{ "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/fermi_lat.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", "[fermi_lat.ipynb](../_static/notebooks/fermi_lat.ipynb) |\n", "[fermi_lat.py](../_static/notebooks/fermi_lat.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Fermi-LAT data with Gammapy\n", "\n", "## Introduction\n", "\n", "This tutorial will show you how to work with Fermi-LAT data with Gammapy. As an example, we will look at the Galactic center region using the high-energy dataset that was used for the 3FHL catalog, in the energy range 10 GeV to 2 TeV.\n", "\n", "We note that support for Fermi-LAT data analysis in Gammapy is very limited. For most tasks, we recommend you use \n", "[Fermipy](http://fermipy.readthedocs.io/), which is based on the [Fermi Science Tools](https://fermi.gsfc.nasa.gov/ssc/data/analysis/software/) (Fermi ST).\n", "\n", "Using Gammapy with Fermi-LAT data could be an option for you if you want to do an analysis that is not easily possible with Fermipy and the Fermi Science Tools. For example a joint likelihood fit of Fermi-LAT data with data e.g. from H.E.S.S., MAGIC, VERITAS or some other instrument, or analysis of Fermi-LAT data with a complex spatial or spectral model that is not available in Fermipy or the Fermi ST.\n", "\n", "Besides Gammapy, you might want to look at are [Sherpa](http://cxc.harvard.edu/sherpa/) or [3ML](https://threeml.readthedocs.io/). Or just using Python to roll your own analyis using several existing analysis packages. E.g. it it possible to use Fermipy and the Fermi ST to evaluate the likelihood on Fermi-LAT data, and Gammapy to evaluate it e.g. for IACT data, and to do a joint likelihood fit using e.g. [iminuit](http://iminuit.readthedocs.io/) or [emcee](http://dfm.io/emcee).\n", "\n", "To use Fermi-LAT data with Gammapy, you first have to use the Fermi ST to prepare an event list (using ``gtselect`` and ``gtmktime``, exposure cube (using ``gtexpcube2`` and PSF (using ``gtpsf``). You can then use [gammapy.data.EventList](..\/api/gammapy.data.EventList.rst), [gammapy.maps](..\/maps/index.rst) and the [gammapy.irf.EnergyDependentTablePSF](..\/api/gammapy.irf.EnergyDependentTablePSF.rst) to read the Fermi-LAT maps and PSF, i.e. support for these high-level analysis products from the Fermi ST is built in. To do a 3D map analyis, you can use Fit for Fermi-LAT data in the same way that it's use for IACT data. This is illustrated in this notebook. A 1D region-based spectral analysis is also possible, this will be illustrated in a future tutorial. There you have to extract 1D counts, exposure and background vectors and then pass them to [SpectrumFit](..\/api/gammapy.spectrum.SpectrumFit.rst).\n", "\n", "## Setup\n", "\n", "**IMPORTANT**: For this notebook you have to get the prepared ``3fhl`` dataset provided in your $GAMMAPY_DATA.\n", "\n", "Note that the ``3fhl`` dataset is high-energy only, ranging from 10 GeV to 2 TeV." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fermi_3fhl_events_selected.fits.gz\r\n", "fermi_3fhl_exposure_cube_hpx.fits.gz\r\n", "fermi_3fhl_psf_gc.fits.gz\r\n", "gll_iem_v06_cutout.fits\r\n", "iso_P8R2_SOURCE_V6_v06.txt\r\n" ] } ], "source": [ "# Check that you have the prepared Fermi-LAT dataset\n", "# We will use diffuse models from here\n", "!ls -1 $GAMMAPY_DATA/fermi_3fhl" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from astropy import units as u\n", "from astropy.coordinates import SkyCoord\n", "from astropy.table import Table\n", "from astropy.visualization import simple_norm\n", "from gammapy.data import EventList\n", "from gammapy.irf import EnergyDependentTablePSF, EnergyDispersion\n", "from gammapy.maps import Map, MapAxis, WcsNDMap, WcsGeom\n", "from gammapy.spectrum.models import TableModel, PowerLaw, ConstantModel\n", "from gammapy.image.models import SkyPointSource, SkyDiffuseConstant\n", "from gammapy.cube.models import SkyModel, SkyDiffuseCube, BackgroundModel\n", "from gammapy.cube import MapEvaluator, MapDataset, PSFKernel\n", "from gammapy.utils.fitting import Fit" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Events\n", "\n", "To load up the Fermi-LAT event list, use the [gammapy.data.EventList](..\/api/gammapy.data.EventList.rst) class:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "EventList info:\n", "- Number of events: 697317\n", "- Median energy: 1.59e+04 MeV\n", "\n" ] } ], "source": [ "events = EventList.read(\n", " \"$GAMMAPY_DATA/fermi_3fhl/fermi_3fhl_events_selected.fits.gz\"\n", ")\n", "print(events)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The event data is stored in a [astropy.table.Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html) object. In case of the Fermi-LAT event list this contains all the additional information on positon, zenith angle, earth azimuth angle, event class, event type etc." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['ENERGY',\n", " 'RA',\n", " 'DEC',\n", " 'L',\n", " 'B',\n", " 'THETA',\n", " 'PHI',\n", " 'ZENITH_ANGLE',\n", " 'EARTH_AZIMUTH_ANGLE',\n", " 'TIME',\n", " 'EVENT_ID',\n", " 'RUN_ID',\n", " 'RECON_VERSION',\n", " 'CALIB_VERSION',\n", " 'EVENT_CLASS',\n", " 'EVENT_TYPE',\n", " 'CONVERSION_TYPE',\n", " 'LIVETIME',\n", " 'DIFRSP0',\n", " 'DIFRSP1',\n", " 'DIFRSP2',\n", " 'DIFRSP3',\n", " 'DIFRSP4']" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "events.table.colnames" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=5\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
ENERGYRADEC
MeVdegdeg
float32float32float32
12856.5205139.64438-9.93702
14773.319177.0445460.55275
23273.527110.2132537.002018
41866.125334.8528717.577398
42463.074316.8667648.152477
" ], "text/plain": [ "\n", " ENERGY RA DEC \n", " MeV deg deg \n", " float32 float32 float32 \n", "---------- --------- ---------\n", "12856.5205 139.64438 -9.93702\n", " 14773.319 177.04454 60.55275\n", " 23273.527 110.21325 37.002018\n", " 41866.125 334.85287 17.577398\n", " 42463.074 316.86676 48.152477" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "events.table[:5][[\"ENERGY\", \"RA\", \"DEC\"]]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2008-08-04 15:49:26.782\n", "2015-07-30 11:00:41.226\n" ] } ], "source": [ "print(events.time[0].iso)\n", "print(events.time[-1].iso)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mean = 28905.451171875 MeV\n", "std = 61051.7421875 MeV\n", "min = 10000.03125 MeV\n", "max = 1998482.75 MeV\n", "n_bad = 0\n", "length = 697317\n" ] } ], "source": [ "energy = events.energy\n", "energy.info(\"stats\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As a short analysis example we will count the number of events above a certain minimum energy: " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Events above 10 GeV: 697317\n", "Events above 100 GeV: 23628\n", "Events above 1000 GeV: 544\n" ] } ], "source": [ "for e_min in [10, 100, 1000] * u.GeV:\n", " n = (events.energy > e_min).sum()\n", " print(\"Events above {0:4.0f}: {1:5.0f}\".format(e_min, n))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Counts\n", "\n", "Let us start to prepare things for an 3D map analysis of the Galactic center region with Gammapy. The first thing we do is to define the map geometry. We chose a TAN projection centered on position ``(glon, glat) = (0, 0)`` with pixel size 0.1 deg, and four energy bins." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "gc_pos = SkyCoord(0, 0, unit=\"deg\", frame=\"galactic\")\n", "energy_axis = MapAxis.from_edges(\n", " [10, 30, 100, 300, 2000], name=\"energy\", unit=\"GeV\", interp=\"log\"\n", ")\n", "counts = Map.create(\n", " skydir=gc_pos,\n", " npix=(100, 80),\n", " proj=\"TAN\",\n", " coordsys=\"GAL\",\n", " binsz=0.1,\n", " axes=[energy_axis],\n", ")\n", "# We put this call into the same Jupyter cell as the Map.create\n", "# because otherwise we could accidentally fill the counts\n", "# multiple times when executing the ``fill_by_coord`` multiple times.\n", "counts.fill_by_coord(\n", " {\n", " \"skycoord\": events.radec,\n", " # The coord-based interface doesn't use Quantity,\n", " # so we need to pass energy in the same unit as\n", " # used for the map axis\n", " \"energy\": events.energy,\n", " }\n", ")" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "MapAxis\n", "\n", "\tname : energy \n", "\tunit : 'GeV' \n", "\tnbins : 4 \n", "\tnode type : edges \n", "\tedges min : 1.0e+01 GeV\n", "\tedges max : 2.0e+03 GeV\n", "\tinterp : log " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "counts.geom.axes[0]" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "counts.sum_over_axes().smooth(2).plot(stretch=\"sqrt\", vmax=30);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exposure\n", "\n", "The Fermi-LAT datatset contains the energy-dependent exposure for the whole sky as a HEALPix map computed with ``gtexpcube2``. This format is supported by ``gammapy.maps`` directly.\n", "\n", "Interpolating the exposure cube from the Fermi ST to get an exposure cube matching the spatial geometry and energy axis defined above with Gammapy is easy. The only point to watch out for is how exactly you want the energy axis and binning handled.\n", "\n", "Below we just use the default behaviour, which is linear interpolation in energy on the original exposure cube. Probably log interpolation would be better, but it doesn't matter much here, because the energy binning is fine. Finally, we just copy the counts map geometry, which contains an energy axis with `node_type=\"edges\"`. This is non-ideal for exposure cubes, but again, acceptable because exposure doesn't vary much from bin to bin, so the exact way interpolation occurs in later use of that exposure cube doesn't matter a lot. Of course you could define any energy axis for your exposure cube that you like." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "HpxGeom\n", "\n", "\taxes : skycoord, energy\n", "\tshape : (49152, 18)\n", "\tndim : 3\n", "\tnside : 64\n", "\tnested : False\n", "\tcoordsys : CEL\n", "\tprojection : HPX\n", "\tcenter : 0.0 deg, 0.0 deg\n", "\n", "MapAxis\n", "\n", "\tname : energy \n", "\tunit : '' \n", "\tnbins : 18 \n", "\tnode type : center \n", "\tcenter min : 1.0e+04 \n", "\tcenter max : 2.0e+06 \n", "\tinterp : log \n", "\n" ] } ], "source": [ "exposure_hpx = Map.read(\n", " \"$GAMMAPY_DATA/fermi_3fhl/fermi_3fhl_exposure_cube_hpx.fits.gz\"\n", ")\n", "# Unit is not stored in the file, set it manually\n", "exposure_hpx.unit = \"cm2 s\"\n", "print(exposure_hpx.geom)\n", "print(exposure_hpx.geom.axes[0])" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "exposure_hpx.plot();" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WcsGeom\n", "\n", "\taxes : lon, lat, energy\n", "\tshape : (100, 80, 4)\n", "\tndim : 3\n", "\tcoordsys : GAL\n", "\tprojection : TAN\n", "\tcenter : 0.0 deg, 0.0 deg\n", "\twidth : 10.0 deg x 8.0 deg deg\n", "\n", "MapAxis\n", "\n", "\tname : energy \n", "\tunit : 'GeV' \n", "\tnbins : 4 \n", "\tnode type : center \n", "\tcenter min : 1.7e+01 GeV\n", "\tcenter max : 7.7e+02 GeV\n", "\tinterp : log \n", "\n" ] } ], "source": [ "# For exposure, we choose a geometry with node_type='center',\n", "# whereas for counts it was node_type='edge'\n", "axis = MapAxis.from_nodes(\n", " counts.geom.axes[0].center, name=\"energy\", unit=\"GeV\", interp=\"log\"\n", ")\n", "geom = WcsGeom(wcs=counts.geom.wcs, npix=counts.geom.npix, axes=[axis])\n", "\n", "coord = counts.geom.get_coord()\n", "data = exposure_hpx.interp_by_coord(coord)\n", "exposure = WcsNDMap(geom, data, unit=exposure_hpx.unit)\n", "print(exposure.geom)\n", "print(exposure.geom.axes[0])" ] }, { "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": [ "# Exposure is almost constant accross the field of view\n", "exposure.slice_by_idx({\"energy\": 0}).plot(add_cbar=True);" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([3.26723811e+11, 3.26671386e+11, 3.26469134e+11])" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Exposure varies very little with energy at these high energies\n", "energy = [10, 100, 1000] * u.GeV\n", "exposure.get_by_coord({\"skycoord\": gc_pos, \"energy\": energy})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Galactic diffuse background" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Fermi-LAT collaboration provides a galactic diffuse emission model, that can be used as a background model for\n", "Fermi-LAT source analysis.\n", "\n", "Diffuse model maps are very large (100s of MB), so as an example here, we just load one that represents a small cutout for the Galactic center region." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WcsGeom\n", "\n", "\taxes : lon, lat, energy\n", "\tshape : (88, 48, 30)\n", "\tndim : 3\n", "\tcoordsys : GAL\n", "\tprojection : CAR\n", "\tcenter : 0.0 deg, -0.1 deg\n", "\twidth : 11.0 deg x 6.0 deg deg\n", "\n", "MapAxis\n", "\n", "\tname : energy \n", "\tunit : 'MeV' \n", "\tnbins : 30 \n", "\tnode type : center \n", "\tcenter min : 5.8e+01 MeV\n", "\tcenter max : 5.1e+05 MeV\n", "\tinterp : log \n", "\n" ] } ], "source": [ "diffuse_galactic_fermi = Map.read(\n", " \"$GAMMAPY_DATA/fermi_3fhl/gll_iem_v06_cutout.fits\"\n", ")\n", "# Unit is not stored in the file, set it manually\n", "diffuse_galactic_fermi.unit = \"cm-2 s-1 MeV-1 sr-1\"\n", "print(diffuse_galactic_fermi.geom)\n", "print(diffuse_galactic_fermi.geom.axes[0])" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WcsGeom\n", "\n", "\taxes : lon, lat, energy\n", "\tshape : (100, 80, 4)\n", "\tndim : 3\n", "\tcoordsys : GAL\n", "\tprojection : TAN\n", "\tcenter : 0.0 deg, 0.0 deg\n", "\twidth : 10.0 deg x 8.0 deg deg\n", "\n", "MapAxis\n", "\n", "\tname : energy \n", "\tunit : 'GeV' \n", "\tnbins : 4 \n", "\tnode type : center \n", "\tcenter min : 1.7e+01 GeV\n", "\tcenter max : 7.7e+02 GeV\n", "\tinterp : log \n", "\n" ] } ], "source": [ "# Interpolate the diffuse emission model onto the counts geometry\n", "# The resolution of `diffuse_galactic_fermi` is low: bin size = 0.5 deg\n", "# We use ``interp=3`` which means cubic spline interpolation\n", "coord = counts.geom.get_coord()\n", "\n", "data = diffuse_galactic_fermi.interp_by_coord(\n", " {\n", " \"skycoord\": coord.skycoord,\n", " \"energy\": coord[\"energy\"]\n", " * counts.geom.get_axis_by_name(\"energy\").unit,\n", " },\n", " interp=3,\n", ")\n", "diffuse_galactic = WcsNDMap(\n", " exposure.geom, data, unit=diffuse_galactic_fermi.unit\n", ")\n", "\n", "print(diffuse_galactic.geom)\n", "print(diffuse_galactic.geom.axes[0])" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "diffuse_galactic.slice_by_idx({\"energy\": 0}).plot();" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Flux (cm-2 s-1 MeV-1 sr-1)')" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Exposure varies very little with energy at these high energies\n", "energy = np.logspace(1, 3, 10) * u.GeV\n", "dnde = diffuse_galactic.interp_by_coord(\n", " {\"skycoord\": gc_pos, \"energy\": energy}, interp=\"linear\", fill_value=None\n", ")\n", "plt.plot(energy.value, dnde, \"*\")\n", "plt.loglog()\n", "plt.xlabel(\"Energy (GeV)\")\n", "plt.ylabel(\"Flux (cm-2 s-1 MeV-1 sr-1)\")" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# TODO: show how one can fix the extrapolate to high energy\n", "# by computing and padding an extra plane e.g. at 1e3 TeV\n", "# that corresponds to a linear extrapolation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Isotropic diffuse background\n", "\n", "To load the isotropic diffuse model with Gammapy, use the [gammapy.spectrum.models.TableModel](..\/api/gammapy.spectrum.models.TableModel.rst). We are using `'fill_value': 'extrapolate'` to extrapolate the model above 500 GeV:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "filename = \"$GAMMAPY_DATA/fermi_3fhl/iso_P8R2_SOURCE_V6_v06.txt\"\n", "interp_kwargs = {\"fill_value\": None}\n", "diffuse_iso = TableModel.read_fermi_isotropic_model(\n", " filename=filename, interp_kwargs=interp_kwargs\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the model in the energy range between 50 GeV and 2000 GeV:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAEOCAYAAACjJpHCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3Xd4VHXaxvHvk1BCkw4qBOm9KkVABJRVUBDbKuprW0Rxrdjd1XWVVXctWBEbomsBEQtSFBUpUhRBQJoUBSEiHek1PO8fCbvZSJIhM5MzM7k/1zWXmTNnztzgwMP5VXN3RERE8isp6AAiIhLfVEhERCQsKiQiIhIWFRIREQmLComIiIRFhURERMKiQiIiImFRIRERkbCokIiISFhUSEREJCxFgg5QECpVquQ1a9YMOoaISFyZM2fOJnevnNd5haKQ1KxZk9mzZwcdQ0QkrpjZz6Gcl9BNW2bWy8xe3rZtW9BRREQSVkIXEncf4+7Xli1bNugoIiIJK6ELiYiIRJ8KiYiIhEWFREREwqJCIiIiYVEhyYW788F3aew/eCjoKCIiMUuFJBdzft7KbSPnc/nQb9i6a3/QcUREYpIKSS5a16zA0xe3ZO6a3+g9eDrL1+8IOpKISMxRIcnDua2q8e61J7N7fzrnvTCDST9sCDqSiEhMUSEJQasa5fn4xo7UqFCSvm98y6tf/YS7Bx1LRCQmqJCE6PhyJRh1fXvOaHws/xi3hLvf/16d8CIiqJAclZLFivDCZSdy82l1GTk7jcte/ZrNO/cFHUtEJFAxX0jMrLaZDTWzUVmONTKzF81slJldX5B5kpKM285owLOXtOL7tG30HjydpevUCS8ihVdUC4mZvWZmG8xsYbbj3c1sqZmtMLN7cruGu//k7n2zHVvi7v2Bi4DWkU+et3NaHM+717Vn/8FDnP/CdCYuWR9EDBGRwEX7juR1oHvWA2aWDAwGegCNgUvMrLGZNTOzsdkeVXK6sJmdA0wDJkYvfu5appbj4xtPoXbl0lzz79m8NOVHdcKLSKET1ULi7lOBLdkOtwVWZN5p7AdGAL3dfYG798z2yHGsrbt/7O4dgMui9yvI27FlUxh5XXvOanocj37yA3eO+p59B9ODjCQiUqCC6COpBqzJ8jwt89gRmVlFM3sRaGVm92Ye62Jmz5rZS8D4HN53rZnNNrPZGzdujGD83ytRLJnnL23Frd3qMWpOGpe98g2b1AkvIoVEEFvt2hGO5dge5O6bgf7Zjk0GJuf2Ie7+MvAyQOvWraPe3mRm3NqtPnWrlOb2kfPp/fx0Xr2yNY2OOybaHy0iEqgg7kjSgNQsz6sDawPIERU9mx/Pe/3bc/DQIS4cMoPPF6sTXkQSWxCF5FugnpnVMrNiQB/g42h8UFB7tjevntEJX7dKaa59czYvTF6hTngRSVjRHv47HJgJNDCzNDPr6+4HgRuBCcASYKS7L4rG5we5Z3vVY1J497r29Gx+PI99upTbR85n7wF1wotI4olqH4m7X5LD8fHk0EmeSFKKJvNsn5bUq1KaQZ8vY+XmXbx0+UlUKZMSdDQRkYiJ+Znt4QiqaStbBm4+vR5DLjuRH37dwbnPT2fR2uDyiIhEWkIXkiCbtrLr0ew43uvfHgcuHDKT0fN+Ub+JiCSEhC4ksaZptbKMvqEjjY4rwy0j5nH9W9+xcYfmm4hIfEvoQhILTVvZVTkmYyb8PT0a8uXSDfzhqSl8ODdNdyciEresMPwF1rp1a589e3bQMX5nxYad3DlqPnNX/0bn+pV5+LymVC9fMuhYIiIAmNkcd89zYdyEviOJdXWrlGZU/w78vVdjvl21hTOemsqw6StJP5T4xV1EEocKScCSk4yrOtbiswGn0qZmBR4cs5gLhsxg2XrtcSIi8SGhC0ks9pHkpHr5krx+dRuevrglP2/exdnPfsWgz5dpJWERiXnqI4lBm3fuY+DYxXw0by11q5TmXxc046QTKgQdS0QKGfWRxLGKpYvzdJ9WDLu6DXv2p3PhizP52+iF7Nx3MOhoIiK/o0ISw7o2qMJnA07lqg41efPrnzlj0BS+/EGrCYtIbFEhiXGlihfhgV5NeP/6DpROKcKfXp/NzcPnauMsEYkZCV1I4qmzPS8n1ijP2Js6MaBbfT5Z+CvdBk3h/TmayCgiwVNnexxavn4Hd7//Pd+t/o1O9SrxyHnNSK2giYwiElnqbE9g9aqWYVT/Djx4ThO++3krZzw1laHTNJFRRIKhQhKnkpKMKzvU5LPbOnNy7QoMHJsxkXHFhp1BRxORQkaFJM5VK1eC165qwzN9/juRcei0lRzS3YmIFJCELiSJ1NmeGzOjd8tqTBhwKqfUrcTAsYvp88rXrNmyO+hoIlIIqLM9wbg7781J46Exi3F3HujVhD+2ro6ZBR1NROKMOtsLKTPjotapfHprJ5pVL8td739Pv3/P1gZaIhI1KiQJqnr5krxzzcncd3Yjpi7fxJlPT+XTheuCjiUiCUiFJIElJRnXdKrNuJtO4fhyKfR/aw63jZzHtj0Hgo4mIglEhaQQqFe1DB/+uSM3n16P0fPW0uPpqUxfsSnoWCKSIFRIComiyUnc9of6vH99B1KKJnPZq9/w948XsWe/9jsRkfDkWkjMbHsejx1mtqygwh6twjL892i0TC3HuJs7cVWHmrw+YxVnP/cV89f8FnQsEYljed2R/Ojux+TyKAPsKoig+eHuY9z92rJlywYdJaaUKJbM389pwlt927FnfzrnD5nBoM+XcSD9UNDRRCQO5VVILgjhGqGcIzHolHqV+PTWU+nd4nienbic81+YwYoN2iteRI5OroXE3X/K+tzMSplZcm7nSHwpW6Iogy5uyZDLTiRt627OenaallgRkaOSVx9JkpldambjzGwD8APwq5ktMrPHzaxewcSUaOvR7DgmDDiVTplLrFz66tekbdUSKyKSt7yatiYBdYB7gWPdPdXdqwCdgK+Bf5rZ/0U5oxSQKmVSePXK1vzrgmYsSNtG96e/4r3Za7R5lojkKte1tsysqLvnOnstlHOCVpjW2oqUNVt2c/vI+cxatYU+bVJ5qHdTihXRaHGRwiQia225+4HM5q2FuZ2Tn4AS21IrlGT4tSdzQ9c6jPh2DZcP/YYtu/YHHUtEYlCe/8R090PAfDOrUQB5JIYkJxl3ntmQpy5uwdw1v3Hu4OnaOEtEfifUtorjgEVmNtHMPj78iGYwiR3ntarOiGtPZvf+g1wwZAazVm4JOpKIxJCQ9iMxs85HOu7uUyKeKArURxIZqzfv5qrXZ5G2ZQ9PXtSCXi2ODzqSiERRpPcjmQ18lVk4fgXKAjPCyFcgtERKZNWoWJIPru9Ai9Sy3DR8Li9N+VEjukQk5EIyFUgxs2rAROBq4PVohYoULZESeeVKFuPNvu3o2fw4Hv3kB/42ehEHtbSKSKFWJMTzzN13m1lf4Dl3f8zM5kUzmMSulKLJPNunFdXKl+ClKT+x9rc9PHdpK0oWC/XrJCKJJNQ7EjOz9sBlwLjMY8m5nC8JLinJuLdHIwb2bsKkpRvo8/LXbNixN+hYIhKAUAvJLWTMbv/Q3ReZWW0yZr1LIXd5+5q8fHlrlq/fmbnoo4YHixQ2IY3aincatRV989f8Rt83vuVAuvPy5SfRrnbFoCOJSJgiPWpLJFctUsvx4Z87UrF0MS4fOouP568NOpKIFBAVEomY1AoZw4Nbppbj5uFzeVHDg0UKBRUSiahyJYvx775t6dXieP75yQ/cP3qhhgeLJLiQComZPWZmx5hZ0cxlUjZp+XjJSUrRZJ65uCX9O9fhra9Xc92bc9i9/2DQsUQkSkK9IznD3bcDPYE0oD5wZ9RSSdxLSjLu6dGQgec21fBgkQQXaiEpmvnfs4Dh7q5V+yQkl598QrbhwdoTXiTRhFpIxpjZD0BrYKKZVQb0z0sJSbfGVXn3upPZeyCd81+YwTc/bQ46kohEUEiFxN3vAdoDrTM3stoN9I5msMPMrLaZDTWzUdmOlzKzOWbWsyBySHiaV88YHly5THEuHzqLD+emBR1JRCIk5FFb7r7V3dMzf97l7uvyeo+ZvWZmG7LvsGhm3c1sqZmtMLN78vjcn9y97xFeuhsYGWp+CV5qhZK8f30HWtUox4B35/OPsYs1okskAUR7+O/rQPesB8wsGRgM9AAaA5eYWWMza2ZmY7M9qhzpombWDVgMrI9ufIm0ciWL8dY17biy/Qm8Om0lVw6bpS18ReJcVJdrdfepZlYz2+G2wAp3/wnAzEYAvd39UTJGhYWiK1CKjEK0x8zGZ24JLHGgaHISD/ZuSpNqZbnvw4X0em4aQ/7vRJpXLxd0NBHJh1zvSMxssZn91czqRPAzqwFrsjxPyzyWU4aKZvYi0MrM7gVw97+6+63AO8ArRyoiZnatmc02s9kbN26MYHyJlItap/Je//YAXDhkJu98s1oz4UXiUF5NW5cApYHPzOwbM7vVzMLdX9WOcCzHvz3cfbO793f3Opl3LVlfe93dx+bwvpfdvbW7t65cuXKYkSVaWqSWY8xNp9CudgX+8uEC7hz1PXsPpAcdS0SOQq6FxN3nu/u97l6HjKXkTwC+NrMvzaxfPj8zDUjN8rw6oBX+CrEKpYrx+tVtufn0eoyak8Z5L8zg5827go4lIiE6mlFbX7v7AOAKoDzwfD4/81ugnpnVMrNiQB/g43xeK1fasz1+JCcZt/2hPsOuasPa3/bQ87lpTFyisRQi8SDUtbbamNkgM/sZeBB4mVz6NbK8bzgwE2hgZmlm1tfdDwI3AhOAJcBId1+U719BLrRne/zp2rAKY286hRMqlqTvG7N5fMIPpB9Sv4lILMt1YyszewS4GNgKjABGuHvczSTTxlbxZ++BdB4YvYh3Z6/hlLqVeKZPSyqWLh50LJFCJVIbW+0DemR2Wj8Rb0VETVvxK6VoMv+6sDn/uqAZs1Ztoedz05i7emvQsUTkCPLqbH/Q3ZeZWUkzu9/MXgEws3rxsDSJmrbi38VtavB+/w4kJxkXvTSTN2eu0hBhkRgTamf7MDLuTtpnPk8D/hGVRCLZNKtelrE3nULHupW4f/Qibhs5nz37NURYJFaEWkjquPtjwAEAd9/DkeeDxBQ1bSWOciWL8dqVbRjQrT4fzfuF816YzspNGiIsEgtCLST7zawEmRMHM2e674taqghR01ZiSUoybulWj2FXtWHd9r2c89w0PluU59qhIhJloRaSB4BPgVQzexuYCNwVtVQiuejSIGOIcK3Kpbj2zTn885MftIqwSIByHf77PyeaVQROJqNJ62t33xTNYJGk4b+Jae+BdB4cs5jhs1bTvnZFnr2kFZXLaIiwSKSEOvw3r3kkJ+b2Znf/Lh/ZCoyZ9QJ61a1bt9/y5cuDjiNR8t7sNdz30ULKpBTh7+c04exmx2EW8114IjEvUoXkELAIOLx8btY/ne7up4WVsoDojiTxLfl1O3eN+p4Fv2yjW6MqPNS7KceXKxF0LJG4FqlCMgC4ANhGxsz2D919Z8RSFhAVksLhYPohhk1fxZOfLyXJjD93qcM1nWqTUjQ56GgicSkihSTLxWqRsaR8b+Bn4BF3nxd2ygKiQlK4rNmym4fHLeHTReuoVq4Ed/doSK/mau4SOVqRWiIFAHdfCYwGPiNjh8P64cUTiZ7UCiV58fKTGN7vZMqWKMrNw+dy4Yszmbfmt6CjiSSkvJq2apOxzHtvMnY1HAGMdfe9BRMvPOpsl/RDzqg5a3h8wlI27dzP+a2qcVf3hhxbNiXoaCIxL5Kd7d+TcTeynWw7Gbr7oDBzFgg1bcmOvQcYPOlHXpu2kuQk4/oudejXqTYliqn/RCQnkWraegj4EDhExpa7ZbI9ROJCmZSi3NOjIV/c1pmuDSsz6PNlnP7kZEbP+0WLQIqEKeQJifFMdySS3Tc/bWbguMUs/GU7J9Yox/09G9OqRvmgY4nElIh2toskmna1K/LxDafw2IXNWbN1D+e9MIMB787j1217go4mEncS+o5Ene0Sip37DjJk8gpe+WolSQbXnVqH/p3rqP9ECr2IziOJd2raklCs2bKbf37yA+MW/MpxZVO4u3tDzmlxPElJmn8ihVPEmrbMrKGZnW5mpbMd7x5OQJFYk1qhJIMvO5GR17WnUuni3PruPM4fMoP5mn8ikqtcC4mZ3UzG0N+bgIVm1jvLy49EM5hIUNrWqsDoGzryxB9b8Mtvezj3henc8/73bN4Z81vwiASiSB6v9wNOcvedZlYTGGVmNd39GeJgh0SR/EpKMi48qTpnNqnKsxOXM2z6KsYv+JU7uzfk0rY1SFZzl8h/5NW0lXx4kUZ3XwV0AXqY2SBUSKQQKJNSlL+e3ZhPb+1Ek+PLcv9HCznvhel8n6bmLpHD8iok68ys5eEnmUWlJ1AJaBbNYCKxpG6VMrzTrx3P9GnJr9v20nvwdO77aAHbdh8IOppI4PIqJFcA/7MptrsfdPcrgFOjlkokBpkZvVtWY+LtnbmqQ03e+WY1pz05mfdmr9HseCnUjmar3fJAKln6VbRDohRmi9du5/7RC5nz81ba1CzPwHOb0vDYY4KOJRIxkd6PZCBwFfAj/124UTskSqF36JAzak4aj36yhO17D3JVh5oM+EN9ShfPaxyLSOyLdCFZCjRz9/2RCFfQVEgk2rbu2s9jE5Yy4tvVVClTnPt7Ntbe8RL3Ir3W1kKgXHiRRBJX+VLFePT8ZnxwfQcqlS7Oje/M5fKhs/hxY9ztTC1y1EK9I2lNxsTEhcB/ZmW5+znRixY5uiORgpR+yHn7m595fMJS9h5I57pT63BD17pau0viTqSbthYBLwELyNibBAB3nxJOyIKiQiJB2LhjH4+OX8IHc3+hevkS/L1XE7o1rhp0LJGQRbqQTHH3zhFJFgAVEgnS1z9t5v6PFrJ8w066NarCA72akFqhZNCxRPIU6UIyiIwmrY/536atmB7+e5gKiQTtQPohXpu2kqe/WI7j3Hx6Pfp1qk3RZG0JJLEr0oVk0hEOa/ivyFFa+9seHhyziAmL1tPw2DI8cn4zTtTOjBKjtB9JFiokEms+W7SOBz5exLrte7myfU3uPLMBpTT3RGJMRIf/mtkjZlYuy/PyZvaPcAIWBDPrZWYvb9u2LegoIv/jjCbH8vltnbmyfU3emLmKM56aypRlG4OOJZIvoTbQ9nD3/yx36u5bgbOiEyly3H2Mu19btmzZoKOI/E7p4kX4+zlNGNW/PSlFk7jytVncNnIev+2Oy3m/UoiFWkiSzaz44SdmVgIonsv5IhKik06owLibO3Fj17p8PG8t3QZNYfyCX4OOJRKyUAvJW8BEM+trZn8CPgfeiF4skcIlpWgyd5zZgNE3duTYsin8+e3v6P/mHDZs3xt0NJE8Hc3qv92BbmRsaPWZu0+IZrBIUme7xJOD6Yd45auVPP3FMooXSeK+sxvzx9bVtW6XFLiIjNoyM/M8Kk0o5wRNhUTi0U8bd3LPBwuYtXILHetW5J/nN9dERilQkRq1NcnMbjKzGtkuXszMTjOzN4ArwwkqIkdWu3JpRvQ7mX+c25T5a7ZxxlNTeW3aStIPxfS/26QQyquQdAfSgeFmttbMFpvZSmA5cAnwlLu/HuWMIoVWUpLxfyefwGcDTqVd7Qo8NHYxF744g+XrdwQdTeQ/jqaPpCgZe7XvyToUOB6oaUsSgbvz0bxfeGjMYnbtS+em0+pyXec6FCuiZVYkOiK9HwnufsDdf423IiKSKMyM81pV5/PbOnNm02N58vNlnPP8NL5P0x9JCZb+KSMSZyqVLs5zl7TilStas3X3fs4dPJ1Hxi9hz/70oKNJIaVCIhKn/tC4Kp8N6MzFbVJ5eepPnPn0VL5armVWpODlWkjMbIKZDTCzhgUVSERCV7ZEUR49vznv9GtHcpJx+dBZ3DJiLpt27sv7zSIRktcdyZXAVuDvZvadmQ0xs95mVroAsolIiDrUqcQnt3Ti5tPrMX7Br5z2xGTenLlKQ4WlQBzNqK0koB3QAzgd2EPGDPfHohcPzKw28FegrLtfmHmsCzAQWASMcPfJuV1Do7akMFmxYSd/G72QGT9upsnxx/BQ76acdIL2PJGjF41RW4fcfaa7/83dOwJ9gF/yCPGamW0ws4XZjnc3s6VmtsLM7snjc39y977ZDwM7gRQgLdRfg0hhULdKad6+ph3PX9qKTTv3ccGQGdw1aj6b1dwlURLVja3M7FQy/sL/t7s3zTyWDCwD/kBGEfiWjMmNycCj2S7xJ3ffkPm+UVnuSJLc/ZCZVQUGuftlueXQHYkUVjv3HeS5icsZOm0lpYoX4Y4zG3Bp2xokJ2ndLslbxO9I8sPdpwJbsh1uC6zIvNPYD4wAerv7Anfvme2xIYfrHsr8cSs5LGdvZtea2Wwzm71xo0aySOFUungR7j2rEZ/c0onGxx3D/R8tpPfgacxdvTXoaJJAghj+Ww1Yk+V5WuaxIzKzimb2ItDKzO7NPHa+mb0EvAk8f6T3ufvL7t7a3VtXrlw5culF4lC9qmV4p187nr2kFRu27+P8ITO494Pv2bJLm2hJ+PK9SbSZXe3uw/Lz1iMcy7F9zd03A/2zHfsA+CAfny1SaJkZ57Q4nq4NKvPMF8sZNmMVnyxcx11nNuTiNqlq7pJ8C+eO5MF8vi8NSM3yvDqwNowcOdKe7SK/VyalKPf1bMz4mzvRoGoZ/vLhAs5/YTrz12ipFcmfvPYj+T6nl4D67p7ndrtmVhMYm6WzvQgZne2nkzHq61vgUndfdFTJj4I620WOzN0ZPW8tD49fwqad+7ikbQ3uPKMB5UsVCzqaxIBQO9vzatqqCpxJRqf2/1wfmBFCiOFAF6CSmaUBD7j7UDO7EZhAxkit16JZREQkZ2bGua2qcVqjKjz9+XLemLmKTxb8yt3dG3JR61SS1NwlIcjrjmQoMMzdpx3htXfc/dJohguXmfUCetWtW7ff8uXLg44jEvOW/LqdB0YvYtaqLbRILcc/ejelWfWyQceSgERkq91EoaYtkdAd3vfk4XE/sHnXPvq0qcEdZ9SnYuk8W7IlwcTEPBIRiT+H9z358o7O/KljLd6bvYauT0zm9ekrOZB+KO8LSKGT1+q/3+V1gVDOEZH4c0xKUe7v2ZhPbulE8+rl+PuYxfR45ismLT3iPGEpxPLqI9lDxv7sOZ5CxmKKNSIdLBLURyISGe7O54vX88j4JazavJtT61fmvrMbUb9qmaCjSRRFpI/EzE4I4bPS3T2mF05UH4lIZOw/eIh/z1zFsxOXs2t/Ope2rcGAP9SngoYLJyR1tmehQiISWVt27efpL5bx9jerKVksmVtOr8cV7WtSrIi6XROJCglq2hKJtuXrd/CPcUuYsmwjNSuW5N6zGnFG46qYaf5JIlAhyUJ3JCLRNXnpBv4xbgkrNuykfe2K3NezEU2O1/yTeBfR4b9m1vgIx7rkI5eIJKAuDarw6S2deKh3E35Yt52ez03j7lHfs2HH3qCjSQEItUFzpJndbRlKmNlz/H4TKhEpxIokJ3FF+5pMvqMrfTvW4oO5aXR9fDKDJ61g74H0oONJFIVaSNqRsWLvDDIWWVwLdIxWKBGJX2VLZqwu/NmAznSoW4nHJyzl9CenMGb+WgpDU3phFGohOQDsAUqQsU/6yiy7FMYsLSMvEpxalUrxyhWteeeadpRJKcJNw+dy4Yszmafl6hNOSJ3tZjYfGA0MBCoCLwEHDu+hHuvU2S4SrPRDznuz1/DEZ8vYtHMf57Wqxl3dG3Bc2RJBR5NcRHTUlpm1dvfZ2Y5d7u5vhpGxwKiQiMSGnfsOMnjSCoZOW0myGf071+HaU2tTolhy0NHkCCJdSI64BIq7r85HtgKnQiISW9Zs2c0/P/mBcQt+5fiyKdzdoyHntDhe809iTKQLyQIy9lU3MvpIagFL3b1JuEELggqJSGyatXILD41dxMJftnNijXI80KsJLVLLBR1LMkV0Hom7N3P35pn/rQe0BX632ZWIyNFoW6sCo284hccuaM7qLXvoPXg6t42cx/rtmn8ST/I9s93MvnP3EyOcJ6K0RIpI/Nix9wCDJ/3Ia9NWUiTZ+HOXOlzTqTYpRdV/EpRIN23dluVpEnAiUNHdz8x/xIKjpi2R+PHz5l08Mn4JExatp1q5EvzlrEac1exY9Z8EINI7JJbJ8igOjAN65z+eiMiRnVCxFC9d3pp3+mXMP7nhne+4+KWvWfiL5oPFKi3aKCIxK/2QM+Lb1Qz6bBlbdu/njydV544zG1ClTErQ0QqFSG1sNYaM0VpH5O7n5C9ewVIhEYlv2/ce4LmJy3l9xiqKF0nmhq51+dMpNSleRP0n0RSpQtI5tze7+5R8ZCtwKiQiiWHlpl08PG4xXyzZQI0KJfnLWY04s4n2P4mWSBWSGvEy6TA3KiQiieWr5Rt5aMxilmfuf/K3Xo1pdNwxQcdKOJHqbP8oywXfDztVAdOijSKJqVO9ynxySycGZu5/cvazX/GXDxeweee+oKMVSnndkcx191bZf443uiMRSVzbdh/g6YnLeHPmz5QomszNp9fjyg7aPz4SInVH4jn8LCISE8qWLMoDvZrw6a2nclLN8jw8fglnPj2VLxav1/4nBSSvQtLCzLab2Q6geebP281sh5ltL4iAIiKhqFulNK9f3ZZhV7chyeCaf8/mitdmsWz9jqCjJTzNIxGRhHMg/RBvff0zT32+jF3707msXQ0GdKtP+VLFgo4WVyI9s11EJG4UTU7i6o61mHJnVy5rV4O3v1lN58cn8dq0lRxIj/nNXeOOComIJKzypYrxUO+mfHJLJ1qkluOhsYvp/vRUJi3dEHS0hKJCIiIJr37VMvz7T2159YrWHHK4eti3XDVsFis27Aw6WkJQIRGRQsHM6Na4KhNuPZW/ntWIOau20v3pqTw4ZhHbdh8IOl5cUyERkUKlWJEk+p1am0l3duGPrVN5fcYqOj8xiX/PXMVB9Z/kS0IXEs1sF5GcVCpdnEfPb8a4mzrR8Ngy/G30Is569iu+Wr4x6GhxR8N/RaTQc3cmLFrHw+OXsGbLHro1qsJfz25MrUqlgo4WKA3/FRH4Eg9wAAAKz0lEQVQJkZnRvelxfD6gM3d3b8jMHzdzxlNTeHjcYrbvVf9JXlRIREQypRRN5voudZh0ZxfOb1WdV6etpOvjk3nnm9WkH0r81pv8UiEREcmmSpkU/nVhc8bceAq1K5fiLx8uoOdz05j54+ago8UkFRIRkRw0rVaWkde1Z/ClJ7J9zwEueeVr+r85h9WbdwcdLaaokIiI5MLMOLv5cUy8vTN3nFGfqcs30m3QFP75yQ/s3Hcw6HgxQYVERCQEKUWTufG0eky6ows9WxzHi1N+pMvjkxn57ZpC33+iQiIichSqHpPCoIta8tENHalRoQR3vf895zw/jVkrtwQdLTAqJCIi+dAytRzvX9+BZ/q0ZMuu/Vz00kxuePs71mwpfP0nKiQiIvlkZvRuWY0vb+/Crd3qMfGH9Zw+aApPTFjKrkLUf6JCIiISphLFkrm1W32+vL0LPZoey/OTVnDak5N5f04ahwpB/4kKiYhIhBxfrgTP9GnF+9d34NhjUrj9vfmcN2QGc37eGnS0qFIhERGJsJNOKM+Hf+7IoItasG7bHi4YMoNbRsxl7W97go4WFTFfSMystpkNNbNRWY4lmdnDZvacmV0ZZD4RkSNJSjLOP7E6X97ehZtOq8unC9dx2pOTefqLZezZnx50vIiKaiExs9fMbIOZLcx2vLuZLTWzFWZ2T27XcPef3L1vtsO9gWrAASAtsqlFRCKnVPEi3H5GAybe3pnTG1Xl6S+Wc9qTkxk97xcSZfX1aN+RvA50z3rAzJKBwUAPoDFwiZk1NrNmZjY226NKDtdtAMx099uA66OYX0QkIqqXL8ngS09k5HXtqVi6GLeMmMcFQ2Ywb81vQUcLW1QLibtPBbLP0mkLrMi809gPjAB6u/sCd++Z7bEhh0unAYd7rxLrHlFEElrbWhUYfcMpPHZBc1Zv2cO5g6dz28h5rNu2N+ho+RZEH0k1YE2W52mZx47IzCqa2YtAKzO7N/PwB8CZZvYcMDWH911rZrPNbPbGjdrxTERiR3KScVGbVCbd0Zn+neswdv6vdH1iMs9NXM7eA/H3b+Oo75BoZjWBse7eNPP5H4Ez3f2azOeXA23d/aZoZdAOiSISy37evItHxi9hwqL1VCtXgnvPasjZzY7DzALNFcs7JKYBqVmeVwfWRuODtGe7iMSDEyqW4qXLW/NOv3aUSSnCje/M5eKXvmbhL/Hxd1cQheRboJ6Z1TKzYkAf4ONofJC7j3H3a8uWLRuNy4uIRFSHOpUYd3MnHjmvGT9u3Emv56dx16j5bNgR2/0n0R7+OxyYCTQwszQz6+vuB4EbgQnAEmCkuy+KZg4RkXiRnGRc2q4Gk+7sQr9Otflw7i+c9sQUhkz+kX0HY7P/JOp9JEEys15Ar7p16/Zbvnx50HFERI7ayk27eHjcEr5Ysp4aFUryl7MacWaTqgXSfxJqH0lCF5LD1NkuIvHuq+UbGTh2McvW76R97Yr8rVdjGh13TFQ/M5Y720VE5Ch1qleZ8Td3YmDvJvywbjtnP/sV936wgE079wUdTYVERCReFElO4vL2NZl8R1eu7FCT92avoevjk3ll6k/sP3gosFwJ3bSlPhIRSWQrNuzk4XGLmbR0I7UqleKvZzXi9EZVItZ/oj6SLNRHIiKJbPLSDQwcu5gfN+6iU71K3N+zMfWrlgn7uuojEREpJLo0qMKnt57KA70aM3/Nb/R45iv+NnohW3ftL5DPVyEREUkARZOTuLpjLabc2ZXL2tXg7W9W0/nxSbwxY1XUPzuhC4mWSBGRwqZ8qWI81Lsp42/uRIvUcixbvyPqn6k+EhGRBOXuHEh3ihXJ3z1DqH0kRfJ1dRERiXlmRrEi0Z8Bn9BNWyIiEn0JXUjURyIiEn0JXUi0jLyISPQldCEREZHoUyEREZGwqJCIiEhYVEhERCQsCT2P5PDqv8B2Mwtn+d+yQH6Hfh3te4/m/FDPDeW8SsCmED83XoXz/zFeMkTy+vreJ4Zw/j+eENJZ7q5HHg/g5YJ679GcH+q5oZwHzA769zmW/z/GS4ZIXl/f+8R4FMT3Xk1boRlTgO89mvNDPTec/IkkFn4fop0hktfX9z4xRP33oVCstSV5M7PZHsKaOiKJRN/7yNAdiRz2ctABRAKg730E6I5ERETCojsSEREJiwqJiIiERYVERETCokIieTKz2mY21MxGBZ1FJFrMrJSZvWFmr5jZZUHniScqJAnOzF4zsw1mtjDb8e5mttTMVpjZPbldw91/cve+0U0qEnlH+f0/Hxjl7v2Acwo8bBxTIUl8rwPdsx4ws2RgMNADaAxcYmaNzayZmY3N9qhS8JFFIuZ1Qvz+A9WBNZmnpRdgxriX0GttCbj7VDOrme1wW2CFu/8EYGYjgN7u/ijQs2ATikTP0Xz/gTQyisk89I/so6LfrMKpGv/9lxdk/AGqltPJZlbRzF4EWpnZvdEOJxJlOX3/PwAuMLMhaHmVo6I7ksLJjnAsx5mp7r4Z6B+9OCIF6ojff3ffBVxd0GESge5ICqc0IDXL8+rA2oCyiBQ0ff8jTIWkcPoWqGdmtcysGNAH+DjgTCIFRd//CFMhSXBmNhyYCTQwszQz6+vuB4EbgQnAEmCkuy8KMqdINOj7XzC0aKOIiIRFdyQiIhIWFRIREQmLComIiIRFhURERMKiQiIiImFRIRERkbCokEihZ2bpZjYvyyPXZfULipmtMrMFZtbazD7MzLbCzLZlydohh/deY2ZvZjtWNXNJ9aJm9q6ZbTGzcwvmVyOJTPNIpNAzs53uXjrC1yySOfEtnGusAlq7+6Ysx7oAd7h7rqs0m1l5YDlQ3d33Zh67EWjm7tdlPn+LjP03Pgonp4juSERykHlH8KCZfZd5Z9Aw83ipzA2TvjWzuWbWO/P4VWb2npmNAT4zsyQze8HMFmXu7TLezC40s9PN7MMsn/MHM/sgjJxtzGyKmc0xs0/MrKq7bwVmAGdnObUPMDy/nyOSExUSESiRrWnr4iyvbXL3E4EhwB2Zx/4KfOnubYCuwONmVirztfbAle5+Ghk77tUEmgHXZL4G8CXQyMwqZz6/GhiWn+BmVhx4BrjA3U8C3gIGZr48nIzigZmlZmaZmp/PEcmNlpEXgT3u3jKH1w7fKcwhozAAnAGcY2aHC0sKUCPz58/dfUvmz6cA77n7IWCdmU2CjPXKM/sv/s/MhpFRYK7IZ/ZGQBPgCzMDSCZjdVvIWIjwWTMrDVxMxppSh/L5OSI5UiERyd2+zP+m898/L0bGHcDSrCeaWTtgV9ZDuVx3GBmbJ+0lo9jktz/FgO/dvVP2F9x9l5l9Qcbuf32A6/P5GSK5UtOWyNGbANxkmbcAZtYqh/OmkbHjXpKZVQW6HH7B3deSsQfGfWTsK55fi4FqZtY2M0sxM2uS5fXhwJ1AOXf/NozPEcmRConI7/tI/pnH+QOBosD3ZraQ//ZJZPc+Gc1MC4GXgG+AbVlefxtY4+6L8xvc3fcBFwKDzGw+MBdol+WUT8lodhuR388QyYuG/4pEkZmVdvedZlYRmAV0dPd1ma89D8x196E5vHcV2Yb/Rjibhv9KROiORCS6xprZPOArYGCWIjIHaE7GKKucbAQmmlnrSIcys3eBjmT00YiERXckIiISFt2RiIhIWFRIREQkLCokIiISFhUSEREJiwqJiIiERYVERETC8v/ksSYETt1zrQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "erange = [50, 2000] * u.GeV\n", "diffuse_iso.plot(erange, flux_unit=\"1 / (cm2 MeV s sr)\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## PSF\n", "\n", "Next we will tke a look at the PSF. It was computed using ``gtpsf``, in this case for the Galactic center position. Note that generally for Fermi-LAT, the PSF only varies little within a given regions of the sky, especially at high energies like what we have here. We use the [gammapy.irf.EnergyDependentTablePSF](..\/api/gammapy.irf.EnergyDependentTablePSF.rst) class to load the PSF and use some of it's methods to get some information about it." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "EnergyDependentTablePSF\n", "-----------------------\n", "\n", "Axis info:\n", " rad : size = 300, min = 0.000 deg, max = 9.933 deg\n", " energy : size = 17, min = 10.000 GeV, max = 2000.000 GeV\n", "\n", "Containment info:\n", " 68.0% containment radius at 10 GeV: 0.16 deg\n", " 68.0% containment radius at 100 GeV: 0.10 deg\n", " 95.0% containment radius at 10 GeV: 0.71 deg\n", " 95.0% containment radius at 100 GeV: 0.43 deg\n", "\n" ] } ], "source": [ "psf = EnergyDependentTablePSF.read(\n", " \"$GAMMAPY_DATA/fermi_3fhl/fermi_3fhl_psf_gc.fits.gz\"\n", ")\n", "print(psf)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To get an idea of the size of the PSF we check how the containment radii of the Fermi-LAT PSF vari with energy and different containment fractions:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 5))\n", "psf.plot_containment_vs_energy(linewidth=2, fractions=[0.68, 0.95])\n", "plt.xlim(50, 2000)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In addition we can check how the actual shape of the PSF varies with energy and compare it against the mean PSF between 50 GeV and 2000 GeV:" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 5))\n", "\n", "for energy in [100, 300, 1000] * u.GeV:\n", " psf_at_energy = psf.table_psf_at_energy(energy)\n", " psf_at_energy.plot_psf_vs_rad(label=\"PSF @ {:.0f}\".format(energy), lw=2)\n", "\n", "erange = [50, 2000] * u.GeV\n", "spectrum = PowerLaw(index=2.3)\n", "psf_mean = psf.table_psf_in_energy_band(energy_band=erange, spectrum=spectrum)\n", "psf_mean.plot_psf_vs_rad(label=\"PSF Mean\", lw=4, c=\"k\", ls=\"--\")\n", "\n", "plt.xlim(1e-3, 0.3)\n", "plt.ylim(1e3, 1e6)\n", "plt.legend();" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "# Let's compute a PSF kernel matching the pixel size of our map\n", "psf_kernel = PSFKernel.from_table_psf(psf, counts.geom, max_radius=\"1 deg\")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVUAAAELCAYAAABpiBWpAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3Xu4HFWd7vHvS5CEgEgQRIQg8ZgRgUEQRBSPF2AwcBQc0TOgclEcRgV9BvXMwHgeRR0f8TYeHVAcEQneEAEVEQVHRI7KLaAGUEYiFxPgcA9XISb5nT9qdXZl0917dXZVd3X3+3meenb3qlVVq7r3/u2qVeuiiMDMzKqx3qALYGY2ShxUzcwq5KBqZlYhB1Uzswo5qJqZVchB1cysQg6qgKSvDboMVRql8xmlcwGfzziQ26mCpEcjYqNBl6Mqo3Q+o3Qu4PMZB+sPugBmZnWSdDrwGuDuiNipzfr/Bbw5vV0feD6wRUTcL+lW4GFgFbAyInaf8njjdqU6c+bM2HjjjddKe+SRR5icNsxG6XxG6VxgPM5n9erV8cADD0yranHBggVx7733ZuW95pprLoqIBZ3WS3o58AhwZrugOinva4HjImLv9P5WYPeIyCsMfb5SbfcfQ9KzgK9T/Dd4c0Q8ImkmcCawG3Af8HcRcWvKfwJwFMV/jvdExEUp/daI2G6qMqxYsYL777//Sent0oZBp9/c5Q06n+lW3D80zXNZPc3jV63dd9O0MvZi8t/OTjvtpOnu895772XRokVZeSVt3m19RFwmabvMQx8KfCszb1v9flB1BjD5P8p7gHcDpwFvSWlHAQ9ExHOBzwKfAJC0A3AIsGPazxckzai/2GbWf6szl2pImk0RV84tJQdwsaRrJB2ds5++BtWIuAyY/G96BhOfTus/3EHAwvT6HGAfSUrpZ0XEExFxC7AE2CPlu6fOsptZPwWwMnNhc0mLSktW8GvjtcAvI6Ico/aKiBcC+wPHpKqErprwoOpk4GvAg8CbUtrWwFKAiFgp6UHg6Sn9itK2y1IaEfGifhXYzPoh+yr03m4PkFK144FA28psSa8Evk8RyZdL+mBEfCSt3lnSzygu/m6luIi7rFthBh5UI+I2YHL0b1cnE13SzWykBBXe2p9BcUt/bpc8l1MEzB0j4lEASU8FvgDsS3GHfTtw9lQHG3hQ7WAZMBdYJml94GkUJ9VKb9kGuGOqnUl6tI5CmtmTLV26dK2/uXVvx1pZUH0nsA8wU9Iy4EPAU1LZTk15nglc3AqoyX7A5sB3KWLlLyjumLtqalA9HziC4r/HG4BLIiIknQ98U9K/Ac8C5gNXTbWz8pcqyVe2ZjWaO3cuy5cvn2aHgOquVCPi0PT0/4IuTarmApL0I+D9EXEDxZ3x2RHxdoqVhwEvnup4/W5S9S3glRQVy8uAD0XEV9pk/QrwNUlLKK5QDwGIiBsknQ38jqKG+piIWNWXwptZn2UH1c0lldtf/UdE/EcPB7oWeHZqznkA8D2KC7Z1qm7sa1CNiEMz8z0OvLHDuo8BH6uyXGbWNK2n/1m6Pqia8kgRD5VeXyjpC6nt6zpVNzb19n/sVd3WrY62c8MyGk9uOetogJ+7z0GWsbmqOduMp//vAt5RSppJ0eloObC3pBuBJyiuXqdsZeSgamYNVOnT/23TDjs9qPpv6f0KYAPg/ij676+UdD9FnHwK8LFU19qVg6qZNVRlD6r27fagKiLeB7wPQNIc4PrS6j8De/bS939Y7uDMbKy0rlSzuqlW1aMKii7yP5pUkJ66qfpK1cwaqj8PqlokvYoiqL6slLxXRNwh6RnATyTdmLrbd+QrVTNroJ6uVKdN0s4UgzodFBH3rSlFxB3p590UnQD2aL+HCQ6qZtZQ/QmqkrYFzgMOi4g/lNI3Sl1VkbQRRQ+r69vvZYJv/82sgap7+i/pj8B2wHodnv5/kKIN6s8krQZuiYgdgC2BSyVtmXb1g4j48VTHc1A1s4aqrEnVW+k+8v95FKPdHUDRDfVzKX05RcXuVhRR/hpJcyLigW4H8+2/mTVUNbf/HcZxLjuIIuBGRFwBbCppK+DVwE8i4v4USH/CkwfZfxJfqZpZA/XUTXW6ff/XjN+ctMZp7pTelYNqBYahC2gv+8vNO2q3Obk3m6PWVbSZ59NTnep0m1RVOn7zqP1dmNnI6FuTqk4Dp6zTgCoOqmbWUH0LqucDh6uwJ/BgRNwJXATsJ2lO6r66X0rryrf/ZtZAlTapetI4zqzdpOpCiif/S4DHKFoLEBH3S/oocHXa1UcmTQrYloOqmTVQTw+quu9pinGc04hUx3RYdzpwei/H8+2/mTVUNbf/khZI+i9JSyQd32b9ZyX9Ji1/kLS8tG5Vad35OaX2laqZNVQlXVBnAKcAf0Px4OlqSedHxO9aeSLiuFL+dwO7lnbx54jYpZdj+krVzBqosgFV9gCWRMTNEbECOIuisX8nhwLfmk7JHVTNrKEqCarZDfglPRuYB1xSSp6Vxmi9QtLrckrt238za6Cenv5361HVSwP+Q4BzJs3QvG0aT/U5wCWSrouIP3YrjINqHw2yV1Mvx879pRiWnldV95Tq5Zn0IHtpNbOnVC8qGaS6lwb8hzCpFUBpPNWbJV1KUd/aNagO+vfdzKyNyupUrwbmS5onaQOKwPmkp/iSngfMAS4vpc2RNDO93hzYC/jd5G0n85WqmTXU9K+1I2KlpGMpekLNAE6PiBskfQRYFBGtAHsocFZqs9ryfOBLaYzV9YCTyq0GOnFQNbMGqq5HVURcSNFrqpz2wUnvT2yz3a+Av+71eA6qZtZQw1kr7KBqZg3loGpmVpHq+v73m4OqmTVQdXWq/eYmVWbWUH0bUOVISfeUBk55e2ndEZJuSssROaX2laqZNVR/BlRJvh0Rx07adjOKsVd3Z2I21fM9m6qZDaGBDahS5tlUqzToifJy8+Z+gb180RsM8Ni5593LNUzu447cfCsGeOxB618tZ2WzqbYbUOXFbfZxsKSXA38AjouIpR229WyqZjasKplNNWdAlR8A34qIJyS9A1gI7J257ZP49t/MGqiy2/8pB1SJiPsi4on09svAbrnbtuOgamYN1Z8BVSRtVXp7IPD79NqzqZrZKOnbgCrvkXQgRSXu/cCRaVvPpmpmo6J/A6pExAnACR227Xk2VQdVM2sgd1M1M6vYcHZTdVA1s4ZyUDUzq8jwDqgylkF1UO3I6ph8L7f306wejp2bNzdfbhkh/7x7qW3L7QH1eMX5es2bo45JB3vR37+d4QyqfY8v7UaMkbSjpMslLZS0Xkr7qKTFadSYiyU9K6VL0ufT9oslvTClb5dmOzSzoVdZ4/++62tQLY0Ysz+wA3CopB2A91I0ul1E0cAW4FMRsXNE7AJcALSaQOwPzE/L0cAX+3cGZtY/KzOXZun37f+aEWMAJLVGjJnBxL8mAUTEQ6XtNmKiz+1BwJlp1sMrJG2aekSsomi4a2ZDz3WquTqNGPM54IfATcCprZWSPgYcDjwIvKrLPraOiEXA62sruZn11+rhDKr9rlNtO+pLRPw6Il4cEW+JiFWlFR+IiLnAN4Bju+2j60GlR1vLOpfczLIsXbp0+n9zEUVQzVkapt9BdZ1GfQG+CRy8rvuIiI1aSw9lNbN1MHfu3Gr+5hxUs0w5YkyLpPmltwcCN6bX5wOHp1YAewIPRsSddRbazPosAv6yMm9pmL7WqXYaMaZD9pMkPY+itvo24B0p/ULgAGAJ8Bjw1npLbWYDEdVchUpaQPHcZgZwWkScNGn9e4G3UzQluAd4W0TcltatAq5LWf8UEQdOdby+N/5vN2JMh3wHd0gP4Jiqy2VmDdKqU52mzIn/fg3sHhGPSXon8Eng79K6P6dmndnGskdVjkHPUZX7xeT2aprdw7E3zcz31IrzQX7vq17miXq44nzLezh2rtzw0UuYqaNur681mNXUl3ZqxrkmqEbEz0r5rwDeMp0DeuR/M2ueoKoHVb1O3ncU8KPS+1mSFkm6QtLrcoruK1Uza6Cebv+7zaaa3QRT0luA3YFXlJK3jYg7JD0HuETSdRHxx26FcVA1s+ZpPf3P02021awmmJL2BT4AvKI0CSARcUf6eXMaW2RXoGtQ9e2/mTVTNbf/ORP/7Qp8CTgwIu4upc+RNDO93hzYi1JdbCe+UjWz5gkqaVKVOfHfp4CNge9IgommU88HviRpNcUF6EmTWg20lRVUJT0bmB8R/ylpQ2D9iMh9WGpm1qNqmlRB1sR/+3bY7lfAX/d6vClv/yX9PXAOxeUxFHUS3+v1QGZmPRnhbqrHUNQlPAQQETcBz6izUGY25oZ4QJWc2/8nImJFqmtA0vpMMSqUmdm0BLCyef36c+QE1Z9L+hdgQ0l/A7wL+EG9xTKz8RawqnlXoTlygurxFL0MrgP+gaLC97Q6CzVsctul9dLUouoJ/XK7ngJskZmvW7eUddkfwOzMD+mxHi5i7snMd3v+LrPlhoXc0+klzNTR9bVvWj2qhtCUv8IRsRr4clrMzPogKhulqt86BlVJ19Gl7jQidq6lRGZmMJJXqq9JP1vD7H0t/XwzxTimZmb1iBi9B1WlQVr3ioi9SquOl/RL4CN1F87MxtiQXqnmPGPZSNLLWm8kvZRiymgzs3pEevqfszRMzrPWo4DTJT0tvV8OvK2+IpmZMbRXqjlP/68BXiBpE0AR8WD9xTKzsVbRdCqDMGVQlfTBSe8BiAjXqZpZfUatSVXJo6XXsyhaBfy+nuKYmTGaT/9bIuIz5feSPs2kQV5H0ahN/NfL5Hu5PaV2yuymtXMPLZq3yByq5567p87TsnhxZsbMGf0ezz90dtvD3H0O+vdyCCf+67t1GaR6NvCcqgtiZrbGiNeplntWzaDoyv3ROgtlZjayQZWJnlVQjPtwV0QMZ2WHmQ2HoJFtUHPkVKf8a0Tclpbb05wvX5t6MzOzdRWwamXe0jA5V6o7lt+kQap3q6c4ZmYMdZ1qxytVSSdIehjYWdJDaXkYuAv4ft9KaGbjaUinU+kYVCPi4xHxVOBTEbFJWp4aEU+PiBP6WEYzG0dDGlS7jae6fUTcSDEX9gsnr4+Ia2stmZmNryG+/e9Wp/pe4GjgM23WBbB3LSUyM4OhffrfbTzVo9PL/SNirQ4fknI78jRSLz1IBnXc3F4ZuXNZ9dKjKndOqdyeUq96ew99RfbbLy/fxRfn7/O0m7Oy3XVZ3u566MzFA5n5cr/vQf3u9v34Q9xNNecz+lVmmplZdWJ13tIw3epUn0nRDXxDSbsCSqs2oeiqamZWjxGtU301cCSwDfBvpfSHgX+psUxmZqMXVCNiIbBQ0sERcW4fy2Rm425Er1QBiIhzJf0Pip5Vs0rpHqTazOozqkFV0qkUdaivAk4D3gBcVXO5zGycRcBfRvfp/0sj4nDggYj4MPASYG69xTKzsRaMXo+qkj+nn49JehZwHzCvviKZmUUjm0vlyAmqF0jaFPgUcC3F/5Av11oqM7MGXoXmyHlQ1Rrl/1xJF1A8rNq+1lKZ2Xhr3f4PoZ7mqIqIJ4AnJH0H2LaeIk2QtAD4HMU0LqdFxEmS5gFnAZtRXDkfFhErJJ0I3BoRZ9Rdrn7I7Q5YdXdWgNmZO82dpC+76ynAll/M3Oc7s3e5xfmnZuXLPe8Nenh+MizdT5tntLuptqOps0yPpBnAKcD+wA7AoZJ2AD4BfDYi5lN0rT6q7rKYWZ9FFAOq5CwNs65BNabOMm17AEsi4uaIWEFxdXoQxehY56Q8C4HXpdePMPFQzcyG3ag9/Zf0A9oHTwFPr61EE7YGlpbeLwNeDCwvTTy4LOUjIj7dhzKZWT+MaJ1qtyDVjwDWrophRpu0flw1m1lfjWCTqoj4eT8L0sYy1u5ksA3wJ2BTSeunq9VtgDum2lGa/fX1tZTSzNaydOlSJD1aSjovIg7reUdDeqXa5IeOVwPzJc2TtAFwCHA+8DOKrrIAR5AxCWFEHBYRG0XERrWV1swAmDt3Lq2/t7T0HlADVq2MrKVpGhtU05XoscBFwO+BsyPiBuCfgfdKWkJRt/uVwZXSzOoQAatX5S1N01M71X6LiAuBCyel3UzRMsDMRtjq5l2EZpnySlXST1I31db7OZIuqrdYZjbOhng8lawr1c0jYnnrTUQ8ICm3L42to9zfldw+Jyt6OPZjmTu9J3cGvF4m6cvtKdXDPnPLmXvevXyWud9PA2PDYEUzb+1z5ATV1ZK2jYg/AUh6Nm7GZGY1a+JVaI6coPoB4BeSWk2sXg4c3SW/mdm0RMDKUb1SjYgfS3ohsCdFg/zjIuLe2ktmZmNriDtUde2mun1E3JgCKkw0st82VQdcW3/xzGwsjWid6nspbvM/02ZdUAxsYmZWuWB4m1R166baqjfdPyIeL6+TNKvNJmZm1RjeGaqzelT9KjPNzKwSEbDyL3lL03SrU30mxbB6G0ralYlRozahmLLazKw2I3f7D7waOJJiJKjPMBFUHwL+pd5imdk4G8mn/xGxEFgo6eCIOLePZTKzcTfEdao5jf93k/TTVldVSXOA90XE/663aPXJ+a7qGL6rl9+RqrufPtzDse/JzLd4cWbG027OPnbuJH3ZXWTJL2fueffyWeZ+P8PSnbWfxx/WJlU5sWP/yX3/gQPqK5KZjbtWk6qcpWlyrlRnSJqZpqdG0obAzHqLZWbjrPX0fxjlBNWvAz+V9FWKfyBvo5jF1MysHqNcpxoRn5R0HbAPRQuAj0aEx1M1s1o18dY+R9bI/xHxI+BHNZfFzAxI06kM6ZVqzsj/e0q6WtIjklZIWiXpoX4UzszG1yiP/H8yxUym3wF2Bw4HnltnocxsvMWIjlK1RkQskTQjIlYBX5Xkvv9mVquRHaQaeEzSBsBvJH0SuBPYqN5imdk4G/Ur1cOAGcCxwHHAXODgOgvVBL1U1eTmraNH1eNTZwF66wV0e27G5VNnAbjrsvxjz86cND13kj7I7ymVe969fJa5308dParq+L3spybWl+bIaVJ1W3r5Z+DD9RbHzGxEB6lObVM7nlZE7FxLiczMhrhJVbcr1df0rRRmZiUj2U21dNtvZtZ3w3r778b/ZtY4rUGq3fjfzKwKI96kyo3/zazvmngVmsON/82scaKhA1DnyBn5/7CU71jgUcak8b+ZDU4AK1fmLU3TS+P/x3Hj/7Zy71J6+f5z5zbK7bGT2fmpJ7nH7mE6KTbI/JByPx/I7wGVm6+XzzL3M6p6Litobk+pLENcp9rxSlXSQZKOKb2/UtLNaXlDf4pnZuNqFOeo+ieKp/4tM4EXUdSnfhU4p8ZymdkYG+ZBqrsF1Q0iYmnp/S8i4j7gPkl+UGVmtRrW2/9uQXVO+U1EHFt6u0U9xTEzS91UhzSodnv6f6Wkv5+cKOkfgKvqK5KZjbtR7VF1HPA9SW8Crk1pu1HUrb6u7oKZ2RgbxTrViLgbeKmkvYEdU/IPI+KSvpTMzMbaKNapApCCqAOpmfXNqD79NzMbmCa2Qc3hoGpmjTOSg1RXTZKAzwEHAI8BR0bEtWndcRRjDHwiIr4taRZwGcVDsfWBcyLiQynvPOAsYDOKB2iHRcQKSScCt0bEGVWUt447j0FO/NeL3HI+lpnvgR6OnfsLOcguv7185p74b90N6+1/zoAqVdkfmJ+Wo4EvAkjamKKn1h7Am1LeJ4C9I+IFwC7AAkl7pnWfAD4bEfMp/l6P6tsZmFlftCb+G8Zuqv0MqgcBZ0bhCmBTSVsBSuvXfDwpzyPp7VPSEulqd28musguZKJ51yMUM76a2bCL0WynWrWtgXK312XA1hGxKM3cugj4VGulpBnANRSzDJwSEVdK2hxYHhEry/sAiIhP9+EczKwPghFuUlUhtUkLgIj4OPDxtVYUswzsImlT4LuSdgLu6rQPMxshQ9ykqtbbf0nHSPqNpN8Ad1AMcN2yTUrrKiKWA5cCC4B7KaoNWv8MsvYh6dHW0uMpmFmPli5dOu2/uYjhHaS61qAaEadExC4RsQvwPeBwFfYEHoyIO9ttJ2mLdIWKpA2BfYEbIyKAnwGt8VyPAL6fUY6NWksFp2VmXcydO7eSvznXqU7tQormVEsoWuO8tUverYCFqV51PeDsiLggrftn4CxJ/wr8GvhKfUU2s0FoDagyjPoWVNNV5jFTZizyLgZ27bDuZormV2Y2woY0prpHlZk1k4PqEMn5suqobK6jR9Ugj53bW6iXX7Lcz72O88nN18ukg1Ufe9CBpl/HD6r/G+iXsQyqZtZsweD/gawrB1UzayQHVTOzCjmomplVxLf/ZmYVc1A1M6uIn/6bmVXMV6pmZhVxnaqZWcUcVEfMsHyhg5zbKLf3Uz+nl2in6rmaeqnrq/rY4zJHla9Uzcwq5qBqZlYRP/03M6uYr1TNzCriOlUzs4o5qJqZVchB1cysIn5QZWZWIdepmplVzEHVzKwivlK1LHX8klTdpbSufQ6DQXYVHdT+mmxYz9VB1cwayUHVzKwifvpvZlYh16mamVXMQdXMrEIOqmZmFfHtv5lZxRxUzcwq4qf/ZmYV85XqGBvWL78T96hq7j5H7XetE9epmplVzEHVzKwivlI1M6uYH1SZmVXEV6pmZhVzUDUzq4ivVM3MKuagamZWIQdVM7OKuJuqmVmFhrlOtW89DSVtL+lySU9Iev+kdYdIulbSP5bSdpN0naQlkj4vSSl9M0k/kXRT+jknpR8p6cR+nU/dVmcuVe+vl2Vl5lLHsYelnLmq3t8oGNbPpJ/dt+8H3gN8us26Q4AXAXtK2jilfRE4GpiflgUp/XjgpxExH/hpem9mI8ZBdQoRcXdEXA38pc1qtbIBkrQVsElEXB4RAZwJvC7lOQhYmF4vLKX/GXiklsKbWV+1bv+HMag2pU71PGAR8PWIeFjS84BlpfXLgK3T6y0j4k6AiLhT0jPS62/3s8BmVq8mBswcjQiqEbGQiatPmLhyXStbn4pjZgM2zE//a739l3SMpN+k5Vk9bLoM2Kb0fhvgjvT6rlQ9QPp5d0Y5Hm0tPZTBzNbB0qVLK/mbG9bb/1qDakScEhG7pOWOqbdYs92dwMOS9kxP/Q8Hvp9Wnw8ckV4fUUrvtr+NWkuPp2BmPZo7d+60/+Zcp5pB0jMp6k03AVan5lM7RMRDHTZ5J3AGsCHwo7QAnAScLeko4E/AG+sst5kNRhMDZo6+BdWI+H+sfUs/Vf5FwE5t0u8D9qmwaGbWMMPc+L8RD6r6afbs2Wy//faDLkZlhmGeqHZPHftpGJ5wDmsAaecvf2nXarJ3w/qgauyC6oYbbkjqnLXGLbfcwrx58wZUoulpFzCadj7TCWpNO5fp6nQ+g/7Hs67anc/tt99exf+xi4DNM/PeW8HxKqOibf14k/ToKD3EGqXzGaVzAZ/POBiGu0czs6HhoGpmViEH1cJ5gy5AxUbpfEbpXMDnM/Jcp2pmViFfqZqZVWgkg6qk0yXdLen6UtqzJF0i6futMVslzZT07TQQ9pWStivlPyGl/5ekV5fSb+3jqbSOuSCVY4mk41PajmnQ74WS1ktpH5W0OI21cHFrvAUVPp+2XyzphSl9O0mX9vt82ulwjvPS93JT+p42SOknSjqyj2WbJekqSb+VdIOkD6f0MyTdUhrfYpeUPkfSd9NnfZWknUr7ajcg+49L+z5V0oyU3pgB2Zv8/TRORIzcArwceCFwfSntJGBH4LXAO1Lau4BT0+tDgG+n1zsAvwVmAvOAPwIz0rpb+3wuM9LxnwNskMq1A/AVYAvg3cCClHeT0nbvKZ3bARTdfAXsCVyZ0rcDLm3A99XpHM8GDkl5TgXemV6fCBzZx/IJ2Di9fgpwZfoczwDe0Cb/p4APpdfbUwyq3lr3vXS+Z5X2uUnpOOeWzvmTwPHp9fHAJ9LrI4ET/f00cxnJK9WIuIxipoGyGUyMwdBqa10e8PocYJ80gMtBwFkR8URE3AIsAfZI+e6ps+xt7AEsiYibI2IFxR/jQRTn0+rNJ4BYexyFjZhod38QcGYUrgA2TSN8reLJn9MgdDrHvSm+F1h7QPJHKAYl74v0ubUGQH9KWro9jNiBYlYKIuJGYDtJW6Z1aw3InvK0vrf1KYJW+XtrwoDsjf5+mmYkg2oHJwNfAt4BfD2lbQ0sBYiIlcCDwNPL6cmaQbIj4kV9Km9Lp7J8Dvgh8BLg4tZKSR+TtBR4M/DBbvuIiKUR8foay56r0zkuT99LOY2I+HT0eVBySTMk/YZiqMmfRMSVadXH0m3+ZyXNTGm/BV6fttsDeDYT4160BmRfFBEPl/Z/Udr3w0wEqrUGZAfWDMgeEe2mJapL47+fJhmboBoRt0XEyyPitaVf5k6DYTdpkOy2ZYmIX0fEiyPiLRGxqrTiAxExF/gGcGy3fdRQ1nXVrnwz2qQNrMwRsSoidqEIjnuketITKG7vXwRsBvxzyn4SMCcF4XcDvyZ1ZY+IhRGxa0R8ZtL+Xw1sRVHltHcfTqkXjf9+mmRsgmoHy4C5AJLWB55GcTu8Jj0pD5Ldb+talm8CB09zH/3Srnx/oqimWL+UNvAyR8Ry4FKKeuw7U9XAE8BXSVVEEfFQRLw1BeHDKeq+b8nY9+MU4wUflJJ6HpC9JkPz/TTBuAfV8oDXbwAuiYhI6Yek1gHzKGZzvWpAZbwamJ+etG5A8UDt/HYZJc0vvT0QuDG9Ph84PLUC2BN4sHVb2RCdzvFnFN8LZA5IXgdJW0jaNL3eENgXuLEU8ERRn3h9er9p60k48HbgsugwbrCkjUv7WZ/ioWL5e+tpQPaaNPr7aZxBPymrYwG+BdxJMXPrMuCoDvlmAd+heBB1FfCc0roPUDzx/C9g/wGfzwHAH1J5PtAl37kUf9iLgR9Q1JtCcft2Str+OmD3QX9HOedI8bT5qvT9fAeYOaCy7UxxC784fb4fTOmXpM/zeop6+tbT/JcAN1EEx/OAOV32vSVF0FoM3AD8O7B+Wvd0igdeN6Wfm/n7af7iHlVmZhUa99t/M7NKOaiamVXIQdXMrEIOqmZmFXJQNTOrkIOqmVmFHFTHiKQtJX1T0s2SrklDB/7tFNtsp9IQij0e78jW8IPp/WmSdsjlf6RlAAADg0lEQVTc9pWSLliX4+aS9Kv0cztJb1qH7Y+UdHL1JbNh5qA6JlKvn+9R9O55TkTsRtEzZpvuW07LkcCaoBoRb4+I39V4vJ5ExEvTy+2AnoOqWTsOquNjb2BFRJzaSohikJl/hzVXa/83DaB8raSXTt5BtzyS/knSdWmw5ZMkvQHYHfhGGsB5Q0mXSto95V+Q9vFbST/NPQlJ+0j6dTrW6a2RoSTdKunDaZ/XSdo+pW+RBni+VtKXJN0mafO0rjV83knAf0/lPG7yFaikCyS9Mr1+q6Q/SPo5sFcpzxaSzpV0dVrWrLMxM+guXV76s1AMWv3ZLutnA7PS6/kUQ9NBcRV3/RR59gd+BcxO7zdLPy+l1CW29Z5igJGlwLxy/knleSVwwaS0WWm7v0rvzwT+Mb2+FXh3ev0u4LT0+mTghPR6AcVISpun94+0OxbFFfbJpfcXpDxbUQwksgXFuKe/bOWjGMDmZen1tsDvB/2dexnM0hphxsaMpFOAl1Fcvb6IYuDlk1VMCbIK+Ks2m3XKsy/w1Yh4DCAiphr4ek+KaohbMvO3PA+4JSL+kN4vBI4B/k9635rZ8xrSeKbpHP82HefHkh7IPFY7L6aYKeEeAEnfZu3PYIeilgWATSQ9NUpjptp4cFAdHzcwMRQgEXFMug1elJKOA+4CXkBRLfR4m310yiN6G0uz1/zl7bp5Iv1cxcTv9lTbtLOStavGZpVedyr3esBLImJsR7y3gutUx8clwCxJ7yylzS69fhpwZ0SsBg6j/SDEnfJcDLxN0mwoJqxL6Q8DT22zn8uBV6RhFcv5p9KamuS56f1hwM+n2OYXwP9Mx9kPmNMmz+Ry3grsImk9SXOZmErnSuCVkp4u6SnAG0vbXMzEoOCkq3kbQw6qYyIigmLMz1eomAH0Korb59Zo9V8AjpB0BcUt7aNtdtM2T0T8mGJ8zUUqRrt/f8p/BnBq60FVqSz3AEcD50n6LdBp6o19JC1rLcCuwFuB70i6jmJ+rlM7bNvyYWA/SddS1P3eSRFEyxYDK9NDs+Mo6kpvoRjW79PAtancd1JManc58J+t9OQ9wO4qplb5HcW0PTaGPPSfjbTUOmBVRKyU9BLgi1GMyG9WC9ep2qjbFjhb0nrACuDvB1weG3G+UjUzq5DrVM3MKuSgamZWIQdVM7MKOaiamVXIQdXMrEIOqmZmFfr/9F4W1XaobnoAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "psf_kernel.psf_kernel_map.sum_over_axes().plot(stretch=\"log\", add_cbar=True);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Energy Dispersion\n", "For simplicity we assume a diagonal energy dispersion:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "e_true = exposure.geom.axes[0].edges * exposure.geom.axes[0].unit\n", "e_reco = counts.geom.axes[0].edges * counts.geom.axes[0].unit\n", "edisp = EnergyDispersion.from_diagonal_response(e_true=e_true, e_reco=e_reco)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Background\n", "\n", "Let's compute a background cube, with predicted number of background events per pixel from the diffuse Galactic and isotropic model components. For this, we use the use the [gammapy.cube.MapEvaluator](..\/api/gammapy.cube.MapEvaluator.rst) to multiply with the exposure and apply the PSF. The Fermi-LAT energy dispersion at high energies is small, we neglect it here." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background counts from Galactic diffuse: 13331.893410079298\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "model = SkyDiffuseCube(diffuse_galactic)\n", "\n", "background_gal = BackgroundModel.from_skymodel(\n", " model, exposure=exposure, psf=psf_kernel, edisp=edisp\n", ")\n", "\n", "background_gal.map.sum_over_axes().plot()\n", "print(\n", " \"Background counts from Galactic diffuse: \", background_gal.map.data.sum()\n", ")" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background counts from isotropic diffuse: 417.41892868591725\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "model = SkyModel(SkyDiffuseConstant(), diffuse_iso)\n", "\n", "background_iso = BackgroundModel.from_skymodel(\n", " model, exposure=exposure, edisp=edisp\n", ")\n", "\n", "background_iso.map.sum_over_axes().plot(add_cbar=True)\n", "print(\n", " \"Background counts from isotropic diffuse: \", background_iso.map.data.sum()\n", ")" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "background_total = background_iso + background_gal" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Excess and flux\n", "\n", "Let's compute an excess and flux image, by subtracting the background, and summing over the energy axis." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Excess counts: 1866.6877\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "excess = counts.copy()\n", "excess.data -= background_total.evaluate().data\n", "excess.sum_over_axes().smooth(\"0.1 deg\").plot(\n", " cmap=\"coolwarm\", vmin=-5, vmax=5, add_cbar=True\n", ")\n", "print(\"Excess counts: \", excess.data.sum())" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "flux = excess.copy()\n", "flux.data /= exposure.data\n", "flux.unit = excess.unit / exposure.unit\n", "flux.sum_over_axes().smooth(\"0.1 deg\").plot(stretch=\"sqrt\", add_cbar=True);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fit\n", "\n", "Finally, the big finale: let's do a 3D map fit for the source at the Galactic center, to measure it's position and spectrum. We keep the background normalisation free." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "model = SkyModel(\n", " SkyPointSource(\"0 deg\", \"0 deg\"),\n", " PowerLaw(index=2.5, amplitude=\"1e-11 cm-2 s-1 TeV-1\", reference=\"100 GeV\"),\n", ")\n", "\n", "dataset = MapDataset(\n", " model=model,\n", " counts=counts,\n", " exposure=exposure,\n", " background_model=background_total,\n", " psf=psf_kernel,\n", ")\n", "fit = Fit(dataset)\n", "result = fit.run()" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OptimizeResult\n", "\n", "\tbackend : minuit\n", "\tmethod : minuit\n", "\tsuccess : True\n", "\tnfev : 466\n", "\ttotal stat : 20055.66\n", "\tmessage : Optimization terminated successfully.\n", "\n" ] } ], "source": [ "print(result)" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=11\n", "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
namevalueerrorunitminmaxfrozen
str9float64float64str14float64float64bool
lon_0-2.497e-02nandeg-1.800e+021.800e+02False
lat_0-3.975e-02nandeg-9.000e+019.000e+01False
index2.683e+00nannannanFalse
amplitude6.033e-10nancm-2 s-1 TeV-1nannanFalse
reference1.000e+02nanGeVnannanTrue
norm3.585e+00nan0.000e+00nanFalse
tilt0.000e+00nannannanTrue
reference1.000e+00nanTeVnannanTrue
norm1.019e+00nan0.000e+00nanFalse
tilt0.000e+00nannannanTrue
reference1.000e+00nanTeVnannanTrue
" ], "text/plain": [ "\n", " name value error unit min max frozen\n", " str9 float64 float64 str14 float64 float64 bool \n", "--------- ---------- ------- -------------- ---------- --------- ------\n", " lon_0 -2.497e-02 nan deg -1.800e+02 1.800e+02 False\n", " lat_0 -3.975e-02 nan deg -9.000e+01 9.000e+01 False\n", " index 2.683e+00 nan nan nan False\n", "amplitude 6.033e-10 nan cm-2 s-1 TeV-1 nan nan False\n", "reference 1.000e+02 nan GeV nan nan True\n", " norm 3.585e+00 nan 0.000e+00 nan False\n", " tilt 0.000e+00 nan nan nan True\n", "reference 1.000e+00 nan TeV nan nan True\n", " norm 1.019e+00 nan 0.000e+00 nan False\n", " tilt 0.000e+00 nan nan nan True\n", "reference 1.000e+00 nan TeV nan nan True" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dataset.parameters.to_table()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "residual = counts - dataset.npred()\n", "residual.sum_over_axes().smooth(\"0.1 deg\").plot(\n", " cmap=\"coolwarm\", vmin=-3, vmax=3, add_cbar=True\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "- Fit the position and spectrum of the source [SNR G0.9+0.1](http://gamma-sky.net/#/cat/tev/110).\n", "- Make maps and fit the position and spectrum of the [Crab nebula](http://gamma-sky.net/#/cat/tev/25)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary\n", "\n", "In this tutorial you have seen how to work with Fermi-LAT data with Gammapy. You have to use the Fermi ST to prepare the exposure cube and PSF, and then you can use Gammapy for any event or map analysis using the same methods that are used to analyse IACT data.\n", "\n", "This works very well at high energies (here above 10 GeV), where the exposure and PSF is almost constant spatially and only varies a little with energy. It is not expected to give good results for low-energy data, where the Fermi-LAT PSF is very large. If you are interested to help us validate down to what energy Fermi-LAT analysis with Gammapy works well (e.g. by re-computing results from 3FHL or other published analysis results), or to extend the Gammapy capabilities (e.g. to work with energy-dependent multi-resolution maps and PSF), that would be very welcome!" ] } ], "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 }, "toc": { "base_numbering": 1, "nav_menu": { "height": "237px", "width": "253px" }, "number_sections": false, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": "block", "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }