{ "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/v0.11?urlpath=lab/tree/hess.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", "[hess.ipynb](../_static/notebooks/hess.ipynb) |\n", "[hess.py](../_static/notebooks/hess.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# H.E.S.S. with Gammapy\n", "\n", "This tutorial explains how to analyse [H.E.S.S.](https://www.mpi-hd.mpg.de/hfm/HESS) data with Gammapy.\n", "\n", "We will analyse four observation runs of the Crab nebula, which are part of the [H.E.S.S. first public test data release](https://www.mpi-hd.mpg.de/hfm/HESS/pages/dl3-dr1/). In this tutorial we will make an image and a spectrum. The [light_curve.ipynb](light_curve.ipynb) notbook contains an example how to make a light curve.\n", "\n", "To do a 3D analysis, one needs to do a 3D background estimate. In [background_model.ipynb](background_model.ipynb) we have started to make a background model, and in this notebook we have a first look at a 3D analysis. But the results aren't OK yet, the background model needs to be improved. In this analysis, we also don't use the energy dispersion IRF yet, and we only analyse the data in the 1 TeV to 10 TeV range. The H.E.S.S. data was only released very recently, and 3D analysis in Gammapy is new. This tutorial will be improved soon.\n", "\n", "This tutorial also shows how to do a classical image analysis using the ring bakground. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from scipy.stats import norm\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "from astropy.convolution import Tophat2DKernel\n", "from regions import CircleSkyRegion\n", "from gammapy.data import DataStore\n", "from gammapy.maps import Map, MapAxis, WcsGeom, WcsNDMap\n", "from gammapy.cube import MapMaker, MapDataset, PSFKernel, MapMakerRing\n", "from gammapy.cube.models import SkyModel, BackgroundModel\n", "from gammapy.spectrum.models import PowerLaw, ExponentialCutoffPowerLaw\n", "from gammapy.image.models import SkyGaussian, SkyPointSource\n", "from gammapy.detect import compute_lima_on_off_image\n", "from gammapy.scripts import SpectrumAnalysisIACT\n", "from gammapy.utils.fitting import Fit\n", "from gammapy.background import RingBackgroundEstimator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data access\n", "\n", "To access the data, we use the `DataStore`, and we use the ``obs_table`` to select the Crab runs." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data_store = DataStore.from_file(\n", " \"$GAMMAPY_DATA/hess-dl3-dr1/hess-dl3-dr3-with-background.fits.gz\"\n", ")\n", "mask = data_store.obs_table[\"TARGET_NAME\"] == \"Crab\"\n", "obs_table = data_store.obs_table[mask]\n", "observations = data_store.get_observations(obs_table[\"OBS_ID\"])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# pos_crab = SkyCoord.from_name('Crab')\n", "pos_crab = SkyCoord(83.633, 22.014, unit=\"deg\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Maps\n", "\n", "Let's make some 3D cubes, as well as 2D images.\n", "\n", "For the energy, we make 5 bins from 1 TeV to 10 TeV." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "energy_axis = MapAxis.from_edges(\n", " np.logspace(0, 1.0, 5), unit=\"TeV\", name=\"energy\", interp=\"log\"\n", ")\n", "geom = WcsGeom.create(\n", " skydir=(83.633, 22.014),\n", " binsz=0.02,\n", " width=(5, 5),\n", " coordsys=\"CEL\",\n", " proj=\"TAN\",\n", " axes=[energy_axis],\n", ")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 6.45 s, sys: 362 ms, total: 6.81 s\n", "Wall time: 3.91 s\n" ] } ], "source": [ "%%time\n", "maker = MapMaker(geom, offset_max=\"2.5 deg\")\n", "maps = maker.run(observations)\n", "images = maker.run_images()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['counts', 'exposure', 'background'])" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "maps.keys()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "images[\"counts\"].smooth(3).plot(stretch=\"sqrt\", vmax=2);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## PSF\n", "\n", "Compute the mean PSF for these observations at the Crab position." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from gammapy.irf import make_mean_psf\n", "\n", "table_psf = make_mean_psf(observations, pos_crab)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "psf_kernel = PSFKernel.from_table_psf(table_psf, geom, max_radius=\"0.3 deg\")\n", "psf_kernel_array = psf_kernel.psf_kernel_map.sum_over_axes().data\n", "# psf_kernel.psf_kernel_map.slice_by_idx({'energy': 0}).plot()\n", "# plt.imshow(psf_kernel_array)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Map fit\n", "\n", "Let's fit this source assuming a Gaussian spatial shape and a power-law spectral shape, and a background with a flexible normalisation" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "spatial_model = SkyPointSource(\n", " lon_0=\"83.6 deg\", lat_0=\"22.0 deg\", frame=\"icrs\"\n", ")\n", "spectral_model = PowerLaw(\n", " index=2.6, amplitude=\"5e-11 cm-2 s-1 TeV-1\", reference=\"1 TeV\"\n", ")\n", "model = SkyModel(spatial_model=spatial_model, spectral_model=spectral_model)\n", "background_model = BackgroundModel(maps[\"background\"], norm=1.0)\n", "background_model.parameters[\"tilt\"].frozen = False" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OptimizeResult\n", "\n", "\tbackend : minuit\n", "\tmethod : minuit\n", "\tsuccess : True\n", "\tnfev : 264\n", "\ttotal stat : 61227.19\n", "\tmessage : Optimization terminated successfully.\n", "\n", "CPU times: user 4.69 s, sys: 26.3 ms, total: 4.72 s\n", "Wall time: 2.37 s\n" ] } ], "source": [ "%%time\n", "dataset = MapDataset(\n", " model=model,\n", " counts=maps[\"counts\"],\n", " exposure=maps[\"exposure\"],\n", " background_model=background_model,\n", " psf=psf_kernel,\n", ")\n", "fit = Fit(dataset)\n", "result = fit.run()\n", "print(result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Best fit parameters:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=8\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
namevalueerrorunitminmaxfrozen
str9float64float64str14float64float64bool
lon_08.362e+012.978e-03deg-1.800e+021.800e+02False
lat_02.202e+012.789e-03deg-9.000e+019.000e+01False
index2.634e+009.309e-02nannanFalse
amplitude4.992e-114.170e-12cm-2 s-1 TeV-1nannanFalse
reference1.000e+000.000e+00TeVnannanTrue
norm2.920e+006.042e-020.000e+00nanFalse
tilt-1.991e-022.060e-02nannanFalse
reference1.000e+000.000e+00TeVnannanTrue
" ], "text/plain": [ "\n", " name value error unit min max frozen\n", " str9 float64 float64 str14 float64 float64 bool \n", "--------- ---------- --------- -------------- ---------- --------- ------\n", " lon_0 8.362e+01 2.978e-03 deg -1.800e+02 1.800e+02 False\n", " lat_0 2.202e+01 2.789e-03 deg -9.000e+01 9.000e+01 False\n", " index 2.634e+00 9.309e-02 nan nan False\n", "amplitude 4.992e-11 4.170e-12 cm-2 s-1 TeV-1 nan nan False\n", "reference 1.000e+00 0.000e+00 TeV nan nan True\n", " norm 2.920e+00 6.042e-02 0.000e+00 nan False\n", " tilt -1.991e-02 2.060e-02 nan nan False\n", "reference 1.000e+00 0.000e+00 TeV nan nan True" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result.parameters.to_table()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Parameters covariance:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=8\n", "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
