{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Generating a sky map and finding sources" ] }, { "cell_type": "raw", "metadata": {}, "source": [ "
\"Download
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**In this tutorial you will learn how to generate a sky map from the selected events and how to find potential sources in the data.**\n", "\n", "As next step you will make a sky map of the selected events to inspect what’s in the data. You do this using the ctskymap tool. \n", "\n", "We start with the usual gammalib, ctools, and cscripts imports." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import gammalib\n", "import ctools\n", "import cscripts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use the matplotlib package to display the results." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use the events selected in the previous step. Since the data correspond to observations of the Crab nebula we should centre the sky map on this source. The energy limits of the sky map should be set to the energy interval of the data (0.66 - 100 TeV). " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "obsfile = 'obs_crab_selected.xml'\n", "emin = 0.66\n", "emax = 100.0\n", "skymap = ctools.ctskymap()\n", "skymap['inobs'] = obsfile\n", "skymap['proj'] = 'CAR'\n", "skymap['coordsys'] = 'CEL'\n", "skymap['xref'] = 83.63\n", "skymap['yref'] = 22.01\n", "skymap['binsz'] = 0.02\n", "skymap['nxpix'] = 200\n", "skymap['nypix'] = 200\n", "skymap['emin'] = emin\n", "skymap['emax'] = emax\n", "skymap['bkgsubtract'] = 'NONE'\n", "skymap.run()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can visualise the skymap." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#module used to stretch the color palette\n", "import matplotlib.colors as colors\n", "\n", "ax = plt.subplot()\n", "plt.imshow(skymap.skymap().array(),origin='lower',\n", " extent=[83.63+0.02*200,83.63-0.02*200,22.01-0.02*200,22.01+0.02*200],\n", " # boundaries of the coord grid\n", " norm=colors.PowerNorm(gamma=0.5),\n", " cmap=plt.get_cmap('jet')) # square root scale \n", "ax.set_xlabel('R.A. (deg)')\n", "ax.set_ylabel('Dec (deg)')\n", "cbar = plt.colorbar()\n", "cbar.set_label('Counts')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Based on the sky map you can now extract a model for all potentially significant sources in the data. You do this using the cssrcdetect script, and to extract only significant sources, you should set the detection threshold for example to 5 sigma. We will make a copy of the skymap since the detection process involves smoothing and we do not want to modify the original map." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "srcmodel = 'crab.xml'\n", "regfile = 'crab_sources.ds9'\n", "srcdetect = cscripts.cssrcdetect(skymap.skymap().copy())\n", "srcdetect['srcmodel'] = 'POINT'\n", "srcdetect['bkgmodel'] = 'NONE' # we will determine the background model in a later step\n", "srcdetect['threshold'] = 5\n", "srcdetect['corr_rad'] = 0.1\n", "srcdetect['outmodel'] = srcmodel\n", "srcdetect['outds9file'] = regfile\n", "srcdetect.execute()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at the resulting model. It contains a point source Src001 at the position of the Crab nebula." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== GModels ===\n", " Number of models ..........: 1\n", " Number of parameters ......: 6\n", "=== GModelSky ===\n", " Name ......................: Src001\n", " Instruments ...............: all\n", " Observation identifiers ...: all\n", " Model type ................: PointSource\n", " Model components ..........: \"PointSource\" * \"PowerLaw\" * \"Constant\"\n", " Number of parameters ......: 6\n", " Number of spatial par's ...: 2\n", " RA .......................: 83.6192131308071 +/- 0 deg (free,scale=1)\n", " DEC ......................: 22.0199996472185 +/- 0 deg (free,scale=1)\n", " Number of spectral par's ..: 3\n", " Prefactor ................: 5.7e-18 +/- 0 [0,infty[ ph/cm2/s/MeV (free,scale=5.7e-18,gradient)\n", " Index ....................: -2.48 +/- 0 [10,-10] (free,scale=-2.48,gradient)\n", " PivotEnergy ..............: 300000 MeV (fixed,scale=300000,gradient)\n", " Number of temporal par's ..: 1\n", " Normalization ............: 1 (relative value) (fixed,scale=1,gradient)\n", " Number of scale par's .....: 0\n" ] } ], "source": [ "models = gammalib.GModels(srcmodel)\n", "print(models)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can overlay the position of the source we found to the smoothed skymap to make sure everything worked well." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax1 = plt.subplot()\n", "plt.imshow(srcdetect._map.array(),origin='lower',\n", " extent=[83.63+0.02*200,83.63-0.02*200,22.01-0.02*200,22.01+0.02*200],\n", " # boundaries of the coord grid\n", " cmap=plt.get_cmap('jet')) # square root scale \n", "ax1.set_xlabel('R.A. (deg)')\n", "ax1.set_ylabel('Dec (deg)')\n", "cbar = plt.colorbar()\n", "cbar.set_label('Counts')\n", "crab = models['Src001']\n", "ax1.scatter(crab['RA'].value(),crab['DEC'].value(),\n", " marker='x',c='white')" ] }, { "cell_type": "code", "execution_count": null, "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": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }