{ "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/v0.9?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/deil/work/code/gammapy-docs/build/dev/gammapy/gammapy \r\n", "\tversion : 0.9 \r\n", "\r\n", "\r\n", "Other packages:\r\n", "\r\n", "\tnumpy : 1.15.4 \r\n", "\tscipy : 1.1.0 \r\n", "\tmatplotlib : 3.0.2 \r\n", "\tcython : 0.29 \r\n", "\tastropy : 3.0.5 \r\n", "\tastropy_healpix : 0.3.1 \r\n", "\treproject : 0.4 \r\n", "\tsherpa : 4.10.1 \r\n", "\tpytest : 4.0.0 \r\n", "\tsphinx : 1.7.9 \r\n", "\thealpy : 1.12.5 \r\n", "\tregions : 0.3 \r\n", "\timinuit : 1.3.3 \r\n", "\tnaima : 0.8.1 \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", "text/plain": [ "
" ] }, "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 12.9 s, sys: 514 ms, total: 13.4 s\n", "Wall time: 3.35 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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23VboLENq5/9KFxmIe5pjoQOXaGdkgPkgiurqZeJhN67Wu6PDwcoBgO38Ae+KofN0OGeSHr/p/fT2AEZni9geYfOwWgdWz1zxlDmE+9dVg9DBPbJOxK//QEUVRtuI5xbvl5sMIru8jdKD4A2IA46Hu3hoRXzr+qRHPsA9WNiZpT+oPOxSeZjnzfKYBkcVFNrkGB6g7ZksTCJEFoNU2A/n4gMoMhcfwNGLyblwfXyCongNmfvDsz78nMjnRQUnkFi6CCzOhLoAnHajY8rTDOmze7ydaR7Yxz2wAGd0DEUnhh/bq4lzfHfKeNvcw6naTBC7MX308yKg3pffZulB8IYEb2nXW9ZDQ3hgPcHeGSMpcgw0xIN2GRAeSuJl7Hn43VjPgwBjGKsNAjGTY64SbrOtAoL001mYt+NOBt/GbWjuVXbA9JAYtnUGxmer+eDEmIdtnd1G4HOQjowqfvDuOotbVcnIgeEdKwe1Hyur49Hr3CXeB/fYDq1tty37y2Cu9jUeqNz/M7VfKp7CGF9i0VFzGftfdulB8AbF48Y8TONQZQDyBsZOFW01zqB4eHnLuyoHGHmcnVeVcc8r7azYNu4siAPDVVycGoBmrIs3CNtHD+1Y7QHHvl68lP1YLusHx5cKA3QQimEjHmfJi8P7G19QroLH2Mdk2yK87Fx4IXEu3i59k/13AHO7qWfVOJBWoQ32JXqAKRY8tzyaI/xc/BnqYqy3DQh7EHxK4sZnbEY8uCsqrMFj8QCuUxU10R9YCi/w3w34UpspsO+hCnty0PAH3kHgMgaDeu5MzQuHOgjIjuPquTMaqV30wXNrHbQAX/9PRZY4WFnv1yIOct/P+3bZwPfirLBN7Iuc+5FKQYRoZ3N25deZeETYvPdFagdQx5ejv1C5Pu7xli6CmXv63dtO+x7Qfdvktp7XMyMOIoAEqoxU7HFui8MozkMKsDkIEl/mNh5A0KvFRBUmqk5q2pnasT08wosiRNtRVOdp31kO54lzx9kQ1wfQcudBBESpnVrGSwPgdqZDuwr/ow0yZlC4augqcLTJOdtzM0NUHdmG+oMx9CW2Sb8oqeXlu7DBer8Q4iudNfo9rHTRFMJxYIl+vQ/VBm227dXhXj5rcUN+tCdhsPcE/4G6H3JUIFRTBr2DSgQXP757Vl2clXlsX7TBdT34PpC7Qm9on0HsarQHYvsDyHZSG3gYiF5mfh725cWBnNp23pYzKNnvy87R2XEUz9t1UwP7OqN0Nv9mKmWc3pN7gaffYxqltgNmaPtI5Zxj7GNSSR106VK34wvktkkPggsQf6vzITYtpq15AVUGECobD+ihrePh9FAHd0b4g8qx3EExDtvGAe6ltmJeaTxHZ6pd4DJTURedCTprHdj3mrqBe6TsfNmxc4HVnOkiyANMgFLMCY797GJ7smNFs4BPberHcBYW7aH019l2tOvRL8A1Om/8+G524Dwc/Pwa+fH5dN3XuS4CIC9Gfzl2vfCWWXoQfMJyGQAiPp+tp3rxkDsQ3lexL7mR2kMsZroIniTrR9aBXWdDbduPgw0g6HnJHog9t20jE3NBTWedgwjrIzuN82qwLaDs6pszP/cww3rIJXaWG9t1lniZja2LFbs5ATD3SuAKbfk1iGDS5SQB3E9VAsHpt6vsddheuhgu1aUZDGxbrwTuoTNuFvFnqEuFX3a5URBMKb1D0t+S9ILytfyhuq5/IKX0dkk/phxG9S11XR/eZL+etGAPckYAO3Hh4XP1ENDZUakLGFPM3CHiLIwH1pmmT+PowdNu6K7UDWyoS0z5CHvxbQH1qHZGNdnnMgZAuD7xuFxDjsN+7jkG7BBYNu07S4ssNarcfj2jB5j+eUFUnDw+S5ybFiLox//xRXCZ/ZHz9JdkVwGMyMwiu+y6vs4yuU7u2ffoBdlyB/UuE8syyk0zwbmkP1vX9cdSSvck/WJK6Wcl/XFJ/4Wkd0v6Vkk/eMP9eiLi6gpJ856r6gMHYPQHGEBkDol7zXIvCy+1B697c6WiKq2pPbgRKsFQ2479nGVEduY2zTiw3BHTNSgdzOLgxa7nHllX3TjXgW3rkxF5DUFq9vFAxzzhyMxhUX4Nfduu66Kmb3HuDgdSZ+l+rvxHuoCY4zlQxnvu99Pb7nqZOLjG82Z9vN4DXQRA11AGYfltkBsFwbquX5H0SvP7IKX0q5I+X23beQyzWhqBARJESzaGZ2oAGlJ50LryUrFpwcZgUnHgzawNqW2sP1VRp6WSP0q/PGSEWD+yINzu5EZ1V7u6BkNUpRg0XjKKc4yZDQCbMzj3XKOmD1XAHHUREII1UhnGbY6ujnu/+Ybx+bwnfi84P/K7/Z7A2A51EcTj8aQ22LkmIDv3NdvWgTICqJtgxmGdH7cO+/gLqOtl0MU2B+FzG+Sp2QRTSu+S9CWSfkHSr0v6sKQ3JH3z0+rT5yI8EB4Q7SAAeDhTQHjIvXgAKl1SGyz4jmqXP5DOStyWqHAM2opMratYqYeAuLPjMubnaqDPmezOIfrq+7jqGg30st9UsZH1gevox5Ha/SMTp2tQA64ArFSYefTiO4ihIgPslbrvS/zPMxJVcj9GVHVpJ7YZGWRXnnm8Vz7vSBcj7LJb3jYAlJ4SCKaUtiT9hKT/qq7rfeW44D/Ysd2HJX3DDXfvsYWHESYY59ClPJRnKsACfUBJbY8msVueNeIDKNoB3enB4OLB7QpniawAoKOwwJGK0dy3Bejc/gmI+XSTHorhTgEP6nZmOgvbuMrvebmEeXAOfHMsZ7C8DDzV0M+FgPF7dhz2wfnBPj5vhx8L8Zef2/9cXO0cqT0rYFSNkS6WHc+DsJoIgm6z9e0JyD5T28PdxZq5l/Hl1wXUz6KklLxq2Ufqun5JegogmFJaVQbAv13X9Ueu2rbp5EvNfpdFazwz0qX6uNp6av/9Q7l7vxmntj+eTpwJbkNz1uUDPnp+oy1OupiOx8Dyvk2V31Ck9nlWhQO4rE1nEx4wLJW6dgAkAvMcKofDnCk7hk5U1NyYNULMnDtumEnNc2U5BykD3bZdM3cmcR9ggj5nsHt/sUGe2rUA1GIJND9HV3srlTzjucr95dwi63L2NWrO2SsN8dKpm77GuUP8vnNfnPF3sWo/J58Unhci2y+L1HW92bX8pr3DSdL/IulX67r+qzd57EWLG/Cxw+GZPVEJRXC1z3N3YRhIBAkAye0//iaO4TP+wA/Dt28Xsz1Ix2OwEsJDhgogCJg4AwVwqANY2TqpgJaXxvfj0V8YEiFCp2qDADX/qqYfnmJGsQK3z5EBQfse98YA8BeAp8BxXdxexvXlPgKga2qH0XANHGycQfl0mNE84DZlB07uAZM0RdXY+8n2/PbltW3rjDlqCn6/h8pagWsY/pJdVrlpJvhVyszuV1JKv9ws+966rn/6hvvxxIWHgAEOc4jpVFK3ZxEG4ul0AAi5wv72dYO4P7yu/rqH072HSe3jS23nibfrah2DYV0ZAKkeIxUggyE5KKOeMSgJ0XGG6oHGLN9sjsULhe3Yhgo294fS6lCaTKWXm+131Z7AnGvcNVhhRpUKWB6oOGX8WkezQwRSr4jtAdLRo+z9cPXSXwbumfdjdOVFcw5dU4MOVF4krgWwjdR+bqKaG1+grs24RrKsctPe4Z/TEnt/30ywRw1U1DHPGfXtog2Qb1QcZyKoTTx8XqvOB5uDX7TnDJUBhdAZxL3SbntzBwrHAwRRkZyVum2Q83G24GljeIkBBdga7MptdxwLddqdTpuStgfS/W0pDaSqkgazzBQPVcpWuY3tsswHMkCiTY5zcfVZ4Rqybewr+yIAG8sxkRAH6gx+rnbpK64dffLwKm/XM0xQ6ckr5mVyrMtBj3N0dudajIcl+fEjsC+TPDXv8G0SNxr729vLPs3Dbx8czhwYSDBAbDVMUo4tCdboWQVum4qFAJIKI3HAjDF6/nBL7bCLDbVno/OCAC5XBU9zvXAo+FzGsK5DlfCX+yr2KGx2ZMSsSJpX0mFD3/Zn+aXDZEExWDqqhFFlB4ydSUWmMw/fmAGcuXlxi+gc8WIFbopwUGLbiW0b++P324Pgj0O7HijPecQybfGlyIvCX3Sn4TvaKZcVAKUeBJ+4uIHZhf9ub4s2p/h2jl44z4rgU6v9IDrLlAoQA5qAa7QZ0g8HLAcO2lyx9REw/XhItGGyPefmgdhSO0SE71rFJuWZKqi6swYlYswg4ufkziCpsE/AJqp5cYDE+4Sazblw/l75G+lyjCls58fzlyPn4dfFX74s7zr3rnAZtneQ9XXYI51lrqhbRV9mAJR6EHwi4g8db2HsM9FWFwdRl7MiPtxuiI8ghzgQxgefhxinzXE4TlSJ4kCKMWjevjMXXgB4auM2HkLjfcPOxXnCxlCRK2VVnj64A8avJ6qe91kqwLdn5+fXnd9uWojmhC7wclsrds/aPv5S6Zoj2I/lJg7Zej+e911q2zi9IrfbVZngiW2c/ToDdlshjFsqz+Cateu527FO4TJKD4JPQCLIRZYXlzu7ck+lBytjSCc8g7zhkdpeSAdTf7NHGxKD1O1e7BPtW1F1jQZx2TLUWexbPreJ1AZUBx7Zci90Glmp57UeKoM4GTgTFW9lbfsCKp6Z40UC4nWPjodKBZj57zUOu2xpOIToa8xdjtVj/H55fjTXIk6K5c+OF8yNjhmyi7hvnDP9Z7voHffnElV9rBJcjjmCa8K82Jex72WSHgSfkLiq5SqVA4jsP4Dmwb88ZB6TBajQLsDoDhAe0sgcIui4p9r75czAPZgK3zFnlerJgJJXJDlR2/bk/fEBjX2Ta+EOIO/PsaTX1c484ZjuNOFaOHPD9glouO2Ua76qEjDM9aDKd7wHfm85DrnYXrzBf0vtqUD9xeDFJQAevy/+QnDAiYMXu6+HWrld0c0Ag44P/XEGzf48p55R4zPnLTMb7EHwc5Sum+8PVrSb+AXvYoLRe9k1RaJsG978HknuLDCqu5exMYV9WE5brgpGQGRQk6sMAMZ+ux2N88XJMbTfBBB75ohnrKypDHTqCUoXJ6bymoXxOuPp3lF7oihiC5lwSmqzzGgu4P+RykvAWaCrvn5vY18oE+bPh7+cfJkDJKDlarGDJ+x03rG/P7vxxUA/ADqOsa32nM3uPPHnZpmkB8EnJDxAzqTiA+qgGL2BiAPMLHwik/HYwi6HhIe6OAg6wEUHSWQGURWOHkvYnNcC5L+rZD4wox2Uog5j5UHG+e6rPW+KrD3m65WKV94BJ7ITt7txXRjwOyoVez7THHO/oy3akdrgAUhPwrasd8Y4DMuHaseMsZ0X2x3ZtjxfLPd75jZHqR0OI7UBuOvF6M8w67vS+Nx+63bfZQRAqQfBz1kiWDhoRMdHrAjsA5X4q0FY32VLjIAlXTTEx+O5QTsyiQiuXefHOfEdPZdSOzPC2YLnsnbZFfntObs+8128BoCJg4oXqPBzk/2OIO/XkfhMGKEHHkdA7XpRdKmE3n58GUahz7BpV189bg8bYhdL5Pw9VbHLCce18NCbrufVzwkzTHwmb4NcCwRTSl8g6Yvquv4/U0rrkoZ1XR8stmvLI/4W9YR6V6l4sLw6S5xPlmXu9PA3uw9cWIF00R6HClirPacwDz6gG9mAe7R9oBO8HZ0tMBbU8oGKUyeet+x8SCusm+OdqIRkUMYLm5Pbs6IDh77BhKm7KGVV18HJYyf9vGIfpQLafk19wMfrz3WI9lVn7Byf6+xqq9R+VnxSJPo3VJv5+bVwpoZUYbk7QlZtG9/Hmbt7r/35prIR/b8sJGyZ5E1BMKX07ZL+tKQHkv4tSS8qFz392sV2bbkENQHvHtH5Pm2hf8eiCO4d9t88qDgMYihFZCgsc1WOgQd7ci9uZESy5TAjWFkXc6QvHkLh/YmTNbEvoDpTCWtBtVaznkwZPJGeJRG9t5yX7PphW3S7pTNX+kBITqUcRoMqGoGItjlfsm+6VGDv57YyKAP0Pt8K5x2nJMUuN1DJjfaQGPf2RnYd7ym2u1XbhhdhVO/d5usgzTJeWFJhyjGDZNnkOkzwOyR9uXLdP9V1/RsppecX2qslFi86elnmhNQ23I9tuatwPPRdVUnc7kicmrMLPHsAIGwpOgyiui5Xe9EvAAAgAElEQVS1q4aMbT/vYwzadgCMtka+fZpK96Y726SvDGSCpCnpBYDTt/WmTS8gyzWLAOxxhxyfsJs9lYyLy/rv5w7r55xizrWDIM4rL3jKSwkQcabraZLcV2etXisRqS757Y4XX+9FKeKzyXn6fY2OEM8/jxVrlk2uA4IndV3PcgEYKaXEi7yXRnj4I8ugrJKrdDzsUdXocqA4MxyqDRw+YPicWZsYtWkXVfdQxbkRk/FRa6mH6DY975d/ZOdHO3iHCRCOA6RLzYcdUWlmoHYlaQYu9rJKJYTFVX+peGIpN7Wlov57uhqOHlcDEQf1qOa6I8NtvF2qs5+zq8zY7ng5cc0AcO4L4M/+UmHJADF9jzZUqc3u/SWH/THeC9dKogkBQHc7bJd9c9nkOiD4j1NK3ytpPaX0dZL+c0l/b7HdWj7xt6tU5ghhkBDU64bmGCQtlYdtQ5nlOIMjL9SryXjxUs++cLuOT9DkteDcIO5OBi9WCjANm/44K5FKkDB9p19+XVxljCARrwGD2dtJylVdXldhsaiLnL9PgM55cz1gVccqjMhfPJEJOdhLbTbmNl2psE1XcSOLJP6QF4PbKVH1I6ugP13AxnXjZcV9eUOZ0XbZT09U2D1AFk0g7jmnbS+M65lHrjJzrsvKBq8Dgn9O0rdJ+hVJf0bST0v6kUV2atnFy8kTw+elpNxREdUoqQxCHkCYjk8oLpWofpiP7wvAub3IVfOo5kXxenOob5wLbXiZfQz73h7gQF8iELqT5Sqv+YpKYVdAYaB2zcbLPJYORM52/NgRBN1hEBl6dArQv2T7ztW+DpyHO8N4gcX0NHc6YeeM5+YvLrejkkkUX0JcL+4F7J5jRjsiL5cuoT6mF61d9rJQbwqCdV1Xkn64+fRyhTAYAEAvv05FZa/xt6VSDdjVJfcC+uDwmnTRsO6GdNig1PZcOiOL4SKyb8pK0TZtjqwNvLs+4FCPPHPD2aZ0kS3J+rqqdraFxwZiv3NnD6zYTQFuU/Xzd1so5w5I+7Xxa4p5APuix2QCwF781pkb99BfFu6sApTccUG/AXgvd4/4S+SwadvNBn4/ET9vrwpe22/pYkqmM2CeU0+PdJtllxawLHIpCKaUfkVX2P7qun7fQnq0pMLDHL2kMJXatnOg2lJhF1OV3FjpYtiFx965OsLA2NDFt3Ic4NH47TFoqDyowDEsJtrDLrP1McA9F9rDSbzfABT2PZgMwdJuOvDEfg858ZeOrP0jFQC6rFagmw26wBk272o7LM7rBkZ7rTNxriXH9WfA7b5S27nkOd7R6eJmA8JW4rk5W8QkAivEZOK2aUAQ+7HPWX1m7fl17ALdZZOrmOAHmu/vaL4/3Hx/i0owey+N4O0j/cnL6kttVSzadkgX8weMai9eXh6A8AdvpovA1mV7c2aksA4A8SBbZ0hSu0ae78cgYZAzsOgLdk1YrLNcxO2W3lfObaRSzNXVNs+79v08/Ch61iOYRLUccedPTBPjHHwaBc8RjucmFbADqGGY7r2X2lOmAsreni/zfrv5wjN2YIHuDIJpuqrMvXVnjV+ny9ism3OWVS4Fwbquf1uSUkpfVdf1V9mqP5dS+ieS/tKiO7csEj1reN78wQTEAEmpvG19buGxijfwQKVSB6qe29NG9t+N4Q4m0fgPsDAwePg5vtQGNM6Pbb1cE+fggwbni6umHvNIv92+5e0DOO7ggTHft34606YPXtR0r2lnw/b3EBW+XR30lwfHj4zxTKXsP6FJPp1ALH3v7BhnAy+Fy+Z3dtZ4mXrp2oTH7fGccX2iaYH7El8CUgnU9xnoor2UY7vpZdCxzTLJdRwjmymlP9CUxldK6SuVn4NeGuHBS/ZbKsnn7lGFDQGS7rFk0LlDhE+0kQEUvJk9HxZW6mqnq1EApofKwKwAoSq0A2h6HB8SY+8cqH054vYyVyOnyg8WkwiNVJw/hGd4PvSRygsDFY/rE22gsRo3jgpeTFSloZ94yL1OoFQGzP1wHTg+4BBDoQAIQGbN/rtnlW2ZVzmqyWwXQdr3h0XCiD3G07eNduFKRfNwgOTDSybWquwq2rpMch0Q/DZJfzOldL/5vyfpTy6uS8srbkDFqI53DyB0FcaT0D3YucsO6AOlywDuQbEAFzacLmeIbJ0PMAC8661OdsuZ2upbBNo44Fyt5trEQc3vWm0wc++p2+Ck/AJxluwVj90D7GFEeHQRMj+SLg5m3xZwgbX6VAX0z218fv5dwv31Y3I8P++4DzbCkdqhTH4cB0E3l/g18RdpVGe7WJ07hgigp8/ScgPhdbzDvyjp30spbUtKdV2/sfhuLZ9gx5uqzVpQlfAkovqiMlNyyr2VbC8VG5Tbb2Kpo5nKzGtur/KcWi8GILVByYWB6KDM9q46xQenyw7Jcs8M8YHnYM9vQnFIN/MCpQdheyZTksr8J16JpmqWb6o4jThvgHykEmfnwcMuXkyB9L0zFaaKGuk2UF5EPltdtPt5oDfXipcl7NTnUXb1kxcejJKXrqxP+yo2Zn9Bcn05d/bzdMro+MADvKb2/YsscxnlTUEwpfQXwn9JUl3XvU2wEbe1SflBWQ/refDdS7zasU1kUZ6t4V5SQDT2wYUBAttkO9m2gBLLGLjRgRK/PSfabUws4zva3+Iy+sC3mxVYDpsm7Q2wJYyE7QgIdiblhVMra8+DnbkP0Qvr0wXEIg0An/fHayMCOOznTByZq+2IiPOuEDLkcYKwXPKQXdy77k42HEt4150JetEPNAfPBIlM3kGUdbzglhUMr6MOH9nvsbLX+FcX053lFLdt+dsxetkGKhWIpW41hOXOGniYXdVL6gYtf7BjeShYZoyFq6yNaNPzAeMPS/RScmxni4OO312Dyz2dBAjX9j+W4XIA31YbyJl0faJ2ySlYOdfUVf+BijrrdjZnrdhHV1RymJmrxV8AXkEnqUx36f1wm6UzdUB3ZOs8wDqq+q6CxhxlD63ZVq6ZSB62e/M9uNrZPOfMcq55LLzh2y2rXEcd/qD/Tyn9FUl/d2E9WkJxW5gDkpc552EBiGTfPLAe0uEGb4ApxpSx3mPBfB1qGVH9DPI4cN1JArAy2Kh+AvMA2N1zCYOINkFnPhHAvSIM4m0wqFfC/pyze379nCmIeqg8+L1Nrod752PpME8NjEwaIFxT27zgzHRk+7s9l/57wLUDoGsJ9BcAjLGH0QHH9eFF4HOQDFQqaHuIkffbXy5evXvT+skzAQt0IF32QgLXYYJRNiS9+0l3ZJklMpy5Mkvw0A2/0IDQzH5j67untmMgHsencnS10QcawuB1b7NXf/HgYP+Oqm2sNuzA5n1zUHPGwnrPvnCjvavo2K/myh5YBntklYDgpgqoeG61n4eHsEjFQ4zK6CoxwAKjAoicdXV5yGXtAbjuCR6qzc7dnOHPgdQGwXnHcg/gps/Y6mB2bgfFduj3w18EzuRp477ySwTA9BAgTAtdL75llOvYBD1zZEXSWyV93yI7tczi7EoqD2pMr2IQxmR3D5/oyu30Yyisc4BztYV2ow3JbXQx1GKoNnO7TJwR+PG8fcTB5ir1GNaDMX6lYxtYEY6cmD/s7cNkKP8ka49CC7FAgp+Lmya6vNxdZg2O6x5kzzFm/3hu/Hb1uOulg2oOGPOsEArk/Yu2yGjvlIrzxzUAXjAR3KV22ly08S6bXIcJfsB+zyV9qq7ry5yLd1aiwd+ZlJesclXQJ+ZhHw+oldp2KR/QUgE6d5g4y/NshdjXyz5u64sGeH/IozHfzzcCg78Y8JJL7Zp6MTBbKgHUsv39esV4Q7JEuN5cj5lyhRWpMJ9Va/NYJc0PwdjPNfcMIL/uEbjdTuYB3BGI4jWK3ncHQO4n14fjuVeX64UaH9M3PeeXDJ0zFSfeWBn0eF63VDzdmEs8+4S2YMnLCoDS9UDwv6/r+iVfkFL6cFx2lyW+qSMAMpkPTGiqHO5BmIXH8UkXWYDb8aLnlkGyqVK6q1a7gOjA2vXc0aheAtAxKNuPBSDyHVU5QDh6FVkP4/Bc3WjwZ9BJRT12dufiZgXAMXpC58rOjAjsDPCoztVq28e47tQz5DxRS101pE8An6vAsd/OpDgv+uyZOaznJYDt1/PM2dY/7sWVXacDlXCjbZUwmU0Vk8WapJWhVFfSoLo4pSjXw18KyyrXAcH3+p+mqOqXLaY7yy0MOFdP11W8czA8ysnzIDH4MfRLbdUDwOJNHD2qI+UHGE+ph0d4vJf3kzbj+jhjmWy9q4c8+AwK2qU/7nRwAOtSbQdhX/q9b9u5B9jZytiOARvbUvGEwrhhPd4OHl6AzcVZnzsynNX6S2KgtmmD5V6E1IV+eSUZqZ0RI1t31vQJINxXGwA9v9lNIvdU2KzbSJ1NU5B2o/mMx9Kw6dBsJlWzUqnnROXF4xERt5IJppT+vKTvVS6mSkwqkRk/dAN9WyoBILxUESoZ4MY6D9VwLye5iHgLebCdKXaln+FJ5TeeYFdv6aPHjAEcnkKGbanL4E07gANVnue2DyxTuuj48XL40kXPZ1cOL/12B43UznWWbed2UYAAxjVUUf2kNoMBHJCY9+2sOdruEF4+Ujs8x++529Skcq9cHPS9+o4Ds1cmksp1dK8095XnjuDwDV3MJz63IQeqfVa1z4PnbNnDYlwuBcG6rr9f0venlL6/rus/f4N9WkrhjU3Ihk+sA0tAqDLNm92T6r096SIQRQYYbXbYFQFWVBcGVsxE8Bg0r3/og57f8c3f5USJH0BjRZmVeNL5wPrGf5ggxwWw3XnhTh4P2o7l+KPDydVTzodwl5naZgiuF9fZnR2ANio1bcV7Fq+Te2KliyloqJczFduwn7ur0A7ufh+9/14TcktlbmWu35GtP1MTJlVJw2kBBi+44aaDZQ+LcbmKCX5xXde/JunHU0pfGtfXdf2xhfZsSYWB5vYY3uIMFB50jzXjYZba5am6bEcOMgxEMlLcvuf2vKiu4FV19XrNvtmGY0jt4FkHrqF9S+1judcSoAcU3futsC/txVnWBmqzXN/WX0KxPYVlbrJwhhs93Zw/ACjb1z3+9MeBsCsXubLfERArtZ8T+ukvJp4LByUvvurXdEVtRuthTm7P85ccwLhq23IutMVzuuy2QOQqm+B3K0+1+cGOdbWkr1lIj26B+ADHkM0Djb1MaucEe0CqP8C80X1wwP48HILtvGJNFzMZ6OLDLFvuVaFZzuBZU3G4eNZGDL3B1ilrk74ANH4N3JlC286sve6el9LCM4nH2QHT7W2c+4nKvYAREk8HAHAN/VpTVTmF422oDdCo2Th1cLD4fUBl9YEXwQQzAXnQ2Df9xcpz5ffCnVcxJMuZrZpzpb+cB89QTIn0F5U7iGJkwLLKVerwn25+vr+u66mvSylFc0wvKg+nlC8sD9SRSpwag456dKR5nTXf7DsKbc7DOlhStN85S3APrNRmHsSwxblECB727AJAF3WTtmNVF8JIuAYE8UqFwRAfycAH5ChG4GwKhw8gEG2DeDY31fZQR7WT/hLS4SYFVze3lO8HLElqq8PMsUIBWPrgzNsDtWcqVW5g7DGW03OYo2rded8H0nHVLizB5FlkrMjOzws/uFODNgFanD+06dNB+DXg/rqjZdnlOt7hj0qK6nDXsjstHoaA+rCqdm4vKhMR+UTzS6UYQLS1xaBnwM8dA26zoZINrMdBJXp4UfMACViLsxw3qq+oTF/JgPGYMfrhaWdeuSSq6djWtpWBjPlCGHA7kh5KekuzvXt5N4fS5ob0fCUdHubzPVCpn+d2RTctAF6xhJQ7TVzVBMhxevDS8v3or18D/4bVeYEF7i2AE+cepm+ADqA2rfJ57qmdw+zFEmT94SV3rGKSgIl7KuVAJeQGVh7F40Jvk1xlE3xB0ucre4e/REXL2la5n72Y+IMf3/JRvSM2ixQu1Fp/SzOIvbhmTJR3EEMAJlfpcBxE5wvA5AMQzzQVmV1F51wYfG+ozOXhGQcMLhwxnjpG2hwg+FDSgwc5HGPzUNpt1m1IekHSzo40n2ewq5TZ0P1t6S0PpPVxXjedSru70muH0qebPnFcLzHmAAfwANjuOeZlNBrkcJHprCz33G/CawBJV03Zht/YHz1ez6dQYB3Xjmdj3/aZKwPgni6+NDlHju8xfJUulnGDmXMNiBDgGXFGzTMNi78tLFC6mgl+vaQ/IelFSX/Vlh8oh870conAOKS2aunhMKg+q8peO9TGYxUGIhUABIjcI+wDhTd7tOO4+rWutmfUBw2qGn3iwz4rQ2l1WOLH5nNpZVrmQnH2CuvxwF+Ae2sgjUYZ8OZVBrTnn89AV1XS2iNpa9eqWA8zwM1m5RgbG3n7tz6UNreks3lePxhIx1PpYJ73h4nuSHqwk+PfZjPpjX3pZF7mMcaMMFJuY2ijYjTKn7N9aTBvF1zArlqHNmTXw50wcxUWiarsoHl+firRBVJ73plaGeCplCOVsBd/MfJC9tAcZ+1uh4yFJTCT+Hl4kPSyZ4hEucom+CFJH0opfWNd1z9xg31aanEAlAp7GofvrodwTe0AXamwKw8NGdj3amgL9c8ZICBIUddYDIB1qLGuKq4oA9HaKIODAwT9oA3+Y7PzgcW64TCDynCYgXQ0yuA0HmcQXG9+a9oM4nkGLGx5o6YN9llvgG3u8TChX6vN9hsb+XhVJa1MpMNZCVynj8OhzmPlBgNpbZz3Xx1mEPTCCQAi4nZa6aKHGBZKsYc4FwtteCiTV26+TE31Fw9M1lVyrocXzIX9uc3YnWEuHopz2wBQuoZNsK7rn0gp/RHlzJGxLf9Li+zYsot7YwmERk1EHfG3NGXl/aGU2oPCH/Bk7Tlz5PdYbftbTHxHGLTu6XIv4lzSxqCACABxNJGGE2lYlTSraAdkfwb6mi62Mxzm/1IGsvk8gxROGuYROVWJM3xo7ayNCwDO55kVyo43lLQyyMcbjfI+58fclYazUi5/c1j6lgYZ+Le2cnuzWWakbot104LbPf36euyfe3RRcT3zhXYIsHdbI8erVCrGwEi3JT2vzHg5vjtMHGhRk6Pzxe21btdGzuxz50AwpfSDyvfkqyX9iKT/WNI/W3C/lloAPx6YGFjqQcfurOAh9Id+oKyS7igDALYnZ5xua4sTAp2o/QBLhR1KxW7m2Rj0DW8vjG17uzApSTo6lIbT7ORBbQZEBoNiq6uq/H88llZHhf05s5xOpb096dEjaW9W7G3HKulzDP7ZrFGPq5zbKuX2V5t2703LtRs2/Z9MyjE9LWy0n9cNhxnwtrZKvzY28udklreZTqV7kxJG47ZdrrlnunB9uefutXcnDQHhsn359jAoxL3aq5KeUy7t9KBh7LxMJlU7PIt295vPiS46y7BrepiMVMD8tgGgdD3v8FfWdf2+lNK/rOv6L6aUPijpI4vu2LILDx4PPhVRYHl8o+ZKRYXz4gmEiWxK2mpUxuHsImOEocSCBvQF1chZnhu740BhECTlY45GBSTOQXCSwUjKTorNjQKCo1H+nk7zgMRmhzq8tdXeZjrNqu90ViqcSMU5Q98HKqB2aG7a1VG2E57OpPG+2RGrzOqqqvSV/g+HBdil/Htnp6j/43FeN51KBxt5/51JUQvdBie7Zn5vPAsFr7t7ijeVXyIepzdXsfehFlPsgYD49ea6rCq/IO9LurfVmBKUr+WoeUlJ2cGTBvmlsdqc/4HaMZ4AtAdfeyjPbcoScbkOCGI2maSU3q5sT/7CxXXp9gjA429Vd4i4Jw5jtgOhg9dMeRCmgTEctQGMmxnn0IgM0D2lPPBeNQX26GqyA+FgkIFCyja5wSB7d7HTrQzzgARQ6qoA3aQZ3Rsb+Vwk6WA/tz+fS8cTadoADczvoUrdvzVJ97aLDXE6zcdYGeRjrg7zcTkerEjN9Ts8LCCIaowdcGMjAyFMEZV9NMrHHAxy/weHxXHj5ax8MHHPvEiGpzgSCgTTc/sdzgfPQ/acYcwdAOT9po8rw/JiGcykk2F5rqR8jc6UQdCfvegYcXFPemS5t0WuA4I/mVLakfQ/SvqY8n344YX26hYIDwsgiLPDB4N7icluGKjMSwGTfKNpY1JJ46ptmOcBBTA9l9QLheJEQfX17AfYIDYqqQAm6VywOdRJWNPRYWYdmw2gpEEGoocPpefefV96+9saxKqzrvvJT+iNvWL7m0yack3mlR28VlRw1FO2HzZtP/98YT2AGja/nZ3cp9NZYY0Hh1nd3t+XZlXDKgdtRjoaFXV9MCjMcdAA7FpjChjtZg/zZN72tsLQ3AHhNlpYoHtz1dyrfZXYUqmweex63A8Pj8IWu9mo8ve3i331uHnhVGqyfCrpbFZMHAAs9mpntO6xBvhuKwuUrucY+b7m50+klH5S+Xp98UJ7dYsEYCLez9/MMMPoKfac4xjv5QGxtE+8Fx/UJgzisEvYByCIakV/YAKwBGcLrkK6ajzZKqquOzu2tyU9/1bpPV9UdM5XX5HGa7r/yU/qdH+qk1lRU6sqA9fWVh68p/MMpusbBXxoe2cnM7PNjcIgWX9mdkJYIPbJg0YtjhklADD9r6rSn7oB3pVh4wRq2O50WrzWsHacI1IJZ0GN8mt/Doqw2Vk7i4aXoef2eviKp0zi/eYFgLliMJD2hoVRen1J7jfmBUwkI5UXoZcX82fkNsp1mOC51HV9IukkpfTjkt65mC7dHvEHB1bmBm8Hui5DOCzgqFl/oMIAPKUJoCWOixgyH5g88G7M9+NLZXB5eMumpK2N4iTYatTcey9sShvr0uxU2n9Dx5MCOuOxtPrOt0nve5/07361pLdLel76gk9I7/l56Z/+vFZ/67e0OjnW2ujoHFgHjc1qbB7fGLIyGmUWSGzhyrjZoKp0Np1rYnbK+TwD2fpGYXbTaVaJk3mMsf2Nx/n4J7MSe4gZQCpMdH2jqPZkZJypmSOmOY+zhmqh4sa6guesa1ayUDxUBXOFBzPH6tfnjrHGifPgQf7Afvf28j5vSHpVpTgCsZPxXntYlb+cbzMASp8lCJo8djmxlNJ/KOkHlK/zj9R1/T+klN6r7Hn+dUn/aV3Xt+a6R2+fFw5AzeHh5yF0OyExXWw71cUKwFLJ5fX2adeZHg84bITjMPCccQwbdfHhQ+ntb5defFF6xzuV0efFd+SVsxPp0SOt774uzU5UT2dKW5vSC58nvfvdkn6vpC+S9EDSofRcJb1nV5qeSIcHWh2v6bnxngaDSvN5BqeHD3MfGMw4OQBLWM/K8w+k97xHevvnS8MVrezv696rn5Je/h1pb0+nk7nmDaPE0TEeZ618Pm+r9puNPfF0XgBwPs/MEkYI61wZlLZGraz6Ilxf1EjMIuTkSo3dUjn7g/xxzBWop+6UIBXSnRkjZdWX8yGkh3OD8RNg7UB33g8V0whFJLwo720Hw8cFwccyEaSUViT9DUlfJ+mTkv55SunvKles+aOSvknSH5L09x+zX8+kRE9tDEFw9fhUZa4Hz0bAO4q9Ka53APScRmyLHjuIMCBwOODEgP2MxxmQ3vnOjGfveNcgg9/2dlZ1x+sZBKVs85seK02OM0Pcvi9t7qgJ3miOuCXpbdLO/Qyk4zVpY1MarWl79opmszyIt7fzID6ZSa/v5nS4/aas71lV1D09/7z0lV8l3f9aZffJXNIvS//6n0i//Eta/eTvaHV6rNForp2dfC4PH0qfek06aYBjc0t67kEBjzf2sy3x8LAw2/lcmjVvlNEoxyaORiUECGeSlFVb7gfMDa8vhRdO7ZuQFO7dUCVuENbn95gURcweI0nDeXECodoTR7k+yHZkiugOQtvEqvLCPGw+R3Zc6fYCoHQFCKaU/p66wS4phyY9jny5pH9T1/VvNsf4O5L+mNqVo25T0dpOAdTcNgXj4+1POpw/uEOVeDzP/IghDABejC+TbX/ZujSQRhYjBwi+4z2jTAe370uj1czkZqcNQpwWQ9pgII3WpOGKVJ9K6dPK4byA1HFev72dQXCca02vHB5qe3aQszQebEqjVa1WtVaHb5z3DbYzGklrW0PpXe+S7n+dpPfbGXyV9Lt+v7Tzw9L/9X9Le3ta2dvTymCgNUlveXikF16ozuMXN7ekrQcNtZxMtLM7Ow+/QX2eTjP4knkiNQ6WZv1oejG32M0MvPTc8YQJQyrOMKmozR4gD6DCJI/UfuFVatsz06CoyNvb0s5eu8KMO0GwJyNECnhQ9G0GQOlqJvhXHnPdVfL5kj5h/z8p6SuU1eOfkvQbkn7wMdteKnE7nBftRBXx6R8pSd/lxXM121UXQimw7cAeKjWsT8VOiF1rRdnZsLWV7V6bG0UV1osvNpUMzjJCTD7dGM3O8sgDNaTiojw8kO79a0mPJL1NmWO8UmJqZifS5Dh/b6xrPD7IDg68LIPMugjLkYpNUO96l/S7f7faAIh8qfR53yr9O4+k3/zN3P58nlnnzo7uPT/Xveosg/HOTuPFkbT7ad0bvaJ7kyNt7lc6aex+s1lhxusbOYwHtrzaIAshO5NJrvTCveCewhQH9kG8xP6KCgjhSCNaQCqMEFBDk+D6oBrDDEejbP9Dk/D4VOkiwPHS7Vp3W+VSEKzr+h8v4HhdLK+u6/qXlMGwvXFKH5b0DQvoxzMlgB0P9Kkt8wosHmSLM8UDpqXyZvewBlenXMXxgXgenGw2srVR453dGGQAGa8XsNt/owmay63Uk+m5OnZus5qdKlu8KmUYOJF0KA1SZoHDYYMma9JoTWk4yPEr5yp2pdNZieFbG+c+pQc7GUTvPbziqr5Xev7zsi49XC264pgJKZXP5+HDYtvc388MdjjU+nimuiqxmQSCr42L99k91sNhZouzhkq5Zx+mlXQRfOZqq1ue18t6bLleNZp7fx7i1ADf0WE+TbJc5vNi9nAW6jnQ/vKMeei3CQhTSkf29yPMmPm4NsHHlU9KesMGTG8AACAASURBVIf9f1HSy5dt3HTyJUlKKd2qUCXUobOO5UxviKcYBoiK6x5JqV1GS2oXL3X1jKwVHCJ4g3nQ10YZW975zhyCsjLIREkbmxkoNtalyVEe/fv7Oj6szm1Qx9Pi2V1BZ60q6WxXWtmX9Du5xyeNNXRjs8S2bKznz2ik+WSq+f5MVTXLg3pS4g5Xnn8gbd2THrxFeuFtKrNmdMmO9Ny7pLfvSR//uDQ/Lao6TBN393itYYunmenO5+epeVyX7W1pZSO7fqu9aQ6RmTV5ycNCfk9nOR4Px4IHOLvZwkvUe1n/pLZ6GgUNgeckKUcN7O7m9a+9lr+bW5TV9mZfD7XBGUZ8KGDKc3Mbpa7rza7lNw2C/1zSF6WUvlB5VHyTpG++4T48deEtTg6wTwTuaW+bagfaevEFnB0MGLx9HnDNsWTbcBzU39VhYTYY1Hd2GvBrlml6nEfTeToCQYF5x/m8tLE6HmRAG6+XAL3zPLcDa1TtfLrGCDnYn57b2/je3m4yVLbulejpvT3pU/9K+rx/Kel9l1/s8VrD9E6zLVNq3LzNlXv0qLS3u6vTRweaTPKxJ43aC1auDzOcwLDITjmPi2yafrSf+a/UnrJgoLYJw9VOv0+eHSKVQco9p3IQqva+pJcr6dFrxcRB1AG2SEp3eZZRFbaJJfNvEwu8Sm4UBOu6nqeUvlPSP1C+n3+zrut/dZN9eBYkxgfy5gUE+e+ZHD7DGgJbRIglg+252kTMoNQeVKslzO5cOyU0ZGWQVazXX53rueH/m8FwMMiAMhicOwlmkYqycNqECs9OMsjs7eUDjNcLEM1OG9tiLY3WMojuV+eqJWl2n3kkvWX0yrkjRfO59Ou/Ln35K9KXfKtyofN3Nwf/lKSflT71Gxnkqjqr4FK2Yc5mmfHtH+T1kjQ5Ur37SLu7WeN/9KjkJpP+tznN1wgb4cOHxVYICFKzcPZy9ga7/sVLD+bH/eO+xomeEFeJ3Z4ISJFnzHLPEuL+41ABEIfKL1aYJ+CI3BUAlK5XReZnJf0ndV3vNf/fIunv1HX99Y9zwLquf1rSTz/OvrdJ3HPoIBi9imw7U0mYB/hGKg88qozXB3Q2yGCYq8QYDi1TArWWCs6Qvvk8h40cT6f6/MlvKu3cz4AyXFXayOg5mM/OA4uHh5XWd3eLN4NGd3elvc80HV/LG89OspcZtbgBzWGTCywVIJxMpM2XZ1odzs4dENKRHnz0f9cXfvHPZPvfe96Tmd/kOKvt05N8jMNGhR+r8V4c52MdHupsOldVZdX2uAkwPjyUPr3bVMlpRsjWVu7T1lbxmm9vFy86IEjBhek0X7c35u3cbJ/ljekV3GHBPceG5+DkNlwPm+LeSxfL36MCE3RNML2UwdNrR94l4HO5DhN8CABKUl3Xn0kpPb/APt0ZAZwG9lsqNwU15VD5YV1XTpZnYhzmCfZS6ahJnmfqtQRPbbkDoKe9YQ/D2H/SlLlaG0lvHR1lNrbVmFemJxpMZq1sjLdWj7QFYxytZta1t5fVYSjnfN54mg90PCnMMwZIo5ri14C1Esw8HEof+9hMo9EntLHxifMUt50d6fOez46drS3l0B5O8PBQmhzp9dcqPXqUjyXpvCDDdFrS5YgLRCW+93Cke1Wlra25ptMSNJ2270mzE+1MZnrwIHuwNzak1V3pjWkBP4CQe+11It0+jAmkUqlBGJ8bPh4aRWgL6jThNg6gUlGDdcn6uyTXAcEqpfTOuq4/LkkppS/Q7c6nvnHpsttFVRZbks9pHNuILJJtsUfNVZgBN57wPk9PO+9LQ+TqqjCz8xU4GKpiF4QNHh1KW/v7GSwBwf032sUFG1vh4WFmYCemUvOf8BSAqXW+Vc7kkDKmed8psnAyzQztbW+XtjYatlmdSdNjnUyqC2ovrI/wF2ykhA1lMN2WqkrrVfZ6D4fKXm17i7Df6TwD4XTaLpQRwUtqOzx8GepvLLEmtYGQ5R4iBRhyr6NKfZeBz+U6IPjfSvq5lBIhM39QeT7iXp6wdAEgNsFK7WKq6yoePh8oUjGYr6g4V1bV9gxKhU1RRZnSUhRIIOsAbXV9Qxn8xmuZCTYqLABIe4eH0vi1me7Pf+ec9Z1OK53M2ulnroYeHhb21/KlHDbEbdIOSfHg4KPm2BQRlaSdT2ZP6YMH+Ri/a3Sk1dGqNDvV4d5cB/vSyy9Lv/VbebuqyuzxhRfyuVMajGvxloeDUjqneQmsj/eL15nOqKSvkQtNCS9qI/oLzWNEncVR7TqqwP6sRBADWOf2YYDXKnGH5Av3QJjlTUGwruu/n1L6Ukm/T3kcfVdd17sL79kdlfPgV3W/safKCfF48pgNrsn6OgfNgcrk36hGqEBkjKxIWqtydRSfQ8SzDdYfjKXBShnsG+s57m42a4on7J8zNooeFJtd5rComQClsz5UYFiZq77sB0BKpUAqQAgjnDcAOLHznLwsbb9a+vWOSbbq4Px47bUMhJ88zPu8fVqcHc8/n8OEcBydO4SmObBbDx7kF8H0xOybx62MDV4i29uNR7kxS8YCpa6+utf3QO1AaanN+ngumPmP+8/LEmeY25xZVqn90r3LclXa3BfXdf1rDQBKJZ7vnY16/LHFd+9uigPhKPyXspcPEJSyjXBVpQIzg0DKINik3Z5no1Rql3Uaqti2pAxS2LvWh6vtlA0pD/rXPq3TRwd69Cg7EQ6agxAeCJOTil3x8DDX9TsxrZhK1NNpBsC9vbb9bzaTDicZ3IbKgE0XztueF3YFIyZX9/VKOv613JdPvZrte6ezEoJzPLXQpFnpF2qw1Kjjj+ZKg7m2Zie5YMMLO9L4YWMHaLzfk2NV1ey8jiFq9fZ2vqbVbuObsXszUQY7QlSkYv7gisfMH9m6ShkAmfEvmkWc9cmW33Rs3LMsV12L71ZWez/Ysa6W9DUL6VEvktqZAW7/c1VHKnXgMK5j72M9BTTnKhMWDZSN7qjTG1a81GPgZjNpY+Mgq5HUBJyeSJMjHb92oI9/XHr11QxsZ/NSUdrrCkpF7SWjwdkeM8DhAaZwgZSXn85LOTEA+2xeGJLPgOYqnhcBOJV0+vHMAL2c/nSaz3OrOYaX2zqa5JS4uiq2yVwwdq61+Tyz4w3CdZqQnyZi+XyyKHOuwChTVUCtsnPw4GoHM/LIeSYQ7rubTLqCnKPN8K6zvi65Km0Ou9/767pumaVTSuOOXXpZgMSHFgeHVEIePE4svunnKiX0fd4Ktk8qrAv7nJQBoKoyOL4wfJTtiURQV5Umk6y+olpKebATNB1jB/HoAjLESEuFBX56V3o0N6CelvAOt3OiPsrOVyoVW1iGc2CqPCfEfCJ9ZpIrq6RBUcXVXId5A3hv7Gdmu2L9u+A8mp/mUJvzkzuVqvqcSeJUAvz396X9SueVXzxAng8AeB011WM9u+yGg7C+B7/L5Tqs+KPKkahvtqyXGxIHOwaQ5xv7drF0Fl7IoWwukwaghg1jI4vkzGxy98aH2SkiSfOznBFXFcYjFYcGyftSWYf9zlmSVGr1HR7mSdNRDTkXavIBfF55ZyV8XyXU45Py8VJVlsPCZmoqRk+LR5oAcuZVadkHdVROZnIkTY91Oi/bMxseBVidzUZg4jfnel3wwuOLne/NnCe9XJSrbIIvKFd9WU8pfYnKeNpWu2RdLzco/sBz88gh9WKsbvPzEu2eg7zS7Hswk4Z77bk2xuMMhtNpdh5sH8708PAVrY6yTW06zUwJRwoOgfk8m8eY48M9uitDnVdmYZmUAXh3LxudX7NzO1IpIOtecnJdOT9PHZTa9fkcCM5UqjjjiKhs/5mkzcblhxkUM8HKME8qRf6wJkfS/rwEZO/v6/VX5/qMxR0SCbS/L+0qp9Ld49oPpdG8Pd0BbJcX2tA+ldrFF2J2Cfc8qr/+3Uu3XMUEv17Sn1AucvBBlXuwL+l7F9utXi6TqOZI7cEzUBlA2J4o7kl8odsYAQAKwhAPh92M/F2y3ohz3t8vajCqpQc7k3kB+/IJhOb0pTnebJYfqteVi24BglOV+olSGdycH+fuk9j79VDH9gSfY0pwB9SZMjCdvNoOJN/ZyQC4NlZhw7PTHPy9t6fTaaXd3WwfffQoAz9OplWKr6oETNcqZgMcJczv4XZOyUwW4Z5dNgdwF7vs5Wq5yib4IUkfSil9Y13XP3GDferlTSTagCi95NM5kklCfKCrxp6ZgOluruIVJT8W+x2Tk+P5JZNjFpge9rK9PenVwwxqztLcc7khab2SdvZLDT3frlKZYwU2RBVsn//iSCU8hO24LrBm356CA3jK2c+nIziSNPhkCXMhXnA4V5Pv3PR2MtHxYbaP7u7mkJvJpMzDAqP+9GvSxmFuN05c5QURYIPYBmfWNzcHeLVxrlkPfo8v17EJfllK6R+G3OE/W9f1f7fYrvVyHXH1x2vCAYgMbrZz1djLeU9VgO9oUux6b+xnj65USsrP59JkVhL7V5VVZ+boeDSXXlFW/xiosZI1HtEzFTbEBEAeQoLN0wf2iq0/VgEzgothw2TKOHiQiuh52s6ocMSMJW29lr3XxD3mCaCmem76ijQcqp6Vklt8YIE7O3nf8Vh66/PSW1/OBzxn5CNpMJdmVWGJEeA4L9g0tQa7col7eXy5Dgi+v67rc/W3yR3+w5J6EHwGpEslkjLrAKSkdr067IEXJt2eNrFs4wJ2e42qWimXkcc+5XFta5JSgyqUUd1VSdQfqKjinhcN48Fb7RNHSYUJwmg92T9WbB6q2DudFbupAKFowVBFBeVDwPKpcnzip17LL4Td3Qxcn95lTpL5eQgPcYEIDiCvR3h/Wzp9VCZ9IiyommUgJ3zJnSIAocf4ddn8evnc5DoguJJSWmum21RKyc00vTxDEgHxRG0wIEUrpmqtqFQXGcJolAflgUodujhBDzZIpgOAaVGyyTMUnM0xyH3eY8DYg8PZ3+1itEFVFM+n9WIBtME5xuosHkAc4+t8f590CQcQs9FRSJWpPXEUz2yfE8uQGTZ2U/eUo5Z7MVM/Pvc0fvfy5OQ6IPhjkv5hSulHlZ+5PynpQwvtVS+fk/iAcZucA6GrzFP7TFSYWaVicwOUPN/Vj4U6B3vzwQqj6QIiZ6h4e/lgK/MCAFK7JNRc2b7ok0u51xe1e6JSUILywrVKqh2phOsqYD9QSQfEcfTGfnZ+kEaMnfTgsASNExxOwPnubmNDrTLzI0xoT9lu+oZKDCQ2QM4zquu9PHm5Tu7wX04p/Yqkr1V+Dr+vrut/sPCe9fI5yVWeQ9jVzLYDBCnbFVUwgHOgUqIJVhlLCgFEHtgNEBIsvK2S3eKqqHRxNj1Xb6XC7JhgfqSixnIunBsxlPTVbYW0TT+HKiE59ItKNXhz0yAHlE+nOeVubVRshtOpzlMAqR+LE+lgZl7fKv/eV2bax9aPoYqTxONBe1mcXCuFsK7rn5H0MwvuSy83JA5wc/tmndsJAQ0eFA/K9jhEbxtWhsMDxwvHZDsmGgcgp/bbgQpxFkr2C+2zX63MrAA+zidWcHbTAH1wFZn+zucWVC5ppVGHpXYNRK8SVlXSxGoIegELrjfs1J1LHsrj59bb/hYrbwqCKaXfJ+l/kvRvq0QpHNV1vb3gvvXyBIXB5BkLSW0Q9ABsT8taURsIPGsDhthVJ4+HRWp7h4nLQ/Wj4AFqLvt5QdihMmjiXYUJEkYCQz1RsRcO7Bgw1uNmvdsP6RMOH6mAcjSAE3LDREtn84vVec697eqOYYTJwvgc8N2O2bPAm5HrMMG/rjwh0o9L+j2S/rik9yyyU70sRgA7L6XVNWOdh9DABIk77DLQe1jHTCVuEY8t2xDz5zJQu+graizbOUB4APi6Sm2+6Hl2T7AHVdM3B0f2c5CnX6j9ru5jKpg3ThCcGthNuXY4OtyD7lNeeuA3jJH74U4lv069LEauqw7/m5TSSl3XZ5J+NKX00QX3q5cFiDM11EECcd/M/hTXebUTV0kZ/APbpmsAn4U2uvoJQMdQBC8nD6NzVRKHCtt53CEgGMNM3OvMMT1NLQIStjsAC1XeC1c4CEpt1ufX5Mw+8Xhx216evFwHBCcppZGkX04p/WXlONjO+Tt7eTbF2dtchUl5NZlZx/Y4N7DROTBJWR0lDczVP1RUfkslrtA9xITmIDgjpLZ67jZJgCfmC0tt9kkWCn32clUj297PGeBkknTAFPCU7cvLw+2Z5wUamt/MFgirXFOb1fr1dCcV0gPgzch1QPAl5WfqOyV9l/Lk6d+4yE718uTFGRvAhb0PQIoeYekiA3JBvY3TNkZnhVRCUdgHRuYDPYaGYB+kdiDLj1RiEemjA5jUBk2vt0fg9mVzObvt1Gdo8zjHUWhfKqCJrZLwncqOJ9vW7ZGA+psxwN5GuBi5TojMbzc/jyX9xcV2p5dFiQ9wt7/x7eKDMcaqxYGJbc1ZnLdDzCBODPrgQc0ESeOA8Rp7UmFjACvTC3A8QBXGSr0+VE8P3h7bOpwsBHN7/6SSkkfQubNhD7AeKKtGACIFGmKAeBX2g7XCar0PvdycXFVK61d0xaxydV2/byE96uWJi6tgAA+Bzaf2ifY9/x2FZeTrDu07tuGDG+DZ0MWiCB7T5xkgeFaxsQFOrHcnwlBlfmbvq8+74R5brg0ebw+jOWyuEc4b2bZMb+C50TiPIsh7BRsHWhw6sET65cHmvTq8eLmKCX7gxnrRy8LFVU+v1hwN+4gDmO8bgZHtfMrIro8PelRQ9oFhneiiyjpSrsE3VnsODtp025zXGwRYvOAA+2K/ZOoBphrwieyPVKrNUDzTaxd68QkXMnGIkfQXgwMxfUGNhm048+4B8GbkqlJav33Zul6WS1wlw0gfbWVd1Vp8Hy/uOVdb/e0arNGm6AVCAVPPAiF0p1KbVcIE3YkhW+9sLoId4n337dwM4CFDABYZKexHCp+fm9f98/8+sAa2rwueeuliVozv26vHi5U+WPqOCSDmTM7B0NU4B0AvnuBsCgDytDVnjfzGFse27OdzbdDettrOB1RYrwYzUmZoW7YeW6cD9bBpb03FeePTcsKA8SgzTem+sjrM+eOk8RAXQK9S2zHk54X4VAAOdh62FEOG3DlynTCmXh5P+mDpOyZezCDaAGPMHL9jYLFUsjYie0RFjSDIfp5NQkEDgG2oDGw71sZEGZDwLEeP67qKPVHKaiwgTbbHlkpWCiXG3JPt2TGcE0Dp7BfWCWB6bUJshDDcmAUCeDlzldpVZE5V2CcA3svipQ+WvkPitjOv5BxLUEltZwMMi8FNWA0MydkJ4R+yfaW2UwAbXMwGAdi8aOqRSpGB6L31UmA+x4qfX60MhhRGqFXCV7xv9NVfDoC/Xxe3Y3rMJOE5Y7VBkOtNX6OTyVm4M1hslC49C1yM9MHSd0DchuUsI3ox2cYZDsvYhuwNB08P64i2OKrBoGKyfsvadLClhiHFUAlRcQcN7OxApeCqbHvY1ExFhcf7684K5vWIKWp+vv5BXaZQg3vUAfGtpl0cT7SNqutlyfx4Ll0xgr0sTq4bLD1QHyy9tOIANVBmYmtqV1aRCvB4IHNXmAwqr8+JAVDNbb2HsMAYu4KJ3aFAvF8MUnZW5tvtq22rhAWi0qJS7zTn7aqp2xyjHS6q+KTlAWTYAJ2duirv7NWBlv8+JYDbW70//mLqZXHy2QRLT9UHSy+1OJujlL2X3yco2AHHHQzukcW2BSOSusHEq9J4TN8srGc/7GIOFJ5dQdseh9jlpeYY/AbAnHl6nm/c3wXV3T3bVI0h+4br5bZPz6V2+6vCf7JipDZ77MHvZuSqYOk/JunFuq7/RvP/FyS9tVn9PXVd/6830L9enoAwcMnD3VQJcpbaTGxFJZ3MGclasx/r3DYII8Sm5sxtaPtvqQ08gFwMTdlXAUGcJa7KVh2fqNrTlrM18oY9XMe95bFNqW2rhK0dqTgzfLuqWVcrTx06UXHE+L1wlZ7rdK9Z77PhRfbby2LkKib4PcpeYWRN0u9VHgs/KqkHwSUSH0gOQA6EhK6MlAGL9e4QweAPkwSAYJLYy6iyQvs4JlzNdTXbY/PwzKIKd9nrACdXvfk/sfZ8H78WEQQ9aNwdFAA+x6BeoecuD5trgRp/qDaQ+zE9WNydM/TR85WdffeyOLnq+o7quv6E/f+5uq5fl/R6Sql3jCyZACQMYuli2hrijgDq4HkMHut80qUTtZ0gzn5W7cNscCfWlnuI3SbnbDI6coYqwOrpZ2cqDg/vx4YKo3Tg6WKB7OPB2sz6hk3TC7pKbXsqMYZdLNXB1x04ACogGBlpL4uTq0DwLf6nruvvtL9vVS9LJz7YYXMEMbvDwcHOwzrmygC2phKfJxWvKYHGsClX5fhdqx1e4kVN3cEBOBEUvaH2vMKu0m7YdlRkIT/ZnRYxr9nTBSP4cn2Yt/lQbdbYBVAOYJF5Ont184G3yTX2/XpZvFwFgr+QUvr2uq5/2BemlP6MpH+22G71smjpUs8Y2D4znNRmYj6pEQOZYGFXZ53dASSecsYxnW1KpaoL7GiorJp7UQQCrrviG/38vE0v0+XeY8BtbB9AE+boYTexWINfP8wJnEOli6y4UsmxVlgutVloHypzM3IVCH6XpP8tpfTNkj7WLPsy5Wf2P1p0x3p5sjKwb5hKCsuldjB1VAthbBRH9RJQMMZYfQb26LY/jgcI8t+BKoLoqooNEo+s5+Oy3Pvgx3AAZnsP4HYvtrNPXgp+PrJtuzzX7kV24HQAjZ7iy65PL4uXS0GwruvXJH1lSulrJL23WfxTdV3/oxvpWS9PTFwlRWAkgJTUjmHzwgquOvPAvGFtHSrHxREr6Mdk4ONUQdwOGVX0TRWGRb/XVJwtp7Y9LBTwhrU5uBESRBWaefg4QAGA280+TCzvOdYAVEwl9PNwx4eDnIO9X5+57SO10+aiet3Lk5XrxAn+I0k98C25uB1NKoPN5xL2wcjgjuwOcCFbQ7pY6dnDb2jPZ2OTShwd7ZI763MW+8N5Ytv63CGwUM4Fx0VkVl6lJYbAOMjEtEJCYeJ14IUwDPvGtDg/RnS6uLqMSu1hRd6vHggXJ733/Q4JgOdxagrf0RblIS3Y9dyhwDb89kF8mWoqFZWW9cOmza5yUt5/BxKfIS6mqTl4nIRt+XhfEQ/foUjqxJYpbO+2PL8O7gih2ISr1TE0R2rHBfo96cFvsdKD4B0QH/gUHGDSH6+OjI0Ne6HUVue6AIZtKGLqABiZD8fAi3xZLKBsn9geYOf9iNMEwEQ5Z8KC3L4XVXwHJAdm3yfaFGMh2sgw8VwDplSq5rp4NZ8+HvDpSX/d75B4KIjb1Hx6SrfVebCzSzTau0cUu91x2MftZc4ko9fY22eZs0ZXOdluZp8uputhPw442B8J4j4MffB+RwDsAnlnlf6bQHPvvwNrdCT1zO9mpQfBOyqXDTRygrtAKf6OrIe0PGyAESwvG/SxT/EbAPT0t8u8p5d5YX0/HnrUc5gvjJBzuswuF89p0LGcdThyPCdbKgHd8VpHNhmvRS9PXnoQvEMSB5LX/kNNHth/j8dj8EYnAE4C2sKxQSZHtG+5LcxjAf2jsH0ENgcxZ31x2+jw8P5Hry3tRrWefWMxhmhLjE6n6CDBIbTWfPBUuxc5OpN6uRm5MRBMKX2LpP+m+Xso6T+r6/r/adZ9k3Ku8t+q6/qv3VSf7qL44GKCoxSW46mVCpBEEIx2QtRgwIfJhgiU7qpk7XY4AMjDRFjOx0NL6IvbJQHDeLwuR5CDooN4BJ8u1kdfvU0Pi3HAZj+3xUrF5NAVvxidIT0gLlZukgn+f5L+/bquP5NSer+kH5L0Fc26b1IuzvC3U0pbdV0fXtZIL09OnPVFViRdtIX5cr590JO/6wUX3L7n7XWpkA6QUhscveK0i7NXnDlejsv7i0TV3lmcT6XZpa6z/WVzLfu5SG1nS5zkHscJbTuAs74HwMXLjYFgXddekv+fSnrR/ntZu1hVvJcFCAOO9DfPofUBHuPjHLwot+UB1kx36ZVkfGpK2o3M0tv12L2ohnZt7zF2UrG1eUiK2wIje8Qm6CXwvVq27Fw9VS6aErxf7vjAEdKlakfV+lRXg2svT16elk3w2yT9jP3/iKR/IenH6ro+eDpduhvCwCRkJIIggxIvMYPR1V6pXRwBIHTg6nIowITG1kZ0NjiYTZXtJmSBDHQR/DZUnA604RVuHAApfU/KH9fAA6MdvJz1ef/cCSS1WS9ZJh5241W1/frFCjmy7zjzXC+LkxsHwZTSVyuD4B9gWV3XH5L0oY5tPyzpG26ud3dDGFiuBjvbw6YndatjDgRdKnRc5iDntjAkzk7ntj+fFtPb8vhBcooBaZwzZJKwnMoygJPX/Iu2RPrlAOXATvaLnw/Ml497mCOYYYdlP4K5fQL4Xp6spJSO7O9H6rp+SVowCKaUvkPStzd//7Ckh5J+RNL7m9qEV0rTyZeatuo32byXa4oDnv9W+B1VPABqpFJKy4sdePtRBXWBMaFGAiYx2JllnsUBoHn/fS5igAcgPbG2NpQfQKkUO91VO2bR1Xa3ccYCEaj5DsoIbLfWxfOnj5wzx+FcHLx7ebJS13VnHdSFgmBTmp/y/O9UVntfquv61xd53F7eXDxMBfGUOQboUO3J0gFBPMsxpi0yH2c7qIQOBICBq+fY6LzStauttBsdKwOVajMxtQ+75FAZwJ0RumPHr4WX1pqrHUMJaMHcAEgcK2/m1IhmBto7Ua8K37TcpDr8FyQ9J+l/TilJ0ryu699zg8fvJUi05UVvKQ+HV49hYMPQvIBqZDUsjx5gqYAEBVkdlGFvXcDnKvMotOOCSorMVeoHAnZbytViLsta8ao3DmqAlOf9euEGmC7XzGfwY3v3Hsf4wh78blZu0jv8pyT9qZs6Xi9XSzTEXwaASByoEQRhTdTgc5YZw2JooVxZxwAAEiRJREFUJ6mkxHk5rCp8Yt4yAIiDRbYvqutM7cKvlTIA7qrY8xyQ19SuTiMVlZeJ3QHbrhnkcOLMm365N7vrRSNdrCDTg9/TkT5j5I6Kez6l4j3dVs6nBUzcW0oKGKqmMxx3JgzUdkpwPKQrBAUg8UKnEQjdLumFD7DvwSJXbR8/xly5DqKrvkzuDtjVtq2DpFTU3lh01hk1/x20I3j77HoeltQD4dORHgTvoLh9zx0J28qTh2+pAB5AGNmPdDFjgm9XTxnkfLsXFnHG5JVVEPaJ6XK0P1EbhN22F8NqFI7hQO5xhB4oHQHNA6lp17NjYv84R0KPmGMltnGVDbGXxUkPgndYury+DoywOc+gQOKD404RqTAd6SJDcibo4BlBNkrVsT4yvi41Pzp8FPrRBUQOYpeBVLSjsv2bsTlnt9gEewb49KQHwTsqccCTpuNARUBxnIvDgRMBPGE47uGMLCrOaBdDTKKH2bd16Yrtky6CqzNXZ2A+oRTqKHbG0+a/F1T1wOZBWMakTM4S4/nTLml9MYi6T5N7OtKD4B0XBl2tPDCldskqj6GL4Siu3q1YOydqA1NkUpEhsg1A5EVSHXwjUESw6XLq+DH9vJzZknmyo5LLO1epLxhnmutyJnka3VwXwRChD7PQRi9PT3oQvOPioRrOkGA6XrLet3eDvk+i5JWfpYs2Oc80cZbk69gvOkMcaBxMnOnFwgbO2nwCKY6LR3tH0gMVzy5zorBdDNiW2g4aV7tJzfP+RS+3Ovbr5elID4K9SGoPVFdfuzy1zn4GajNBZ0pVWOaANuxoM66XCsh0zY3sDpZo++uyH0ZbpGeF+NzElUoWik/4Tixg1SzfUsmc6VLrT1XiJkmjc9Ya7Y09ED4d6UGwlwvioR8RFJ1hUTjVA5Ujs4mMj0yMCFa+P3a5Ddt+VcVLva9iq5vbfn7sSgWwnHk5oHqIEHY6Ygtp3+MRAUJCbJgU3kNrOGdnxJ4mR+wh8554/3t5OtKDYC+S2g4E/+5ySERPq9QONPZMDWeY/Hfw6Rr8tA/IbqoACVkfXU4Hby86YVz17JpljlAgQBCwS8qB1EntEvzeHvt7W4QYeerfwNYDiD34PX3pQbCXc3EAiQzKmZt7hvEeV/a/axJ2VOsYuuIqaGSMmypsCw/2QO1Z22LsoH/cueK5wEyu5NN0wjKlNoAhTBkQARRAA9SYZIrsEbbzyau8SIK/fHp5OtKDYC+XSvR+utqHXS5OdA4DAyg37H+0LUqlGIOroLTnObr+H0CL8XXuPXbV1+MbncFeNsdxnGzKwZAyXaT8TVVS6vyaOEgPVeZU9iKz0RTQy9ORHgR7uSBdoTDRKzu1T9f+W8oA6Hm07O/MEjVXtl7K4EXbDo58Yu6wh+xIJXYvhsvADtkeVTcKXm+pHSzutf5gi1NrJ9r5AMc4b0svz470INhLp8RYOK9AzRy9qHxSOzxkrLbXFRDY0sX5M2BDsXjBvFl2KulIJbCYfWGCDmCeDcJ2nIN7ZAkBoqSWF12oVCpT48A5VZlHGZsnE8jTVq22nTN6iyMb7eXZkR4Ee7lSGLCwITId8NC6ygcIYsdjFjepqJgeJuKsTMqMcCO0KbUr0jjQdnmXuzJSIhhO1e7LSO15UBT2c4nH4hhUj1kNfe/yfvfybEkPgr1cKTE8pusTbYcwQNLUYnseHweQEHBdhza7gMlVYXfKeOUaBx9XxxWWx2o3Lm6bjFkmXTGQKXz3au9ySA+CvbypzMO31GZKBA6PlbMudlSCiKdqq7oesOxOjHUVO5w7Ijy4eUMZKKl0U0k6UFaXo4Mk9tmBEOBlwiW34aGax9xe7JIwV/eUSwXEq+b7RBdDePqA6GdTehDs5Uq5jInhdACctlXm8LjXbO+OgDipk9QGFY/HQzwHGTvghoq6TZs4UMjKcFWUb9ToqIpTg5CZ9WIxBvp5aNt73B+MdNXacOkB8NmXHgR7ubYw+AEaBvxYGfiI61tVcRocqcQOeiFSV4dJgTtVO7PCc3djfB5szh0oddhWKnm8Do4OwoSueMFUZ3CA3SDs63ZLrgXxf1yXriDuXp496UGwl89KhuFbKjY61MGpipoKg2L+YLZ3QItVmt3Lym/3/LpqeqD23B7evw2Vycxl+ztDnCt7fgf2n3V4uV31dbbozDYWnehBb3mkB8Feri1dzIb0NqnEzM2Uy9gfKHuRCSB2O6BPRIR0ZY0QBoPDxOsA4qWeWtuAkE+MTt+i5zjaCJ3BRRDDDOATSXkBh4lt288Nu1zSg2Avjy0RLGBJFAcA/LwuYPSaerygp9ghTHLk9kU+qNhdlW48nQ1VtytcxdVylvl39G7HPvox43wrvSyH9CDYy+ckgJeng02UGVqs9tKVN0wsYaz4DDihkq4oq61zZTUb1ukz3insh/MGNuggGENtWB+zWaS2E8XrLkZbYVdYTy/PvvQg2MtjS7STSQXEcHbELBIvRBpnjSMsJU58RAAyVV4O1F201MGH311ZHLJlTNZehf2kwgIdBD1A2uda7mKxvSyH9CDYy+ckETycJXnQtDtDnDH9/+2de6xdRRWHv19voaW8sVdSKKQQXoKJiC1vYwOE1PgCLEqIaGuEoDxrDAh/GIkxgfhAQ0VICrQqREAa0GoqKBRUaKGtLaUUsbYFGxvFoAkPobnt8o+Z6Zm72ee+uOfsc+5eX7JzZmbPnr3W3eeuM7NmZu2+wnVlQ9bUk0trCJOxLFt+UjSExZD4+bl8drv40vhi0IZcnjweYR4b0elO3Ag675pi7ycZh3w5TTIW+cRGMnxpQiMZzzSMTft6E2k9YT5MHVdypLr5spi8jaLcouE7TO2mXR9ppnd84fpUVtbDdLoLN4LOqJIbB+gf0greOataXIs3kTA8nUBjzSE0JkYm0Nhf/FZJO/nwtBj4NNVLfsB8h0o+9M39i2nNYrO23Ph1P24EnZbQbJa1zPeWD1dTeKu07nACjQXRqSeYfIn5kpdkkIoGsOgDLK5vTPfPd7WkhdcDLZmhSZnTfbgRdEadMv9b+iwOnYsztimMVXHmNvkOU6SZ3K+YR3HOFzEXfYb5+sSUF/0nWHK/ZD7jXaaXMzZwI+i0lLIZ23wnSOoFJgOTtsD10BgC5/7DRL6XuLgLJF8yA++MbJO25uU7PPL3giQ5ms04O2MLN4JOWyhbIJ2Tz+6m4WialOij/17ivLeWjGG+3S33FeZ7iBOp7TRET+0WQ98X5XbGJm4EnbYy2ILi4pIZaBirZKCKkV6KUaqL/sic4g6QYttu/OqHG0GnEgbyryV/Xl+hXplPEd4ZMDWfAMlni9O1ZYFey9JOPXAj6HQkZfuMyygzpsXwV3lPcbB7OvXDjaDTsTQzSs38ifl1uxfO+7Y2pxluBJ2uZKDhtC9lcYaDf18cx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bgQdx6k1bTeCkmZI2iFpdlY2T9JqSZ9ttzyO49SbthpBST3ATcBvs7K9gBnAicCF7ZTHcRyn3T3BK4AHgH9lZYqf1mZZHMdx2hdKS9LBwLnAGYSeHwBm9pqkdcBK4DsDtXH0CSe0VEbHccYmT65e3fSczNrTAZN0P/A9M1suaSGwxMx+Mcg1PwXOi9lJLRbRcZyxzZtZerGZXQQtNoKSLgMujtl9aQx9J0eBLjGzB1smwLtA0htmtmfVcow2rlf3MVZ16xS92tYT7HfTIfYEq6RTHtBo43p1H2NVt07Ry9cJOo5Tayp5x4iZzanivsNkcdUCtAjXq/sYq7p1hF6VDIcdx3E6BR8ORyT1SPqzpCUxf5ykpyQtktSVfydJh0h6TNIGSeslXRXLD5L0qKSH4mL1rkPSLEl/kbRR0tdjWVc8M0kTJT0taW18LjfE8oWSNktaE4/jY/m+kn6V1Z+btdVRu62Gq1s8NzOWrZf0eFZ+QdTt6pYKbWZ+hN7wV4F7CBM2AHcAvYQF3rOqlm+EOk0BTojpvYEXgWOBG4HjgE8Al1Yt5wj06gH+BhxOeMXw2qhXVzwzwiqJvWJ6N2AFcDKwEJhdUv964KaY7gVejXrvFb+z44GHqtZrhLrtBzwPHBrz783OPRif9c9Tm604OvbXsp1Imgp8DFiQFfcQdrHspLG0p6sws21mtjqmXwM2AAcTdNtJ9+p2IrDRzDaZ2XbCP8mn6JJnZoHXY3a3eAzklzJgb0kiGL5XgT46cLfVCHS7kLBm7+V4fbPdZC17nm4EAz8AriH88yR+CPwaOAV4uAqhRhNJ04APEn6Z5wO3A5cCP6tOqhFzMPD3LL81lnXNM4vulzWELaSPmNmKeOrbkp6VdLOkCbFsPvA+4B/AOuAqM9sZf9jSbqt726xCU4ap21HA/pKWSVol6fNZU4sJuq2MuraGqrvPVR/Ax4FbY3omcTg8lg5C72EVcF7VsoySPucDC7L8RcAtVcs1Ql32Ax4D3k9wXwiYACwCvhHrzAZujueOADYD+1Qt+yjpNh9YDuxJ2ETxV+CodsrpPUE4DfikpC2EYdUZkrqxd1SKpN0IQSvuNrOOWJIwCmwFDsnyUwm9pK7DzP4LLCP4MLdZ4G3gLsKwH2AuYchoZraRYASPqUTgYTBE3bYCS83sDTP7N/AE8IF2yll7I2hm15nZVDObBlwAPGpmn6tYrFEh+pDuADaY2ferlmcUeQY4UtJhknYnPLdfVizTkJHUK2m/mN4DOAt4QdKUWCbgHOC5eMnLwJnx3IHA0cCmdss9FEag20PAhyWNlzQJOIngu24blSyWdtrGaYSh4rroowG43sx+U6FM7xoz65N0OSEuZQ9wp5mtr1is4TAFWBTja44D7jOzJXHZUi9h2LiG4LMF+BawMEZbEnBt7DV1IsPSzcw2SFoKPEvwyS8ws+eatN0SfLG04zi1pvbDYcdx6o0bQcdxao0bQcdxao0bQcdxao0bQcdxao0bQcdxao0bQacfkg6UdI+kTXEv51OSzh3kmmmSRrS2S9IcSQdl+QWSjh3itTNT6LNWIenJ+DlN0rDfix31mz/6kjmjhRtBZxdxNf+DwBNmdriZfYiwG2NqC287B9hlBM3sS2b2fAvvNyzM7NSYnEaIeOKMMdwIOjlnANvN7LZUYGYvmdktsKs39IcY6HK1pFOLDQxUR9I1ktbFgJs3SpoNTAfujkE194jRRKbH+rNiG2sl/X6oSkg6UyFA7jpJd6aIJZK2SLohtrlO0jGxvFfSI7H8dkkvSZocz6WwUDcStnetUQhk2q+HJ2mJpJkxPVfSizFA6GlZnV5JD0h6Jh67zjkVUnWkCT865wCuBG4e4PwkYGJMH0kIcQShl/TcIHU+CjwJTIr5A+LnMmB6do9lBMPYSwiXdVhevyDPTApRf4CJ8bqjYv4nwNUxvQW4Iqa/QoxEQ4hkcl1MzyLEr5sc86+X3YvQg52f5ZfEOlMIe317CYFP/5TqEQKgnh7ThxL2dFf+3Ot++N5hpymSfgScTugdziAEyJyvEBp9ByEWXJFmdc4C7jKzNwHM7NVBbn8yYVi+eYj1E0cDm83sxZhfBFxGiBkJjZf7rALOi+nTgXPjfZZK+s8Q71XGScAyM3sFQNK99P8bHBu8DgDsI2lva2WsPGdQ3Ag6OeuBT6eMmV0Wh4UrY9E84J+EUEfjgLdK2mhWRwwvAvJw6+fXDcTb8XMHje//SKIW99HfnTQxSzeTexxwipn9bwT3c1qE+wSdnEeBiZK+nJVNytL7AtvMbCchOk1PSRvN6jwMfDGGS0LSAbH8NcL7T4o8BXxE0mGF+oPxAjBN0hExfxHw+AD1Af4IfCbe52xg/5I6RTm3AMdLGifpEBrx8VYAMyW9RyGW4/nZNQ8Dl6eMspcNOdXhRtDZhQVn1TkE47NZ0tOE4eS1scqtwBckLScM8d4oaaa0jpktJcT8WxnDen0t1l8I3JYmRjJZXgEuARZLWkvz8PFnStqaDsIrBOYC98fQUzuB25pcm7gBOFvSaoLvchvB6OU8C/TFSZp5BF/fZkJ4++8C6V0u24BvEoz471J55EpgukKI+edphMpyKsRDaTm1J84e77AQp/AU4Mdm5r20muA+QccJM7X3KbyreDtwccXyOG3Ee4KO49Qa9wk6jlNr3Ag6jlNr3Ag6jlNr3Ag6jlNr3Ag6jlNr/g8ylNTwzmi16AAAAABJRU5ErkJggg==\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 1.47 s, sys: 155 ms, total: 1.63 s\n", "Wall time: 11.2 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/deil/software/anaconda3/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 14.9 s, sys: 248 ms, total: 15.2 s\n", "Wall time: 4.26 s\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "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 2.67 s, sys: 15.2 ms, total: 2.68 s\n", "Wall time: 834 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 1.29 s, sys: 8.82 ms, total: 1.3 s\n", "Wall time: 339 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: 1435.66\n", "Excess: 941.34\n", "Excess / Background: 0.66\n", "Gamma rate: 0.18 1 / s\n", "Bkg rate: 0.23 1 / min\n", "Sigma: 22.14\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 .. 5.000103.91766798597166 .. 456.996399239735071.096e-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 .. 5.00090.36639418669868 .. 325.95579656991361.571e-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 .. 5.00030.815031634197425 .. 221.897913448486181.190e-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 .. 5.0006.40018134993381 .. 87.997677879024427.476e-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 }