ0_θ(-0.0025_0.0025)π_ψ0π_χ0π_f2.15eV_L3.npz',\n",
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" '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/cyl_r30nm_h30nm_p375nmx375nm_20x20_mAg_bg1.52_φ0π_θ(-0.025_0.025)π_ψ0π_χ0π_f2.16eV_L3.npz']"
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]
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},
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cd = os.path.join(examples_dir, \"rectangular/scattering\")\n",
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"glob.glob(cd + '/*.npz')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['meta',\n",
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" 'dir_sph',\n",
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" 'k_cart',\n",
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" 'omega',\n",
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" 'E_cart',\n",
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" 'wavenumbers',\n",
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" 'σ_ext',\n",
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" 'σ_abs',\n",
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" 'σ_scat',\n",
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" 'unitcell_area']"
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]
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},
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"execution_count": 48,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"#f_finite_mesh = '/home/mmn/repo/qpms-article/lepaper/figs/examples/rectangular/scattering/40x40_psi1.npz'\n",
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"f_mesh_y = '/home/mmn/repo/qpms/examples/rectangular/scattering/inf.npz'\n",
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"f_mesh_x = '/home/mmn/repo/qpms/examples/rectangular/scattering/inf_big_px.npz'\n",
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"data_y = np.load(f_mesh_y)\n",
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"data_x = np.load(f_mesh_x)\n",
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"list(data_x.keys())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 107,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(8.798339185764132e-14, 3.7485521428797764e-17)"
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]
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},
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"execution_count": 107,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sigmas = [[data_y[s], data_x[s]] for s in ['σ_scat','σ_abs','σ_ext']]\n",
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"omegas = [data_y['omega'], data_x['omega']]\n",
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"kxs = [data_y['k_cart'][:,:,0], data_x['k_cart'][:,:,0]]\n",
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"# for colorbar range\n",
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"#maxsigma = max(np.amax(sigmas[2][0]), np.amax(sigmas[2][1]))\n",
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"#minsigma = min(min(np.amin(sigmas[l][0]), np.amin(sigmas[l][1])) for l in range(3))\n",
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"maxsigma = max(np.quantile(sigmas[2][0], 0.999), np.quantile(sigmas[2][1], 0.999))\n",
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"minsigma = min(min(np.quantile(sigmas[l][0], 0.001), np.quantile(sigmas[l][0], 0.001)) for l in range(3))\n",
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"maxsigma, minsigma\n",
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"\n",
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"# manual ranges\n",
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"omegamin = 2.09 * eh\n",
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"omegamax = 2.24 * eh\n",
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"kmin = -0.6e6\n",
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"kmax = 0.6e6\n",
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"\n",
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"imshow_extent = (kmin / 1e6, kmax / 1e6, omegamin / eh, omegamax/eh) \n",
