{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# PSF normalization\n", "\n", "Let us assume that we have reduced an observation, for which we have determined the PSF by stacking the flux of point-like sources. The PSF we obtain will not be as high S/N as the instrumental PSF that has been determined by the instrument team. Moreover, it is likely to be fattened due to the some small pointing errors. We need to find out what fraction of a point-like flux the PSF we have determined represent. In order to do this, we use the growth curve of the theoretical PSF that has been determine by the instrument team, and compare it to the growth curve we determine from our PSF.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# import what we will need. \n", "%matplotlib inline\n", "import numpy as np\n", "from astropy.io import fits\n", "from astropy.table import Table\n", "from astropy.io import ascii as asciiread\n", "from matplotlib import pyplot as plt\n", "from scipy import interpolate \n", "from scipy import special\n", "from scipy import signal\n", "from scipy import fftpack" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2) Real data: MIPS observations\n", "\n", "We will look at a real stack of point sources in the MIPS ELAIS-N2 observations, and try to find its normalization factor. \n", "\n", "Let's load the stacked PSF:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "stackhd_im = fits.open('./data/70101880.70101880-0.MIPS.1.help.fits')\n", "stackhd = fits.open('./data/70101880.70101880-0.MIPS.1.help.psf.fits')\n", "psf = stackhd[1].data\n", "hd = stackhd[1].header\n", "cpix=np.int((hd['NAXIS1']+1)/2.0)\n", "rad=40\n", "plt.imshow(psf[cpix-rad-1:cpix+rad,cpix-rad-1:cpix+rad])\n", "plt.colorbar()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "resol= np.abs(stackhd[1].header['CD1_1'])/np.abs(stackhd_im[1].header['CD1_1'])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "1.0" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "resol" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "hdp = stackhd[2].header" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Read in MIPS 24 $\\mathrm{\\mu m}$ Instrumental PSF\n", "We take the instrumental PSF from [Gonzalo J.Aniano's webpage](http://www.astro.princeton.edu/~ganiano/Kernels/Ker_2017/PSF_FITS_Files/)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "insthd = fits.open('../data/PSF_Original_MIPS_24.fits.gz')\n", "psf_inst_full = insthd[0].data\n", "hdinst = insthd[0].header\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "#hdinst\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "rad=1000\n", "cpix=np.int((hdinst['NAXIS1']+1)/2.0)\n", "\n", "plt.imshow(psf_inst_full[cpix-rad-1:cpix+rad,cpix-rad-1:cpix+rad])\n", "#psf_inst=psf_inst_full[hdinst['CRPIX1']-rad-1:hdinst['CRPIX1']+rad,hdinst['CRPIX2']-rad-1:hdinst['CRPIX2']+rad]\n", "psf_inst=psf_inst_full[cpix-rad-1:cpix+rad,cpix-rad-1:cpix+rad]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Normalise instrumental PSF such that integral=1" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "psf_inst=psf_inst/(np.sum(psf_inst))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's build the growthcurve for our PSFs." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# find the brightest pixel, it will be our center.