{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "
\n", "**This is a fixed-text formatted version of a Jupyter notebook.**\n", "\n", "- Try online [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gammapy/gammapy-webpage/v0.9?urlpath=lab/tree/astropy_introduction.ipynb)\n", "- You can contribute with your own notebooks in this\n", "[GitHub repository](https://github.com/gammapy/gammapy/tree/master/tutorials).\n", "- **Source files:**\n", "[astropy_introduction.ipynb](../_static/notebooks/astropy_introduction.ipynb) |\n", "[astropy_introduction.py](../_static/notebooks/astropy_introduction.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Astropy introduction for Gammapy users\n", "\n", "\n", "## Introduction\n", "\n", "To become efficient at using Gammapy, you have to learn to use some parts of Astropy, especially FITS I/O and how to work with Table, Quantity, SkyCoord, Angle and Time objects.\n", "\n", "Gammapy is built on Astropy, meaning that data in Gammapy is often stored in Astropy objects, and the methods on those objects are part of the public Gammapy API.\n", "\n", "This tutorial is a quick introduction to the parts of Astropy you should know become familiar with to use Gammapy (or also when not using Gammapy, just doing astronomy from Python scripts). The largest part is devoted to tables, which are a the most important building block for Gammapy (event lists, flux points, light curves, ... many other thing are store in Table objects).\n", "\n", "We will:\n", "\n", "- open and write fits files with [io.fits](http://docs.astropy.org/en/stable/io/fits/index.html)\n", "- manipulate [coordinates](http://docs.astropy.org/en/stable/coordinates/): [SkyCoord](http://docs.astropy.org/en/stable/api/astropy.coordinates.SkyCoord.html) and [Angle](http://docs.astropy.org/en/stable/coordinates/angles.html) classes\n", "- use [units](http://docs.astropy.org/en/stable/units/index.html) and [Quantities](http://docs.astropy.org/en/stable/api/astropy.units.Quantity.html). See also this [tutorial](http://www.astropy.org/astropy-tutorials/Quantities.html)\n", "- manipulate [Times and Dates](http://docs.astropy.org/en/stable/time/index.html)\n", "- use [tables](http://docs.astropy.org/en/stable/table/index.html) with the [Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html) class with the Fermi catalog\n", "- define regions in the sky with the [region](http://astropy-regions.readthedocs.io/en/latest/getting_started.html) package\n", "\n", "## Setup" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# to make plots appear in the notebook\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "numpy: 1.15.4\n", "astropy: 3.0.5\n" ] } ], "source": [ "# If something below doesn't work, here's how you\n", "# can check what version of Numpy and Astropy you have\n", "# All examples should work with Astropy 1.3,\n", "# most even with Astropy 1.0\n", "from gammapy.extern.pathlib import Path\n", "import numpy as np\n", "import astropy\n", "import os\n", "\n", "print(\"numpy:\", np.__version__)\n", "print(\"astropy:\", astropy.__version__)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Units, Quantities and constants\n", "import astropy.units as u\n", "from astropy.units import Quantity\n", "import astropy.constants as cst\n", "\n", "from astropy.io import fits\n", "from astropy.table import Table\n", "from astropy.coordinates import SkyCoord, Angle\n", "from astropy.time import Time" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Units and constants\n", "\n", "### Basic usage" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# One can create a Quantity like this\n", "L = Quantity(1e35, unit=\"erg/s\")\n", "# or like this\n", "d = 8 * u.kpc\n", "\n", "# then one can produce new Quantities\n", "flux = L / (4 * np.pi * d ** 2)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$$1.3058974 \\times 10^{-11} \\; \\mathrm{\\frac{erg}{s\\,cm^{2}}}$$" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# And convert its value to an equivalent unit\n", "flux.to(\"erg cm-2 s-1\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$$1.3058974 \\times 10^{-14} \\; \\mathrm{\\frac{W}{m^{2}}}$$" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flux.to(\"W/m2\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "More generally a Quantity is a numpy array with a unit." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$$[0.01,~0.021544347,~0.046415888,~0.1,~0.21544347,~0.46415888,~1,~2.1544347,~4.6415888,~10] \\; \\mathrm{TeV}$$" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "E = np.logspace(1, 4, 10) * u.GeV\n", "E.to(\"TeV\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we compute the interaction time of protons." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$$35.233361 \\; \\mathrm{Myr}$$" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x_eff = 30 * u.mbarn\n", "density = 1 * u.cm ** -3\n", "\n", "interaction_time = (density * x_eff * cst.c) ** -1\n", "\n", "interaction_time.to(\"Myr\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Use Quantities in functions\n", "\n", "We compute here the energy loss rate of an electron of kinetic energy E in magnetic field B. See formula (5B10) in this [lecture](http://www.cv.nrao.edu/course/astr534/SynchrotronPower.html)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4.0519325060487625e-13 erg / s\n" ] } ], "source": [ "def electron_energy_loss_rate(B, E):\n", " \"\"\" energy loss rate of an electron of kinetic energy E in magnetic field B\n", " \"\"\"\n", " U_B = B ** 2 / (2 * cst.mu0)\n", " gamma = (\n", " E / (cst.m_e * cst.c ** 2) + 1\n", " ) # note that this works only because E/(cst.m_e*cst.c**2) is dimensionless\n", " beta = np.sqrt(1 - 1 / gamma ** 2)\n", " return 4.0 / 3.0 * cst.sigma_T * cst.c * gamma ** 2 * beta ** 2 * U_B\n", "\n", "\n", "print(electron_energy_loss_rate(1e-5 * u.G, 1 * u.TeV).to(\"erg/s\"))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Now plot it\n", "E_elec = np.logspace(-1.0, 6, 100) * u.MeV\n", "B = 1 * u.G\n", "y = (E_elec / electron_energy_loss_rate(B, E_elec)).to(\"yr\")\n", "plt.loglog(E_elec, y);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A frequent issue is homogeneity. One can use decorators to ensure it." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Incorrect unit: Argument 'E' to function 'electron_energy_loss_rate' must be in units convertible to 'J'.\n" ] } ], "source": [ "# This ensures that B and E are homogeneous to magnetic field strength and energy\n", "# If not will raise a UnitError exception\n", "@u.quantity_input(B=u.T, E=u.J)\n", "def electron_energy_loss_rate(B, E):\n", " \"\"\" energy loss rate of an electron of kinetic energy E in magnetic field B\n", " \"\"\"\n", " U_B = B ** 2 / (2 * cst.mu0)\n", " gamma = (\n", " E / (cst.m_e * cst.c ** 2) + 1\n", " ) # note that this works only because E/(cst.m_e*cst.c**2) is dimensionless\n", " beta = np.sqrt(1 - 1 / gamma ** 2)\n", " return 4.0 / 3.0 * cst.sigma_T * cst.c * gamma ** 2 * beta ** 2 * U_B\n", "\n", "\n", "# Now try it\n", "try:\n", " print(electron_energy_loss_rate(1e-5 * u.G, 1 * u.Hz).to(\"erg/s\"))\n", "except u.UnitsError as message:\n", " print(\"Incorrect unit: \" + str(message))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Coordinates\n", "\n", "Note that SkyCoord are arrays of coordinates. We will see that in more detail in the next section." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10d37m30s 22d00m52.2s\n", "Distance to Crab: 63d12m28.2297s\n", "Distance to Crab: 63.2078415848386\n" ] } ], "source": [ "# Different ways to create a SkyCoord\n", "c1 = SkyCoord(10.625, 41.2, frame=\"icrs\", unit=\"deg\")\n", "c1 = SkyCoord(\"00h42m30s\", \"+41d12m00s\", frame=\"icrs\")\n", "\n", "c2 = SkyCoord(83.633083, 22.0145, unit=\"deg\")\n", "# If you have internet access, you could also use this to define the `source_pos`:\n", "# c2 = SkyCoord.from_name(\"Crab\") # Get the name from CDS\n", "\n", "print(c1.ra, c2.dec)\n", "# separation returns an Angle object\n", "print(\"Distance to Crab: \", c1.separation(c2))\n", "print(\"Distance to Crab: \", c1.separation(c2).degree)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Coordinate transformations\n", "\n", "How to change between coordinate frames. The Crab in Galactic coordinates." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "184d33m26.8478s -5d47m03.6851s\n" ] } ], "source": [ "c2b = c2.galactic\n", "print(c2b)\n", "print(c2b.l, c2b.b)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Time \n", "\n", "Is the Crab visible now?" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2018-11-29 15:02:05.481158\n", "58451.626452328215\n" ] } ], "source": [ "now = Time.now()\n", "print(now)\n", "print(now.mjd)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# define the location for the AltAz system\n", "from astropy.coordinates import EarthLocation, AltAz\n", "\n", "paris = EarthLocation(lat=48.8567 * u.deg, lon=2.3508 * u.deg)\n", "\n", "# calculate the horizontal coordinates\n", "crab_altaz = c2.transform_to(AltAz(obstime=now, location=paris))\n", "\n", "print(crab_altaz)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Table: Manipulating the 3FGL catalog\n", "\n", "Here we are going to do some selections with the 3FGL catalog. To do so we use the Table class from astropy.\n", "\n", "### Accessing the table\n", "First, we need to open the catalog in a Table. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: UnitsWarning: 'photon/cm**2/MeV/s' contains multiple slashes, which is discouraged by the FITS standard [astropy.units.format.generic]\n", "WARNING: UnitsWarning: 'photon/cm**2/s' contains multiple slashes, which is discouraged by the FITS standard [astropy.units.format.generic]\n", "WARNING: UnitsWarning: 'erg/cm**2/s' contains multiple slashes, which is discouraged by the FITS standard [astropy.units.format.generic]\n" ] } ], "source": [ "# Open Fermi 3FGL from the repo\n", "filename = os.environ[\"GAMMAPY_DATA\"] / Path(\n", " \"catalogs/fermi/gll_psc_v16.fit.gz\"\n", ")\n", "table = Table.read(str(filename), hdu=1)\n", "# Alternatively, one can grab it from the server.\n", "# table = Table.read(\"http://fermi.gsfc.nasa.gov/ssc/data/access/lat/4yr_catalog/gll_psc_v16.fit\")" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['PRIMARY', 'LAT_Point_Source_Catalog', 'ROIs', 'Hist_Start', 'GTI', 'ExtendedSources']\n" ] } ], "source": [ "# Note that a single FITS file might contain different tables in different HDUs\n", "filename = os.environ[\"GAMMAPY_DATA\"] / Path(\n", " \"catalogs/fermi/gll_psc_v16.fit.gz\"\n", ")\n", "# You can load a `fits.HDUList` and check the extension names\n", "print([_.name for _ in fits.open(str(filename))])\n", "# Then you can load by name or integer index via the `hdu` option\n", "extended_source_table = Table.read(str(filename), hdu=\"ExtendedSources\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### General informations on the Table\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " name dtype shape unit n_bad\n", "-------------------- ------- ------- ---------------- -----\n", " Source_Name bytes18 0\n", " RAJ2000 float32 deg 0\n", " DEJ2000 float32 deg 0\n", " GLON float32 deg 0\n", " GLAT float32 deg 0\n", " Conf_68_SemiMajor float32 deg 28\n", " Conf_68_SemiMinor float32 deg 28\n", " Conf_68_PosAng float32 deg 28\n", " Conf_95_SemiMajor float32 deg 28\n", " Conf_95_SemiMinor float32 deg 28\n", " Conf_95_PosAng float32 deg 28\n", " ROI_num int16 0\n", " Signif_Avg float32 5\n", " Pivot_Energy float32 MeV 0\n", " Flux_Density float32 ph / (cm2 MeV s) 0\n", " Unc_Flux_Density float32 ph / (cm2 MeV s) 5\n", " Flux1000 float32 ph / (cm2 s) 0\n", " Unc_Flux1000 float32 ph / (cm2 s) 5\n", " Energy_Flux100 float32 erg / (cm2 s) 0\n", " Unc_Energy_Flux100 float32 erg / (cm2 s) 5\n", " Signif_Curve float32 0\n", " SpectrumType bytes16 0\n", " Spectral_Index float32 0\n", " Unc_Spectral_Index float32 9\n", " beta float32 2639\n", " Unc_beta float32 2680\n", " Cutoff float32 MeV 2918\n", " Unc_Cutoff float32 MeV 2918\n", " Exp_Index float32 2918\n", " Unc_Exp_Index float32 3028\n", " PowerLaw_Index float32 0\n", " Flux30_100 float32 ph / (cm2 s) 3034\n", " Unc_Flux30_100 float32 ph / (cm2 s) 3034\n", " nuFnu30_100 float32 erg / (cm2 s) 3034\n", " Sqrt_TS30_100 float32 3034\n", " Flux100_300 float32 ph / (cm2 s) 0\n", " Unc_Flux100_300 float32 (2,) ph / (cm2 s) 836\n", " nuFnu100_300 float32 erg / (cm2 s) 0\n", " Sqrt_TS100_300 float32 5\n", " Flux300_1000 float32 ph / (cm2 s) 0\n", " Unc_Flux300_1000 float32 (2,) ph / (cm2 s) 327\n", " nuFnu300_1000 float32 erg / (cm2 s) 0\n", " Sqrt_TS300_1000 float32 5\n", " Flux1000_3000 float32 ph / (cm2 s) 0\n", " Unc_Flux1000_3000 float32 (2,) ph / (cm2 s) 111\n", " nuFnu1000_3000 float32 erg / (cm2 s) 0\n", " Sqrt_TS1000_3000 float32 0\n", " Flux3000_10000 float32 ph / (cm2 s) 0\n", " Unc_Flux3000_10000 float32 (2,) ph / (cm2 s) 137\n", " nuFnu3000_10000 float32 erg / (cm2 s) 0\n", " Sqrt_TS3000_10000 float32 3\n", " Flux10000_100000 float32 ph / (cm2 s) 0\n", "Unc_Flux10000_100000 float32 (2,) ph / (cm2 s) 670\n", " nuFnu10000_100000 float32 erg / (cm2 s) 0\n", " Sqrt_TS10000_100000 float32 2\n", " Variability_Index float32 0\n", " Signif_Peak float32 2387\n", " Flux_Peak float32 ph / (cm2 s) 2387\n", " Unc_Flux_Peak float32 ph / (cm2 s) 2387\n", " Time_Peak float64 s 2387\n", " Peak_Interval float32 s 2387\n", " Flux_History float32 (48,) ph / (cm2 s) 0\n", " Unc_Flux_History float32 (48, 2) ph / (cm2 s) 64623\n", "Extended_Source_Name bytes18 0\n", " 0FGL_Name bytes17 0\n", " 1FGL_Name bytes18 0\n", " 2FGL_Name bytes18 0\n", " 1FHL_Name bytes18 0\n", " ASSOC_GAM1 bytes15 0\n", " ASSOC_GAM2 bytes14 0\n", " ASSOC_GAM3 bytes15 0\n", " TEVCAT_FLAG bytes1 0\n", " ASSOC_TEV bytes21 0\n", " CLASS1 bytes5 0\n", " ASSOC1 bytes26 0\n", " ASSOC2 bytes26 0\n", " Flags int16 0\n" ] } ], "source": [ "table.info()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "
\n", " name mean std min max n_bad\n", "-------------------- ----------------- ------------------ ------------- -------------- -----\n", " Source_Name -- -- -- -- 0\n", " RAJ2000 185.63785 100.58523 0.0377 359.8812 0\n", " DEJ2000 -2.235143 41.53712 -87.6185 88.7739 0\n", " GLON 186.2728 107.57225 0.12616104 359.9692 0\n", " GLAT 1.2272784 36.499836 -87.95155 86.36791 0\n", " Conf_68_SemiMajor -inf nan -inf 0.6587264 28\n", " Conf_68_SemiMinor -inf nan -inf 0.32094488 28\n", " Conf_68_PosAng -0.21967074 51.926346 -89.94 89.92 28\n", " Conf_95_SemiMajor -inf nan -inf 1.0681 28\n", " Conf_95_SemiMinor -inf nan -inf 0.5204 28\n", " Conf_95_PosAng -0.21967074 51.926346 -89.94 89.92 28\n", " ROI_num 424.7771918259723 238.84623199551552 1 840 0\n", " Signif_Avg -inf nan -inf 1048.9587 5\n", " Pivot_Energy 2104.4626 2578.198 100.79754 37201.97 0\n", " Flux_Density 1.2938883e-11 2.1723061e-10 4.2151523e-16 1.1447582e-08 0\n", " Unc_Flux_Density -inf nan -inf 6.864756e-10 5\n", " Flux1000 2.7506988e-09 2.764754e-08 4.905819e-12 1.2976768e-06 0\n", " Unc_Flux1000 -inf nan -inf 2.8939553e-09 5\n", " Energy_Flux100 2.5601129e-11 1.8885869e-10 1.6522738e-12 8.9300825e-09 0\n", " Unc_Energy_Flux100 -inf nan -inf 2.5295337e-11 5\n", " Signif_Curve 2.431611 3.8773124 0.0 84.97297 0\n", " SpectrumType -- -- -- -- 0\n", " Spectral_Index 2.2145069 0.36053884 0.50000006 5.715894 0\n", " Unc_Spectral_Index -inf nan -inf 1.0611331 9\n", " beta -inf nan -inf 1.0 2639\n", " Unc_beta -inf nan -inf 0.3376085 2680\n", " Cutoff -inf nan -inf 13326.353 2918\n", " Unc_Cutoff -inf nan -inf 3750.5642 2918\n", " Exp_Index -inf nan -inf 1.0 2918\n", " Unc_Exp_Index -inf nan -inf 0.044299893 3028\n", " PowerLaw_Index 2.249819 0.30635425 1.0975342 5.715894 0\n", " Flux30_100 nan nan nan nan 3034\n", " Unc_Flux30_100 nan nan nan nan 3034\n", " nuFnu30_100 nan nan nan nan 3034\n", " Sqrt_TS30_100 nan nan nan nan 3034\n", " Flux100_300 2.3779466e-08 1.2034207e-07 1.0022202e-14 5.37625e-06 0\n", " Unc_Flux100_300 -inf nan -inf 9.567011e-08 836\n", " nuFnu100_300 5.7192215e-12 3.026846e-11 2.4912323e-18 1.3717709e-09 0\n", " Sqrt_TS100_300 3.8165362 8.915827 0.0 215.4162 5\n", " Flux300_1000 8.619365e-09 6.732932e-08 3.9778793e-15 3.2167186e-06 0\n", " Unc_Flux300_1000 -inf nan -inf 1.897159e-08 327\n", " nuFnu300_1000 5.904836e-12 4.7984526e-11 2.9117903e-18 2.2924256e-09 0\n", " Sqrt_TS300_1000 7.471796 19.89813 0.0 568.66296 5\n", " Flux1000_3000 2.1950213e-09 2.2779465e-08 1.5087699e-15 1.0701934e-06 0\n", " Unc_Flux1000_3000 -inf nan -inf 6.0994774e-09 111\n", " nuFnu1000_3000 5.1461344e-12 5.3878357e-11 3.765228e-18 2.5253446e-09 0\n", " Sqrt_TS1000_3000 8.607782 22.247915 0.0 711.6319 0\n", " Flux3000_10000 4.836294e-10 4.6478523e-09 9.338969e-16 2.1617714e-07 0\n", " Unc_Flux3000_10000 -inf nan -inf 2.9860603e-09 137\n", " nuFnu3000_10000 3.0733539e-12 2.8322539e-11 5.6769025e-18 1.3210241e-09 0\n", " Sqrt_TS3000_10000 6.98671 13.919392 0.0 465.89935 3\n", " Flux10000_100000 7.399214e-11 3.2253794e-10 1.0387837e-17 1.13814576e-08 0\n", "Unc_Flux10000_100000 -inf nan -inf 7.880918e-10 670\n", " nuFnu10000_100000 1.1641434e-12 4.635748e-12 9.385276e-20 1.1601801e-10 0\n", " Sqrt_TS10000_100000 4.019383 5.470039 0.0 111.192406 2\n", " Variability_Index 154.12613 1230.7148 0.0 60733.92 0\n", " Signif_Peak -inf nan -inf 255.07051 2387\n", " Flux_Peak -inf nan -inf 2.1237443e-05 2387\n", " Unc_Flux_Peak -inf nan -inf 1.4785873e-07 2387\n", " Time_Peak -inf nan -inf 364203776.0 2387\n", " Peak_Interval -inf nan -inf 2630000.0 2387\n", " Flux_History 3.5440095e-08 2.2605154e-07 0.0 2.1237443e-05 0\n", " Unc_Flux_History -inf nan -inf 2.3038561e-07 64623\n", "Extended_Source_Name -- -- -- -- 0\n", " 0FGL_Name -- -- -- -- 0\n", " 1FGL_Name -- -- -- -- 0\n", " 2FGL_Name -- -- -- -- 0\n", " 1FHL_Name -- -- -- -- 0\n", " ASSOC_GAM1 -- -- -- -- 0\n", " ASSOC_GAM2 -- -- -- -- 0\n", " ASSOC_GAM3 -- -- -- -- 0\n", " TEVCAT_FLAG -- -- -- -- 0\n", " ASSOC_TEV -- -- -- -- 0\n", " CLASS1 -- -- -- -- 0\n", " ASSOC1 -- -- -- -- 0\n", " ASSOC2 -- -- -- -- 0\n", " Flags 45.77356624917601 265.7116050036644 0 2565 0\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n", "/Users/deil/software/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/numpy/lib/nanfunctions.py:1426: RuntimeWarning: invalid value encountered in subtract\n", " np.subtract(arr, avg, out=arr, casting='unsafe')\n" ] } ], "source": [ "# Statistics on each column\n", "table.info(\"stats\")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Source_Name',\n", " 'RAJ2000',\n", " 'DEJ2000',\n", " 'GLON',\n", " 'GLAT',\n", " 'Conf_68_SemiMajor',\n", " 'Conf_68_SemiMinor',\n", " 'Conf_68_PosAng',\n", " 'Conf_95_SemiMajor',\n", " 'Conf_95_SemiMinor',\n", " 'Conf_95_PosAng',\n", " 'ROI_num',\n", " 'Signif_Avg',\n", " 'Pivot_Energy',\n", " 'Flux_Density',\n", " 'Unc_Flux_Density',\n", " 'Flux1000',\n", " 'Unc_Flux1000',\n", " 'Energy_Flux100',\n", " 'Unc_Energy_Flux100',\n", " 'Signif_Curve',\n", " 'SpectrumType',\n", " 'Spectral_Index',\n", " 'Unc_Spectral_Index',\n", " 'beta',\n", " 'Unc_beta',\n", " 'Cutoff',\n", " 'Unc_Cutoff',\n", " 'Exp_Index',\n", " 'Unc_Exp_Index',\n", " 'PowerLaw_Index',\n", " 'Flux30_100',\n", " 'Unc_Flux30_100',\n", " 'nuFnu30_100',\n", " 'Sqrt_TS30_100',\n", " 'Flux100_300',\n", " 'Unc_Flux100_300',\n", " 'nuFnu100_300',\n", " 'Sqrt_TS100_300',\n", " 'Flux300_1000',\n", " 'Unc_Flux300_1000',\n", " 'nuFnu300_1000',\n", " 'Sqrt_TS300_1000',\n", " 'Flux1000_3000',\n", " 'Unc_Flux1000_3000',\n", " 'nuFnu1000_3000',\n", " 'Sqrt_TS1000_3000',\n", " 'Flux3000_10000',\n", " 'Unc_Flux3000_10000',\n", " 'nuFnu3000_10000',\n", " 'Sqrt_TS3000_10000',\n", " 'Flux10000_100000',\n", " 'Unc_Flux10000_100000',\n", " 'nuFnu10000_100000',\n", " 'Sqrt_TS10000_100000',\n", " 'Variability_Index',\n", " 'Signif_Peak',\n", " 'Flux_Peak',\n", " 'Unc_Flux_Peak',\n", " 'Time_Peak',\n", " 'Peak_Interval',\n", " 'Flux_History',\n", " 'Unc_Flux_History',\n", " 'Extended_Source_Name',\n", " '0FGL_Name',\n", " '1FGL_Name',\n", " '2FGL_Name',\n", " '1FHL_Name',\n", " 'ASSOC_GAM1',\n", " 'ASSOC_GAM2',\n", " 'ASSOC_GAM3',\n", " 'TEVCAT_FLAG',\n", " 'ASSOC_TEV',\n", " 'CLASS1',\n", " 'ASSOC1',\n", " 'ASSOC2',\n", " 'Flags']" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "### list of column names\n", "table.colnames" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "# HTML display\n", "# table.show_in_browser(jsviewer=True)\n", "# table.show_in_notebook(jsviewer=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Accessing the table" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "25" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# The header keywords are stored as a dict\n", "# table.meta\n", "table.meta[\"TSMIN\"]" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Row index=0\n", "
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Source_NameRAJ2000DEJ2000GLONGLATConf_68_SemiMajorConf_68_SemiMinorConf_68_PosAngConf_95_SemiMajorConf_95_SemiMinorConf_95_PosAngROI_numSignif_AvgPivot_EnergyFlux_DensityUnc_Flux_DensityFlux1000Unc_Flux1000Energy_Flux100Unc_Energy_Flux100Signif_CurveSpectrumTypeSpectral_IndexUnc_Spectral_IndexbetaUnc_betaCutoffUnc_CutoffExp_IndexUnc_Exp_IndexPowerLaw_IndexFlux30_100Unc_Flux30_100nuFnu30_100Sqrt_TS30_100Flux100_300Unc_Flux100_300 [2]nuFnu100_300Sqrt_TS100_300Flux300_1000Unc_Flux300_1000 [2]nuFnu300_1000Sqrt_TS300_1000Flux1000_3000Unc_Flux1000_3000 [2]nuFnu1000_3000Sqrt_TS1000_3000Flux3000_10000Unc_Flux3000_10000 [2]nuFnu3000_10000Sqrt_TS3000_10000Flux10000_100000Unc_Flux10000_100000 [2]nuFnu10000_100000Sqrt_TS10000_100000Variability_IndexSignif_PeakFlux_PeakUnc_Flux_PeakTime_PeakPeak_IntervalFlux_History [48]Unc_Flux_History [48,2]Extended_Source_Name0FGL_Name1FGL_Name2FGL_Name1FHL_NameASSOC_GAM1ASSOC_GAM2ASSOC_GAM3TEVCAT_FLAGASSOC_TEVCLASS1ASSOC1ASSOC2Flags
degdegdegdegdegdegdegdegdegdegMeVph / (cm2 MeV s)ph / (cm2 MeV s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)erg / (cm2 s)MeVMeVph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)erg / (cm2 s)ph / (cm2 s)ph / (cm2 s)ssph / (cm2 s)ph / (cm2 s)
bytes18float32float32float32float32float32float32float32float32float32float32int16float32float32float32float32float32float32float32float32float32bytes16float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float32float64float32float32float32bytes18bytes17bytes18bytes18bytes18bytes15bytes14bytes15bytes1bytes21bytes5bytes26bytes26int16
3FGL J0000.1+65450.037765.7517117.693883.40295770.062844510.0481047341.030.10190.07841.031856.8131251159.08131.005343e-121.4910649e-131.0159622e-091.5759212e-101.3569529e-112.0731739e-123.396615PowerLaw2.4109560.08232082-inf-inf-inf-inf-inf-inf2.410956nannannannan1.8083163e-08-8.39548e-09 .. 8.236045e-094.1752856e-122.16875486.9407333e-09-1.3528098e-09 .. 1.3669199e-094.543647e-125.2697111.2366493e-09-2.2512775e-10 .. 2.3434676e-102.8553431e-126.022245.78052e-11-4.04457e-11 .. 4.8533958e-113.7841312e-131.50919342.8396294e-11-1.484277e-11 .. 1.91547e-114.3172041e-132.421168640.753517-inf-inf-inf-inf-inf6.361567e-08 .. 0.0-2.777704e-08 .. 2.0913118e-082FGL J2359.6+6543cN4
" ], "text/plain": [ "\n", " Source_Name RAJ2000 DEJ2000 GLON GLAT Conf_68_SemiMajor Conf_68_SemiMinor Conf_68_PosAng Conf_95_SemiMajor Conf_95_SemiMinor Conf_95_PosAng ROI_num Signif_Avg Pivot_Energy Flux_Density Unc_Flux_Density Flux1000 Unc_Flux1000 Energy_Flux100 Unc_Energy_Flux100 Signif_Curve SpectrumType Spectral_Index Unc_Spectral_Index beta Unc_beta Cutoff Unc_Cutoff Exp_Index Unc_Exp_Index PowerLaw_Index Flux30_100 Unc_Flux30_100 nuFnu30_100 Sqrt_TS30_100 Flux100_300 Unc_Flux100_300 [2] nuFnu100_300 Sqrt_TS100_300 Flux300_1000 Unc_Flux300_1000 [2] nuFnu300_1000 Sqrt_TS300_1000 Flux1000_3000 Unc_Flux1000_3000 [2] nuFnu1000_3000 Sqrt_TS1000_3000 Flux3000_10000 Unc_Flux3000_10000 [2] nuFnu3000_10000 Sqrt_TS3000_10000 Flux10000_100000 Unc_Flux10000_100000 [2] nuFnu10000_100000 Sqrt_TS10000_100000 Variability_Index Signif_Peak Flux_Peak Unc_Flux_Peak Time_Peak Peak_Interval Flux_History [48] Unc_Flux_History [48,2] Extended_Source_Name 0FGL_Name 1FGL_Name 2FGL_Name 1FHL_Name ASSOC_GAM1 ASSOC_GAM2 ASSOC_GAM3 TEVCAT_FLAG ASSOC_TEV CLASS1 ASSOC1 ASSOC2 Flags\n", " deg deg deg deg deg deg deg deg deg deg MeV ph / (cm2 MeV s) ph / (cm2 MeV s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) erg / (cm2 s) MeV MeV ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) erg / (cm2 s) ph / (cm2 s) ph / (cm2 s) s s ph / (cm2 s) ph / (cm2 s) \n", " bytes18 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 int16 float32 float32 float32 float32 float32 float32 float32 float32 float32 bytes16 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float32 float64 float32 float32 float32 bytes18 bytes17 bytes18 bytes18 bytes18 bytes15 bytes14 bytes15 bytes1 bytes21 bytes5 bytes26 bytes26 int16\n", "------------------ ------- ------- --------- --------- ----------------- ----------------- -------------- ----------------- ----------------- -------------- ------- ---------- ------------ ---------------- ---------------- ------------- ------------- -------------- ------------------ ------------ ---------------- -------------- ------------------ ------- -------- ------- ---------- --------- ------------- -------------- ------------ -------------- ------------- ------------- ------------- ---------------------------- ------------- -------------- ------------- ------------------------------- ------------- --------------- ------------- ------------------------------- -------------- ---------------- -------------- ----------------------------- --------------- ----------------- ---------------- ---------------------------- ----------------- ------------------- ----------------- ----------- ------------ ------------- --------- ------------- ------------------- ------------------------------ -------------------- ----------------- ------------------ ------------------ ------------------ --------------- -------------- --------------- ----------- --------------------- ------ -------------------------- -------------------------- -----\n", "3FGL J0000.1+6545 0.0377 65.7517 117.69388 3.4029577 0.06284451 0.04810473 41.03 0.1019 0.078 41.03 185 6.813125 1159.0813 1.005343e-12 1.4910649e-13 1.0159622e-09 1.5759212e-10 1.3569529e-11 2.0731739e-12 3.396615 PowerLaw 2.410956 0.08232082 -inf -inf -inf -inf -inf -inf 2.410956 nan nan nan nan 1.8083163e-08 -8.39548e-09 .. 8.236045e-09 4.1752856e-12 2.1687548 6.9407333e-09 -1.3528098e-09 .. 1.3669199e-09 4.543647e-12 5.269711 1.2366493e-09 -2.2512775e-10 .. 2.3434676e-10 2.8553431e-12 6.02224 5.78052e-11 -4.04457e-11 .. 4.8533958e-11 3.7841312e-13 1.5091934 2.8396294e-11 -1.484277e-11 .. 1.91547e-11 4.3172041e-13 2.4211686 40.753517 -inf -inf -inf -inf -inf 6.361567e-08 .. 0.0 -2.777704e-08 .. 2.0913118e-08 2FGL J2359.6+6543c N 4" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# First row\n", "table[0]" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<Column name='Spectral_Index' dtype='float32' length=5>\n", "\n", "\n", "\n", "\n", "\n", "\n", "
