camera/1_Build_detectors.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# build obs_vista camera description\n",
    "\n",
    "In this notebook we will build the files describing the VISTA camera geometry and properties. We are now using the gen 3 yaml format to describe the camera. \n",
    "\n",
    "https://github.com/lsst/obs_base/blob/master/python/lsst/obs/base/yamlCamera.py\n",
    "\n",
    "For stacks the gain is effectively multiplied by the number of exposures (6). However there are complications due to clipping. We are currently working on replacing the per stack gain with a per exposure gain such that the gain must be multiplied by the exposure number when computing the variance later.\n",
    "\n",
    "http://casu.ast.cam.ac.uk/surveys-projects/vista/technical/vista-gain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lsst_distrib          g7ae64ea4b3+059940673e \tcurrent w_2022_03 w_latest setup\n",
      "obs_vista             23.0.0-1   \tcurrent setup\n"
     ]
    }
   ],
   "source": [
    "# What version of the Stack are we using?\n",
    "! eups list -s | grep lsst_distrib\n",
    "! eups list -s | grep obs_vista"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 Load camera data files\n",
    "Originally we produced a fits file for each ccd based on the obs_subaru example. Now we are deprecating all gen 2 code and using the yaml camera description format only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yaml\n",
    "import lsst\n",
    "import lsst.afw.table as afwTable\n",
    "import lsst.afw.geom as afwGeom\n",
    "import lsst.geom as geom\n",
    "import numpy as np\n",
    "\n",
    "from astropy.io import fits\n",
    "from astropy.table import Table\n",
    "from astropy.coordinates import SkyCoord, Angle, AltAz, EarthLocation\n",
    "from astropy.wcs import WCS\n",
    "import astropy.units as u\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Use an example stack to reverse engineer the camera geometry\n",
    "ex_stack='/Users/raphaelshirley/Documents/github/lsst-ir-fusion/dmu0/dmu0_VISTA/dmu0_VIDEO/data/20121122/v20121122_00088_st.fit'\n",
    "ex_stack2='/Users/raphaelshirley/Documents/github/lsst-ir-fusion/dmu0/dmu0_VISTA/dmu0_VIDEO/data/20121122/v20121122_00144_st.fit'\n",
    "ex_stackZ='/Users/raphaelshirley/Documents/github/lsst-ir-fusion/dmu0/dmu0_VISTA/dmu0_VIDEO/data/20120924/v20120924_00582_st.fit'\n",
    "ex_fit='/Users/raphaelshirley/Documents/github/lsst-ir-fusion/dmu0/dmu0_VISTA/dmu0_VIDEO/data/20121122/v20121122_00088.fit'\n",
    "gain = Table.read('./gain.csv')\n",
    "readout_noise = Table.read('./readout_noise.csv')\n",
    "saturation = Table.read('./saturation.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=16</i>\n",
       "<table id=\"table140313233023136\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>id</th><th>NB118</th><th>Z</th><th>Y</th><th>J</th><th>Average</th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>1</td><td>3.648</td><td>3.628</td><td>3.63</td><td>3.717</td><td>3.66</td></tr>\n",
       "<tr><td>2</td><td>4.28</td><td>4.251</td><td>4.206</td><td>4.247</td><td>4.25</td></tr>\n",
       "<tr><td>3</td><td>3.957</td><td>3.947</td><td>3.858</td><td>4.045</td><td>3.95</td></tr>\n",
       "<tr><td>4</td><td>4.154</td><td>4.102</td><td>4.041</td><td>4.335</td><td>4.16</td></tr>\n",
       "<tr><td>5</td><td>4.16</td><td>4.139</td><td>4.125</td><td>4.517</td><td>4.24</td></tr>\n",
       "<tr><td>6</td><td>4.063</td><td>4.074</td><td>4.11</td><td>4.179</td><td>4.11</td></tr>\n",
       "<tr><td>7</td><td>3.882</td><td>3.78</td><td>3.787</td><td>3.903</td><td>3.84</td></tr>\n",
       "<tr><td>8</td><td>4.153</td><td>4.216</td><td>4.176</td><td>4.326</td><td>4.22</td></tr>\n",
       "<tr><td>9</td><td>4.639</td><td>4.5</td><td>4.396</td><td>4.589</td><td>4.53</td></tr>\n",
       "<tr><td>10</td><td>3.964</td><td>3.94</td><td>3.867</td><td>4.107</td><td>3.97</td></tr>\n",
       "<tr><td>11</td><td>4.594</td><td>4.492</td><td>4.499</td><td>4.876</td><td>4.62</td></tr>\n",
