From 7af5b8df62b8a3593ac81adb6b0b10c3cc933012 Mon Sep 17 00:00:00 2001 From: luthienliu Date: Wed, 6 Jul 2022 00:30:59 -0400 Subject: [PATCH 01/10] Change to FITS_tables tutorial --- tutorials/FITS-tables/FITS_tables.ipynb | 771 ++++++++++++++++++++++++ tutorials/FITS-tables/requirements.txt | 3 - 2 files changed, 771 insertions(+), 3 deletions(-) create mode 100644 tutorials/FITS-tables/FITS_tables.ipynb delete mode 100644 tutorials/FITS-tables/requirements.txt diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb new file mode 100644 index 00000000..2cf5ec90 --- /dev/null +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -0,0 +1,771 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Mb0-v-tzcpN6" + }, + "source": [ + "# Working with Chandra FITS tables\n", + "\n", + "## Authors\n", + "Lia Corrales, Kris Stern, LĂșthien Liu, Zihao Chen, Saima Siddiqui\n", + "\n", + "## Learning Goals\n", + "* Download a Chandra FITS table file from a URL \n", + "* Open a Chandra FITS table file and view table contents\n", + "* Make a 2D histogram with the event list data\n", + "* Close the FITS file after use\n", + "\n", + "## Keywords\n", + "FITS, file input/output, table, numpy, matplotlib, histogram\n", + "\n", + "\n", + "## Summary\n", + "\n", + "Chandra image data is stored in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n", + "\n", + "In this tutorial, we will use `astropy.utils.data` to download a Chandra FITS file, then use `astropy.io.fits` and `astropy.table` to open the file. Lastly, we will use `matplotlib` to visualize the Chandra event list as a histogram, effectively producing an X-ray image of the sky." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vfrMqJd9cpN9" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from astropy.io import fits\n", + "from astropy.table import Table\n", + "from matplotlib.colors import LogNorm\n", + "\n", + "# Set up matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IexsOCvKcpN-" + }, + "source": [ + "The following line is needed to download the example FITS files used in this tutorial." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0zp1lvcEcpN_" + }, + "outputs": [], + "source": [ + "from astropy.utils.data import download_file" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6u1ChU47cpN_" + }, + "source": [ + "FITS files often contain large amounts of multi-dimensional data and tables. \n", + "\n", + "In this particular example, we'll open a FITS file from a Chandra observation of the Galactic Center. The file contains a list of events with x and y coordinates, energy, and various other pieces of information." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "r6F-JgTCcpN_" + }, + "outputs": [], + "source": [ + "event_filename = download_file('http://data.astropy.org/tutorials/FITS-tables/chandra_events.fits', \n", + " cache=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "me6HB0RrcpOA" + }, + "source": [ + "## Opening the FITS file and viewing table contents" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Cp_kqCg4cpOA" + }, + "source": [ + "Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2ABOyWmxcpOB" + }, + "outputs": [], + "source": [ + "hdu_list = fits.open(event_filename, memmap=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "yEuBPS8ycpOB", + "outputId": "8bc4c565-e09c-4de0-d99b-1d05fcfb00a3" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Filename: /root/.astropy/cache/download/url/333246bccb141ea3b4e86c49e45bf8d6/contents\n", + "No. Name Ver Type Cards Dimensions Format\n", + " 0 PRIMARY 1 PrimaryHDU 30 () \n", + " 1 EVENTS 1 BinTableHDU 890 483964R x 19C [1D, 1I, 1I, 1J, 1I, 1I, 1I, 1I, 1E, 1E, 1E, 1E, 1J, 1J, 1E, 1J, 1I, 1I, 32X] \n", + " 2 GTI 3 BinTableHDU 28 1R x 2C [1D, 1D] \n", + " 3 GTI 2 BinTableHDU 28 1R x 2C [1D, 1D] \n", + " 4 GTI 1 BinTableHDU 28 1R x 2C [1D, 1D] \n", + " 5 GTI 0 BinTableHDU 28 1R x 2C [1D, 1D] \n", + " 6 GTI 6 BinTableHDU 28 1R x 2C [1D, 1D] \n" + ] + } + ], + "source": [ + "hdu_list.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FCoyC8sIcpOC" + }, + "source": [ + "In this case, we're interested in reading EVENTS, which contains information about each X-ray photon that hit the detector." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kTHnKQPicpOC" + }, + "source": [ + "To find out what information the table contains, let's print the column names." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "CfQyzNPNcpOC", + "outputId": "244569b7-9235-43e1-f471-d0789a538b0a" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "ColDefs(\n", + " name = 'time'; format = '1D'; unit = 's'\n", + " name = 'ccd_id'; format = '1I'\n", + " name = 'node_id'; format = '1I'\n", + " name = 'expno'; format = '1J'\n", + " name = 'chipx'; format = '1I'; unit = 'pixel'; coord_type = 'CPCX'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n", + " name = 'chipy'; format = '1I'; unit = 'pixel'; coord_type = 'CPCY'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n", + " name = 'tdetx'; format = '1I'; unit = 'pixel'\n", + " name = 'tdety'; format = '1I'; unit = 'pixel'\n", + " name = 'detx'; format = '1E'; unit = 'pixel'; coord_type = 'LONG-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n", + " name = 'dety'; format = '1E'; unit = 'pixel'; coord_type = 'NPOL-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n", + " name = 'x'; format = '1E'; unit = 'pixel'; coord_type = 'RA---TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 266.41519201128; coord_inc = -0.00013666666666667\n", + " name = 'y'; format = '1E'; unit = 'pixel'; coord_type = 'DEC--TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = -29.012248288366; coord_inc = 0.00013666666666667\n", + " name = 'pha'; format = '1J'; unit = 'adu'; null = 0\n", + " name = 'pha_ro'; format = '1J'; unit = 'adu'; null = 0\n", + " name = 'energy'; format = '1E'; unit = 'eV'\n", + " name = 'pi'; format = '1J'; unit = 'chan'; null = 0\n", + " name = 'fltgrade'; format = '1I'\n", + " name = 'grade'; format = '1I'\n", + " name = 'status'; format = '32X'\n", + ")\n" + ] + } + ], + "source": [ + "print(hdu_list[1].columns)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YpH2-4qPcpOC" + }, + "source": [ + "Now we'll take this data and convert it into an [astropy table](http://docs.astropy.org/en/stable/table/). While it's possible to access FITS tables directly from the ``.data`` attribute, using [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) tends to make a variety of common tasks more convenient." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n7zMyhRhcpOD" + }, + "outputs": [], + "source": [ + "evt_data = Table(hdu_list[1].data)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sEmGEMR1cpOD" + }, + "source": [ + "For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "c00cCz9McpOD", + "outputId": "86eda857-3fff-4960-f488-477ee510a85c" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "\n", + " time ccd_id node_id expno ... pi fltgrade grade status [32] \n", + " float64 int16 int16 int32 ... int32 int16 int16 bool \n", + "------------------ ------ ------- ----- ... ----- -------- ----- --------------\n", + " 238623220.9093583 3 3 68 ... 951 16 4 False .. 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" + ] + }, + "metadata": {}, + "execution_count": 9 + } + ], + "source": [ + "evt_data" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "86Qa6PUucpOD" + }, + "source": [ + "We can extract data from the table by referencing the column name. Let's try making a histogram for the energy of each photon, which will give us a sense for the spectrum (folded with the detector's efficiency)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "9YkZY2wqcpOE", + "outputId": "8422589a-217b-4b12-b9d0-d9f8520b0c0c" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'Number of photon events')" + ] + }, + "metadata": {}, + "execution_count": 10 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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I4ChgUURsTIljETCpL7GZmVnvFJmA8V/J7lK/OhV9WtI7I+LcksccB2wArpT0NmA58Glgv4hYl+o8DuyXlkcBj+W2X5PKqpVXOodpwDSAsWPHVqrSNDzBopm1kiJDfN8PHBkRsyNiNtm3/b60RnYCJgCXR8SBwDNkl662S5M9Rh+OsYOImBUR7RHRPmLEiFrt1sxs0Cv0PBFgGLAxLe/Vx2OuAdZExNL0/lqyJPKEpJERsS5drlqf1q8lm/Sx0+hUthZ4T5fyW/sYmw0g7pA3q78iSeRfgd9JuoVsmO+76NJy6I2IeFzSY5L2j4iVwBHA/ek1Bbgo/VyQNlkInJWGGR8MbE6J5mbgXyQNT/UmAjPKxmUDgy8HDl7Vfvf+AlFfRebOmivpVuBvU9E5EfF4H4/7KeDqNDJrNXAq2aW1+ZKmAo8CJ6a6N5IN7+0gG+J7aopro6QLgDtSvfMjYiNmZtYwhS5npQ7vhbU6aETcRTY0t6sjKtQNoOJTFFMfzexaxWXNz5eozJpL0T4Rs5bWmXyceAYff/GoL0/AaGZmpXXbEpE0BFgREW9sUDxmZr3iwRT9q9uWSERsA1ZKau479MzMrF8U6RMZDqxIz1h/prPQz1Y3M7MiSeRLdY/CzKwBPMCi9go9Y13Sa4HxEfFLSbsDQ+ofmplZZe4HaR49js6SdDrZ1CTfS0WjgOvrGZSZmbWGIkN8zwQOBbYARMQq4NX1DMrMzFpDkSTyQkS82PlG0k7UcIZdMzNrXUU61n8t6VxgN0lHAmcA/1nfsMx65uviZv2vSEtkOtlDpO4FPkE2IeIXu93CzMwGhSKjs/4iaQ6wlOwy1so0KaKZWUvyfFq1U+TxuO8Hvgs8RPY8kXGSPhERN9U7ODMza25F+kS+Abw3IjoAJL0euAFwEjGzhnEfWHMq0ifydGcCSVYDT9cpHjMzayFVWyKSPpgWl0m6EZhP1ifyYV56mqCZmQ1i3V3O+kBu+Qng3Wl5A7Bb3SIys4rcGWzNqGoSiYhTGxmImZm1niKjs8YBnwLa8vU9FbyZmRUZnXU9cAXZXep/qW84ZmaN5cuEfVNkdNbzEXFZRNwSEb/ufPX1wJKGSPqdpJ+l9+MkLZXUIekaSbuk8l3T+460vi23jxmpfKWko/oak5mZ9U6RJPJNSTMl/Z2kCZ2vGhz708ADufcXA5dGxBuATcDUVD4V2JTKL031kHQAcBLwJmAS8J30THgzM2uQIpez3gL8I3A4L13OivS+FEmjgfcDFwJnS1La30dTlTnAl4HLgclpGbLnmnwr1Z8MzIuIF4CHJXUABwG3lY2rv/gmKjNrVUWSyIeB1+Wng6+Bfwc+D+yZ3u8DPBURW9P7NWQPvyL9fAwgIrZK2pzqjwKW5PaZ38bMrNfcP9J7RZLIfcAwYH0tDijpWGB9RCyX9J5a7LPAMacB0wDGjh3biENak/IfidbiVnrzK5JEhgEPSroDeKGzsA9DfA8FjpN0DPBKYCjwTWCYpJ1Sa2Q0sDbVXwuMAdakB2LtBTyZK++U32YHETELmAXQ3t7uGYjNzGqkSBKZWcsDRsQMYAZAaol8LiI+JunHwAnAPGAKsCBtsjC9vy2t/1VEhKSFwI8kXQK8BhgP3F7LWM3MrHtFnifS5+G8BZ0DzJP0VeB3ZPemkH7+R+o430g2IouIWCFpPnA/sBU4MyK2NShWMzOj2B3rT/PSM9V3AXYGnomIoX09eETcCtyalleTja7qWud5ss79SttfSDbCy8zM+kGRlkjnCCpyQ2sPqWdQZtZcPCDBqilys+F2kbke8N3hZmZW6HLWB3NvXwG0A8/XLSIz65FbBtYsiozOyj9XZCvwCNklLTOzumiG+0M6Y3CS7l6RPhE/V8TMzCrq7vG453WzXUTEBXWIx6xhfEnIrO+6a4k8U6FsD7JZdfcBnETMzAa57h6P+43OZUl7kk3dfirZHeXfqLadFdMM13zNzPqq2z4RSXsDZwMfI5uefUJEbGpEYGb9zZe7zHrWXZ/I14APkk1c+JaI+FPDohoA/AfIBqp6jVpy67w1dXez4WfJJjb8IvA/krak19OStjQmPDMza2bd9Yn06m52q/5Nyq0Ss9bl/7/dK3KzoXXDTfCBx79Ts+Lc2jAzs9LcEinJ31bNzJxEzKwKf1GyIpxEGsz/Mc1e4v8Prc9JxAz/MTMry0nEzBrKCXtgcRIxa3L+o2vNzEN8zcysNLdEzKwU38lt0A8tEUljJN0i6X5JKyR9OpXvLWmRpFXp5/BULkmXSeqQdI+kCbl9TUn1V0ma0uhzMbPBpW36DdtflumPlshW4LMRcWd6TslySYuAU4DFEXGRpOnAdOAc4GhgfHodDFwOHJymqZ8JtAOR9rPQU9VbPfhbt1llDU8iEbEOWJeWn5b0ADAKmAy8J1WbA9xKlkQmA1dFRABLJA2TNDLVXRQRGwFSIpoEzG3YyZg1gVomOH/Dtt7q1z4RSW3AgcBSYL+UYAAeB/ZLy6OAx3KbrUll1corHWcaMA1g7NixtQneBi23SnrPyWng6rckIulVwE+Az0TEFknb10VESIpaHSsiZpE9XIv29vaa7desN38cB3LCcZIYvPoliUjamSyBXB0R16XiJySNjIh16XLV+lS+FhiT23x0KlvLS5e/OstvrWfcZs2ubFJzErCyGp5ElDU5rgAeiIhLcqsWAlOAi9LPBbnysyTNI+tY35wSzc3Av3SO4gImAjMacQ5mA4ETh9VCf7REDgX+EbhX0l2p7Fyy5DFf0lTgUeDEtO5G4BigA3gWOBUgIjZKugC4I9U7v7OT3azV+Q+8tYr+GJ31/wBVWX1EhfoBnFllX7OB2bWLzqx+3CFvA5HvWDfrR25xtC5/Kcg4iZj1AycPGyg8AaOZmZXmJGJmZqU5iZiZWWlOImZmVpqTiJmZlebRWb3gETVmZjtyS8TMzEpzS8TMrI8G842HbomYmVlpTiJmZlaak4iZmZXmJGJmVkNt028YVCM5nUTMzKw0JxEzMyvNScTMzErzfSJmZnUwWO4dcUvEzMxKc0vEzKzOBnKrxEnEzKyBBlpCafnLWZImSVopqUPS9P6Ox8xsMGnploikIcC3gSOBNcAdkhZGxP39G5mZWc8q3ZTYaq2Tlk4iwEFAR0SsBpA0D5gMOImYWUuqdrd7syaXVk8io4DHcu/XAAd3rSRpGjAtvf2TpJW9PM6+wB9LRdhYjrP2WiXWVokTWifWpopTF1dd1ag4X1upsNWTSCERMQuYVXZ7Scsior2GIdWF46y9Vom1VeKE1onVcRbT6h3ra4ExufejU5mZmTVAqyeRO4DxksZJ2gU4CVjYzzGZmQ0aLX05KyK2SjoLuBkYAsyOiBV1OFTpS2EN5jhrr1VibZU4oXVidZwFKCL68/hmZtbCWv1ylpmZ9SMnETMzK81JpBv9PaWKpDGSbpF0v6QVkj6dyr8saa2ku9LrmNw2M1K8KyUd1chzkfSIpHtTTMtS2d6SFklalX4OT+WSdFmK5x5JE3L7mZLqr5I0pcYx7p/73O6StEXSZ5rlM5U0W9J6Sfflymr2GUp6R/oddaRtVcM4vybpwRTLTyUNS+Vtkp7Lfbbf7Smeaudcozhr9rtWNqhnaSq/RtkAn1KqxHpNLs5HJN2VyvvtM32ZiPCrwouso/4h4HXALsDdwAENjmEkMCEt7wn8HjgA+DLwuQr1D0hx7gqMS/EPadS5AI8A+3Yp+zdgelqeDlyclo8BbgIEHAIsTeV7A6vTz+FpeXgdf8ePk91E1RSfKfAuYAJwXz0+Q+D2VFdp26NrGOdEYKe0fHEuzrZ8vS77qRhPtXOuUZw1+10D84GT0vJ3gX+q5e++y/pvAOf192fa9eWWSHXbp1SJiBeBzilVGiYi1kXEnWn5aeABsrv0q5kMzIuIFyLiYaCD7Dz681wmA3PS8hzg+Fz5VZFZAgyTNBI4ClgUERsjYhOwCJhUp9iOAB6KiEe7qdPQzzQifgNsrBBDnz/DtG5oRCyJ7C/JVbl99TnOiPhFRGxNb5eQ3bdVVQ/xVDvnPsfZjV79rtM3/MOBa/saZ0+xpmOdCMztbh+N+Ey7chKprtKUKt39Aa8rSW3AgcDSVHRWumwwO9csrRZzo84lgF9IWq5sqhmA/SJiXVp+HNivSWKF7L6i/H/KZvxMoXaf4ai03LW8Hk4j+xbcaZyk30n6taS/T2XdxVPtnGulFr/rfYCncomznp/n3wNPRMSqXFlTfKZOIi1A0quAnwCfiYgtwOXA64G3A+vImrnN4LCImAAcDZwp6V35lembUVOMKU/Xro8DfpyKmvUz3UEzfYbVSPoCsBW4OhWtA8ZGxIHA2cCPJA0tur86nHNL/K67+Ag7fuFpms/USaS6pphSRdLOZAnk6oi4DiAinoiIbRHxF+D7ZM1tqB5zQ84lItamn+uBn6a4nkhN7M6m9vpmiJUs0d0ZEU+kmJvyM01q9RmuZcdLTDWPWdIpwLHAx9IfKtLloSfT8nKy/oW/7iGeaufcZzX8XT9Jdglxpy7lNZX2/0Hgmtw5NM1n6iRSXb9PqZKug14BPBARl+TKR+aq/QPQOZpjIXCSpF0ljQPGk3Wy1f1cJO0hac/OZbJO1vvScTpHB00BFuRiPVmZQ4DNqal9MzBR0vB0mWFiKqu1Hb7ZNeNnmlOTzzCt2yLpkPRv6+TcvvpM0iTg88BxEfFsrnyEsmf/IOl1ZJ/h6h7iqXbOtYizJr/rlCRvAU6oR5w57wMejIjtl6ma6jOtRe/8QH2RjX75PVmW/0I/HP8wsibnPcBd6XUM8B/Aval8ITAyt80XUrwryY28qfe5kI1cuTu9VnQeg+y68WJgFfBLYO9ULrIHij2UzqU9t6/TyDo1O4BT6xDrHmTfIvfKlTXFZ0qW2NYBfya7nj21lp8h0E72R/Mh4FukWStqFGcHWd9B57/V76a6H0r/Ju4C7gQ+0FM81c65RnHW7Hed/t3fns79x8Cutfzdp/IfAp/sUrffPtOuL097YmZmpflylpmZleYkYmZmpTmJmJlZaU4iZmZWmpOImZmV5iRiVoWkbdpxxt+Gz+RcSbov5Ffd3aEs6UpJn+hSdrykmyTtIuk3uZvkzEpzEjGr7rmIeHvudVFfd1ijP9zHAHdHNgVONXPJborLOwmYG9kkgouB/1WDWGyQcxIx6yVlz3X4iqQ7lT234Y2pfI80od/taWK8yan8FEkLJf0KWCxpd0nzlT0n5qfKnkfRLuk0Sf+eO87pki6tEMLHyN1tLOnj6Zh3SfpeupN5MfDG3DQXe5Dd+Xx92uz6tB+zPnESMatuty6Xs/Lf3P8Y2WSTlwOfS2VfAH4VEQcB7wW+lv54Q/aciBMi4t3AGcCmiDgA+BLwjlRnPvCBNF8awKnA7ApxHQosB5D0N2QtikMj4u3ANrJ5q7aRzbl2YtrmA8CtudbLfcDflvhMzHbga6Jm1T2X/jBXcl36uZxscjzI5qg6TlJnUnklMDYtL4qIzmdFHAZ8EyAi7pN0T1r+U2qtHCvpAWDniLi3wrH3juz5MpA9E+UdwB3ZVEnsxksT680Fvp6OdRLZdB+kY22T9KKkPXP7Mus1JxGzcl5IP7fx0v8jAR+KiJX5ipIOBp4puN8fAOcCDwJXVqmzVdIrIpuFVsCciJhRod5/AyMlvQ14Jy/vI9kVeL5gXGYV+XKWWe3cDHwqzZ6KpAOr1Psv0mUmSQcAb+lcERFLyaYd/yjVn2K3kmziP8j6Pk6Q9Oq0v70lvTbtK8imD58D3BQR2xOGpH3ILsn9ucR5mm3nJGJWXdc+kZ5GZ10A7AzcI2lFel/Jd4ARku4Hvko2G+vm3Pr5wH9F9mjbSm4A3gMQEfcDXyR7ouQ9ZI/CzU91Phd4Gy9PSO9N+zHrE8/ia9ZgafTUzhHxvKTXk03LvX8aeouknwGXRsTiKtuPJHu2+pF9iOE6YHpE/L7sPszAfSJm/WF34JY0CkvAGRHxoqRhZM+muLtaAgGIiHWSvi9paA/3ilSUHqx0vROI1YJbImZmVpr7RMzMrDQnETMzK81JxMzMSnMSMTOz0pxEzMystP8P+GigmljWLA4AAAAASUVORK5CYII=\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "energy_hist = plt.hist(evt_data['energy'], bins='auto')\n", + "plt.xlabel('Energy (eV)')\n", + "plt.ylabel('Number of photon events')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Zd7bVk4IcpOE" + }, + "source": [ + "## Making a 2D histogram with some table data" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E8U-se8zcpOE" + }, + "source": [ + "Next we'll make an image by binning the x and y coordinates of the events into a 2D histogram. \n", + "\n", + "A one dimensional histogram, as shown above, shows the number of events within each bin corresponding to one axis of information. In the plot above, we chose histogram bins in the energy, shown on the x-axis.\n", + "\n", + "A two dimensional histogram finds the number of events binned according to two dimensions. To make an image, we will bin the number of events by x and y position on the sky." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cEqsE2U1cpOE" + }, + "source": [ + "This particular observation spans five CCD chips. First, we determine the events that only fell on the main (ACIS-I) chips, which have number ids 0, 1, 2, and 3. We can do this by creating an array of True and False values (`ii` below) to filter out events that only fall on those chips." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Mb4RHcJLcpOE" + }, + "outputs": [], + "source": [ + "ii = np.isin(evt_data['ccd_id'], [0, 1, 2, 3])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2z9PQUh9cpOF" + }, + "source": [ + "### Method 1: Use hist2d with a log-normal color scheme" + ] + }, + { + "cell_type": "markdown", + "source": [ + "We can make a 2D histogram plot directly with the function `matplotlib.pyplot.hist2d`, as shown below.\n", + "\n", + "In this example, we choose the `matplotlib` color map named \"viridis\", and we choose to distribute the colors logarithmically using `matplotlib.colors.LogNorm()`.\n", + "\n", + "To see what colormaps are available with `matplotlib`, see http://wiki.scipy.org/Cookbook/Matplotlib/Show_colormaps\n" + ], + "metadata": { + "id": "UQwNh3ppn6c_" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "tjB8Rxa1cpOG", + "outputId": "c97a7a5d-972d-451c-f5ea-a92454983570" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'y')" + ] + }, + "metadata": {}, + "execution_count": 20 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "NBINS = (100,100)\n", + "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS, \n", + " cmap='viridis', norm=LogNorm())\n", + "\n", + "# Show the color bar scale next to the plot. The color corresponds to number \n", + "# of photon events (counts) in each pixel.\n", + "cbar = plt.colorbar(label='Counts')\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zUYM11V5cpOF" + }, + "source": [ + "### Method 2: Use numpy to make a 2D histogram and imshow to display it" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fh5bDy-gcpOF" + }, + "source": [ + "When we plot with `matplotlib.pyplot.hist2d`, it forces the plot into the default figure size, which could cause your image to appear stretched. \n", + "\n", + "By using `matplotlib.pyplot.imshow`, we can avoid stretching the image. To do that, we need to make a 2D array containing the number of counts per pixel bin using `numpy.histogram2d`, as shown below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "hw-xj7pdcpOF", + "outputId": "5b992c7f-5797-45d1-984b-6d3b4f608faa" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'y')" + ] + }, + "metadata": {}, + "execution_count": 40 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "NBINS = (100,100)\n", + "\n", + "img_zero, xedges, yedges = np.histogram2d(evt_data['y'][ii], evt_data['x'][ii], NBINS)\n", + "\n", + "# This array describes how to map the position of the 2D array containing the image\n", + "# to the x and y positions on the sky\n", + "extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n", + "\n", + "plt.imshow(img_zero, extent=extent, interpolation='nearest', \n", + " cmap='gist_yarg', origin='lower', norm=LogNorm())\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Gggs4qvFcpOG" + }, + "source": [ + "## Close the FITS file" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KNYSKxLucpOG" + }, + "source": [ + "When you're done using a FITS file, it's often a good idea to close it. That way you can be sure it won't continue using up excess memory or file handles on your computer. (This happens automatically when you close Python, but you never know how long that might be...)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "AI8mrIGWcpOG" + }, + "outputs": [], + "source": [ + "hdu_list.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cwSittwlcpOG" + }, + "source": [ + "## Exercises" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zX5Gr3CdcpOH" + }, + "source": [ + "Make a scatter plot of the same data you histogrammed above. The [plt.scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) function is your friend for this. What are the pros and cons of doing it this way?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "haxhlHMIcpOH", + "outputId": "22fd37cb-a934-4296-dfea-7872324e18ad", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + } + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "energy_scatter = plt.scatter(evt_data['x'][ii], evt_data['y'][ii], s=1, alpha=0.1, color='b')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "84C-9XGUcpOH" + }, + "source": [ + "Try the same with the [plt.hexbin](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hexbin) plotting function. Which do you think looks better for this kind of data?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "s-aWczHzcpOH", + "outputId": "5d50aeba-7cc1-479b-e88b-bb9720c329fe", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + } + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "energy_hex = plt.hexbin(evt_data['x'][ii], evt_data['y'][ii], norm=LogNorm())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sB7gbTBBcpOH" + }, + "source": [ + "Choose an energy range to make a slice of the FITS table, then plot it. How does the image change with different energy ranges?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Hq1VDm35cpOH", + "outputId": "041e1abe-28c3-4209-9454-609aea4786a3", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + } + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'y')" + ] + }, + "metadata": {}, + "execution_count": 44 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "NBINS = (100,100)\n", + "ii = (evt_data['energy'] > 3500) & (evt_data['energy'] < 5000)\n", + "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS,\n", + " cmap='viridis', norm=LogNorm())\n", + "\n", + "cbar = plt.colorbar(ticks=[1.0,3.0,6.0])\n", + "cbar.ax.set_yticklabels(['1','3','6'])\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "code", + "source": [ + "" + ], + "metadata": { + "id": "uFehWSaZsLrV" + }, + "execution_count": null, + "outputs": [] + } + ], + "metadata": { + "astropy-tutorials": { + "author": "Lia R. Corrales ", + "date": "January 2014", + "description": "astropy.utils.data to download the file, astropy.io.fits to open and view the file, matplotlib for making both 1D and 2D histograms of the data.", + "link_name": "Viewing and manipulating data from FITS tables", + "name": "", + "published": true + }, + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.12" + }, + "colab": { + "name": "FITS-tables.ipynb", + "provenance": [], + "collapsed_sections": [] + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/tutorials/FITS-tables/requirements.txt b/tutorials/FITS-tables/requirements.txt deleted file mode 100644 index d1d0ba14..00000000 --- a/tutorials/FITS-tables/requirements.txt +++ /dev/null @@ -1,3 +0,0 @@ -astropy -matplotlib -numpy From 588b5cbaabc8ca24c836705d8c15566e5e2eb1e9 Mon Sep 17 00:00:00 2001 From: luthienliu Date: Wed, 6 Jul 2022 00:50:07 -0400 Subject: [PATCH 02/10] Changes to FITS-tables tutorial --- tutorials/FITS-tables/FITS-tables.ipynb | 367 ------------------------ 1 file changed, 367 deletions(-) delete mode 100755 tutorials/FITS-tables/FITS-tables.ipynb diff --git a/tutorials/FITS-tables/FITS-tables.ipynb b/tutorials/FITS-tables/FITS-tables.ipynb deleted file mode 100755 index beeee957..00000000 --- a/tutorials/FITS-tables/FITS-tables.ipynb +++ /dev/null @@ -1,367 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Viewing and manipulating data from FITS tables\n", - "\n", - "## Authors\n", - "Lia Corrales, Kris Stern\n", - "\n", - "## Learning Goals\n", - "* Download a FITS table file from a URL \n", - "* Open a FITS table file and view table contents\n", - "* Make a 2D histogram with the table data\n", - "* Close the FITS file after use\n", - "\n", - "## Keywords\n", - "FITS, file input/output, table, numpy, matplotlib, histogram\n", - "\n", - "\n", - "## Summary\n", - "\n", - "This tutorial demonstrates the use of `astropy.utils.data` to download a data file, then uses `astropy.io.fits` and `astropy.table` to open the file. Lastly, `matplotlib` is used to visualize the data as a histogram." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "from astropy.io import fits\n", - "from astropy.table import Table\n", - "from matplotlib.colors import LogNorm\n", - "\n", - "# Set up matplotlib\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following line is needed to download the example FITS files used in this tutorial." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from astropy.utils.data import download_file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "FITS files often contain large amounts of multi-dimensional data and tables. \n", - "\n", - "In this particular example, we'll open a FITS file from a Chandra observation of the Galactic Center. The file contains a list of events with x and y coordinates, energy, and various other pieces of information." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "event_filename = download_file('http://data.astropy.org/tutorials/FITS-tables/chandra_events.fits', \n", - " cache=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Opening the FITS file and viewing table contents" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hdu_list = fits.open(event_filename, memmap=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hdu_list.info()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this case, we're interested in reading EVENTS, which contains information about each X-ray photon that hit the detector." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To find out what information the table contains, let's print the column names." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(hdu_list[1].columns)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we'll take this data and convert it into an [astropy table](http://docs.astropy.org/en/stable/table/). While it's possible to access FITS tables directly from the ``.data`` attribute, using [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) tends to make a variety of common tasks more convenient." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "evt_data = Table(hdu_list[1].data)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "evt_data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can extract data from the table by referencing the column name. Let's try making a histogram for the energy of each photon, which will give us a sense for the spectrum (folded with the detector's efficiency)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "energy_hist = plt.hist(evt_data['energy'], bins='auto')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Making a 2D histogram with some table data" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We'll make an image by binning the x and y coordinates of the events into a 2D histogram." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This particular observation spans five CCD chips. First, we determine the events that only fell on the main (ACIS-I) chips, which have number ids 0, 1, 2, and 3." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "ii = np.in1d(evt_data['ccd_id'], [0, 1, 2, 3])\n", - "np.sum(ii)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Method 1: Use numpy to make a 2D histogram and imshow to display it" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This method allows us to create an image without stretching:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "NBINS = (100,100)\n", - "\n", - "img_zero, yedges, xedges = np.histogram2d(evt_data['x'][ii], evt_data['y'][ii], NBINS)\n", - "\n", - "extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n", - "\n", - "plt.imshow(img_zero, extent=extent, interpolation='nearest', cmap='gist_yarg', origin='lower')\n", - "\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')\n", - "\n", - "# To see more color maps\n", - "# http://wiki.scipy.org/Cookbook/Matplotlib/Show_colormaps" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Method 2: Use hist2d with a log-normal color scheme" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "NBINS = (100,100)\n", - "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS, \n", - " cmap='viridis', norm=LogNorm())\n", - "\n", - "cbar = plt.colorbar(ticks=[1.0,3.0,6.0])\n", - "cbar.ax.set_yticklabels(['1','3','6'])\n", - "\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Close the FITS file" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "When you're done using a FITS file, it's often a good idea to close it. That way you can be sure it won't continue using up excess memory or file handles on your computer. (This happens automatically when you close Python, but you never know how long that might be...)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "hdu_list.close()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Exercises" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Make a scatter plot of the same data you histogrammed above. The [plt.scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) function is your friend for this. What are the pros and cons of doing it this way?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Try the same with the [plt.hexbin](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hexbin) plotting function. Which do you think looks better for this kind of data?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Choose an energy range to make a slice of the FITS table, then plot it. How does the image change with different energy ranges?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "astropy-tutorials": { - "author": "Lia R. Corrales ", - "date": "January 2014", - "description": "astropy.utils.data to download the file, astropy.io.fits to open and view the file, matplotlib for making both 1D and 2D histograms of the data.", - "link_name": "Viewing and manipulating data from FITS tables", - "name": "", - "published": true - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From 55d4cfa7ed72cb072aa98cf0e9ad23ccd210f76f Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Wed, 6 Jul 2022 05:08:13 +0000 Subject: [PATCH 03/10] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tutorials/FITS-tables/FITS_tables.ipynb | 1305 ++++++++++------------- 1 file changed, 536 insertions(+), 769 deletions(-) diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb index 2cf5ec90..b0c276dd 100644 --- a/tutorials/FITS-tables/FITS_tables.ipynb +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -1,771 +1,538 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Mb0-v-tzcpN6" - }, - "source": [ - "# Working with Chandra FITS tables\n", - "\n", - "## Authors\n", - "Lia Corrales, Kris Stern, LĂșthien Liu, Zihao Chen, Saima Siddiqui\n", - "\n", - "## Learning Goals\n", - "* Download a Chandra FITS table file from a URL \n", - "* Open a Chandra FITS table file and view table contents\n", - "* Make a 2D histogram with the event list data\n", - "* Close the FITS file after use\n", - "\n", - "## Keywords\n", - "FITS, file input/output, table, numpy, matplotlib, histogram\n", - "\n", - "\n", - "## Summary\n", - "\n", - "Chandra image data is stored in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n", - "\n", - "In this tutorial, we will use `astropy.utils.data` to download a Chandra FITS file, then use `astropy.io.fits` and `astropy.table` to open the file. Lastly, we will use `matplotlib` to visualize the Chandra event list as a histogram, effectively producing an X-ray image of the sky." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "vfrMqJd9cpN9" - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "from astropy.io import fits\n", - "from astropy.table import Table\n", - "from matplotlib.colors import LogNorm\n", - "\n", - "# Set up matplotlib\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "IexsOCvKcpN-" - }, - "source": [ - "The following line is needed to download the example FITS files used in this tutorial." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "0zp1lvcEcpN_" - }, - "outputs": [], - "source": [ - "from astropy.utils.data import download_file" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "6u1ChU47cpN_" - }, - "source": [ - "FITS files often contain large amounts of multi-dimensional data and tables. \n", - "\n", - "In this particular example, we'll open a FITS file from a Chandra observation of the Galactic Center. The file contains a list of events with x and y coordinates, energy, and various other pieces of information." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "r6F-JgTCcpN_" - }, - "outputs": [], - "source": [ - "event_filename = download_file('http://data.astropy.org/tutorials/FITS-tables/chandra_events.fits', \n", - " cache=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "me6HB0RrcpOA" - }, - "source": [ - "## Opening the FITS file and viewing table contents" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Cp_kqCg4cpOA" - }, - "source": [ - "Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "2ABOyWmxcpOB" - }, - "outputs": [], - "source": [ - "hdu_list = fits.open(event_filename, memmap=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "yEuBPS8ycpOB", - "outputId": "8bc4c565-e09c-4de0-d99b-1d05fcfb00a3" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Filename: /root/.astropy/cache/download/url/333246bccb141ea3b4e86c49e45bf8d6/contents\n", - "No. Name Ver Type Cards Dimensions Format\n", - " 0 PRIMARY 1 PrimaryHDU 30 () \n", - " 1 EVENTS 1 BinTableHDU 890 483964R x 19C [1D, 1I, 1I, 1J, 1I, 1I, 1I, 1I, 1E, 1E, 1E, 1E, 1J, 1J, 1E, 1J, 1I, 1I, 32X] \n", - " 2 GTI 3 BinTableHDU 28 1R x 2C [1D, 1D] \n", - " 3 GTI 2 BinTableHDU 28 1R x 2C [1D, 1D] \n", - " 4 GTI 1 BinTableHDU 28 1R x 2C [1D, 1D] \n", - " 5 GTI 0 BinTableHDU 28 1R x 2C [1D, 1D] \n", - " 6 GTI 6 BinTableHDU 28 1R x 2C [1D, 1D] \n" - ] - } - ], - "source": [ - "hdu_list.info()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "FCoyC8sIcpOC" - }, - "source": [ - "In this case, we're interested in reading EVENTS, which contains information about each X-ray photon that hit the detector." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kTHnKQPicpOC" - }, - "source": [ - "To find out what information the table contains, let's print the column names." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "CfQyzNPNcpOC", - "outputId": "244569b7-9235-43e1-f471-d0789a538b0a" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "ColDefs(\n", - " name = 'time'; format = '1D'; unit = 's'\n", - " name = 'ccd_id'; format = '1I'\n", - " name = 'node_id'; format = '1I'\n", - " name = 'expno'; format = '1J'\n", - " name = 'chipx'; format = '1I'; unit = 'pixel'; coord_type = 'CPCX'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n", - " name = 'chipy'; format = '1I'; unit = 'pixel'; coord_type = 'CPCY'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n", - " name = 'tdetx'; format = '1I'; unit = 'pixel'\n", - " name = 'tdety'; format = '1I'; unit = 'pixel'\n", - " name = 'detx'; format = '1E'; unit = 'pixel'; coord_type = 'LONG-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n", - " name = 'dety'; format = '1E'; unit = 'pixel'; coord_type = 'NPOL-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n", - " name = 'x'; format = '1E'; unit = 'pixel'; coord_type = 'RA---TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 266.41519201128; coord_inc = -0.00013666666666667\n", - " name = 'y'; format = '1E'; unit = 'pixel'; coord_type = 'DEC--TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = -29.012248288366; coord_inc = 0.00013666666666667\n", - " name = 'pha'; format = '1J'; unit = 'adu'; null = 0\n", - " name = 'pha_ro'; format = '1J'; unit = 'adu'; null = 0\n", - " name = 'energy'; format = '1E'; unit = 'eV'\n", - " name = 'pi'; format = '1J'; unit = 'chan'; null = 0\n", - " name = 'fltgrade'; format = '1I'\n", - " name = 'grade'; format = '1I'\n", - " name = 'status'; format = '32X'\n", - ")\n" - ] - } - ], - "source": [ - "print(hdu_list[1].columns)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YpH2-4qPcpOC" - }, - "source": [ - "Now we'll take this data and convert it into an [astropy table](http://docs.astropy.org/en/stable/table/). While it's possible to access FITS tables directly from the ``.data`` attribute, using [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) tends to make a variety of common tasks more convenient." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "n7zMyhRhcpOD" - }, - "outputs": [], - "source": [ - "evt_data = Table(hdu_list[1].data)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sEmGEMR1cpOD" - }, - "source": [ - "For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 1000 - }, - "id": "c00cCz9McpOD", - "outputId": "86eda857-3fff-4960-f488-477ee510a85c" - }, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "\n", - " time ccd_id node_id expno ... pi fltgrade grade status [32] \n", - " float64 int16 int16 int32 ... int32 int16 int16 bool \n", - "------------------ ------ ------- ----- ... ----- -------- ----- --------------\n", - " 238623220.9093583 3 3 68 ... 951 16 4 False .. 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I4ChgUURsTIljETCpL7GZmVnvFJmA8V/J7lK/OhV9WtI7I+LcksccB2wArpT0NmA58Glgv4hYl+o8DuyXlkcBj+W2X5PKqpVXOodpwDSAsWPHVqrSNDzBopm1kiJDfN8PHBkRsyNiNtm3/b60RnYCJgCXR8SBwDNkl662S5M9Rh+OsYOImBUR7RHRPmLEiFrt1sxs0Cv0PBFgGLAxLe/Vx2OuAdZExNL0/lqyJPKEpJERsS5drlqf1q8lm/Sx0+hUthZ4T5fyW/sYmw0g7pA3q78iSeRfgd9JuoVsmO+76NJy6I2IeFzSY5L2j4iVwBHA/ek1Bbgo/VyQNlkInJWGGR8MbE6J5mbgXyQNT/UmAjPKxmUDgy8HDl7Vfvf+AlFfRebOmivpVuBvU9E5EfF4H4/7KeDqNDJrNXAq2aW1+ZKmAo8CJ6a6N5IN7+0gG+J7aopro6QLgDtSvfMjYiNmZtYwhS5npQ7vhbU6aETcRTY0t6sjKtQNoOJTFFMfzexaxWXNz5eozJpL0T4Rs5bWmXyceAYff/GoL0/AaGZmpXXbEpE0BFgREW9sUDxmZr3iwRT9q9uWSERsA1ZKau479MzMrF8U6RMZDqxIz1h/prPQz1Y3M7MiSeRLdY/CzKwBPMCi9go9Y13Sa4HxEfFLSbsDQ+ofmplZZe4HaR49js6SdDrZ1CTfS0WjgOvrGZSZmbWGIkN8zwQOBbYARMQq4NX1DMrMzFpDkSTyQkS82PlG0k7UcIZdMzNrXUU61n8t6VxgN0lHAmcA/1nfsMx65uviZv2vSEtkOtlDpO4FPkE2IeIXu93CzMwGhSKjs/4iaQ6wlOwy1so0KaKZWUvyfFq1U+TxuO8Hvgs8RPY8kXGSPhERN9U7ODMza25F+kS+Abw3IjoAJL0euAFwEjGzhnEfWHMq0ifydGcCSVYDT9cpHjMzayFVWyKSPpgWl0m6EZhP1ifyYV56mqCZmQ1i3V3O+kBu+Qng3Wl5A7Bb3SIys4rcGWzNqGoSiYhTGxmImZm1niKjs8YBnwLa8vU9FbyZmRUZnXU9cAXZXep/qW84ZmaN5cuEfVNkdNbzEXFZRNwSEb/ufPX1wJKGSPqdpJ+l9+MkLZXUIekaSbuk8l3T+460vi23jxmpfKWko/oak5mZ9U6RJPJNSTMl/Z2kCZ2vGhz708ADufcXA5dGxBuATcDUVD4V2JTKL031kHQAcBLwJmAS8J30THgzM2uQIpez3gL8I3A4L13OivS+FEmjgfcDFwJnS1La30dTlTnAl4HLgclpGbLnmnwr1Z8MzIuIF4CHJXUABwG3lY2rv/gmKjNrVUWSyIeB1+Wng6+Bfwc+D+yZ3u8DPBURW9P7NWQPvyL9fAwgIrZK2pzqjwKW5PaZ38bMrNfcP9J7RZLIfcAwYH0tDijpWGB9RCyX9J5a7LPAMacB0wDGjh3biENak/IfidbiVnrzK5JEhgEPSroDeKGzsA9DfA8FjpN0DPBKYCjwTWCYpJ1Sa2Q0sDbVXwuMAdakB2LtBTyZK++U32YHETELmAXQ3t7uGYjNzGqkSBKZWcsDRsQMYAZAaol8LiI+JunHwAnAPGAKsCBtsjC9vy2t/1VEhKSFwI8kXQK8BhgP3F7LWM3MrHtFnifS5+G8BZ0DzJP0VeB3ZPemkH7+R+o430g2IouIWCFpPnA/sBU4MyK2NShWMzOj2B3rT/PSM9V3AXYGnomIoX09eETcCtyalleTja7qWud5ss79SttfSDbCy8zM+kGRlkjnCCpyQ2sPqWdQZtZcPCDBqilys+F2kbke8N3hZmZW6HLWB3NvXwG0A8/XLSIz65FbBtYsiozOyj9XZCvwCNklLTOzumiG+0M6Y3CS7l6RPhE/V8TMzCrq7vG453WzXUTEBXWIx6xhfEnIrO+6a4k8U6FsD7JZdfcBnETMzAa57h6P+43OZUl7kk3dfirZHeXfqLadFdMM13zNzPqq2z4RSXsDZwMfI5uefUJEbGpEYGb9zZe7zHrWXZ/I14APkk1c+JaI+FPDohoA/AfIBqp6jVpy67w1dXez4WfJJjb8IvA/krak19OStjQmPDMza2bd9Yn06m52q/5Nyq0Ss9bl/7/dK3KzoXXDTfCBx79Ts+Lc2jAzs9LcEinJ31bNzJxEzKwKf1GyIpxEGsz/Mc1e4v8Prc9JxAz/MTMry0nEzBrKCXtgcRIxa3L+o2vNzEN8zcysNLdEzKwU38lt0A8tEUljJN0i6X5JKyR9OpXvLWmRpFXp5/BULkmXSeqQdI+kCbl9TUn1V0ma0uhzMbPBpW36DdtflumPlshW4LMRcWd6TslySYuAU4DFEXGRpOnAdOAc4GhgfHodDFwOHJymqZ8JtAOR9rPQU9VbPfhbt1llDU8iEbEOWJeWn5b0ADAKmAy8J1WbA9xKlkQmA1dFRABLJA2TNDLVXRQRGwFSIpoEzG3YyZg1gVomOH/Dtt7q1z4RSW3AgcBSYL+UYAAeB/ZLy6OAx3KbrUll1corHWcaMA1g7NixtQneBi23SnrPyWng6rckIulVwE+Az0TEFknb10VESIpaHSsiZpE9XIv29vaa7desN38cB3LCcZIYvPoliUjamSyBXB0R16XiJySNjIh16XLV+lS+FhiT23x0KlvLS5e/OstvrWfcZs2ubFJzErCyGp5ElDU5rgAeiIhLcqsWAlOAi9LPBbnysyTNI+tY35wSzc3Av3SO4gImAjMacQ5mA4ETh9VCf7REDgX+EbhX0l2p7Fyy5DFf0lTgUeDEtO5G4BigA3gWOBUgIjZKugC4I9U7v7OT3azV+Q+8tYr+GJ31/wBVWX1EhfoBnFllX7OB2