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"maxsigma, minsigma"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 135,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x360 with 7 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"%matplotlib inline\n",
|
||
"ipm = \"nearest\" # interpolation method for griddata\n",
|
||
"f, ax = plt.subplots(3,2, figsize=(6,5))\n",
|
||
"#ax[0,0].set_title(\"TE\")\n",
|
||
"#ax[0,1].set_title(\"TM\")\n",
|
||
"ax[0,0].set_title(\"$y$ polarisation\")\n",
|
||
"ax[0,1].set_title(\"$x\\,(z)$ polarisation\")\n",
|
||
"for l in (0,1):\n",
|
||
" for c in (0,1):\n",
|
||
" ax[l,c].tick_params(labelbottom=False)\n",
|
||
"for l in range(3):\n",
|
||
" ax[l,1].tick_params(labelleft=False)\n",
|
||
"\n",
|
||
"\n",
|
||
"for c in (0,1):\n",
|
||
" ax[2,c].set_xlabel('$k_x/\\mathrm{\\mu m^{-1}}$')\n",
|
||
" \n",
|
||
" om = omegas[c]\n",
|
||
" dom = np.amin(np.diff(om)) / 2 # It should be equidistant, but...\n",
|
||
" kx = kxs[c]\n",
|
||
" dkx = np.amin(np.diff(kx)) / 2\n",
|
||
" #grid_y, grid_x = np.mgrid[om[0]:om[-1]:dom, np.amax(kx[:,0]) : np.amin(kx[:,-1]) : dkx]\n",
|
||
" grid_y, grid_x = np.mgrid[omegamin:omegamax:dom, kmin : kmax : dkx]\n",
|
||
" \n",
|
||
" # source points for griddata\n",
|
||
" ompoints = np.broadcast_to(om[:,None], kx.shape)\n",
|
||
" points = np.stack((kx.flatten(), ompoints.flatten()), axis=-1)\n",
|
||
" \n",
|
||
" for l in range(3):\n",
|
||
" grid_z = griddata(points, sigmas[l][c].flatten(), (grid_x, grid_y), method=ipm) / 1e-12 # square micrometers\n",
|
||
" im = ax[l,c].imshow(grid_z, origin='lower', vmin=0, vmax=maxsigma/1e-12, extent=imshow_extent,\n",
|
||
" aspect='auto', interpolation='none')\n",
|
||
" \n",
|
||
" # manual xticks, so they are the same as in the Beyn mode image\n",
|
||
" #ax[l,c].set_xticks(np.arange(-0.6,0.7,0.2))\n",
|
||
"cax = f.add_axes([0.83, 0.15, 0.05, 0.7])\n",
|
||
"plt.subplots_adjust(right = 0.78, left=0.12, wspace=0.15, hspace=0.15)\n",
|
||
"cbar = f.colorbar(im, cax=cax)\n",
|
||
"cbar.set_label('$\\sigma / \\mathrm{\\mu m^2}$')\n",
|
||
" \n",
|
||
" \n",
|
||
" \n",
|
||
" \n",
|
||
" \n",
|
||
"for l, txt in enumerate(['$\\\\sigma_\\\\mathrm{scat}$','$\\\\sigma_\\\\mathrm{abs}$','$\\\\sigma_\\\\mathrm{ext}$']):\n",
|
||
" for i in (0,1):\n",
|
||
" ax[l,i].text(0.02, 0.95,txt,\n",
|
||
" color='white',\n",
|
||
" horizontalalignment='left',\n",
|
||
" verticalalignment='top',\n",
|
||
" transform = ax[l,i].transAxes)\n",
|
||
" ax[l,0].set_ylabel('$\\hbar\\omega / \\mathrm{eV}$')\n",
|
||
"\n",
|
||
"plt.savefig(\"sqlat_inf_scatter.pdf\")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 85,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(150, 201)"
|
||
]
|
||
},
|
||
"execution_count": 85,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"kx.shape"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 65,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(150, 201, 3)"
|
||
]
|
||
},
|
||
"execution_count": 65,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"data_y['k_cart'].shape"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 76,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([[6045.26556378, 6045.35790435, 6045.44931265, ..., 6045.44931265,\n",
|
||
" 6045.35790435, 6045.26556378],\n",
|
||
" [6050.13423404, 6050.22664897, 6050.31813089, ..., 6050.31813089,\n",
|
||
" 6050.22664897, 6050.13423404],\n",
|
||
" [6055.00290429, 6055.09539359, 6055.18694913, ..., 6055.18694913,\n",
|
||
" 6055.09539359, 6055.00290429],\n",
|
||
" ...,\n",
|
||
" [6760.96009093, 6761.06336363, 6761.16559369, ..., 6761.16559369,\n",
|
||
" 6761.06336363, 6760.96009093],\n",
|
||
" [6765.82876118, 6765.93210825, 6766.03441193, ..., 6766.03441193,\n",
|
||
" 6765.93210825, 6765.82876118],\n",
|
||
" [6770.69743144, 6770.80085288, 6770.90323017, ..., 6770.90323017,\n",
|
||
" 6770.80085288, 6770.69743144]])"
|
||
]
|
||
},
|
||
