{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Starting an IFS simulation from scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's suppose that you want to model the ideal IFS and don't have any idea (or don't really care) about what the PSFLets look like and where they are located. In that case, you don't need any datafile and can get started ASAP!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's load things first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import glob\n",
    "%pylab inline --no-import-all\n",
    "plt.rc('font', family='serif', serif='Times',size=20)\n",
    "plt.rc('text', usetex=True)\n",
    "plt.rc('xtick', labelsize=20)\n",
    "plt.rc('xtick.major', size=10)\n",
    "plt.rc('ytick.major', size=10)\n",
    "plt.rc('ytick', labelsize=20)\n",
    "plt.rc('axes', labelsize=20)\n",
    "plt.rc('figure',titlesize=20)\n",
    "plt.rc('image',origin='lower',interpolation='nearest')\n",
    "\n",
    "import sys\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initializes the logger used throughout the software\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from crispy.tools.initLogger import getLogger\n",
    "log = getLogger('crispy')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Operate in your working directory (where your parameter file lives)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "os.chdir('/Users/mrizzo/IFS/crispy/crispy/WFIRST/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T / conforms to FITS standard                      \n",
       "BITPIX  =                    8 / array data type                                \n",
       "NAXIS   =                    0 / number of array dimensions                     \n",
       "EXTEND  =                    T                                                  \n",
       "COMMENT                                                                         \n",
       "COMMENT ************************************************************            \n",
       "COMMENT ********************** General parameters ******************            \n",
       "COMMENT ************************************************************            \n",
       "COMMENT                                                                         \n",
       "NLENS   =                  108 / # lenslets across array                        \n",
       "PITCH   =             0.000174 / Lenslet pitch (meters)                         \n",
       "INTERLAC=                  2.0 / Interlacing                                    \n",
       "PHILENS =    26.56505117707799 / Rotation angle of the lenslets (deg)           \n",
       "PIXSIZE =              1.3E-05 / Pixel size (meters)                            \n",
       "LENSAMP =                  0.5 / Lenslet sampling (lam/D)                       \n",
       "LSAMPWAV=                660.0 / Lenslet sampling wavelength (nm)               \n",
       "FWHM    =                  2.0 / FHWM of PSFLet at detector (pixels)            \n",
       "FWHMLAM =                660.0 / Wavelength at which FWHM is defined (nm)       \n",
       "NPIX    =                 1024 / Number of detector pixels                      \n",
       "BW      =                 0.18 / Bandwidth                                      \n",
       "PIXPRLAM=                  2.0 / Pixels per resolution element                  \n",
       "RESLSTSQ=                  2.0 / Nspec per Nyq. sample for lstsq extraction     \n",
       "R       =                   50 / Spectral resolution                            "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from params import Params\n",
    "par = Params()\n",
    "par.hdr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First off, you are going to trick crispy into building a fake wavelength calibration. This is usually important because in the real world, the wavelength calibration is the step that ensures that you can get good data out of your IFS images. For this exercise, you are going to use an a priori wavelength calibration (it's built into crispy) to generate monochromatic flatfields. From these flatfields, you are going to build up your wavelength calibration - just like in real life!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate monochromatic flats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, what's our wavelength range? We are going to use the fiducial case of 600nm - 720nm, which is the first band of the WFIRST IFS. We are going to construct a few monochromatic flats across that range. The function we need is in the IFS module (that one has a lot of important functions)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function createWavecalFiles in module crispy.IFS:\n",
      "\n",
      "createWavecalFiles(par, lamlist, dlam=1.0)\n",
      "    Creates a set of monochromatic IFS images to be used in wavelength calibration step\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    par:   Parameter instance\n",
      "            Contains all IFS parameters\n",
      "    lamlist: list or array of floats\n",
      "            List of discrete wavelengths at which to create a monochromatic flat\n",
      "    dlam:  float\n",
      "            Width in nm of the small band for each of the monochromatic wavelengths.\n",
      "            Default is 1 nm. This has no effect unless we are trying to add any noise.\n",
      "    \n",
      "    Notes\n",
      "    -----\n",
      "    This function populates the fields par.lamlist and par.filelist which are subsequently\n",
