horsehead_fits.ipynb

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      "name": "horsehead_fits.ipynb",
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      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Hyenni/analysis_Astronomy_Data/blob/master/horsehead_fits.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "U6ZlmUERbAkI",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# Lecture 1. Understanding Data"
      ]
    },
    {
      "metadata": {
        "id": "sWtOzLVMbF_X",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### SAMPLE 01. Download a sample FITS file"
      ]
    },
    {
      "metadata": {
        "id": "d7tt7rxLVKS1",
        "colab_type": "code",
        "outputId": "a0ada2b2-01f9-465d-94ec-67129b238a7e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "import urllib\n",
        "urllib.request.urlretrieve(\"http://data.astropy.org/tutorials/FITS-images/HorseHead.fits\", \"HorseHead.fits\")"
      ],
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('HorseHead.fits', <http.client.HTTPMessage at 0x7fed658404a8>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "metadata": {
        "id": "bwKRakY2bMjP",
        "colab_type": "text"
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      "cell_type": "markdown",
      "source": [
        "###SAMPLE 02. Load a header of a FITS file\n",
        "\n",
        "cf) FITS Format: Header Unit\n",
        "\n",
        "                1                2                3                 4  ~~~ 8\n",
        "1234567890123456789012345678901234567890 ~~~ 890\n",
        "-------------------------------------------------------------\n",
        "####Structure\n",
        "  \n",
        "* KEYNAME\n",
        "\n",
        "* = 9번째\n",
        "\n",
        "* value => =과 /사이 \n",
        "\n",
        "* /\n",
        "\n",
        "* comment string"
      ]
    },
    {
      "metadata": {
        "id": "f_1vJrNkWE77",
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        "outputId": "3f325621-7c22-4067-e80d-f1fc0e8c3c5f",
        "colab": {
          "base_uri": "https://localhost:8080/",
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      "cell_type": "code",
      "source": [
        "# Initialize variables.\n",
        "file_path = \"HorseHead.fits\"\n",
        "header = \"\"\n",
        "\n",
        "# Open a file.\n",
        "file = open(\"HorseHead.fits\", \"rb\")\n",
        "\n",
        "# Read a header from the file.\n",
        "end_found = False\n",
        "\n",
        "while(end_found == False):\n",
        "\tbuffer = file.read(2880)\n",
        "\n",
        "\tif(buffer == \"\"):\n",
        "\t\tbreak\n",
        "\n",
        "\tbuffer = buffer.decode(\"ascii\") #change text (handing)\n",
        "\theader = header + buffer\n",
        "\n",
        "\tfor i in range(80):\n",
        "\t\trecord = buffer[i*80:(i+1)*80]\n",
        "\t\tif(record.startswith('END')):  #if 'END' exist, header finish\n",
        "\t\t\tend_found = True\n",
        "\t\t\tbreak\n",
        "\n",
        "if (end_found == False):\n",
        "\tprint(\"The file is not correct FITS format.\")\n",
        "\n",
        "  \n",
        "# Close the file.\n",
        "#file.close()\n",
        "            \n",
        "print (header)"
      ],
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "SIMPLE  =                    T /FITS: Compliance                                BITPIX  =                   16 /FITS: I*2 Data                                  NAXIS   =                    2 /FITS: 2-D Image Data                            NAXIS1  =                  891 /FITS: X Dimension                               NAXIS2  =                  893 /FITS: Y Dimension                               EXTEND  =                    T /FITS: File can contain extensions               DATE    = '2014-01-09        '  /FITS: Creation Date                            ORIGIN  = 'STScI/MAST'         /GSSS: STScI Digitized Sky Survey                SURVEY  = 'SERC-ER '           /GSSS: Sky Survey                                REGION  = 'ER768   '           /GSSS: Region Name                               PLATEID = 'A0JP    '           /GSSS: Plate ID                                  SCANNUM = '01      '           /GSSS: Scan Number                               DSCNDNUM= '00      '           /GSSS: Descendant Number                         TELESCID=                    4 /GSSS: Telescope ID                              BANDPASS=                   36 /GSSS: Bandpass Code                             COPYRGHT= 'AAO/ROE '           /GSSS: Copyright Holder                          SITELAT =              -31.277 /Observatory: Latitude                           SITELONG=              210.934 /Observatory: Longitude                          TELESCOP= 'UK Schmidt - Doubl' /Observatory: Telescope                          INSTRUME= 'Photographic Plate' /Detector: Photographic Plate                    EMULSION= 'IIIaF   '           /Detector: Emulsion                              FILTER  = 'OG590   '           /Detector: Filter                                PLTSCALE=                67.20 /Detector: Plate Scale arcsec per mm             PLTSIZEX=              355.000 /Detector: Plate X Dimension mm                  PLTSIZEY=              355.000 /Detector: Plate Y Dimension mm                  PLATERA =        85.5994550000 /Observation: Field centre RA degrees            PLATEDEC=       -4.94660910000 /Observation: Field centre Dec degrees           PLTLABEL= 'OR14052 '           /Observation: Plate Label                        DATE-OBS= '1990-12-22T13:49:00' /Observation: Date/Time                         EXPOSURE=                 65.0 /Observation: Exposure Minutes                   PLTGRADE= 'AD2     '           /Observation: Plate Grade                        OBSHA   =             0.158333 /Observation: Hour Angle                         