{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "
\n", "**This is a fixed-text formatted version of a Jupyter notebook.**\n", "\n", " You can contribute with your own notebooks in this\n", " [GitHub repository](https://github.com/gammapy/gammapy-extra/tree/master/notebooks).\n", "\n", "**Source files:**\n", "[data_fermi_lat.ipynb](../_static/notebooks/data_fermi_lat.ipynb) |\n", "[data_fermi_lat.py](../_static/notebooks/data_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 pepared Fermi-LAT datasets.\n", "\n", "The main class to load and handle the data is:\n", "\n", "* [gammapy.dataset.FermiLATDataset](http://docs.gammapy.org/dev/api/gammapy.datasets.FermiLATDataset.html)\n", "\n", "\n", "Additionally we will use objects of these types:\n", "\n", "* [gammapy.data.EventList](http://docs.gammapy.org/dev/api/gammapy.data.EventList.html) for event lists.\n", "* [gammapy.irf.EnergyDependentTablePSF](http://docs.gammapy.org/dev/api/gammapy.irf.EnergyDependentTablePSF.html) for the point spread function.\n", "* [gammapy.cube.SkyCube](http://docs.gammapy.org/dev/api/gammapy.cube.SkyCube.html) for the galactic diffuse background model. \n", "* [gammapy.cube.SkyCubeHPX](http://docs.gammapy.org/dev/api/gammapy.cube.SkyCubeHPX.html) for the exposure. \n", "\n", "* [gammapy.spectrum.models.TableModel](http://docs.gammapy.org/dev/api/gammapy.spectrum.models.TableModel.html#gammapy.spectrum.models.TableModel) for the isotropic diffuse model.\n", "* [gammapy.image.FermiLATBasicImageEstimator](http://docs.gammapy.org/dev/api/gammapy.image.FermiLATBasicImageEstimator.html) for generating a full WCS dataset, that can be used as an input for image based analyses.\n", "\n", "\n", "## Setup\n", "\n", "**IMPORTANT**: For this notebook you have to get the prepared datasets provided in the [gammapy-fermi-lat-data](https://github.com/gammapy/gammapy-fermi-lat-data) repository. Please follow the instructions [here](https://github.com/gammapy/gammapy-fermi-lat-data#get-the-data) to download the data and setup your environment." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from astropy import units as u\n", "from astropy.visualization import simple_norm\n", "from gammapy.datasets import FermiLATDataset\n", "from gammapy.image import SkyImage, FermiLATBasicImageEstimator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## FermiLATDataset class\n", "\n", "To access the prepared Fermi-LAT datasets Gammapy provides a convenience class called [FermiLATDataset](http://docs.gammapy.org/dev/api/gammapy.datasets.FermiLATDataset.html#gammapy.datasets.FermiLATDataset). It is initialized with a path to an index configuration file, which tells the dataset class where to find the data. Once \n", "the object is initialized the data can be accessed as properties of this object, which return the corresponding Gammapy data objects for event lists, sky images and point spread functions (PSF). \n", "\n", "So let's start with exploring the Fermi-LAT 2FHL dataset:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fermi-LAT 2FHL dataset\n", "======================\n", "Filenames:\n", " counts : fermi_2fhl_counts_cube_hpx.fits.gz\n", " events : fermi_2fhl_events.fits.gz\n", " exposure: fermi_2fhl_exposure_cube_hpx.fits.gz\n", " isodiff : ../isodiff/iso_P8R2_SOURCE_V6_v06.txt\n", " livetime: fermi_2fhl_livetime_cube.fits.gz\n", " psf : fermi_2fhl_psf_gc.fits.gz\n", "\n" ] } ], "source": [ "# initialize dataset\n", "dataset = FermiLATDataset('$GAMMAPY_FERMI_LAT_DATA/2fhl/fermi_2fhl_data_config.yaml')\n", "print(dataset)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Events\n", "\n", "The first data member we will inspect in more detail is the event list. It can be accessed by the `dataset.events` property and returns an instance of the Gammapy [gammapy.data.EventList](http://docs.gammapy.org/dev/api/gammapy.data.EventList.html) class:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "EventList info:\n", "- Number of events: 60275\n", "- Median energy: 80340.5078125 MeV\n", "\n" ] } ], "source": [ "# access events data member\n", "events = dataset.events\n", "print(events)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The full event data is available via the `EventList.table` property, which returns an [astropy.table.Table](http://docs.astropy.org/en/stable/api/astropy.table.Table.html#astropy.table.Table) instance. 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. Execute the following cell to take a look at the event list table: " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<Table length=60275>\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
ENERGYRADECLBTHETAPHIZENITH_ANGLEEARTH_AZIMUTH_ANGLETIMEEVENT_IDRUN_IDRECON_VERSIONCALIB_VERSION [3]EVENT_CLASS [32]EVENT_TYPE [32]CONVERSION_TYPELIVETIMEDIFRSP0DIFRSP1DIFRSP2DIFRSP3DIFRSP4
MeVdegdegdegdegdegdegdegdegss
float32float32float32float32float32float32float32float32float32float64int32int32int16int16boolboolint16float64float32float32float32float32float32
145927.0291.66242.234174.543711.867838.045583.535855.6387314.034239561457.866485143723955956500 .. 0False .. TrueFalse .. True0275.6980889740.00.00.00.00.0
221273.046.9858-40.6389247.489-58.873934.1051224.20968.2524198.319239562739.085752143223955956500 .. 0False .. TrueFalse .. True064.79749315980.00.00.00.00.0
57709.2121.84149.2288169.86832.301771.563634.292536.717325.5439239563180.302869069323955956500 .. 0False .. TrueFalse .. True030.572186470.00.00.00.00.0
221224.083.5626-4.21744207.783-19.077120.508992.160532.3033239.141239563382.213920842423955956500 .. 0False .. TrueFalse .. True027.41250959040.00.00.00.00.0
698997.0320.895-1.3278951.2218-33.971835.3621158.74112.086772.2029239566572.951248048323956564500 .. 0False .. TrueFalse .. True0106.4754811230.00.00.00.00.0
119159.0318.81112.302862.6361-24.41626.5896213.89417.715623.9409239572348.06172527623957167000 .. 0False .. TrueFalse .. True0185.3464272920.00.00.00.00.0
56175.6279.25147.883576.691522.073929.103461.004862.1731321.104239572763.4317601723957273600 .. 0False .. TrueFalse .. True024.45073395970.00.00.00.00.0
1.41812e+06100.311-47.4481256.468-21.264161.2256294.1890.4753144.149239573788.813178156923957273600 .. 0False .. TrueFalse .. True068.2716146410.00.00.00.00.0
62164.9331.492-41.2264359.42-53.404928.1408229.92752.0142189.054239578601.168200070023957766300 .. 0False .. TrueFalse .. True090.3322626650.00.00.00.00.0
.....................................................................
51296.879.031178.9327133.86822.239951.1726267.81499.7602357.79444418973.822128485344441859000 .. 0False .. TrueFalse .. True0181.68898350.00.00.00.00.0
60315.7243.681-50.5669332.430.2826824.8501255.68374.8804195.14444421777.761658294944441859000 .. 0False .. TrueFalse .. False157.33589029310.00.00.00.00.0
90000.1282.698-33.19872.66219-14.33398.49144343.55947.3965191.033444422182.738750746644441859000 .. 0False .. TrueFalse .. True0187.6024691460.00.00.00.00.0
61988.7247.98-48.1091336.1460.022033933.6499144.27180.3966221.396444422758.145869914744441859000 .. 0False .. TrueFalse .. True039.20983272790.00.00.00.00.0
54282.9159.924-58.3628286.3620.20555424.1196287.13865.0847177.524444425794.794252223744442461900 .. 0False .. TrueFalse .. True0196.2096688750.00.00.00.00.0
146728.0244.848-46.5876335.7542.6032645.25395.3364491.871137.032444425911.819270521044442461900 .. 0False .. TrueFalse .. False165.63278573750.00.00.00.00.0
135433.083.527827.9053179.529-2.6910617.491152.085853.306313.822444430968.96893918844443059900 .. 0False .. TrueFalse .. False197.64468312260.00.00.00.00.0
61592.1231.214-5.45521357.43540.647346.6356141.04762.7584256.631444433607.906544394444443059900 .. 0False .. TrueFalse .. False128.72906577590.00.00.00.00.0
80480.8228.244-45.044327.56110.952837.3149193.71483.3882221.57444433702.069561244344443059900 .. 0False .. TrueFalse .. False1122.8918192980.00.00.00.00.0
124449.0238.008-51.0371329.4292.300632.4522199.50480.9768214.48444433764.433572336144443059900 .. 0False .. TrueFalse .. True0185.2554872040.00.00.00.00.0
" ], "text/plain": [ "\n", " ENERGY RA DEC L ... DIFRSP1 DIFRSP2 DIFRSP3 DIFRSP4\n", " MeV deg deg deg ... \n", " float32 float32 float32 float32 ... float32 float32 float32 float32\n", "----------- ------- -------- ------- ... ------- ------- ------- -------\n", " 145927.0 291.662 42.2341 74.5437 ... 0.0 0.0 0.0 0.0\n", " 221273.0 46.9858 -40.6389 247.489 ... 0.0 0.0 0.0 0.0\n", " 57709.2 121.841 49.2288 169.868 ... 0.0 0.0 0.0 0.0\n", " 221224.0 83.5626 -4.21744 207.783 ... 0.0 0.0 0.0 0.0\n", " 698997.0 320.895 -1.32789 51.2218 ... 0.0 0.0 0.0 0.0\n", " 119159.0 318.811 12.3028 62.6361 ... 0.0 0.0 0.0 0.0\n", " 56175.6 279.251 47.8835 76.6915 ... 0.0 0.0 0.0 0.0\n", "1.41812e+06 100.311 -47.4481 256.468 ... 0.0 0.0 0.0 0.0\n", " 62164.9 331.492 -41.2264 359.42 ... 0.0 0.0 0.0 0.0\n", " ... ... ... ... ... ... ... ... ...\n", " 51296.8 79.0311 78.9327 133.868 ... 0.0 0.0 0.0 0.0\n", " 60315.7 243.681 -50.5669 332.43 ... 0.0 0.0 0.0 0.0\n", " 90000.1 282.698 -33.1987 2.66219 ... 0.0 0.0 0.0 0.0\n", " 61988.7 247.98 -48.1091 336.146 ... 0.0 0.0 0.0 0.0\n", " 54282.9 159.924 -58.3628 286.362 ... 0.0 0.0 0.0 0.0\n", " 146728.0 244.848 -46.5876 335.754 ... 0.0 0.0 0.0 0.0\n", " 135433.0 83.5278 27.9053 179.529 ... 0.0 0.0 0.0 0.0\n", " 61592.1 231.214 -5.45521 357.435 ... 0.0 0.0 0.0 0.0\n", " 80480.8 228.244 -45.044 327.561 ... 0.0 0.0 0.0 0.0\n", " 124449.0 238.008 -51.0371 329.429 ... 0.0 0.0 0.0 0.0" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "events.table" ] }, { "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": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of events above 50 GeV: 60275\n", "Number of events above 100 GeV: 21874\n", "Number of events above 200 GeV: 8028\n", "Number of events above 400 GeV: 2884\n", "Number of events above 800 GeV: 821\n", "Number of events above 1600 GeV: 113\n" ] } ], "source": [ "# define energy thresholds\n", "energies = [50, 100, 200, 400, 800, 1600] * u.GeV\n", "\n", "n_events_above_energy = []\n", "\n", "for energy in energies:\n", " n = (events.energy > energy).sum()\n", " n_events_above_energy.append(n) \n", " print(\"Number of events above {0:4.0f}: {1:5.0f}\".format(energy, n))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And plot it against energy:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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lVqOcs86oxN8++YE+w+cxa81ONcoR8ZAvg+wqAH8C6jvnbjGzxsBZzrlPSyJg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\nESmFVOBFRERKIRV4ERGRUuj/AT46grylAWBDAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 5)) \n", "events_plot = plt.plot(energies.value, n_events_above_energy, label='Fermi 2FHL events')\n", "plt.scatter(energies.value, n_events_above_energy, s=60, c=events_plot[0].get_color())\n", "plt.loglog()\n", "plt.xlabel(\"Min. energy (GeV)\")\n", "plt.ylabel(\"Counts above min. energy\")\n", "plt.xlim(4E1, 3E3)\n", "plt.ylim(1E2, 1E5)\n", "plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## PSF\n", "Next we will tke a closer look at the PSF. The dataset contains a precomputed PSF model for one position of the sky (in this case the Galactic center). It can be accessed by the `dataset.psf` property and returns an instance of the Gammapy [gammapy.irf.EnergyDependentTablePSF](http://docs.gammapy.org/dev/api/gammapy.irf.EnergyDependentTablePSF.html) class:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "EnergyDependentTablePSF\n", "-----------------------\n", "\n", "Axis info:\n", " offset : size = 300, min = 0.000 deg, max = 9.933 deg\n", " energy : size = 17, min = 50.000 GeV, max = 2000.000 GeV\n", " exposure : size = 17, min = 184244434125.149 cm2 s, max = 308160738535.443 cm2 s\n", "\n", "Containment info:\n", " 68.0% containment radius at 10 GeV: 0.10 deg\n", " 68.0% containment radius at 100 GeV: 0.10 deg\n", " 95.0% containment radius at 10 GeV: 0.52 deg\n", " 95.0% containment radius at 100 GeV: 0.43 deg\n", "\n" ] } ], "source": [ "psf = dataset.psf\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": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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k3Mqqy1h7eK1nTnn/R+jSE9M9AT8zYyapialhKqmInEtQQt0Y8ziwAFgJrAeO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\nRK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 5))\n", "psf.plot_containment_vs_energy(linewidth=2, fractions=[0.68, 0.95, 0.99])\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": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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NRpoZTTQ3eNACD1poIwPMPrQqtGHNysKalUVhcnKln2Ns2hTvkBCahITQKaQN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\nfCIiOdfspu4MuqMfHerXPN5WrGhxXqjUgIgHRvP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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 5))\n", "\n", "for energy in energies:\n", " psf_at_energy = psf.table_psf_at_energy(energy)\n", " psf_at_energy.plot_psf_vs_theta(label='PSF @ {:.0f}'.format(energy), lw=2)\n", "\n", "erange = [50, 2000] * u.GeV\n", "psf_mean = psf.table_psf_in_energy_band(energy_band=erange, spectral_index=2.3)\n", "psf_mean.plot_psf_vs_theta(label='PSF Mean', lw=4, c=\"k\", ls='--')\n", " \n", "plt.xlim(1E-3, 1)\n", "plt.ylim(1E2, 1E7)\n", "plt.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exposure\n", "The Fermi-LAT datatset contains the energy-dependent exposure for the whole sky stored using a HEALPIX pixelisation of the sphere. It can be accessed by the `dataset.exposure` property and returns an instance of the Gammapy `gammapy.cube.SkyCubeHPX` class:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Healpix sky cube exposure with shape=(18, 12288) and unit=cm2 s:\n", " n_pix: 12288 coord_type: galactic coord_unit: deg\n", " n_energy: 18 unit_energy: MeV\n", "\n" ] } ], "source": [ "exposure = dataset.exposure\n", "print(exposure)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# define reference image using a cartesian projection\n", "image_ref = SkyImage.empty(nxpix=360, nypix=180, binsz=1, proj='CAR')\n", "\n", "# reproject HEALPIC sky cube\n", "exposure_reprojected = exposure.reproject(image_ref)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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MAP8AwP8A4OcB+D8B/Fs55x9PKTUA/lsAHwrgs3POfycql29CxCZMJWXswUunAGPhh3YG\nosi2cmgxFN5eAc+uKVJAo0mS+TBfROkCPZlG+js6Pju0QllLHmYwY94DoYUBzek0XBOzm7Ydju86\nTGq2CYy6eSGhsgFujnp8TS9eMCh74FQCB2/QnwDJ0gTlah0aHQHMXrnPrsWeeC7A3oLF2u1VSsCw\nF0xKeVX2gIwXv3pecu6BRAkYIGGWXgFAy1aJBn02yIPCIOcRqOwRNsjbZI5tyG6ejXiVN4OhfAWA\nb805/6aU0hHA6wD+IIDvyDl/aUrpCwB8AYD/CMAnAHgXgP8QwJdgAB9XPDuGgoGFXR195lJSZdnf\n8Tiqto5j5NGAI1EhBwIMYiVNs2QtGlcDLBZvIAKMI/b1BBRz2Agki3Me3UcGc7od0ON0Nx5387VT\nVgYXs6903aw+M7Dx2I5n0Lc0uibEu1Qri8/15dwa3JnlaHomfJ7KrJFyNP/Emqj+aMsUoMwaasEl\nGsBq8u9JswUMmuYSQLn0Ojiddz+iN8kDjFI6/u2kXA9YuF12bExBweGhxICiJk2DtWdsJHvUX48K\nKCml9wbwMQB+OwDknE8ATimlTwHwsWOydwD4LgyAYsyux4b6j0FAtUq6XoSZhmc7sfDr4wAg9ndo\nMYNI2wLtYQaQRQEEKAYgXtq2RWgz2WIrETio6guYgWbBWoixtIfhmroOON0idUPeq9Mt0PfIXY+u\nG5jFXTc8Db6/wwOYmUfESKw53Pyuo4GZBu8atqL5gPoXdGXHoHL1+K0gewbch2A8NW0pAceefFHe\nmrCmEGdhmqbEPrx03q+XdprYOG3j44hxeGmB2RYyAUFwXiOWx8ZBYD1eek5LtfLYDOXnA/h/AHxt\nSumjAHwfgN8D4GfmnH8YAHLOP5xS+oAx/bcB+FMAfhuAzykV7LnuGqVT9RSDibIZO372bGAyrz0j\nNtJeAcer+XgCjcOSnTTNkM4AhdNNFR2cURnL88h+YmIgoWqtrnPibIQ/YzXid+eB7XQdcBoNJ90d\ncNMOANN0uGo6nMfBv2tm3FJsu+uWwKLPiL3OdADnX/34VjSwr/JZuFMu1wUsmYrGKXOJ1F8vQyJA\nUNvHy6hjS7bA5NJfLT86j8JKwuBh53rsAUYJRCBp9kiU/qEWxCqQrUCoWTorNc5xyeurJI8NKC2A\njwbwu3PO70opfQUG9ZYrOecOwKfXFq4MwzOcJ7pJbD/hv2fPRkB51gDPXpuZhKq0FFwMMI7XM6Cw\nOmtxnpYNny5gw0gP+CDiqrvGeA0D1oBzuh0BxdReNn1JE+Ac+h6HrkPb9QuGYSDBbEOBxf4mA36/\nvBxuYtNg086ypd5iACiCCuK9wrhtJffgplleD0tkK4lcinWgL6WJyvOawj1py/hfEq/uSGqZi6aP\n8pTCagZ2Dyz4WIHHAxPO49XptcEDyRZrVsLTxy0Gs2VTUdaypQ7bUojUymMDyrsBvDvn/K7x/Bsw\nAMo/TSl94MhOPhDAj2wVlFJ6J4BPtXM1oOtKdjW0s03E7CIL9dZxBBMPNI7HGTQm5nJcq7WsYWaE\nbxVkUoGdOE/RbCxqYGdhoOg6Yi1qlJfzth3SH++A09WQvklDm0+3QHcYwxqkpsOh79F0/cBYumUz\num5gfgYcJWDJzTY4ALOxf4uxAJhtJajbWNLS2W3nsiPGovXVyBZQaBpgDTwREJnwgLe1DUxplg4n\nzAORErBE+UospQQqtQAWSQ0Ilq7ZzvkvAjm9t9ptLmE2JjUqMBVl2NEavGgBeK08KqDknP/vlNI/\nSSn9iznnfwDg4wH83fHvMwB86fj7TRVlvR3A2wEgpZQnd93GX2PC3l0GIAoixyNw/QxrwDher9nH\n8TiyFwo3wAGWbGNhb9lgIZ6aKxrF2JuL0/X9rMKaVFrqViwMpbsbQKMfr/10O5R1up0BZrSx2HE6\n3eIwGkbMA4ybp4xEbSnArAZTNhFJ5BqpzILTN0E6ZR8NhXk2lBJLAcqG+UvEW7Pilbf1CWEPhLY+\nY1waWEvAsjVoXwImtWylJDVgcolslcvAomFAzDxKNpEadqn5F+yF5qxbYGJjaq28GV5evxvAnx49\nvP4RgN+B4V5+fUrpswD8IIDfvLdQ9dxiVdbkmTUCy7NnSzdgZiiTvstUXRGoMFtZqLzG4y23YY+Z\ncDoLK8npNLsLczkA0LUEKHdAf4WFWqzrZltJ38/pu7tl+44EJt0dcLoe1GI3L4b4fiD/ljw1M9mZ\nouUy2RtsApdmaV8xqQUKFc7XSRmRWovXt9SwlBXYvIwRy9qD9eDD1ZU+xKVSSrvFWva2WaWmrD3A\nUhP3UFJiLZoualft2LwFGtwXIvBhxjKxKgINIJjT0vhpXrO18uiAknP+GwB+qRP18fcqV56sIS4D\njLGUZ8/W6q7Ds3YAkWfXS+bBxvjj9ZhJ1GDHK9+OogASsZOkjx4od72xm163wDWd881glVfXLVVe\n3d3Qzq6dgaS5m3vRxEQIFbQHti1wHOo9tHcDU+l7tCNO6b5Y/MdsxYq3YwWKks2kxv5hTY1cf60O\nYA0IHnBofK26S2eqtTYUzc9MRAcuXRyprKYJ0mo52vP2qGdK+WsBZg+AXZpui3FFZXgAvFW2146t\n+1n74ayoHB5RPHYCLN+VaEPbn7If2NIb1cgNUrvJs2dkK+EAA5WmwcLl99lrY/z1DBbmbstAwiBj\nAMIuZ0MLMTzqFkvt52IoLVxtpDCwqfYZOPTDH87DIhEGl548uToBlu5uvmkdz4NOAK793jWl73Bo\nejTNbFsB1oDCqq/7so8tUKkpl0EhYiksiUYMBR2Oi6Rmi/uomK2PeAHxXmHelyQ9FaKyk5J4ab3j\nGtAo3ToNr02nosDuAcvWI9xah1J73yzvpetStA0egCziC4V7dpO3vA3lZQpvp2JUjY30fJOuzPD+\nrAVefxuxj4B5MJCwO7DaRzjfs9fGhSsHzMDB0mJ4zAcAV9juSlG8Ackd1kvjOgBn4HBYrkpkpjJ5\ndRGLavsh7PXXR5XXyHBMxWYqr4m1rHel5PutRvvpDrSLLFM+YGmEd69aQMXukDIaj9U08OsEYrWV\npimxl0uYi7VNdxH27CiW1tsiP9orzFNzWbyV5YKtlB/N0LcYiAcwtQO4V68ntSzDytPzCOA8cPUA\nrnYwrRmfba1KzbTyIMel+qId1wF/8m3ntfLKAIp3Mww8ro/zcUseYItRwgpgo7t3zOtK2L7CcROQ\n2LzhCjOA2Ktr8S2lYyl9DFSlB3DE/OXxkZngakzfDX/pDBw64DACD6+PsYWNZsw/HoeijLmcbkcW\nMnYZHq1vXoznV2PLBy8wYGmsZ2O8FWG3PhLdU6sk0bYqWo9nU/GklCYEwlodzE7RAc9jKiye6ovj\nvFupM29PalU2nF4ByYvbC1RRu2plC1i2QC+6jpJoXSYKAmdcBk56zGxFgcPE25dwjxFe5ZUDFGMm\nDCaea3BqxwzmGju5A5MH17PrmaGonWQBONdDZRMbMcZhT8ZYCIMHgwsDzJZYd2R/kPMYfjWGGVMZ\nl7Xjbow7U/jd0JNea2eVWHcHdMcZQPqRqZysJ45bvRyvlyPq9Etg13U4tDOo2PofTs7PzfOCZvdf\nZhUl9RZvHhkZ0T211oKBSH1b4jESnf3fx/sKcm6/NlhEnm8MHDrD9vJE3+koSWkG7w3WXpwCzhZT\n2CNeWV68156ovhK47GmL5eWV8ws2EZTDbsJeG/R4cd6sj/X3PvLKAMr1s+Wq95Zchc1EMtlN3u99\nZuO7qaem3yMByQgWz54t7SUW3rZAMqCwXwOP43ieJN6ABFgDydYT1VfW/oAZLOx4BA10AJ5hDTDn\n+fxwNzCX6zNwN6q1bMrSkVfX6Q5oXmCxyPM0guzN6OFmiyJHo/5hZE1NM6ywN3XRZE9pxkWQ3tXS\nQG0qMDbmu3dozGODKdtyNA1vdsnbwlh90dNglRewbI8CIDMJHogiVdZ0rfCBxVNnWfxC9Rfk43g4\n+bRHcTrtcd6v/mmZHRAO1JFEoKXx3BaTvYN9Tdv4Ghrnrw3idLDdAu6of2x5gHllRps8qgosWq9X\nK68MoESr3tlrwW7YBB5sFzEPLgaaBSMRMLl6hgEkFEhaLFnKgcIOWKrCgGWXY9ny81B7iR7fYVaD\nGbjYMNZQGjs/ALidR9imw+CRNo6ex+vxPGGxcLMb0wGYbEt9j9H9bAjuh9G6bTHtQtzQIM6DMIsy\nEN0qxRNdW6LbvHCaknG9JIdmUJttSc0M12MpHgjVsBIFkMbJb3EeYEUguqXL3yM1gKBt9q5hi9Vc\nKl5bttJtlQH44OEBJT9jYF0HT0eBpVpLmQtvtaJi2hwdHxGkr5VXBlCAJaDw4kUza7QtZrhl/crC\nuD6qv3h7leM1gc8RSNcYBkxmHAwmhzG+wRJIOH7Rcqy7gYVHr4oNAQwkvPnGEYNnlg1LLaU1ILE0\nd3OdqRncke0+TeouWpvSZ6A/A+2Z1F/PBqM9gHm7lwFcUtsMK+tHEJkApFl23ipQge/VVVojssdI\nXiueN9eW6svOo6booBIZyzUeThqvTg+UNB+DDbeV7SveNXgDrKaL1EgeOFwKKt69uo9Ebaipw5sq\n9hLviU0VPWO7Ak6WY36m03E/s5PF5JreP3uPdGLOquoaeWUARW0o6t11GM+XRnQCkYWn19WoH7ta\nM5hUYiUNZtZyTecNxR/oF1i+pnysDMUjuqbC4rknd0Wrd/T2mtRcDQYQYWI+3ckh7pCAI62oB4Zj\nM+K3V8M6lL4fAGTa7fiMBbNpR7vO6Oplz8PURu4gLB3YUymVvhmvaUsD/x5mUpIa0FL7CLAGDR34\nS4Z3FvUQayTOAwmO94CF29k66SLAeAjZAhWtz2MFCMJq665pE4K0UZ0eGOmkw0TBwjuO2ArouIZ5\nRHF7voUCvIKAolsuM9pOAxyrtVYW+9FmwuowM8wnNapfYbBPHOj8OP6+Ruk847tnT2EpGelZYXKm\nMH59WOlhoDJup4JubGM0rxzb2d4O12+gwTfbwttuZHXOohJvRwC7umZQG3kMxFrhXnlPQDGmiwAp\n8iKzOtkjy2umt22LiQKaxi0YEpUX2VKidSXKRBhYdEDXexfFR+CitgHrRZ4XUs04owNug9kPERR2\nCZZfCizatr11adhexuKl6zCPBvo219xrb0qYJFyBwXOMidjIT0mGAsw3xv7MSD/dKKMuNkA2ZHx/\n/W3DugvbzFHVYclYhwGGHTOYtBTHnl6m7gKFsfuwhXu/npTmYOYm3GBgIcCye5k9xdiKDVctlTH+\nHlqg7WcmcpQRuj2PaG2/V0B7Avp2DUBNg9T0LltQKbneXsJoauwdNcJ1204AnrCXmQcegP90ozgu\nQ2exbAvxyrOn7rESSLyxEC0zKsfSWrj96Tn3qlKv5vJLQLMFJh5z0LI0rnbMrAGQ2jc3Kpevh3UN\n/MzsmfDnDCLQU/HsJsDaQJ+cNFvyygCKusPxzbiypSGTuqYlI/tx3qeLdwxmNdjhCB9MTL3VYGk7\nMQ8vBZVpvkDhKPxG4r12/OoqczHwYFC7pXiTI4WNbb46zmCyWO5+IJtTN4NJ285qL3sYpAKzVfSM\n11teW4srrwSHh1JleeVGixlZFutnxjBmHDxg69MugU4EDtybalRaW3UxWFidkaG/dhbdY81QIimx\ngtr0Fg6J2wMAe+rSsve03+INQBgwtiS6/xbmbbei4+Uqb7PW9tTIKwUoTNnUCDWpu47XMxt5/bXZ\nVdhGioaM8M9eEwM8A4hpLC1cje5mQ7G0DZYAw0OA59HlgQsDBsd5oGIgRu7B0zzU0txiBhETi8+Y\nGE47Mo72PG/NYjd38nw4z0DNPrm2vwqxlC2KDcRrQTyvLy9+a7Giqc4uYS+eumxrvy99Umo3AbAa\nFNTVl4/5SetWLp5Ki1VX0ZYte1RezGJYlecBHofVzN75vnB79srLUH955XP+VuJZaq5BPw2teXhK\nCqy9vFRqwUA9vvj8wd2GU0o/F8CH5Zz/55TSawDanPNP1lfzOOLt8W+G+YnHAbPKy4zMvBZlGiwP\ntGmjDc5sI7FjNcwbmHhuwvyn/jv65KNlTZaWQUSdQKP5YI9ZDWYAB8zdwLowKz/6WfXVdjNgtC2m\nb9pPPY9+1DsgAAAgAElEQVRsKRtTG5sB5Q0A4PSaLvrmiYouZNS9uy4eUbAEE4+l8AaZjcRFmzzy\nVMJTdVkeHag5rU45vMtUQ37J8O7ZXCztFZZ1l8Ywr2yN12uKfj2pAZ9ooL8vc6mp32s3X1e0WMBT\nfzWoWJPSr+0nNUZ6LaNWNgElpfTZGD6/+34AfgGADwLwVbjn7sAPLRG6Tt5dTYOFkXhaU9HM6q3J\nDmDrLAxIeGGi2k8UTNQDLAISnWtMV1K6SsTzUmA5jKiKS19D65o2HJCaCz21fcxvU5XxI1vTfTsZ\nqKTlQ5hUXdb9MYU3TT8ZxqMBXdemeEylxp6hUlJX7XlxvHUuEZhFoAL4QDG1FX5v8NhIJOrhxWVz\nGq9dlk/BRgd2XtmkZfYS7l0Pp/MAckv2qsc0XaltKt4UMLqvXpu88i5lYCq8aIDBR3diB+63vUpJ\nahjK5wL4ZQDeBQA55x+gb76/ZURdhAHx7uJt4yc7im36eFwCy7PXgKvXMHhqHTF4crFNJFprwqvh\n1V2YB3sbuO1cpWaOVwIW7kHsrnyH9SM3jy8WHkYA4HY96vK97A5znG2TvwKYQ3HE3mMr0cGb97z0\nZCs+KvdSUbWcB3hbQFFyE/Zm1B5weLP5kn3GW8Vu05KoLg7TaYsHVPeZ9UcqsD3gU1OXlem1YSuu\npmwrIyrnjCWA711YGvabZn1eYikVioaV1ADKbc75lNIwIKaUWlz+SepHE14pv5o583dOFqu8W9qX\ny1gHG9hbDCCiTKTFmpkcETOSqGvukdr5lM37bLiw4aFx/njxo3R53lnOVsN3Tg81Q/20JsVvpw3e\ntcxC83nhwMMAwn1E22cf3mK1WzT66WCscV56K84DDs+WwqxCQUFVXrXMhEXDPBWaibbbi/NkL4Bw\nWdFxTZ2RRHFbKjSvLcYuPIkYyFa7SmykBBiXvEs1gPJXUkp/EMBrKaVfA+DfA/Dn91f1eKL4sdTx\n82p4GyTH7USMuUygwIZ2zzDfSBwDEdtOSiDizTerr3QjXudV3A0PmEFG4+y6xM7THAYGB8z2kymO\ngVqM95ymWboP19owIsBQ1dNWfq8Mb2PKGvE2rtQ6p3UzPWHyovKgvUG0Ag2n9YDD8rBBnuNLbEMl\nSsuuw15+PvcGVa/tFqdg5A3SJVWSV48nkdrsISRqc20b2TV4a53WJRLt83WJ1ADKFwD4LAB/C8Dv\nBPAXAXz1w1T/sDIt6PYGiGmH4OMyMQ+EZsV39+NqsNy7S+0kanxnUIHz614BtruxV47Osw5ybu0x\n4SHhVtIx2FyNaV8bkrT0yWC7f20LHMetWE53y689Tvd4VH/1y+FQjYOlAb00YG+JqZwi0CiBzR6Z\n7CR0PQwqwBJY3NX+jmpMVSVeE3XRYiQKClweTy8MbDyPMAUIj61E517vj4AwGnhZatVNXMYWiEHC\novJqJFLTaTsi9lK6PlaJ1bbJYyRmY1k4M1GaB/2mfM65B/Anxr+3rJiHl64ATcZQgCWIrNRgI3Nx\n2YnuKMwGeRuAGVAS1gAztYqOuYvbIkMOV9Enu3Wu9TBgWLhpMC2cX327Fsvu3LfGbDMbUkEDSgBx\nH/uGrly/oGmubH37xAMYD1i4na76YQNkvDBv0IfERyovb/1JxExKzKZG/cVTqAhYSlKbriZPafCu\nBRqvPC3XYyKl62bA9iYL2UlX8hEF6hiJ9cU9aukQUFJKfwuFyU7O+SPrq3k8aRp50dkgPC3Kc2B6\n1o/J30F+1QDfUngr6aI5GQuDyRZD0dePPbFA4V6+aBhi1VepXoyGAHJu8O6h2aZso0hHSl9hfGzZ\na8OJxJvMeGzFjvWF9gDG2ueBzDSjrmh/ZE/ROFD8FgvxwlBxzm2ImFcNsGh4DUjsAR/vTfFkx+Td\nrcO7Vv7VFfF76rP0npfXluwxxLOUGMonj7+fO/6+c/z9dwA8v6SylNIzAH8Vs9HhG3LOfyil9CEA\nvg6Da/L3A3j76AjwXgD+ewDvBeC35px/qFQ+34SuG76zcW1v3PTxLNqfy7ZYOZ2Am9GT6TV2DQbm\nx+1hq83g1T1YB3pvo8ee/jww8epLksY+nLX19K1reuH2q+Bn7ZFt8s392tacAALWZIuaNopcgo/H\nCPZ4dUVhNcJ17/m6Yq2XGKePwMQFiOh6nLSLRZVOUt3yhY8jA7vF1bAQBicFlq1zIGYqegxqo5e2\nFObFeePqQ4FM44TV5PfABIiZRg0LUTBqsJ7/WR+K+qMtNZu0PJUSAkrO+R8DQErpV+acfyVFfUFK\n6X8B8IX11UxyC+Djcs5vpJSuAHx3SukvAfh8AP95zvnrUkpfhcFm818B+K0A/msAPwjg38dgz3GF\n9fEHuXmzQb5dRqys9yw8wPcSZo+MwUMN8QY2AL3qTh22628JuCBxDCwlUOF6dYNKvoZG4ux6TAnS\nYt7/y4qkEXYxko4LRieD1nk1Ur5ZHlm19RnYbLkbm7HdEwaIS2d7UdsW7MYZJBYzcgqLmIkHOJwn\nUp/tZScKKmrM92TPgB+l98DTRBkBnGMuJ6pT5VI2YSMBO1FEZamxvghm1I89hlySPWlrkr4tpfSv\n2UlK6VcAeFt9FbPkQd4YT83CnQF8HIBvGMPfAeA3jMc28tmIWCWmeXFvRN9jWiG/8ExiG0rptvBM\nnr81oturqLsw5LiXvz2iGzR4ZUTzJ/5TMUBRuxGlt/tnwDFlJVBmGsC9OJDHAJaoDm3qVlv2sJSS\nZtWbyxTnNxv5m2bcs27s0qlxPqCE5SqpA4ZeqlMNtQBqWCvhmq503jj1a49spB495jAvjabFxnn0\ntycd5LhGtrp9KZ6BhCXcKHTfKzlJqS96UuPl9VkAvial9D7j+U8A+Mz6KpaSUjoA+D4AHwrgKwH8\nHwB+Iuds+4S8G8DPHo//NIA/g2Fl4dtL5d6NufUrjbkH0s2L2U14Ag9aFT99mVE9vPjcBtpS1+JX\nThcLmlrLdgNmI7zJnuU9PHeJdn2ChOs8xmNgrH5joBqvzXZjBsbeeZ49uljlZVP0BQDNvdk686U2\nDFZblYzuZ4nTfDV1eOFWNrDcXRhY4iqfaxkKPp5ab6t9KlrOYlX9+D4s2oqYhTwUM9EwT7Wm9XB9\nGsZxkDSlMC5vj1zSRWvriK6RP5Zlv7z3heUpMZmSYX6PHXPPhK/Gy+v7AHxUSum9AaSc8/9XX7xb\n3hnAv5RSel8Afw7AL/SSjWl/AsAn1ZZtLxN7rKYGgjK0qtuFa37EbHz3PqplAKLzLI9MMdnSukpS\nYh4sEago4EQkXkHEgOVu+dvRR7f4ZncduQyLmku96wRUSrJnWxWWPV5bylAUbGrL8gzzpbTahr2q\nMa8MbcvKJboZrq8BVl2rtP4E2AYVzztM89iU7A7rutRNeXGt2AaVSDxwikTrqMnj1bdXvGtTsADW\nC0+1rVze3hX2ZjfRsD2yCSgppf9UzgEAOecv3FfVUnLOP5FS+i4AvxzA+6aU2pGlfBCAovF9bMc7\nAXyqF8f0DgAW30AHaPQgfb/9TbDOj4IBQ8EEiJmFxwY0fqt7b4nOuxRMrGvWlqXfqifJds8krj8P\nINLdzb/RVKfvdw32e2RLbbVq9s521ILKJXIft2gtQ389WQw2AbDoAFdiHlEaBRoDkis6VtCBU8/i\nOtdNrpJL86lEb/KleS2/AqXqIBr4TKTEEHvAtZl470rUd/c4r9Tch/fQ3xkDY/h59VXMklJ6/5GZ\nYNy1+FcD+HsA/jKA3zQm+wwA37RVVs757Tnnt+WcF/Yc0yVP6XosF+N5IDJ9A33rzkUaYWC7q9r8\nq/bpROlK+bdeQ93h2AMODeNrxLon6r2c0kj4yGBYPaV6XW+AV3XWJWCkeSIGoiq0rXoiY6XnFWM2\nDS/M/g7t/OfZSLbiS3/A8pdtLYcWaJu1bSSypTSFMFMMsyWO0/CxTc00/5Ztxf7UMZ/DIntKFKZx\nXtmlvxrZmjrqX00+FtMpmNTsRPzQUqPy+nI+Tyl9GYBvvrC+DwTwjtGO0gD4+pzzt6SU/i6Ar0sp\nfTGAvw7gT15YPoDl4ND3wKHvadNCcmu1D2stbCgMEAYAZ8wazDsMCxuNwAPr7u91NbOpBLP/qRxv\nDXP1lVNePmf7jZaprwO3+3b8s++pYD1KTdmaeUo8gcjdACzEWGoMgvbsNIw1Z2yD8UBpj+oqmsnv\nYQ0eWKgcKkefaE1Kqfzcz1toLHY3lt+wTmua3eMxXFlHQ2HR2hWuRhkM90jm+Hqu9XC5PJPX9Hqs\ns/kt8crmOACrtyuSRn6jurw67FiZiSdbixh7AE0/94OpfeNxidEvlDYVUmOUV3kdwM+/IB9yzn8T\nwC92wv8Rhh2NLxadVS7GOx7gTrfDmpO2BTr7eBYLd0XuQjwa9Jhvs81n2LsrEs+O8tASddHSHEhF\n48/D3+k0b6/SybdWJhZC8T314mBEK6mpImM7MxyT0oCp5RvI1KjIagFlz8rjh0oHUPs4TzPcmwhc\nPKBpmsGxZdHLCVwURAB/nYqF86DOgOTZWVo518vRMugyi3YVBrFLpmegvLXhe8uNpnel8tVYrzYu\nvffAPMHygAVYxqk8yEp5E1kxfwDw/gC+qL6Kx5G+H1+IZhj37IZdtRi+4AtgMsibdN0wQLa3s9fX\nVYv5u+vMSOyu8jyqH9Pyd9P0Q1egc97xd3UF46+yFE0TMQr1KrNXSYmwAiN/X57TcBkdcB7B4nQC\nnj8Hbm7mPbvMGH9zO4bfLY3z458BRNcNHfjcYTWoR2onj30srrZfHnvlW91bjMZTwUXAwl8G9SRa\nxPjQou1rsW77eZxtZglnkOFzy7MAYMy9ynz+efphAEE9Z7WHNZfRBucIytRwfet6+dNBm+MQ/Opb\npnFwymXxMF7Pa7tAtDGkAqkHMqU6tI8bmNg8kfvTQ7sNfzIddwD+Kbn4vmWEqRlrZfoeOJ96HJoX\n852ZRhW1pXBX4G+bmBjQNJj381q0AuuuqN3oisJ1PrI1FSh2kY14feW8/HeYr5HTZ7k/GMFlBI4+\nY+H4YCouYiy561cD96oFMqhzuMcWInWXifphnIMyIzCJZGvRoqdWiNLWxLFE7YrcjhkoGgdg9ANh\nfe+U18yeYc2Y32Mgeg7MS2PtXFdnRUb8aFPK6PPFXlmaLhroVbhcHbijt5TDtsovtYPfYgaLKL2q\nFPeop4yVLM6bdXwtSwfqAOWLc86LNSAppXdq2JstvQwI9inzg11h02Cx662qZfoey91wdT2GuuV6\nCxen1sAf4O2x29wuIu3MUmolaou1x34NMAw87G8EjsU1E6j0/dqDy0BlYiujzQSArj2xZ3LX1Ru9\n3SsJQCeKL6nMOH1Ul6Y38UxI3nkJUC5hKiXVXglU+JjDzphVY1EeYGY8qjrRAd+M8fzWcDzoWFVd\njZPX2+bF2l36LHEEOtEbVyuaF3LM6WrL47ZZmAKaHSsDOUga9gLrJe30zAQ4LOwgYZy+VmoA5SP4\nZPzA1i+pr+LxRMGkaYbtpvoeOHTdrIJZHN8B3XEcDK+B3AHpFsOtsS3ce+ePB1/epXdrnsCgoSCw\nB1TUN2bz7mBeTGkqrjs55le5A3Aawk3d5VEBVncF+qStwT1iLjWdOWInpXDv+D4g54GGByh8fp9P\nsKq9JgKDUpi2R4HCy6PqEZ7h9v0aDBb1YO7pPOCrqsNbz2LhHlB4dpwa1+P7iAKRB0reW+3Fabl6\nrNfvAUYkK4cIecbA8h3hUaRp5p0W9khpt+E/AMA+rPXPLBjDKPPf7Kvm5QvTeH0Rug5oux7pdAvc\nHMaZdjeDyIREY/jVHYbLPGC2n7Cnl31DRL277HXy5kWe2JyMXysFlZIYmHjAZG1W8DvLLwOkAUuH\nycMr3w6AwXaR1eLGM3DzYjbYS2/lgTpSU6109U6nr5EIlLxwlhrQUdlSbXmgwkASGfK9l7h4/c2S\nZSnj4DIiL5+mwWTis3vlLZzkPwaTaR8xeVb8ZjBDsR7PKjEePJPkBdZAwb3eAzEv/Z75gg7Y0QDu\npWO5BNgUNEp7ekX2E1chT8/vkl2It6S0OeSXAPiSlNKX5Jz/wMNW+3LEQ9mmGf3t22Z2D2ZvJNvX\na9qGhRctWmlq2DaProz1mt+tJ9Rg/rKjMQZ7m4GZ7SyuLCjf2xRSgYP/ojRnCRuZCUg1uPgLPL1O\nt4PRnjaHzP2MMdG6ky0wmVpNaT2Q8RiKiheuRmo9rpUaIGEQ2bKvcBt4BXNJBTfFjee8YaSnyvLq\nCA36TTy7nVgL5h7e9XOPUoYCCdd0vaRh4bfD8zLbYjEavxVm4RznjcWazxMPoKK0CioqEWvzfq1u\n3t9tqocA5lKWblJiKB+ec/77AP5sSumjNT7n/P2XV/tyhG9S1wG35O3VND0O7R3QXWHS7XejK+zN\ni2Xm10HkgLsvL3fij2sB666ioMBpvMHd4qNjrcNTc3lgwuzE2AeDjIEaq73GsrKBx3n+VbaiX2fs\n88L7iwckj53UMhMFk+mKnZegBEKap+QtVhIFAwaREpBsqcK4HXs8xzhuwRDsXAAGWLoUc736u1CB\nOQxmIqrdkrWkMR0DC7Du4RGwcBrAt5swmwGFeSBkvpgRAG2FRSASgdHLEg9Itry7PDsKsDTEr9Se\nFwBMyYby+QA+B8CXO3G2Q/BbRjw9IId3HXAwf+LnLzC5EE+fBu6w2MBwUVAHTB+iMndi/jCV/SbM\nXy+0Nb9APBcxYALFc1pmSCaeisvq8MDEjO7mudXLscdkzvPNY7uIuVnfvBhsJs/fM9zL5+8Zzk+n\nBZM5d0tDvGdi8QZ677gECjVqLQ94IvHYEYsHJlusZMu24pVbapuXLmIfK9WWxTUz8wD8NSuWvw/i\ngHkQ4nDuMgYsfT8oUq336tYrWwxF0/USdnDSlewxHggoQEDS1Mqe9CXw4Xbw/bGPVkTqLb5vNpL0\nWIOGPXtlmvxO7VmsWFJ5fc54+Ek55xuOGz+U9ZYSb4Di8LtuMNAf+n5coHc7fGhrsqeY19eorjmo\nmssGZzPS80DMr4aJraYHYuJq59Y1EqW1ujWf1/08MLFjNr6f5Ph2PNfjkcnY/ViwFAIVBhOzoYzs\npAQmtg7FW2vCz8yOo1XzHph4wOExoK08kUTMxM49G4kHOJd6fJUApAQkXl5lQXZPeEEk5+dj/lUP\nMGB+5uyO3PcATjMnBnwgKQGGpvM8wEpfnzQprdPw3lQvfuvX0kZSCyQ9lmUD640jI7ccHoFcby/q\nB/wMJ8emyvfCpAZ8vgeAqry8sDdV+CaoNA1wdZQAlr4nF9gXmLZnv+IdiUwMWGzRI3fnTo6BuSts\neX4Bs/2EgaXU7flJe2ouD0w8ALmlvzsAL4Zfs4kY89CRXtVhoydYBCZsS6kFk+muV3ZsD2weSkpG\neA9MPDVYDVPZ0x4PLDy1l0kp3AaQSBQwONz7a1usFpja7Ljr176RHrBEq/AR5LM0nueXZ0fxWNEW\nI+FHtvWG1gBLJJzHRpxoiup5f9lv5O0VsZBocW+NlGwoPwvDd0leSyn9YsxWhffGYGV4S0nkPWTh\nd6fhJX/WnJDeeGM5RWsPwLPredSbtl+3wVW7TE+/PLDb4z5iBpQGy8etH/BSULA8Nu/Qj2mp2Guh\nYMJ/nfzy3x3lN1tKN9hPbm6HVfHG6E53a/dhYyzOAsYaMCkBCg9emtZjIdrx9cXRcM8I6YFZJBEY\n3AdM9roTR55iXriqtFgiVsPHzEY0DpjBQ301dP0Rq8EYWHSFvccwInYCrAGBB1IGiRJQbYGJDtZR\nOP8C6xEkKpPDTDSvVxZfL/8Cy10G7D57Enn16fMsSYmhfCKA345hO/k/TuE/icGd+C0lOhB4HkWm\n1bpil+HT3aiyuR02i+yvZk+mtgUOV1jaTvTXPoXTYf40L5N666b6WD37yHQ1hXMFs5LNxNplGzye\nnTgGFgKYmxczQzF1lqm3nr9n3H7ldmGAz12Pm5u1rYQHFHtGHpDYr86CPfBRFcvqDsqgtzXb2gKQ\nGvsGsB9MatyI7yv8ITCrx+qyOOXPtkWLgk8JfFsAOM4DEPtqWLrjcXa07HsgdTOwWG+2suwt4S1e\n2KdS3YK9QbiUxsItzNuatQYUvK6zR/W1R7wt7dVewu3U40hPYu+pefrttZ2YlGwo78CwM/Cn5Zy/\n8YKyH1V4MSPrBnWW2vfAtFLeZtan0QagX5cBgNebHR8fNukxA4ipy2zOxVualETTeb/q9usxkI7S\nGLh4qi5iJ6aj8Ly7JlvJidalDOzEbCO6CUHkyaWDvAckmofPS4b66S7KbfbycRz/lsQDBnUJ9kCk\nBCT3UX/VtHVPXE1bvOfL4dYPDi1wJHDiODtve+ozmI3OuoLKBuoEfx8wwLet1LCcXvKH1401YJTS\nQI73itZXcheO6lfwKdlR1HvvQVReJjnnb0wp/XoMK+afUfgX1lfz8iUaqKzTds2AF3cdcM3GZttB\n13YgZredtgXaE3DNXZcHal2UyOosDue5AZNw0K/31HrnmOdxHZasxOIIHBZsxM7ZhiIAk+9IvUXO\nCtP5mTaCHIGYjPCsL/e2WSmxjGiV/BaY1LCX6MXY+8J4TKVpsDLA14CJByR7QWVP+hpbip2rTUgl\nUkPysTpi2GCly5p4dmyTktbKR+wNZnEmBioeiFh8yY6CQtrF/Ylvy3D9VHYNqEQqLI7jt1+3W9F2\nM3DYKKXt0XFSPfXU26tWanYb/ioMNpN/A8BXY/gQ1l+rr+LxhAHEOq6JnbctMG0X0h7mWTe7D9t2\nLIs72WOeLzF70O6tgGJdwBiKgUtETC2Pd86eZ1a3AcmdhN1KfIcBNBRkKP35dnYJvnmx8twagOZ2\n9O56Djx/D/KpW8w47U915pGKS9nLdMWFMD6vYS81L8SelyYS9frywpnJlIz8W/XUtmcrn4LGVetf\nh6dCZPEAvm3XgGJ1TuuLu+XkQ21u3dh9+Q1gIJiubfzTZcYlDy8rU50DGkqna1wg6Ti9d+yBSiQ1\nwAKsnQ0MQIClYh1YuhbrLz8r3eeLQeZBAQXAr8g5f2RK6W/mnP9wSunLAfyP9VU8jvDNsW3sWYPF\nCx3PHXC4uVmPRm07uBIfr+YB9Pn4KK+1C9t5T382QJuai78/z1vgQ8rSLfE53gM1O76hNqhnF4OI\n/d1Suy0dgQm7AN/cAm+8Ma8vmVReNzPYdB1OpzUT6fsYTDxGUgKPrbwsCibeupfSxpLahhopzeR1\nUN5KVzLWXwIiqVnfJ10bw+mnb8yJlECZByQOYwM9D1LA4L7PjKTv5z33JobSDd0OWK5jUV6fsQQE\nO1YXY53eqd1hun90HvlcRqABOXbvVyGuRiy/XY9Zc00YMExqt5mdPPDGZ/OyNod8Mf4+Tyn9CwB+\nFMCH1FfxOOKhbdeNs6ExjQ0yL26A154Bh7bH/CXHBmgOY8bzcvrU3Q3xV8DcPa8xM4Or8Zw3kjRQ\nYaO9fnzUjDOsHrM87lXKH6u3OIzVWmqIP2FyC7bfcyf2kDOxktMMMLZV/Sh3p3HwGJPpTFPBpJaN\neL/q8WXhNYBRYi167EmkEoqk5FLsrZiPgGSPfSMCK2VEUX1NMxB0rWeLqei6k8V9bZfgYnGHdgYQ\nSytrYnEL4FmzzVgazIrnHr5tBYj3DOO3sccaaHgjJAUzS6OgEsXxryeldDZ6mDBwlFRgQGwCXuwa\n3a/7JrOUWqkBlG8ZvwP/nwH4fgyj3Z+or+JxhA18wNz5zH5iYrO2rrMdiO9mNU57NWc24U0QAeCq\nwdJ+wnMgI902b+A5jf3ZCnoOY/HmTT39WrfnX2YlnsrLAMSxndyRFxcDR3cmpwW6R2+8Abzxk7i7\n6XF7mmehqg8vDfJ7wGQLSPi89IEsTy5hI6U4D0giMCmxkktUVVy+V67+Tt+TbxACTXS9ERgz4+B7\n23UDuNx1y3PLZ6ppvQfMYhYqbAIjBgDm9B2FRWyF8zBYMLD0EpYp7eq+UFouaw+oaFkaxuVGmy9t\n1av1e2ovoJ4Vs9QY5e3rjN+YUvoWDIb5D99f1csVVnUZMzH6xi+IgUnbjqqvydB8GlQ+bJAHMG/H\nch7A5XXIxxGti3ruv7ZFi+371VIeYAYY0PnqyrBWa1n+DktwMRWXLWBUFReDiVEJZ48utqEYwJi7\n8Bs/idvn/bTekdUUq5kkluone0763CIQMYm2Z+FzmwVzWARqJUDzhFU2NfaNEoMpDdwlUFEAURdj\nD8z02M5TM9tKVM2ljIbvC+8oDPiTANa/2/02W4qJ1WeTEG03q73s/WW7i/Wvu26c0Fh+zNze1FS8\nr4UNpJ5dpGRX8dJFwkDgdSllM73E7ZUIeCK7Cf+yWzi/J+jmZ/YybCiT5JxvAdymlP4sgA/ek/cx\nhAcMG1wYYHiAsW29mlOH1Iyr46fRIMXTxGkVPTAP1IwwFmaJzHbCXYnnQ2pG9MRAi8HFnrKuPfHU\nXT1WzOR8WoLH5ApMoPL8xRJMnj/H+dTjzjG+e6qJiFFYGP96IOKl9crccksurczX45clW2tMPFDZ\nWqNSAqKIIakj46GN186olFikrllhYzu7pbKhnttscQvnjmYZZ/nuOqAZ399bYHrd2N7hAYK620Yq\nMGBmAOxCbHEdluXqoN5Len77VWpAJCovMs7rNXiS4QOIKV902UWtXLJ2BbhgZcZmgSn9WgBfgeEe\nfHXO+UtTSh+BwbPsfwfwO3L2TLGDMNLyrMc6Je8tZMa+m3GHsiNO5QtqmsF9uEnzFvhNI0/L62Jm\nzzDD/B38zR23PpDFIKKOAD38vboMZG4pbnQLNoeDFZjYQkZa0Gj7dT1/jvPzE17cDFoyM8az4dVe\ndl4tvQUi0RMtqcK0o0e7JGyBiQckOtA9pJQGfo2vXacSMSIeiPlYGQnnj8AksqPwfWZGankYYJRJ\nWnpTQbNqK0l7eAsXXbU9Pa8x/Aqz0tkG8ZKFMnIt9oDGznUBJBAzBQ9USgymJF55nh2F05W2ZOkx\nACDZDdUAACAASURBVMcZSyaiLsMPbUPxZO/3aYuSUjoA+EoAvwbAuwF8b0rpmzHsePxvAvh0AJ8A\n4FujMrjDKoXTwc1eqKaZ1WRXttbiOG5xbx+N4sLtE7d9DzzrgGc9cGVdlgf7I+ZHZiZC3oW4xXzr\njaUkOrcnqN+BZwDh3x6rxYlTW8yT6wa4u3FcgWndyWIl/AvgjfcMNpPn75nUXLYSnpnI6bQ0vCoj\nURbiGeb5OepxVFbJQB/JHpZSUnHVqr9KYVH+2m+neL82IBvrMABRcNE/XZjp1avPkQehSUNsr0oz\nqq3a5XNRQOB31Yz1puqyDV0tXydtnuw/p3EXY5pkMO/nPbAgx4C//f3UPgrz2E5P6XrJA/hAw+Fb\nY7Xm1/q2DPLWVk9sGx3ecVif99b75JXpSkrpz8MHjgTgp9dXUSW/DMA/zDn/o7HurwPwKZjXFvXY\nYEXaUa/GjqyzVwaYcw+8NqXpcd2/B9Mq+j4D3WtDwqYB2nHdymTIp6dwPALJPrZlBvvXMW8seY0B\nZGxrFlaLMVvRbsFABayBhrdUMWC7lfORJWV7M9leImqv56Pd5Pnzea3J6XZSc5knDu8VafruM517\nqii7Vd5xKY4H/5q9vTz2E9lvorZE4tkpPMM2z/Q53itHwyIw2QIRry5uy/EYAwmvPeFBhdmF/bIm\nAM0aXLgMBRI7vhrVbMfjsh913bgtzAgszWkAEbWzKINhdVn/HNPHJti6qLfc+2Qwi7c9awQqKgos\npe5VApUS6NgowywlAg4eXTjtpAJ03iWdmNdKiaF82YVxl8jPBvBP6PzdAP4VDCqwvwDgBwB8VakA\npWjckc1AbwDDYjR7MtKbPozfgoXbUh7Oj+P2989eGzaWPF6PbKXHACJp/LVB/RazcV4BpDS/MFBZ\nXTFme4nV4ai6TNfHLETB5PnzeX2Jxd28mLy5bm6WzITtJ6zyMnDx9uzi52S/08AkcV56z9uL6/BA\nLGJKHkN5GeJtx6LHCghAeeFj9JukPOvTtncWMxQDEa8dFs9i7Zm2THfuI79vCib2rO+60aIoQK9q\nMmM4en3GdniNisl070bnS2/gv8JyibGBjboZN3IMpyw97520HrA08gs53is91iyF226/nuprcvFx\nAEQnCLVS2svrr+y9uHuIxz5yzvmvYwCWdYaU3gngU+1cfar5/Nwt87IO+dAsXwSgxwFjb510BlfL\nrzp23Qwmto7F/o49kPgxGmtpMKu6mGQ38D+PY2JdfbotmNmHgcqdnJ8HRnI6kRfXaanuYuCY1prc\nzDaUrsP5NIOJuggbmOj6k9IAHh17HVa/LKjpvcEs2mplC0jU6BgZ0FUl8JCyZzuWCIRYxXVoB9Bg\nlZeqwrQMd1UjVzreuDT+Hsbf0iprYOmgcWjWzLXp53Ber8LXynM6BsHJuWYMuzKg6Wb1hnl62TCg\nGyaVFgJ6rsKsW+D8CiAmOthHoLJXGBjs3ANBD+xUPPXx3jUowOU2lIeWdwP4OXT+QQB+qJQh5/x2\nAG8HgJRSVpfRI5YDXNsvPVHOPXB9nG+cqXKGWV2Ptr3BlQ2ub/wk8PrbgPd6G/D668RKng/np9Oo\nU0hjAdfA668NQHR1xNIQzzYUtpvo9+buMHQVxlr26DKDv0UJgNgbqPYRAxVT3ZnNhONuXuD8/IQf\n+7ElkOinUaK1J/YcgLXdhMXSlJjKFihEthRNq+0pybQDb7McJPeCSe5HI2+BpZTUXx57sPNI1XZ1\nXAKJActkd2ixzgRg+oKpVm6yuqnn6Tz1PQ59P/Tgvl+5iR/pPbuj/mPG9sVCWFmfon99P7+n9msT\nnKYZ+qoxmKYbwQ7zlE53K/aOeRGkx1ZKbseXStQtFXiifBETMWG2Yr8Mqq0BCLGUydFhB0q8VQDl\newF8WErpQwD8XxiM8L9lTwF2AzI9VZ1wTeAyhmfq7HlcJWxg0/RA7nqk0+0QoUyk7+eB+3Q3btlC\nQMKr7I/X9iYPjVxslmCioDK1evw11tIByEsAMTEmYl9WtDZPxnb5tsnpdmQltKjx5gXOpx4vRlZy\ne7MGELaj2F+0Cj58Vs75Fnspqb881uLlMYm8y/Z8j6Tv6QWV8jzV0ZZsGcVNPDBh9Zb9md2kbYHU\nVoKIucWrddbS4oDBMaWZ4whc0PdIXbcy0jfNcI/OnbgOd+P9a+Z3kZ+f3sPzOFm0y2AN9fEIPHs2\nhzUNgBPQ9ct1KewFpscMMNG36tWdGBTmDf7KRLyuVwKNSCImojYVZUQKkpEtpWmG9+SOkWdD3hKA\nknPuUkq/C8C3YXg2X5Nz/jt7yrDFigwIbMw79zPS3p6WHZc78l030Oa2Ba6fDTsTX/X9wEpOt8CN\nvSkZi2/Qd8c57HQ3GPSbZngRzaB/vF6+1MnmQAkrxjExE7KDAMsRloGBAc6ATL24bm7WCxhJ3ZWf\n3wzbd40gcnuDyU2Y1xWw6stmnqVFgyolwNnK4wFXCUxKrsl7xJuwlxiLgY0OiLVMJ1JzKZiEACJs\nZslKDnRMa66ihim4YAQY24ZHKWbbDmqxvp9VPWP0gdY42DuLDjgcl2pqU0HbrHnyzOyX9wOYjfS8\n2JYnj/1pqfYyUGFwAJagoAsigeUADYnzQAQU1xSOt8CGheNZkQ7MAGcLFCIxZ4XV0+6He3UQt/KS\nJlRlM2lK6dsB/Oac80+M5z8NwNflnD+xvpptyTn/RQB/8dL83IlUVWEvtx3z4MeGQeukFnd7Ix5g\ntg3J8WpUgb3X4D58Gu0sz1/MTOX0tiWAtIdZHdbyC31YvrD2RURgDp+8zgRU+LsuxkwMWMwt2Fa6\ns89v38+sZFSH3T3vJtu8sQ8jNLqAUVmJziojBmLHq/GJLlXzbm0kuYeVlIDM6s99HbPQAX5L9Dpr\nRFVeXv3WBg9gFsykbX0gKYFJc5jZh39VAJr1Q6WXKPU9mm6+8eZ9ae8bG/GbccLSYOnibNu2eNuw\nNA3QnGaQNdWXXk7XzUwFmMHDGwA9wzvngZx7LCa4U+HxfeY8Cg49yIGisgxTlQFY2MSA8nujUoM9\nP8PABAByzj+eUvqA