\n", "jmax, imax = np.unravel_index(np.argmax(psf), psf.shape)\n", "jmax_inst, imax_inst = np.unravel_index(np.argmax(psf_inst), psf_inst.shape)\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# build the array of coordinates\n", "x = np.arange(hd['NAXIS1'])\n", "y = np.arange(hd['NAXIS2'])\n", "xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')\n", "xp = (xv-imax)*np.abs(hd['CD1_1'])*3600.\n", "yp = (yv-jmax)*np.abs(hd['CD2_2'])*3600.\n", "r = np.sqrt(xp**2 + yp**2)\n", "\n", "x_inst = np.arange(1+rad*2)\n", "y_inst = np.arange(1+rad*2)\n", "xv_inst, yv_inst = np.meshgrid(x_inst, y_inst, sparse=False, indexing='xy')\n", "xp_inst = (xv_inst-imax_inst)*np.abs(hdinst['CD1_1']*3600.0)\n", "yp_inst = (yv_inst-jmax_inst)*np.abs(hdinst['CD1_1']*3600.0)\n", "r_inst = np.sqrt(xp_inst**2 + yp_inst**2)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# build the growth curve\n", "radii = np.unique(r)\n", "encircled_flux = np.zeros(radii.shape)\n", "nbpix = np.zeros(radii.shape)\n", "for i, radius in enumerate(radii):\n", " idj, idi = np.where(r <= radius)\n", " nbpix[i] =len(idi)\n", " encircled_flux[i] = np.sum(psf[idj, idi])*resol**2\n", " #multiply by ((np.abs(hd['CDELT1'])*3600.)**2)/4.25E10 as map is in units of MJy/sr\n", " #encircled_flux[i] = np.sum(psf[idj, idi])*((np.abs(hd['CD1_1'])*3600.)**2)/4.25E10" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Normally we run the code below for the instrumental PSF. This is slow and remains the same for each field so I just load up the result instead." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```python\n", "radii_inst = np.unique(r_inst)\n", "encircled_flux_inst = np.zeros(radii_inst.shape)\n", "nbpix_inst = np.zeros(radii_inst.shape)\n", "for i, radius in enumerate(radii_inst):\n", " if i % 1000 == 0:\n", " print(i,len(radii_inst))\n", " idj, idi = np.where(r_inst <= radius)\n", " nbpix_inst[i] =len(idi)\n", " encircled_flux_inst[i] = np.sum(psf_inst[idj, idi])\n", "``` " ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true }, "outputs": [], "source": [ "inst_data=np.load('../data/MIPS_encircled_flux_inst.npz')\n", "encircled_flux_inst=inst_data['encircled_flux_inst']\n", "radii_inst=inst_data['radii_inst']" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Encircled flux')" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEKCAYAAAAfGVI8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvqOYd8AAAIABJREFUeJzt3Xd8lfX9/vHXm4QwQtgB2WGDso0K4sK9V7W4sVqx37qqdVWtte2vjg6t2mqlxTrq3gvcCi723kP2CoRAAiEkOXn//jg3GjGEEHJyn+Rcz8eDR865zzk5l7fJuXKvz8fcHRERSVx1wg4gIiLhUhGIiCQ4FYGISIJTEYiIJDgVgYhIglMRiIgkOBWBiEiCUxGIiCQ4FYGISIJLDjtARbRs2dIzMjLCjiEiUqNMnTp1k7un7+15NaIIMjIymDJlStgxRERqFDNbUZHnadeQiEiCUxGIiCQ4FYGISIJTEYiIJDgVgYhIglMRiIgkOBWBiEiCqxHXEYiI1EZFkRIWrs8jd0cRuQVF5BYUU1AUYWdRCYWREnYWRTh3UHsyWqbGNIeKQEQkhpZkbeOrJZvYuqOInPxCpq7IYfP2QnYWl7Axb+deXz+wUzMVgYhIvNtZHOHbjdvJ2V7I4qxtvDF9DTn5hRQURdiQ+/2HfWpKEulp9RjUsRmp9ZKol5xEs4YpDO7SnLT6dUmrn0zDlCRSkutQLzmJukmGmcU8v4pARGQfFRRF+HxhFuu2FrAiO583Z6xhS37Rd493aN6AQR2bUT85iYb1kjjv4Pb0aJ1G3aT4PCyrIhAR2YudxRE+nZ/F10uzWbd1BxOXbSavoPi7x9s1bcDvzzyIVmn1aZ6aQueWqaQkx+eHfllUBCIiu3F3Zq/ZypjZ61mwPpfJyzazvTBCWr1k2jVrwOAuLbj4sI70a9+UhilJ1EuuUy27cGJFRSAiAuQXFjN+0SY+W5DFuEUbWZ9bQN0ko0frNAZ1asaFh3bkxANbkxynu3f2R8yKwMw6AM8ABwAlwCh3f9jM7gGuAjYGT73D3cfEKoeIyJ7sKIwwfWUOXy/N5ulvlpNXUExa/WSO7N6SY3q04qQ+B9CkQd2wY8ZcLLcIioFfu/s0M0sDpprZR8FjD7n7X2P43iIie7QxbycPfrSQt2asJb8wghn0b9+Um07owZCuLeL2oG6sxKwI3H0dsC64nWdm84F2sXo/EZHyFBaX8I9PF/P2zLUsz84H4MjuLbliaGcGdWqWEH/570m1HCMwswxgIDARGApca2aXAVOIbjXkVEcOEUks7s60lTm8MX0NH8/LYn1uAUf3SOeiwzrSt11TDsloViv3+e8rc/fYvoFZI2Ac8Cd3f93MWgObAAf+CLRx9yvKeN1IYCRAx44dD16xokIzromI4O5MXLaZ+8bMZ+