OBSZD   =              26.3715 /Observation: Zenith Distance                    AIRMASS =              1.11587 /Observation: Airmass                            REFBETA =        66.3196420000 /Observation: Refraction Coeff                   REFBETAP=     -0.0820000000000 /Observation: Refraction Coeff                   REFK1   =        6423.52290000 /Observation: Refraction Coeff                   REFK2   =       -102122.550000 /Observation: Refraction Coeff                   CNPIX1  =                12237 /Scan: X Corner                                  CNPIX2  =                19965 /Scan: Y Corner                                  XPIXELS =                23040 /Scan: X Dimension                               YPIXELS =                23040 /Scan: Y Dimension                               XPIXELSZ=              15.0295 /Scan: Pixel Size microns                        YPIXELSZ=              15.0000 /Scan: Pixel Size microns                        PPO1    =       -3069417.00000 /Scan: Orientation Coeff                         PPO2    =       0.000000000000 /Scan: Orientation Coeff                         PPO3    =        177500.000000 /Scan: Orientation Coeff                         PPO4    =       0.000000000000 /Scan: Orientation Coeff                         PPO5    =        3069417.00000 /Scan: Orientation Coeff                         PPO6    =        177500.000000 /Scan: Orientation Coeff                         PLTRAH  =                    5 /Astrometry: Plate Centre H                      PLTRAM  =                   42 /Astrometry: Plate Centre M                      PLTRAS  =                23.86 /Astrometry: Plate Centre S                      PLTDECSN= '-       '           /Astrometry: Plate Centre +/-                    PLTDECD =                    4 /Astrometry: Plate Centre D                      PLTDECM =                   56 /Astrometry: Plate Centre M                      PLTDECS =                 47.9 /Astrometry: Plate Centre S                      EQUINOX =               2000.0 /Astrometry: Equinox                             AMDX1   =        67.1550859799 /Astrometry: GSC1 Coeff                          AMDX2   =      0.0431478884485 /Astrometry: GSC1 Coeff                          AMDX3   =       -292.435619180 /Astrometry: GSC1 Coeff                          AMDX4   =  -2.68934864702E-005 /Astrometry: GSC1 Coeff                          AMDX5   =   1.99133423290E-005 /Astrometry: GSC1 Coeff                          AMDX6   =  -2.37011931379E-006 /Astrometry: GSC1 Coeff                          AMDX7   =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX8   =   2.21426387429E-006 /Astrometry: GSC1 Coeff                          AMDX9   =  -8.12841581455E-008 /Astrometry: GSC1 Coeff                          AMDX10  =   2.48169090021E-006 /Astrometry: GSC1 Coeff                          AMDX11  =   2.77618933926E-008 /Astrometry: GSC1 Coeff                          AMDX12  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX13  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX14  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX15  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX16  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX17  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX18  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX19  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDX20  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY1   =        67.1593591466 /Astrometry: GSC1 Coeff                          AMDY2   =     -0.0471363749174 /Astrometry: GSC1 Coeff                          AMDY3   =        316.004963520 /Astrometry: GSC1 Coeff                          AMDY4   =   2.86798151430E-005 /Astrometry: GSC1 Coeff                          AMDY5   =  -2.00968236347E-005 /Astrometry: GSC1 Coeff                          AMDY6   =   2.27840393227E-005 /Astrometry: GSC1 Coeff                          AMDY7   =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY8   =   2.23885090381E-006 /Astrometry: GSC1 Coeff                          AMDY9   =  -2.28360163464E-008 /Astrometry: GSC1 Coeff                          AMDY10  =   2.44828851495E-006 /Astrometry: GSC1 Coeff                          AMDY11  =  -5.76717487998E-008 /Astrometry: GSC1 Coeff                          AMDY12  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY13  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY14  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY15  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY16  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY17  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY18  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY19  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDY20  =       0.000000000000 /Astrometry: GSC1 Coeff                          AMDREX1 =        67.1532034737 /Astrometry: GSC2 Coeff                          AMDREX2 =      0.0434354199559 /Astrometry: GSC2 Coeff                          AMDREX3 =       -292.435438892 /Astrometry: GSC2 Coeff                          AMDREX4 =   4.60919247070E-006 /Astrometry: GSC2 Coeff                          AMDREX5 =  -3.21138058537E-006 /Astrometry: GSC2 Coeff                          AMDREX6 =   7.23651736725E-006 /Astrometry: GSC2 Coeff                          AMDREX7 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX8 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX9 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX10=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX11=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX12=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX13=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX14=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX15=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX16=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX17=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX18=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX19=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREX20=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY1 =        67.1522589487 /Astrometry: GSC2 Coeff                          AMDREY2 =     -0.0481758265285 /Astrometry: GSC2 Coeff                          AMDREY3 =        315.995683716 /Astrometry: GSC2 Coeff                          AMDREY4 =  -7.47397531230E-006 /Astrometry: GSC2 Coeff                          AMDREY5 =   9.55221105409E-007 /Astrometry: GSC2 Coeff                          AMDREY6 =   7.60954485251E-006 /Astrometry: GSC2 Coeff                          AMDREY7 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY8 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY9 =       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY10=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY11=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY12=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY13=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY14=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY15=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY16=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY17=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY18=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY19=       0.000000000000 /Astrometry: GSC2 Coeff                          AMDREY20=       0.000000000000 /Astrometry: GSC2 Coeff                          ASTRMASK= 'er.mask '           /Astrometry: GSC2 Mask                           WCSAXES =                    2 /GetImage: Number WCS axes                       WCSNAME = 'DSS               ' /GetImage: Local WCS approximation from full platRADESYS = 'ICRS              ' /GetImage: GSC-II calibration using ICRS system  CTYPE1  = 'RA---TAN          ' /GetImage: RA-Gnomic projection                  CRPIX1  =           446.000000 /GetImage: X reference pixel                     CRVAL1  =            85.274970 /GetImage: RA of reference pixel                 CUNIT1  = 'deg               ' /GetImage: degrees                               CTYPE2  = 'DEC--TAN          ' /GetImage: Dec-Gnomic projection                 CRPIX2  =           447.000000 /GetImage: Y reference pixel                     CRVAL2  =            -2.458265 /GetImage: Dec of reference pixel                CUNIT2  = 'deg               ' /Getimage: degrees                               CD1_1   =        -0.0002802651 /GetImage: rotation matrix coefficient           CD1_2   =         0.0000003159 /GetImage: rotation matrix coefficient           CD2_1   =         0.0000002767 /GetImage: rotation matrix coefficient           CD2_2   =         0.0002798187 /GetImage: rotation matrix coefficient           OBJECT  = 'data              ' /GetImage: Requested Object Name                 DATAMIN =                 3759 /GetImage: Minimum returned pixel value          DATAMAX =                22918 /GetImage: Maximum returned pixel value          OBJCTRA = '05 41 06.000      ' /GetImage: Requested Right Ascension (J2000)     OBJCTDEC= '-02 27 30.00      ' /GetImage: Requested Declination (J2000)         OBJCTX  =             12682.48 /GetImage: Requested X on plate (pixels)         OBJCTY  =             20411.37 /GetImage: Requested Y on plate (pixels)         END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "IPq1hFcUbUPv",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### SAMPLE 03. Decode a FITS header."
      ]
    },
    {
      "metadata": {
        "id": "Ay1fUctkblVO",
        "colab_type": "code",
        "outputId": "028a5c73-4007-4be6-a787-d6f81c750944",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        }
      },
      "cell_type": "code",
      "source": [
        "def get_value(header, keyword):\n",
        "\tvalue = \"\"\n",
        "\trecords = int(len(header) / 80)\n",
        "\n",
        "\tfor i in range(records):\n",
        "\t\trecord = header[i*80:(i+1)*80]\n",
        "\t\tif(record.startswith(keyword)):\n",
        "\t\t\tbegin = 9;\n",
        "\t\t\tend = record.find('/')\n",
        "\t\t\tvalue = record[begin:end].strip()\n",
        "\t\t\tbreak\n",
        "\t\tif(record.startswith(\"END\")):\n",
        "\t\t\tbreak\n",
        "\n",
        "\treturn value\n",
        "\n",
        "  \n",
        "# Decode the header.\n",
        "bitpix = 0\n",
        "naxis = 0\n",
        "naxis1 = 0\n",
        "naxis2 = 0\n",
        "bscale = 1.0\n",
        "bzero = 0\n",
        "\n",
        "value = get_value(header, \"BITPIX\")\n",
        "if(value != \"\"):\tbitpix = int(value)\n",
        "\n",
        "value = get_value(header, \"NAXIS\")\n",
        "if(value != \"\"):\tnaxis = int(value)\n",
        "\n",
        "value = get_value(header, \"NAXIS1\")\n",
        "if(value != \"\"):\tnaxis1 = int(value)\n",
        "\n",
        "value = get_value(header, \"NAXIS2\")\n",
        "if(value != \"\"):\tnaxis2 = int(value)\n",
        "\n",
        "value = get_value(header, \"BSCALE\")\n",
        "if(value != \"\"):\tbscale = float(value)\n",
        "  \n",
        "value = get_value(header, \"BZERO\")\n",
        "if(value != \"\"):\tbzero = int(value)\n",
        "  \n",
        "print(\"BITPIX = \", bitpix)\n",
        "print(\"NAXIS = \", naxis)\n",
        "print(\"NAXIS1 = \", naxis1)\n",
        "print(\"NAXIS2 = \", naxis2)\n",
        "print(\"BSCALE = \", bscale)\n",
        "print(\"BZERO = \", bzero)"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "BITPIX =  16\n",
            "NAXIS =  2\n",
            "NAXIS1 =  891\n",
            "NAXIS2 =  893\n",
            "BSCALE =  1.0\n",
            "BZERO =  0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "l8l3vJgXihot",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### SAMPLE 04. Load a FITS data."
