{ "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/v0.8?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 \r\n", "\tversion : 0.8 \r\n", "\r\n", "\r\n", "Other packages:\r\n", "\r\n", "\tnumpy : 1.13.0 \r\n", "\tscipy : 0.19.1 \r\n", "\tmatplotlib : 2.2.3 \r\n", "\tcython : 0.28.5 \r\n", "\tastropy : 3.0.4 \r\n", "\tastropy_healpix : 0.2 \r\n", "\treproject : 0.4 \r\n", "\tsherpa : 4.10.0 \r\n", "\tpytest : 3.7.1 \r\n", "\tsphinx : 1.7.6 \r\n", "\thealpy : 1.11.0 \r\n", "\tregions : 0.3 \r\n", "\timinuit : 1.3.2 \r\n", "\tnaima : 0.8.1 \r\n", "\tuncertainties : 3.0.2 \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", "obs_list = data_store.obs_list(obs_id)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "ObservationTable length=3\n", "\n", "\n", "\n", "\n", "\n", "\n", "
OBS_IDGLON_PNTGLAT_PNTLIVETIME
int64float64float64float64
110380359.999991204-1.299995937911764.0
111140358.4999833831.30000202121764.0
1111591.500005656831.299940468341764.0
" ], "text/plain": [ "\n", "OBS_ID GLON_PNT GLAT_PNT LIVETIME\n", "int64 float64 float64 float64 \n", "------ ------------- -------------- --------\n", "110380 359.999991204 -1.29999593791 1764.0\n", "111140 358.499983383 1.3000020212 1764.0\n", "111159 1.50000565683 1.29994046834 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., 1., 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": {}, "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 4.24 s, sys: 687 ms, total: 4.93 s\n", "Wall time: 4.94 s\n" ] } ], "source": [ "%%time\n", "maker = MapMaker(geom, offset_max=\"2 deg\")\n", "maps = maker.run(obs_list)\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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z25szPX+NFdV2pMyyqvY+PaPDnR5DO5ZQJUJkGE9nzM503WPrZgbUaD7zIrMOSu4B9hJstI9tkXGgXzBfxsVZvTM8NgjjPkrHktdzdPArFx0Pwsfz75WMboP0gHhF4iEP/sD6pKnVTeNyD+SpHcf7Y3XrC5bXow1sU3Vx3LJJWwb1urrqx2OPc2+r39MyNdLtlStafv1SPFQFhgMjcocHgAggACZuxwRAHCjm6qqrjys8scxr7jY+tzMO1WWZXi3o1I73xaDSeRDj/qVuJhH3XUYMyM7xvvvn3OOyDBV+Q+4DM4wvLDddekC8AnFnAmqex+W5zahWZjHE0zlDY/Iw4XBGeIydMx48lTBGVCcmyqqCWTjDgGU525C6VVnwzLqtzBmHM1mfUExmgMEzWcqQERwBgCHHviTpRYV6D/vkXLJEALlHCidRyZB8K4DS8146LOiTmwL8frzAhTsrvC6it+VqvS8gZfhTuZChYXjespd/c4cZIUL8/pQvwzGH2u0Mn9/fc6Zvi+rcA+IVCKome/byQM+UvZXL0uN8kgFETNaxtUm4ChONSYkaiepFvJo7XKRgW5sK1kC4CsyKSebFSRfFPfGZe5tdxaytbSQpSvejMrp3eN3Ox8Y4VgZD7IbY2NzjzjkwHGyDsCvGwB1UpTfZX2V2Dr8VKZIDdZ1Dw3Y8UXGPFQUhSucHY0Q7btfzMWR8x8rmirGCzXs9TH9+PG60DKhnUeb/Pg6cRxvu2Lnp0gPiJQsPNh5OHny3X+23f/3hXOh8Kp2r3bDNsjSX1PUkSl1W4/ZKVw89N5lzOM69u66CYf+iIMWJAog51uMhPcMEoPZiBqivpSpeOitYIBzUAUxnz2/qPNgCuB56RDslIDqrHRfH+TiWziNYqhdjOLbjl7HQx3m03VaMljC08fF7cNDmWfLCwp4uyIIAAy9LoXm7jIkz2psqPSBesqAWejoZnrxVdTeCGiiD3Kqkz+l86XnZsQ4gqLAOch4j6LY7dx549RiA1UtUAdoAHHZDWZs4a9zx47Yo2Kln0eAgUNtPwkdgmLA+2A/iYUS1omQZ790TPhpIwzq3u6usNnMPsvtFLfR4PfrpjHqsri2QeydoHoA6bts7VAA1qqqDVmmXc/BFZfXKNR4p4OzWgdUnM4DIQneirgCMeM7LxYuXiu9uuurcA+IlCg+d59eWLMsdALwnnMYfevcEwiSkmIyltxCvp9uyFkuOc4Y0smPcsfOkEJJKkVnjtkB3BkhdtQ8WB+iwYLgN0h0PAMQL6qqKjJN7q+nXaCSNB9JwllX6AwV787EDAAAQvnfV1RcY+uVjUsb2eT8AEu7FHSHuxXZZVVRIJ0wJtodDyitx05eBtTdUhO2c2vHlmGK68UXTnSlSPMNPYzuH5116QLxEcWeKqyMwJyk/XL7vr09sF2d3UrCVMmaudAy4PdAnuE+AUnVkglFncaEu6Dgj4fuyTfrmXnK/N1cFYZOPE+6D2EfaBVjot3viB4YyqLx+D67y8jcVf0s7aLlQ+N4oDvi+aPj9Pi5O0O+z1Aaw47oDx23FUqjmtEEfYfd430tWuswZtkybcFZ709XmHhAvSQDDHeVsEry4KwpbV5kRMFBUHCFVjgnswds4QlbUTT1zFuegSqCzAxkgU1Z+hlX6FqYe9+bqM7YnxCcWdq65gsUinpbItec6z+DUvt9qx/HOUFprb7KqpNNaauqWHdWZTR3Tp1n+P46OscL55IuFO1lcrQSASvD0sBocGdj3vF1Xi8ux83ZcfCE5bP9/ZP3x41msuCaebK/szXOzDMTony8sJZiXUQCuQdxUB0sPiJckGNh5oHw/XR7EMhUPtlXbudjofDI1CpZUgpR7UqWwCbqhnevVxfcDa2dNXZAowVTqejVdFQTQSo8qALRv33l7TGyAFi/7feU0x/VxZn5VlV+LdlZORu39LLr3vW/9w8nh1abdK4wttQQz+gjThnW515ZzHehKBwXtbClYrgPQQt0xxCzgjg/szXi3ASZsr1IXVEtNw50/3KMviA7srs2U5pObLFd6fymlL5b0PynvBllL+rGmaX4kpfSKpJ9Stn1/Z9M0B09o5rkXtx2W8XhMJlcRS/vX1M7HUO/A6SDI33LyMnkI1xkqsz5nQW4Xc3vXXMH8YKOnRVvlZB8ULwcN7xcpZqWdk3vwQgfY0u5JWhtKi0UGxPm8a39bq6XVYT5mWEkrQ+nQ0IDFyTeNl8IxVZoakLP2FYy8THtzNu6qpXv4fbx80ViWOsf/PRC7dHCwKHL9csH0frmt0O2ZDqT0tbLr+MJQ2kSXqfY3Ra4a8CtJf65pmo+llDYl/UpK6e9L+hOS/hNJXyrpj0v60Svu11MTZ1lbCnDzTIiZuvFzUtdziFpMvKLU3cvY7VLlhEIFcvWTVd/Znu/ZwTXdIeI1+dyRQb6tZ9wQ61dOTPrEe1evOZeUQcCqtjbYoH0gaVZ1gRJzwmH73XotDYfS6liq29nqHlayfrgXmJ7UtWNyXwQ7S5HjzbEwbe7bz3XW7MCBHbZMc1zG4rD5jtoxKAstOCP080qG7uBIPUs0kxJMvQ3ZOLiKzHNdpkXeJLlSQGya5jOSPtP+/1FK6dclvVPh8KvVnTfXThwMYYc8jDzIqGauWrnhXgrA4iFfV1e1dCO+262w2zEJfNtRYgFhO85SvVq3gx19cW8owIiUnuSS9QGqqK1srM7L8659sjsz9Ym6OZImkxb49jMontTSeJHV59O24+Vm8twL+5Uwln5fnLehbl1AVHjAb9q2wxjSdwLtvdhvueg4W3NW5uzrWDkAuyzkSn9Lu6BXFVq2t4pviYqUQds8u/yfMXeQJSKgdE7dFHlmJoGU0rskfZWkX5L0CUkfUo6l/Y5n1aenIW6rc0AktIZV2ScioOgPPsHHPPye+7tsUrgtzpmaMwD6VzpYpIizg2HCAqri5RMA4AIQy3tCCPqlwOyagn3RLjbTgbqbHrEwAPoryiE1K8PsSMF5wzFrtbQyiP5zHcBxTbEhlDMf7ztjnew4d6Cw+GwonBjlBlQ+HoPiM1eHETensIhMivNdI3gSS1uxv6X33xl4UjdlU+qyVn8+HCR9wewB8SlISmkq6cOS/mzTNPvK9u/fu+S4D0n61ivu3hckMDBS9NygzwPqBnTE2QFqKIBXF3/HxfuhYnIuS+GSupPPhcnnzJHj3Rbo9RYBbyaX73Pi9wTAuy0KtotKSgwjDpVTa5vg5LligRkNsmosZcdKOdklaTzOr4OD7HjZVxR5wCGR1I259IBo7ofqPwfqFkzF5LCqiA1U2/eJtVX+ptJyDzrmEmf9pdnDwZD+ISWwl88N4nZPFiju13PdXXzh9IXyOuY4p5QO7e1HmqZ5f3nMlQNiSmlVGQz/ZtM0H3nSsW2H39+eVzL+505YuVEPsX+5R7gEGmdUHpsodVd0V3lhGbJzPQh3WJzLxHwcI5EdI0XIBwDueyAPiuMdUGAdgLLs3j0vmvGRuuAOc9tsP3/JvhspO01W2yf2tJL293O/CBHiYV4sMmiORlI9z+cfKlILa4UdEq877BOwIYuoUtcrDiCQm8x9IJ7D7ABa2loBXFIXMVfwjPhvdnZfCvADdGl7oXCk+bazAJn3xX8vF19Ey+u7qYP+l3bS512aptl4q2Ou2sucJP2Pkn69aZq/dpXXvgpxFclBkDJdro4CNANFgVJADfsfjE+KLAGpG27hbNDfu4rjzA37X1Mcu6eYBJ6PzLWZBBP7O1F3nxCEtlFTZcdwf0wkZ6RMLIq/EoqAXXK9Rc+6zqBHFsfOlrQ6kk4W0uFMenMeqXLl78D4MRYlKHglnzKAXorfzovVetUg2fEOXoAK3w0UziSvTYnZYKButaNyQSuDzR04/d4cTLkG7XiKZFX8pV0cSsTOHuj8mN0kuWqG+A3KjO/jKaVfaz/7QNM0H73iflyKuK3HDeyEP7h9sfQYS12W6Pscu2OEieYG79pezjyHxV+OJ3wEJsC5++qqerJj6O+4eOFB93AegM13kcOzC1iing8V6nhpyF8dShuTHGazWGQVmDEbSFofSNOp9NK9fOxsltXoh1WO32IsT5TB2ZkpY8rkhwERzC11CyNIoca6CcDNFoC+h7MA5uSoY0bgt/YiDc4AS7VYit8GRwugxeLj/eR5w8nCsf6s8BsT+7nM0bOmyNx5K/PLTZCr9jL/gq65F/lxwmSmqg0gworqLx6+gc4X4LyjADUCsAFRtzXxGdfxmD+vzELfuC4TyY33UneCe5UUBzpYCWDmNQYdWGGBntLm5gHCSdzbTMgRauxcOQtl3IbR7C3iXkYKsNzeljan0mCQjxuNpNVZ10SBigyjdYcO906Yw2HxOaDkJdf4jvHjd/ItGMrfFXMC4MPYYl9GPASotB26mgx4AsKAuQfr02d+MwpnuPmjVjd1tKx6RDiU1C304c/wdVGZLyLPzMt80wR1h21FNxWqJ8KD5sxM6joueOD9QWTFZ8c31CmYJkzUvdXY5vzhJxfYYxo9+8AZKPdEEVoKVLgaSogPDh1XxcrMC/oC8DpzYQycjc4k7dbScC/CaKYtI5xMpJMqA6aUGSR/F+2NlemCUnhVN9v35Xab7CUDQ3M1knuB7braj2DLdI2ARUQ2bs7mOcbvn9+ANE5fTEo7Lao37XMPUtg7pbDLlsUZynqRvpj6b8d9e/ws43KdHCtvJT0gPkVx+wzqYJkPW6pass89I6Es+ICKxY58BEe76lPaDE8V6k7pUHFVr8yBrosXE9yZDdcrw03Ka7kTxttfqLtPiL/4fl85thCHx3SaX+Ox9OZ+Vo8PWzW5rjNIHi/OT3rYqhd/wKYLcHs1GB8LqWui8IB2+kv/ZNdx9d8XHA+V8rH28QKI3ExSjmX5DHlpMr8Hfit3/jDGPtZlu/5cuI24se9vIkvsAfEpCZMDFdFzD50N8L7WefBAdWRSkLEwb9vbUlSKLgsv1EU7C8Wq7qzzUF212w39zoiW1dvzzZAoDOvsh/vCW+ugsNL23dkjnxP+gXhNxKTMbraVmeFolFng4YE0m8eYMybOYobW3lyxNQMTn9qFDli+CJUgDZNHFfdreLEH97IPrT0HUhYIt82Wtlvvj+x8t7PK7tfBin7jWS+LbPjEd+Dnt5laGzyLLF48K5heygIh11l6QHzKwkPsToISsB5n63NG4TFohH5goOcBdZuOq56e7eGTg700nD0Bmu5d5D44DpthOZncNuU2JxwUUuxwJwWT8v7TDjawY4UayHXp08FBG1u4CNUY1RKb2dZAWq0jvtHZ0r4d5wuUmwkAKswEsHA87fyuntFROhnKwg1DZWbPb+cLpDu+cLqwCLqqjjgYcV+052FEsr4fKKqyqzjOF1UfD+5z0vZrU5GNgxkA9bw0PVxn6QHxKYo/SBjG3Y5Tenxd5UD1GhbfydpzR4irx+vqBkp7LJuzEFe93KvoE7dkAHzvYTq0A4v0yd/Y96cKO2qlbgFWxLcfIFTmBWU2CSAxhnsH0f9xq889WhTjO8xt7C2ypxkA3lGYLzAjeFA1k517hiXxOeNfBlzz2znTXrb5F4uBb7+Kk4bziV2VIqTI4wUX9tedJg7IvsiidjvQ8ZecdH8OOB9hUV1TOJ1wTjGu5aJ+3eUm3cszF/dCeuxYaSMaFZ/xuU8IwM3BiQcQkJopnB3uPXWQZfIxed1LKnXBye1Csu9dLXcnDYHJ2KpgNqj9Ure8mKvjLBj0Bxa5odhEidQ5rsuYEoBcVZEdgkpHWTA28FLbFtsNNApv7JYC4EZtvw7VdfZwv27rZPycVdI/Z8t+rHvR3alGKJDbjHkW6Af2QV/gShuwM0UHOV8EHRgfFef5tcsKTbD8SlFwA/Fn7SaozT0gPiXhQfJgWlRKB7V1nd80noeJVRtgczshth0eeIC19Px6m4SBAFhsWrVMVXTAgrH4lqYc7+oV9jefUL4THedWRRt+D1IUd9hWZocvKVR8ZzgAbVJWmQH5kaRhe1BVx14zUux7QiaHOwi8D/7bAeLEV7opwe/XbY+opL54lQ4r7iVZe55Z5DJv22QRdLbuv78DEcALC3bVu+yXrL3SAUSfYbg+XmVQ/zKTwXWWHhCfkgyKFw+EPt/wAAAgAElEQVQeeaJ87hkNPtkRbHrS+Z3nSu8eMWweBuOghkq0LEvEX95/B9TH2atq+94rpXifyonqwOtB6rAgUuXuSNpsn0oYoIq2PLvjzFRQd8fP6zi6qaIcJ78f9g0B9H38l9mAHeyWMS1ngj4O/puXzJDjWARh0rJjSqeKLzA+1u4o8/PdvOK/XQlufk/+HOFc62zZUFznusqFADGl9CWSvrxpmv8tpbQuadg0zaPL7dr1EWdrU3X3MMHu4kL1lzJ8wzeQok3a94cNQKRqjCfzuw1RCgBAXUa1RV3iAUB19DxYv56rbfTXmavbwpy5bCqYLoHIHkhOf1Ad15UDriXpxDwB7l3F3lYrijQ4UNbKqjeFISgYMbJzSjsq9+B23GVA5rZDruHeZ9kxbpcrFxvZMZyX2heeW2+Phab0PPN/Z/Teti+iUjBAGLgzTrch+2/EZzxraDmNtXdT5C0BMaX03ZL+tLJd+t9Sruj+o5L+wOV27XoJRvgXlB/MfWUbVlkd2/dKmem8oZ62WJEBGCY0wJMUE7EMxWDy0baztoEiPa0sEDFSN98XEAXQCeGRuvGVY0U4y7G6KpsXuuB8V+N4zZXtd5+TtLqfVWCPd1xXN+6S668qp/At6jzBj9trbihMBh5aI+sP4LiifO6hpDfUTetzx5fsL17wksF69pDbbb38vxShRbS3UKi4jBOhL7Bd7Jh4dZexUTd30A+eL87xHGZfvFwb8VhOv3evpu6s9KbIRRji90j6WuW6hWqa5l+mlO5daq+umfiKf6RY5ZnszuBYbbH3eEwerIuHDPYkdbcxpR1UQ0DS9yV2D6fbGCuF59cBxtPNXKVlIr+pYBR8T3ECz4wBELkXwNrZkmd7OPt6pAjnWK0DUCcjnW0d4Pe1McxscjjM6nW1H4zcTQvcw2H7auz9IwWoHWs5y3MzCIsRnlc3Q3j+savVMGxP02sU8Zo8D6jplI+T/Sa+OJY2QDeneDiQFAvd2H4P97TL2vDfTYrnyu/H99SWnXdTQPEigHjcNM0iF6qRUkpDnc+KuvUC0OFNBHCWqSFu43Hj+7Bor1z53a4HMMEaYYyn1jZ51LAgArMP7BpuQIftDYvXQl2gk87bEd1Gx4Tz8eA+cIyU9kiYjWRAP5C2tnJ2yv5+BkTaP5E0aQcsDTIojhSlyhzAtttqOL+9mwHQmZL/Hm5P83Hx38sZoo9huSUp3/ni5ozX4zapucgz4xrBQN3UTNRvGCrijNP77KxxpDDXwPIO1S1txv2wkJSebV/8vP2bwhQvAoj/KKX0AUnrKaVvkvQfS/o7l9ut6yX+QLg3jwBlYtnmyg83ExL1yicf7RHrxURzb7OrgEnd8mKc6x5hZ4clA3J7oN+Pq3ZMRjZP96BqJp9X3kRKDzTtuYrPJPdwDgpbrNSZ+c1mGRB323MBZ82l9UXOYJGCecKqNiWNBhkMNybS0USaziLsx8OcSqDHQYTdzO2J9LF0RJRqrH9GJgvXrnSeVbtNkcpDXN9Dn1CDNxXZQuwyWBaVYMHiGXHAg6WX4DlSl9nyGW36/kDORm+CXAQQ/7yk75L0cUl/RtJHJf3EZXbqOko58d324w4MtycuU384DnVKimoqHFd6nHEmAFKEvvCwlg6ZSl1xplaGhDCRYQ+lw4BjURlwDHg/nLGUwEKfXJ2ENSVJg4NsT0Rlpy0cK2t1DsGpqm5lHljmqB3w+Twf431aUzcG0O8N+yTj5YuEbwWxLMSoFEJr3IQCw5fC3ue/qQNkaSvkOqQIck/EUvrvKXUD+mGzpRmgfBEDinBtT1E8tu9uCii+JSA2TVNL+vH21csSKR8cV0n43j2yHEPVFQzpHvMFO2TyAZDkNZcxYA5Y2LO4jtvy/JxSdV12P56q5ml6pSfa2a0b9WmvzAHmHNQw6TwoYuMb1GFz9YyWs1JViwiqpo1V5RJhw6F0PJf2DyKdD2cIrMk984BWaTbgvjgXNuZjg5lCCvbPGCxTo91U4mW8ALZ9O4ffk7YWyg4gAsmpZOTX4pkgxQ5VnAVXerz626hbBcfja52F8ozdFHnsvaSUPq4n2AqbpvnKS+nRNRQeIvfoSgEEvn+HG6+lMM67B5aJ6YyI0mIAAw89jhk8me5F5AH2zcdpG0YBQ+J4PJ2IT3pshF68wO/fWROpXg7Q1FB0W2ppC6V4hdf1W20/x4vtBSuGg5YFzuMeGfvjSmpmuToO9+Jgf6SwoZWOICY6djRenmvsNrWRzudPO7iUaimLHP/3LRWGygsBajmhXCyOZX414+0qrIdClWFZ7kV2oKbyNznlrrEcq2vS4BlxM8xNkCeB+7e0f7+n/fuh9u93KhaPXtRdLZn4bvdh0uBUcFug1+crM0k8SNgnO2Dg3mqp6/l0UPMUrTIfmorIpMpxrjM5JgBgQByjFIDlG1x5YQhnQWvqggPfLxTVfKTI5GExmSjiGUuP5rBlgeOxNGhn5qzOgCJJG3XrqR5L43k4HzyLw8NS3OOPKk+2D32TulsoNJIeKtihs0LuFSbmLH5VXUCSut7m0vFUmh5gfL6XijvG+E3cNinFs+GLNL+Tm3Q8o4pUPwC2BMGb4FCRngCITdP8a0lKKX1D0zTfYF/9+ZTSP5b0ly67c9dFfOVFVXQ2SJgGLJKH2z2SMDWAym1Bnifraq5PPOL4ljl3ysomSGlbmlh7ru5x3pkzQ12Qhenw1xkEIOdj5ZN5aPdH23hCpW464tqwjS0cZRCkMCyVb0aj/NmesgNGyovMeJadK3hZpdhWwE0cZSYPVXg8p3qmbtzlQ2Ww+Jy6jjJnzNgHPdC+9KgznoB1befxu5e/7VSZOW8rzC70u/ztfCEpi0S4o4g+utagoh9u65Td702Qi6j/Gyml39OW/1dK6esVm4X1YrLsoUDN9NCGdYXnj3xVqWtQl0JF4cH1DdsdXH3CjKytkn0MivMp3cTkcqeMdN5GhHdxWQyb99PPc3uVj4k7lGBq2AFfVExsxmdV0spAGgyk9UlsOPVwP9TGafuZsx4cAcOhNFnE4gHw0JdyUy+CoPndSlW4rBJeLioezkOfakUFnbJ2I4uJO1ymCrWZ9h0QUcffVLceJPZInruSVSOYALi/hfJi4tqHh+Dwu7rHufRqX3e5CCB+l6S/kVK6077fk/SnLq9L11ccEGE5PCjOrMjaoJQ/HkMeaOxkblcqc1sBDGeClAGTuhNZ9n8HMp9ctYKhopomO8cnyTLxQGsHvGVOBQdKz5qAWZbq21lh0raRQWsjmM8jWPwMbEa5yvbY2lmRzvZyro0i+/f8Jr5dqv/1e/ffB1MA5bpKm6w7QnyywQJXivdcw7cydccOL1gt48b1pG5RijI0xgEc9dqdJb6Q+P/dWeWmF1fjb4JcxMv8K5J+Z0ppS1JqmubNy+/W9RPUqUNl9kCeq9sLpYgb8wmHp7B0lAAapK2hRsPmSEujUstLCvB0xuNhJYScgAsAlwcCu1rujKAs5cVfKeyHJWC6qsn9Y+uUInRD6qra41G2C67N8tYAc0nzur3uLKvBc0mfbY/fkLS1yEHcdxcxyc/YVatmV1Xeo4VQGPcQlw4oVz2Z+A5amwrGTAiPF8b1sXMVGJA6UXiVMaF4gd2SlbqdetTes3/ueeLcTxnQXaq6ZEDhZeflC5MUjix/RhZ2nVvDEFNKf6F4L0lqmqa3IbbCQ76vCMvgwSvtNC7O9Mo9L6RuuSgpWEK5217phPFJhA0M1uLOFvrAi/vweD63WzmIAxwlgKo4tgSRkinRB+7tbB/kSqrrbC9saulR3VXPYGle3OKoliZ1Br/RIsqKjcdhX6zqzMx9n2spYvkAfY89ZF9i99C+oTYkyD53j3OZ5wyjZKycGfsWAFKwP6mrVvNdaWJhXGXvYXHcR5n94qyS78md5jfzHHbMNacKEOfZvSn2Q+liKrMnIYyVvc+/fjndub7CRAGgYGjLDNd4QJ2dOSAS3Hxo50uhLnsWiTtfnPWh4mB/k5YzDvqOjbIM0fHrT+w82Edpn+QvbfCdTxwHbdrgvpjIqZbqgwAMUs88BW5V4VBAVd0/6BaHXVVmhmxT6vueuCpJjOGGuoH0vv2B17bkHjyDaKBInyvtpvw2sGPfksFrNGJ68Hg3V0s323uaK9sOPdOGPnpxCj7f0vnq1r7QAdpSF6Bdw3G7pTPfmyQXUZl/2N+nlP6qpL99aT26puLhJkw4qWu4Rpg0Hmvn6gkqE0UYfDUf6bz4g+0ABTv0uET6SlslYHtsm7NRQI2JzHtnMgiA6KALMPv+LQCK21r3lT23G8qT388nHg6w2JS0PdJZsVj6/0Y7dmd1/6oMiJNJTgMc1F1PLmPitjIWKTZo4jfy4gZ+LmBB2FLTHovphP65QwXnjlfo5vdmnBkvALF0mrhnmUWDDCnGdkcRw4pKvmX3RYyjA6lXOaLfOARR53GE3SqVeYlMJH3p0+7ITREmOg8bYAjAUPRACjCi4AEPNUHIgKQzPx54ZwTusOEHhaHAiPCAOpN0ld5VWTeo44F2Vc8LhXItL7qKwEhonwBr+gXw+jEEma9IeocykC3qLhAwDtMW5NjMfrGQ5ouu6jlUtkEeHITqXM8jr9xtiAgs12MfsfGREeI504A/vyVjSEiR/5Y8B84Efdz8+YGh0Sc3TdxRN1gbO3KtAGGuy8Lgi5ZvUeD3zd+RMvtmywVYuNeZ9JCemyIXsSF6xsqKsu3+L19mp667+APuxmrpvDfRjwUUsUEOinMBVLcryr7zeDACoFm9l4XAlKu6G92HS84pJ+6y+3aV3PuL+KbqZZ85v2r7jyOknnWLCTC5qzrbBeu6dZRU8T0glZRtkItFqM1eEahU+70f7lyBpcOw/Fgt+b8zPrcfcpzbS/16y8T7515mQA1bqXuQfQ8YgFPWdwLs/TdqrA2cf7BOFxanW6kyKzJWpPz7frZpmpu0KDwVYSK7N9ljuUbFcS6eRoVKxbGuBkvdmMZSVXHbFZkYsDDOXfYgu8EdVuvgWHqQfbI/yagvnbeVeSgHx3uYByA1lzRbZBa4MpSaKgrbwrpOlQERTzrqNCwMW11d5z2cD+bhgec38WwVn/gzhenCYwsP28+TIk6wTPfze/bKQKVpg8WhshdtcK57gDnWYxcBNlLtfExR/+mjFCyT/WpgvIRccb7bobElc/9oGZRau0mgeBFA/K+apnm/f5BS+lD5WS/dB1vqqknYXqRukYJlLM1VNFhjCbjSeVWaFV0K+6OzMHf6eNYE4RfLvI+eh+3e4IGiOII7Fdbb8wFRtxfOrJ3S8+4VX3AYfFrSvXneY4UJjl3Ni17QF4Bix8aR75wxw/JYtBzY3fHzOYWdlJhRwBjbKrZGBymElMg1BZB5/jImCAdJwAxG56qyjyWA5iYMjmdRheX5PVWKohn8Ztia3UbK7+oRCji9KDxxWwHxPf6mLRD71ZfTnesvDoowlZGidh2hHXh0F4pcVL7nIXN1hclArJwDExOTeoWVwhng3ltCTbA3STFJ3Q7odi/SyjxI2lU92gRUmPDYCEsbVTm5+Tssvj9RtvElSStVt5QaIPXCIMcdzud5f2bY2+YwZ7LMZtn+6GYDgq9hRGVKpaueTPqRfcY48BuNFDGIM0V6o7MsfhPGTzrvxPCQKpw57vwCMAE133jex9YXtROFHRSTw7Hi2eBZIqB/y8af58GrsMN2Z/a6SQ4V6QmAmFL6QUkfUC4My/hDGH7sCvp27cQnuBR2IlbsZJ9L8TBtKryqRzofusFEdRVPCmeHt+krvXtxpe7ewFttO2+qy5J8UvkEpb8eF8eEcnXMA57dyywFqK0oGI572WFbhCwxbivKpbwGVVaf18fZHjidZkfJ7m52pkza+9qcZvvj2jjbFff3c4ziWnudQ4Vp4NReiAOgbAy8WKyruDBOd6ZR+AGnDE4JbHszO88dZwi/91jBAnkuPNDfbcxllpKPO22y2HhMotfTJBPFPcwEmROGVIbu3CR5LCA2TfNDkn4opfRDTdP84BX26doKq/hI0l11vX2k6qG2esHTqSLLgQo4XtvObY4e4+chIMQREnO2qW6pLVQtV6OOFSX1h20/PLcVKStRS112Kp2fMFvttcmzRfXfVrBIj6FcVVT9YV+RlyW9MpHutTv4zGbZyTKdZkAkvrCqclXsnSpvOTBoEWI0CuA8OMhgejyXTg/yOLAYHLb3eKxgcwD7uiIo2ysBASa+APr/+UssKu0BSCwqgLTbThnLbeVniPAcIhB8UcKMQKUdqTupCajeVOQj0ybtAsY8T25ScRbrtSPdHHKT5EkM8d1N0/wLST+dUnpv+X3TNB+71J5dY2Hyb6ir6sLAvKS/swc2bfKq06z+2JpKte4sz1cBbG67XGawR30qA3ilYGrensceAs5uU/T++Bj4PbiR34PGAQlPe0MVXZe0s5NfVRVe5/VJLvRQVdl7vDqSNlvny8YkO1GO5hkMB4PMFPn/yiADq+rIP/YtF7i3ZH2W/V7uLPL4Qu7TWXFTHM9zQHvS8qgBNydwHbZwhWETq4h5whcrV289LMZLvEmxCLjnnsUPoPbMJdjpTQy3QZ5kQ/x+5e1Hf3jJd42kb7yUHl1j4YEHaCjUcNR+jzHenSFSOBs8oNcrl3hdRFQdBxuPbfRyWUw2DyHBaww7AJBok5zVqboTiewIjPHOht025wZ/JpkzScaF8cDGBXOVAghWlcFsOMwbSU0mGRSn0wx6bDy1MpBWx9L2trQxzSxwsK+zgOy1UT7mtM6fVXVu/44i+NvT8SrFFgb0h/66LRVQh1nhefV9Uw4VsY7OAMuSaYyx2+YOlBeFs7FQmElYPKTMdOknC9qKfVYrvO8ehYCNd0sRwnOo/LzSDjJUxCNiW71p9kPpySrzn27/+76maTpmiZRSmXzRSysM1GuKhwWAZIWFlaC6YNMiRxIW6czPhR/Ny+ADekfKmR4ea1eqNqV9jM9Q5aj1x/k+Yb3Aq/cLAAdcsFe6Pc6ZMiEt0/a13l5739qrJZ0sMuihHksZDAmyHo+lhw+DLepAZ1kpVLiZzaS9vfx68DCcRtvjDKCrw3zu3p70sI7UPwd+HvihAvAovIE2QOUdxgxbrMcgsogAkL7oeOYSLAy2BiDSJjZI1GVUYMBX9ntRAfuRYmHzQiF32/vaVyQJsEAD+JhDOPc2MkTkFyWVKvOyz3pRPEgPFUzLYw/JxMBeR6WbMjeYieheRo8fdHWT45jAe/adP7TLPL6rdpz3YUfBCk4UHlzfHQ8PM32RIk6NPrJhPGFH4/b/sMmxpLuTrBbPZtJrD/PYIeOxdPdum2HSMjxsidvb+TVuPcrzuTrFYj2HObV/KRQ7GnXtjbQ3bYF1Nu/a2TxsZ7/9P8zKHSde9ILfAyZOKh8LotpzTos2nM3z23D+iTKwYff0QH8Py0EzcG0Dhx2/P9oG1yJlUdYW7NfT+9wmfdPkSTbElyW9U9nL/FUKDWJL8Xv2skQqRWgNDgwPwSk9qqg42GwAKuLXlqmoDkI4AVBzXW2r7Tj+LjPo+0Pu+awEH3tlZ39oYJaumgF8G8rAOlGoftOWlR3NIstkfZLBaTQKllcpV8je3pbu3892ws89zOccL8ImuLWV2WBdd5ngwUEwyfVJbmdlkN/z3XwuHbZUdr1Vzcfj3N5kobPd/CSd1V7c1XkgYPz2FOYPwMwBzfPCjxXqMQK7BjBXFdoDqvpxe50jO482YYeA4aECyFH3AUjMKb7Y8TvzbLGPCnbMQwWLvInsUHoyQ/xmSX9S0n1Jf80+f6QcjtPLE8RDUrYVtj5Xe6Tug+x2CVRGN+YDnDyMBFN76Is7RQBDQIzjKZ2FOLuAjQKaTGLEjf+0t6uuirypXPXaYy/HowCwza3YEa+qpDtbGYjYH2XrIIOelEFpdzefS/rd9nZ2nqyOgukBflKAo5cQu9NeczAIJrm/HxXD2YyKfpxU0eZkkvuzsieNqgAgFg9PjYNhue3WPfKYMA4VbLoMTxorFjdiG4eKRQtbnl+HxRLgPFHEMpb2W48vlGLrCZ4LDy7HxIE5g8iImypPsiF+UNIHU0rf1jTNh6+wTzdGABlniJ51woPlXtwyxovPPRTCY9ZGCrXWj+d6gOKqnU+sXMl0/Pquinn6GcexJ4nUzaqA3QCG7oEmVAYwRKUdjboqriQN523A9YH0+utZ5V0fZyfL2iiDIayurtsisvPsXa6qfDzXHAzy++Ew7I6DQQu67Y/A8ZwjdY+X8nXHVdfZ4PGb7t1lXMoCCrDvQ0WAvad1Ongypm4u4Xi3S7vmwPvy9+I3A8QdKFfseM51JxnPikcl3FR5Sxti0zQfTin9YeWMlbF9/pcus2PXXdzjXClsaDgP5sqrLcG6bjfiAfbwj3VlFZSHuaxcQogFqi0BvQTzSl1nCA81k4nyUL7ZFZNA6npU/f6q9r7Iid1U9t7uDLogA7gAYITC1HV8ftSCIAxuPs/q7W/9ZvYsv+tdcf76ONsd6zqryEdz6Y3dcLBIwQiP5vkYKQPp3bv5mPFYWtnN3ueNSTBEzl0b5WsAkFtb0suzGE+YOeltzg4BMs+zdocJXlq8xq5iryqyl2CVUjhjSocMca/r6hbBQO31tEjiDnHujRSscFPxzJT50qTr3XpATCn9qPJi//sl/YSkPybply+5X9deAJM9dSuHOJABloTaMNHIJAAcCRGZKtghk4eA3YliVSdmzbcGdTVY6jIQnD+wSgznqHbYGr3+IR7HgbJJ4IvaPqK+jlraM2t1aexzfOZMbbGQXnstfz6b5fd1HSr13kJn+6gQbjOZSC/eG2hQ1Tk20dRdSWcB27NZBtXd3QyqL+x02ehwmO2IK4MoJXZS6SwAfGsrt3PQeq83W4RCxTxqxxabsYOFxxA6ILrKSSgVYDZTACgLm6uxsDzAcdCO+10FUPozAqvzyAQSAPCUA5iYS3xPaEw0Hg50k+UiXuavb5rmK1NK/6xpmr+YUvphSR+57I7dBPGJMlXYAz1hHpuQVxYhHhEvIM4N3zoAlghgklPrYTbOVGAmA3UrXxOYy8PPxAMQce4MlYEPwHij6sa9fcm29OLdzLQOZzl9bmUo/fYDnW0X6jY+2Nh43NryDnK7VZU9vFIOixmNcp7ybC69uZ9Z52CQAW40qs9ADDmpcrpeVeVjcLRIGeROW5A8rTMLnLZUrKpyf8fjtiDDKDtjAPaOSs3vMshMeGWQQft1ZTApq3qzULlqzV8Y36ZCowB42PsZFsdChVOEnf9IAPA8dd4vFNqFZ7VQRBdh8TtSF9jpEw6jm8wOpYsBIuM2Sym9ojyWv+PyunRzBLWSvVa8AIPUXZV9tZa6ai2eQEAMexEhIQAelWaYOFI3RpFroga5HYqJRpwaqWA7ilzbWtlD3NTS6cMInxkrgyGe3MWi3ezpbnZmoAZTxJUQFxgdKu5WHSAm6SztDkfI0SwD1Ys7Uf364CBymtfG0kt3MygezbL6XNfddh4+zOdIXQ/18SIY4XAY4TtSfr/RZsccL6SV/bCBrmIA3M/51ANFSiAMzR0uZ/ZUBTDCzKmOw+9F5ojbAzkXDQLNwotK8HzNi898Ayw82G7f9MwVTDYAIaFGN10uAog/m1LalvTfSPqY8hz48Uvt1Q0SwmAGCrWUh5m/ntUhdR90Vm6Aig1+hnYuAdGwTClsV2QneNEF2nKDvefoJvvr204+Us4XHo2kV17JDErKQHHvXgYX7H6ozV/2ZWErfONhtvNJAYY4QabTbqwhLHJrS3rHyzn7ZDaLz19+OTM6QnHqOjJZJOlkmM+VAnT39zMgHi8ysPJ93a4WOGCwUz46yOA/HgfoDoeZ/c7nGXibtr+ndexbsq7IemFh2VI3hpOwJCnCWSqFecXzxz2Okd8PEPXoBY4powjmypEAbkc8UReEMekM1I25hLF6auBNlos4VaiO/eGU0s8qj927L7VXN0z84cKe4w4KF9RfHlZsgoCbl8d3x4g/6O4NdCcN58EUmHTuCU32Pf3DAH+qsO0RFI0NcK1Vb08LdXhnR1qbZJQZjxdq2vg/HBWnLe2AbeFxdmcLqXewPeyRo1E+H5UcponqPWrVXmyJVft5YwDItXnvgHzaBmnTp8FAZ9sVkBmDvbOpc9D32iCH5vBbvKnQBMhYYcGhDuGhomYjDB7mTzu04el3/nux0PI7efk1bIC+6HIutmbaIFwMNuge7tsgF2GIZ9I0zbGk45TST0t69XK6dPPEH0iyMNg3xHOPpQBLfzg9VKOxY1jVYXE8yKRyDdpzUdUcFIlVRKU7tbacfaD6rbZ9nk4zyN2/n1ViKdvoABspA+ULO9JL96S1L31nPuHuXb2wu6sX/p+P67d+M9ge6vV4nMF0MMhq+Urb2aqK1L1RAZhpNNSdV9Z0Z36kk3mt2SyzRlgnThvS/0ajULWlAHfsiKNRZrdpEMUjAEeE8B0HTv5Op5kp17U0/FQwcRY5d4KRdokHF+cMvw/MsIwMAPh8Tw8+uzvI436yaAPOq2B3DxW2wbMyafbsVAo79Z66jpTbwg6lzxMQTZaRm4udmNK/L+lHlH/Ln2ia5r9OKb1H2YP9CUn/UdM0N278ecCkrvqMEwSQc9WXCYQt0m07/HCE8cD2OIYJiB2JSSMFIxzYZ4T2oC65OraqthTXy9Krr2bAe+WV/BcwODhoHRMDaTjKNrfp1iCf8MoXZd15d1eaHWr68JNnNrp798IWeNQC2hffb4FtFu1yndGodeo8lN4xrLR6/760s6PVxYnuvPZvpP19Hc8rHR50VeGtrcxAJ5MM4CdVhPbAZs/2Zamk4zoY6WyW1W1UZMD5zH4onRWSGA6DJW/Oc6qXg4t7jAmc3lcXdDYUIVb87q5leK1CnGsnyjbY1WHYcasqfn93quF4Yfc8FlBUdDJybkMgdilvFxCbtz7kvKSUViT9denVHcQAACAASURBVEnfpFwh/p+klP62cmWdPyLp2yX9QUl/923267kV1I6Z8mqNp1cKADorhmrnuecZGxPqdqVgFrXiR8EOxUQcWrtDxQTCQ8m1yZbxibOp7F3+8i/LcYDvuJeZ0MsvZ4bWLPJ0GY1CjYTp5bSTzYx6669Kr6xJ4/WOjXB7O3uPYYwbk9z2eJxteJ95LYMWucpVle2Gx/McavPi1h3pa75GGq5Kn/xX0sc+pvq1B2eqLEwRZ9DDh2G7PG1tf8NhBkopYiBxvHBfqNwEkp9V3Kki8HuxyECNWWAs6UuG0qyS/pW6KZAsbJW64VCE0UwVwISZxcET7/OJtXugDNzYUfndUdF5drB1+kKLA+VNZW/5ngIMbxw7eYI8FhBTSn9Hy4EvKWdmvR35Wkm/0TTNJ9tr/C1Jf1Th+Kz1BbDP6yCAlBd/8PhD7EWUZ8IZghpL5RPsQc4WkaEizAf7UFLX8ywFG6RogBeZIOZwIun+KxkQX3klbHdVJVXzSlUVNj0A6yzjpKoyHXvtMxlx9velxfHZ8bS11jK3kyozHNLlxuOs/u23JXAWi9hSdDjMIPViXUtf9OWS3im99F5pMtFL+x/V8WKuvb1wtuABh90B3m4PJVQHFR2Ve38/2B+OG+yP2ENp87gdZEBpMpFO9+I3XrG/a8pqMzZbD7Vi8YKpDxXq7IHOM3gC47n2ylDamXeLQHi4jxeGYCEmDvJAtxMMpSczxL/6Nr97krxT0m/Z+09L+jplFfrnJP1LST/6Ntu+NoKdb6bMBlBdPOarTOfCE8jeu6gxsDvCaHiIqZ7tlUqO2v9vKyZPaTAf2vdD5VjAd71Leuf9DFb7+xlkUJMJacG7vFiEx1mS9MlPZkD81KekQZIePtR4nNXN1WGopVSsgdXhFMG+R4ygFMUaplO1//w+SV+Tv/x3/pj08gd0/2d+WvrYAz1qaybu7WX2ubOTc6lPq1ClJ5P8f9Rz7gEwxM5JKNF8HiAthW3SHS2SzgpIHKstdmtj7U41PL0E6BPqIoWdmODpdXXVX869I2ljGCo7W7Kutr/nqrLXm0XUmapvocBzeBvBUHoCIDZN848u4XrL2F/TNM2vKgNj9+CUPiTpWy+hH89U3CbkecBlWpwzBJgAIRmI79tR299jOwdPNZOIbAW82LBNQjruKACTkJM7WzHZsb3N5xmoiBOczbIqurMTntuzqOv5kTRak+bHZwwrtQ4Pwl3YXxlAPK2Dda4MMhCutiyNlybrkt5lI7IlvfS10su/oPXxAx2aDXLVQnGkrHLf2RlIk43cv4O8zDiLRE2eTPI4TCZx/0fzMA8Ql4ijyO2XmCPKWpIAEUCIOWPR/l4UAoFVwuawNbt2cBYR0NoOjxd5UUTjGCsCirFj8lyhNjsY3kRJKR3a248s2zn07doQ3658WtIX2/v7yrVUl0rb4fdLUkrpbdktn1dZKJggwc84VlBtPRxCCo8ijKFSpIQhhOB4Gp9vCUr72JRgATCHHUlfcS9KcU0mmVFt7uTZvljU2t/PjGuxkLbGAYqDQRRuQGU8K1EDtRwMtDIdZ3CUtDo71OqiOjufNDkA9o2Huc2dHenudgbFjbb469p0KC3Yn++ujcLvku7f1/b2/31mDwTY6NJikdtFv28Wlfb3z7NUvNPb210748OHeQxOq1DFh8OIdWSsx+McjrNZRwkt7H7EC+J5BhhxppWLJSBKBILHrz6SNG9/ZNRfthtloQM0AWhsxpT0Ql2+qV7lpmk23uqYqwbEfyLpy1NKv0PSv1F2onzHFffhuRAM5B7ywE54MLktdRPwVxUgSL4raX4wDLdVMYFggbBN358FTzcMYUVnUTJnbONkIR3sVZpuD7WzU59lfEjddLzhMMp7jceSppvScKV11R7p+OGh1sbKjGxxfKZ7k0J3OJNO9gKUAKi7d3Of3vFytjeebR/wWqW7//v/ofTyD0rv+SblHS8Wkv6xND/Sys4dvTx486zuITGEvGYz6XOvL7Q6Wuholp07sDv64CE3gOSj1jSwNpLqYdgUPV+bRa2at4DYekWobwgYAmgESmMrPrXvPeCe35aQKikD2esKZsczQz/wTPO7e5UiCk3sK8JtbipDvIhcKSA2TVOllL5X0t9T/l3/RtM0/+9V9uF5EmyJHvrgYTUAo9TNOHFjuKXxdjYIwgOJrYptJqWuvZHvnYWeVDnQGj/I7m4Ghldfrc5ymaX8PeExs5nONnQCtFbqWlpkVDndP9Trr2fg294+PLM3SpEyN593M1KkUEGP5tLhQQaUvT3p058Olvqlv/wzevXVn9EXvfe/zF7t+bG0/6Y0P1IatPbKRVbRPa5wsQiv82yW74NcaGyHUgY8yo8Nh3mBgDUSUM7Wp6QCvv56TuWrFc6YlVk+F5sxYTiAm9uGa/vLNqBjxblexUgKxughXKjpc8WOjwAeAeMHyg4+j3e9zfKWgJhS+vuS/sOmafba9y9I+ltN03zz27lg0zQflfTRt3PuTRS8zqzkqDIwNwJ0SfVCfSpDdBqFijVSbAO6UAAiNio81x6sTSbMqjIoHc0i5u/RfgDedBrFW0etY+TE7GfH89COd+pHZ7UKDw+C8UkRRjOfhz0Qj7AUjBNH9Xye/TJS7s+nPpULKiwk/fNP5ErcOz/7GY1Gn9HOTvaI37uX29jby/czHufNqFwdxnmDUPxhdzeyVNjk6nQaLJM0vvVJBkr2cKFaj8cvDgy51tStPXhs/0c7kELN9W1CmawlaGFnREsg/nRhnyOE1wCOBP+XzrXbKhdhiHcBQ0lqmuZzKaV7l9inWyfOCvg/cYS8qLBMjKHvlcGkOSjawACPXVHt/8k6QfWSMhhuSLpjBRewCTK5UZNXR1mFlcJDjN3v0UFmcy/uBNB4fjM5xaij83kGHykKPnj2B6mBhMNwzmcVgc2flbQ6l8av5fucfkq6/wnpK74it0lmC+B8vIjslb29YHandTcdD7tgGoQzZ8cKSxAoTlgP/ZO6oTkA8Kx1dHh2Er8Rn2HK8E3I8A7zrJRpoGVZt1M7jgUWUwnA67bCHghDLgKIdUrp1aZpflOSUkpforcZmN3Lk8VDb3B8+Odu9wPMCNp2lalWqExeVkzqqlS8lyLH2QskSF2PKwBFaSxyffEM431dG0nzScTo8bkHMDvonTk5WhBxwCIdcLGQ9mfdYGa3v/GXykA6kCafzm28/HIwz5O2bbzY9I2YRK63Ns7OEsB0MolwH8YHtZ9it1KAn5TvdTyO+6PvpTeXxc0XLkwirgHw+5cB/Z7Gx+8KU/TjAVzvRw+GXbkIIP7nkn4hpUQYzu9Vtl738pSFieL/d0cJ6XjUwsOe5EyQSUX2wlDSC+0xAC2ACIhIwSTIKx6NuqAAYEg6q/hCLCL7I8Mq6zo7MXZ3dVZKixS5ulWfsUPS3myWayfiuSU7BDA5OMgVZJj8eFvHCnDBYwoozh5ILz6QvkrSu98dtRcPZwHm2EilCNBeHeUyYqjLUnbsbG9nhjga5ft5cz8CsakDebzoetnXRjoLEGeR4tbZkdF/Q7X3gTYA6ANgaAgsnFIE7rtX2oGQbUixFd7UPZWfhrwlIDZN83dTSu+V9LuV5+L3NU2ze+k9u8XicWFMIryPUlYVmSSE67CXMqs/dkOA0essci4yaM8nO2R1lJ0cxN0BfBRPkLosyIOr8bQ2dQYMiiQsFt2Nn2BUZKVUVXZEPDqI0B28yW8chN0LYe8Y4r8BDilY1QPl8/TPA6DwmqO67+5KD/Zbj30bQ7k5jVhK7hOzwac/ne+ZcmUUn10sMsjiMWdh8D2lp+M2M8nY5MNFBnq2owXI2F3Pa2RSEIKAal8syUP2vZ1ZJIhoYAuAmxpW8zTksYCYUnp30zT/ogVDKeIFX21V6I9dfvdur/AwY/OhEgkeaTyT28oOFJwtgCBtSKFSHyi2nJQCSCeS7ik7IcbjNsthiS0steoyFavJ1sA+6MetDoMFApqwPqnrRcZzXdcZrI7nEde4f5Djs2bqFliVwjPKJluwRgBxT5GOdvRr2RGzU9g269qKbLT9XRmGik3Q+W/v5r5JudLPF73S5lLfbcOSWtZ7UuWF4LDNhSY1EEClTUwD1UPpsB0LHFuwfO6ZEl3sq+z2Kg/fWti52BDRFsqtaXtZLk9iiN+vrBr/8JLvGknfeCk96uVM3NnCi6IQPPjOHmF//tDXiuKj/AVY2B3vJUmv3s8TF88o7Gx/P1RJ8o1PFpnNvf56vgbhKZ7/qxZYV1pP9OkobIc4YKQMQhSWhT3uH8Rknik2ZocRwwoX7ecI3lbKbhF3ty/pNyQ93JPu7Uk7o3CGwIIpirBYZDB78CDUZZxCeKSd4W20df4BzpOFztIFUZ2n01DPPYPlzF6p7j4nABpmDUKjCMVCcwDIy5Ab2OGBfXeTM1CepjwpdQ874fuapnFtRSml8ZJTerkkwX5EiA4A6Hsmu0qN8B6GyLnIWJlh7oyDxVDVulQXAY/BIAqsEsCMfZEX9QilAEveo0ZSyIHtQ/f3pc8+yHu17ClUQxjfQDl2jnQ2fwDLwGUWBVRKABSVcW8hjRfSzoG0vRXOHKlbrGF1FJVrTluPMlsMnCwilAeVmIIVm7Y1AUzw4CB76VeGmWVPp60poY6+rimDvzu6pNg5z+2CQ3Xz2t25RhgX9TF7VnhxuYhT5RclvfcCn/VyiVIG7TI5WP2Z/MScwZaa4hyYhVTs4dI2TtEDr0p9vMhqIIwnDfLEBggGBRI3ddQO9GyP1VG04XswA4gPq1zuyguZkq44VDgH5ooUN4ACp0SlrkrJmPAd52KvO9mX1luVfmUobS0ipnBlIFVt/1cGAZQr7WJxvAjQwyTA5lWdArOt/XQmaVxlVRs26jUsh4psJH6f8hlwYZsJnGQepeB2xF4uLk+yIb6sXJ1mPaX0VYq5tqVYdHu5QinDb5wFoT7zI5WFIGBK/Hi1MiM5VQakBw8ixGR7O9sTiTV8/fVcg7Cpo0wWzgNPbUPFRL2UQjXGe32iAJC6zurpwYH0qYOs1lJEhrg5ClRQzoyy/McK+5ovFmUF8loBkM6YjyR9rh2/1brdM7uS1trMlem0y3oJtuYe2TL1tA7gr6quuiyZJ/thBsSJumr0SntvxIbiGCK/GSD3e/PngPdsBNXHF35h8iSG+M2S/qRyAYYfVsy1fUkfuNxu9fIkcZvinnS2ZSUlu6izuKGYZNijJorK2OuKWnyotlS3IUvl8CCCl3d3M1M8WUQWx0YLiqd1VgUpcIADgXaPF7mdNx5Kj3BeKAPBTJkZEhbijoUjRW4uwOZxd+41hS1JEb4ECPqOdr7hOudQcLWZSQ8/lfu6vZ0dKFtbkXEyGmX2d7To2kEBSNIJieckpGjWXgsvPQ6n0UCatgsRgdvkFFOBqCwRhYOMmoVuR+zDab4weZIN8YOSPphS+ramaT58hX3q5YKCB5EJgmo5UtTAu2PHU/DhSJEXO1QwH49BrCqpOoiah6NRjrN79HqEz6BaLhZR8Qa1mLS8o7r1fB9kZrenALmxutuyljZQj7UDFF21pEo0O9vxuRQFL1btc2IxAUTMDrRLjN5Y4YDB+eIxmBTDhR37jn6zWdRNxE64tycN91qPdyU1exGQ7io3Y0Bx4KHdP+wYFojX2FliD4RfuFzEhvjVKaV/UOQy/7mmaf6Ly+1aLxcR90p6zitB2FTk9pjGdYXnspI0sMkpxSTGI3xsgdV4iAlFWR2G53U0ysfs7kq/OYuwF4B4pvD8YvRfKEBxXQFQ2PmIo2Oye5YN2Rt4V3G0nCrA0LdgkLWH2YExdHWaY08kDT4RHmiA3tkvKjPjdlpnIHzllcyej2bZ9LC9Kx3MpbVhtiGeeePVeqgXOtvdEDV5TxE9wJihEvNZD4JPVy4CiO9rmuZMRW5zmf+QpB4QnzNhcnjmhmewwMq2ldnhVAEYj9piC9vbUbgVQNxTBphNSRPKWy1ae18lDeddprKncI7g8KAgLcUNCKOB3Y3a9jcVTh9CanCMAHD02YFtoGCHgCbvj5TBFxXdM0Rc5fRA50oZEF+X9PD1WEDufDLsq+zTIgXTwyvNplQnrQeeuEYqdK8MpZrwplkeL4+nLFXi0m7Yy+XIRQBxJaW01m5BqpSSm556eU6ldMBIMZnGypNvZscntZN7T2dl6Js6CoeeFSydh3pJoC8eYK+vB/uTQg0kbu7UrllZO/SNKt9e0QeWi/2w9KA6ILKBFqmNjxSVhNbU3V3Qs4KcKdImhTMAy0ZS/SCzQ0KV2Lb0cBZguLubWaBvUHVSdfO+Dw6kN+fZueN2Q65ZMsFeLb58uQgg/pSkf5BS+knl5+FPSfrgpfaql6ci5QRico2V2deaoiZfo5xCtltLk0WEfJwoA9xxe86+Qp3FUTBSNwbODfsOWgAf9kCcBQAoGRlDO983d6e9uu3XsbrB2pRDPlK3/64G43xCjedzwNB3JwQcjxUhPnNlW+iDPemFPWnShtjMFxl4G0kPZ+GIItD8YXvuG7uRk75nr0rBghlL/vZydXKRXOa/klL6uKQ/oPyb/eWmaf7epfesl6cuDo44F3ziE7qxLMgbLzUAAkh5lZmFuvm4Dsg4gEhHw+njmRX0iwK4zowARto6bvuKk4XrANQAHOf7tq8IhXEBWEKVKLzL2HCPtYIFn3nuqwC3StkeOpO016IwTB11GLugjzcOMWygbift5WrlQuPeNM3PS/r5S+5LL5csgIcXoK3sc3dQSAEyVMKh/iJqcgmcHiAtRfZFoy4wDuw7QMfzbk/sfMAOlZs2YE6EmgyUGexcGXRqO5+tW2mzUVedXyn+jwd7X91aguxaSFssEFTXcQfOroL1eTUiFg5n0Z6Bwv99oerl6uQtATGl9Lsl/XeS/m1FKb7Dpmm2nnhiL8+loF5uKgMDoRsehlICoqufAAmFFGCJUqi1pJoR38e5K9amOz4439knKXsrygwqKdv+HJixsXEs6nEJNgCvZ3DQ3xW7DtXEAbhGEcjOQgB7HCgKt1JQI1kbnO+1DmGsqPtk4fgCw7g4SPZydXIRhvjfK28G9dPKm9/+CUlfdpmd6uXyxOP4pG6KlzMT3wUOZ4Q7YXB4rKlbX8/tcgBYmWbn3l0Y3JG1Qc1AwAWnhhSqM+qtO2LIvMEDXdt59MvrQeI5BjB9gagUWTBs6uWOG1IIPbOEva+9/L/XnCxVYd8O1M0D7jlnvHq5GrmoyvwbKaWVpmlOJf1kSukXL7lfvVyCuA2O96ihnift3lbPdy6rOkuRT1tO2vK9b4Ze9iNZO/7ytENA2u2SXgmcvUO88g9sFuAFFF31dhbmdktMC6v2HX/LLUKxLZ4Ux7stFFXb++s763nprjLLpperk4sA4iylNJL0aymlvyLpMwqHXi/XTACKE2XHBh5ij2/zSekqLn8pMDvX+e0J3KvMcYAbjglXHfke9dGvxcbqntGC9xXw8d3nAJmkLujiBFnGtACzsobkRDnLJyl2rKMt+slfAqY9LKgcU46lX7BF9tWe2eccz77Jvaf56uQigPh+5WfteyV9n/JG8992mZ3q5fLE2Rzsz5mSq5hSgMBMYeciNOSRApBQvT1bBtDk+7IgAeAqey/7nrZw6qi9nocKVeoWbwDgOA+GBviOle2ntMduhCwSpSe7UXeLWL53uyXXo/+eTogA+l6hBjlWMFvuYawMyp6e18vly0XCbv51+98jSX/xcrvTy2WKG+69snapotXFe88pJnzFAbDMhkFFBRQBNy9iSiyiis+cSXrcJCDozhRXMWFSOHY21PUWewwkXmf3ugN6SFJ4rQFDPIq+Ux7n7LRjM1d303jGAQD1dMN1RbkvxpD7KdX5Xq5GHguIbezhY3fXa5rmKy+lR71civjkhx2VmRBlRovsPRO8ZD6cB8h4SAlbGgCcTPypsroOsEoZHPAoA4jeB3ewAG5UqKENLwQhhWPIQ3NgfuyHvKlwnnibUt6T5cDGjc+xbQKIA2X1ms2f3DkF8DuAon6jFnsNRMa0Z4TPRp7EEL/lynrRy6ULk5Mq2zCwMj8W5lXZi3OHds6i+JxcTld3h9Y+4TFjawfvMwB9oKiHOFS2G6r9u6lQadkKAVCR9YlzAR9nprBY37e4UYTrIMRDeqFa+uJsmXaSAmQJskacZbNJlIf+bCrspwCtmxSw8fYAeTXyWEA0VbmXGyJlwO8yz7AzxUFxnntnqyXHu6rtxwBGHhBOsQX3HKO2ejwe1a4JeXE7nxTgyjXdzoft0O+fz8uiDoQY0WdXoQHu8lwXZ40sFLW6bK8Mvia0iK0SBgr268fx/x4UL1/6wOxbICXAwZqcyTiLApCkruqHus25XhgBB4TsuzKEZaf9nD1svSbjm4pUQqqH+B7GFI9wcCXOESmBx1kYQEzfnOl5WA+skm1PPQAbUPItXaVQy7F/etkxP45FxRcLxkGKwhiezeO2xV4uX/rA7FsiJXMCFFCf3XHgDGyk80wFD6jb4k7tnNIbCyACnjg2NpTtiXiKR8qgeU/hgKCKtle5Rs3eKNqnAo+rzmNFkVwCyAEoj0scqxuYTT89ptGBfaAM4hzr9liAlyyYZXGfsmPZRtQzgYZ2Ti9XJ31g9i2SUmV0dQ42Qlqap8WV3uCBItDYN0niM4815AHzHGNSBz0shjQ/D4ehIILvIKeiP7WiSIQUThe809wz1+JevZiC1PWEO3PzuEBYGxk6XkWHvjnb9PqN3AeqNQzSy6jJ2hiqZ4XPQvrA7FsiAA+pa16S322LeH4BxIW6Hlapq8Yts6U1dhzXproOx29YGzho2BRrVwHWHO+Axnl7ymDiDg9nkWzHWSt7tWXneyzgsgXCYwIRnCd7iglAMDg2TswA7lwqq/eUDiG3s3rfvE89OF6NXDQwe6A+MPvaCowNdXGi2OlNirg6gMtZEp8hMC7i/TjP4xKZ0DA+d74Aykfq5h2fKjzVqL2oqbyw3RHes6euiuxgKPs/4L6usENyLx7vuMxk4I4arnukrhPGQful9i9lvWZF2/QRe+lU3S0sl4HfMnDu5XLk8wnMnqsPzL72glpc1gckREY67yWVfe4qIUxwUbzcQ0w72CidlbnaDVCVIUHl9cu0vDJn2cHDwc4LU7i4d3pof0vHB4DMOJWgy5i4/fTU2vC2Xb2HKZYVhfrslGcjTwrM/qOS7jdN89fb97+kvABK0g80TfMzV9C/Xp6iwNp8b2ZsWnhJsfGx7wjsaqKoKIO6DTOCpZUeafZPcTveyM6hPx7uMlB3IyXfkpR7qOz78jvYltscFwqnjGfr0F9niFJXTQWwWES47tzO9dAjquA4e/VFgetP1Q0knyqyY5wh96B4tfIkhvgDyt5lZE3S71I2n/ykpB4Qr5k4ezpQeIZheky+FYWNDJUXRuk2Q98KwCeu77R3pAhVIQjZvcEe4gMweWEEt216/J4Hent/CAvy81ztRgCmgTKIAWjltUftWFCHkfHzYGkWgVPl/VHIZXbnEqwPR81UXXMDbXFc6Wjp5WrkSYA4aprmt+z9LzRN84akN1JKvVPlGgpgQ7l7KSaoO0Bcfd1Q7Jh3ZOcN7Fw8rrJzK2sLr6xvuu4qIcHXAIM/lGXQN8K1vcDqtP1uX8HGpMh6geG5KQBPNu/LVEYvZsHL1XAPWKfwBOE9XJt2y9jCyo5HZaZ/vc3w2ciTAPEFf9M0zffa25fUy7USdzB4jKCrsZ7vSyaJh8GwLaYXLKgVQdMeuiJ1WRgs8sTawFFBXwAFV0FLL7jatmBYCPu0uCf9cSwR4MULDdssJ4N73Q/ss1LcNloXx9EGY80+2WxcxfFeNKD04vfAeHXyJED8pZTSdzdN8+P+YUrpz0j65cvtVi+XIe4RJa+ZiiulZxXV7ZFiggKY5ENjR/TMDUAG5w3OEyY48Xhl4DJFFchnLrNcKP5QWZtSMFAKP3g5Lq+vuKIAIR56VFtXx92+CHhxT7QJAI7tr5cAIwyotEU62/WFgUXJHUEcW3rOe7lceRIgfp+k/yWl9B2SPtZ+9tXK2s9/cNkd6+Xpy7LJWZYzcs9tqTq6KufgWqq1fh33HDvowg5pDzZaOiwcfFbafmHzo+/sgAcYejFYZ6leVqsMt3HWinMGx1NZ+MHvgXN8Iy22U2XvFE+LxPvubdAf90ovY6K9XL48FhCbpnkg6etTSt8o6T3txz/XNM0/vJKe9fLUBWAhgwNGh7Ef1dDtaFVxLp/B4oaKuoEebye7RpkK54HhgAVghlpJPKSH+aBeS+cdJ6QQutru8YNr6lbodnHVlNjJLQVjLUNxuLdSlXeHE3322M4y1tHjMkt26Gpzzw6vTi4Sh/gPJfUgeAMEdZeQGo/hW7X3A4WDwkvYO5DgOBiqWyoLVdztb4BUaYdzu+OhovJLyR7ZzxjGtmrtONvCQcI1ASi2FdhQqNbOfN1OVylYHW364uDOKBwusEG1xx0ptj9whixrF3UbddxB0gtQlJlAvVyuXCiXuZfrLwAPG9F7XUTYl9vFsNlNFKxxpm4mBxN5WdxeUtd7O1jyfw9foVKMM0wPC/Lgas9q8S0InIWxHwlto1a7HZK+egod4S7snlcGSbu90bNnAHdXw+kHjLeMnfRFwx0v9INx7+XqpAfEWyRz5eoxACJZImwngMNh2H4Gs/IipWXcoNvcZN/BxMoK0jA6L8GFCg9zc5udF5Xlmg6eDkJci82z3Da3XxzLvbIwoLo6o5XOs2NXZd2jDnC57dKzgsaKYG2PYXRgdHti72F+NtID4i2SUu2TunFvUjdGDnFDv7Mj2pTCa0xhgydVefay/u7MKAVQwVHi2xE4eNOPZfF7bhqYF+ew4RRxhm7D8wrhJTCVmS301es3AsgwR2y3vo+Nmyy8nz0IPjvpnVm3TJyZ4BktnScrxbGPE2czgKGr1AP7v4NK6e3295znKXaUW0kqlgAAF7FJREFUAnMGVzKx0rnhjoxlXnGOL/eaXha76H2Wvfe/pZPF7Z9+735f5Vi42t+rys9GeoZ4C4UJt6pwVMC4ADScBDg3SkBzhufVtKn954ACIM0VKYFV8TntunpMBgv1EGXfATpe7IG/7Mvin/F/DyjHmbOmLut0hrjenjtb0gZ9c7a6jOkdKOItyVmWcownY+FgTk1H2GMvVydXxhBTSt+ZUvpn7esXU0q/07779pTSx1JKf/aq+nNbpbR94VBZUzcMBIZF4DOANyyOq4pz5grb45oyAEztvJKVeu1FZ1aAFWEvW8q2wU1FySx3hgBi/rkzVHfWeJ/ZusBBze2VUgCdbzswUaQjOivmntxDDFPkGmt27pZyBe5tG6dedX52cpUM8f+T9O81TfO5lNL7JP2YpK9rv/t25cIRfzOlNG2aptztspenJCUgSmGbK4/D20n63sC+gyV5NetDBXMCEJ2NVdYuTMs/cwbqwLKl8xWJAVaY7FBRoHXZBu/O3sp4QHcKsTcM1y8nyDJPsi8SpSPJwdXVZBYcxtHb5v+9XL1cGSA2TePbDvxfku7be7SIRt3Qsl6espT2NGLovHjsqmKvE5+kUgYawkmI4XO7Fyr0yN775lBSF0gAW1efS9uje5051o9xAMZzDhi542Js7z3MBebrYIiUThYPbvftE5hIvg8LwMc44E13pxWLhWfz9Ib9ZyfPyob4XZJ+3t5/RNI/lfRTTdM8Wn5KL09DmIAzZRvWVOdZ45a6m9m7x9jVSADFJ7izyIW6XmzUWdRHWNPYjpfCFjlSVJ4uveGEAAHgq8qg6P11e6EUAeMEkXPNgYLpAr4+MQC8Uq1mI6xaAcjriqo3ZVkvBzzvG86dFTuudOL0cjVy5YCYUvr9yoD4e/isaZoPSvrgkmM/JOlbr653t0NgLl4iy78rVcUneVSl8ylrHOuxdG7XI42O96WDAuBcVYCUxwOW18Ar7vnEJcsCdBx8PVhaOu+VdieTt7dQBkCYpS8S2EmHxfFeSagcP9+cy8esl6crKaVDe/uRpmnef+6YpinT+59qB75H0ne3b/+QpLuS/mdJ72ua5hOfZ1uX19FbJqi8O4qcXU8vk30mdRkiIEH83iNlxwQT3gHHgWRkL8APkJsqYvROlB0MbDj1msLp4X2vrV0PofFN37kGdQvfIelF++yBojZkmTsMMOMV9vAZjqdWpBQMkcUG4GN71F2FrdJVfU/9m0v6bHvPfZbK05emad7SHHepDLHdfoAtCF5VVo3f//mCYS9PV5jUAAW2Q3cElGEzztDwlNaKXN9BcSyA5TY6cp7HxXVG9p2fxx4mhAaVThnuBUaLms29eNEEGCGZLBPrJyzR7Y61MuhvKoOVp/whpA0mRbYPtSEZDy8o4TGe2CoJOqeK+EN1WWsvVytXqTL/BeUF+n9IKUlS1TTN11zh9Xsx8dxg7IWwLXcgUBqf/GS8Xp7ZIXXDXZxt4fDgmp71QjA3e4kAXofKwAI4ubpKG76H87B4OTukD7Uykx1Lerm95nZ77JuKkmIciyrueylzLx7IPVcwSC+g63tCw0gdeLkX2iV32att93L1cqkq89OUXmV++oJKR7Xpsb1Qdym+iv0Nj7SnoNUKRwzeWikKspbhOhznjoPSmeBM0FkebUzVdUqgsgKK7iDxuEm2CnX19pHdo8dJDtX1vgP4zjy5/kKZ3VWKOEkHPhYf30uF/o0VhXEf2Oe9PF155ipzL8+3lJMaMJwoVLkjBaDBltx7zAsHDbvoHSrYnbcPqKBaesye1GWRZQYH6jU2Rw9gHihYpe8IWMpceSMocq+5J+x5XsaLdvGmw4yXbQDl4TclA3TH0ZZi0XDbbF/u6/mQHhBvuTgbmijbzF5UsJpHCjuYT+Bx8RkguaWoV+js0EGVyU9bvuVpWRTCA6pdlgVE1wqHSwlohP0gJ/Yqs0I8DAmmTPyle6Id7AE7V9GdAfM5bFY2fnNldtjvtPfspQfEXjoTl7qIqJDkJi/LMinDSGiLh8ptbYCMp/xJXe92CUxlNosU4LeqbhEKD1kp4yJpx8NbvHpOyUZLMHOvsPfZx6JMC3TxMSDPm2ujHvv2p708O+kB8ZYLk/dAkXf8/7d37jGaV+Ud/3xnlnEYdrlYtgYBsxhFi01qKagITTdgDKa1FYqXmNJCU40t3mgarf7RlDRNML3Qxq3FBHVp1VStBNqtQWxxta2AwhZYLpZSFi3pptVskV2WZZmdp3+c8+zvec++s3NhZt73nXk+yS/z/u7nzOU7zznP5cTYv7hFcYmZGf6caEHF57eCFQXCRSGKTb/2+TDYRXa2wrDQK6x+/QRl3tDL+rtXOM5LRk/z8RwZp+ihOLGidZv6tz9c22al+D8aH3Z7FfGscDM8pCCucVyUvJJ2DDSO6XizWYZx5bxDdMPQfhYa9A6B41DYHSXReRItqOj9jkuWRiFpq1/HPrrn1oWwFaAxurlJb3M7lI1pfz5F0C5f6sIb16eOxWoPhK/+Pci5w+EhBTE5/Af6JJ2V5RZPmzPcxhq6AHke8XMUR0zMF+7nNInDU6dfnm8UzHhdGxfYz6ExFjZ/lsf7xXlT93yfTGf9eTiNB17H4X78p+Hv8v76PbEPY80zWkHMYfLwkIKYAL2B2m4ltaEx7fC3LXQahbOdh5tuzhPOu6BMNvfH2ML14TlxGBuFbzbiXGM7f+mbe9hnmuu8TNdeej3Bfr3/Q4hOHeiCs+OUQivYrXMpGTwpiMlhXGz20T98pB2eempbPO7iEsXOhTSKT7TaIm34yno6UfJMkFi/kHB96xSJQ9EomG4VtmW3fsSRcZZjlBQ9o5v3c0H0eEMP1YEuVpNwv69L4/OevsZLDpWHjxTE5DDRWovxfXCkBRZF61A4HiNf25jC6Expn9UOHcfo8nxdwMbD+Ta0Jt4XQ3Hi0N63WJU7Fl14hiO9vf7V3x9F1/vt7YqWaiwj5p57n3uMcZzJcJGCmPTgnk8f7nmKnFt90bvsObguDnGd5dbz23qgY5pf+0vowuKW4bF0c5TrKMIVvbltOqAvGtV6b92qO77u7w1tdKdLG+LTriUdl109QDfHSLjHnTH+Xh/uH6Jks+ynzNemKA4fKYhJD/6HHrMrPNTEc5mhy999hl4rLTpNYvpaHG76+TaNr7WcXOyeoRPbOPT2Z8S0P0+988yYOB8YvbqiN3Qnzgt6P/w+X4+a8MxpOk9y/N4dpBNsn1P09z5FqXoTq4wnw0UKYnIELgIuXDG/2ZmhdyGkKIger+cWntMWSfVtIjzPrdNJOq+1C1ecd4yCHYfbMbwnlgmLC1lF6/I4usKsfszbuKEei2FE3g5/7z66aQL3LsdSaFN0YU1P0ht3mAwfKYhJX+IwNNYujHOCse5fG5/oc26exjdOGTrG7JU4VI0OGD/noT/+/iiiLpjtvN4YXUVuv9YLKkRLFLp1mcfprDo/dyxdCTLPeW5jMuP3YJJu+NxasR7SlMPk4ScFMZkVF4+n6EQIOiFw8Yge3mgZuRjM0FXAiYLo+HMmKPN7Xt/Qt3YpgrimiccFKjwrLiHg7XILN1pn6+hS6aLluY5iOXp2jBd+8O+Jz1XG+ctooXosow+T95BiOCqkICZHxYeYLi7RI9wvqDoKmVtR/dL1ZppnemhK+yyFY9CbsXKoz7PaWMk47wi97Y7zgO2SBlEAoZs79WvcMo0boR8uvB4IHr8HyfCSgpgcFf+jjo4HJzpGPCMlxudF3NKL4uAi4l5kFyIPY/FyWzGo2fOMp+q5WKCB0I62nNZEOBctQq+G7av1QWd5+tyhO5BiCM9M2F9HV4sxetrd25xFX0eHFMRkTtxT63/oHo7jAhUrbJ8EnEBX7w86awuOzCH2uUF/T+QApa6iF3Z14Y3rL49ThqMuRF7Itn02dPOSLsrTFEF1AR6v7T5Y3+tD9zG6atguiO49dryPLoJ76C3ekIwGKYjJvIgWkVtsMcXPRWJD3f8RxVHhQ952bRHoxMar60w259uKMu6o8QIN/tlDbVzAYiZMOzcYK9X4XKjorZQd+xgdO63Tpw1W94K60SpMMRwtUhCTedMv4ySKmzspDtDFJ0IX4ByHvnE9Zy++Gj3BTptV4nUMo8Uaw3l8zRO3Yl30nNZCnaZb6gB6PeUxMB16q2VHqzZOK/yQIojpQBlNUhCTBRGzNOIxt5iepptvi+lz0fPrq+hBb3GG6PBwQfLqMS5GntIHRwqUZ8/sred91b4YjxjXWolludp5zeisic93z/k0veLqIvhUOJ+MHimIyaJwsfOsFp9TjMIWnSgxgLv1uMbwmIhXuBa9OdLREoxD4jbGcaK5rxW+WP+xn+eb0O5W4LxPMfslpgsmo0kKYrJo2jlFL+HlwuTWWMz+aENhpjjSSnNL0MNwfLnS5+gVwNgO6K3K44tRRbGNQhzDa2bCvXHo7vtR0H0Ivq/pW6y+nYwuKYjJ88Lnz6Cruh1T6qA37zh6pGPIjltYsYDrFMVjPR7uP0BZqhO68BendYrEsJj4/tj2YyhhP/G4P8vjDaGzdPeHLaYDtnGZyWiSgpg8b9yqg16x83qG0VqDXovNM0Xc+ovWmuNC5lbY/uZcjI30e91q89jIKHjRqpugy2eOFXtiLnccDu+jd9H5ZHWRgpgsCW4dxbJfHorjsXsxgyM6VdwjHQtDxCFza33FX9qYN+zPi17wmGcdHSHx/dTzsa6jzy26AO8Pn1MMVy8piMmSE4eQMQTFvcvtfJ17b6ELdXGHCnTWmS8ov55eL3YcikcBjM/0dsV9P/9c+BoLxPoQ2a3Cg6QYrnZSEJNlIwZze8n8NnPE4wxjcYiYAePPeLa5x5/v5z2tsBVGv87p9wvfOkxifGOcL8x85NVPCmKyrBwMW2u9ebjODL0B2LEOo4uT0RVOcO+wW3q+xgrNcwj3O7HwBPQ6cg7SawnGMJp0mqwNUhCTFcGHmbGuoe8foAijV+b2NL7xcA0UUXSLs62vGK3P/c2+z2H6vGAUtih8sTJNO9eYrA1SEJMVJ1pbMag5rvY3QW9l63aFvDaExkXWn9NmsLiXOwpdzKSJn/09ydpDZjb3VUOApNFoaLJo4lA6Olti2lwM8vZtujnmgui0udOz1UxMEVzdmJnmuiYFMRlaoqOlX3WZOCSOgtimz40118avydphPoKYQ+ZkaGnjCSNjfa6bra5iWn/JfElBTEaCfiI31zVJslD6FRlJkiRZk6QgJkmSVFIQkyRJKimISZIklRTEJEmSSgpikiRJJQUxSZKkkoKYJElSSUFMkiSppCAmSZJUUhCTJEkqKYhJkiSVFRdESedKOiTpsnDsakk7JL19pduTJEnirKggShoHPgZ8NRxbD5wLvAZ450q2J0mSJLLSFuL7gC8D/xuOedHGLACbJMlAWbF6iJJOBS4BLqRYhACY2V5JO4G7gT862jPOPvvsZW1jkiSrkx07dszruhVbQkDSl4A/MbM7JW0FtpnZ385xz18Dl9bdqWVuYpIkq5u41M5NZnZ5e8GyCqKkq4B31d0T6IbHJ9fGvdvMbl62BjwPJD1tZscNuh1LTfZr9FitfRvGfg1kkan5WoiDZBh/WEtB9mv0WK19G8Z+ZRxikiRJZSCLTJnZFYN47wK5adANWCayX6PHau3b0PVrZNZlTpIkWW5yyFyRNC7p3yRtq/uvknSHpBsljeT3SdLpkr4u6WFJD0r6QD3+Ykm3S7qlBsaPHJIulvTvkh6V9Lv12Ej8zCRNSvq2pPvqz+WaenyrpF2S7q3bq+vxEyT9fbj+yvCsocryWmjf6rnN9diDkr4Rjr+j9u2DK9YBM8utWMm/DXye4uwB+BSwkRJMfvGg27fIPp0CnF0/bwAeAc4CrgVeBbwZeM+g27mIfo0D/wm8FJgA7qv9GomfGSXaYn39fAxwF/A6YCtwWZ/rPwp8rH7eCOyp/V5ff2fXAbcMul+L7NuJwEPAS+r+j4dzN9ef9d/4M5d7G9r/oiuJpNOAnwduCIfHKdkzM3ThQiOFme02sx31817gYeBUSt9mGN2+vQZ41MweM7ODlD+YX2JEfmZW2Fd3j6nb0eauDNggSRQR3ANMM4RZXovo2zspMYHfr/fPlsW2Ij/PFMTCnwEfovwhOX8O/ANwHnDbIBq1lEjaBPw05T/2FuCTwHuAzw6uVYvmVOC/wv4T9djI/MzqFM29lDTWr5nZXfXUH0q6X9J1kl5Qj20BfgL4b2An8AEzm6n/5DzL6wsr3IVZWWDfzgROkrRd0j2SfjU86iZK3+6ufV1+Bm1iD3oDfgH4RP28mTpkXk0bxaq4B7h00G1Zov68Fbgh7F8OfHzQ7VpkX04Evg78JGWKQ8ALgBuB36vXXAZcV8+9DNgFHD/oti9R37YAdwLHURI2/gM4c1BtTgsRzgd+UdLjlKHXhZJG0Wrqi6RjKAU1PmdmQxfmsEieAE4P+6dRrKeRw8yeBLZT5jx3W+FZ4DOUqQGAKynDSjOzRymC+MqBNHgBzLNvTwC3mtnTZvZD4JvATw2kweSQGTP7iJmdZmabgHcAt5vZrwy4WUtCnXP6FPCwmf3poNuzhHwHeLmkMyRNUH5ufzfgNs0bSRslnVg/Hwu8AfiupFPqMQFvAR6ot3wfuKieexHwCuCxlW73fFhE324BflbSOklTwGspc90DYSCB2cmKcT5lOLmzzukAfNTMvjLANj1vzGxa0nspdTXHgU+b2YMDbtZCOAW4sdYHHQO+aGbbaijURsrQ8l7KHC/AHwBba1UoAR+u1tQwsqC+mdnDkm4F7qfM4d9gZg/M8uxlJwOzkyRJKmt+yJwkSeKkICZJklRSEJMkSSopiEmSJJUUxCRJkkoKYpIkSSUFMelB0oskfV7SYzW39A5Jl8xxzyZJi4odk3SFpBeH/RsknTXPezd7ubblQtK36tdNkha8bnjt35alb1myHKQgJoepWQQ3A980s5ea2c9QskBOW8bXXgEcFkQz+w0ze2gZ37cgzOz19eMmSmWWZBWTgphELgQOmtn1fsDMvmdmH4fDVtI/16KdOyS9vn3A0a6R9CFJO2vx0GslXQacA3yuFgg9tlY9Oadef3F9xn2S/mm+nZB0kUqx352SPu2VVSQ9Luma+sydkl5Zj2+U9LV6/JOSvifp5HrOS1ldS0kxu1elKGuP5Sdpm6TN9fOVkh6pxU7PD9dslPRlSd+p2+FzyZAw6IoYuQ3PBrwfuO4o56eAyfr55ZSyTFCspwfmuOZNwLeAqbr/wvp1O3BOeMd2ikhupJT4OiNe37RnM011ImCy3ndm3f8r4IP18+PA++rn36JWzKFUXPlI/Xwxpf7eyXV/X793USzbLWF/W73mFEru8UZKEdd/9esoxVwvqJ9fQskxH/jPPbduy1zmZFYk/QVwAcVqPJdS7HOLSvn3Q5Radi2zXfMG4DNmth/AzPbM8frXUYbuu+Z5vfMKYJeZPVL3bwSuotS8hG5ho3uAS+vnC4BL6ntulfR/83xXP14LbDezHwBI+gK934OzyswEAMdL2mArVesvmZMUxCTyIPDLvmNmV9Wh49310NXA/1DKM40BB/o8Y7ZrxMIqOy/0+njf0Xi2fj1E9/u/mGrM0/ROOU2Gz7O1eww4z8yeWcT7khUg5xCTyO3ApKTfDMemwucTgN1mNkOpojPe5xmzXXMb8Ou1xBOSXliP76Ws99JyB/Bzks5orp+L7wKbJL2s7l8OfOMo1wP8C/C2+p43Aif1uaZt5+PAqyWNSTqdrr7fXcBmST+mUovyreGe24D3+o7CQkvJcJCCmBzGyuTWWyhCtEvStylDzg/XSz4B/JqkOynDwKf7PKbvNWZ2K6Vm4d21FNnv1Ou3Ate7UyW05QfAu4GbJN3H7CXyL5L0hG+UZRKuBL5Uy2XNANfPcq9zDfBGSTsoc527KQIYuR+Yrg6eqylzg7soJfz/GPC1a3YDv08R9H/045X3A+eolNF/iK68VzIkZPmvZM1TvdCHrNRZPA/4SzNL620NknOISVI8vl9UWcv5IPCuAbcnGRBpISZJklRyDjFJkqSSgpgkSVJJQUySJKmkICZJklRSEJMkSSr/D27glmz40Jm4AAAAAElFTkSuQmCC\n", 