bWLzqx+3CFvA5HvWDfrR25xtC5/Kcg4iZj1AycPGyg8AaOZmZXmJGJmZqU5iZiZWWlOImZmVpqTiJmZlebRWb3gETVmZjtyS8TMzEpzS8TMrI8G842HbomYmVlpTiJmZlaak4iZmZXmJGJmVkNt028YVCM5nUTMzKw0JxEzMyvNScTMzErzfSJmZnUwWO4dcUvEzMxKc0vEzKzOBnKrxEnEzKyBBlpCafnLWZImSVopqUPS9P6Ox8xsMGnploikIcC3gSOBNcAdkhZGxP39G5mZWc8q3ZTYaq2Tlk4iwEFAR0SsBpA0D5gMOImYWUuqdrd7syaXVk8io4DHcu/XAAd3rSRpGjAtvf2TpJW9PM6+wB9LRdhYjrP2WiXWVokTWifWpopTF1dd1ag4X1upsNWTSCERMQuYVXZ7Scsior2GIdWF46y9Vom1VeKE1onVcRbT6h3ra4ExufejU5mZmTVAqyeRO4DxksZJ2gU4CVjYzzGZmQ0aLX05KyK2SjoLuBkYAsyOiBV1OFTpS2EN5jhrr1VibZU4oXVidZwFKCL68/hmZtbCWv1ylpmZ9SMnETMzK81JpBv9PaWKpDGSbpF0v6QVkj6dyr8saa2ku9LrmNw2M1K8KyUd1chzkfSIpHtTTMtS2d6SFklalX4OT+WSdFmK5x5JE3L7mZLqr5I0pcYx7p/73O6StEXSZ5rlM5U0W9J6Sfflymr2GUp6R/oddaRtVcM4vybpwRTLTyUNS+Vtkp7Lfbbf7Smeaudcozhr9rtWNqhnaSq/RtkAn1KqxHpNLs5HJN2VyvvtM32ZiPCrwouso/4h4HXALsDdwAENjmEkMCEt7wn8HjgA+DLwuQr1D0hx7gqMS/EPadS5AI8A+3Yp+zdgelqeDlyclo8BbgIEHAIsTeV7A6vTz+FpeXgdf8ePk91E1RSfKfAuYAJwXz0+Q+D2VFdp26NrGOdEYKe0fHEuzrZ8vS77qRhPtXOuUZw1+10D84GT0vJ3gX+q5e++y/pvAOf192fa9eWWSHXbp1SJiBeBzilVGiYi1kXEnWn5aeABsrv0q5kMzIuIFyLiYaCD7Dz681wmA3PS8hzg+Fz5VZFZAgyTNBI4ClgUERsjYhOwCJhUp9iOAB6KiEe7qdPQzzQifgNsrBBDnz/DtG5oRCyJ7C/JVbl99TnOiPhFRGxNb5eQ3bdVVQ/xVDvnPsfZjV79rtM3/MOBa/saZ0+xpmOdCMztbh+N+Ey7chKprtKUKt39Aa8rSW3AgcDSVHRWumwwO9csrRZzo84lgF9IWq5sqhmA/SJiXVp+HNivSWKF7L6i/H/KZvxMoXaf4ai03LW8Hk4j+xbcaZyk30n6taS/T2XdxVPtnGulFr/rfYCncomznp/n3wNPRMSqXFlTfKZOIi1A0quAnwCfiYgtwOXA64G3A+vImrnN4LCImAAcDZwp6V35lembUVOMKU/Xro8DfpyKmvUz3UEzfYbVSPoCsBW4OhWtA8ZGxIHA2cCPJA0tur86nHNL/K67+Ag7fuFpms/USaS6pphSRdLOZAnk6oi4DiAinoiIbRHxF+D7ZM1tqB5zQ84lItamn+uBn6a4nkhN7M6m9vpmiJUs0d0ZEU+kmJvyM01q9RmuZcdLTDWPWdIpwLHAx9IfKtLloSfT8nKy/oW/7iGeaufcZzX8XT9Jdglxpy7lNZX2/0Hgmtw5NM1n6iRSXb9PqZKug14BPBARl+TKR+aq/QPQOZpjIXCSpF0ljQPGk3Wy1f1cJO0hac/OZbJO1vvScTpHB00BFuRiPVmZQ4DNqal9MzBR0vB0mWFiKqu1Hb7ZNeNnmlOTzzCt2yLpkPRv6+TcvvpM0iTg88BxEfFsrnyEsmf/IOl1ZJ/h6h7iqXbOtYizJr/rlCRvAU6oR5w57wMejIjtl6ma6jOtRe/8QH2RjX75PVmW/0I/HP8wsibnPcBd6XUM8B/Aval8ITAyt80XUrwryY28qfe5kI1cuTu9VnQeg+y68WJgFfBLYO9ULrIHij2UzqU9t6/TyDo1O4BT6xDrHmTfIvfKlTXFZ0qW2NYBfya7nj21lp8h0E72R/Mh4FukWStqFGcHWd9B57/V76a6H0r/Ju4C7gQ+0FM81c65RnHW7Hed/t3fns79x8Cutfzdp/IfAp/sUrffPtOuL097YmZmpflylpmZleYkYmZmpTmJmJlZaU4iZmZWmpOImZmV5iRiVoWkbdpxxt+Gz+RcSbov5Ffd3aEs6UpJn+hSdrykmyTtIuk3uZvkzEpzEjGr7rmIeHvudVFfd1ijP9zHAHdHNgVONXPJborLOwmYG9kkgouB/1WDWGyQcxIx6yVlz3X4iqQ7lT234Y2pfI80od/taWK8yan8FEkLJf0KWCxpd0nzlT0n5qfKnkfRLuk0Sf+eO87pki6tEMLHyN1tLOnj6Zh3SfpeupN5MfDG3DQXe5Dd+Xx92uz6tB+zPnESMatuty6Xs/Lf3P8Y2WSTlwOfS2VfAH4VEQcB7wW+lv54Q/aciBMi4t3AGcCmiDgA+BLwjlRnPvCBNF8awKnA7ApxHQosB5D0N2QtikMj4u3ANrJ5q7aRzbl2YtrmA8CtudbLfcDflvhMzHbga6Jm1T2X/jBXcl36uZxscjzI5qg6TlJnUnklMDYtL4qIzmdFHAZ8EyAi7pN0T1r+U2qtHCvpAWDniLi3wrH3juz5MpA9E+UdwB3ZVEnsxksT680Fvp6OdRLZdB+kY22T9KKkPXP7Mus1JxGzcl5IP7fx0v8jAR+KiJX5ipIOBp4puN8fAOcCDwJXVqmzVdIrIpuFVsCciJhRod5/AyMlvQ14Jy/vI9kVeL5gXGYV+XKWWe3cDHwqzZ6KpAOr1Psv0mUmSQcAb+lcERFLyaYd/yjVn2K3kmziP8j6Pk6Q9Oq0v70lvTbtK8imD58D3BQR2xOGpH3ILsn9ucR5mm3nJGJWXdc+kZ5GZ10A7AzcI2lFel/Jd4ARku4Hvko2G+vm3Pr5wH9F9mjbSm4A3gMQEfcDXyR7ouQ9ZI/CzU91Phd4Gy9PSO9N+zHrE8/ia9ZgafTUzhHxvKTXk03LvX8aeouknwGXRsTiKtuPJHu2+pF9iOE6YHpE/L7sPszAfSJm/WF34JY0CkvAGRHxoqRhZM+muLtaAgGIiHWSvi9paA/3ilSUHqx0vROI1YJbImZmVpr7RMzMrDQnETMzK81JxMzMSnMSMTOz0pxEzMystP8P+GigmljWLA4AAAAASUVORK5CYII=\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "energy_hist = plt.hist(evt_data['energy'], bins='auto')\n", - "plt.xlabel('Energy (eV)')\n", - "plt.ylabel('Number of photon events')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Zd7bVk4IcpOE" - }, - "source": [ - "## Making a 2D histogram with some table data" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "E8U-se8zcpOE" - }, - "source": [ - "Next we'll make an image by binning the x and y coordinates of the events into a 2D histogram. \n", - "\n", - "A one dimensional histogram, as shown above, shows the number of events within each bin corresponding to one axis of information. In the plot above, we chose histogram bins in the energy, shown on the x-axis.\n", - "\n", - "A two dimensional histogram finds the number of events binned according to two dimensions. To make an image, we will bin the number of events by x and y position on the sky." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cEqsE2U1cpOE" - }, - "source": [ - "This particular observation spans five CCD chips. First, we determine the events that only fell on the main (ACIS-I) chips, which have number ids 0, 1, 2, and 3. We can do this by creating an array of True and False values (`ii` below) to filter out events that only fall on those chips." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Mb4RHcJLcpOE" - }, - "outputs": [], - "source": [ - "ii = np.isin(evt_data['ccd_id'], [0, 1, 2, 3])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2z9PQUh9cpOF" - }, - "source": [ - "### Method 1: Use hist2d with a log-normal color scheme" - ] - }, - { - "cell_type": "markdown", - "source": [ - "We can make a 2D histogram plot directly with the function `matplotlib.pyplot.hist2d`, as shown below.\n", - "\n", - "In this example, we choose the `matplotlib` color map named \"viridis\", and we choose to distribute the colors logarithmically using `matplotlib.colors.LogNorm()`.\n", - "\n", - "To see what colormaps are available with `matplotlib`, see http://wiki.scipy.org/Cookbook/Matplotlib/Show_colormaps\n" - ], - "metadata": { - "id": "UQwNh3ppn6c_" - } - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 296 - }, - "id": "tjB8Rxa1cpOG", - "outputId": "c97a7a5d-972d-451c-f5ea-a92454983570" - }, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "Text(0, 0.5, 'y')" - ] - }, - "metadata": {}, - "execution_count": 20 - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "NBINS = (100,100)\n", - "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS, \n", - " cmap='viridis', norm=LogNorm())\n", - "\n", - "# Show the color bar scale next to the plot. The color corresponds to number \n", - "# of photon events (counts) in each pixel.\n", - "cbar = plt.colorbar(label='Counts')\n", - "\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zUYM11V5cpOF" - }, - "source": [ - "### Method 2: Use numpy to make a 2D histogram and imshow to display it" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "fh5bDy-gcpOF" - }, - "source": [ - "When we plot with `matplotlib.pyplot.hist2d`, it forces the plot into the default figure size, which could cause your image to appear stretched. \n", - "\n", - "By using `matplotlib.pyplot.imshow`, we can avoid stretching the image. To do that, we need to make a 2D array containing the number of counts per pixel bin using `numpy.histogram2d`, as shown below." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 296 - }, - "id": "hw-xj7pdcpOF", - "outputId": "5b992c7f-5797-45d1-984b-6d3b4f608faa" - }, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "Text(0, 0.5, 'y')" - ] - }, - "metadata": {}, - "execution_count": 40 - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
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3YeXDuE6sgEi2FOfMbP3GWO7aiGNVMSymUigUJkUxFcAJc6IEIIOwlLKrczzvz5ZQzKKf1ZBhegS6emcZ+Flxj4hmbvfva5hvlo5iGWjWjhJsTL9jON/vzp075+bIPLlcN2k+rYBh6b0oHUOm22D/rABJs7OvXVRLmRnys2RTdEJkkGBWAcHXkCEyj3FswyDEzGGR7C+r48TjkaktQjGVQqEwKYqpAIcPrySii1KRwWi2lmRBXmPOVrQSxLc+pVCmq4l9xevJWDL3ao+TLvCsvBivYepD3496AWkmwZnYxwzDaQEik6CehWkYo1R1P7633cVppVlUS8m6DoZLSPMBlh4/kydlFiOmAnUf1K3EuTHMY9H4mbbSzCdzrqP+i3Nd5LTG+kiZToU6mzEUUykUCpOimAqQVYaj9GcyoijB6HPAZNCUyLFNVpNGmk/9F8fJEHUmI4rw2MhqWN8m9m+Q7USpRwsBU0VwvbJxc/wxubLZo0ErXJbmkRYc6jHi/JhUioGRWQpQMk9fw+p9cc6sccwa2lEXxQRgZL5MTRnb+PfC5E9x/GPhJKxbFf8fZNa1DMVUCoXCpKiXSqFQmBS1/QFIl6X5qF5T9KzcJrcw3MqYumdbGTrB0eU/Umtm7OIWLZ63opGOd6bOBw8elLQ6T4bbWPlqZanHsMg8ybFl2ei8ffJcmb8lbsXcxqZ8j5POadHRzG1Zq8lrEbc/zC/LbW4WnTuWpY/K17iNcVvnPN6+ffuq+8StDE28zLyfbUWYd4ZbmrUodbmFimMqRW2hUNgQFFMB/IaOEobKWzKKzCmK0o5u25mbe3ZvaSZJ43FmhfN3s4LYlpnqPTazJkv+eA0lreeYmbt9zqZ2BiHaoZBF2WMbr9M999wjSXrNa14zN1e7xNPNnUXqpdmzMrNixv3Yls/M0tvrljkajoVHUAGd5cBxjleuU1Y0nsGsfIZZzSneL1Nok5XRjJ5l+M8qNGQoplIoFCZFMRXAkiBKgCyzePweJQCdulinmBnUpXkzp7/T4WxRhT+mBYgS0s5tZh1mKK77wz7j9R43WVTUm9B8a6ln6eocqVm6BGase/WrX71q7tJ86AT1VpnOg05c1jNklQo9bubA5VrE508WQJ1Tds1YKoJFrIapLKi7yXR/1DllwYN0tGMqCt83svCrrrpKa0ExlUKhMCmKqQDMhyrNpDNds7MauwwO85vfEjJzvmKQGHUqmSaeGdgt2bO8uYb79zzo6h3n4X49FlqzImtijlXfm+EHkZ2RyY0lqJLybPlxDKwkGME0FXwu0mxdqY9imoHIJJjQyWvqcdOxTZqxYDNEj4Fjk+YtdnS591wjUzEj9DVmT6yhHcfHsfka9xsZY+lUCoXChqCYCpAF17Eur9/eWWZ26k7MDuiyHn0qqBNwH8yMHyWN98f0AckSLlnqOJ2kWRMtF1F68Zi/s5pfxJiugKkW4pgYtEe/GGkmgWlBs64l89lwv8zW7zXM9C+U7PQXsi5Kmk9UxPQPWbiH18HjNuvIfFrMZpiOgf5DkXFxzvQFIjuJ92YoBXVpkrRnz5656zMUUykUCpOimMoASw/6AUjzNWSYwDgDExUzaDDzeKX3Z+YrwP4pTS2NsqqJlsSs6cL7xmOshOe5R6nHiocO06d/R7Qk2JuUuiH36+chzaSnjzHYzfeL6SpY4Y9JoLLny3QFTG0ZPUrdP58zE1PHNaVntsGk3PE6r4fHxJQXGUujdSxLqcDUmX429H+ihXAtKKZSKBQmRb1UCoXCpKjtzwBuQSKYj3Qsw3y8fqygOctKSvPbqCyjvLR6S8NsdHTbjspjz405RUzhswLkDHzMMqYZNLkfOXJE0my7lbmJM4O955wVsPdYqHCke358dnTWs2KVeXml+dy3rA1ExzNeL83nEc5+Tz425ky5yOGSv5usLg+3qnSci1sxbs8YTuI1XpS3eAzFVAqFwqQopjLgwIEDkuZNeNJ8eDjNqVlIP/OO0rwaJYwlOp27KMUzRkTHrCzfKR3jyDoyRR4VnVQ0Z3WRyBjMMGzCjnNmFneGBcT+mYuWFQmzFBRUUlLSx7FQslNRy/tK86bwTDHL75T6TGMQWaAVsT7G581UCLENTclZLSjmQ3Y/HqPvwzQWa0ExlUKhMCmKqQxgbtcsSRDd8y0ZooQZYzNkA/EaS0a6rnNs0SHMEpe1ZCyVolSk/mVMGh06dOjoNTbTspaPv2d1keiOb8mfBcz5GHPfMvgx3pNBdF6XTA9DWPJndam93mYdDshj8qysqiFrM1E3lLkdUO/G7PqxP2bRZ3+Z7oz3zgJf6aiY1fiOa3E8KKZSKBQmxdKZSmvtFEl3Snq49/6W1tqHJf2wpKeGJj/Re7+7rYi+D0h6k6RvDsf/cujjBkm/NLR/b+/9lmWNN3urj+k6MlZg6UOmwpoyiwL+qCehziLex5KF0jyOmZKd8HFLxTgnzp2SOY7B1zAg0paETGqb8XjcdraK/dMxi3oGn8+YCutHM2VEPOd7ez2YrCkbk38n1Kkw0DNeQ5ZpROc3t3VoBZ32MqsMQ0I8bs+Lz0Wad8/3er3sZS+TNEsHcTxYj+3Pz0r6a0kvCcd+vvf+MbR7o6Qrhn+vkvRBSa9qrZ0j6d2S9krqku5qrd3We39ChULhpMNSXyqttd2S3izpfZJ+7hjNr5f0kb4iGu9orZ3dWtsh6TWSbu+9Pz70ebukN0j6/SnH6sAsS54o1S0dKBktnaIEGKsRzIpvUSdBXcRYuoHIGmgxomt2HD/d5u0iz/tkeiSmF/QYY/8+5zX0X/uGZIFs1LOwnjFTI8Y5Wnpzvx+ZHEMcqOvIAgq53mYdDg+IPidj/dH6FiU9dWXUs2WpCXwN/WCyEA76RtH/KOqRWH+aejbXWvJv5XiwbJ3Kb0j6BUnkve9rrX2xtfb+1pp/PbskHQhtHhqOjR1fhdbaja21O1trd9r5qlAorD+WxlRaa2+RdLj3fldr7TXh1E2SDko6XdLNkt4p6T0ner/e+81Df9q7d28/RvM5sLxBlCL0VKQkyywhWU1jKa8gSD0FWQ1TIUrzaR0tYTLPV9YgpkSmjiKOxf1bWv/N3/yNpNWpBZnOgdafTM+UWYTiNS5jEcfv9bf0NmOxVI+SeCwYk88wXu/+yDaiXoTgGvr5ZmVJDPodMflXPEZLI4MSI6Ojvw6tWhk7pmcwUyG4euXxYJlM5Qcl/Whr7QFJt0q6rrX2u733R/oKnpH0O5KuHdo/LOmicP3u4djY8UKhcBJiaS+V3vtNvffdvfdLJb1N0qd77/9u0JNosPa8VdKXh0tuk/TjbQU/IOmp3vsjkj4l6XWttW2ttW2SXjccKxQKJyE2wvntf7bWzpPUJN0t6aeG43+kFXPyPq2YlN8uSb33x1trvyzp80O791hpOyVM7+nwJM1nqOd2aFHbMYVeVO76Gpo9GTwWKTtN1G5jZV/msk6KTrNxzHfi/rz1cpvdu3evulaaz2pH9/ksAz8dwLwFyfLZ0FRKxSOLosfxjW1/4liY1Y65b5l7JF5D1wHfz/PIKjl6m8XMexF0TGSgKHPkxrHQhSAr0E7XCea19Zrv2jWnvjwm1uWl0nv/jKTPDJ+vG2nTJb1j5NyHJH1oScMrFAoTYsu76T/88Ip6hk5F8a1Od3CaSKO0YAAhFZFZZniamW2Spbt4FnpPBpRl62ctXUpxmr2leZdvph+I6QKslGSNHZsjs2z3zODPcIOYe5XOgAwZYLs4JoPBjvGZsVYT18tjiv3T/M/scVmwJhmcFede67g+HpPPMVdw5trP7HzMfZtVKOQ4vQbMwXs8KDf9QqEwKbY8UzHGQsyl2Rve0s+S2BIsc+mnlBjLMC/N53Jl3tCsPrLvyYp1lEDxGHUr1B1E/QBduhlOH8fvbPcXXHCBpNXu/vHayNosta1f8JgYdhDHQt3GojEZNOn6mUVWQCc0rm1W94fs1To5r4Gfaeyb+X3N9jIGTHZEB8gsXQVZsdeYeW2l+d8Ymdai/MvHQjGVQqEwKbY8U9m/f7+k+YzwWUIh1qrJQu6ZenAsNWRWV5gaed8nk/RMlkSrQ7RuUDpT6pFdxf7oiOf7RUuR2QUTB9ESFXU2DFTz+mSSkjof61vGUghI82yMyYayZ8bQACZcytIAuF9K/iy4khY7BixGpkh9Dh0Ms2RT7ofPLqtwSZ2Z1//888+fa3u8KKZSKBQmxZZnKn4zO14oS9LMQDZK+tiW6f7IVJhoSJpJbfq4kN1kPg8cS6YzGEuIRD+MbB7cpzPRU7x+LEkzdTnx3pwH0z9G0NpDvUYcE+vXUDeR6VT8zLwOTJCUsQL65jD1ZEx6xN8E/Uji87W+xaEZTMKV/Ub4G/D6U28S+2U6Bt/3wgsv1HNFMZVCoTAp6qVSKBQmxZbf/njbQ3NkVESOuUpnkbB0z6eJl8ozaaYUozKUDm4RpPek0NlWwOA2IosidhvTYY/FbaJzmik+lZVWKmZbGiq5WZsmKxfKLQaPZ8pdIlN6053A92Z0b3wOLJjObG5ZFnqaiRe56TPbnNuwQHvm5Ej3BeadlWbrcPbZZ68av83PVFIfD4qpFAqFSbHlmYrf7s7fYWmbZTYjK6BiVZK+9rWvSZpJB0pXZvKK/bOY+CKTcub6Ho/bNBvHy+9jeU/iXJnhP5NgXrsxxTJN19K8Yx8D5bIsZcycRqe4LB+JscjEzFAE34cK7PibIFMcq7QYnwOZxKIKC3RjIGv1/CJTYdY/mrWjccDj9/h4nz179ui5ophKoVCYFFueqdik/Oijj0qaD46T5s2SzPgWJaT3qDS90hSY9U8nNDKYLFuZpSj33FFSk/Ewg5r1I1mtILZh1v7YhtUdF2U/o/T3utlsH8HKgWPrE5kc9RTUm2Q6J+pqPEbqMWIbj5/1trOqgxwbdXUxCHJRRUVpxjCinsq/CTsdsg525pLANXSbCigsFAonDbY8UzFDYW7RuOdmdTsmtIkSwAFlTEVgSeC+ovQey6LPtABZrRczCI83C9NnhnpK0cxNnFLb88gsIZa8TANgyxGd76SZ85WlK53dsjQPYxnlqWuJ4Fx9TRYwygBCj5c6Fmn2HOl677ExQZU0YzqeM9crzpm/G+qc/NzjPDxe34fJmuL4mazK1/ivAySfC2MpplIoFCbFlmcqtlxYInhPn1kqDLaJEsZ73TFfCkup6Abt/ukTYgmZpa1kpndLLvqkxDFQOjEYMYI6Ie7Box6JegO6hzsMwZXy4rjJQhgomY1lrPZNvIZ1nMeSWsXPrKTosZiRZqkbGOg3Fp4Rx2m4/0xvYibHNu4vS9HBuTMdadQzcc5+Vp5r6VQKhcJJgy3PVJgM2hIz87i01DjvvPMkzUsPaT45Myv9Gffff//Rz6wCyDGsRWfgsHzWDopjYXoEIibxYToGYlGt5izRtZRXBbSkHEvlEMdARkL2FD1HfY3PWXpbajuNqDR7nm5LKZ55QTNhNC1GTOgtzVgs2QZZWrx+rJa1Ea181OewvlBmieJzzix1x4tiKoVCYVLUS6VQKEyKLb/98fbBuTMyl+9FWckJZsan670paaTSLA7vbQhzgETnK9YgYv6TzJGNmevo1GdzeOzXClVS94MHDx5t62PMDu/7WukYt11UIjIgLzPF0qTvufL5SPNmYp/zc41z5drxGWVbYrr709ROs3E8xvv5msz5jdtz1oiKW0oqXelMGbfpDP70PE5EQWsUUykUCpNiyzMV5lxlpjNp3vWaLuCRuTD4kI5sdKiKxywRLUUsrTKTppkD7+exRannMfga//V9WY8m9sfv/rtjx46j52jiNSxdbSrPKhRawWwJmbnpc/1toh5LKxHHmTFDKQ/oJAOy5M9qNdHUazBwMasKyO9ZDR+apsn2qIiOc6Ii22sdf3P+DfjZROZ2ojgmU2mt/cehhnGhUCgcE2thKhdI+nxr7S+1Unr0U30Ku9MG44477pA0b15lTWJppoNgGoAsUMtShzV1qI+JEo4SlxKM++k