From 6a96005a628d464f9b9fe4c44b16383a4cd4278e Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Fri, 5 Jul 2024 15:22:09 +0200 Subject: [PATCH 1/7] add spei r comparison --- .../example04_package_comparison.ipynb | 239 ++++++++++++------ 1 file changed, 157 insertions(+), 82 deletions(-) diff --git a/doc/examples/example04_package_comparison.ipynb b/doc/examples/example04_package_comparison.ipynb index 7fb8f11..65c6444 100644 --- a/doc/examples/example04_package_comparison.ipynb +++ b/doc/examples/example04_package_comparison.ipynb @@ -22,7 +22,22 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Versions\n", + "python: 3.10.12\n", + "spei: 0.4.2\n", + "numpy: 1.26.4\n", + "scipy: 1.12.0\n", + "matplotlib: 3.8.3\n", + "pandas: 2.2.1\n", + "\n" + ] + } + ], "source": [ "import spei as si\n", "import pastas as ps\n", @@ -74,7 +89,7 @@ "outputs": [ { "data": { - "image/png": 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", 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+/OEP+6UDPvCBD2D9+vX45je/CU3TcOONN6JWq+FNb3oT7r777phIefXq1bj++utx3XXX4bLLLoPrurj33nsTjZdyuYz77rsPn//85/HjH/8Y4+PjeOUrX4kf/ehHfnK8vJicnASAhvc5E7j00kvR1taGf/mXf8HnPvc5tLe3413vehf+9V//NZTjJQ/+67/+Cx//+Mfx6U9/GpZl4R//8R9nzHh5xzvegSVLloAQgj/5kz/JdMwnPvEJ/OpXv8Jdd90F0zRx9NFH45/+6Z/wmc98xv/NySefjJ/85Cf40pe+hCuvvBKnnHIKfvrTn+Kmm26SpQ4k5jUUKhVVEhLzApx5+Ld/+zf8/d///aFuzpzju9/9Lj772c9i+/btqcn4Dlc4joM1a9bgHe94B374wx8e6uZISBxySM2LhITEvMC9996LT3ziE9JwScCtt96KwcFBvP/97z/UTZGQmBeQbiMJCYl5gVtuueVQN2He4ZFHHsEzzzyDL3/5yzj99NPntRBaQmIuIZkXCQkJiXkKXjNp5cqV+MlPfnKomyMhMW8gNS8SEhISEhISLQXJvEhISEhISEi0FHIZL9dddx3OPPNMdHZ2YuXKlXjnO9+JLVu2hH5zzjnnQFGU0H/RgmR79uzB29/+drS1tWHlypX4zGc+A8dxpn83EhISEhISEgseuQS7999/Py6//HKceeaZcBwHX/jCF3DhhRfihRde8LNzAsDf/d3f4dprr/X/5tknAVYz4+1vfztWr16Nhx56CL29vXj/+98PwzDwz//8z5naQQjBgQMH0NnZOatpuSUkJCQkJCTmDpRSTExMYM2aNbH6ctEfNo2BgQEKgN5///3+Z2effTb95Cc/mXpMT08PVVWV9vX1+Z9973vfo11dXdQ0zUzX3bt3LwUg/5P/yf/kf/I/+Z/8bwH+t3fv3rp2wLRCpcfGxgCw4l8ibrzxRvzsZz/D6tWr8Y53vAP/8A//4LMvmzZtwmmnnRbK5XDRRRfhox/9KJ5//nmcfvrpseuYphmqx0E9jfHOnTubSkM+n2HbNu6991689a1vhWEYh7o5hxyyP+KQfRKH7JMwZH/EIfskjPnaHxMTEzj22GMbru1NRxvxNNWjo6P4wx/+4H/+gx/8AEcffTTWrFmDZ555Bp/73Ofw+te/Hv/7v/8LgNVE2b17N37729/6x1QqFbS3t6Onpyex+NzVV1+Na665Jvb5TTfdFHJJSUhISEhISLQuKpUK/vqv/xpjY2Po6upK/V3TzMvll1+O5557LmS4AMw44TjttNNwxBFH4LzzzsP27dtx3HHHNXWtq666CldeeaX/9/j4ONatW4cLL7yw7s21ImzbxsaNG3HBBRfMK2v4UEH2RxyyT+KQfRKG7I84ZJ+EMV/7I2tB0KaMlyuuuAK33347HnjgAaxdu7bub9evXw8A2LZtG4477jisXr0ajz76aOg3/f39AFhhuCQUi0UUi8XY54ZhzKtOn0ks5HtrBrI/4pB9EofskzBkf8Qh+ySM+dYfWduSK1SaUoorrrgCv/zlL3HPPffg2GOPbXjMU089BSCoFLthwwY8++yzGBgY8H+zceNGdHV14ZRTTsnTHAkJCQkJCYnDELmYl8svvxw33XQTbrvtNnR2dqKvrw8AsGjRIpTLZWzfvh033XQTuru7sWzZMjzzzDP49Kc/jbPOOguvfvWrAQAXXnghTjnlFPzN3/wNvvKVr6Cvrw9f/OIXcfnllyeyKxISEhISEhISInIxL9/73vcwNjaGc845B0cccYT/38033wwAKBQKuPvuu3HhhRfipJNOwv/9v/8X73nPe/DrX//aP4emabj99tuhaRo2bNiA973vfXj/+98fygsjISEhISEhIZGGXMxLo8CkdevW4f777294nqOPPho9PT15Li0hISEhISEhAUDWNpKQkJCQkJBoMUjjRUJCQkJCQqKlII0XCQkJCQkJiZaCNF4kJCQkJCQkWgrSeJGQkJCQkJCYc5iOi55ne5s6VhovEhISEhISEnOOKdPF3S/2N3WsNF4kJCQkJCQk5hyUUqCp0tDSeJGQkJCQkJA4BCDN2y7SeJGQkJCQkJCYe1DQhslv0yCNFwkJCQkJCYk5B6WMfWkG0niRkJCQkJCQmHNMQ/IijRcJCQkJCQmJuQeh0m0kISEhISEh0UKgkMyLhISEhISERAtBhkpLSEhISEhItBSYYFe6jSQkJCQkJCRaBJSy/5qBNF4kJCQkJCQk5hyEUtAm/UbSeJGQkJCQkJCYc1BI5kVCQkJCQkKihcCYl+YgjRcJCQkJCQmJOYfUvEhISEhISEi0FKhMUichISEhISHRSpBJ6iQkJCQkJCRaCsxtJJkXCQkJCQkJiRaBFOxKSEhISEhItBSkYFdCQkJCQkKipUAoleUBJCQkJCQkJA4PSONFQkJCQkJCYs5BKJVuIwkJCQkJCYnWAaWQtY0kJCQkJCQkWgeSeZGQkJCQkJBoKcjCjBISEhISEhItBUoho40kJCQkJCQkWgdUJqmTkJCQkJCQaCVQ///lhzReJCQkJCQkJOYchFAZbSQhISEhISHROpCCXQkJCQkJCYmWgiwPICEhISEhIdFaoE1LXqTxIiEhISEhITH3kG4jCQkJCQkJiZYCkaHSEhISEhISEq0EOg3qRRovEhISEhISEnMOJtht7lhpvEhISEhISEjMOShkVWkJCQkJCQmJFgKVVaUlJCQkJCQkWgmUymgjCQkJCQkJiRYCkXleJCQkJCQkJFoJzG00B5qX6667DmeeeSY6OzuxcuVKvPOd78SWLVtCv6nVarj88suxbNkydHR04D3veQ/6+/tDv9mzZw/e/va3o62tDStXrsRnPvMZOI7T1A1ISEhISEhItB7mLEnd/fffj8svvxwPP/wwNm7cCNu2ceGFF2Jqasr/zac//Wn8+te/xi233IL7778fBw4cwLvf/W7/e9d18fa3vx2WZeGhhx7Cj3/8Y9xwww340pe+1NwdSEhISEhISLQcKG2+qrSe58d33nln6O8bbrgBK1euxBNPPIGzzjoLY2Nj+OEPf4ibbroJ5557LgDgRz/6EU4++WQ8/PDDeMMb3oC77roLL7zwAu6++26sWrUKr33ta/HlL38Zn/vc53D11VejUCg0dSMSEhISEhISrYPpCHZzGS9RjI2NAQCWLl0KAHjiiSdg2zbOP/98/zcnnXQSjjrqKGzatAlveMMbsGnTJpx22mlYtWqV/5uLLroIH/3oR/H888/j9NNPj13HNE2Ypun/PT4+DgCwbRu2bU/nFuYd+P0stPtqFrI/4pB9EofskzBkf8Qh+ySM+dAftuOAUBpqQ9b2NG28EELwqU99Cm9605vwqle9CgDQ19eHQqGAxYsXh367atUq9PX1+b8RDRf+Pf8uCddddx2uueaa2Od33XUX2tramr2FeY2NGzce6ibMK8j+iEP2SRyyT8KQ/RGH7JMwDmV/bB5SMDmpoqenx/+sUqlkOrZp4+Xyyy/Hc889hz/84Q/NniIzrrrqKlx55ZX+3+Pj41i3bh0uvPBCdHV1zfr15xK2bWPjxo244IILYBjGoW7OIYfsjzhkn8Qh+yQM2R9xyD4JYz70B3mmF/ePbEd395v9z7hnpRGaMl6uuOIK3H777XjggQewdu1a//PVq1fDsiyMjo6G2Jf+/n6sXr3a/82jjz4aOh+PRuK/iaJYLKJYLMY+NwxjwQ7ChXxvzUD2RxyyT+KQfRKG7I84ZJ+EcSj7Q9U0QFFC18/allzRRpRSXHHFFfjlL3+Je+65B8cee2zo+zPOOAOGYeB3v/ud/9mWLVuwZ88ebNiwAQCwYcMGPPvssxgYGPB/s3HjRnR1deGUU07J0xwJCQkJCQmJFgUT7M5BtNHll1+Om266Cbfddhs6Ozt9jcqiRYtQLpexaNEiXHbZZbjyyiuxdOlSdHV14eMf/zg2bNiAN7zhDQCACy+8EKeccgr+5m/+Bl/5ylfQ19eHL37xi7j88ssT2RUJCQkJCQmJhYfmA6VzGi/f+973AADnnHNO6PMf/ehHuPTSSwEAX//616GqKt7znvfANE1cdNFF+O53v+v/VtM03H777fjoRz+KDRs2oL29HR/4wAdw7bXXNnkLEhISEhISEq2GOQuVzkLvlEolfOc738F3vvOd1N8cffTRIXWxhISEhISExOEFQgEyF+UBJCQkJCQkJCRmAqy2UXPHSuNFQkJCQkJCYs7RrOECSONFQkJCQkJC4hCAYo6qSktISEhISEhIzAQIRdPRRtJ4kZCQkJCQkJhzTCfaSBovEhISEhISEnMOQqmMNpKQkJCQkJBoHVBIt5GEhISEhIREK0GGSktISEhISEi0EggFmuVepPEiISEhISEhMeeQSeokJCQkJCQkWgqyPICEhISEhIRES0EKdiUkJCQkJCRaCtJtJCEhISEhIdFSYEnqpNtIQkJCQkJCokVAm3YaSeNFQkJCQkJC4hCAUEBRlKaOlcaLhISEhISExJyDUqBJ20UaLxISEhISEhJzD0IpVMm8SEhISEhISLQSmiRepPEiISEhISEhMfcghErNi4SEhISEhETrgEJqXiQkJCQkJCRaCIRS6TaSkJCQkJCQaB1QCinYlZCQkJCQkGgdUACqdBtJSEhISEhItAoolYJdCQkJCQkJiRZCs0UZAWm8SEhISEhISBwCEEpltJGEhISEhIRE64BpXqTbSEJCQkJCQqJFwMoDMO1LXkjjRWJe4J6X+g91EyQkJGYJn7nl6UPdBIn5CAqoqtKU9kUaLxLzAj/dtPtQN0FCQmKWMDhpHuomSMxD8MKMzeh2pfEiMS/gkGnIziUkJOY1XPl+SySAUkBTFOk2AoBN24fxYu/4oW7GvEHFcg51EzJBTm4SEgsX8v2WSAIFcxs1MzwWnPGybXAS+w5WD3Uz5gUopfi//9MavmbJvEhILFxI40UiCb5gtwnH0YIzXgih8kXxQChgOeRQNyMT5DOTkFi4INPJRiaxYEEpoEnBLoNLqHxRPBBK4bZIX7iENuX3lJCQmP+QmxOJJMjyAAIIlcwLBzPkDnUrsoHS1mmrhIREPsg5WSIJFICmNFcmYMEZL5J5CUBpc8l/DgUIldRyq+KnD8swd4n6aBUGWGJuQSiFpipNzf0Lz3iRzIsPQlvHkGultkqE8bsXZYJBifpwW0N6JzHHoBQyzwuH60r3AwehFKRFJg1K0TJtlQhDbhYkGoHIMSKRAMKNF8m8MOZlob8opuNiymycv4XQ1qFrJfPSurDltjqG3cNT2LR9+FA3Y97AkTuTlsCtm/fDdNw5vCJzG0nmBV6o9AJfBDdtH8YvntjX8HeUtk4ED5Wal5aFZF7i2DNSwXP7xw51M+YN5BBpDTzw8iAq5twZL5QCihTsMhwOmhdCKWp24wHGRLBz0KAZAJHRRqm49tcvHOom1IXtygcXhQwcCGOhz8kLBXPNgHPBrnQbgQnDFtqkMRlxERECmBmSz7XSBEpaiCWaa2wfnDzUTagLuTDF0UppCuYCcoy0BuZaahDUNsp/7IIzXhZinpcrb34q9DehNJNfspVyp9AWYonmGvN5PNMF+L7NBJwW2jjMBeQYaQ2wTeRcXg9QZLQRw0Lc8VQjLiJCgZrdmHkhtHVU/gvR6JwpzGdBrMzPkwyXLPzAgTxY6DrEhQJK59bQpKDQ1ObykS1M42WBTRpORFNAMzIvrRTBQ9E6CfXmGvO5aOVc79RaBQtxEzUdLLQ5eaFirtcMmedFgLsAo42iYYYUgJmJeWmdCbSV2jrXmM/GSyvpquYSC3Eemg7m8xiWCDDXucEopVDnqjDjAw88gHe84x1Ys2YNFEXBrbfeGvr+0ksvhaIoof/e9ra3hX4zMjKC9773vejq6sLixYtx2WWXYXJyZkSJCzHaKBrNwTQvjUdYS5UHWIBC65mCM4/dRjLEPRmOLDQagmReWgNz7QZmtY3mKNpoamoKr3nNa/Cd73wn9Tdve9vb0Nvb6//33//936Hv3/ve9+L555/Hxo0bcfvtt+OBBx7Ahz/84dyNTwJZiG6jiCnMNC8LzG3UQm2da0TdhvMJrnQbJYJIRioEyUK1BiidW8aQUDSdpE7Pe8DFF1+Miy++uO5visUiVq9enfjdiy++iDvvvBOPPfYYXve61wEAvvWtb6G7uxtf/epXsWbNmtgxpmnCNE3/7/HxcQCAbduwbTv0W9t1YTtu7PNWAW+32H7HIaG/bdtBzXYa3qNl23Bc2hJ94VIKK+l5JvTH4QbbjT7/+dMnlmXDJYd+jM2nPgEA03YO6Tw0n/qDR6Qd6rbMpz6ZD0hca1wCy4rPw7MF4hJAUby5X4u1px5yGy9ZcN9992HlypVYsmQJzj33XPzTP/0Tli1bBgDYtGkTFi9e7BsuAHD++edDVVU88sgjeNe73hU733XXXYdrrrkm9vldd92Ftra20Gd79qqYHAB6altm+K7mFhs3bvT/fXBcQ09Pj//35kEFBwaU0GdJ6K8Ck5Naw9/NB1SrGu655z6sKCd/L/bH4YbxieRnOB/6ZMoGJqfmzxibD30CAE/3KRgxFfT0bDuk7ZgP/UEo4LpyjMxXiP3RP6Divgf68HJbnQNmEPt7VRRU4J7f7cXiIvusUqlkOnbGjZe3ve1tePe7341jjz0W27dvxxe+8AVcfPHF2LRpEzRNQ19fH1auXBluhK5j6dKl6OvrSzznVVddhSuvvNL/e3x8HOvWrcOFF16Irq6u0G9/d8uzOHJJCd3nnzDTtzYnsG0bGzduxAUXXADDMAAAX9vyB3R3v9n/jbn5AJ57bC+6u9fXPdfWgUncuOep0LHzFV9+9j6cdfaZOHZ5e+jzpP443PCVFx9Ad/dZ/t/zqU9Gpix8d9vDofYdCsynPgGAoYf34MBoFd1ve+Uhuf586g/bJfjsY79Dd/dFh7Yd86hP5gOS+uOWwSfw5jefiJNWd85JG+4YfxqdJR1vfetxOGJRCUDgWWmEGTdeLrnkEv/fp512Gl796lfjuOOOw3333YfzzjuvqXMWi0UUi8XY54ZhxAYhAQBFbfnBKd6bQ2jofhRVhenQhveoaTqod65WgKrpqW1NetaHC1yS/AznQ5+oGgGFcsjbwTEf+gQAKBRQHPp5aD70B1UIKJ0/89B86JP5hHB/KFBUbQ77R4GuaVC14JpZrz3rodKveMUrsHz5cmzbxujT1atXY2BgIPQbx3EwMjKSqpPJA7IAq0onhkovsDwvpIUio+YSlNJ5HWbaSsU/5xIyhDxAK81DhzvmOm9TkKQu/7Gzbrzs27cPw8PDOOKIIwAAGzZswOjoKJ544gn/N/fccw8IIVi/vr4bJAtcsvBCpROT1GXN89IifSHzvCQjGrp49wv96B2rNXWumx/bM+Pl7lup+OdcwpVGnQ9K0VQ0SatgYKK593E+ghyCaCNVUZo6NrfxMjk5iaeeegpPPfUUAGDnzp146qmnsGfPHkxOTuIzn/kMHn74YezatQu/+93v8Kd/+qc4/vjjcdFFzN958skn421vexv+7u/+Do8++igefPBBXHHFFbjkkksSI43ywiULLywvmh6e0GyFGVupXpAMLU1GdNf67P4x9DVpvPxh2zCq1swaL67cVSfCdWWSOo6FnIW5arm4+lfPH+pmzBj4ZumhbUO46/lkDepMws+wOxfMy+OPP47TTz8dp59+OgDgyiuvxOmnn44vfelL0DQNzzzzDP7kT/4EJ554Ii677DKcccYZ+P3vfx/SrNx444046aSTcN5556G7uxtvfvOb8YMf/CB/6xOwEF+UqNuAUApzweV5kcXbRNguwfCkGav5NB03kktILOHhdEFkGvxEOLJffPBuWIhMlEPIvM7DlBfUY+v7J2rY+EL/XFzRKw+Qvw9zC3bPOeecuoPwt7/9bcNzLF26FDfddFPeS2fCQnQb8XpNqsrotazMSytR+gvR6JwOXuwdxz0vDeD/nH1cyPXnUhrTQGWFS5o/Ng1EukcSsRBrrDULvoEiFNCa8xDMWxCysDZdfM1wCfDIzpE5uaaqzFPNy1xjrn12cwFKw64wSimgNE657bZQinIKmWZeBF/8ologQpuvE+MSOuO7RFlVOhnSnRaAevZyq8xFeeAQsqDWG870EkIxUbPRO1bNfY6q5WY23CkFFKW5OWTBGS+Ou/B2PBRhNokQirKhwWpQ82auUz1PB63k4poL8B0QiRiuZBoGiENmPnJJVk9OhuyXANwlsBD7Y6Ex/Xwz4lKKDcctw6NNsC//+fsdeKE3W64WAFBkVWmGhViYMbq7pQDKhtawvhGhrVMQrZVcXHMBXuuJ+6A5ohqYPGDMy8y6jeYqVHrSdPx/bxuYxN6RbFk4DxUW4iaqWfBuWIibE5fOPJt5KMHnHZdQnLiqEzsGp3Kfw3FJw421CAXSbQSgtdiGrIguWIQC5YLWUPfSSjoSWZgxDL5zjxquhMajz/Kcc6YFu3NVmPHTNz/l//vxXSN4cs/B2b/oNCCZxAALuR+cBRZVxtcaSikMTW1qY5KbQFCAZoLpF5zxojQZdjVfQb3FQdRZUkpRMrSGuV5aaQJtJZZoLsCT9lFP88InkenQ1M4sUNyEzM3iJLKMLqUhJmY+wiFEMokeAsHuwuuQ6TCh8xGEBJGfhqY0NYZJzshRBXMUKj3foatK7sH0jbtfnqXWTB/8oYZ33xRlQ22YcKyl8rzIJHUhcCYqoNyDz5vVrRBCYc9CtNFcPDdLYBkJBSZr89t4ccnC2pFPC/7YPbTNmA3Mho7sUIIbYy4FdFVtyuAkOSPtVKW5dWrBGS+aquSeNJ7cMzo7jZkB8METEm16bqPaAmJeKF2Y0QjNIuoyEsdBs5OlMyvRRnMzxkRXGSEUU/OceWmlSL/ZxoLWvBAKd4Y3BIcSlAaZ2Q1dbcoAJznmKEVh/zWT52XBGS+KouR2P1gznDJ9JuG/+BHRZtnQGjIvrVJfhfoL9CFuyDyC6zMvgbsI8EKlmzRAZkOwy1xaM3rKRIhaHZdQTJrz950FvCR1C2dNmxb4GF6IrzczXg51K2YOfM5xKYWhNufOyZvlXrqNPKhK/qRBMy1inEkkMS+UAuWC3lCw2ypuo4W8M2sWXGwddRuSaez0XEJhz0qo9BwzL5Ri0rRn/ZrTgXQbBfCNlwW0yHMsNOaFu4FdQqFralM6REIp3BxrqiKT1DFoipJ7Mm02emMuwG8lmiI+i+alVdxGSQbaQsPzB8Zy/T7QvIRZKUKbN0BmY6KdqygxK2K8TLUA8yLdRgy8G5pxDcx3uAtM88LFusQT7DbrNsp6HKVeqLR0GzErLi+sDKn2DxWCHbf4GVAysmheWkNL4u/M5nk7p4N/++2WXL93SVgMy41XdxrpyJ1ZqG00V8nYxA2GSzDtaKMn9xzEDQ/unG6zUpFW8+kHD2xvKmtpKyNgDw9tO2YDsxHBdygRchtpapNuo3yC3WYjhBec8cKQz4LJk1BnrpEs2M2meQmMgtlr30zAn9zm72OYNvLqVJjqX9ADkcDAa1bzMh29TL1zArNveNoOFbRR0w+Vrlkuqg2M/+kgbTfeO1ab95FSM42FvDlZqBl2CaHQ1fxeDH6OPGyUdBtNA/PZbRTdefPPyoXGeV5oguEzH7GQ80Bw5DWQeY6XmOZlWtFGZFYKMwKzbyC7ERZqutFGs117iFIKNWEPVU8Ls21gYkEu8PyOFtAa72PhGS9MaM6Zl2bujddkywoFzVWVXoDGC/Og5YHtzN/BRxMWduozL43dRtFj5yMWMq3MkddA9ndAEQPUpWg6Ysh1ZydUWvzf2QIhQUVsFm00PeMlbyKtmUI9N8M/97w071nSZrDQmZcFp3nxWF+96SR1+eYZybz4yN8L89ttxP43zLxQrzzAwnAbLeTJjSOv8SKWBwACl9p0Mno6ggEwUxBDuGcTfEcIIFbvqanzHaIds+umh1Db7sKqUMzB3+s8d/b03lHc81L/7DRoBuHOwFicT+D11Cil0NVplAfIxbw0F0a/AI2X/LBbQLAbdRtlEewGC8v8frl8A22et3M6yMvucdYlymyQaYQ7EzrztY2ibq3ZguhucSmFmuSTyXm+Q2EsO3XcRpZD5v272gyaYYD7x2vYPTy/i28CgEvIIWVearaLr+YMBqgHrrULygPkvzdKs5d6URRAVZWm3sXD3nihlM5z5iXJbQS0ZWBeKIUnuprVJk4brAjY/G/ndOAQkmuHxqLEwjWNgBlgXmY8Sd3csHuEws8d4RJmvDca//XPd2jysLiEpD4/2yULUrTuh0rn6G5CacPN2XyA4x5azYvpEOwczl/5OQ3cXR1oXvKfoxlXWjNduECNl+y7svmehZY3LZrnpaRnK8yoNVHraa5BKCvrsJDdRoTmY5YC5iX4G2AL97Q0L7OQpA6YA82LYGwQStFV0qcVtcN3mHMNp858Yy+wCsUczeiiHEKnZZzOFZiA/tAZWXnrCDWCn1+KUOhac3Ny3vxiiqwqLSLfSzKf1/akF59QNrAaLUTEY17mu1FAPP/qfDYip4u8UQmB5iWsKZlOYUYtw5jJi7kShYv95xKKRWUjV6K6aHQSz6Mz16g3Dmx3fruNrvrfZ5o6rhl2ziUtwryQQ1sGYqarWhPP5cOZl+ZCpbMLdimV5QGaxnwPdQsEu+HPsgwszrzM49sDILRz/s9VTSMvw0dpUCKAHw9ML1RaV5XZcxvN6FnjoDTcB11lI1fE0advfir0tzvDk35W1GNeLCefa3Guse9gtak+a9Zt1ArMizsLIvhc18/JcjQCYzjZemNoKpqRyOWd61hhxvw47I0XvhDMV3aCCBO2/xllCYQaTSR0GtbznMLX5szzdk4DeXdIXPUfZd5cmi8BlAhdVWdcsEsoy2cy23VrxAgGQii6SvmMl6odXgjpITJe3Do7dcsl83qj4bi0qZxYvvGSY4lyCVqCefEZ0kP04Mg0Mm4nn4/60XzTSVKXp00KZKh0U+CDbr6yL340R0jzAhh6FuYFHvMyP++No1XaOR2Iob5ZwJmBaDQPy7DbzALCXY0zHyqtz4GB7JKg2JtLKbrKeq5EddFFdz5GG9luuph3PsBtkvWLuj4zXYuQlmBeeH8cKq2S6zElMwVFUfzIPlYeoInnnVOwqzZRjxBYYMZLMx3NO3m+zhm+6DbCvBiq2tCvSDjzMs83MJxJmq/PYCaQt0w8z/ESDZUX3Sd5QChQ0NUZ17wEEW2z9/CimaJdgtzMS5Rxmouqz0mnd+tEndnu/A4eIIQ2lVaiGcGuS9AwCed8ACEUBb25TLQzdf2ZZH1UJdC96FpzwR5c8JsVMkkdWKcrioK80Ubs2Pk5aSS5iChl2Q8bTb6E0JZgNAil0JrMKdAqyOs24omifFbKm8c1VWnK9eMQgpKuzXiGXZfMvuEpCnUBz22UU/MSZV4oDevI5gr1QmvteZ7nxaUUdhM7IX5HuQS7lMK0W4N5KTaZRn8mMNOCXb5euN4GuZlTN+PaPuzLA7iEQlPy5evjNPp8nTSSxLmMUVEaWrc82mi+3hsH270396K0CvKK2HhV4oCVYsdm0Tolnw8oGuqsCHZnO8w9EK0HG41FZSNXqHSMecm5O2wGSRXu6zE+1jx3GxHSXJJDP8NuzvHfEswLpey9OkTPbaYZREVR/Lmn2VBpUavX+Hoe4SCZFzaR5kF0VzffwLUK0WgjTW2sBA8Wltlt43QxFwvgoUbedPQuDUS7esRtmLQoNoJDCIq62nR23jRQbyzO5usTdZ25lGJxm4Gxqp35HEmal0OhU3Dq0Py2S+b1u+rSZt1GzB2R59YcQlFrBebFpSho6owYwi8cGM99TF4XTSNoiuIb9nnXUo68EbyyPABYp+VNGz7fNS8UjJWIJqnT1YzMSwtEG/m6ifn6EGYAeUNzucvIf4besc0YLgB7N0qGNuPMi0ubTyOe+RoR1y4hFMs7ijhYsTKfI+42OjT6kjSjyfEijeZqE7VtYBIP7xjOdYxL0JTguxn3daswL66neZkJ5uVf7nypievPrFiYa15cQqE2OdnkdWWxax7ubiNvUc91jC+EnJ8LJ0lYHAjNJhLzd+3z3CgIRMmHuiWzh7xZJznrQilmpHSCS1hW5plPUjf7uip+7iCyA1jWXshnvDhx5uVQGMtpVaVtIZJqLvD8gbHcO32XEFg5a3QBbAOmKvkYYJe2BvPiRubiTduHYTVpdFUtJ/c6NNPMC3cbuU14Mfw25QjfppRdUwp2m7AWHb9eyvxcOYlXmjxamFFXs2TYbZUkda2RCTgK2yX4n8f3Zvpt3nwMXO8yUyUeXOL55mc6zwvhIZUzetrINdj/igxMe1FvWB5DhBXTvOCQGMsuSRbl8vpqc/UODE1aucdUswnZmjFw3RZiXoq65vfLLzfvw2gOo1qE04SmaCbdn5RSqGqwcWq29mnekHqZpA7s4WsqkCfaqJkcBHMJHhYdT1KnotEjnw2jYM9wBWOV7FqDJPBIGvHvVoiKiqJqu7h/y2Cm3+bNhMmTmUVLJzTbRQ6hKOrqjOd54dFQs2q8RDQvTW1SSILb6JAxL/HPuVtrriKghifN3JFDhMbdb1lAmxgjbotoXlzvveJd6ZBsVd8HJ0z0jlVDnxEK1HLmtpnJGl2UAoaq+saQMg23Ua4Mu2jOaF9QxksgMsreEY6wm5uP4C9+aJdEASXDk2MJxGaWebnz+V48d2BsWue4b8sg/vfJ/f7fzMhqvWgjkmMn6qYsWmngmozAbTR95qVkaDOeYTcIlZ5FzUtUsEvy7wqjjNOhKguS5q7iRsFczUPDk5af9C8rXEKbchs1EzjgEgolxyb0UMHxNS/c+KSZ+vXhHcP4/dah0GeE0FxsIr/eTBnhMxXgkTc4AYoimReX5t+RufM+VJplMA27jWim13o2ygO4M5COumq7IUp4LnQTswGXZCtA1kwW59lwGzWbMbMeCOUG8ixqXqKCXcEfn/V+rGi00SES7DopiehsZ27d18NTZm79U7NuI0pZFEueXB7NRI4eCriEhDQvWfvITKhjRZrQ+RA6czopHhwwE2Mw6zkUhQl2D/tQabeJ8K55r3lJFOwik5HGKf2ZrTo6fR9rNEU6XwBbzHbxknZlMF5oePHNAiJGG81AxW2H5BezZ0Hg1prxUwvXYP8rLraKoqBc0GI1i9LguCTiqjw0G5Y0jYI1x8zLYBOaF0Kbq23UjPbOIUx/Md91cC4BCloQbZSV0TMdNzYOCEXukggzKdiN5pQCmnNT511zFMjyACAk26IuQky7Ph/BdSvhPC/ZGCY+GGfy3maCpnRJfCFphaioKNhE1Xgyj7o9soAliqIBszFNv3Yzhn0WBJqX2XUbqQpi425JWwEjU43FkTzsXOz/2XQbsXYm93VanhceoTJXr8BYxcqteXGbEJQCges7b6h02dBijNlcYNJ0MhtpUebFIdnEqjU7zrxQSnMXo5xZwS68uYZOa82IlrNpBFkeAM2FSvMd6XxdOCmNF75j4WWNjyVNTBqNkPXlrAfbDU/gzUxu8wFZJ3M/WiYX88L+S0pS1wxmy3jh551V5sVzeUXf0SXtBYxmEI/zw8TD2aQ/k60Uzl1nHnJJchZd2yUoGXOXZl5VlNyal2aZF4rmNC9tBf2QRBzd9MhuPLpzJNNvmRBeC7uNMvSr6bixZ80irHIyLzNohCfVmGtGs5ufeZHRRsIEna+2USFDheZDBULjgs2szAuNRKrMSHtmhHkJLxytEtIdRdbwZ2545Ok3Hq7IQuVnJkndbBgvNMGtOdPgeY2iRvOSNiNTrpekEiCzGW1Ur6+dFKOJGS/anLhJKpaDzpKeexPCQnmbSVKXn51zKUV7UTskEUe2SzNnb+aFGUW3USbNi01i44DQ/IJdQvPNK/XPxdYLl1J/npkTt5Eio42EDLvZO8IhXNQ6e+3iuPuFfozX8oUZ+wOKRI2XjMfOcLSRO0OaFxoxxnR15sWksw2X0kwZa5spQcEFpRSYEcPOIWSWNC+sPMBsPjqXJAvPs7qN+FoiHj+bgt16xgtNWWwsl5VvmAvmZXjSwqquUlN5XppxGxFKPcFuvmuVjXy5fKaDf/ttkN2WEIrxjMYLT0EghvNn07wkuY3yh0rPxHzMQWjz9YxEaGr2cUwp07xI5oXwwozZLbm0iXE2cN/LAxiaMHMdwwW74fIA+QS7M2kUzARN6bokwiS1qtuIZHQbeRNbjvtji5zw/KfZN4TmL52RBS6hMGY9wy5jH2PMS0a3kc98hdxGsyfSryeOVpXkcWC7LJR9LjLsDk2aWL2olJt5Ic0yLxRQc5b/cAljXvK6UZrF03uD9A8upZk3mYR6+ZNcrnkhmfo1WbDbBPNCZjLPS1xC0ZTbSMn3bknmBcEErSrZaSuXUBRmmfbmsJooec/ErNEkdRk1L4QluJvJSdoh09+xsnMEf/u1mlrLdsm8AEaTrGUBF+z6rj/v2Ga73nFnJ9qIJxiczdeHGXDx4ndL2oxMzEsS85U3kVYe1GNe0ih12yEo6VqoHymlmMjJ1GbBkMe85K1zxZjGZvosP/NCKNO85BWwNgvRPcWYl2wVyx2XxkKlszIv0d+ROszLS33JpRzcGZiPxevPRJFVVcm3nsryAAiYlzxqZyeiFp8OfvbwbgzWYVYsJ5tVLoK7fsLzDM2U/ZBQCm2m3UYZBWn1EK3vwunKVivM6BKaKWKjqWgjysN5MSNJ4NiCOvOvu0tnn7kklFXujQl22wqZUrEHEYXCmJtBoWPS9ZKMF2boJVcgtl2CYkSwu2ekgq/+dsuMt2940sSKzmLu+9cUZXrMSx7NC6FoK2hzJtgVjYY8zAvPsCsmqcvEvNhx48Ul6czLp37+VCI7kbfgaz34aTkanG/vSAVVa+YYMSnYBbxiUuxFyfqeBMm7pn/9bQOTGKumT6aWS3Iv/Iwyb25x4AvfjLqNZmDH6pKFUR6AZNyJJmkuspxbUUTjdZp9Tim0Wcj5NRcuP/6ORvsga56XJOaFaQVmtp3i9ZKMF87ypuV5Kelht9FEzZmVUOGK5WJR2ci9kTJ0tan28CiWPCuUQyjaCxrMORLsigyPS5BZ88ILM4rsahZGKynaiIVKJ99v/3gNvWO12OczKTzPmiz05sf2pjJBeaEoMlQaANtNqaoCLYfbiKd3ngnrlYUSpp+nGbcRf/Gbad9sRPG4M+BjZVlGg7+DBXB6551rpFUIjsL1dUvZzx0ktktOUpf3ZXcIhabN/OtOyMyLwuPXAAw9vugbajwCKfH4BM0LiRjQM4k0cTSfa9LyvBSNsGh90nSaSsefpX0lQ8s9pxS05gp7NvN+E0LRVpybUOmo0UBo9mgjh9BQv+TK8xLTvCD1fh1C8ez+eFkWl8xchl3qbZQbPeKKFTe8RNRzCvzH77bGDDRWmPEw17y4nlAuTRSXdsxM0d5uA0Gb2YTbiOd5acZ44YNxZssDNK9uf3bfGGyXwInkupiNkO65QKPnzZGWp6TuMZSFw9OIAcrSaedX57uzpHnxI0lm2W2U1H+apmRaTPk7F45wmz3BbhD1GP+8oKupgl2WLyT4bCpHsrQ8sF2Kkq7mOjcPCW6uMKOni8oxal0KtBfmJlQ6uglxCcV4LZvmhRCKohHO85I5w26UeUF6krqOoo7nkoyXGXYbZcmwW7WdDOtY8lxzz0sDsWeqHo6al8d3hRMJuYRN+HmU7dxyFh/YwEQNW/omcrenEfOSJNKK4pebD2C7wMgR0nxhPr8uzgwbL83SlDc9uhsDE2ZCqPTsVyaeDRCabZflC05zuY0Cd0zUbcSS1uVrq0OCSLyZhEsw68yLm2K8ZGUkk6K9xFwWIrYPTk57weSbKCA8D/nMS0KTeZI6cYxMms6MVwEHGPOZl3nhIcFNZ9hV8o0RlxCU5yhJne2SmPEyZWYU7HLmheRjXkyHxOblop4eXXXCqs7ENYkL+2cChGbLsNuIeWFI/n738FRi/xx25QFuf6Y39LfrLdZ53EYkYUJ5sXcCv986mLs9jfydVgbjZbRqo+oEs2pSnpesSfiC8gAzaLxkXLATj/X6hynkg8/norjfbCCrfztNs1EPhLBcPpQy94jYN80YC7NV6C6obTR7z46mCHZ1NZuAlB8XdRslGXM3P7YXu4cr02ovF0draiS3DN8oJTw8nqRO/G423UZ6TgEUobwqeXOaF1XNt0C5nuZlLpgXO1IsM+97agiaFyYEb64wY1FXU5mXgpY81slMMi8k/i4nGfgVy627BqQ95vGajYMVO9beLMEnSWhp4yX6MLlQLl+0UTyPiu2QpoRpLkHdh5rFeHEIgRNa2NliFb4f/u/6D93fvc/g5mU6GXZdwiYKx00ozDiPSzSkIWtkAYuWyVnbhbKIMkKZe0QMlW6Wecm7YGXBXIRKux77GHMbZRQKJ2U4Tst747jN5TIJnYN4gQMRtsEhJNWItXh5AJF5qc2e28jQ1Fw5PHhUTXNuI6bbyuPrdAkTZB8S5iWnoa+rSkjzkoWdMm03poErGmrdvDZpInBCZ6aAJaU8lB91M+xWLCeTgRbFHm9TIM6ZlHrRRoeb2yj6InGdQL5oIxKj9B1C/BL1eUAprWv0mE59ixVg2gTxffVzoCQeV/9cXGuRNsFTSjPX8OCIVoTOA14bxSFhsRrFzOQXmGtkNV5cwiI18oZK88XZiBgrehMZoV1CchctzXReT4w8G5qXiuXgf5/cFzBXkWtk3bEFzIu4u05O9Jg1yVij62mqGst3UU/zYjkERV0LPdepWXIb2S7JXbDV9ZmX5tzXSaHShNA6eXpYYca8zMs1v34eA+PxqJx6iBovxDPUrIyGk5i7J6vmBYgzUSVdS2ReeKHPpOeVJEZvFlnZ2YrlNiXc3j1cQVdJj9XUmjPB7gMPPIB3vOMdWLNmDRRFwa233hr6nlKKL33pSzjiiCNQLpdx/vnnY+vWraHfjIyM4L3vfS+6urqwePFiXHbZZZicnMzd+Chl73o1NPJGGxl6OFTabnL31SiJk+XGqcKk9oTr/sAT7OZujiDASv7edil+8MCO3OdsliHhOWKciE+VzoHoczaQpzxAM24j3id6xNWgNcG8uAS+YHdmQ+ezG55fvPXZXIvR0ISFTduHWf2kaUQEJrqNaLLbyMnoCmx0PV1VYgu243qp5FPdRmrEbeQ2tYlqBMdlG7Y8IKR5txHTvMR31zuGpvDte7alHlcy8jMvU6aTuwSL7YTd2C6hWNJWyJQgUFGYnocbpFmN36REqux+4+9H/UKfSHSpNoOksjNJ+4NqJs1LHLtHpnDcyo6YQT5ngt2pqSm85jWvwXe+853E77/yla/gP/7jP3D99dfjkUceQXt7Oy666CLUaoE1/N73vhfPP/88Nm7ciNtvvx0PPPAAPvzhD+duvBWZwXmSOjVHemLXpShGHr5DSHPGSwbNS0PmhdCI2yiuAM8KcfeeBNNxc583z84idixlSd3cSFVp4os+W8x48UK+GxmkzQl2eZ6XeJK6KBOTqa2EQFMV6GpzosvUdpLshRmHJixUciS3qtiOH902nQk6Kc8L12FE4bjTZ14cz30dnYcaRRuVdC0i2LVnh3lpwoXoEoqSoTZl2KXlD7EcUjdPT9FQczMvtksxZeY7xkpwGy1uK2QKl6aeWzcozAi4GfooLgUACrqaaKxxOUSSIeEnlpuBuZPQbGVnGmle0rBnuIJXLO+Ia17QHHOk5z3g4osvxsUXX5z4HaUU3/jGN/DFL34Rf/qnfwoA+MlPfoJVq1bh1ltvxSWXXIIXX3wRd955Jx577DG87nWvAwB861vfQnd3N7761a9izZo1mduS5DbSEnY8HI/sGMapRy5CRzG47aAwY/B7263v/kkDoRR2Q81L/fNG86hMR8zayPAxm8g7M52aMK4bMC9RzUsr5nkJdlsUhTp0K9e85MvzEqTZjmq4mukrvqDORMK7cDuzJxh0SP3FKoqK5cL2fPpJmpes4MeJjBOPTIy3cfoZpHmfRCNseGRK0jiwHIJiR9hAmzJdtBdzT9EN0Qzz4lJmXDWjQaFIDu+3XVI3CV1By+66Ec85ZWWLFBKPCc1HhGJFZyFzuLSuKr7B4uZgXqKbHjWlxo+Y9JDScHZ1Mk1WUkT03GnIFm0Ux+CEiZOP6AptnoIkdfnPN6Nvxs6dO9HX14fzzz/f/2zRokVYv349Nm3ahEsuuQSbNm3C4sWLfcMFAM4//3yoqopHHnkE73rXu2LnNU0Tphmk3R8fZ7HEjkNg24F1bFo2EwBRCtOyQ98BQM+zB9BVVHH8yg7/M8txoKuAZTv+72uWDVP4Oyscl6Bmxq8bXIuErpP8GxcOhf8bx3GhgsJ2XP8zQihs2/b/Nw3shaKwU65ZqVlwXJLrPm3XDbUlDxzXRc2yYDkOHFf1z2E7DlRQuG78vP5vmrjebMOy2eRWNU0oNP1VMi0bmqrAcrKPKdclUBT23FVQ2LYLy7JAKWV9RfP1iW07ACVQvfbqipH52LrndQkUSmFnuDfbIZismLDbs0074xUTtuPCsm1oCvxxJ457/u9648T0PrOE3zkugZLwe9thY3Q64820bCiUgILCsmzYOv/c8sSd8XFu2g4MFaF+rFpsbmqmLfX6w7JdgLigtP78IaJm2jA0YLyaf160HQdKwjxUNS1UrOTzEUKhUAIz51xj2i4bNwnHpPVJ1bRCY8p2CRaVdIxMVmHb7XWvRygBCIHFxyalmdYOVYF/jH8uzyCIjQ3LhgIKBUDNtKALhqdlOzBUBaZloaDmMwCi/WHZ3rilBNSbX5LWmKrlwLTT1zlKqX+8CEIJVITXZkLYvC++E1mf94waL319fQCAVatWhT5ftWqV/11fXx9WrlwZboSuY+nSpf5vorjuuutwzTXXxD4fGBpBT0+P//eTg4yq3Tul4N6p7XixLfz7bTtU3De1Ay8L4/Hl3SocCjw2tgvV7ezhP92rYH9FQU/Prkz3zdHbq+LJWi+KvU8lfl+1NTz+5GbQPemDbPsuFe06sHHjRgDA5kEFFQfoFdozMKCip6fH/9807NuvojSxDwUVUPdtjn0/UAUGBuufI4r+fhXG1AB6rJczH8PR26/ioYf7sG9AwagO9PQwvc1TwwrGLWDPpIKenr2Jx/L+mE/YPKRAgYqeO+9CW503aecEMD6q4tlnh9Ez9Gymc+8/oKLmAs89N4iKtwH8zdRLGBxQoU4CK5bn65NnehUMlIG+IQV3/HYvOmbGdsG+vSqcYYrJ/UBlW/3Js3dAxd339WFt/fXAx7MjCvYPKHjUOYD9YwoGVaDHejk07qPvQFKf7BgHNEXD/Q/8Htu8ax/oVWETxMb+3v0qHjb3Y6rBvdTDllEFfVXgwJSCuzbu8ft63xR7B9h1d4fbuEsFHWayxfb+Z/x7A+JtzIOk/tizT8U9d+9Ff4P5Q8SICRzYr+Kglb89z/YpGBhX8MSTvXB3B/26dUzBngMKenr2x44ZGFDxwH292L5f9eeJLNjfq+KhR3th7kh/ftE+2TkBuETz72v/ARUdUxRDu4CJl+uPg4EBFY8+2sfmrtHn4doaXnjxJfRMvJh6DKHA+KiGvZUR9PTsCZ0LiPfvlA30HlBhuUDPHQegC6TZcwcUOJaKO3+7Ee1NvtO8P/ZPAduHVfR7mQKS1hhKgYqlYfNTz6DU+3Ti+dLuY2BAxfZKP7TBLdjTGXz25JN9qDhAWx87X6WSLVXBzHOSs4CrrroKV155pf/3+Pg41q1bh/auRejuPtf/3Nx8ACVDRenABN7ymiNwwqqO0Hn+cOvzeOP6dTjliC7/s2fu3AJNVfDatYtxwSnMqOp/aDfcA+Po7j4tVztvHXkSJ5+4At2vXxf7jhCKT27aiNNe/Rp0vzbdNfbYr1/A4IE9uOCC82EYBszNB1CxXaj7x9HdfSoA4LaRzejuPt3/3zTc9T/P4PTjl0FXlcRrvtw/gd+NvYTu7jMz3+PNA4/j2CO60H3RiZmP4fjfoSfx2j9aix2bD2BZewHd3acAAJTn+jBSsWHuOoju7leHjrFtGxs3bsQFF1wAw5ihFXeG4Dzdi+Ku53HueW/F0vZC6u8e23UQj9d24KQTl6N7w9GZzv2bsadQtVyc/MoVqFouTMfFhWe9AneMP4PjlreBjG7L1Sd9D+7CKUd0YfjZXpxz7vFY2VnMdFwj3H3LMzh1TReOWdqG805eWfe3N/Y+hjPXn4DTj1qc6dzO073Y/mwv/uiMtSC7D0JRFHRfdGJo3PN/1xsnj+4aQXHrZrzxTRtw6hr27v/64GbYhKK7+49Cv7199Cm89jVH4KJTwxuwPOjYOoQ9IxXovRM497zjsbyD9fWz+8cw+HQvRit2bG655xfP4vUnLsdEzfHnj9tG2IYj+o4/tH0YyzsKOHFVZ2ob6vVHz9hT6L741bhj7KnY/adhz0gFOzftgXGwWnfOScLII3tg7hnD6SevwMWvWu1//vutQ3jiD7vQ3f262DG3jWzGRReeimfv2urPe1lwy+ATOPGUVeh+3drYd2l98sjOEdDnHsfFF18MRVHwm7Gn8JZXH4GDFRvdZ8bPE23nm994LB7bdRDdZx2Lf37ufhx3wlp0v/W41GOqlotbR55GV0kPzXe/OrgZlMaf9/Ckic13b0PFdHH+haegrRAs2wf+sAtPTuzFueevx7I6c1ASov3xQu84Ki8MwOllyfC6u0/HrSNPhsZI1XJRfvI+nPKqE9F9ZvI696uDTyXex60jT+Lko5bgdUcvxhlHLwGlFLeNPIXXnXEkDlYsdJ/B+pp7VhphRo2X1avZwOzv78cRRxzhf97f34/Xvva1/m8GBgZCxzmOg5GREf/4KIrFIorF+GTrUBp+MVUVBUOHoWtQNC320roEUFUdO4Zr2DNSwQWnrAKFiqKhQdVU//cEChyK3IslhQICJfG4mu0yv6Wi1j0vBdNGGIYBwzCgqCpKBiMN+XGqyv6tqgp0Xa/jp1RQKrACbEnXZA6J5Pamto8qqcfsGprCuqVtqeF2BAAUFYSG+0HVNBR0CijpbeH9MZ+gqCoKmgpFjY+18O80FHUNSoNnHzkKmqZCVVUUDQWWS6HpOgxNQ0HX4NKcfaKoKBYMFHQdaNDeXFBUFA0dasL7FgWhgEOzjzfTBVyqsHegoKNmE3/cR98FjqQ+URSNRf+IbVQU6Gq8LYQCNNdzikPx5iFN06BpenAuVUOpYIBWndj5HQK0lwqYskjo3vg9idg2VIVDFZy6tnEbk/rDpQraigWoOe5T1di8Gu3vTMeqGnQ9/p4QMIFq0vlUVUG5WPDHeRIIYdWfF7cFi7ZDKGpO8nzHEe0Tqqj+PeoamxOXd5Wxb8xseK+KoqBYMPw5kbl06vfRlE3RUTRAEb43RWGi3Nj41VwYugbdpew5iMeoKgq6lun9SwPvD03ToXvPmHr9Hh0j4yZBZ0lPXcdsl/jlbKLfayqbK/j8w2oRqjB0HYrq+r/PPCabutsUHHvssVi9ejV+97vf+Z+Nj4/jkUcewYYNGwAAGzZswOjoKJ544gn/N/fccw8IIVi/fn2u60WV78QT4aVFG1lejpH+8Rp2DU0BCPK8iKdy3OlEG6WLY9sKjVNyO5FoI0p5Xo/4cYpSX7jZSEzZnGA3Pc/L9fdvx76D6ZQfL5/gEBIrD5A378R8gEtYXZNGAj1Km6ltFCQ544JdHoFkNJHnhQt2NVWJ5VmYDhqF44uwCUWtThKuKHgyLJakbhrRRn60V/jzJJufpXefZpI6N7nGmh9tlDI3FTMKL7NELdYHy7uSN0lds8kI/fpXkc9tl6CaklEWYILdevPwjqFJfPe+7aHPHJfmimjj7QCCZ0UpxeI2I3NlaR4qzRM2Nno2pkNQLoQjy9h8mBYOzfpPzCcjfmdo6owkIuV50kREx0jFctFVMlLXuaRzAIEgV7wHiulVlc7NvExOTmLbtiA2f+fOnXjqqaewdOlSHHXUUfjUpz6Ff/qnf8IJJ5yAY489Fv/wD/+ANWvW4J3vfCcA4OSTT8bb3vY2/N3f/R2uv/562LaNK664ApdcckmuSCMAsQ7kmRHToo1sl/h5Svj3Qb2R4PeWmy1LYhSUAnbKKDIdF22FxgtdUrRRNJSbg+ezSWU6aP3yAKzKdd3mxNtH0zPs1mwXE3UU+q63MIj9DwRZWlstVJpQlrejUXSK60WM5UvuR73Mk3zBCwwaTVVg5n1u3jgxNCV1jDYDVlVazRQt4LgkNf15EqpeMqxmQs1F5Cm+yoptZruOSyh2D0/hFSs6Yp/z5xSKNvLyvCQ1wzdwafB3GiyHTDsiil0j+2+nU16CG+DRe7IaRBvpKSnxOWyXxqKRmok24iUYxNdiUdnIXFmaL8iEsnDnhsaLTdBe0EJ5ZNi7nRwy7GeOT8gNQ4gXyThjodJe1tuUDLtV20VnSU81sgnxGMPIY63ZrPyFLoSV87wyc5ak7vHHH8fpp5+O009n/qwrr7wSp59+Or70pS8BAD772c/i4x//OD784Q/jzDPPxOTkJO68806USiX/HDfeeCNOOukknHfeeeju7sab3/xm/OAHP8jd+Gg4M6nzkAEhNb3AHiRNbLPBvFgOQdnQGk6gblJ5ADU5N4TWIISaTxpp71JSZdNGqMe81GyCyToFzfjCwJ6B2M7WrG3kF6vLEP6eVtOmEVjfMOOAT2Ksr/Ln6dBVBbrW2NjK276sodsuobnydkx5IZmEhovf5YVLKAw9HpqaNNxsN7thsP9gFdffvz32OTdWo+GwfBykvXO8ijjAducFPXl6tlx3VvK/1APf/TeTpDmthITt1h8PjUqGuCSe0sKlFJWceV6izAsAdJWM7KHS3oLMSyg0Gj81x0W5oMfmwLQcK+J7H517XRpPYtksgpIk6W2pWC46S0bqu5h27JTloK2geYYeu3FKAcX7vzlhXs4555y6uwJFUXDttdfi2muvTf3N0qVLcdNNN+W9dAzxDLuNmRdeWJA/7CTmhdWnaC7DbtpxlsOqpDYa2FG3kb+w12Fe0kAbGAWWQzLtmEUw5ir5u5rTmHnhqbhDbiMCFIzmsggfSrA04o1dgZw5aC5LcrCzo57bKEtto6rlYmjSxLqlLOTOZ14yFjPMCl53iI+xH/5hJ976yhUxNgJg718+5sXx8rx4ibimY7xkdLUx5jNbG6u2m5gQjZcHYEkGxXmFpCapAxByd0+ZDjqKOkacePr8LDXSZhouSa4FlQWUJifLtF2CWp08Lo1yjiRlQy4bWlN5XqLuvLaChmqG8yhK8H5y46XR+DFtlk1ZBH8/HRLPt+IQ7oZMYF7o9HIgiaCe4eFSoOQ967jbyPGYl+R7dClFUv7DquWiraDDUAPjzk8UqeQqe+WjxWsbhW/ZEXyDSc/ScggICS/Arke7ic/CdklzNTzqUM6Wm03zwlwrwd+UxgtHct9olgKUScmQOJLKsjeCoiipA7dmu5g06+SdoYw6j07qbPcONDeEDx2Y5qVxsTpW2ygvtav4/aT7mhdmsOoZ0vE/f2AMv3hin/83nwBLBS1XorjGoKEaPgMTtdQdazPMi6Y0VxtKBGduYpk9UzQvSe/wJ3++OfZZxXIwkcA0Oq43D0U0aS5hm4m0DYM4bwUJ6hLcLdPWvDDk1rw0WRuL78bjzAuZVtVol8Tn6baCnpt5cVyKUqRsQ9a6WZQGm0iHsPpUjTUvLoq6FjsP17NF74nXhkpionj9upl0G5GIoSqOv2oD5oUSJBq5IvMiHquAGWXNUC8tbrwkFGas6zYifu2JUHbUyG6o2cqyhKaXB7C4YLfBQ0qqbaSpUX89+7eqNBZfRivbijBtkpsN0NX0TLE1m2CyDvNCPOaFW/ccFM2XRT+UcCmyaV74zj/XgsN+Syk8t1FYS9GQebHdEKXuEgJVVbConF2ImBWKsDDZTvq7Y7v5BLtViy3g/gQdYeyywmlgNIR/SxJdMlv747XXqraLyYT6N2naO4dQGEk1CTwoghE4YdroLOpMoxR52NF09nMB19tgNLNGBu7ruBHGdV3NwEnIhG5oSm6XGqvo3XhuToPIvKQJskWYDhNni+AGXsnQYu+ILwBPEuzS5l3SUfD5RTRUo0EhU5bLiiumXM9NcRtVvHdZ1Lxwg63Z8gAtbbzEaxvBrwGRXPyMeqxLUCCRT4ziC2S7pKnF1KVItUhNT/OShXkRf5JWQA4ANBXZmJeU35hufrdRo+ilpJ0oB9udxMW5lNIUnf38hksIChl2WoEYszk2j++4qGecMzdN/eNqNgmJGXlhxjxCxKxQBSbNrqMXo5TmchvVbJcVMuTMicc+5X0367mNouPfSRHrj1asmDi0atVzG8XnoXrieu5aCdxGbLI3EiJuLCdbNfNGyCXYnY7bCJ7mJfK57VK0F/WmSrEAnhu6iXIFUdie8dKMAaAoXPNCAs1LnfP0jlVRtVwUDRUi08zFq0klEbhhkybYnTnmhbHi3PgG4LGHIvPioKtcX/OStF5VTDemeeEam2bLA7S08RK9X/8hp7hTuBjPJcFk6ySEStsuhdHEi0ppek0kzrw02qXH7wmxSp8cmtrY4k5TsAMslXZS3Zd6qKezMRtoXjgzFR2s7B4VpIUKzle4hDMvDdxGTWk2WH8QCt9t5HoTXFbmxY4wL9qsGS+BMVXP5Vo0tLrRJWngoc6Op3/J677wNUeRMZ6kIeDCyyhMh8T6rWq7iQJ1xyXQteTaRmkFEXl1Yj4vTVkO2tKMF5dMu/I1R9b3fnqC3eRoI9tlOUPyGLQimtUmRmHzMPVmmRclYF5Khlb32Xx948t4fPfBmNuIz4FawjzBXb5agraFayJnRvMSyAw4e6KqYRc/E+zWizYKCp7S0HHMbcTKY3hrDtj6pCBu2GZBSxsvhhav2urnskjoXMsPlQ60Hn4kSERY10xYoKoodd1G5QxuoyjqFcvKwrwoSp1QaTfI8/J//+dpVDII1NQ61yzpWl23EYsO8DQSUaV9C2peeKh0FjZNzFNStdwMfc0MFW5cU491UL3kag2ZF8sN7eA449VVMjBezSdobARVMEZtN303XDLy6W34sOeiREJoInvRaAF2CWLvOGt3vB9ZxGC8/VaS8WK5oXBXDttlc0qU9XQbzCsiU1O1XLQZWrLbqIkowSTkKfAp7sbzgniGT5LmpbNkNGXQ8jbFDeX8bbRdZnRE+7SgZ6tqzdcbHn1Yj3lxCfDQ9iHPbSQUWCSB5CF6vEsoNM8YjkUb8bE9Y3leAhch4LmNhHNz4yVtE87dRtE1uOIJdjU1mAeJx7g3m+elpY2XsqFHdpfsJUlzlbBIF/bARes25pt2ae6qq4Dnb62bpC5dpZ0GPqCSXspG0UYAUg05gGle+Ff9EzU8vXesYXs0VU3V2XSU9Iah0o5LYsm7mnEFzAcwmlirW0kciO/8N77YjzueTa7jJUL1JjI/j4T3b77oEkLx/IHkZ1a1w8YLD2meDeYlpHlxkzUjAFAysi0GHOycSkjzwnVtHLraOITaJSQxYi/JBeqS5MrwpkswVg1H/lRtF7WEiD3bJUGSOhKeV/Q6BoDIGFcsF+WCluI2mhnBrp5DH0I8l3wzCDQv4c+taTIvboLmpZkNkOWw6J9oV7Bw6frvCqXBGMyieSGU4tn9YygZUeZFYFWTjBclRbDbpEv6zud6sfGFcKZ7Qr21UGReYm4jF51FI3Ud8xmkiPeDGS8e8xLSvChM95Sr9QwtbbyUCuEX2y9FryqJlqjt8CRpYaGqqoSNGdslMFLo3XowNNWf+GyXYMdgIPLj0UZ5Jx0+oJKgptxn6Df13EbCxOsSiid2jzRsj64mu+QAoL2g1TVegIABECd8HqLXanAIizZq6Dbyd0fsnk3bzcRAqGoQocJdnTw0k1BgrGbjBw8kF62LCnbZwqnOotsoGPdRLRpHSdeaWqh4H/AEk+LroNXZMATHIzFCK0kAqWtx9pRSmsq8LGkzYvfE3EOqn2ZdvA+tjmBXZIKqdh3jZYYEu5qaPefPdJgXrnmJhUo7FF0lI5eIW8RMuY0ckizY7SpnYym5O8fxNjP1mReKo5e2JQh2kchY8GO4ADzpO0PP7zbaPjiF0Wq06jNj+V1hg6ApyW6jVM2LsMEKMy+Ox7wIGXa9+ayed6AeWtp4aTP0EG3o+B2X7NpIyrALxOnjZrNJGprqU+Zb+iZww0O7/O9M221KFBYwLyICMVWjnZOSwkIBbMfBGaaCruGZfY2ZFzWF4gsSUaXfX1rGTEKS7nF+IWkHRjLQxIDgl/b6xsoUIqpAURSfBeRuIz8VgHf9tMWnGnEb8d1bZ0lPdHVMB6KBbLukjtsoH/PC7FlR58KMdVHzYqiN3wGXUhT0+HugJcwT4s6Qw/bC+6PGS8VysaKziIlIegDLIYluI65dSIOmim4jh7mN9Pg7M90Mu7xJSfeahqD0SraF8oUD4/j91kF2rMe8RI+yXYKush4aE+M1O5cOR+wH1neKl84he//YbjhfE7/8onJ95oUvvqLmxdDrz4EupXj9sUtjxguXByRtDv0kdSnRRnosGrUx+sZqsXFFvbVGfMeiLn6W58VI17xQIRdVzG2UwLxAOTzdRsWIOIpZfem5TSzPbRQV5dWLyElDzXbx5J6Doc90YSLdd7ASMqyaZV44tRb5FED9yB8OUY8Qhelw1XtQR6SRccVOFVjOD+8YBsAmAL3OrhLw6FU3PEHwsynzXKx75c1PxT5zqbfTarCQBG4P9rflEFQb1l/hYYvEp2B5ojDOvNTbedacSKg0ZX7ztDpZHJu2D2N40mzQtjDE98dyk2sDMeM23yTLfyq6iqJuI84ePLIznTV0XZIYqs4pchF6AhthOi6WthUwWgkvZDXbxYqOYiziyPHcVNFNVFq0Ea9rI/aj7zZS43k/WJK6+gbbpOlgLJ7fLnKv2Rd5vjE09MZ5jQA2/20fYMwzZ1aTBbth5uqrv92C/aPVjG0KR7bZhKCgKyzBXA4j2XcbRZmXkl43rQB3d4uh0vWMU4DNBX9/4SvxR0cviZ1LVZLZQIeQ1FDpoHxIvnWld6waTzVCAvaHj9Po5rdmu+gopjMvvnQj0tYpy0F7UfMyfHsZdsEFu3NUHmA+oWyokVwWbIKsF23keiFt4vdiqGeA+oNw/2gVv3xyf/gIwYLcdzA8OPw8L3mZF5LuUmEvTf3j6+V54TtEBoq1S9pwYCzbxAEwt9MP/7ATAFsso1kjo0jLwcBf3Cxiu+2DkxirzCxzkAVJ7rCAecmw8xcWT8sh2dxGSrBb90OlvcmFUtZvaeMpSbDbaGIFmJgw6+LBIUaP2U6y2yjr9TlsL2KHR1zxd8D1WRgGw8sb8c174mn6OVyaXMwy6d1IGqOWQ7Cis5jKvERF6pwtUyNMZFofsFIAnNVgn1VttlNNchuZGTQvd784gCeH6ve3qHnZM5xeUBUIFiVDVTKFNrMCrMFGJanwquUSdBb10LvASgZkcwWxAIC4a5QlqssuSmfRRvG5uatcv0QAN1Y4m+AQ0jASziUUyzqKMU0ld8ul6VrSktSxYID82acPjNaSk+EpnhHl3YcWiTZyCEXJSDeWOMsW1WNWLVYSQUxSx1kaUTOXBy1tvJQMNeY20utEG9lemDSvAMqRZgTUo/9qkVDUKJKMF1bPIq/bqF6odDbBbr28LGLI3uK2xnoI8d00HSLoOJjfuN4gNDTVL4ImnieIqGrcN///J/bhxb7xur/ZP1rFTq9q+EwhiSnhCQ4zMS9Cht2sxgufAHTVS1LHRX1ekj+HkFSxcCxU2s2mK3JI/hwiYiKrNLeR46aHCSeBRycAfFPCPo/mG9E8tnN40kwde5z5iruNkjQvCUyHGzZeHt4xjOcPjKFqp7iNPM1c1DgKoo2U2O8Lmhp6V/lkn+Q2YqLo+s9o28AUGtkAmhrohf5/tz5b97d8ATUy1sYSQ+b5sUlJ6phgN3gXCKEwM2pgosyj7TFs7QUNUzkqS7M8L/EFmUXm1ckY7o1FbqQ20jQB6fN5PbdcUKU8yXhBU4LdwUkzIckre5cZu8s+UyMRTo5LmcejrtsoXodpynTR7rmNRPecyvO85Gq917Ymjpk3aItEGwV0bXIUgebR8K4bdhsl6UIKejxEUUTNTspnEeRB2D9aDb3kpkPQliFJXRT1imRlcXeJ4ZdRiG4jgL2s9fK0CGf1j+eDuOZpeupB3OmJzU7W9SSjb7zWcJfx1J5RPOK5s2YKZkI9mSApVSPBbjhUOpfmhQR5HHjEB9cPEBKv78VRtUlod8d84407mdPfeSAyl9FoI/5+cuo7K6qe2wRgUVbcdepGxgpfTKcsF1bKY/Dz7ETelaQFNWlDYDkEKztLPuO3pW8CL/VOMOMlyW3kMsFu1DgK8rzEz1/Qw7WQKpaLspHsNlKVxiLlrQOTsEm8v1lfsn/rQthqo/eeG5B6AhOUBDEXDaFMXxSdqgK3UdB/LqUw6ySe+/XTB3wWlCWpC05qu+w5txV1TOViXliodMxtVNbrbuaiY9ol2Qz0pMhKJg9IduXVy18W1E1r/M7yDV3VYoZENBkeZ3ZVz4DhbRUvycPB06ONAulGiHmxA8FuwMixsZjs+WiMljZeioYWFyWmRBvZLkHRs66ZfiD4TkvwfSfRtSJqdlDZ9ar/fSb2PYu6iLuN8mteKFJsl0zMSz23UdRH29nAx8vaE/ybhVp7zIvDsqEWDTV155S2ayM0PaIqir6xWoYSC6TprJ1pcBP0JYTW34X4x9LwQsE1L1XLxbd+tzXlKC6eE2sb0cDHTnlhuhTmxQobkzw7L8B33Mn947jp50yDWLfGFjLUHpyy8KXbnvfPq+dIPzBlOWgvaACUkKsoqhvhlL3lENRS7EFuPMYNlbjbzUgQlVsOwfKOgu9CMB0XBysWTNvFso5irJ4Xy82jhIwRgLFfSTtzy2NAxfe5anG3Ubw9YpbSNOweqSQyLzYJjFpxIWkUJUg8zVJBU2KLXhJsN2AFuZg/aUPZXtRhCg0llKJmucICH3a9/WHrEIYmmCYrjXlpK2io5GBerBTmpaNo1O2XaPh4mqYpC7iBoiaIqLnRmx4qnU2z+UWPXesbr2Hd0rYEtxF8Zpe/b1G3EZA+jwNBiYEww0JhOYylZhuxQPOieEL8w85t1FbQwsyL5/NMijayXS89P+Up+IPvxWgJDl3NYLx4D3C37y+m/kOICtQsl6BUaCbaCKnMS7TIVRLyiJG7yunMyzW/fl74K2AQeB/UbIKioaGjqKeeQ1eDiVi8pbzMSyODzXGpP8FGJ9qbH9uDF3uT3U7/9tuXUvU0DonnlPCZl4ZZk1m0i+sbesxtNFa18VL/ROpxPM8LcxvRkE+aUq9WVOoilt6nLH9FWvFEknsXJC7SthuUJbBc4icgs0m+9APcbcLHDFsUqE81c2jeZGg6BGlRrWK4uYgoM8LdS3HBLhvb/rh3iC/eZbmNwgul5bAaRtFIjfqaFzWUkZdvBpIEsmJ9mCTUbLazTrIxRCNSXEgaRaD5uUYy7vJth4SEmWnulHIhXMuHEIqq7fqLZzRJH6tEzX7vRjaI3DVZ1NM3UElwXIKSHmdeCrpat/xAVOPCCwNnh2DYCpqXJCOPGzbJmpdsFesnag5Mx0XvaBVHLW1Lrg3ouXG4ERbf/NK6TAkX/fK2jtdsfPLnT/nfi9FGYpK6ZtDSxkspwmQEodJxJiXIokhi1HjUrwcwt1G93XvNDl6cqH5hrGqjq6SHPrMcgvZCukpbhIJgR5jsNhIHViPjJT3PSxSdJT01NPD5A+MxFsi0g0zFzG2kst1KysLIja0obUpptiR1lFL0jdUa3rNLGPVcs1189hdPh77rHzdxsJIchvHCgfFUmtghcS0HN14aV5UOF2a0XYKqTTBp2nULa6oquy6f94NkVaofbZRuOKX3Z1edXC/NaF7CzEvgNhITvuXdlVZt5jbRvMWLD4/oebhbxWzAvCRl2E2ixEu6FnMDRgvpmQ7BwYoFSoHOoh4X7Hru6yjbkOZWCNxG4XlLUZTEKsNiltIkbBuYxMlHdCa60Ryh9AlfSCil2d1GarbEdrZQ3JZHgSa9t6VIFluXMpeZ5vWTroXdsqZLfEGvQ2iov7h2qKDH6wPVvzdetZz9zcdaEusVOo6Gn+d0mBc/7FqNuwS57q1ukroM76zjsud8YKyGY5a1JxovvA2hJHUk/t6kIVqHqWq5uOuFPt+YFJOccleZgsOwtlFJ10ILikMYhZbkG/SZF4KEaKN4GF/SpCGiarv+zkJUxysKsP9gFWuXtEFcQMwc0UaaipC/OD5W2DmyhDrmSQBUT/NSs+MpyU0hTXnNZruXRll2kxIABoUZ67/4E6aDiuU23GXYhO3+a7YbE+45bnqOjOEpCxU7hZFIKNjHjZdGz8CNTDCWQ1CzXEyabt2FgOd54RMJd6+xeiNsYUyfXNPbVK+yNC+fkQeiEa0qwU6ZbRK8hcYNhMc9z/bioW1Ddc/JRYq6ytwUXOga1bxoquLrkapO8vjhxmP0PYjOEyxPhxqPiglF5SUxLxG3EY82iuxQ05gXyzOOkuatpAW0UX6WbQOTOHVNV6rbiC+4PMzcIbShBst3BySUK0iCFRLspruvS4aGqmBlEW/BCzEvgq7FcgI2L2oscKMxqbhhfdBE8XZBU1MTLvLrixvLrJqXAMFveR+ludeSdCT8uyTDPK2941Ub/Z7bKHpvnNXk/wFJG+QG0VSe5kXzXFncJcgjGKPMC2N6DkO3USkWKk38TIRRa5HH8nPmJRptlOTXq0cZMs1LwDowsAfbP17Dqq4ixAXEdNzE+hlJ0BX490VpOv2fdJ9RZNHFcNTTvJg28YR0QbSEJYhYuWC3M8FttHckCMNMUuQHrrH67ewbq2FZe6Hh4up4uz7TiVc4thO0KxzDk1Zq/pWk4/w8Lw36NxrtYrmsOOWU6dRdCFQlPEFyQZ2usiR1eVgScXjXy7LbnOYlYPd0QRPBdELsC75wKwrLJdM3Xqt7TjFbtum4gQFHwtFGhqb4YbHVNOaFpriNIu+G7Qkwo5sFy2XMCMCeAWdeFAXoKOoxwa7laS+igQBsfkrQvLguCnrc2GH3F8ki7m3Q6mV1Hpo0sXZxGU7CYwy5jbyFxHRYmZB653T955HRbSQwcDxJY9ICVTLCbiOXUFQsxzdKDFUNuUYth6DmBMxLiNF02N8FXc2teUsSbzfSPUbLPUxf85IsBeBzZjSChx0HX9DfCA4hGK85GJ60cMSiUqyPRN1NEG2UzNynGRtcW8drNFmui7NPXIG2AtPf8ehAfg7Fu0YTtktrGy9M8yLsbLzdXZIVzcuex5PU8Rok4XNnEezaPvPCXz52zgmTlQ0XkUewqynwrWIKTtPFj0vKEBpFdreRUlfzYjospb34sooROKZnHCZlUf2M4LpJ2n2mRVQREk4+1jdWw5FLyg2ZFy7gtBKMF8eNfwawl25o0kw1XqI5JXj7ikYWtxFC98zdBJOmU5d54ZoX0WXCNC9BbaNmqgt3ldPdg81EG4mLtCHQ/DyxHsArLasoGho27z3YMJeHnxRNZeH1aXleNJX145I2AzWXsWcxaj1ldxornJhSe4gzI3xRNB3iR7MkabwojQcODE+a6ZoX28vImxo4EHaNlBuIxE2HoKOoJ773tksCtxHXC3nva70FnxuNhlrflSJeRzSC01zcZUOLRRtV7MBYjYaKc0YVYGO1ZGi+ccPFyPmZF28ujfZ9A5cwFzEDbCHOr3kRzkUE5iVqvKRE8LDr0oaJJ/3zeMzLwYqFVV2l2OacbSKDZHlActK8+tcIisdy9/2Jqzrx+bedDCBuaLHaRvmTxAItbryU9LBgV7Reo/1tu9Sv6swmaP4NTXStFDSmedk9nJwvhO3q2TFRzctkzUFHUYdIsfEJMIuNqauB0LRxkrpGxkv2gdFZ0mM5KzhqNps0uHASCBsvnHkpRSYjxyUYnDD9LKK89oXYpGTXGDv/jzft8f/uG6vhyMXlxtFGnpDPdEiIcgZ4hEL8+CnLhemQ1CiFJKMnCBtswLzQ8I7M9nzzkzWnrmaFT1a8bwgNQqUJTb+XJIi/Kmha6qTsRFyqWcAExIHxwvucCMwQD2Mt6Rq29k82dFP4VXa995D3XzTCw9AUVCwXy9oLqDrAd+7bgZe8PEC2S/DsvrHM0UY8qiPRbaSrfm0m03H9iJ32YtxtJPYLoRSjFQvd//F7OG7yztx0PbdRgmsl6jZimbrr54vikWZJv+B1lwCPeXGD0OTouyIit2BXcLPWK7fCNjtxtxE38qIZj/l7ze+lLGxgbYe5pJthXrK67EQ4RKy+nJ7HJwtErUga85I23ydt1gmhMSPIIUxAO1GzsaTdSNG8KKFoI0WJ6lGo/3naffAMu4QELtc3n7AcQPh5BknqDsvyAHHLmIeSRne0tqcodwnxw045kgaFoTEG4Qu/TE7eVLWY5oXSuL940rQ944Wdc8p0MF6zM4eK6kqQH4Nbw0kvRBarOD740sBcIGk7FtNxUbNJiLK3nCAyhWfYjdLAIxXLLySnqcz9kqR5STLQbBLOrdI3zoyXRq4yzryYkRT5QOBSimJ40sTS9gIqKYtqNKcE4IVK61pDA4K/pCIUhYUDp++g2TEOIYLmJQiVJpT93Ug8SSmN1Y7SIzqC6H02x7ywfxcExtKlATPEKfWSoeL4lR0Ni/FxloJpXly//VGWTlMVTJoOlncUUHMV9I5W/cWwf7yGn2zaFXMvcMRrD5Fk48Jhbp2iocH0qnUXPG1MPbEkZ6T+5/G90BQFAxO1OsyOlhg4EHVfs2SX9ZkXLp5PAmPABM0LCYwX001/Jq5nOLPor8bjg1W+DtxGWoLwE4Dfp8F1KCqW688zUUPEdgPmhRCKshHoHnlkXqMooSQksl5qkFQzCaILnFKPYU3I45MFoVwuScaLkhwqDSSH/N/1Qj9+/cyB2Hl4ocmCFq/JxiUKfI4BkGhQ170PEtR7cjztoZhLLFyYMYgcPOzcRoUUUW2S2txy2UvvEsSS1CW5VgxdxeCEFfNnczC3EY25oACPeRGijb561xZc8dYTMt9XiHlJWdiBZIsbYAOIf14vz0sea5dH74h2RzhJHTMOGfMS9P3wpAXX6yeeX0SL6ApYBk4gaqC5kTo5/eM1rF5Uari48lDpRLcRSRbsDk2aWLe0DVUr2W1mJ7iNAsFu42ijpEVx0nTqun14qK1ovGicWUS8RhcHZ7m4y6F/ooaVXSX/eyZETGNe8hf94wwDpSyTsBhh5DMvHqVfMjT80VFLQmPkid0HY+fkE7bmCXZ9t1GEidQ1FRXLwbKOIqou0Dte8xe3ms1C0rnmItpVsVBmz+0c07x4u0fOEpgOQVfJ8HUwaTttPvHf//Ig3vuGo/Fy/2TiOODGkOoVZhQ3GzG3keeerbchqXosaFKrbJeFcQOi5sX1z50Gzphm1VfYAlNJaXJhRsBjXsRQaepFG3ldy9khDlGwy1PV8+tYLoGhqyyTdy7mJZ7OHuCuk/rGi2iMOimapizgm9S6VaVT5vskdt103ISaW9TXuiVFDBHKXVfBnBO/Zn1WyWeHPcEujwDjSA2VPtzcRmnZHpN8nrYo2KVJVaXjO57BOhoI/sIlpeqeMB10Fg3wB717uOLTZlmgKfAnrOQkdXznlOwS+v22Ifz8sT3+b+q5AaLhmUng7BJzG6n+9cXyADWbZeuNal6GJk3YhPpGGA/7C58/uTCjHVlIq5aLrpKRKUmd6SYbL7YbN0JYOy2sW1JOdRu5JK4vcQkyMS9RnQbHZK0e8xKI2/j86HJXihpoXpKuzfVHfBLfM1zBUUvb/O8NoTha/D7ju7hG4KHSLqGhCECxz7jLZO2SMt7wimWh3fY37n45dk7uauD3wN2V3P/PoasKpkyXMS8O0DsmGi+MLUyLyIi+G6nRQJ5gt2Swgn+EUCzrKHgZgOv0i+q5NgwdJ67qxO7hqcTipTzPC5+HeM4kwDNeIoLVglb/ujXbM3ASvuMROUCgeeFzZb1xLOYhSc8tFCBcHiB9rorO1YRQb5PkaV4iczxjVPn4YjpG/j7bDtPz5A2VBpLLFzQCfx8B7jaahuaFBu92alXpBMEukFzehrkDw3NZyVBDWrfoqfgmkjNAQP7st67o/nJZtFFBKEETYl7ADEQFyYZtI7S08ZImqCoZaizFdJDnJSFJnTBwmcZAQUFTMDhhYiplJ161iO9v5RM3R8C8cPYj2/1wyk1XgwWWW8NhsPOm1WSarDm+oDDNbcRTrmcZnA6hIJRNimzhYL+3hAJxpu2imMK8OL7bSElkIQLXWMRH64ajaUyHoK3YONGfQyhsh4R0ScE5kwW7w5MW1i1tSzReeN2S+OROQyUP0hCNkAGY0TMyZdWhZBV/QuS7JErh+6QJ5Xle4teueqnl+SS+Z6SCowXjpV64Kzfu84CPMa4rE/O8+IJdL5Lng286Fq9euyhk4KbVjeL6HtuJRFwJfamrCiqWg6VtBUzYwMGK7Y8/bnCna17Cu0qXkETXLnfrMM0La+uStgLKfgbj5P5SFRYJVS5oeMWKdraIa3FNhB8qrbD3uWI5aPONl0iosBD5lIaa4wptC8P2wriBsOaFM1xpCEKls9Y2CsYmf2ZJw4pnWBWvw6KNWBujuhPOAAPcMAw2D9w92Jxgl/U9m1uyTdhx5mVm8rxEmVwxf1ki85Ji8ERF8V0lA4MTZur4ITSobSQKdvNMB75WzWtTdLyKeYJ4igw1JQdQI7S28ZLywhU0LcF4IX79CpfQEF0sUoZcTGloKgYn6jMv7MXxKEsn2CFP1Fj577zwdzchzUuYJucuASCdVal6O04gTo1zWG56bokoeF8Ggl3+uZDnxWH9K07wAGNeeH9rCttJR3MhBIUZI/1B4sZLo0gLIBDsctdR6DuSHAo8PGli3ZK21IUUQKLRk4VGJxSxHVnJ0DA0aXop8JNA/WgjUe/hi+E485Jwbe42KHjG/d6RCtZFmJd0t1FzSeoIRYwiJlQIlRYWzXJB80Xu1NM4ROG7KVQFpkt8t6JLwn1paComTVYH6aClYHVXyT83F5nz/BvRW+ZMx/0vD/r3Xi8DrsgqLm4z/PDPev0yaTooGyqOWtrma3jitY28UGnvO15Rmt9flHkoNMglwjYSdTQvXM/ANS82K5DYyHjhzyNLHiBLYKQJpV5V6bRxJRiQ3njgwygp3xaf21zCBbucOfLyvOj187MkgbOcUWavHkRjpeAl22tcvytt0wBB1xL+LngXkvVVSXoi0R3I0VUysGe4giVtheSW0aC2EX/H4jqsRnNd4O71BbvCWIxqXqAw1v2wE+ym7SCT1OaWJ9h1SMAC8JdJ1Lz4dSQ84yWNeTFtEsquyqltQ1NR8ViIvOCWvBbSvISZG/HvpOyHQLDj9H+TMDJ41tBogqBixPhg9+otBkK+Dd4Hfqi0zQW7YR/28JSFRW2Gb5gZmuK/4JRSPLpzxI8Si4KFWwbPMa1GShSBYDcpVDrZbTQ8ZWHd0nJitWd+j0nH6QmF85KOj7JnJUPF4KSF9qKechR7zmKSOh4qHcrzksS82Gwx5zvQ3SMVHLUsMF4KDWqTuDkjNfgY47Vl+OMRXVAi4yayc0kh6ECYeYlqXkQDWvOYl6KuwnSBY5e3hdxGVduFS8Nuo9B7Tyg++rMnWChzSjQQZ0aYGJ21dXGIeUlesFSFubTaCjoMTcXRy9pSBMFho69quSgVUtxGGZgXgIegxhGLNvIWuY6iXlcnEkQbZRPsssifQMyqKdlcAzzaiO/89YiLsygYkJx5Ed1ehSaZF86+58nVEhrTuoaJmuNnBs4KPn8TwXBIYl50lSWnTBbsJulkSIx5aSto2D9axdL2ZOOFC/uZro59ltttxM+hBoJdcWyL6w33KijKYSjYTfPdJ/k8bZegXGApoHlUAffF8pLmAN+ZqDA0BYOTZqq1y2k+vghYDovE0Rskt6sHPmGLzEuUlRCZmLTaRrUQ85Kc54VHUESFap2leN4KPmGLIYwABC0C97Mzt5FYaG1owsTyjqLgt1V9Sth0CP7z9ztSXGPJLEDa8wgdxwW7rhs3XuoJdpcku40aMS+Ncq0EguQAZUPDRM2uW+9H9RT7vGsI9TLsKkG0EWdgRPBQ2YLO3KcTNQddpSDvkF4nBLQ55oW1zXYJDD0sYPRzcLhBZmUxJXy0uB4H320amgrLCTQQJPI+GJqCKZMZLyUNOHZZe2C8OGG3EX/H+XjTVMUryqfh54/t9TN0A0xE/NOHdwNIZl6WtBm+gVGvX6Ysx9fGvOeMtYmaiOjutGK5aDN0//6iGWbTjJd7XxoIsRsUcZex+Bz8PC9eXpi6gl1vDGd5//zfR8ZttFSC+BwDg5KFvvN+4ikrOEp6wKq7nhRAfD91P0ld9tpGgOA2qhMgEYXoNioVNEyajt/uLBGemhrk6eIRiUkMIW9TWt8nbVCTmBdFYRsbzrxEb5O/FzzrLYDQ2hjFi73j+M8HdsTPoQaZgnkagCRQUD/l6WHHvKTF4acZL0Fto8AyjPoSLe/lLmgqBsdrOGJRKXE3zsFfLMtlRboMNayBcFyS/WXwkmRpCvwQvWASEP72nlpSQiPA8wt7AzdNiMaZoyiTkVTfyLSZoVNzeKh0INjlA7PmBHleRNfLwYqNJW0FX9wWUOc8AysRJoxwP0WzvSoKUncfoeO881oJmhex5oqImu1iaUchMdrIcUlqDSNDjYccRpG0mysXNNQaVL5VvHEpRhv5GXapYFTFavF4mhfP5RAdffUSMEb1YFnA8yTxDKe+sSUwL8ww5wUBAxbEduM1o/zfCwaGKowZ0d7TVBVTJhufZT3KvBBfsCsuCrxPOTPylhOW4+Edw14kHGvj8KTpZ5sOoo0CVvJ1Ry/FH5+2xmtFiuZFZW4jrl/52DnHJ1ZPZy7cwBCqWI3cRsnT9o8e2gXTIf5CoCmIjU0eUQWImhcmhG/IvKg8VDrf5ixgTCGwJMF9tBV0v4xH0VBDyTCjGptSlHkR3EaOG+R5qZezJg7GdvMoTfFdrfcqiO9m2dAwZToec54tIks0RqhgOCQyL5oSMnZEpEUoidIJboB0lXSfeUkS7LI5Nuw2Cp866JvRih3L1B3KV+NtIqPGNp8f+D0z5uUw07yk1Z5IjjYKBLu8MiaP0w+5jTzfPI82WrO47KcfF8EfQFTzIvpoDY1NrMUU8VwUPNROV6N5XhTfncNFm4C3W0gYzFncRhWvaq+iIKSJSapvxEJDdZh+FEDgKuIDs2a7KOlxtxFAfSMzqnnhRga7p+T+iIphtZT7eXLPweA4jxFKdBuRZMEuwCagNOalraAlToiaGi+kFgX3A4soeUUH60H1Fp+AefEybapBdA93LYmoWgRlL9rIdEisb+uFSkd1RlnAqWWbsAXJdxvRwPgUWQ0RzI0Xv55LKTTPxcgEu2IfBOfRtcBtVNYojl3eLmhe2HvAi9fxcSOWHqhYDsqGxqqDC22cNB3BJcwi6Yp6wCouajNCrrjkfmGsUDwqKbzpiE7wNTvsNhLfAfbb5PnEctxQXTFDRcx1IEYb8VT/pk3Q0Ujz4ulW9IT8IMkIs8U8MeV1d7yIh3cMhxggsVyF4YW+cyNPNN6IZ6xwJtglJJTnxRLmbsslGJmycNfzfXVbKTI+Lg20eVkgFmYsGx7z4mlTsvRRNFCEuYTjxxLB2E4q5Jpk1ETrVfF1pKtsYEmK2ygwoMSq0hAMrPA1xCzzwXWCOYpQKiRnjSNIUtec36iljZe0UGkjIQKE08NJhdLEQcTLqrNIJoo1i0spESjwfw8wY4O5jRT/YRmaiklvYm2EGx7cGexulLhgd3Gb4Vey5a9WmoVftVx/kk1zG+0frWDtkrJgDLCz8uuIqNnMJx4V7HLRL8CLkoV3p7yfdI2VqBc1L3zxtRwihIPHWZLoi5wWYfWvd7wUuP4I211aDgm5C/g503z2aQnHXO5bT9S81C+Sx4+P7rjLhoaOopFyBANnBKM5TrjmxSUebR41XrjmRVdxsBLX1TBXV3KbmeYlP/Piu41EwS4J8vRwd2wUtmBM/uaZ3iCpnWfscubFz7BL49FGUxYTqJ5/JMG6JeVQtBHPAl0IuY2oH1Ex5bnY+L3z60yZjr+Yh/K8JCbXS9O8INF4iS420arVzG3EjmEbMcHQqaN5sV0aqnBtqIi5Diw3MNBY2DPboXeW9Pqp8IWxV2+8VyxHeN88Fwo8zQtlETC3PL4vFPW0qGxgzCt06W8qFW68BHmDLJegs2iE8ryI76Xjjb+ix7wfGK3iDw0KgPLMz3wudWn8XU2DKySQLBc0TNYcv5p4FuZFLEnADbwkZjlI2KgmblaTtI9R5oUbrV0lA0tTBLtiojw/2kgJG1gi6Ve140lAxTnKJYE8IQl8I67gMIw2SqMwkyJXWIbdsFXrukEImk9je8m0DI0ttMs7iqmiXUBwGzkBs9DpJajTNQWTtWzGy+9eGkDNJt4gFQszAorKQjMPTtkhn2yaS4j7+oF05mW3l/sjWj9nRWcJg+Nm6Lemw3Zm1Wi0kZCPgk9UogHAJzFdVVh2XiWseXEIgeXSVM0LyxMSbnvaPVcs1zcyOc3KK3mHnnmKxqIeHEJRKiSn1G+UyAoIh7vzPikXNHTUjUhT/Ik8OBZCeHuQJC/qNhKjjQYnTCyK1Nmq5zZqVvNCKWJuIzGJXpoYVsx4/Kun92PU24GLGV3Dgt3wzlhXVU/zouG4LiZK5MwLNwp8t5E4CSus3RXTQdFgwnXTCdwVk6YbYlULuhqrwxMg3W00UXNiUUnRxS1uvATHRPVJ9TQvlkPCzIuSwLwIRqSmKnBdlom6cbQR/Fwj9TReX779Bew7WA19RmiQpM4lBDuGJjFasWDogvHiux8UXzcBhDMMm152YXExZUnqgg2kX1XaZQkKJ1NqtXFwgzsk2BXGVz0SRizMWPRqlfECilnCyXkKfSB4t5N0LX6SurqC3XjbQpmLPS/DorKBJe3JmyY2TwXpGIAghxMQbAo5qlaceeHsDWO/3LrjlW/ED8uq0mkZdoG4P48JdsM5QrhFK4pW+YAsaCoWlQtoK+iJ4bOKR63VhImST7Yd3k63oKmYNO1MkUe2SzBh2ozOVoLCjNxYWdJewGjFCgnh0jLs1uxA86IoyeKxPSOe8eIZgPycK7uKGJgIV/zlgj6W5yVZ85IE0wuf1lXV6x/4zIuiBMxLmkjOceMJANPu2XRcX6sjuo06iuEdpUsap9RPaocYFp8XRJgQuSi7bGh1I414zS1OJ/O2a4KYzqXJzAuP9EgzXuq7jUjuXRA3kC1PsOu7jUi4qnSa24j3q+kQjHo78CCjq+obL5rnTg1n2GW6Ej4OReavZnuLshtoLti54fvlKxaLDGwrsGgRHokzadp+2wPBrhYzBhr1y5TloGzosc/FPk50Gxl13EYpmhfLE2fz7mHMSzzaThTs8lDpjqLRWLBbRzTK0TtWCxlQ4rG81tV5J63EAy8P+vcRrXKuIChkKuYFEXUyAM+wK4ZKU7/AJaUsamkiweUvghsvfF6JMnv1ILowy4JgV2xzPYhu/4D1iLuAAr1R0Pf3vNSPO5/rBZAUzgxfiM3B17r3bzgaq7xs23HBrlDbSIg2EnVrYpqLiu3GXOl8s9VWYC74euOVeukgGm//ktHSxkua2ygJPEmdQ0hocuWp6vlnXLFuaCqWtBloL2q+mCzp+jwCh7uNDF31SwPwHBTFlDojIhyP8vWZl0io9JI2AyMVK7SLT7PEuTYGSErvzLD/YBVHLin7mgn+Eq7qKqE/yrzYLjpLBmpCtVdKGS1ppAxMwEuWVtBgaGz3zPQ8qn8tvnDxe4zCTjA00iKsLIf4dTt4sirLIWgv6qEXjO3k870q0WRYeeEKImuuWSilGC8v9Y17FHqQ6IkbK9GQcp95SdD1MANcSTRe6u0Mm2FeuIHMKhaH87yEktQljBXmNmIp8S2H+ItYKFTaJf7kzaP6/HtRmQHCF38xkqlmu1jUVkDNckPUuug2qlgOSoaKtoKG8artzQeMMfEzt7qBYHdK0GMIPeD/S9woaJ4gOO42Cr+TUVeQ6QT1YNi7I7A0daI3LJdgQhDbM81LeO6yScC88MWQu43qCXZ5cEOjUOm+sZrgZqf+/+gaZ14oTj6iCy/1Tfj33FU2fHE0AD+QAGCJSPlGznLC0WyUUhSNeJ4Xjorl+sk608D6PnD1iMUWG0HM8yJqXjRVxcGKjZEpq+7x4jjgc6CmqjG3LU8zoQnz/dCEhWHv/EmBG9wo9c/hzfHrX7Esdc7mwmpVEdcYUVIRdv3WEpgXnienraCjYrp13ZyE4vAtzNioZLkIy+GFGYPP+CQvDiI2UTHaa3GbgbKhxSJQKGVZdQ1v4ix5uQZUhX3W6YWl6l4YZ6rlSSn+5Y6X2HUJDQa/EuxGfealrYCDFTsUOp22C+KMB5BeWIuHj/rRHN45V3QUMTgRNl5qDkGnwLwEOhrquQySR17FS7bFXDgs8ZTuueN4G5hgl99TeFFwhbBmUViXFmHFmRdeYCwpf0WSy0QM20yiiaPJsPJC1FLwnUi5oKGjoMfKM9zxbB+29E94E0g4DJoKdDo/LxOhxycun3mZzOc2As1eHoBnI+URCVyEyftQdNGJFHuorT7lTz0D1GNeaBDdArC+YOyIHVpcuJuST5BipGHNJlhcNrz8RIFfnZdr0BRP86JraCvoGK85PjM4WrFDUVCKwopKjlftumyjLUTzqAoT/sbcRko4caRpu6E5wnSC6CNFEMgD8HVcSbAcJlLlfWFoNJl50QO3EQ+p7crqNlLrJ6kbSEjs6TMvlBkHJ67qxIt9E4mCXYAZJHw+MtQgHUZSaYSCFiQq5eOeo2a7MRYoCq694e0TWVKOtPnNjRgvUybTvOiqgl89tR///eieuteOCXa5FyDKorjUN4r4u1mxHJ8FTEo06hIa0mclJWCMRhJxA4qHOvPfBBv7MHtaseKaF57orr0oMC+R94Wfr2+shsVtBrvG4RZtVK9keXQRsl2+mxGiNwi8aCPBuiTUyxWgYFG5gPaiHitwxQe84TEvvDgYLxkfchvVnFTmxSUUzx8YY9d1mb86yrxwMeviNgOjU1aIpUgLneOLN++H6Msn1ktSFS8SyDugkGAQmraLjlIg2OVh5vz4tLWOp6nXVVbQTlOYO45rXlwquo3ix4uCXb4opNX3MIWFj90j68OOiBAxKZ1/1U5Pp86uTUL0dBSNdg2iW4zvRMqGho6SHqsVY3u+eq7FEs/t0rB7jTMv0fvhTFpB0zCUqHlJ3z1niZ4S70tTI0nq9CDaKMa8JDxkcddsuQLz4gah0jwiYVHZwMGKHeoDPm65QSHq3Wq2iyVtBqqWG3EbMSZMUxU/J05bQcN4zfY0CypGq7bwvNk5S4aG8aqTsJMUXdHB7l9RvGijyNiK6rZY4cggoVvcHRvck11nJ2s6BEOTpr9x0ZW4YJexY4JLxisP0CEwL463oRARCHbTXfWm42JkykLFiruNeLSR61LG7o7VfEOjq6yH3EYFISJRnOOTdvGGEP0UdVFk0bxwNoHrRqLi+qQMvy/3T2BkygoZLyVPsMvnx60Dk3ihd7zutUUXOF/0E8OeBWObz31TVkTX2Ih5Edoa3JsC0V4VE+WJgt0we8o+11TmEo1vBOG5jXRULCZ6L6bU4rp183788avXePcPP69SVrS28dKgZLmIaCQEwKnQcESO7XLRrMe8FLTYy8hymqh+RVufeVHDgl1DUzHhiQmTwDPBAmyynvAGP4s28uhEbzBw5iUk2E1hIUQkiZcHJ02s6Cz65+ALRRoCzUtgvPD1sp6ynruNdJUxLzwaK5rnhYvV6tU24sUG0+7ZEpgXdt9s590Z0bwYWnzMiALJJLjEC5Vu0m0kVobmoYNL2wtYt6Qcy2Nhu4RlGPW0LW5kkROHsOvT5hHNi0efGyluo6S+5tAa7KxFuP5kx5PUhXe+/PnxukfRshBcA8HbLLqNgozMqt93XWUDI1NWyHjhO8EkNqTmECxuK/iZocMUPTOKpkzmNioXmGGiqyxX03jVjvVrSdcwVk3SsAVj0naov4BqHjObxLzUK8lhevNLEuoLICkGJwLjJTlUWsiwKxRm7CwaPtN0w0O7/JIJHH7pkjq1vAbGTWYs2lHmBX55AM4ArF5UCkcbiW4jI3jmumA8xO9dCbGIUbdRZs2L7uV5odQPCedIYik3vtCPl/snQmxGSWfyAha0oWD74KQfQZWGZLdRSlVpLSzYrViOL8hNO0ac0h0SX/8MTYU4xHltPU0VBbsBYxnOEaRioubE3hFuqLYVmIvVTDG2945U0FbUsLS94G+we57prdtfUbS08VIv+18UUcoLCBTY4gLP87ysXlTCn52xFu0FPRYqzQV1hqag4u3a/SR1WiDY5W6jej5qMdFYkCcgiDYSBbt+qLTPvCSHDTfCnuGg1o2qIJQEDIizNcwnzuh3vht2PddZPeOF59DQvXwjmrdzEzUvjHlJ1rywbLicMmbCyrTr2W6geQEYgzRlOkzzInRS0nW4kQXA11WE2xFOQx5FHbsPQDDxA4H48/iVHbj0TceypIYh44XlZ1CUaI6FoJimf17XY14iE0jIbTRhYlFb/ZBsEUkUdBq4G8tPUudpQ3y3kUCJs2ykwXtQNFimVEfYVYeMF09jIU6ki8oGRitWaAfJWbykCbJmu1jcZqBmk9CYDjQEgdu3vcCSM+reAk2pWLaAem1mVXmj77OhKaH3mC+gvJlRzYuaoFHgUBSeQDItl0u6ALK9qGNo0vKZnkKC5sURFnieUySqedkxNIWBiO4tyHicHirdP15jeXb8+ZLr47y5mv0FVVVw3IqOkGBX3HiImpeCYDwkBQhwbRu7t7DxXLXd1LmJw/KMTW7cRouoJhkvPHkmIUHiRf6MuXvHcSkWlY26mpuwQV2HeSFCqLRvvLi+kZhkDIssCW9zlHkp6BHjRTDqw5oX9j3f2PP7FHMhBedgBhBfN1lV6fAzUxTgkZ0jOO+kVd7fbGw0cvFF0dLGiwixYGESokXjgGQ/IGdoSoaGN7ximWdBRowXK4ii4bSz6TEvYrQRE+ymGy+2kERNFOxqSjRJHcuMOFELa15ElXk0fJF9HNzbDx7Y7k+YPOstwN0EJMS8LPZYHv9+fbcRCfyy3rnqLXa8wBwX7Kre5CdqXqyI5oVSirEqE7s5Xhg1oWwXXTTUZJ8woTHRX0FTMWHaaC/qCexclHkJdsflghbz2Tsures2agTRjRddfKI7WR7iGaTpZp8rSjj/BcDCiYu6FguV5sX3Cjpj/haXk/M6JEGvY4xGwSdcRUHgNtJUsAKKbHIveOkJxEUTgF/AMwhzZYsGjzZyCfxszNzm6SrrGIm4jcRQ1SgopWgv6P7C60d2kCALKBfslv1oI8XLABwvu1DU2W4zei1diAgSF1D+nrbFoo2S3b0c8UVa0LzUcRt1FHWPeeG7Y8QMbtulvqiaL5Sm44aS1O0dqWBoKmy8BAZfYCyPVizc8WywW+4fN3HM8nZvsyfeHw3t4AHguJXt/jzQUdRDizwvWwKExeXRaCP2WwViqLQoGK9aLtqLcU1YuD+Ir/3jeV7Ed6ygKzFdh+0SL4FmwIRyg5Ezy+uWtuHkIzrxUt9E0AuRZy66/fmin2a8MFeOwLyYQgkYNT5WXcGwApLXujS3kaYE75zqbUwcl2eq5mNLwWTNjm2c+LtWLmiomGwcJKVIGK/aWOxtqhSw9eqwNV7SKsJyiIXCOMJ+QEFbIUyybYW4YJenwjd0xdd18BDOC09djdcfuxSAt4DWnNQMuyzDbGB8TJqssJeuiJMOW9h5LHxY8xLs4D7586dC547qSH719AH0eyHQjjAJKIriLxwcq7qK6B8PwqVNT7BbtVyWH8N7wfyXLcGdwkMVw6HS8Twvtkv9tjLqlocB9vk6CULZbrRkaIkvquUQLO8ohnZvBV1lWYQzGB3MeGELTLmgoWKHn7dDiOc2as54AYKFLOq+5JV9OWyH+BoNVdgBsUiXcGFMlzCDLol50VU1tLPNijyaFx7G7Qt2HeqlZ2c6BZdyTQ6rfi0yLzzhm0OY0N12SMh94BLiCwf5PScxL/xdTWMjSoYaqgcFCL59zrz4odI201XFFpBAwyJmlfbboEYWUMFtBMSZl/gCFZ63TCe9sOuU6fibIxHMgNcxNGn6C6mhBnXJOMQdueHVDbIcgvZCwLz0j9cwMmnFzh9UPWZt3zE0FXIv9Y3XcOyyIMOxogTvqoKwNu41axdjuee6jrq2OcPK2igUv3WCrLzcEAi5jQgNRSNVbRfLO4p1F0U/z4uSXJgxSfNie8V9mYvEY14MkXlRcOzydpyypiukeyE0fK+aqoYi4LggOspsJTIvQhb1pA0kkwKEzxHXvKgQ93V8beEGDBAY2h//780h7wVnXqJ6TtdjbwoJWjwREzXHl1coCgubrlhO5o0TsICMF+4XTAMXEwJCdtwEg4f5BkXjRY8zL14FZUP1KkgbqhcKDKxZXMZij9XgRePq5WUIxGhM86L75QGSH6KoeREH+siU5b/QlCKkFQCA4UkLu4Yq3rWIEHHAXkaxiSs7SxgQIo54Equa40ITciJQmkxZFr3iaYx50f1oI64nEDUvrrewcaaBUIr+cROWw3blRYNRm3w3mhQqbTkEKzqLMbcR95E3Nl4CUWWbEWdeXDK9UOlQWyM756jonAt2uUiVP8P2AiuYqYYmJMZgRFk3niW6oKt+ZtisyFp4D/CSj3maF0qDccVFlFxQ7Lqe20hkXrycKY5L0VbQ4RBWgoIboJx54Tk4AFa64mDFCo1VbmwkhWHz6+iq4u8g2bnZjplFG7HNBQ+V5otEe0oCQTGrdNCGcLSiGCHFGTARTLclfhL0NxfsRrUdHOPCpC/u5C2HYElbAYOTUc1LnEXk89uKzqL/nvM5zHGZTmh4Km68qGo4ad7QhBkqJTIwXsMxy9s94bPiZcflwv6wsP1Nxy/3xZr8vvm9hkKlBXE5TzPA0/8DvKq7Z7w44VDequ1iRQPjhdey4walqE9j148X2nW8LN1iBF2p4M2nnoH3ihXtOHJxG/YLCfuizGmIefGum5SE008bIDDeFdPxDVNeVFIEd9MGWcfjgvmo5oUz4NFoI0JZ/h5HDLP32PToOSkNBxWkYaJm+1G5/BqWQ3JVA29544X3U9wQCfuVkzUvJGbwiKIkAGgrxhezmk08LUfAvPAMuyJ0zcv+aYQnIiJMdHzhcQjBpJikLuUhioyKONAtN1yEkLMUAJsYDlYs7BmZCvpCGJxRwe7KzgjzYjPBrulFDGlacN0kmpMnCmP1k9jiYnoZdjlFy+6Z+ucXjZeBcROWR1OWDQ0uZWxX0aOTCWW6kG0Dk+x4x8XyjkKIeeG+cL67TOxLQvGHrUMhtxFPriTCcVmodL08GPUgzkVR0WHUWOCal6jbqL2oY9K0E0KlVT99un8OEhSo6yobiaJtEeLknkfzwjU4oubF8HL52A7xjBfNLwEgvp+8wB4vrmc5PCKFGxg8MV3QB4vKBg5O2aH70VWlbuhyyQu7VQX9UMC8MPqd5XlhodJ80U1LIKirapx50VThPQ5CkVVFSYxia9TH9US5FS/0OhrlZzlsTuLh8wBgqDQm2BVzM7UVdL84KH9fesdqeOWqzpALFhCZl4DpG5q0Qu9cn6d5Ga86MDQ1HJmkxN0mIsQhWtDVxNpG3PAv6qoXAk5Dbp3oxrNmuVjRWawbcWS7zLXJn4moT4ten4O7ULg7B0AQ4aWqaC/qOHFVJ3PLCMdG63KJxgif19PKLyjevCu6mfxoIzU52qhoBKxu1I3E7i3JbeRtSPj64J17zBOwi9FGSe1MYniSEGJeEESHHlbGS8FLSsVj4TmKejiLqCX4Q32DJyH3RJTWb/Pi90XUbLaQ8iJibPIlsUWi4EcbiYtVMADFOjsuoSHBbhJboHn0dKgwo2gIebscRWGLA//dhOng2OUd2DVcid0jM17CbV9UDhdnZMyL4UUbBddN89GyhYmgZrsoG3og2PV2yH5hRj+DKWca2A5kYKIGXv25pKu+Vc4MMna9HYNTuOXxvd7xhFXFFQY+Z1wKelJoZ9Av//n7HSHBbqkQTwHvZ/LM8GJt3nMQvWPV1O+jC1M0bNnyo40CChcA2ouax7yImhdmHCQyL6rq5yqqB0opPnbjk/7faZNSEvzaYCHNi+A28jQvvmBXeK+45sVxk11yfnSLsAvsKht+FlMOzjCFERhBJUPzXU/8tlwC35U05UUL+syLNz7Dxou4KVBjLp1Q/R2HhDYG8aKM9UXuXFhcbwFQlHjUj+kyd1ZHUQ8xL9HFYPfwFNYuiReU5O/L3oMVHJ1QcJIvvKJgd2jSxLgwT0yZDlZ2FjFetf1wZz42o2H/UYjf8U0KENaE8XdHzKLMmJHgYHEeq9ouVnaW6jIvPFSaRzFGF99CwubHclnyzGhhRgDQNAWXvvEYvMFLBhctTSJuPpLKA9SLII1qDfkYT9MBthf0UAXuaLRfIRpt5Ll8zjpxOY5Z1s7aqLD5uWI5vpYOSGdo3YhcIemZUwpMmLZvvLDpmK2FppucEDYJLW+8LPKEmjYJi7UKuhqKc6c0nvbZpXFrNMrQMPFe1Krl9HjgMxeLx3EYOq9tFExgmhY2OPikXdQ1TJquL9hN2uUvbguHioqTIHNBMWGVqij+jhMAhidNnH7UYuzxjBdHcBupihJre1tEQGfaLBqBC0n5df1oIxo1XkTmhQl2eaj0eSevxCtXdTKtDQmiCBRfO8GYF9Mh3u5BC7mNeMEvR0h/nRSFUNR4leCA9g12foHRNDxlhjQvSRXJXcLOnyVt/n1bBvGfD+wMfcbnU+4SKIY0L+FFKJrnhT+W9qLuhdKL7QrXdhE/5zVeGuldpiwXBwUXQZqGKQmWS/ywVkK9d8cz6m1PE8AzAItsHxC4jWyPXeP3zLuYu400wXjh9xLdGUeNiaKh+mOjzN1Gwu6UV/nWVFZzixsvpsOTVqroTGFeeM0oEWKfiaHIqorEEPxoeYB6gQZp0BIYu4KX3TuseQkWA1Z9Wwv1X9HbaPCSEXtHKli7pC0xgk5RwjmehibNiEHPjLWxqs3yYAnMiwIu2G10rzTURrEwZVAgM6juLTIj4deTuTWWtBsh4+V3+xU8fyDQoXCDm0duRkuVJGleHJe5O0XmhTFNij/W+GfiPM7EwMF5RKODpx2oV/gyLaN6MvPCsovXbIJ9Byupmpew8cLacPpRS7DUqzytKixLdM0OC3bZRjq+RvHIskawHBokYgQz4qLeg0ZYAMZLAaNVO6Z5KepqQyuOUaHhz8S6ImmwvAJ0PNqIuxSig0NXVeZTFyY7TRHCKgXjpVxQMen5iqP+YY6OIgsp5O9W1G3kuAQ1j6EoGZp/b6MVG+uWtPlCOrGyrKbGw+g6imG2SczzomtsUTUdN1DpR/NhGCqqtutHG/mCXUXBias6sayjyEK0vazEpkP8hZpQiqEpE5YTcRvZLsu8qfKEaEEoq+m5lERwvYc4uYmTDcCMspFJK5TnhY2bpNwY2YqHWS7BvVsGUkMko1VWE/O82K7vew40L0xQGgqV9twyfDH5wQPbYTqu56Jh9Hoj42Vwwgwi2witGwobuxePgRST1BU00W0EvzCiE3k/fMGux7xMmQ4KghHCBbus0CM7rug902iSuqhosCzolgLBrpBhlwTZTAFWUoAbr7rGdFmceYm2u2hoieG63BCPsprlQtwI0oRFiBnU+bVUhhph7LyFvbOo+xqnaJ6XJ3YfxBlHLwmd58jFZQxOmL7RvmekgnVLy0LbItcV2IShSRPLOsKRbGXDM150BYbODR1Pc5Tx3rgbBwhHcnG9EXMbBcwL/56GzsE2Ze0FPeQ22jOl4N/u2uov9hZ3G4UEu8L9JpbfoEL4fzA2ysKGkbVNCRl30TBsziIDQsLHBEOEQ2Q7xEeTtIHkuan2HazgX+54KdHLwES1wWeM/QlfU1UUVD1xsE3CFcmTMj1H59gkcHZR/FsUZWdFyxsvi9sMjFbsmOZFTBOeBodQaP4DYMdOerlB6oFb65x54WK36EMzNDVWVTos7mOiL0qpXxujXsRU0VBh2m4QbRRzG1FfTFzSw5M8n2TEfBwAjzYKt729qIcqaZuOi/ai7tOKunDfSZQldwkEGXaZ5kUc69xybyvo3j0pPo2qIDDsSgZzG/mCXe+eXRIk+IsLHD3jxWPHAp84D2Nl91qzXQxNWSG3UUFPFuhFGToRihJmwC48dRXu3TIQ+53m9UPIbRTZadkO17zwCq/BM5mohV0mnHlxCcVvn+/DV3/7MiZrji/YbfN87/UwNBkYL0H/ZDReHJaPRPGMbb5wG77biHjGVdxtVDQ0mLbrC3YnPWG7obGFKcS8ePesKAq6ykY42ihB88INI/ZvzWdZeDdz3z5fSLhgl52PJZ/kcwDfDPjn1uNMD89UCwRzA8A1L/FxI763g5Omv8sFstd4ibqeuEuloxS4jaJ5Xh7eMYwNxy0LnefIxWW2YfJYr97RGtYubkNnyQi5hPg7w1Mr+NeMLGC6xtz4fHPH+oUmsE1hiFMnE+yyf4cy7Hp6naJQIJMzMzzTOQc3xjpKTCvG4RDg9HWL8MSegwCCKFTOahCSwLxE5gOen0usbQQwl3MowZ0edxtpEcOb9wmhvKp0HeZFMMBFpBWrLRkq9h2s+hvBOPOiRKKN4t4JVWEh56ZDQoJoHg4dBWc1GZIN1qhrWlUU/309vIwXL3zSjQht+eB9aNuQ90ncKHATrFEWihh+KNHxwrMV8heVh+NGDdGCziveCm4jVcGLveN4cNsQW6C9cOHOkuGnl05DQWMUb5LbyHaYUcLbUzQ0oV6PguUdBSxrZ1EEtkPC9F9kt9FWiJdEEEPkVMUrhqep0CKiNCBwCfgZdrnbSHhxudHk58jx3EbjNRtL2wte5ANjFgK3kebvMhw3EHeJSb3EEEq+UxfDWEW/b81m5xiYMP3FK0r1sufNXB5pG4pwIi0X65a0+flKWJvg913Vm9g5ov1nucQvpcCz7PJnkqx5Yfd30yN78CevXcO0Qp4LtaOo4/MXn5TcaA+DE6Y/kUQFhY3AjcaAefFCpb0+d4m3u3N5qHSS24iNgSmTMVKL21i4NGdeuKaGo6ush/5WFMVnTTjK3vkAxddJiTmRCIXfvwAzSMQkYyzRJPu7ZjO3sNju5FDpeJ4XVUGsbUCYMX2xdwInH9GVsb8D1i6WH8hbhEXNS0FFKNvtlr7J2LXWLmkLMVdjVRtdZZ3NFZPhXC/8XsWFUkwSF6SbIJ4hKrgWFGQmmIp6wGCE3EYu17wExTe5obzvYJB4Ewg0PJ2e0S9iRWfRL2AZyvOSINhN0rw4nr6QJ1LkaCto4QR3aoLbSPg+tTxAipGXJrxX1WSjpmRozHjx2psYbZQg2A2d29OFAcCUFWyudTVZjM6z9LLrqzH9IMAMXHEMKYDvBjy8jJc2g9UhiWQUZBlWXXz97pdTj41azkAy88IfxphXGNF2gtpGFSHaKMq8cHeJODloqoLn9o/hxd5xXwvgEKYpmfIqVKeBi5OVBOPF8vyw3O3FNC/sOFUBlrUXfQMpvDtkuw9xR9BeiIuUFcWrS6SwVNpVO2BeTCes8uc7X559WPcmOPH5qIoC22HUJhc7qwrLMXHk4jIzXghFmYdKe4wSF7SJpRW49qKtGGRDLng75KjbSDRwOfW892DFTySWxNhFJykgTHtGd4eLvXo6Uaie8RJmXsI+dVVh2gQWxRPk9GkvaiGXIb+fkqH5QroOL5swZ16yYHDC9FmDRrmSouBuI8XbEfIFlIevBnleSEKSOi/ayKW+24i7ucarNlwaMC/igrCobMR2h9Gw5pLnuuDJ53RVCVHVvttIhR9mXfAWMK5/6CgaXomJ8I6eCXbjbEMoVFpkXpIEu4J4+KXecZy0OjAo6jHuEzUHXaVA9xNiXnzBrhG4jbRoeYD4fLd2aTl2P4qiYFlHEfdtGcS379nqH8u/E9FV1kOVrFkfUH9zx8d2Gmsggj+fgq7676lYyoKzS1wjxe6RjaM9IxUcJRgvfBPSUYpvxMSIQl/zkiLYTda8UE/zgtD7Es2/E3cbIeY28nVYhOe6aqw5465Mf1OUwrwUdRV7D1YE5iUh2ihBsCuC6cJYX/EkjuxzNVHPRWigSWsv6IkuJF0NF2JUPOkAwMZxVrS88bKoXGCTXVQlrqsYmKjFrG4RSdZoWhIoAPiPe7Zi59CUnxvA0IJohTS3ERDO/qmprN6M6QlsufujsxQXI0ZR1FVPNOudS9hN2g6zrms2QdHQ/IUeYANyeWeRLcwuE0kW/N0h28GJL1VUpMz/ySd2TWEh4pwJ4ZFEHCXPJcDdRob3m5BWQQFMzy3EdyeqoqBvvIa1S9p8DU/R0AS3keZTjg4hgebFW0Q7hF1WQfPcRoLPOhBjsxuq2QQrO4vYO1IJ3EYJoZGJdXloMJGLE5zlECwuF0Lh1orwvGqRCsK6Fp54irqGqhA6HkQb6X40GodLWDgkj3ThLrKs4YoAcxv554skK6SUom+slnQYgMCVxyNJeHQX3w0Tr328xpEoqOeibtvTvEyarOAhdwnwUGkxtB5gxks0JcFfvG5d6O+SoWG0wtLkl7ywW7GSs1iAjrMUjMHR/Ii4dp95ibiNkpgXgQWJZrBNFOwKhsdLfRM4aXV91x7AXMvjHisCIBSyLD6LxW0GOoveXKI0rhB+5OJySGvEsay9gO/etx0P7xhJPK7mGeFx9xJzbzPBLjfqGYPYSErFF8/XH7sExyyPRzxxN5VofBgamxP3jFSwbkmYedE99lF0GwGMmQuMF6+qtPdMkgW7kfnA17yE583opld0CwFBgUX/eyVIF+F6bGCjulcAS1DXXtR9kS8XG0fhMy/eRjCmedGCHFpAuGAvh6LA76tJ0wnVxUrShorFY9uK8XeF94u4xipQ/I1k1lqFwCwYL1dffbWf+4H/d9JJAXVdq9Vw+eWXY9myZejo6MB73vMe9Pf3N309lnXTjgmSCrqK/nGWRMkKMQPBgm4niGynLBftEaqXjyXLIf6iyneYgdsoqXaE51MXJgddVdA/XvOMFzZoWFVjNRQWmoSiHnYbidlmuVI70LwEeV4Y81LwWQUx2zDrh/qFGTkMT0inqqxwHZ/szYgrhLsEeB0T7l4T740xLyRUM6irbOCeFwewdknZ9yuXxCR1huqJmalfFwkI3BdtQphzSPPiBHkgxDbUbBdrFpex72DVX6yMROYlzNjwz3ifiQaS5TLmJZqlF2Av7a6hqdBOXhfEnrzdXNcUMl4KOlPyRzQvYqg0n2iTipDGwXZ9gxMmlnt6qKgxPzBh4iu/fSn1DJbDjEu2qw4StHG3keMZybw4ozjRlwvMSON5Xngyx4IWhFn7zItwz10lI/aO/Olrjwz9zYwXGyVDQ7nAhOsht5HnJtVUJfQsuLj81DVdvnuFC8X9dicJdgX2jEUicnctUvO88EVttGJhSXv98g2qt7Mer8e8eO/AVRefhKMSQp3T0FkycO2fnAqAuQXavEXlyCVl/Pnr1qKzpMcK0wKMsVvRUURnKc68tBVY9nHdF/cyVqHRssSN7jOOXhoK5+aaMu42aivoIWbzxFWduOelgRDz4ldu94x+fn7Fax+fJ3y3kTc+XBKJZvPe7a39E7jujhfZMQ7xsuyGmZfTjlwUuh+eFZ2DRDYVootITBDXqF5fxWTueM5yJLuTmBZs38GK/z4lRRsNVBX8w23Pe+2LMy9cIsDKATh+xKDmuY1EvR8QLh7bXtATE7TqquJv1r2mwnTYJiZPLq1ZYV5OPfVU9Pb2+v/94Q9/8L/79Kc/jV//+te45ZZbcP/99+PAgQN497vf3fS1mNvICmX/A5hV2T9ew0TN9qJJuEHCaUzmtgiOCVTcaaFevPKt7elrdC9HBw/NjB7Hzy1an6qqYGDC9KNCuGWra6ovbk0Ddxv5zIuqwKXwi8gxtxFBSWduIz6ou8oGSt6ky40mMdmQ7cbbngS+Q9FVBcNTFha3FXy3kfhitBfZTpq/gzpnZxI0L2Uhx8eVF5yIqu3ihFWd3m6BGTeEwr8vfk8ht5HHyoh0Mo9KEDUvgR6BTRCmQ3DkkjKrWO0ZmEUtCLPlSNq1EBpEtxmqIrSFFWSrJbiNVnYVccKqTrxm7WL/M1Hsyf+2vP5UFVGwyzUZwfl4BlvudmNiYxqibtNQ0Fmo+vBUsHhGqeWxhMrKIvhun1P7PFSaa0BISh4aIJ7nhTMv3NXAJ9uo5mVR2WgYzVA2NBysWL4Rr6uqL0gFxGrYSmhjwbNB/9FRS3yhc7TCc1qotCjY5e/96q4SPvSWY2PtUxX2u5f7J2KZgZPWLR7hw5gXNulHNS+2S73cKslTes2OlzXgOGY5y+kxNGlhdRdL2f/G45bhsxe9EqetXYRn9o3FjhmaNLG8o4iukhFjt9sMPZbnhZUHqL8oJwlGAWB5B9Pf8IrsvGIxx1knrsBD24exZnHZ/6yoMZdhRylgYydqDso6e4ZRtxF34URFtQVv83PV/z6LR3cyFsohxMsaHZ73/uGPT6l7f9FIHH5NSmmi3oQQmhi1WLEctBc0FDSl7rxd1Bnz0lHSE/O8GLqK7ePwM8hHWSfAizayWIFTkfnVVeYSjTLVouC5XEhjXtQgxwvY+1CzXXQU9djGsR7qh9U0CV3XsXr16tjnY2Nj+OEPf4ibbroJ5557LgDgRz/6EU4++WQ8/PDDeMMb3pD7WqFoo0io9PaJGiZNx9OxsEnK9SIqNFWB6RJ0ZVi0+fO0vF2tTQgKuuJblSWvqnT0VDz2PxodMTBh+kYQD+s0VAWlglY3qqWoa16m2UBcyF84Sllm1UDzovrtOdJ7qbmI2XJFtxF84WwSxLA9rnlRVQVDExZOXdMF03FjmpdVXSU8uXs0uGdNiRl3/LplQ/Op05Kh4XvvO8O/ruNStBc48+KGtEO2S/yQZtPTmfAdvOK5Gwp6OFSaMwNc0V+zXaxdXGYhjl7buGtNRDRcFvD0UoLbiN8DpTSWpZfP2VddfHKsf5nxElyP60c4aykyL+z7MPNSMjSMVlnCpySxcRp49lMiGGZRI40xmunni9bgMR3mEuO7Ve7WSouEYBEGGtoKOnabFY/qFxY8Jc68/NHRi0PROUlY/4ql+PhNm3HeySuhqgrafE0MZ14CVivOvIR3xpNm+B5PO3IRVng1eTiMiNuobHgTvKbi+JVxl5CqKLj5sb1wCcUHNhwT+o4iHlrAU/KP10S3UThio15WXoA9S16MNQ2aomBVVwlAMM7+6KgleNKLzBFx0GOMiroqZONlx5QKms/8+XleAm9tIvhmJokBXuGVK7E8lqStoHtF/9hv1x+7FMcsa4skf2TGS1lIaDdWtVHWw5oXyw3WA5fGDSiuqVnSXvAru3NWMUkzGb+v4N8uDQdG6CoL6PjML57B8Ss7YobIi33juP2ZXkTB8mfpHutZx3gx2OatbOhwSZyNNTQFuycVHOkZDMxtFz6HqjJjqctLXMrPwQW7XO/H1w9XYG/aU4yXKPOieBtgsThoFsyK8bJ161asWbMGpVIJGzZswHXXXYejjjoKTzzxBGzbxvnnn+//9qSTTsJRRx2FTZs2pRovpmnCNAPf/Pg4SzJk2zZKJYIp04Zp2QAlsG32ImkKxYHRKsqGht6DUyjpCmzb9ooSsjepatpAmw7bttmgtG0QEpyDg39n2i6qpo2a5UChBKAeXa9SmLYDRI5VKNNihD4DxeBEDVXLQc1irpeJqglVYSJGEPZSUe9e+LUBQAVBxXRQVNm9EJfAclxUaizJWM20MVmzUFApdIVCoezYb/7FabBtG5pCUTUtWI4DUBe2bYNSAtN20VHQQu3k1+0dq2FFZwG2zeq+gLoAJRiaqKGzuBj94wQV04KCoJ2rOgzsHZkC8e5B8a5Biev/RgFFzcuBoyqI9zklMB0XS0oqXKqgajnQQLw2U1i2A9Nm56uYFlQUYKjAwakacxOAQlcBhRLULAe2baNm2lAVNoFUaiamTAurOgsoF9RQH/Pfc1i2A1ASehamafv3rClAtWbBtgsglMBQKKZM228rofExJY4H0w6ux8XIoASUuCxs3LZRUD3jyA360HEJNBCMTNZQNhT/+SaN4Sg0lbWZUs/wtdk7pID69zkyUfX7eP9o1TeCOSqmjTZD8cdpzXKhUhcqKGqWDdtxYWgKalZ4HAOAprCxrFKKjmIBEzU2PjUFqIq/J25ofPzxq1YBiI8X/rdt2zhqcRGvXtsFQ2V/X/fOU0LvkuXYXv86ofezbKihMaorCkYnazDUoO1/8ur49RV+v7aNmmVjUUmr3/+U4PdbB3HvlW9BW0EP/db20hKE+wqomhYOTppY2VX03imKmjfGAPa9rqmhfgCCeWRgrIKuBu0yNAXL243Qb05e1Yb/emA7cwsKY3SiYqGkAWVDwcEpE5Zl+dcq6QpUUL9fCKFwHAeO67KAh4Q2qKCYqllAwvfL2nQcODjlzbsuihrFRC24ngbg5x96fbjPVIqipsBxHP+5D09U0aZR9n7WLG/MO1ApAXEcOI7L3nXh/VFAcGC0gsVlxuBUaiZsl/3Ocd3Q+5iE0Jxh2aH7o4Sgf8zCWMWCbTsg3rn4MVNVC0MTNf8++fnGKyZKOmOFXJf687jYDkoJdIVieUeBzfGWAyMyrlTqbbi9NrmuC9dxYNuBBUNcFxXTwaKSjvGqJayxFAUN3lzKxsKnbn4GSzsKIITNZ0Vd8d9BEQoo2r15AwAc20HNdrGqs4iqyebRLJhx42X9+vW44YYb8MpXvhK9vb245ppr8Ja3vAXPPfcc+vr6UCgUsHjx4tAxq1atQl9fX+o5r7vuOlxzzTWxz++66y60tbVhYEDFgw/1Y98U0DPB/JIvDCrYdkBFlw7ccd8m9FWBnp5t6B9U0a57qdfH9mOoDTB3UgwMqOjp6fH/V8TggIrbf9ODfftV/MHZjx3jCkpDW1BxFAAaNj/2KAaGNDz33BA6Bp7xjxuqASBa6Hw796hwbAU7du2BM0RBbRUPPPgw9owpsGsKNj/5OI7rAgYHB2PteW5EwbaDCpYUKXpqW1hehj4Vv7nzAAAdD256GAdNoKgBiwoUu4dU9PTs9K+9pV/BAQPYNazg3t/tQUkDnu9X0FdVMFSg6Bl/wf/twICK3/ymB9vGFVSngJ6eXTCrGh575BHsnVKwZVTBK8he7JpQsFcH9k8p6OnZBYAxDdv2MIu7p6cHO8aB0QkNm594AuYOtgjv26tiRAfGbYC4SqzPBwZUjGuA3Uaxth3YsXsv/nD/bnQaQH+/iiftPhwcY33zzH4F450U/VUF+7YBAyMKnnx8P/qGVGx6cA+2DKrosV7G/ilg17CKgybQc+c+bB5UsLwIwAn6eP8U8OKwip7qFr8tL+5TQPtp6FlM2UDvARU9PXuxa6+Ke8e2Yms7a/c9G3+LPftV/O+v9uO/d6iwCWL3x/HsENvxKXupf9+VioId27fD7aeoVoJraoqG+++/D8tLAKCit78fjz/Sixf3q1hRAswBirHdwMBAvD+j6Nuv4o679qB/QIUC4Pbf9GC4BuzpVzFUY+19dEBB7zA71/deUPHRU8K7os29ClaWAXMH6xsAuOOOO/D8IMsSvXNcQUkHtOEdsTaNW8C2vSrKOrCyRLFvUMVWpx8KgANGcA+mC0xOaA3vh2Pjxo0AgNcAqA4DPT2BZoeP6RdHFYyYgL2PojoZnHtyVMXdd90FrrEd6FPxUGU/dBXoGXw29ZrPDygoa6wfnu5VsKIM1Lan0wwv9Sk4pqTgvrvvin03NKSiqgM9Pfv9z3r3q/jtXXvw2KCCYzopatuBHfsUPDD8MnZ3sN883q+g3QjGEQefR7aMKeirAD09W5GGyXENO55/Ej17w5+PDKoYMYPnNzCg4uEn+lDWgDYd2DcFlHqfxqD3fhwcUPGi2QubAP1F9izvuvNO9PaxnE1Jz3KgX8Vv7zqA3l72TonYO6LgRRvYNabgvnv2YNQEnh0IxmkStvUqGKgq6OnZ47+3L40qaNOBxx5+EC/tV9HTsx1bdql4cGIrlhaB/b0qnjAPQFEA48BTAICtYwoeH1SwuACMmMDtd+zHyEENL28bw6QN3HvPbnTUyQMpzhkHKsDOIRU9PdsAAM8NsjbunwIKk70gfRR9zwXHbB1T8FIvy5Ui9v39D/Zh2AQGKgosAvT07EV/f3jd6u9X8czmPmiWiv7+STxl9aHDANzdwfjYOQEc1aFiaIiNkb37Vdy9cS8Ejw62jwNDoxpWlil2jwNPPNaL8ZcpXuxXUHWAIVPBbzfuQacBbHxBw0mLKe63dmBpEdgypODARLAucOzZrcIaoOgZY+uN6QKTFQ1dqOKJpw7C3jaV3qECZtx4ufjii/1/v/rVr8b69etx9NFH43/+539QLpfrHJmOq666CldeeaX/9/j4ONatW4cLL7wQXV1duHXkSZxx5tFYMjSF7jccBQBQnuvDHb0v4fR1i7D2uGVYTSi633g0ft7/OJZ3FKCrCtYtbcNr1y3CW45fjl8d3Izu7tNx2wj7XxF3jj+N8y98FX598Bm89o+OhLt7FG89fQ3Gaw6+v+UxvPlNb8S9v3kJp7/mKHSfHlRKPTBaxX9ufxTd3Wf7n2393TbscwexYkU7Tly7CM9W9uNVrz0OODCOwW3DeMPrj8fgS49ixYoV6O4+I9Serm3D6Nu8H8ev6ED3Oa8AAPx6dDPOOfcU4LH7ccbrzsSeg1UcubiEFR1FjD51AN3dgVja3HwAJUPF/uf68fa3vQpFQ8PUE/th9I7jmGVt6N5wdOiez7vwVZh6uhenthdw/skrcf3OTXjjG0/CcwfG8dKTB9B93qvxwNYhptcZrqD74lf6x9928EkAQHf3H+HpfWO4afdmrF//Krzl+OUAgId/9YKX48XF8+O96O6+KNTnt41sRslQcdqRnRjavQXLVx2B7otORWdJx20jm3HKK1fg9yM70d39Fuy4dzvOOmE5dg5XULEcjO8exVnr12Hi2T6c94aj0PvwHnR3n4Rn94+htmUIveM1vPXc4zH85AGcecwSPDL1Erq7Geu3Y3Dq/2vvzaPlquq87+/eZ6rpjrk3N/MAISFMCQQCYQoIJHBtHhQVHniUoRFBQ/eSNCK8LQJNr4XdKq0v4rAcEdsXAVuUph9tDBBbwSBJwDAlhBBCyEBI7lz31rjfP/bZp85YdU5V3aFu9mctFrlVdeqcs+ucfX77N3x/OLhxN7ovLJ3Lm+u24+zFU/HS029Zv8XBwQw2/347uruPxc5nd2D5ke1YOrsVjx/ahA9/+CT8pmczlp91NP7p5eewbG4ruruX+V7byqv7MZDJo/ukmdZ5974/iIVHTceS2S1Yd3ArurvPBADc+dIzOO9Dp2FqUsX331iHjo5OnLtyIf7nyTew5MgpaE1omNYcw7YXd3uuYTcvPPE6TjplFjbmd2IkV8AFq0/A7p5h7Nv0HuiBIXR3n4j9z72DHVsPoLv7ZPxk9wZ0d5/q+I73/vg2lsxqwfJ57fj1oc3m730isGUfsoUiMrt60dVk4OhpTXhz4250d59kbTswksNfnngD7UkNJ8xqwcv/sxMnLeH3bspQ8dbmPejuPhGZXAEP7n4B3d0ryp5PLpfDU089hQsuuACa5v80+U3PZuxuakVrC8FMQ8Fp89uxfuB1dHefDADYldyBi8+ab4UC/vj4q5jXkcTM1hguOs4bBrf2/dIeaApF9/HTsP+5d7B4WhNOO6I98PNN2z9ATFVwyrw2z3u/OrgJU5sMdHcfa732whOvY+XZ8/HeC+9i9QnTsLCrCbvW78BRXSl8MJjF5SfPQs+GXZjVFsfKhZ2O8RDzCLbswxGFIrqXzvDsU/DzfX/BJauOdSS+AkDTwg9w9xNvWNfhrw9txlELpmDelATakzp+//r7+NCZ8/B0+jV0d5+AP//mNSyb24ZMvoDWuI7tm95Dd/dS/N+HX0aRMd9rc93QFpxx9pH46x92oLv7OMd7M3f34X/e/ACH9g3gby46AQeHstj+zFswRvLo7l7iey69L7yLXYfS6L5wER4/tAnd3Scht3k3Bv+6BavOOwcvP/UWuruPx4v/+TrOP2MepjUb+L99L+OEY7ugm78lAGza1YsXf/8mTl08FW/sG8Q5H1qA7+98EXPndaAnncXqVUeXVbG2z9+v7x3AwKv70X3+AgBA/uW9+Ms7PRg6NIwFc1tx5lEdOGFWi7XNH978AH9evwMtcc36jl8f2oxjl0zHSK6IN/YNoG8kh+7u46znl+A3PZtx1ulzsWvDu8jki1i8sAMzWmM4x7w+AGD7/j7sfOI59BlT0d29DE898lesXn2Mo2pq065e/H/vvISFc6dgxwdDOPP0RVg2tw3pTe9hOFvA2wfTOOv0uTxp/4U/YpAmcN6HlmF6SwyJbQegvd2D7tULHWPyyu+24fiZzdY9NZwt4K6XnsW8mVOwaMEUrDramfgcxKiEjey0trZi4cKF2L59Oy644AJks1n09vY6vC/79+/3zZERGIYBwzA8r2uaBk3TQAkFKIWuqdbElTC4INvcjhQODOUwtz0BTdOgKhSaqphaCwQx8zsIoVAUFZRSz+RnaApAFeQZwMDDGImYjmyR51YYusYT5mz7B4B4jOef2F/TNRUz2+LIFxmK4CqouSKBoak8jqnzzxJCoaoql0i3zklDtsCgqqXvJISCEV71wwhFvggkDR2tyRgM3XU8hsY1NxgQjxlc18IUgXMfe1NcQ6ZIsKt3BKcc0QFN06BrCnRNg6Gp6Eln0dGcgKGpvNrHtb2q8A63mqYhpmtmtZBmfUbsN2looCCeMSeEeyQSho5CkcfOmxKGlTTMzBi5pmnIMyAZ15GK5fHBUA6aqiAZMxA3NL4949/PiALDjBWDqsgWgWRMxz+sOro0xrHS5wVFEMQM3p3ZGnelAFVRzPNTwYhiXYuaxrVIhvM8j+TAYC7wgRrTNfRn+HmIihxDpfw3Vp3XY9JQoWsaNE01qzcIYoaOvuE8muM6YrqKIggI8V7DbgxNRc9IAe0pAx8MZkGoAkIV6KpiXXODWV5RoWka0tmi5zvzRYJkzLDOF+CfjRkaMukcAIK4oYERao2LIEUUZAv8HmiKG1wTyNB4XoGZV6VpGgjlCbeVzkeg2a4xN4RQHBjMYihbwMlz22DoGuK2e+Tvzl/k+LyhKUjnikjG9LL7N3TNutYLjF8r5T7/ocXTA99TFcVxTACgawpAFAxmC2hvipv3oop3ezJ4fW8/PrliPvKMIGF4j5NSPq/1ZwqYZc6BQSR0FTPbU9Bc+W/nLJqGP27vsballK/4mxIG2lMxDOWKYERBzDzuVExD3NAAQvlvTyl0TQMIAfG51wE+HzBCoSmK5/0ZbUkcTO9FkfH7M88ohrIFaKr3s4K4oVm/m7j2BnMMcRVoTsQwkjd/L/C5PGboPNBFnM+RuKFhX38GXS0J7Dw0jCLh+TxFEHNe0KFpwY9R+/xNFcVxzLqmom84j3yRgZhjJO4lcS31pHNoTRiOsc8UgKa4joShYci8LwmheG3fEJbMbgXAr/VETEdXSxy7e9IAoY75FwAWdLXg3BkMvz5k3l+EwNB1x++vaSqGc0W0pQwM7umHofPvMDQVClUQ0zJghOKdnmGsOHIKnn/roPWZ5rjhuZYBPve0pWLW6wXwvKKmuOaZe8sx6jovg4ODeOuttzB9+nQsW7YMmqZh3bp11vtbt27Frl27sGJF+ZVVOQjxquWKRKFZbXHs7xuxSgCFTolfQ8K02YvHjaiAyJml0rxah2fTi6TcrFk5ZEdXvFLiCiXobIpx1VGzPCydLVgJZuJ43BLK4pzspdICoZUh+v3oKsW8jiRuWbXIs302X7QaKor95AreLHORFLfrYEn8SVdE9QdBz1DOEgwTDe3sTGuOWUnBVsKuPdPeqjZSA4W5hPx9Ed5k0py9VNpsLBc3+/+oCsWiaU248ewjHQm7eSthl78mhO9W2lYjuuqtNhKl0oSURKXsPVDs+7CfS/9IDmcv7PQoL9vhOi8lET2FEkth1N6YEeAVR1aZPHgCoEYpetJZpGKa2VyPl6ZWQlO53lBrXOcJp6ZYon2M+4dzVgLwUDbv6bni11OKj0dJb8ZwSaTbP5M31aXtInWaQh1Jwm6Rutrg1Xi7DqYt1d1yfcw0hWJgJF+x15ldpNDeebcaFApHabY4jlyxiP5hZ6n03r4R9A0LpVjmmxwZU7mC9aGhHNorJOzed9lS33OllODLFzsraYQ4Z5NZzSOSaQHwB5aoNipyyQRC/Hsllc7Rm9Qv6EgZ2Ns7gv5hnowf1xX0D1dopaKWRNTEvvuHc0iqzCrHB0rtAUSCsrv/kKZQ7OkbQWeTAV1RrErAfLHoSNoPg7tcWaEEh4ayZmWeV6Awky+iJ+3Np0lnC0iYPazEsb6+tx/XPfiiY4znT0mi+3huKIcRoAzqbZTO5tEa13mptCKeqwnM60haGlc7DgzigmO6kLdVGx05NYWVizrdu0HCUBxJ97xIAWiKWG1Ud+Pllltuwfr167Fz504899xz+OhHPwpFUXDFFVegpaUF1113HdauXYtnnnkGGzduxLXXXosVK1ZUVWkkIKYh4jZeWuIaWhMa9vWPICnkvwnvzUPNklR7hdJQQF8jMaHmi0WrhFczDReRqS4uajuqWfFiR6Fcqp9Y1TZcR0FTiKNUWshb2zHM8lL3NZg1jSBxfGKf7uxyP/XYIL0boY+QsfV2Eecq9DGEIZhxjSPAdSKE8JvVmNG2D0J4WbG90scOv/6J1UWa2UThAK56Kx6KWVPMLq4pZkY8P8aWhHigl3r3iN8kWyhawneOMVK8YyRufFFezPfv1Hnxq/LpH87h7KM60NUU87wnUG0aIUIwS+jZ2HVeAG5Q2rV7RPfo3nQOKUP17cMShEYpN14SmiVj7lcqLQzQXKHoOUfelsHPeLEr7PqXSlsl72a5fKlU2tmtVig714vhXAHvHBqC6KXlbupoR7eMl/L7V2jJQMsVmee+iwL1OV9RTs+7n5fuxf39JeMlqNoopnMRt550tmKVViW9GTvDZjNTofMiypgBWFUodvFGQkjZB6hiLgD9jAFdpXh5dx+uM8vOdVOss1IrFaGxY5gGnKg2ss8jdrVxwCskJ9ofdKRKIp+iRYJbt6US7vYAlBD0pLNW1Z97AZk1j9lt9A2ZYx/TFGth9MiNK3DaEe02RWWGtqSO5fPbAfjP8W78SqWFGnRLXDVF6vj7y+e3Y/n8dutef+vAEFYu7LSUqgFudC6b6w2ffu6cBTh2Rik0RMyqsXGvNtq9ezeuuOIKHDx4EJ2dnTjzzDPx5z//GZ2d3AL7t3/7N1BK8bGPfQyZTAarV6/Gt7/97Zr2yR9aOcfNq6sUbaba5L7+EUvnRTx8AZiel9I2gz59jYDSSjJbMLsZ55nVRE4zvRF+N56meJvGqZRYk0iuyJA0eKl00uCt7MWx6QrXobGjqxQjebeHh3tbErrKvTmF4JLJkoZJ6XupOTG6j10outpf1RSupqoQglZzFccVdgtochl9M1vj2HUobY0D/2zpfcU0OOMa9dww9nOzN9SzIx70QOkhmtC58dKaKLkdudqrEBBj1u8lWim4H15+RqMolRaTsaEKMSbTSKQlnQ/7PDMwkseUlIHvX3VywPk59TqyhaIp1FbqhGyfaFNGSW6b2IyXTN5sL5HJY2CEK5pWQlMoPhjM4NgZLdYxiO+zH3/KzN7LFZjDkBXH6/YSiO8WpdJ6gOdFkC8yUzSsCF1RQFD0aMuUKwGOBlc4/mAwC4XyUs75U5KBn+ael5zHwHWj2jpxhxMIDEaEDZ3fb/fslTyme/uGLQ2TbKHgu1+hfdSTzjrui1pgTJTrKlZrBHtz1LOO6sCUlI5X3utHvlDyHBSKJW0kN3Z9Iz8eu3GFpUcjvqucJ2HB1BS6WviiQehO9Q3nMd/1xLPPI4ApJGdvM2O+1ymMF7MvnCiXjuJlcxsowvPSkTJ8+4plC0WHyJ6gfziPlrgGw2w6CvD5VmiexXVnbqmhUlNLLIzx4nxNHG5rQjfF6nwWxIUi9vQOY3ZbAvM6Ep7vqERJy0qUwIej7sbLww8/XPb9WCyGBx54AA888EDd9pk0uBtRXKwAv+haEzpSMRX7+0ZsIl+lLrUjOWcvofKeFzNslC9w97oZLhLeCD+hN41Sz8OREpvxYnpMhnNcBMjQFOsC01WKjKvPg2Gpr7rDRsxqDin6y/jhp2FCCb9J/PrFvLGv39HszO55aUuU3NeZXBFtCec+Z7bFrZWPEM5yCzTx81d9L3bhwtQUrvPipmAaIsUisxrWxUzPi12Hw+6NyJsCYuLhKjRxPGPk43kRXrZsvggYoi+WbR9+npeRHKY2G2XDHprPg0/oN4h+T4KEXpqshPS7kKJPGqoV0gyDphJ8cDCLloRmXd9eFc7SZJbLF00J79ID0O55sXeN1kzxRhE26k1nAx9KuULR0VeKgXnO4aQ53sTWaikyhmnNMVDTAP+7844K/GzosBEthbqCvFFhocTrDSrJ7DvFDPf1jViidYGeF1NHanAkuO1JNQxnC9bvZu3f/P2PM5Vm39g3YLUHAOBRQbejUOrbYkVgN1wAr1q2m6Ns3dRTBu/p1jecQ8LVAzPrMjbdInWaqefVHFctkU+hbuxWja6EPdQM8MXcoaEsuppjvhor2XwRXc2GZ0z6hrNojWtW6wtBa1xHbzqH6S1O40VXKZeaKKMhBvj3NhJ/t5jzveYygET/JgY+px8/szWy8S6+sclQHQ1tKzHqOS9jAe+4m3PcGIbwvJgND52eF2qFjew/1mBAXyO77HrO9G4It6iq8BwKvxuPUoKPuKTLT5jVYslIi7DRcI4r7K5c2IkppmHj1xBM9DZyy0Fn80UkDcVSnQ1ys/s9mBVCTM+C87NJXcWGtw/h2BnNtu2JZby0ODwv3jj/8TNbcN2Z3M1b6kRa2okIm8V0xXM+dlSF+BgvxFRmVW3hn1LOi1sU0C4gxsM/Zs6LTVnX7/MC8VAXhibgjI1rPt4agPAOvbHyq13F1qMmV+DS8kL7RoSOBEdPb7YebASmG9qcTFKGast5qYwVNoprlmexXAw/Wyh6rh17zos7pFFS2KXoH/FfFDDGH2hWXykr58V5DjdfsNCzbS3MaouHcvdrKsFAJlfRGLEr7PYN58pWn1RCIfB4ekoy+859vj+QsQz1oPs+buvsW+4+iwIhZksTKz+QWLl2dkptE+x5YgGeF0V4XsIdQzlDyE0qxr0X3OBxvucO/RRc6tSaQjElpVvhy6w515XzJgZRcIVlqBWS0az2AHYy+QK6mmOeMetN5yzVdPv3CcFWN7pCLYn/cvj1NhJTdmvcv/eeEMYUL3/14yf43uvlEOedHO+cl/EgqSvoH8l7cl7aErr18EjZE3Ypf2jbZfIBhqFMIcB4KU3ufBLnK15VMTstl7nxPuFqGnfyvHYc0cnFGXKmy3zYvLAuPG6apTzol3vhbg/AKSW+iuMLmmxLxos998Q/YTdpqNiw45C1iuLjUOpt5PC85L03hqZQS65bvGc3/EXCdNzW/dpxVuZrgWGjIvc2CW+DiHEPZkr9N8T5CfJm53EuX18yQp379R6MMHriuoK06JNii40LCXF7O/i4rmB/f8Yhg+2HXVFWdCsXzQ5F6Eiw9oKFlhEucl6E50Uo7LpX6EFoipmwm9D5w9HX82Ifg6InkdmeMzSc8xovXGGXd8P2664M8N9EbKebYdgo/U2iwcdlVluiYosBcTyhE3ZNg3dgJFfxNy+HX9jInhAsUBV+PTbFVIzkCoH3fdw0uKM/asvjDk/7havdLQz8GuEKRM5LmN8F4HNZJU+CoMkn9OIHId7QjqZQy0AUnmuFEt88rkoUXX2TRPuLuKaYrQOcn8/mi5jmY7xkzfBtzJZmAHAjqG8469kv97yUzxESuOc/MceJNAGvSi/lHi0xL0WNGaHkcUoZqmeOKbtd5D1NQOK6ir7hnCOm19Ucw8fNxmIALIlwhTg9L/YfdDCTKxs2yubF6pOvukUoQVjiYW88QS5fRMLgk4vfReGfsOu8wQnhFnpC44mRmQD3MWA3iEpTmRXy8hgv/KGzYGrKcUyi86mwxK2+RWWWTCKc4LhxCR//uKZYCVtOuNGiUb+wEX/QJg3Fqp4ihFgJu0GTWr7AQxvO6qDKv1mhWISiECR11eoDYl/5CS+ZffWZ0BS8319y6wfBK0lKiceiG7ZVaRRwfMJ4UW2eF+HCDYOm8pyXlrhmjYdf/xN+/rxfkjCmDwxkcHAw4zD+ePWJap2TMIZ0haJ/OG8lzNsRpybGLMjzUm9mt8dD3aulsFH5aVJVKAqFknchqL9QGPzCRu7+VwD32HWmDLTENfQP5wLve9FBuT4+l2D8PD8ifChwJ4TbETkvYR9+cVuIvRKpmIrBkbzvPOO+DNxJtYbKxxkoLR6DKuj8EE01/b5boQQtcc2qtvFL2J3W4jVeBDFXvmBrQvf3vKjlPS/CaPN/j4AQWM9Rv87UBwYyNXkbxRwcNWF3UhgvPOcl57gxYpqC04/ssDwpCc2W80JLK//Sj8H7mPh5XkQFBKVwGBSawiuX7GXHUeDxfsU3mUpXia/nZdjleTFUPsEmDMVM2PUvmeTH65/z4peJnjRULJ7W5DCquMYKj9UKS5wSnvOilTl3K2HX4TI1w2Y69fW86GrJM5b3aTSYE2Ej2xjFNOrIiHeTK/Dj9A/zBJM3PRy8rJ2v4HifGREHplY1jpjA47qCff0jlT0vSmlys3JeVMVK1g0aVst4Mb0zCbOPiD3HoByixLo5plo5FXYXOp+kFeu4AFirome2vo9ntx5wVIANO8JGJe+JphDT8xI8DuIeNFRqlbGPDrw54xkLOjCvo3LnZZGwW8nzolJiGaC1ohASEDZy/q4aJehoMtAc16wGmkE5L/v6hmt6uPjhLIBhvjk3KnUaotVWG/mRtCWvh/ns/oERh/fPLntgx52XEtMU/OvHTwAgwi+8Kq5S52eBfa7xJOwSYv4uxDdhN1Mo+oaN7MdmP1aesBtgvJSpztJ9ngsCSmA1+gXgMcwtyYU6JIM3Gdr4d5Uea3jOi3/dv6pQtCd1x+pfoRQKhad8NyhhV3QmdnfQFMmfYr9Rav4BM9HWbM/uzuL2MzREI0a7tyCm8ZBZQleQK/KE4qCEKUP1KZUO8Bq1JXQsNQWPBNecPs+8mah1sYqwUTnDTZybfVUlwlX27tee8zd/n+E8sZJ/BQUz5Ja1VV+J5m7uUJDVTdhcFWvUuSKsRL7AJxZ7NnxvupTbYBkvtgk8oSvoGw5RqUJtmhOW8SKqjUjgBC2MF0LE6o1Ey3lR+flwvSJqNZoT13KfrYOxMFrsXbzdk2ShWMpdsXu2VIU37vPTTwJKJfCiMs9ejj5anDKvHUdPa674OU0xvX8VPCmO7sk1ujgoRUDYyKnfo1BieV76hnOB931cU7DrUNrTTLIW/DSo/Dw/7rBR2ZyXiJ4XdxPNcjQZKt4+MISptjGI2TrQ2/ErWZ5i87wMZbxzdTk0WjLk/XRexD3ml2+SyZlho4CLKqmr0JXSfdUa5zkv3CizpVAoPGE36LhFIrIfCuWewJglv+FND6jV8wLw+yYVU0N7joFJYrzwnJdc4MVsv2hFnNHKebH9oEO27tN2xAPGnUTLk3ZLnpeoCXHCe5DOFqCrbs+L19AQr9t3E9PEw0G1XPVB4+CX86KYRoR7UpnfkcSXLz7W8doi0xNz6hHtuHgJlxkXCbvlJng/406Eq+zaJY5jNY03jVIM52HrDMzh4maqx8DjeTnOLxS/WM4Mi7iF0CohHuoJXcGQ6Xmxd+kVD5eMy3gJ4wIV+Sb8nLinSeS8KOU8L4CVC9SWsCd5h815oTbji5g5KiXpAHviqTBE7MZLX9oZWyem90d8Nz8nfq/1j/iHjezVb6ILuEqpRyKgnkS5RXW1NGmXQ6WlztkhF+SBUEK8ia8+oTRV4XpRwngJuu9jGsWuQ8N1NV5EebT9+IYyeZ+wkXO+LNeFWRFaUCF/oISulF0w2UnFVOz4YAgdqZKOTSLAeHGHduzw8EuwZ9cP+2/n1pChVHhemH/YqGCGjWz7E5WPALB4ehPWnHuk9V5Lgue8FJhXsDWdLQSWqXNhTv8SZUoIYqpihtuJZ2w0heLAYMbyxFcLAUytsvA30KQwXhKGN+fFzpJZrda/RbWMX87LjgNDnjIzgLv+8mZLcbuFSgjB+Yu7LAMoWtiIWKWkfvXzQeW3Ih9CIPI84ppiW/2VuUhdD7eSSJ3380Hn0xzT0GGuRoTxUu7cReKpU6AJtoRd77YiBKIqBMOFUthPwKuNSjkvAiGQZYerdxZKCruRk0J5jlPSNDQBoCedRVvSx/NiroTiumpppJRDs61ihX6QMF4ICf4t+XjyfwsvmOZjnAah2rxn4iEjyr+5gnIWzXHVPC5eTSAmuGzB63mhhPiEjfiDYGDYP2wUM0UXxTHoKrXutYmAptCKISP+OW68Cj2gWhAKy3ZKOi92458nkgrjBfC/VuKagnfr7HkplW6b+9AV9A7nPEaXYT0U+XGVW1iVdF7CHUNCV8NXGxkqdhwYdCxi42ahhBs/z4tAeF6iiCZ6wkauvD+xQPDzfoucl/9z6hzrNcZK9zshxBHGaTE9L249HcNM2K28qPVCCKycr5iqWAUC1rZKqWqxFkrijIeb8aJ7c17s/IsZswRKxkvJ88J/0CLjMWM/FUoewmC+AmbXnjHf8hxEydPTVT7Ba2YNvtvw0hRvzgvALxb7NRgzqzl42Kj8D+9XwUQpNwSiJhsLuM5LwWMwuFEV6pjYRYgnrgcbLwT8t0rn4Qk7FIoMCUPxuDuF8q+dma0J7OkdMZNs+QNpxGfVVQkhYw8Iz4TT4+EOGzVVKJMGRJmtUADmIS/DrMBytwewQ0nJk3WiqYOiKYSX3YeY1HWVoNU8fhH2EAmVqsLLvFOGCpXyPCt7GaNQ/rRDCCwDxb7iFjkvfp4XQ1MsRVBN4eJ8UUN6USgUo13nYY0XIRffP5KvmKBdCUp8qo0owVA273j9+Jkt+JsTZjiMFz8s4yVVz7ARdXhaE7qCvnTW81BvjmnoH85DPJDKabOIUumwYaOkoQR6EtykDBXv9ji9T3GzLYubcp4Xw/QwRfK80NI8zr+79J5I2BUhcvfjSxQ0nH5kh3ObgPwSQ1VKife2c9DMUumyOS/lwkamMZ00VK+WmcIT/2vNeSEkuhjlpDFehkLUsQOwqmUsnRdzG0qAT542x3cbsXKPaf7eECunI8LEKCSrNfPh4JHyD/C8GBr15LwMmDkvlUIhqkI9SWo0IGwUFlE1VKlsUaNOl6NoqWCoXmMDgCUzrSk858UZNuIJkkndm52e0FXP6mB2exzvHkojZxoHM1vj2N0zHPlcE4bN8zKUtcrFhSFql0hP6AqaQ3he7BoeOdOY5QYqAaXB1xQFrMn7jr/hfWd4bLuykiZgho3cnhezgkqhFL3DOSR1FZpKkc5wBWV77ktvOucIwVBCLO+YPSynUF5t5FcqHbNpkMQ06qkEqzcjuWIoY0TADcnKU6QYv/4Quj6V8K02UigGR/KO19uTOuZ1JCsbL7qCg0PZ+npezDJtQUJXfT0vzXEN/SM2hd0y2ixcpbwQIWwUzfNSKDJMtRlwgWGjYrDHWVep+ZyJ4Hmx3d8Fl3elNaHh2BnNNq0UV8KuKb5ph5LSoiOIgms+t8Jd5TwvgQm7xPK8+HmSNYXgg8Ha1ZsJvOHSSkwK4yVprvjCTNpW2Mh86Iof9J8uOS5QyVMzHwru6haBuCaiGC+6GYLSFOJbxuYOUdm3s++HVxtxt3yYFavZacT6W+SeRE02Fgh5+kpjL8ZcQAkso8lPn4KXzXIBQG/YiKFQFOrEeceNam+xIJjdlsC7PWk+eSq8aeXOg+nI55q0rdbsOSFcxZchWyhNNnFNCfUgs2t4ZPO23kYVE3a9BqdmVkOEUbhUqU/Oi7nqVClB/3AOKbMSKZ3NOz0vvmEjOMJGVsKumbDolwgfM/UtgJIOkz35td4M5wqexO9y6Ar1iBj6wXvdFGsWqAOAY2Y0WyFZ6/sVgsFM3jf5O4znBUDdE3btntC4xpPT/fq42aty8mVKpSsp7LrhOS/hHl/i2vN6XrzaL379fQTCCKjkZbbjCBu5vDqz2hL438vn8LneRzndL8ymUlLRUHDr6egKtYRQfc9LoZ7wu4CQkmiirwaayvOfavY40lJu5M83vBNum5r2OEEQq/JQnhcRNqKwBIcAYEZrPDC/QKXUUhD1WxUSYiYBR/BeGFqpT8aIn+dF9Srs8tedom4xjYfMkmZjxkpwMSm3ERHeXeuGEn+ROjdC4M6+Xc5M0PNbDesKT94shY2cN45I2H2/3+myjOle/YfZ7Qm8e2iYJ+xSgpShon84FzlUxj0vpkidQw6/pNhb8ryoVs5IOezJnkJsz66wG3SI9rCRQFNoaA8kDxsJrR5a6m1kXsf9w6Vmj+lsAamYWsp5yfOO3M7jKa3GCSHWRCh+Cz+jgScC8vfFA8ZPWbpecHGvaPkKYTwvIum6fySHlhC/eTk+vmyWx3jRKJcA8Dv2lriGdw6mbQ35nMQ0vgioZ6m0plCH8ZLQFfSmvcYLIBKYbTkvFXobhQ4bRfC86CpFU0x1/DYJXfXNeSlXESVyXqLI3zvCRkX/ilSro7bPbj2icZRUzC9x6+mIZ0k1OS92T6Cf7IMIFdZ6fRmqqDol2PJeX6ht6t7baDwoSf9Xvqjsnhc/WXs/dJWvPnWFYqjM90b3vBSsMmy/nJdBn5tLJHMKRKl0XFdCiXuJvA8BJcQqBa4G0TG6kitVVYjjxhVdZv0URQFYHYY1M2HXHXZgjCGmUbx7aNiqtgG4HLp7cpnVFsfunjTmtCes94T6axB2uW7xIE7qCoZ8Gof55bzEQ+a8CLVfgBsv9tU1F4jy/12Ir/HCGw+G8UAumtbsqFIazhWsahCF8JwXXkrN8y3s6peiqsq+UuPVRqrjb35+fDz8PS/Uel9MjKMZNqKUG7dh0SJ4XnJF5igvryeqQjBoNvl00xTT8Mp7fXjwb5f7bhvXFHSkjLq1BgD4XGdfcFgJu4EPddFZOjgkU9J5CXcMcV2JlHR/REfSMQZxs9u2G3dvIzu6lfNSXdjInbBr/0wm72z7EqQjUy7nRXyX25Mv5qRyRpldcsKxP9vi8tbVR/vuL6ErFSUhKmF/BpTzJNqZFMaL1QAwpOdFrC7DtAnn38svCK1MTK4az0vRthLx7daZ9xcccpdKD4zwUukwK1Z311sh1ldtkQQ19XIqPTBVSh0JaQrhblTA/8Em9HN4ewASWGr7/sAIZraVKsT8wkZJg6+y7KWa021NPN0olPiuEnlZu9fVLAzQjE1ldGFXCnFtpuezbvhkVjJeUoaK04/sBAO/iYN+F8XnQSC0c8LE5FOGipTZpsIKG5nSAYqVsKuUPC9GqSxd5PbYJ2J7tRFQaqwp7kk/nZeYrTLs659Yws+LEuu6qDei7DMsmkJCeWpEqKtvOIdpzcHXVbVopgE5Q/VWQiqU4E+3fSjQGxDTlLqGjABY/dwEcY0n7FZuSEmCc14Ugmw+/CJqYVcTBkbCN/H7xw8f4/g7oavoTXul9IuM+Uo3ALawUYTJ0t4R3F0qLRApAnax00JA8QX3vATnvDTHNBxyNUK1jJdAo4yYVahe7Ankx89q8byvKZU9QWEI4+H0HFvNe50AKJSElosWybpc8C2cNouYwMtdtCIUFRZd4Q8GMem446iBCbuqM2E3bk/YDRM2KjJH2EgITtVSbZQN4cFyawSInA4A+MblSz2f556X0src7+GnKxT7+zNOz4uu+saki4yZ4Tn+3ryOZGDypq46V3ViaMQKxb0qEgrMds9LU0zDMbamluUQX5ctMGgqRVtSR3tS9zRmtEPgv5LKFyobkm5E2IN7wrjBITwvukqRNsUbM7lSzktHynA8rHi1kY9GkhJsvPB7ln+H3atgDzXUE3toKwx62FJpylfX/cO1Vxv5oVKKwYy3A7q1/zITj6YQ/C9Tk6lecLVpZwimbzjnexyqrUUADeF5CRs2WjStCSfPaw99zMvnOz87szWOXYfScF9nFcNG2eDcET/s+V9B362pXKVcvOUnAihQKuS8JM2QuKNJsVmhGjS25cJGTTEVnztnQeD+eOJ/bRovAKxFhb0CuBKTwngBzNK5ECdNTc8LIST0/MiTassnQqoKjeSaNazqCmLuw1tt5JewK/IhBDGzvUAiZNgo5xKUI6T8DVsJv47RfohwXWm/pVWYr6qxyj0vYny8YSP+mQMDI1bVDyA8L95jOW9xF578615r4pnfkQxcKbrL1N2OgKFswXHMfmGjasi5+sOUK5VWfMJGgFPEKiwlkTpm5RmVSqUJ0jm356WAzibD4Sp2e174oRGb8en9jQ2N+k5U7pLSekEJQonOCcKWSlMzMbUeCbt+8LBR5e7WfhBC8Omzjqjr8YjFokCoSftd+y1xzQrPUFLG80IJsvnw1Ua1Mq8jiTf3D3rEQff1jTgWQ3YMhTdmjZKwa89d5F4dH+OF8rCRWKgolJreR+9nbzp3QVnvXsrgv4W9jFyIPwYeoyKqkbyfoZSUXYTpKq2r52U4V/DVWvNj0hgvcV0J5S4XoQilzI3kxvK8lJk8xHeGRVcodFPtFfBWSoUVqRNubR42qux54WEz6vgbiFYpZUdsV2m1L5o6WvslpKxOg2F6XsTxJW0PP4USFExdnv39GUtvBeCxbD8P2WUnz0ZcV6z3jpvRgqOn+9+URpnSQUKcZdL83IjV26ia2K8YFk9Ij1bIefE5z7ChUDsiSVZUGylEqOKaCbtmzy/heSkUgSlJw+HqdYdkuMFXqibzOyYeNvLeU7UY0+Vw52pUwtDCGS8CnrBbf+OFK9gGe17GGk1xVRvpCorMX6ejJa5ZBji/ZoOrjTIREnZrJWV4vUVpc1ES7JHlidNRFgdcMdrmeQkIG43kSjknCoHpefEuRud1JMuOUcLH86IH3H/29w8OZkOJavodez36Gol501ApZrSGC71OipwXwMw+j1AqrdDwvYhEqbSY5P0qJ6rJedEUah2zR7nQpzEjAKtpn/1vgBsxvNdN+f1yFVNnrgIQvamkQBhClQxB1R02CvAcCDRTsMwvZ0LEhA2VS1MLpVv+OdVfN0alePgzp1nx/zlTEpgzxb85n1u0yX2YfcM5h6tUGBjVel6EZ8fdl4mHjfy38ct5Ed8VJSYPiK7FpdJmxczhoKbna2Akj84mA73DpRwB3gSu9HfSUHwnVdFWwY9YQKi3XPfhWiARw0bTmmO47UJvkmIQfXXQefFDpaJUemKsNRVKXTov/N/BxktpgVRRYXeMPC8Av6/thki+yLD62GmBn7e6M0dqD1Dq71Qo+ufTaKqoNrJ5Xqps9CnCRvZxFF7sIHSF4uBQtmITWT9a4hpuXHlk5Q9WQFzbukIxs61y01RgEnlewjbqEitLWmHlb0dosXAp96KvB0a0HAiLbua7CKPFfUMYqoLX9/Z7Qha64hWpA0z3ZLFysib3+DhXzOL4q0HsrlIcuFQKV9pv2dWA6XXhnZWZY7KkhCd16grXCbEnsP2fU+dg6ZxW3++c1ZYIFdorFwMGzNYAPquNrCvsE5VswRnyKafzEpTzwjudRw0b8WtHJDSrtpi70I5JxUqeF4AbL3YvkzspVBw2pSSw6ioW4M7mK9RIpxAKShDJM0ZI+coON+mMvxhfrWgKX/FXk9Q4GmiKN2wEwPfatxsvQIWcFx+V2dFkbnvScb8t7ErhnEWdgZ9XKAGDd6FZDi4AVwob+RlnfLFUCpkpFJF6/NhJGV61eV2hZZ91ukZxcDCDJp/wfSUUSrDE1cC3GizjRaWYedh5Xgz/FbebkuclatgozwWH8sx3ZavS4PwEPwxz1SkMIbcrck57HFefPs8jYx8UNhI3QKX4Ixd/sz8gxf9H1/PinthohfEXCbsA9zLYJ0suqc+slZ7dbVlrgzAAluIlABwczHj68hwYyPiWrfopYkaBa/A485HKdZUOckFHTdgVIUqFENNDZk8k50mKKcOZxNwS1xyegG9dcZLjO0W3aACBejf2aiM7o+V5UWg0z0sU3Oqp9UQYL1EqpUaTI6emMMOWlyDuDz/jpTmu2QzZ4PCy6Dc2WmPox7yOJPb1lZS2//kjx1fcRlecnutKqLSkIh2k3iuqjaywUS2eFzN52p44HsbzcmgoiwVTU1Xtsx780yXHAQCO6mrCrJCel0ljvCyf1x7KIo5pitUOPay3QRWeF6XUoNFNdTkvpYvKfXERQnDOoqme7QyVOtK4Yppi5T/kbA/0wP2qzoebvTyvGkqel/Lbu1eNlKD8akAtJTPHFefxKcLzolLEIuYlhEFXS52Nf/vqPlzociW/tqcfl58y27VVqd1BVKycl7y3jL2sSF3ARBhlZQiUSn0ZpVYuWMoSjSMYzuaRMjSH5+XIzpTDK+jvdeQfCAqlxGzVRnZGL2GXRErYjcI7h9I41+d+rQeqYoZJJ4jnxX2eohmq3zXQEtcsI1b0KvNDNRV2RyPXKYj5HQl8MJiJtE2l5Fc3mkIwmCkp7PqGVs2cOVIHz0vSzOWZZ895UULkvAxlkTLqH/IMy+x2brCsvWAh+vv7Q20zMe6GOvB35x0VKmzziWWzcNZRHWa1S7jT182EXd10yfs9qLmOSfScF/GwCnvT6qpTLyVuJj0SQkLlXOhqQNioRs9LpeO/ZdUix9+0wvjbFXndC3dq5rzoKg2sDKgF7urlq6Vn3ngfHzq6NFnHNAWv7e3HEZ3uVQpDplBjtZEn5yU4YTfQeKmQnOeH0KkpmI3zFEqQNEp9ioYyXFbfPqHObk/g3KODH9b2w74hICYeC6o2miA5L1HI5IpYNK1pVL5bGKMTJWHXTUJXAsOl9oRdSoI9tCWRurEzXo6d0RLZ22CYi6qwUkSaLWxULmHXfp+HFf70I2mo6B/xJuxWqjY6VGXOy3gyaYyXsAjVUqVCzoUdVSn1hjBUr4IrEN3zYijUetDEtPBl1rrqzXkRE0eYnAtDcYWNRLVRlVeCOOdKq/3jZjoFjsqpbQJwjHPcNWcrhKDA+E1XjzCRG1GmPmRWFtgfeEldDVQkrkfOi9OwDE7YDTJedIX4hmLKIVZ+hSKsUulSryGKdC56OMw+ua9c6J9HkNBVX08VY9E6tIdFIaNnAKgKweJp4XR9qvluABMmYdeNoQZ7P+05L4SQQKM0anuAejC7PYErlvs34w1CGAJ2napyaO5qI9971lmJSQnBcLa6ELRVKh2x2uhQldVG40ljHW0dUWg4RV7AVLg0H2SaQn0vKjXAbRqEoZVKeqM0i+PVRs6wj1glZ0Os/Oud8yLmorDJz4JKOUdTmw0cbxo8zbqrEzbluhqGVh+NATdCm+G93mHMaXfGXxOGgoXT/Fdr2XyxKtc+IdyTJHpd2Y/D3edGQBEcNoqasKtSaraNKEJR+O+StIWNompbhKWzybA6YtsRDTnrTVSF3SjoCsVRXaOTM1AyXiam56VcYnNLXLPC3HbFZTciYXcsPS/VYG9bEsb7Yq82Cmr6yD0vpb9VhWA4l6/KeBGCge7GjJXyCwcy+aoSdseTxjraOlKp2sWOSKjSzIvW70IoJyjmh1DYBfwFvIKI+7jaRTUHr8CJmPNSp1LpqHkWlcZ/alMMFy+ZgVwuh2uOclb+iLL0mKr4SlbXiiiV3tM7jBmtTsGkpK462hHY6R3ORTJEBTFNwUiugJFcwdXwTvV9uAPlc17CGuUCXaHIFYtQi6XWGfZGiWlrFRg+Ds+bM1b+vJ9AoarQUUncpJQgpo+O9+IzZx8xal6dUthoYnpeAAQuIprjmmXYEATPMyJhdyxzXqpB5CoqlIa6vjWbSF2gwq7i9OJQwnMsq/G08VLpvMPDpQYsuAXimSE9Lw2CW/G1HPbKC131F9aKqvNi11uJEoe/4tQ5nlVps3nRqZRU9ry4SqVFCKpmz0vESadc/NuNe7gVSqBRfkP+P92LI+03DKJU+oPBnKcH0rJ5bTiyw7vC7h/Jo0tXqwpjxTVekZDJh5+w6lltJCTcdYVZ90WTw3jJRw6H8X481TVY1Ks4hzDQUQwbfeJkdwJ3/aBmJeNE9bwAvNGnH5pCcd9lSwGE03kZy7BRNQjxTJUShMmp1WippUhQIrqmOFXTVUpsC4ZoJHUFA66cF6D8M8be0qSRmLim/ChDIxgbijl58LCRv4GghIyBCniLdn6xBIl4+WGo3jYIomzXngAchDtsVGu1UdhSaTdRPF/13DYMvFS6gL0+npdzF031FbfTFYrPn39UVfuLm9VvQLheW0Bw2EhXo4dcRLVR3kwodHpeCIbMSrsoaAqtujuRqkS7l8Jyyrx2JCZo0mslVIVOaM/LvZdWLjMud98qotqoQcJGYRermsrzyT7375t4V+mABYfD80J5d/hqjBfVfAa4j63cM8byvDRY2Gji3g2jTLlVgB+iD5ERUDPvVpCtxIzWOL5gthivdTV4/xUnWscQLufF7qLk/6920hDhi6grpkrVRuVQyuhF1INZbXG8czCNPX0jZbtP2/nRNafgSE8FUjhE2ChKM+WypdJRdV4otXobeXNe+ENF6BEVQ6g4i+2iGrT2bUcjYffTZx0ROR9ooqBRMqE9L2EgpIzOCxUNYsf4oCKiq1yKQA1IH3CjKRS7DqXx1919ZXRenPOn8LwYVV6rKcOrNu+We7AjnhnSeGkQolQbAaVwS5B3Q6HVx+mTNZZvCuNHpeVjm4BPwm6N1UaEkKpis5TWoi1DInsCorB4ejNe39uPnqEs2pPhwkC1lEhz4yVaiKV8zkvE/CPze4YyeauxZcpWKs3/zz8TJilcfL7aEICmBFelHK5oKp2w1UZhKVdtZPVYm+DWixCpC5t2oFGKV97rQ/9wLjhh19VsV1UIBkZyMKpc1PoJtn5qxbzAz+sKQVIP19h4ItHYd0MNUFq5E7Id1dR40cwSZzcx1wUYha9+Ykl1G7rQFFLRWk8ZqsOFWGt7AKC6Ek5qqrlWQ1TDMyoxTUEmXwRD+DBOLcT1UtgoLJQEa0ZUM66M8YRCTaGY2RrHvClJAKWVsnAtZ/LFUCtCdyPOKKi0+m0nKwnNv3dUI0EQHF4Wr0/0B6golRaSApXQVIKdB9NlE5I118J36axW/HH7waplF8K2yhEQQtCeqr/kxGhz2BovUR+A9nwXv/YA912+tOoHXVA5bFSUEAm7nzptLpbPby9tU2PCLlCd16GWvBWFRtcyicr0lljZ/kb1JKbyxp9RfoJyOi+1lhmvOHIKTj1iivl9pWR1oSIczvMSXSzPvu1ohgUbkUarBPGjnLdVhPPGsj1ANfCCDTPnJYzOi3ley+a2oy+dC/C8OMUol89vx2t7+qr25qYMNbLnsj1Zn2fQWHL4Gi802spfM0MVQWGjiRAvDJOwK0T6Sn/z/9fmeYnu3qQkmqifZ9tRDiscP7MVXc3h8l1qJa4rSGcLQIQUV1526n292gf/UDaPhM81rDmMl/D9m7SIOWDubSf6Q2ysmQjzS60QBOeJ1Fo4MFbopo6SapZLV0KjFNNbYpjdHsehoax/V2l3tZFCsXLh1KrDhElDjZxvdmIdmiuONY1/R1RJlGojgMclubR+9eGO0SZMqbQba9Ko4WFRXdiolgon4uv9qienHdE+KkmjfsQ0Bb3pbKSS+ekJ4MQl0z2vuxOyw7K3b8S3O6y41oXGEW+TMQaelwn+EBtr/PRwGo1y97xah3loLFg+vw0tcY2XSoe4zwyN4sQ5rWiOaehJZwO7SrvH5cpToyn/2kka0fNX7vpfx1a9v/Gi8e+IKom68hcTqrs30ESikhiRH2KFW0s8vRpVWRrR81WvbcNyRGfKp3/R6BDTFOzuGY6UuG0osPJSHK+rCnQluicsX2COTsEC3QyXir5APUPZ0GGjqjuV15DsO1m5x+y629CUqTAsJeyO5QFF5/JTuFGhUAJarHyNxjQF919xEh58bic3XgKS7N33yrK5bVUfY1KP7nlpRA5b4yVqzotaIWw0EdAUEtmwoiS4f05Yqg4bVV0qPbmqUeKagg8GM5GUloO4YeURVRnXqkI8mjbidXG9d6YM7OkbDmW8cOmAyIcBoLKc+eHIvA6vodpoUBLcRqRREnYFmkJQCGG8APycmuMaetK5wK7S9XQ4+VUbTUYmzxMgIjSiVohuho1OmNWC+Z0TcyLhpdLRLlpCai87rjZsVO0DSiGjn7A7lsQ0BQcHs1aPqlq/qxqvhUoJZrR6c3zsxnpnk4H3esIZL36u8NDHIj0vk5Jy2lqW52WCh40EitmcMSwtcS1QhK8WL6UfSUOZsKkN9eSwNV6irt6F52XZ3PaqxchGG1UhVYUMajVeqvEYRM05qte2E5G4puDQUHZc8xpEibTndeoyXnqHQ+a81JKwKz0vkxGeZO7/uxLTE94oxotKo4mcihYuQV2l63m5r1w4FbPbvSrgk43D13iJqLDbCOWbWgiROt/tajyv+y6PrlMTVeHYjkJqN7gmEnGd4oPBTM1ihbXQmtCsdhV2NJVAN6+PzpSB3T3DoTxtag06L7VoxEgmLpXu+Sj95sabqIrqojmlf3uA+noal89vx9SmsamUHE8mzxMgIpGrjZSJm6grCNMewH+72s6ruYqGXrVUGykRVz0THUNVcHAoW5ecl2r51pUn+eoU2UUZO4TnJWTYqBaFXRk2moRUuOfDaqdMBKI24hVzpN82k20+Gysm9tN4FIm68teU0ZWkrwcrF3aisym62NB4GGW1eF7oJLvZ47oIG42f5yVIKFGESwEzYTek8aKp1T+IuILp5Pl9JRye5xZ87fAeaWN4QDWgRLxGhVfTbxNCqlt0Hu7IaqOQrDl3wYR3aa4q03yrHOMRDqul2kilpGEb7PkR1xQUimxcPS9BEEKscFZLXEOhyELlVamUBlaWVEJTq/faSCYuBOXn3KjejPEkatgooSvQVRqowt7oTTfHg8nzBIhIU0yNpONx8rz2yh9qUMbDoxS12suxbQ19kSYiorHmeHpeyiHE8ygl6EgZ4dsDVJvzMsk8axIO7ydXxnhpoFynqIYWIQRtieDweqwKrazDnYm31Bsj2pI6rjtz/ngfxoRgPIyX9oSOhV1NVW072WLECuX6PBNVRfXYGS3Wvzubwhkvulr9KnrZ3DbpRp+EUFI+l0mljZPrVE1ycVsiuPlhcgJ6XSc6csQk46KZMrU5ho8vm1XVttx4mVwPt5hGJ+wEdsffHGP9uzNlhMqRUmn12hVHVWnUSiY2zT7VbHYaqVS6Gs9iOePlm//7xFoP6bBjYs6WkjGl0bwYky1sBPDQUWIcS6XDEtbzIrVaJG7+3woP6EaqNlowNYXhbCHSNrdeuCjwvSh9zSQcabxIGi75dTJ6XuK6MmHDRnYWTE2htUzsXtCa0DAloIJJcnhSKczSSNVG1YS8T5xTfb8iiZeJP1tKRp2Jrl/jZnZbAm2J/HgfRl1J6mpVbRbGmk+fdUSozy2e3ozF05tH+WgkkwmVVt9SQnL4IY0XScOFYI6f1VL5Qw1GV7MRWEYpkRwONFLOi2T8mfhLPcmo87dnyKqr8eb+K08a70OQSMaVqNopksObcTNeHnjgAcybNw+xWAynnnoqXnjhhfE6lMOesxd2jvchHPakGiDfRSIZTZQGStiVjD/jYrz84he/wNq1a3HnnXdi06ZNWLJkCVavXo33339/PA5HIpFIJOOMRqWysiQ842K83Hfffbj++utx7bXX4phjjsF3v/tdJBIJ/OhHPxqPw5FIJBLJOCOFCSVRGHNfdTabxcaNG3H77bdbr1FKcf755+P555/33SaTySCTyVh/9/f3AwByuRxyudzoHvAYI85nsp1Xtcjx8CLHxIscEyeNOB7NMWVUj7cRx2Q0majjEfZ4CGOMjfKxONizZw9mzpyJ5557DitWrLBev/XWW7F+/Xps2LDBs81dd92Fu+++2/P6z3/+cyQSiVE9XolEIpGMPkXm33VZcniRTqdx5ZVXoq+vD83NwXILDZElePvtt2Pt2rXW3/39/Zg9ezZWrVpV9uQakVwuh6eeegoXXHABNK2yGNhkR46HFzkmXuSYOJHj4UWOiZOJOh4islKJMTdeOjo6oCgK9u/f73h9//79mDZtmu82hmHAMLxqnZqmTahBryeT+dyqQY6HFzkmXuSYOJHj4UWOiZOJNh5hj2XMM6R0XceyZcuwbt0667VisYh169Y5wkgSiUQikUgkfoxL2Gjt2rW4+uqrcfLJJ2P58uX4xje+gaGhIVx77bXjcTgSiUQikUgaiHExXi6//HIcOHAAX/7yl7Fv3z4sXboUv/3tb9HV1TUehyORSCQSiaSBGLeE3Ztuugk33XTTeO1eIpFIJBJJgyJVgSQSiUQikTQU0niRSCQSiUTSUEjjRSKRSCQSSUMhjReJRCKRSCQNhTReJBKJRCKRNBTSeJFIJBKJRNJQNERvIzeil2TYHgiNRC6XQzqdRn9//4SSbB4v5Hh4kWPiRY6JEzkeXuSYOJmo4yGe65V6Rjek8TIwMAAAmD179jgfiUQikUgkknozMDCAlpaWwPcJq2TeTECKxSIWLlyIjRs3gpBoPdRPOeUU/OUvf4m8z2q2q2Yb0TH73Xffjdwxe6yOcSy3G+vxGOvt5DVSn+2qHZNGODd5jdRnO3mNOJmocytjDAMDA5gxYwYoDc5saUjPC6UUuq6XtcqCUBQl8g9V7XbV7gsAmpubx2R/YzketWw3VuMx1tvJa6R+2wHRx6QRzk1eI/XbDpDXiJuJOLeGebY3bMLumjVrJvx21e6rWsbyGMd6u7Hcl7xGat9mPLYby33Ja6T2bcZju7Hcl7xG6redHw0ZNprM9Pf3o6WlBX19fVVb0pMJOR5e5Jh4kWPiRI6HFzkmThp9PBrW8zJZMQwDd955JwzDGO9DmRDI8fAix8SLHBMncjy8yDFx0ujjIT0vEolEIpFIGgrpeZFIJBKJRNJQSONFIpFIJBJJQyGNF4lEIpFIJA2FNF4kEolEIpE0FNJ4GQX+8Ic/4OKLL8aMGTNACMHjjz/ueH///v245pprMGPGDCQSCVx44YV48803HZ/Zt28fPvWpT2HatGlIJpM46aST8Mtf/tJ3f5lMBkuXLgUhBC+99NIonVX1jNV4bNq0CRdccAFaW1sxZcoUfOYzn8Hg4OBon15V1GNM3nrrLXz0ox9FZ2cnmpubcdlll2H//v2++zscrpEw49FI18i9996LU045BU1NTZg6dSo+8pGPYOvWrY7PjIyMYM2aNZgyZQpSqRQ+9rGPec55165d+PCHP4xEIoGpU6fiC1/4AvL5vO8+//SnP0FVVSxdunS0TqtqxnI8HnjgASxevBjxeByLFi3CT3/601E/v2qo15j8/d//PZYtWwbDMCr+9tu3b0dTUxNaW1vrfDbRkMbLKDA0NIQlS5bggQce8LzHGMNHPvIR7NixA7/+9a+xefNmzJ07F+effz6Ghoasz1111VXYunUrfvOb32DLli249NJLcdlll2Hz5s2e77z11lsxY8aMUT2nWhiL8dizZw/OP/98LFiwABs2bMBvf/tbvPrqq7jmmmvG6jQjUeuYDA0NYdWqVSCE4Omnn8af/vQnZLNZXHzxxSgWi57vnOzXSJjxaLRrZP369VizZg3+/Oc/46mnnkIul8OqVasc98XNN9+MJ554Ao8++ijWr1+PPXv24NJLL7XeLxQK+PCHP4xsNovnnnsODz74IH7yk5/gy1/+smd/vb29uOqqq3DeeeeNyflFZazG4zvf+Q5uv/123HXXXXj11Vdx9913Y82aNXjiiSfG9HzDUI8xEfzt3/4tLr/88rL7y+VyuOKKK3DWWWfV/VwiwySjCgD2q1/9yvp769atDAB75ZVXrNcKhQLr7Oxk3//+963Xkskk++lPf+r4rvb2dsdnGGPsv/7rv9jRRx/NXn31VQaAbd68eVTOo16M1nh873vfY1OnTmWFQsF6/69//SsDwN58881ROpv6UM2Y/O53v2OUUtbX12d9pre3lxFC2FNPPeX4/sPhGgkzHo18jTDG2Pvvv88AsPXr1zPG+PlpmsYeffRR6zOvv/46A8Cef/55xhj/7SmlbN++fdZnvvOd77Dm5maWyWQc33/55ZezL33pS+zOO+9kS5YsGf0TqpHRGo8VK1awW265xbGvtWvXsjPOOGO0T6lmqhkTO5V++1tvvZV98pOfZD/+8Y9ZS0tLvQ8/EtLzMsZkMhkAQCwWs16jlMIwDPzxj3+0Xjv99NPxi1/8AocOHUKxWMTDDz+MkZERnHPOOdZn9u/fj+uvvx4PPfQQEonEmJ1DPanXeGQyGei67mjkFY/HAcDxPY1AmDHJZDIghDgEpmKxGCiljvM9XK6RMOPR6NdIX18fAKC9vR0AsHHjRuRyOZx//vnWZ44++mjMmTMHzz//PADg+eefx/HHH4+uri7rM6tXr0Z/fz9effVV67Uf//jH2LFjB+68886xOJW6MFrjkclkHNcawK+TF154AblcblTPqVaqGZOwPP3003j00Ud9vaPjgTRexhhx4dx+++3o6elBNpvFv/zLv2D37t3Yu3ev9blHHnkEuVwOU6ZMgWEYuOGGG/CrX/0KCxYsAMBd6ddccw1uvPFGnHzyyeN1OjVTr/H40Ic+hH379uGrX/0qstksenp6cNtttwGA43sagTBjctpppyGZTOKLX/wi0uk0hoaGcMstt6BQKFifOZyukTDj0cjXSLFYxOc//3mcccYZOO644wDwPDBd1z25B11dXdi3b5/1GfuDWrwv3gOAN998E7fddht+9rOfQVUbo1fvaI7H6tWr8YMf/AAbN24EYwwvvvgifvCDHyCXy+GDDz4Y5TOrnmrHJAwHDx7ENddcg5/85CcTppWANF7GGE3T8B//8R/Ytm0b2tvbkUgk8Mwzz+Ciiy5yrAjvuOMO9Pb24ve//z1efPFFrF27Fpdddhm2bNkCALj//vsxMDCA22+/fbxOpS7UazyOPfZYPPjgg/j617+ORCKBadOmYf78+ejq6irbVn0iEmZMOjs78eijj+KJJ55AKpVCS0sLent7cdJJJ1mfOZyukTDj0cjXyJo1a/DKK6/g4Ycfruv3FgoFXHnllbj77ruxcOHCun73aDJa4wHwueaiiy7CaaedBk3TcMkll+Dqq68GgAl9nYzmmFx//fW48sorcfbZZ9f9u6tmXINWhwFwxe/t9Pb2svfff58xxtjy5cvZ5z73OcYYY9u3b/fE+Blj7LzzzmM33HADY4yxSy65hFFKmaIo1n8AmKIo7Kqrrhq9E6qR0RoPO/v27WMDAwNscHCQUUrZI488Ut+TqDPVjImdAwcOsJ6eHsYYY11dXexf//VfGWOH1zViJ2g87DTSNbJmzRo2a9YstmPHDsfr69atYwCscxXMmTOH3XfffYwxxu644w5PDsOOHTsYALZp0ybW09NjXRPiP0KI9dq6detG89SqYjTHw042m2Xvvvsuy+fz7Nvf/jZrampy5EtNJGoZEztBOS8tLS2Oa4RSal0jP/zhD+t5KqGRxssoU24iFmzbto1RStnvfvc7xlgpifC1115zfG7VqlXs+uuvZ4wx9s4777AtW7ZY//3ud79jANhjjz3G3n333VE5l3owWuPhxw9/+EOWSCQ8N+5Eo5ox8WPdunWMEMLeeOMNxtjhdY344R4PPybyNVIsFtmaNWvYjBkz2LZt2zzvi2TMxx57zHrtjTfe8E1Q3b9/v/WZ733ve6y5uZmNjIywQqHguEa2bNnCPvvZz7JFixaxLVu2sMHBwdE/0ZCMxXgEcfbZZ7MrrriijmdTH+oxJnaCjJfXXnvNcY388z//M2tqamJbtmxhhw4dqus5hUUaL6PAwMAA27x5M9u8eTMDwO677z62efNm9s477zDGGHvkkUfYM888w9566y32+OOPs7lz57JLL73U2j6bzbIFCxaws846i23YsIFt376dfe1rX2OEEPbkk0/67vPtt9+esJUkYzUe999/P9u4cSPbunUr+9a3vsXi8Tj75je/OebnG4Zax4Qxxn70ox+x559/nm3fvp099NBDrL29na1duzZwn5P5GmEs3Hg00jXy2c9+lrW0tLBnn32W7d271/ovnU5bn7nxxhvZnDlz2NNPP81efPFFtmLFCrZixQrr/Xw+z4477ji2atUq9tJLL7Hf/va3rLOzk91+++2B+52o1UZjNR5bt25lDz30ENu2bRvbsGEDu/zyy1l7ezt7++23x/J0Q1GPMWGMsTfffJNt3ryZ3XDDDWzhwoXWveiuSBNMhGojabyMAs888wwD4Pnv6quvZowx9s1vfpPNmjWLaZrG5syZw770pS95LpJt27axw36/dwAABO9JREFUSy+9lE2dOpUlEgl2wgkneEqF7UzkB9NYjcenPvUp1t7eznRdrzhe4009xuSLX/wi6+rqYpqmsaOOOop9/etfZ8ViMXCfk/0aCTMejXSN+I0HAPbjH//Y+szw8DD73Oc+x9ra2lgikWAf/ehH2d69ex3fs3PnTnbRRRexeDzOOjo62D/8wz+wXC4XuN+JaryM1Xi89tprbOnSpSwej7Pm5mZ2ySWXlPXejSf1GpOVK1f6fk+QwTYRjBfCGGPV5MpIJBKJRCKRjAcTN3VaIpFIJBKJxAdpvEgkEolEImkopPEikUgkEomkoZDGi0QikUgkkoZCGi8SiUQikUgaCmm8SCQSiUQiaSik8SKRSCQSiaShkMaLRCKRSCSShkIaLxKJZFw555xz8PnPf368D0MikTQQ0niRSCQNw7PPPgtCCHp7e8f7UCQSyTgijReJRCKRSCQNhTReJBLJmDE0NISrrroKqVQK06dPx9e//nXH+w899BBOPvlkNDU1Ydq0abjyyivx/vvvAwB27tyJc889FwDQ1tYGQgiuueYaAECxWMS9996L+fPnIx6PY8mSJXjsscfG9NwkEsnYIY0XiUQyZnzhC1/A+vXr8etf/xr//d//jWeffRabNm2y3s/lcrjnnnvw8ssv4/HHH8fOnTstA2X27Nn45S9/CQDYunUr9u7di29+85sAgHvvvRc//elP8d3vfhevvvoqbr75Znzyk5/E+vXrx/wcJRLJ6CO7SkskkjFhcHAQU6ZMwc9+9jN84hOfAAAcOnQIs2bNwmc+8xl84xvf8Gzz4osv4pRTTsHAwABSqRSeffZZnHvuuejp6UFraysAIJPJoL29Hb///e+xYsUKa9tPf/rTSKfT+PnPfz4WpyeRSMYQdbwPQCKRHB689dZbyGazOPXUU63X2tvbsWjRIuvvjRs34q677sLLL7+Mnp4eFItFAMCuXbtwzDHH+H7v9u3bkU6nccEFFzhez2azOPHEE0fhTCQSyXgjjReJRDIhGBoawurVq7F69Wr8+7//Ozo7O7Fr1y6sXr0a2Ww2cLvBwUEAwJNPPomZM2c63jMMY1SPWSKRjA/SeJFIJGPCkUceCU3TsGHDBsyZMwcA0NPTg23btmHlypV44403cPDgQXzlK1/B7NmzAfCwkR1d1wEAhULBeu2YY46BYRjYtWsXVq5cOUZnI5FIxhNpvEgkkjEhlUrhuuuuwxe+8AVMmTIFU6dOxT/+4z+CUl43MGfOHOi6jvvvvx833ngjXnnlFdxzzz2O75g7dy4IIfjP//xPdHd3Ix6Po6mpCbfccgtuvvlmFItFnHnmmejr68Of/vQnNDc34+qrrx6P05VIJKOIrDaSSCRjxle/+lWcddZZuPjii3H++efjzDPPxLJlywAAnZ2d+MlPfoJHH30UxxxzDL7yla/ga1/7mmP7mTNn4u6778Ztt92Grq4u3HTTTQCAe+65B3fccQfuvfdeLF68GBdeeCGefPJJzJ8/f8zPUSKRjD6y2kgikUgkEklDIT0vEolEIpFIGgppvEgkEolEImkopPEikUgkEomkoZDGi0QikUgkkoZCGi8SiUQikUgaCmm8SCQSiUQiaSik8SKRSCQSiaShkMaLRCKRSCSShkIaLxKJRCKRSBoKabxIJBKJRCJpKKTxIpFIJBKJpKH4/wHlaqIXIgKkSgAAAABJRU5ErkJggg==", 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" ] @@ -85,9 +100,9 @@ ], "source": [ "# get rolling sum\n", - "prec_rsum = prec.rolling(\"30D\", min_periods=30).sum().dropna()\n", + "prec_rsum = prec.resample(\"ME\").sum()\n", "prec_rsum.plot(\n", - " grid=True, linewidth=0.5, title=\"Precipitation, 30day rolling sum\", figsize=(6.5, 4)\n", + " grid=True, linewidth=0.5, title=\"Precipitation, monthly sum\", figsize=(6.5, 4)\n", ");" ] }, @@ -110,18 +125,18 @@ "data": { "text/plain": [ "date\n", - "1980-01-30 -0.946377\n", - "1980-01-31 -0.810205\n", - "1980-02-01 0.018504\n", - "1980-02-02 0.040376\n", - "1980-02-03 0.216153\n", + "1980-03-31 0.798607\n", + "1980-04-30 1.341499\n", + "1980-05-31 -0.429903\n", + "1980-06-30 -0.089408\n", + "1980-07-31 1.136106\n", " ... \n", - "2016-10-27 -0.744963\n", - "2016-10-28 -0.744963\n", - "2016-10-29 -0.732095\n", - "2016-10-30 -0.805841\n", - "2016-10-31 -0.850192\n", - "Length: 13425, dtype: float64" + "2016-06-30 2.535965\n", + "2016-07-31 1.829305\n", + "2016-08-31 0.736336\n", + "2016-09-30 -1.299582\n", + "2016-10-31 -1.315595\n", + "Freq: ME, Length: 440, dtype: float64" ] }, "execution_count": 4, @@ -130,7 +145,7 @@ } ], "source": [ - "spi = si.spi(prec_rsum, dist=scs.gamma, prob_zero=True, fit_freq=\"ME\")\n", + "spi = si.spi(prec_rsum, dist=scs.gamma, prob_zero=True, timescale=3, fit_freq=\"ME\")\n", "spi # pandas Series" ] }, @@ -169,40 +184,40 @@ " \n", " \n", " date\n", - " rain\n", - " rain_calculated_index\n", + " rain_scale_3\n", + " rain_scale_3_calculated_index\n", " \n", " \n", " \n", " \n", - " 1980-01-30\n", - " 1980-01-30\n", - " 43.1\n", - " -0.946377\n", - " \n", - " \n", " 1980-01-31\n", " 1980-01-31\n", - " 46.8\n", - " -0.810206\n", + " NaN\n", + " NaN\n", + " \n", + " \n", + " 1980-02-29\n", + " 1980-02-29\n", + " NaN\n", + " NaN\n", " \n", " \n", - " 1980-02-01\n", - " 1980-02-01\n", - " 56.3\n", - " 0.018504\n", + " 1980-03-31\n", + " 1980-03-31\n", + " 219.0\n", + " 0.798607\n", " \n", " \n", - " 1980-02-02\n", - " 1980-02-02\n", - " 57.0\n", - " 0.040376\n", + " 1980-04-30\n", + " 1980-04-30\n", + " 217.8\n", + " 1.341101\n", " \n", " \n", - " 1980-02-03\n", - " 1980-02-03\n", - " 62.8\n", - " 0.216153\n", + " 1980-05-31\n", + " 1980-05-31\n", + " 139.4\n", + " -0.434361\n", " \n", " \n", " ...\n", @@ -211,55 +226,55 @@ " ...\n", " \n", " \n", - " 2016-10-27\n", - " 2016-10-27\n", - " 37.5\n", - " -0.744964\n", + " 2016-06-30\n", + " 2016-06-30\n", + " 369.6\n", + " 2.535965\n", " \n", " \n", - " 2016-10-28\n", - " 2016-10-28\n", - " 37.5\n", - " -0.744964\n", + " 2016-07-31\n", + " 2016-07-31\n", + " 334.7\n", + " 1.829305\n", " \n", " \n", - " 2016-10-29\n", - " 2016-10-29\n", - " 37.8\n", - " -0.732096\n", + " 2016-08-31\n", + " 2016-08-31\n", + " 333.6\n", + " 1.749250\n", " \n", " \n", - " 2016-10-30\n", - " 2016-10-30\n", - " 36.1\n", - " -0.805842\n", + " 2016-09-30\n", + " 2016-09-30\n", + " 122.4\n", + " -1.333315\n", " \n", " \n", " 2016-10-31\n", " 2016-10-31\n", - " 35.1\n", - " -0.850193\n", + " 129.6\n", + " -1.315595\n", " \n", " \n", "\n", - "

