bigdframe.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "37aa3541-451b-47de-919f-4f67f5e70962",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from hipscat_import.catalog.arguments import ImportArguments\n",
    "from dask.distributed import Client\n",
    "from hipscat_import.pipeline import pipeline_with_client\n",
    "from hipscat_import.catalog.file_readers import FitsReader\n",
    "from pathlib import Path\n",
    "import lsdb\n",
    "from astropy.table import Table\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f48f5b44-f314-47bb-849c-95e4fec2715e",
   "metadata": {},
   "source": [
    "## Get hipscatted catalogs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33e588e3-338e-4c5a-9f60-657a17f10df4",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_mag = lsdb.read_hipscat(\"/ocean/projects/phy210048p/shared/hscmags/hscmags\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4cdec82f-96c4-4211-8ff4-8a4b5dc86b57",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_pz = lsdb.read_hipscat(\"/ocean/projects/phy210048p/shared/hscpz_quaia_cross/demp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8b7dabc7-07c5-4eae-85d9-e390913200bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_hsc_g = lsdb.read_hipscat(\"/ocean/projects/phy210048p/shared/hipscat/catalogs/hsc/hsc-pdr3-forced-g\",\n",
    "                              columns=['coord_ra','coord_dec','modelfit_CModel_fracDev','modelfit_CModel_exp_apCorr'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ecec443-d943-4e04-a09d-c78d4ef787f2",
   "metadata": {},
   "source": [
    "## Crossmatching"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff496ee7-6b23-43db-b0e7-fc3a55160e4f",
   "metadata": {},
   "source": [
    "*This crossmatches all hipscatted catalogs to build the big dataframe. Need to extend to rizy bands once they are available* "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f5986001-086e-4bbb-9220-26d5ffcb23d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/jet/home/edonoso/.conda/envs/lsdb_env/lib/python3.10/site-packages/lsdb/dask/crossmatch_catalog_data.py:108: RuntimeWarning: Right catalog does not have a margin cache. Results may be incomplete and/or inaccurate.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "match1 = cat_mag.crossmatch(cat_pz, radius_arcsec=1, suffixes=(\"_mag\",\"_pz\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a90ba099-d218-4985-bccd-e3446b1df509",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/jet/home/edonoso/.conda/envs/lsdb_env/lib/python3.10/site-packages/lsdb/dask/crossmatch_catalog_data.py:108: RuntimeWarning: Right catalog does not have a margin cache. Results may be incomplete and/or inaccurate.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "match2 = match1.crossmatch(cat_hsc_g, radius_arcsec=1, suffixes=(\"\",\"_hsc_g\")).compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6f00c6be-87dc-4f8c-bc31-a1bbe3a5fd66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['object_id_mag', 'g_cmodel_mag_mag', 'r_cmodel_mag_mag',\n",
       "       'isprimary_mag', 'i_cmodel_mag_mag', 'z_cmodel_mag_mag',\n",
       "       'y_cmodel_mag_mag', 'g_cmodel_magerr_mag', 'r_cmodel_magerr_mag',\n",
       "       'i_cmodel_magerr_mag', 'z_cmodel_magerr_mag', 'y_cmodel_magerr_mag',\n",
       "       'i_extendedness_value_mag', 'ra_mag', 'dec_mag', 'Norder_mag',\n",
       "       'Dir_mag', 'Npix_mag', 'object_id_pz', 'photoz_best_pz',\n",
       "       'photoz_conf_best_pz', 'photoz_risk_best_pz', 'stellar_mass_pz',\n",
       "       'sfr_pz', 'ra_pz', 'dec_pz', 'Norder_pz', 'Dir_pz', 'Npix_pz',\n",
       "       '_dist_arcsec', 'coord_ra_hsc_g', 'coord_dec_hsc_g',\n",
       "       'modelfit_CModel_fracDev_hsc_g', 'modelfit_CModel_exp_apCorr_hsc_g'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7db7e5db-f5ad-43c4-a06d-912b98fa60dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>object_id_mag</th>\n",
       "      <th>g_cmodel_mag_mag</th>\n",
       "      <th>r_cmodel_mag_mag</th>\n",
       "      <th>isprimary_mag</th>\n",
       "      <th>i_cmodel_mag_mag</th>\n",
       "      <th>z_cmodel_mag_mag</th>\n",
       "      <th>y_cmodel_mag_mag</th>\n",
       "      <th>g_cmodel_magerr_mag</th>\n",
       "      <th>r_cmodel_magerr_mag</th>\n",
       "      <th>i_cmodel_magerr_mag</th>\n",
       "      <th>...</th>\n",
       "      <th>ra_pz</th>\n",
       "      <th>dec_pz</th>\n",
       "      <th>Norder_pz</th>\n",
       "      <th>Dir_pz</th>\n",
       "      <th>Npix_pz</th>\n",
       "      <th>_dist_arcsec</th>\n",
       "      <th>coord_ra_hsc_g</th>\n",
       "      <th>coord_dec_hsc_g</th>\n",
       "      <th>modelfit_CModel_fracDev_hsc_g</th>\n",
       "      <th>modelfit_CModel_exp_apCorr_hsc_g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>_hipscat_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1152921505319878656</th>\n",
       "      <td>42045736963038719</td>\n",
       "      <td>24.054588</td>\n",
       "      <td>23.396921</td>\n",
       "      <td>True</td>\n",
       "      <td>23.116793</td>\n",
       "      <td>22.991911</td>\n",
       "      <td>22.942009</td>\n",
       "      <td>0.015796</td>\n",
       "      <td>0.013386</td>\n",
       "      <td>0.013754</td>\n",
       "      <td>...</td>\n",
       "      <td>134.998711</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.998711</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.984133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921505357627392</th>\n",
       "      <td>42045736963038720</td>\n",
       "      <td>25.580059</td>\n",
       "      <td>25.21903</td>\n",
       "      <td>True</td>\n",
       "      <td>25.100201</td>\n",
       "      <td>24.645592</td>\n",
       "      <td>24.43956</td>\n",
       "      <td>0.065117</td>\n",
       "      <td>0.075567</td>\n",
       "      <td>0.091862</td>\n",
       "      <td>...</td>\n",
       "      <td>134.999295</td>\n",
       "      <td>0.001358</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.999295</td>\n",
       "      <td>0.001358</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.984036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921506351677440</th>\n",
       "      <td>42045736963038773</td>\n",
       "      <td>25.030376</td>\n",
       "      <td>23.988865</td>\n",
       "      <td>True</td>\n",
       "      <td>23.663059</td>\n",
       "      <td>23.368797</td>\n",
       "      <td>23.357758</td>\n",
       "      <td>0.060486</td>\n",
       "      <td>0.033936</td>\n",
       "      <td>0.036098</td>\n",
       "      <td>...</td>\n",
       "      <td>135.000339</td>\n",
       "      <td>0.002146</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.000339</td>\n",
       "      <td>0.002146</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.983837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921506624307200</th>\n",
       "      <td>42045736963038772</td>\n",
       "      <td>24.754566</td>\n",
       "      <td>24.394215</td>\n",
       "      <td>True</td>\n",
       "      <td>24.060602</td>\n",
       "      <td>23.625294</td>\n",
       "      <td>23.278343</td>\n",
       "      <td>0.032087</td>\n",
       "      <td>0.034663</td>\n",
       "      <td>0.032505</td>\n",
       "      <td>...</td>\n",
       "      <td>135.001126</td>\n",
       "      <td>0.002717</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.001126</td>\n",
       "      <td>0.002717</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.986229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921506678833152</th>\n",
       "      <td>42045736963038774</td>\n",
       "      <td>25.10216</td>\n",
       "      <td>25.138165</td>\n",
       "      <td>True</td>\n",
       "      <td>24.504381</td>\n",
       "      <td>24.458683</td>\n",
       "      <td>24.559799</td>\n",
       "      <td>0.052118</td>\n",
       "      <td>0.082332</td>\n",
       "      <td>0.059367</td>\n",
       "      <td>...</td>\n",
       "      <td>135.000903</td>\n",
       "      <td>0.003075</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.000903</td>\n",
       "      <td>0.003075</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.986281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136546866888704</th>\n",
       "      <td>41245601735642630</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>30.601063</td>\n",
       "      <td>True</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>25.078793</td>\n",
       "      <td>25.170525</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>15.339904</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>...</td>\n",
       "      <td>225.000867</td>\n",
       "      <td>-0.003261</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.000867</td>\n",
       "      <td>-0.003261</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.978625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136547735109632</th>\n",
       "      <td>41245601735642646</td>\n",
       "      <td>24.479988</td>\n",
       "      <td>24.141069</td>\n",
       "      <td>True</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>23.193203</td>\n",
       "      <td>23.12009</td>\n",
       "      <td>0.042538</td>\n",
       "      <td>0.048195</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>...</td>\n",
       "      <td>225.002088</td>\n",
       "      <td>-0.002689</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.002088</td>\n",
       "      <td>-0.002689</td>\n",
       "      <td>0.237221</td>\n",
       "      <td>0.978815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136548003545088</th>\n",
       "      <td>41245601735642660</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>True</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>...</td>\n",
       "      <td>225.000674</td>\n",
       "      <td>-0.0027</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.000674</td>\n",
       "      <td>-0.0027</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>0.978612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136549396054016</th>\n",
       "      <td>41245601735642697</td>\n",
       "      <td>27.26774</td>\n",
       "      <td>26.499187</td>\n",
       "      <td>True</td>\n",
       "      <td>25.776463</td>\n",
       "      <td>25.616077</td>\n",
       "      <td>25.280712</td>\n",
       "      <td>0.30529</td>\n",
       "      <td>0.3099</td>\n",
       "      <td>0.115172</td>\n",
       "      <td>...</td>\n",
       "      <td>224.998604</td>\n",
       "      <td>-0.001842</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.998604</td>\n",
       "      <td>-0.001842</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.978366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136549614157824</th>\n",
       "      <td>41245601735642673</td>\n",
       "      <td>24.492102</td>\n",
       "      <td>24.224945</td>\n",
       "      <td>True</td>\n",
       "      <td>23.767303</td>\n",
       "      <td>23.416489</td>\n",
       "      <td>23.210777</td>\n",
       "      <td>0.044715</td>\n",
       "      <td>0.057063</td>\n",
       "      <td>0.035063</td>\n",
       "      <td>...</td>\n",
       "      <td>224.999934</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.999934</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.978527</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>478695732 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          object_id_mag  g_cmodel_mag_mag  r_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                                \n",
       "1152921505319878656   42045736963038719         24.054588         23.396921   \n",
       "1152921505357627392   42045736963038720         25.580059          25.21903   \n",
       "1152921506351677440   42045736963038773         25.030376         23.988865   \n",
       "1152921506624307200   42045736963038772         24.754566         24.394215   \n",
       "1152921506678833152   42045736963038774          25.10216         25.138165   \n",
       "...                                 ...               ...               ...   \n",
       "12682136546866888704  41245601735642630              <NA>         30.601063   \n",
       "12682136547735109632  41245601735642646         24.479988         24.141069   \n",
       "12682136548003545088  41245601735642660              <NA>              <NA>   \n",
       "12682136549396054016  41245601735642697          27.26774         26.499187   \n",
       "12682136549614157824  41245601735642673         24.492102         24.224945   \n",
       "\n",
       "                     isprimary_mag  i_cmodel_mag_mag  z_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                           \n",
       "1152921505319878656           True         23.116793         22.991911   \n",
       "1152921505357627392           True         25.100201         24.645592   \n",
       "1152921506351677440           True         23.663059         23.368797   \n",
       "1152921506624307200           True         24.060602         23.625294   \n",
       "1152921506678833152           True         24.504381         24.458683   \n",
       "...                            ...               ...               ...   \n",
       "12682136546866888704          True              <NA>         25.078793   \n",
       "12682136547735109632          True              <NA>         23.193203   \n",
       "12682136548003545088          True              <NA>              <NA>   \n",
       "12682136549396054016          True         25.776463         25.616077   \n",
       "12682136549614157824          True         23.767303         23.416489   \n",
       "\n",
       "                      y_cmodel_mag_mag  g_cmodel_magerr_mag  \\\n",
       "_hipscat_index                                                \n",
       "1152921505319878656          22.942009             0.015796   \n",
       "1152921505357627392           24.43956             0.065117   \n",
       "1152921506351677440          23.357758             0.060486   \n",
       "1152921506624307200          23.278343             0.032087   \n",
       "1152921506678833152          24.559799             0.052118   \n",
       "...                                ...                  ...   \n",
       "12682136546866888704         25.170525                 <NA>   \n",
       "12682136547735109632          23.12009             0.042538   \n",
       "12682136548003545088              <NA>                 <NA>   \n",
       "12682136549396054016         25.280712              0.30529   \n",