      "    used by the buildcalibrations function. If this createWavecalFiles is not called, the\n",
      "    two fields need to be populated manually with the set of files and wavelengths that\n",
      "    you want to use for the calibration.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from crispy.IFS import createWavecalFiles\n",
    "help(createWavecalFiles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So here we go:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Wavecal folder is: ..//ReferenceFiles/wavecalR50_660/\n",
      "crispy - INFO - [ 600.6  605.6  610.6  615.6  620.6  625.6  630.6  635.6  640.6  645.6\n",
      "  650.6  655.6  660.6  665.6  670.6  675.6  680.6  685.6  690.6  695.6\n",
      "  700.6  705.6  710.6  715.6  720.6]\n"
     ]
    }
   ],
   "source": [
    "lamc=660.\n",
    "lamlist = np.arange(lamc*(1.-par.BW/2.),lamc*(1.+par.BW/2.)+5.,5.)\n",
    "# lamlist = lamc*np.linspace(1.-BW/2.,1.+BW/2.,fileshape[0])\n",
    "\n",
    "# let's create our new wavelength calibration directory to not mess up anything\n",
    "# comment this out if this was already done and you are fine overriding the files in your folder\n",
    "# try:\n",
    "#     os.makedirs(par.prefix+'/testWavecal660')\n",
    "# except OSError:\n",
    "#     log.error('Wavecal folder already exists!')\n",
    "#     raise\n",
    "\n",
    "log.info('Wavecal folder is: %s' % par.wavecalDir)\n",
    "log.info(lamlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_600.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_605.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_610.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_615.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_620.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_625.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_630.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_635.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_640.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_645.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_650.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_655.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_660.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 5 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_665.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_670.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_675.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_680.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_685.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 5 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_690.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_695.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 5 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_700.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_705.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_710.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_715.fits\n",
      "crispy - INFO - The number of input pixels per lenslet is 4.995459\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming slices are evenly spread in wavelengths\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 4 seconds total\n",
      "crispy - INFO - Writing data to ..//ReferenceFiles/wavecalR50_660/det_720.fits\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['..//ReferenceFiles/wavecalR50_660/det_600.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_605.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_610.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_615.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_620.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_625.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_630.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_635.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_640.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_645.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_650.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_655.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_660.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_665.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_670.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_675.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_680.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_685.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_690.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_695.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_700.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_705.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_710.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_715.fits',\n",
       " '..//ReferenceFiles/wavecalR50_660/det_720.fits']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "createWavecalFiles(par,lamlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "par.R = 50\n",
    "# par.wavecalDir = ''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at what we did."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['..//ReferenceFiles/wavecalR50_660/det_600.fits', '..//ReferenceFiles/wavecalR50_660/det_605.fits', '..//ReferenceFiles/wavecalR50_660/det_610.fits', '..//ReferenceFiles/wavecalR50_660/det_615.fits', '..//ReferenceFiles/wavecalR50_660/det_620.fits', '..//ReferenceFiles/wavecalR50_660/det_625.fits', '..//ReferenceFiles/wavecalR50_660/det_630.fits', '..//ReferenceFiles/wavecalR50_660/det_635.fits', '..//ReferenceFiles/wavecalR50_660/det_640.fits', '..//ReferenceFiles/wavecalR50_660/det_645.fits', '..//ReferenceFiles/wavecalR50_660/det_650.fits', '..//ReferenceFiles/wavecalR50_660/det_655.fits', '..//ReferenceFiles/wavecalR50_660/det_660.fits', '..//ReferenceFiles/wavecalR50_660/det_665.fits', '..//ReferenceFiles/wavecalR50_660/det_670.fits', '..//ReferenceFiles/wavecalR50_660/det_675.fits', '..//ReferenceFiles/wavecalR50_660/det_680.fits', '..//ReferenceFiles/wavecalR50_660/det_685.fits', '..//ReferenceFiles/wavecalR50_660/det_690.fits', '..//ReferenceFiles/wavecalR50_660/det_695.fits', '..//ReferenceFiles/wavecalR50_660/det_700.fits', '..//ReferenceFiles/wavecalR50_660/det_705.fits', '..//ReferenceFiles/wavecalR50_660/det_710.fits', '..//ReferenceFiles/wavecalR50_660/det_715.fits', '..//ReferenceFiles/wavecalR50_660/det_720.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam600.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam605.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam610.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam615.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam620.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam625.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam630.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam635.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam640.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam645.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam650.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam655.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam660.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam665.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam670.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam675.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam680.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam685.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam690.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam695.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam700.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam705.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam710.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam715.fits', '..//ReferenceFiles/wavecalR50_660/hires_psflets_lam720.fits', '..//ReferenceFiles/wavecalR50_660/polychromekeyR50.fits', '..//ReferenceFiles/wavecalR50_660/polychromeR50.fits', '..//ReferenceFiles/wavecalR50_660/PSFloc.fits', '..//ReferenceFiles/wavecalR50_660/PSFwidths.fits']\n"
     ]
    }
   ],
   "source": [
    "listfiles = glob.glob(par.wavecalDir+'*.fits')\n",
    "print listfiles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's show some images. We use the Image module of crispy for convenience."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_600.fits\n"
     ]
    },
    {
     "data": {
      "image/png": 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Fv8kMvZdKrzLkTOUztHNmHzpDR+Z1oTMUuTSWzlCv35x0o/wvmw5ZkqExGdnGMkQ0yo+i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\n5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111f802d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from crispy.tools.image import Image\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(Image(listfiles[0]).data)\n",
    "plt.colorbar(fraction=0.046, pad=0.04)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And a little zoom in:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_600.fits\n"
     ]
    },
    {
     "data": {
      "image/png": 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f8f8eHpflzrGSP8bzBk63/uiwyVYetE1VB14yWW5oqDoXhszQ0RGTXfHdQyZbvG+Je35y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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111f5e290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(Image(listfiles[0]).data[450:550,450:550])\n",
    "plt.colorbar(fraction=0.046, pad=0.04)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The PSFLets are slowly changing because the geometry that we chose results in almost integer spacing in both X and Y between neighboring lenslets. If you want more diversity (usually it is preferable to have diversity), then change the lenslet size of detector pitch by a little bit."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run a complete wavelength calibration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have monochromatic flats, it is time to run a wavelength calibration, just like one would do in any IFS. The function we need is in crispy.tools.wavecal. This is a much more complicated function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function buildcalibrations in module crispy.tools.wavecal:\n",
      "\n",
      "buildcalibrations(par, filelist=None, lamlist=None, order=3, inspect=False, genwavelengthsol=False, makehiresPSFlets=False, makePolychrome=False, makehiresPolychrome=False, makePSFWidths=False, savehiresimages=True, borderpix=4, upsample=5, nsubarr=3, parallel=True, inspect_first=True, apodize=False, lamsol=None, threshold=0.0)\n",
      "    Master wavelength calibration function\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    par :   Parameter instance\n",
      "            Contains all IFS parameters\n",
      "    filelist: list of strings (optional)\n",
      "            List of the fits files that contain the monochromatic calibration files. If None (default),\n",
      "            use the files in par.filelist\n",
      "    lamlist: list of floats (optional)\n",
      "            Wavelengths in nm at which the files are taken. If None (default),\n",
      "            use the files in par.lamlist\n",
      "    order: int\n",
