check_ptsr-mask.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np, healpy as hp, pickle, curvedsky as cs, sys, local, tools_cmb, binning, plottools as pl, warnings\n",
    "from matplotlib.pyplot import *\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sys.path.append(\"/global/homes/t/toshiyan/Work/Lib/actlib/actsims/\")\n",
    "sys.path.append(\"/global/homes/t/toshiyan/Work/Lib/actlib/soapack/\")\n",
    "sys.path.append(\"/global/homes/t/toshiyan/Work/Lib/actlib/\")\n",
    "sys.path.append(\"/global/homes/t/toshiyan/Work/Lib/actlib/orphics/\")\n",
    "sys.path.append(\"/global/homes/t/toshiyan/Work/Lib/actlib/tilec/\")\n",
    "from pixell import enmap\n",
    "from soapack import interfaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "aobj0 = local.init_analysis_params(ptsr='base')\n",
    "aobj1 = local.init_analysis_params(ptsr='PT')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0FBDcnnQSOgAZVZbvFK3imZ9MoPidCQBsOdAw6TtLvtUVITbsx1e5vdnpl6ayA5FvfGzxRqVby4NfHEpOeVmLNjccJu/jTXzW4OPgzBQU1wUpWIhIp3Bh3lpWnTeHRW8mRiSajCD4i4s48soP+E3vD7n19E/gdO9et++grYSH9SK4ek2LNuPzkZdR692LyTcSsS5VdUFyWmm3fh95Tj2Q3Z5ldVm6KkREOoWA8XFFwbssvzSPyNFj8XXPw9c9j8ixB7Hm/EH8otd7bTLUfWrfhWwZG2jZ4Pgww/fjR8Xvev6a8vXkOhkML9iM8SU53eX4qBncgz7+1ke7xFtaIEs6vKer87jug6nYqMPkkcv5XsFcTsiuT3VZkiL1NsLqSISVkQIAivyVjA7YNj1/vjZazQn3/ZzC+RGyVm/H7ZbFigtCXDn5dU0K7CAq3VoOvftnlNzyYeNolgkGWXfNQYw7dQmPDXwntQWmodYWyFKw6MRiNn7eOJ0X6tn1C33gPzcBsOWw3mydGGPxqXdpIpa0q6er83j0y0NZvLovmbn1/OaAFzkle4v+HnYgt1cM5MmbTyB/8U5MTT21g3rQ99crubnkZfr7WztRIt+UgkUaub1iIHfMO5riV+K/0DYfaPj32bem3T+cm7cO4+npx1B4x+zmDY6PFfeP44mj7/vGM/1FJD3V2wjbY/VEgB6OnxxHMzbbim5ClibWRqt54LGTGHZrDTnPfETOMx+x32MVXLfuVNam2c2WXv1yFN0/TzLj3o1R8H6Ax7Z9u5UURST9BE2AYn8O/f05ChUpomDRiSxtqGHyO1dS8vvZuIuWxc8jujHcRcuouLiQyS/+LNUlemrDmgJCy1oudgSQuyHCyp292rkiERH5KgoWncjH9f3IWpY8gTuV1eSuSq/TAiY7Siw/lLTN9Rt8ju5WKSLS0ShYdCJhN4ivLnmbbWigrmd6TYn59cSXWXNaHk6oebhwQiEqL67izkFPp6gyERFpjYJFJzI8+CW1hcnDg8nIwE1yqX1ndlbOei75j1epP2Q4OD5wfPiGDmbbf4zh8qHvMDiQXpNVRUTSga4K6WRm1AT4wyXnEZyzDDccv22zr3seS38/jPumPMRx2em3vPDaaDV/3HQMABNzVzE5e03aXQEjItLZ6HLTNPJBXYxHtx3Ga5+NBuDEMYu4s8/stF7PQkREOhYFizQTsy5rozUA9PEHCZo0Ow8iIiIdWmvBQjch66R8xqFUcwxERKSD0di5iIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIhIm6u3Eept+q2zIy3pqhAREWkzZ5cdxbx3h1PyZgMAa07zk9N/J59MeFxr76QpBQsREWkTm2NhFrw8gsEvbcddshLcGCOWl7D1qH4sG1vPqIysVJfI4oZaljUU0i+wjYlBrQfkBS2QJSIibWL/D8+mz9Tl4MZatK24ZyLPnXgnY4PBFFQG79Q6XLnwe/S9wWLWb8Tk5rL6h/0Zd9xS/lH6dkpq6mxaWyBL41AiItImYvO7Jw0VAFlf+nmmcnz7FtTEBW/8iIK7snEXLSO2o5LouvUMun81i/85gmq3ldtIyz5RsBARkXbnr4X9Mjel5LU/ra9nxF+2E3hzfrP90Y3l9HlgATdsOpyYdVNSWzpQsBARkTZR2ycKJuloOVWDo4wNrmvniuKynSjEko+k2IYIARPTxNJvQX9yIiLSJh474W/s+M+D8RcXNe7zFxex47xDeObEu9p0fsX9lX04ZMFURt9xGSPvvozjl57CO7Xxt7zuDkSKuycNPU5WJqOyN2jE4lvQVSEiItImDst0GHzxMj4pHUHx+33JqKhj/eF52KMqGJvRdm8/m2Nh/vroGZS8XU3eJ/Mxfj/1Hw7nh2f+mKVn3EVPJ4uKoZn0+jgbNxxu9lw7sA99/HM0YvEt6KoQEekyXgxn89bOkbyxZhgl3Sv5+5AnKfHrLsHtYWss/gZe4Au16eusilRz3LtXsN95n7WYOOqEQtQ9X8DzI57ksZ1D+fPbJzHiDxuIbd6CL787ay4YzAGn6KqQfdXaVSEKFiKS9hY31DLt0x/S74oqYpu3YOvrwfGx49yJ1H53B59NfCLVJYpHri0fx4z/PYSiv8xO2v7lfx3Kz370DOd32wzArDqYEx7CiMwNnJhdRcD42rPcTq21YKFTISKS9n634SQyn+9OdN3S3TvdGAVvlFGeWUr9hAhBo8WR0sHwrI3M2Et7fQ/LoIzNjdtHZMIRmSsTWwoVXtBJJBEPxazLqkg1qyLVmvzVgSx8bgS93l7fYn90YzmFL6zihXBBCqqStnBqzirskRXgtAwJTijE+COXMSmoe5a0JQULEY+8X+dy2YbDOPb1qzn29au5ZdsI1karU12WAE4M3K3bk7bZ6jBVsdQvLS3eyHcyOWXAYpyRQ3BCu+dzOKEQ9YcMZ2qv+RqdamM6FSLigX/X+vjdxRcSnLOMoeGPAHi/uJQXphzNk7+9ldKAJgim0s6hUfqWFMPyz5s3OD7s8IH0C8xNTWHiuYDxcXPhZ9z5VCUPfn4I1cvyyag0dPvOJn4/9CEmZ2kksa1p8qaIB8bMnUbJeRuI7dzZbL8TCpE/I4OHBs7Qp6QUun7TGF555HCKbm8+oc9fXET5qaXMvvEO/XzS0NZYmLdq+5BpIhyZtY08RyNTXtLkTZE2ZGbmE9u5tMV+Nxzm09cO4OXz5jM1Z2eSZ0p7uLnwM3589WyOL7yWggWWrC0Rotk++l63krtKbiVoNKKUjgp8Ic7KqUxsKVS0FwULkTYWDVl6+RUqUq00kMON332al444gC21ORRnVTN9wOtkOwoVIl5SsBDxQHh8bXx54D1OLZpABv0mbKCvrxrQG1iqnZO7jXNy32qyJyNltYikK10VIuKBE4YuwV9U2PwSN8eHGTaIk4sWMdCfnbriRETakSZvinjk7LKjmLNiED1nxz8Fbzu0gSsmvM01PVanuDIREe9pSW+RNlZvIyyPxHh55wEATMubT39/tm5mJCJpScFCREREPNNasNBHKREREfGMgoWIiIh4Ji2DRcy6lEWqebIqnzLdDEpERKTdpN0ci7JINaf87eeU/LsK34q1xIb2Z/0xubx8yR91vwYRERGPdInJm49X9eTGF89i8LVzWrStuvUQ7vvu/RyTFUtBZSLita2xMO/VFfLStrEAnNrzUyYFyyn2t/4BYkUkDECJL0C2o8Wx2kqN24DPGIImQMTGiNgYAeMjYFreylw6ry5xr5AH1x1G35nJg0P35fCvyjEck/VJO1clIl6LWZej5v0Yd253iubWA3DTqDFUjm1g4XF3keNkNutf7dbxZm0B1y84l9ptWRT2q+D8gXO4pPuGVJSftubWR3hq+yReKxtJMBDlxpEv89c1x7CpMpdjBy7n3J6zmRjUzd7SXVqNWBwwdxpFN/th7sIWbfUnTqD7dWt5fsjrKahMRLzyfp3LuW9fxPArl+KGw80bHR/rrp/EgkvvbPx0XG8jHHjXVfR/aTvuomWN/ZyRQyiavoE7S95oEUTk64lZl8erevPw5acTnLOs8efijB7e+GfuhEKwX38GT1/NH4vf1YhRGugSl5tm+GO4weSDMA3dfOQHa9q5IhHx2r3lR1PwXqBlqABwYwx4cTuLG6KNu16ryWfAs5t3h4pEP3fJSt75dAQf1ofaoer0trAhwn1rjmgWKgDcJSt3Pw6HcRcs5c3XDuS5cHHj/oiNURapZlbd7lNV0rmlVbB4ePQjlF1q8RcXNdvvLy6i28XruK2vRitEOruPXxtJr1dXtdruLlzOTWtPo95GqIjVcOPiU4kt/zxJxxj7PR7huqVT27DaruGmtacR/Udhy7Dntjw1PejxLdzw/plAfPTpkJsu57LTfswthx7PT4/9TwY9dzHVbl17lC1tJK2CxaiMLKZPepStU0rxDRmECQbxDRnE1imlXDfgNfJ9uhGUSGfnD4Ot3ssnW2spq+hBjRv5ymM59VEaoppQ2K5iMYgZNsfC3L3xGApfLsNduIJo+SZiK1cz7N5Krlg/ReGiE0uryZsAk7NcZtx8G5/Uh3gvPJTDQx8xLhgmz8lKdWki4oG63haTE4Jkp0IAHB9Dem4hxwkSMD4uGDKHGd36E9u5s0XX8sNyuWDIq21ccfqbXLCch3oO3qe+4eG9GFRazrTl04jeXkTmxrnN2t1Fy1g4/RB+c1k1txZpsn1nlFYjFrvkOVlMznK5oWAZk7NchQqRNOL2r8Xt17vVdn9hL87s/Unj5M3TcxZRd/DQ+OTBJpxQiJoJNUwJLW3TeruCs7sthiMrWvwZ4/habG840scVA95ia3WIzM21SY+XsyHKyqrWf8bSsaXdiIWIpLc3DruLqTkXUnxxEdGN5c3anFCIJf9Twjm5/2rcVxrI4Vf3PsSvlp+J80gBTtRSMdSHM3EHyyY+iM/og8e31dsX4uMJjzP2sXMJvppHwbydRHpkUvZdP6XPRglsr2P7Ad3YcnCMhaf8hRwnk5sDUdxgZtJPt5ps37kpWIhIp1IayOH/Dvg7p5z/c4rm9iU4Pz4xMza0P5WlIa6YNKPFcyZnRnh81MPcfPUJAPxnr9mMzqjCZ3RFiFd8xuGVg+7n1WHDeGrDeHpllXNHycv85oBT2FKbw8Cscq4v/LDx0t4jiz/n7WEH0/PdlsfaPN7w216z2/k7EK+k1ToWncmjOwv43w2HsOajEtxMyxVT/sVP89ekuiyRTiNmXTbHaphZ2w+ACZnrKPD5dOqzk4hZlwcq+/HU1SeS/dl6YtsrMH4/W84ewyO/uo1RGfo5dnRdYknvzqIsUs0xL/+MolmG7h9vxmYHWX5RNz47/a9aqEdEuoyYdZlWNoX584aQvzj+HjXoByt4ovQNfCYtpwCmFQWLDuLxqp789qmzGHDT3ObXeDs+VtxzEA9Nmc7kLN2NVUREOrYusfJmZ/BmxUh6LLYtF45xYxS/7fDIlsNSU5iIiIgHFCza2cflJeSWJb/+PrcszMflJe1ckYiIiHcULNpZQU6Yut7JJyXV9c5iSM8t7VyRdHYx67I1FqbSrSVmdRpNRFJLl5u2s+lD/sHUiy4k++1Qs3X1nVCIHT+q4uH+zwM5KatPOo+10Wp+u/F4Ppk+hp4LqonmZlA5KINbrrufyZkRTX5rA/U2gh+f/mxF9kKTN1MgZl0OW3AW2z/tRe/5Lq7fUHv2DuaN/4d+Yck+Gz79Ukqfrmh+104gctx4tl0WZsHEJ1JUWXqpduu4f8dIHr3/BPLKokSyHSqGOdz1g/sU4KRLa23ypkYsUsBnHJ4b/TAfDinipaPHMjS0iUvyP9MKgLLPtsbC8UnAZetatGUt30R4ZQlMTEFhaejZ6hLumjmFEf9cTWx7BVlAfq8Cfjrue1w4dLbWnxHZg6J2ihT7czgjVM3f+7/HL3qu1KI+8rVUupbcsnDL21QDsS830XNhCopKU3++7yyG/3Ip0Y3l2Pp6bH090fUb6H/Zdu5/8iTNaxHZg4KFSCfl216ddL/JCBDLgIiNJW2XfVfjNpC/LEKsqqpFW7R8E73nRai30RRUJtJxKViIdEKDAzms+X4x/uKiFm3bp46h4Oy1jXf3lG8uQoxAdevBIVAdJYICnEhTChYindSkUxay5vxBu29V7fjwFxWy+dAY1w14LbXFpYlsk0G4TxAnO7tFmy83l83js8gxwRRUJtJx6aoQkU6sxm3guvLDeHfDYApywhzZayW/7LlEVyp46PINk3j72YMoueXDxhVznVCIsl+M4ZKpr2nypnRZuleISJqK2BiVbh15TqZOf7SBXZebPvmn4+mxYCfGdanpn0vf61byx34vUeLXujPSNSlYiIh8CxEbY2usljoLhb4Msp2MVJckklJax0JE5FsIGB/FGp0Q+Uo6ESsiIiKeUbAQERERzyhYiIiIiGcULERERMQzChYiIiLiGQULERER8YyChYiIiHhGwUJEREQ8o2AhIiIinlGwEBEREc8oWIiIiIhnFCxERETEMwoWIiIi4hkFCxEREfGMsdamugYRERFJExqxEBEREc8oWIiIiIhnFCxERETEMwoWIiIi4hkFCxEREfGMgoWIiIh4RsFCREREPKNgISIiIp5RsBARERHPKFiIiIiIZxQsRERExDMKFiIiIuIZBQsRERHxjIKFiIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIiIiGcULERERMQzChYiIiLiGQULERER8YyChYiIiHhGwUJEREQ8o2AhIiIinlGwEBEREc8oWIiIiIhnFCxERETEM/5UFyAdX4Epsg00xDeMwexqMI3/a2yj1bZk24kHTXa33N7bc8Em679Hn2THtUn7JNlnTLxvq+17HHMfjruv/Zr138e+u/bZVvbv0+vt62sl3W+/dq3Nqk324zS7vjT/rkyzjrb1v1KJ5zX/62l3H9ok2dfYtue+PY9lW21rfrwm/Uwr+/fs3+Q4rfb5imO2fD4t+xnY9a+6Zb+m++Nb8z+rf91aewIirVCwkK/UQAOTnCkYx4BxGr/imHjQcJz4b9PGrwbTpL1ZW+P2rsd79GvSZo2Jj6k1adtzX9NtaxLvKMZgd/Uh8UaZaNvV3zZu73ou8ec6ux/v2dZi29lbv2RfTbPtvfVtto/W+3/V8aDl9l77G9vqsRvbmh3TNmnfvd20zezZj1379/wa72eMTfx4d7fH/4h3tzmNj5tvO+zeJvGcxrbG9sTjpv+xt31ui21f43a8zdf0sbE47Nq/a5+LQ+KrcRv77/66u3+zvsRfK97uJtptYn/ieYm+Ppruj3//jcdM1O5jV60k+oPPgA+TeGxwMIltk9h2Eo/jj3zFKwu+3m8Q6Wp0KkREREQ8o2AhIiIinlGwEBEREc8oWIiIiIhnFCxERETEMwoWIiIi4hkFCxEREfGMgoWIiIh4RsFCREREPGOsbbH4r0gzxphFQF2q6xCRDiHTWjs61UVIx6UlvWVf1Flrx6e6CBFJPWPMvFTXIB2bToWIiIiIZxQsRERExDMKFrIv7k91ASLSYej3geyVJm+KiIiIZzRiISIiIp5RsBARERHPKFjIXhljTjDGLDfGfG6MuS7V9YhIahhjHjTGbE6sayPSKgULaZUxxgfcDZwIjASmGWNGprYqEUmRh4ETUl2EdHwKFrI3E4HPrbWrrbUNwJPA6SmuSURSwFo7C9ie6jqk41OwkL3pC6xrsr0+sU9ERCQpBQsRERHxjIKF7M0GoF+T7ZLEPhERkaQULGRvPgKGGGNKjTEZwPeBF1Nck4iIdGAKFtIqa20UuBx4HVgKPG2tXZzaqkQkFYwxTwBzgGHGmPXGmAtTXZN0TFrSW0RERDyjEQsRERHxjIKFiIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIiIiGcULERERMQz/x/CYggWpEawfgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 