From e3f0484d4f530caff6f8e2d1e641ba02151d5f33 Mon Sep 17 00:00:00 2001 From: 93395f5d82c059171982160c793907e6 <93395f5d82c059171982160c793907e6@app-learninglab.inria.fr> Date: Wed, 3 Sep 2025 22:18:12 +0000 Subject: [PATCH] etude incidence varicelle --- module3/exo2/exercice.ipynb | 1321 ++++++++++++++++++++++++++++++++++- 1 file changed, 1302 insertions(+), 19 deletions(-) diff --git a/module3/exo2/exercice.ipynb b/module3/exo2/exercice.ipynb index e9b2eed..ce5d867 100644 --- a/module3/exo2/exercice.ipynb +++ b/module3/exo2/exercice.ipynb @@ -21,26 +21,974 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { - "ename": "FileNotFoundError", - "evalue": "File b'inc-7-PAY.csv' does not exist", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mdata_url\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"inc-7-PAY.csv\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 707\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 711\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 451\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 816\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 820\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m 1047\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1048\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1049\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1050\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1051\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m 1693\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1694\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1695\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1697\u001b[0m \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n", - "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n", - "\u001b[0;31mFileNotFoundError\u001b[0m: File b'inc-7-PAY.csv' does not exist" - ] + "data": { + "text/html": [ + "
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1813 rows × 10 columns

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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n", + "Index: []" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "raw_data[raw_data.isnull().any(axis=1)]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "data = raw_data" + ] + }, + { + "cell_type": "code", + "execution_count": 10, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "def convert_week(year_and_week_int):\n", + " year_and_week_str = str(year_and_week_int)\n", + " year = int(year_and_week_str[:4])\n", + " week = int(year_and_week_str[4:])\n", + " w = isoweek.Week(year, week)\n", + " return pd.Period(w.day(0), 'W')\n", + "\n", + "data['period'] = [convert_week(yw) for yw in data['week']]" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "sorted_data = data.set_index('period').sort_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "periods = sorted_data.index\n", + "for p1, p2 in zip(periods[:-1], periods[1:]):\n", + " delta = p2.to_timestamp() - p1.end_time\n", + " if delta > pd.Timedelta('1s'):\n", + " print(p1, p2)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.int64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(sorted_data['inc'][0])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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MWLg2UkTvqqLFWIdq/eL3zFyGZRt34eG3V7ZpO+oGorOEpq8E5q3aWpX6Jm/iQEQ9AfwdwLcYY9sQiIhGA5gAYDWAG3lWTXFmSbeVUftwORHNIqJZ69ev9+16RVGOPDsfCp5bC9U3EADglSUb8HLjhtTlRB6vPcc4P0ITUDiH9uuCEeqANr2XFxd3zDjmaA0X6Zp8G9umKC+kCtfCDsGr72/E2be8hD++vKyju5KA14ggoloEhOHPjLGHAIAxtpYxVmCMFQH8AcCkMPsKACOE4sMBrArTh2vSpTJEVAOgD4BEqEzG2O2MsYmMsYmDBnXM6WDlDOqaXPC6W6t01/SFP7yGf73jNXdGD7T35J82PxmeY2/ARXe+3qHt843KtPlr0bhue5u1o1prdRbuuVx8GBoKzFu1rYN7koSPtRIBuBPAAsbYTUL6ECHbeQDmhtePArgwtEAahUDx/DpjbDWA7UR0XFjnxQAeEcpcEl5/DsAMVo18FsrbldbmgwlSDWER5q/ahi/84VVsEQLCVQKcs2pvi6Gn5q1p1/bSoloj8fKxOPP9jTjjphfapI1rH50X+TdwVOn+qN1R6mmH7QEfzuFEABcBOE0xW/1FaJb6LoBTAXwbABhj8wA8AGA+gKcAXMUY4zz/lQDuQKCkXgLgyTD9TgADiKgRwHcAXF2Rp/NEscjwxJzVXnb15dAsrjxtrgIb7+ueXIBXlmzEOyu2llyH7l1E1koer8llc9DpLBKqEO3Bxd79yrJEWsY5BKhmuxunhzRj7CXo5+kTljJTAEzRpM8CcKgmfQ+A8119aSs8+OYKfO/v7+In54zHxcePbLN2OHGoBs6BoxIMmm58d+Tcr4Z1J9GFKuiTDq2eY3FnUyvWbtuDAwb1rEi7aRwcuwSq8HVkHtIAtu1pAQC8v36nM28537AmEiu1LYfiA58dy+qtu70UpmJXS+l2NSzmlYa6M67WR/TlHC6563WcduPzFWs3ow0BYrFS9SEjDgB6NQQMlI9tejkLWV0KzqG9FkxbM5/41YsdrjAtDR0/1XwiylYDfMfZrA82V7TdNHGzOjOq+WztjDggFvdwFnt3cwEjr34cv322MZm5HGulkHNo9iAO+TaOt+BT++ZdLX51iaasXCFdhYO9PaE+f9W+jpTDrFLioM4yPi743Ux892/vlFy+koEqK42MOCCeuPxAlq27g0VRd6BLOVYFkc7BopDm4SBy7fVlSnyc5Zt24eHZqxLp1TDnq6EPpayhHdHttFuQbMcv4/Vlm/C3N1e4MxrgE5Cxo5ARBwjyYY/vVOrcmLFwbRT/x6pzSGHtUyreWb4Fz79XnvPV+b+bab3f1ZeQpM6h7d7I8k278OzCdW1Wv4hKeTZnNEZGNb6P7DwHmMMs72kpYt22Jm3eNFi3bY/kzWvTOcRimRIa8sTf34p3OrpFq1BkWOU4aGbDjibr/a4evbY9+/6xm1/A7pYCll1/dpu3VSnT18yUNUAmVqp2RGIlOXnr7hbcPO29sqvf0yITA5vOoZJRTX2