      "            Order of the polynomial used to fit the PSFLet positions across the detector\n",
      "    genwavelengthsol: Boolean\n",
      "            If True, generate the wavelength calibration. Creates a text file with all\n",
      "            polynomial coefficients that best fit the PSFLet positions at each wavelength.\n",
      "            If False, then load an already-generated file.\n",
      "    inspect: Boolean\n",
      "            Whether or not to create PNG files that overlay PSFLet fitted position on the\n",
      "            monochromatic pictures, to visually inspect the fitting results\n",
      "    inspect_first: Boolean\n",
      "            Whether or not to create a PNG file that overlays PSFLet fitted position on the\n",
      "            monochromatic picture of the first file, to visually inspect the fitting results\n",
      "    makehiresPSFlets: Boolean\n",
      "            Whether or not to do a high-resolution fitting of the PSFs, using the sampling\n",
      "            diversity. This requires high-SNR monochromatic images.\n",
      "    makePolychrome: Boolean\n",
      "            Whether or not to build the polychrome cube used in the least squares extraction\n",
      "    makePSFWidths: Boolean\n",
      "            Whether or not to fit the PSFLet widths using the high-res PSFLets\n",
      "    makehiresPolychrome: Boolean\n",
      "            Whether or not to build a polychrome cube at a high spatial resolution for future\n",
      "            subpixel interpolations\n",
      "    savehiresimages: Boolean\n",
      "            Whether to save fits files with the high-res PSFLets\n",
      "    borderpix:  int\n",
      "            Number of pixels that are not taken into account towards the edges of the detector\n",
      "    upsample: int\n",
      "            Upsampling factor for each high-resolution PSFLet\n",
      "    nsubarr: int\n",
      "            Detector will be divided into nsubarr x nsubarr regions. A high-resolution PSFLet\n",
      "            will be determined in each region from the average of all PSFLets within that\n",
      "            region\n",
      "    parallel: Boolean\n",
      "            Whether or not to parallelize the computation for the high-resolution PSFLet and\n",
      "            polychrome computation. The wavelength calibration step cannot be parallelized since\n",
      "            each wavelength uses the previous wavelength solution as a guess input.\n",
      "    apodize: Boolean\n",
      "            Whether to fit the spots only using lenslets within a circle, ignoring the corners of\n",
      "            the detector\n",
      "    lamsol: 2D array\n",
      "            Optional argument that, if not None and if genwavelengthsol==False, will take the argument\n",
      "            and use it as the current wavelength calibration to build the polychrome.\n",
      "    threshold: float\n",
      "            Threshold under which to zero out the polychrome. This is only useful for reducing\n",
      "            the file size of the polychrome, and has only very little impact on the extraction.\n",
      "            To be safe, for science extractions threshold should be kept at its default value of 0.0\n",
      "    \n",
      "    Notes\n",
      "    -----\n",
      "    This function generates all the files required to process IFS cubes:\n",
      "    lamsol.dat: contains a list of the wavelengths and the polynomial coefficients that\n",
      "                describe the X,Y positions of all lenslets on the detector as a function\n",
      "                of lenslet position on the lenslet array.\n",
      "    polychromekeyRXX.fits:  where XX is replaced by the spectral resolution defined in the\n",
      "                            parameters file. This is a multi-extension fits file with:\n",
      "                            - a list of the central wavelengths at which the final cube will be reduced to\n",
      "                            - an array of the X positions of all lenslets\n",
      "                            - an array of the Y positions of all lenslets\n",
      "                            - an array of booleans indicating whether that lenslet is good or not\n",
      "                            (e.g. when it is outside of the detector area)\n",
      "    polychromeRXX.fits: 3D arrays of size Nspec x Npix x Npix with maps of the PSFLets put in their correct\n",
      "                        positions for each wavelength bins that we want in the output cube. Each PSFLet\n",
      "                        in each wavelength slice is used for least-squares fitting.\n",
      "    hiresPolychromeRXX.fits: same as polychromeRXX.fits but this time using the high-resolution PSFLets\n",
      "    PSFLoc.fits:    nsubarr x nsubarr array of 2D high-resolution PSFLets at each location\n",
      "                    in the detector.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from crispy.tools.wavecal import buildcalibrations\n",