612x388.8 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptsr0 = hp.fitsfunc.read_map(aobj0.fptsr)\n",
    "hp.cartview(ptsr0,lonra=[143,247],latra=[-5,22],min=0,max=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oWC8C6ze0aDM+H7nptd69mBySsHWpqguQ3Uq79fvIdeoBb64MkgPTVSEi0imkGR/X5r/D6qtzCZ80Bl/3XHzdcwmfchQbLh3MT3u92yZD3Wf3W8r2MWktGxwfZvhhfL/wHc9fU76aHCed4fnbML4Ep7scHzVDetDX3/pol3hLS3pLh/d0dS43vz8NG3GYPHI1385fyNSs+mSXJUlSb8OsD4dZG84HoMBfyeFptk3Pn2+MVDP1wZ/QZ3GYzPW7cLtlsuayINdNfk2TAjuISreWY+/7MUW//6BxNMsEAmy68SjGnr2CxwfNTW6BKai1Jb0VLDqxvYv0pPICUXt/oQ/6+1YAth/Xmx0Toiw/+15NxJJ29XR1Lo99cSzL1/cjI6eeXx35Amdlbdffww7kropBPHn7VPKW78HU1FM7uAf9frmW24teYoC/tRMlcqgULFLIXRWDuHvRSRS+HPuFtu0bhn9deEfK/cO5fccwnp55Mn3unt+8wfGx5qGxPHHSg4c8019EUlO9DbMrWk8Y6OH4yXY0Y7Ot6CZkKWJjpJqHHz+DYXfUkP3Mh2Q/8yGHPV7BzZvOZmOK3WzplS9G0f2zBDPu3Sj576Xx+M6vt5KiiKSegEmj0J/NAH+2QkWSKFh0Iisbapg89zqKfjsfd9mq2HlEN4q7bBUVV/Zh8gs/TnaJnirbkE9wVcvFjgByysKs3dOrnSsSEZEvo2DRiXxU35/MVYkTuFNZTc661DotYLIiRPOCCdtcv8Hn6EZQIiIdjYJFJxJyA/jqErfZhgbqeqbWlJhfTniJDefk4gSbhwsnGKTyyiruGfx0kioTEZHWKFh0IsMDX1DbJ3F4MOnpuAkute/MLsjezFX/9gr1xwwHxweOD9/QIez8t9FcM3QuQ9JSa7KqiEgq0FUhnczrNWn87qpLCCxYhRuK3bbZ1z2Xlb8dxoNT/sqpWam3vPDGSDV/2HoyABNy1jE5a0PKXQEjItLZ6HLTFPJ+XZTHdh7Hq58eDsDpo5dxT9/5Kb2ehYiIdCwKFikmal02RmoA6OsPEDApdh5EREQ6tNaChW5C1kn5jEOx5hiIiEgHo7FzERER8YyChYiIiHhGwUJEREQ8o2AhIiIinlGwEBGRNldvw9Tb1FtnR1rSVSEiItJmLiw9kUXvDKdoTgMAG87xkz1gDx+Pn621d1KUgoWIiLSJbdEQS14awZAXd+GuWAtulBGri9hxYn9WjalnVHpmsktkeUMtqxr60D9tJxMCWg/IC1ogS0RE2sQRH1xI32mrwY22aFtz/wSeO/0exgQCSagM5tY6XLf02/T7hcVs3oLJyWH99wYw9tSV/K34raTU1Nm0tkCWxqFERKRNRBd3TxgqADK/8PNM5bj2LaiJy974Pvn3ZuEuW0V0dyWRTZsZ/NB6lv99BNVuK7eRloOiYCEiIu3OXwuHZWxNymt/Ul/PiD/tIm3O4mb7I1vK6fvwEn6x9Xii1k1KbalAwUJERNpEbd8ImISj5VQNiTAmsKmdK4rJciIQTTySYhvCpJmoJpZ+DfqTExGRNvH41D+z+9+Pxl9Y0LjPX1jA7kuO4ZnT723T+RUPVfblmCXTOPzuGYy8bwanrTyLubWxt7zuDoQLuycMPU5mBqOyyjRi8TXoqhAREWkTx2U4DLlyFR8Xj6DwvX6kV9Sx+fhc7IkVjElvu7efbdEQ//3YeRS9VU3ux4sxfj/1Hwzne+f/gJXn3UtPJ5OKoRn0+igLNxRq9lw7qC99/Qs0YvE16KoQEekyXghl8eaekbyxYRhF3Sv5S8mTFPl1l+D2sCMaewPP9wXb9HXWhas59Z1rOeyST1tMHHWCQeqez+f5EU/y+J6h/PGtMxjxuzKi27bjy+vOhsuGcORZuirkYLV2VYiChYikvOUNtUz/5Hv0v7aK6Lbt2Pp6cHzsvngCtd/azacTnkh2ieKRm8rH8vr/HEPBn+YnbP/iP47lx99/hku7bQPg7TpYECphREYZp2dVkWZ87Vlup9ZasNCpEBFJeb8pO4OM57sT2bRy3043Sv4bpZRnFFM/PkzAaHGkVDA8cwuvH6C9vodlcPq2xu1JGTApY218S6HCCzqJJOKhqHVZF65mXbhak786kKXPjaDXW5tb7I9sKafPP9bxj1B+EqqStnB29jrsCRXgtAwJTjDIuBNWMTGge5a0JQULEY+8V+cyo+w4TnntBk557QZ+v3MEGyPVyS5LACcK7o5dCdtsdYiqaPKXlhZv5DkZnDVwOc7IEpzgvvkcTjBI/THDmdZrsUan2phOhYh44F+1Pn5z5eUEFqxiaOhDAN4rLOYfU07iyV/fQXGaJggm056hEfoVFcLqz5o3OD7s8EH0T1uYnMLEc2nGx+19PuWepyqZ9dkxVK/KI73S0O2bW/nt0L8yOVMjiW1NkzdFPDB64XSKLikjumdPs/1OMEje6+n8ddDr+pSURLdsHc3Ljx5PwV3NJ/T5CwsoP7uY+bferZ9PCtoRDfFmbV8yTJgTMneS62hkykuavCnShsy8PKJ7VrbY74ZCfPLqkbx0yWKmZe9J8ExpD7f3+ZQf3DCf0/rcRP4SS+b2MJEsH/1uXsu9RXcQMBpRSkX5viAXZFfGtxQq2ouChUgbiwQtvfwKFclWnJbNrd96mhcnHcn22mwKM6uZOfA1shyFChEvKViIeCA0rja2PPB+pxZNWjr9x5fRz1cN6A0s2S7K2clFOW822ZOetFpEUpWuChHxwNShK/AX9Gl+iZvjwwwbzJkFyxjkz0pecSIi7UiTN0U8cmHpiSxYM5ie82Ofgnce28C149/ixh7rk1yZiIj3tKS3SBurt2FWh6O8tOdIAKbnLmaAP0s3MxKRlKRgISIiIp5pLVjoo5SIiIh4RsFCREREPJOSwSJqXUrD1TxZlUepbgYlIiLSblJujkVpuJqz/vwTiv5VhW/NRqJDB7D55BxeuuoPul+DiIiIR7rE5M3ZVT259YULGHLTghZt6+44hge/9RAnZ0aTUJmIeG1HNMS7dX14cecYAM7u+QkTA+UU+lv/ALEmHAKgyJdGlqPFsdpKjduAzxgCJo2wjRK2UdKMjzTT8lbm0nl1iXuFzNp0HP3mJQ4O3VfDPytHc3Lmx+1clYh4LWpdTlz0A9yF3SlYWA/AbaNGUzmmgaWn3ku2k9Gsf7Vbx5zafG5ZcjG1OzPp07+CSwct4KruZckoP2UtrA/z1K6JvFo6kkBahFtHvsR/bziZrZU5nDJoNRf3nM+EgG72lupSasTiyIXTKbjdDwuXtmirP3083W/eyPMlryWhMhHxynt1Lhe/dQXDr1uJGwo1b3R8bLplIkuuvqfx03G9DfONe69nwIu7cJetauznjCyhYGYZ9xS90SKIyFcTtS6zq3rzyDXnEliwqvHn4hw+vPHP3AkG4bABDJm5nj8UvqMRoxTQJS43TfdHcQOJB2EauvnIC9S0c0Ui4rUHyk8i/920lqECwI0y8IVdLG+INO56tSaPgc9u2xcq4v3cFWuZ+8kIPqgPtkPVqW1pQ5gHN0xqFioA3BVr9z0OhXCXrGTOq9/guVBh4/6wjVIarubtun2nqqRzS6lg8cjhj1