gm6M3PbPIGcVT1DOIRLWSc75UuXRHTrTJ4/cFAHx+0n5SeluuhbvLOAXPx2pNjHhbMHC9F935Wqr4TBltqH5kxAHxLsbHHyXtgtXcWsS5t74spdk5h9LaKRW6jeDLjRtT1TF7+ZZEmo8Yxfa6l23YiSUepsXVhp6h5VtDrTy1fL5me0qfN+5oQlOrH1G5/E8x19tqMMN6cfEGfOv+2d7tZ5yDjGpU0GfEAfHE5QppG5FI+wmXbtiJTTvlEBU2hTQfJG05VGS/hPJbEj1gKyUWO+WXz5VctiMn2oOhcrIkf48K98WGo382DZfdPctIkBau2YaRVz+O197fiBcXx8EYK6ZzqEgt1YMl63eUVI5zbtX4PjLigCTnYNvBpZ30uoPvfZzg2mu06OZ6JTz6q3GwdyTagmCt395U1mL9kiUC70shQfjnvLWRBR2g1zmIz/b9f8zxa7yTDZBv3vd2SeWq11YpIw4AxAXf45zflKNaRxxsLHUkVmrD2SPWrVu0kuGm/fuSJrZSW6GTrTtabN7ZjGOmTMN1Tywoqx6fjUCPunx0rSNG4rf+82sferVbjYHmygE3f0+L6P1X4evIiANEsVKKzJ7QTiZb9e2wuIp16zkHNbyyJo+BkJbS7SqcFwmk3fm3tRPclnAxmrag7UOV54TxoOMcSvF9qEIRe1ko1V+Bl6tGHUxGHBBPZJ9d1NMpzw3QWYP4DIT2Giq6vpTDOQilSurP3gzxPe1sLmBXc8efTid6NPtwiTrIhznpTZ9T90tT5OG3V+KVEg6bqgaUKoqt4qCsGXEA4l2MD/V/cu7qdHVrFkmftbZNOQfhWksclNeQZu5HCvV2pA3tMcF8nkeMzXXbc0tw+LVPt2GPAizbuMt6X/y+umfwCxktmCo72vCFbl586/7Z+EIFDptavmmXtyVWtaAKGYeMOEz+3xfw+/AgkjYJZ6T56D478faSyWoXDIVIpulLml5XalHPKxV11ET75K9fkn63Fu0LczmwvbrXl25C47rAekYU+ZQqumgvzqES2NNSwEm/eBbfeaD0eEeloNShXMWMQ0YcFq7ZjlVb9wDwMytLK1vU1VVNuwTtgqE8YimHE7XnI+bagXXweZ4PHLv49sIFv5+JM24Kwms79UuOutRXqxsupUSgtW2Qbpm+OH2FIbiD6QuL2vdsbhcH50I1Kui7PHEQEYfPNedJ+xF1dfnU0FYEZFdzK/4iWJT4LBhXP+RpnghRod5+g10NUtgWLc9ZaT8xb/VWe7iRcid/qe+zWAnOQeyH5n4pCmlbdNebnnmv7NMSq2+p1cNnzekoZMRBAOcKKknFdXWVo5BmjOF/p72HkVc/jrtfXqrNUywyLFqjPyz+f6fJu7IPNrq9kGcs0AR1M245mfB/+yApVqp86+f+9uVEmtiO7n4loT6SL7MkinyaWjQLrkc9sljJ3oYvXEUqQcj2DlRvjzPiIKAtqLhuEnjVb8i0dMPOaIG/Z+YH2jy/fbYRZ/3vC5ir2e3uVA40enLumrC5uD1VTFMKsWzPnZDa31YfJ0MFNoKie4+A/G3Xbmv7QISlQOzjFfe+WVIdoihVt2iraT7EwrX4l+uJXY3hKGyoxt46iQMRjSCiZ4loARHNI6Jvhun9iegZIloc/u0nlLmGiBqJaBERnSWkH01Ec8J7t1Ao5CeieiK6P0x/jYhGVv5R3eAK6YrqHDSD1E8hrYc0Zwxd4bGO1oS6FFu9jet2YN6qrVHYB8BPzmxCRaKxpqyEH6LEYVpY1m83L+C2JlVFc1ym/aZ0qS2J4puZ7wcxs2zvIWpPaDAt5/DYu8lzPhL9cry7UqO/VuMia8PeLlZqBfAfjLFDABwH4CoiGgfgagDTGWNjAUwPfyO8dyGA8QAmA7iViLiL5W0ALgcwNvw3OUy/DMBmxtgYADcDuKECz5YakUK6gl9Kq5D2KWfIJJ4QVymG9KXFG7B8s11mrsLVdjnvMG1RfogSR4tBQ3rVn98yt5muSQApTXxt93w2CxXQOQDAI7NX4pgp06Lfrs0OAVgtbDJMId5FvLTY7avgOgyxVM6BtePxrNNS+jzpYDcS7lg4iQNjbDVj7K3wejuABQCGATgHwNQw21QA54bX5wC4jzHWxBhbCqARwCQiGgKgN2NsJgtG+j1KGV7XgwBO51xFeyLyZK/kd9JZd5SxGIjy9Uq9IrWaBOeQoi6m/PUqU+YLF2P/AGax0qZdzdp0QB/mxAW+UPocnWl7Rp91UM3iu3aq+V59f5NfQVM/NO2qu3yfYdlWYqX2tPp5sIwT4DjiDWnZVVUcqXQOobjnSACvARjMGFsNBAQEwD5htmEAlgvFVoRpw8JrNV0qwxhrBbAVwABN+5cT0SwimrV+feVN1XwW27TrcclOcOma8S7r03ZiN6mzaDK8h4445Gercta1KSR6z3rz2VYm/Y0N/FlfXZouxHmynlIUun5l1HyujYCKO16SjR50zX64STbj9Dgi3UlQSyUOvFh7rLV7KuBoV8WhlfyJAxH1BPB3AN9ijG2zZdWkMUu6rYycwNjtjLGJjLGJgwYNcnU5NdqCV6m0KatoNljR7or1JmhDCUO3jNGedrHcrijZTQuLzcmxUIKxPu+mD9dheyIvzoHZf5vrljOWS7x1Y6FJeX6f7+d6ZtO5ES60px6oFG5TxV4fPoOIahEQhj8zxh4Kk9eGoiKEf7m94woAI4TiwwGsCtOHa9KlMkRUA6APgPL43xIQKaRLGF/rtzdh5NWP46G3ZFZTNwnKMWX12VGVMt4qNaXSnUfRNjPDpMystKSSL5TNrWVa1lje1hmHDNbm8V0EXeMl7Rvx2ez4+D248pTNObQDjSjXF0NENVpX+VgrEYA7ASxgjN0k3HoUwCXh9SUAHhHSLwwtkEYhUDy/HoqethPRcWGdFytleF2fAzCDteHbOu3G53Dvq0kxQjl+Dvywj7++Locs1j6G105Rn6lo2eG76jPVSSBpMonHQqZFpHMoRyFdcskABw7uqU2vdHgUvhDZTvbjsDpWWu6ZNiy+a6fLP+LNDzf7VcTr07Yhp5r6NqxvN2MZFaVbKwXldrcUsNJxDnq5aKsQINUCH87hRAAXATiNiGaH/z4B4HoAZxLRYgBnhr/BGJsH4AEA8wE8BeAqxhhfba4EcAcCJfUSAE+G6XcCGEBEjQC+g9DyqS2wp6WA99fvxA8enmvMU8q6Zgrep6vKxDn4LKjijkpnaTJ35VZMX5h0WvvFPxdh1DVPaMUn6oIx6wN5wSjpfXjk4X1RHfPStjdyQHfpd99uddp8Ns5hR1PB6lioA/9ePsTB9kZsz5s3UDTfDYxrB/5+yqNYdWM3SbiYcE+/mXH1q2SFtFDsxOtnlFSHf1vlU4cookDZNVUeZg1dCMbYSzBzn6cbykwBMEWTPgvAoZr0PQDOd/WlEtgYHtkpHmAS9cPi3VuTI+NuhjGGOSsD3wIfHwHTmBKrN+excw4mm/zbnguCC5ayI0tTIs18aQrZ8vmrzSqsMfv0jILImfCpI4bi1zMane3ZGAdumz915ge49MRRzrqA+HuV4nQnwrbQm+iZTiTPGNOcxVHZZSctIywu8iKhc+ocSnyn7SmdKSVsiIqY0y67qoqjy3lIcysJXbA2W1ygb5w+FgBw6LA+URrfMd776gf4+RMLDfVqdlqGvokTybRglKinczZuW6D05wDYZTReFllCnpFXP44toamp2JcjhvfFGYfsoxaV4OvRbRPDrQj9PPy4gKghAHGwN2tWy/vYtrtVqk+EydTR1wquVNGHeTwk0xMWUYb2RTNs165b1/6yDTsx8WfTrOIitS/PLtKEfqkQyp6LqE5dA0eXIw42No7BfI8rBvfpVQ8giEk09vtP4qG3VmD+6jiOkVcUS8OAkIiDYcyUu1sxTnlLtTVqZDtr/Uz6a4P6Hu57Y3miLz4WIQnioDR96i+fwwOzlnt5t6fZsfJnbE1DUDT48t1vGO/Vhw5+SYW0X93b95R2fKUJaThhQP7GOYFzcImNdAvvfW8sx4YdTXhk9kpz/5Tf/wzDw7QFKsGV2dacjkbXIw588bLITnXfnIdo4GN63qpAFPL0vLUQP63PQTmmMSWa7/lwFy7odspGfYelHtXJzIqwoj0tRfxz3hos32QOZay2qXu2bXta4LKpyTuisi7dsBPfe/DdRPRWHdKI3WKFtLuMLYdNrMa9v21yfVsba7clQ6iUA+14TuRh2mtRfaLWoxpB2A6hWr3F/EzqvO6mER9XCqUqzUXwMV+NHETXIw5WzsFMx7m8lH9EftJUfa38Cn0OyjFaIhXFPNos+Mfbsalspc4xICLrLigVcRDw1T+9iZP/51lzBqVJ3ePsaGp1WmXlcnbOIconnoVs2O23Fov41n1vJ6zOdIgU0pWQLxjA3736SPodfDKxWSFc5Y4Yn1hh4usQ10/x/avjbcVmeROhG4/8M/9JY2kY90X+3a227YjDrqbyj4H99v2zK9CTtoFTId1ZUdSZdto4h5ws++Xhj+trclJ+H/ZfTbriT2/iwME9cckJI431BHUx3PtqvGiVQhuMNMCycenV4B4mu5sL6FaXTxXmQX3tBx7WAAAgAElEQVTGyJRYSPbRASRCdgv1mgjxntYieqosBwKx0sOzV+Hh2avw+Un7WdtNY1PvtTHUfE81qGDctrvCk34xA3WaZywH2k2VktivR2wtJvZzoRBGPhHJ1cMcVv3O2v4p5dryIKgdFSAO3CijChmHLsg58L9Mp+ST/4rgnAMf1Pyj1tfkpXrUTaTPZHpq3hrcMqNRmiC6wfKwImtNiBqUGeVrWUKGdI6j9uuXSNut6AJKiS6pLgC6edxaYM7dbmIBiMQ9Rfz4/+Zr85nqTKOQTnd8qg8FSSbVKBwrh494Z/mm3ViS0lTVBf2YSvA10ZUpTIYqQvQRm/nshtRylbbWErGzDH8gFW3Zz1LR9YhD+BEYdKw6l/8ly8XEIfjNF5GaPEmTI6mQTlb2F4PIwqVPUE061dw+VjOl+Fj4RQ11ZnH2JQ6ZHqeri7XOQa9P91ptvbdMX4y7X1kWpUuhpw19SqPTsVm32XCpwCGK2Lo7qTyuyevFSh2lwtQ9q7ohMomVpDzqxsyx0QH8nBjTcK7l4jDBcrFclHt+RVug6xEH4UId6LE+wqxzSC5olHphNA0E0VLGx3xUzbNNs7gk4DlZfe/FeTjR9X8ZCc5BI1YqFJm0qG/cmTyLoLuidOSvUfV9EENJm4hkGiWjzYDBlBcAPnn4EG2elxqToa5rc8l3ApRxiFSZ0HLCym/x3ZqszRJcrlKL7vl8RETJWFJt91K61+Uxcf8kV10KKqHcrjS6HnEIv0GRmZlhvc5BflU8jyqSSVorpVks7WIlFYwFHtFcQccd/KxlNNObyN5PnyewvTtjGdU+PuIcYrQUWOoDlkxB9MQJWIk1gy98aavq36MO3wz9Zmz46IGD0LtbyBUJjbQUirhLiZYaZGn7BcZHES6ucya5vCsgoH5z5IYa76gtxTWtBZY4S6TkujLiUA0QxEoG1tYmVopMz8J6EiGQE7t7/55Ji5dHfgaGT/76Jfzw4bn4cOMufPO+t+W+6ExZDZInWz/9omymH9zJcNLJDvtE51TfuZevQgXm4mk3PgfA93wO+bfPLvhHnxynfSf3zPwgOt41LVzN8h296ZF8nO/E8bJ9j4k42Puh8+dRrdJULN+0Cx//1Yup2ikHzYWi0WAgLUqJCtzW6HLEwSYntu28uNVHqzJ5/vDiUsxaFgeQLeeITVEs5FNOXGCu/b95eG+tPcwEYOAcXGVSiE3SzEV1PkSx7YUGWwvMuaCp9ytxhrEPdNZKPnJxIvLMJ8b7FxdcvfiwEpvk9zfYx5BeEa5yDvHvJsOZBy7OQdeO+J1VsVRTawH/nJckmG3JObQUihWzBis3BEtboOsRB+GvOqj/+PKy8J5u1xLYnOvC9C7b6O/oZcN5t74ilHOXFGPV9PYwNwX0C2dTaxFzV241lvHpS6zML02MBujP8G4pFKVFwSfstg+LXupU5B7yprp8A+W5dsFAQPxdVmAH79vLWQ/HyQf6nIGi7xcPYWJzHuWQXr+h3wniYCEwHOJmaEezzJF89BfP4mePL3D2rZLIxEqdFIwBB/3gKeM9FTki1Odz0U7I91OWqhDzKSYuRN3qksSBh6MQoRuE1z25MBGJNW1f9rS47bVNBgAcerGSu3G1lA/nYPouYlhpHX7wyXG6yoS+GIiD0JyvICIncQ76un55/hFedfXpVqslbCpMtPfo/fsn+sGhvm5Jdyak7y9Ez3WZsuq+j0hPD7/2aamOtduShgpqXyqNllCsdO6EoWXXlVkrVQFKHSs5Iolz8K1Hl63WQ06pK5c84tFezzPz12LNVjnUQCmD0GeCcX2HjctQm1blynzyvyJY7bR6KKRlzsJPT1HqVNT1RKzLx5yYyE/nQCDnNxZl3oHvjv7JanLk9cym1qINsodYSewCv/7hJ8fhga8er82jq5YHshShvjPdmSyJvrXhmttSDMRK+/Xv7s7sQCUPDqoUuh5x8BKRJNNyFHhDR8TBUI86mX3YcB1umb7YmcdHFzZ7ucwRlEIcfPr79odByHLbupy0akmwDgCAv78VO/ulPS4yT5RK59BLOVfaJCO3gbGYsB25X1+vMr46h7gN06IfT2EGZvxWNXl7iBQVas582E7a8xx+/0IQKv7w4X0wuHcDnvrWSQB0nIP82xWmHQA2eVjnteUxnC2tDDX5mICXYzabcQ5VAC/lqtbcM+AcmhwUXh2Lldq5FIsM0xfI4Ydl+bZfQ6UovnxKxH4O/vUkaIO2XsMNQ8mBPev95LeGLD5B9JJVBecoTP+PkzH1y5Oc+QnkxTnkcqQ17xVRo8aVMubLAcwdat3EqfCNiJ8pa/B7xeZdeDH0LeG1Hrxvbxy8by+NzsGNtgyFUQpaCkXU5nMlRQdQcWAK3VF7ISMOKfLkcxSJQkx5DJEcnGku3PvaB4nonaMG9nCWU/tZysHtXh7S4V+rv4RDrmw6nY8M11GakHjIkF5+OgdjH0vjrAjA6EE90buhFleeMjqR52nFksZnnSOIFlz6PKpYyfT+Q9rg1aYOUeBJzT01jb9+0YxVfN6cJtBjezjwVRoRcYD53djw+tLYynFQT7c+qL3R9YiDj1jJkB54Q6cbAq6d1rINfrFvVm5OHnBSXxN7Bvt2661Q/JMGPnUXHPbxgM4ipfT2TMjnyIs7ihanMkyPozKQF7/Rg+QzrNdu24NbBG9touQOfbNGRJILMoZt6JW8JudMFcE54e6H491SiUQasZK+nbjGXE737d19+8lj86XfHU1PWgoMtfnYLDmt8vvXM2LRcXs4MKaFkzgQ0V1EtI6I5gpp1xLRSuVMaX7vGiJqJKJFRHSWkH40Ec0J791C4ewgonoiuj9Mf42IRlb2EWXYvl+f0BvVNImIYpm6MY/aniMqzuzlfou1rjVxMOoskyqFNMPWHqNJ/u2jyDvugP7SQqrbcROAJ75xEv7xtRNA5Kd4NXVzewmRNpkirlHfgU7MpeocJk6Zps3jYjAkzgHmRSZHKb+joR3x2fa0FLBsw85oHL74vVNx2LA+Wv8P8bvlS+ActlX40KJKoLVYnlhJFAtXI+fkwzncDWCyJv1mxtiE8N8TAEBE4wBcCGB8WOZWIuLb29sAXA5gbPiP13kZgM2MsTEAbgZwQ4nPUjb4wBf9DUTkKA6yZzqY/dlF66Xfix2OaabJrJod6p323KjEmCtHkSndU25OHGmKSxNk7Ne9Fn+8VJbh67pCRBg3tDeO3K9fEM4khRjMBw3CmR3a42XBrKu4qhfQ1aMVhXmolMS4UoyZFdLBmR3mPsZ16NPrw3MlRJ3M1//yNk755XMRp9aroQY5QygWSTSoMRrQNSseB/qraUkDjZlLkrGobO1WEsUiCzmHXBQcURfR990VW4xGDmII8r0yKitj7AUAm1z5QpwD4D7GWBNjbCmARgCTiGgIgN6MsZksmLn3ADhXKDM1vH4QwOlEHaN5cn0ecYI99Lb5qEIRi9dtT6S5xkFDbQ5jB/e0Z0J51hFpkKaZNGIlVx1D+3ZDt7p8qgnuGwiRe9iawjvo+gMAZ44bjH17NygZ7Ou4jqD4jHDJCc6Qp6FGDjpoFiv5jRfTIsWdvcRF/fn3AgMJrocjIiMREt9BPpf8RrpmfyqEW9+8Kyl2e2OZ2TenrcFD1nevy6NHaPG2U3HMW7llNz79m5fxQ4MuLc2xqR2BcnQOXyeid0OxE98CDgMgyjdWhGnDwms1XSrDGGsFsBXAgDL6ZYV1fij3nvjGSdLvHKVfkFsKDOOH9sbQPg3a+7rqavO55LkQWt2Fu/1K0A+1Cts7SKeQtrcbyb8pmSblE64DebbfQy9Z7zaXBOTnr6vJYcp5hybuk4U6JP1T/Dy9A4U0F+fo84gLDIPl2UnTTwDHHyBPNZu+DZB3x7ypYkQczHNEVkj7LYYiV7SzAgfrVBKcOHSry6NH2M+dTTKHwMOcmETHNZ2UONwGYDSACQBWA7gxTDf5CNl8h1x+RRGI6HIimkVEs9avX6/L4oRt96re2VdZ0HOerLlUJ2Po3VCLEYp83bbA1uZzXqZ+7cWK+hw0E+W11VOZ7iQgEQ/42fMzBixak+Tq9Jnln2qIDMZkRz2f0wB9/BxkzsHvmUy5KKhE45Wu1mHWtwHyIhaZL7O4DdESSTrnRFRIa3QOOr+GnkJIGHXh7Wjwc0W61ebRPYxOoBIwLjYyLfwiYW9qLVYdgSiJODDG1jLGCoyxIoA/AOCC4RUARghZhwNYFaYP16RLZYioBkAfGMRYjLHbGWMTGWMTBw3yiROjq8N2T77ZoJwPbZKnutrzOdheRG3ej+0u1WcjLdR2bIM4zaFBppzxroHCvzF0dvoqZ8HLj+hvDoXBwEpyeNPWxVSHtWRbKkYOcJsh58jglZDiHYt1mcK166pWq4k4B823v+PF96M8OYMTosuU9b//MSdRRgxqV4kjOSsJHq69vjafOEKYI3aO09chcg4zFq7DZ259ufIdLQMlEYdQh8BxHgAuVHsUwIWhBdIoBIrn1xljqwFsJ6LjQn3CxQAeEcpcEl5/DsAM1obCdNfOVqT+qjwXJXAORcbCiam0ZZiEQGCe6EOE2muj4RMULcpbIlch1xGLKYK//loHUedg60uR+TtVuTgBE2ssZRDQ3FrEiWMG4vyjh+vzc2gIztpte3BXGCBS145pTHBLO1eIeVN5vo6J8nOedfOulqiN4GwQuc8q8jm/eSRyaNUWXoLrWWpyFG3+TPNCF34cSI6Zd1ZsbTc9og98TFn/CmAmgIOIaAURXQbgF6FZ6rsATgXwbQBgjM0D8ACA+QCeAnAVY4xvz64EcAcCJfUSAE+G6XcCGEBEjQC+A+DqSj2cDi5Ty8N//HT0O5cjPHjF8XjuP08Jfpegcygy/eJmq6WuRidWSpYoNRRIWqj6Dxvn8IrFgiTRlwpNBHGBEw8uSsMl2sAY8KkjhuLpb380+K0hFuI3Vk1X1ZZ2hSKJQx3HTOZiN4eojsvvmWXcRTOY5UoEPefgS/h1dDSxUwaFymY750AWncOvLpwg5JN9I6oBTa0FrNu+J5oTOYrDZ6jvjj+j6Z3261GXSHthsdsCq73gjPPMGPu8JvlOS/4pAKZo0mcBOFSTvgfA+a5+VAp2zoElBu3Ekf2ja74rTbewsEjeq6ab9pu1eYLXeTXtsMkIArYpg97S8AOzVhjv+b43NZes69XUoYgs/MRt/hwJA7Bf/244cHAQ4iBhLAAm9VENsaL2R9U/mRCIlWT/gg077PGEbIt7OQYMfbolFzJdG6JeTvJzEN5QTY6MnvqDBUswUS+TT8E9tiX+/S9v4+n5a3HmuMEAgj7mIuIg5+XKe1NQAp2fj+6M9I5CldDj9oN9N2kvy3UOqUw7w3IthhGiq6o2n0vK57U6Bw/OwaOPtiixOrPDtUqkV1/oxDE28F6lOT5V5hzssnkfpTDPKy5uWgcuoS5Vl6ESNO5s6VrviJDYP+hs6cV+uMSmrkfesjtJfH5/0dE4TOByTLoa7hDG34/4nsRn7dlQix0GE2LJ8kziHKqDODw9fy2AIOIxEMyP6BwSA+dggutAo45GlyMO5djMUKhIc+kDiopFR44oilqq9uI///ZOorzOWknbjtdOsLx6ajTE4co/v+VuWIP1O+KY+y0Fs3WG2p4rDLaqsI50DpYyjLmD0EV5oSicHX1oahHNPVnJuiHZ6zr46woqaFVIO4gHAHzzvtkA5IX99IP3keT/yzclQ7kAfKGMOQcTcejVUGMUjZm84UvlHNTnbWot4P43PrTOi+bWIlo9Qq8DAdEycQ7ymeVJqUQ16Rd06ILEwQzXp8qFyjbXZBcHRaAE1OgcLHXU5knj56CTF1cGNkKU14iVfMIp6zD1lWXR9djvP4lbn1uizRe1Fr43abHV5Jdk04JeyKUc9+ccVAKk3mdSH8QDg4oWMaSreVVcBTg4B9gV0j6L0frtAQEXFcCBFVKcRzdeOPcpvn+JOAhP0qMubzRNlXUT5XMOaldvmb4Y//X3OXh8zmpjmROun45Tw/PBXRDNjU06B6LAm3z0fz9h7RvQdh7dpaDLEQfr/HCJLMLgZU7OQbhfNIgvbMpkX86hUoeSi019LJSlctTkcxXTbTTU5t2ZNNCFSbftkCOZt+UdF5n7bGoJQuZTDw6OzDwgjIqrchbnTxyOE8cMiPpZ6vuryeUS5pC2oIKMMe0z3/2lYyITX/WRV2gCOgJy9F7VaU/H8fEAgKKZqphNXfSN56EI1+K86d1Qq81vAj9XQ51HG7YHYjObZ/yGHc1G7khFnkTOQW6Lv0MiJIjRmx9sxq88zmzpSHQ94mC9F9/tpTmTOZcLJqlt9wYkvUjFiaGLs6OiVrMg6/rtc/ZAWscadcHMe54g5oO6mnTDjXdFfp/J3mzdHQdl87dWEltIh9p8DieMHoD+obVJgrMgwgmjBwJwcJkW6vT6f5+OupqccExoUBH3zDVB98wNtXljVNYPDOefi2NL5Xx1Y4pzDkQx1yvmE4c9GfoZlI+vRZ0D95bWzUsd7gnP1VCb4e+x1B26elY7A4v6qT5THKQzWc9nb3tFK1rroMhBWnQ94uBcMAJcfPz+ift8V3Tj0+9Z2xAtDsTBA8QiJ6dYyUMh7SMXte006zSHo6ty+JpcuhPEbOjuyTmofg6y7DaZf86KWJ+TLiqrO2fUFyVd9QQ2TWqbAYNtGdgntNpJs1YwmEUVonOgDbw9m1+Bbjxwwi86isr5ZOpg7ossIuRgCAIxvvRfp5k7L6BXQy0G9ao3OpOWugYfNlw2Pw78Zfg1U+6557qK6iENXZI4WNhy4VofLC0QWSzfpN9tcbwnRGLlzlYPfe0EAMlYNjronOB0bLjPiWcmKykgGQbClKdSYqVxQ3uXVE73nGKfRH8BSedgqdN2pKauHV18JCbk0REPsS0dUi38nn01nWJInia+uhhKKlxiJd6OaeiRhTqYdA6MMfTrXhdZevmAYNP3lLYMq89eFPRN6muJx4f/BKoixqELEgfbPUmBlgRfeFyf+ot3vhZdc9n2Ufv1w8KfTsZHDxwUtiWXefiqEzHrB2fg8W98BLU1fnJ+l3gLAFosO0CdiEsdnOrB9G9+oA/Q60NoSiUyRQcR5CIcwM9Dl9/z4jB4HzSZRasoHfEIypWucxDr8a1CHxE1GM8+HCD/jLaxpVVI14QK6ZyJcxDFVBaCKV6rFmKGIbbHIGrT+bxEPw11ucSwCeJQZE7OYVWJpt8dja5HHGwLhnCtExOUFngv3o011OaNO4NRA3pgYM96jB/aRxvDSTdXfU48s5mB5jX+DVqdg9CXpRv0XFOgeLX3x1c8Fe3WPcupcuq4H+Zyyzftwu9feN/ZF27PfvsLsmUVF18xxvCX1z7ERuUkt9j2Xe7Fbf96lLNNqR3BCW6p49TAgBvScQ7+O1IiwjvLt1gD3emGFA/pzc29AbuzpK19jpxCHUzhTlTl8h8unhjWZfBJgVl849pwqVysGIYl6ZtUyvOnLtJm8NPudCJYo7IKt7RiJYScgKF897o8djUXcNFxsb7CZBWj9kNcqHVESB2044b01gZBU9HUUjQOUi3noDydKlYyOUAFJpv2vvgSVu6IpWPXxd06R470744xYGDPOq1XsctXY9yQQAS2KVz097TI75/CBrhVi/rsogWL+P5F72gf0YbIOexyBZ8zfgOKlMAuhWePujzO+a09AJxWIa0RK9lMeP1EXPG1bd6pTpz8vA1tTDMHD6azjBOhEytF31opWiFjwg5Dl+McfKGTknC5LR8ehw3rg7MPHyLl6dOtVlakKTseEtJFiAu1bsejEgcivUK6b3dZJttcKOKlRn28Fp/Ac3U1OWlCNbVYZNHOGe9HHeau3CaXEurVytSV37GiWHfXD/VhRN4ag/c41zmYwkDEfVE50pK64w3dJwhiNOnNRz9z1DDp98fG7etsQ8fJ1Qh+DhHnYNI5WBTSsoWTqHPwf3ficyb6GumQkpUxxhJOqTc/8x6emhuboeoc2Ux+DqUYcpSqC2kLdD3i4Pm9dAMxDp/BojwFQbTTUihKA39Xcys+3LRLkomaZMjq7lcdV4/MXpXIL4qVBvaMY9+Ih6Q0txaNlidas1olqU45eMi2s3KJuWycw+HD++CgMHaR2hX9ofayDJsjJ3yANCEykvUHf02mx3z3a45iGn9oH7NNn/6o9Xxv8kFyHpgV0oG+LFnv6EHyiYNi+bp8DnddOjFRplBMiq+4WMnkIS1mN5nVBvlYpHSWzlgGMy6c6jfgv3M5mBXfmrSNO5sjMSLHr6YvxhX3xlxmknMwx1aqsuMZUqPLEQfd93r7h2fiG6eNkdJMOgdVhizKIFsKTGKZ/xiGVn5y7pq4XiWQGoe4CPmcG0EkWyKJopOfnRvHN2xqLRo5BK3OQfldm89Jz6vr1xUnjwbgs4sOys5btTVxb59e9Qmldrwji9N48/fPig8clA+SkTmHYw3WYbpXklCAwqxoj3fi+u/EiwXclH6RNOFbZ4yV2pF7FONLJ4xKpJmOojYdgqQ+n1h+1MAeOO3gwVBR0CjZ+fgVuV6TIYGLc7j/q8cl0m2cQ1KvwHlGjUm4oV1bf0WoOocBPeqiiLGV0DlUE7oecdB8r3496hLu+boFVXcEpeqlLLLvOuWWaYDnJOJg9y34+5XHgxTOQcT+A2K5dlNrUVrxf3LOeNwaKkVrPOIg19XEQQBXbdmNJUrojDPHDY4ck1wyVj6vzr7lpcQ9sjyzLv37/xDO5RWeT7VW6t9db/pYq/Hx6FUfq+D4M5vekYtzyAtnLhs5B30yvnXGgYk8WnGR0rWAu9BxDkFFjAHTF8o7Y5X2icVNTovFYpI/4URGMmW1PLfpnRRZrDPgeQpFhqfnr8Vqg9WPiQDkLERINw/Vhf+6Jxck8qhRU489YICRcyiJNFSPVKkLEgejCZ1KHDR5lAWMIA+ogT3rvJVttiziIe1L1u/AGmVSDOnTLWjbINQ9ev/++Oe3PophfbuhqbUg6zyIMLxfEPvH9Iwi6kJv7UKR4YTrZ+Cht1dqygR/b55mdw607aT2tBSwcM12fLAxaZEj7uh0NSSslSSzSbNYSMVvvhBbEvGudqsLpoi6UBJx4qB/Jr6TLigLadrNpNj9B99cLt1Tg9Ex6IP88RPlGJJB89RNkNhbk76lUEyGkBF1Dlz0YtRBWeRpgeI55K7DtH/OCzhv0RNe6bT8k/FmkoYdqoOlCFVk9PvnZWu21kIRK7ckw2q4TFn3VnQ9ayXP8WqyVlJlv3wAfOWkUfjSiaPw6d+8HI1Vm3KJ1zGwZz0+Nl5m3UVHrtNvfD5RlsdrslkrHbRvL9TX5NDcWkzEq+GTQLcrVntckw8WW1ugMv6u7n5lmTEPYF8YXwwPObnhqYVCX5I7Mh2BUYlfzDn4T879B3TH0L7xWQJ8kexWG0yRW7+gmqAGljAmbonvpFuLRem5ZcLl3T0wAFNnfqBtI5kzCSKAafqaOFtCKG7St+h8N/LhWBIPFXIFHFQDFvK6eQZe/msOy7LkNODjmxIbKNvcdC3mJqdT02E/JekcqoiedEHOQQ91qOgV0oppnMBCf2TsIAzt280Z/TKaDBHLXExMQpc/BY/06gqfkQ9DX6g7a163bnHZvkfenXFT1iZLTB/fNc4V/dVUscv8UCwpvn8Gs3Oaim61eammOC5OUJca04e3Y+qbyDksXBNbX4nGAj6IdVSae+qun5nymc+QPmu8bJ0kfiOTrirQu8l11Qo6B1EcpIONKBaKKQMiwrwod69Phga3rf8uBzhTWVNsJZ/NycT9+8llqog6dD3iYNrNJBYRnUI6GIjPv7c+SjtxTOCd2y2MGySKlbhI4