{ "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://static.mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gammapy/gammapy-webpage/v0.17?urlpath=lab/tree/ring_background.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", "[ring_background.ipynb](../_static/notebooks/ring_background.ipynb) |\n", "[ring_background.py](../_static/notebooks/ring_background.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Ring Background Estimation\n", "\n", "## Context:\n", "One of the challenges of IACT analysis is accounting for the large residual hadronic emission. An excess map, assumed to be a map of only gamma-ray events, requires a good estimate of the background. However, in the absence of a solid template bkg model it is not possible to obtain reliable background model a priori. It was often found necessary in classical cherenkov astronomy to perform a local renormalization of the existing templates, usually with a ring kernel. This assumes that most of the events are background and requires to have an exclusion mask to remove regions with bright signal from the estimation. To read more about this method, see [here.](https://arxiv.org/abs/astro-ph/0610959)\n", "\n", "## Objective:\n", "Create an excess (gamma-ray events) map of MSH 15-52 as well as a significance map to determine how solid the signal is.\n", "\n", "## Proposed approach:\n", "\n", "The analysis workflow is roughly\n", " - Compute the sky maps keeping each observation separately using the `Analysis` class\n", " - Estimate the background using the `RingBackgroundMaker`\n", " - Compute the correlated excess and significance maps using the `CorrelatedExcessMapEstimator`\n", " \n", "The normalised background thus obtained can be used for general modelling and fitting." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup\n", "As usual, we'll start with some general imports..." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from regions import CircleSkyRegion\n", "from scipy.stats import norm\n", "\n", "import logging\n", "\n", "log = logging.getLogger(__name__)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's import gammapy specific classes and functions" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from gammapy.analysis import Analysis, AnalysisConfig\n", "from gammapy.makers import RingBackgroundMaker\n", "from gammapy.estimators import ExcessMapEstimator\n", "from gammapy.maps import Map\n", "from gammapy.datasets import MapDatasetOnOff" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Creating the config file\n", "Now, we create a config file for out analysis. You may load this from disc if you have a pre-defined config file.\n", "\n", "In this example, we will use a few HESS runs on the pulsar wind nebula, MSH 1552" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# source_pos = SkyCoord.from_name(\"MSH 15-52\")\n", "source_pos = SkyCoord(228.32, -59.08, unit=\"deg\")" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "config = AnalysisConfig()\n", "# Select observations - 2.5 degrees from the source position\n", "config.observations.datastore = \"$GAMMAPY_DATA/hess-dl3-dr1/\"\n", "config.observations.obs_cone = {\n", " \"frame\": \"icrs\",\n", " \"lon\": source_pos.ra,\n", " \"lat\": source_pos.dec,\n", " \"radius\": 2.5 * u.deg,\n", "}" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "config.datasets.type = \"3d\"\n", "config.datasets.geom.wcs.skydir = {\n", " \"lon\": source_pos.ra,\n", " \"lat\": source_pos.dec,\n", " \"frame\": \"icrs\",\n", "} # The WCS geometry - centered on MSH 15-52\n", "config.datasets.geom.wcs.fov = {\"width\": \"3 deg\", \"height\": \"3 deg\"}\n", "config.datasets.geom.wcs.binsize = \"0.02 deg\"\n", "\n", "# The FoV radius to use for cutouts\n", "config.datasets.geom.selection.offset_max = 3.5 * u.deg\n", "\n", "# We now fix the energy axis for the counts map - (the reconstructed energy binning)\n", "config.datasets.geom.axes.energy.min = \"0.5 TeV\"\n", "config.datasets.geom.axes.energy.max = \"5 TeV\"\n", "config.datasets.geom.axes.energy.nbins = 10\n", "\n", "# We need to extract the ring for each observation separately, hence, no stacking at this stage\n", "config.datasets.stack = False" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AnalysisConfig\n", "\n", " general:\n", " log: {level: info, filename: null, filemode: null, format: null, datefmt: null}\n", " outdir: .\n", " observations:\n", " datastore: $GAMMAPY_DATA/hess-dl3-dr1\n", " obs_ids: []\n", " obs_file: null\n", " obs_cone: {frame: icrs, lon: 228.32 deg, lat: -59.08 deg, radius: 2.5 deg}\n", " obs_time: {start: null, stop: null}\n", " datasets:\n", " type: 3d\n", " stack: false\n", " geom:\n", " wcs:\n", " skydir: {frame: icrs, lon: 228.32 deg, lat: -59.08 deg}\n", " binsize: 0.02 deg\n", " fov: {width: 3.0 deg, height: 3.0 deg}\n", " binsize_irf: 0.2 deg\n", " selection: {offset_max: 3.5 deg}\n", " axes:\n", " energy: {min: 0.5 TeV, max: 5.0 TeV, nbins: 10}\n", " energy_true: {min: 0.1 TeV, max: 10.0 TeV, nbins: 30}\n", " map_selection: [counts, exposure, background, psf, edisp]\n", " background:\n", " method: null\n", " exclusion: null\n", " parameters: {}\n", " safe_mask:\n", " methods: [aeff-default]\n", " parameters: {}\n", " on_region: {frame: null, lon: null, lat: null, radius: null}\n", " containment_correction: true\n", " fit:\n", " fit_range: {min: 0.1 TeV, max: 10.0 TeV}\n", " flux_points:\n", " energy: {min: 0.1 TeV, max: 10.0 TeV, nbins: 30}\n", " source: source\n", " parameters: {}\n", " \n" ] } ], "source": [ "print(config)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting the reduced dataset\n", "We now use the config file to do the initial data reduction which will then be used for a ring extraction" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Setting logging config: {'level': 'INFO', 'filename': None, 'filemode': None, 'format': None, 'datefmt': None}\n", "Fetching observations.\n", "Number of selected observations: 20\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 270 ms, sys: 6.1 ms, total: 276 ms\n", "Wall time: 278 ms\n" ] } ], "source": [ "%%time\n", "# create the config\n", "analysis = Analysis(config)\n", "\n", "# for this specific case,w e do not need fine bins in true energy\n", "analysis.config.datasets.geom.axes.energy_true = (\n", " analysis.config.datasets.geom.axes.energy\n", ")\n", "\n", "# `First get the required observations\n", "analysis.get_observations()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AnalysisConfig\n", "\n", " general:\n", " log: {level: INFO, filename: null, filemode: null, format: null, datefmt: null}\n", " outdir: .\n", " observations:\n", " datastore: $GAMMAPY_DATA/hess-dl3-dr1\n", " obs_ids: []\n", " obs_file: null\n", " obs_cone: {frame: icrs, lon: 228.32 deg, lat: -59.08 deg, radius: 2.5 deg}\n", " obs_time: {start: null, stop: null}\n", " datasets:\n", " type: 3d\n", " stack: false\n", " geom:\n", " wcs:\n", " skydir: {frame: icrs, lon: 228.32 deg, lat: -59.08 deg}\n", " binsize: 0.02 deg\n", " fov: {width: 3.0 deg, height: 3.0 deg}\n", " binsize_irf: 0.2 deg\n", " selection: {offset_max: 3.5 deg}\n", " axes:\n", " energy: {min: 0.5 TeV, max: 5.0 TeV, nbins: 10}\n", " energy_true: {min: 0.5 TeV, max: 5.0 TeV, nbins: 10}\n", " map_selection: [counts, exposure, background, psf, edisp]\n", " background:\n", " method: null\n", " exclusion: null\n", " parameters: {}\n", " safe_mask:\n", " methods: [aeff-default]\n", " parameters: {}\n", " on_region: {frame: null, lon: null, lat: null, radius: null}\n", " containment_correction: true\n", " fit:\n", " fit_range: {min: 0.1 TeV, max: 10.0 TeV}\n", " flux_points:\n", " energy: {min: 0.1 TeV, max: 10.0 TeV, nbins: 30}\n", " source: source\n", " parameters: {}\n", " \n" ] } ], "source": [ "print(analysis.config)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Creating geometry.\n", "Creating datasets.\n", "No background maker set for 3d analysis. Check configuration.\n", "Processing observation 20365\n", "Processing observation 20366\n", "Processing observation 20367\n", "Processing observation 20368\n", "Processing observation 20136\n", "Processing observation 20137\n", "Processing observation 20151\n", "Processing observation 20282\n", "Processing observation 20283\n", "Processing observation 20301\n", "Processing observation 20302\n", "Processing observation 20303\n", "Processing observation 20322\n", "Processing observation 20323\n", "Processing observation 20324\n", "Processing observation 20325\n", "Processing observation 20343\n", "Processing observation 20344\n", "Processing observation 20345\n", "Processing observation 20346\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 13.8 s, sys: 1.62 s, total: 15.4 s\n", "Wall time: 15.7 s\n" ] } ], "source": [ "%%time\n", "# Data extraction\n", "analysis.get_datasets()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Extracting the ring background\n", "\n", "Since the ring background is extracted from real off events, we need to use the wstat statistics in this case. For this, we will use the `MapDatasetOnOFF` and the `RingBackgroundMaker` classes." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create exclusion mask\n", "First, we need to create an exclusion mask on the known sources. In this case, we need to mask only `MSH 15-52` but this depends on the sources present in our field of view." ] }, { "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": [ "# get the geom that we use\n", "geom = analysis.datasets[0].counts.geom\n", "energy_axis = analysis.datasets[0].counts.geom.get_axis_by_name(\"energy\")\n", "geom_image = geom.to_image().to_cube([energy_axis.squash()])\n", "\n", "# Make the exclusion mask\n", "regions = CircleSkyRegion(center=source_pos, radius=0.3 * u.deg)\n", "exclusion_mask = Map.from_geom(geom_image)\n", "exclusion_mask.data = geom_image.region_mask([regions], inside=False)\n", "exclusion_mask.sum_over_axes().plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the present analysis, we use a ring with an inner radius of 0.5 deg and width of 0.3 deg." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "ring_maker = RingBackgroundMaker(\n", " r_in=\"0.5 deg\", width=\"0.3 deg\", exclusion_mask=exclusion_mask\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a stacked dataset\n", "Now, we extract the background for each dataset and then stack the maps together to create a single stacked map for further analysis" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/terrier/Code/anaconda3/envs/gammapy-dev/lib/python3.7/site-packages/astropy/units/quantity.py:481: RuntimeWarning: invalid value encountered in true_divide\n", " result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n" ] } ], "source": [ "#%%time\n", "stacked_on_off = MapDatasetOnOff.create(geom=geom_image)\n", "for dataset in analysis.datasets:\n", " dataset_image = (\n", " dataset.to_image()\n", " ) # Ring extracting makes sense only for 2D analysis\n", " dataset_on_off = ring_maker.run(dataset_image)\n", " stacked_on_off.stack(dataset_on_off)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This `stacked_on_off` has `on` and `off` counts and acceptance maps which we will use in all further analysis. The `acceptance` and `acceptance_off` maps are the system acceptance of gamma-ray like events in the `on` and `off` regions respectively." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MapDatasetOnOff\n", "---------------\n", "\n", " Name : U95u2STT \n", "\n", " Total counts : 40051 \n", " Total predicted counts : nan\n", " Total background counts : nan\n", "\n", " Exposure min : 2.34e+09 m2 s\n", " Exposure max : 8.18e+09 m2 s\n", "\n", " Number of total bins : 22500 \n", " Number of fit bins : 22500 \n", "\n", " Fit statistic type : wstat\n", " Fit statistic value (-2 log(L)) : nan\n", "\n", " Number of models : 0 \n", " Number of parameters : 0\n", " Number of free parameters : 0\n", "\n", " Total counts_off : 88113384 \n", " Acceptance : 22500 \n", " Acceptance off : 49447599 \n", "\n" ] } ], "source": [ "print(stacked_on_off)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Compute correlated significance and correlated excess maps\n", "We need to convolve our maps with an apprpriate smoothing kernel. The significance is computed according to the Li & Ma expression for ON and OFF Poisson measurements, see [here](https://ui.adsabs.harvard.edu/abs/1983ApJ...272..317L/abstract). Since astropy convolution kernels only accept integers, we first convert our required size in degrees to int depending on our pixel size." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Using a convolution radius of 0.04 degrees\n", "estimator = ExcessMapEstimator(0.04 * u.deg)\n", "lima_maps = estimator.run(stacked_on_off, steps=\"ts\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "significance_map = lima_maps[\"significance\"]\n", "excess_map = lima_maps[\"excess\"]" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(
,\n", " ,\n", " )" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# We can plot the excess and significance maps\n", "plt.figure(figsize=(10, 10))\n", "ax1 = plt.subplot(221, projection=significance_map.geom.wcs)\n", "ax2 = plt.subplot(222, projection=excess_map.geom.wcs)\n", "\n", "ax1.set_title(\"Significance map\")\n", "significance_map.get_image_by_idx((0,)).plot(ax=ax1, add_cbar=True)\n", "\n", "ax2.set_title(\"Excess map\")\n", "excess_map.get_image_by_idx((0,)).plot(ax=ax2, add_cbar=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is often important to look at the signficance distribution outside the exclusion region to check that the background estimation is not contaminated by gamma-ray events. This can be the case when exclusion regions are not large enough.\n", "Typically, we expect the off distribution to be a standard normal distribution." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fit results: mu = -0.02, std = 1.00\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# create a 2D mask for the images\n", "significance_map_off = significance_map * exclusion_mask\n", "significance_all = significance_map.data[np.isfinite(significance_map.data)]\n", "significance_off = significance_map_off.data[\n", " np.isfinite(significance_map_off.data)\n", "]\n", "\n", "plt.hist(\n", " significance_all,\n", " density=True,\n", " alpha=0.5,\n", " color=\"red\",\n", " label=\"all bins\",\n", " bins=21,\n", ")\n", "\n", "plt.hist(\n", " significance_off,\n", " density=True,\n", " alpha=0.5,\n", " color=\"blue\",\n", " label=\"off bins\",\n", " bins=21,\n", ")\n", "\n", "# Now, fit the off distribution with a Gaussian\n", "mu, std = norm.fit(significance_off)\n", "x = np.linspace(-8, 8, 50)\n", "p = norm.pdf(x, mu, std)\n", "plt.plot(x, p, lw=2, color=\"black\")\n", "plt.legend()\n", "plt.xlabel(\"Significance\")\n", "plt.yscale(\"log\")\n", "plt.ylim(1e-5, 1)\n", "xmin, xmax = np.min(significance_all), np.max(significance_all)\n", "plt.xlim(xmin, xmax)\n", "\n", "print(f\"Fit results: mu = {mu:.2f}, std = {std:.2f}\")" ] }, { "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": "3.7.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 2 }