4FqZqsHTKkhxlGd7j/aIjFU2aHltWz4YOWNzLs/qgNGNflsCsOxPnasbA2kAet8/HObPWje9z6NChVWOLba3boquAxxLTGFAvlTkQch5jeXMzJjCXUWcAACAASURBVERzMJNCsa/Yj1kff1dxzv5sc7qvIaN7LjgmU+m9/5KkKyT9d0k/Iem+1tqvtNZedsJ3LxQKmw5r0qn03ntr7aCkg5K+LWmbpI+11m7vvf/CMge4LFi62WJBKRWr7NmVn3tsSg9p3lGKOpSsVhCDD9k/A9Gk+SAxsoOsRhAdtFijOe75GZbP4L0sNaTHP+YElyV4ouv9V77yFUnSueeee7SNP5speNxmN0yEFe9NtudUFzH0gi79zEbv30KsH21kaSOlPKkVx0QWmKWGpG7OxzPGy+RbrJcUay051QR/Y9HC+FxxzJdKa+1nJf24pEcl/bakn++9f6u19gJJ90l6Xr5UCoXCcrAWpnKOpH/Ze38wHuy9f6e19pblDGv5sASx9GOAVpRk3nNbWrMKXXy7W3JZKjApUJaQh2HzY4lzotRjrRoGHcY9Pv0sGLBoRPbE/skoIqthFUPeJ0sQTr0CkxJF1uHx013fbb3WWboEMjcz0qxaHyv8+Rl5DV72stmO32Pi74Z1gCKT8DWs4eNrrPeRZr9Lj4VWSYaDRHiO7o++WPF6pqXMkmQfL475Uum9v3vBub8+4REUCoVNhXJ+KxQKk2LLOr8xQxrzn0ZTM5Vxpoh0/ZbGS4syo3lUdLo/mz8zZbGUmxy57WHulDgnRtTye6TqNGubJnuMWb5WKotpRs+2J14PO71dfvnlc/2bmjN6mPWK4paGCnGa5bO6Tp4bI8q9FlGR6s923uO6ZFtjg5HBdHKMY/A4mX2OvzNptu2hGdrzy+bM3/2J1PsxiqkUCoVJsWWZSqywF8Fsa/EzzcWWElEC0DzL/iwJshy4BjO1WwLHMVMi0tEpy5w2lp0/YxI0WZJ1ZLlRzWaoHM0cCmmet1LRbTJHNjrgMSguc6NfS7F7Kj25/mYNmfMbnSfHqhvGfr3uHr/bOC+sNM9mqPi1STiuqR3YvJZ8VvH5mhXRRH0i9X6MYiqFQmFSbDmmYmnAoEAGC0ZJzJyflNreV0vzOWJpBs1C+7n/ty7FUo9Z3aR5qcrMXdFcTKe0scDILLWC2zA7XVY/2vDasQ5NpjNgG6/FAw88cLStXcnpGj9mCo5ztsPa9u3b07FKM+dG34f6HuqVYv9jYRlZBUGfG8t2F39zzAZH/chjjz226nz8nLkgcO7MBkc90olg6UyltXZKa+0LrbVPDt8va619trW2r7X2B62104fjZwzf9w3nLw193DQcv7e19vplj7lQKDx3rAdT+VlJfy3Jpoxfk/T+3vutrbXfkvSTkj44/H2i9355a+1tQ7t/01q7WtLbJH23pJ2S/rS1dmXv/YQinyzVqF3PLABmAd7bHzlyRFIuIRmMZulA/UUGt/WYzFBsGYljsqSx1GMKhLjX93W06PB4luSIlRDp+i3NBwGa8XidzBLi3Kl3oS4qVhtglnuvu9eFtXCk2dr5WrMBVmuU5lkF6+dkAZcMJCQDynQqdM/3by2rfcQ5+z4M6MySQJHdMBduPOd+o+PdiWKpTKW1tlvSm7Xi3q+2shLXSfrY0OQWSW8dPl8/fNdw/keG9tdLurX3/kzv/X5J+yRdu8xxFwqF545lM5Xf0EpskF+D2yU92Xv3K/khSbuGz7skHZCk3vu3W2tPDe13Sboj9BmvOYrW2o2SbpSkiy++eHRA1qlwv8mQ7yxM3NKHNVmi1CODYA1lVguMbViXx2wjy4JO/wfuy+N8fE9agSztxoLi4jWLsq27ng/d6Z34x/eL1pOdO3dKmulZ7GqfhRCQxVAf4ONRZ8Pn6TaZmz4DCI1FKSPG0jow6VcMx/CYXBXT480Sa9HvhcGM1v+YDcbxjqXFjKEVPpaxmBPF0pjKEBd0uPd+17LuEdF7v7n3vrf3vtcLXigU1h/LZCo/KOlHW2tvknSmVnQqH5B0dmvt1IGt7JbkAiwPS7pI0kOttVMlvVTSY+G4Ea85btiWb4lIyeu9eHyrk20w8C+rEse6v9StZMl1LOWYMiBL7Oy2Y7qayD48TupdxpIFRVgCMyAysyQYTCHgNYj7dktlpn2k5SW2yeosSTmTM+hbRBYozaQ1fTbIROOc6QOSPaN4bWzjVA4M6stqKdHq4zFmKTrdH9NHsrZ1vJfZkv1epsDSmErv/abe++7e+6VaUbR+uvf+byX9uaQfG5rdIOkTw+fbhu8azn96yDB3m6S3Ddahy7SSMOpzyxp3oVA4MWyEn8o7Jd3aWnuvpC9oJaOchr//o7W2T9LjWnkRqff+V621j0r6ilYSRL3jRC0/hUJheViXl0rv/TOSPjN83q/EetN7f1rSvxq5/n2S3jfFWP72b/9W0jxNpRNTBPNqGFl2r7GaOkTmcj/mqs5i4PEznemoQIxtfR+a0b0ViNsTUn+ao7P+x+rleAuS5fOg6TQrVu7r3b9pPAMxsy0fzf4sgxrvTVOvnyUVwtLisAgpD9Cjaz1zvMT1d/90chwzwUvzpmnP1feLbenceM0112gqlJt+oVCYFFvOTZ/mwbUo/eiWz2xoUUIywI9u9IskJduQSUTWQ8Umv2dF2MkoWB8mSlXOw+NlbRlpxhg4bpp1Izujudkgc4n3ooLc82C1A2m+8iEd2bIC8F67rKKitPq3MdaW5u74nMnCPAavX1xTj5eKft4/C/fgb8/3iWZ0X+d+XLB+1645b43jRjGVQqEwKbYcU2FuUda3yfaqND/7b1Yvl2bbrLZxPC7NJLvdzimB7bCX1UfOcpSOtaXOwzoOS9msL88jOq7FscXrmCDKbdZSK8jnsuRDnov7t7MdTb3xGs+JCZiYwT6CqQjMIFgdQJrXT/m3wMp/UY9EM7FZzqJqgx4vqz74fHSY8zpx7nw+cQxmjFMwFKOYSqFQmBRbjqlQj8BKcLRySDMmQY35wYMHJa2uQzuW5Xys3nA8N7bvt0NerNvCPTatQItC2encxdrN2dgYnBbB9Ais90u38dgPg/iykAEeMxugDiEmLGItnZiegnP19V5vVlig4580YyisXmB2Q+uNNO8az6oM8Zny90MLTsY+aAFk5YPMokYr6BQoplIoFCbFlmMqDNIbk6pxz80kR5bIrGMcQR8T92cplVUQtCQcS5od9STeW3uvPWahiv1wbgzQi+yGiaPcL/fpsa11P2RJmfu/52LdA/Uwi3wqyMrIPqXVlg5pvr5QVu2R4RFjFQXj9ZT4rFsc14nPYVHlRoYBMJyBVRXjGHzO+havT/yduv8pUx4YxVQKhcKkqJdKoVCYFFti+xOzlBum3TRhMkO7NJ/ZnHQ+5vFgiVFHRft+prGR8rJ4O93Ds1KmxCL3bZqSWQsno9L+7Iha5wDJtho002bZ1aTVCm2P12kq3H/mqOW1Yj5b38eOWy6+Ls1vBRiqELcyY4py9++tZhaa4N+JfwM+bpd8K/OlmSl8LBwgKoKpkOX9/ExjdDqfs7eLWQUHPpspUUylUChMii3BVA4fPnz0MzOOW9FpM6KlR5QArIBnSZC97emCbTMwTbNRajgzOp2hmM0tSkpfP1YVMFPqun86wzG3iTSTcl4XKoQjmMGfGfL8PStWTvM27x/bUoFqdrBjx465MTEHLgMWI1OMrvTSvAnZ6xMVnf4t+JmMZa7PKi2QFbttZLwep58dFfB8/vEzGW5mUva9pyjIThRTKRQKk2JLMJX4NqbOgXoSM4ooKcdyu2aBbLyGzmi+f2QS1lswWI+BelFScs9Np7rYv1kGWRRN1tH8aUlGvYKloXVF8ZzHZOnMLPuZHon1frIcu9TReGy+L02ncZw017MyQnZPhgVY1xKvcT9kmTy/yJzu8fq+MTObdTJkNTTpx/AJ9+Ox+Ll6LFmKjkXVHZ4riqkUCoVJsSWYii0L0nyCIubqpJZdmkmLscRFEczLOlaHOdPHcG9N9pFl4GfVu2xsrPHCEIVMz8PM+KxQGC0VlLx0P//a174mSbr88suPXsP6ynT4i5LfFQQ5Xktv/83c0ONzlOZTUXDecUwMiIz6CybWYnIuJvSS5tkwHRbj8+W4WZHAzzuOnVZEPrv4m/PnbJwnimIqhUJhUmwJphJ1EX6LWxKMWTXiXpP6F+65o/6CYQD0LRlLuhPP0UU7s/4wnSFd8KPUpmWI0trn4zUMLuRePgvI43ocOnRI0oxpRN8T1pb2GKyjyOou0b09078YZEC0IMVrqM9h2kePO/o70S/Ikp9WrQimreS6RSsU52aGYtaRWX/82yMjNRuJ7G9RgOiJophKoVCYFFuCqUSpwYAyemvaohClBmv10r8gq0FMNuD7UDcRr6dnJZlFlo6B1o2M1VhSUVdjSckE1fF61plhbRxpPlkS0w24LnK8ht69rOiXBSyy/hLvl7EDWoF4PILJqpkWI1q8zL7sJWsW4zlTXxLnysBF1nKOYzGTYGChWVT8nZLJMe1pTOdp1nLVVVfNrcOJophKoVCYFPVSKRQKk2JLbH/iVsMUkDkymOU+M7XR9EgHN2lGf1n2lIq32BcVhcx67/6zHCkMdswyvnlOdLZiXtUYkOfwAlP+RflO9+/fL0m6+uqrJc3nl2FWtHhPg0GU0aQ6lmeG4QHxOfheDOSkuThe560X8xgzf4s0e86eq9eJDmdZtnsbB/w8shy+3KJSMZ9VQGBb/s1y+CwDxVQKhcKk2BJMJeZ2pUKWLIHKs3jOyi2mUohmOUumsQqIWRYxYywcIGtLhkKWE6USKxwy652VjVGRx0oB/p4pja+88kpJM8nLnL5ZXRuvIc3QdO6K42UlQt+HCud4jVkBC5rHNWX/ZHte26zaADPVua3vmylfGV6QuSbwOdJ5MnNYZCUHZteP/WcuDVOhmEqhUJgUW4KpWBJLs1rKrPHiNzfd+KX5Gr6sGRTf+nSJd/+UkFHqUf9CXQrHIc0kGRMXuf8obSn9fS1z7GaZ7Blyn4XKU48wFrAYTbK+p1kk9RrRuY75WT0P9+G5xzQDXlMmosoqBvCYJf4jjzyy6tr4m6CujOvjNc/cAMh4mH4jgvodhnfEcAPWsPa46ZogrQ6OnBrFVAqFwqTYEkwlWiNofaFVJnPuGkuUw/rC0rwrNvfAWf9j1zLYMXPJph7DiCyHDmVkBVmQHUMRWBsnWmdYt4bOapbEUbflz0yAlQVEkgmxomKW+sCgtLZeLLYly2CSKc8rc/jjfdxXpvPwOmUVDzhnJlzymBZVfdi+ffuqfvm7jVbQnTt3alkoplIoFCbFpmYq9p+IUntMq06/grjntMTK9CH8PhZsSD1DJvWsc2DqgKxuC+sJ0VU99s/6OJ4bQxUW+S5wfaJ1JlqN4hxZeyfqPBxs6OfguWV+PAzK9DgznZbhOVrfYrZ05MgRSastdtSnMTVEBupUvLZMdZn5hpBdZuyMz5U+OvwurU7yFNeAehkpTwY/FYqpFAqFSVEvlUKhMCk29fbH9WCiUpF0m9sFU1Rm3orIlHA8xxwZjLCNWzLWAvI1rhmTubm7Hys8Gf2c5UZhrljT5SyjvSm5KTPpfJajhlsOKnCjydRUn45gmdmVTl0G6/REek+zs+fsXCkRftZUjhpZRDDXklHF2Zj9HMZyosTtDyOMWa+I9YDimDg2r0Hcjr7yla+cW4epUEylUChMik3NVHbt2iVptYSku7PB7PTZOSrW6N4dr6cp0JL4ySeflLRaqlLJRwc6XxMlpVmGlcg0F0fnN0sqhgiw2l1UKjLXLl38owRmLlfPzZLSps5ohrXi1G0tmT3WTGlpSetx01kwPmeyDuaMic+ZjJOskvOL11MpTTYVf2ecG39XEV4zP3vWgmJFAWmmCHcb1rbKqj4sA8VUCoXCpFgaU2mtnSnpf0s6Y7jPx3rv726tfVjSD0uyJ9RP9N7vbiuv1Q9IepOkbw7H/3Lo6wZJvzS0f2/v/Za1jMFZ3GNuTksfSx1m6CILGe4vaSYJmQ0tSiOajJnNzd+j4xMD8CxNzW4saaI7ufuhY5ilbtR5MAiQbIwu/3FOnI/XILImBqwx7CDLzEb3fAY9ZqEPDNqjQ15kCTSB01ktMkUyEbOEBx98UNJMDxPZn+fIzPU0b0fGxXpObsusfXFuY7/LLByD60OXhMjIrG80m58Sy9z+PCPput77N1prp0n6v621Px7O/Xzv/WNo/0ZJVwz/XiXpg5Je1Vo7R9K7Je2V1CXd1Vq7rfe+PEN7oVB4zljaS6WvvEq9yT1t+LcoM8z1kj4yXHdHa+3s1toOSa+RdHvv/XFJaq3dLukNkn5/DWOQtHovbOcnv+FZR9dv9UxnQImSVQdkTRqmL7CUypy7uE+3lLVUjToDsxifo+SPYEjCWHWALCu9+/fenZnmY//MGes5Z67xlrjMb+u+osMbnfPMqGghMaOTZuyJiZxYDzvrx3Pjs4pz9vP1M3nooYckzapNeiz8fUnzrJL3jeviY37e/C1G9kdnN8+LAaTSchiKsVSdSmvtlNba3ZIOa+XF8Nnh1Ptaa19srb2/tWb+tkvSgXD5Q8OxseOFQuEkxFKtP733ZyV9b2vtbEkfb629QtJNkg5KOl3SzZLeKek9J3qv1tqNkm6UpIsvvljS7A2d1ai1hKHFJQvUYtAbgwOjSz8tOQb1MHFPT78Xavqz2iyWoqxx7L5imgHPlSEDtFhktYgZxsBM89JMIjKxEwPyoh6JLuVka1nqTIP6iyx147HCGOJcPSdbT2gV43OR5p+ZU3GyZvYi3x+zpUynxYoEZMWea/ydMpyBfjxZ2odlYF2sP733JyX9uaQ39N4f6St4RtLvSLp2aPawpIvCZbuHY2PHeY+be+97e+97zzvvvGVMo1AorAHLtP6cJ+lbvfcnW2tnSfoXkn6ttbaj9/7IYO15q6QvD5fcJulnWmu3akVR+9TQ7lOSfqW1ZtH7Oq2wnVE8++yzeuKJJ+ZSFEjzUtTfs72vkWnnpbxejiUJa+v6PlnyHksbsw/qR7KQfgeEcV9uiZbVgh5Ly0BP3niMFRd9revexLlSP0LP1AjPlZ6vfmaZH4/XnwFymVWLtZNo9cusP743/VbsKxLnwzbUsy2yqDHo0M/KFpl4jsGsHH+cs1krKxN6ftEKukwsc/uzQ9ItrbVTtMKIPtp7/2Rr7dPDC6dJulvSTw3t/0gr5uR9WjEpv12Seu+Pt9Z+WdLnh3bvsdK2UCicfFim9eeLkv5pcvy6kfZd0jtGzn1I0ocmHWChUFgKNrWbvpWVzjUqzSuz6IDE7/Ezg/Yy93YGc9GNm6bT2D9Nm6arWX4PjsnI3OiZ+4N1bEy1o8Ocx+JrF+U7ZX8MIMwUzV4fX+M50uydjZsF5R999FFJ0oEDMyPhK17xCknzLvzMMBfHwNCEbNtpsIYSHehoxo9z4ph8f5ujI7itYna3LEM+cyiP5bdZFspNv1AoTIpNyVROOeUUbdu2bZUy0aDilMrELKDQsASwRKcSU5qvcZOZO+Px+DlTUsa+otTzPceKfi/KzMaqeplEtumdZvmMnZH9MVWDpbgVnlJe6yZ+z8IYDFYQsEk/MrmxSgFcpwjWQ2L4RNaWz9fPztdmTIX9sfpjvJ6s2HPOlMp0yKObwRVXXDE3j2WgmEqhUJgUm5KpPP3007r33nvnJFoE6wvTXBwlvd/4zOKeBWr5XnSjHgsQk2YOTr6WTlH333+/pNl+Ot7TbWkij2HuND+yKmOWdIrHyJ5iW68LAx/JciLjoFmbZujYP13TvXaW1vZLevnLX370GprumdoiM+n7GuogbPLNWEcW2hCvifBvjnq1jHUwKJBr6ueR1c6+8MILJc10iW4T89JG58ipUUylUChMik3JVFprOu20047qEqI+w29tpnVk7ZhoCXFbn7P0uOCCC+baWhrZgS3qTuL3uH+m1YT1YHyfKBXNWqw3smTMJBfTGNCFPAujH0uaxPpIcdxMI8EUDjEgkomWzKzooBfb+j5mEF4DjzEyCbIAj5eu63HeTGJEi1Fcf6aToNVvUa1sWoboth/Hy/u5fzPT2M79HD58eNWY1mLNmhLFVAqFwqTYlEzl1FNP1bZt21Krg9/WZjGWDv5uqRT3/5Ry7sNSI0pIMxQG4tEdPYIV/OiDkqUqtP7FUsjWGtauiXP58pdXIiK+53u+Z9XcPaZoJWIaBrc1E8sSLrO2sRmKr3Ed6zgXj5N6nmi58/r4L3VbZgvWJUgz3xUmjM4Sg1NPwSDTzLXfx8YSYJOVxP7oPp+lMRirs0RWE397DFb1GB3s6L/LRjGVQqEwKTYlU3nmmWe0f//+uT1rBBMTkUnEvao/00qwKGCOPgljyZqleT8SshxKWWneWuUxZZLYEvDqq6+WNJ8GgGVEpHnvUku5zJJGXYQtC76WpUbinCjZmWJBmj0/M06ySUtoplOQ5v2DMt8TWlb4vI3M0sMk04uSZdMfhd63UedBfyDqarLUCobXwX5Ctvos0+ITUUylUChMinqpFAqFSbEptz+GaW1M2mRqaOppKp1liTdMH8855xxJ83VoIlWnWzgpNYPhpJl50IpauoDTPBqvp0mT84rnaCL1+vB4vLfhe/u+0bmLlQMYIOc1yXLUMletsXv37rmxUCnqLYCdB6MSnOZ/b6Eyh0hmrKMbPZ0R4zXZdlPKqxqwEiRN2fG3R7cC/hboTBnHwOd95ZVXaj1RTKVQKEyKTclUWms69dRTj5pZo0l5zDxsNpO5lDP7liWC28Ys7gxUZGZ5S84sn6rHQHM3c8DGcY+ZfKO0pQMbzdruNzNDs9Kfx212EMHqeUxvECW95+y1feyxxyTNB2TG+Xt8Y45m8ZmN1SnOTO6+l5kDleoeU/wdMY8tM/1l9YsNKnWzCg5MNUF3fYZpxH4Y9hHHvR4oplIoFCbFpmQqZ511lq655hrt379f0uq9KqvExSAraeawFZmEWQ2lhL9HyU9zMPOnMo9rhKU13ecZth+vZ+0eI8vX6jmTTdG9PvZLdsOQ/HiO0ppm+mjap5nY8zl06JCk1RUKyMY8bh+nLieuh4/Zdf2yyy6TtFqnwgRdhn83Wa1jpsGgaZdOfdl9PB/PNas1RQdL1uiOrglmKP4dLQo6XCaKqRQKhUmxKZmKsWfPnmO2YU1Zf4/Bb5ZUrs1sXY3bRglMi5AlsdswTWM8Z2lE3U1WCZEpIi1Vs+RHY850/m6dULTo+F52mKIeJjrf7dy5U9JMQlLiZ1KVegzWuYnWD89trIYPUzpkxy66aKXKi5lplvqA1h8y0axuMUMp/NzpEBjBFJRZCk1azGgBYwWD7JzXO2Nay0QxlUKhMCk2NVNZC1hTdlGNWTIfJ1dehHvuuUfSzMphtmPpLs2kjdmRv9NSERkRUwZaMlpKxbaWzm7rc2YAtmJFSe+2tkTRJT4yIbvhM0m2pStr/MZzDDcgc+G4sjl7LJmeim7/TJcgzeuUaPnKUmg64NGslYnOrb/KKi2yIiRZiDSvfyGb5XFpXidH69J6oZhKoVCYFPVSKRQKk2LLb3+WjWuuuWbV97UojwmbxmM08969e1edY+a3qGh2nhFTcVN1f/fWLCoKvSWwQ57zk7htZkZnPRtHNruvGEXs7YFBF/OoFPU5Orl5zt5uxa0U85B4C+DjUenNPC1U0HrbErcavqf78RrQvB23fG7Dv16LaOb2Pak85tYmmtHHak5ZSb1eKKZSKBQmRTGV5wEWsZtXvvKVa+6Hjn42iVvaRnduK6zNBqxYtlI2Ki0taZmb1uzATCAyIZ/zNT7HjHaxP+axZV+ZyZ0Oc8xhIs0YG8dkNuK/kSlSKUyWk+Vk8fi9XmZ0vl82JrelcjfrnzWrGLqxXiimUigUJkUxlS0EZv56LpnA7r33Xkm5mZI1iFhvJkp3p3lgCgdL5qiLYGgF9Rg2pUY9jKWz7+1zviZLM0D3f4/JDC6rdcSAQjOVrOqA4bnR1T+Ofyz9BXVOUbflcTN0Y70yvhnFVAqFwqQoplI4Llx11VXHfc0ih0Jn+Ldkt/Q+cuTI0TaW2syQn1m6jAMHDkiaOaeZmTDoTprPZs8wAFZ/jOfoju/jbhuDBM20rJthwGLGOljf2XPO6jJ7XViVYb1RTKVQKEyKYiqFDcVYqMPxMCLreSJjoV7H/ja2XtFPRhpPikW9T+yX1RjMINx/9M0x+2DYAlNFSOO1jcg+op6HvkpOf7reKKZSKBQmRTGVwvMex8Nq1hIEav8d62UY+CfNdDWsaWTWYX+YmGrUoGdwVn+ZtavNOqwvyfQ8TB+xUSimUigUJkW9VAqFwqSo7U+hANgEvsgUbjBglCVGvZWSZtschgP4e8y94py6rEvFXMRZSV/mmVlvFFMpFAqTophKoTAh6BK/FrazCGY+DDcg64mfHVaw3u75RjGVQqEwKRrrlWwGtNaOSHrwGM3OlfToOgxnGaixbwxq7KtxSe/9PB7clC+VtaC1dmfvfe9Gj+O5oMa+Maixrw21/SkUCpOiXiqFQmFSbOWXys0bPYATQI19Y1BjXwO2rE6lUCgsB1uZqRQKhSWgXiqFQmFSbJqXSmvtzNba51pr97TW/qq19p+H45e11j7bWtvXWvuD1trpw/Ezhu/7hvOXhr5uGo7f21p7/QaO/cOttftba3cP/753ON5aa785jPGLrbXvC33d0Fq7b/h3w7LHHu57SmvtC621Tw7fT/p1XzD259O6P9Ba+9IwzjuHY+e01m4fxnJ7a23buo6/974p/klqkl40fD5N0mcl/YCkj0p623D8tyT9h+HzT0v6reHz2yT9wfD5akn3SDpD0mWSvirplA0a+4cl/VjS/k2S/ni47gckfXY4fo6k/cPfbcPnbeu0/j8n6fckfXL4ftKv+4KxP5/W/QFJ5+LYr0t61/D5XZJ+bT3Hv2mYSl+B8wmeNvzrkq6T9LHh+C2S3jp8vn74ruH8j7SV3H3XS7q19/5M7/1+SfskXbtBYx/D9ZI+Mlx3h6SzW2s7JL1e0u2998d7O5FnFAAAA1BJREFU709Iul3SG5Y5dklqre2W9GZJvz18b3oerHs29mPgpFr3Y4zTa8y1X/r4N81LRTpKY++WdFgrC/NVSU/23p3Y8yFJjvDaJemAJA3nn5K0PR5Prlm3sffePzucet9AVd/fWnNhmLExbsjYJf2GpF+Q5NRo2/U8WXfNj914Pqy7tCJ8/qS1dldr7cbh2AW990eGzwclXTB8Xpfxb6qXSu/92d7790rarRUp9/INHtKawbG31l4h6SatzOH7tUJN37mBQ0zRWnuLpMO997s2eizHiwVjP+nXPeCHeu/fJ+mNkt7RWvvn8WRf2d+sq9/IpnqpGL33JyX9uaR/phWK5xQPuyU5a87Dki6SpOH8SyU9Fo8n1ywdYexv6L0/MlDVZyT9jmbbgbExbsTYf1DSj7bWHpB0q1a2PR/Q82Pd58beWvvd58m6S5J67w8Pfw9L+rhWxnpo2NZo+Ht4aL4+418PZdJ6/JN0nqSzh89nSfo/kt4i6Q+1WmH408Pnd2i1wvCjw+fv1mqF4X4tX1E7NvYdw7GmFZr+q8P3N2u1wu1zfaZwu18ryrZtw+dz1vEZvEYzZedJv+4Lxv68WHdJL5T04vD5L7SiC/mvWq2o/fX1HP+6PLB1+lH8E0lfkPRFSV+W9J+G43skfU4rir8/lHTGcPzM4fu+4fye0NcvakUfc6+kN27g2D8t6UvDsd/VzELUJP23YYxfkrQ39PXvhzntk/T2dX4G8T/mSb/uC8b+vFj3YY3vGf79laRfHI5vl/Rnku6T9Kd+QazX+MtNv1AoTIpNqVMpFAobh3qpFAqFSVEvlUKhMCnqpVIoFCZFvVQKhcKkqJdKoVCYFPVSKRQKk6JeKoUNQ2vt+4egvTNbay8ccsm8YqPHVTgxlPNbYUPRWnuvVrxsz5L0UO/9v2zwkAoniHqpFDYUQ0a4z0t6WtKre+/PbvCQCieI2v4UNhrbJb1I0ou1wlgKz3MUUylsKFprt2kl7cBlWokO/pkNHlLhBHHqsZsUCstBa+3HJX2r9/57rbVTJP1Fa+263vunN3psheeOYiqFQmFSlE6lUChMinqpFAqFSVEvlUKhMCnqpVIoFCZFvVQKhcKkqJdKoVCYFPVSKRQKk+L/A+ovGSH4KILSAAAAAElFTkSuQmCC\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "NBINS = (100,100)\n", - "\n", - "img_zero, xedges, yedges = np.histogram2d(evt_data['y'][ii], evt_data['x'][ii], NBINS)\n", - "\n", - "# This array describes how to map the position of the 2D array containing the image\n", - "# to the x and y positions on the sky\n", - "extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n", - "\n", - "plt.imshow(img_zero, extent=extent, interpolation='nearest', \n", - " cmap='gist_yarg', origin='lower', norm=LogNorm())\n", - "\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Gggs4qvFcpOG" - }, - "source": [ - "## Close the FITS file" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "KNYSKxLucpOG" - }, - "source": [ - "When you're done using a FITS file, it's often a good idea to close it. That way you can be sure it won't continue using up excess memory or file handles on your computer. (This happens automatically when you close Python, but you never know how long that might be...)