csiborgtools/notebooks/flow/process_upglade.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Copyright (C) 2024 Richard Stiskalek\n",
"# This program is free software; you can redistribute it and/or modify it\n",
"# under the terms of the GNU General Public License as published by the\n",
"# Free Software Foundation; either version 3 of the License, or (at your\n",
"# option) any later version.\n",
"#\n",
"# This program is distributed in the hope that it will be useful, but\n",
"# WITHOUT ANY WARRANTY; without even the implied warranty of\n",
"# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General\n",
"# Public License for more details.\n",
"#\n",
"# You should have received a copy of the GNU General Public License along\n",
"# with this program; if not, write to the Free Software Foundation, Inc.,\n",
"# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from h5py import File\n",
"from astropy.cosmology import FlatLambdaCDM\n",
"\n",
"import csiborgtools\n",
"\n",
"SPEED_OF_LIGHT = 299792.458 # km / s\n",
"\n",
"\n",
"%load_ext autoreload\n",
"%autoreload 2\n",
"%matplotlib inline\n",
"\n",
"paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Read in upGLADE\n",
"\n",
"- Mask out galaxies with bad redshifts\n",
"- Convert heliocentric redshifts to the CMB frame."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Initially, we have 3313157 objects.\n",
"Masking 1174652 objects that have `e_zhelio` < 0 or `zhelio` < 0.\n",
"Masking 1714681 objects that have `e_zhelio` / `zhelio` > 0.1.\n",
"Finally, we have 423824 objects.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_2891959/606063485.py:16: RuntimeWarning: divide by zero encountered in divide\n",
" mask = (data[\"e_zhelio\"] / data[\"zhelio\"] > 0.1) | (data[\"e_zhelio\"] > 0.1) #& ~np.isnan(data[\"zhelio\"])\n"
]
}
],
"source": [
"fname = \"/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all.h5\"\n",
"data = {}\n",
"with File(fname, \"r\") as f:\n",
" for i, key in enumerate([\"RA\", \"dec\", \"zhelio\", \"e_zhelio\"]):\n",
" data[key] = f[\"data\"][\"block0_values\"][:, i]\n",
"data[\"DEC\"] = data.pop(\"dec\")\n",
"\n",
"print(f\"Initially, we have {data['zhelio'].size} objects.\")\n",
"\n",
"# Ask about this\n",
"mask = (data[\"e_zhelio\"] < 0) | (data[\"zhelio\"] < 0)\n",
"print(f\"Masking {mask.sum()} objects that have `e_zhelio` < 0 or `zhelio` < 0.\")\n",
"for key in data.keys():\n",
" data[key][mask] = np.nan\n",
"\n",
"mask = (data[\"e_zhelio\"] / data[\"zhelio\"] > 0.1) | (data[\"e_zhelio\"] > 0.1) #& ~np.isnan(data[\"zhelio\"])\n",
"print(f\"Masking {mask.sum()} objects that have `e_zhelio` / `zhelio` > 0.1.\")\n",
"for key in data.keys():\n",
" data[key][mask] = np.nan\n",
"\n",
"print(f\"Finally, we have {np.sum(np.isfinite(data['zhelio']))} objects.\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.scatter(data[\"zhelio\"], data[\"e_zhelio\"], s=0.1)\n",
"\n",
"plt.yscale(\"log\")\n",
"plt.xscale(\"log\")\n",
"plt.xlabel(r\"$z_{\\rm helio}$\")\n",
