secondary_sources_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from astropy.io import fits\n",
    "import numpy as np\n",
    "import os.path\n",
    "import matplotlib.pyplot as plt\n",
    "from astropy import wcs\n",
    "from astropy.nddata import Cutout2D\n",
    "from astropy import coordinates\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.wcs import WCS\n",
    "import matplotlib.gridspec as gridspec\n",
    "import aplpy\n",
    "import pandas as pd\n",
    "from photutils import SkyCircularAperture\n",
    "from photutils import aperture_photometry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "path = '/Users/justin/Documents/Master_Thesis/data/catalogues/chandra_7ms/tbl05.fits'\n",
    "cat = fits.open(path)[1].data\n",
    "a = ['goods_b', 'goods_v', 'goods_i', 'goods_z', 'candels_105_', 'candels_125_', 'candels_160_', 'hugs_', 'spitzer_ch1_', 'spitzer_ch2_']\n",
    "b = ['goods_b', 'goods_v', 'goods_i', 'goods_z', 'candels_105', 'candels_125', 'candels_160', 'hugs', 'spitzer_ch1', 'spitzer_ch2']\n",
    "c = ['goods', 'goods', 'goods', 'goods', 'candels', 'candels', 'candels', 'hugs', 'spitzer', 'spitzer']\n",
    "minarea = np.zeros(47)\n",
    "aperture = np.zeros(47)\n",
    "spitzer = np.zeros(47)\n",
    "minarea[25], minarea[27], minarea[37], minarea[38] = 50,50,50,50\n",
    "aperture[25], aperture[27], aperture[37], aperture[38] = 1.5,2.,1.7,1.7\n",
    "spitzer[25], spitzer[27], spitzer[37], spitzer[38] = 14.,5.,5.,4.\n",
    "aper_pixel = 1.\n",
    "min_area = 1.\n",
    "for j in range(len(a)):\n",
    "    for i in [25,27,37,38]:\n",
    "        if j < 4:\n",
    "            aper_pixel = aperture[i] / 0.03\n",
    "            min_area = minarea[i]\n",
    "            n_thresh = 64.\n",
    "            min_cont = 0.0001\n",
    "        elif j < 7:\n",
    "            aper_pixel = aperture[i] / 0.06\n",
    "            min_area = minarea[i]\n",
    "            n_thresh = 64.\n",
    "            min_cont = 0.0001\n",
    "        elif j == 7:\n",
    "            aper_pixel = aperture[i] * 9.4\n",
    "            min_area = minarea[i]/2.\n",
    "            n_thresh = 64.\n",
    "            min_cont = 0.0001\n",
    "        else:\n",
    "            if spitzer[i] > 10.:\n",
    "                aper_pixel = 0.\n",
    "            else:\n",
    "                aper_pixel = spitzer[i] *1.7\n",
    "            min_area = 1.\n",
    "            n_thresh = 64.\n",
    "            min_cont = 0.0001\n",
    "        if aper_pixel != 0.:\n",
    "            conf_path = ' /Users/justin/Documents/Master_Thesis/data/catalogues/' + c[j] + '/' + b[j] + '.conf'\n",
    "            im_path = ' /Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + '.fits'\n",
    "            dualim_path = ' /Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + '.fits,/Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + '.fits'\n",
    "            cat_path = ' /Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/' + c[j] + '/cat_' + a[j] + 'x' + str(i+1) + '.cat'\n",
    "            wht_path = ' /Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + 'wht.fits'\n",
    "            rms_path = ' /Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + 'rms.fits'\n",
    "            rmswht_path = ' /Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + 'rms.fits,/Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + 'wht.fits'\n",
    "            check_path = ' /Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/' + c[j] + '/cat_' + a[j] + 'x' + str(i+1) + '_aper.fits,/Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/' + c[j] + '/cat_' + a[j] + 'x' + str(i+1) + '_bkg.fits,/Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/' + c[j] + '/cat_' + a[j] + 'x' + str(i+1) + '_bkg_rms.fits' \n",
    "            if j < 4:\n",
    "                path = 'sex -c' + conf_path + im_path + ' -CATALOG_NAME' + cat_path + ' -WEIGHT_TYPE MAP_RMS -WEIGHT_GAIN N -WEIGHT_IMAGE' + rms_path + ' -DETECT_MINAREA ' + str(min_area) + ' -PHOT_APERTURES ' + str(aper_pixel) + ' -CHECKIMAGE_NAME' + check_path + ' -BACK_SIZE 90 -DEBLEND_MINCONT ' + str(min_cont) + ' -DEBLEND_NTHRESH ' + str(n_thresh) + ' -MASK_TYPE NONE'\n",
    "            elif j < 7:\n",
    "                path = 'sex -c' + conf_path + im_path + ' -CATALOG_NAME' + cat_path + ' -WEIGHT_TYPE MAP_RMS -WEIGHT_GAIN N -WEIGHT_IMAGE' + rms_path + ' -DETECT_MINAREA ' + str(min_area) + ' -PHOT_APERTURES ' + str(aper_pixel) + ' -CHECKIMAGE_NAME' + check_path + ' -BACK_SIZE 60 -DEBLEND_MINCONT ' + str(min_cont) + ' -DEBLEND_NTHRESH ' + str(n_thresh) + ' -MASK_TYPE NONE'\n",
    "            elif j == 7:\n",
    "                path = 'sex -c' + conf_path + im_path + ' -CATALOG_NAME' + cat_path + ' -WEIGHT_TYPE MAP_RMS -WEIGHT_GAIN N -WEIGHT_IMAGE' + rms_path + ' -DETECT_MINAREA ' + str(min_area) + ' -PHOT_APERTURES ' + str(aper_pixel) + ' -CHECKIMAGE_NAME' + check_path + ' -BACK_SIZE 50 -DEBLEND_MINCONT ' + str(min_cont) + ' -DEBLEND_NTHRESH ' + str(n_thresh) + ' -MASK_TYPE NONE'\n",
    "            else:\n",
    "                path = 'sex -c' + conf_path + dualim_path + ' -CATALOG_NAME' + cat_path + ' -WEIGHT_TYPE MAP_RMS,MAP_WEIGHT -WEIGHT_GAIN N,Y -WEIGHT_IMAGE' + rmswht_path + ' -DETECT_MINAREA ' + str(min_area) + ' -PHOT_APERTURES ' + str(aper_pixel) + ' -CHECKIMAGE_NAME' + check_path + ' -BACK_SIZE 17 -DEBLEND_MINCONT ' + str(min_cont) + ' -DEBLEND_NTHRESH ' + str(n_thresh) + ' -MASK_TYPE NONE -FILTER N'\n",
    "            os.system(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "flux=[]\n",
    "fluxerr=[]\n",
    "ra = cat.field('RA')\n",
    "dec = cat.field('DEC')\n",
    "for i in range(len(a)):\n",
    "    flux.append(np.zeros(47))\n",
    "    fluxerr.append(np.zeros(47))\n",
    "for i in [25,27,37,38]: #H band standard\n",
    "    path = '/Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/candels/cat_candels_160_' + 'x' + str(i+1) + '.cat'\n",
    "    t1 = pd.read_csv(path, delim_whitespace=True, header=None, names=['#', 'x', 'y', 'RA', 'Dec', 'MagAuto', 'MagErrAuto', 'FluxAuto', 'FluxErrAuto', 'MagAper', 'MagErrAper', 'FluxAper', 'FluxErrAper'])\n",
    "    if i == 38:\n",
    "        radius = ((t1['RA']-53.1813364).pow(2) + (t1['Dec']+27.7292173).pow(2)).pow(0.5)\n",
    "    else:\n",
    "        radius = ((t1['RA']-ra[i]).pow(2) + (t1['Dec']-dec[i]).pow(2)).pow(0.5)\n",
    "    for j in range(len(radius)):\n",
    "        if radius[j] == min(radius):\n",
    "            flux[6][i] = t1['FluxAper'][j]\n",
    "            fluxerr[6][i] = t1['FluxErrAper'][j]\n",
    "            ra[i] = t1['RA'][j]\n",
    "            dec[i] = t1['Dec'][j]\n",
    "for j in range(len(a)): #all bands\n",
    "    for i in [25,27,37,38]:\n",
    "        if ((j > 7) & (i == 25)) | (j==6):\n",
    "            pass\n",
    "        else:\n",
    "            path = '/Users/justin/Documents/Master_Thesis/data/catalogues/cutouts/' + c[j] + '/cat_' + a[j] + 'x' + str(i+1) + '.cat'\n",
    "            t5 = pd.read_csv(path, delim_whitespace=True, header=None, names=['#', 'x', 'y', 'RA', 'Dec', 'MagAuto', 'MagErrAuto', 'FluxAuto', 'FluxErrAuto', 'MagAper', 'MagErrAper', 'FluxAper', 'FluxErrAper'])\n",
    "            snratio = t5['FluxAper']/t5['FluxErrAper']\n",
    "            radius = ((t5['RA']-ra[i]).pow(2) + (t5['Dec']-dec[i]).pow(2)).pow(0.5)\n",
    "            n=-1\n",
    "            for k in range(len(radius)):\n",
    "                if (radius[k] < 0.2/3600.) & (snratio[k] > 1.):\n",
    "                    if n == -1:\n",
    "                        n = k\n",
    "                    else:\n",
    "                        if radius[k] < radius[n]:\n",
    "                            n = k\n",
    "            if n != -1:\n",
    "                flux[j][i] = t5['FluxAper'][n]\n",
    "                fluxerr[j][i] = t5['FluxErrAper'][n]\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
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   "outputs": [
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     "name": "stdout",
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      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   6.18390093e-07,   0.00000000e+00,\n",
      "         6.25774053e-07,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   1.02229853e-06,   8.13933185e-07,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00]), array([  0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   1.07526112e-06,   0.00000000e+00,\n",
      "         1.36302059e-06,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   1.54737036e-06,   1.12333373e-06,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00]), array([  0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   1.54353860e-06,   0.00000000e+00,\n",
      "         2.46522242e-06,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   2.65171401e-06,   1.69532803e-06,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00]), array([  0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   2.33235998e-06,   0.00000000e+00,\n",
      "         5.76870494e-06,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   4.15617196e-06,   2.62154397e-06,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00]), array([  0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         1.68803502e-05,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   8.66603194e-06,   5.42354129e-06,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00]), array([  0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         2.11614448e-05,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   9.34439152e-06,   5.28950774e-06,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
      "         0.00000000e+00,   0.00000000e+00])]\n"
     ]
    }
   ],
   "source": [
    "for j in range(len(a)):\n",
    "    for i in [25,27,37,38]:  \n",
    "        if flux[j][i] == 0:\n",
    "            path = '/Users/justin/Documents/Master_Thesis/data/surveys/cutouts/' + c[j] + '/cutout_' + a[j] + 'x' + str(i+1) + '.fits'\n",
    "            im = fits.open(path)[0]\n",
    "            position = SkyCoord(ra[i]*u.deg, dec[i]*u.deg, frame='icrs')\n",
    "            rad=aperture[i]/2.\n",
    "            if j > 7:\n",
    "                if spitzer[i]>10.:\n",
    "                    rad=(spitzer[i]-10.)/2.\n",
    "                else:    \n",
    "                    rad=spitzer[i]/2.\n",
    "            circaper = SkyCircularAperture(position, r=rad*u.arcsec)\n",
    "            phot_table = aperture_photometry(im, circaper)\n",
    "            if phot_table['aperture_sum'][0] < 0:\n",
    "                print('negative flux ' + str(phot_table['aperture_sum'][0]) + ' for source x' + str(i+1) + ' with filter ' + b[j])\n",
    "            fluxerr[j][i] = phot_table['aperture_sum'][0]\n",
    "#convert to Jansky\n",
    "fluxratio = [1.95338693e-7,9.238062e-8,1.98796897e-7,4.12286699e-7,1.12851106e-7,1.16912375e-7,1.51876003e-7,9.9999999e-10,3.92276e-6,4.80825e-6]\n",
    "for j in range(len(fluxratio)):\n",
    "    flux[j] = flux[j]*fluxratio[j]\n",
    "    fluxerr[j] = fluxerr[j]*fluxratio[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "flux_cat = [[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[]]\n",
    "for i in [25,27,37,38]:\n",
    "    flux_cat[0].append(1001 + i)\n",
    "    flux_cat[1].append(flux[0][i])\n",
    "    flux_cat[2].append(fluxerr[0][i])\n",
    "    flux_cat[3].append(flux[1][i])\n",
    "    flux_cat[4].append(fluxerr[1][i])\n",
    "    flux_cat[5].append(flux[2][i])\n",
    "    flux_cat[6].append(fluxerr[2][i])\n",
    "    flux_cat[7].append(flux[3][i])\n",
    "    flux_cat[8].append(fluxerr[3][i])\n",
    "    flux_cat[9].append(flux[4][i])\n",
    "    flux_cat[10].append(fluxerr[4][i])\n",
    "    flux_cat[11].append(flux[5][i])\n",
    "    flux_cat[12].append(fluxerr[5][i])\n",
    "    flux_cat[13].append(flux[6][i])\n",
    "    flux_cat[14].append(fluxerr[6][i])\n",
    "    flux_cat[15].append(flux[7][i])\n",
    "    flux_cat[16].append(fluxerr[7][i])\n",
    "    flux_cat[17].append(flux[8][i])\n",
    "    tf1=(0.15*flux[8][i])+fluxerr[8][i]\n",
    "    flux_cat[18].append(tf1)\n",
    "    flux_cat[19].append(flux[9][i])\n",
    "    tf2=(0.15*flux[9][i])+fluxerr[9][i]\n",
    "    flux_cat[20].append(tf2)\n",
    "\n",
    "ar = np.array(flux_cat)\n",
    "at = np.transpose(ar)\n",
    "df = pd.DataFrame(data=at, index=None, columns=['id','F233','E233','F236','E236','F238','E238','F240','E240','F202','E202','F203','E203','F205','E205','F269','E269','F18','E18','F19','E19'])\n",
    "df['id'] = df['id'].astype('int64')\n",
    "path = '/Users/justin/Documents/Master_Thesis/softwares/eazy/inputs/test_cat_2.cat'\n",
    "df.to_csv(path_or_buf=path, sep=' ', index=False)\n",
    "path = \"sed -i '' '/id/s/^/# /g' ../softwares/eazy/inputs/test_cat_2.cat\"\n",
    "os.system(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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