"execution_count": 76,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.diff(data_y['k_cart'][:,:,0])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 82,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([-604832.84966793, -605319.96337236, -605807.07707679,\n",
|
||
" -606294.19078123, -606781.30448566, -607268.41819009,\n",
|
||
" -607755.53189452, -608242.64559895, -608729.75930338,\n",
|
||
" -609216.87300781, -609703.98671224, -610191.10041667,\n",
|
||
" -610678.2141211 , -611165.32782553, -611652.44152996,\n",
|
||
" -612139.55523439, -612626.66893882, -613113.78264325,\n",
|
||
" -613600.89634768, -614088.01005211, -614575.12375654,\n",
|
||
" -615062.23746098, -615549.35116541, -616036.46486984,\n",
|
||
" -616523.57857427, -617010.6922787 , -617497.80598313,\n",
|
||
" -617984.91968756, -618472.03339199, -618959.14709642,\n",
|
||
" -619446.26080085, -619933.37450528, -620420.48820971,\n",
|
||
" -620907.60191414, -621394.71561857, -621881.829323 ,\n",
|
||
" -622368.94302743, -622856.05673186, -623343.17043629,\n",
|
||
" -623830.28414073, -624317.39784516, -624804.51154959,\n",
|
||
" -625291.62525402, -625778.73895845, -626265.85266288,\n",
|
||
" -626752.96636731, -627240.08007174, -627727.19377617,\n",
|
||
" -628214.3074806 , -628701.42118503, -629188.53488946,\n",
|
||
" -629675.64859389, -630162.76229832, -630649.87600275,\n",
|
||
" -631136.98970718, -631624.10341161, -632111.21711604,\n",
|
||
" -632598.33082047, -633085.44452491, -633572.55822934,\n",
|
||
" -634059.67193377, -634546.7856382 , -635033.89934263,\n",
|
||
" -635521.01304706, -636008.12675149, -636495.24045592,\n",
|
||
" -636982.35416035, -637469.46786478, -637956.58156921,\n",
|
||
" -638443.69527364, -638930.80897807, -639417.9226825 ,\n",
|
||
" -639905.03638693, -640392.15009136, -640879.26379579,\n",
|
||
" -641366.37750022, -641853.49120466, -642340.60490909,\n",
|
||
" -642827.71861352, -643314.83231795, -643801.94602238,\n",
|
||
" -644289.05972681, -644776.17343124, -645263.28713567,\n",
|
||
" -645750.4008401 , -646237.51454453, -646724.62824896,\n",
|
||
" -647211.74195339, -647698.85565782, -648185.96936225,\n",
|
||
" -648673.08306668, -649160.19677111, -649647.31047554,\n",
|
||
" -650134.42417997, -650621.53788441, -651108.65158884,\n",
|
||
" -651595.76529327, -652082.8789977 , -652569.99270213,\n",
|
||
" -653057.10640656, -653544.22011099, -654031.33381542,\n",
|
||
" -654518.44751985, -655005.56122428, -655492.67492871,\n",
|
||
" -655979.78863314, -656466.90233757, -656954.016042 ,\n",
|
||
" -657441.12974643, -657928.24345086, -658415.35715529,\n",
|
||
" -658902.47085972, -659389.58456416, -659876.69826859,\n",
|
||
" -660363.81197302, -660850.92567745, -661338.03938188,\n",
|
||
" -661825.15308631, -662312.26679074, -662799.38049517,\n",
|
||
" -663286.4941996 , -663773.60790403, -664260.72160846,\n",
|
||
" -664747.83531289, -665234.94901732, -665722.06272175,\n",
|
||
" -666209.17642618, -666696.29013061, -667183.40383504,\n",
|
||
" -667670.51753947, -668157.63124391, -668644.74494834,\n",
|
||
" -669131.85865277, -669618.9723572 , -670106.08606163,\n",
|
||
" -670593.19976606, -671080.31347049, -671567.42717492,\n",
|
||
" -672054.54087935, -672541.65458378, -673028.76828821,\n",
|
||
" -673515.88199264, -674002.99569707, -674490.1094015 ,\n",
|
||
" -674977.22310593, -675464.33681036, -675951.45051479,\n",
|
||
" -676438.56421922, -676925.67792366, -677412.79162809])"
|
||
]
|
||
},
|
||
"execution_count": 82,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"data_y['k_cart'][:,0,0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 79,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"(150,)"
|
||
]
|
||
},
|
||
"execution_count": 79,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"omegas[0].shape"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 114,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"'/home/mmn'"
|
||
]
|
||
},
|
||
"execution_count": 114,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import os\n",
|
||
"os.getcwd()"
|
||
]
|
||
},
|
||
{
|
||
"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": "3.7.3"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|