tITRsb1KnW2FlliYXQppGvyFIqVHIsmBYucOMnrhIivOrHBESP6ynWESj1TS4zpF5EnvnES/n7l8VKabe7Vh2IbUYT2ufCMZXF37hYrCZOUJXeItsCHOoU077M6Hmy6AEDkHFh0RsJnjhqGMfv00hdw9MnrSFjo3zEPK+3ayaqKYnV8fOHY/QDofVpyEXGIN1A7Haea6d6dwDh4i+BMjm696mukM+EBgXPQDAMX52ASk5UjVlLnTjX5RvicIX0XEa0jorlCWn8ieoaIFod/+wn3riGiRiJaRERnCelHh+dONxLRLRTONiKqJ6L7w/TXiGhkZR/RD+rk160hqqKYAFx58mj87YrjMWlU/7AeQeYZDvP/POsgtaposheKLLFgBZEt9QPrd188CkP7dkOOyBo3ifeXgUle0p+eMBRHDO+Ljx+6L2747OGJMl8/dQxe+q9TceclE3HhMSMQhcGxjHPdRBs3tDeO3r+/lGbbSXGZ/lvCoUifPmIoALNJZNS+ZK0kBsRLgh/1qbVW0vSVfyd1PKg6B7U+LrITd6OnHLSPsd8mpFkoA0VxMiOR3XyUm0ETZAKiLlxfCjc5urhUNRLnwPDi4vX44cNzoYOqUxARcA78vr6/BwzqIf027di5U6rung6uaDSmxd5oyuqz0CtDoJr0FD6cw90AJitpVwOYzhgbC2B6+BtENA7AhQDGh2VuJSLOR98G4HIAY8N/vM7LAGxmjI0BcDOAG0p9GB/4vnpj4D3lg+dyhGOEc6ZFmSv3Jq4XlJnRTjDsSGuBRfJasW3TGJl86BDekFf4jCIDvvnXt6Pftfkc6mpyuO2LR2PMPj0T+WvyOQzv1x2nHzIY13/2cMlvwAQfZzrAvsDpIsRyTFC4GRVi8+ICJzoocVz98YMNdSRFNICZc+CEl9+/8xLZHyDiHIRvtGWX7Kndo96t8ksjYikypl2QCGQ1H3362ydj2nc+GhBWYYWzmRari1hsrRS8u1eWbJTui7njOZDskegJ7btOqvn4I9TW5JynCIpwmWLrdDaA+F7Scw4qqsk3wkkcGGMvAFCjrZ0DYGp4PRXAuUL6fYyxJsbYUgCNACYR0RAAvQRymT0AACAASURBVBljM1kwIu5RyvC6HgRwOqkzsZIwvHwf2bSoKDZB5By474Hk/ax0o1Wrc3APrNeXbnJGZeVEZpvHeb0mBIutWbYetONREczP1KuhJvJIltoO673pgglCquv9c/lv0GMC8Nmjhkf3TUTovCOHYkT/7pg0qj8G9qyLnpf3Wcc5iIukOmT5N/3d83FMJpUb/Pihbm9kDi/OQaML4H1V63js3z+CB68IxH79e9RhzD69Aq97YYFMiuDkdysi4hy4GNLGaYZ/9SLC+GQ1UxUqh2caV7W5pLk3z/vuiqSvjWunr4qVThgd+NCYYyvZ6wvKKn3YyzgHHQYzxlYDQPiX88vDAIj2divCtGHhtZoulWGMtQLYCsAd17pE+Cp8dPRJlduqoSqAWGm9cUdTZL0jn4srKj2Dnacq283l0gf408FbOe6qA/aB7kvLTUdmvvS907R+B/U1AdPZzaHEVb3LgVg5SwTceMER1r6+8N1T8ZWTDkBtPocHvno8jhnZP3peZlj8WwoM76/fEeVTuSfu4/LoO7Fnu/pNcznCiP7dYIddxCKiUGSRD8kZh+wTcazBMZ+yMcV+A7pj4khZ7EdEkmhFfSY5LIzcn5zIOTj6qRKrTULQwtMO3seqhFehM6vlIt6afC7ha8SJxZ0vLU3W5WhQbad7XcD5mf0ckvWp700VLdrO0WhvVFohrVslmCXdViZZOdHlRDSLiGatX79el8UJoymr0g1dp1SLj//3qfHauoqMYV14Fq+5HywajEmdg3sH8S8TR1jvx/213XdWofUK5xizT0/851kHJuo5+7A43tSBg2PRFQPDY+8mTWL7dK/1tngyWeOo13NXbcXulkJSkaxpqL42J+UT31u8+Mtlnpm/FkUW6xTU+7owzbpv6tI7RCILy5px+UcPSNT/n2cdFHFJQWwleWHStUqQnTqfVkJJiCabahiV+Lxkvb5scO/YTFjUKcxZsRVH/fQZAMCVp4xGPidyDvrRK6aqsav696iLRFy1+Zx0ot20+WsTz6R7BhNMekCzQlrTdyWNCLj2U+Oi36bw4x2BUonD2lBUhPDvujB9BQBx1RoOYFWYPlyTLpUhohoAfZAUYwEAGGO3M8YmMsYmDho0qKSOG4mDx+qkOtXojiwkAhas3o7vPvhO4p7YDkM8GNPoHExt8wEq+i64xFNenAP0du0A8Pg3PoKD9+2dqOfbZx6YzIxgsmzcoSea3noLQx/jeoK/n/7Ny4l74n0xymqiZeG9RXF6lP59Mgy4yM2J1fufOTJgjEVv9VIkBrxW2672yBHJ85IH9qyPfudzcVTWqF6tNR7BpsbiJd5fvxMTfzZNuicGZGSQF/bZPzpTe0gPY8D81bF4R+Ue/URp5lDxtXmSxGT/ds8sZ10mPP7u6sRi/5WTRgEQiWZ8b/ueFrzwXnIDq7ZAFHBxHJ2BODwK4JLw+hIAjwjpF4YWSKMQKJ5fD0VP24nouFCfcLFShtf1OQAzWBsGJVErjs6+deQDkjoHvdIaWLB6WyKyaHSf189ipxqTzsH2GtRwH3261eIbp43BX79yrNQZccCeelAJBJX0du1BP0n6y6GGUOZgTM85AH6HBYkY3Ls+7qJBbBckqCU17eiKhI9rskY6JAzpzb+hWmu/HnU4ccwA9G6IF0XdAu+iifx51F3tt8UQG5o8QTTdAIEpq97PQe2LLb4Q/87zViXHNhex6gwYbNybuLOvi86htnYTw/rGorjAYkyfryaX8zLa4LDlfWPZpoQjKBdfxWd3xOW/ed9sKaZa3F+5jZcbN+LUg/bBdZ85DACwZ28SKxHRXwHMBHAQEa0gossAXA/gTCJaDODM8DcYY/MAPABgPoCnAFzFGOOk8EoAdyBQUi8B8GSYfieAAUTUCOA7CC2f2grix/m3j4zC7B99DEByQJo8ccWBqGfNnbMdQCCT/tEjgalf0s/BQ6mnLmhE+M7HDsJYIbKpSszO14iiXBPRtqPn99QscohyWccy64PNUl7uV+Grt9CbsgrXiYXeLVZSIYuV+OKf/EaALE7R1SPKkPViJT+oZS+cFH9LPn5E0ZPoz5LPEZpaC1iyLg5NYhYr2ThNfV8A4AefHBflMVkyqVi8dgf+JHh9dwtl+KbglBy//vyR0fU7K7YY50ltnrxOS+RwOWn+9LH5Uhr/5vF5DnH599Zu19aj5XyJcMHEEcjnCJt3Js8e6Sg4bekYY5833DrdkH8KgCma9FkADtWk7wFwvqsflYL4cXo11EbmhD4256qYRrfQ+NpZPTJ7FR56K4hTpCqkufhKHUg3/0usWFUXbdNkF8e7aWG17a1sYiXepjr3Ra5G3K3q2vnyiSO1dZigO7RdfBUu8ZT2vkYOrLajRhrhEpBWg86BQ1ycdO9Q5QBV8LvTF6yT0kUZPu+LODbrhaNm8znCy42yaaneGo+s4ivRlFVFz3qunE36xSQsvcKn+tRv5ACMPFqvzrpKRN/udehWm8fulgKmL1iLzwjWaGJTNXnyOmedw0YYbc6TOoW0aRianimfI+w/oDs+dJxP357och7SIsTvneQckvlVZZuOoLgWJ35XnMhqjKO8sivlmCg4lXkrkx2iBGd/I7GS/l7wNykW00EbTtogmjLhNzMajXXo2ua37r3sWNzw2cO0RFTtl0hUTToH/jvSOWgeOkck2dnrFp+tuwzB5JT+v7JEf2BTkCccL9LGhSSxkgrtIkUuzsG+o+d51B14YiNj+NT8uM9I9GpsJTa5zedyxh1/TS4XWDN5EggbYbSJPUlDnE2wzce6fM6pFG9PdDniIH4/267NFPpYTCXN23MtcbqJodM5AMmJqob1dtUbODXFv2028CboCMzz3z0F7/3s48aF3RyTRyeqk/+6YAsACCQJ9kNvBRbUHxk7EP9yzH7a51WfT3xms59DSBwMOocgj8w56BYP9expXR2m+jn4ZqJYZDh4315xCJSIsCXL6HVqZCcO4V+rkQOShMeHywWAq04NzlSJiZD5TGf+3mvzhKmvLNPm4V73ukgCokUdh0hEfnqObIloIw6m2Eoc914W6wEZMyudXaH62xtdjjiI00IcswkPWU1J1YpIO1xcKgck5fQJnQMP2qYMFPkoUbUhnYwrXegJbX8p3D0LhQf1qpdCWPsu7FqxSqS38JW+h3UZ0tVq1m6TraP00TjVSmL5ffz+5HJcEmhyggOCZxMVrm21KYx0Dixoc1DPeqlvuoVNq/9wcA6uRTCoI+BYdjbHjpcmT2sV3BM+5hwYVm/Rn+HA+7B5VzMemBW7UI0b2ju65vNFp2jWPb/47PW1sm+NnTiY6wSA8UKfADn0+CXH7y+1kXEOHQjx+4nx8H2WpqTOIVnKd4kTF6mkziH4O3el7MWZlzgHdxuqQ5J22DnrSfo5+IoJgtLxTd3kiS2eXP3wg0s85XMGtV5cqPwOE/jir4/FBbS0ijqH9BM/Unx76AIKRYZCkUU6iEispOmczlPcyTk4FkGehzGGe1/9UKhXyePp2xFYIunb+topwemDIwfEcZYOHdY7OsgKCJzgAD1x0OkiJOKgnN+hcvfHCycMmpzg4n7EZUUrRQAY0DO2usvn7KbE7Y2uRxyEa9tCYtrlyiGNk3lcO+BYTh+nbVfCW/B+XXj7q1K6SMx8ZPRqsDWtqMxVBwFQAq35ipFU6COGpqvDBVc1ah8+P2kEhvRpkNL4Ahfk54u//pn5QTT6/rt1Di5EopHWuGwPxWM8EiuFjpVchxVxDkrfppx3KBpqk17n5OhjRBwUKc2vLozDm0hRcaNy/psJMT+DmTicHfqZiPGpJozoi16C6TA3qdaJlXTPKRJglTiIvkhfOnEk/np58ihT3tfm1qJ0qJKoU2RgUqh9ccMXcA57kSlrZ4PJyiWhkNaUVZ3gdDsg52KrSVM5BNMuWjzz2aR4lerJuR2J3DqH5A4uKSbwJQ7JzojHS9pw0tiBXm04OQdlAbjuM4drFeo8F5+rarW8HX4gvV7nI8vMP3n4UI8nkMEXKfEgor9dcYKUh7/DmHOQxT/q9+rXvU7bFrmslRATIY4bPnsYzpkwTMpTMbk5M8dNEkOic3DfEw6+KJfCOahjQmS0/uNjcpRlNbbS7S8ske6LVS3bsEsyb5bEyw7Orb3R9YiDsOwfvG88mNS5bVJIS9ZKWs7B3r5OwfiVMPwBh2mBk8RgHko+daLaZP7G/oZ1iPFvEiIW5bfo6Tp+mDxhVfCdseu98XMzOEzrj0s8JRkUGPKK740vlrozN+Tfmo0CxZzK7y86WpKH+6IuH+zwa4R32qNe3vVzsVGRMbQWi04Zv+kduXQOvB7RV8VGWMsBN/4Q9dH8fI+gHa5PiDOIARaBWJyjU2rrDspSw/GLyBFhYM96fH7SfpHZbnwv+MvNhdVAl+LY+PLdb0ihR8QNZj6XjPrckeh6xCH8/ndcPBEfEXaj6iDX7SxyZD4qMM7jXmyD9uI0dbCZduKyzsFDrJTQOST7rsa7N9WxWQg3nSRM8u/+PeKd6c/POwwPfDWI/qkzKayN4v+4dvyJFHOHPesxyb5JEI3wXadqbqzK8XUKS/GZbHbyNnDiKR5sb3LI4yG71b6oYiUTf5tzEAfT0blygjv0i258q171BJljve1fj8Ivz0/6+Yj9Vd8x16u0FIqJgHZ6ziH4O7h3faKPQd3MoFsKEme+v1H6Hd+Pr5taC9LpdOK9fI6cYcPbE12OOHCMHCifnauOV5vy1PQ7DSSFtGNXqsun5hEVW2L/0nCp92vkqNxCyxZaQOzLkfvJZy801OajoxBtfdEcZy3BV1ThXoPtnF+QHvsIcBlwInJuQuzgIA6W8yps4MRhl2D9oxL52C9GHwLexfVwEPxMWcX6fDhYUz0inv72yXIeCsyJo8CGhmcQrcESRFEQt519y4vSPd1z8s3LQ187UWuAUGR+0gIbV8kgWytJEYUFhTRjDKu3xnqLjkCXIw6moa9+c9suNyqjHSguuVIyKbEr9eAcxOv/96lx+OOlx2j6IovHRg1MHu7Dccnx++PYA/SR0rfubklE4ZTbERYL7f3gr26BNyl8bRAXShViADgdnKbIkN9bS8Q52BdY2xnYuvK+4Dvq3cJz8VDmUV8EJ6xCkUUL6S8+eziG9+sGIsKfLpsUd8vwrgMxmJtzEB/FR7yma0dE74YajBoon+6WzwVmwJHexECMRfGQ7kAmIJjzi9ftkO7pOAeelidK9HHLrhYwxgziQ/vGQfxZLDJsE4iDrHOI152/zVqB46+bgbc/lMPNtCe6HnEw2a0rC7TO96ZOsWDQLoSO9vPRgBXY4cSuVF/WFGDuX4/dH/sqFjdBPcGu/+B9e2H80N7WE9VMDoHTFgQK13+8vdJcVloszJNHt+zwz6EqE5P54tK/e/59Ixfyf++u0t/g9Wj6peLJOauxYUcztu5qiXaY6s5fJQa6xb8UsZJ6hjdvp7k1Fiup31qM7SMeO3vBMSPw0n+dFtQjWbrp23aZsvLB3WrRu/nQeDWLOq8AYEifBqzasjvS+aicZaRzsIrBgr9Jj21orYLEtlTR3U3PvBdwDsbWhPotBhuMmYPr5XOxh/SrSwMRVaNC1K59dB5mLDSHHa8kuhxx4FAHsTp5dYNHtQ03HQjk0+60+XGsnFKsf8QipoWHEEyMlkJRsgcXcea4wUEfDG2u2OxmbaVAe8aFB9KOiWOfXoE47OunjbG2Ic7vW6YvlhTkItS14kZBTq3WY1oIN4chLZZu3GmMnJu0ZtGMBeFa3QCYcMNnD5PrDdtpsYj1IvEJY2gVrJVM/bPt7n0U0nazZmNxoR45k+6gp14NNdjdXMAToUd8op3IWsnN0apZ6mr00VqLAuegowLBsbPp5maiDpgP9MnnhPcf/rnhqYVobi2CMYY3P9iEu19Zhi/fbQ89Xim4D7HtZOADW/1+6uTVmfSpR1nq/Rzs7XPxzOvL4iMr1Mnhw5qrskodKNwJbt3dYlycuNgibchsET2FsyXMSl7CkvXyLuh3XzwqiiJb61A6+KpOVCuzA4UotSpcJ38BsdjCJbfX6xzE+377sKToknMO5kWQj4U5K7di+55WLaGX+mci4Dn7O/ETGaUXK+m43nwuh9Yiw+0vvK9tO69wDjddIG8CgjLBX5VzqM3ntBwHF+HU5HPaV8QMOodE3y2ZgoOSAi7wpLED8cXj9o/L5WJTYt67DTua8fDslWgtMPz3P+a4G68guhznwMU5rp2fVqwkTNyfn3eYMWSCtX2tOan9tw6+eRau2Y4NO5qN/eKLka+vgu6shoE9xbMVzH1Rnf0OEk2JHc37KqTFne8Bg3rgsOF9pPsi8XAFZGPhThxIcg4mGbiIUsRKJmVysyX0NC/y++ffN/bFh3MgEArCjvrHnx6v3NeUKcEoQy0xoEfS76ImJ4u4TMS5EHmom9+/OnRMAe4enr0qakut79SDBoVHWuqf94KJw7FvGCn3xmfe0+YBgnHMCf3UL02SnBHzuVw0JsXxXiiyhHipPdD1iIOJc1B2docN6wMVomzUZHxSyv7bpdDyKaPPI1wb8nDi4GtM89CVJybSRG9SqwWQMkttOywVvn5VY/aJle7jhya/obgmuKpsKcR+A0kvX/m3On6CTMJ9A+cmxtYBzGIaG+egLpw6QiL2z/TWcyRzDscpBgq6cal+w1Is+HRjWTXrNIuV+GYvWS9/5J0aAwabOKoml1RI19XkQoW0vowrAjI/NY6xQHpQk6OkOTTFz6OO9+ZC+58Q13WJg/KRxcn7mSOHRe75ImRrIRN1KF08k6aKtKIn04oQiZUM9f3h4onR9YQRfRM7cUAlQvp6dD4isse3g+MypHdXQkl8/xOHSG0m64lrcsU62tNSMMrwE2IlBxepJR6QuSfAHITRR6zEsVxzJoDYvJFzIPn8A5Vb0xVTNxVinrp8Do9cldxMqBXpeqNyDiarKL7I2wwhvvbnt6T0lkJR4pBUBMeqJiUJJlPWoC2/wIqMBd9SDc8BhKasGs5h6YadUqyq9kKXIw4c6scX2XndAgjIA9CXc3hYmRyu8xXUdsx5nFm8Fm2+aJk4kbHCTlwXrE0ta5w8oIQSsLvAUrse2bSQD+/XTfrdTSAWugVbPBPDNJl/84Ujw/uBCKBe89wJm3oNZyCmmMRKatW6UwEBh1hJKaM7MEbiHGwLXFEknsYmE/2Lf8fXl544MmF9BSTniJYjycmEyuTY1+ohVlKNFwKO0EIcNKashWIRDHpTVoBzxsAjs81WfUA8pnQWWjW52DNffPdc79Le6HLEwTQkTD4EImTioH91alHVfNRrwnl8lUqJnvizmp5ZTK+tMcmq3f3KUTKMgbiQu3pqem9quqjQ1T1/XU0OP1Fi9avgZxRzyxLdRDYpSE15TGIll+7LR/Sm5lF1O0G9Ypv6eggyd6c750KFzTHUvJlQ6tBkUzmHhFjP4yQ+0wbqlIMG2T3BNWKlAgs3E5Z3xxjDN++brb3PxylXSKu+KoBMEH02kW2NrkccmF5GKe6sbAtcnN++Ey8Havv/MnEE3vj+GVKaj+hJzGJWFNuJg1hOZ3Io1uFqR9391te43zmHSSGtpop99PEXsd1nnHPQEAe1Cr2YIL42jQsXkfHaKCh5vnZq0iw4L+kc/AhVMrpqsozJKxnQ+y/o2tfrHGRzUzPnUDTWoRtTf7vieAzu3eA8W1rtYzE8t9e8NpB1OefFisy+4SgadA4dgbJWMiJaRkRziGg2Ec0K0/oT0TNEtDj820/Ifw0RNRLRIiI6S0g/OqynkYhuoVJMIDxheufizs6HczB1UKznrksnJu77fHP18RtqcxjUSw6PkVrnYABfS01ZJc7BcydoyqNOSB9xFIfpvekOs+d1+RB5HfhtrjzUTWTxvfzknPHOs6BNnIMuTIN8Px3nMKRPAy4SzCN1ecxKVf92ojJKIXGMGImDUo2uWZVzaFDMyNWorL5m5RNG9PU6VEct21ososiYVZlvP+ciLmkbU9wgwFYX52zbGpXgHE5ljE1gjPGV8GoA0xljYwFMD3+DiMYBuBDAeACTAdxKRJy3ug3A5QDGhv8mV6BfehgU0rLIyDCRPd4WL3vS2IE47eDBmvZ9dA5KkRL7Itbj2vWbFck+O8EYJuc0IvlUtKXXfSJxn+OzRw3HC989VbpvfG2adJ7XtGC7Flx+v6VQxKPvrMKyjRoFr0TY9PU9NXdNdG3iNNW+uExmXXUYQ6/k3f1N7JZVz+IcJSKfqv0T+28UKym/tTqHvGyt1E05f4IX8dE5iKjN51CTJ2cATbVksRgMNZvOwWYaLZYycaMi0bItE6qera3QFmKlcwBMDa+nAjhXSL+PMdbEGFsKoBHAJCIaAqA3Y2wmC2Q+9whlKg6Tn4P40zQhfRgaPjnKCcqnDoxSQm0Dcn91gxGIF1DTTkVsRz1kRtfOvFXbDPXInIPuXXI78UOG9MJ+A+TAiCaFtG2K72zSx2ByLbj89rbd5hhOYhWmHfenj4jPbzBvOMxiGbUdE8Q6jLojD85BbcvHSsvmDKg6jZra0fVHPdtAPZxIdYLTbZZMc0TlSvR9lMsWwrMlbMp8u3d5XHDL7hb0akj6H4vPbOtde50zXS5xYACeJqI3iejyMG0wY2w1AIR/9wnThwFYLpRdEaYNC6/V9ASI6HIimkVEs9avX19ahw1+DrI3a2k7TiCOwWOagOpn1R1i88J78rPpzGp9+rJue3z+rok4xBE9TcQhvh7er7s2j9cCRmQ1xxTrcQWxE6GebSDi0Xf0cZZc/eX3bUpB+YhZfYVH7hdJVC2cm/pbJQ4+okEP4iCkmxe4+MalJ4zEOE28K5Opre7+gB7JSMFA8n3pxnJNjqTzv02Kb85d6HUO2uYj72ubKbNatlBkoYe0mevaKYRV33+AOerzmq17MFQjGpI5B3Pf2us8oHKJw4mMsaMAfBzAVUT0UUte3Vs16f+1j88Yu50xNpExNnHQoEHpeytUnJB7ijsrj92XUXfh4BxOGhv3+8DBPfGny45N5OGxfQDgp+cemnBGstUv4k3hUBY16mVUj4NzkHaCHmIlEwKxUjCR//JvyWcGzCeXAcDXTtHHXrr9oqRexwXfMzds8YzEMWJahEQ5ue+Go5QwJrZQ7rp6TQucWPayj4wyxA6z91ciDj31J86p0L3lfI6wuyVebAcqdUVOcBaxkuk5a6IxL6fX1eTw1ZMPiNoXwceu6euo7/3OS47BF47dDx8JD6kSbze1FhJiMt6mzpRVxV7BOTDGVoV/1wH4B4BJANaGoiKEf3mEuRUARgjFhwNYFaYP16S3CWLOQdmhCdcmsYPPvI2OvTRkHjWwR8QtfPzQJEcAAP8uBKHradgZN7W6PSbFCXPBxBGGPMFfk7zUR2ThG6aZNzHWEO/IFr67T7faRNoPzj5EuwNzwaWv4c3bLFp85Pz1wgJg1jnYf6t48wdnJNLE72KyipKIg6FuPw5Q/W0mDr6iNN1iJyrwezfUOL2odS3xZtTDtHi/1O/bWihGMb5GC/49nz5iaGQebBMriajNE35+3mG4N9wIie+pubWo5SRFU1bbJsEV9qVSKJk4EFEPIurFrwF8DMBcAI8CuCTMdgmAR8LrRwFcSET1RDQKgeL59VD0tJ2IjgutlC4WyrQZ7AppUxn37Kl1iJUAYNGa7QDMohzxwPu+3fS7r/Xbm7TpInyC80UnannoHIzRX1MuKqZ6eA98d8/d60qLG+mrkP7x/8235ImvTdXJYUVM7y5OX3b92dYx1rd7rfZQJ4lz8BAr2cwxOUyE0RmAUJxHhnbU+FwmJ7g4v1kkx0WVOmuwOLaSPLb5+xLn319e+xCBtWqQ1lMYW7271USOhfe9LkrGzc9gcw5sKTCtcUf/HnVgDFi9dTf6dk9uhoDAKbW9xErlRGUdDOAf4WCuAfAXxthTRPQGgAeI6DIAHwI4HwAYY/OI6AEA8wG0AriKMca3v1cCuBtANwBPhv/aBCY5ss9OMBXnYJnk68KF/Z0VW/TtCA2ZBonPAuqzxEaWPSYrF3GyG61P4jzfPesgbR6J+BrMOvkk9iUOJuspF5xiJS9i5x4vPj4vaeJL2SxlovoMTdZ4EAcRJpGacxH0aCcZ+j6ZR3x3No6VRznWERDe/k7lKFyuFxQtlnjEU26EID6HyLWu2Rbr8eSHUNpW+6wQXl0AS26QsXV3i9HJdv8B3bF6q6EPFUbJxIEx9j6ARJxcxthGAKcbykwBMEWTPgvAoaX2JQ1MCmnJWsmxs7WBf3SX3TvgtyD3667nHLxcQTyycJbedjoYh5FzEMax6UAh8VlN4blNp36ZoJtgPnDrHNwQx4gpiJsPkUvjM+llEOHhbGeqZr5gaaYLo60rq55BLllFGZ4tEZZc88ZlUZmZOEScgyaP6Tl1nAOHjmPq3aDfoKl9EZEMSBhfm8xoRT1Kq4Fz42H42wNdz0OaX5gJu3FhFz+KSSfkwzlwGAe9kG4iDj6baz/OwexEBPhNUjH1xDFJ6ysgHfH15RxKNRd2Va8Syp+dm9y3iFlMqgkv7s7jGQ4YFBgT+LwWk9GA+O1MDnl80bpg4nCtjgdILnrb9sgHOPkEU6xV+qgj8o8JJ/qZzt/e3VKIjv/UEUXj5osvwhqirnJMJ4wegN7Cu/jF5w7X1qm2lGAclBzPzE+e5sbfLT/uVdt3onbznu5yxIG/WZs5ncmMzIdi80Hqs6n1MTvsZvAt8IEP91KwKIHVdN/4QM56TMQhOqbRb9EvkTZ4hM+Qf+sWSlmspK/H5wwHV/gSAPh6GA7Dh9iYRG3iOzXJ8DmsR28qfThhtGxJJ4khDf0ViUFtnvC9yQcn8ohmrD7vUatzcIjYdPP54H1jY4lFP5uMe748SSK4XPSTaMsiXgOSY2r0oOR57nmhX6ZvsGV3Mxat3a69V2l0OeJgNmWNr00LpTiYyoxipAAAEsRJREFUjj2gvzZPGic4H4clk+ikUpxlMdI56O+L6b7BBm15iMyLf8Q5eK76OnNAHzg5B486fPwGeB6Tp7DYF9sCyMdSOWNKhK0/gHx4kwq1C70UkYuPWa3Y/nWfORz9NYf9iPB5Jt3762EwWIg4B4FLqMvnMGlUf/xbeO4CANTX5FGTz3l9a5cVl3r/l+cnT67j7RQZM4oqX30/OEFy9Vb38b3lousRB6MTXJyiemNyiNTcNIGY8tcGowWRFEHTvsu2wWeRu/SEkThqv774l2P209fhYX1icgITwd+v7TjQ2M/BWR0A4OQD9b4ux47SE26OBavtOy91Yut22uLCYnr+aFGxvJ7ovVgemnfHJDIS8dwit3Ooi3P46kcPMN5zEW4fhbR8+pm1ujCPPwcswuRnwbkMcT4XGMMxI/sZTWY5jNPOQQxEB9Ke9TXoUa/xkJZ0Dvb53R56hy5IHPQKWPFjmhRQBcvpURx3vbwUAPCPt+1x3QHzRPPZOfs4wvjsNAf3bsBDXzsxEdhPB5Oll5duPMxjtd92iLhUmGTRU788CUAyWBuH61QttXndosz1AEEBfT1eCumwMZPITszTz7HD9oWtLQBac1m1Lz73TXkHC6IZUx7RadNFzABoF1MTZ8lFv3w+s1DGb/QR8RKbyr/VxfucCXEoFdPmUzQrdy3+5YTn8UWXIw4cyVcbpxwyRO+k5QrWBaQLteujczDBZ+NQ6fFjNqX0L2sTn/B351q8AOB3XzzaeK8un8OQPg34+XmHae9fcvxIa93qc+rk+KYJLoI/q+1p+OuwLYC8P+qpdyJ8iDtHOdF1XTqwkQPjHbJpHItxhUx57rgk9nw3cdhXnDxaWyeHy0Oaz2e+EPsYiJggco/d6/IJcRsRRfqMbnV2R8Uv/fENNK6Xz4y+6Lj9pfHcHjrpcvwc9kqYXqrs1OTezVQCJosQHwWvD+dQac7TSBxSiJVMPg4AsCMMlOezK7KZseZyhJnXaK2pAcieyz6Y5BBTmXrioyvgC49ND+DDdfVqqPFyjLS1Nffas5yLzmCDQpZjn14NGNCjDht3NhuJjUicmlr03PgAgUsyxgUTkvcf4D83RfHNtj0teHXJxiDdMKZEouFaP3o31ODda8/S5uHz2sTR8Odpai3iAyUS8LWfHo98jiJ/DNsxp5VC1yMOXOfgUCDpMH5oH7x6zekY3Nt/l2aDyWHMBxOGB/4EPzj7EGMeviN68XunltyOCNPa5LPj5BYWPrJSn2FfDlfksn4R654woq9TrHHWoftq0/kiZAsOGCmkrWIl/tecx8eih8O02Ork4Cps3AsHJ3g+nLFqCsshigyNR6yG7+Po/ftp76sYP7R3WHcovikyfP0vb0eBLsuJAMDz2DZ2vHqXWEnFAQN7JN6lKaJBJdH1iEP4N3kalV95k3NQKfCZjCacMGYg3vrhmVZLD85d+MhsfVBObCUO3RGWCbTxuHeJrSSHPQ8Rl0lHxR20bGE+yEPcxnkT23vmYVa+rjkFjuOmC47A7OVbvE2FdeBj4Kj9+uJvV5ygzUPRX3c7+/XXR/oV38cUg3iQP4fP4Td3XToRpxwYBIjmVnetxSIaBbNQkzWeqM8wGYLw72ibCvz7+Ri8iNCJzHz0n+Wiy+kcmMFcqVIKHn44vcs8z4XPTxrx/9s78yCpijuOf357ICzHwiLowrIsKmI4IrhERETRkgiRBIMmXlFEo1Ewin8YNYll5bA8KrE8sKJUApVLTaWMCRqjMamoMZdIiQcgXmUFlNIYlEONQFXnj9dv9+3M6zdvZt57+8b9faqmdran5813f9vzft2/7v51j0msMEp9RlSW00pwh5WSJc7oIipjaimiVkxBvA17cTiwuT9D+jdEju783m8cBx4lxdd89CHFGXx9Fh3RxncXVpeIwHeWIlLyaNk45yCfcNjI0PKgPZwZhe0HDRlQupPVWF/X5UwaAmGltwKpKHY5RjHBm/bEUcVpzKG7nUR16P3Pd4WVPtoTvlAi6Ey+MW9Ckaa06HMjB5+ofQ7VMGlUMwD9K8z743PDovCdmOVQaqKtXCYcGD5Rn/TEt2s+ZUzLALZs99Z3lzobIopSPedgj7eaUVf/xnpn/LmQqNGMKXMVV5r4veuopdS+/eJEPlxhmDhO2a8T538UttO/sBPialPBG/HIweGRA/8grP/tda+E8yU4nYPjvQundh9v42+eK7XUNQn6nHNw51ZK5ovnp9KOChk9fNls1r6xPZHPi8KPS0ZNApeDKz120kd+uzpFD319Nod/549AdDrtagnel5JyrC78mHtU/p6ujYoR90BXuDRpGv0eckSduq6RQ/UUHksaxG92cZxDcJlq2D4HcO8ujxPC8b/vUXMy3WGl8M+ZM6Hnvp3TOtu4/ouTeywg6D6LQp1D4riOCY2zqSwOY1sG0jZsANd9fpKzzsRRQ5zD0yTx876XCqPkDdf/Iri6KwnncJBr9VmPsFK6tvPnI8IOdPLpSo6Y8o0/Dq69JUEWHD6KlU++HhorL4fN358X2Xb9FTtx5oWCsuu79jn0bGcu+/ohzChH5TuH1mb3/IcfQmxydBz3a+h2LPdeeBQzDy5uE915odQ5pEZhM0jKEQ/oV89TV52QzMWqxL+pJDXnkARxBhlx2n01YSXwRm+jhjoyjwZaR9ShSstPHN8jk2kldI4dxv2XzGTaGPeKG7+3mOZoKS5xYutXzTuMpXMOjhwNTR0ztOSqv+DNMgzfHvHCSsW978IbrOtr4ndW+jW4G6+/AizOApGo9CRdGp3Lar3P2Vtl+49Dn3MOrkadVabDLBERMCb10Eg5xLFznGV6e6qMuUaN3ILm+usr7zrrLT/x0Ko0+HSOjd5H0d+GKlwx6SBpT0v4zjJqX0Z9nTDUkU3Y54Gl4SudymGvPzKO4xxCEgIWpsV22W7h1NGs3/I+V55UnCDQp+tgoYhg2nsf7gGiNyweesAgXn57t7ND57/37Zh7WqqhtuINCeBKvOd7ddfSulrkt0tnsez4g6taupglvu1nRoRYzviMd9xpmr3opOdQqsWfwPw4ord4uj0G1hkqSwj/MJwhjg2ccRGRqu28t+ugn9LX8TdYQmAkVhhWisgFVSpBoN/Tj3JUO+0y7hERZ2t3bRZ1aGlvaWJa+9CqF7zEoc+NHOZPPpBDDxhUNGTtzuvTG6rSYUpbM1Pamqu+zj1fnVFWeoZKeTLGZr0ZB7Vw39ottA0r/+zouATbQFIbHquhc+wwvjy9jUvmuPcwnNrZxqmd7ph4Usw8aDjtLU1cMXd86p9VCr+DEOfEveCN3Z83uezeZ3vUOfPI8OSTcTiyo4ULjhnHhbPdSQv9ieio75LvHFx+c0C/eh5YOqtineXQ55zD2OEDQ7faDx/o/cMWRUw69VWOdhzgU0icFNquY0/jcsrU0XQMH+g8cS4JgnMOj1x+bGqfE5fG+jpuPq04xXNv0NzUGMuJZ0FwM5uLR5cfy8ZtO3osww4Lsy6Z1VHV3qSG+jquXTAxss64/QexZftHRXmXgkzvGMbGbTszmXAuRW6cg4jMA24D6oEfG2NuzPLzm5saeel782KlRVaK+dHZR3Tt8YjilMCa7UoQEaa1x0uXUPmHdD+t1pkp6THOJvmL6pRMOHBw0f6cQQWrhZ688njah6cfTr719KmsWf8m40cWH/Tjc+2Cicw6ZH+mpdj5iUsunIOI1AN3AnOBrcBaEVljjNmYpY44mTaVcOZPaY18fcVZ07j0nmfpyOBLWC3BDkLe5h+Ubs6aMZamfg0lMwkUUrjEdkxLeiHKIC0D+3HerHGRdRrr6zhpUniurqzJhXMAjgReNca8DiAi9wELgUydg5IeJ09pZeCSBo4bH35AT57QTkJtUF8nFc2zFO7V0A5AOHlxDqOBLYHftwIzekmLkgIiwvETwvPo5JEbFk3hkIjhv1LbvHHjyez4aK8zn5KSH+cQ5rqLZmRE5CLgIoD29spXFihKKapZuaLUBs0DGp1nqij52eewFRgT+L0NeKuwkjFmpTFmujFm+ogR+Q9PKIqi1Cp5cQ5rgfEiMk5E+gFnAGt6WZOiKEqfJRdhJWPMPhG5FHgUbynrKmPMhl6WpSiK0mfJhXMAMMY8DDzc2zoURVGU/ISVFEVRlByhzkFRFEUpQp2DoiiKUoQ6B0VRFKUISep4zKwRkV3AZsfL7cC/S1yiGdhRZZ0krgF9U29SWpLQm6WWUnWyagtJ1cmTXv2uxXt9gjFmsKtyF8aYmnwAz0S89p8Y719ZbZ0krtFX9SaopWq9GWspZZdM2sInUa9+1+K9HnXvDD4+qWGl92PUeTCBOklcA/qm3qS0JKE3Sy2l6mTVFpKqkye9+l2r/HOKqOWw0jPGmOnlvpZHVG+61JLeWtIKqjdt0tAb95q1PHJYWeFreUT1pkst6a0lraB60yYNvbGuWbMjB0VRFCU9annkoCiKoqREzTgHEVklIu+IyIuBssNF5B8i8oKIPCgiQ2x5PxFZbcufE5E5gfd02vJXReR2SeEYqAS1Pi4im0VkvX2kclqOiIwRkb+IyCYR2SAil9vyFhF5TEResT+HBd5zjbXhZhE5KVCehX2T1JuqjcvVKiLDbf3dIrKi4Fq5s20Jvam33wr0zhWRddaO60TkhMC18mjfKL3p2jfOkqY8PIBjgSOAFwNla4Hj7PPzge/Z58uA1fb5SGAdUGd/fxqYiXfA0B+A+TnW+jgwPQPbtgJH2OeDgZeBicDNwNW2/GrgJvt8IvAcsB8wDngNqM/QvknqTdXGFWgdCBwDXAysKLhWHm0bpTf19luB3mnAKPt8MvBmzu0bpTfdtpvmPy4Fw3bQ84a7k+55kzHARvv8TuArgXp/xjunuhV4KVB+JnB3HrVm8c+P0P47YC7eJsNWW9YKbLbPrwGuCdR/1H6pMrNvEnp7w8altAbqnUfgZptX27r09lb7javXlgvwX7xOQ67tW6g3C/vWTFjJwYvAF+zzL9F9mtxzwEIRaRCRcUCnfW003qlzPlttWR61+qy2Q8Zr0xjmFiIiHXi9lX8BBxhjtgHYn/6wNezM79H0gn2r1OuTiY1janWRV9uWIrP2W4HeU4FnjTEfUxv2Der1Sc2+te4czgeWicg6vCHaHlu+Cu+f+wxwK/B3YB8xz6pOiXK1ApxtjJkCzLaPc9IUKCKDgPuB5caYnVFVQ8pMRHkqJKAXMrJxGVqdlwgpy4Nto8is/ZarV0QmATcBX/OLQqrlxr4heiFl+9a0czDGvGSM+awxphO4Fy+WjDFmnzHmCmPMVGPMQmAo8AreTbgtcInQs6pzohVjzJv25y7gHrzQWCqISCNeY/2lMeY3tvhtEWm1r7cC79hy15nfmdk3Ib2Z2LhMrS7yalsnWbXfcvWKSBvwAHCuMeY1W5xb+zr0pm7fmnYO/uy8iNQB3wbusr83ichA+3wusM8Ys9EO13aJyFF2CHYuXswvd1ptmGl/W94ILMALTaWhTYCfAJuMMbcEXloDLLbPF9NtqzXAGSKynw2FjQeezsq+SenNwsYVaA0lx7Z1XSeT9luuXhEZCvwebw7qb37lvNrXpTcT+6Y94ZLUA6+3vQ3Yi+flLwAux5vtfxm4ke4J3w68CZ5NwJ+AsYHrTLdGfA1Y4b8nb1rxVoGsA54HNgC3YVfYpKD3GLwh9PPAevv4HDAcb4L8FfuzJfCeb1kbbiawqiMj+yaiNwsbV6j1DWA7sNu2n4k5t22R3qzab7l68TpmHwTqrgdG5tW+Lr1Z2Fd3SCuKoihF1HRYSVEURUkHdQ6KoihKEeocFEVRlCLUOSiKoihFqHNQFEVRilDnoCgpICIXi8i5ZdTvkEAWX0XpbRp6W4CifNIQkQZjzF29rUNRqkGdg6KEYJOiPYKXFG0a3ubFc4FPAbcAg4B3gfOMMdtE5HG8vFizgDUiMhjYbYz5gYhMxdsR34S3wep8Y8x7ItKJl1vrQ+Cp7P46RSmNhpUUxc0EYKUx5tN4KdeXAXcApxkvR9Yq4PpA/aHGmOOMMT8suM7PgKvsdV4ArrPlq4HLjDEz0/wjFKUSdOSgKG62mO58Nr8Avol34MpjNjtyPV6aFJ9fFV5ARJrxnMYTtuinwK9Dyn8OzE/+T1CUylDnoChuCnPL7AI2RPT0Pyjj2hJyfUXJDRpWUhQ37SLiO4IzgX8CI/wyEWm0efadGGN2AO+JyGxbdA7whDHmfWCHiBxjy89OXr6iVI6OHBTFzSZgsYjcjZct8w68I0Zvt2GhBrwDmjaUuM5i4C4RaQJeB5bY8iXAKhH50F5XUXKDZmVVlBDsaqWHjDGTe1mKovQKGlZSFEVRitCRg6IoilKEjhwURVGUItQ5KIqiKEWoc1AURVGKUOegKIqiFKHOQVEURSlCnYOiKIpSxP8Bww7flN5vXR8AAAAASUVORK5CYII=\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sorted_data['inc'][-200:].plot()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Etude l'incidence annuelle" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", + " for y in range(1990,\n", + " sorted_data.index[-1].year)]" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "year = []\n", + "yearly_incidence = []\n", + "for week1, week2 in zip(first_august_week[:-1],\n", + " first_august_week[1:]):\n", + " one_year = sorted_data['inc'][week1:week2-1]\n", + " #assert abs(len(one_year)-52) < 2\n", + " yearly_incidence.append(one_year.sum())\n", + " year.append(week2.year)\n", + "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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