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\n", 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3cpzncWrcI7GGR7nI7vgdHBc5a/73s9yWKWP7J0Bppk3gt2tfekmJ13VpggkQr0FaQz3gQWAwnj4Cd22DcwEHqz1u29sZlNjgCDlhQLdOgNYj6YIGl6ldm1Q2m1wEr9YJ0PZ9m0e1PS+56AxxXnVSn6HVP7fTslOzIWyLTsmjaMO2fGyeh59da5eznZHn2dprXUyC6xjs2tjGNh/dqiws2I6R6BxrCw6povaj2WubsmiW+zrJBIjXKC2g2VPZev/sbIFdAAg4N+x93RaGYhsiTo8ztYNa6zaTsTfbObXOuLiXyowAAat7DPIWTAEKwAhW6KBk+m6m4ljC6FiXEqMvnGuvKmojE1D0nGz/M2j6u0GQ73ixo20GROccH6ZWGrLDZlvMYguObQXzNsvIv6szmbAHm5FS8gw7cxt+1efiuxcdc9tBcgLEK5aWwSUVCBgUOAscRmF1ErvRWcaqmENnHF5zlvGgY2B5uwsGAI5JZRI4URapaqbtg5vUjJd7qSq7HR+OjbRN02o0x9jmZmCeNecZvDyZ2CF1L+Oy/I4nNEgbSNtJZFuZrJ3mOyaENm3S9tBZxs4u7Jzud5sfTvsAt9MLtzFDnkO74BXtJ2NW2jrcbBeO2nZ4k4HiNoPiBIhXKACBVRNUPhwnydjmB+AZ5Fx/r63UktSZnxcY9S+pKjgAC9iSGbPOuGKzg7md0YFDAvCwdxJvNwAKqPrl4vgd7XMYyzYvrdVW51K3Dh+YUguIBnmuDXPDg++wGbNK+sQ16a9BkqwZtl3mfIDh4yAyM23NBO2Ewbm28fGM+6YthGfsatu2IxooAVfO45hVxr8Zv1Nr77xtMgHiFUkLhu0LaycC8XbEFpJb3FaVZta2PQggcWl5h+zQl6gdBhaDCxXY9qs2wHqR8X20mTGwOcdUOrDcQMt59IUBzKBvgf1M7dgz71AiX9PhRWboVtFRJ50i6NJaLavfFvbke7HKytIEHL9K8Sgzgdjp1F4D8wXpfNg6/XvyHCxtONVOasEIO6L432zQbTJR8u4ZPG3uuK0yAeI1iF9+q2TJ2DZjhsLgMXAwmABEA6ArorC9XQQpqYwLcDxKHXCumH2n6R9OHwMiIOZipdvAP7lY15CQEwolOIQHOx9eWe7BbMb2L9tQ28ovBCe3v4E90G7fDh+r74Agn67u4zx0q94+xmX/W2eV+4XKTcgLk4jXg2kHrb34rdOF6/hZmkFyn37PKDLCO4T91rbX2wqKEyBeg/jlsV1sm5NgmwrFy+pYM7NDD/ptA7+1ySEcDyDargcbIPbR57Te5VbNdb/tMW2dF5d5bDneYS4Asr297gPPhphB2wYBgvb5bguwbr3vAEx7DNu5jquQu51kHMLT2ky3Xb/LGFCZBBbNca0tsHWuJeNJwRMD1Xr8fqU5pwXf1yHXeQLEKxJ7gP3ye2Emr/hmNkK2RpvSZ/BDPTMzsXpjdRj1iPNoExCxoLajuhu0tzHd1kZqQz/3n4xZiL2c3BuMxR5PBwXDmjje4MPkwvM7S2E52Eptu/RKegSkc2+eeKJ9M51vVmpwJ6bUAOWQKWeZsN/2S/cBe7DZJ+cZqLnX1tlDm7Tvhbyi89r/Wzuzr2mmz7G3kSVOgHiFYlD0S8cngEipewMMzgFUYQcJ42RIxmEW7XKWbagE8Y3L1MHWrjZHri+q+3FqDjCD2wN+J2MQQXzPHsS27dljjRgM+XQoC4I9lXPMdmBsdr54UafW/plUFkfbDu42W+a6K33aTNE6Zjr9j0rszBKzdDutAPKn6tdc5ycVnNjfTk4tALZAD9ByrTZRoI0EYBKgL7cRFK8VELuu+wlJ/mySj6Y8z2/s+/6PdV33sSR/LiVU61f3fX/4jGZeedkGDkkFQWZ1PI/YzAAJAGk/Y8bwNGO12UG+foEdDIyDosvYHsQAoF8M1latploLYHam7Xw3OFl1bz3BhAuxwH3raY7aSMbhNsmYdbbB3gRB28nUBmvbM057rfreDnKeJ8+UiQR7Z8u+zDINrAbE1jSQjONE7QQx2PIcHZxu217bZvvsLU65ZFJ1GJPTLm1ftFyWUXST5boZ4jrJ7+z7/ru7rnsjyXd1Xfc3k/zaJP95kp+c5Nck+ZPX3K8XJrwgtv/AtJLxS7XNbsP2nVTHxgeH8+1ZTqoHNhkH6TplDxBGPCD9wjNoXHKe++AcA4avwYBtw2Z4HvTJQO2YRpfoIszEbNTP1A4opyP2uVhNx+e25yOt/czOlajf22on2s7G/20wdwtO21iVr++QoGc5YNJ8N1jOmu3cB2K1l3hOxyfaS08bx7nogPJ93Ra5VkDs+/6Hk/zw8P/jruu+L8kXpzosN7nBtttWNUR4cfH0ner4pNYYZBvOCNgMoRi8uLAwgwbS6zirdhn6BHA4U4VBAFNrQzho006SWfO9fQ6woaTaB/e1zyp1y0DbDBSr83upgeDz1DxmhLg77scMGtlWIZvngzeXQHPu0axylroEAyomTM5qZ3IRtAzuBm2zTNiavf6tjdMAaRunJzSO8bvomomAPcfaeWYThM+97fLSbIhd130yyU9P8p1Jvj/JZ1JK2v2ql9WnFyG8SF2zzeByou0OabEACHZ82CbZzsr+zuBqjfLJ9oGUjNXCFgxhEQz01h5qULSq6Lbmzf9MAuvmODs5rKZRWZrzXVi3dSIYYH3POJXaGDw7DmC+9M95v7RlGypgBZg4ZtQsKxmDYXSMQYdnTD8sZmNtu22wv7NVkovPivvnfTXQ0mbr0ScQ/TbLSwHEruvuJfnmJP9l3/cHKaXsfu6W4z6T5GuvuXtfkPASMlMzGK0SwmiY0a3mIU7Fo9Yhwb5tGIZVQVRkr9PifhHDCCWnH20WRq+2WPjKQO7FowAGVEcPULOvZKweG/TNbrAF8gz48zostNEOWvePHGyHxNgE4GN3UipY39W9cR4sG1vscks7tlV6pUSrvIjLdsHSvESpnTvbwrN4VttSBn18a5JhMtsG/LyXmCtak4MLgNzUSjhd13k57W/p+/5T7THXDohd1+2mgOGf7/v+W5517NDhTw3n3QjGvs1mxAvXxg+iOpL32qa62Qb4OONUuTawG2/vWapq3rIVWJKDpLFNcn1A03nWBOra4cNAtrfZ+dK2WSXjQd3ea3Q8YT+AzXy4D1RUJgEcANhaAR/3wx5nAtDNvgAEQAwgNAN9mjopuJ+YEZy9gYprb7+ZnNeJhqni8Z+n2pnNmvlte7VHJotBkd+QtltTAdvbcnKOeeT94FhMCK13m8mhDeN61aXv+7vvdcx1e5m7JP9Tku/r+/6PXOe1r0PaYOPkYiaDWYPVI5gH0hrUYTtmXH7BDaDtWh8AkFV3wLANWnbAMdckbtC2xnuptryoDdv+6LvvoS0u0F4PxoaKTPVwG/Jto3PMJJVcDjJmtUcpoE7/94dzeR52InDPNi20jhd+U9scHRbk54/jiL7b3mlHE8DiSc8VzOkH5/CMPPEYVC1MBLwrgN262WdPPMIkxJK4eKS5jnPrb4NcN0P8yhTG971d133PsO339n3/rdfcjxcuNognYzWEl4wX0nnBZm0MWIDBxnOrfVZ97Jxo49q8eh92O17gNmbtNIWFmnWYlTBI91PYCYDoAqj2khtQDIQAOeftpE4WSS09hmMEIDfImF3dS3I/NeiauM2HqazW7NbPz88ZhuT1aGZ65gx4h98ALI5ZBNzWOnep49o8ZjPZyxwlzhPf1afFtkLaMOt30HoyDudJxo6+bXnS/GFTtQOG9/Q2gOJ1e5m/PbfULmt1LBl7Hf3yuNpIy0LYbg9nhm2wGgY2ah9sxaqLbVhsM+vYpM7wjpNzxW2niWFTWqaA4bI5r2u+M2DaaswuLWbGd9o8J9TQu7n4guK9hundT3JvlnSzpF9XgIUpmt3Zq8592UHVsls7KOxEATwttluapbUB6mb9dtjwfLi2f1ezattfbadkuxf+4l3CLNAGkzvQmn6gknuQAu6OWeSeXppX9orktt3PSxXPkPbIOXaQF88siqDc41SwQ/UFVBzD5+wJ1hIhdc3G8qQOJDMvUgWjdugbAOHzUJtQY1HjULu5loHGYGi7Ge0DGqi6BJ7b9uW6gkwK9IPrnSY5Gi50mFK70QHTBgezMIALlZ2gaNhkctFL7NgwB1IDDi4t5uo22ENt0jDIRdv4jupuNubBam+zA+6d2cIkl4zTQDFt+Bq+RzQJT4pMZmu1eRtlAsQXLC1zsLROldbz6EFiu46ZIp8MVudAwxba8Av2eQC3HmaOtVHdYvXN92LVbdu9e4CbHTkejvaTsZcVJkMRWoeW8AyfZpzmZtXaAruxep6MzQJtHm9ykUHbbME2t9F6uz3B8Nxtr/MzMIOkz86kae8Jlm1Pe5s1s9my3Sq0w8CSAoJoIW1/fK69/LdJJkB8AdI6DOxtJaCZF9LpZO0Lx36286Jvq//XnrvTtAODYZ9VWTyn9AGW5nOxr3GMvYyokL6uBzyqpdUwjm3ZBQwU58k6RdXlGa2SvJnqQIClEU5jtmW7mLNw/Nx5bq6b2NpBW3tYGy1gBskksS1l0RPMessnv6u9uLBfq6kGxPYdQVVvJ0b6xzuI0J8d/W+Qd/YN0QzYn20v9Tt5m0BxAsQXIAAgNkOH2bTqsdmFByazvbfvqF1YE0HSdrr45U7qQCJ2rO1jW2nG4m2wRKtOl8W4GZhoh+PYtpvx9TAFAHKO69vofFRz1GHAi9XjXDOR/jqLZK52DnMxKycZx3ZyDpkxALBB0SyeZ88z2Kaye0kDfzLZYC/lWdsbbXXbz52+OhAdUKVtnpML7dph5eft+yNsiwKzACTXbcH6tsgEiF+gMChQ9VhEyAyM4xBeRAYmL+dSfxxD+XjYUwugDAJCLgzANrYn48o49K21HyFtzJqZBN9duYVr2wvpEBauZxWaT2xWhNlgK2Qgbob2H2UcGMx1zNg8yP0cvMQBfVmkANHdoU33l3OYlGy2sIrrZwMAtYHxDDIvDwGQ0Y/9jIPTk5omaK3DKn/LZLET23F0pPMAcop42IO9TW3nXtz3O7MBEDfVg9+aGW6yTID4AmXbwG8N4X6BUbmcgYGHmPY86NfNuTBADyIf55hHpC2RD4A688Je45apwXz31DbebntLz5r/6Q/XnKfmVdPGnZRsEcwEsKRNxrGQ9nIbFNhmDz8gYBWZSWg/yYMkHxiufZYaAO/g8j7j37G10+ElJ/AaNmYV12E3TFQAoPuGqQHhnYHlmiV6Umx/Z/fTfeF++N0xafBnRxb3so682ZtkMbvIdm+LTID4ggRAuZuxUZoXH/GgPWv2JWN1ldhD5xH7RQRIPYgc4sFgc7sMEJiXawq2BnPac/D3qjkPFtfmbifVBmV1PhmzVAbqIgWY9lILNjzS9czcUOVaVmPbXOuIAIz8R9HZ+8MffSaQ24vKe7KbZ3w/BITzjDbZPjnaXALLbRka13Ph4FYj4Dd1phD9MFhvK+7B5GC7sc01sHWba/y+zYcbaZ1z28wvN1EmQHxBYlXOWQA7zTHbZnLCTuzESMYODg8yx56h9roCDp7N1l5lsKRtVDgPLAO1Q3Lok1kjKhXnMzEAGi0gmtG1zIKByjFtMLrbIJRmm82R8+0hbm20BtOdFNbTzZLF+mJtx22ed9pw5o/7yDFtH1pnDWJgcbyfn0syBuNtzMxhQPxvFohWAuC5QIXf1zb+sbWLtvd6W+S5ALHrup+Y5Kf2ff+/d113J8m87/vHV9u1myWz1ODppLIL9iGwuS5jAz0vKC+rQaudyWEJOCOScYFP2sHzaDbieDfP6gCa7X872j7TefQFxsj5DuHhei3bRJXG5sh3zt3Tc6OQLPa5bYPQ92H7GqXGGLyoybNsByeLPcM2E3BPLpkG4GDrpU8IvxX2yDYm0fY6AK4NroadOezI5hNPOP5NW2a4k/HEHf3PuzJLZZrWSpigYIyc41jZ2yDvCYhd1/2mJL85JfrhpyT5eEoB119wtV27OeKAaHt8bfD3scm4dp5VmVkuDhx7+LwmS8uOou+ADmleDCqyE9oByT30GTNQshbafGIXlSC/1syjTfszMDurArUsGZfQct1BHCI23vNMbIKwVxkboe1tLaDyGz0dvvTb6aOBAAAgAElEQVSbUn9uW11Ds3dCXWDXHOfQFwQzyhsZOztsW7UmgNhT7LxmH2Pm3EYV0GcmmtYZRH+xD7bPhPfE7xhA7RAt2kAum2RuijwPQ/ytSX52St3C9H3/z7qu+8iV9uoGS5uh4fAbD0jSy7A38sK2sYMAGeyztUeZmTlImKBlO0pwepAm533RudgmAUTb8DiWuDTsTgZDZ1c4R9ZsiIFlWySMzmreveHzNMWDb+bkQg2EicAQt8VrUvDBtsYnw7UOM7aRGkgtPBPun+M8ufh3XqR6zx2+RFtJBVSexV4KiLaefvrjiQkxuLa2VbNjv5ttNpWvxWTEdZw/zWRop43v5ybL8wDicd/3J6VQTdJ1HWNvEkkb8U8WByDhijdWxfyCOzfVHkkGHowKFTKpamYyBknsby5bdZYxKJxlzFq2xbLNdV+Ac2uPM6uwqml7loVrO0g4uWg7w8DfLofgUBCeGUBg1gRw3UkFWHvhDYCcS3/nzTbYn7N1kmqD47nYYWTxBOEsHWymNmVQ+chqatsu0QX001WVfKzTKs3qMYGQLmkmjIay1PmE9LjcmSfS2+Jpfh5A/Dtd1/3eJHe6rvuFSf6zJH/5art1M8VGf7+wvHjYmQAt/vySJlUdZE0VbFTJuGQ+dimrRHhQGfjOaiBuzHY/pAUChMFiW1Mydpa0FWHaZ9Jm8Xg2dRgMAOWSZBm2PU7yTirQwxy5d08yZng2N6wyZo582vnAvfEso7bYBwCjpqKqtuzYQM/qirYtY1uELbc2xaSGH7VOnT2dj2ngSYpn3qo+7xysGvBuUzGTOuG5nJkLPXCeJ5Tk9oBh8nyA+LuT/IYk35vktyT51iTfdJWdusliIzQvH4PFQBj936qsfnHNeqxe8pLbTslABiRb47rV9uex9XA+zGUvF9vkOMCg9apzT/bUug/c+zaPrQc2RWq9zsp+6oB3DrPZDvfZAs62Z7/NKQIw+nflns1uvZ3nZYaMra2tVWlnjfsDw7Za6onE9wogu1AHglniNBVEfR0HZ9v8MsvF35LrJmOGn9wOdTl5DkDs+36T5E8Nf5O8h7RgZ0cC7G2Ti0VFUYUNmh6Y9jAChizGfpZxqSw8tQbOZKwuPsvbis2Q/wEFgJ24vG0ZCvaUm4mh5prJISyoxAQAo3LVlpPhfv2MrB56wuEctqFKttk+HAtYWXUEdF3LEOAhvs8OKJ4J1/Bvb/NB+8xa9ZPvmDtshknGvylVjshusgPLvylq8SrjZRowI+xqm3PWt0Us2GFIf/3Mb7pcCohd131vnmEr7Pv+y66kRzdU7Gm2mEnZ+DzPxWrPqIvMtq7czIzNQGYAYw/sU21qrSfVaqRVSYdieDC1tQxbz7fvJbnIjuiPr2N7owOnuU/bwzgGRwcAZo+zUx4dCA6YMGif6Bpml1zHz6gFantuHTbTp5b5AshOmzZmGWeEMNAMgM5OcdwnbWA7bHO86aOrAvl+HFvKc3aQPzZKADqpwMh9+llQHbzLRVBv19S+6fIshvg1w+dvHT4/M3z+6owLC08yiGvItfF8sAnHDiYVGJNiM3QNPGxOfiFbta5lHK4v2IoHk1UdO3CS7ba4NuOGe2oHQxubaIZllcyDFca13NLWOtVOZhZEn10s1xMJ7Oqy9U0AXTN6ix1Me/pupxcOHn6jln37+XENbHKe3LaxdNTr1gzh7BDUbDu26Lsr+HCvtAujNXgTStSKtYsWELnObZJLAbHv+3+ZJF3XfWXf91+pXb+767q/m+QPXHXnbpJYTUQANwdoex0M25sAj73UAf1k2A/L2WnaQn3mhT/OmE0k4wHTskXUSFRxp/kx2Axa9m5zfdvIkrHn1iEb9mS35oNNqiNlo30OgL6XEsu3q+3bAAeG+Ch1snHBCPffzpO2PX4P284AI1TUNocb9dVi+y5twjod7+nnty2mEOE4wn88EXif78d1Hhe5uOYNz+Q4NXyrNSFYHJxudnsb5HmcKne7rvuqofx/uq77ihST1SSD+MW2F9IhN7w0hILwwj1NjVMzm0oqc9jJ2Pu6zZvsitYtmFmV9YuOuo3taKnrcY6N/CvdRxuAbceGnQZsN0h7bRfUZy8fQPwb4Ma9OluDc7kHe4Xpj/sC23NANPeM2cIqJN5jTBmt88BB6Umd7Ogb1+GT3xSg21aA1Z7kvYyjC3je/K44SPYyniiT6ow5To1KsHmA/9vYV+7V6nc7kXGfnLen7bdBngcQf0OSP9113QeG74+S/Pqr69LtkNaZgOpjwEy226/8cjv5n4HfxiwmVR1zbJ4zPjjGrNIqk9kqgppv5wR9MBAmF+2O0X5UN98TQGLgpk07PFwXsA32ZolUQN3qbGu75HsbfGwV3tfi/luvKsfhlLCX2MU0fP+tzJp9ZliYIVrGzn3YNst5bawnQOxccK7bmi+sUbRVljinfU4G8tb5d9PlebzM35Xk3+q67n6Sru/7d6++WzdHrI4CfnjkeOlgCRjjHcRrVZQXy1WObdvBiG8mstI2lgXF4G/blr2nrarZiqumOAPCdqr2xTFDtHC+VVGrqGcZP0MYSJfC3OwMeZIxwBymVNe2N3hveA4O3sZ51arFnfbTR+6jVQOt2sNoMW/A4lx4lt/dgGTAaWP4zOINQLOMNQPbTgFgs8ekmkLMDumb7boOvua+nXLpT/rq+NrkopZw0+U9AbHrut/XfE+S9H0/2RBTX2QnxPPCIq5m4xduV//Tls+xoBLupNgrAFQfD9tDAEe/6FZnk7GK3mY7tH1o1TIXjzALaVlmGyfZipkdqqodULAdvM52FBxlDAS2OyYVCPBO8wyScYAyZgnACIDZZKwuJuNoAPrDs3G6W1uIwaxu22/tSYHfjf1uAzBrqxPxCeA6zIh1aczymGwdGuYAeq6Nl5rsK9s3HfFwG+R5VOYn+n+Z4n3+vqvpzs0Vp9UdpxrkHbyKbcf5vQgvocHBLzaAyuxOeMxpLmY/OJ5slsoAABF/epDzYjsUo00ndCxaa2dKLmahWD22fdKMiGNRCW3nWzfP0I6heUodQwMgqYkrbbN32JMP6umO2iBz5CzjUCDYpSsCeZVABLNF1CbOJ1ifgaxlZmaTAGFbdZz7aaMJ6P8iNTIBx9IHUovv0nZy0cFHXxxzSV9tW7TjhudyG+R5VOZv8Peu6/5