{ "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/v0.10?urlpath=lab/tree/cta_data_analysis.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", "[cta_data_analysis.ipynb](../_static/notebooks/cta_data_analysis.ipynb) |\n", "[cta_data_analysis.py](../_static/notebooks/cta_data_analysis.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![CTA first data challenge logo](images/cta-1dc.png)\n", "\n", "# CTA data analysis with Gammapy\n", "\n", "## Introduction\n", "\n", "**This notebook shows an example how to make a sky image and spectrum for simulated CTA data with Gammapy.**\n", "\n", "The dataset we will use is three observation runs on the Galactic center. This is a tiny (and thus quick to process and play with and learn) subset of the simulated CTA dataset that was produced for the first data challenge in August 2017.\n", "\n", "**This notebook can be considered part 2 of the introduction to CTA 1DC analysis. Part one is here: [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb)**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup\n", "\n", "As usual, we'll start with some setup ..." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\r\n", "Gammapy package:\r\n", "\r\n", "\tpath : /Users/jer/git/gammapy/gammapy/gammapy \r\n", "\tversion : 0.10 \r\n", "\tgithash : c6bfb5371a5a1682cea9aaf56ebedb3c42010a43 \r\n", "\r\n", "\r\n", "Other packages:\r\n", "\r\n", "\tnumpy : 1.16.0 \r\n", "\tscipy : 1.2.0 \r\n", "\tmatplotlib : 3.0.2 \r\n", "\tcython : 0.29.3 \r\n", "\tastropy : 3.1.1 \r\n", "\tastropy_healpix : 0.4 \r\n", "\treproject : 0.4 \r\n", "\tsherpa : 4.10.2 \r\n", "\tpytest : 4.1.1 \r\n", "\tsphinx : 1.8.3 \r\n", "\thealpy : 1.12.8 \r\n", "\tregions : 0.3 \r\n", "\timinuit : 1.3.3 \r\n", "\tnaima : 0.8.3 \r\n", "\tuncertainties : 3.0.3 \r\n", "\r\n" ] } ], "source": [ "!gammapy info --no-envvar --no-system" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord, Angle\n", "from astropy.convolution import Gaussian2DKernel\n", "from regions import CircleSkyRegion\n", "from gammapy.utils.energy import EnergyBounds\n", "from gammapy.data import DataStore\n", "from gammapy.spectrum import (\n", " SpectrumExtraction,\n", " SpectrumFit,\n", " SpectrumResult,\n", " models,\n", " SpectrumEnergyGroupMaker,\n", " FluxPointEstimator,\n", ")\n", "from gammapy.maps import Map, MapAxis, WcsNDMap, WcsGeom\n", "from gammapy.cube import MapMaker\n", "from gammapy.background import ReflectedRegionsBackgroundEstimator\n", "from gammapy.detect import TSMapEstimator, find_peaks" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Configure the logger, so that the spectral analysis\n", "# isn't so chatty about what it's doing.\n", "import logging\n", "\n", "logging.basicConfig()\n", "log = logging.getLogger(\"gammapy.spectrum\")\n", "log.setLevel(logging.ERROR)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Select observations\n", "\n", "Like explained in [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb), a Gammapy analysis usually starts by creating a `DataStore` and selecting observations.\n", "\n", "This is shown in detail in the other notebook, here we just pick three observations near the galactic center." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "data_store = DataStore.from_dir(\"$GAMMAPY_DATA/cta-1dc/index/gps\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Just as a reminder: this is how to select observations\n", "# from astropy.coordinates import SkyCoord\n", "# table = data_store.obs_table\n", "# pos_obs = SkyCoord(table['GLON_PNT'], table['GLAT_PNT'], frame='galactic', unit='deg')\n", "# pos_target = SkyCoord(0, 0, frame='galactic', unit='deg')\n", "# offset = pos_target.separation(pos_obs).deg\n", "# mask = (1 < offset) & (offset < 2)\n", "# table = table[mask]\n", "# table.show_in_browser(jsviewer=True)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "obs_id = [110380, 111140, 111159]\n", "observations = data_store.get_observations(obs_id)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "ObservationTable length=3\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
OBS_IDGLON_PNTGLAT_PNTLIVETIME
degdegs
int64float64float64float64
110380359.9999912037958-1.2999959379053661764.0
111140358.49998338300741.30000202119542841764.0
1111591.50000565682677411.2999404683352941764.0
" ], "text/plain": [ "\n", "OBS_ID GLON_PNT GLAT_PNT LIVETIME\n", " deg deg s \n", "int64 float64 float64 float64 \n", "------ ------------------ ------------------ --------\n", "110380 359.9999912037958 -1.299995937905366 1764.0\n", "111140 358.4999833830074 1.3000020211954284 1764.0\n", "111159 1.5000056568267741 1.299940468335294 1764.0" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "obs_cols = [\"OBS_ID\", \"GLON_PNT\", \"GLAT_PNT\", \"LIVETIME\"]\n", "data_store.obs_table.select_obs_id(obs_id)[obs_cols]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Make sky images\n", "\n", "### Define map geometry\n", "\n", "Select the target position and define an ON region for the spectral analysis" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "WcsGeom\n", "\n", "\taxes : lon, lat, energy\n", "\tshape : (500, 400, 9)\n", "\tndim : 3\n", "\tcoordsys : GAL\n", "\tprojection : CAR\n", "\tcenter : 0.0 deg, 0.0 deg\n", "\twidth : 10.0 x 8.0 deg" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "axis = MapAxis.from_edges(\n", " np.logspace(-1.0, 1.0, 10), unit=\"TeV\", name=\"energy\", interp=\"log\"\n", ")\n", "geom = WcsGeom.create(\n", " skydir=(0, 0), npix=(500, 400), binsz=0.02, coordsys=\"GAL\", axes=[axis]\n", ")\n", "geom" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Compute images\n", "\n", "Exclusion mask currently unused. Remove here or move to later in the tutorial?" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "target_position = SkyCoord(0, 0, unit=\"deg\", frame=\"galactic\")\n", "on_radius = 0.2 * u.deg\n", "on_region = CircleSkyRegion(center=target_position, radius=on_radius)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "exclusion_mask = geom.to_image().region_mask([on_region], inside=False)\n", "exclusion_mask = WcsNDMap(geom.to_image(), exclusion_mask)\n", "exclusion_mask.plot();" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['counts', 'exposure', 'background'])\n", "CPU times: user 3.54 s, sys: 512 ms, total: 4.05 s\n", "Wall time: 4.11 s\n" ] } ], "source": [ "%%time\n", "maker = MapMaker(geom, offset_max=\"2 deg\")\n", "maps = maker.run(observations)\n", "print(maps.keys())" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# The maps are cubes, with an energy axis.\n", "# Let's also make some images:\n", "images = maker.make_images()\n", "\n", "excess = images[\"counts\"].copy()\n", "excess.data -= images[\"background\"].data\n", "images[\"excess\"] = excess" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Show images\n", "\n", "Let's have a quick look at the images we computed ..." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "images[\"excess\"].smooth(3).plot(vmax=2);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Source Detection\n", "\n", "Use the class [gammapy.detect.TSMapEstimator](..\/api/gammapy.detect.TSMapEstimator.rst) and [gammapy.detect.find_peaks](..\/api/gammapy.detect.find_peaks.rst) to detect sources on the images:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "kernel = Gaussian2DKernel(1, mode=\"oversample\").array\n", "plt.imshow(kernel);" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['ts', 'sqrt_ts', 'flux', 'flux_err', 'flux_ul', 'niter'])\n", "CPU times: user 1.02 s, sys: 139 ms, total: 1.16 s\n", "Wall time: 11.5 s\n" ] } ], "source": [ "%%time\n", "ts_image_estimator = TSMapEstimator()\n", "images_ts = ts_image_estimator.run(images, kernel)\n", "print(images_ts.keys())" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=2\n", "\n", "\n", "\n", "\n", "\n", "\n", "
valuexyradec
degdeg
float32int64int64float64float64
21.389252197266.42400-29.00490
10.278207204266.82019-28.16314
" ], "text/plain": [ "\n", " value x y ra dec \n", " deg deg \n", "float32 int64 int64 float64 float64 \n", "------- ----- ----- --------- ---------\n", " 21.389 252 197 266.42400 -29.00490\n", " 10.278 207 204 266.82019 -28.16314" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sources = find_peaks(images_ts[\"sqrt_ts\"], threshold=8)\n", "sources" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "source_pos = SkyCoord(sources[\"ra\"], sources[\"dec\"])\n", "source_pos" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot sources on top of significance sky image\n", "images_ts[\"sqrt_ts\"].plot(add_cbar=True)\n", "\n", "plt.gca().scatter(\n", " source_pos.ra.deg,\n", " source_pos.dec.deg,\n", " transform=plt.gca().get_transform(\"icrs\"),\n", " color=\"none\",\n", " edgecolor=\"white\",\n", " marker=\"o\",\n", " s=200,\n", " lw=1.5,\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spatial analysis\n", "\n", "See other notebooks for how to run a 3D cube or 2D image based analysis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectrum\n", "\n", "We'll run a spectral analysis using the classical reflected regions background estimation method,\n", "and using the on-off (often called WSTAT) likelihood function.\n", "\n", "### Extraction\n", "\n", "The first step is to \"extract\" the spectrum, i.e. 1-dimensional counts and exposure and background vectors, as well as an energy dispersion matrix from the data and IRFs." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/jer/anaconda/envs/gammapy-dev/lib/python3.7/site-packages/matplotlib/patches.py:75: UserWarning: Setting the 'color' property will overridethe edgecolor or facecolor properties.\n", " warnings.warn(\"Setting the 'color' property will override\"\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 3.44 s, sys: 144 ms, total: 3.58 s\n", "Wall time: 3.49 s\n" ] }, { "data": { "image/png": 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jo0mOjq71+siOnfgiZzuvrF/DjYOG1nKI3kCAuxfMxWm3c23f+n/nEVYbP+7Tjw+2fmc6w+Y2wOQk3HNQjkl1OsJjaNYU9MgroPxxREWBfXiNBIUEDiAVf0NZu4N9eFNYHRKlOSFyOipyeq33xD4cqXgBIi8PnmjxbYJANrg+NtoCIy8DFPi+QypeBktbjlpuZW5+IWv3FeLy+UiIjGR8eobRUldZGbJsprC8jLZRUVzeqw+X9OjF1ur4X6TVRu/EpAY51KbAqmncd84EHl+2hF/P+pJpXbvRMzEJqd4Fz8rNptzj5ebBw9BCJEmGdEjlhdUrG/Tzac20jN+syXHEuxoVc2fIdcp5DeJbj7g+gKq3jMQKNiSQD/6dqIgLIPKy8IgDWXuAcoBnEdSz09V1H5T+Caw9UfHP14wvWjtBxBSyd/+F3cW3U+L/FdcPGESMw8H+8nLm5uVSVFXF25s28LuRwdsI5+7MYXq37gBYNK1FiyHEOBw8MmESmw8dZHZuDrNys1FK0SWhLXeOGssn27eS7Ky9qzwZTSniIyIo93pMZ2jSghAXaLGh16lYUDZU3NPgzza6NyRgxORi7kKp8BEKVUpB9G+QsgcMrcWISTXsl0ARlD0CeA35sDoSLYt37eK/m3vz3MgiJsVaUXbDiXWKi2d4WkcGte/AvYvmMzKtU73qMQvz8zhSVcXw1FNLzjQnSin6JbenX3L7Wu9F2+0cdblCHkMXocTtJtpuxxsI4A0EiLLZzroMs+kMWxpaLAQOQT29vMfRD4GKNRyJrXu1BFf4oqydIPZhpPJVcH0A9mGgnEhgL/i3G7HB6N+iabWdvF/XeWvjBu4bO4HIyATEPduIU57A9G7d2XzoAHctmMvdY8YxPiODCKsR9yuqLo5eVJDHQ+Mntprau9EdO/HahnVc1L1H0DuENfv2ICI8s2IZOUeLsGkWlILxGZlM79qdtNi4JrS6+TCdYTMhIuDfbCQCfFtBfGBJBhWHuGcaytHBcM9rESovPyTKmoaKexAJFIJ3A4gX5RgFMb9Fim9D2QfX+blVhXtIiY6hc0IbRB8AVW/Xue5XQ0ewYu8elu/ZxdubNpAaG0tAF/aXlzOmUzpPTpraqm4T+yW3JyDC4l35TMjoXOeaco+HexcuINkZzYXdezIsNQ1rtWTZ3J253LVgLrcOHcGItPDZLZ8upjNsBkR8SMXfwZ+PipwGzl8AdggUGNp+Ve+h2/rXnyn25xpdJXHPNq3hTYSypEJkao3XBAHqrkPMKSpiYMoxQQoLULewQ4zDQZ+kZC7r2Zu02DgOVJSjaRrpcfE1pLpaC0op/jBqDPcvWkCF18t5nbvUSADtLSvllq8+J87h4N8XXVqjrjIxysnVffszIjWNB79eSLuoKLq0adscl9FkmM6wOah8FcSFin+6ZmxP64Oy9UG3pELp3ej6PajIacfXGMOaliFVb6KcvzLkr84WLB2N22XL6Fpv6SJYjt0G+raDpf5+aE0pAiK0jYqibVTDFGLCmYz4BB6dOJnXNqzj/S2bGZKSSqTNyu7SUnYePYrL7+e/l11ZZ4E5QFabtlzeqw+fbN/KH0a1rjuRkzGdYRMjgQOIdwUq4V/1Jjk053XogQPg+h/i/gSxVscD/TlgSUfF3Imy9WpCq5sfFTHZGEplH1Ur/tUxNo7V+/ZW91l/DpYE9LLHAR9KS4KIiShrF7yBAAUlxaTGNCBB1YpIi43jgXHnsr+8nE2HDuALBOifnELu0SIqfd6QU/kmZmbx3nebKPd4iHG03qmHpjNsatzzUI5zg0rmAyjnT5HSP0Hsw6hAISDgvK7WRLuzBvtwcH0ErveRyCvZU1Zq1BL6/URZbWw8eICqo/cRGVgAEZca8VTlAP8upPyviJbCiqJL6NKmbZ1FzGcDKTExpMTEHH++Yu/uOrPQJxNtt5PodHK4qtJ0hiY/HBLYg2qA6oqydECwoFQEytEyCqebE6WsEHsvVUX3823+Ahbu70FKwihiHHbc7m/5Tbf3qCo/iKfNK7SJPSHRYh8CkZdQVPQvrJWP8KOeTzffRbQwNKUapJ0I4A/oWBqo6BOumM6wWWioJp9ASLmEs4d9lVbuXz6Gm/t6uHvwZjT9GUBASyPgU9yz7kaW71/H70dFMCnTGMp+sKKCuXk5zMtry6PDutExZgNQ/5S6s4ke7RJZU1jIlKyuQdcVlpdR7vXU2FW2Rkxn2MQoawb4Nhl1dEEQ/26ML3rweRhnE39btYJLew5kWGcjhnpc6NU9C4s1lSem3MxdC+byyfZtvLt5E95AgDhHBOMzMnly0lRSIgYgFc9CxIygbX9nC+PSM3hr4wYKy8qOj0Cti8+2b2VwSge2HT6Ew2olK6FNvQmXcMZ0hk2NYzJSegdEXoXSgsSu3DNREZNCy1qdJeQVH+VQZSVTu3y/izmWSNH9W1D2EShN4/bho7h7wVz+c+mPsGpajS4KkRgQL+hFYAmtB9naibDauLbfQB5esoiHxk+sFUvVdZ0nly/l8x3b6dK2LYerqqjweilxu5jcuQuX9ezdZIIVTYHpDBsZET94VxnF1f5cQEDcSMltSPwzaFpC7c+4FyC+dai4vza9wS2U1YV7GVstuFAL8QFGRjQ1NpYkp5PsoiO1JLWUUoiyA/7GNzhMmNqlKwFd5zdzvmJkWidGd+pEpNXGrpISXlq7iiJXFQ+Nn8jEzlnH/7DsKS3l/S2buWfhPB6eMInoENnocMF0ho2I6BWGND6gIqaDbQAoDfFug4on4Mh0dOdNqIjzMIqu86ulqQpRMQ8YOoEmALj8fuLqyWQqSzIE8gEj0RTrcFDl89VaJ3oZ6GVm6OEkpnfrzuhOnZift5NPtm/DG/BT6fUS43DwzqU/Ivakn3vHuDjuGDmal9ev4YU1KxukExkOmM6wkRDRkfLHUdbOEHV9jRiVcgwCx/voFa9C1XvG8CQELEkox2RwjA4roYWmIM7h4GBlRd1vOiYiZY8Y81jQOFRZWWPGyXE8C6rlzsw5wicTHxHJ5b36cHmvPogIv5kzk9+NHF3LER5DKcV1/Qdx/ecfc7CiolWUK5lR5MbCt9kQMT3JEZ6IFv0LY5hS1OVobV5Fi3sUFTHBdIR1MLpjOt/s3oXbX3vHp6wZYM2AytfZceQwPj1A15Nax3RfHlL1X7BmGCNIxdM0hoche8pKqfB6Gdg+eE2rw2plbHoGX+/KbyLLGhfTGTYS4pmLijg/ZNZSRZxvTJIzCUpydDR9k5J5d/OmOt9X0b8h4Mvm8MF7+XF36/GCJD1QjF76MBy9GrCAbxNS9S5SfCNS+W9Er2e3eRZT7HKREhPTIAmvDjGxFLtDy4SFA+ZtcmPh3w2RV4ZeZ+sJAUNCKSyEWJsQEWHToYPMytnBd4cP4fb52V9RzoYD+/j9yHNIj/8+9rezxMOb345nWNvtTG83Gyn+AMEO/p3GAKy4h1COycd/xhI4CK4PkbLqLp+GaEieJditViq8Dds5V3q9RLQQ9e8zpXVcRUtEaTS8uNp0gifjCwR4btVy8ouLuaBbD24aPBS7xcqWw4d4fuVyLnn/P4zplE6HmBgOVFZQ4fFyQbfuTO8+zfhpSjHiXgzer1Fxj9eKEypLMkT/CirfQipeQMXe0xyX2SLJSmjD0SpXyPpDEWHJrgJuGdo6OqRMZ9hYWDqDbyNYQwz69m0Ea2dzV3gS/1q3Bpffz3NTp2M/ocB3eGoa7172I+bvzOXFtauYmtWVC+Lj6ZWYVLOmkATwLkVF/Tx4wiTqKii+EQkcQFlC9+meDdgtFiZ1zuL9LZv57YjawhjHWLZnN5pS9E6sf15POGHGDBsJFTEFcc9GpHbA/xiGyspXqIipTWhZy2d/eTkrC/fwh5FjajjCE5mU1YVpXbtxxFVFn6Tk2vGtwB5jhIKtX9BzKWVHOcaBZ8kPZX6r4IpefdhdVsKrG9bi8desyxQRvszezuPLljCqYydyjx79vhsojGnSnaFSqiPwFtAe0IGXReR5pVQH4B2gHLhaRMI/qm3tDpZ0pOJvEP1rlKpZqS8ihiKzVIB9VDMZ2TKZm5fDxMyskN0N07p25675c/hJ3/61pfr1YtASG9Z2pyVDoPAMLG59RNpsPDx+Ei+uWcn1n3/C+IwMUqJj2FVSwofbtlDh9TA+ozOF5WV8vWIpEVYbV/buy6h65suEA019m+wH7hCR9UqpGGCdUmoe8FPgNqAzcA3wzya26wdDxAWeJYh7Pvj3gr4Pcc9CIi6CyIsM9RXfdkObDw0Ve59ZSnMSu0pLmRpCPAAgNSYWq6ZR4nbT7mShVhVp/KFpCFIOqo66xLOcGIeDu8aM42BFBYt35fPtgf0sKsjnR737cF3/gUTajH+3evV40pfWruJwVWWdA+vDgSZ1hiKyH9hf/f/lSqltQCqGVrte/Qjb4JkE9iFlfzYEWKOuBmsX4zbZ9ZkxKN39GWLNqn7/SrANMgUDzhC9vtsza2fQyxD/bmPYVD2I6IhnKSr61kayMPxJjo7mkh69uPnLT3l80nkM7VBTSVxTikEpHXh04nncOW82Pdsl0q1tu2ay9vRptgSKUioDGAisArKBt4FS4CfNZdOZIHoFUvYQKvKy6vY6AwUQfR3ivAapeB7Q0WL+0FxmhgWZ8QlsPLifYan1y/cD7C4tASChjm4TpawQMRlxvQ/Rv68/QeX9BpTdmN1sUi/L9uyiU1x8LUd4IolRTi7s1pOvcnaEpTNslm2JUioa+Aj4jYiUicguERkrIjNEpLyO9W8rpSqVUpX5+S202t0zF6y9ajjCE1HKior+NfizEX8LvYYWwpSsLiwuyKfS6w267ovsHZyX1bVu8QaAyEsMhZrKlxC9qsZbxo5wMVL5Oir6NjObH4KluwqY1Dkr5LqJnbNYvmd3/Tv2ZiY/P59jvqT6cXyUYpM7Q2VkEj4C/iMiHzfkMyJyrYg4RcSZmZnZuAaeBiKCuOeiIqcHXaeUDeWYAu7ZTWRZeJLkjGZceiaPLVuCqw7BBYB5O3NZt7+Q6V271XscpRyo2AeMaYQlNyMV/0Cv+hC99CHk8LlIyR9BP4pU/B1xzTTivSZ1Uubx0C4q9BjVWIcDTal6f2/NTWZmJsd8SfXj2mPvNXU2WQGvAdtE5JmmPHfj4ga9BGXtEnqprRdS9Xb4BkabAL+u0zMxkVWFe44XV1/dtz/RDgf5xcXMys1mb1kpD4+fRHxEiFkyKhIVczuiHzWSWq73AQtE/woVeYHx//4dRkKr5HOIvf/snTMThEibjXJP6K4Ul8+HX9fDsiulqS0eDVwLbFZKfVv92j0iMrOJ7fiBUYA0sKXOlPIPxoK8nby96Vs6xMRwXlZXDlVUsLAgj0+2byM5Opp+SclMzurCmI7pNWYAh0QlgG+LoQrk/EXNxJWtL8rWF3HPMRJgcU+jtNYzTP6HYGRaRxYW5IWM4369q4BBKR3qD120YJo6m/wNrdITOEBrB/4dYAsRiPdtRlla3q1+S+CL7O18sWM794+bQOeENsdfv234SArLy3hy2VJ6JSYxMTN07KoW/q1G7WHsA/Vm8FXEFMT3HXgWQeQFp3sZrZIJGZ35z+aN5BQV0bVt3fO6K7xePt2xlV8ODj7SoqUSfu67BaKUqu44+SroOhEv4p4HEVOayLLw4VBlBe99t4mHJ0yq4QiPkRoTy8MTJrKoIJ+coqJTPr6456AippgqQqdJpM3G7cNH8fCSRaypnlF9IoVlZTyweAFDUlLp34Dxoy2R8Luxb6k4JoJ7DuL6AhU5o9bbIl6k/Cmw9Qta93a2Mjs3hwkZnYOKhMY6IpjRrTuzcrPp2nbkqZ0gsBciLw69ztrDKJQX3awBPYlhqWn8buRoXt+wjtc3rGdg+xT2lpWybv8+jrpc9GjXjoz4eLyBwKmFMFoI5m/7B0JpTiNz6foMvfgW9Kr/ovv3IIH9iOsLpOQ3oByo6P9rblNbJGv27WVceujwwdj0TFYV7j2NMyiMmv5QtMySkJbCgPYpPD91OjO6defT7VvJLipiWpduvDBtBtcPGMzyPbv5xRefsPHA/uY29ZQJP/fdQhHPCsT1CYgOKgCVb0D5s4jWFhznoKJvA2sPs56tHlw+PzGxCI1oAAAgAElEQVSO0G2JMXZ7nWrXoVDWLPBuhFAZf99GsGSau8Ig7Cot4b/fbeLB8RNrJVTOSc/gu0MHeWLZEu4eM45eYaRoY/7GfwCk6kOjXCbqClSbV9ES/oWWOAfVbiYq6nJDQUVLMh1hEBIiIzlYEbqX+GBlRchymjqJmIJ45iBSfyG3US/6JSri/FM//lnEW5u+5are/erNLPdJSubmwcN4bcO6JrbszDCd4Rki3g2IZz4q7lGUfWjNwU+WdijnDaiIyUjFU2Etc6QXXYNedE2jHX9cegZz83JDrpu7M5fxGaeejVfWLLD2QMqfqdMhigi43gW9FBznnPLxG8qPP3qfH3/0fqMdv7E5WFHBjiNHQnajjOrYiVK3+7SSXc2F6QzPEHF/gYq6KvhYz4iLjbIOf+gv+9nKhIzObD54MGisaefRIhYV5DdI0aYuVPStoGxIya8R1yfovl3ong3olf9BSm5HvN+aKkIh2H7kMP2T24dMkGhKMTQ1la1HDjWRZWeO6QzPANFLwJ8TUo9QKQ3lmASexU1jWBjitNu5c/Q5/HXFN3yRvb1GO5fH72d+Xi4Pfr2QW4cOJ9F5egXRStlR0b8D5+2IeyEUXwOlt0DVW0YoQznAt+OHuqRWiV90bJaGuQ2bZiGgNyRp1TJoUAJFKZUOdBWR+crQULfWJahw1qGXgtamYTsJS3skkN8aK85/MPokJfO7EaN5buVyHvvma+IjIoixOxCB3klJ3DNmHD3POCDvA/eHoCWgEl4Ca2+UUobUmnc1UvUW+LNRzmtDH+osJCU6hk+2bW1Qt9XO4qNM79q9iSw7c0I6Q6XUjcBNQBsgC0jDEF+d2LimhQEqAvSKhrXhSSXKFBCtF12EN75dz4L8nYxNz+Dafv05WFlJXnEx3x0+QEJEJFlt6u58OCUq3zRKnGLuQanvRwooZQPHaLD1NybmeTqiHOPP/HytjJ7tEtFF2HL4EH2Skutdt6e0lL1lpQztkNqE1p0ZDdkZ/goYhqE7iIjkKKXCJ1/emGhJoEUbrV623kGXimcJKiK4qs3ZzMvr1rC7tIR/Tr+IGIejxnsev5+nVnzDMyu+4c7RYxs0z7cuRK9AvEtQ8S/UcIQnorRoiLoeqfo32MeZFQAnoZTiit59eGHNSh6feF6dmf1Kr5fnVi3nkh69sNUzw6Yl0pCbf4+ckH5TSlkxK1OB6jY8xxSk6gNEAvWuE99mCBwAe3j2bDY2ecVHWVW4l3vHTqjlCAEcVit/GHUOe8vK+PZMinm934BtIEqLC77O1hfEC4Gdp3+uVsyEjM5MSM/kjrmzmZmz43h81+P3syBvJ7+fN5vubduFnfx/Q3aGXyul7gEilVKTgVuALxrXrDAi4jzwrUEqngPnzcbOohoRAd96pOLvqOjfGurLJrWYlZvN1C5diQoyAMpusTCjew9m5mQzKOU0JbYCR1CW0K2QSmmIJQ0CRaGLtM9SruzTj25t2/Hy+jU8uHghAdHRReic0Iaf9R/IjG7h12DQkG/nXcANwGbgZmAm8GpjGhVOKGWFmLuh8jWk+JeINcOIJUoA9H2AFRXze5StT3ObGhT9QP0iqaeyTmuffcrn/u7QIe4aPTbkupFpHXnj2/WnfPzjKJsxPrQhiNtYf4p0/tvTP8i6vF/fccrnbkr2lJbyj7WrSIuN49mp00iKcqJQrDuwj0+2b2N/RTk3Dhp62iGN5iCkMxQRHXil+mFSJzawZoJ3Dfh3gnICAnoJWPtUPzepD78eqHc+8onYLRb8Z1KqYeuPVPwdoq4O2m4nejEE8o1xrya1KHa5uH/xAq7p25+JJxVfd2nblgu6dufhJYt4a+MGrhswqJmsPHXqdYZKqc0EiQ2KSPDp3GcTVW8jvg2o2HtqqF2LeMGzCCl7CGLuQdkatvtqDkLt6I51n2ht3/nBz53kjCa/pJiUmJig6/KLi0l21q9qExJrd6OW0LvCyBzXh+tzlH3UaQm8htrRHes++e9lV57ysVsKX2RvZ0RaWi1HeAyn3c4954zn/776jIu69yQh8jTaJ5uBYAmUC4AZwOzqx9XVj5nAh41vWngg3vWIdyUq9uFasv9K2Q0NvehfIeVPIuJvJitbNpM7d2FWbujb61m5OUzqfPoxPKUUynkzUvky4l1b630RHXF9iniXQ1T4OqvGxBcIMD9vJxd0Cy5iHOtwMKpjeoNaLFsK9TrD6ol1u4DRInKniGyuftwFmOqk1Yh7Firy8hqJk5NR9qFgaQ/e1U1oWfgwqmMnDldWMjs3p941y/fsZtPBA0zM7HxG51K27qiYu5CKl9GP3oBe9hR65Wvole8hJbcg3lWo2EdQWm2BWRM46nJhs1hIjYkNuXZA+/bkFx9tAqt+GBqSQHEqpcZUS/ajlBoFmEEwMKap+b6DBsxBVo5zEe8ylCN4697ZiN1i4b5xE3hg0QJ2FhdxQdcepMcbvd77ysuYmZPN0t0F3F9P6c2pIOI1Yrt4jESX71vwlhmJlYip1WNDzd7k+hCkwV1UCtViR4bWRUOc4Q3A60qpY8VZJcD1jWdSGKFXgYpq2JdHawt6ZePbFKakxsTy9HnnMzM3m9/Pm8XhqkoqvF50XegUF8fVfQfQoQG7kWCIeIyBT1o8Ku4JlOV7eXoJHECq3kHKHqyek3JmTre10iYyCpffz8GKiqCq5ABbDx+iU1wQAZMWRsiiaxFZJyL9gX5AfxEZICJnUN/QitCiQCqDauQdRz8K5sS1oMQ4HBS7XMTYHfx8wCDeuOhSZl/zUx4Ydy45R49wy8wvyC8pPv0TVL1j9JJH31HDEQIoS3tDxEFLNNaZ1IndYmFCRmbIGK/L52NRQR5TTlNhqDloSG/y/Sc9B0BE/txINoUNSkUitt7gWQYRE4KuFc9ClDkIKihvfLuevWWlvDBtRo0C7CRnDANTOrBkVwEPLV7IU+edT7uoqFM6togL8XyNinu2/ul4SoOonyKlv4Won2BokpiczIXde/D7ubPp2S6R4Wkda73v8ft5cvlSRndMP22FoeagIe14lSc8AsD5QEYj2hRWqIjzEdeHiF6/SrN410NgH9iHN6Fl4UVRVRXz83Zy95hx9XaijE3PYEyndL7I3n7qJ/CuA2s3lCW42IOytDWGQnnDS6W5KUlyRnPf2An8ffVK7l80n0X5Oylzuylxu5iZk81v58zEabNz0+ChzW3qKdGQousapfJKqaeAzxvNonDDNhhl32TEmqJ/hbJ+r8Is4gPPUqTqTVTMXYYySpjSGPWFJzI/L5cxndJDJkimd+3OH+bP5uq+/RtUqH0cvQyltWvQUqW1M+TZGoFwri88Rk5REZ/u2Io34Oe7w4eYl5eLy++nbWQU49IzuHnIMPolJbfKdryTiQLOrL6hFaGUQqJ+jnJ/hZT9BbEkGskS31ZD2VpFGjLyZoYyKPklxYzulB5yXUpMDJFWK0VVVSGLtGugRSH+sgZlQkVKUSp8Yl1NydLdBbyybi1X9O7DLUOG47Qb/653l5bw6fZtbD1yiNSY2LBzhNCA22Sl1Gal1KbqxxZgB/C3xjctfFBKoSIvgPgXAQu4F4OWArH3oeKfQVl7IOWPo5c9joi7uc1tFcipCifZBoJ3E6IH1yQWvQJ8m8AePm1kTUVBSTEvr1vDQxMmMqNbj+OOEKBTXDy/Hj6SiZlZPPbN12E576chMcNjnSgzgPOADiLy90a1KkxRVa+AsqHafYAW/xe0iMkoW29U1OWo+JdARSLlT2C0e5ucSHp8AlsOhZ6XcbCigiqfn3ZRpxaYV1oc2IeC64PgC10fgm1IaJmvs5Avs3cwo1sPMuMT6l1zec/euP1+thwOn9knx2iIM3zkWDeKiBSKiF8p9XajWxZmiD8X8W1ExfyxziykUlZjIJFeUV30a3Iikzt3YcmuAiq8wcuUZuZmMyEj89TihdUo58+N9snKt4yC+RMQcRmve9egnNed8rFbO75AgKW7C5gcoh1SKcXULl2Znxd+WpANcYY1JJyrxV0HN445YYx7NsoxNai0v1IWVOR0xDOrCQ0LD9pFRTEhM5PHly2pMQzqRJbt2cXigrzTEg2VwAFwfQriRSpfRw5NQC++Gb3iZaTiBaT4ZkQ/iIr7i7krrINyrweHxdog0YVOsXEcrgq/BoN6naFS6m6lVDnQTylVVv0oBw4CnzWZhWGC+HaAfUjohbah5gS2erh+wGCSopzcPvsrPtuxjcOVlZR53CzI38n1n33MA4sXMCilA+VezykdV9xzkNI7AR0V+ydUu0+N+K5ygusjRHyouGfRYv4QfOTrWYzdYsUT8Deovc7l95/Wzr25qTebLCKPAY8ppR4Tkbub0KYwJQANUbJWNmOtSS0smsZtw0aw7chhZuZk878tm8kvKcav64zpmM6UrKG4Az4eWbqYdlFR3D58VEjBAPEsQ1wfoeKerNF1ohyDwTEY8ecbLXqBvRCiBvFsxmmzkRoTy4YD+xicEnzI0/I9uxnQPqWJLPvhCKZn2ENEtgMfKKVqpdbMlryTsKQYwq6WENPA/LnGWpM6UUrRKzGJtNhY7pw/h1uGDOdHvfvW2Glc03cAc3bmcs+CuTw28bx6e5ZFdKTqP6jo22u13x0/nzUTnDcirvdQ9v6Nck2tAaUU07p246OtWxjYvkO9CtaF5WWs3VfIjYMacJfUwggWM/xd9X+fruPxVCPbFXYoxyTEPStkSYG4Z6Eck5vIqvDl7U3fMiQllWv6Dah1y2XRNKZ17calPXvzz7VBZNF8mw1lGmuv4CezD4fAYcRfcOaGt2JGd0zHp+v8dfkS3HXEdfeUlvLg4gX8tP/AM1YXag6C3SbfVP2/58tJxXHKHABcG/swcL0Prk8g6tI6l4hnMfi2gfPmprUtzKjwelm2ezf/mD4j6Lrzuxg7lcLysrpvlwMFKFufkAXASlmMHvNAAVgzTt/wVsru0hK+yN7B0l0FWDWN5Xt289G2rYxLz+S8rC4gsKpwL9uOHOa6/gOZnBWeQ7Qa0oGyHDj5Nrmu185qlLJAzH1I2YNIYCcq4gKwGhPCdO93UPkv8G0Eay+k4lmjK8U+ytTOq4PvDh2ke7t2dc7kPRG7xcKItI6s3VdIavczk/cyqZuVe/fw4pqVXNC1O/+YPoM2kVHoIizOz+Pl9Wt4buVyxqdnMiw1lT+MGoPDGr4TIIPFDNsDqRgjQgfC8U6mWIyWPJOTUJa2EPcEeBYgFS+AXoRIOQQOgW0QxP4FZU2BwEHEMw8q34HYu2qNCzjbcfl9OG0N+yMRbbfj9tczTsGSgXi+BpGgu0ORAPi2QOTFp2NuqyW/pJgX16zkgXHn0qXN98klTSnO7ZzF+MzOvLhmJRVeL+eFkVRXfQRz41OA64A04JkTXi8H7mlEm8IapUVB5AyIuADxLIHKf0Obf6DZTui7tXZBOUYjnpVI2V8g9mGUNa35jG5htImI5EBF8La5YxyoqGBA+7qTI8YweBf4t4EtSNzQuxosiTVENkzgs+3buKRHrxqO8EQ0pfjl4GHc8Pkn7CktpWNceNdnBpuB8qaITACuE5EJJzwuFJGPm9DGMEXA9V9U7J01HeEJKMcIVOSFiOv9JratZdMnKZkil4u8EPMzStwuvj2wn5FpdQ+GV0pDRV2NVDxvFF3XgfgLkMqXUZFXnbHdrQmXz8eqwj1MqmcC3jFsFguTs7owL4wGP9VHQyS8PlJKTcfoRIk44fWzXtw1KL71oGJQwXYkAI7J4Po/RC8xC36rsWgaM7p159X1a3lw/MQ6C3h1EV7fsD6k7JdyjAGpMIquHRPBMQG0eNAPg3sh4l2Kct5kltWcxFG3izhHBLGO0LnSzgkJLNlV0PhGNTINUa35J3AlcBtG3PAKILTW0tmOPwdlD921qLRosHYBf14TGBU+XNyjFwmRkdy/aD7bjhyuUbJUUFLM4998zZGqSm4Y2ICfccRUVNwTAEj5o0jJrUj5M6BFo+KeMRymSQ2sSsMTaFhzgDcQwKo1pLO3ZdOQ1M8oEemnlNokIg8ppZ4GzNvkUEjAGFjeIKyYXSk10ZTijpFjmJmzg+dXLkdTikSnkxK3mzKPh6lZXbikZ+8Gt30pSwo4f4Zy/qyRLW8dJDqdaEqx82gRWfXEDI+xunAvfRKTm8iyxqMhzvCYvEeVUqoDUASYkeZQWDoYw+VDLBPxG7tCS4cmMSuc0JTigm49mNa1OzuPHqXM6ybKZqdrm7atYifSkvHrOpM7Z/HJ9m3cMXJ0vdn4feVlbDxwgNuGjWxiC394GuIMv1RKxQN/BdYDArzSqFa1BhyjoOoNJHAQZQnyV9O7CiwpqFBtfGcxmlJ0bWv2DTc2hysrmZWbzfy8nVR4vfj1AKUeD1U+L3ePGYftpF34wYoK/vz1Iq7p17/euTXhhDoVRVplDJONAHqIyKpGsyoIQ4YMkbVr1zbHqU8ZqfoA8a1HxdxnlNychO7LgdLfgdYOUKAiUPYhxjBzc6fYcLKz4aWXYNEi8HggIwNuuAEuughawZe0Kdh48ABPLV/KuPRMzu/SjdTYWHyBAAvyd/LEsqUIwq1DR9ClTVs8fj/L9+5mTWEhV/ftz/Ru3Zvb/AYzZMgQ1q5dW+c295Sc4fEPKbVbROquZ2hkwsoZig6VryC+TajIC8Ex1hgvqh9FKt+EqnfBPhoVfSNo7UEqwbME8cxHRVyIqqetz6QaEbj7bg4+8QSvYwSyqzAGfP8SGNe9O3z1FWQFLw852yksK+OPC+bwx9Fj6ZtU+y7GFwhw76L57C4toUubttg0jb5J7ZnYOYvYMOtBDuYMEZFTfgB7Tudz1Z+dijFHJRe4q/q13sAK4E1AC/b5wYMHSzih67rong0SKH1UAkcul8CRH0ng8CUSOHSuBFxz6v6M/4gEjt4qumtWE1sbZtx/v6wCaWOEbmo9bgGRjAyRQ4ea29IWzQurV8q7mzcGXeP2+eTqj/8n+8rKmsiqxqHaf9TpW063kfC0pr0opSzAi8BkYC+wRin1OYZCzoXAVRhzVmafpl0tDqUU2Aeg7AOqZ594kfLnDQGBiPPq/oylLcT8ASl7ABznmv3LdXHoEMV//jMzgPpKs/8B9C8o4KYXXoCHHqr1/q6te/j6fyvYviYXn9tLQvt4RkwfzPALBuOMPTs6Tj1+P8t27+KFaRcEXeewWpmUmcW8vFx+2n9gE1nXtATrTf6Cup2eAk43mj0MyBWRvOpzvAdcBFiqz6VDg6Y5hiVKaYheBf4tEPPr4GutnRBLOnhXgmNsE1kYRrz+Oh8BocYOPQ/c9MorcO+9x+OHuq7zwVNfsHnpVsZdMYppN00iIsrB/ryDfPPxKua+9TU3P/VTMvs0SySoSSlyVRFtt9MmMrTz79a2HV/vym8Cq5qHYDvDYJqFp6tnmArsOeH5XmA4xr/Zr4Ac4J+neezwwL8bLJ3rHBp1MsrWD/wFpjOsizVrmNOAZVsBrFYoLDQSK8CX/5zH3h2F/Om/vyEy+vvfQ9dBnek6qDObl27jn3e8ye9fu4XEtNadxbYojUAD8wYBXa9X1LU1EEzP8OtGOF9dP0kRkQ0YTrHuDxnT+C4FaNOmTSOY1UJRnGZAouVTtL+Y8qMVOCLtJGckop1q3WAg0PAydYsFqrspKkoqWfLhCu7/8I4ajvBE+p7Tk3MuHcH8t5fw47svOTW7woADFeXkHj2KiJASE0NA19lVUkJ6fPB20LX7C+netl0TWdk45Ofno5Q6cVrVxyJyLTSszvCHZC/Q8YTnacC+UB+qNvZaMLLJjWNaE2HpCIE8RNxBJ+kBiG+LMUDKs9gYMaqcYB+M0sJXu2/9gs0sencph/YWkZAcR2VpFZqmcc5lIxj3o5HY7A0shenZk1GffcYnIZalAZSVQQejVGnFF2vpP643sW1ign5uzKXDeOTKZ7nk9mlERIVXxrQ+coqK+M/mb8ktPkrvxCQ0pdhRdIRyr4eX1q7i8UlT6v3skaoq1hQWcsPA8JPzP5HMzEyKiorqHLrd1M5wDdBVKZUJFGIkTH7SxDY0K8rSFrH2AM/XEFH/Pz7dn2c4Qd92xNbP+JxeDFWvI7YhKOf1KC34F7olISJ8+vdZbF66lRn/N4V+43phsVgQEfI372bmK/PZsmw7//fcz7E7GuAQf/ELfvb449zP9y1SdXEzwNVXQ/WIy8Kc/XQfGlo/Mj4xjvikWI4UHiWtawqVZVW4Ktw4YyPr3VG2ZDYePMBfly/lp/0GcPeYccdFWAO6zuJd+dw1fw5/WbqYP50zvtZni10uHl6yiEt69gq7UppToUmdoRgD6G8F5mAkTV4XkS1NaUNLQEX9CCl7BCwZKFvtglU9cACO3gC2Pqi4h4+r2ShA9HJw/Q8puxdiHwkbh7h61ga+W7adO167pUamVilF537p3PL8z3njvvf44KnPufpPl4U+YFYWidddx9tvvMGPgbomLZ8H3JuUBL/5zWnZrOvCtpXZfPTMF+zaupfImAhc5W6y+mcw/qrR9B4VHsXGVT4fTy1fWmcdoUXTmJiZxWsXXsIvPv+UvaWlXNarNxnxCbj9flbu3cOigjwu6NaDy3v2rucMrYOQzlApNQ+4QkRKqp8nAO+JSP3bmiCIyExg5ul8trWgrF0g+tdI+aNgHwERk6uLrivAsxQqXwVrV4h7HnVSLE1pMeC8ASpfRypfQ8Wc3he9KRER5r+zhCvumFFvyYqmaVz5x4t54OInufCWKUTHFENgHyjNEMPVEmp/6J//5LKSElZ9+inPUbvo+uakJPj4Y+jc+fhHOnZPJXvtTkbOCH67V3yohNx1eYguTL9pMr/62/VYbVa8Hh/r523ig6c+I2dCXy66dWrIGSvNzaL8PPokJddZUH2Mfskp3DpsBDlHi1izr5Avc3Zg0yz0TUrm2SnTSHJGN6HFzUNDdobtjjlCABEpVkolNaJNZwXKPgjinwP3fKT8WdBLjElu9gGgxaDiHqvlCGsQ+SMoCQ8dxL3Z+/C6vHQbErwTxBkbxblXRFNWcDvOdAXWzkAA/DlGqCDyqpqK4A4HfPQRA7/6ijdffJE3Fy8Gnw86dTLa8X7xCzhJBXvEBYO4/+L5lBWVo8U4WLKrgP0V5Vg1Rc92SQzpkIqmFK/c+Q7RCdH88a3basQM7Q4bIy4YTN+xPXnu5n/RLq0NYy6pN/fXIliyu4Are/cNuW5KVlfm5eXy9iVXNIFVLY+GOENdKdVJRHYDKKXSabU5zqZFaQkQdQUq6vt/fOJZYTi4EAPNlRaN2AaCd42xs2zBFB8sJTk9dMZY3HMZMmY5O7aMpcOA24whW2DUZnrmIWX3Qeyfas6M0TSYMcN4AOi68Vo9OOOcjL1iJL964nW8Q5IYkpZGVkIbfLrO/7Zs5uV1axgrCaz8ch1/+fKuepMnztgofnLPpbxx//uMumjoqWfDG4ldJSUUlBQDkBGfQHp8PKUeN4lRdeYMapDodFLm8SAhZsa0VhriDP8EfKOUOlZqMxa4Kch6kzNBKuu+JawDpSUYKs7+PHAvQPTDoGwoa29wjK9THKI5sEfYcFd6gq4RfwFS9V++XfsjvN62xx0hHJsrcxFYUpCyxyHhH/V35YRwSroIOQOcBDxO0t7Np++FyQyalESEM4IBVZF8+NlSXvBtY/Blfeg5InhMMKNPJxxRdnI35NNtcPP2P288eIB3N2/kUGUlvRITAXhj4waSnU68/gClHjcdCT6jpNTtJtJqOysdITRM9n+2UmoQMAIjhv9bETnS6JadrSgnohc1qA1HAgfAswzcM1GOyYZ0vbgR7ypwvQdR16KaYddYWVrJqpkbOLT7CBaLRmq3DuzbuZ/iQ6UkJNXzhXTPAsc0ln9ZwE8fqFsbT9mHIdaZZ9SVs3LvHvaUlfHv267j4PkHWfLBCv72q1fxef0kJMUxZsYQUouT+I9rF1U+X1BpKqUUaV07cKTwaLM6w2927+LldWu4afBQRqZ1xFL9B8Gv66zYu5tHlizmrY0beHLy1KDHWVSQx4i0jkHXtGaCteP1EJHt1Y4Qvq8H7FR927y+8c07C7EPgMqXkMARlKX+Alc9cATcnxsOz3lzzZ2UYywSKETKHjaeN5FDDAQCfPb32Sz/fA19xvQgo3dH/L4Aq2eu50hhMf/+0zv89oXB4M8BBCwp4BgDRCCeJWzedCv2iEIy+9bfBqcckxHPQtRpOsOZudlc3rM3DquVTj1Suea+y2ut0d9bRmr5fhbl5x2Xp9JFcPv9WDWthrq2z+PDamu+WcFHqqp4ae1qHp4wkc4JNRsSrJrGOZ0yeHLSFH722Udcc3A//ZJT6jxOidvFF9k7uHvM2dvtFOy3+DuM2+Gn63hPgHMbxaKzHKUiwTEeqXoHom+v/5al/BHQOqGc/1fnGmVJhZh7kbJ7wDGmQe1/Z4Ku67z1wP+oKKnkgY9+T0zC99nHSdeMZfem9zmc/SxbFi2k55gr0SxWxLsOqt4GxyQqyyr4z6ML+L9nrwt+m2ZJBr30tGz0+P1sP3yIB8ZOCLqu66BMLF8uYfXgPQxISWFWTjYL8/MIiI4voNOtbVumde3OkHbJbF+dw0W3nX9a9pwKe0pL2Vv2/+3dd3hUxfrA8e+7m94ICS0hlNBraKFXpYsCIihyRcWLKHrtvfwU67V3Ab0q4NVrQwQB6VVpEnpvoYUWkpBeNzu/P85JSEjZAMmmMJ/n2Yfds3POzsmGN3PmzLyTgNVioVH1AGp4GV0gS48cok+DBgUCYV7t6gQxsFFjnlq2hHcHDqFtrdr5fsbH4i/w3vq/GNioMc0q+QyTq1HcdLycfsGhSqn0vO+Jo6kT2tXxGgeJU1DJn4DXHflupih7PCr1R8iMgGqfFhs4xCUE5doGMtag3PtD5iZU+mLIPmEUsDZCPAaDW5d8LcsrsevPfZyOPMdTMx4sMGhapa8gpN5ylLzJ04wYJ1IAACAASURBVEN+pGHrA/Qa1ZUadQdgS2+Dr/uXNGgSxeT333WcHMGeCFcY2NNtNtxdXApkbL5USLNgavr7svtIFM/EX2BQoyZ8NMQYXmKz2/n7VBS/7d/LrEV/UsvLje9fm01aSjrefl50GtSO8EHtcPMonUxD286c5qc9uziXkkzj6oHYlZ0DsTG0rlmLcW3bsfbEMZ7q7nhBq/s6deGFlcuYGrEJN6uVjnWCsYiwP+Y8Z5KTGNOqDUObNCuVOldWJWnfrwc6lmCbVkpEPMBvCqR+h0p4DOXSDLEEouzxYNsLLmFgbYy4tXd8LLeuqIy/IH25kUnbY5i5oLqCrF2o9HnG5bbvC8ZKfSalFGQfB3sMiBu4NC20dalUGmSswZL6Fff9nycuaS+gsruCR3/E4m8G75lItbdo0LYuw+6Nwd3LDVumjQObD+Ph7UG7vq9RrcYTVPNaC7Qo9nxUxlrErctl/kQN3m5uZNntJGakO1wCs+7w1izYGsG7jdowNE/KKheLhR716hP16w7eX7+b0PZ1GTeoN74BPsScvcCvyzby1uLltBsYRuPQIPo1DKWhf+E3xM4lJ7M3Jhpbtp1aPj60rVU7XyKEFZFH+G7Xdv7ZIZxuIfVy131Jy8pi+dEj/N+q5SRlZFCjBHeKa3h54WKxMvWG4ew6d5ZDcbHYleKmZi3oXDdErylD8X2GdTCyzHiKSAcuJlnwAyrGbcoqTMQDvCeC1z8gcyuoRER8wOchUImoxNdKdNdPYYWMPxHv8eA5Lv8+7r3BrSekzjAGgPu9bqQZy1iLSptnZN621gWVBtlR4NYbvG5FLMZNEJW1B5X0LsragqU/BfDwtGcRlzTIWI2Kf8gYHJ4di7h1zV3jpdOgdiybtZpHv7gvXz3tyaMh7ReU1x1F3gVXtuPGetTeE6/oZ+pisdAjpD7LI48wysFsisUxJxnRvCV/vr+UAz9toeuNnfAL9OXCuXgWz1jJ/o2HePer+/jCdoJaHepxLiWZaUeOENC/PkMzm7Luf+upeZc3rxxfST2/ajzevSf+HsYfk5MJCczcsZX9MTG0r1MHN6uVhYcPkJqZxaiWrRncuAknE40yb/UfTF2//HPRPV1dualZC4J9fblvwTyiU5Kp5lF8cE9Iz8Db1RWLCO3qBNGuTuF9h9ey4lqGg4G7Mea6v8/FYJgIPF+21dJyGH2IPfNtU8oK9kSUPcnxdLyMVSC+BQNh7vEtKK8JkPA0ZG1F2Q6gMjYi3hPAtT0iRotBZcdA2m+ohOeg2utgv4BKegfxeZyMrOZERb6Bq6c508O1NdhuQiW+anxGntyNXn6eZKRnFqyn152Q+gMq8RXwfTzfIlpKKbDtRSV9YCz4brny2RA3NmvOa2tX0T2kPkG+hf/sFh06wNnkJJ4adSu+Nw1lx+o9bFuxi9SkNLz8PMlMy+LFnx6n/XVtOLjVyqyd29h17iyPd+tJhyAjIUTbTC+2z9/Nfz6ewA+7d/LCyuW81X8Q51NTmLJ6JWNat+HpHr1z5wgrpTgYF8vnmzdyNjmJjGxb7lokRekUVJemAYF8s20L/y4myQIYd4p71Kv6+RmvRnF9hrOAWSJyi1LqVyfWSXNAxBPl1gUyVoDnyCLLKZUN6cvA57Hi+xbFAh5DjXVZsCPV3ioQZMVaA3zuhdRfjAXYxQPxGoe4tcPdxY6IEH8+Af+aRqtRXOqD76OoC5NReOX+JY0+EUO1GgX/g4t4oiw1wbUDKuEplEtzc3B1tnGjRaUiPvdd8SVyjiYBgdzeph3Pr1zGPe070i2kXm4fYkJ6OgsPHWDegX20q10Hf7O11XFAGB0HhAFwdNdxTu4/RVjfVgA0rh7AD3+u5p2Bg3MDIUDXYR2ZP20JcafiGB/Wngtpaczet5sNJ08yqVNnetVvcMn5C80Da/DGdQN5avliTiUm8s1wx2vgjA9rz2trV3MuOZnaPoX/kTibnMTyo0d4d0DxQ2uudSXpKOhkLhUKGHOTReT1MqyTVgLieSMqba5x6VgIpRSkzgQU4jHA8QFd20DWTiPAFdfa9Bxl3IDJ2gHu/QBjXnGXoR1Y99vf+cu6tDamGGZuzN3015xNdB1WSHezPQYsnli8xyLV/4O49QBsgAXx+gfi//lVB8IcQ5o05eEu3Vh85BAT5//GS6uW8/yKpUxe+Dsxqak827MPbi6FtxOO7jpBq+7Nc2ecHIqLxcVioWOd/KsZurq50iy8Ccd2G7mMR7dqzdz9+/B1dysQCPPydXdndMvWnE1Ozr1jXJyWNWsR7OvLi6uWsS/mfM46Q4DxO7DvfDT/t2o549qEFdkS1gwluYEyVCmVe1lszk2+AXix7KqlOSIujcF7IipxijE7w70/YvE1LykPoNLmgP0CWEMcHgtAZceBSge34ufZiliNFGRZezFWjjX0vbUHH93/BR0HhBHUqLZZVlBu3SBjKXjfwaaFW0iMTcptVeWTsQxx62Pu5w4exQ9/uVodgoLpEBTMqaREziYn4SLGkBVfd3eysrNJzcwiKjGBEL/8g8SzbXasLhfvRq85fpQuwXULbXlbXSzYs+0ABPv6kWHLpmUNx9P6e9dvSIbNxrnkZOo4CGCJGRk0DgjgxqYt+HDDOrzd3HITMuyMPktaVhZ3hnWgd4OGDj/3WleSYGgVEXelVAaAGLcUq25Ss0pE3HuBNRiVNh9S70dZfEFlgHghHkPAY6CRKixrl7GofXGyIsBSHZES/EpY/IFMUhJT2fB7BOt/30zsqThSk9J48vopDH9gMCP+NQQPLw9waUp2WgTrf/6EP2Ym8dBnE7FeMrRF2U6g0pcifq9d+Q/jCtX19aOub/7LdlerlYGNmzDvwH4e7Jz/j0OtBjXYuXYvAGeSkjiVmMgthdyMUUpxbM9J+oy+OJtGofBxczzkxt3FhUAvL5YfPcIdYcWPGFhz7ChdgkPo06Ahveo3YPvZM7lzk+8K60C7OkFVOlV/aSpJMPwOWCEiMzAGW9+DsaSnVgGISyPE9xFjiIs9AXA1g5rZA+IxBJW+ENy6F9lvqJQdMteBpXoJJ+l7kpUew5t3vk/Tjk35xwu3ENIsiKwMG0tmrmL+tCX8PnUJ7a9vw4ARKziwrQZ9blrC89+MxbvWxWEgSmVC5npUyizEewLiUnGmgo1o3oInly5m3oF9DG/WIvdn0qZnC356ey47dkcy/fhuejVoyLmU5AL7H9h8GBdXa+5smmy7nXSbjZLEpazsbLzd3Fhx9AgjmrfEt4iEqicS4tkYdZKpw4wkFRYROgYF0zEouNDyWvFKtIi8iAwF+mPcUV6qlCrJWjxlojItIl8RKJWFSngBcW1jTN275H+jsdD9l6jsU5Adg/g+grgWP9Yv/eyjRG7fjqv/JJp2K5ioPCszi6mPzsTHL47bJm/HGvglHp5JqNSfIWsLWENBrMZiV9YGiNdoo34VTHRKMq+vXY2LxcLgJk2pX82fDJuN7/74kw2nTvLwjddzffNmPLp4IV/ddDOe5jzmC9EJfHDvNEb+ayidBrYDjDnR0yP+JtjXlzf7F75EbI4/jx9j8ZFDNK4ewK7oczzZo1e+1qtSir3no3lvwzrubNee6xo2KuZoWl7FLSJfomBYkehgePmUPQGV+CYA4jkUXNpgDLreiUr/w7is9n0WMlagsrYjvi9ebFleeqzMLZze9ToH9vSj3407jUzc1oItkczU8+xZOo7Q8HvwD7k9X12wHQOywRqMWOsU2LcisSvFtrOnWR55hJjUVFwtFsJq18G++gT7lu1mwD/6sKF2Jl4e7tzVtDWz31vAmp/XUbthLRq3a0hY31Y06duCl/5cyT/C2vHNtq38q0tXOgXVLfTz0rKyeGb5Esa2CaN7SD3m7t/HnP17aFQ9gBY1amKz29l65jTJmRlMaN9JD5e5TFcVDEWkG/Ap0BJww0jXn6KUKpdViXQwvDJKZUNmBCpjCdiOA0byVPEYDK4djPGGKhOV+AZYqhUYz6eUgsyN2JOn8ekzAYx7+UVq1tyBSv2vkQjCfQBYaoJKNKb/pS9gx/qaHD3cg1GPFL9AeWV1aGska35ez7Z1e9nZ3ovMmBSanFWMvrkPLbs15UJcEnNWb2a9JZ5bunbk8RED2Xc+mjf+WsM97TvRt0HD3AwzAFGJCXzy9wYaVKvOA+FdclvxmdnZbDh5glNJiVhEaBoYSAdzOp12eYoLhiXpM/wMY+GmX4Bw4E7A8Yo6WoUiYgX3roh70XeLRdzA7wVI+QoVPxncuhh3o1U6KmM9iIVk28OcO7WYWvVqAP3BpRlkLEElPGWu4OcBbl0Rnydw8VOcObLBeSfpZDnrLJ89Hs07904j6J7eHPTOYBGZrL1wiOjUFEIHN+Zpqz/r31jEgeBQWnZuwst9rufrbRH8d+c2woNDcLdaORp/gZMJCYxs0ZKRLVrl685ws1rp2zC0HM/02lCi3ENKqcMiYlVKZQMzRGR9GddLKycibuDzANjHQcZfuXOTxWcyuLRExSRity+6WN6lHrhMRLwnopQ93+W1UnsRS9VvvSz8YjmDx/Vh8NjrsCvFqcRE0m02qnt65o4VbCTe/PL+77zww2M0DQzkrQGDORp/gb3R0WTZs2lV01hywM1BEgmt7JQkGKaKkVZ4u4i8A5wBHM8M1yo1sfiDZ8HLW79AX6xWC6cOn6Fuk/zzWy/tZ9y38RD1WhTeN1ZVJMYlsW/jQcY9byw2bxGhXrWCCWzb9GrBnI8XcnjbUZp2NG54hPpXJ7SIJA6a85VkBsp4jH7CfwEpGIvAl2AtR60qslgs9BzZhVU/rCu2XEpiKhFLttHr5tKZNVIST1z3Mk9c97LTPg+MGSmhbes7XEtZRAjr04oj2485p2LaZXMYDJVSx5VSaUqpRKXUK0qpx5VSh51ROa1i6ntrDw5EHGbt7ML7A9NS0vnyyW/pOqwT1WtX7JX7rla2zV6yRe8BV3dXbFnZZVwj7UoVl8JrF8WsgqeUCiuTGmkVno+/Nw99NpGPJ3/J6p/W03FAW9r0bombuys7Vu/hzzmbCOvdklGPDivvqpa5GnUDOHnwNHa73eEKeVEHTtGhv+MlO7XyUVyfYdUcD6Fdtcidx1kyYxXpqRmobMWcjxYy48Uf8a/lR7cbO/HAh3cT0uzamAVRr3kwnj4e7Nt4iNY9il5NL/bMBY7sOMaEN24vsoxWvopL4VV4OhTtmrZ1+U5+enceIx4Ywj//PS43vX3ShWTW/rKBtb9udHCEqkVEGHz3dfz0zlwe/8/9uSnM8spIy+Dbl3+i7609cffU0/orKod9hiLSTUQ2i0iyiGSKSLaIJDqjclrFEn3iPD++PZeHPv0nPUZ0zrfOh291H4ZNGshtT41g2uMzycrMKseaOlfHAWH0HtWNdyd8zppfNpCWYiwZZMuyEbF0B+/9cxo16gZyw739y7mmWnH0oGutxNbO3kjPkV2KvQTuOCCMv377m20rdtNlaIciy1U1A+/sS2jb+vzx1Qq+fv570pLSsWXa8A3wocfIztz0wCCHfYpa+SrRt2PePbYqpbKVUjOAsk02p1VImxZuoWcJhsr0urkLmxZucUKNKpbokzGc3B/FDRP7M2XOk0zb+g6vznsGvwBf3hj7IdtW7irvKmrF0IOutRKxZdlIS04nMMjxIOFa9WuQGJtU6nUYaBlTKuWW2X8pjerks23lLhZ8sYynZjxIrfo1873XsHU9et/Slc8e/gYvX0+ad9YXVhVRSQddW9CDrq9pVhcrYrGQkVbIYk6XSE1Kw82zdNYNrgyUUvw+dQl3vXJbgUCYo17zutz21AjmT1vq5NppJeWwZZjnrnI68ErZVkerqESE1j2as2XpDnqOLP5SOWLJDtr0LD4n4pVw1KLLmX3y/irn/poe3BKJ1cVCs07F5xVsd11rZn+4gKhDZwhpqpfqrGiKbBmKyAgReTDP600iEmk+RjunelpF0mdMd1Z8v5b01Iwiy8ScimXbip0OA2ZVcurgaZqHN3GYIdxqtdKsYyNOHTztpJppl6O4y+Sngd/zvHYHOgP9gMllWCetgmrZtSmNwhoy7dEZJMQUHF0VdfA0Hz/wH26aPBi/wGtnJTaloET5/AHELK9VOMVdJrsppU7mef2XUioWiBURfQPlGiQijHthFAumL+O1Wz+gZdem+NepRtT+05zYf4rk+BRuf25UvkWQrgXBTeqw6Y8tDtePsdvtHN52lOvH9XZi7bSSKi4Y5rttqJT6V56XhfcSa1WexWJh+AODadevFVMfncm5E+ep2ySI0Db1cfd0Y8H0pZw9Gs2oR4eVOIFBZde8c2MyUjM5suMYTdoXnYR119p9+AX6Ur+KpzWrrIoLhptE5F6l1H/ybhSR+4C/i9hHuwacOXqOqY/N5IaJ/el5cxdcXC/+GiXGJfHLe/OZ+sgMHvxkAq5uVT8gWiwWbpo8mFkv/8Qj0yZRIzigQJkzkef48e3fGP9SyYYHac5XXDB8DJgrIuOArea2Thh9hyPLumJaxaSU4tspPzN88uBCb5L4Bfgy4fWxTH98Fiu+/4shE66N8fnhg9pxNvIcLw1/mza9W3Dd2J7UbxlCfHQCG36PYNMfWxnzxHBadS86mYNWvopL1BAN9BCR64GcVbIXKqVWOqVmWoV0fG8UyfEpdB8eXmQZi8XCjfcP4osnZzHorr5VfhrasT0nWfjlMo7tOUloWH0ObYlkxXd/4uruQt2mQfQZ3Z1nvn2o0BajVnGUZJzhSkAHQA2A7at202VIB4cBrn6Lunh4e3By/ykatHLO4vDOHl8IsGf9Ab6d8hPDHxjCve+Mz+0nzczIYvOibfw+dTGN2zfUgbASqNp/srVSl56SgW+Aj+OCGJls0pLTy7hG5ScxLomZL/3Ife/dRc+RXfLdMHJzd6XnyC7c//5dzHr5JxLjSn96ola6dDDULouPvzdxZ+IdllNKEXf2Aj7+VXcU1vq5m2nfrw2NwhoUWSa0bQPa92vD+rmbnVgz7UroYKhdlk6Dwti0aCu2LFux5Q5tjcTFzegzq6o2L9lOj5GdHZbreXMX/l68zQk10q6GDobaZQkKrU1I0yCWzlxdZJnMjCzmfb6Y627r6XCKWmWWGJtEYLDjLD6BwdVJikt2Qo20q6GDoXbZ7pxyK5v+2MrsD+YX6Avbu+kgzw56jVOHznBoayTLvl1D0oWqGQg8vN1JSUh1WC4lIRUPL53uv6JzWjAUkX+IyE7zsV5E2uV5b6yIbBWRR51VH+3KVavhxxNfTyYjNZNXR7/P5w9/w1fPfc+DXZ7lxWH/xr+WH7c9czOte7bg7LFopox6l3mfL8Zut5d31UtVWO9WbF603WG5v//YRlifVk6okXZVlFJOeQA9gOrm86HApjzvzcVYqP5HwKe443Tq1ElpFUdyQoravmq3eufuz9RLI95WCbGJBcokxCaq9+75XP349txyqGHZOXP0nHp64Csq7lx8kWXizsWrpwe9qk5HnnVizbSimPGj0NjitJahUmq9UuqC+XIjEJLn7ZyOJZXnuVYJePt54RfoQ2JsEs9+/zB+AQWz1fgF+PLAxxPYsWYPx/dFlUMtS0/UwdP87805PDPoVd4c9xEXziXw9MBX2fnn3gJlTx0+wycP/If+43oTFFq7HGqrXY6SpP0vC/8EFuV5PQeIAL5TSukBWZXMml820GdMdzy9PYos4+njSZ/R3Vn7y4ZKOz93ycxVrPpxHX3HGDNKfKr7EH8unm9fmc2Um9+leecm9B7VFYCDEUc4e/w8wyYNzN2mVWyinJxcTUSuA6YCvZSREqwk+/wXGAUQEBDgFRtbot00J3n+hjd4/KvJDmdZRJ+M4ZMH/sPr859zUs1Kz/p5m1n67WoenT6p0LWRow6e5t93fEK7vq0IalSbuk2DCOvbKl8SC638BQYGEhcXl/eu1xyl1Hgo4xsoIvKgiGw3H8EiEgZ8BYwoaSAEUEqNV0p5K6W8Q0OLTpGklY+sjKwS3S1193QjK7P48YkVUXZ2Ngu+XMY9b4wrNBAChDQL5t637yAxNpmbJg+m44AwHQgroNDQUHJiifkYn/NemQZDpdTnSqn2Sqn2GJfkc4DxSqmDZfm5mnNVr+PPmchzDsudiTxHQB1/J9SodO1Zd4CA2v4O8xC27dOSC9HxRB0646SaaaXJmX+6XgICganmQFybUqro1CdapdHtxnDWzt5I047FL4i0+uf11AwJ5Ovnvic9JQOf6t50HtKeFl2bVujMNmciz9G4fUOH5axWK43aNuBM5Dm94FMl5My7yROVUtVzWoo6EFYd3W7sxKGtkexYs6fIMvOmLmbZrDXERyfQumcL+t7anYat6zH3s0W8PvZDzh6LdmKNL4+IUNK+dbu9+NT/WsWlOzW0q+bl68nkD+5i6mMzOb4nit6ju1G9ltG3duFcPLM/WMCir1fw2Jf30XtUt3z79hnTnQ3zI/h48pc88fUD5Z7qKiUhhQ3zt7B3w0GyMrLwr1WNoEa12LvxIDc/fEOxgS4rM4vD248y4sHBTqyxVlp0MNRKRYNW9XhqxoOs+O5P3rz9Q3wDfFAKki4kkxSXzKNfTCoQCMFodfUY3pn4cwksmL6Uu18dWw61N/z12