{ "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/v0.19?urlpath=lab/tree/tutorials/analysis/2D/ring_background.ipynb)\n", "- You may download all the notebooks in the documentation as a\n", "[tar file](../../../_downloads/notebooks-0.19.tar).\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 map \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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:56.626948Z", "iopub.status.busy": "2021-11-22T21:06:56.626104Z", "iopub.status.idle": "2021-11-22T21:06:57.187083Z", "shell.execute_reply": "2021-11-22T21:06:57.187267Z" } }, "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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.189766Z", "iopub.status.busy": "2021-11-22T21:06:57.189226Z", "iopub.status.idle": "2021-11-22T21:06:57.381499Z", "shell.execute_reply": "2021-11-22T21:06:57.381669Z" } }, "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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.384028Z", "iopub.status.busy": "2021-11-22T21:06:57.383688Z", "iopub.status.idle": "2021-11-22T21:06:57.385110Z", "shell.execute_reply": "2021-11-22T21:06:57.384925Z" } }, "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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.387876Z", "iopub.status.busy": "2021-11-22T21:06:57.387568Z", "iopub.status.idle": "2021-11-22T21:06:57.388800Z", "shell.execute_reply": "2021-11-22T21:06:57.388973Z" } }, "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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.391807Z", "iopub.status.busy": "2021-11-22T21:06:57.391502Z", "iopub.status.idle": "2021-11-22T21:06:57.392629Z", "shell.execute_reply": "2021-11-22T21:06:57.392809Z" } }, "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.width = {\"width\": \"3 deg\", \"height\": \"3 deg\"}\n", "config.datasets.geom.wcs.binsize = \"0.02 deg\"\n", "\n", "# Cutout size (for the run-wise event selection)\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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.397526Z", "iopub.status.busy": "2021-11-22T21:06:57.397186Z", "iopub.status.idle": "2021-11-22T21:06:57.399320Z", "shell.execute_reply": "2021-11-22T21:06:57.399505Z" } }, "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", " required_irf: [aeff, edisp, psf, bkg]\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", " width: {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: 20.0 TeV, nbins: 16}\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: null, max: null}\n", " flux_points:\n", " energy: {min: null, max: null, nbins: null}\n", " source: source\n", " parameters: {selection_optional: all}\n", " excess_map:\n", " correlation_radius: 0.1 deg\n", " parameters: {}\n", " energy_edges: {min: null, max: null, nbins: null}\n", " light_curve:\n", " time_intervals: {start: null, stop: null}\n", " energy_edges: {min: null, max: null, nbins: null}\n", " source: source\n", " parameters: {selection_optional: all}\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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.401741Z", "iopub.status.busy": "2021-11-22T21:06:57.401439Z", "iopub.status.idle": "2021-11-22T21:06:57.439114Z", "shell.execute_reply": "2021-11-22T21:06:57.439296Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Setting logging config: {'level': 'INFO', 'filename': None, 'filemode': None, 'format': None, 'datefmt': None}\n", "Fetching observations.\n", "No HDU found matching: OBS_ID = 20136, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20137, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20151, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20282, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20283, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20301, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20302, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20303, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20322, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20323, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20324, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20325, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20343, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20344, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20345, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20346, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20365, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20366, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20367, HDU_TYPE = rad_max, HDU_CLASS = None\n", "No HDU found matching: OBS_ID = 20368, HDU_TYPE = rad_max, HDU_CLASS = None\n", "Number of selected observations: 20\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 33.9 ms, sys: 2.35 ms, total: 36.3 ms\n", "Wall time: 36.2 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": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.443745Z", "iopub.status.busy": "2021-11-22T21:06:57.443463Z", "iopub.status.idle": "2021-11-22T21:06:57.444856Z", "shell.execute_reply": "2021-11-22T21:06:57.445034Z" } }, "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", " required_irf: [aeff, edisp, psf, bkg]\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", " width: {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: null, max: null}\n", " flux_points:\n", " energy: {min: null, max: null, nbins: null}\n", " source: source\n", " parameters: {selection_optional: all}\n", " excess_map:\n", " correlation_radius: 0.1 deg\n", " parameters: {}\n", " energy_edges: {min: null, max: null, nbins: null}\n", " light_curve:\n", " time_intervals: {start: null, stop: null}\n", " energy_edges: {min: null, max: null, nbins: null}\n", " source: source\n", " parameters: {selection_optional: all}\n", " \n" ] } ], "source": [ "print(analysis.config)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-11-22T21:06:57.446818Z", "iopub.status.busy": "2021-11-22T21:06:57.446528Z", "iopub.status.idle": "2021-11-22T21:07:08.075551Z", "shell.execute_reply": "2021-11-22T21:07:08.075786Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Creating reference dataset and makers.\n", "Creating the background Maker.\n", "No background maker set. Check configuration.\n", "Start the data reduction loop.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 9.94 s, sys: 612 ms, total: 10.6 s\n", "Wall time: 10.6 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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:08.079301Z", "iopub.status.busy": "2021-11-22T21:07:08.078920Z", "iopub.status.idle": "2021-11-22T21:07:08.309633Z", "shell.execute_reply": "2021-11-22T21:07:08.309842Z" } }, "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.axes[\"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 = ~geom_image.region_mask([regions])\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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:08.312242Z", "iopub.status.busy": "2021-11-22T21:07:08.311920Z", "iopub.status.idle": "2021-11-22T21:07:08.313226Z", "shell.execute_reply": "2021-11-22T21:07:08.313489Z" } }, "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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:08.322521Z", "iopub.status.busy": "2021-11-22T21:07:08.322119Z", "iopub.status.idle": "2021-11-22T21:07:09.080595Z", "shell.execute_reply": "2021-11-22T21:07:09.080771Z" } }, "outputs": [], "source": [ "#%%time\n", "energy_axis_true = analysis.datasets[0].exposure.geom.axes[\"energy_true\"]\n", "stacked_on_off = MapDatasetOnOff.create(\n", " geom=geom_image, energy_axis_true=energy_axis_true, name=\"stacked\"\n", ")\n", "\n", "for dataset in analysis.datasets:\n", " # Ring extracting makes sense only for 2D analysis\n", " dataset_on_off = ring_maker.run(dataset.to_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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:09.082709Z", "iopub.status.busy": "2021-11-22T21:07:09.082376Z", "iopub.status.idle": "2021-11-22T21:07:09.094649Z", "shell.execute_reply": "2021-11-22T21:07:09.094888Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MapDatasetOnOff\n", "---------------\n", "\n", " Name : stacked \n", "\n", " Total counts : 39183 \n", " Total background counts : 38320.57\n", " Total excess counts : 862.43\n", "\n", " Predicted counts : 38320.92\n", " Predicted background counts : 38320.92\n", " Predicted excess counts : nan\n", "\n", " Exposure min : 1.11e+09 m2 s\n", " Exposure max : 1.30e+10 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)) : 26399.35\n", "\n", " Number of models : 0 \n", " Number of parameters : 0\n", " Number of free parameters : 0\n", "\n", " Total counts_off : 86301192 \n", " Acceptance : 22500 \n", " Acceptance off : 49478076 \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 appropriate 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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:09.098512Z", "iopub.status.busy": "2021-11-22T21:07:09.098208Z", "iopub.status.idle": "2021-11-22T21:07:09.141405Z", "shell.execute_reply": "2021-11-22T21:07:09.141602Z" } }, "outputs": [], "source": [ "# Using a convolution radius of 0.04 degrees\n", "estimator = ExcessMapEstimator(0.04 * u.deg, selection_optional=[])\n", "lima_maps = estimator.run(stacked_on_off)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-11-22T21:07:09.143553Z", "iopub.status.busy": "2021-11-22T21:07:09.143267Z", "iopub.status.idle": "2021-11-22T21:07:09.144674Z", "shell.execute_reply": "2021-11-22T21:07:09.144857Z" } }, "outputs": [], "source": [ "significance_map = lima_maps[\"sqrt_ts\"]\n", "excess_map = lima_maps[\"npred_excess\"]" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-11-22T21:07:09.155010Z", "iopub.status.busy": "2021-11-22T21:07:09.154690Z", "iopub.status.idle": "2021-11-22T21:07:09.375590Z", "shell.execute_reply": "2021-11-22T21:07:09.375793Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "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.plot(ax=ax1, add_cbar=True)\n", "\n", "ax2.set_title(\"Excess map\")\n", "excess_map.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": { "execution": { "iopub.execute_input": "2021-11-22T21:07:09.380160Z", "iopub.status.busy": "2021-11-22T21:07:09.379819Z", "iopub.status.idle": "2021-11-22T21:07:09.622827Z", "shell.execute_reply": "2021-11-22T21:07:09.623084Z" }, "nbsphinx-thumbnail": { "tooltip": "Create an excess (gamma-ray events) and a significance map extracting a ring background." } }, "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": "3.9.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 2 }