namelon_0lat_0indexamplitudereferencenormtilt
str9float64float64float64float64float64float64float64
lon_08.868e-06-3.307e-071.375e-06-2.489e-170.000e+001.785e-07-5.767e-08
lat_0-3.307e-077.777e-067.601e-071.052e-160.000e+00-3.887e-07-6.703e-08
index1.375e-067.601e-078.665e-033.102e-130.000e+00-2.039e-04-8.827e-05
amplitude-2.489e-171.052e-163.102e-131.739e-230.000e+00-1.314e-14-3.559e-15
reference0.000e+000.000e+000.000e+000.000e+000.000e+000.000e+000.000e+00
norm1.785e-07-3.887e-07-2.039e-04-1.314e-140.000e+003.650e-031.011e-03
tilt-5.767e-08-6.703e-08-8.827e-05-3.559e-150.000e+001.011e-034.246e-04
reference0.000e+000.000e+000.000e+000.000e+000.000e+000.000e+000.000e+00
" ], "text/plain": [ "\n", " name lon_0 lat_0 index ... reference norm tilt \n", " str9 float64 float64 float64 ... float64 float64 float64 \n", "--------- ---------- ---------- ---------- ... --------- ---------- ----------\n", " lon_0 8.868e-06 -3.307e-07 1.375e-06 ... 0.000e+00 1.785e-07 -5.767e-08\n", " lat_0 -3.307e-07 7.777e-06 7.601e-07 ... 0.000e+00 -3.887e-07 -6.703e-08\n", " index 1.375e-06 7.601e-07 8.665e-03 ... 0.000e+00 -2.039e-04 -8.827e-05\n", "amplitude -2.489e-17 1.052e-16 3.102e-13 ... 0.000e+00 -1.314e-14 -3.559e-15\n", "reference 0.000e+00 0.000e+00 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00\n", " norm 1.785e-07 -3.887e-07 -2.039e-04 ... 0.000e+00 3.650e-03 1.011e-03\n", " tilt -5.767e-08 -6.703e-08 -8.827e-05 ... 0.000e+00 1.011e-03 4.246e-04\n", "reference 0.000e+00 0.000e+00 0.000e+00 ... 0.000e+00 0.000e+00 0.000e+00" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result.parameters.covariance_to_table()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Residual image\n", "\n", "We compute a residual image as `residual = counts - model`. Note that this is counts per pixel and our pixel size is 0.02 deg. Smoothing is counts-preserving. The residual image shows that currently both the source and the background modeling isn't very good. The background model is underestimated (so residual is positive), and the source model is overestimated." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "npred = dataset.npred()\n", "residual = Map.from_geom(maps[\"counts\"].geom)\n", "residual.data = maps[\"counts\"].data - npred.data" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "residual.sum_over_axes().smooth(\"0.1 deg\").plot(\n", " cmap=\"coolwarm\", vmin=-0.2, vmax=0.2, add_cbar=True\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectrum\n", "\n", "We could try to improve the background modeling and spatial model of the source. But let's instead turn to one of the classic IACT analysis techniques: use a circular on region and reflected regions for background estimation, and derive a spectrum for the source without having to assume a spatial model, or without needing a 3D background model." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/adonath/github/adonath/gammapy/gammapy/spectrum/extract.py:230: RuntimeWarning: invalid value encountered in true_divide\n", " self.containment = new_aeff.data.data.value / self._aeff.data.data.value\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 5.27 s, sys: 51.8 ms, total: 5.32 s\n", "Wall time: 3.94 s\n" ] } ], "source": [ "%%time\n", "on_region = CircleSkyRegion(pos_crab, 0.11 * u.deg)\n", "exclusion_mask = images[\"counts\"].copy()\n", "exclusion_mask.data = np.ones_like(exclusion_mask.data, dtype=bool)\n", "\n", "model = PowerLaw(\n", " index=2.6, amplitude=\"5e-11 cm-2 s-1 TeV-1\", reference=\"1 TeV\"\n", ")\n", "\n", "config = {\n", " \"outdir\": \".\",\n", " \"background\": {\"on_region\": on_region, \"exclusion_mask\": exclusion_mask},\n", " \"extraction\": {\"containment_correction\": True},\n", " \"fit\": {\"model\": model, \"fit_range\": [1, 10] * u.TeV},\n", " \"fp_binning\": np.logspace(0, 1, 7) * u.TeV,\n", "}\n", "analysis = SpectrumAnalysisIACT(observations=observations, config=config)\n", "analysis.run()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Fit result info \n", "--------------- \n", "Model: PowerLaw\n", "\n", "Parameters: \n", "\n", "\t name value error unit min max frozen\n", "\t--------- --------- --------- -------------- --- --- ------\n", "\t index 2.560e+00 1.080e-01 nan nan False\n", "\tamplitude 4.373e-11 3.981e-12 cm-2 s-1 TeV-1 nan nan False\n", "\treference 1.000e+00 0.000e+00 TeV nan nan True\n", "\n", "Covariance: \n", "\n", "\t name index amplitude reference\n", "\t--------- --------- --------- ---------\n", "\t index 1.166e-02 3.316e-13 0.000e+00\n", "\tamplitude 3.316e-13 1.585e-23 0.000e+00\n", "\treference 0.000e+00 0.000e+00 0.000e+00 \n", "\n", "Statistic: 27.448 (wstat)\n", "Fit Range: [ 1. 10.] TeV\n", "\n" ] } ], "source": [ "print(analysis.fit.result[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Classical Ring Background Analysis\n", "\n", "In this section, we do a classical ring background analysis on the MSH 15-52 region. Let us first select these runs in the datastore" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "data_store = DataStore.from_file(\n", " \"$GAMMAPY_DATA/hess-dl3-dr1/hess-dl3-dr3-with-background.fits.gz\"\n", ")\n", "data_sel = data_store.obs_table[\"TARGET_NAME\"] == \"MSH 15-52\"\n", "obs_table = data_store.obs_table[data_sel]\n", "observations = data_store.get_observations(obs_table[\"OBS_ID\"])" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# pos_msh1552 = SkyCoord.from_name('MSH15-52')\n", "pos_msh1552 = SkyCoord(228.32, -59.08, unit=\"deg\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We first have to define the geometry on which we make our 2D map." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "energy_axis = MapAxis.from_edges(\n", " np.logspace(0, 5.0, 5), unit=\"TeV\", name=\"energy\", interp=\"log\"\n", ")\n", "geom = WcsGeom.create(\n", " skydir=pos_msh1552,\n", " binsz=0.02,\n", " width=(5, 5),\n", " coordsys=\"CEL\",\n", " proj=\"TAN\",\n", " axes=[energy_axis],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Choose an exclusion mask.\n", "We choose an exclusion mask on the position of MSH 1552. " ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "regions = CircleSkyRegion(center=pos_msh1552, radius=0.3 * u.deg)\n", "mask = Map.from_geom(geom)\n", "mask.data = mask.geom.region_mask([regions], inside=False)\n", "mask.get_image_by_idx([0]).plot();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we instantiate the ring background" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "ring_bkg = RingBackgroundEstimator(r_in=\"0.5 deg\", width=\"0.3 deg\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To facilitate classical image analysis, we have a special class called `MapMakerRing`. Here, we do the analysis over the integrated energy range. To do an analysis for each image slice of the map (eg: to investigate the significance of the source detection with energy, just call `run` instead of `run_images`" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 11.4 s, sys: 426 ms, total: 11.8 s\n", "Wall time: 6.01 s\n" ] } ], "source": [ "%%time\n", "im = MapMakerRing(\n", " geom=geom,\n", " offset_max=2.0 * u.deg,\n", " exclusion_mask=mask,\n", " background_estimator=ring_bkg,\n", ")\n", "images = im.run_images(observations)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use `compute_lima_on_off_image` in `gammapy.detect` to compute significance and excess maps. A common debug plot during Ring Analysis is to make histograms of the `off` count rates, so we will plot that as well.\n", "\n", "For this we will first create a Tophat2DKernel convolution kernel for the significance maps. To convert from angles to pixel scales, we use `geom.pixel_scales`:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "scale = geom.pixel_scales[0].to(\"deg\")\n", "# Using a convolution radius of 0.05 degrees\n", "theta = 0.05 * u.deg / scale\n", "tophat = Tophat2DKernel(theta)\n", "tophat.normalize(\"peak\")" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "lima_maps = compute_lima_on_off_image(\n", " images[\"on\"],\n", " images[\"off\"],\n", " images[\"exposure_on\"],\n", " images[\"exposure_off\"],\n", " tophat,\n", ")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "significance_map = lima_maps[\"significance\"]\n", "excess_map = lima_maps[\"excess\"]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "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": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# create a 2D mask for the images\n", "image_mask = mask.slice_by_idx({\"energy\": 0})\n", "significance_map_off = significance_map * image_mask" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fit results: mu = -0.07, std = 1.03\n" ] }, { "data": { "image/png": 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ydvFipyMZ43fKVABUdS5woMTmbsAWzzf7U8C7wHWqukZVh5b4yfJybtc5cOAAAwcOZNmyZVxyySWkpaWRYBd/n2oT34drW/8agF/OmMHbq1c7nMgY/1KZMYDGQPG1ezM920olInVEZBzQSUQev8D7RotIuoik+8vI/6lTpxg+fDjLly/n0ksvLbr4JyQ4HSsodGowhBcGDQJg5Cef8Pm33zqcyBj/UZkCUNqdGecdjVPV/ap6n6peoqrPXOB941W1q6p2rVu3biXiVQ1V5f7772fevHk0btyY2bNnV2palim/R3r14rHevckvLGTEBx8wf8cOpyMZ4xcqcx9AJlD8a24TYFfl4hQRkWuBay+99FJvHM6rSs4uXLjwH8yaNZGwsGpcffUnvPpqsYt/sUXgjG/9dcAAsk+c4NUVKxj6zjvMfeghOnTo4HQsY1ytMi2ApUBLEUkUkQjgFuBTb4RS1amqOrqsa2Y7ZfPmaXzxxW8AGD78TRo16uJwouAlIowbOpQb2rblcG4uV111VanPZjXG/KCs00AnAQuB1iKSKSKjVDUfeACYCWwA3lfVdd4I5Q8PhMnKWsfkybegWki/fmNo1+4mpyMFvdCQEN654QYGJCayZ88errzySruD1JgLsDuBy2nMGDhxIpsJE7px6NB22rX7ETfe+G7pi1XZ/HRH5Oaf4L/b/8iuXem0aDGIn/xkOiEhP6y6ajcJm0BX1juBbS2gCynlSlHwdW/eX/1rDh3eTqPqrbku7i5kzpyqz2bOKzIsmptvnsJ//tOZbdu+YM6cP9G//1NOxzLGdVy5Gqhbu4BUlc83/5PvD68mNqION7f7M+GhFV+Jz/hOjRpNuPHGSYiEMHfun/n228+djmSM67iyALh1EPifixezYs/nhIVEcEu7p6kR6f5pqsGsRYsB9O//NABTptzOwYPbHU5kjLu4sgC4sQUwffNmHpk1C4DrWj9K4xptHE5kyqJPn0dp1epacnIO8sEHI8jPz3E6kjGu4coC4LYWwIZ9+7jlww8pVCWl2R20r3eF05FMGYmEMHz4m8TFtWD37uVMn/6g05GMcQ1XFgA3OZmXx43vv8+R3FxGJCWR2uxOpyOZcqpWLY4f/ehDwsKiWL58Aq+//rrTkYxxBZsFdBG//eILNmRn07pOHd647jqeX2A10y+UmILbALj6kgf5dNNz/Gz0aDotXkzHBhdYptvmipog4MqrmVvGAKZt3sy/ly4lPCSEd268kZgIe/ygP+vUYAidGlxDTn4+N77/PodybDzABDdXFgA3jAFkZWVx1yefAPD0FVfQuWFDx7IY77m65YN0btiQbQcPcseUKRS6+EZIY3zNlQXAaarK3XffTdbx4/Rv3pxf9+rldCTjJWEhEUy+6SZqRUUx9dtvee6bb5yOZIxjgn4MoLSu3qVLX2HatM+JCosluf6zPDUnKB5oFjQS4+J46/rrGTppEk98/TV9mjalT9OmTscypsq5sgXg5BjAvn0bmDXrEQCGtnqEmlF28Q9E17RqxWO9e1Ooyl2ffMKJvDynIxlT5VxZAJwaA8jPz+Wjj35Mfn4Oycl30q5uapWe31StMamptK9Xjy0HDvDEV185HceYKhf0XUDFzZ79e/bsWUlcXAuGDBkLC5c7Hcn4wJhiD+rp2SSBdVk/48XFSzic+xOa1rzM86YS+5R4bUwgcGULwAnbt3/NggUvIBLK9de/RWRkDacjmSrQqHpr+jT9MaB8sulZ8gpsaqgJHlYAgJMnDzBlyh2AkpLyexISejodyVShlGa3Uy8mkQMnd/LV9tecjmNMlQn6AqCqfPbZTzl6dCdNmvQkJeUJpyOZKhYWEsF1rR9FCGHxzg/ZcXiN05GMqRKuLABVOQto1ao3Wb9+MhER1bnhhrcICbFhkWB0TldQ3gmnIxnjc64sAFU1C2jv3r3MnPkwAEOG/Iu4uBY+PZ9xt+JdQV9//aTTcYzxOVcWgKryyCOPkJNziEsvHUJy8h1OxzEOK94VtGjRi+zYMd/pSMb4VNAWgK+++oq3336bsLAorr7636U/1N0EnbO6gj6527qCTEAL7A7v80zezsnP5/5XXgEgpclPiFu1A9hRdbmMq6U0u51NOSvJylrL118/yVVX/d3pSMb4RFC2AJ6dP5/NBw7QNj6eXgk3Ox3HuExYSATXXfcGIqHWFWQCWtAVgM379/PX+UX/oMcNHUpoSLjDiYwbNWrUhT59HuN0V9CJE9YVZAKPKwuAr6aBqio/mzaNUwUFjOzYkZRmzbx6fBNYUlJ+T7167TlwYDPPPPOM03GM8TpXFgBfTQN9d+1avty2jdrVqvHcwIFePbYJPGFhkQwdOh6A559/nm3btjmcyBjvCuxB4GIO5eTw8MyZADw3cCB1Y2IcTmRczfNM4QSgQ/1BrN77BY9ccw1Tbi7jmJGtHmf8gCtbAL7wu6++Yu/x4/ROSOCuTp2cjmP8yMDE0cRGRPDxxo18sXWr03GM8ZqgKACLMzMZl55OWEgI44YOJcTm/JtyqB4Zz5N9+wLwyxkzyCsocDiRMd4RUF1A57S601Ip1AImLL8PBbo3vpnJ63/E5PUOhDN+7aEePXh1xQo2ZGfz0tKlPNSjh9ORjKm0gG8BLN75EXuObaFmZH1Smt3udBzjpyLDwnjxqqsA+GNaGlnHjzucyJjKC+gCcDgni9nbJwJwdctfEhFazeFExp9d06oVV7dsyZHcXH5nj5A0ASCguoBKmrX1ZfIKc2gT35dWdewhL6biTj9GskWtSwiRu3ltxUqE0TSu0ab091ddNGMqLGBbADt2fMP67DmEh0Qx+JIHnI5jAkSd6AR6NL4RUGZs+ReqhU5HMqbCqrQAiMhwEZkgIp+IyJW+Oo+q8sUXvwGgZ5ObqBlVz1enMkEopdntxEbUJvPoelZnfel0HGMqrMwFQEQmikiWiKwtsX2wiGwSkS0i8tiFjqGqH6vqvcBIwGersG3cOIXMzIVEh9eiV8ItvjqNCVKRYTEMTBwNwJfb/kNuvq0TZPxTeVoAbwCDi28QkVDgJWAIkATcKiJJInKZiHxW4qf41/AnPft5XUFBHl9+WVSHUpvdSWRYtC9OY4Jch/qDaFI9iWOnDjB3x/+cjmNMhZS5AKjqXOBAic3dgC2quk1VTwHvAtep6hpVHVriJ0uKPAtMV9XlpZ1HREaLSLqIpO/bt6/cH2jZsvEcOLCZ2rVb0rnh0HLvb0xZiIQw+NJfAMKizMnsP5HhdCRjyq2yYwCNgeJ/8zM9287nF8BAYISI3FfaG1R1vKp2VdWudevWLVeY3NwjzJnzJwAGDvwbofaAd+NDjWu0oWODwRRqPjO3+qRBa4xPVbYAlLamgp7vzao6VlW7qOp9qjruvAet4HLQ33zzPCdO7CMhoRdt2lxfrn2NqYgBifcQGRrD5gOL2bx/kdNxjCmXyhaATIoWTDytCbCrkses0HLQu3btYuHC/wNg0KDn7Rm/pkrERtQmpdkdAHy1/VWbFmr8SmULwFKgpYgkikgEcAvwaeVjld8f//hH8vNP0rbtDSQk9HIigglS3RoPp0ZkXfYe38q6fWlOxzGmzMozDXQSsBBoLSKZIjJKVfOBB4CZwAbgfVVdV9lQ5e0CWrduHRMnTkQklAED7MlNpmqFhUSQ0rRonam0796gUG21UOMfyjML6FZVbaiq4araRFVf82yfpqqtVPUSVf2LN0KVtwvo0UcfpbCwkC5dfkqdOq28EcGYcunYYAhxUY3YfzKDVXtmOh3HmDJx5VIQ5WkBzJ49m88//5zY2Fj69ftDFaQz5lyhIWH0b34XAHO+/y+5ubkOJzLm4lxZAMraAigsLOS3v/0tUNQKiI2tXxXxjClV+3pXUC8mkcO5exk/frzTcYy5KFcWgLJ6//33SU9Pp2HDhjz88MNOxzFBTiSE/s3vBuDpp5/muD0zwLicKwtAWbqAcnNzefzxxwF46qmniLGHvBsXaF2nN42rtyErK4t//etfTscx5oJE9bz3bTmuUaOuOnp0eqm/W7jwH8ya9Svq1k3ivvtWEVLaXb9pab4NaEwpth1cxv9W/5patWqxfft2atWq5XQkE2REZJmqdr3Y+/xyrYTc3KPMm1c04WjgwGdLv/gb45DEWp3p37w5s7/7jv8bNow/X3FF+Q9yzgOujfE+V3cB5eSU3gWUnv4KJ0/up0mTnrRseU0VpzPmwkSEv3gu+v9YtMieH2xcy5UF4PQsoKioc2cBnTp1nAULXgCgX78/2JIPxpV6JiQwtFUrjufl8cy8eU7HMaZU7u47OXr0nH78ZZkfcOLEPhpVb8MlGZGQmVbqrsY47c/9+/PZt9/ySno6v+rZk4RyrG1lTFVwZQvgfPIKclmQ8S4A/ZrdYd/+jat1bNCAm9u1I7eggD/Pnet0HGPO4VcFYPmezzl26gANYlvSsnYPp+MYc1F/Sk0lRISJK1aw5UDJ5ykZ4yxXFoAzg8D5x85syy88xTc7JgH27d/4j9bx8YxMTqZAlT/atGTjMq4sAGcGgcNiz2xbsWc6R09lUz+mBa3r2HLPxn/8oV8/IkJDmbRmDav37nU6jjFnuHsQ2KOgMI/5O94BIKXZHYi4sm4Zc8aYtNSzXndssIMlO6fw4w83MiLp5tL3SU3zfTBjivGLK+mqvbM4kptF3ehmtI3v63QcY8qtd8KthEgY6/fNZf+JTKfjGAP4QQEoKMxn3o63Aejb7Hb79m/8Uo3IuiTXvxKlkAWZ7zodxxjApQWg+CDwmqwvOZSzmzrVEmhXN9XpaMZUWK+EmwFh1Z5ZHM3NdjqOMe4sAMUHgefteAuAvs1uI0RCHU5mTMXFRzclKT6FAs1jYeZkp+MY484CcNrJ/CMcOLmTuKhGXFZvgNNxjKm03k1vBWDZ7k85mXfU4TQm2Lm6ABzN3Q/Yt38TOBpVb02LuK6cKjjJ0l0fOx3HBDlXF4ACzaNWVAM61BvkdBRjvKZPQlErYPHOD8kryHE4jQlmrr8PoE/TnxBq6/2bANK8VicaV2/DzqMbWb5nGt0b3+D9k1T2eQL2PIKg4Oora4iE0bH+VU7HMMarRITeTX/M++v+wMKM9+nacJj7vuRYAQkKLvtbd7bYiNqEhoQ7HcMYr2tTpzfx0U3JPrGDtVlfkdygxBcdu4CaKuDKMYDT9wGE2sCvCVAiIfT2jAXMz5iEaqHDiUwwcmUB+OE+gOpORzHGZy6rN4AakfXIPvE9m/YvcDqOCUKuLADGBIPQkHB6NrkJgPk73kFVHU5kgo0VAGMc1LnhNVQLq8HOoxuY8/33TscxQcYKgDEOigitdmYa6DPz5zucxgQbV88CMiYYdGt8Pd9kvMusrVtZvns3nRs2dDpS5dk0Ur9gLQBjHFYtvAZdGl0LwN+sFWCqkLUAjHGBnk1uYtmuD5m8fj2b9++nZZ06TkdylrUgqoQVAGNcoEZkXdrXG8yKPdO49cPvGdrqxovuY4+QvAArIGVSZV1AItJWRMaJyGQRub+qzmuMvyh6YEzRI1BtqWhTFcpUAERkoohkicjaEtsHi8gmEdkiIo9d6BiqukFV7wN+BHSteGRjAlN8dFMuietKfmEuK/ZMczqOCQJlbQG8AQwuvkFEQoGXgCFAEnCriCSJyGUi8lmJn3qefYYB84GvvPYJjAkg3TxTQpfu+phCLXA4jQl0ZSoAqjoXOFBiczdgi6puU9VTwLvAdaq6RlWHlvjJ8hznU1XtBfzEmx/CmEDRsnZ34qIacShnD9/uX+h0HBPgKjMG0BjIKPY607OtVCKSKiJjReQ/wHnbtyIyWkTSRST9RN7hSsQzxv+IhNCt8fUALNn5kcNpTKCrTAGQUraddzETVU1T1QdV9aeq+tIF3jdeVbuqatfo8JqViGeMf+rYYDDhIVFsP7SCrOPbnY5jAlhlCkAmkFDsdRNgV+XiFDm9HHRO/jFvHM4YvxIVFnvm+QCLrRVgfKgyBWAp0FJEEkUkArgF+NQboX5YDjrWG4czxu90a1TUDbR67xeczDvicBoTqMo6DXQSsBBoLSKZIjJKVfOBB4CZwAbgfVVd541Q1gIwwa5uTLNiU0KnOx3HBKiyzgK6VVUbqmq4qjZR1dc826eTkN24AAAOn0lEQVSpaitVvURV/+KtUNYCMOaHKaFLdk6xKaHGJ2wxOGNc6vSU0MO5e21KqPEJVxYA6wIy5uwpoTYYbHzBlQXAuoCMKXJ6Suh3h1aw99g2p+OYAOPKAmAtAGOKRIXF0rFB0SosS3ZNcTiNCTSuLADWAjDmB6e7gWxKqPE2ex6AMS53epXQrQfTWb5nGr0TbnE6UuALkucJuLIFYIw525lVQnfaKqHGe1xZAGwMwJizFZ8Sumn/AqfjmADhygJgYwDGnO3sVUJtMNh4hysLgDHmXDYl1HibDQIb4ydOTwlduutjluyawpi0R8p9DHuQvCnOlS0AGwMwpnSXNxoOwNqsrzhVcNLhNMbfubIA2BiAMaWrG9OMhBrtOVVwkrVZXzsdx/g5VxYAY8z5dW54DQDLd3/ucBLj76wAGONn2tVNJTI0hp1HN9hgsKkUGwQ2xs+Eh0ZxWf2BpO/6hOV7PmPIpQ86Hcl4WxXdSWwtAGP8UOcGRd1Aq/d+QV5BrsNpjL9yZQGwWUDGXFjD6i1pGNuKnPxjbMie63Qc46dEVZ3OcF6NqrfW0V3+43QMY1wpfdenfL75HzSrmczIji/65Bx234B/kj/9aZmqdr3Y+1zZAjDGXNxl9QYQHhLF94dXsf9EhtNxjB+yAmCMn4oMi6Fdvf6ATQk1FWMFwBg/dnoweNXeWRQU5jmcxvgbKwDG+LEmNZKoG92c43kHbZloU252H4AxfkxE6NzwGmZufYnluz8nqW4/pyOV25i01PLvY4PTXuHKFoBNAzWm7JLrX0mohLP1YDqHcvY4Hcf4EVcWAFsMzpiyqxZeg6S6KYCyYs90p+MYP+LKAmCMKZ9OnsHglXum2zODTZlZATAmADSv1ZHa1RpzJHcfWw4scTqO8RNWAIwJACJyphWwYvc0h9MYf2EFwJgA0bHBVYRIKJv2L+Bo7n6n4xg/YAXAmAARG1Gb1nV6oRSycu8Mp+MYP2AFwJgA0rnhUKCoG0i10OE0xu2sABgTQFrEdaFmZH0O5uziu0MrnY5jXM4KgDEBJERC6dhgCGALxJmLq9ICICIxIrJMRIZW5XmNCSadGgwGYOP++djd9OZCylQARGSiiGSJyNoS2weLyCYR2SIij5XhUI8C71ckqDGmbGpG1ad5zY7kF55iwz57Wpg5v7K2AN4ABhffICKhwEvAECAJuFVEkkTkMhH5rMRPPREZCKwH9noxvzGmFB3qDwKKnhlszPmUaTVQVZ0rIs1LbO4GbFHVbQAi8i5wnao+A5zTxSMi/YEYiorFSRGZpqVMUxCR0cBogJqR9cv+SYwxZyTV7ce0Lf/ku8MrOZSzh1pRDZyOZFyoMmMAjYHiz6HL9Gwrlao+oaoPAe8AE0q7+HveN15Vu6pq1+jwmpWIZ0zwigyLoU2dPgCs2fulw2mMW1WmAEgp2y76hHlVfUNVP7vggW05aGMq7Uw3UNYXqF70n6YJQpUpAJlAQrHXTYBdlYtTxJaDNqbyLql9OTHhcWSf2MHuY986Hce4UGUKwFKgpYgkikgEcAvwqXdiGWMqK0RCaV/vCqDomcHGlFTWaaCTgIVAaxHJFJFRqpoPPADMBDYA76vqOm+Esi4gY7zjdDfQ2qyvKSjMdziNcZuyzgK69TzbpwFeX3tWVacCUxtVb32vt49tTDBpGNuK+OhmZJ/4nq0Hl9KqTk+nIxkXceVD4UXkWuDauKhGTkcxxq+JCMn1r+Sr7RNYvXdWuQtARR7YbvyHK9cCskFgY7znsnoDAWFj9je2NIQ5iysLgDHGe2pG1aN5rY4UaB7r981xOo5xEVcWABsENsa7bGkIUxpXFgDrAjLGu5LiUwgLieD7w6s4lLPH6TjGJVxZAIwx3lV8aYjVtjSE8XBlAbAuIGO8r0P9KwFYvXeWLQ1hAJcWAOsCMsb7LqndlZjwOPafzGDX0U1OxzEu4MoCYIzxvqKlIQYAsDrLloYwVgCMCSrJtjSEKcYKgDFBpEFsS+pGN+NE3mG2HFjidBzjMFcWABsENsY3ROSHwWDrBgp6riwANghsjO+cXhpiU/YCWxoiyLmyABhjfKdmVD0SbWkIgxUAY4JS8XsCTPCyAmBMEGob35dQCef7w2s4mpvtdBzjEFcWABsENsa3IsNiaFmnB6Cs25fmdBzjEFcWABsENsb32tVNBWC9FYCg5coCYIzxvVZ1ehIWEknGkXUczslyOo5xgBUAY4JURGg1WtXuAVgrIFhZATAmiLWr1x+AdftmO5zEOMEKgDFBrGXt7oSHRLHz6EYOntztdBxTxawAGBPEwkOjaF2nF2DdQMHICoAxQc66gYKXKwuA3QdgTNW5tHY3IkKj2X1sMwdO7nQ6jqlCriwAdh+AMVUnLCSCNnV6A7Auy1oBwcSVBcAYU7WSPDeFWTdQcLECYIzhktpdiQyNYe/xbWSf2OF0HFNFrAAYY4q6geL7ANYNFEysABhjAGhX9/RsoDRng5gqYwXAGANAi7guRIVVZ9+J78g6vt3pOKYKWAEwxgAQGhJG2/i+gHUDBQsrAMaYM4p3A6mqw2mMr1VZARCRVBGZJyLjRCS1qs5rjCm7xLhORIfXZP/JDPYe3+p0HONjZSoAIjJRRLJEZG2J7YNFZJOIbBGRxy5yGAWOAVFAZsXiGmN8KURCaRufAthgcDAoawvgDWBw8Q0iEgq8BAwBkoBbRSRJRC4Tkc9K/NQD5qnqEOBR4E/e+wjGGG86/aSwdVmzrRsowIWV5U2qOldEmpfY3A3YoqrbAETkXeA6VX0GGHqBwx0EIssf1RhTFZrVSiYmPI6DObvYfexbGlVv7XQk4yNS1grvKQCfqWp7z+sRwGBVvcfz+nagu6o+cJ79bwCuAmoBr6hq2nneNxoY7XnZGthUxs9S1eKBbKdD+EggfzYI7M8XyJ8N7POVVTNVrXuxN5WpBXAeUsq281YTVf0I+OhiB1XV8cD4SuSqEiKSrqpdnc7hC4H82SCwP18gfzawz+dtlZkFlAkkFHvdBNhVuTjGGGOqSmUKwFKgpYgkikgEcAvwqXdiGWOM8bWyTgOdBCwEWotIpoiMUtV84AFgJrABeF9V1/kuquu4vpuqEgL5s0Fgf75A/mxgn8+ryjwIbIwxJrDYUhDGGBOkrAAYY0yQsgJQQSLyvIhsFJHVIjJFRGo5nckbyrm8h98QkQQRmS0iG0RknYj80ulMviAioSKyQkQ+czqLt4lILRGZ7Pl3t0FEejqdyVtE5GHP38u1IjJJRKKq4rxWACruC6C9qnYAvgUedzhPpZ1veQ9nU3lNPvCIqrYFegA/D6DPVtwvKZqUEYj+CcxQ1TZAMgHyOUWkMfAg0NVzo20oRbMqfc4KQAWp6izPTCiARRTdB+HvzizvoaqngHeB6xzO5BWqultVl3v++yhFF4/GzqbyLhFpAlwDvOp0Fm8TkRpACvAagKqeUtVDzqbyqjCgmoiEAdFU0T1VVgC8425gutMhvKAxkFHsdSYBdpGEM8uadAIWO5vE614EfgsUOh3EB1oA+4DXPV1cr4pIjNOhvEFVdwIvADuA3cBhVZ1VFee2AnABIvKlp0+u5M91xd7zBEXdC287l9RryrW8hz8SkVjgQ+AhVT3idB5vEZGhQJaqLnM6i4+EAZ0pWkesE3AcCIgxKhGJo6ilnQg0AmJE5LaqOHdl1gIKeKo68EK/F5E7KVr5dIAGxg0VAb28h4iEU3Txf9uzNlUg6Q0ME5GrKXrmRg0ReUtVq+RCUgUygUxVPd1qm0yAFABgILBdVfcBiMhHQC/gLV+f2FoAFSQigyl6tsEwVT3hdB4vCdjlPUREKOo/3qCqf3c6j7ep6uOq2kRVm1P0/+3rALr4o6p7gAwROb029QBgvYORvGkH0ENEoj1/TwdQRQPc1gKouH9T9FyDL4r+n7FIVe9zNlLlqGq+iJxe3iMUmBhAy3v0Bm4H1ojISs+236nqNAczmfL5BfC258vJNuAuh/N4haouFpHJwHKKupNXUEVLQthSEMYYE6SsC8gYY4KUFQBjjAlSVgCMMSZIWQEwxpggZQXAGGOClBUA4/dE5AnPSoqrRWSliHT3LBVQocXeRKSRZ1re6deTPMd+WESeEpEL3iBojL+waaDGr3mWBP47kKqquSISD0SoqlfuYBaRBsBiVW3mjeMZ4ybWAjD+riGQraq5AKqaraq7RCRNRLoCiMgoEfnWs22CiPzbs/0NERkrIgtEZJuIjPBsby4iaz3HnwXU87Qs+nr2Of2+yz37rhKRJSJS3bPvPBFZ7vnp5Xlvquf8p9ezf9tz1+f5jhPqeebEUk/r46dV+qdqgoIVAOPvZgEJngv8yyLSr/gvRaQR8HuKngEwCGhTYv+GQB+K1nT6WynHHwZsVdWOqjqv2HEjgPeAX6pqMkXruZwEsoBBqtoZuBkYW+xYnYCHKHrWQgug9wWOM4qiVSEvBy4H7hWRxPL90RhzYbYUhPFrqnpMRLoAfYH+wHty9pPMugFzVPUAgIh8ALQq9vuPVbUQWC8i9ctx6tbAblVd6slxxHP8GODfItIRKChxriWqmul530qgOXD4PMe5EuhwurUB1ARaAtvLkdGYC7ICYPyeqhYAaUCaiKwB7iz269KWuC4utxzvLU4ofansh4G9FD2xKgTIOc+5Cij693e+4wjwC1WdWY5MxpSLdQEZvyYirUWkZbFNHYHvi71eAvQTkTjP05Zu9NKpNwKNRORyT47qnuPXpOgbfSFFi8+FVvA4M4H7PUtYIyKtAuUBKMY9rAVg/F0s8C8RqUXRSopbgNEUrRePqu4Ukb9S9PSvXRQtIXy4sidV1VMicrPn3NUo6rcfCLwMfCgiNwGzKXpwSUWO8ypFXUTLPYPF+4Dhlc1tTHE2DdQEPBGJ9YwVhAFTKFrmeorTuYxxmnUBmWAwxjPoupaiQdSPHc5jjCtYC8AYY4KUtQCMMSZIWQEwxpggZQXAGGOClBUAY4wJUlYAjDEmSP0/OEM/xkedQasAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "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(\"Fit results: mu = {:.2f}, std = {:.2f}\".format(mu, std))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The significance and excess maps clearly indicate a bright source at the position of MSH 1552. This is also evident from the significance distribution. The off distribution should ideally be a Gaussian with `mu=0`, `sigma=1`" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Excess from entire map: 4896.4\n", "Excess from off regions: -1030.4\n" ] } ], "source": [ "print(\n", " \"Excess from entire map: {:.1f}\".format(\n", " np.nansum(lima_maps[\"excess\"].data)\n", " )\n", ")\n", "print(\n", " \"Excess from off regions: {:.1f}\".format(\n", " np.nansum((lima_maps[\"excess\"] * image_mask).data)\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again: please note that this tutorial notebook was put together quickly, the results obtained here are very preliminary. We will work on Gammapy and the analysis of data from the H.E.S.S. test release and update this tutorial soon." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "- Try analysing another source, e.g. RX J1713.7−3946\n", "- Try another model, e.g. a Gaussian spatial shape or exponential cutoff power-law spectrum." ] } ], "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 }