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "AI8mrIGWcpOG" - }, - "outputs": [], - "source": [ - "hdu_list.close()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cwSittwlcpOG" - }, - "source": [ - "## Exercises" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "zX5Gr3CdcpOH" - }, - "source": [ - "Make a scatter plot of the same data you histogrammed above. The [plt.scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) function is your friend for this. What are the pros and cons of doing it this way?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "haxhlHMIcpOH", - "outputId": "22fd37cb-a934-4296-dfea-7872324e18ad", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 265 - } - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "energy_scatter = plt.scatter(evt_data['x'][ii], evt_data['y'][ii], s=1, alpha=0.1, color='b')" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "84C-9XGUcpOH" - }, - "source": [ - "Try the same with the [plt.hexbin](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hexbin) plotting function. Which do you think looks better for this kind of data?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "s-aWczHzcpOH", - "outputId": "5d50aeba-7cc1-479b-e88b-bb9720c329fe", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 265 - } - }, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "energy_hex = plt.hexbin(evt_data['x'][ii], evt_data['y'][ii], norm=LogNorm())" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sB7gbTBBcpOH" - }, - "source": [ - "Choose an energy range to make a slice of the FITS table, then plot it. How does the image change with different energy ranges?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "Hq1VDm35cpOH", - "outputId": "041e1abe-28c3-4209-9454-609aea4786a3", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 296 - } - }, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "Text(0, 0.5, 'y')" - ] - }, - "metadata": {}, - "execution_count": 44 - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" - }, - "metadata": { - "needs_background": "light" - } - } - ], - "source": [ - "NBINS = (100,100)\n", - "ii = (evt_data['energy'] > 3500) & (evt_data['energy'] < 5000)\n", - "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS,\n", - " cmap='viridis', norm=LogNorm())\n", - "\n", - "cbar = plt.colorbar(ticks=[1.0,3.0,6.0])\n", - "cbar.ax.set_yticklabels(['1','3','6'])\n", - "\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')" - ] - }, - { - "cell_type": "code", - "source": [ - "" - ], - "metadata": { - "id": "uFehWSaZsLrV" - }, - "execution_count": null, - "outputs": [] - } - ], - "metadata": { - "astropy-tutorials": { - "author": "Lia R. Corrales ", - "date": "January 2014", - "description": "astropy.utils.data to download the file, astropy.io.fits to open and view the file, matplotlib for making both 1D and 2D histograms of the data.", - "link_name": "Viewing and manipulating data from FITS tables", - "name": "", - "published": true - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.12" - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Mb0-v-tzcpN6" + }, + "source": [ + "# Working with Chandra FITS tables\n", + "\n", + "## Authors\n", + "Lia Corrales, Kris Stern, LĂșthien Liu, Zihao Chen, Saima Siddiqui\n", + "\n", + "## Learning Goals\n", + "* Download a Chandra FITS table file from a URL \n", + "* Open a Chandra FITS table file and view table contents\n", + "* Make a 2D histogram with the event list data\n", + "* Close the FITS file after use\n", + "\n", + "## Keywords\n", + "FITS, file input/output, table, numpy, matplotlib, histogram\n", + "\n", + "\n", + "## Summary\n", + "\n", + "Chandra image data is stored in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n", + "\n", + "In this tutorial, we will use `astropy.utils.data` to download a Chandra FITS file, then use `astropy.io.fits` and `astropy.table` to open the file. Lastly, we will use `matplotlib` to visualize the Chandra event list as a histogram, effectively producing an X-ray image of the sky." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vfrMqJd9cpN9" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from astropy.io import fits\n", + "from astropy.table import Table\n", + "from matplotlib.colors import LogNorm\n", + "\n", + "# Set up matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IexsOCvKcpN-" + }, + "source": [ + "The following line is needed to download the example FITS files used in this tutorial." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "0zp1lvcEcpN_" + }, + "outputs": [], + "source": [ + "from astropy.utils.data import download_file" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6u1ChU47cpN_" + }, + "source": [ + "FITS files often contain large amounts of multi-dimensional data and tables. \n", + "\n", + "In this particular example, we'll open a FITS file from a Chandra observation of the Galactic Center. The file contains a list of events with x and y coordinates, energy, and various other pieces of information." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "r6F-JgTCcpN_" + }, + "outputs": [], + "source": [ + "event_filename = download_file('http://data.astropy.org/tutorials/FITS-tables/chandra_events.fits', \n", + " cache=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "me6HB0RrcpOA" + }, + "source": [ + "## Opening the FITS file and viewing table contents" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Cp_kqCg4cpOA" + }, + "source": [ + "Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "2ABOyWmxcpOB" + }, + "outputs": [], + "source": [ + "hdu_list = fits.open(event_filename, memmap=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "yEuBPS8ycpOB", + "outputId": "8bc4c565-e09c-4de0-d99b-1d05fcfb00a3" + }, + "outputs": [], + "source": [ + "hdu_list.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FCoyC8sIcpOC" + }, + "source": [ + "In this case, we're interested in reading EVENTS, which contains information about each X-ray photon that hit the detector." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "kTHnKQPicpOC" + }, + "source": [ + "To find out what information the table contains, let's print the column names." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { "colab": { - "name": "FITS-tables.ipynb", - "provenance": [], - "collapsed_sections": [] - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} \ No newline at end of file + "base_uri": "https://localhost:8080/" + }, + "id": "CfQyzNPNcpOC", + "outputId": "244569b7-9235-43e1-f471-d0789a538b0a" + }, + "outputs": [], + "source": [ + "print(hdu_list[1].columns)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YpH2-4qPcpOC" + }, + "source": [ + "Now we'll take this data and convert it into an [astropy table](http://docs.astropy.org/en/stable/table/). While it's possible to access FITS tables directly from the ``.data`` attribute, using [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) tends to make a variety of common tasks more convenient." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "n7zMyhRhcpOD" + }, + "outputs": [], + "source": [ + "evt_data = Table(hdu_list[1].data)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sEmGEMR1cpOD" + }, + "source": [ + "For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "c00cCz9McpOD", + "outputId": "86eda857-3fff-4960-f488-477ee510a85c" + }, + "outputs": [], + "source": [ + "evt_data" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "86Qa6PUucpOD" + }, + "source": [ + "We can extract data from the table by referencing the column name. Let's try making a histogram for the energy of each photon, which will give us a sense for the spectrum (folded with the detector's efficiency)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "9YkZY2wqcpOE", + "outputId": "8422589a-217b-4b12-b9d0-d9f8520b0c0c" + }, + "outputs": [], + "source": [ + "energy_hist = plt.hist(evt_data['energy'], bins='auto')\n", + "plt.xlabel('Energy (eV)')\n", + "plt.ylabel('Number of photon events')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Zd7bVk4IcpOE" + }, + "source": [ + "## Making a 2D histogram with some table data" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E8U-se8zcpOE" + }, + "source": [ + "Next we'll make an image by binning the x and y coordinates of the events into a 2D histogram. \n", + "\n", + "A one dimensional histogram, as shown above, shows the number of events within each bin corresponding to one axis of information. In the plot above, we chose histogram bins in the energy, shown on the x-axis.\n", + "\n", + "A two dimensional histogram finds the number of events binned according to two dimensions. To make an image, we will bin the number of events by x and y position on the sky." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cEqsE2U1cpOE" + }, + "source": [ + "This particular observation spans five CCD chips. First, we determine the events that only fell on the main (ACIS-I) chips, which have number ids 0, 1, 2, and 3. We can do this by creating an array of True and False values (`ii` below) to filter out events that only fall on those chips." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Mb4RHcJLcpOE" + }, + "outputs": [], + "source": [ + "ii = np.isin(evt_data['ccd_id'], [0, 1, 2, 3])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2z9PQUh9cpOF" + }, + "source": [ + "### Method 1: Use hist2d with a log-normal color scheme" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UQwNh3ppn6c_" + }, + "source": [ + "We can make a 2D histogram plot directly with the function `matplotlib.pyplot.hist2d`, as shown below.\n", + "\n", + "In this example, we choose the `matplotlib` color map named \"viridis\", and we choose to distribute the colors logarithmically using `matplotlib.colors.LogNorm()`.\n", + "\n", + "To see what colormaps are available with `matplotlib`, see http://wiki.scipy.org/Cookbook/Matplotlib/Show_colormaps\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "tjB8Rxa1cpOG", + "outputId": "c97a7a5d-972d-451c-f5ea-a92454983570" + }, + "outputs": [], + "source": [ + "NBINS = (100,100)\n", + "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS, \n", + " cmap='viridis', norm=LogNorm())\n", + "\n", + "# Show the color bar scale next to the plot. The color corresponds to number \n", + "# of photon events (counts) in each pixel.\n", + "cbar = plt.colorbar(label='Counts')\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zUYM11V5cpOF" + }, + "source": [ + "### Method 2: Use numpy to make a 2D histogram and imshow to display it" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fh5bDy-gcpOF" + }, + "source": [ + "When we plot with `matplotlib.pyplot.hist2d`, it forces the plot into the default figure size, which could cause your image to appear stretched. \n", + "\n", + "By using `matplotlib.pyplot.imshow`, we can avoid stretching the image. To do that, we need to make a 2D array containing the number of counts per pixel bin using `numpy.histogram2d`, as shown below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "hw-xj7pdcpOF", + "outputId": "5b992c7f-5797-45d1-984b-6d3b4f608faa" + }, + "outputs": [], + "source": [ + "NBINS = (100,100)\n", + "\n", + "img_zero, xedges, yedges = np.histogram2d(evt_data['y'][ii], evt_data['x'][ii], NBINS)\n", + "\n", + "# This array describes how to map the position of the 2D array containing the image\n", + "# to the x and y positions on the sky\n", + "extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n", + "\n", + "plt.imshow(img_zero, extent=extent, interpolation='nearest', \n", + " cmap='gist_yarg', origin='lower', norm=LogNorm())\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Gggs4qvFcpOG" + }, + "source": [ + "## Close the FITS file" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KNYSKxLucpOG" + }, + "source": [ + "When you're done using a FITS file, it's often a good idea to close it. That way you can be sure it won't continue using up excess memory or file handles on your computer. (This happens automatically when you close Python, but you never know how long that might be...)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "AI8mrIGWcpOG" + }, + "outputs": [], + "source": [ + "hdu_list.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cwSittwlcpOG" + }, + "source": [ + "## Exercises" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zX5Gr3CdcpOH" + }, + "source": [ + "Make a scatter plot of the same data you histogrammed above. The [plt.scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) function is your friend for this. What are the pros and cons of doing it this way?