"plt.ylabel(r\"$\\sigma_{z_{\\rm helio}}$\")\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Masking 10510 objects that have `zcmb` > 0.06.\n",
"Finally, we have 413314 objects.\n"
]
}
],
"source": [
"zcmb, e_zcmb = csiborgtools.heliocentric_to_cmb(data[\"zhelio\"], data[\"RA\"], data[\"DEC\"], data[\"e_zhelio\"])\n",
"data[\"zcmb\"] = zcmb\n",
"data[\"e_zcmb\"] = e_zcmb\n",
"\n",
"\n",
"mask = (data[\"zcmb\"] > 0.06) #& ~np.isnan(data[\"zhelio\"])\n",
"print(f\"Masking {mask.sum()} objects that have `zcmb` > 0.06.\")\n",
"for key in data.keys():\n",
" data[key][mask] = np.nan\n",
"\n",
"print(f\"Finally, we have {np.sum(np.isfinite(data['zhelio']))} objects.\")"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAnYAAAHVCAYAAAB8NLYkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9eazs6V3f+75/81Rz1Zr32vPueXS73W5jMJzjezv3ck7U9yaRITeYWFaASDGYBlmYgE0iIiOICXJAsoiUEEVCWA4KigjpHMskHLCb9tDddrd72PNe81Bz/ebpuX/8ai13Q+Pg4N5ubz8vqdR71frVqmEtyR8/z/P9fhUhhECSJEmSJEn6jqd+u1+AJEmSJEmS9K0hg50kSZIkSdItQgY7SZIkSZKkW4QMdpIkSZIkSbcIGewkSZIkSZJuETLYSZIkSZIk3SJksJMkSZIkSbpFyGAnSZIkSZJ0i5DBTpIkSZIk6RYhg50kSZIkSdIt4k0V7H7rt36L06dPY9s2jzzyCF/4whe+4fWf/vSnueOOO7Btm3vvvZc/+qM/es33hRB85CMfYWVlBcdxePe7382lS5f+0s/5L//lv/DII4/gOA7tdpvHH3/8W/m2JEmSJEmSboo3TbD71Kc+xRNPPMFHP/pRnnnmGe6//34ee+wxDg4OXvf6z3/+8/zwD/8w73//+3n22Wd5/PHHefzxx3nhhReOr/nVX/1VPvGJT/DJT36Sp59+Gs/zeOyxx4jj+Pia3//93+dHfuRHeN/73sdXvvIVPve5z/H3//7ff8PfryRJkiRJ0reaIoQQ3+4XAfDII4/w8MMP85u/+ZsAlGXJ+vo6H/jAB/i5n/u5v3T9e97zHoIg4A//8A+P73v729/OAw88wCc/+UmEEKyurvIzP/Mz/OzP/iwAk8mEpaUlfud3focf+qEfIs9zTp8+zT/7Z/+M97///X+t15kkCUmSHH9dliXD4ZBut4uiKH+Tj0CSJEmSpFuUEILZbMbq6iqq+gauq4k3gSRJhKZp4j/9p//0mvvf+973ir/9t//26z5mfX1d/Kt/9a9ec99HPvIRcd999wkhhLhy5YoAxLPPPvuaa77v+75P/ORP/qQQQoinn35aAOLf/tt/Kx544AGxvLws/tbf+lvi+eef/ytf60c/+lEByJu8yZu8yZu8yZu8fdO3zc3Nby4kfZN03gT6/T5FUbC0tPSa+5eWlnj55Zdf9zF7e3uve/3e3t7x94/u+6uuuXr1KgC/9Eu/xK//+q9z+vRpPv7xj/P93//9XLx4kU6n85ee98Mf/jBPPPHE8deTyYSTJ0+yublJo9H4Zt62JEmSJEnfJabTKevr69Tr9Tf0ed4Uwe7bpSxLAP7pP/2n/J2/83cA+Hf/7t9x4sQJPv3pT/PjP/7jf+kxlmVhWdZfur/RaMhgJ0mSJEnSN/RGH9t6UxRP9Ho9NE1jf3//Nffv7++zvLz8uo9ZXl7+htcf/fcbXbOysgLAXXfddfx9y7I4e/YsGxsbf4N3JEmSJEmSdPO9KYKdaZo89NBDfPaznz2+ryxLPvvZz/Loo4++7mMeffTR11wP8JnPfOb4+jNnzrC8vPyaa6bTKU8//fTxNQ899BCWZfHKK68cX5NlGdevX+fUqVPfsvcnSZIkSZJ0M7xptmKfeOIJfvRHf5S3vvWtvO1tb+M3fuM3CIKA973vfQC8973vZW1tjY997GMA/NRP/RTvete7+PjHP84P/uAP8nu/93t86Utf4rd/+7eBaqnzgx/8IL/8y7/MhQsXOHPmDL/4i7/I6urqcZ+6RqPBT/zET/DRj36U9fV1Tp06xa/92q8B8Pf+3t+7+R+CJEmSJEnS38CbJti95z3v4fDwkI985CPs7e3xwAMP8OSTTx4XP2xsbLymPPgd73gHv/u7v8sv/MIv8PM///NcuHCBP/iDP+Cee+45vuZDH/oQQRDwYz/2Y4zHY975znfy5JNPYtv28TW/9mu/hq7r/MiP/AhRFPHII4/wx3/8x7Tb7Zv35iVJkiRJkr4F3jR97L5TTadTms0mk8lEFk9IkiRJkvS6blZeeFOcsZMkSZIkSZL+5mSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4RMthJkiRJkiTdImSwkyRJkiRJukXIYCdJkiRJknSLkMFOkiRJkiTpFiGDnSRJkiRJ0i1CBjtJkiRJkqRbhAx2kiRJkiRJtwgZ7CRJkiRJkm4Rb6pg91u/9VucPn0a27Z55JFH+MIXvvANr//0pz/NHXfcgW3b3HvvvfzRH/3Ra74vhOAjH/kIKysrOI7Du9/9bi5duvSaa06fPo2iKK+5/cqv/Mq3/L1JkiRJkiS90d40we5Tn/oUTzzxBB/96Ed55plnuP/++3nsscc4ODh43es///nP88M//MO8//3v59lnn+Xxxx/n8ccf54UXXji+5ld/9Vf5xCc+wSc/+UmefvppPM/jscceI47j1/ysf/7P/zm7u7vHtw984ANv6HuVJEmSJEl6IyhCCPHtfhEAjzzyCA8//DC/+Zu/CUBZlqyvr/OBD3yAn/u5n/tL17/nPe8hCAL+8A//8Pi+t7/97TzwwAN88pOfRAjB6uoqP/MzP8PP/uzPAjCZTFhaWuJ3fud3+KEf+iGgWrH74Ac/yAc/+MG/1utMkoQkSY6/nk6nrK+vM5lMaDQa/6tvX5IkSZKkW9h0OqXZbL7heeFNsWKXpilf/vKXefe73318n6qqvPvd7+app5563cc89dRTr7ke4LHHHju+/tq1a+zt7b3mmmazySOPPPKXfuav/Mqv0O12efDBB/m1X/s18jz/K1/rxz72MZrN5vFtfX39m36/kiRJkiTd+oQQBEnOzVxD02/aM30D/X6foihYWlp6zf1LS0u8/PLLr/uYvb29171+b2/v+PtH9/1V1wD85E/+JG95y1vodDp8/vOf58Mf/jC7u7v8+q//+us+74c//GGeeOKJ46+PVuwkSZIkSfruI4QgTAscQyVMCwA8S0dRFMK0wDW14/tvhjdFsPt2enVIu++++zBNkx//8R/nYx/7GJZl/aXrLct63fslSZIkSbp1HQU419QAjv8dJNUuX3+W4Fr6a74nhMCPMxRFuWmrdm+Krdher4emaezv77/m/v39fZaXl1/3McvLy9/w+qP/fjM/E6qzfnmec/369W/2bUiSJEmSdIt69eqbH2cEcYYfZ8fbrbbx9Uh1dJ1n6URZiWfpN23V7k0R7EzT5KGHHuKzn/3s8X1lWfLZz36WRx999HUf8+ijj77meoDPfOYzx9efOXOG5eXl11wznU55+umn/8qfCfDcc8+hqiqLi4t/k7ckSZIkSdIt5CisuaZGlBZYusLmMEQIgWfpqKpKzTao2QaKouAYKoezhK5nvGal7432ptmKfeKJJ/jRH/1R3vrWt/K2t72N3/iN3yAIAt73vvcB8N73vpe1tTU+9rG
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"\n",
"plt.scatter(data[\"zcmb\"], data[\"e_zcmb\"], s=0.001)\n",
"plt.xlabel(r\"$z_{\\rm CMB}$\")\n",
"plt.ylabel(r\"$\\sigma_{z_{\\rm CMB}}$\")\n",
"\n",
"plt.xlim(0, 0.05)\n",
"plt.ylim(0, 0.006)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(\"../../plots/UPGLADE_zcmb_vs_ezcmb.png\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Write only masked galaxies to this file, but also save the mask."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Writing 413314 objects to `/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_PROCESSED.h5`.\n"
]
}
],
"source": [
"fname = \"/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_PROCESSED.h5\"\n",
"mask = np.isfinite(data[\"RA\"])\n",
"print(f\"Writing {mask.sum()} objects to `{fname}`.\")\n",
"\n",
"with File(fname, \"w\") as f:\n",
" for key in data.keys():\n",
" f[key] = data[key][mask]\n",
"\n",
" f[\"mask\"] = mask"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Having generated this file, next step is to run `field_los.py` to evaluate the density and velocity field along the LOS of each object that is not masked.\n",
"- Then, the next step is to run `post_upglade.py` to calculate the cosmological redshift of each object in UPGLADE.\n",
" - Based on Carrick2015 samples calibrated against Pantheon+"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Results verification"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fname = \"/mnt/extraspace/rstiskalek/csiborg_postprocessing/peculiar_velocity/UPGLADE/zcosmo_UPGLADE.hdf5\"\n",
"\n",
"with File(fname, \"r\") as f:\n",
" indxs = f[\"indxs\"][:]\n",
" mean_zcosmo = f[\"mean_zcosmo\"][:]\n",
" std_zcosmo = f[\"std_zcosmo\"][:]\n",
"\n",
"\n",
"plt.figure()\n",
"plt.scatter(mean_zcosmo, std_zcosmo, s=0.001)\n",
"\n",
"plt.xlabel(r\"$z_{\\rm cosmo}$\")\n",
"plt.ylabel(r\"$\\sigma_{z_{\\rm cosmo}}$\")\n",
"\n",
"plt.xlim(0, 0.05)\n",
"plt.ylim(0, 0.006)\n",