       "<tr><td>12</td><td>4.018</td><td>3.886</td><td>3.898</td><td>4.006</td><td>3.95</td></tr>\n",
       "<tr><td>13</td><td>5.14</td><td>5.728</td><td>5.764</td><td>6.054</td><td>5.67</td></tr>\n",
       "<tr><td>14</td><td>4.725</td><td>4.695</td><td>4.774</td><td>4.911</td><td>4.78</td></tr>\n",
       "<tr><td>15</td><td>4.088</td><td>3.754</td><td>3.977</td><td>4.152</td><td>3.99</td></tr>\n",
       "<tr><td>16</td><td>5.608</td><td>4.634</td><td>4.18</td><td>5.426</td><td>4.96</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=16>\n",
       "  id   NB118     Z       Y       J    Average\n",
       "int64 float64 float64 float64 float64 float64\n",
       "----- ------- ------- ------- ------- -------\n",
       "    1   3.648   3.628    3.63   3.717    3.66\n",
       "    2    4.28   4.251   4.206   4.247    4.25\n",
       "    3   3.957   3.947   3.858   4.045    3.95\n",
       "    4   4.154   4.102   4.041   4.335    4.16\n",
       "    5    4.16   4.139   4.125   4.517    4.24\n",
       "    6   4.063   4.074    4.11   4.179    4.11\n",
       "    7   3.882    3.78   3.787   3.903    3.84\n",
       "    8   4.153   4.216   4.176   4.326    4.22\n",
       "    9   4.639     4.5   4.396   4.589    4.53\n",
       "   10   3.964    3.94   3.867   4.107    3.97\n",
       "   11   4.594   4.492   4.499   4.876    4.62\n",
       "   12   4.018   3.886   3.898   4.006    3.95\n",
       "   13    5.14   5.728   5.764   6.054    5.67\n",
       "   14   4.725   4.695   4.774   4.911    4.78\n",
       "   15   4.088   3.754   3.977   4.152    3.99\n",
       "   16   5.608   4.634    4.18   5.426    4.96"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gain #electrons/ADU - see Table 3 in https://www.eso.org/sci/facilities/paranal/instruments/vircam/doc/VIS-MAN-ESO-06000-0002_v108.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=16</i>\n",
       "<table id=\"table140312421620272\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>id</th><th>NB118</th><th>Z</th><th>Y</th><th>J</th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>1</td><td>22.903</td><td>22.782</td><td>22.791</td><td>27.231</td></tr>\n",
       "<tr><td>2</td><td>22.394</td><td>26.694</td><td>22.007</td><td>26.665</td></tr>\n",
       "<tr><td>3</td><td>20.708</td><td>24.783</td><td>20.186</td><td>25.402</td></tr>\n",
       "<tr><td>4</td><td>21.734</td><td>25.758</td><td>21.145</td><td>27.222</td></tr>\n",
       "<tr><td>5</td><td>21.77</td><td>25.989</td><td>21.586</td><td>28.364</td></tr>\n",
       "<tr><td>6</td><td>21.258</td><td>25.579</td><td>21.504</td><td>26.241</td></tr>\n",
       "<tr><td>7</td><td>24.378</td><td>23.737</td><td>19.814</td><td>24.505</td></tr>\n",
       "<tr><td>8</td><td>21.732</td><td>26.474</td><td>21.853</td><td>27.16</td></tr>\n",
       "<tr><td>9</td><td>19.418</td><td>18.838</td><td>18.401</td><td>19.209</td></tr>\n",
       "<tr><td>10</td><td>24.888</td><td>24.74</td><td>24.28</td><td>25.786</td></tr>\n",
       "<tr><td>11</td><td>24.039</td><td>23.504</td><td>23.543</td><td>25.512</td></tr>\n",
       "<tr><td>12</td><td>25.233</td><td>24.403</td><td>20.398</td><td>25.153</td></tr>\n",
       "<tr><td>13</td><td>26.898</td><td>29.973</td><td>24.128</td><td>25.341</td></tr>\n",
       "<tr><td>14</td><td>19.78</td><td>19.652</td><td>14.989</td><td>20.558</td></tr>\n",
       "<tr><td>15</td><td>17.113</td><td>19.643</td><td>16.65</td><td>17.38</td></tr>\n",
       "<tr><td>16</td><td>23.477</td><td>19.398</td><td>17.497</td><td>22.714</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=16>\n",
       "  id   NB118     Z       Y       J   \n",
       "int64 float64 float64 float64 float64\n",
       "----- ------- ------- ------- -------\n",
       "    1  22.903  22.782  22.791  27.231\n",
       "    2  22.394  26.694  22.007  26.665\n",
       "    3  20.708  24.783  20.186  25.402\n",
       "    4  21.734  25.758  21.145  27.222\n",
       "    5   21.77  25.989  21.586  28.364\n",
       "    6  21.258  25.579  21.504  26.241\n",