       "12682136549614157824         23.210777             0.044715   \n",
       "\n",
       "                      r_cmodel_magerr_mag  i_cmodel_magerr_mag  ...  \\\n",
       "_hipscat_index                                                  ...   \n",
       "1152921505319878656              0.013386             0.013754  ...   \n",
       "1152921505357627392              0.075567             0.091862  ...   \n",
       "1152921506351677440              0.033936             0.036098  ...   \n",
       "1152921506624307200              0.034663             0.032505  ...   \n",
       "1152921506678833152              0.082332             0.059367  ...   \n",
       "...                                   ...                  ...  ...   \n",
       "12682136546866888704            15.339904                 <NA>  ...   \n",
       "12682136547735109632             0.048195                 <NA>  ...   \n",
       "12682136548003545088                 <NA>                 <NA>  ...   \n",
       "12682136549396054016               0.3099             0.115172  ...   \n",
       "12682136549614157824             0.057063             0.035063  ...   \n",
       "\n",
       "                           ra_pz    dec_pz  Norder_pz  Dir_pz  Npix_pz  \\\n",
       "_hipscat_index                                                           \n",
       "1152921505319878656   134.998711  0.001234          6       0     4096   \n",
       "1152921505357627392   134.999295  0.001358          6       0     4096   \n",
       "1152921506351677440   135.000339  0.002146          6       0     4096   \n",
       "1152921506624307200   135.001126  0.002717          6       0     4096   \n",
       "1152921506678833152   135.000903  0.003075          6       0     4096   \n",
       "...                          ...       ...        ...     ...      ...   \n",
       "12682136546866888704  225.000867 -0.003261          6   40000    45055   \n",
       "12682136547735109632  225.002088 -0.002689          6   40000    45055   \n",
       "12682136548003545088  225.000674   -0.0027          6   40000    45055   \n",
       "12682136549396054016  224.998604 -0.001842          6   40000    45055   \n",
       "12682136549614157824  224.999934 -0.002113          6   40000    45055   \n",
       "\n",
       "                      _dist_arcsec  coord_ra_hsc_g  coord_dec_hsc_g  \\\n",
       "_hipscat_index                                                        \n",
       "1152921505319878656            0.0      134.998711         0.001234   \n",
       "1152921505357627392            0.0      134.999295         0.001358   \n",
       "1152921506351677440            0.0      135.000339         0.002146   \n",
       "1152921506624307200            0.0      135.001126         0.002717   \n",
       "1152921506678833152            0.0      135.000903         0.003075   \n",
       "...                            ...             ...              ...   \n",
       "12682136546866888704           0.0      225.000867        -0.003261   \n",
       "12682136547735109632           0.0      225.002088        -0.002689   \n",
       "12682136548003545088           0.0      225.000674          -0.0027   \n",
       "12682136549396054016           0.0      224.998604        -0.001842   \n",
       "12682136549614157824           0.0      224.999934        -0.002113   \n",
       "\n",
       "                      modelfit_CModel_fracDev_hsc_g  \\\n",
       "_hipscat_index                                        \n",
       "1152921505319878656                             1.0   \n",
       "1152921505357627392                             1.0   \n",
       "1152921506351677440                             0.0   \n",
       "1152921506624307200                             1.0   \n",
       "1152921506678833152                             0.0   \n",
       "...                                             ...   \n",
       "12682136546866888704                           -0.0   \n",
       "12682136547735109632                       0.237221   \n",
       "12682136548003545088                           <NA>   \n",
       "12682136549396054016                            1.0   \n",
       "12682136549614157824                            0.0   \n",
       "\n",
       "                      modelfit_CModel_exp_apCorr_hsc_g  \n",
       "_hipscat_index                                          \n",
       "1152921505319878656                           0.984133  \n",
       "1152921505357627392                           0.984036  \n",
       "1152921506351677440                           0.983837  \n",
       "1152921506624307200                           0.986229  \n",
       "1152921506678833152                           0.986281  \n",
       "...                                                ...  \n",
       "12682136546866888704                          0.978625  \n",
       "12682136547735109632                          0.978815  \n",
       "12682136548003545088                          0.978612  \n",
       "12682136549396054016                          0.978366  \n",
       "12682136549614157824                          0.978527  \n",
       "\n",
       "[478695732 rows x 34 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "match2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e387bc02-d794-4a13-97c9-f0106e0729f0",
   "metadata": {},
   "source": [
    "## Filtering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c28a5bd0-3d46-4b40-bf8f-5cd6e2a813f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "c1 = match2['isprimary_mag']==True\n",
    "c2 = (match2['g_cmodel_mag_mag'] > 17.8) & (match2['g_cmodel_mag_mag'] < 26.5)\n",
    "c3 = (match2['r_cmodel_mag_mag'] > 17.8) & (match2['r_cmodel_mag_mag'] < 26.1)\n",
    "c4 = (match2['i_cmodel_mag_mag'] > 18.4) & (match2['i_cmodel_mag_mag'] < 25.9)\n",
    "c5 = (match2['z_cmodel_mag_mag'] > 17.4) & (match2['z_cmodel_mag_mag'] < 25.1)\n",
    "c6 = (match2['y_cmodel_mag_mag'] > 17.1) & (match2['y_cmodel_mag_mag'] < 24.4)\n",
    "c7 = match2['photoz_risk_best_pz'] < 0.55\n",
    "cg = match2['i_extendedness_value_mag'] == True\n",
    "cs = match2['i_extendedness_value_mag'] == False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "65a1c58a-2220-471e-9c2e-efa731351872",
   "metadata": {},
   "outputs": [],
   "source": [
    "# conditions for galaxies\n",
    "ctotg = c1 & c2 & c3 & c4 & c5 & c6 & c7 & cg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6d8ef7d4-7e28-4f34-9ace-fe6fa87235f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# contidins for stars\n",
    "ctots = c1 & c2 & c3 & c4 & c5 & c6 & c7 & cs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e5221cc7-2009-4968-a8a1-e3bb83a2ca2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Big dataframe of galaxies\n",
    "bigdf_gal = match2[ctotg]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "64f8c5ed-57c4-4c74-b331-9479427cece3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(bigdf_gal['ra_pz'],bigdf_gal['dec_pz'], s=0.5, alpha=0.5)\n",
    "#plt.xlim([200.3,200.5])\n",
    "#plt.ylim([0.9,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4bc0d858-2c49-4807-a04a-c386b593a740",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(bigdf_gal['photoz_best_pz'],bins=50);\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "17d5ff25-5da2-42b3-a864-e3a26e94a9fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "bigdf_star = match2[ctots]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "09b3d246-e3a2-4522-83ec-f1f78be6dbde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(bigdf_gal['ra_pz'],bigdf_gal['dec_pz'], s=0.1, alpha=0.01)\n",
    "plt.xlim([150,200])\n",
    "plt.ylim([-2,5])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "54d295d2-17b7-4815-86e9-87d44b6d76e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>object_id_mag</th>\n",
       "      <th>g_cmodel_mag_mag</th>\n",
       "      <th>r_cmodel_mag_mag</th>\n",
       "      <th>isprimary_mag</th>\n",
       "      <th>i_cmodel_mag_mag</th>\n",
       "      <th>z_cmodel_mag_mag</th>\n",
       "      <th>y_cmodel_mag_mag</th>\n",
       "      <th>g_cmodel_magerr_mag</th>\n",
       "      <th>r_cmodel_magerr_mag</th>\n",
       "      <th>i_cmodel_magerr_mag</th>\n",
       "      <th>...</th>\n",
       "      <th>ra_pz</th>\n",
       "      <th>dec_pz</th>\n",
       "      <th>Norder_pz</th>\n",
       "      <th>Dir_pz</th>\n",
       "      <th>Npix_pz</th>\n",
       "      <th>_dist_arcsec</th>\n",
       "      <th>coord_ra_hsc_g</th>\n",
       "      <th>coord_dec_hsc_g</th>\n",
       "      <th>modelfit_CModel_fracDev_hsc_g</th>\n",
       "      <th>modelfit_CModel_exp_apCorr_hsc_g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>_hipscat_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1152921505319878656</th>\n",
       "      <td>42045736963038719</td>\n",
       "      <td>24.054588</td>\n",
       "      <td>23.396921</td>\n",
       "      <td>True</td>\n",
       "      <td>23.116793</td>\n",
       "      <td>22.991911</td>\n",
       "      <td>22.942009</td>\n",
       "      <td>0.015796</td>\n",
       "      <td>0.013386</td>\n",
       "      <td>0.013754</td>\n",
       "      <td>...</td>\n",
       "      <td>134.998711</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.998711</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.984133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921551700492288</th>\n",
       "      <td>42045736963018849</td>\n",
       "      <td>24.016159</td>\n",
       "      <td>23.269417</td>\n",
       "      <td>True</td>\n",
       "      <td>22.95722</td>\n",
       "      <td>22.786869</td>\n",
       "      <td>22.684387</td>\n",
       "      <td>0.016694</td>\n",
       "      <td>0.012158</td>\n",
       "      <td>0.01209</td>\n",
       "      <td>...</td>\n",
       "      <td>134.992048</td>\n",
       "      <td>0.01114</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.992048</td>\n",
       "      <td>0.01114</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.988991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921567982780416</th>\n",
       "      <td>42045736963039303</td>\n",
       "      <td>22.424358</td>\n",
       "      <td>21.161945</td>\n",
       "      <td>True</td>\n",
       "      <td>20.000065</td>\n",
       "      <td>19.487711</td>\n",
       "      <td>19.279285</td>\n",
       "      <td>0.00478</td>\n",
       "      <td>0.002541</td>\n",
       "      <td>0.001014</td>\n",
       "      <td>...</td>\n",
       "      <td>134.99728</td>\n",
       "      <td>0.014269</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.99728</td>\n",
       "      <td>0.014269</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.987904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921583589785600</th>\n",
       "      <td>42045736963039299</td>\n",
       "      <td>23.655003</td>\n",
       "      <td>22.278936</td>\n",
       "      <td>True</td>\n",
       "      <td>20.373072</td>\n",
       "      <td>19.562859</td>\n",
       "      <td>19.206282</td>\n",
       "      <td>0.013493</td>\n",
       "      <td>0.006327</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>...</td>\n",
       "      <td>135.008939</td>\n",
       "      <td>0.013954</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.008939</td>\n",
       "      <td>0.013954</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.987415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921585061986304</th>\n",
       "      <td>42045736963039350</td>\n",
       "      <td>24.194645</td>\n",
       "      <td>22.723289</td>\n",
       "      <td>True</td>\n",
       "      <td>21.085957</td>\n",
       "      <td>20.404121</td>\n",
       "      <td>20.115389</td>\n",
       "      <td>0.020891</td>\n",
       "      <td>0.009521</td>\n",
       "      <td>0.002234</td>\n",
       "      <td>...</td>\n",
       "      <td>135.006446</td>\n",
       "      <td>0.014686</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.006446</td>\n",
       "      <td>0.014686</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.988142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136394034839552</th>\n",
       "      <td>41245601735642073</td>\n",
       "      <td>19.52508</td>\n",
       "      <td>19.097111</td>\n",
       "      <td>True</td>\n",
       "      <td>18.92342</td>\n",
       "      <td>18.828474</td>\n",
       "      <td>18.782982</td>\n",
       "      <td>0.000861</td>\n",
       "      <td>0.000783</td>\n",
       "      <td>0.000452</td>\n",
       "      <td>...</td>\n",
       "      <td>225.004374</td>\n",
       "      <td>-0.016768</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.004374</td>\n",
       "      <td>-0.016768</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.978686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136418227585024</th>\n",
       "      <td>41245601735658997</td>\n",
       "      <td>24.942692</td>\n",
       "      <td>23.653639</td>\n",
       "      <td>True</td>\n",
       "      <td>22.93626</td>\n",
       "      <td>22.555008</td>\n",
       "      <td>22.341095</td>\n",
       "      <td>0.036869</td>\n",
       "      <td>0.025989</td>\n",
       "      <td>0.009736</td>\n",
       "      <td>...</td>\n",
       "      <td>224.990821</td>\n",
       "      <td>-0.024463</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.990821</td>\n",
       "      <td>-0.024463</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.977935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136475400142848</th>\n",
       "      <td>41245601735659284</td>\n",
       "      <td>19.521549</td>\n",
       "      <td>19.310869</td>\n",
       "      <td>True</td>\n",
       "      <td>19.02541</td>\n",
       "      <td>19.136189</td>\n",
       "      <td>19.065266</td>\n",
       "      <td>0.001053</td>\n",
       "      <td>0.001218</td>\n",
       "      <td>0.000615</td>\n",
       "      <td>...</td>\n",
       "      <td>224.98754</td>\n",
       "      <td>-0.013351</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.98754</td>\n",
       "      <td>-0.013351</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.977867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136500238811136</th>\n",
       "      <td>41245601735659401</td>\n",
       "      <td>25.046307</td>\n",
       "      <td>24.379961</td>\n",
       "      <td>True</td>\n",
       "      <td>23.902685</td>\n",
       "      <td>23.769619</td>\n",
       "      <td>23.83688</td>\n",
       "      <td>0.040515</td>\n",
       "      <td>0.043588</td>\n",
       "      <td>0.02235</td>\n",
       "      <td>...</td>\n",
       "      <td>225.007035</td>\n",
       "      <td>-0.012502</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.007035</td>\n",
       "      <td>-0.012502</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.979246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136501203501056</th>\n",
       "      <td>41245601735659549</td>\n",
       "      <td>23.073734</td>\n",
       "      <td>22.320704</td>\n",
       "      <td>True</td>\n",
       "      <td>21.964497</td>\n",
       "      <td>21.79026</td>\n",
       "      <td>21.694639</td>\n",
       "      <td>0.00854</td>\n",
       "      <td>0.007113</td>\n",
       "      <td>0.00409</td>\n",
       "      <td>...</td>\n",
       "      <td>225.006601</td>\n",
       "      <td>-0.010948</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.006601</td>\n",
       "      <td>-0.010948</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.97924</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10994135 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          object_id_mag  g_cmodel_mag_mag  r_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                                \n",
       "1152921505319878656   42045736963038719         24.054588         23.396921   \n",
       "1152921551700492288   42045736963018849         24.016159         23.269417   \n",
       "1152921567982780416   42045736963039303         22.424358         21.161945   \n",
       "1152921583589785600   42045736963039299         23.655003         22.278936   \n",
       "1152921585061986304   42045736963039350         24.194645         22.723289   \n",
       "...                                 ...               ...               ...   \n",
       "12682136394034839552  41245601735642073          19.52508         19.097111   \n",
       "12682136418227585024  41245601735658997         24.942692         23.653639   \n",
       "12682136475400142848  41245601735659284         19.521549         19.310869   \n",
       "12682136500238811136  41245601735659401         25.046307         24.379961   \n",
       "12682136501203501056  41245601735659549         23.073734         22.320704   \n",
       "\n",
       "                     isprimary_mag  i_cmodel_mag_mag  z_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                           \n",
       "1152921505319878656           True         23.116793         22.991911   \n",
       "1152921551700492288           True          22.95722         22.786869   \n",
       "1152921567982780416           True         20.000065         19.487711   \n",
       "1152921583589785600           True         20.373072         19.562859   \n",
       "1152921585061986304           True         21.085957         20.404121   \n",
       "...                            ...               ...               ...   \n",
       "12682136394034839552          True          18.92342         18.828474   \n",
       "12682136418227585024          True          22.93626         22.555008   \n",
       "12682136475400142848          True          19.02541         19.136189   \n",
       "12682136500238811136          True         23.902685         23.769619   \n",
       "12682136501203501056          True         21.964497          21.79026   \n",
       "\n",
       "                      y_cmodel_mag_mag  g_cmodel_magerr_mag  \\\n",
       "_hipscat_index                                                \n",
       "1152921505319878656          22.942009             0.015796   \n",
       "1152921551700492288          22.684387             0.016694   \n",
       "1152921567982780416          19.279285              0.00478   \n",
       "1152921583589785600          19.206282             0.013493   \n",
       "1152921585061986304          20.115389             0.020891   \n",
       "...                                ...                  ...   \n",
       "12682136394034839552         18.782982             0.000861   \n",
       "12682136418227585024         22.341095             0.036869   \n",
       "12682136475400142848         19.065266             0.001053   \n",
       "12682136500238811136          23.83688             0.040515   \n",
       "12682136501203501056         21.694639              0.00854   \n",
       "\n",
       "                      r_cmodel_magerr_mag  i_cmodel_magerr_mag  ...  \\\n",
       "_hipscat_index                                                  ...   \n",
       "1152921505319878656              0.013386             0.013754  ...   \n",
       "1152921551700492288              0.012158              0.01209  ...   \n",
       "1152921567982780416              0.002541             0.001014  ...   \n",
       "1152921583589785600              0.006327             0.001253  ...   \n",
       "1152921585061986304              0.009521             0.002234  ...   \n",
       "...                                   ...                  ...  ...   \n",
       "12682136394034839552             0.000783             0.000452  ...   \n",
       "12682136418227585024             0.025989             0.009736  ...   \n",
       "12682136475400142848             0.001218             0.000615  ...   \n",
       "12682136500238811136             0.043588              0.02235  ...   \n",
       "12682136501203501056             0.007113              0.00409  ...   \n",
       "\n",
       "                           ra_pz    dec_pz  Norder_pz  Dir_pz  Npix_pz  \\\n",
       "_hipscat_index                                                           \n",
       "1152921505319878656   134.998711  0.001234          6       0     4096   \n",
       "1152921551700492288   134.992048   0.01114          6       0     4096   \n",
       "1152921567982780416    134.99728  0.014269          6       0     4096   \n",
       "1152921583589785600   135.008939  0.013954          6       0     4096   \n",
       "1152921585061986304   135.006446  0.014686          6       0     4096   \n",
       "...                          ...       ...        ...     ...      ...   \n",
       "12682136394034839552  225.004374 -0.016768          6   40000    45055   \n",
       "12682136418227585024  224.990821 -0.024463          6   40000    45055   \n",
       "12682136475400142848   224.98754 -0.013351          6   40000    45055   \n",
       "12682136500238811136  225.007035 -0.012502          6   40000    45055   \n",
       "12682136501203501056  225.006601 -0.010948          6   40000    45055   \n",
       "\n",
       "                      _dist_arcsec  coord_ra_hsc_g  coord_dec_hsc_g  \\\n",
       "_hipscat_index                                                        \n",
       "1152921505319878656            0.0      134.998711         0.001234   \n",
       "1152921551700492288            0.0      134.992048          0.01114   \n",
       "1152921567982780416            0.0       134.99728         0.014269   \n",
       "1152921583589785600            0.0      135.008939         0.013954   \n",
       "1152921585061986304            0.0      135.006446         0.014686   \n",
       "...                            ...             ...              ...   \n",
       "12682136394034839552           0.0      225.004374        -0.016768   \n",
