csiborgtools/notebooks/perseus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5a38ed25",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-04-12T14:25:46.519408Z",
     "start_time": "2023-04-12T14:25:03.003304Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scienceplots\n",
    "import astroquery\n",
    "from tqdm import trange, tqdm\n",
    "\n",
    "sys.path.append(\"../\")\n",
    "import csiborgtools\n",
    "\n",
    "%matplotlib widget \n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "79919270",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Norma\n",
    "cluster = {\"RA\": (16 + 15 / 60 + 32.8 / 60**2) * 15,\n",
    "           \"DEC\": -60 + 54 / 60 + 30 / 60**2,\n",
    "           \"DIST\": 67.8}\n",
    "\n",
    "Xclust = np.array([cluster[\"DIST\"], cluster[\"RA\"], cluster[\"DEC\"]]).reshape(1, -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "96740b90",
   "metadata": {},
   "outputs": [],
   "source": [
    "paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)\n",
    "nsims = paths.get_ics(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "90033fb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "Xclust = np.array([cluster[\"DIST\"], cluster[\"RA\"], cluster[\"DEC\"]]).reshape(1, -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "194baa83",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 101/101 [00:44<00:00,  2.25it/s]\n"
     ]
    }
   ],
   "source": [
    "matches = np.full(len(nsims), np.nan)\n",
    "\n",
    "for ii in trange(101):\n",
    "    cat = csiborgtools.read.HaloCatalogue(nsims[ii], paths, minmass=('M', 1e13))\n",
    "    dist, ind = cat.angular_neighbours(Xclust, ang_radius=5, rad_tolerance=10)\n",
    "    dist = dist[0]\n",
    "    ind = ind[0]\n",
    "\n",
    "    if ind.size > 0:\n",
    "        matches[ii] = np.max(cat['M'][ind])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "392f6eee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6ff7d5b9dc2f4b3fa6f563ee91f59655",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": "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       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAflklEQVR4nO3df3TV9X348Vf4kcCEBBMlISMBWltjtbAOK6a6ddXMyOH4o6Q/7HGWUk532hOpkLNV6dZST6fB7kxoK2D1ODw7p8zWP7CjntrDsonHs4AYxo6uk1ZrD1hMqG4kiCMw8vn+0a+p0UT5kZub3Pfjcc49x3zuzcfXy+Anz3NzbyjKsiwLAACSMS7fAwAAMLIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYgQgAEBiBCAAQGIEIABAYibke4CxrK+vLw4cOBBTp06NoqKifI8DAJyELMvi8OHDUV1dHePGpflcmAA8AwcOHIiampp8jwEAnIb9+/fHzJkz8z1GXgjAMzB16tSI+O0foNLS0jxPAwCcjJ6enqipqen/Pp4iAXgG3vixb2lpqQAEgDEm5ZdvpfmDbwCAhAlAAIDECEAAgMQIQACAxAhAAIDECEAAgMQIQACAxAhAAIDECEAAgMQIQACAxAhAAIDECEAAgMQIQACAxAhAAIDETMj3AABA7s2+7dF8j3DKfrVmUb5HKFieAQQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEhMwQbgN77xjSgqKhpwq6ur67//6NGj0dzcHBUVFTFlypRoamqKrq6uPE4MADAyCjYAIyIuvPDCePnll/tvTz75ZP99K1eujK1bt8bDDz8c27dvjwMHDsTixYvzOC0AwMiYkO8BcmnChAlRVVX1tuPd3d3xwAMPxObNm+OKK66IiIhNmzbFBRdcEDt27IhLL710pEcFABgxBf0M4C9+8Yuorq6O97znPXHjjTfGvn37IiKio6Mjjh8/Hg0NDf2Prauri9ra2mhvbx/yfL29vdHT0zPgBgAw1hRsAC5YsCAefPDBeOyxx2Ljxo3x4osvxh/90R/F4cOHo7OzM4qLi2PatGkDPqeysjI6OzuHPGdra2uUlZX132pqanK8BQDA8CvYHwEvXLiw/5/nzp0bCxYsiFmzZsUPf/jDmDx58mmdc9WqVdHS0tL/cU9PjwgEAMacgn0G8K2mTZsW73//++P555+PqqqqOHbsWBw6dGjAY7q6ugZ9zeAbSkpKorS0dMANAGCsSSYAX3vttXjhhRdixowZMX/+/Jg4cWK0tbX13793797Yt29f1NfX53FKAIDcK9gfAf/FX/xFXHPNNTFr1qw4cOBArF69OsaPHx+f+cxnoqysLJYtWxYtLS1RXl4epaWlsXz58qivr/cOYACg4BVsAL700kvxmc98Jl599dU499xz4/LLL48dO3bEueeeGxERa9eujXHjxkVTU1P09vZGY2NjbNiwIc9TAwDkXlGWZVm+hxirenp6oqysLLq7u70eEIBRbfZtj+Z7hFP2qzWLcnJe378Teg0gAAC/JQABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABIjAAEAEiMAAQASIwABABKTRACuWbMmioqKYsWKFf3Hjh49Gs3NzVFRURFTpkyJpqam6Orqyt+QAAAjpOADcNeuXfG9730v5s6dO+D4ypUrY+vWrfHwww/H9u3b48CBA7F48eI8TQkAMHIKOgBfe+21uPHGG+P++++Ps88+u/94d3d3PPDAA3H33XfHFVdcEfPnz49NmzbFv/3bv8WOHTvyODEAQO4VdAA2NzfHokWLoqGhYcDxjo6OOH78+IDjdXV1UVtbG+3t7UOer7e3N3p6egbcAADGmgn5HiBXHnroodi9e3fs2rXrbfd1dnZGcXFxTJs2bcDxysrK6OzsHPKcra2tcfvttw/3qAAAI6ognwHcv39/3HLLLfH9738/Jk2aNGznXbVqVXR3d/ff9u/fP2znBgAYKQUZgB0dHXHw4MH4wz/8w5gwYUJMmDAhtm/fHt/5zndiwoQJUVlZGceOHYtDhw4N+Lyurq6oqqoa8rwlJSVRWlo64AYAMNYU5I+Ar7zyynjmmWcGHFu6dGnU1dXFrbfeGjU1NTFx4sRoa2uLpqamiIjYu3dv7Nu3L+rr6/MxMgDAiCnIAJw6dWpcdNFFA46dddZZUVFR0X982bJl0dLSEuXl5VFaWhrLly+P+vr6uPTSS/MxMgDAiCnIADwZa9eujXHjxkVTU1P09vZGY2NjbNiwId9jAQDkXFGWZVm+hxirenp6oqysLLq7u70eEIBRbfZtj+Z7hFP2qzWLcnJe378L9E0gAAAMTQACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACRGAAIAJEYAAgAkRgACACSmYANw48aNMXfu3CgtLY3S0tKor6+Pn/zkJ/33Hz16NJqbm6OioiKmTJkSTU1N0dXVlceJAQBGRsEG4MyZM2PNmjXR0dERTz/9dFxxxRVx3XXXxX/+539GRMTKlStj69at8fDDD8f27dvjwIEDsXjx4jxPDQCQe0VZlmX5HmKklJeXx9/+7d/GJz7xiTj33HNj8+bN8YlPfCIiIp577rm44IILor29PS699NKTOl9PT0+UlZVFd3d3lJaW5nJ0ADgjs297NN8jnLJfrVmUk/P6/l3AzwC+2YkTJ+Khhx6KI0eORH19fXR0dMTx48ejoaGh/zF1dXVRW1sb7e3tQ56nt7c3enp6BtwAAMaagg7AZ555JqZMmRIlJSXxxS9+MbZs2RIf+MAHorOzM4qLi2PatGkDHl9ZWRmdnZ1Dnq+1tTXKysr6bzU1NTneAABg+BV0AJ5//vmxZ8+e2LlzZ3zpS1+KJUuWxM9+9rPTPt+qVauiu7u7/7Z///5hnBYAYGRMyPcAuVRcXBznnXdeRETMnz8/du3aFd/+9rfj05/+dBw7diwOHTo04FnArq6uqKqqGvJ8JSUlUVJSkuu
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.log10(matches[~np.isnan(matches)])\n",
    "\n",
    "\n",
    "plt.figure()\n",
    "plt.hist(x, bins=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9cc660b0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv_galomatch",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  }
 },
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 "nbformat_minor": 5
}