       "    7  24.378  23.737  19.814  24.505\n",
       "    8  21.732  26.474  21.853   27.16\n",
       "    9  19.418  18.838  18.401  19.209\n",
       "   10  24.888   24.74   24.28  25.786\n",
       "   11  24.039  23.504  23.543  25.512\n",
       "   12  25.233  24.403  20.398  25.153\n",
       "   13  26.898  29.973  24.128  25.341\n",
       "   14   19.78  19.652  14.989  20.558\n",
       "   15  17.113  19.643   16.65   17.38\n",
       "   16  23.477  19.398  17.497  22.714"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "readout_noise # [electrons]? from https://www.eso.org/sci/facilities/paranal/instruments/vircam/doc/VIS-MAN-ESO-06000-0002_v108.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=16</i>\n",
       "<table id=\"table140312421618352\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>detector</th><th>saturation</th><th>non-linearity</th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>int64</th><th>float64</th></tr></thead>\n",
       "<tr><td>1</td><td>33000</td><td>2.2</td></tr>\n",
       "<tr><td>2</td><td>32000</td><td>3.3</td></tr>\n",
       "<tr><td>3</td><td>33000</td><td>3.8</td></tr>\n",
       "<tr><td>4</td><td>32000</td><td>3.5</td></tr>\n",
       "<tr><td>5</td><td>24000</td><td>2.0</td></tr>\n",
       "<tr><td>6</td><td>26000</td><td>3.0</td></tr>\n",
       "<tr><td>7</td><td>35000</td><td>2.0</td></tr>\n",
       "<tr><td>8</td><td>33000</td><td>3.4</td></tr>\n",
       "<tr><td>9</td><td>35000</td><td>3.3</td></tr>\n",
       "<tr><td>10</td><td>35000</td><td>4.4</td></tr>\n",
       "<tr><td>11</td><td>37000</td><td>4.6</td></tr>\n",
       "<tr><td>12</td><td>34000</td><td>2.6</td></tr>\n",
       "<tr><td>13</td><td>33000</td><td>10.0</td></tr>\n",
       "<tr><td>14</td><td>35000</td><td>2.7</td></tr>\n",
       "<tr><td>15</td><td>34000</td><td>1.7</td></tr>\n",
       "<tr><td>16</td><td>34000</td><td>3.3</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=16>\n",
       "detector saturation non-linearity\n",
       " int64     int64       float64   \n",
       "-------- ---------- -------------\n",
       "       1      33000           2.2\n",
       "       2      32000           3.3\n",
       "       3      33000           3.8\n",
       "       4      32000           3.5\n",
       "       5      24000           2.0\n",
       "       6      26000           3.0\n",
       "       7      35000           2.0\n",
       "       8      33000           3.4\n",
       "       9      35000           3.3\n",
       "      10      35000           4.4\n",
       "      11      37000           4.6\n",
       "      12      34000           2.6\n",
       "      13      33000          10.0\n",
       "      14      35000           2.7\n",
       "      15      34000           1.7\n",
       "      16      34000           3.3"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "saturation #ADU? non-linearity - percent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Camera geomtry\n",
    "It is possible to set a given CCD world coordinate system using the camera geometry and the telescope tracking radec. We may therefore want to describe the camera geometry by taking an example exposure and taking the offset of the pixels from the reference radec in the centre of the focal plane. These will be different for stacks vs single exposures due to dithers changing the pixel bounding boxes. These will also differ depending on the dither patterns adopted by a given survey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "POINTING: 35.43265 -4.72313\n",
      "1 (5406.375, 6832.391) (array(5405.375), array(6831.391)) (array(5398.81344965), array(6842.24391529)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43192856, -4.72219667)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.94007405, -4.0782962)>\n",
      "2 (2482.837, 6845.058) (array(2481.837), array(6844.058)) (array(2474.15164877), array(6851.27979031)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43182297, -4.7225415)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.66564138, -4.07718605)>\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: FITSFixedWarning: RADECSYS= 'ICRS ' / Coordinate reference frame \n",
      "the RADECSYS keyword is deprecated, use RADESYSa. [astropy.wcs.wcs]\n",
      "WARNING: FITSFixedWarning: PROJP1 = 1. / Old style WCS \n",
      "the PROJPn keyword is deprecated, use PVi_ma. [astropy.wcs.wcs]\n",
      "WARNING: FITSFixedWarning: PROJP3 = 44. / Old style WCS \n",
      "the PROJPn keyword is deprecated, use PVi_ma. [astropy.wcs.wcs]\n",
      "WARNING: FITSFixedWarning: PROJP5 = -10300. / Old style WCS \n",
      "the PROJPn keyword is deprecated, use PVi_ma. [astropy.wcs.wcs]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 (-431.6327, 6849.338) (array(-432.6327), array(6848.338)) (array(-439.55658627), array(6849.60932079)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43189576, -4.72310527)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.39002539, -4.07732451)>\n",
      "4 (-3348.992, 6852.811) (array(-3349.992), array(6851.811)) (array(-3360.42619197), array(6849.52171247)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43156255, -4.7234435)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.11419777, -4.07834334)>\n",
      "5 (5396.107, 2949.336) (array(5395.107), array(2948.336)) (array(5394.79674479), array(2957.09870851)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43252443, -4.72239401)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.94303911, -4.44316611)>\n",
      "6 (2477.565, 2953.229) (array(2476.565), array(2952.229)) (array(2474.69163855), array(2956.14640333)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43237619, -4.72285362)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.66724337, -4.44292878)>\n",
      "7 (-439.3481, 2957.282) (array(-440.3481), array(2956.282)) (array(-444.25671477), array(2955.87770691)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43218327, -4.72326375)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.39000943, -4.44318238)>\n",
      "8 (-3354.422, 2964.089) (array(-3355.422), array(2963.089)) (array(-3360.36289523), array(2958.4588785)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43208537, -4.72366494)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.1131347, -4.44373156)>\n",
      "9 (5389.051, -940.345) (array(5388.051), array(-941.345)) (array(5393.53561623), array(-934.36016314)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43307588, -4.7225619)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.94428285, -4.81066261)>\n",
      "10 (2473.604, -935.0881) (array(2472.604), array(-936.0881)) (array(2474.31553165), array(-935.62650491)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43271774, -4.72318103)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.66803343, -4.81161427)>\n",
      "11 (-445.1697, -931.6677) (array(-446.1697), array(-932.6677)) (array(-444.44473637), array(-934.89455088)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43271942, -4.72343597)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.39047802, -4.81186427)>\n",
      "12 (-3361.077, -930.3582) (array(-3362.077), array(-931.3582)) (array(-3361.76491426), array(-938.4336374)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43258549, -4.7238958)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.11316628, -4.8122129)>\n",
      "13 (5392.87, -4822.053) (array(5391.87), array(-4823.053)) (array(5399.74312594), array(-4820.99094832)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43330416, -4.72302968)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.94368161, -5.17771678)>\n",
      "14 (2465.172, -4827.306) (array(2464.172), array(-4828.306)) (array(2474.01618674), array(-4828.78982679)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43349174, -4.72326865)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.6680948, -5.17891191)>\n",