      ]
    },
    {
      "metadata": {
        "id": "uz4hVr7DihyV",
        "colab_type": "code",
        "outputId": "633b9e03-9ff0-4a5b-931f-6c95fdf510df",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        }
      },
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "# Read a data from the file.\n",
        "\n",
        "# binary data (byte)\n",
        "data = file.read(naxis1 * naxis2 * int(bitpix/8))\n",
        "print (data)"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "IOPub data rate exceeded.\n",
            "The notebook server will temporarily stop sending output\n",
            "to the client in order to avoid crashing it.\n",
            "To change this limit, set the config variable\n",
            "`--NotebookApp.iopub_data_rate_limit`.\n",
            "\n",
            "Current values:\n",
            "NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
            "NotebookApp.rate_limit_window=3.0 (secs)\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "id": "XIugwlHMupGl",
        "colab_type": "code",
        "outputId": "52042a82-bd7f-4b0f-b7e5-e0ec0deb0555",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "cell_type": "code",
      "source": [
        "# 1-D array (signed short)\n",
        "data = np.frombuffer(data, dtype=np.dtype(\">i2\"))\n",
        "print(data)\n",
        "print(data.dtype)"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[ 7201  6642  6642 ... 11987 12546 12546]\n",
            ">i2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "FVYOwDOCuqd8",
        "colab_type": "code",
        "outputId": "3f4e3ee0-c3c2-4aad-8466-cdda7c833334",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 158
        }
      },
      "cell_type": "code",
      "source": [
        "# 2-D array (signed short)\n",
        "#naxis2 = height\n",
        "#naxis1 = width\n",
        "\n",
        "data = data.reshape((naxis2, naxis1))\n",
        "print(data)\n",
        "print(data.dtype)"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 7201  6642  6642 ...  9498  9498 10057]\n",
            " [ 6642  6363  6642 ... 10057 10616 10616]\n",
            " [ 6922  6642  6922 ... 10337 11175 10616]\n",
            " ...\n",
            " [ 5412  5132  5412 ... 13000 12580 12021]\n",
            " [ 5796  5517  5796 ... 12546 12546 11987]\n",
            " [ 5796  5796  6076 ... 11987 12546 12546]]\n",
            ">i2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "uQXV3rBPusw0",
        "colab_type": "code",
        "outputId": "ef8d9e11-89c0-48ce-e0ef-e5bb19af8010",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 158
        }
      },
      "cell_type": "code",
      "source": [
        "#data = (data + bzero) / bscale\n",
        "#print(data)\n",
        "#print(data.dtype)"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 7201.  6642.  6642. ...  9498.  9498. 10057.]\n",
            " [ 6642.  6363.  6642. ... 10057. 10616. 10616.]\n",
            " [ 6922.  6642.  6922. ... 10337. 11175. 10616.]\n",
            " ...\n",
            " [ 5412.  5132.  5412. ... 13000. 12580. 12021.]\n",
            " [ 5796.  5517.  5796. ... 12546. 12546. 11987.]\n",
            " [ 5796.  5796.  6076. ... 11987. 12546. 12546.]]\n",
            "float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "KJEta7gG3Ig9",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "###SAMPLE 05. Display a FITS data."
      ]
    },
    {
      "metadata": {
        "id": "xpdZtmvyzAn-",
        "colab_type": "code",
        "outputId": "d35fcbcd-c4df-4279-adb7-0aa034568da1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.cm as cm\n",
        "\n",
        "plt.imshow(data, cmap=cm.gray)\n",
        "plt.grid(None)\n",
        "plt.show()"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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QTCaTMcPNZDLabDbq9/sKBoPGw3E/oEqehVSMAsdkMrHCXzqdNvqBgh/rBALa39/XW9/6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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fed657ad748>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}