    "help(buildcalibrations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Wavecal files: ['..//ReferenceFiles/wavecalR50_660/det_600.fits', '..//ReferenceFiles/wavecalR50_660/det_605.fits', '..//ReferenceFiles/wavecalR50_660/det_610.fits', '..//ReferenceFiles/wavecalR50_660/det_615.fits', '..//ReferenceFiles/wavecalR50_660/det_620.fits', '..//ReferenceFiles/wavecalR50_660/det_625.fits', '..//ReferenceFiles/wavecalR50_660/det_630.fits', '..//ReferenceFiles/wavecalR50_660/det_635.fits', '..//ReferenceFiles/wavecalR50_660/det_640.fits', '..//ReferenceFiles/wavecalR50_660/det_645.fits', '..//ReferenceFiles/wavecalR50_660/det_650.fits', '..//ReferenceFiles/wavecalR50_660/det_655.fits', '..//ReferenceFiles/wavecalR50_660/det_660.fits', '..//ReferenceFiles/wavecalR50_660/det_665.fits', '..//ReferenceFiles/wavecalR50_660/det_670.fits', '..//ReferenceFiles/wavecalR50_660/det_675.fits', '..//ReferenceFiles/wavecalR50_660/det_680.fits', '..//ReferenceFiles/wavecalR50_660/det_685.fits', '..//ReferenceFiles/wavecalR50_660/det_690.fits', '..//ReferenceFiles/wavecalR50_660/det_695.fits', '..//ReferenceFiles/wavecalR50_660/det_700.fits', '..//ReferenceFiles/wavecalR50_660/det_705.fits', '..//ReferenceFiles/wavecalR50_660/det_710.fits', '..//ReferenceFiles/wavecalR50_660/det_715.fits', '..//ReferenceFiles/wavecalR50_660/det_720.fits']\n"
     ]
    }
   ],
   "source": [
    "# we can check that the file list has been loaded:\n",
    "log.info('Wavecal files: %s' % par.filelist)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One important aspect is that we can choose to use the same models for PSFLets as the one that was used to construct the monochromatic flatfields. This basically assumes that we have 100% knowledge of all the PSFLets, and can be set if par.gaussian_hires=True. Otherwise, we can actually use the deconvolution functions within crispy to approximate the lenslet PSFLets, by dividing up the detector into nsubarr^2 regions and averaging the PSFLets over these regions. Let's assume for now that we have excellent models of our PSFLets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "par.gaussian_hires=True # assuming we know the PSFLets perfectly a priori"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you choose to change that to False, you should also change the following nsubarr parameter to >4 since there is likely variation of the PSFLet across the field of view. Let's go! This takes a few minutes. It will finish by a parallel process so don't worry if your computer heats up a bit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Building calibration files, placing results in ..//ReferenceFiles/wavecalR50_660/\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_600.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_600.fits\n",
      "crispy - INFO - Initializing PSFlet location transformation coefficients\n",
      "crispy - INFO - Performing initial optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_600.fits\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_600.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_605.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_605.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_610.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_610.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_615.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_615.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_620.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_620.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_625.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_625.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_630.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_630.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_635.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_635.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_640.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_640.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_645.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_645.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_650.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_650.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_655.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_655.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_660.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_660.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_665.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_665.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_670.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_670.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_675.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_675.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_680.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_680.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_685.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_685.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_690.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_690.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_695.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_695.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_700.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_700.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_705.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_705.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_710.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_710.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_715.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_715.fits\n",
      "crispy - INFO - Read data from HDU 1 of ..//ReferenceFiles/wavecalR50_660/det_720.fits\n",
      "crispy - INFO - Initializing transformation coefficients with previous values\n",
      "crispy - INFO - Performing final optimization of PSFlet location transformation coefficients for frame ..//ReferenceFiles/wavecalR50_660/det_720.fits\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Saving wavelength solution to ..//ReferenceFiles/wavecalR50_660/lamsol.dat\n",
