csiborgtools/scripts_plots/borg_acl.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy\n",
    "import scienceplots\n",
    "from h5py import File\n",
    "\n",
    "import plt_utils\n",
    "\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "with File(\"/mnt/extraspace/rstiskalek/csiborg_postprocessing/ACL/BORG2_0.25.hdf5\", 'r') as f:\n",
    "    voxel_acl = f['voxel_acl'][...].flatten()\n",
    "    voxel_dist = f['voxel_dist'][...].flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = numpy.linspace(0, 100, 10)\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "mask = voxel_dist < 20\n",
    "plt.hist(voxel_acl[mask], bins=\"auto\", histtype='step', density=1, label=r\"$0 < R / (\\mathrm{Mpc} / h)  < 20$\")\n",
    "\n",
    "mask = (voxel_dist > 20) & (voxel_dist < 40)\n",
    "plt.hist(voxel_acl[mask], bins=\"auto\", histtype='step', density=1, label=r\"$20 < R / (\\mathrm{Mpc} / h)  < 40$\")\n",
    "\n",
    "mask = (voxel_dist > 40) & (voxel_dist < 60)\n",
    "plt.hist(voxel_acl[mask], bins=\"auto\", histtype='step', density=1, label=r\"$40 < R / (\\mathrm{Mpc} / h)  < 60$\")\n",
    "\n",
    "# plt.scatter(voxel_dist.flatten(), voxel_acl.flatten(), s=0.1)\n",
    "plt.legend()\n",
    "plt.title(\"ACL of individual voxels\")\n",
    "plt.xlabel(r\"$\\mathrm{ACL}$\")\n",
    "plt.ylabel(r\"Normalized bin counts\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"../plots/BORG_Stephen_ACL.png\", dpi=450)\n",
    "plt.show()"
   ]
  },
  {
   "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
}