read_write_fitting_parameters.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "import os\n",
    "from astropy.io import fits\n",
    "from astropy import modeling\n",
    "import scipy.integrate as integrate\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_csv('/media/richard/Backup Plus/314kpair_DR16_final_Z_0.4_v11.5_star_fo_in_pair.csv',low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data[(data.SN_6020_15==True) & (data.CL_1_COUNTS_2==True)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 87%|████████▋ | 2245/2577 [05:43<00:21, 15.12it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no such file:spec-1379-53063-0124.fits\n",
      "no such file:spec-1379-53063-0233.fits\n",
      "no such file:spec-1379-53063-0331.fits\n",
      "no such file:spec-1379-53063-0348.fits\n",
      "no such file:spec-1379-53063-0441.fits\n",
      "no such file:spec-1379-53063-0447.fits\n",
      "no such file:spec-1379-53063-0630.fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2577/2577 [06:30<00:00,  6.60it/s]\n"
     ]
    }
   ],
   "source": [
    "f=open('/media/richard/Backup Plus/firefly_release/error_not_fit.txt','w')\n",
    "#data=data[6953:]\n",
    "for i in tqdm(data.index):\n",
    "    if os.path.exists(\"/media/richard/Backup Plus/firefly_release/run/output/spFly-%s\"%data.specname[i])==True:\n",
    "        fitting=fits.open(\"/media/richard/Backup Plus/firefly_release/run/output/spFly-%s\"%data.specname[i])\n",
    "        head=fitting[1].header\n",
    "        data.loc[data.index==i,'black_mass_best']=float(head['HIERARCH remnant_mass_blackholes'])\n",
    "        data.loc[data.index==i,'stellar_mass_best']=float(head['HIERARCH stellar_mass'])\n",
    "        data.loc[data.index==i,'total_mass_best']=float(head['HIERARCH total_mass'])\n",
    "        data.loc[data.index==i,'SFR_0']=float(head['HIERARCH SFR_ssp_0'])\n",
    "        try:\n",
    "            data.loc[data.index==i,'SFR_1']=float(head['HIERARCH SFR_ssp_1'])\n",
    "        except KeyError:\n",
    "            data.loc[data.index==i,'SFR_1']=-999\n",
    "        data.loc[data.index==i,'color_BV']=float(head['HIERARCH EBV'])\n",
    "        data.loc[data.index==i,'age_lightw']=float(head['HIERARCH age_lightW']) \n",
    "        data.loc[data.index==i,'age_massw']=float(head['HIERARCH age_massW'])\n",
    "    else:\n",
    "        print('no such file:%s'%data.specname[i])\n",
    "        f.write('%s \\n'%data.specname[i])\n",
    "        data.loc[data.index==i,'black_mass_best']=-999\n",
    "        data.loc[data.index==i,'stellar_mass_best']=-999\n",
    "        data.loc[data.index==i,'total_mass_best']=-999\n",
    "        data.loc[data.index==i,'SFR_0']=-999\n",
    "        data.loc[data.index==i,'SFR_1']=-999\n",
    "        data.loc[data.index==i,'color_BV']=-999\n",
    "        data.loc[data.index==i,'age_lightw']=-999\n",
    "        data.loc[data.index==i,'age_massw']=-999\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2577"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv('/media/richard/Backup Plus/314kpair_DR16_final_Z_0.4_v11.5_star_fo_in_pair2577.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, ' BH Mass for Best fit')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bl_mass=data.black_mass_best\n",
    "bl_mass=bl_mass.astype(float)\n",
    "\n",
    "mpl.rcParams['agg.path.chunksize']=1000\n",
    "mpl.rcParams['font.serif']='Times New Roman'\n",
    "mpl.rc('font',family='Times New Roman')\n",
    "ax=plt.subplot(1,1,1)\n",
    "civ=ax.hist(x=bl_mass,bins='auto',color='black',alpha=1,rwidth=1,linewidth=1,histtype='step')\n",
    "ax.set_xlabel(r'$log(M/M_{\\odot})$',fontsize=12)\n",
    "ax.set_xlim(5,11)\n",
    "#ax.set_ylim(0,100)\n",
    "ax.set_xticks(np.arange(5,11,0.5))\n",
    "plt.xticks(fontsize=12)\n",
    "'''ax.spines['bottom'].set_linewidth(1)\n",
    "ax.spines['top'].set_linewidth(1)\n",
    "ax.spines['left'].set_linewidth(1)\n",
    "ax.spines['right'].set_linewidth(1)'''\n",
    "#ax.set_yticks(np.arange(0,10000,1000))\n",
    "ax.axvline(x=5.5,ls='--',color='gray')\n",
    "ax.axvline(x=7.5,ls='--',color='gray')\n",
    "plt.title(r' BH Mass for Best fit')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    }
   ],
   "source": [
    "g=data.loc[(data.black_mass_best<8)&(data.black_mass_best>5),'GroupID']\n",
    "for i in g:print (i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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