      "crispy - INFO - Computing wavelength values at pixel centers\n",
      "crispy - INFO - Making high-resolution PSFLet models\n",
      "crispy - INFO - Starting parallel computation\n",
      "crispy - INFO - Computing PSFLet widths...\n",
      "crispy - INFO - Reduced cube will have 19 wavelength bins\n",
      "crispy - INFO - Making polychrome cube\n",
      "crispy - INFO - Saving polychrome cube\n",
      "crispy - INFO - Saving wavelength calibration cube\n",
      "crispy - INFO - Total time elapsed: 264 s\n"
     ]
    }
   ],
   "source": [
    "buildcalibrations(par,\n",
    "                    inspect=False,         # if True, constructs a bunch of images to verify a good calibration\n",
    "                    genwavelengthsol=True, # Compute wavelength at the center of all pixels\n",
    "                    makehiresPSFlets=True, # this requires very high SNR on the monochromatic frames\n",
    "                    makePSFWidths=True,\n",
    "                    makePolychrome=True,   # This is needed to use least squares extraction\n",
    "                    upsample=3,            # upsampling factor of the high-resolution PSFLets\n",
    "                    nsubarr=3,             # the detector is divided into nsubarr^2 regions for PSFLet averaging\n",
    "                    apodize=False,          # to match PSFlet spot locations, only use the inner circular part of the \n",
    "                                           #detector, hence discarding the corners of the detector where lenslets are \n",
    "                                           #distorted\n",
    "                    threshold=1e-4,\n",
    "                  ) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the files we constructed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['.DS_Store',\n",
       " 'det_600.fits',\n",
       " 'det_605.fits',\n",
       " 'det_610.fits',\n",
       " 'det_615.fits',\n",
       " 'det_620.fits',\n",
       " 'det_625.fits',\n",
       " 'det_630.fits',\n",
       " 'det_635.fits',\n",
       " 'det_640.fits',\n",
       " 'det_645.fits',\n",
       " 'det_650.fits',\n",
       " 'det_655.fits',\n",
       " 'det_660.fits',\n",
       " 'det_665.fits',\n",
       " 'det_670.fits',\n",
       " 'det_675.fits',\n",
       " 'det_680.fits',\n",
       " 'det_685.fits',\n",
       " 'det_690.fits',\n",
       " 'det_695.fits',\n",
       " 'det_700.fits',\n",
       " 'det_705.fits',\n",
       " 'det_710.fits',\n",
       " 'det_715.fits',\n",
       " 'det_720.fits',\n",
       " 'hires_psflets_lam600.fits',\n",
       " 'hires_psflets_lam605.fits',\n",
       " 'hires_psflets_lam610.fits',\n",
       " 'hires_psflets_lam615.fits',\n",
       " 'hires_psflets_lam620.fits',\n",
       " 'hires_psflets_lam625.fits',\n",
       " 'hires_psflets_lam630.fits',\n",
       " 'hires_psflets_lam635.fits',\n",
       " 'hires_psflets_lam640.fits',\n",
       " 'hires_psflets_lam645.fits',\n",
       " 'hires_psflets_lam650.fits',\n",
       " 'hires_psflets_lam655.fits',\n",
       " 'hires_psflets_lam660.fits',\n",
       " 'hires_psflets_lam665.fits',\n",
       " 'hires_psflets_lam670.fits',\n",
       " 'hires_psflets_lam675.fits',\n",
       " 'hires_psflets_lam680.fits',\n",
       " 'hires_psflets_lam685.fits',\n",
       " 'hires_psflets_lam690.fits',\n",
       " 'hires_psflets_lam695.fits',\n",
       " 'hires_psflets_lam700.fits',\n",
       " 'hires_psflets_lam705.fits',\n",
       " 'hires_psflets_lam710.fits',\n",
       " 'hires_psflets_lam715.fits',\n",
       " 'hires_psflets_lam720.fits',\n",
       " 'inspection_600.png',\n",
       " 'lamsol.dat',\n",
       " 'polychromekeyR50.fits',\n",
       " 'polychromeR50.fits',\n",
       " 'polychromeR50.fits.gz',\n",
       " 'polychromeR50stack.fits.gz',\n",
       " 'PSFloc.fits',\n",
       " 'PSFwidths.fits']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(par.wavecalDir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of these files are described and explained in the papers associated with this work. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Construct fields to extract"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's construct a field that we will want to extract. For example, we will use a flatfield."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function testCreateFlatfield in module crispy.unitTests:\n",
      "\n",
      "testCreateFlatfield(par, pixsize=0.1, npix=512, pixval=1.0, Nspec=45, outname='flatfield.fits', useQE=True, method='optext')\n",
      "    Creates a polychromatic flatfield\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    par :   Parameter instance\n",
      "        Contains all IFS parameters\n",
      "    pixsize:   float\n",
      "       Pixel scale (lam/D)\n",
      "    npix: int\n",
      "        Each input frame has a pixel size npix x npix\n",
      "    pixval: float\n",
      "        Each input frame has a unform value pixval in photons per second per nm of bandwidth\n",
      "    Nspec: float\n",
      "        Optional input forcing the number of wavelengths bins used\n",
      "    outname: string\n",
      "        Name of flatfield image\n",
      "    useQE: boolean \n",
      "        Whether to take into account the wavelength-dependent QE of the detector\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from crispy.unitTests import testCreateFlatfield\n",
    "help(testCreateFlatfield)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Reduced cube will have 44 wavelength bins\n",