bqraSmJNG/Q1MuOqwjp/drG3a8amNmU909c2/Pi+kWgZnVBV4DnnP31wHcfUOpx/8NvFvWa919FDAKIDMzM7ZtJSK1wtYdRfx7/Le8P3c9S7K2kZJch3vOOJDzMzuQWk8nSe5JLM8aMmA0MN/dHyy1vE1w/ADgHGBOrDKISGLILyzmo3kbuHfMfDbm7eTQzs0ZMeQgjj+wNW2aNAg7XtyLZUUOBS4FZpvZjGDZHcCFZjaA6K6h5cDVMcwgIrXYtp3FPDB2AW9MX8O2ncUk1TFevnoImRnNw45Wo8TyrKEvgbIutdM1AyKyX3YURnh31lqe/Go589flcu7Adpw5oC2DOjWjcf3EPfunsrTTTERqjJIS57lJK3nww4Xk5BfRslEKfzzrIC4dkhF2tBpNRSAiNcL0lTn85YOFfL00m26tGvHg8AEc2a2lTv+sAioCEYlryzdt56435/Dlkk00bViXu07rzeWHZ6gAqpCKQETiUqTEeWnyKh77fAl5BcX85pReXDy4E410GmiV0xoVkbgzdUUO178wnTVbdpCaksQzVx7KwZ10JlCsqAhEJG64Oze+NIM3Z6wlrX4yfzy7D5cc1rFGj/VfE6gIRCR0JSXOe7PXMfrLZcxYtYXzD27PXacfmNADwVUnFYGIhMrd+e1bc3hu4kraNqnPL47uys0n9tDB4GqkIhCR0CzJyuM3r89m8vIcrjqyM7ed3EsFEAIVgYhUu0iJ89TXy/nz+wsojJRw12m9ufKIzjoWEBIVgYhUq4KiCNe9MJ2P5m3gkIxm/O6Mg+jTrknYsRKaikBEqs2mbTu56eWZjF+0kbtO683Pj+wSdiRBRSAi1eT9Oeu5/fVZ5BdGuPH4Hlx5ROewI0lARSAiMffl4k1c+/w02jZtwP+uPEy7guKMikBEYmrs7HVc/+J0Wjeuz2v/dzjpafXCjiS7URGISEzsLI7wz8+W8sgnixnUsSmjRxxCs9SUsGNJGVQEIlLlCotL+NWLMxg7Zz2DuzTn4QsGqgTimIpARKrccxNXMHbOeq4Z1pVbTuoVdhzZCxWBiFQZd+eB9xfy4uSV9GvfhJtP7Bl2JKkAXcstIlXm0U+X8K9xS0mrn8y95/TVlcI1hLYIRKRKvD5tNQ9/sphurRrx1jVDSdUEMjWGtghEZL9NX5nDTS/PpGPzhrxw1WCVQA2jIhCR/ZJXUMQtr86iXnIdXhw5WNcJ1ECqbRGptKJICZf/dzLLNm3nP5dl0rpx/bAjSSVoi0BEKqU4Er1WYOqKHO4/ty/DerUKO5JUkopARCrls4UbeW/2On55TFfOO7h92HFkP6gIRGSfuTt/em8eLVJTuP647jpNtIZTEYjIPvvfhBUsz87niiM6U79uUthxZD+pCERkn3y1ZBO/fWsuHZo34IJDOoQdR6pAzIrAzDqY2WdmNt/M5prZDcHy5mb2kZktDr42i1UGEala01bm8H//m0pqShLvXHsELRrpVNHaIJZbBMXAr929NzAYuMbMDgRuBz5x9+7AJ8F9EYlzW/OL+PnTU0irX5fRlx9C04YaTbS2iFkRuPs6d58W3M4D5gPtgLOAp4OnPQ2cHasMIlJ1rn9xOpu3F/LQ8AEM7tIi7DhSharlGIGZZQADgYlAa3dfB9GyAMo8+djMRprZFDObsnHjxuqIKSJ7MHv1VsYt2sj1x3Xn0M7Nw44jVSzmRWBmjYDXgF+5e25FX+fuo9w9090z09PTYxdQRMqVW1DENc9Po1nDuvz8SE04XxvFtAjMrC7REnjO3V8PFm8wszbB422ArFhmEJHK21kc4TevzWZ1Tj6jLsukcf26YUeSGIjlWUMGjAbmu/uDpR56GxgR3B4BvBWrDCKyf54Y9y3vzV7Hr0/sySEZ2iVUW8Vy0LmhwKXAbDObESy7A7gfeNnMrgRWAufHMIOIVNJbM9bw0MeLOLJ7S64Z1i3sOBJDMSsCd/8S2NN158fF6n1FZP/NW5vLDS/OoFOLhvz7ssyw40iM6cpiEfmBvIIibnxpBk0a1OWBn/TTEBIJQEUgIt/ZURhhxJOTWLpxG3/X9QIJQxPTiMh3Hnh/AdNWbuHvwwdofoEEoi0CEQFgS34hr09bzbCe6Zw9sF3YcaQaaYtARFi/tYDfvzOX3IJibjyhR9hxpJqpCEQSXHGkhMv/O4kF6/MYMaQTfds1CTuSVDMVgUgCi5Q4t7w6iwXr87j9lF784uiuYUeSEOgYgUgCe2L8Ut6YvoZzB7Zj5JFdwo4jIdEWgUiCWpKVx18/WEiX9FT+9tP+mnc4gWmLQCRB3f3WXFKS6/Dw8IEqgQSnIhBJQF8u3sTXS7O55LBO9G2vg8OJTkUgkmCe+moZl4yeSOvG9bh4cKew40gc0DECkQSyJCuP+8YuYFjPdP5x0SBS6+kjQCqwRRBMOL/7smNikkZEYiZ7205+9tRkUpLrcN+5/VQC8p2K7Bp62cxus6gGZvYocF+sg4lI1dm0bSdHPPAZqzbv4O/DB3BAk/phR5I4UpEiOAzoAHwNTAbWEp10RkRqiEc+WcyOogh3ntqb43q3DjuOxJmKFEERsANoANQHlrl7SUxTiUiVmfBtNs98s4JT+x7AVUfpojH5sYoUwWSiRXAIcARwoZm9GtNUIlIl1m8t4OdPTyGpjnH7yb3DjiNxqiJHi6509ynB7fXAWWZ2aQwziUgVcHfuenM2kRLn1V8MoWOLhmFHkjhVkSLIMrOOuy0bF4swIlI1Vmbn8//em8fH87O449ReDOzYLOxIEscqUgTvAU50Ivr6QGdgIXBQDHOJSCWVlDi3vz6Lr5dmc82wrlwxtHPYkSTO7bUI3L1v6ftmNgi4OmaJRGS/jP5yGV8vzeayIZ245aReYceRGmCfh5hw92lEDxyLSJzJyivgrx8upNcBafz29B9dCypSpr1uEZjZTaXu1gEGARtjlkhEKqUoUsLdb85lZ3EJ/7hoEHWTNJSYVExFjhGklbpdTPSYwWuxiSMilfXoJ4t5f+56juvVim6tGoUdR2qQihwj+H11BBGRyikoinDLq7N4Z+ZaTuvXhn9eNCjsSFLD7LEIzOwdomcLlcndz4xJIhHZJ/+bsIJ3Zq7l6qO6cOMJPcKOIzVQeVsEf622FCJSKd9u3Mb9YxdwcKdm3H5KL800JpVS3tGku919HHCqu4/b/d/evrGZPWlmWWY2p9Sye8xsjZnNCP6dWhX/ESKJKGd7ISP+O4k6dUwlIPulvC2CNmZ2NHCmmb1I9IKy7wSnkZbnKeAfwDO7LX/I3bW1IbKffv3KTDbk7uSFqwZzcCddOSyVV14R3A3cDrQH/sYPi8CBY8v7xu4+3swy9jOfiJTh5Smr+HRBFtcM66oSkP22xyJw91eBV83st+7+xyp8z2vN7DJgCvBrd8+pwu8tUuu9PGUVt746i4M7NeP647qHHUdqgb1ecVLFJfA40BUYAKwjuqVRJjMbaWZTzGzKxo26fk0E4KN5G7jttVn0bJ3G81cdRr3kpLAjSS1QrZceuvsGd48EE9v8Gzi0nOeOcvdMd89MT0+vvpAicWrM7HXc/tosOrdI5YWRg1UCUmWqtQjMrE2pu+cAc/b0XBH53pKsPH753DRSkuvw2CWDaJ6aEnYkqUXKu6CseXkvdPfN5T1uZi8AxwAtzWw18DvgGDMbQPRg83I0iqlIhdzw4gwa1E3ihasGk9EyNew4UsuUd9bQVL6fh6AjkBPcbgqsJDovwR65+4VlLB5duZgiievrpZuYuzaXm0/soRKQmCjvrKHOAGb2L+Btdx8T3D8FOL564okkrkiJ8+cPFjD6i2WkpiRxfmaHsCNJLVWRYwSH7CoBAHcfCxwdu0giAvD450t4Yty39G3fhPd/dRStG9cPO5LUUhUZhnqTmd0F/I/orqJLgOyYphJJcE+MW8pfP1xE91aNePnqIZpbQGKqIj9dFwLpwBvBv/RgmYjEwKINedw3dgFHdm/JW9cOVQlIzFVkPoLNwA1m1sjdt1VDJpGEVVAU4brnpwNw3bHdaZhSkY12kf2z1z81zOxwM5sHzAvu9zezx2KeTCTB5BUUcd0L01m4IY9/XDSQQzuXewa3SJWpyDbnQ8BJBMcF3H0mcFQsQ4kkmoKiCFc+PYVPF2Rx1ZGdOa1vm72/SKSKVGi7091X7TbWeSQ2cUQSj7vz+3fmMWnZZh65cCBn9m8bdiRJMBUpglVmdjjgZpYCXA/Mj20skcRQFCnhiqcm88XiTfxkUHuVgISiIkXwC+BhoB2wGvgQuCaWoUQSgbvzlw8W8sXiTdx2ci+uOCIj7EiSoCpy1tAm4OJqyCKSUJ6dsIJR47/lwkM78ouju2iqSQlNeYPOPUr0ArIyufv1MUkkkgCWZG3jLx8sJKNFQ+49p49KQEJV3hbBlGpLIZJAvly8iZtengEO/xlxiEpAQlfeoHNPV2cQkURw91tzeOabFTRPTeGRiwbSrVWjsCOJVOiCso/MrGmp+83M7IPYxhKpfaau2MxzE1fS64A03v/VkQzr2SrsSCJAxS4oS3f3LbvuBJPN6ydYZB8s2pDHhaMm0rRBXZ698jBapWkkUYkfFSmCiJl13HXHzDpRzkFkEfmhwuISrn52KoWREv7388NIT6sXdiSRH6jIdQR3Al+a2bjg/lHAyNhFEqk9Vmbnc/HoCazavIOfDc2gd5vGYUcS+ZFyi8CipzPMBQYBg4lOVXljcG2BiJRj0YY8Lvr3BHJ3FHPtsG78+sQeYUcSKVO5ReDubmZvuvvBwLvVlEmkxtu6o4ifPvENBoy54UidHSRxrSLHCCaY2SExTyJSS0xdsZkTHxpH7o4i7j2nr0pA4l5FjhEMA642sxXAdqK7h9zd+8U0mUgN5O7c/MosdhaX8OY1Q+nXvuneXyQSsooUwSkxTyFSC2zILWD4E9+wPDufe844UCUgNUZ5Yw01dvdcIK8a84jUSCuz8xn57BSWZ+dzwSEduHRIRtiRRCqsvC2C54HTgalErxsoPSCKA11imEukxhi3aCNXPRMdmksTy0hNVN5YQ6cHXztXXxyRmuXlKau49dVZpNVP5vGLD+aI7i3DjiSyzyoy1tA5Ztak1P2mZnZ2bGOJxL+iSAn3jplPRouGTLzjOJWA1FgVOX30d+6+ddedYNyh38Uukkj8m7FqC6c8/AVb8ou44fjuNEyp0PTfInGpIj+9ZZWFfuolYb0waSV3vDGb1JRk7j+3L+cMbB92JJH9UpEP9Clm9iDwT6IHia8jegC5XGb2JNGDzVnu3idY1hx4CcgAlgM/DUYzFakR7hsznyfGf0vrxvV459ojaNVYo4hKzVeRXUPXAYVEP8BfAQqo2OT1TwEn77bsduATd+8OfBLcF6kRXp26mifGf8sR3Vry+c3DVAJSa1Rk8vrtVOID293Hm1nGbovPAo4Jbj8NfA7ctq/fW6S6/W/CCu55ey6Hdm7O6MszqZecFHYkkSqz1yIwsx7AzUR353z3fHc/thLv19rd1wWvX2dmmuBG4pq789jnS/nLBwtp3bgeo0eoBKT2qcgxgleAfwH/ASKxjfM9MxtJMO9Bx44d9/JskapXUBThT+/N59kJKziuVyv+fF4/0urXDTuWSJWrSBEUu/vjVfR+G8ysTbA10AbI2tMT3X0UMAogMzNTM6JJtVqRvZ3LnpzEiux8rhjamTtP601SHdv7C0VqoIoUwTtm9kvgDWDnroXuvrkS7/c2MAK4P/j6ViW+h0hMZeUWcMnoieRsL+L5qw7j8K66UExqt4oUwYjg6y2llu11rCEze4HogeGWZraa6EVo9wMvm9mVwErg/H0NLBJLW3cUcdLfx5NXUMxjFw9SCUhCqMhZQ5Uaa8jdL9zDQ8dV5vuJxNryTdv58wcLyMkv4taTe3LiQQeEHUmkWuzxOgIzu7XU7fN3e+zeWIYSqW6jv1zGiQ+N5+N5WZw7qB1XH9U17Egi1aa8C8ouKHX7N7s9tvuFYiI1krvz6CeL+eO78+jfoQlf3jaMB386QAeGJaGUt2vI9nC7rPsiNdKDHy3i0U+XcHq/Ntx3bl+dHioJqbwi8D3cLuu+SI1SHCnh2QkrePTTJRzXqxWPXDCQOtoKkARVXhH0N7Ncon/9NwhuE9zXICtSY63I3s4vn5vG3LW59Dogjb/9tL9KQBJaeTOU6Tp6qXXGL9rI7a/NYtvOYh6/eBAn9zkAM5WAJDbNKyAJwd257bVZvDxlNakpSTw0fIBODxUJqAik1isoivCPT5fw8pTVXDakE7ef0ksziomUot8GqdWyt+3k2uen88232ZzRvy13ntZbo4eK7EZFILVSQVGEhz5axH+/Xk6kxLn3nL5cdJhGsRUpi4pAah1356aXZzBm9npOOqg1t5zUk26t0sKOJRK3VARSq2zJL+RvHy5izOz1DM/swP0/6auzgkT2QkUgtUKkxBkzex23vjqLHUUR+rdvwr3nqgREKkJFIDWeu3PNc9N4f+56uqSncsuJ0ZFDNV6QSMWoCKRGW7U5n5tfmcnEZZu5dHAn7jnzIBWAyD5SEUiN9dWSTYx4chL16ybxuzMO5PLDM7QrSKQSVARS42zfWcyTXy7j0c+WUKeO8f/O7sPZA9uFHUukxlIRSI3y2cIsrnhqMu5w0kGt+cNZfWjdWGMgiuwPFYHUGC9PXsWtr80C4KYTenD9cd1DTiRSO6gIJO6VlDjjF2/k1tdm0euANJ68/BDaNm0QdiyRWkNFIHHt6yWbuPmVmazdWkCP1o144arBNEtNCTuWSK2iIpC4FClx/vTefJ78ahld01O579y+nNqnDU0aaipJkaqmIpC4U1Ly/QVip/Q5gD+f109zCYvEkIpA4kZBUYS3Z6zlhckrmb5yC5cfnsHvzjhQ1waIxJiKQOLC9p3F/OWDhTz19XLS6iVz9VFduOnEHioBkWqgIpDQTV+ZwyX/mcj2wgh92jXm7WuO0GTyItVIRSCh+mDuem5+ZSYAT/