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bastonerobastonero
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Spotting the infamous bug
The `self.init()` wasn't called, and it was messing up the minimization.
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‎Examples/sscha_and_aiida/clean_runs.sh‎

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rm *.pdf
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rm otf_run*
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rm input_tmp.in
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rm log*

‎Examples/sscha_and_aiida/debug.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"\n",
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"plt.rcParams.update({\n",
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" 'text.usetex': False,\n",
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" # 'text.latex.preamble': r'\\usepackage{sansmath} \\sansmath',\n",
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" 'pdf.fonttype':42,\n",
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" 'font.family':'sans-serif',\n",
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" 'font.sans-serif':'Arial',\n",
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" 'font.size':14,\n",
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" 'mathtext.fontset': 'stixsans',\n",
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"})"
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"e1 = np.load('./ensembles_P0_T0/energies_pop1.npy')\n",
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"e1_ref = np.load('./ensembles_P0_T0_flare/energies_pop1.npy')"
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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": 8,
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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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"array([1.43868396e-05, 1.43867750e-05, 1.43880794e-05, 1.43880354e-05,\n",
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" 1.43876365e-05, 1.43876491e-05, 1.43881572e-05, 1.43880628e-05,\n",
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" 1.43881299e-05, 1.43880515e-05, 1.43883702e-05, 1.43884091e-05,\n",
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" 1.43877871e-05, 1.43878373e-05, 1.43874900e-05, 1.43878636e-05,\n",
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" 1.43875186e-05, 1.43875482e-05, 1.43883338e-05, 1.43881900e-05,\n",
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" 1.43863038e-05, 1.43861772e-05, 1.43872463e-05, 1.43872393e-05,\n",
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" 1.43875951e-05, 1.43876925e-05, 1.43882204e-05, 1.43884404e-05,\n",
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" 1.43877097e-05, 1.43877564e-05, 1.43874619e-05, 1.43873153e-05,\n",
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" 1.43875307e-05, 1.43875338e-05, 1.43885549e-05, 1.43885293e-05,\n",
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" 1.43879409e-05, 1.43879718e-05, 1.43876421e-05, 1.43876900e-05,\n",
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" 1.43871590e-05, 1.43871877e-05, 1.43885125e-05, 1.43885110e-05,\n",
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" 1.43882812e-05, 1.43883588e-05, 1.43880605e-05, 1.43880690e-05,\n",
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" 1.43875240e-05, 1.43878062e-05])"
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]
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},
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"execution_count": 8,
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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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"e1-e1_ref"
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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": 14,
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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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"0.0"
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]
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},
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"execution_count": 14,
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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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"np.abs(e1-e1_ref).max()"
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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": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"e1 = np.load('./ensembles_P0_T0/xats_pop1.npy')\n",
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"e1_ref = np.load('./ensembles_P0_T0_flare/xats_pop1.npy')"
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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": 16,
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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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"0.0"
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]
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},
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"execution_count": 16,
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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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"np.abs(e1-e1_ref).max()"
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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": 17,
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"metadata": {},
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"outputs": [],
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"source": [
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"f1 = np.load('./ensembles_P0_T0/forces_pop1.npy')\n",
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"f1_ref = np.load('./ensembles_P0_T0_flare/forces_pop1.npy')"
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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": 18,
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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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"1.1266246074947972e-08"
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]
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},
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"execution_count": 18,
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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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"np.abs(f1-f1_ref).max()"
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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": 19,
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"metadata": {},
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"outputs": [],
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"source": [
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"f1 = np.load('./ensembles_P0_T0/stresses_pop1.npy')\n",
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"f1_ref = np.load('./ensembles_P0_T0_flare/stresses_pop1.npy')"
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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": 20,
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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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"1.0972052829011716e-11"
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},
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"execution_count": 20,
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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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"np.abs(f1-f1_ref).max()"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.9.16 ('aiida-sscha')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.16"
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "dbf713cbd6c5cb781e360dd03dc580f1c4e0f3272ba8f8d2e6f58f9ae4ed7519"
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"nbformat": 4,
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"nbformat_minor": 2
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}

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