      "crispy - INFO - The number of input pixels per lenslet is 5.016181\n",
      "crispy - INFO - Using PSFlet gaussian approximation\n",
      "crispy - WARNING - Assuming endpoints wavelist is given\n",
      "crispy - INFO - Creating Gaussian PSFLet templates\n",
      "crispy - INFO - Writing data to ..//SimResults/imagePlaneRot.fits\n",
      "crispy - INFO - Writing data to ..//SimResults/detectorFramepoly.fits\n",
      "crispy - INFO - Done.\n",
      "crispy - INFO - Performance: 50 seconds total\n",
      "crispy - INFO - Writing data to ..//unitTestsOutputs/flatfield.fits\n"
     ]
    }
   ],
   "source": [
    "par.savePoly=True\n",
    "par.saveRotatedInput = True\n",
    "testCreateFlatfield(par,useQE=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Read data from HDU 1 of ..//unitTestsOutputs/flatfield.fits\n"
     ]
    },
    {
     "data": {
      "image/png": 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2C8Y9HdG28DCZNGEszvj3WhyjSzkiPgqKRS/einHfEEgxUyfif559B1M8jdw0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/ZksFJlxdx+8k1TWoPL6b442leJekoKamEhOuqeV2khKPB5tunA736G7L3DG/dkoYatZXYcI1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\nlLOMY9cUycIDVx4O7wvsS1vbMZPxp/Oe5OY8bew2juXiiUt+C/e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czrQ9WoEFaFMODEke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mtSCgE3BUAkcO7rhbizibU9kxTEq4SmIoGrKYYUU1EE6ohKSZoMa+D38NMPiM0OUl4Q5SWT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\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K4c0MVQ+ulGyJTkJiWgRZ00XBZu6rGP8DAaIbdFQ+tFL8Zjl3CjrnhUvuCRKe5iwXhuXi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\nGmVfTQUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11336a250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Read data from HDU 1 of ..//unitTestsOutputs/flatfield.fits\n"
     ]
    },
    {
     "data": {
      "image/png": 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WViTbpGUlA9PST+tvvr1xUQ9bgTMti3k5Or90qX5uS7aFuXhgTWuqAQBMhJIFABCgZAEA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11341c410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(Image(par.unitTestsOutputs+'/flatfield.fits').data)\n",
    "plt.show()\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(Image(par.unitTestsOutputs+'/flatfield.fits').data[500:550,500:550])\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Reduce the flatfield!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function reduceIFSMap in module crispy.IFS:\n",
      "\n",
      "reduceIFSMap(par, IFSimageName, method='optext', smoothbad=True, name=None, hires=False, dy=3, fitbkgnd=True, specialPolychrome=None, returnall=False, niter=10, pixnoise=0.0, normpsflets=False)\n",
      "    Main reduction function\n",
      "    \n",
      "    Uses various routines to extract an IFS detector map into a spectral-spatial cube.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    par :   Parameter instance\n",
      "            Contains all IFS parameters\n",
      "    IFSimageName : string or 2D ndarray\n",
      "            Path of image file, of 2D ndarray.\n",
      "    method : 'lstsq', 'optext'\n",
      "            Method used for reduction.\n",
      "            'lstsq': use the knowledge of the PSFs at each location and each wavelength and fits\n",
      "            the microspectrum as a weighted sum of these PSFs in the least-square sense. Can weigh the data by its variance.\n",
      "            'optext': use a matched filter to appropriately weigh each pixel and assign the fluxes, making use of the inverse\n",
      "            wavlength calibration map. Then remap each microspectrum onto the desired wavelengths\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    cube: 3D ndarray\n",
      "        Reduced IFS cube\n",
      "\n",
      "crispy - INFO - Read data from HDU 1 of ..//unitTestsOutputs/flatfield.fits\n",
      "crispy - INFO - Reduced cube will have 19 wavelength bins\n",
      "crispy - INFO - Writing data to ..//SimResults/flatfield_red_lstsq_conv_resid.fits\n",
      "crispy - INFO - Writing data to ..//SimResults/flatfield_red_lstsq_conv_model.fits\n",
      "crispy - INFO - Elapsed time: 11.791295s\n"
     ]
    }
   ],
   "source": [
    "from crispy.IFS import reduceIFSMap\n",
    "help(reduceIFSMap)\n",
    "detector = reduceIFSMap(par,par.unitTestsOutputs+'/flatfield.fits',method='lstsq_conv',smoothbad=False,fitbkgnd=False,niter=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Let's plot what we have got"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Read data from HDU 1 of ..//SimResults/flatfield_red_lstsq.fits\n",
      "crispy - INFO - Read inverse variance from HDU 2 of ..//SimResults/flatfield_red_lstsq.fits\n"
     ]
    },
    {
     "data": {
      "image/png": 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Dvbmvj2swaXxU/hE54ZgRBQAAQC+YEQUAAJhRjHVEu8KMKAAAAHrBjCgAAMAc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\nEw0AzgkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11336a8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ftsize = 15\n",
    "cmap='viridis'\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.imshow(Image(par.exportDir+'/flatfield_red_lstsq.fits').data[5],cmap=cmap)\n",
    "plt.axis('off')\n",
    "plt.colorbar(fraction=0.046, pad=0.04)\n",
    "plt.title('Data',fontsize=ftsize)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BMN6zDwAwtJdnyMJ6Sd855FEyQAbrYztS56EPT34fAPDFCWL/0ND534rgSRrQ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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1120535d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from astropy.io import fits\n",