3sEI7snq4SEKlmKgIJxYbcAu4dM5+3ZqylX/sm/POiQXRo3jDsWCIJSUUg1Sort4CbX53F+EUbAbhiaGduO6Wn5hEWCVEoRWBmy4E8IAIUu3tmGDmkeq3dsoMLRk1gzZYd3Hh8D4b1Sqdf+6ZhxxJJeGFuEQxz900hvr9Uk5ISZ+yc9dw7Zj5b8gt58Kf9OWuARgsViRfaNSQx9cw3yxk1/ltW5+yga3oq//3ZoRzauXnYsUSklLCKwIEPzcyBJ9x9VEg5JEbmrt3K6C+W8eaMNfTv0JRbT+7FaX3baPYwkTgUVhEMdfe1ZtYK+MjMFrj7+NJPMLORwEiAjh07hpFRKsHd+WpJNpeMnkhKch2GH9KRO07tpSEiROJYKEXg7muDr1lm9gZwKDB+t+eMAkYBZGZmerWHlH1SUuK8M2stT329nOkrt9CgbhJPXHowR/VIDzuaiOxFtReBmaUCddw9L7h9IvCH6s4hVWfu2q3c9NJMFm7IIz2tHjed0IORR3Whfl2dEipSE4SxRdAaeCMYQyYZeN7d3w8hh+ynokgJk5Zt5mf/nUyj+sk8NLw/p/VtS0pynbCjicg+qPYicPdvgf7V/b5SdfIKinh5ymoe/3wJm7YVkpJUh+d+fhi92zQOO5qIVIJOH5V9Mm7RRq59fhp5BcUM6dKCO05tz4AOTemS3ijsaCJSSSoCqZBpK3N4fuJK3pi+hp6t0/jTOX0Y0KGphokWqQVUBLJH7s74xZt4f856Xpy8knrJdTi2VyseGj6ARvX0oyNSW+i3Wcq0ZssOHhi7gLdnriUlqQ4XHtqRO07trQIQqYX0Wy0/kLO9kH+NW8pzE1dSWFzCFUM7c+vJPXUqqEgtpiIQAFZkb+f378zj84VZlDi0bFSPN68ZSrdWOggsUtupCBJcpMQZ/eW3PPjRIpLr1OH/junKCQceQL92TTRTmEiCUBEkqAXrc/nju/OYtzaXnPwijumZzn3n9qVNkwZhRxORaqYiSDBTlm/m/TnrefKrZZQ4DOjQlDtP68S5A9tpC0AkQakIEsTW/CL+NX4pj3++FIBjeqbzuzMOonPL1JCTiUjYVAS1WEFRhDGz1/Hx/A18vnAj+YURhnRpwYPD+2sXkIh8R0VQS2Vv28kloycxf10urdLqcfbAdlx8WEcOatsk7GgiEmdUBLXIqs35jJ2zjrFz1jNj1Rbc4c8/6cd5B7fX/n8R2SMVQS1QUBTh/rELeGXKKrYXRmjXtAE/PbgDmRnNOD+zQ9jxRCTOqQhqKHdnzppcnvp6OR/OXU/ezmKaNqzL+788nF4HaDhoEak4FUENs2pzPq9MWcUbM9awavMOkuoYx/VqxbmD2nPCga01ObyI7DMVQQ2Qs72Q6atymL8uj8c+W8KOoghDu7XkumHdOf7A1jRPTQk7oojUYCqCODZ37VYe/ngxXyzexI6iCABDurTggZ/0o2OLhiGnE5HaQkUQZ5Zt2s5TXy1j3rpcpq7IoWnDFM7s35bT+7ehd5vGtEhN0WQwIlKlVARxYNXmfO4fu4AJ32aTvb2QBnWTOKhtYy4/vDPXHduNZtr1IyIxpCKoZrvO9nlt2moWbchj6cZtbMjdiRmcO7A9nVs25NxB7WnbVFf+ikj1UBHEWKTEmbRsMwvW57ImZwezVm9l0vLN1EuuQ+82jTmiWzrdWjXiyO4t6dNOV/2KSPVTEVQhd2dD7k6y8gqYtiKHScs3fzfGD0D9unVo27QB1x3bjZ8N7ayzfUQkLqgI9kNRpITlm7azYH0eH87bwLiFWeQWFH/3eIvUFM4a0I7BXZpzRLeWNNeBXhGJQyqCShi3aCOvTFnFpwuyfvDX/ln929GnfRNapdXjwDaN6dBcp3iKSPxTEezFiuztTFq2mdlrtrJ04zbW5OxgeXY+zVNTOHtgOzI7NaPnAWl0TW+kCd5FpEZSEZSSlVvAgvV5bN5eSPb2QqatzGHM7HW4Q6N6yXRv3YiD2jXhksGdGHF4BnWT6oQdWURkvyV8EZSUOCs35/Ppgiz+8sHC767gBWiemsKVQztzwaEd6dIyVUM5i0itlLBF8NWSTTz++VJmrtpC3s7oAd4jurXk2mO7kZ5WjxapKTRpUFcHd0Wk1gulCMzsZOBhIAn4j7vfXx3vW1AU4YvFm3h2wgrGL9pIu6YNOGtgW/q0bUKfdk04sE1j/dUvIgmn2ovAzJKAfwInAKuByWb2trvPi8X7FRRF+HzhRsbOWccn87PYtrOYZg3rctdpvbl0SCfqJesAr4gktjC2CA4Flrj7twBm9iJwFlDlRfDIJ4v517il5BdGaNawLqf3a8MpfdtweNcWOtArIhIIowjaAatK3V8NHBaLN2rTpD5nD2zHqX3acFiX5vrwFxEpQxhFUNZOeP/Rk8xGAiMBOnbsWKk3Oj+zg+bsFRHZizD+RF4NlP50bg+s3f1J7j7K3TPdPTM9Pb3awomIJJowimAy0N3MOptZCnAB8HYIOUREhBB2Dbl7sZldC3xA9PTRJ919bnXnEBGRqFCuI3D3McCYMN5bRER+SKfRiIgkOBWBiEiCUxGIiCQ4FYGISIIz9x9dyxV3zGwjsKKSL28JbKrCOLGkrLGhrFWvpuSExM7ayd33eiFWjSiC/WFmU9w9M+wcFaGssaGsVa+m5ARlrQjtGhIRSXAqAhGRBJcIRTAq7AD7QFljQ1mrXk3JCco109tCAAAICklEQVS6V7X+GIGIiJQvEbYIRESkHLW6CMzsZDNbaGZLzOz2sPPsYmYdzOwzM5tvZnPN7IZgeXMz+8jMFgdfm4WddRczSzKz6Wb2bnC/s5lNDLK+FIwkGzoza2pmr5rZgmD9DonX9WpmNwb//+eY2QtmVj9e1quZPWlmWWY2p9SyMtejRT0S/J7NMrNBcZD1L8HPwCwze8PMmpZ67DdB1oVmdlLYWUs9drOZuZm1DO5X23qttUVQam7kU4ADgQvN7MBwU32nGPi1u/cGBgPXBNluBz5x9+7AJ8H9eHEDML/U/QeAh4KsOcCVoaT6sYeB9929F9CfaOa4W69m1g64Hsh09z5ER+K9gPhZr08BJ++2bE/r8RSge/BvJPB4NWXc5Sl+nPUjoI+79wMWAb8BCH7PLgAOCl7zWPBZUV2e4sdZMbMOROdxX1lqcbWt11pbBJSaG9ndC4FdcyOHzt3Xufu04HYe0Q+rdkTzPR087Wng7HAS/pCZtQdOA/4T3DfgWODV4ClxkdXMGgNHAaMB3L3Q3bcQp+uV6Oi/DcwsGWgIrCNO1qu7jwc277Z4T+vxLOAZj5oANDWzNtWTtOys7v6huxcHdycQnQBrV9YX3X2nuy8DlhD9rAgta+Ah4FZ+OFtjta3X2lwEZc2N3C6kLHtkZhnAQGAi0Nrd10G0LIBW4SX7gb8T/SEtCe63ALaU+kWLl3XbBdgI/DfYjfUfM0slDteru68B/kr0L8B1wFZgKvG5XnfZ03qM99+1K4Cxwe24y2pmZwJr3H3mbg9VW9baXAQVmhs5TGbWCHgN+JW754adpyxmdjqQ5e5TSy8u46nxsG6TgUHA4+4+ENhOHOwGKkuwf/0soDPQFkgluitgd/GwXvcmXn8eMLM7ie6KfW7XojKeFlpWM2sI3AncXdbDZSyLSdbaXAQVmhs5LGZWl2gJPOfurweLN+za9Au+ZoWVr5ShwJlmtpzo7rVjiW4hNA12aUD8rNvVwGp3nxjcf5VoMcTjej0eWObuG929CHgdOJz4XK+77Gk9xuXvmpmNAE4HLvbvz5OPt6xdif4xMDP4HWsPTDOzA6jGrLW5COJ2buRgH/toYL67P1jqobeBEcHtEcBb1Z1td+7+G3dv7+4ZRNfhp+5+MfAZcF7wtHjJuh5YZWY9g0XHAfOIw/VKdJfQYDNrGPw87Moad+u1lD2tx7eBy4KzXAYDW3ftQgqLmZ0M3Aac6e75pR56G7jAzOqZWWeiB2InhZERwN1nu3srd88IfsdWA4OCn+XqW6/uXmv/AacSPWNgKXBn2HlK5TqC6CbeLGBG8O9UovvePwEWB1+bh511t9zHAO8Gt7sQ/QVaArwC1As7X5BrADAlWLdvAs3idb0CvwcWAHOAZ4F68bJegReIHrsoIvrhdOWe1iPRXRj/DH7PZhM9EyrsrEuI7l/f9fv1r1LPvzPIuhA4Jeysuz2+HGhZ3etVVxaLiCS42rxrSEREKkBFICKS4FQEIiIJTkUgIpLgVAQiIglORSAikuBUBFJjmFnEzGYEwza/U3po4Qq+/h4zuzm4/QczO34/82SY2Q4zm7E/36cqmdnwYNjid8POIjWHikBqkh3uPsCjwzZvBq6p7Ddy97vd/eMqyLTU3QfsywtiOeyxu78E/DxW319qJxWB1FTfEIzEaGaNzOwTM5tmZrPN7Lvhxs3szmACko+BnqWWP2Vm5wW3l5eaDCTTzD4Pbh8dbIHMCEYzTdtbKDN708ymWnTCmZGllm8LtkImAkPM7BAz+9rMZprZJDNLM7ODgtszgolIugevvaTU8id2FYlFJ16aFnyPT/Z/lUqiSt77U0TiS/BBeBzBvANAAXCOu+cGH+gTzOxtogPOXUB0mO9kYBrRoZ4r6mbgGnf/KhgptqACr7nC3TebWQNgspm95u7ZREcXnePudwdjXy0Ahrv75GAehR3AL4CH3f254DlJZtYbGA4MdfciM3sMuNjMxgL/Bo5y92Vm1nwf/rtEfkBFIDVJg2B/fAbRD/SPguUG3GtmRxGdM6Ed0Bo4EnjDg0HHgnLYF18BD5rZc8Dr7r66Aq+53szOCW53IDqoWTYQITraLES3TNa5+2QAD4YgN7NvgDstOhHQ6+6+2MyOAw4mWioADYiO+jkYGO/RyVVw97ImOxGpEO0akppkR7A/vhOQwvfHCC4G0oGDg8c3APWDxyoymFYx3/8u7Hod7n4/0f3tDYhuZfQq75uY2TFEh5ce4u79gemlvl+Bu0d2PbWsXO7+PHAm0a2DD8zs2OC5TwfHRga4e093v2dP30OkMlQEUuO4+1ai8/3eHMzr0ITo5DlFZjaMaFEAjAfOMbMGwf79M/bwLZcT/asb4Ce7FppZV48OE/wA0RFNyy2CIEeOu+cHpTF4D89bALQ1s0OC90kzs2Qz6wJ86+6PEB2CuB/RUT7PM7NWwXObm1knosdIjg6GUka7hmR/aNeQ1EjuPt3MZhI9BvAc8I6ZTSE65PCC4DnTzOylYNkK4Is9fLvfA6PN7A6iU4bu8qugWCJE5woYW9aLS3kf+IWZzSI6xPGEPWQvNLPhwKPBsYQdRLckhgOXmFkRsB74Q3C84S7gQzOrQ3T44mvcfUJwMPr1YHkW0cnPRfaZhqEWqSSLzjf9bnA6a9wIdlHd7O6nh51FagbtGhKpvAjQJN4uKAMeA3LCziI1h7YIREQSnLYIREQSnIpARCTBqQhERBKcikBEJMGpCEREEtz/B9dQzrLtUD+cAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii, encircled_flux)\n", "\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Looking at the shape of the encircled flux, it looks like the background level of our PSF is not zero. Let's check" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.003720775\n" ] } ], "source": [ "# This is clearly. \n", "print(np.median(psf[0:5,:]))" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Encircled flux')" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(nbpix[10:], encircled_flux[10:])\n", "plt.xlabel('Number of pixels')\n", "plt.ylabel('Encircled flux')" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "len: 777\n", "29.0\n" ] } ], "source": [ "print('len:' , len(nbpix))\n", "print(nbpix[6])" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Lets do a linear fit to the outer part of the curve to determine the backgound\n", "p = np.polyfit(nbpix[50:], encircled_flux[50:], 1)\n", "#bkg=p[0]/(((np.abs(hd['CD1_1'])*3600.)**2)/4.25E10)\n", "bkg = p[0]/resol**2" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0036798443196937457\n" ] } ], "source": [ "print(bkg)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "#print(nbpix[100:])" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Lets correct the psf and encircled flux\n", "psf = psf - bkg\n", "encircled_flux = encircled_flux - p[0]* nbpix" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Encircled flux')" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii, encircled_flux)\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our PSF does now behaves correctly.\n", "\n", "Now let us compare our growth curve with the encircled energy curve from the instrumental PSF. " ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii_inst, encircled_flux_inst, label='Calibration')\n", "plt.plot(radii, encircled_flux/np.max(encircled_flux), label='Our PSF')\n", "plt.xlim([0, 15])\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')\n", "plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will work below 30\" where our PSF is well behaved" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii_inst, encircled_flux_inst, label='Calibration')\n", "plt.plot(radii, encircled_flux/np.max(encircled_flux), label='Our PSF')\n", "plt.xlim([0, 20])\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that while the calibration curve still rises beyond 30\", our PSF has reached a plateau. Let's note the calibration $C(r)$. Our PSF encirled energy is of the form:\n", "\n", "$E(r) = \\alpha C(r \\times \\beta)$\n", "\n", "Where $\\beta$ is the fattening of the PSF.\n", "\n", "We could take the derivative, but this too noisy. Instead we do a brute force approach" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seb's suggestion.. look at derivative!! Also see how correction parameters change as a function of where I do correction" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii_inst, encircled_flux_inst, label='Calibration')\n", "plt.plot(radii, encircled_flux/np.max(encircled_flux), label='Our PSF')\n", "plt.xlim([0, 100])\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "rf = 0.700, ff = 0.620, residual = 0.000\n", "0.106128015\n", "rf = 0.590, ff = 0.640, residual = 0.002\n", "0.102811515\n", "rf = 0.610, ff = 0.660, residual = 0.002\n", "0.09969601\n", "rf = 0.720, ff = 0.750, residual = 0.004\n", "0.087732494\n", "rf = 0.690, ff = 0.730, residual = 0.004\n", "0.09013612\n", "rf = 0.740, ff = 0.760, residual = 0.004\n", "0.08657812\n", "rf = 0.760, ff = 0.770, residual = 0.004\n", "0.08545373\n", "rf = 0.720, ff = 0.750, residual = 0.004\n", "0.087732494\n", "rf = 0.860, ff = 0.820, residual = 0.004\n", "0.08024313\n", "rf = 0.860, ff = 0.820, residual = 0.004\n", "0.08024313\n" ] } ], "source": [ "rfactor = np.arange(0.5,3., 1e-2)\n", "ffactor = np.arange(0.5,3., 1e-2)\n", "# work with the data points between 3 and 25\"\n", "for r in np.arange(3,20):\n", " idx, = np.where((radii > 2) & (radii < r))\n", " xv = radii[idx]\n", " yv = encircled_flux[idx]/np.max(encircled_flux)\n", " resid = np.zeros((len(rfactor), len(ffactor)))\n", " for i, rf in enumerate(rfactor):\n", " tck = interpolate.splrep(radii_inst*rf,encircled_flux_inst , s=1)#changed s=0 to 1 as I was getting NaNs\n", " yfit = interpolate.splev(xv, tck, der=0)\n", "\n", " for j, ff in enumerate(ffactor):\n", " resid[i, j] = np.sum((yv-yfit*ff)**2)\n", " imin = np.argmin(resid)\n", " rmin, fmin = np.unravel_index(imin, resid.shape)\n", " print(\"rf = {:.3f}, ff = {:.3f}, residual = {:.3f}\".format(rfactor[rmin], ffactor[fmin], resid[rmin, fmin]))\n", " print(np.max((psf/np.max(encircled_flux)/ffactor[fmin])))\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This shows a minimum, with some degeneracy. " ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.imshow(np.log(resid))" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "rf = 0.790, ff = 0.790, residual = 0.005\n" ] } ], "source": [ "imin = np.argmin(resid)\n", "rmin, fmin = np.unravel_index(imin, resid.shape)\n", "print(\"rf = {:.3f}, ff = {:.3f}, residual = {:.3f}\".format(rfactor[rmin], ffactor[fmin], resid[rmin, fmin]))" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(radii_inst*rfactor[rmin],encircled_flux_inst, label='Calibration')\n", "plt.plot(radii, encircled_flux/np.max(encircled_flux)/ffactor[fmin], label='Our PSF')\n", "plt.xlim([0, 20])\n", "plt.xlabel('Radius [arcsec]')\n", "plt.ylabel('Encircled flux')\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.2247631205398632" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# The two curve overlap\n", "rad=20\n", "psfok = (psf/np.max(encircled_flux)/ffactor[fmin])\n", "cpix=np.int((hd['NAXIS1']+1)/2.0)\n", "#np.sum(psfok[cpix-rad-1:cpix+rad,cpix-rad-1:cpix+rad])*((np.abs(hd['CD1_1'])*3600.)**2)/4.25E10\n", "np.sum(psfok[cpix-rad-1:cpix+rad,cpix-rad-1:cpix+rad])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "psfok is the PSF that a source of flux 1 Jy has in our data, and is to be used for source extraction.\n", "## As units of map in MJy/sr, divide by 1E6" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "589726700.0" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.max(psfok)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.hist(psfok.flatten(),bins=np.arange(-0.1,0.1,0.001));\n", "plt.yscale('log')" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "#psfok2=psfok/1.0E6" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#plt.hist(psfok2.flatten(),bins=np.arange(-50,200.0,1));\n", "#plt.yscale('log')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Validation\n", "To check PSF is reasonable, lets look at a 24 micron source (Spitzer index 201233 in spitzer-cat-full-master-mips24.fits) that has a flux of 812.65 microJy. Maximum value in our normalised PSF gives a peak below. Since PSF is double resolution of map, it could also be off centre. Map has value of 0.5315 MJy/sr but does appear to be off centre. " ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Max PSF = 0.47886 Jy/sr, off pixel Max PSF = 0.21144 Jy/sr\n" ] } ], "source": [ ",bins=np.arange(-100.0,100.0,1.0print(\"Max PSF = {:.5f} Jy/sr, off pixel Max PSF = {:.5f} Jy/sr\".format(psfok2[cpix-1,cpix-1]*8.12E-4,psfok2[cpix-2,cpix-2]*8.12E-4))" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: hdu=0 does not contain any data, using hdu=1 instead [aplpy.core]\n", "WARNING: Cannot determine equinox. Assuming J2000. [aplpy.wcs_util]\n", "WARNING: Cannot determine equinox. Assuming J2000. [aplpy.wcs_util]\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import aplpy\n", "import seaborn as sns\n", "sns.set_style(\"white\")\n", "cmap=sns.cubehelix_palette(8, start=.5, rot=-.75,as_cmap=True)\n", "fig=aplpy.FITSFigure('./data/70101880.70101880-0.MIPS.1.help.fits')\n", "fig.recenter(214.39,52.5, radius=0.004)\n", "fig.show_colorscale(vmin=0.0,vmax=10.0,cmap=cmap)\n", "fig.add_colorbar()\n", "fig.colorbar.set_location('top')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In summary, the PSF is within 10% of this source, and given noise and shape of source will add additional uncertianty this seems reasonable." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Create PSF fits file" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "collapsed": true }, "outputs": [], "source": [ "stackhd[1].data=psfok2\n", "stackhd.writeto('./data/output_data/dmu17_MIPS_EGS_20190204.fits',overwrite=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }