Try ccdproc astrometry.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astroquery.vizier import Vizier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "center = SkyCoord(135.563301393, 49.76324262, unit=('deg','deg'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "viz_gaia = Vizier(catalog='I/337/gaia')\n",
    "viz_gaia.ROW_LIMIT=-1\n",
    "gaia = viz_gaia.query_region(coordinates=center, radius='30 arcmin', catalog='I/337/gaia')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ccdproc import CCDData\n",
    "from photutils import DAOStarFinder\n",
    "from astropy.stats import mad_std\n",
    "ccd = CCDData.read('ey-uma-022R.fit')\n",
    "bkg_sigma = mad_std(ccd.data)\n",
    "daofind = DAOStarFinder(fwhm=3.0, threshold=5. * bkg_sigma)\n",
    "sources = daofind(ccd.data)\n",
    "bright = sources[sources['mag'].argsort()[:30]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "gaia.sort('__Gmag_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from ccdproc import astrometry as astrom\n",
    "x, y = bright['xcentroid'], bright['ycentroid']\n",
    "x, y = astrom.remove_duplicates(x, y, tolerance=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.modeling import models, fitting\n",
    "r, d = gaia['RA_ICRS'], gaia['DE_ICRS']\n",
    "matches = astrom.match_by_triangle(\n",
    "    x, y, r, d, n_limit=30, tolerance=0.02,\n",
    "    clean_limit=5, match_tolerance=0.02, m_init=models.Polynomial2D(1),\n",
    "    fitter = fitting.LinearLSQFitter())\n",
    "i1, i2 = matches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
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    "i2"
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    "x"
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  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "idp, idx = astrom.match_by_fit(\n",
    "    x, y, r, d, i1, i2, tolerance=0.00138889)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "array([0, 2, 3])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
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   ],
   "source": [
    "idp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WCS Keywords\n",
       "\n",
       "Number of WCS axes: 2\n",
       "CTYPE : 'RA---TAN'  'DEC--TAN'  \n",
       "CRVAL : 135.19683274323401  49.692117170561744  \n",
       "CRPIX : 1543.0  1024.5  \n",
       "CD1_1 CD1_2  : -0.00016587864604585486  -0.0001488163963875111  \n",
       "CD2_1 CD2_2  : -0.00022838515568534252  0.00026324797457884919  \n",
       "NAXIS : 0  0"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wcs = astrom.create_wcs_from_fit(x, y, r.data, d.data, idp, idx, xref=1543.0, yref=1024.5)\n",
    "wcs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WCS Keywords\n",
       "\n",
       "Number of WCS axes: 2\n",
       "CTYPE : 'RA---TAN-SIP'  'DEC--TAN-SIP'  \n",
       "CRVAL : 135.56330139299999  49.76324262  \n",
       "CRPIX : 1543.0  1024.5  \n",
       "CD1_1 CD1_2  : 0.00015466617567099999  8.0679635065000002e-06  \n",
       "CD2_1 CD2_2  : -8.1372895240600001e-06  0.000154600989856  \n",
       "NAXIS : 3073  2048"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccd.wcs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([ 444.82033693]), array([ 557.0450302])]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wcs.all_world2pix([135.586500], [49.819250], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([ 1619.74502698]), array([ 1390.01159188])]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ccd.wcs.all_world2pix([135.586500], [49.819250], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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