      "15 (-451.8867, -4820.927) (array(-452.8867), array(-4821.927)) (array(-445.20754908), array(-4827.7260976)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43328642, -4.7237741)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.39100525, -5.17984041)>\n",
      "16 (-3367.577, -4818.762) (array(-3368.577), array(-4819.762)) (array(-3362.55638469), array(-4829.64540572)) <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.43312873, -4.72416184)> <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (35.1142432, -5.17961113)>\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f=fits.open(ex_stack)\n",
    "trackingRaDec=SkyCoord(f[0].header['RA'],f[0].header['DEC'],unit='deg')\n",
    "print('POINTING:',f[0].header['RA'],f[0].header['DEC'])\n",
    "for i in range(1,17):\n",
    "    w=WCS(f[i].header)\n",
    "    print(i,\n",
    "        (f[i].header['CRPIX1'],f[i].header['CRPIX2']),\n",
    "        w.world_to_pixel(SkyCoord(f[i].header['CRVAL1']*u.deg,f[i].header['CRVAL2']*u.deg)),\n",
    "        w.world_to_pixel(trackingRaDec),\n",
    "        w.pixel_to_world(f[i].header['CRPIX1'],f[i].header['CRPIX2']),\n",
    "        w.pixel_to_world(0,0),\n",
    "        \n",
    "    )\n",
    "    plt.scatter(w.pixel_to_world(f[i].header['CRPIX1'],f[i].header['CRPIX2']).ra.deg,\n",
    "                w.pixel_to_world(f[i].header['CRPIX1'],f[i].header['CRPIX2']).dec.deg)\n",
    "    plt.plot(\n",
    "        [w.pixel_to_world(0,0).ra.deg,w.pixel_to_world(0,2048).ra.deg,\n",
    "         w.pixel_to_world(2048,2048).ra.deg,w.pixel_to_world(2048,0).ra.deg,w.pixel_to_world(0,0).ra.deg],\n",
    "        [w.pixel_to_world(0,0).dec.deg,w.pixel_to_world(0,2048).dec.deg,\n",
    "         w.pixel_to_world(2048,2048).dec.deg,w.pixel_to_world(2048,0).dec.deg,w.pixel_to_world(0,0).dec.deg])\n",
    "    plt.annotate(\n",
    "        \"{} ({},{})\".format(i,int(f[i].header['CRPIX1']),int(f[i].header['CRPIX2'])),\n",
    "        (w.pixel_to_world(0,0).ra.deg,w.pixel_to_world(0,0).dec.deg))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gen 3 YAML file version\n",
    "\n",
    "In gen 3 the camera is defined in a single yaml file. Since we are currently developing obs_vista to be compatible with both we here also make the yaml file. gen 2 will be deprecated fully at some point before LSST commences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plateScale = 16.95    # Calculated from 0.339 arcesc/px and px = 0.02 mm\n",
    "#1.24 from necam example\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$-360^\\circ00{}^\\prime00{}^{\\prime\\prime}$"
      ],
      "text/plain": [
       "<Angle -360. deg>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.coordinates import SkyCoord, Angle\n",
    "import astropy.units as u\n",
    "posang=-90\n",
    "Angle(-(-posang + 270.)* u.deg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ccdSize=2048 #2048 #This must be smaller than the actual image we should get the maximin\n",
    "spacer=200\n",
    "\n",
    "#Physical mm distances are never used. Everything is in terms of sky arcsec\n",
    "pixelSize=0.02 # mm\n",
    "plateScale= 0.336 # arcsec \n",
    "# Sets the plate scale in arcsec/mm:\n",
    "pixelScale = plateScale/pixelSize #    # Calculated from 0.339 arcesc/px and px = 0.02 mm\n",
    "\n",
    "f=fits.open(ex_stack)\n",
    "trackingRaDec=SkyCoord(f[0].header['RA'],f[0].header['DEC'],unit='deg')\n",
    "\n",
    "\n",
    "camera = {\n",
    "    'name': 'vista',\n",
    "    'plateScale':plateScale,\n",
    "    'transforms': {\n",
    "        'nativeSys': 'FocalPlane',\n",
    "        'FieldAngle': {\n",
    "            'transformType': 'radial', #'radial' or 'affine'\n",
    "            'coeffs': [0.0, 1.0]\n",
    "        }\n",
    "    },\n",
    "    'CCDs': {}\n",
    "    \n",
    "}\n",
    "\n",
    "for i in range(16):\n",
    "    h=f[i+1].header\n",
    "    w=WCS(h)\n",
    "    \n",
    "    #ref_pos=w.world_to_pixel(SkyCoord(h['CRVAL1']*u.deg,h['CRVAL2']*u.deg))\n",
    "    ref_pos=w.world_to_pixel(trackingRaDec)\n",
    "    this_dict={\n",
    "        'name': 'ccd{}'.format(i+1),\n",
    "        'id': i+1,\n",