    "BB = fits.getdata(par.unitTestsOutputs+\"/flatfield.fits\")\n",
    "BBres = fits.getdata(par.exportDir+'/flatfield_red_lstsq_resid.fits')\n",
    "BBmod = fits.getdata(par.exportDir+'/flatfield_red_lstsq_model.fits')\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(131)\n",
    "plt.imshow(BB[850:-100,150:300].T,vmin=0,vmax=np.amax(BB[850:-100,150:300]),cmap=cmap)\n",
    "plt.axis('off')\n",
    "plt.colorbar(fraction=0.046, pad=0.04,orientation='horizontal')\n",
    "plt.title('Data',fontsize=ftsize)\n",
    "plt.subplot(132)\n",
    "plt.imshow(BBmod[850:-100,150:300].T,vmin=0,vmax=np.amax(BB[850:-100,150:300]),cmap=cmap)\n",
    "plt.axis('off')\n",
    "plt.colorbar(fraction=0.046, pad=0.04,orientation='horizontal')\n",
    "plt.title('Model',fontsize=ftsize)\n",
    "plt.subplot(133)\n",
    "plt.imshow(100*BBres[850:-100,150:300].T/np.amax(BB[850:-120,150:300].T),vmin=-2,vmax=2,cmap=cmap)\n",
    "plt.axis('off')\n",
    "plt.colorbar(fraction=0.046, pad=0.04,orientation='horizontal')\n",
    "plt.title('Residuals (\\% of data max)',fontsize=ftsize)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The residuals are caused by an imperfect wavelength calibration (small errors in centroids). In this region it is less than +/-2% of the peak data value, and the induced errors in recovered flux are +/-1% in slice number 5 (see above). These are systematic errors that we can calibrate by using an IFS flat field."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to know the correspondence between slice and wavelength, we can do the following"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "crispy - INFO - Reduced cube will have 19 wavelength bins\n",
      "('Wavelengths at midpoints for lstsq (nm): ', array([ 603.48591977,  609.29942699,  615.16893696,  621.09498916,\n",
      "        627.07812827,  633.11890422,  639.21787224,  645.37559291,\n",
      "        651.5926322 ,  657.86956154,  664.20695787,  670.60540367,\n",
      "        677.06548705,  683.58780178,  690.17294734,  696.821529  ,\n",
      "        703.53415785,  710.31145087,  717.15403098]))\n",
      "('Wavelengths at endpoints for lstsq (nm): ', array([ 600.6       ,  606.38570655,  612.22714804,  618.12486136,\n",
      "        624.0793886 ,  630.09127706,  636.16107931,  642.28935325,\n",
      "        648.47666214,  654.72357468,  661.03066505,  667.39851296,\n",
      "        673.82770368,  680.31882816,  686.87248301,  693.4892706 ,\n",
      "        700.1697991 ,  706.91468254,  713.72454087,  720.6       ]))\n",
      "crispy - INFO - Reduced cube will have 19 wavelength bins\n",
      "('Wavelengths at midpoints for optext (nm): ', array([ 603.48591977,  609.29942699,  615.16893696,  621.09498916,\n",
      "        627.07812827,  633.11890422,  639.21787224,  645.37559291,\n",
      "        651.5926322 ,  657.86956154,  664.20695787,  670.60540367,\n",
      "        677.06548705,  683.58780178,  690.17294734,  696.821529  ,\n",
      "        703.53415785,  710.31145087,  717.15403098]))\n",
      "('Wavelengths at endpoints for optext (nm): ', array([ 600.6       ,  606.38570655,  612.22714804,  618.12486136,\n",
      "        624.0793886 ,  630.09127706,  636.16107931,  642.28935325,\n",
      "        648.47666214,  654.72357468,  661.03066505,  667.39851296,\n",
      "        673.82770368,  680.31882816,  686.87248301,  693.4892706 ,\n",
      "        700.1697991 ,  706.91468254,  713.72454087,  720.6       ]))\n"
     ]
    }
   ],
   "source": [
    "from crispy.tools.reduction import calculateWaveList\n",
    "lam_midpts,lam_endpts = calculateWaveList(par,method='lstsq')\n",
    "print('Wavelengths at midpoints for lstsq (nm): ',lam_midpts)\n",
    "print('Wavelengths at endpoints for lstsq (nm): ',lam_endpts)\n",
    "lam_midpts,lam_endpts = calculateWaveList(par,method='optext')\n",
    "print('Wavelengths at midpoints for optext (nm): ',lam_midpts)\n",
    "print('Wavelengths at endpoints for optext (nm): ',lam_endpts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Start from known wavecal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the case where we want to use another wavecal (e.g. obtained from lab measurements), we can set this up with par.PSFLetPositions = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# par.PSFLetPositions = True\n",
    "# par.wavecalDir = par.prefix+'/Calibra_170425/'\n",
    "\n",
    "# watch out to be sure you have the correct R that matches the wavecal! In this case, it is R=70\n",
    "#par.R = 70"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Repeat the flatfield exercise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#from crispy.unitTests import testCreateFlatfield\n",
    "#testCreateFlatfield(par,useQE=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# par.PSFLetPositions = False\n",
    "# par.R=50\n",
    "# par.wavecalDir = par.prefix+'/wavecalR50_SC/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# from crispy.unitTests import testCrosstalk\n",
    "# testCrosstalk(par,pixval=25,method='optext',useQE=False)\n",
    "# extracted = reduceIFSMap(par,par.unitTestsOutputs+'/crosstalk.fits',method='lstsq',smoothbad=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# extracted = reduceIFSMap(par,par.unitTestsOutputs+'/flatfield.fits',method='lstsq',smoothbad=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
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}