csiborgtools/scripts_plots/paper_environment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "from os.path import join\n",
    "\n",
    "import csiborgtools\n",
    "import healpy\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy\n",
    "import scienceplots  # noqa\n",
    "from cache_to_disk import cache_to_disk, delete_disk_caches_for_function\n",
    "from h5py import File\n",
    "\n",
    "import plt_utils\n",
    "\n",
    "\n",
    "sim2boxsize = {\"csiborg\" : 677.7,\n",
    "               \"csiborg2_main\": 676.7,\n",
    "               \"BORG\": 677.7,\n",
    "               }\n",
    "\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "with File(\"/mnt/zfsusers/hdesmond/BORG_final/mcmc_9844.h5\", 'r') as f:\n",
    "    d = f[\"scalars/BORG_final_density\"][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.0"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "@cache_to_disk(30)\n",
    "def _plot_sky_projected_density(nsim, simname, grid, nside, MAS=\"PCS\",\n",
    "                                dmin=0, dmax=220, volume_weight=True):\n",
    "    paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)\n",
    "    # nsnap = max(paths.get_snapshots(nsim, simname))\n",
    "    # Some work here to get the box\n",
    "    boxsize = sim2boxsize[simname]\n",
    "\n",
    "    if simname == \"csiborg\":\n",
    "        field = numpy.load(paths.field(\"density\", MAS, grid, nsim, in_rsp=False))\n",
    "    elif simname == \"BORG\":\n",
    "        with File(\"/mnt/zfsusers/hdesmond/BORG_final/mcmc_9844.h5\", 'r') as f:\n",
    "            field = f[\"scalars/BORG_final_density\"][:]\n",
    "            field = field.astype(numpy.float32)\n",
    "            # field = field.T\n",
    "            field += 1\n",
    "    else:\n",
    "        with File(\"/mnt/extraspace/rstiskalek/csiborg2_main/fields/chain_15517_1024.hdf5\", 'r') as f:\n",
    "            field = f[\"density\"][:].T\n",
    "\n",
    "    # field /= numpy.mean(field)\n",
    "    # field += 1\n",
    "\n",
    "    angpos = csiborgtools.field.nside2radec(nside)\n",
    "    dist = numpy.linspace(dmin, dmax, 1000)\n",
    "    return csiborgtools.field.make_sky(field, angpos=angpos, dist=dist,\n",
    "                                       boxsize=boxsize, volume_weight=volume_weight)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_sky_projected_density(nsim, simname, grid, nside, MAS=\"PCS\",\n",
    "                               dmin=0, dmax=220, volume_weight=True, ext=\"png\",\n",
    "                               to_save=False):\n",
    "    dmap = _plot_sky_projected_density(nsim, simname, grid, nside, MAS,\n",
    "                                           dmin, dmax, volume_weight)\n",
    "    obs = numpy.genfromtxt(\"/mnt/zfsusers/rstiskalek/csiborgtools/data/2MPP.txt\")\n",
    "    \n",
    "    dist = obs[:, 6] * 3e5 / 100\n",
    "    \n",
    "    mask = (dist > dmin) & (dist < dmax)\n",
    "    obs = obs[mask]\n",
    "\n",
    "    print(obs[:, 2].min(), obs[:, 2].max())\n",
    "\n",
    "    with plt.style.context(plt_utils.mplstyle):\n",
    "        healpy.mollview(numpy.log10(dmap), fig=0, title=\"\", unit=\"\", rot=75)\n",
    "\n",
    "        healpy.projscatter(numpy.pi / 2 - obs[:, 2], obs[:, 1], s=0.05, c=\"red\",\n",
    "                           label=\"2M++ galaxies\")\n",
    "        \n",
    "        # for name in [\"Virgo\", \"Fornax\"]:\n",
    "        #     d, ra, dec = csiborgtools.clusters[name].spherical_pos\n",
    "        #     ra *= numpy.pi / 180\n",
    "        #     dec *= numpy.pi / 180\n",
    "        #     healpy.projscatter([numpy.pi / 2 - dec], [ra], s=30, c=\"black\", marker='x')\n",
    "        # healpy.projscatter(obs[:, 2] - numpy.pi / 2, obs[:, 1], s=0.25, c=\"red\",\n",
    "                        #    label=\"2M++ galaxies\")\n",
    "        # healpy.projscatter(obs[:, 2] - numpy.pi / 2 , obs[:, 1], s=1, c=\"red\",\n",
    "                        #    label=\"2M++ galaxies\")\n",
    "\n",
    "        # if plot_groups:\n",
    "        #     groups = csiborgtools.read.TwoMPPGroups(fpath=\"/mnt/extraspace/rstiskalek/catalogs/2M++_group_catalog.dat\")  # noqa\n",
    "        #     healpy.projscatter(numpy.deg2rad(groups[\"DEC\"] + 90),\n",
    "        #                        numpy.deg2rad(groups[\"RA\"]), s=1, c=\"blue\",\n",
    "        #                        label=\"2M++ groups\")\n",
    "\n",
    "        # if plot_halos is not None or plot_groups:\n",
    "        #     plt.legend(markerscale=5)\n",
    "\n",
    "        if to_save:\n",
    "            # fout = join(plt_utils.fout, f\"sky_density_{simname}_{nsim}_from_{dmin}_to_{dmax}_vol{volume_weight}.{ext}\")  # noqa\n",
    "            fout = \"test.png\"\n",
    "            print(f\"Saving to `{fout}`.\")\n",
    "            plt.savefig(fout, dpi=plt_utils.dpi, bbox_inches=\"tight\")\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3145728/3145728 [06:06<00:00, 8572.34it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-1.50601 1.48367\n",
      "Saving to `test.png`.\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 850x540 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# delete_disk_caches_for_function(\"_plot_sky_projected_density\")\n",
    "plot_sky_projected_density(15517, \"csiborg2_main\", 512, 512, \"PCS\", dmin=100,\n",
    "                           dmax=125, volume_weight=True, to_save=True)\n",
    "# plt.savefig(\"test.png\", dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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"
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 },
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}