    "        'serial': str(i+1),\n",
    "        'detectorType': 0,\n",
    "        'bbox': [[0,0], [ccdSize, ccdSize]], \n",
    "        'pixelSize': [1.,1.],#mm? pixels?\n",
    "        'transformDict':{\n",
    "            'nativeSys': 'Pixels',\n",
    "            'transforms': 'None'\n",
    "        },\n",
    "        #This was set based on inspecting the results - ccdSize is removed and flipXY are set to get corners correct and up and down correct\n",
    "        'refpos': [-h['CRPIX1']+ccdSize,-h['CRPIX2']+ccdSize],\n",
    "        'offset': [0,0],\n",
    "        'transposeDetector': False,\n",
    "        'pitch': 0.0,\n",
    "        'yaw': 0.0,\n",
    "        'roll': 0.0,\n",
    "        'amplifiers':{\n",
    "            'AMP_E2V':{\n",
    "                'rawBBox': [[0,0],[ccdSize, ccdSize]],\n",
    "                'hdu': i+1 ,\n",
    "                'ixy': [0,0],\n",
    "                'perAmpData': True,\n",
    "                'rawDataBBox': [[0,0],[ccdSize, ccdSize]],\n",
    "                'rawSerialOverscanBBox': [[0,0],[0,0]],\n",
    "                'rawParallelOverscanBBox': [[0,0],[0,0]],\n",
    "                'rawSerialPrescanBBox': [[0,0],[0,0]],\n",
    "                'readCorner': 'LL',\n",
    "                #not correcting for expNum which is done in vircamIsrTask\n",
    "                #CASU gain values defined in e-/ADU = 1/gain as defined in LSST Science Pipelines\n",
    "                'gain': float(gain[i]['Average'] ), \n",
    "                'readNoise': float(\n",
    "                    np.mean([\n",
    "                        readout_noise[i]['Z'],\n",
    "                        readout_noise[i]['Y'],\n",
    "                        readout_noise[i]['J']\n",
    "                    ])/(gain[i]['Average'] )\n",
    "                ),\n",
    "                'saturation': int(saturation[i]['saturation']),\n",
    "                'flipXY': [True, True],\n",
    "                'linearityCoeffs': [\n",
    "                    float(saturation[i]['non-linearity']/100), \n",
    "                    int(10000)\n",
    "                ],\n",
    "                'linearityType': \"None\",\n",
    "                'linearityThreshold': 0,\n",
    "                'linearityMax': int(saturation[i]['saturation']),\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    camera['CCDs']['ccd{}'.format(i+1)]=this_dict\n",
    "    \n",
    "with open('vircam.yaml', 'w') as file:\n",
    "    documents = yaml.dump(camera, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24.186333333333334"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i=10\n",
    "np.mean([\n",
    "                        readout_noise[i]['Z'],\n",
    "                        readout_noise[i]['Y'],\n",
    "                        readout_noise[i]['J']\n",
    "                    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'vista',\n",
       " 'plateScale': 0.336,\n",
       " 'transforms': {'nativeSys': 'FocalPlane',\n",
       "  'FieldAngle': {'transformType': 'radial', 'coeffs': [0.0, 1.0]}},\n",
       " 'CCDs': {'ccd1': {'name': 'ccd1',\n",
       "   'id': 1,\n",
       "   'serial': '1',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-3358.375, -4784.391],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 1,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.66,\n",
       "     'readNoise': 6.630601092896175,\n",
       "     'saturation': 33000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.022000000000000002, 33000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 33000}}},\n",
       "  'ccd2': {'name': 'ccd2',\n",
       "   'id': 2,\n",
       "   'serial': '2',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-434.837, -4797.058],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 2,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.25,\n",
       "     'readNoise': 5.9110588235294115,\n",
       "     'saturation': 32000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.033, 32000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 32000}}},\n",
       "  'ccd3': {'name': 'ccd3',\n",
       "   'id': 3,\n",
       "   'serial': '3',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [2479.6327, -4801.338],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 3,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.95,\n",
       "     'readNoise': 5.938481012658229,\n",
       "     'saturation': 33000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.038, 33000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 33000}}},\n",
       "  'ccd4': {'name': 'ccd4',\n",
       "   'id': 4,\n",
       "   'serial': '4',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [5396.992, -4804.811],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 4,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.16,\n",
       "     'readNoise': 5.939503205128204,\n",
       "     'saturation': 32000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.035, 32000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 32000}}},\n",
       "  'ccd5': {'name': 'ccd5',\n",
       "   'id': 5,\n",
       "   'serial': '5',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-3348.107, -901.3359999999998],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 5,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.24,\n",
       "     'readNoise': 5.970047169811321,\n",
       "     'saturation': 24000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.02, 24000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 24000}}},\n",
       "  'ccd6': {'name': 'ccd6',\n",
       "   'id': 6,\n",
       "   'serial': '6',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-429.56500000000005, -905.2289999999998],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 6,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.11,\n",
       "     'readNoise': 5.9467964314679636,\n",
       "     'saturation': 26000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.03, 26000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 26000}}},\n",
       "  'ccd7': {'name': 'ccd7',\n",
       "   'id': 7,\n",
       "   'serial': '7',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [2487.3481, -909.2820000000002],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 7,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.84,\n",
       "     'readNoise': 5.907638888888889,\n",
       "     'saturation': 35000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.02, 35000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 35000}}},\n",
       "  'ccd8': {'name': 'ccd8',\n",
       "   'id': 8,\n",
       "   'serial': '8',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [5402.4220000000005, -916.0889999999999],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 8,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.22,\n",
       "     'readNoise': 5.96263823064771,\n",
       "     'saturation': 33000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.034, 33000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 33000}}},\n",
       "  'ccd9': {'name': 'ccd9',\n",
       "   'id': 9,\n",
       "   'serial': '9',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-3341.0510000000004, 2988.3450000000003],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 9,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.53,\n",
       "     'readNoise': 4.153642384105961,\n",
       "     'saturation': 35000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.033, 35000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 35000}}},\n",
       "  'ccd10': {'name': 'ccd10',\n",
       "   'id': 10,\n",
       "   'serial': '10',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-425.6039999999998, 2983.0881],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 10,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.97,\n",
       "     'readNoise': 6.280940386230058,\n",
       "     'saturation': 35000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.044000000000000004, 35000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 35000}}},\n",
