two-point-algorithms.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'\n",
    "%config IPCompleter.use_jedi = False\n",
    "\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import dask\n",
    "import dask.dataframe as dd\n",
    "\n",
    "from daskdecorators import dask_hist\n",
    "import hist\n",
    "from hist import Hist\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "matplotlib.rcParams['savefig.dpi'] = 120\n",
    "matplotlib.rcParams['figure.dpi'] = 120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://127.0.0.1:61625</li>\n",
       "  <li><b>Dashboard: </b><a href='http://127.0.0.1:8787/status' target='_blank'>http://127.0.0.1:8787/status</a></li>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>6</li>\n",
       "  <li><b>Cores: </b>6</li>\n",
       "  <li><b>Memory: </b>30.00 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:61625' processes=6 threads=6, memory=30.00 GB>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import multiprocessing.popen_spawn_posix # For python 3.9\n",
    "from dask.distributed import Client, LocalCluster\n",
    "\n",
    "cluster = LocalCluster(n_workers=6, \n",
    "                       threads_per_worker=1,\n",
    "                       memory_limit='5Gb')\n",
    "client = Client(cluster)\n",
    "\n",
    "#dask.config.config[\"distributed\"][\"dashboard\"][\"link\"] = \"{JUPYTERHUB_SERVICE_PREFIX}proxy/{host}:{port}/status\"\n",
    "#client = Client(scheduler_file='/global/cscratch1/sd/cwalter/dask-mpi/scheduler.json')\n",
    "\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns: ['id' 'mag_r' 'z' 'ra' 'dec' 'g1' 'g2'] #Rows: 0.0626302\n"
     ]
    }
   ],
   "source": [
    "#scratch= os.environ[\"SCRATCH\"]\n",
    "scratch = '/Users/walter/LSST/work'\n",
    "\n",
    "selected = ['id', 'mag_r', 'z', 'ra', 'dec', 'g1', 'g2']\n",
    "\n",
    "#df = dd.read_parquet(f'{scratch}/parquet-skysim/*.parquet', columns=selected, engine='pyarrow')\n",
    "df = dd.read_parquet(f'{scratch}/skysim-sampled', columns=selected, engine='pyarrow')\n",
    "#df = df.persist()\n",
    "\n",
    "print('Columns:', df.columns.values, '#Rows:', df.z.size.compute()/1e9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 62,630,200 elements in the Sky Sim\n",
      "There are 6,607 elements in the small area with 21,822,921 combinations\n"
     ]
    }
   ],
   "source": [
    "from scipy.special import comb\n",
    "\n",
    "#small_area = df.query('40 < ra < 44 and -34 < dec < -30 and mag_r < 26').sample(frac=.008)\n",
    "small_area = df.query('0 < ra < 4 and -4 < dec < 0 and mag_r < 26').sample(frac=0.15).persist()\n",
    "\n",
    "number_in_sample = small_area.index.size.compute()\n",
    "print(f'There are {df.index.size.compute():,d} elements in the Sky Sim')\n",
    "print(f'There are {number_in_sample:,d} elements in the small area with {comb(number_in_sample, 2, exact=True):,d} combinations')\n",
    "\n",
    "ra = small_area.ra.compute().to_numpy()\n",
    "dec = small_area.dec.compute().to_numpy()\n",
    "g1 = small_area.g1.compute().to_numpy()\n",
    "g2 = -small_area.g2.compute().to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 33.4 s, sys: 3.26 s, total: 36.7 s\n",
      "Wall time: 36.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "from numpy import deg2rad, pi\n",
    "import itertools as it\n",
    "\n",
    "from astropy.coordinates.angle_utilities import angular_separation\n",
    "from astropy.coordinates.angle_utilities import position_angle\n",
    "\n",
    "positions = np.column_stack([deg2rad(ra), deg2rad(dec), g1, g2])\n",
    "pairs = np.array( list(it.combinations(positions, 2)) )\n",
    "\n",
    "ra1, dec1, g1_1, g2_1 = pairs[:,0,0], pairs[:,0,1], pairs[:,0,2], pairs[:,0,3]\n",
    "ra2, dec2, g1_2, g2_2 = pairs[:,1,0], pairs[:,1,1], pairs[:,1,2], pairs[:,1,3]\n",
    "\n",
    "separation = angular_separation(ra1, dec1, ra2, dec2)*180/pi*60\n",
    "angle = position_angle(ra1, dec1, ra2, dec2).rad\n",
    "\n",
    "gamma1 = g1_1 + g2_1*1j\n",
    "gamma2 = g1_2 + g2_2*1j\n",
    "rotation = np.exp(-2j*angle)\n",
    "\n",
    "gt_1, gc_1 = -(gamma1*rotation).real, -(gamma1*rotation).imag\n",
    "gt_2, gc_2 = -(gamma2*rotation).real, -(gamma2*rotation).imag\n",
    "\n",
    "tt = gt_1*gt_2\n",
    "cc = gc_1*gc_2\n",
    "tc = gt_1*gc_2\n",
    "\n",
    "xip = tt + cc\n",
    "xim = tt - cc\n",
    "\n",
    "# Alternatively.  xip is real part of [eqn 32 of https://arxiv.org/pdf/1411.0115.pdf]\n",
    "gamma_gamma = gamma1 * gamma2.conjugate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping Cell\n"
     ]
    }
   ],
   "source": [
    "%%script echo Skipping Cell\n",
    "\n",
    "sep_hist = Hist.new.Reg(100, 0, 300, name='Theta').Double()\n",
    "phi_hist = Hist.new.Reg(100, 0, 360, name='Phi').Double()\n",
    "\n",
    "sep_hist.fill(separation);\n",
    "phi_hist.fill(angle*180/pi);\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize=(4.5, 2))\n",
    "\n",
    "fig.suptitle('Separation and Orientation of Galaxy Pairs')\n",
    "sep_hist.plot(ax=ax1)\n",
    "ax1.set_xscale('log')\n",
    "ax1.set_ylabel('Counts')\n",
    "ax1.set_xlabel(r'$\\theta$ (arcmin)')\n",
    "\n",
    "phi_hist.plot(ax=ax2)\n",
    "ax2.set_xlabel(r'$\\phi$');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.04 s, sys: 40.9 ms, total: 2.08 s\n",
      "Wall time: 286 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "import treecorr\n",
    "\n",
    "cat = treecorr.Catalog(ra=ra, dec=dec, g1=g1, g2=g2, ra_units='deg', dec_units='deg')\n",
    "gg = treecorr.GGCorrelation(min_sep=1., max_sep=200., nbins=20, sep_units='arcmin', brute=True)\n",
    "gg.process(cat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1884ea2e0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 465,
       "width": 698
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xip_hist = Hist.new.Reg(20, 1, 200, name='XP', transform=hist.axis.transform.log).Mean()\n",
    "xip_hist.fill(separation, sample=xip)\n",
    "\n",
    "xim_hist = Hist.new.Reg(20, 1, 200, name='XM', transform=hist.axis.transform.log).Mean()\n",
    "xim_hist.fill(separation, sample=xim)\n",
    "\n",
    "centers = xip_hist.axes.centers[0]\n",
    "xip_results = xip_hist.view()\n",
    "xip_values = xip_results.value\n",
    "xip_errors = np.sqrt(xip_results.variance/xip_results.count)\n",
    "plt.errorbar(x=centers, y=xip_values, yerr=xip_errors, fmt='.', markersize=9, label='$N^2$ Brute Force')\n",
    "\n",
    "plt.title('$\\gamma \\gamma$ Correlation')\n",
    "plt.xscale('log')\n",
    "#plt.yscale('log')\n",
    "#plt.ylim(bottom=0.5e-6)\n",
    "plt.ylabel(r'$\\xi_+$')\n",
    "plt.xlabel(r'$\\theta$ (arcmin)')\n",
    "plt.errorbar(gg.meanr, gg.xip, yerr=np.sqrt(gg.varxip), color='red',marker='.',markersize=2, ls='none', label='Treecorr')\n",
    "plt.legend(prop={'size': 7})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:.conda-dask]",
   "language": "python",
   "name": "conda-env-.conda-dask-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}