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + }, + "id": "haxhlHMIcpOH", + "outputId": "22fd37cb-a934-4296-dfea-7872324e18ad" + }, + "outputs": [], + "source": [ + "energy_scatter = plt.scatter(evt_data['x'][ii], evt_data['y'][ii], s=1, alpha=0.1, color='b')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "84C-9XGUcpOH" + }, + "source": [ + "Try the same with the [plt.hexbin](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hexbin) plotting function. Which do you think looks better for this kind of data?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + }, + "id": "s-aWczHzcpOH", + "outputId": "5d50aeba-7cc1-479b-e88b-bb9720c329fe" + }, + "outputs": [], + "source": [ + "energy_hex = plt.hexbin(evt_data['x'][ii], evt_data['y'][ii], norm=LogNorm())" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sB7gbTBBcpOH" + }, + "source": [ + "Choose an energy range to make a slice of the FITS table, then plot it. How does the image change with different energy ranges?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 296 + }, + "id": "Hq1VDm35cpOH", + "outputId": "041e1abe-28c3-4209-9454-609aea4786a3" + }, + "outputs": [], + "source": [ + "NBINS = (100,100)\n", + "ii = (evt_data['energy'] > 3500) & (evt_data['energy'] < 5000)\n", + "img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS,\n", + " cmap='viridis', norm=LogNorm())\n", + "\n", + "cbar = plt.colorbar(ticks=[1.0,3.0,6.0])\n", + "cbar.ax.set_yticklabels(['1','3','6'])\n", + "\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uFehWSaZsLrV" + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "astropy-tutorials": { + "author": "Lia R. Corrales ", + "date": "January 2014", + "description": "astropy.utils.data to download the file, astropy.io.fits to open and view the file, matplotlib for making both 1D and 2D histograms of the data.", + "link_name": "Viewing and manipulating data from FITS tables", + "name": "", + "published": true + }, + "colab": { + "collapsed_sections": [], + "name": "FITS-tables.ipynb", + "provenance": [] + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} From 52d5e78757091c534b1ebf26cfe6671590fa0d5f Mon Sep 17 00:00:00 2001 From: Lia Corrales Date: Fri, 22 Jul 2022 13:44:32 -0400 Subject: [PATCH 04/10] Update tutorials/FITS-tables/FITS_tables.ipynb Co-authored-by: Matt Craig --- tutorials/FITS-tables/FITS_tables.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb index b0c276dd..df642d8f 100644 --- a/tutorials/FITS-tables/FITS_tables.ipynb +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -23,7 +23,7 @@ "\n", "## Summary\n", "\n", - "Chandra image data is stored in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n", + "Chandra image data is stored as a table in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n", "\n", "In this tutorial, we will use `astropy.utils.data` to download a Chandra FITS file, then use `astropy.io.fits` and `astropy.table` to open the file. Lastly, we will use `matplotlib` to visualize the Chandra event list as a histogram, effectively producing an X-ray image of the sky." ] From 09c5f8f7e29b5dd333bf47b5db66425eea0fa85d Mon Sep 17 00:00:00 2001 From: luthienliu Date: Sat, 6 Aug 2022 16:35:08 -0400 Subject: [PATCH 05/10] FITS-tables.ipynb --- tutorials/FITS-tables/FITS-tables.ipynb | 1 + 1 file changed, 1 insertion(+) create mode 100644 tutorials/FITS-tables/FITS-tables.ipynb diff --git a/tutorials/FITS-tables/FITS-tables.ipynb b/tutorials/FITS-tables/FITS-tables.ipynb new file mode 100644 index 00000000..9c35f26b --- /dev/null +++ b/tutorials/FITS-tables/FITS-tables.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","metadata":{"id":"Mb0-v-tzcpN6"},"source":["# Working with Astronomy Data using FITS tables\n","\n","## Authors\n","Lia Corrales, Kris Stern, LĂșthien Liu, Zihao Chen, Saima Siddiqui\n","\n","## Learning Goals\n","* Download a FITS table file from a URL \n","* Open a FITS table file and view table contents\n","* Make a 2D histogram with the event list data\n","* Close the FITS file after use\n","\n","## Keywords\n","FITS, file input/output, table, numpy, matplotlib, histogram\n","\n","\n","## Summary\n","\n","Chandra image data is stored in FITS files, frequently referred to as \"event lists\". Any time a photon interacts with the detector, the position, time, and energy of the photon (referred to as an \"event\") is stored. Thus Chandra event lists are stored as table data, where the position and energy information is stored in the columns and each row corresponds to a separate photon interaction.\n","\n","In this tutorial, we will use `astropy.utils.data` to download a Chandra FITS file, then use `astropy.io.fits` and `astropy.table` to open the file. Lastly, we will use `matplotlib` to visualize the Chandra event list as a histogram, effectively producing an X-ray image of the sky. The data we are downloading has several tables, so we need to go through several steps to find and open the table we want."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"vfrMqJd9cpN9"},"outputs":[],"source":["import numpy as np\n","from astropy.io import fits\n","from astropy.table import Table\n","from matplotlib.colors import LogNorm\n","\n","# Set up matplotlib\n","import matplotlib.pyplot as plt\n","%matplotlib inline"]},{"cell_type":"markdown","metadata":{"id":"IexsOCvKcpN-"},"source":["The following line is needed to download the example FITS files used in this tutorial."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"0zp1lvcEcpN_"},"outputs":[],"source":["from astropy.utils.data import download_file"]},{"cell_type":"markdown","metadata":{"id":"6u1ChU47cpN_"},"source":["FITS files often contain large amounts of multi-dimensional data and tables. \n","\n","In this particular example, we'll open a FITS file from a Chandra observation of the Galactic Center. The file contains a list of events with x and y coordinates, energy, and various other pieces of information."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"r6F-JgTCcpN_"},"outputs":[],"source":["event_filename = download_file('http://data.astropy.org/tutorials/FITS-tables/chandra_events.fits', \n"," cache=True)"]},{"cell_type":"markdown","metadata":{"id":"me6HB0RrcpOA"},"source":["## Opening the FITS file and viewing table contents"]},{"cell_type":"markdown","metadata":{"id":"Cp_kqCg4cpOA"},"source":["Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"2ABOyWmxcpOB"},"outputs":[],"source":["hdu_list = fits.open(event_filename, memmap=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yEuBPS8ycpOB","executionInfo":{"status":"ok","timestamp":1654881155348,"user_tz":240,"elapsed":189,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"8bc4c565-e09c-4de0-d99b-1d05fcfb00a3"},"outputs":[{"output_type":"stream","name":"stdout","text":["Filename: /root/.astropy/cache/download/url/333246bccb141ea3b4e86c49e45bf8d6/contents\n","No. Name Ver Type Cards Dimensions Format\n"," 0 PRIMARY 1 PrimaryHDU 30 () \n"," 1 EVENTS 1 BinTableHDU 890 483964R x 19C [1D, 1I, 1I, 1J, 1I, 1I, 1I, 1I, 1E, 1E, 1E, 1E, 1J, 1J, 1E, 1J, 1I, 1I, 32X] \n"," 2 GTI 3 BinTableHDU 28 1R x 2C [1D, 1D] \n"," 3 GTI 2 BinTableHDU 28 1R x 2C [1D, 1D] \n"," 4 GTI 1 BinTableHDU 28 1R x 2C [1D, 1D] \n"," 5 GTI 0 BinTableHDU 28 1R x 2C [1D, 1D] \n"," 6 GTI 6 BinTableHDU 28 1R x 2C [1D, 1D] \n"]}],"source":["hdu_list.info()"]},{"cell_type":"markdown","metadata":{"id":"FCoyC8sIcpOC"},"source":["In this case, we're interested in reading EVENTS, which contains information about each X-ray photon that hit the detector."]},{"cell_type":"markdown","metadata":{"id":"kTHnKQPicpOC"},"source":["To find out what information the table contains, let's print the column names."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CfQyzNPNcpOC","executionInfo":{"status":"ok","timestamp":1654881156156,"user_tz":240,"elapsed":137,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"244569b7-9235-43e1-f471-d0789a538b0a"},"outputs":[{"output_type":"stream","name":"stdout","text":["ColDefs(\n"," name = 'time'; format = '1D'; unit = 's'\n"," name = 'ccd_id'; format = '1I'\n"," name = 'node_id'; format = '1I'\n"," name = 'expno'; format = '1J'\n"," name = 'chipx'; format = '1I'; unit = 'pixel'; coord_type = 'CPCX'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n"," name = 'chipy'; format = '1I'; unit = 'pixel'; coord_type = 'CPCY'; coord_unit = 'mm'; coord_ref_point = 0.5; coord_ref_value = 0.0; coord_inc = 0.023987\n"," name = 'tdetx'; format = '1I'; unit = 'pixel'\n"," name = 'tdety'; format = '1I'; unit = 'pixel'\n"," name = 'detx'; format = '1E'; unit = 'pixel'; coord_type = 'LONG-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n"," name = 'dety'; format = '1E'; unit = 'pixel'; coord_type = 'NPOL-TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 0.0; coord_inc = 0.00013666666666667\n"," name = 'x'; format = '1E'; unit = 'pixel'; coord_type = 'RA---TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = 266.41519201128; coord_inc = -0.00013666666666667\n"," name = 'y'; format = '1E'; unit = 'pixel'; coord_type = 'DEC--TAN'; coord_unit = 'deg'; coord_ref_point = 4096.5; coord_ref_value = -29.012248288366; coord_inc = 0.00013666666666667\n"," name = 'pha'; format = '1J'; unit = 'adu'; null = 0\n"," name = 'pha_ro'; format = '1J'; unit = 'adu'; null = 0\n"," name = 'energy'; format = '1E'; unit = 'eV'\n"," name = 'pi'; format = '1J'; unit = 'chan'; null = 0\n"," name = 'fltgrade'; format = '1I'\n"," name = 'grade'; format = '1I'\n"," name = 'status'; format = '32X'\n",")\n"]}],"source":["print(hdu_list[1].columns)"]},{"cell_type":"markdown","metadata":{"id":"YpH2-4qPcpOC"},"source":["Now we'll take this data and convert it into an [astropy table](http://docs.astropy.org/en/stable/table/). While it's possible to access FITS tables directly from the ``.data`` attribute, using [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) tends to make a variety of common tasks more convenient."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"n7zMyhRhcpOD"},"outputs":[],"source":["evt_data = Table(hdu_list[1].data)"]},{"cell_type":"markdown","metadata":{"id":"sEmGEMR1cpOD"},"source":["For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"c00cCz9McpOD","executionInfo":{"status":"ok","timestamp":1654881158017,"user_tz":240,"elapsed":159,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"86eda857-3fff-4960-f488-477ee510a85c"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["\n"," time ccd_id node_id expno ... pi fltgrade grade status [32] \n"," float64 int16 int16 int32 ... int32 int16 int16 bool \n","------------------ ------ ------- ----- ... ----- -------- ----- --------------\n"," 238623220.9093583 3 3 68 ... 951 16 4 False .. False\n"," 238623220.9093583 3 1 68 ... 180 64 2 False .. False\n"," 238623220.9093583 3 2 68 ... 831 8 3 False .. False\n"," 238623220.9093583 3 0 68 ... 223 0 0 False .. False\n"," 238623220.9093583 3 1 68 ... 974 64 2 False .. False\n"," 238623220.9093583 3 3 68 ... 134 0 0 False .. False\n"," 238623220.9093583 3 3 68 ... 224 0 0 False .. False\n"," 238623220.9093583 3 3 68 ... 262 0 0 False .. False\n"," 238623220.9093583 3 3 68 ... 155 0 0 False .. False\n"," 238623220.9093583 3 3 68 ... 422 0 0 False .. False\n"," ... ... ... ... ... ... ... ... ...\n","238672393.54971933 1 3 15723 ... 331 0 0 False .. False\n","238672393.54971933 1 2 15723 ... 859 10 6 False .. False\n","238672393.54971933 1 3 15723 ... 179 0 0 False .. False\n","238672393.54971933 1 1 15723 ... 1024 16 4 False .. False\n","238672393.54971933 1 0 15723 ... 456 0 0 False .. False\n","238672393.59075934 0 1 15723 ... 984 0 0 False .. False\n","238672393.59075934 0 3 15723 ... 1004 8 3 False .. False\n","238672393.59075934 0 1 15723 ... 456 0 0 False .. False\n","238672393.59075934 0 1 15723 ... 663 16 4 False .. False\n","238672393.63179934 6 1 15723 ... 129 0 0 False .. False"],"text/html":["
Table length=483964\n","
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timeccd_idnode_idexpnochipxchipytdetxtdetydetxdetyxyphapha_roenergypifltgradegradestatus [32]
float64int16int16int32int16int16int16int16float32float32float32float32int32int32float32int32int16int16bool
238623220.909358333689208512439815095.6414138.9954168.07235087.7723548353413874.715951164False .. False
238623220.90935833168437237489534984865.5674621.18263662.19684915.93366676292621.1938180642False .. False
238623220.90935833268719289484337804814.8354340.2543935.22074832.5523033287512119.01883183False .. False
238623220.90935833068103295483731644807.36434954.3853324.46444897.27548317733253.036422300False .. False
238623220.90935833168498314481835594788.9874560.32763713.63434832.7353612343914214.382974642False .. False
238623220.90935833368791469466338524635.45264268.0533985.84964645.935004381952.723913400False .. False
238623220.90935833368894839429339554266.6424165.32034044.54694267.6058357133267.533422400False .. False
238623220.90935833368857941419139184164.8154202.22563995.93534170.8189758043817.036626200False .. False
238623220.90935833368910959417339714146.99374149.3644046.33764146.91065764462252.729515500False .. False
238623220.90935833368961962417040224144.12844098.49764096.5154138.09157213546154.109442200False .. False
.........................................................