       "  'ccd11': {'name': 'ccd11',\n",
       "   'id': 11,\n",
       "   'serial': '11',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [2493.1697, 2979.6677],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 11,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.62,\n",
       "     'readNoise': 5.235137085137085,\n",
       "     'saturation': 37000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.046, 37000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 37000}}},\n",
       "  'ccd12': {'name': 'ccd12',\n",
       "   'id': 12,\n",
       "   'serial': '12',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [5409.077, 2978.3582],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 12,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.95,\n",
       "     'readNoise': 5.9032911392405065,\n",
       "     'saturation': 34000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.026000000000000002, 34000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 34000}}},\n",
       "  'ccd13': {'name': 'ccd13',\n",
       "   'id': 13,\n",
       "   'serial': '13',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-3344.87, 6870.053],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 13,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 5.67,\n",
       "     'readNoise': 4.670311581422693,\n",
       "     'saturation': 33000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.1, 33000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 33000}}},\n",
       "  'ccd14': {'name': 'ccd14',\n",
       "   'id': 14,\n",
       "   'serial': '14',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [-417.172, 6875.306],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 14,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.78,\n",
       "     'readNoise': 3.849302649930265,\n",
       "     'saturation': 35000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.027000000000000003, 35000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 35000}}},\n",
       "  'ccd15': {'name': 'ccd15',\n",
       "   'id': 15,\n",
       "   'serial': '15',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [2499.8867, 6868.927],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 15,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 3.99,\n",
       "     'readNoise': 4.483959899749373,\n",
       "     'saturation': 34000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.017, 34000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 34000}}},\n",
       "  'ccd16': {'name': 'ccd16',\n",
       "   'id': 16,\n",
       "   'serial': '16',\n",
       "   'detectorType': 0,\n",
       "   'bbox': [[0, 0], [2048, 2048]],\n",
       "   'pixelSize': [1.0, 1.0],\n",
       "   'transformDict': {'nativeSys': 'Pixels', 'transforms': 'None'},\n",
       "   'refpos': [5415.577, 6866.762],\n",
       "   'offset': [0, 0],\n",
       "   'transposeDetector': False,\n",
       "   'pitch': 0.0,\n",
       "   'yaw': 0.0,\n",
       "   'roll': 0.0,\n",
       "   'amplifiers': {'AMP_E2V': {'rawBBox': [[0, 0], [2048, 2048]],\n",
       "     'hdu': 16,\n",
       "     'ixy': [0, 0],\n",
       "     'perAmpData': True,\n",
       "     'rawDataBBox': [[0, 0], [2048, 2048]],\n",
       "     'rawSerialOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawParallelOverscanBBox': [[0, 0], [0, 0]],\n",
       "     'rawSerialPrescanBBox': [[0, 0], [0, 0]],\n",
       "     'readCorner': 'LL',\n",
       "     'gain': 4.96,\n",
       "     'readNoise': 4.005981182795698,\n",
       "     'saturation': 34000,\n",
       "     'flipXY': [True, True],\n",
       "     'linearityCoeffs': [0.033, 34000],\n",
       "     'linearityType': 'None',\n",
       "     'linearityThreshold': 0,\n",
       "     'linearityMax': 34000}}}}}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "camera"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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