"plt.tight_layout()\n",
"plt.savefig(\"../../plots/UPGLADE_zcosmo_vs_ezcosmo.png\")\n",
"\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Combine datasets\n",
"i.e. match to the original UPGLADE file"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"data[\"zcosmo\"] = np.zeros_like(data[\"RA\"])\n",
"data[\"zcosmo\"][mask] = mean_zcosmo\n",
"\n",
"data[\"e_zcosmo\"] = np.zeros_like(data[\"RA\"])\n",
"data[\"e_zcosmo\"][mask] = std_zcosmo"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.scatter(data[\"zcmb\"], data[\"zcosmo\"], s=0.01)\n",
"\n",
"plt.xlabel(r\"$z_{\\rm CMB}$\")\n",
"plt.ylabel(r\"$z_{\\rm cosmo}$\")\n",
"plt.xlim(0)\n",
"plt.ylim(0)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(\"../../plots/UPGLADE_zcmb_vs_zcosmo.png\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure()\n",
"plt.scatter(data[\"zcmb\"], (data[\"zcosmo\"] - data[\"zcmb\"]) * SPEED_OF_LIGHT, s=0.001)\n",
"\n",
"plt.xlabel(r\"$z_{\\rm CMB}$\")\n",
"plt.ylabel(r\"$c (z_{\\rm cosmo} - z_{\\rm CMB}) ~ [\\mathrm{km} / \\mathrm{s}]$\")\n",
"plt.xlim(0)\n",
"plt.ylim(-1000, 1000)\n",
"\n",
"plt.tight_layout()\n",
"plt.savefig(\"../../plots/UPGLADE_zcmb_vs_dzcosmo.png\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Save the data\n",
"- In a format matching what Gergely shared."
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'RA': array([0.78773861, 0.62294948, 0.02316041, ..., nan, nan,\n",
" nan]),\n",
" 'zhelio': array([0.02934783, 0.03313865, 0.03167664, ..., nan, nan,\n",
" nan]),\n",
" 'e_zhelio': array([9.929941e-06, 6.920645e-06, 7.919160e-06, ..., nan,\n",
" nan, nan]),\n",
" 'DEC': array([-0.75227238, -0.75948143, -1.21628749, ..., nan,\n",
" nan, nan]),\n",
" 'zcmb': array([0.02812447, 0.03191 , 0.0304483 , ..., nan, nan,\n",
" nan]),\n",
" 'e_zcmb': array([9.91813946e-06, 6.91241472e-06, 7.90973125e-06, ...,\n",
" nan, nan, nan]),\n",
" 'zcosmo': array([0.02811476, 0.03163086, 0.03017893, ..., 0. , 0. ,\n",
" 0. ]),\n",
" 'e_zcosmo': array([0.00078133, 0.0006812 , 0.00069302, ..., 0. , 0. ,\n",
" 0. ])}"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Writing to `/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_WZCOSMO.h5`.\n"
]
}
],
"source": [
"fname = \"/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_WZCOSMO.h5\"\n",
"print(f\"Writing to `{fname}`.\")\n",
"\n",
"with File(fname, \"w\") as f:\n",
" for key in data.keys():\n",
" f[key] = data[key]"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"40M\t/mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_WZCOSMO.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/shared/python/3.11.7/lib/python3.11/pty.py:89: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
" pid, fd = os.forkpty()\n"
]
}
],
"source": [
"!du -h /mnt/users/rstiskalek/csiborgtools/data/upglade_z_0p05_all_WZCOSMO.h5"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "venv_csiborg",
"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": "3.11.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}