2.410956
1.8667319
2.732786
2.1493483
2.3051133
" ], "text/plain": [ "\n", " 2.410956\n", "1.8667319\n", " 2.732786\n", "2.1493483\n", "2.3051133" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Spectral index of the 5 first entries\n", "table[:5][\"Spectral_Index\"]" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Hardest source: 3FGL J2051.3-0828 PSR 0.50000006\n", "Softest source: 3FGL J0534.5+2201s PWN 5.715894\n" ] } ], "source": [ "# Which source has the lowest spectral index?\n", "row = table[np.argmin(table[\"Spectral_Index\"])]\n", "print(\n", " \"Hardest source: \",\n", " row[\"Source_Name\"],\n", " row[\"CLASS1\"],\n", " row[\"Spectral_Index\"],\n", ")\n", "\n", "# Which source has the largest spectral index?\n", "row = table[np.argmax(table[\"Spectral_Index\"])]\n", "print(\n", " \"Softest source: \",\n", " row[\"Source_Name\"],\n", " row[\"CLASS1\"],\n", " row[\"Spectral_Index\"],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Quantities and SkyCoords from a Table" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$$[2.8553431 \\times 10^{-12},~3.5327822 \\times 10^{-13},~6.7680339 \\times 10^{-13},~\\dots,~7.3150578 \\times 10^{-13},~1.0483972 \\times 10^{-12},~4.7821024 \\times 10^{-13}] \\; \\mathrm{\\frac{erg}{s\\,cm^{2}}}$$" ], "text/plain": [ "" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fluxes = table[\"nuFnu1000_3000\"].quantity\n", "fluxes" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "coord = SkyCoord(table[\"GLON\"], table[\"GLAT\"], frame=\"galactic\")\n", "coord.fk5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Selections in a Table\n", "\n", "Here we select Sources according to their class and do some whole sky chart" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "# Get coordinates of FSRQs\n", "fsrq = np.where(\n", " np.logical_or(table[\"CLASS1\"] == \"fsrq \", table[\"CLASS1\"] == \"FSQR \")\n", ")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# This is here for plotting purpose...\n", "# glon = glon.wrap_at(180*u.degree)\n", "\n", "# Open figure\n", "fig = plt.figure(figsize=(14, 8))\n", "ax = fig.add_subplot(111, projection=\"aitoff\")\n", "ax.scatter(\n", " coord[fsrq].l.wrap_at(180 * u.degree).radian,\n", " coord[fsrq].b.radian,\n", " color=\"k\",\n", " label=\"FSRQ\",\n", ")\n", "ax.grid(True)\n", "ax.legend()\n", "# ax.invert_xaxis() -> This does not work for projections..." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Now do it for a series of classes\n", "fig = plt.figure(figsize=(14, 10))\n", "ax = fig.add_subplot(111, projection=\"aitoff\")\n", "\n", "source_classes = [\"\", \"psr\", \"spp\", \"fsrq\", \"bll\", \"bin\"]\n", "\n", "for source_class in source_classes:\n", " # We select elements with correct class in upper or lower characters\n", " index = np.array(\n", " [_.strip().lower() == source_class for _ in table[\"CLASS1\"]]\n", " )\n", "\n", " label = source_class if source_class else \"unid\"\n", "\n", " ax.scatter(\n", " coord[index].l.wrap_at(180 * u.degree).radian,\n", " coord[index].b.radian,\n", " label=label,\n", " )\n", "\n", "ax.grid(True)\n", "ax.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Creating tables\n", "\n", "A `Table` is basically a dict mapping column names to column values, where a column value is a Numpy array (or Quantity object, which is a Numpy array sub-class). This implies that adding columns to a table after creation is nice and easy, but adding a row is hard and slow, basically all data has to be copied and all objects that make up a Table have to be re-created.\n", "\n", "Here's one way to create a `Table` from scratch: put the data into a list of dicts, and then call the `Table` constructor with the `rows` option." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=2\n", "\n", "\n", "\n", "\n", "\n", "
ab
int64str4
42spam
43ham
" ], "text/plain": [ "\n", " a b \n", "int64 str4\n", "----- ----\n", " 42 spam\n", " 43 ham" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rows = [dict(a=42, b=\"spam\"), dict(a=43, b=\"ham\")]\n", "my_table = Table(rows=rows)\n", "my_table" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Writing tables\n", "\n", "Writing tables to files is easy, you can just give the filename and format you want.\n", "If you run a script repeatedly you might want to add `overwrite=True`." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "# Examples how to write a table in different formats\n", "# Uncomment if you really want to do it\n", "\n", "# my_table.write('/tmp/table.fits', format='fits')\n", "# my_table.write('/tmp/table.fits.gz', format='fits')\n", "# my_table.write('/tmp/table.ecsv', format='ascii.ecsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "FITS (and some other formats, e.g. HDF5) support writing multiple tables to a single file.\n", "The `table.write` API doesn't support that directly yet.\n", "Here's how you can currently write multiple tables to a FITS file: you have to convert the `astropy.table.Table` objects to `astropy.io.fits.BinTable` objects, and then store them in a `astropy.io.fits.HDUList` objects and call `HDUList.writeto`." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "my_table2 = Table(data=dict(a=[1, 2, 3]))\n", "hdu_list = fits.HDUList(\n", " [\n", " fits.PrimaryHDU(), # need an empty primary HDU\n", " fits.table_to_hdu(my_table),\n", " fits.table_to_hdu(my_table2),\n", " ]\n", ")\n", "# hdu_list.writeto('tables.fits')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Tables and pandas\n", "\n", "[pandas](http://pandas.pydata.org/) is one of the most-used packages in the scientific Python stack. Numpy provides the `ndarray` object and functions that operate on `ndarray` objects. Pandas provides the `Dataframe` and `Series` objects, which roughly correspond to the Astropy `Table` and `Column` objects. While both `pandas.Dataframe` and `astropy.table.Table` can often be used to work with tabular data, each has features that the other doesn't. When Astropy was started, it was decided to not base it on `pandas.Dataframe`, but to introduce `Table`, mainly because `pandas.Dataframe` doesn't support multi-dimensional columns, but FITS does and astronomers use sometimes.\n", "\n", "But `pandas.Dataframe` has a ton of features that `Table` doesn't, and is highly optimised, so if you find something to be hard with `Table`, you can convert it to a `Dataframe` and do your work there. As explained in the [interfacing with the pandas package](http://docs.astropy.org/en/stable/table/pandas.html) page in the Astropy docs, it is easy to go back and forth between Table and Dataframe:\n", "\n", " table = Table.from_pandas(dataframe)\n", " dataframe = table.to_pandas()\n", "\n", "Let's try it out with the Fermi-LAT catalog.\n", "\n", "One little trick is needed when converting to a dataframe: we need to drop the multi-dimensional columns that the 3FGL catalog uses for a few columns (flux up/down errors, and lightcurves):" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "scalar_colnames = tuple(\n", " name for name in table.colnames if len(table[name].shape) <= 1\n", ")\n", "data_frame = table[scalar_colnames].to_pandas()" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "# If you want to have a quick-look at the dataframe:\n", "# data_frame\n", "# data_frame.info()\n", "# data_frame.describe()" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "b' ' 1010\n", "b'bll ' 642\n", "b'bcu ' 568\n", "b'fsrq ' 446\n", "b'PSR ' 143\n", "b'spp ' 49\n", "b'FSRQ ' 38\n", "b'psr ' 24\n", "b'BLL ' 18\n", "b'glc ' 15\n", "b'rdg ' 12\n", "b'SNR ' 12\n", "b'snr ' 11\n", "b'PWN ' 10\n", "b'BCU ' 5\n", "b'sbg ' 4\n", "b'agn ' 3\n", "b'ssrq ' 3\n", "b'HMB ' 3\n", "b'RDG ' 3\n", "b'nlsy1' 3\n", "b'GAL ' 2\n", "b'pwn ' 2\n", "b'NLSY1' 2\n", "b'css ' 1\n", "b'gal ' 1\n", "b'BIN ' 1\n", "b'NOV ' 1\n", "b'SFR ' 1\n", "b'sey ' 1\n", "Name: CLASS1, dtype: int64" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Just do demonstrate one of the useful DataFrame methods,\n", "# this is how you can count the number of sources in each class:\n", "data_frame[\"CLASS1\"].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you'd like to learn more about pandas, have a look [here](http://pandas.pydata.org/pandas-docs/stable/10min.html) or [here](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "- When searched for the hardest and softest sources in 3FGL we did not look at the type of spectrum (PL, ECPL etc), find the hardest and softest PL sources instead. \n", "- Replot the full sky chart of sources in ra-dec instead of galactic coordinates\n", "- Find the 3FGL sources visible from Paris now" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 2 }