J6tcVfWNBsv7+wgG5XbuLOfhqtEOnsPnp1JL1eWddqu7t0NbdtPId6G6YiWsOty88muvqzBB2jHDY7zM0rp7VhtV3DbRvPIfK3Pi3Dntvy1PTg2dv5xXvnA7HRp2Nuu4YZ5/yA3x97Gj865d8Z/NyVVLt17VG2tJGUChaj0jOZOfExdkwpxlcyGBMI4CsZzI4pxdw88FXyfLoRlEhn5w+BrT7AJ1trKa3oQY0b/tJjOfURGiKaUNiuolGIGrZFQ9y35WT6vFSKu3QNkfKtRNeuZ9gDlVy7eYrCRSeWUpM3ASZnurx++518XB/k3dBQjg9+yNhAiFwnM9mliYgH6npbTHYQEp0KAXB8lPTcTrYTIM34uKxkAa93G0B0z54WXcuPy+GyklfauOLUNzl/NX/tOeSg+oaG92JwcTnTV08nclcBGVsWNmt3l61i6cxj+NWMau4o0GT7ziilRiz2ynUymZzp8ov8VUzOdBUqRFKIO6AWt3/vVtv9fXpxfu+PGydvnpu9jLqjh8YmDzbhBIPUjK9hSnBlm9bbFVzYbTmcUNHizxjH12K77AQf1w58kx3VQTK21SY8XnZZhLVVrf+MpWNLuRELEUltbxx3L9OyL6fwygIiW8qbtTnBICv+fxEX5fyzcV9xWjY/f+Cv/Hz1+TiP5uNELBVDfTgTdrNqwix8Rh88vq7eviAfjZ/NmMcvJvBKLvmL9hDukUHpt/wUPxshbVcdu47sxvajoyw9609kOxncnhbBDWQk/HSryfadm4KFiHQqxWnZ/O+Rf+GsS39CwcJ+BBbHJmZGhw6gsjjItRNfb/GcyRlhZo96hNtvmArAv/eaz+HpVfiMrgjxis84vHzUQ7wybBhPlY2jV2Y5dxe9xK+OPIvttdkMyiznlj4fNF7ae0LhZ7w17Gh6vtPyWNvGGX7da347fwfilZRax6IzeWxPPv9TdgwbPizCzbBcO+Wf/ChvQ7LLEuk0otZlW7SGebX9ARifsYl8n0+nPjuJqHV5uLI/T91wOlmfbia6qwLj97P9wtE8+vM7GZWun2NH1yWW9O4sSsPVnPzSjyl429D9o23YrACrr+jGp+f+txbqEZEuI2pdppdOYfGiEvKWx96jBn93DU8Uv4HPpOQUwJSiYNFBzK7qya+fuoCBty1sfo2342PN/Ufx1ykzmZypu7GKiEjH1iVW3uwM5lSMpMdy23LhGDdK4VsOj24/LjmFiYiIeEDBop19VF5ETmni6+9zSkN8VF7UzhWJiIh4R8GineVnh6jrnXhSUl3vTEp6bm/niqSzi1qXHdEQlW4tUavTaCKSXLrctJ3NLPkb0664nKy3gs3W1XeCQXZ/v4pHBjwPZCetPuk8Nkaq+fWW0/h45mh6LqkmkpNO5eB0fn/zQ0zOCGvyWxuot2H8+PRnK3IAmryZBFHrctySC9j1SS96L3Zx/YbaC3ezaNzf9AtLDtrwmVdT/HRF87t2AuFTx7FzRoglE55IUmWppdqt46HdI3nsoanklkYIZzlUDHO497sPKsBJl9ba5E2NWCSBzzg8d/gjfFBSwIsnjWFocCtX5X2qFQDloO2IhmKTgEs3tWjLXL2V0NoimJCEwlLQs9VF3DtvCiP+vp7orgoygbxe+fxo7Le5fOh8rT8jsh9F7SQp9GdzXrCavwx4l5/2XKtFfeQrqXQtOaWhlrepBqJfbKXn0iQUlaL++OAFDP/ZSiJbyrH19dj6eiKbyxgwYxcPPXmG5rWI7EfBQqST8u2qTrjfpKcRTYewjSZsl4NX4zaQtypMtKqqRVukfCu9F4Wpt5EkVCbScSlYiHRCQ9Ky2fCdQvyFBS3adk0bTf6FGxvv7imHLkyUtOrWg0NadYQwCnAiTSlYiHRSE89ayoZLB++7VbXjw1/Qh23HRrl54KvJLS5FZJl0Qn0DOFlZLdp8OTlsG5dJtgkkoTKRjktXhYh0YjVuAzeXH8c7ZUPIzw5xQq+1/KznCl2p4KFryiby1rNHUfT7DxpXzHWCQUp/Opqrpr2qyZvSZeleISIpKmyjVLp15DoZOv3RBvZebvrkf51GjyV7MK5LzYAc+t28lj/0f5Eiv9adka5JwUJE5GsI2yg7orXUWejjSyfLSU92SSJJpXUsRES+hjTjo1CjEyJfSidiRURExDMKFiIiIuIZBQsRERHxjIKFiIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIiIiGcULERERMQzChYiIiLiGQULERER8YyChYiIiHhGwUJEREQ8o2AhIiIinjHW2mTXICIiIilCIxYiIiLiGQULERER8YyChYiIiHhGwUJEREQ8o2AhIiIinlGwEBEREc8oWIiIiIhnFCxERETEMwoWIiIi4hkFCxEREfGMgoWIiIh4RsFCREREPKNgISIiIp5RsBARERHPKFiIiIiIZxQsRERExDMKFiIiIuIZBQsRERHxjIKFiIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIiIiGcULERERMQzChYiIiLiGQULERER8YyChYiIiHjGn+wCpOPLNwW2gYbYhjGYvQ2m8X+NbbTalmg7/qDJ7pbbB3ou2ET99+uT6Lg2YZ8E+4yJ9W21fb9jHsRxD7Zfs/4H2XfvPtvK/oN6vYN9rYT77VeutVm1iX6cZu+X5t+VadbRtv5XKv685n897b5DmwT7Gtv237f/sWyrbc2P16SfaWX//v2bHKfVPl9yzJbPp2U/A3v/Vbfs13R/bGvxp/WvWWunItIKBQv5Ug00MNGZgnEMGKfxK46JBQ3Hif02bfxqME3am7U1bu99vF+/Jm3WmNiYWpO2/fc13bYm/o5iDHZvH+JvlPG2vf1t4/be5xJ7rrPv8f5tLbadA/VL9NU02z5Q32b7aL3/lx0PWm4fsL+xrR67sa3ZMW2T9n3bTdvM/v3Yu3//r7F+xtj4j3dfe+yPeF+b0/i4+bbDvm3iz2lsa2yPP276Hwfa57bY9jVux9p8TR8bi8Pe/Xv3uTjEvxq3sf++r/v6N+tL7LVi7W683cb3x58X7+uj6f7Y9994zHjtPvbWSrw/+Az4MPHHBgcT3zbxbSf+OPbIV7g2/6v9BpGuRqdCRERExDMKFiIiIuIZBQsRERHxjIKFiIiIeEbBQkRERDyjYCEiIiKeUbAQERERzyhYiIiIiGcULERERMQzxtoWi/+KNGOMWQbUJbsOEekQMqy1hye7COm4tKS3HIw6a+24ZBchIslnjFmU7BqkY9OpEBEREfGMgoWIiIh4RsFCDsZDyS5ARDoM/T6QA9LkTREREfGMRixERETEMwoWIiIi4hkFCzkgY8xUY8xqY8xnxpibk12PiCSHMWaWMWZbfF0bkVYpWEirjDE+4D7gdGAkMN0YMzK5VYlIkjwCTE12EdLxKVjIgUwAPrPWrrfWNgBPAucmuSYRSQJr7dvArmTXIR2fgoUcSD9gU5PtzfF9IiIiCSlYiIiIiGcULORAyoD+TbaL4vtEREQSUrCQA/kQKDHGFBtj0oHvAC8kuSYREenAFCykVdbaCHAN8BqwEnjaWrs8uVWJSDIYY54AFgDDjDGbjTGXJ7sm6Zi0pLeIiIh4RiMWIiIi4hkFCxEREfGMgoWIiIh4RsFCREREPKNgISIiIp5RsBARERHPKFiIiIiIZ/4P0B/PC2z2JcAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 612x388.8 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptsr1 = hp.fitsfunc.read_map(aobj1.fptsr)\n",
    "hp.cartview(ptsr1,lonra=[143,247],latra=[-5,22],min=0,max=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py4so",
   "language": "python",
   "name": "py4so"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}