+ioeTybw6JdqCOvvOgMClh1PHbwMmdPYaa+abtpld/p7dj1ue389HDcNgHGX\nYiukvRrcVtrzbEW0yj1QMTWCqRkMOFjtZumAGehU3bXYJfjFOs3IVO6ed5PxnQGFbSbRSnjvDyjb\nKry46Jsoerz1WyrHezEYyBRUzn3so18rnh2FZatcjjPwYq8ts5Ecj4P9xOKrwSRSf2kD+OYxI2kA\n9ClmKwBSOxjwvY86pWbpcr4AHAGdyWOT/u46TN9OsXvhXYaVp0plBgAefFXLw8VFn8jjMr09vxRI\nptsnZWi5DDpRV7E4z5aiqi3zCtNyJ5Ud3X/g4QGlTyl9cM75BwEgpfRz8cALGx9CeNCwcXwab8fe\nYR/Yamm2o99ssPScf+6cPa6ONsKa99T1aKSnLngcv09vzOV4JFZCHl3eDNFeeFtAqQtsDAyYsVg4\nb52yUHdR+AQuJ5w7LFa+G5iwIZ6/wMisRIFljw1l6xl65x4oeGqwKG2pTg9UojRax/QiXgA2XrlR\nOaERntgI7881qbkMTNrWZyU8mdl7EQvwKA138zUYW2GWYVt9AGvA6eRd1UnioQEyvaum9ruFb5Mx\nl2KznbCw99eWJ9jqVmAGAs/GomlK+S9lLMZMFCC8VfS8DkUdEBqs9/mqlRpA+Y8BfHdKydyIPwbA\n59RX8Thypo4GzJ2VVRKmUzU9a/Tth4OEn3vguhsG3sGLpsfxeJr0xFPPV+N804wqrnYIb6/oJXf2\nCwOWo5upryy8STNLMQ+tBah0czjbSKat6QeGZWtLjIHogkV1DbbLU1ZyqQ0lkih9BBCRPcVLWxq8\nPVApqb4uZSuXlqHaJPtV9dYEJi3TmKslK5mMEQIkpcaESCvqsEaYiiOp6adZMCc5Yzm588DEwgxE\nrGm88wVrGczpZsWIu6UdhY3pbIjnxY18vuXlFTEXL1wHeu8V8O5kVAezJw9cGDxYzQUsP8bV4CW5\nDeecvzWl9NEAfjmGe/l5Oef/d181L1/OHaZphb0309qSMXwRNop1Xtst93hczo76HmjGgfXQDgZ7\nm/kc+27wxTdDvNlKjtdA/z5YGOQn+4nMFO2Ft8YAWHjNaEOBmZ1M6rfzMh1vR0+M5E5UWben2eDu\nrTNhYzzvJhwBiQLK4pJkAPHsKHzsxdeqs0phnkw6fOfNVbWXtm1LPKN8VAbb8UpzDbWXsHfXBCYT\nkDRYM5MATBpvOdiY3hizN2XV/rtQiR1WaRNmY71nPzFhLYFtYsiYaPeWTYvTLrnNEmhuqImZm4e1\nLcSmaBruGe+BefC2fJxeQYKvzwOTLXDhfBpm5Z/l2GMpfJ0uCBCY1NgITUJASSl9eM75749gAszr\nQj54VIF9f301L1/6scPlZjmrsdmm2lS8hVe83fa0/2M7rFcBZhc6nj1dHXu89uwGh2fdrOrqe+CN\ndrCp9Gegt73BbucG84zRs6HwyDKp2OjN6fOs2jJQ6TosDPVjnvNNN7gBiwuw2kp0S/rb01K9ZeHR\nvl12X1XYJmFinTSytZQWNvJxCTS2WIo3PjK41Brovbqm8rC89hIYHZy2WR7vpWYAbxrPm6vxHUAi\nEIn0fVO6AExqqOgCZAZQOTTLyQHbT1jf1LbDQGXG+XM3s5Hcrl8XBhNgSeJt7UuL4f1ntRbv8cQD\nL9+VaO2Kl2+6dDrWMkt3LmImNWDjqbGiLVpKa1gaD70KUmIon49BtfXlTlwG8HH11bx84T5tL+/C\nE2S8KbzXke1yah2QOzPPdvgbKm07dGJ7P+7GQbc9dTgeu0Fd1rbDgG5bstiix0WPty3vb5eNtBec\nvoy4GD3NVdk8uNgIT8BzPvULtRUzEmZfnqqLGcoeICnaUGTQPqnVc+OZ6m2I0tWq2fawjAgMeJa7\n56XbEgUT+/VYyRXt0bUCDgMTZiuLQkXt6l1gBBgTK3G8wGrp4JjOexbmRsz9DRjVXQ5omLCq25rC\nakEz/BsbavrZ84tVWR0dR+tLNA+n5fMtg/MedrIllu9AxxG4lEDHFD7RJDGSEFByzmYn+aSc8w3H\npZSe1VfxOOIxEkBmn2O46md5Ftr3A2DY91NYr2tqH/vjb0m07WDUHmwsHdq2w+H5e2YPsKPZT2z7\n+9v5hfamzgC9tCMjWTCU8+CmPAJIPnUrUPDWjvBKd1ZhRRs/cjoNs6ZEX2SsHdwjiYBCy91atFjr\nBmxl6wCn7GCv6msv04nKNUxI1Od048lNe4gHJqUKS6BiDZ7+Kn11qLxpvYwfvbKO2/WzOosvwxg2\nsFTHsoHeXiP7VoupsCJbCrBmJia13kl6h5mp3BdMOL3VYx8eZ+YBILShKLgswh4CUEi+B8BHV4S9\nqcIdpW0JbelmqJHP7CkGQqqDze2sQ+97DLYUYjT8dzcaC7sOuGvJhfN0QtueliuVecbYHpYX0ec1\nm5moxB14MaWBiNo/GCjUO4vjbG0JrzVhI7ypvJSNaHlT0x1Q0WcE1A3E0fjlqcK28unAMIU742UJ\nWErhpTZ4cwWvjSX3YhbP22uynUwFOiveOc4DE7WFlITZsvVb7+FbGk+ovtQUSB6Bil2irkuxcJ4A\net9VOR6Xl5DHEbTBem2Ksg39BoqlKYFKyeMLeBhG0sg5183gYPXaF5rYhqJAwmn3NK5kQ/lZGHYB\nfi2l9IsxM8P3xrA3+1tKGCSAuQPZQO9N3PSlBGYA4cHm3MzhCkqsfjhTO4Ah38yAetiTOTQnt26T\nBfjQS5q7fpqB8b5IrI5iBqEbOI7FLNIqK7E0nai8VLXlqb0s/xZFrqXQBhg2i1UACSfNhQBvlgms\nx1J+JmyYXxXtXLNLNlEPGJ5of+FJzWJ/rvaKVF1kn2OVqqf+0sqUEhpgTH8OmEwdSJxEtgBqrM9A\nxZ14jC7D/H7xIkbFxaYZVFvaVzvJYzuRJ2C1BYv2EU81BvhqLgaMxaVSeHS8JcpoNJ+FKUthFmKf\n+lNRt4y93bXEUD4RwG/HsFHjl1Nd/wzAH9xZz6MI2074fcmNv6KZt/Fe5COXRCsny1RAWQCv7G0a\nP2xiQ87gtUjb9+j7fhrsOZ69r27EyB6pqbwvK3L7PZbBhkwtT9Mq2PC1RaIzK5XFmNaXX7TaCZQN\nVqwWPTTLtioYNFjq43WsrVV7PaQwmDQNqOM4a0o8MNkrJTCZ0lA4d549F0Wg4mnZOrr/TbO0p/A9\nsQ97LUCDnqH9cRnol5/Ay1ivjAeWTGZ1CXQcgUwNeHA+L40+wRJLaehct7nXXYoBTFv5G6A2qFfr\nWX5Xcs7vAPCOlNKn5Zy/cUeZb4rYy88PmmcjxiDM9ZBBh/XQkyF+7JhMqe1Yv8PNaawDq0OAzSSV\nLTGoaLg3ueOB/eZmuW28shPdYkZVVZpHjaDsHlz6GuNK/cXtdZ4Vu19655qxtPmHdvaqb1M7rMED\nwIillMbkkrprM+30b87LA6XtJHw8bthkFGAUTDxa7DUsYhdTB1k6guSuX4Gtnk+eaFG7R1Dx1JkK\nNgwWfK+A5bfmD83IOpzJHbMUAxJgyUJ0vcbUXDquMb6XvMB65ziSWnZj4Z4bcSnOs6fUSo0N5Zek\nlL5D9vL6fTnn/2RnXS9VOgydouln12GTqQNiVkvxO8UMxl4AS2NxPc16+n5QZzWUjzt5264NsQok\nEU0H/HfYYwc3N+uBX918t1RVJe8tBSWtC6B4LGc6NbMancd689qoQ9fM7uz8LOeLWVrvq6IWAyHW\njhsrJuOU4wGG2nD42AMJu9d9v2R/Br5rV+ENFrLFULiTAUt2Mu0V14H3i2OPQk8taROpaa3MhOhO\nW4SpUBBsZ+KWNAgqNiE0dZe39kyBaGI6/XKvLw9cvPUqNaKshq/cA4gtgOE83rmFcV1atlcvbypp\nfawGJExq0n5SznlScY17ef06AG85QLFvJKJf6loXDAJLygvQYD4a/yI1FdtXmJGYCotBSV0az1SX\niX4cyYQHbP4g0R4wKIGIx06UqSgw2X302IgBCVNofQmUZXj621L6WjlL2T2WRlaAXqqxD7BXoIk3\n1qn7cN+v00a2lC2xCU+kB/QGwUX5jTh37Knc0y9ZOfZrW/tMn5A+hZ6DnBVYqqJ4YhYCi4CK3mfe\n6kZVX3yPtozyfJnMUkw8cDlLPLe8xpbisRQPNCIg8USBwZOzc8zGeXtHFFT2Sg2gHFJK1znnWwBI\nKb2G4SPpbylR9DVQ8b6zDSxX2UZsxdLzHzMTNfA1zUytbU8hrrPE9PmXB3jO46msPIbigYeVW1Jr\nAb76bFU23ecISDymwjMjTzcdvQw806oZJiP9duPFFUBF87MtBVg/zxr3YK1HwUlBywZM3qvL1Vj1\n530gssjbr3/7XtjJzEryzcndOJQZijK6iSWM7jw2uUuGGBugwnLul/dH2Z0yD9VWcLts4nSgCSUw\n21CUpUTgUiPMUviaHgpcGFi8sjOWA36LGFS0TbVSAyh/CsB3pJS+dmzTZwJ4x446HkVOmC8mYXh4\nTY/p62uAAACFe2wlN7GawwMXBS1LrwDG6jGWaGDxvo9uL6ilK7EQNZR7dhYWjwFZO1S1pUDCIMLF\nanpIXE2HtdlizYvV0C/bVKwuZTH3ER6Dq4BJLpbBaWviYXE2854W0epWK7r7wtYCRm0Qg4nZSGhm\n4hm51ZOQhe0Xz54tJzk1oKJyaMZ77GTRhY9moJ9YSLP0BrVq2xFMzEBvotvdc3Xe1iwl1mLFJvjv\ngjeQ90GcldfIcQmMeMxrnDwei6kFM5NNQMk5/7GU0t8C8PEY7sUX5Zy/bUcdjyYu+vfrmSl/h/ps\nLybWjANYgobNEFllpgC0/kb9muFYmPcC6nvFIAA4A3wBRJSd7E0zbbSHNSOJQETTTdexflzFcE/0\nhVaJDPL2IWXeunwx6NeCgebD+llFYzU/Y6+cKT/Gj7y187Pnj2Vx2nMHHKaN5+4GUOnTWBCrwPJ8\nkVsN5QoMTMb94IyZmKehHfPaJa9PW1VtC7zxxrjWV74uGYIKsGIpDMKWxTaM9FSDBjBmV+FboO/+\nVCfm56SDcmRcj7y/pvsw/nrsHFKHnW+BSkm0PI1TIIn65R6psrfknP8SgL90z7peqvDs02RaiNRj\nMtarq7DFK1vxwMCE2YimP0taE91+fGp3v3z5pjY1PsPw1FiRukvrKKnF3LIQg0YtQ/FeAE6X5Byo\n9NTCkmXwLedyIxCJQAVY2kFUphm1ZZMBypvAuG13+oiVpd+gPzSzYwjge0AtPLpqhAdv7QDTd3fO\nC52WGd5tTzje901Vpyy8hut0WtuZ7J656kKHpVizzY14YhhYqrfsEpNzWyyfjQU1gG9iG0EyQESs\nhM/11iiQIEhXEhv3+DgCEh0jWc3lLdq8BGA2ASWl9MsB/BcAfiGGzzkfALwn5/zeO+t6qWILdRos\ndYVmrD8AaMeOqwO4enSpi+jkVXJasxFLY8IApLM0NcyXmAnHewyiBDRabmlVe1jeeE8VHJShQMI4\nHbAEncW1oSw1w6K+uKyeaOCDCDtvuKCC9UaW+rw43youeIY6AYlsKSVR9akbuSUekNixqbr0fFxf\nYqwo2qIn+i5N08zXejoNg4g5zTDbL10471BsZXtuxOwBZpO7Q7Oc6HE6YPnNdHUhZvDwDPJ7Bn8W\nVXt5oFBbvgcqduyJXYu9DzxWtlheK5sMaqSGofyXAD4dwJ8F8EsB/DYAH7qjjkcRG9TUowdY3kDP\nWK8sRG0oqr6yX+6k6iLMW2+zRAMOxyuQbNlTOExVYhyneaP1I/brMRJO09GxgogCDijOk2j2xuIx\nF2UpDBoGLCoNlhMQbUjDCbEcGD1Q8SSK98rwBlN9TpzflQVFajCtVp/Ag9Re0Qi+WvHeT4hxPvW4\n69YgEvYlZwZhqqe+nz9019C7smBtDuix11dDoO9N4Dh8ocoSMOE1mIuJIWbQqGXMNWJVqHq+p3Pv\nXdgCFg9ISvn4Vnu2EwaSyqnKlG9Tcs7/MKV0yDmfAXxtSul7dtQBAEgpfQqAL8I8Fv3enPN3j3Gf\ngdkN+YvHRZVIKX0sgC8D8J05599fKj8avHhgsfOr3kdefScjNqLvpHZaW+sC1Hn9cLpofyp9z/W3\nZBPhtIu1JVY+tRuIgcS7x1vpFEA0Xhc3mpSM5g39GnhweRafEQ8GC5ah9cuAVWrHXp25jpNsc5s2\nPOyBpp0HW1XRLmTqHGegHyGVO/BUcVrni8piI/y4aLHrsNiux5JH+7ppNWx79PrvaudgvgZ+MUnY\nOG91qKj2gFVc5sZsDMbKtO+lMEsprZyv7QPMPCzMez9Aab3yom65F1Q4jWsqwNozbEtq0j5PKR0B\n/I2U0h8D8MMA3rajDpPvAPDNOeecUvpIAF8P4MNTSu8H4A9hYD8ZwPellL455/zjAP5dAL8KwBfb\n91miwk8YboABhc0sDs55BnDXA4d+ntWarhVYMxcTZTHAMg+Hcx7+9d7jmnDdFLH0cobeW4jZBoLw\nLZCpyR/ZVEogUvKFt2emKi5rpxfeUxwDT6bzRT/pBxUpTyg8+5dNOljVoqyXX1h1Uzc9g5Zrahjr\nl/zMQ7BVdZYZ6u0GNIXhZfLqosWLpwFM7sbPQ9tXPnXLnpqPrNk12+4TuFlen4FnUucBLgRzHo3W\nc/PwsnqPtM1/34/usi2QjzO4tPSuNTThYrYCLG0QgO8BFgGIPgHv64+QfHa8FyTsfdVyGgqzMZMn\n3LZFy4GOa6UGUN4+lvu7AHwegJ8D4NN21AEAyDm/QadvwwyEnwjg23POPwYAKaVvB/BrAfwZzNfZ\nY4N52kWrusNjKfDixk4ErAcREw9Q7JdVF8pK1AAbzXx5HUPNVwl5pmjlRiqsLRCwMAURDd8CEk7H\neS0dpIzF9Uu5Jnz7FBAsH78I9sJYX1A2ojMyjc90bnY3dtrgrdMt7NwvbW8q0UzW7CnMUizMxIzy\nDfWNyfbQY/4UtXl2uTo6a2x22Epe5uv7OWxkJ97Yruq4Lemlf9oakCOVNwze/fLFqxTNoutQzj1W\nIGT5mKWs2h3UV7uwcc+AzCCk4LCnLAYSPu8lDNhWEe+RGrfhfzwevgDwh+9TWUrpNwL4EgAfAODX\nj8E/G8A/oWTvHsMA4KsxbJX/l3POf69UdsnYqud8zN9CmG7o2LG7fslA+N0sMRHV6Xp68mDy5aaJ\nAMVbIzI2vwgKLDy4e0Z4a38N84iApHPKtHK5jeza6w2+bGxnVZdOHqweTqsvyhao2Ln1B7MBmNEW\nEDZCzzoSD1SUgU7YQA2edoemMGtH32P4DPWqssLQ4H23RG0vfQ+cbqeNSLVoCyuxE70OZiN2DeYy\nrGk9cb3bRA7EFFX1m4M6lFFO7sX2vuMycIhEQYfDH6J8FS6T69Bwd8IThEcSAsq49iTckinn/JE7\n6rE8fw7An0spfQwGe8qvhs888pj+2wBUrXmxAUS9vTy2AjrmgWcBLNaZxk7Yjee68+xUv0wEt/S5\nW4DigYhnnLdrj0AEFBfZM0pqrZp0GgYsAYfDQOm5jaVwu20r4Ifz3LAGFmDpHql9opWyuN6F8X6c\naPAnEUyi/qCyAC6adEyqr0tHFLajNIe4AVNDqCMvyqCRuGkmEPDUq1tF1gCEDfQPLdxGBrDSbVH3\n4gbz4nn29uLL2rOfV1gvYkYCOo6AIRJlKRqm+XVS9dBG+U/eUY4rKaXPBfDZ4+mvyzn/EADknP9q\nSukXpJR+BgZG8rGU7YMAfFdF2e8E8Kl2bi8+G9vt5k3GeKwfnA5G7uyXZio8U/VUHLUvk4oHHMAa\nPOy67LfGRqEDO8eXbCadpLM0JTayZZznNmibvNmTvlz8fFTFFQEL57mic3WX9GQ1Q+uXYWr/VmZb\nLJO8nICZndngfSfxkeSe1F59P4BKabjxXKImQFqOxKYO4mRcRBqr8oq0dPzLtqjar1jWSFS/PjGW\n1AAAIABJREFUtyjUzpkxuRNAYNK1N/BnvpHaqxYjvU0jPQDR+EgURPQ92pJLgcQk7Kqk6rpYcs5f\nCeArASCl9KEppTQa5T8agzv6j2JgIH9k3MUYAD4BwB+oKPvtGOw7SCll1nvrLNXCDHQitYiupoaU\nM8X1WNlbVHiF89RmYTleHLBkHvwLrEGC46OB2869eI/ZAMP9KAGJxzy2WIp3Pd4sieN0RsgviKrK\n9Fl6E4g7+GrRyIai5z2wWigLOPu6SfkqHiixLQWYB0le5zExLcKPwdZuAedxKt3sc8+JrOlWVIuV\nQ0HkCRcN3vxn3mu6Ff8WyHiqNXYE0/q0PZ56CxhsZV03O4MYUAKxzS9so5wr4LAd19IqS7mEtHl5\nleVcUnaopnLkMRc2fhqA35ZSusNgj/m3c84ZwI+llL4IwPeO6b7QDPR7xOhopOZSo7x6fimA2Ey3\nlzhAgIdGytW74Dy5fvynab1B1hvoeWD34kr5IxDQvPexmXhh2i5lJiweEAJLYOFZHLMTFm8CweEe\nqHBfUT98BipunJXhqaoiUPHsafbXdbNHEn9EywbzbtXJBmnbkaV0XUy9agwVbJBvGqS2wRH9yk5i\nA7ptqniWrUtKqiW7tuNxsHlc0XWGbaK8LApoh2ZgiGw38bDSc3LQjTmntKDnDJ+paN/nvN6AvMUY\ndCJUYi0l8YCkkXA48TyJ2iOPtrAx5/xHAfzRIO5rAHzN3jJZSkb4aDZqcZ6B18LhxAHLTsIdrGbT\nQav/4IRx2TUAwb9RmhKDKbGMGuaBQloFEw9YakQBpHfClJWqnUXVntHCRqX8OiFZgcQIKjU2ExP+\nnAKzFF09rl5JzF4WdYwz9MNkWO8xe3ztmF8HOqvU9NMHvjTJ1B7aJ8vaxMfmNcn7d5k6rYhxY4U1\ni3qZzXksxn6ZDTqXC2D2EEPvMxRrcmnQ9datRN+Y3yN7AYaBws41rwcwWyzbk0db2PiyRRF1oVLA\n+mbpQOGFg+KsPGYukDSWX8WrHxjWzlj+GoaiM3sFoaiMWhDhOM8zS1VYXv0KIBG4aDsj0dmUgomC\nSsRYjHV47GRrArJ1DprdAjMRYPXOGbPNjdUx/CVRAxMDEvPsMoxgoDEPL6tvJbqdfcn9qiRjY5um\nn9ZtqEw7X2PZz70FwbwxZA2QAL4dkeMUZNTNmUEi8rKL4i8RZQQc7j2q0qaSe5jMljCwRHm89+lB\nVV54uIWNL1VKKi9g9ugyQPBUYsB8Q1n1ZaJlIkgDLF8sBQKTqBNFaqwthlLLckrgY78R6+C2e6ot\nD1C0HVqWd28iALG4iLZzfmWClt5jJ1HfKXmALZ5fh9WuClMU2R66fh5MmZWcsdZOsS2FFzoeMAOV\nqm6S6z7YYFp7suX9xULeYgyOyqAszHOn1ryvvz7bTYrfdwlEgXVqaoMVkNulsg0qsr8ou1F2yIzE\nPL5Ax9YfIhWXJx7wRCxiLyspyd78e9LXLmxscM+FjS9bIs8uT1WhbMPyN/AXzlkeTzXmtaPBUg1W\n6mClmYKVt4dhePm5DX1F3JYHF4dvgYgHKN6vCoOFByoKJj3WndmeM/cHd1NIJ4/JFlNhBwBTfxWN\n8c3MMKa2j/mmwYzAw+LP3bwWShc2MjA1XY802VDuxtGVv40SzZ8tWHrrODqb2kuCp12EPbbEnlQG\nHvcBE7e5VG/Br2Bx37h9JfXYXtnavl6lNFC/LGYSxXsTtK18nuxZ2HiDey5sfJlig50aYL0BwI6B\nJRNR8ImYB5dTs2Fh6cFvsRQPACyeB2XPSA9JAyedBxhRuRaum0JGAFICFDh5gHWHjkDF6+Q2U2wl\nHT+7GoO8TiS2VKmLZ1wBKrxIFphn1jy4NXR8ll+eUZuYF9YKVKZKxhYZuPTwR87FCE1X0Yw7/jb0\nCV9jXcFKemsXA0cEJpF3V2Q7iT7XwMe8WFTL0HaW2lA7OSxJNA7UgMKlrMR710plPgT7KS1s/BQA\nHzS6/iKl9C4A7z9G//6c8zfcs+4HF3vBo1kkD/R6HjEQ62NdkA+URtNq27w8XhyHR2ouYHZxjFRY\nQJnhWLyW3zv5vD9taw24lDo5n3tMRGdQkejKeO0P3uLXK8kTuaF7iye1DrtQ3cJnmuGP6jHe/0tt\nI30/r0MxsOEB1DPO85qLFj2SrcpVdtKfsfgAl0qEDlgWZW63po7zXN8trbe7d0lWi3cDMOE0Z7o3\n9uEvBTtgvRcZs60z3WvAnxxEDHavbHDFKU3vHG+l3RKdoJXy7QGZEkP5/Ri8u0yuAfzLGOwnXwvg\nLQUoNojYDfJmnDwIaBodrNz1JxQHive8tlQ8I3EpvgYEzk4ch2+prbzy1fDO+SOw2JtG69Zz7yXS\n8cfCjJGUXgp12PCeE1+/SYmd6LnHXJitsE7fxDYvnGbNDkiYUd7sMLwQ7yx52nb+2uNstxmBBViP\n5sxaFjfDGSbHPPZdErbrXx+XM/9ISutDol227bfETOzP89zy7CMarjYWYF6H4r13eyWyq+wZqF+G\n1IDJXikByjHnzHtsfXfO+UcB/GhK6S1nlLfBSmezHmiUDPegtCjEWxxLDR3mgStiKTUAASwZCrev\ntOjRC4/ymKeX17YIQDwQqfll8QCkFG/LLaKXQxnLFlBE6q9SXm/SYo21AViFPbUmdZUMkrY774Kt\ntEt33QhU1Eid+O4wIvBUneO9X2D1Sd7pehzQ5DitoiQ1zITjGQw84I4Aj9ngWdiMHUaO1/cZiL0P\ndNUa9CNmcUl7NE+kCquVEqD8ND7JOf8uOn1/vMVEGYoee1JaaW3hbLi3cjzDu8nWOhRvlqMbItba\nQaIZU++UtQUkCghAvKmjpldQ8eqLOn70EvAL4w3qms/bZ8kDfE+NVbOhaOQBxu2ziYh+a6cBFrsR\nq8rH7AreJoxmjOfNIXlw7k+DmsYAyf5s5+qFuq0nxsKjv47yJcv2hkSAUQMknqZti5nY91j4u/bK\nRrhMZSkLdRelifYXuw+ImJTWpwA+YNQwib2qK++R3Bc4S4DyrpTSZ+ec/wQHppR+J4C/tqOOR5Ga\nizaw8NRcpfUnlmfLPRhYM4+atnrsQMu0dJC0Naqykh3GA4St8yjOS+P9wgnfMwuqlQhk+MXlduxR\ncVn5SeK4X1narse0yegi/wggqqqa6iN1F9tYeFufxVoXirc4tPMMndlKQ25mK4BRkXBvsFWy48Vt\nFLsIU+N6CUw4jg3xBi62TT4zGQWvaGt7zxX/oWULCO4bHwnn2QtekZQA5fMA/E8ppd8C4PvHsF+C\nwZbyGy6s76XJ1g2wl5xZiG6xAizZh2dbgZPOkz1MRVfPcp3RbH6vO/De3wg8SsBRSgtJo8d7QGUv\nADGwtFivS7nEbsJegXafPWbCExj9tgowD3y8+M6E7SVsI+Ct442R9COYMDC1ozrM1r94HwprxtFj\nYC7l+xgZ3Vk8slMCmYhFADNYcLiyDI3Tc2UsfA2mTuR764FLj6V9bMfeA66UbDF71rE8pHhgcgmw\nlDaH/BEAvyKl9HEAPmIM/gs55+/cWcejiDdolVRgHgPRvFugAcTrUfasPTk7cd4XC2u3ZLG4WuCo\nDSulrSkDKHfQ2s67t6N7L0jktRWde23QgSEqe8GKxoGfN5bkT/+egQkEWM314mYY5I7HeRbOhnkb\nPFndxaykbQkM+/UK9sUFoMw4puu9x6jqadGYYQBrTy42rjMzWRjWu/n8ztmGZcFuKJ3lnz6RjTV4\nXHq5OhbsXa/yEFLb9vuACVC3DuU7AbwlQYRFBzbVQ3qgAvk1cAG2DfAWpmBkEjGUrY7kqaUgYTUL\nGmvBpBZsLgWnqF1bsqVHvqTDa/q97MRTi05qrUKcnXtsxVxueTdfkOrLBnYGl5Yu5Ij1Cv2+n4GF\nV+Xzdid5/C193piFbfgaPl1jQWtWymfCjMTSeH+WTvftYsahbsPMPExVNoU7HmDAaFMZ2xJN1v55\nlaj9nmZkjzbg/2/vTINtK6o7/lvn3QdqnCdKBYMmGoWkJC8qaKJSIvj0g4gmakgpojEVCxPBSiXo\nhxg/icZEn3EglScRLBU1ECVqcIhxiqLgYx4EAg5PKYeKlSgIl3vPyoe9+54+fbp7d+/hnHPP63/V\nqbN39+phT+u/11q9u3MmuF5qmItsnxAfqUCYUHz/7ggqg5g7DOKxlNDFHBMnHPdNx/7A0K27DwLY\n8KTl1uluh/JSblr3fI+cvBDMKDAf2rq8bKiV58I38MPAJRXf9xlmqDBMYiRGCd7FhCjW1phaoMuQ\nkyECGVkjyRyXlxnW3LTuiksqodh9E/HElsA2siEXl7uypS9ob8dNDKG4/7Z14nWjMf282aOyjJg7\nBD8FTS9CGpHzKfsUxJ6/mGyb9laKUFLgXqgQ8fiIyIZNGDGXGMyO4oLZm9VN9x1Pk0I32zGlnkMo\nMZmmPLddd9tOc69JaD/0MLovC74HKHZ/bLmCmJ263s4PycPstfUN8LD7auQNqdjKzA3MA9x5Z+Xu\nsn39a85BmViAPbOv6+4y7jS7bjtO47ZrYJNaDDtGE4L0Ifa9idn2uanceIr7/Yg7yss+h7Zl4pZ1\n+2PcXT7YLz+hZy4E37PhQ9cYSoiIckmIlmUOOELxEYR9o7j/sYvhyocQ8rW79bj5TYqxSaGnEotb\ndwpR5bThbruIkYmb3nQ97Otr98MOzMd+KV/Hx+aHM+2519R2eeHkm8WdzPBhmFgYRjEaJe1zFRmS\nsS0SrUd3me9RDLnYri6Ynj7etZDcwH0MRtYslZ3i+goF5G2rwz1Gmxi24h0BsnAD7r54SWjQQMgK\njXkQfB8FTx1foI42irstSbhoqiPH3QUrRCgGvrcIWxG5ysbnNvG5xmz43Gpt+2nX6SMQ33+KTFtS\nMf8+8kqpM7XfPtjnwEcKoZvbljVyI4a5ue1vWUxb7igve9RgzFqZsnzGFbEYC2Pn2rRCd2MLoalX\nDHkYYtncqBaxct1ddizFWDSuS6vpY8SY+ysE1xpx83zWiO9nx0YMiWyOpwnFEI4btHeD8i4RjZkm\nhk1rGysttJSDQSwtZ0bi2KlNedGykfqSlyNjY2UIJfXAbcXkU2A4aU1KLJfB3b40pYdIxt33EYBP\nxvcfqqcNScW2ffuh8+5uuyTuqytUX4iIQ1ZKimXiDsbwWTY2fGm2/Nb+uP5g0iENQxIHHTRR/Hag\n2WeZTA05XpuM7ho5P4BNa9slGFfxp4wAiyEUe2ma8NEXK/GlmzI6hvX1iWUyRSYegt6oycTEDg1R\nbFrbMSLwDZLxycfc2rnurtgz6cq0qTcXK0MoxqVhEDoh7htiKK9pvwuRQPMFiyniGKmkpLn5ITLK\nJSXffmp67Hz6CCZUl48giKTHyqUMJTZpRuGMLBmbZEJpO61t04+7x7BzHUbrlXWxY1QpxrU1tpbM\nNYtUhX531QRhAu3euIplnfgGA/j+3e0QUknHFz+xt2Nzd/kslbvW/ZaH+5shGmbJxLcNzdZJ0zOR\nEydxn8EYceTW5dvuipUhFGg+MU1moavcYvt9XIRU5Zuzn0suMYLIyYv1LwVGmdrlQ0TiWi2h8in9\ncetxYdxS7oeMOUOEffWYNHexr5mpXTYqt9TUdCtjv8vLVqz2cGFjiWwyybMX/XKtFfAvFBaKtbSF\nTR72v0si9rGFYicm/e71WZJxXWMhMrFdmbaby/1OzBcnca2TGMks4sNFaOcWy8XKEErKm659opre\ndO26XLkeniVvn1L23fSUt44m2ZhMTv2hPsYQcnn56oq5KH0uMbPvO1afpeLLs3++2IltZdgk4pax\n+xwaMWaU14jJPGE76gbXLIXqTrECE3eWIYqpL+gdwrDJxDetvE1ANmIWTSoMybnkYeCzQky66fvM\nEODxxJ21vj6bZtJtC2UrWE9F6jYh2BZIyM1lE41v9m6T7pJM08fJvnq6KHjo7wU4BXMlFBE5FngH\n1TP4U1V9Rp2+G9hD9fzsVdWz6vQjgb3AjcCpqqEp2ybo88S5BJTSRoiEUttpept2t5vKxsrEyCtH\nJpSfglQS8Sn+FKQQVup1NsrfnY16nclsxz5icZdCMGkE5HYy++3MaH0SL1lbg83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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ ".show_image>" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "exposure_reprojected.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can use the slider to slide through the different energy bands." ] }, { "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 data analysis. Currently Gammapy only supports the latest model (`gll_iem_v06.fits`). It can be accessed by the `dataset.galactic_diffuse` property and returns an instance of the Gammapy [gammapy.cube.SkyCube](http://docs.gammapy.org/dev/api/gammapy.cube.SkyCube.html) class:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sky cube galactic diffuse with shape=(30, 1441, 2880) and unit=1 / (cm2 MeV s sr):\n", " n_lon: 2880 type_lon: GLON-CAR unit_lon: deg\n", " n_lat: 1441 type_lat: GLAT-CAR unit_lat: deg\n", " n_energy: 30 unit_energy: MeV\n", "\n" ] } ], "source": [ "galactic_diffuse = dataset.galactic_diffuse\n", "print(galactic_diffuse)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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GAQPaG5xxUrIwBjELx4HNF4HrO2p1jxxVrgrsjG2QdlHrjhZwzpphUcszWp1D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\n9/23fJ6TjupU2wWT91GvIYqGC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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ ".show_image>" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "norm = simple_norm(image_ref.data, stretch='log', clip=True)\n", "galactic_diffuse.show(norm=norm)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again you can use the slider to slide through the different energy bands. E.g. note how the Fermi-Bubbles become more present at higher energies (higher value of idx)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Isotropic diffuse background\n", "\n", "Additionally to the galactic diffuse model, there is an isotropic diffuse component. It can be accessed by the `dataset.isotropic_diffuse` property and returns an instance of the Gammapy [gammapy.spectrum.models.TableModel](http://docs.gammapy.org/dev/api/gammapy.spectrum.models.TableModel.html#gammapy.spectrum.models.TableModel) class:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "TableModel\n", "ParameterList\n", "Parameter(name='amplitude', value=1, unit='', min=0, max=None, frozen=False)\n", "\n", "Covariance: None\n" ] } ], "source": [ "isotropic_diffuse = dataset.isotropic_diffuse\n", "print(isotropic_diffuse)" ] }, { "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": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "erange = [50, 2000] * u.GeV\n", "isotropic_diffuse.plot(erange)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimating basic input sky images for high level analyses\n", "Finally we'd like to use the prepared 2FHL dataset to generate a set of basic sky images, that a can be used as input for high level analyses, e.g. morphology fits, region based flux measurements, computation of significance images etc.\n", "For this purpose Gammapy provides a convenience class called [gammapy.image.FermiLATBasicImageEstimator](http://docs.gammapy.org/dev/api/gammapy.image.FermiLATBasicImageEstimator.html). First we define a reference image, that specifies the region we'd like to analyse. In this case we choose the Vela region." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": true }, "outputs": [], "source": [ "image_ref = SkyImage.empty(\n", " nxpix=360, nypix=180,\n", " binsz=0.05,\n", " xref=265, yref=0,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next we choose the energy range and initialize the `FermiLATBasicImageEstimator` object:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": true }, "outputs": [], "source": [ "emin, emax = [50, 2000] * u.GeV\n", "image_estimator = FermiLATBasicImageEstimator(\n", " reference=image_ref,\n", " emin=emin, emax=emax,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally we run the image estimation by calling `.run()` and parsing the dataset object:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": true }, "outputs": [], "source": [ "images_basic = image_estimator.run(dataset)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The image estimator now computes a set of sky images for the reference region and energy range we defined above. The result `images_basic` is a [gammapy.image.SkyImageList](http://docs.gammapy.org/dev/api/gammapy.image.SkyImageList.html) object containing the following images:\n", "\n", "* **counts**: counts image containing the binned event list\n", "* **background**: predicted number of background counts computed from the sum of the galactic and isotropic diffuse model, given the exposure.\n", "* **exposure**: integrated exposure assuming a powerlaw with spectral index 2.3 in the given energy range\n", "* **excess**: backround substracted counts image\n", "* **flux**: measured flux, computed from excess divided by exposure\n", "* **psf**: sky image of the exposure weighted mean PSF in the given energy range\n", " \n", "You can check the contained images as following:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['counts', 'background', 'exposure', 'excess', 'flux', 'psf']" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "images_basic.names" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To check whether the image estimation was succesfull we'll take a look at the flux image, smoothing it in advance with a Gaussian kernel of 0.2 deg:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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ikL5DqRSda7QM5Hbz2s30Qa7+qqdnrue0cdXJvy+TXJN2JcIZ/7Fd50Ilrom4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\nv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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "smoothed_flux = images_basic['flux'].smooth(\n", " kernel='gauss', radius=0.2 * u.deg)\n", "smoothed_flux.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "- Try to reproject the exposure using an `AIT` projection.\n", "- Try to find the spectral index of the isotropic diffuse model using a method off the `TableModel` instance.\n", "- Compute basic sky images for different regions (e.g. Galactic Center) and energy ranges\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What next?\n", "\n", "In this tutorial we have learned how to access and check Fermi-LAT data.\n", "\n", "Next you could do:\n", "* image analysis\n", "* spectral analysis\n", "* cube analysis\n", "* time analysis\n", "* source detection" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { 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