wkr90ZT26weKXiTxhxPaek+Z44tRcAMCD0OEXBqlknD7nMAtfk7YYMHgTW1tiMi41z2BCTbss/IPvs1RmxYBqPd4Gc85DuA+DMH1s7Z+zXAzFgckcDJ/3Uj3ZUbsevKj5AB9MEvuaNQCYm1MRXa8R+yL9830AvM47xzvt5+/Jgv2USkPFj9pHYLt3hz7Mdc4bKROHYwY9sfC/TTW8izjuWG4WFXuudpLbU9zgeRhiK/tJfvKL7shNF9QqO1EIqk0u2gjZb7aIPeuOjm1VzLbGoJ0uVkldBMIsB3XLtsE2GNmBxIRYOGRlGzPkXKtuHrQAzFLfCVWhPRduMBi3zh72U/Gaa7rijQd761yCXcG+PMB5vrat4ZxAZs2fVXEDIqAEmLfFGOzBB/QszotGYGPt5IlWQJYSZgKcPXa2cU2u0bLmeQqIwijRGmZNuziVboPtEHkeG6IzVnaSfDjJH7zKTt0kgRXxf3LxBdlWZgsWwGB1qA4vuu1p24KgkzEDgSV49rY603perTJHx/jYXR2/7d4uk5bJ0lf6y0DkexswTt8d2rLZ8segdOwc1/d9MqBdwCGpQJpmO/9vuz77+DMocpzZsts1KJutbjMLPEsAXNq27RMW6nCwZ8UKWo0HXO/mYhbVbVKNL5PnYYhfo//XSX6k7/vbYkN9IWLGYU+mq4RY5fSsig2Q7cuMvZxtsLdVbsfTwQLMQMxqttmo3K69hs6McVn/9p6d4N+GaTAQ3U87H+iDB2q7XEAb0mGbKp5T+r1OzXVGxed5nKRUy3Gojx1JT4f7aAu4JjVVD9NFG8foIqsAnEHP0QaXgYnvORkDqVV39hk8k+22RO7FtkjbiFmND9ba2j33k+wPGzebZH5SHSu8r23BjtsgzwOI/23f95/yhq7rPtNum2TMGJyetZ9iw7Fa/TjlJXIlHBd6sDcaUGrzSJ3l4hXrkhpyAbPEoQNQu6yTQbd1qhiQ2u/JOAuCtmx7S+rAOU61LZ40x9jexj577dsB19o/XSYL26Lzvp9mHGridtwe92f13Wo3gAgbx+bYOka4FwdhW7BDbouLtAfZJgMmlKOM7bCIA9exJy5mBdBQ+9cp7x4hTH3Ku8M7tJdksSh/83k5d71OFutkvdmu3t8WMEyeDxC/1F+GArE/82q6czMFAATcbD8jPvBBkt15+TsaIoBhcQAlAzmpgyoZFwt1MLUN9ag4AABgyP+tAd6xgNwD0qZstTZLBIBuc5dZawSmSvut+mm2xUBepA5cGJ+rhdtz7DqKgCLs0OEvdtbwjB2qsy3v2+AHGzaIYZM0kB/rGNpHM2jtgxR+aB1gtjMigCIOIIDageT2YNNGn+TOZvzMcZ4wecByuyT78+TOsgJikpwMF+tmyUKAaEa7zZRzU+VSQOy67vckoTDsAZtTfo9vvIa+3SjhpdvP+EXBUbI7T/aGWfdkoEAMNvJssdl4IDqOjZfR13SNu4XOgVW2YSFekxiHAYOYe3CwsAUQS2paGYHKdgK5BqRtlRjkLS1gsrCUvaA4eQAK3y9gZ+9422dvX6QwoW0xoH5Ojv1rbai2dxps8ApznedhG2gR20AFR0lSJx9YIoCKmP2bUa4zti27oKzzx881klkBv6SwQ/52ZhXod3MR4G+LXPqb9X3/9Um+vuu6r+/7/vdcY59upKC6whj8/yzJ2XoAkJPk6abGFp5lrF4jDjFp2ZqZoW2TsBZe/DaTgkFnOyOsEzbbhsUYDBwC4n55wM313YCICueVCZOqytnmyD0Y+Oi39/t8bI48t1XGz9DnOsja4T0tM6Y9q+z8Xg7qTi6qkEwy3pYt38kFtkruMCwvZmUThIHRQdhum9/9Tsqzv5exuv9Ux6+THK2T/rAA4u7wwE7XSb8p6nLrVGqdSbdBnsUQv6Tv+3+a5C92Xfcz2v1933/3lfbsBooHCjY6bHerJPPhjbU65sFj9mWxemnVc56Lg9LstPU2wxrZRt9gcIRczNSev3dNe8l2T6aZkz2gDihuhfacieKQIcTbHFqTVPAywLm/Dvo20LcxdfyPSmzw9D1vi7O01zgZq8/eHh2LFrCTytjpw47+HEfo0C0mBXuKeeYG0nmKTTGb6ryL2jxLcrRJuk2ys67PsbUFm1HeNnkWq/8dKcuPfsOWfX2Sn38lPbrhYlsYTOVpxgOcmR210gVNDTBOm/JAxkbk0k+27SBW81qm6RjIVvBSokZzHdio7W5tSJFVO67t8BcY0LHa4NzT1CwTM77WGw7oEXfouoLPAsQj3cNuCmvCO+8so7bEFr8lrJp0OK9ml9Qiodj2HMAdfbYsNc15PF/6RcrdYlZse5tNMbvwDAEsfi9PmL7uzmDDzqCl8Pxtb/WaOw6TcsRAy6RvkzxLZf7Nw79f3ff9qBBI13Xbakm+9uKYuKSGdLybqs6iBt1JGUxeJwT7EwMxqTayNpcVQGTwm0Xy6cBnBrTjHe3h5lp4glHV7Lmk71btknEq2HHGpf/N8MyMAflZ6vIHnjwAxG3Ld7LtnvpkT7e9xXznzyl9yRj8lxkvQ+qgZu4NYAV8AStA30HhADz3QgiOVXtfy4HatDVid7JBH2e8NAAs0eaFuc5fZ6z+nrepe1inFtZdZzz5eKK5rQ6V5Pnsvt+RpFWZt2177cXeTGw8DHzbye6m5JYmZbA9Si0Ka4BqvbsADEDFS8pMzyCE6TgHtg3Kpn0M7DgmrPa7sknrWEBVcw1EGIpLVF22+BHfd4dnARhZLd9P8tbwyfVQ4wHDt1K90Y9TQMLrmvieUTvtZTYg8TzYnowdG4C2GVnLYD05bdQ3Z3hwzon+WrbnSYRJamddwPBwU9ITWV/7acYgRj9aG+M8yVy2wPMspFkB2pyMq74jlxXluI3yLBviR5N8cYqX+aenvqv3c9E2PskgDCTb82zQX+pvZ55063EgNizR7M9gAshsKzUFY1s131Ep95u2HPBrhkVgNqW0zgFlXryNs1lhG8frMuCpQsM9Wi212mW7JuEy85SQpA/MS5vLlHhKymt9MDU/9yA1HZJQpr15dVj9WJIfGT6pggPg3slFB8U6tXzYNhWYfi5mhVXZZgd4ujQ/QGwHTDvBEdjMhOWlSWHQXrbgNCVm8DTl+ZylTKCPU8GZCcgLRLV2ZwDQxXXp93qTbE7qb4h5ZBvTbgH7tsmzGOIvTvLrknw8yR/R9scp4TiTPEPMMAyI+ykv+2x4o4ghdAkm4sL4zifMwiEU81S7lwO1ASAzNDzPSQXsmdo0a4M97ClcaDYroJgUENo5KoxlljowzWJtJ2tBBzvZbpI3l8mDB8U2tnyU3Dmpg5nq4rBdgOiNJG/eT+7dK4HDJydJHlWQISZxmQKqH05yb+jM4aYCLHY/Jgs7LrpUu916VTUAq/1eMxnV2KFXjkslqDrDeU8yBkzAhklhoWNd1/LpcC6mCZsz6D/Ml8m2UzsAtZ1KvKNMZAjvyDpjgH/tALHv+08n+XTXdb+y7/tvvsY+3RrB2WCWBEBuNhe9nF4+FLFn2aqsVWhmdnv+fE2YAec5HIQ+OEDX4LgzqFP+SwoIz2Zj9dtOGDMVX2cnBWRmm/oslsvqLFgskuVJ9bgChk/U/jzJnVk9L0nONmP26/vGDrg/6DWbw7IfW2DrMR+VPBvuGUAzS7INkPPtefaxfIfVodq3GoAdObtbzkcchwiQE8/qvvnemDQd0eD3xxN3K21WzW2V97Qh9n3/zV3X/dKUjJWltv+Bq+zYTRcPSIfhABTrlEGcVLuSsy5wVDB7u5CnQZL9ziDxj8qxbQ0++gibtJfMHkr6uFyWv/m8bJvNkuNVZZIGd9ipHUW0S2rYcjhhPq9AtV4XUGTgYhdEPcQznKGN/f3Sp80mWa3GQeh2yMyTzGfJ3rKw3cWiHJ+jyrD3UrNYMA1wjSR5ukp212MPMWo321BzLYAPtkLiQmGxBIp7NT6Dm4EIJwmOIJjaG0k+lGIaoBYibNQxmkkF6TZ42+XazHhnzedt9S4j7wmIXdf9yZTf5+cl+aYk/1GSv3/F/bpVgsriOD1XubG6Ys8gQEOe8v6y2u6cWYK9z2oVbbp4rO0/c527DXBxChyvS/rXYpHcvz+oj+viOZ/P6wCGFRLQizfTjp1lalrY7qIcC+NcrZLDw+ThUfXKAyDY0DyAT9cVQJMSTMx9UAfRLOtkU9T8DNfvZsmbSRZHtVL23Xlyd7/0qZuV/5fLcp2jo+T4cJxtY4cTtsm2YMU6NYMFNulJyZVlou18YuKwkGnE+/Fmki9K+X12F+U+N5vkydEQbJ36e5MSybN0nCjXtYPNzrTXQZ7Hy/wVfd9/Wdd1/7jv+9/fdd03JPmWq+7YTRerQszGVrXWzT7Egb0A1zIFDPf3y4u+uxoM7Mo1cxhOMlbjYAyoxAwyO17SHM/fLOWaO/Nir9vfr6zxyWGxMc7XZTBahQXoTk6qjY+0sL1FaQu75NPVEEpyUu1yPJe7qeWnzs0NKUB9pNXBd+fJ/f1kfVTDcJIat0lfZrMKovN5cm8/mQ/GuDfulfuYz8fAfbwq931yktw9qeDmicC/YZtR4pCn/VSbH5MdzG6TahrAPrjNI57hPCbQByn9u3evPv/1utzH7vCMFot678uDcm1XAKK/eLzNfC23HRyfBxDJ8Dnquu5jST6f5CddXZduj9hx4copiG117XeX3DpLGYzn9qxZznNLUW9gKZxr29Nc7bDOxzwVaGALDFLnBVuVns2qCtlvauL/ZlMGowHxnsBlsymgd7wqn0kpIsC+w8OBUa6T44eV1QKADzKObbyfZF/FB3gmgOyDk5xXaTl/BvPy/dGjwlxnqSYAzl8u630A6LNZ0g8AniSrt2twesusbK8DNAF3KlfbRumwJocuOY40+l15n8zo91KYLTGKAN/p+uIEgCNvNkt2NhXIAda2PJltobcdCJHnAcS/0nXdgyT/fZLvTvld/tSV9uoWiePzkgpU9v66bBSMxt69gxSV7+nh2ENNaAUpaRv9D/sj4JfrOdDYoRmwD9sAsZVtNsnpSQWYxSJ5662qRh+fjD3Rs1nywTeTn/iJ5I2P3k2We8lmk/7ho3zuc8nBQQ0SXg1I180qQM4eKbxmv7QHy+xmhck9eFBYa7+pA345sGgXKAC4j46Sdw+Sg43uU5OMWSH3gVreCWzPNsn8YfVU20zRpmzaqUJ1bxjf/gDASenb4XCcc5sBVMDX5g089vNBtb93r/zd2a/3/PSoPJujVfLu6mLwvD3/d3hmCgN7XUDQ8jxOlT84/PvNXdf9lZTn9yVX2qtbIoAaToKkqq2X2WYcA+aMBxjIWcrsbmYJEGLkx5kBm2gL1WJ7WjdtRP1yiM/5MYMzZd4wktWqgnRStn/gfvLGR5bJJz95ThW7d340/9ryB7L4oZMcHlYb4O6i2CnP1mVQr1b1Wnf2izoM4wMQbS8DqM2EYKrnDpd1YdXRfVt1BgR9r9ji2LdYFGZ7vJ+cHJZn7EIL/HaYRxxy43TL3VQnFf0721ysruMai857Pi8gMhuD+XJZwHGzGU8wBP3zPm3U1nnfhnbO1uW7r9sWpL3N8jwM8Vz6vj9Octx13V9M8omr6dLtkvZFaj12rfcOVQp2QFzdk4wzLRzeAnhyvPOBYQHzjBkBHkwb+OfN3yzJcvC07i7qoLt3L3nzzfL9yVGxJR4dFdBZr8sxH/tYki/5kuQrvjL58EeTfCg5++Hk739nPvQ935N7P/h2VqsKNkfDm0jojcENZpYUcHzwoPy1YTenJ1WNh6miksP4Vu8M+9U27ThPmHsxIPL/3rI4Y7pNnaT6VECkKKt/b8ejnr8LA8gfbarj6DzcR7+pJ1PCanZSQM/38OBBYeZng3318VC07yDJO8M7REHYN1LNJzO1szPYhLdFKrwOoPjjAkTJ+15aoeu6/zDJH0v5Tb+p7/v/ruu6L03xYH9/kv+k7/tb9+xtD0zqy9/OvjAM4vCSquKwLCTq5FLtOWA4uWgMTy5WnnFK3Tw16DqpHuD9/TLQ3nor+fBHyuf9+8nOR95M9u/m3upp7j18mMePNjkZAGm5HPZ/8iclH/63U9Yk+2Sy80PJz9okDx9m7+hp9lZPs1iss1wmDx9WVvjmm6UP63W1Pa7XlaWhGn/kI8kXfWKRvPXh0tmjJ8k77+THHhagPj2pALs7nHdnOdgR1xVIcAi5QvSJTAQAI/t2BnV3eTTOfeb3pVRWMo7JxDZ7mpSQn1UxhbybcUl/ZwcxacFEiZ0sHSvgh+d/Pi/sGScYKvk6BQxxBvCOnfdrk2xWNYLBoTivm7xfQHxfMZpd1+0k+eNJfmGSzyb5B13X/aWUyjq/LMnXJflFSf76++zXjRByYJ01gOC9bAcDtkECoGcZA+CJthPHBvNEzXKc3CaVzXSzAhSwIEBksShg+NGPFsb3sY8NavD+/kAR94p9MMkbeZjT1Sar1TAQ770xeCLeTMk4/ni58O5HKsVb7eXO8jiLxeNzMMVbihPk4cPydzCwHZjXYpF80UeT/OwvT77qq5K9N8sT+Fffnw/+w+/KB7///8m7n1vl5KTaOj/0ZmFQn3+nquUAPs6iw8NqcwQIT07G1zV4nq6qnc/ZKy7yy+9znGYS2lzMYcZGCIv3RGonDWr6IjVj6JxFL5K9dY3TXJ6U9s4rY2es2gPU3br2H6eaHSuvg1wKiF3X/eVsB74uJQ70/cjPTvLP+77/geEafyHJL8+YLN36ian1LNsOZWcIA2Weavtr4wX5xI6Icd95u620K/jtzMb2waSqkQ8eFGb4xR9P7r016MuzWbI6Tk5Oy0g8OU02m5FNLvOdgWI9TPJ2yjD8fJKnBUjv3y9gujrOTpL7h4/PvaKow2ebCjxJYTC7Ug/zyU8mv+A/SJlPBzfwT0jyE/508nf/53zg731n+oPHOTio9sE330w+/FYNW7o3OGj2loWJPnw4qJuHZf/JydimCevCBnq0qsHdTFyO/XRxhcvygB0a5CgAawHOo+ZdyfD73t+M7Z9kF8F+HxyU83DcYHJBnbeq3q7+97rJsxjiH36f+54lX5zkX+n7Z5N8eYoK/VeT/LMkf/J9tv1Ky6z5n+wUL0rVFg/gnGXzhz0HI3lSQZHvgJ5nGodxnF9/NjALqZD8LRbJG/cLgNz7yN0yuk6OCxi+807OTsrVCFzGfre/n+xgvHv6z5I7j5L8UJInybs/Ukbv/fvJ+rS0tV5nf/9x9pbFQ8rgJlvk7r0K1PN58qG3BlX53/g3UxaFvNc87V+ffOVx8uhRuh/8wSxP3i7xd8tyP2+9Ve2B3YMPlL5sNrn38POZz1c5OipA+XRVPLV40Xkuq1Xyuc8NcX7zZLbO+WJT2G9xiOAUI6YzGVf0cbwp4tL+bdQBLJSgdaIA8KqvFNPJPd5bJm+uagwn4nfSGU3kmr+Ocikg9n3/d67getvYX9/3/T9KAcbxwV33mSRfewX9eGnCS0j2ihPpAUPUZBwbDrcgZAaGYFB0mIdffAblutk3a6gKNjoCsOfzokovl0n27wwu5afJyXGeHm7OQ2aSOhDP25zNCuAdHJSRefc46U+LnS8ZUkDm56OWzBXb7lBXd2aFwbEA0ofeTPLmhwqyXerb+2ll/8OHmc/fPgfrLBbZWQwsfXknefODRb0/OU4OD7NYrEYOlbN1jb+0Z5j+7cySXo4fqqI77AYVF4eIow5aFsa+VbMfsEKNZUIkAuFsXRguDqT1uthRAUU0DIDa8a6o0i1Y3jaG2HXdE339lm0rh+bKo1UAACAASURBVL5fG+L7lc+mKDXIx1Oow1YZOvypJOm67tbklrcq0462ky3g/GazQ2Z5kvPbTBe2AYCzVBsRdq7FcB1CLRjgO/NClj72saoaAgRZ3ikq7lE54eCgsEI8lADZcjk4Z3DZPnyYHDxO5j86qNfHteH16WDIu5Msl1ksVlmtqr1wtcq5J/rBg+JE2dsfvC4f+UjpbO5c8pR/WvLxjycHj7Pz2c9mvjlJN58VdX02S2Zduaf9u8lit/RrvR5l1sCyPEnMZqV/ngCc83z2sNr6PEElYxugIwwcXmP7YPt+JOMwKlTxo5THnCTvvDP2rh8cyPOudsxKCdE6zcV36TZJ3/d33+uY6wbEf5Dkp3Zd95OS/H8pTpRfdc19eOnigbJt/RSM70l1kixTHSBZ16wWO1mwPzk9r531vS6GbYabTWFoe8s6+AHKo6Nk7+Cg2AVTTmxj9kY2tuWyAg906+ioqMebTW1nfVZAMUn297NcrnJ4WO13DGYyXvbuzQuIzXcL0/wX/yL54N9M8iu2POUfHjq0l9y7l931o/HNrjfJpq8P4eDdHD98kkePhkDpw7HjhYwYnsd6XXOid+dFrafpR49q7UbY1zyVLeK4cFEM/052siTVfMKxVCaC8R8kmR0kjw5KbOIoKH1Tc5MpKOs1v9Nse93lWgGx7/t113W/LcnfSPmd/3Tf9//3dfbhVZE2oNcFFQAtM711ileyneWtcruG4jZbIy++26CQAba7s3VlZUkBgs99LknezQdXT883zmbFm5nUAOaRCr5eVwAkZw7qtxjgej12yuDZ3pmV8I+Tk2LHm83K6cvlOsvl48zeeZwk2fuhHy47ft5nk3xZkp873O13JP23JT/4g2V/Uju32ZTrrtfp15t0B+8mKbbCzw8e7SdHyY89rAwYPxKguF6Xe3/zzcGOuCiB6EkJjD45SY6Paokv24lgiM5gMSgCcs5px8nGhGd1G4B9RDubYZEo/f68R8Q6or67XBjt3WaG+DzynoDYdd3fTPIf933/aPj+wSR/oe/7X/x+Ltj3/bcm+db3c+5tEtuGACyHXiTjRaBIuN/Vy26GYZuVMyJ8LWevLLI9QwOVFYCDJRX19SRvDAN/Pq9ZEUdHNRVvNkvuP1zlzr0fqQcSP3MOiLuFnZ0cJ6vVefodec6QttmsxBI+HFTnzz8cnBizos7uzp/krX/8d/JTvv3/KPbCT3yisEd0xaMnBWwP3i0FbZfzZH2as6OTUor/sLRzJhJ7cFAY6qNHZT8mBUCRXOcHD0rMHyaFwS9znrlz/APJk3UBKswVK/0GDpHCtod4sXmDZwtWrZeYibVd2W8n1d5IP3D8vKFzJ3k+hvgWYJgkfd//WNd1H7nCPr1WYocIdh2H1ZylMI15ygx/N/UlhjGsMy4x1asdZ0icM82U4ggUArCcDsHQZC3g2Dg4KEwITzQ2s+MhZo8sESrQfHz2TvZOTofwm7Pk4N08HfZh4+J4QDcx+NaQl6OjgqfOOz7bFAD+gR9I/sk/2WSxeDvL5dvn7RNfiH1vfz+5M3g8jo7K34++U4CPAG6uTdxhmxZHho7V6MWimBneGCp3r1ZDqNJbyZ3DZH5YVFq0AcJmMvzed1Ir4FiwHdvuCNBZg9gmG+0n7tFqOw4ajrUN+3WX5wHETdd1n+j7/geTpOu6n5jJ5HAlwkubVPBC1SW2jTAMav1Z3UIlPtP+RWoGymwz/GWsQSJsg+ntDAg9H76TP9ShLs9m2Wxq6A1AAkH78PLd8zSKpwK+1rSITY7+PF0VkCIHGUdHN6uhOBwLi/X9ENXzdFVY7FtvFdBKqklgNYTUPHpUiyDYxLgzT+7Ma6kyCifcu1fB8+ioht4wefAcAcq9VbJYVy8uf/zGrT0v2mbb4TbwayukW1to9ydV7T7bcs4kRZ4HEP/rJN/edR1hOD83Zb3mSV6gbItTdJofKg9G+rupjJJ4Q1Qj2OJ5gPa8sjIHmJEdklRWlYzjEXEWn21q2MudZYp3Nsls9eRCutvjw5qKN5+fnDMnQlnW68rwsBM+ORznENMeDBLARANHpW6Pfbop9393nnzRO0O44+AAIazn4KCA9uc+l3z2s8nbhVjm/v0ShH53f5wrTWLO3XvJ3oOCrIvFamRaSCog4pWez8s9nj4sQdFkEPE7tiYN/udncuk1i2NXk/F6Oq5ctG6O5XoUo53rvZmAsch7AmLf93+967qfkeTnpDzX3973/TtX3rPXUNqXEoP6qfaTl4onkjWNiSdwpst5KX45AwCMk1VlHzsDE0rGWQ5kcXBuUrbPZjl3iBwe1qBsg8NqVf0ZqMeEspwKlAG11ao6NMxEUcXJUiGn+UwoAig+3dR1nY/XyfEPJfce1uvAUB8+HKpzP0w+93byueG5fdFBAb7dRYnqwW4I+J6tk/5ole7e3ew8eCMf3D9OTk5qLUfFZaJq7+8n90+S1WHOa046zpQUTnv/CadxtEAyBk5X5uZ4VOvWS51UMHT0gteOmaTIs1L3vqTv+386gGFS4wU/MajQ33313Xv9xC/nMjWW0IMGgzhC5ZK7w/FOHTtJqd2Xk2pQT3K+GP3dFDWacl5nsqPBxO7dq57oZFAX3znJo0c11/hwyAtbLGqxVwDI9kL+khqm0w1g9UQVWlA7z8F0UwBpR06gs1S733o9Lq12mpIo+GiVnHx/OeYjHyltwjofH46rg69Tg61ReZMCyo8eVU/zh+dPix7+5pvJep1ufZrdg4PMj1aljJcCu2GLJyfJ5qTaedP8Vna2bFLXYk7GdTOxP1LZPBmDYTIu3eV4w5m2T3bD7fIshvg7UlTjb9iyr0/y86+kR5OMXlLsis51prLNk2EfNkWOt8eQSjmwCIqNLnUcjHA2K/a004FRUrlmsSgxgN1iL1k9zWa1yTvvFHXznXdqXi/VcSjQSv1BSnM9XVX7Ioxvf7+CFGxwkxJPh7A2yyzFHpdVYbSbTc1JxnueVKCBLa43ycm/KMBN/yh6u5syodA+QL5aVUBmgkjKuW+tN+nmuyWgPDlHv8Vi5a8525TncF50dmjDwdWX1SpE/b2sFiEhV2aEOOZ4dF6EzIwwmYDwMnlW6h52wq/u+37lfV3XXWbemOQFSfvC2uHi7BSAjmPaOEM8m8c6jtzY83CO4QR7iXcXZUCTwvdm1tm7Xw4ENB49KoDIOS4fdtwkw2Iv5G+9rmlxXPfgoJTC6lMcOfuroThsKos6STnP68nwvAwGSQWY4wye3oOynohrKCbVjrZJZaoHYqow3VGI0vo0OXqazLriRT85PbeLkr2zOx9qMK6Sw6PSh02qwytD35jgkMtAq2uOIc6QcBuAk5+BdL15LrLESbbL8zhVviPJz3iObZNcgbQvvQvIIgz81jGz7eUnVMdLGrD+RlLT0Xo5PQ4PKQd2cs58bMM7967KueIwmqSyMv587rlKncrqzm1bAj7i7QB2h6qce8630alU29xxiuqKkM6IOnpyUpkq9kr6TyhSN0t9YOfxOk/P6zb6fnvdG3ZBnF0GQYT77vTXeo8R9l1mF3Rb7J/k2fIsG+JHU6rT3Om67qenPtf7qY6qSa5B2hfZ437efAcY2zhFvIxmJ0kZpP066R9VG+IbWmhptUp+5O1q+1ssBufIgEpevL6bVQZ4uq7xfUlNcyPsBYDB63xwmPxoSiBzUovh3su4FBomg7NUL+y5bWxzsfyWgYG4zicZZ3Cs9XdwWAOwbQLArHBnmUobDw9ztlqX/h8UtvzoUV0nBvZ7cFDsme+mqOeOE2X5WCYo7H+7+rMK3NbPBAB3dAzHb7MfTvJseRZD/MVJfl1KAYZvSAXEgyS/92q7Nck28Uu903y2AwV1aabvp6mLIAEc58b4TbK/rkHMgBwFU8m8w+P87lDcwaWnqKt4dFSABdsY1x8ucw5meFDX63Lsk5SlMQkoPkkJV+E+YMJMArSH/c3hStbYzZadwmZHBM/xUZLTg2T37Qr2XmJ1McRf5uQkTw835znPDx+W8J1Hj3JeaiypdkgDum2FpNC1AG1bIoPUk50tBjwPs8HJVvj+5Fk2xE8n+XTXdb+y7/tvvsY+TfIMuUwVdhBum+5lluBKKfZKLlIdAJSkZ7DD6H7sYVVvndGRDOxy6NjhYSkLe5BaucfAvZPC/JYpB+3Mq13UQIftE+cAwMj9OA0NNduxfa1dkfjMxzo3zXmPhn277xQ2yAQxkvV6tJrf0RDgTXHZ/f26CBbLI+w/qstA0D+YHfUHqXQDILamEX4/ngHPcpYxS+TYSX788jw2xJ/Zdd3fanKZf2ff9//N1XZtkueV1myGekjZL/8hGPIJVVmk5vQCgpvNkBKMejwwQGIhAWGz0U0KqLydAjy0T+gIat9hqiq/HDp2J2UNZthSW8YMEHHWB4BIP7xIk5nVSp/Edp5qP88NZvk45d4dbtMuAn/uHBrU/lPFarIswd39kiL4oUe1j66EvZdxHrqFZSPom/vpiWHyHr84eR5A/Oq+789V5CGX+ZckmQDxFZVNxgZ7BpvXf3bMW1JU1p0kGWr9nQ0hLQcp4HWWWlgiGRecBYgyHHcw/A3O5632LRdBXQ379jJmUJSssjOJ/QAa1aWJqwSYYVN9KtNE8Lyilm8yDozmO4UuTgcb4WJR2O+jRzVo297y3fm44jfs+e5+8oFl0q+Ga89qEYinqd5zfjPAvGv65WfZygSEL0aeBxB3uq7bG5YgTdd1dzIOoJ/kFZR2USqDYVLZiAO4UenWJxdr96FiL3QebZ3q/5PUyjxmNK4SbQcCquKu9hlcXePR52E7dC3InaadpDJjip+iojp0yZNHa4s7ltcdEwGOIOyErgfJdxwrLhQBGJ4va6r7oA+tl/h5ZALDFyfPA4h/Lsnf6rruz6S8i78+yaevtFeTfMGCDc3A5H18ApQwpdOMlylwySrnxbasD/UbgEOl41qAJAN9T/tnw3X2UtRmBjiFUA2sAMgqRW0/S3FKzDJeWMsqN2A/TwmRcK1IwmEAX1jmXnKernd0VILKd2Z1Aao3hoIPOE28St9qVTzOeNUPDoYQHp7rJlmvynUfD9fHtEDAfAvMlgkAr06eJ5f5D3Vd971JfkHK7/MH+77/G1fes0m+YLkkJC9JZWxWn9cp4PEkY5bmMB7HtHlJzaSAD/bI2fDpDAxsmtjRqN3oPkSf2xwKO2qLmEWW64QVk9p4pm0AtO+lBVpA1SXT2tjJ1SrZXdVYRQDxyVENRaLiNkySXO81N7Wpzh3YN3ZWogBamUDweuR5GGL6vv9rSf7aFfdlkmsSD652dTgzE8DO8XAwmWhbG/uYjNkhAJaMQYi4yFMdg3e1LTrgQgc7KaBNezBBHCePM3ZGuIJ4MnZeWIXGm52hrazK+sY7s1qdp5uVbUlVk523vTPYEVerWnzWgM8k5Hz0efOXVPvsrV+T9xWT9wTErut+TpL/IclPS7WfP+n7/v4V922SKxLYGyCIDcsr/SVVjXRxgda470yKZKyGm2nh1DDw2DuNg2SV+pKZLcHwUKNRg0/VP9sLT3SOwRBG1oaq8Hmi41YpsZm2m+5uCkAeDyzR5cc2qZ54rmNgo4+2f/JceY7OmomeH5POJFcrz8MQ/8eUxaD+YpKfleTXJvnXr7JTk7xYaR0pMDuXrj9uzmnj29p8WTtIUIVP9EfutQEWp40Htu1kDlze5pkGEDcpIPfGcC2AlbadaO9wFQDUSzC02SBrncc1L4Q1nVTG+HRTba2b5LwAL9kyPF/YsAPMfR2A0J5lM9ZJrkeeV2X+513X7fR9f5bkz3Rd9x1X3K9JrkDsaW4ZV5v98Dzi0B0+ATQcOtvsga36eFlfHVx+mV2NvGx7Zbmv1pPMnwOa7cCxHdP77KXnvrKuxzMJrHXecWo20GVpdZ5kTnWM7+9ZduBJXrw8DyAedV23SPI9Xdf9oSQ/nFqPdJIbIs6CmKd4Zp0LbIaISgcIubyU7W+ohQxoPMxmiKfaZruZAWCm/zfNnxkq53Eti7NSYFpcg/vGm4xKbpC1LbUNfHaKn7NIOG+dusRnUoEQ1XeWMmD2MgZat9cCNfZYA+gkVy/PA4ifSvl9fluS356y0PyvvMpOTfJiBYYDKKJyJlWt9VobSWUm2OuSiyyNUBbAB/udGSKOEgMi+8gMYbDjNDGI4hBJKsgQKuNiqwYzA9Z5FZtUwCE8524u2h85ptN5VrX9zGifc5hIjnIxj7utlwfgorY7Gyepk8DkVLleeZ6wm385/Ps0ye+/2u5MchWyTR0GvAyS0afVRAPFrDnOOcbb4h2dMgdYAqJmPQRgc236xfcTbXfsXlLByuC+N/xxb4Anx5EVQ9wfpcEcSgTw0n6bzWIWS7GKo5TMHoO1C1u0z3KZ8TPfVhJskuuTZ5X/+t48Y3W9vu+/7Ep6NMmVCHFutiM+TWVGLmEPq2o9ns799WAnJGZHbfh4AA0wXKYCiNPUAEFURtsH3Q4LwHMuLBZGCfOz/dDXB/za6uK2Kx6nVuBp2ZoBlns8r9zT9NuZJ/QRIeaRvGY/tzO1Ncn1ybOe99dcWy8muXKB4QAI2MzaNT0AunXzHaBgm8NCsNnhJOB8jse5ASuDxdkT7WIUgDd/d1KDvNP0yXF7x+qb+9maAlC3Ca1hBUMADLWcaj1kz8AkAWOuYRssILbUc0ElRuU3k3ZANhPTtMbvy5Nnlf/6l5ftm+Tmi50k2P/aaiuIjfzYAA2Wl7XvT1gkqnIbV2fVHXbHOXvNsQh9smqfjFmq1WSuaXU8Gavb9MVlxfysZvpsnU/uQ1vNO7kIdI7ZpH+TzfDlyhSY/ZrJWQpTQS0DEO0Mcf1Eh+dYLaSGH2XuaZvzYIttzF8yXhWOazmY+l6qbXKj/a5ag6r5RsaM1XZHVN03UhkYDM8xk2eptkRY85MUWyD3j6pLZgvB5FwPm2ZbBMPPpa0LmYyzWPw5eZVfjkyB2a+RMOBgP+1awMnFgQhoEVhs50LrfU3GwcSuUmOvbFIB1t5tgxxs8mkKMD1p+rzU33lsYIqqi41vOVz3jWEfFbjX+sOuGLVzonZggnbcLDMGcrfHM7MK3gai+9MxjIC1K5u3509ytTIFZr8m4gBgB0UzcGE9XXN8MlY5+b8NQLaw30wHWyVgZqdJn/FC6o7xo6rNU13L4LotbtDOC8Jd9lMZ55NUG2cydnTY4+5MmzZVsc3COcu4EC5q/zqVObZxnNwjLN0ZKmaTE2O8PpkCs18DcRwiy5TCrOwFTcaFV7c5VubN/47fQ6x646Q4S12G0yW7UD2TCo7DCqDnTJa+ABAAzeGwD1X+WOfA9ABBsz3nUpspttKyPMwAAKifD6E3AK9Dh3wNA5+lTeVri1tMoHg98ryB2bNMgdk3Ujzw8HreybikP4InFKeBnSe2gxnsbId0ZobXBLaz42TYdpQx2HIM7A5wswfbKjjqb3IxfhEVlMXnWQy+DW9x4QQDTptNwnNy5krrnZ+lgOGD4VhCg9qQJlRsqoVb9W9lAsHrlx9PYPYqU2D2jRZUOgBrW0VmmJhfjDZf2Goz7M8eWQR2Ndc5dn7gRGnDeY4yXgTKqXZWI105pg0Y93764uoy3Bd94ZhW6J9rQdpxY++zgZTrX6Yqe6JycLtNGlMc4vXLswKzf3mSj/d9/8eH79+Z5MPD7t/V9/3/cg39m+QFCmDmCi/24iZVnd7L2JkAi9nPuDTXQue7DUDQ1WnOMi4HZrACEFepmR4nuaiiI2cZM0zA2kVpXYILgFqqLeyiVmM3W9rF2eMSYbaJRvfJxPAoNWulBVyeGyE7yxTPepr7hx23AeSTXJ08awL6XSneZWQvyb+TYj/8M0kmQLxh4kBph8gkY6ZDBontWQAoQIJK7IoyVnP9YgGyLOrUFoUwmPBnVdQABctznB/9xQwAKLUFIDgf1dvrr9hbDHga1PlEHcfJk9QJxv0/SA1v4hnQBu3Cxu3g4tpk0mxTpSe5OnkWIC76vv9X+v7tfd9/Psnnu66bnCo3UAAJF4O9rDo1oGFwbNXDxXBSv6ngYzsZ0jLKLhU423qHiLcBIFb5Hdqz1GeSvJuLDJPqPnYkeXJo4wJpm5REGDD2P/7s8QbIDzO2kZoxe21pTAKu3gPg4gB7VvD7JC9engWIH/SXvu9/m75+OJPcCMF2llSwWmk/YIJ9jEDlVarTBLUYFa9PAZhuluzMkm4YzQCubX8Am6tum+GZfTqYGbbGgk+uTGNbJgUa9oZP2NUy44IO7QJUzuG2DdJATK4xHm36BcNFXJoMMGtjD2Herq5jm6Ftq5w/xSBevzwLEL+z67rf1Pf9n/LGrut+S5K/f7XdmuRFinOM+Z6M1V+8sQ64di4uA5Mc3XUKM4RdHWecH5xUdoRqnYxLYtEHnCZWKc3w9lPrCdKGnR2wxzbtbaFPq9gA5aHuGTshnnEHfVvNdxUgGPZl5gE7Vngel4lDo9z2lMp3vfIsQPztSf7Xrut+VZLvHrb9zJT38ldcdccmefFCVojth+2Aw67n8lqU/ren+CTJetAJzXL4s+3PZfvTfHrBKphcu9gVLNFhMmn+d73H9v4AF/qSjBmiw1sAZ1TsTcZhM63t1aDlLJydbFfFrQq3fXcbbejPJNcjzyru8HaSr+i67ucn+dJh81/t+/7brqVnk7wwYXC5vFWb85uMA5vJbeY42BO2rsdq/3FqjULbGJPK8hzuQp9cTsssrS29DwtzgQb3H7WX/hO2g7qMA8hqahsWs85YvYaR4txoVVs7lriXNuQoQ3vHOs/qPv23x32j/ZN3+frleeIQvy3JBII3XNo4OZeism3QAElWi2PpAJOksq1Vam3FPmPbob29TsujfUqRATZdKij4WDO/TfNpxmX1lvvm02zYzg4zRJ6B781B57Y3upajn2W0zQ4gM1QzWlYaxLzABDKB4fXLFPf5mogHPXZBF3xF7LhggNt+Biid6H87E2wPtP2MMBbUZ4PMWWrYSlsNxuy1VUO5H9rw4vRWN0917kaf2Cc9UTgkiGfkbRarvfbgJ2NHEcya2EL3B3abVNbpfHKezSTXIxMgviayLY92m51rJ2N24kosGx2TjFVgvL3O+TVjmulc2xoBum1FUSk+68oybWEK95HMl3a5T1ge1+NcO1HscTZIO9yG+6Dt1v7YAibOGWy3XvqgrXLTDkSr3JNcn0yA+BqIVctWlWwN/HZ+MNjbEJI0xzgWcJ4y+J9e0g/AxFkkgKFZIeFCgJUBvQUn5xVbnTWbbcEZQCSch5Jftj0+q/+0iwrtiaS112IqcP/dJ2fHmBG2a1hPcvUyAeJrJtvAjYHoQbxpjvN5zidG5vpLagzdNi+2HRrrZr+P93W2LYW6DSwMfJtmmwHeIOaYP1f/4Rgv/GRG6G0+p71X+mEzRet84vg+F9nyxBKvTyZAfA0EgNsW6EtYyjbm5wo3bZqewQy7lwGR0v52OJw15zrWsAXU6PhkDBIuA+YUPBwkVvF9Py3jNdvkfO7XQNmG57T95H5b+yfZK26bbBoHobf9AkCn0Jvrl2sDxK7rfnWS/2r4epjkP+37/v8a9n1dSu70n+37/o9eV59eJ2FgbQvQbpmaAcXHOaPlLBeB5yw1ds8eUzs82nhFq4xRO5zj+MdngQOqKbY9t7uNiSU1F3mZixPDs4R7s+0TEG2r23AtA74nJvrcMveWXU/AeD1ynQzx/03y7/V9/2Nd1311km9M8uXDvq9LKRzx57uuu9f3/eFljUzyhQkOj1ZVNCi1lWSQdu2UpNoDsSXC+Fo7mhneZeWyWq8twLLMuL+WPjWDhX14hr02ssXgQoaLq/vY+92q59wXYL+tfWezeK0anE52mDi/OjqP7Jopfe965doAse97Lzvw95J8XN/9PkzZSlck9vQm1WZFcYHWQUAMYltogAFs9rfS8ayX4sKtZkEucmCgaf+sqsIWHTq0La85uWgLBdRc8gwAx+FhsLe9EpnrnD2d1wIiz8YhQMRhts8vqcDavvTbCvhOcvXysmyIvyHJX9P3b0nyD5P8ub7vH28/ZZIXJS724CyP04w9xohDUQAbgxNqsMHB9sPk4jKksLC2NqOBzVkn9iDbe2v2uC0c6FT78CgDerA3AMvly2wvdGwg6nsbnuTYzUXGJcgcKI7azH27vJjFdtJJrk+uHRC7rvt5KYD4VWzr+/7TST695djPJPna6+vd6yMu00WQNaqsmUxy0ZYFO7vMttdWh27VxGRck9CACAhxPIDSsjWr4m1KoJlpUhexosAtYMiaLIBVW/TVbNW2vmcVyrDtcFtJMdo1q22zctrnP8mLka7rnujrt/R9/6n2mCsFxK7rfmuS3zR8/SVJ3kryTUm+eqit+EwZOvypoa1tsbuTvE9BzSX/+PSS44gDdIwgpbZwIrQpcbRv1mYGhD2tLfbKNRzg3VbQSWogsz3KndpydZ1j7dtP8qa282kgtDrtStkONIfdGpjbSWNXfxbYpWtR7mn/BIZXJ33fv2cd1ysFxGH5AZYg+ESKavypvu+//yqvO8nziVmibXywLBcXgMF5oAMeziZpBzLsz+WwWrUReyF2t6R6cAGmy2IJEddZpJCDUwFRg+dJ9hfJep2cbSrArZr22hJg2DFnGReH8DMin7tNt2s9yFF7yTgtMVuOneT65DpV5t+X5ENJ/kTXdUmy7vv+Z13j9SfZIg59gfFsC0Fp//fKeMlFdmZguyyQGxbo7A2Yq1MHfX2A0Kv62Vt+mfq+TlmP+TDJ/CSZzQpjvJeLLLftN9fdy8XwJOdz49nGe4xdERsizpZk7IVumeTkSHl5cp1e5t+Y5Dde1/Um2S625cEEHW+IF7UFFoBrk+qAsX2P+oEEHgOYyfayWAYIyn1h22trBrZxkrBGOyPw5nJPLj4B+3qa5OHQ5mIzLsZK2TFkozatGtP/Ni8cB9B66JtZM/1vORbalgAAEjVJREFUnSdmvNsyXSa5fpkyVV5TsY2MrJJFiif2bqqaaK+rwcmLQXkQu7ACJcaSsRoJG0zGsY+ALKE2beqdvb7OD7aX+Dhj9dymgHVqHUeACfbWZtVYpcVzjKMEsDcgtjGPvjafNjc4UN0208m7/HJlAsTXVFjRzQOW5TBxeDg+sS2QkGwPTG5Zjp0EbV1Be5WTiyvyuQ07Upyuh/2PtlYZOym4VxetwF4I4Ltkl6/HvTqOkn1tbCWVc1qniL9jVnC4Uobre3W9CQxfnkyA+BoKA651hmCTY9Ce6bMFQwMZ31sQ2LZqXJta14LntgwZ76fd9hznVaOqOySGPrbpiu1yp63X2OFIrSd5o+2AKaDf9nlbhg2McwqfeHVkAsTXVOxJTsYMypWxYUMABy+MixMk1T7GIG9zercFgxsQDVrOJkm2A6TDe5xlY4B1MQocRdG9oPJzP6jjfMcs4LqNrRMHjzn50C0Dbhkj13OwNsdNzPDlywSIr7G0A3Cd4hggLg+wwdkBu7JH1wULovMoxLrNY+qS+vTDf1bTW9W6vdZlgdSIc0Idc+gQn0WKU+h+qhlhnbr0qCuGR+2ZTcKsYX5tTjRyrO1c+7I87UmuXyZAnCTJ9krUAKEdI4CAc4tdDovMjzZ7xMBBQHcyVinb3GAXdHWYDfvaqjw4LtpwGa4D47WaTJD5/SQPUhkiAeu0scpYNccuSZ8ccM1zAITdZ7eJ3dFe/YklvlyZAPE1F9RTBHU3qSovISjJ2AHBQG5V721FYX09VtEDpNritNH/VmVRSXGk2FtNPwCltlqN722jtgFEr6BHsDqedxgx7JIKO3dSvfQAvmMuW5W/rfWIk2Uv00B8VWT6HSYZOVm85oltiQYjzmkLH7DdoNiG1wAAbWVqxPnNdzIu4IAKf5DxEgRRO85jRm03ILkwA99xHD1JVWdhiPSXsBwmCEKU7unZpDnGcZDPWg7gsiyfSa5fJkCc5Fzasv8Gv2TMtrZlhrReZRc3sIfa+cvb6v25eg3B3rsp9k3OeZY3mv5brbZ9EUZmdbotYnui9loAT8bMuE27oz2A0aaFy2QCw1dDJkCcJMnFAXmWcVWbVgAUQlwAT1fPcUXpNravjcuz+sw+GBjlyGB1TzJe3J32AB1sfvSFdY8B13u6ZutFd5aMC0RwDWINt6X6AYKroY92RO2qjUleXZkAcZJzaVVnD14HLQMU9r4aEG0fI8h7luK1dawhTglqFNKeF2IyyzttzjPDMxi2dkq/5C2zBfR9X+36MDwTAJH7c0EKAPYkBQxxwrQL37f1Eyd5tWQCxEkuiEvqmwlRXRunhsv0G5wIQVmmZo24WEPrlXVhAzPORSq4tCotjM99dnEJ1G1Akj7CBgFC1GHLtoKzAL1BzEwY9dlZLEkdYC46O4XXvLoyAeIkI7G90CzGaW4nKWyPatYtO8NjCyBuUpkiYS3tWi5ttobtjk8yzhV2NZloG9JrmwO9YYyr1NTF/VR1F7sh+cXEJKJ207bzl6O2AH/bFwH+SW6GTIA4yQXZpsoBSIADgAjQADyADNVvkrEaC6DANg26OzrHMX0EeifV60tmSLv2CWq2nRy0w/FtYVrbOvluJwwLUUXXckHZWaoXGvbbAv+2dZ8nefVkAsRJtooHbKsStx5eOzRQlc3g7GF2G/NUgHTlaMCljZEESGCgHBsdh80O0G1T5/pm36naasWOnm3piMlYjYZpEgfpPrdq+CSvpkyAOMlzi7NS7HTAc7ubku3xIBUQHb7iTJHk8qwPAyg2S4B2kZJVsj+09ySlziFAhS3RDI6+OzwGtmugcx+PUtVkV+HBREDsIczRz4TFutpn1mnbJK+mTIA4yXMJoIWqSnByhs83hn0fTgmXSapXGLHXOKlhO62dzUUS7FmGee4P17AHF0B09WnADecQwNTmapshttVqULPb1f8ISIfV0vZZxpOFwXBSlV99mQBxkvcUBjGDn1AZii/spgAitkP2uVoMDhmr39jenqRWmnaBWXt2yVG208dhLWaCDrp2WIzzjGnjWMe3FbtdCg1xWmPrIec42xAnu+HNkgkQJ3kuMaCYsQFw+6kggBfanmiroC7/72Bme5GTMQNzNWvA9SylAvbTjFVeGFwyVtGTi6sLshZKMo6ndKqhw3ZQtTdb/uwkcvhPMoHhTZEJECd5bjEoeo2VZMy+TlPyjQ9SQBFAtEcaoGmBwrF6Lprg4hKcc5zCLknpawO1HQZ01vxF+127cNbsQ7BxnmYMgpgBUL37S86f5GbIBIiT/LgElgS7awONiefzqnxeJyX6TCqjcuC0wQQbHLZH1xJ0cVj6RPsu3EC7rXd8Wx61920T+kt+tI9tA7cnuXkyAeIkP27ZNuhts2MFuqepK9G1BRbIKiHuEOYGyBH7h2fZMYTOXMFOCaA+TbXt3c3FFDyzQ+IZre46BtFFJCgJ1has3Ruu5TjFCRRvrkyAOMn7lm3qrr2+eKLtcQUEvX4Lq9A9zcXUuqSCFE6Pw1ysPB39b8bo8v605VJddoxsWwslqfZKq9W0y720Tp9JbqZMgDjJCxdA7m6KsyUZF2OwOD/6soBvV4qBIa6aY9rA8WQMkPPmOK5Ndk27SFRbYBYgdSaNS5NNAde3QyZAnOSFCs4H4hLZBuDgIW6X8kQtBaDm+kQIrm7T6FpQZJvtiM8qqECfkTaY2xkmLuawyEUWO8nNlgkQJ3lhYkCgkILj8AhrARCTmtUBYFkNdSiPly4g8Ps4/3975x5rV1HF4e/XFiilUECupFBIIbwEExHLG2MDhJT4AixKiCg1QlDexoDwh7ExJhAfaKgISYFWhQhIQ7WaCgoFlWepLaUUEWnBxkYxaMJDadq7/GPW9M7dnHNf3HP2OfeuL9m5M7Nn771W9+26M7NnftN/C4FyA/tyPLAqApFbq6Vadrkcj8LmHPyqLdeySx+BcOwQATEYdXLwq7aeyg8aVOrkeqVGYh5nzBOwcxDKAg+lsGsOvnmqTqPtCSbwzkBZVQcvbclU7SzPRzAcW0RADEaVaoCozuXLy/SygCv0zTnMAg95XC53ucspO5NILcQczHrpm+NYyoiVa5bLr8a5G17Oc8wCsc18iaA3foiAGLSEZkEkjw3mLUfLjxbNpsg0Cla561z9GJNXsmRy4Gv0RbjRL39MmxnfREAM2kYet8tzCuGdY3PQN8G5VMguJbuqW4lOpb8oQ6O9W8queHXb0GxL/urcKAAH44MIiEFbyUGv/GpbJXdhyy1MG9WD/oo7+aPN25XnZDXrRmINZTDMzwrGLxEQg7YznC5pKfhQqtZUu9q5bi99q0/y+Z3oP0G8VLlu9Kxg/BIBMaiVZuIO5flqUJxUqVPVXCynyeQAWv1KHMEvaEQExKCjGGiddCOqU2Kqy/BivmAwHCIgBl3FQNN6YODpM0EwGBEQgzFFBL/g3RC/P0EQBE4ExCAIAicCYhAEgRMBMQiCwImAGARB4ERADIIgcCIgBkEQOBEQgyAInAiIQRAETgTEIAgCp+0BUdLRkrZJmluUXSlplaTPtNueIAiCTFsDoqSJwPXAb4qyqcDRwDHAue20JwiCoKTdLcRLgXuBfxZlzTY+C4IgaCttU7uRtC9wJnAyqUUIgJm9LmktsBL49kD32P+oo1pqYxAEY5RVq4ZUTWbtaZhJugf4rpk9LmkRsMzMfj7INT8BzvLslBabGATB2OatIr3EzM6rVmhpQJR0MXCBZ6fR1z3ey4270Mzua5kB7wJJb5rZLnXbMdqEX93HWPWtE/1qWwux30OH2EKsk058WaNB+NV9jFXfOtGvmIcYBEHg1LKFgJmdX8dzh8mSug1oEeFX9zFWfes4v2rpMgdBEHQi0WV2JE2U9CdJyzx/hKTHJC2W1JX/TpL2k/SQpPWS1km63Mv3kfSgpKU+Mb7rkDRH0p8lvSjpa17WFe9M0mRJT0pa4+9lvpcvkrRB0mo/jvTyaZJ+WdSfV9yro1Z5Ddc3Pzfby9ZJergoP8d9u6JtDphZHKmV/BXgTtLHHoBbgR7SZPI5dds3Qp+mA0d5elfgBeBw4DrgCODjwEV12zkCvyYCfwUOBHYE1rhfXfHOSLMtpnp6B+AJ4DhgETC3Qf1rges93QO85n5P9d/ZScDSuv0aoW+7A88B+3v+vcW5+/xd/yzfs9VHx/4VbSeSZgAfBRYWxRNJq2d66Zsu1FWY2WYzW+Xp14H1wL4k33rpXt+OAV40s5fMbAvpP8wn6ZJ3Zok3PLuDHwONXRmwqySRguBrwFY6cJXXCHw7lzQn8BW/vtkqtra8zwiIie8DV9F/n/MfAL8Cjgfur8Oo0UTSTOCDpL/YC4BbgIuAn9Zn1YjZF/hbkd/kZV3zznyIZjVpGesDZvaEn/qWpGck3SBpJy9bALwP+DuwFrjczHr9j1xe5XVXm11oyjB9OwTYQ9IKSU9L+lxxqyUk31a6r62n7iZ23QfwMeAmT8/Gu8xj6SC1Kp4GzqrbllHy52xgYZE/D7ixbrtG6MvuwEPA+0lDHAJ2AhYDX/c6c4Eb/NxBwAZgt7ptHyXfFgCPA7uQFmz8BTikLpujhQgnAp+QtJHU9TpZUje2mhoiaQeSoMYdZtZx0xxGyCZgvyI/g9R66jrM7D/ACtKY52ZLvA3cThoaAJhH6laamb1ICoiH1WLwMBiib5uA5Wb2ppn9C3gE+EAtBhNdZszsGjObYWYzgXOAB83sszWbNSr4mNOtwHoz+17d9owiTwEHSzpA0o6k9/aLmm0aMpJ6JO3u6Z2BU4HnJU33MgFnAM/6Ja8Ap/i5vYFDgZfabfdQGIFvS4EPS5okaQpwLGmsuxZqmZgdtI0TSd3JtT6mA3Ctmf26RpveNWa2VdIlJF3NicBtZrauZrOGw3RgseuDTgDuNrNlPhWqh9S1XE0a4wX4JrDIVaEEXO2tqU5kWL6Z2XpJy4FnSGP4C83s2Sb3bjkxMTsIgsAZ913mIAiCTATEIAgCJwJiEASBEwExCILAiYAYBEHgREAMgiBwIiAG/ZC0t6Q7Jb3ka0sfk3TmINfMlDSiuWOSzpe0T5FfKOnwIV47O8u1tQpJj/rPmZKGvW+4+7dg9C0LWkEExGA7vorgPuARMzvQzD5EWgUyo4WPPR/YHhDN7Itm9lwLnzcszOwET84kKbMEY5gIiEHJycAWM7s5F5jZy2Z2I2xvJf3eRTtXSTqheoOB6ki6StJaFw+9TtJcYBZwhwuE7uyqJ7O8/hy/xxpJvxuqE5JOURL7XSvptqysImmjpPl+z7WSDvPyHkkPePktkl6WtJefy1JW15GWmK1WEmXt1/KTtEzSbE/Pk/SCi52eWNTpkXSvpKf82H4u6BDqVsSIo3MO4DLghgHOTwEme/pgkiwTpNbTs4PUOR14FJji+T395wpgVvGMFaQg2UOS+DqgrF+xZzYVdSJgsl93iOd/DFzh6Y3ApZ7+Mq6YQ1JcucbTc0j6e3t5/o1GzyK1bBcU+WVeZzpp7XEPScT1j7keScz1JE/vT1pjXvt7j6PviLXMQVMk/RA4idRqPJok9rlASf59G0nLrkqzOqcCt5vZWwBm9togjz+O1HXfMMT6mUOBDWb2gucXAxeTNC+hb2Ojp4GzPH0ScKY/Z7mkfw/xWY04FlhhZq8CSLqL/v8Gh6eRCQB2k7SrtUvrLxiUCIhByTrgUzljZhd713GlF10J/IMkzzQB+F+DezSrI4an7Dzc+uV1A/G2/9xG3+//SNSYt9J/yGlykW5m9wTgeDP77wieF7SBGEMMSh4EJkv6UlE2pUhPAzabWS9JRWdig3s0q3M/8AWXeELSnl7+Omm/lyqPAR+RdECl/mA8D8yUdJDnzwMeHqA+wB+AT/tzTgP2aFCnaudG4EhJEyTtR5++3xPAbEnvUdKiPLu45n7gkpxRsdFS0BlEQAy2Y2lw6wxSINog6UlSl/Nqr3IT8HlJj5O6gW82uE3DOma2nKRZuNKlyL7q9RcBN+ePKoUtrwIXAkskraG5RP4pkjblg7RNwjzgHpfL6gVubnJtZj5wmqRVpLHOzaQAWPIMsNU/8FxJGhvcQJLw/w6Q967ZDHyDFNB/m8udy4BZSjL6z9En7xV0CCH/FYx7/Cv0Nks6i8cDPzKzaL2NQ2IMMQjSF9+7lfZy3gJcULM9QU1ECzEIgsCJMcQgCAInAmIQBIETATEIgsCJgBgEQeBEQAyCIHD+D+bR12PV930PAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "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": {}, "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 740 ms, sys: 146 ms, total: 886 ms\n", "Wall time: 10.4 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
19.798252197266.42400-29.00490
8.9666207204266.82019-28.16314
" ], "text/plain": [ "\n", " value x y ra dec \n", " deg deg \n", "float32 int64 int64 float64 float64 \n", "------- ----- ----- --------- ---------\n", " 19.798 252 197 266.42400 -29.00490\n", " 8.9666 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": {}, "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/python3.6/site-packages/matplotlib/patches.py:83: 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 5.37 s, sys: 241 ms, total: 5.61 s\n", "Wall time: 5.66 s\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%time\n", "bkg_estimator = ReflectedRegionsBackgroundEstimator(\n", " obs_list=obs_list, on_region=on_region, 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 849 ms, sys: 14.4 ms, total: 864 ms\n", "Wall time: 868 ms\n" ] } ], "source": [ "%%time\n", "extract = SpectrumExtraction(obs_list=obs_list, bkg_estimate=bkg_estimate)\n", "extract.run()\n", "observations = extract.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\n", "\t--------- --------- --------- --------------- --------- ---\n", "\t index 2.225e+00 2.616e-02 nan nan\n", "\tamplitude 3.013e-12 1.396e-13 1 / (cm2 s TeV) nan nan\n", "\treference 1.000e+00 0.000e+00 TeV 0.000e+00 nan\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: [ 1.00000000e-02 1.00000000e+02] TeV\n", "\n", "CPU times: user 360 ms, sys: 6.28 ms, total: 366 ms\n", "Wall time: 366 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.observations.stack()\n", "print(stacked_obs)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=4\n", "
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e_refe_mine_maxdndednde_errdnde_ulis_ulsqrt_tsdnde_errpdnde_errn
TeVTeVTeV1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)
float64float64float64float64float64float64boolfloat64float64float64
1.564748141661.02.448436746821.09665927288e-121.2341157896e-131.35849249895e-12False13.8584822281nannan
3.831186849562.448436746825.994842503191.57243008959e-131.9436004648e-141.98486309052e-13False13.7091592194nannan
10.05.9948425031916.6810053721.19005011546e-142.6277413917e-151.78643655366e-14False7.46562284258nannan
26.101572156816.68100537240.84238652677.4706997312e-164.14358281946e-161.83474469974e-15False2.75570747694nannan
" ], "text/plain": [ "\n", " e_ref e_min e_max ... dnde_errp dnde_errn \n", " TeV TeV TeV ... 1 / (cm2 s TeV) 1 / (cm2 s TeV)\n", " float64 float64 float64 ... float64 float64 \n", "------------- ------------- ------------- ... --------------- ---------------\n", "1.56474814166 1.0 2.44843674682 ... nan nan\n", "3.83118684956 2.44843674682 5.99484250319 ... nan nan\n", " 10.0 5.99484250319 16.681005372 ... nan nan\n", "26.1015721568 16.681005372 40.8423865267 ... nan nan" ] }, "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", "fpe.compute_points()\n", "fpe.flux_points.table" ] }, { "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": {}, "output_type": "display_data" } ], "source": [ "total_result = SpectrumResult(\n", " model=fit.result[0].model, points=fpe.flux_points\n", ")\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 }