238672393.549719331315723933199493350404902.9073082.49565212.49954766.2295122211814819.828633100False .. False
238672393.549719331215723596412472047034691.513418.98934853.51174595.80373142302012536.866859106False .. False
238672393.5497193313157231000608452451074494.7133015.71855230.8864353.0186585852599.565217900False .. False
238672393.549719331115723270917421543774188.33253743.59574472.074134.2213861346315535.7681024164False .. False
238672393.549719331015723232988414443394117.61473781.87744425.754068.4873168014996653.081545600False .. False
238672393.590759340115723366103316447663140.90483356.32084733.68163048.56643621360214362.48298400False .. False
238672393.590759340315723937646370741953681.21223925.54524231.83543651.97243717348614653.954100483False .. False
238672393.590759340115723406687374847263723.40143396.2524762.4213631.7224167615366652.82745600False .. False
238672393.590759340115723354870393147783906.073344.7754834.993807.0835243621659672.882663164False .. False
238672393.631799346115723384821325925233230.92045596.84962519.22023401.03274913561875.935912900False .. False
"]},"metadata":{},"execution_count":9}],"source":["evt_data"]},{"cell_type":"markdown","metadata":{"id":"86Qa6PUucpOD"},"source":["We can extract data from the table by referencing the column name. Let's try making a histogram for the energy of each photon, which will give us a sense for the spectrum (folded with the detector's efficiency)."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":296},"id":"9YkZY2wqcpOE","executionInfo":{"status":"ok","timestamp":1654881162366,"user_tz":240,"elapsed":1297,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"8422589a-217b-4b12-b9d0-d9f8520b0c0c"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'Number of photon events')"]},"metadata":{},"execution_count":10},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["energy_hist = plt.hist(evt_data['energy'], bins='auto')\n","plt.xlabel('Energy (eV)')\n","plt.ylabel('Number of photon events')"]},{"cell_type":"markdown","metadata":{"id":"Zd7bVk4IcpOE"},"source":["## Making a 2D histogram with some table data"]},{"cell_type":"markdown","metadata":{"id":"E8U-se8zcpOE"},"source":["A one dimensional histogram, as shown above, shows the number of events within each bin corresponding to one axis of information. In the plot above, we chose histogram bins in the energy, shown on the x-axis.\n","\n","Next we'll make an image by binning the x and y coordinates of the events into a 2D histogram. \n","\n","A two dimensional histogram finds the number of events binned according to two dimensions. To make an image, we will bin the number of events by x and y position on the sky."]},{"cell_type":"markdown","metadata":{"id":"cEqsE2U1cpOE"},"source":["This particular observation spans five CCD chips. First, we determine the events that only fell on the main (ACIS-I) chips, which have number ids 0, 1, 2, and 3. We can do this by creating an array of True and False values (`ii` below) to filter out events that only fall on those chips."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Mb4RHcJLcpOE"},"outputs":[],"source":["ii = np.isin(evt_data['ccd_id'], [0, 1, 2, 3])"]},{"cell_type":"markdown","metadata":{"id":"2z9PQUh9cpOF"},"source":["### Method 1: Use hist2d with a log-normal color scheme"]},{"cell_type":"markdown","source":["We can make a 2D histogram plot directly with the function `matplotlib.pyplot.hist2d`, as shown below.\n","\n","In this example, we choose the `matplotlib` color map named \"viridis\", and we choose to distribute the colors logarithmically using `matplotlib.colors.LogNorm()`.\n","\n","You can find more about `matplotlib` here: https://matplotlib.org/stable/plot_types/index.html\n"],"metadata":{"id":"UQwNh3ppn6c_"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":296},"id":"tjB8Rxa1cpOG","executionInfo":{"status":"ok","timestamp":1654881707422,"user_tz":240,"elapsed":1170,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"c97a7a5d-972d-451c-f5ea-a92454983570"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'y')"]},"metadata":{},"execution_count":20},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["NBINS = (100,100)\n","img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS, \n"," cmap='viridis', norm=LogNorm())\n","\n","# Show the color bar scale next to the plot. The color corresponds to number \n","# of photon events (counts) in each pixel.\n","cbar = plt.colorbar(label='Counts')\n","\n","plt.xlabel('x')\n","plt.ylabel('y')"]},{"cell_type":"markdown","metadata":{"id":"zUYM11V5cpOF"},"source":["### Method 2: Use numpy to make a 2D histogram and imshow to display it"]},{"cell_type":"markdown","metadata":{"id":"fh5bDy-gcpOF"},"source":["When we plot with `matplotlib.pyplot.hist2d`, it forces the plot into the default figure size, which could cause your image to appear stretched. \n","\n","By using `matplotlib.pyplot.imshow`, we can avoid stretching the image. To do that, we need to make a 2D array containing the number of counts per pixel bin using `numpy.histogram2d`, as shown below."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":296},"id":"hw-xj7pdcpOF","executionInfo":{"status":"ok","timestamp":1654882383776,"user_tz":240,"elapsed":265,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}},"outputId":"5b992c7f-5797-45d1-984b-6d3b4f608faa"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'y')"]},"metadata":{},"execution_count":40},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["NBINS = (100,100)\n","\n","img_zero, xedges, yedges = np.histogram2d(evt_data['y'][ii], evt_data['x'][ii], NBINS)\n","\n","# This array describes how to map the position of the 2D array containing the image\n","# to the x and y positions on the sky\n","extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]\n","\n","plt.imshow(img_zero, extent=extent, interpolation='nearest', \n"," cmap='gist_yarg', origin='lower', norm=LogNorm())\n","\n","plt.xlabel('x')\n","plt.ylabel('y')"]},{"cell_type":"markdown","metadata":{"id":"Gggs4qvFcpOG"},"source":["## Close the FITS file"]},{"cell_type":"markdown","metadata":{"id":"KNYSKxLucpOG"},"source":["When you're done using a FITS file, it's often a good idea to close it. That way you can be sure it won't continue using up excess memory or file handles on your computer. (This happens automatically when you close Python, but you never know how long that might be...)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"AI8mrIGWcpOG"},"outputs":[],"source":["hdu_list.close()"]},{"cell_type":"markdown","metadata":{"id":"cwSittwlcpOG"},"source":["## Exercises"]},{"cell_type":"markdown","metadata":{"id":"zX5Gr3CdcpOH"},"source":["Make a scatter plot of the same data you histogrammed above. The [plt.scatter](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter) function is your friend for this. What are the pros and cons of doing it this way?"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"haxhlHMIcpOH","outputId":"22fd37cb-a934-4296-dfea-7872324e18ad","colab":{"base_uri":"https://localhost:8080/","height":265},"executionInfo":{"status":"ok","timestamp":1654882483292,"user_tz":240,"elapsed":1028,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["energy_scatter = plt.scatter(evt_data['x'][ii], evt_data['y'][ii], s=1, alpha=0.1, color='b')"]},{"cell_type":"markdown","metadata":{"id":"84C-9XGUcpOH"},"source":["Try the same with the [plt.hexbin](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.hexbin) plotting function. Which do you think looks better for this kind of data?"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"s-aWczHzcpOH","outputId":"5d50aeba-7cc1-479b-e88b-bb9720c329fe","colab":{"base_uri":"https://localhost:8080/","height":265},"executionInfo":{"status":"ok","timestamp":1654882511407,"user_tz":240,"elapsed":798,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["energy_hex = plt.hexbin(evt_data['x'][ii], evt_data['y'][ii], norm=LogNorm())"]},{"cell_type":"markdown","metadata":{"id":"sB7gbTBBcpOH"},"source":["Choose an energy range to make a slice of the FITS table, then plot it. How does the image change with different energy ranges?"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Hq1VDm35cpOH","outputId":"041e1abe-28c3-4209-9454-609aea4786a3","colab":{"base_uri":"https://localhost:8080/","height":296},"executionInfo":{"status":"ok","timestamp":1654882615039,"user_tz":240,"elapsed":791,"user":{"displayName":"Lia Corrales","userId":"03737332005355202815"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0, 0.5, 'y')"]},"metadata":{},"execution_count":44},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"needs_background":"light"}}],"source":["NBINS = (100,100)\n","ii = (evt_data['energy'] > 3500) & (evt_data['energy'] < 5000)\n","img_zero_mpl = plt.hist2d(evt_data['x'][ii], evt_data['y'][ii], NBINS,\n"," cmap='viridis', norm=LogNorm())\n","\n","cbar = plt.colorbar(ticks=[1.0,3.0,6.0])\n","cbar.ax.set_yticklabels(['1','3','6'])\n","\n","plt.xlabel('x')\n","plt.ylabel('y')"]},{"cell_type":"code","source":[""],"metadata":{"id":"uFehWSaZsLrV"},"execution_count":null,"outputs":[]}],"metadata":{"astropy-tutorials":{"author":"Lia R. Corrales ","date":"January 2014","description":"astropy.utils.data to download the file, astropy.io.fits to open and view the file, matplotlib for making both 1D and 2D histograms of the data.","link_name":"Viewing and manipulating data from FITS tables","name":"","published":true},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.9.12"},"colab":{"name":"FITS-tables.ipynb","provenance":[],"collapsed_sections":[]}},"nbformat":4,"nbformat_minor":0} \ No newline at end of file From 165521fe38fa41ed605c1af44c0e6b512f6cddc8 Mon Sep 17 00:00:00 2001 From: luthienliu Date: Sat, 6 Aug 2022 16:38:10 -0400 Subject: [PATCH 06/10] . --- tutorials/FITS-tables/requirements.txt | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) create mode 100644 tutorials/FITS-tables/requirements.txt diff --git a/tutorials/FITS-tables/requirements.txt b/tutorials/FITS-tables/requirements.txt new file mode 100644 index 00000000..9da18a57 --- /dev/null +++ b/tutorials/FITS-tables/requirements.txt @@ -0,0 +1,16 @@ +astropy +astroquery +IPython +matplotlib +numpy +jupyter +scipy +notebook +spectral-cube @ git+https://github.com/radio-astro-tools/spectral-cube # as of: 2021-09-21 +radio-beam +reproject +dust_extinction +gala +synphot +pyvo==1.2.0 +pvextractor From 87e37161db125a017f420d3d5d2e59d10f273129 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sat, 6 Aug 2022 20:46:23 +0000 Subject: [PATCH 07/10] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- tutorials/FITS-tables/FITS-tables.ipynb | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/tutorials/FITS-tables/FITS-tables.ipynb b/tutorials/FITS-tables/FITS-tables.ipynb index d559038d..80897956 100644 --- a/tutorials/FITS-tables/FITS-tables.ipynb +++ b/tutorials/FITS-tables/FITS-tables.ipynb @@ -611,11 +611,6 @@ "name": "FITS-tables.ipynb", "provenance": [] }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, "language_info": { "codemirror_mode": { "name": "ipython", @@ -625,8 +620,7 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.12" + "pygments_lexer": "ipython3" } }, "nbformat": 4, From 11226006f857b8efb8e5305a31b0b197259093d8 Mon Sep 17 00:00:00 2001 From: Lia Corrales Date: Wed, 5 Oct 2022 14:37:22 -0400 Subject: [PATCH 08/10] Update tutorials/FITS-tables/FITS_tables.ipynb --- tutorials/FITS-tables/FITS_tables.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb index df642d8f..a5330e06 100644 --- a/tutorials/FITS-tables/FITS_tables.ipynb +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -192,7 +192,7 @@ "id": "sEmGEMR1cpOD" }, "source": [ - "For example, a preview of the table is easily viewed by simply running a cell with the table as the last line:" + "For example, you can use the `pprint` method to preview a text-formatted version of the table. By using the `max_lines` keyword in the example below, we can limit how much space the text takes up." ] }, { From 4741456e0707c1108ac6c24277f8df2ad593c719 Mon Sep 17 00:00:00 2001 From: Lia Corrales Date: Wed, 5 Oct 2022 14:37:28 -0400 Subject: [PATCH 09/10] Update tutorials/FITS-tables/FITS_tables.ipynb --- tutorials/FITS-tables/FITS_tables.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb index a5330e06..8ccfe9d2 100644 --- a/tutorials/FITS-tables/FITS_tables.ipynb +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -208,7 +208,7 @@ }, "outputs": [], "source": [ - "evt_data" + "evt_data.pprint(max_lines=10)" ] }, { From ff33c7389b5212536e79a237de53f655fc94ced2 Mon Sep 17 00:00:00 2001 From: Lia Corrales Date: Wed, 5 Oct 2022 14:37:46 -0400 Subject: [PATCH 10/10] Update tutorials/FITS-tables/FITS_tables.ipynb --- tutorials/FITS-tables/FITS_tables.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/FITS-tables/FITS_tables.ipynb b/tutorials/FITS-tables/FITS_tables.ipynb index 8ccfe9d2..43719daf 100644 --- a/tutorials/FITS-tables/FITS_tables.ipynb +++ b/tutorials/FITS-tables/FITS_tables.ipynb @@ -104,7 +104,7 @@ "id": "Cp_kqCg4cpOA" }, "source": [ - "Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." + "It's possible to open a FITS file directly from the URL using the `Table.read` method (see [Getting Started with Table I/O](https://docs.astropy.org/en/stable/io/unified.html)). However, the Chandra event files contain multiple FITS table extensions. As part of this tutorial, we want you to get familiar with exploring FITS file contents, so we will open the FITS file directly with the `fits.open` function. \n \n Since the file is big, let's open it with `memmap=True` to prevent RAM storage issues." ] }, {