notebook2_identify_point_and_diffuse_sources.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e5f97367-89e0-4207-8dd3-6504dd195549",
   "metadata": {},
   "source": [
    "# UVIT view of Centaurus A; a detailed study on positive AGN feedback\n",
    "## Jupyter notebooks used in the study: Notebook 2\n",
    "\n",
    "We are making the scripts used for the study publicly available. This notebook is associated with the section 2.2 of the article. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cc7a3288-120f-451f-b745-c187a15667dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Could not import regions, which is required for some of the functionalities of this module.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import astropy.units as u\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from astropy.io import fits\n",
    "from astropy.wcs import WCS\n",
    "from astropy.stats import gaussian_fwhm_to_sigma, SigmaClip\n",
    "from astropy.table import join, Table, setdiff\n",
    "from astropy.nddata import Cutout2D\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.convolution import Gaussian2DKernel, convolve\n",
    "from astroquery.xmatch import XMatch\n",
    "from photutils.aperture import CircularAperture\n",
    "from photutils.detection import DAOStarFinder\n",
    "from photutils.background import Background2D, SExtractorBackground\n",
    "from photutils.segmentation import detect_threshold, detect_sources, deblend_sources, SourceCatalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "525b1e48-f606-4e86-bc04-e0914e75ca3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "position = SkyCoord('13:26:16.9588 -42:51:36.902', frame='icrs', unit=(u.hourangle, u.deg))\n",
    "size = (16.99948 * u.arcmin, 14.07162 * u.arcmin)\n",
    "\n",
    "# distance to centaurus A. \n",
    "distance = 3.8 #mpc\n",
    "pixel_scale = 0.416858 #arcseconds\n",
    "pixelscale_in_Kpc = distance * 1e3 * np.deg2rad(pixel_scale / 3600)\n",
    "pixelarea_in_kpc = pixelscale_in_Kpc ** 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "60609aed-33ad-4d8c-ac53-40c335e1e5b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: FITSFixedWarning: RADECSYS= 'ICRS ' / Julian coordinate reference frame \n",
      "the RADECSYS keyword is deprecated, use RADESYSa. [astropy.wcs.wcs]\n"
     ]
    }
   ],
   "source": [
    "where_is_data = 'data/'\n",
    "F148W_hdu = fits.open(where_is_data + 'wcs_AS1G08_023T01_9000001978uvtFIIPC00F1A_l2imb.fits.gz')\n",
    "F148W_error_hdu = fits.open(where_is_data + 'wcs_AS1G08_023T01_9000001978uvtFIIPC00F1A_l2erb.fits.gz')\n",
    "\n",
    "final_tbl = Table.read('final_table.fits') # generated by Notebook1\n",
    "\n",
    "F148W_wcs = WCS(F148W_hdu[0].header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "44fd8d09-427b-4855-9d24-20438f18f034",
   "metadata": {},
   "outputs": [],
   "source": [
    "F148W_pixel_scale = (F148W_wcs.proj_plane_pixel_scales()[1].to(u.arcsec) + F148W_wcs.proj_plane_pixel_scales()[0].to(u.arcsec)) / 2\n",
    "F148W_pixel_scale = F148W_pixel_scale.value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e4817ab5-38a8-4c34-83f4-ac59c1afc66c",
   "metadata": {},
   "outputs": [],
   "source": [
    "F148W_cutout = Cutout2D(F148W_hdu[0].data, position, size, F148W_wcs)\n",
    "F148W_error_cutout = Cutout2D(F148W_error_hdu[0].data, position, size, F148W_wcs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e02c3eaa-010d-4d4d-a346-b6b75e374e2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "sigma_clip = SigmaClip(sigma = 3., maxiters = 10)\n",
    "bkg_estimator = SExtractorBackground()\n",
    "\n",
    "F148W_bkg = Background2D(F148W_cutout.data, (400, 400), filter_size = (3, 3), sigma_clip = sigma_clip,\n",
    "                       bkg_estimator = bkg_estimator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b15f4a9c-1a9d-4ab4-9f19-18fa731df7dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "F148W_fwhm = (1.4 / F148W_pixel_scale)  # FUV FWHM = 1.4 arcseconds\n",
    "F148W_sigma = (1.4 / F148W_pixel_scale) * gaussian_fwhm_to_sigma  # FUV FWHM = 1.4 arcseconds\n",
    "F148W_kernel = Gaussian2DKernel(F148W_sigma)\n",
    "F148W_smoothed_data = convolve(F148W_cutout.data, F148W_kernel)\n",
    "F148W_smoothed_bkg = convolve(F148W_bkg.background, F148W_kernel)\n",
    "\n",
    "daofind = DAOStarFinder(fwhm = F148W_fwhm, threshold = 1 * np.median(F148W_bkg.background_rms))  \n",
    "sources = daofind(F148W_smoothed_data - F148W_smoothed_bkg)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1ed75b6e-1541-4ff8-99a0-406eded593bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "146"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sources)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "588c78d8-e887-4c72-8492-43f8446a0d28",
   "metadata": {},
   "outputs": [],
   "source": [
    "skycoo = F148W_cutout.wcs.pixel_to_world(sources['xcentroid'], sources['ycentroid'])\n",
    "sources['RA_J2000'] = skycoo.ra.degree\n",
    "sources['DEC_J2000'] = skycoo.dec.degree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "88084afb-bdf9-40bb-9a22-dafabf0b83e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "GAIA_stars_tbl = XMatch.query(cat1 = sources,\n",
    "                              cat2 = 'vizier:I/352/gedr3dis',\n",
    "                              max_distance = 1 * u.arcsec, \n",
    "                              colRA1 = 'RA_J2000',\n",
    "                              colDec1 = 'DEC_J2000')\n",
    "\n",
    "not_stars_tbl = setdiff(sources, GAIA_stars_tbl, keys = 'id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7ea2fc5a-0d73-4046-8866-c5380a7567c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "102"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(not_stars_tbl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d984733d-d8ce-47c8-ada8-bb82c1dcda4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "not_stars_tbl_coo = SkyCoord(ra = not_stars_tbl['RA_J2000'] * u.degree, dec = not_stars_tbl['DEC_J2000'] * u.degree)\n",
    "final_tbl_coo = SkyCoord(ra = final_tbl['RA_J2000'] * u.degree, dec = final_tbl['DEC_J2000'] * u.degree)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ff849253-3033-4330-a0bd-4310b854c478",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Star-forming sources\n",
    "max_sep = 2.0 * u.arcsec\n",
    "idx, d2d, d3d = final_tbl_coo.match_to_catalog_sky(not_stars_tbl_coo)\n",
    "sep_constraint = d2d < max_sep\n",
    "SF_sources_tbl = final_tbl[sep_constraint]\n",
    "SF_sources_tbl.write('SF_sources.fits', format = 'fits', overwrite = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0f08fb62-65ec-4208-a234-2a5b6c6c830b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(SF_sources_tbl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6396a912-81b1-428a-9990-4d141ef56465",
   "metadata": {},
   "outputs": [],
   "source": [
    "# diffuse sources\n",
    "nonSF_sources_tbl = final_tbl[~sep_constraint]\n",
    "nonSF_sources_tbl.write('nonSF_sources.fits', format = 'fits', overwrite = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5bf6d3e4-7042-4344-820d-2cae0cba4c91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "269"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nonSF_sources_tbl)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}