ybmfrqINr2MTNUe3u6cPXaev+ZsZPdf+4lYsp3OQzoUuf+WpTup27hOkQvJaxVcUaOxK+pDz0Cp+NJT09XpI2fV6SNn1d6NB9SUW95Vdru92H2SE1LUE9e9rBLjkpxUy/w2zI9QLw7/tzp3PLrAe3a7XX3z4g/qllr3qEPbIgvd/8iOY+rpga+oyJ3Hyrqq2lUobgaKbhlqpc7d052gRsaMix2r9xDWp5XDfjRvPy9C29Tn6K4TtO3dkiM7jhF9PAaL1UKD1iFlOoMjMyOLOR8v5JFp9xbaqhMRJrw2lpioWF679QOGTLiersM64hvgQ9zZeDbM28yeDQe4+9WxhLYtOrehVrHpYKiVqaxMG24eJVshz9XdhX0bDzL3M2NyUmib+mTbspn72SLqNKjJiIeGEtqm/hXXJSUhhQMRkWSkZlCthi/NOzfB6mJl2/Kd1G9Rl7pNir8DPOH1sbxx+0d4+Xny49u/kZacjo+/N+GD2jPmqeF4+3ldcd208qeDoVamAoOrs2vtPofl7HY721ftxruaF/e+M56mHRvltiZtWTa2LNvJ9MdnMuH122nRpWnufkopzkfFkpKQipevJ7Xq1yjQCk2MS2Lep4vZsWYPTdo3xMPHg5ioOL57bTZ9xvQg9lQcbXu3dFjHGnUDqRESSIf+bRnx4JDL/EloFZ0OhlqZ6jggjN8+XsiF6ITcO8yFWf3zemJPX+D1hc8TUDv/wGwXVxe63tCRgDr+fPXsd7wy9xncPd3YtHArq39eR2JMEtVq+pEUl4y7lzt9Rnen9y1dsVgsxJ9P4IN7p9P+ujZMmfNUvmUITh85y8/v/s7xvSep3yrk0ioVysXVSrYt+8p+GFqFpoOhVqY8vNzpNaob/53yM5M/urvQReUT45L4/tXZ9L+jT4FAmFfTjo1o3K4hfy/ayom9p4g6eJqbJg+mZTdj0LZSikNbI1kwfRn7Nx1i4lv/4LtXZ9PtxnBumNi/wPGCG9fhwU8m8MzA11j7ywaHCRXSUzOIiYotUXZrrfKpuMP+tSrjxvsH4lPdmw/unc72VbvJzjZaVhlpGayb+zfv3v05Nls2Y58d6fBY3Yd3ZsG0pZw9Gs1jX95H6x7Nc2eviAjNOjXm4akTsWXa+N+bv3Ly4GkG3dW3yOO5urly1yu3sm3FTlKSis9avXnRNpp1alxomjKt8tPBUCtzVquVu18by/W392LFd2t5qv8r/N/wt3huyBvsWruX254ZgV+gb4mCjG+gD8f3RTH22ZG4exaeHMLF1YWxz93Mqh/W0bF/W4cJE8L6tsa/VjWmPTKjyIWuTh0+w4IvlzFgfB/HJ6xVSvoyWXMKi8VC5yEd6DykA8nxKaSnZuDt54mnj6eRZdgipCSmOrwju2fdATx9PAlpFlxsucCg6lSr4UdirOP0mCJCm14tSIlP5YNJ0xk4vi9hfVphdbGSEJPIut/+Zs0v6xnz5Ag9dKYK08FQczoff+98NzJEhA7Xt2XTgi1cP653sftuWbaDRm1LNrwmIKg6sacvOC6IsWjT7c/fTOyZeFb+7y9m/t+PuHm4km2zEz64PY9Mm0Rw4zolOpZWOelgqFUIfcZ05+vnvyd8SPsiL5eP7TnJqUNnaFfCxZVq1A1gx5o92O32YrPinDxwitSkNBq0rkejsIZ0HtyezPRMMtOz8PT1wGq1XtE5aZWL7jPUKoRGYQ3oMbwzH93/Jcf3nsz3Xs4YxGmPz+TuV8cSuesEqUlpxR4vKzOLY3tPUrdxHf78dVOR5ex2O/OnLaX3qG75gp6bhxs+/t46EF5DdMtQqzCGTRqIf61qfPXs9/gG+OTOQNmz4QDe1by4541xNA9vzN4NB1n1w18MmzSwyGOtnxdBcKPa3P78KD6cNB1bpo0+Y7rlG9qTEJPI7PfnY8u06RsjmvPXQLla4eHhKiIioryroZUhu93Ovo2HOHcsGquLlQat69Gwdb3c9+POXuC9f05j4Pi+9L21e75LYKUUfy/axpyPF/LotEkENarN+ahYfn5nHif2RxHWpzVefp6cPxnDwS2RdL2hIyMfHlro+Eet6gkPDyciIqLQifI6GGqVUsypWL554QeSLiTT/cZwqtfxJzE2iU1/bDUSK7x+e4Fs09EnY9i34SDpqRlUq+FHu36t8PTxLKcz0MqDDoZalaSU4vjeKCKWbCclIRVPHw869G9Lkw6hOtu0VqjigqHuM9QqLRGh4SWX0Jp2pfTdZE3TNHQw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNjC+mswAACNZJREFUA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA3Qw1DRNA8ohGIpIZxHJFpHRebY9JiJbReQ2Z9dH0zQNnBwMRcQKvA0sybPNB+gMdAHGObM+mqZpOZzdMnwI+BWIzrNNzH+Vk+uiaZqWy2nBUETqAjcD0/NuV0olAbuACOAnZ9VH0zQtLxcnftZHwDNKqWwRyfeGUurfwL+L2lFE/guMAnB3dyc8PLws65nP0aNHCQ0NddrnOYs+r8qnqp6bM89r165diEhKnk1zlFLjAUSpsrs6FZEHgXvNl9W4eElcA0gFJiml5pZZBUqBiKQopbzLux6lTZ9X5VNVz62inFeZBsMiP1RkJrBAKTXb6R9+mSrKF1Xa9HlVPlX13CrKeelxhpqmaTi3zzCXUuru8vjcKzSnvCtQRvR5VT5V9dwqxHmVy2WypmlaRaMvkzVN09DBUNM0DdDBsAARsYrINhFZYL5uLSIbRGSWiFTKn5eI1BORVSKyT0T2iMgj5vZgEVkpIvPMaZGVjogMEZEDInJYRJ41t1WK70xEPETkbxHZYX4vr5jbZ4rIURHZbj7am9uricj8POUn5DlWhZrff7nnZr7Xz9y2R0TW5Nk+1jy3R8u00kop/cjzAB4H/ocx9Afga6AmxlTCIeVdvys8pyCgo/ncFzgItALeAloDNwH3l3c9r+C8rMARoBHgBuwwz6tSfGcY4259zOeuwCagGzATGF1I+eeBt83nNYE487x9zN9ZF2BeeZ/XFZ6bP7AXqG++rpXnvbnmd/1jzjHL4lFh/2qWBxEJAYYBX+XZbMWYN23n4qDxSkUpdUYptdV8ngTsA+pinJudyntuXYDDSqlIpVQmxn+WEVSS70wZks2XruajuDuaCvAVYwqXD0YwtFEB5/dfwbmNw5gNcsLcv6j8BWX2fepgmN9HwNMY/4lyfAwsBLoDS8ujUqVJRBoCHTD+Un8GfAHcD3xXfrW6YnWBk3leR5nbKs13ZnbLbMdIXrJMKbXJfOsNEdkpIh+KiLu57TOgJXAaYz7/I0opu6qg8/sv89yaAdVFZLWIbBGRO/Mcag7GuUWY51o2yrs5XVEewI3AVPN5P8zL5Kr0wGhNbAFGlXddSul8xgBf5Xk9Hvi0vOt1hefiD6wC2mB0awjgDswCXjLLjAY+NN9rAhwF/Mq77qV0bp8BGwFvjOm6h4Bmzqynbhle1BMYLiLHMC63rheRythaKpSIuGKkT/teKVUhBrmWgiigXp7XIRitpkpHKRUPrMbo4zyjDBnADIzuAIAJGJeSSil1GCMYtiiXCl+GEp5bFLBYKZWilIoB1gLtnFlPHQxNSqnnlFIhSqmGwFhgpVLqjnKuVqkw+5i+BvYppT4o7/qUos1AUxEJFRE3jO/t93KuU4mJSE0R8TefewIDgP0iEmRuE2AksNvc5QTQ33yvNtAciHR2vUviCs5tHtBbRFxExAvoitG37TTlMh1Pc7qeGJeQu8w+HIDnlVJ/lGOdrppSyiYi/8LInG4FvlFK7Snnal2OIGCWmQHeAvyslFpgDneqiXE5uR2jTxfgNWCmiOwy33vGbEVVRJd1bkqpfSKyGNiJ0Wf/lVJqdxHHLhN6Op6maRr6MlnTNA3QwVDTNA3QwVDTNA3QwVDTNA3QwVDTNA3QwVDTNA3QwVArgojUFpH/iUikOVd0g4jc7GCfhiJyRWPDRORuEQnO8/orEWlVwn375aRcKysist78t6GIjLuC/e8Wkc9Kv2ZaadHBUCvAnB0wF1irlGqklOqEMbsjpAw/9m4gNxgqpSYqpfaW4eddFqVUD/NpQ4wMK1oVo4OhVpjrgUyl1PScDUqp40qpTyG3dfSnmXBzq4j0uPQAxZURkadFZJeZ+PMtERkNhAPfm8k9Pc3sJeFm+SHmMXaIyIqSnoSI9BcjUe8uEfkmJ0OKiBwTkVfMY+4SkRbm9poisszc/oWIHBeRGuZ7Oemo3sKYNrZdjISq+Vp8IrJARPqZzyeIyEEzUWnPPGVqisivIrLZfOS+p5Wj8s5ooR8V7wE8DHxYzPtegIf5vClGaiUwWk27HZQZCqwHvMzXAea/q4HwPJ+xGiNA1sRI0xWat/wl9enHJVmGAA9zv2bm62+BR83nx4CHzOcPYGa+wcic8pz5fAhG/rwa5uvkwj4Lo0X7WZ7XC8wyQRhziWtiJGBdl1MOIxFrL/N5fYw54+X+vV/rDz03WXNIRD4HemG0FjtjJOr8TIyU7dkYueguVVSZAcAMpVQqgFIqzsHHd8O4XD9awvI5mgNHlVIHzdezgAcxclbCxeUptwCjzOe9gJvNz1ksIhdK+FmF6QqsVkqdBxCRn8j/M2hl9EYA4Ccivqosc/VpDulgqBVmD3BLzgul1IPm5WKEuekx4BxGiiULkF7IMYoqI1xeRubLLZ93v+JkmP9mc/H/wZVkUbaRv7vJI8/zouptAborpdKu4PO0MqL7DLXCrAQ8RGRynm1eeZ5XA84opewY2XCshRyjqDJLgXvMNE2ISIC5PQljfZZLbQD6ikjoJeUd2Q80FJEm5uvxwJpiygP8Bdxqfs4goHohZS6t5zGgvYhYRKQeF/PzbQL6iUigGLkkx+TZZynwr5wXkmdRJK386GCoFaCMzqyRGEHoqIj8jXGZ+YxZZCpwl4hsxLj0SynkMIWWUUotxsg5GGGmE3vSLD8TmJ5zAyVPXc4Dk4A5IrKDotPa9xeRqJwHxtIGE4BfzJRXdmB6EfvmeAUYJCJbMfo2z2AEv7x2AjbzZs5jGH2BRzHS7r8H5Kw1cwaYghHMl+dsNz0MhIuR+n4vF1N0aeVIp/DSNJN5tzlbGXkSuwPTlFK61XaN0H2GmnZRfeBnMdZazgTuLef6aE6kW4aapmnoPkNN0zRAB0NN0zRAB0NN0zRAB0NN0zRAB0NN0zQA/h+LdCcpUPdGaAAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%%time\n", "bkg_estimator = ReflectedRegionsBackgroundEstimator(\n", " observations=observations,\n", " on_region=on_region,\n", " exclusion_mask=exclusion_mask,\n", ")\n", "bkg_estimator.run()\n", "bkg_estimate = bkg_estimator.result\n", "bkg_estimator.plot();" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 917 ms, sys: 17.9 ms, total: 935 ms\n", "Wall time: 988 ms\n" ] } ], "source": [ "%%time\n", "extract = SpectrumExtraction(\n", " observations=observations, bkg_estimate=bkg_estimate\n", ")\n", "extract.run()\n", "observations = extract.spectrum_observations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model fit\n", "\n", "The next step is to fit a spectral model, using all data (i.e. a \"global\" fit, using all energies)." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Fit result info \n", "--------------- \n", "Model: PowerLaw\n", "\n", "Parameters: \n", "\n", "\t name value error unit min max frozen\n", "\t--------- --------- --------- -------------- --- --- ------\n", "\t index 2.225e+00 2.616e-02 nan nan False\n", "\tamplitude 3.013e-12 1.396e-13 cm-2 s-1 TeV-1 nan nan False\n", "\treference 1.000e+00 0.000e+00 TeV nan nan True\n", "\n", "Covariance: \n", "\n", "\t name index amplitude reference\n", "\t--------- ---------- ---------- ---------\n", "\t index 6.842e-04 -9.885e-16 0.000e+00\n", "\tamplitude -9.885e-16 1.950e-26 0.000e+00\n", "\treference 0.000e+00 0.000e+00 0.000e+00 \n", "\n", "Statistic: 91.148 (wstat)\n", "Fit Range: [1.e-02 1.e+02] TeV\n", "\n", "CPU times: user 304 ms, sys: 7.01 ms, total: 311 ms\n", "Wall time: 314 ms\n" ] } ], "source": [ "%%time\n", "model = models.PowerLaw(\n", " index=2, amplitude=1e-11 * u.Unit(\"cm-2 s-1 TeV-1\"), reference=1 * u.TeV\n", ")\n", "fit = SpectrumFit(observations, model)\n", "fit.run()\n", "print(fit.result[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Spectral points\n", "\n", "Finally, let's compute spectral points. The method used is to first choose an energy binning, and then to do a 1-dim likelihood fit / profile to compute the flux and flux error." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "*** Observation summary report ***\n", "Observation Id: [110380-111159]\n", "Livetime: 1.470 h\n", "On events: 2377\n", "Off events: 34876\n", "Alpha: 0.041\n", "Bkg events in On region: 1434.36\n", "Excess: 942.64\n", "Excess / Background: 0.66\n", "Gamma rate: 10.69 1 / min\n", "Bkg rate: 0.23 1 / min\n", "Sigma: 22.18\n", "energy range: 0.01 TeV - 100.00 TeV\n" ] } ], "source": [ "# Flux points are computed on stacked observation\n", "stacked_obs = extract.spectrum_observations.stack()\n", "print(stacked_obs)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=4\n", "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
e_refe_mine_maxref_dnderef_fluxref_efluxref_e2dndenormloglikenorm_errnorm_errpnorm_errnnorm_ulsqrt_tstsnorm_scan [11]dloglike_scan [11]dndednde_uldnde_errdnde_errpdnde_errn
TeVTeVTeV1 / (cm2 s TeV)1 / (cm2 s)TeV / (cm2 s)TeV / (cm2 s)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)
float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64
1.5651.0002.4481.112e-121.638e-122.443e-122.724e-120.98611.6610.1110.1140.1081.22113.858192.0580.200 .. 5.000103.9176679854109 .. 456.996399246008371.096e-121.358e-121.234e-131.273e-131.196e-13
3.8312.4485.9951.517e-135.469e-131.997e-122.226e-121.0363.7550.1280.1340.1231.31213.709187.9410.200 .. 5.00090.36639418623737 .. 325.95579657384921.571e-131.989e-131.942e-142.026e-141.863e-14
10.0005.99516.6811.794e-141.958e-131.840e-121.794e-120.66313.5200.1460.1560.1370.9947.46655.7360.200 .. 5.00030.8150316340727 .. 221.897913450260721.190e-141.783e-142.628e-152.795e-152.466e-15
26.10216.68140.8422.121e-155.211e-141.296e-121.445e-120.3525.6070.1950.2250.1680.8652.7567.5940.200 .. 5.0006.400181349922619 .. 87.997677879492817.476e-161.836e-154.145e-164.768e-163.569e-16
" ], "text/plain": [ "\n", " e_ref e_min e_max ... dnde_err dnde_errp dnde_errn \n", " TeV TeV TeV ... 1 / (cm2 s TeV) 1 / (cm2 s TeV) 1 / (cm2 s TeV)\n", "float64 float64 float64 ... float64 float64 float64 \n", "------- ------- ------- ... --------------- --------------- ---------------\n", " 1.565 1.000 2.448 ... 1.234e-13 1.273e-13 1.196e-13\n", " 3.831 2.448 5.995 ... 1.942e-14 2.026e-14 1.863e-14\n", " 10.000 5.995 16.681 ... 2.628e-15 2.795e-15 2.466e-15\n", " 26.102 16.681 40.842 ... 4.145e-16 4.768e-16 3.569e-16" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ebounds = EnergyBounds.equal_log_spacing(1, 40, 4, unit=u.TeV)\n", "\n", "seg = SpectrumEnergyGroupMaker(obs=stacked_obs)\n", "seg.compute_groups_fixed(ebounds=ebounds)\n", "\n", "fpe = FluxPointEstimator(\n", " obs=stacked_obs, groups=seg.groups, model=fit.result[0].model\n", ")\n", "flux_points = fpe.run()\n", "flux_points.table_formatted" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot\n", "\n", "Let's plot the spectral model and points. You could do it directly, but there is a helper class.\n", "Note that a spectral uncertainty band, a \"butterfly\" is drawn, but it is very thin, i.e. barely visible." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "total_result = SpectrumResult(model=fit.result[0].model, points=flux_points)\n", "\n", "total_result.plot(\n", " energy_range=[1, 40] * u.TeV,\n", " fig_kwargs=dict(figsize=(8, 8)),\n", " point_kwargs=dict(color=\"green\"),\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "* Re-run the analysis above, varying some analysis parameters, e.g.\n", " * Select a few other observations\n", " * Change the energy band for the map\n", " * Change the spectral model for the fit\n", " * Change the energy binning for the spectral points\n", "* Change the target. Make a sky image and spectrum for your favourite source.\n", " * If you don't know any, the Crab nebula is the \"hello world!\" analysis of gamma-ray astronomy." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "# print('hello world')\n", "# SkyCoord.from_name('crab')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What next?\n", "\n", "* This notebook showed an example of a first CTA analysis with Gammapy, using simulated 1DC data.\n", "* This was part 2 for CTA 1DC turorial, the first part was here: [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb)\n", "* More tutorials (not 1DC or CTA specific) with Gammapy are [here](../index.ipynb)\n", "* Let us know if you have any question or issues!" ] } ], "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": "3.6.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 2 }