       "12682136418227585024           0.0      224.990821        -0.024463   \n",
       "12682136475400142848           0.0       224.98754        -0.013351   \n",
       "12682136500238811136           0.0      225.007035        -0.012502   \n",
       "12682136501203501056           0.0      225.006601        -0.010948   \n",
       "\n",
       "                      modelfit_CModel_fracDev_hsc_g  \\\n",
       "_hipscat_index                                        \n",
       "1152921505319878656                             1.0   \n",
       "1152921551700492288                             0.0   \n",
       "1152921567982780416                             1.0   \n",
       "1152921583589785600                             1.0   \n",
       "1152921585061986304                             1.0   \n",
       "...                                             ...   \n",
       "12682136394034839552                            0.0   \n",
       "12682136418227585024                            1.0   \n",
       "12682136475400142848                            1.0   \n",
       "12682136500238811136                            1.0   \n",
       "12682136501203501056                            1.0   \n",
       "\n",
       "                      modelfit_CModel_exp_apCorr_hsc_g  \n",
       "_hipscat_index                                          \n",
       "1152921505319878656                           0.984133  \n",
       "1152921551700492288                           0.988991  \n",
       "1152921567982780416                           0.987904  \n",
       "1152921583589785600                           0.987415  \n",
       "1152921585061986304                           0.988142  \n",
       "...                                                ...  \n",
       "12682136394034839552                          0.978686  \n",
       "12682136418227585024                          0.977935  \n",
       "12682136475400142848                          0.977867  \n",
       "12682136500238811136                          0.979246  \n",
       "12682136501203501056                           0.97924  \n",
       "\n",
       "[10994135 rows x 34 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigdf_star"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7acb2d76-f3f4-442b-b6d0-338a8551386f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>object_id_mag</th>\n",
       "      <th>g_cmodel_mag_mag</th>\n",
       "      <th>r_cmodel_mag_mag</th>\n",
       "      <th>isprimary_mag</th>\n",
       "      <th>i_cmodel_mag_mag</th>\n",
       "      <th>z_cmodel_mag_mag</th>\n",
       "      <th>y_cmodel_mag_mag</th>\n",
       "      <th>g_cmodel_magerr_mag</th>\n",
       "      <th>r_cmodel_magerr_mag</th>\n",
       "      <th>i_cmodel_magerr_mag</th>\n",
       "      <th>...</th>\n",
       "      <th>ra_pz</th>\n",
       "      <th>dec_pz</th>\n",
       "      <th>Norder_pz</th>\n",
       "      <th>Dir_pz</th>\n",
       "      <th>Npix_pz</th>\n",
       "      <th>_dist_arcsec</th>\n",
       "      <th>coord_ra_hsc_g</th>\n",
       "      <th>coord_dec_hsc_g</th>\n",
       "      <th>modelfit_CModel_fracDev_hsc_g</th>\n",
       "      <th>modelfit_CModel_exp_apCorr_hsc_g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>_hipscat_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1152921506351677440</th>\n",
       "      <td>42045736963038773</td>\n",
       "      <td>25.030376</td>\n",
       "      <td>23.988865</td>\n",
       "      <td>True</td>\n",
       "      <td>23.663059</td>\n",
       "      <td>23.368797</td>\n",
       "      <td>23.357758</td>\n",
       "      <td>0.060486</td>\n",
       "      <td>0.033936</td>\n",
       "      <td>0.036098</td>\n",
       "      <td>...</td>\n",
       "      <td>135.000339</td>\n",
       "      <td>0.002146</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.000339</td>\n",
       "      <td>0.002146</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.983837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921506624307200</th>\n",
       "      <td>42045736963038772</td>\n",
       "      <td>24.754566</td>\n",
       "      <td>24.394215</td>\n",
       "      <td>True</td>\n",
       "      <td>24.060602</td>\n",
       "      <td>23.625294</td>\n",
       "      <td>23.278343</td>\n",
       "      <td>0.032087</td>\n",
       "      <td>0.034663</td>\n",
       "      <td>0.032505</td>\n",
       "      <td>...</td>\n",
       "      <td>135.001126</td>\n",
       "      <td>0.002717</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.001126</td>\n",
       "      <td>0.002717</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.986229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921510386597888</th>\n",
       "      <td>42045736963018599</td>\n",
       "      <td>23.765141</td>\n",
       "      <td>23.244118</td>\n",
       "      <td>True</td>\n",
       "      <td>22.538471</td>\n",
       "      <td>22.217865</td>\n",
       "      <td>22.036289</td>\n",
       "      <td>0.01611</td>\n",
       "      <td>0.01538</td>\n",
       "      <td>0.010062</td>\n",
       "      <td>...</td>\n",
       "      <td>135.004395</td>\n",
       "      <td>0.004557</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.004395</td>\n",
       "      <td>0.004557</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.985443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921512148205568</th>\n",
       "      <td>42045736963018623</td>\n",
       "      <td>23.324654</td>\n",
       "      <td>22.591885</td>\n",
       "      <td>True</td>\n",
       "      <td>22.240723</td>\n",
       "      <td>22.03056</td>\n",
       "      <td>21.959774</td>\n",
       "      <td>0.014575</td>\n",
       "      <td>0.011517</td>\n",
       "      <td>0.010666</td>\n",
       "      <td>...</td>\n",
       "      <td>135.002861</td>\n",
       "      <td>0.004971</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.002861</td>\n",
       "      <td>0.004971</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.985805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1152921515780472832</th>\n",
       "      <td>42045736963038874</td>\n",
       "      <td>24.902676</td>\n",
       "      <td>24.705908</td>\n",
       "      <td>True</td>\n",
       "      <td>23.994253</td>\n",
       "      <td>23.719196</td>\n",
       "      <td>23.699333</td>\n",
       "      <td>0.052621</td>\n",
       "      <td>0.056989</td>\n",
       "      <td>0.037956</td>\n",
       "      <td>...</td>\n",
       "      <td>134.996025</td>\n",
       "      <td>0.004544</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>4096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>134.996025</td>\n",
       "      <td>0.004544</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.9875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136523865325568</th>\n",
       "      <td>41245601735659592</td>\n",
       "      <td>24.007427</td>\n",
       "      <td>23.463627</td>\n",
       "      <td>True</td>\n",
       "      <td>21.981031</td>\n",
       "      <td>21.172455</td>\n",
       "      <td>21.329884</td>\n",
       "      <td>0.063759</td>\n",
       "      <td>0.036201</td>\n",
       "      <td>0.009331</td>\n",
       "      <td>...</td>\n",
       "      <td>224.997139</td>\n",
       "      <td>-0.009118</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.997139</td>\n",
       "      <td>-0.009118</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.978109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136538255982592</th>\n",
       "      <td>41245601735642525</td>\n",
       "      <td>25.565186</td>\n",
       "      <td>23.849463</td>\n",
       "      <td>True</td>\n",
       "      <td>22.46981</td>\n",
       "      <td>21.863396</td>\n",
       "      <td>21.570576</td>\n",
       "      <td>0.0813</td>\n",
       "      <td>0.031822</td>\n",
       "      <td>0.007817</td>\n",
       "      <td>...</td>\n",
       "      <td>225.003142</td>\n",
       "      <td>-0.005594</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.003142</td>\n",
       "      <td>-0.005594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.978886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136539845623808</th>\n",
       "      <td>41245601735642602</td>\n",
       "      <td>25.767666</td>\n",
       "      <td>25.130713</td>\n",
       "      <td>True</td>\n",
       "      <td>24.731062</td>\n",
       "      <td>24.712986</td>\n",
       "      <td>24.327229</td>\n",
       "      <td>0.113638</td>\n",
       "      <td>0.120082</td>\n",
       "      <td>0.056707</td>\n",
       "      <td>...</td>\n",
       "      <td>225.003478</td>\n",
       "      <td>-0.004054</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.003478</td>\n",
       "      <td>-0.004054</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.978988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136545189167104</th>\n",
       "      <td>41245601735642598</td>\n",
       "      <td>24.630835</td>\n",
       "      <td>24.165575</td>\n",
       "      <td>True</td>\n",
       "      <td>23.786692</td>\n",
       "      <td>23.819485</td>\n",
       "      <td>23.506701</td>\n",
       "      <td>0.035995</td>\n",
       "      <td>0.0388</td>\n",
       "      <td>0.022563</td>\n",
       "      <td>...</td>\n",
       "      <td>224.995777</td>\n",
       "      <td>-0.004141</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.995777</td>\n",
       "      <td>-0.004141</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.978049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12682136549614157824</th>\n",
       "      <td>41245601735642673</td>\n",
       "      <td>24.492102</td>\n",
       "      <td>24.224945</td>\n",
       "      <td>True</td>\n",
       "      <td>23.767303</td>\n",
       "      <td>23.416489</td>\n",
       "      <td>23.210777</td>\n",
       "      <td>0.044715</td>\n",
       "      <td>0.057063</td>\n",
       "      <td>0.035063</td>\n",
       "      <td>...</td>\n",
       "      <td>224.999934</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>6</td>\n",
       "      <td>40000</td>\n",
       "      <td>45055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>224.999934</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.978527</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>128861334 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          object_id_mag  g_cmodel_mag_mag  r_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                                \n",
       "1152921506351677440   42045736963038773         25.030376         23.988865   \n",
       "1152921506624307200   42045736963038772         24.754566         24.394215   \n",
       "1152921510386597888   42045736963018599         23.765141         23.244118   \n",
       "1152921512148205568   42045736963018623         23.324654         22.591885   \n",
       "1152921515780472832   42045736963038874         24.902676         24.705908   \n",
       "...                                 ...               ...               ...   \n",
       "12682136523865325568  41245601735659592         24.007427         23.463627   \n",
       "12682136538255982592  41245601735642525         25.565186         23.849463   \n",
       "12682136539845623808  41245601735642602         25.767666         25.130713   \n",
       "12682136545189167104  41245601735642598         24.630835         24.165575   \n",
       "12682136549614157824  41245601735642673         24.492102         24.224945   \n",
       "\n",
       "                     isprimary_mag  i_cmodel_mag_mag  z_cmodel_mag_mag  \\\n",
       "_hipscat_index                                                           \n",
       "1152921506351677440           True         23.663059         23.368797   \n",
       "1152921506624307200           True         24.060602         23.625294   \n",
       "1152921510386597888           True         22.538471         22.217865   \n",
       "1152921512148205568           True         22.240723          22.03056   \n",
       "1152921515780472832           True         23.994253         23.719196   \n",
       "...                            ...               ...               ...   \n",
       "12682136523865325568          True         21.981031         21.172455   \n",
       "12682136538255982592          True          22.46981         21.863396   \n",
       "12682136539845623808          True         24.731062         24.712986   \n",
       "12682136545189167104          True         23.786692         23.819485   \n",
       "12682136549614157824          True         23.767303         23.416489   \n",
       "\n",
       "                      y_cmodel_mag_mag  g_cmodel_magerr_mag  \\\n",
       "_hipscat_index                                                \n",
       "1152921506351677440          23.357758             0.060486   \n",
       "1152921506624307200          23.278343             0.032087   \n",
       "1152921510386597888          22.036289              0.01611   \n",
       "1152921512148205568          21.959774             0.014575   \n",
       "1152921515780472832          23.699333             0.052621   \n",
       "...                                ...                  ...   \n",
       "12682136523865325568         21.329884             0.063759   \n",
       "12682136538255982592         21.570576               0.0813   \n",
       "12682136539845623808         24.327229             0.113638   \n",
       "12682136545189167104         23.506701             0.035995   \n",
       "12682136549614157824         23.210777             0.044715   \n",
       "\n",
       "                      r_cmodel_magerr_mag  i_cmodel_magerr_mag  ...  \\\n",
       "_hipscat_index                                                  ...   \n",
       "1152921506351677440              0.033936             0.036098  ...   \n",
       "1152921506624307200              0.034663             0.032505  ...   \n",
       "1152921510386597888               0.01538             0.010062  ...   \n",
       "1152921512148205568              0.011517             0.010666  ...   \n",
       "1152921515780472832              0.056989             0.037956  ...   \n",
       "...                                   ...                  ...  ...   \n",
       "12682136523865325568             0.036201             0.009331  ...   \n",
       "12682136538255982592             0.031822             0.007817  ...   \n",
       "12682136539845623808             0.120082             0.056707  ...   \n",
       "12682136545189167104               0.0388             0.022563  ...   \n",
       "12682136549614157824             0.057063             0.035063  ...   \n",
       "\n",
       "                           ra_pz    dec_pz  Norder_pz  Dir_pz  Npix_pz  \\\n",
       "_hipscat_index                                                           \n",
       "1152921506351677440   135.000339  0.002146          6       0     4096   \n",
       "1152921506624307200   135.001126  0.002717          6       0     4096   \n",
       "1152921510386597888   135.004395  0.004557          6       0     4096   \n",
       "1152921512148205568   135.002861  0.004971          6       0     4096   \n",
       "1152921515780472832   134.996025  0.004544          6       0     4096   \n",
       "...                          ...       ...        ...     ...      ...   \n",
       "12682136523865325568  224.997139 -0.009118          6   40000    45055   \n",
       "12682136538255982592  225.003142 -0.005594          6   40000    45055   \n",
       "12682136539845623808  225.003478 -0.004054          6   40000    45055   \n",
       "12682136545189167104  224.995777 -0.004141          6   40000    45055   \n",
       "12682136549614157824  224.999934 -0.002113          6   40000    45055   \n",
       "\n",
       "                      _dist_arcsec  coord_ra_hsc_g  coord_dec_hsc_g  \\\n",
       "_hipscat_index                                                        \n",
       "1152921506351677440            0.0      135.000339         0.002146   \n",
       "1152921506624307200            0.0      135.001126         0.002717   \n",
       "1152921510386597888            0.0      135.004395         0.004557   \n",
       "1152921512148205568            0.0      135.002861         0.004971   \n",
       "1152921515780472832            0.0      134.996025         0.004544   \n",
       "...                            ...             ...              ...   \n",
       "12682136523865325568           0.0      224.997139        -0.009118   \n",
       "12682136538255982592           0.0      225.003142        -0.005594   \n",
       "12682136539845623808           0.0      225.003478        -0.004054   \n",
       "12682136545189167104           0.0      224.995777        -0.004141   \n",
       "12682136549614157824           0.0      224.999934        -0.002113   \n",
       "\n",
       "                      modelfit_CModel_fracDev_hsc_g  \\\n",
       "_hipscat_index                                        \n",
       "1152921506351677440                             0.0   \n",
       "1152921506624307200                             1.0   \n",
       "1152921510386597888                             0.0   \n",
       "1152921512148205568                             0.0   \n",
       "1152921515780472832                             1.0   \n",
       "...                                             ...   \n",
       "12682136523865325568                            1.0   \n",
       "12682136538255982592                            0.0   \n",
       "12682136539845623808                            1.0   \n",
       "12682136545189167104                            1.0   \n",
       "12682136549614157824                            0.0   \n",
       "\n",
       "                      modelfit_CModel_exp_apCorr_hsc_g  \n",
       "_hipscat_index                                          \n",
       "1152921506351677440                           0.983837  \n",
       "1152921506624307200                           0.986229  \n",
       "1152921510386597888                           0.985443  \n",
       "1152921512148205568                           0.985805  \n",
       "1152921515780472832                             0.9875  \n",
       "...                                                ...  \n",
       "12682136523865325568                          0.978109  \n",
       "12682136538255982592                          0.978886  \n",
       "12682136539845623808                          0.978988  \n",
       "12682136545189167104                          0.978049  \n",
       "12682136549614157824                          0.978527  \n",
       "\n",
       "[128861334 rows x 34 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigdf_gal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7534586-8430-4839-830f-70c8d9ed283d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6a136bc-c7c4-4713-8d16-3516af33e8a8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d82180b5-dfac-4aa5-974f-e4533d7a5a29",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5efde9f1-208a-45cc-86b8-da0138293c62",
   "metadata": {},
   "outputs": [],
   "source": [
    "risk = cat_pz['photoz_risk_best'].compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c97a9ca9-47a1-4940-9369-9f324145935c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "43195dbf-8032-40ae-9a3f-992d07979ccb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.4562315e+07, 2.0674265e+07, 1.6772169e+07, 1.4010455e+07,\n",
       "        1.2359272e+07, 1.1366881e+07, 1.0806927e+07, 1.0494816e+07,\n",
       "        1.0316927e+07, 1.0225046e+07, 1.0167209e+07, 1.0177488e+07,\n",
       "        1.0261493e+07, 1.0341663e+07, 1.0387856e+07, 1.0475048e+07,\n",
       "        1.0626251e+07, 1.0865853e+07, 1.1095990e+07, 1.1274857e+07,\n",
       "        1.1413834e+07, 1.1514360e+07, 1.1602053e+07, 1.1663217e+07,\n",
       "        1.1702757e+07, 1.1738740e+07, 1.1765148e+07, 1.1788189e+07,\n",
       "        1.1832186e+07, 1.1903145e+07, 1.1995006e+07, 1.2093454e+07,\n",
       "        1.2161703e+07, 1.2167210e+07, 1.2076292e+07, 1.1841185e+07,\n",
       "        1.1469618e+07, 1.0920103e+07, 1.0248822e+07, 9.4806790e+06,\n",
       "        8.6337180e+06, 7.6941910e+06, 6.5965760e+06, 5.2418140e+06,\n",
       "        3.5826260e+06, 1.8815140e+06, 6.7403100e+05, 1.6193500e+05,\n",
       "        2.8587000e+04, 1.6740000e+03]),\n",
       " array([2.45366944e-04, 1.60500389e-02, 3.18547115e-02, 4.76593822e-02,\n",
       "        6.34640530e-02, 7.92687237e-02, 9.50733945e-02, 1.10878065e-01,\n",
       "        1.26682743e-01, 1.42487407e-01, 1.58292085e-01, 1.74096748e-01,\n",
       "        1.89901426e-01, 2.05706090e-01, 2.21510768e-01, 2.37315446e-01,\n",
       "        2.53120124e-01, 2.68924773e-01, 2.84729451e-01, 3.00534129e-01,\n",
       "        3.16338807e-01, 3.32143456e-01, 3.47948134e-01, 3.63752812e-01,\n",
       "        3.79557490e-01, 3.95362169e-01, 4.11166817e-01, 4.26971495e-01,\n",
       "        4.42776173e-01, 4.58580852e-01, 4.74385500e-01, 4.90190178e-01,\n",
       "        5.05994856e-01, 5.21799505e-01, 5.37604213e-01, 5.53408861e-01,\n",
       "        5.69213569e-01, 5.85018218e-01, 6.00822866e-01, 6.16627574e-01,\n",
       "        6.32432222e-01, 6.48236930e-01, 6.64041579e-01, 6.79846227e-01,\n",
       "        6.95650935e-01, 7.11455584e-01, 7.27260232e-01, 7.43064940e-01,\n",
       "        7.58869588e-01, 7.74674296e-01, 7.90478945e-01]),\n",
       " <BarContainer object of 50 artists>)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(risk,bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e198b91-55b2-4431-b5e6-3f1bc6a325e1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "lsdb_env",
   "language": "python",
   "name": "lsdb_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}