13425 rows × 3 columns

\n", + "

442 rows × 3 columns

\n", "" ], "text/plain": [ - " date rain rain_calculated_index\n", - "1980-01-30 1980-01-30 43.1 -0.946377\n", - "1980-01-31 1980-01-31 46.8 -0.810206\n", - "1980-02-01 1980-02-01 56.3 0.018504\n", - "1980-02-02 1980-02-02 57.0 0.040376\n", - "1980-02-03 1980-02-03 62.8 0.216153\n", - "... ... ... ...\n", - "2016-10-27 2016-10-27 37.5 -0.744964\n", - "2016-10-28 2016-10-28 37.5 -0.744964\n", - "2016-10-29 2016-10-29 37.8 -0.732096\n", - "2016-10-30 2016-10-30 36.1 -0.805842\n", - "2016-10-31 2016-10-31 35.1 -0.850193\n", + " date rain_scale_3 rain_scale_3_calculated_index\n", + "1980-01-31 1980-01-31 NaN NaN\n", + "1980-02-29 1980-02-29 NaN NaN\n", + "1980-03-31 1980-03-31 219.0 0.798607\n", + "1980-04-30 1980-04-30 217.8 1.341101\n", + "1980-05-31 1980-05-31 139.4 -0.434361\n", + "... ... ... ...\n", + "2016-06-30 2016-06-30 369.6 2.535965\n", + "2016-07-31 2016-07-31 334.7 1.829305\n", + "2016-08-31 2016-08-31 333.6 1.749250\n", + "2016-09-30 2016-09-30 122.4 -1.333315\n", + "2016-10-31 2016-10-31 129.6 -1.315595\n", "\n", - "[13425 rows x 3 columns]" + "[442 rows x 3 columns]" ] }, "execution_count": 5, @@ -282,7 +297,7 @@ " date_col=\"date\",\n", " precip_cols=\"rain\",\n", " freq=\"M\",\n", - " scale=1, # note that scale is not the same for the standard deviation in SciPy\n", + " scale=3, # note that scale is not the same for the standard deviation in SciPy\n", " fit_type=\"mle\",\n", " dist_type=\"gam\",\n", ")\n", @@ -359,6 +374,60 @@ "# climateind_spi" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using SPEI R package" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1] \"Calculating the Standardized Precipitation Evapotranspiration Index (SPEI) at a time scale of 3. Using kernel type 'rectangular', with 0 shift. Fitting the data to a Gamma distribution. Using the ub-pwm parameter fitting method. Checking for missing values (`NA`): all the data must be complete. Using the whole time series as reference period. Input type is array. No time information provided, assuming a monthly time series.\"\n" + ] + }, + { + "data": { + "text/plain": [ + "date\n", + "1980-01-31 NaN\n", + "1980-02-29 NaN\n", + "1980-03-31 0.772307\n", + "1980-04-30 1.244421\n", + "1980-05-31 -0.357370\n", + " ... \n", + "2016-06-30 2.646909\n", + "2016-07-31 1.735676\n", + "2016-08-31 1.552881\n", + "2016-09-30 -1.315847\n", + "2016-10-31 -1.267677\n", + "Freq: ME, Name: SPI, Length: 442, dtype: float64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from rpy2.robjects.packages import importr\n", + "from rpy2.robjects import pandas2ri\n", + "pandas2ri.activate()\n", + "\n", + "sr = importr('SPEI')\n", + "\n", + "spir_res = sr.spi(prec_rsum.values, scale=3)\n", + "r_spi = pd.Series(spir_res[2].ravel(), index=prec_rsum.index, name=\"SPI\")\n", + "r_spi" + ] + }, { "attachments": {}, "cell_type": "markdown", @@ -369,12 +438,12 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -391,7 +460,7 @@ " height_ratios=[2, 1],\n", ")\n", "spi.plot(ax=ax[\"SPI\"], grid=True, linestyle=\"-\", label=\"SPI\")\n", - "standardp_spi.loc[:, \"rain_calculated_index\"].plot(\n", + "standardp_spi.iloc[:, -1].plot(\n", " ax=ax[\"SPI\"],\n", " color=\"C1\",\n", " grid=True,\n", @@ -401,16 +470,20 @@ "# climateind_spi.plot(\n", "# ax=ax[\"SPI\"], color=\"C2\", grid=True, linestyle=\":\", label=\"climate_indices\"\n", "# )\n", + "r_spi.plot(\n", + " ax=ax[\"SPI\"], color=\"C2\", grid=True, linestyle=\":\", label=\"R package\"\n", + ")\n", "\n", "ax[\"SPI\"].set_ylim(-3.5, 3.5),\n", "ax[\"SPI\"].set_title(\"Comparison\"),\n", "ax[\"SPI\"].set_ylabel(\"SPI\"),\n", "ax[\"SPI\"].legend(ncol=3)\n", "\n", - "# (spi - climateind_spi).plot(ax=ax[\"DIFF\"], color=\"C3\", label=\"SPEI - climate_indices\")\n", - "(spi - standardp_spi.loc[:, \"rain_calculated_index\"]).plot(\n", + "(spi - standardp_spi.iloc[:, -1]).plot(\n", " ax=ax[\"DIFF\"], color=\"C4\", label=\"SPEI - standard_precip\", grid=True\n", ")\n", + "(spi - r_spi).plot(ax=ax[\"DIFF\"], color=\"C3\", label=\"SPEI - R Package\")\n", + "\n", "# ax[\"DIFF1\"].set_ylim(-0.05, 0.05)\n", "ax[\"DIFF\"].legend(ncol=2)\n", "ax[\"DIFF\"].set_title(\"SPEI minus other package\")\n", @@ -426,9 +499,11 @@ "source": [ "Difference is very small between SPEI an the standard_precip package. However there is a significant difference beteween the SPEI and climate_indices package, not sure why. Maybe it has to do with the fitting method used for the gamma distribution?\n", "\n", - "The standard_precip package does not explicitely support the Standardized Precipitaion Evaporation Index, as far as I can see. However, the SPI class in standard_precip could probably be used, even though the naming of `precip_cols` is not universal. In general, the standard_precip package needs much more keyword arguments while the SPEI package makes more use of all the nice logic already available in SciPy and Pandas.\n", + "The standard_precip package does not explicitely support the Standardized Precipitation Evaporation Index, as far as I can see. However, the SPI class in standard_precip could probably be used, even though the naming of `precip_cols` is not universal. In general, the standard_precip package needs much more keyword arguments while the SPEI package makes more use of all the nice logic already available in SciPy and Pandas.\n", + "\n", + "The climate_indices package needs even more code.\n", "\n", - "The climate_indices package needs even more code." + "The SPEI R package also has a similar result but seems to vary a bit more. More research is needed to understand why that is the case. Most likely is the differences in fitting the gamma distribution." ] }, { @@ -441,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -457,7 +532,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -569,7 +644,7 @@ "[544 rows x 2 columns]" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -580,7 +655,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { From 8e29318e0293c498894724b736b8e463fe4e9121 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Fri, 5 Jul 2024 15:28:57 +0200 Subject: [PATCH 2/7] Update example04_package_comparison.ipynb --- doc/examples/example04_package_comparison.ipynb | 1 + 1 file changed, 1 insertion(+) diff --git a/doc/examples/example04_package_comparison.ipynb b/doc/examples/example04_package_comparison.ipynb index 65c6444..f3eca60 100644 --- a/doc/examples/example04_package_comparison.ipynb +++ b/doc/examples/example04_package_comparison.ipynb @@ -14,6 +14,7 @@ "* standard_precip (Python)\n", "* climate_indices (Python)\n", "* pastas (Python)\n", + "* SPEI (R)\n", "\n", "## Required packages" ] From 27be463a7f25b362b49881b242c398ddc8e46c92 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Wed, 18 Sep 2024 10:06:30 +0200 Subject: [PATCH 3/7] mypy src/spei/plot.py:58: error: Argument 2 to "plot" of "Axes" has incompatible type "ExtensionArray | ndarray[Any, Any]"; expected "float | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes] | str" [arg-type] Found 1 error in 1 file (checked 8 source files) --- src/spei/plot.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/spei/plot.py b/src/spei/plot.py index b589553..498e71b 100644 --- a/src/spei/plot.py +++ b/src/spei/plot.py @@ -55,7 +55,7 @@ def si( colormap = plt.get_cmap(cmap) if background: - ax.plot(si.index, si.values, linewidth=0.8, color="k") + ax.plot(si.index, si.values.astype(float), linewidth=0.8, color="k") ax.axhline(0, linestyle="--", linewidth=0.5, color="k") droughts = si.to_numpy(dtype=float, copy=True) From feb7e17c74da9e41bdd2d4fb61dd055dd3bd5503 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Wed, 18 Sep 2024 10:06:54 +0200 Subject: [PATCH 4/7] format with ruff --- doc/examples/example01_indices.ipynb | 4 +-- doc/examples/example02_distributions.ipynb | 5 ++-- doc/examples/example03_drought_NL.ipynb | 8 +++--- .../example04_package_comparison.ipynb | 27 +++++++++---------- src/spei/utils.py | 13 +++++++-- tests/conftest.py | 1 - tests/test_climdex.py | 1 - tests/test_plots.py | 1 - tests/test_si.py | 1 - tests/test_validate.py | 1 - 10 files changed, 33 insertions(+), 29 deletions(-) diff --git a/doc/examples/example01_indices.ipynb b/doc/examples/example01_indices.ipynb index 56dbc4d..01be882 100644 --- a/doc/examples/example01_indices.ipynb +++ b/doc/examples/example01_indices.ipynb @@ -37,10 +37,10 @@ } ], "source": [ - "import spei as si # si for standardized index\n", + "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import scipy.stats as scs\n", - "import matplotlib.pyplot as plt\n", + "import spei as si # si for standardized index\n", "\n", "print(si.show_versions())" ] diff --git a/doc/examples/example02_distributions.ipynb b/doc/examples/example02_distributions.ipynb index ff7b746..4c5a5f9 100644 --- a/doc/examples/example02_distributions.ipynb +++ b/doc/examples/example02_distributions.ipynb @@ -35,10 +35,11 @@ ], "source": [ "from calendar import month_name\n", - "import spei as si # si for standardized index\n", + "\n", + "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import scipy.stats as scs\n", - "import matplotlib.pyplot as plt\n", + "import spei as si # si for standardized index\n", "\n", "print(si.show_versions())" ] diff --git a/doc/examples/example03_drought_NL.ipynb b/doc/examples/example03_drought_NL.ipynb index 601a9ef..0f4ca9d 100644 --- a/doc/examples/example03_drought_NL.ipynb +++ b/doc/examples/example03_drought_NL.ipynb @@ -43,13 +43,13 @@ ], "source": [ "import datetime\n", - "import spei as si # si for standardized index\n", - "import pandas as pd\n", - "import pastas as ps\n", "\n", "import hydropandas as hpd\n", - "import scipy.stats as scs\n", "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "import pastas as ps\n", + "import scipy.stats as scs\n", + "import spei as si # si for standardized index\n", "\n", "print(si.show_versions())" ] diff --git a/doc/examples/example04_package_comparison.ipynb b/doc/examples/example04_package_comparison.ipynb index f3eca60..f8c0d08 100644 --- a/doc/examples/example04_package_comparison.ipynb +++ b/doc/examples/example04_package_comparison.ipynb @@ -40,11 +40,11 @@ } ], "source": [ - "import spei as si\n", - "import pastas as ps\n", + "import matplotlib.pyplot as plt\n", "import pandas as pd\n", + "import pastas as ps\n", "import scipy.stats as scs\n", - "import matplotlib.pyplot as plt\n", + "import spei as si\n", "\n", "print(si.show_versions())" ] @@ -418,11 +418,12 @@ } ], "source": [ - "from rpy2.robjects.packages import importr\n", "from rpy2.robjects import pandas2ri\n", + "from rpy2.robjects.packages import importr\n", + "\n", "pandas2ri.activate()\n", "\n", - "sr = importr('SPEI')\n", + "sr = importr(\"SPEI\")\n", "\n", "spir_res = sr.spi(prec_rsum.values, scale=3)\n", "r_spi = pd.Series(spir_res[2].ravel(), index=prec_rsum.index, name=\"SPI\")\n", @@ -471,13 +472,11 @@ "# climateind_spi.plot(\n", "# ax=ax[\"SPI\"], color=\"C2\", grid=True, linestyle=\":\", label=\"climate_indices\"\n", "# )\n", - "r_spi.plot(\n", - " ax=ax[\"SPI\"], color=\"C2\", grid=True, linestyle=\":\", label=\"R package\"\n", - ")\n", + "r_spi.plot(ax=ax[\"SPI\"], color=\"C2\", grid=True, linestyle=\":\", label=\"R package\")\n", "\n", - "ax[\"SPI\"].set_ylim(-3.5, 3.5),\n", - "ax[\"SPI\"].set_title(\"Comparison\"),\n", - "ax[\"SPI\"].set_ylabel(\"SPI\"),\n", + "(ax[\"SPI\"].set_ylim(-3.5, 3.5),)\n", + "(ax[\"SPI\"].set_title(\"Comparison\"),)\n", + "(ax[\"SPI\"].set_ylabel(\"SPI\"),)\n", "ax[\"SPI\"].legend(ncol=3)\n", "\n", "(spi - standardp_spi.iloc[:, -1]).plot(\n", @@ -679,9 +678,9 @@ ")\n", "sgi.plot(ax=ax[\"SGI\"], grid=True, linestyle=\"-\", label=\"SGI\")\n", "sgi_pastas.plot(ax=ax[\"SGI\"], color=\"C1\", grid=True, linestyle=\"--\", label=\"pastas\")\n", - "ax[\"SGI\"].set_ylim(-3.5, 3.5),\n", - "ax[\"SGI\"].set_title(\"Comparison\"),\n", - "ax[\"SGI\"].set_ylabel(\"SGI\"),\n", + "(ax[\"SGI\"].set_ylim(-3.5, 3.5),)\n", + "(ax[\"SGI\"].set_title(\"Comparison\"),)\n", + "(ax[\"SGI\"].set_ylabel(\"SGI\"),)\n", "ax[\"SGI\"].legend(ncol=3)\n", "\n", "(sgi - sgi_pastas).plot(ax=ax[\"DIFF\"], color=\"C3\", label=\"SGI - pastas\")\n", diff --git a/src/spei/utils.py b/src/spei/utils.py index a524dd2..1974fb1 100644 --- a/src/spei/utils.py +++ b/src/spei/utils.py @@ -3,9 +3,18 @@ from typing import Union from numpy import array, nan -from pandas import DataFrame, DatetimeIndex, Grouper, Index, Series, Timedelta +from pandas import ( + DataFrame, + DatetimeIndex, + Grouper, + Index, + Series, + Timedelta, + concat, + infer_freq, + to_datetime, +) from pandas import __version__ as pd_version -from pandas import concat, infer_freq, to_datetime def validate_series(series: Series) -> Series: diff --git a/tests/conftest.py b/tests/conftest.py index 54802d1..3cfd9d5 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,6 +1,5 @@ import pytest from pandas import Series, read_csv - from spei.si import spi diff --git a/tests/test_climdex.py b/tests/test_climdex.py index 0d359c6..1183e6f 100644 --- a/tests/test_climdex.py +++ b/tests/test_climdex.py @@ -1,5 +1,4 @@ from pandas import Series - from spei import climdex diff --git a/tests/test_plots.py b/tests/test_plots.py index c07ef45..bd921bb 100644 --- a/tests/test_plots.py +++ b/tests/test_plots.py @@ -1,6 +1,5 @@ import matplotlib as mpl from pandas import Series - from spei.plot import monthly_density from spei.plot import si as plot_si diff --git a/tests/test_si.py b/tests/test_si.py index 47a5b75..6e75ab6 100644 --- a/tests/test_si.py +++ b/tests/test_si.py @@ -1,6 +1,5 @@ from pandas import Series, Timestamp from scipy.stats import norm - from spei import SI, sgi, spei, spi, ssfi diff --git a/tests/test_validate.py b/tests/test_validate.py index 17ea6dd..f459336 100644 --- a/tests/test_validate.py +++ b/tests/test_validate.py @@ -2,7 +2,6 @@ import pytest from pandas import DataFrame, DatetimeIndex, Series, Timestamp, to_datetime - from spei.utils import validate_index, validate_series From 6de087e9f5485c7b51345be601968c54602a8df8 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Wed, 18 Sep 2024 10:07:19 +0200 Subject: [PATCH 5/7] remove black, isort and python3.9. add python3.13 --- .github/workflows/tests.yml | 22 +++++++---------- README.md | 21 +++++++---------- pyproject.toml | 47 +++++++++++++++++-------------------- 3 files changed, 38 insertions(+), 52 deletions(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 8d3c801..862f6f4 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -12,11 +12,6 @@ jobs: fail-fast: false matrix: include: - - name: Test suite with py39-ubuntu - python: "3.9" - os: ubuntu-latest - toxenv: py39 - experimental: false - name: Test suite with py310-ubuntu python: "3.10" os: ubuntu-latest @@ -32,23 +27,22 @@ jobs: os: ubuntu-latest toxenv: py312 experimental: false + - name: Test suite with py313-ubuntu + python: "3.13-dev" + toxenv: py313 + experimental: true - name: Type check with mypy - python: "3.9" + python: "3.10" os: ubuntu-latest toxenv: type experimental: false - - name: Formatting with black + isort - python: "3.9" - os: ubuntu-latest - toxenv: format - experimental: false - - name: Linting with flake8 + ruff - python: "3.9" + - name: Formatting and linting with ruff + python: "3.10" os: ubuntu-latest toxenv: lint experimental: false - name: Codacy Coverage Report - python: "3.9" + python: "3.10" os: ubuntu-latest toxenv: coverage experimental: false diff --git a/README.md b/README.md index dc497a1..7b773c3 100644 --- a/README.md +++ b/README.md @@ -10,17 +10,14 @@ [![Tests](https://img.shields.io/github/actions/workflow/status/martinvonk/spei/tests.yml?style=flat-square)](https://github.com/martinvonk/SPEI/actions/workflows/tests.yml) [![CodacyCoverage](https://img.shields.io/codacy/coverage/908b566912314666b84e1add22ea7d66?style=flat-square)](https://app.codacy.com/gh/martinvonk/SPEI/) [![CodacyGrade](https://img.shields.io/codacy/grade/908b566912314666b84e1add22ea7d66?style=flat-square)](https://app.codacy.com/gh/martinvonk/SPEI/) -[![MyPy](https://img.shields.io/badge/type_checker-mypy-2A6DB2?style=flat-square)](https://mypy-lang.org/) -[![Format: isort](https://img.shields.io/badge/imports-isort-ef8336?style=flat-square)](https://pycqa.github.io/isort/index.html) -[![Format: Black](https://img.shields.io/badge/code_style-black-black?style=flat-square)](https://github.com/psf/black) -[![Linter: flake8](https://img.shields.io/badge/linter-flake8-yellowgreen?style=flat-square)](https://flake8.pycqa.org/) -[![Linter: ruff](https://img.shields.io/badge/linter-ruff-red?style=flat-square)](https://github.com/charliermarsh/ruff) +[![Typed: MyPy](https://img.shields.io/badge/type_checker-mypy-2A6DB2?style=flat-square)](https://mypy-lang.org/) +[![Formatter and Linter: ruff](https://img.shields.io/badge/linter-ruff-red?style=flat-square)](https://github.com/charliermarsh/ruff) SPEI is a simple Python package to calculate drought indices for time series such as the SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evaporation Index), and SGI (Standardized Groundwater Index). This package uses popular Python packages such as Pandas and Scipy to make it easy and versatile for the user to calculate the drought indices. Pandas Series are great for dealing with time series; providing interpolation, rolling average, and other manipulation options. SciPy enables us to use all different kinds of [distributions](https://docs.scipy.org/doc/scipy/reference/stats.html#probability-distributions) to fit the data. For the calculation of potential evaporation, take a look at [pyet](https://github.com/phydrus/pyet). This is another great package that uses pandas Series to calculate different kinds of potential evaporation time series. -Please feel free to contribute or ask questions! +Please feel free to contribute or ask questions! If you happen to use this package, please cite: Vonk, M. A. (2024). SPEI: A simple Python package to calculate and visualize drought indices (vX.X.X). Zenodo. https://doi.org/10.5281/zenodo.10816741. @@ -47,14 +44,14 @@ To get the development version download or clone the GitHub repository to your l ## Literature -1. B. Lloyd-Hughes and M.A. Saunders (2002) - A Drought Climatology for Europe. DOI: 10.1002/joc.846 -2. S.M. Vicente-Serrano, S. Beguería and J.I. López-Moreno (2010) - A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. DOI: 10.1175/2009JCLI2909.1 -3. J.P. Bloomfield and B.P. Marchant, B. P. (2013) - Analysis of groundwater drought building on the standardised precipitation index approach. DOI: 10.5194/hess-17-4769-2013 -4. A. Babre, A. Kalvāns, Z. Avotniece, I. Retiķe, J. Bikše, K.P.M. Jemeljanova, A. Zelenkevičs and A. Dēliņa (2022) - The use of predefined drought indices for the assessment of groundwater drought episodes in the Baltic States over the period 1989–2018. DOI: 10.1016/j.ejrh.2022.101049 -5. E. Tijdeman, K. Stahl and L.M. Tallaksen (2020) - Drought characteristics derived based on the Standardized Streamflow Index: A large sample comparison for parametric and nonparametric methods. DOI: 10.1029/2019WR026315 +1. B. Lloyd-Hughes and M.A. Saunders (2002) - A Drought Climatology for Europe. DOI: 10.1002/joc.846 +2. S.M. Vicente-Serrano, S. Beguería and J.I. López-Moreno (2010) - A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. DOI: 10.1175/2009JCLI2909.1 +3. J.P. Bloomfield and B.P. Marchant, B. P. (2013) - Analysis of groundwater drought building on the standardised precipitation index approach. DOI: 10.5194/hess-17-4769-2013 +4. A. Babre, A. Kalvāns, Z. Avotniece, I. Retiķe, J. Bikše, K.P.M. Jemeljanova, A. Zelenkevičs and A. Dēliņa (2022) - The use of predefined drought indices for the assessment of groundwater drought episodes in the Baltic States over the period 1989–2018. DOI: 10.1016/j.ejrh.2022.101049 +5. E. Tijdeman, K. Stahl and L.M. Tallaksen (2020) - Drought characteristics derived based on the Standardized Streamflow Index: A large sample comparison for parametric and nonparametric methods. DOI: 10.1029/2019WR026315 Note that the method for calculating the drought indices does not come from these articles and SciPy is used for deriving the distribution. However the literature is helpful as a reference to understand the context and application of drought indices. ## Alternatives -There are other great packages available to calculate these indices. However, they are either written in R such as [SPEI](https://github.com/sbegueria/SPEI) or don't have the Standardized Groundwater Index such as [climate_indices](https://github.com/monocongo/climate_indices). Additionaly, these packages provide ways to analyse spatial data and calculate potential evaporation. This makes these packages complex, because it is easier to only deal with time series. However, support for spatial data is something on the to-do list so help is appreciated. +There are other great packages available to calculate these indices. However, they are either written in R such as [SPEI](https://github.com/sbegueria/SPEI) or don't have the Standardized Groundwater Index such as [climate\_indices](https://github.com/monocongo/climate_indices). Additionaly, these packages provide ways to analyse spatial data and calculate potential evaporation. This makes these packages complex, because it is easier to only deal with time series. However, support for spatial data is something on the to-do list so help is appreciated. diff --git a/pyproject.toml b/pyproject.toml index 226658e..979abc9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,10 +13,10 @@ requires-python = ">=3.9" dependencies = ["numpy", "scipy", "matplotlib", "pandas"] classifiers = [ 'Programming Language :: Python :: 3 :: Only', - 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3.10', 'Programming Language :: Python :: 3.11', 'Programming Language :: Python :: 3.12', + 'Programming Language :: Python :: 3.13', 'Topic :: Scientific/Engineering :: Hydrology', 'Intended Audience :: Science/Research', "License :: OSI Approved :: MIT License", @@ -29,22 +29,15 @@ homepage = "https://github.com/martinvonk/spei" repository = "https://github.com/martinvonk/spei" [project.optional-dependencies] -linting = ["flake8", "ruff"] -formatting = ["black[jupyter]", "isort"] +ruffing = ["ruff"] typing = ["mypy", "pandas-stubs"] pytesting = ["pytest>=7", "pytest-cov", "pytest-sugar"] coveraging = ["coverage"] -dev = ["spei[linting,formatting,typing,pytesting,coveraging]"] +dev = ["spei[ruffing,typing,pytesting,coveraging]"] [tool.setuptools.dynamic] version = { attr = "spei._version.__version__" } -[tool.black] -line-length = 88 - -[tool.isort] -profile = "black" - [tool.mypy] mypy_path = "src" @@ -56,13 +49,16 @@ ignore_missing_imports = true pythonpath = ["src"] [tool.ruff] -line-length = 88 +extend-include = ["*.ipynb"] +lint.extend-select = ["I"] +show-fixes = true +fix = true [tool.tox] legacy_tox_ini = """ [tox] requires = tox>=4 - env_list = format, type, lint, py39, py310, py311, py312 + env_list = format, type, lint, py310, py311, py312, py313 [testenv] description = run unit tests @@ -70,14 +66,6 @@ legacy_tox_ini = """ commands = pytest tests - [testenv:format] - description = run formatters - basepython = python3.9 - extras = formatting - commands = - black src --check --verbose - isort src --check - [testenv:type] description = run type checks basepython = python3.9 @@ -85,13 +73,20 @@ legacy_tox_ini = """ commands = mypy src - [testenv:lint] - description = run linters - basepython = python3.9 - extras = linting + [testenv:ruff] + description = run ruff checks + basepython = python3.10 + extras = ruffing + commands = + ruff check --extend-select I --preview + ruff format --check + + [testenv:ruff_fix] + description = run ruff locally and fix issues + extras = ruffing commands = - flake8 src --max-line-length=88 --ignore=E203,W503,W504 - ruff check src + ruff check --extend-select I --fix + ruff format [testenv:coverage] description = get coverage report xml From 46fbb28f15d645d2f100037be23139ed6b9282f8 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Wed, 18 Sep 2024 10:07:28 +0200 Subject: [PATCH 6/7] update version to 0.5.0 --- src/spei/_version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/spei/_version.py b/src/spei/_version.py index 53e89ca..1580ed7 100644 --- a/src/spei/_version.py +++ b/src/spei/_version.py @@ -1,7 +1,7 @@ from importlib import metadata from platform import python_version -__version__ = "0.4.2" +__version__ = "0.5.0" def show_versions() -> str: From 4efa368741da6bda496e443aada0f8c4d817a918 Mon Sep 17 00:00:00 2001 From: Martin Vonk Date: Wed, 18 Sep 2024 10:15:41 +0200 Subject: [PATCH 7/7] add some more tests to up coverage --- tests/test_si.py | 75 +++++++++++++++++++++++++++++++++++++++++- tests/test_validate.py | 35 ++++++++++++++++++-- 2 files changed, 107 insertions(+), 3 deletions(-) diff --git a/tests/test_si.py b/tests/test_si.py index 6e75ab6..c7b5fac 100644 --- a/tests/test_si.py +++ b/tests/test_si.py @@ -1,6 +1,7 @@ -from pandas import Series, Timestamp +from pandas import DataFrame, Series, Timestamp from scipy.stats import norm from spei import SI, sgi, spei, spi, ssfi +from spei.dist import Dist def test_spi(prec: Series) -> None: @@ -32,3 +33,75 @@ def test_SI(prec: Series) -> None: si.pdf() dist = si.get_dist(Timestamp("2010-01-01")) dist.ks_test() + + +def test_SI_post_init_timescale(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=30, fit_freq="ME") + assert si.series.equals( + prec.rolling(30, min_periods=30).sum().dropna() + ), "Timescale rolling sum not applied correctly" + + +def test_SI_post_init_fit_freq_infer(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=0) + assert si.fit_freq is not None, "Frequency inference failed" + + +def test_SI_post_init_grouped_year(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=0, fit_freq="ME") + assert isinstance(si._grouped_year, DataFrame), "Grouped year DataFrame not created" + + +def test_SI_post_init_fit_window_adjustment(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=0, fit_freq="D", fit_window=2) + assert si.fit_window == 3, "Fit window not adjusted to odd number" + + +def test_SI_post_init_fit_window_minimum(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=0, fit_freq="D", fit_window=1) + assert si.fit_window == 3, "Fit window not adjusted to minimum value" + + +def test_fit_distribution_normal_scores_transform(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=30, fit_freq="ME", normal_scores_transform=True) + si.fit_distribution() + assert ( + not si._dist_dict + ), "Distribution dictionary should be empty when using normal scores transform" + + +def test_fit_distribution_with_fit_window(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=30, fit_freq="D", fit_window=5) + si.fit_distribution() + assert ( + si._dist_dict + ), "Distribution dictionary should not be empty when using fit window" + for dist in si._dist_dict.values(): + assert isinstance( + dist, Dist + ), "Items in distribution dictionary should be of type Dist" + + +def test_fit_distribution_with_fit_freq(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=30, fit_freq="M") + si.fit_distribution() + assert ( + si._dist_dict + ), "Distribution dictionary should not be empty when using fit frequency" + for dist in si._dist_dict.values(): + assert isinstance( + dist, Dist + ), "Items in distribution dictionary should be of type Dist" + + +def test_fit_distribution_invalid_fit_freq_with_window(prec: Series) -> None: + si = SI(prec, dist=norm, timescale=30, fit_freq="M", fit_window=5) + try: + si.fit_distribution() + except ValueError as e: + assert ( + str(e) + == "Frequency fit_freq must be 'D' or 'W', not 'M', if a fit_window is provided." + ) + else: + assert False, "ValueError not raised for invalid fit frequency with fit window" diff --git a/tests/test_validate.py b/tests/test_validate.py index f459336..4a49482 100644 --- a/tests/test_validate.py +++ b/tests/test_validate.py @@ -1,8 +1,8 @@ import logging import pytest -from pandas import DataFrame, DatetimeIndex, Series, Timestamp, to_datetime -from spei.utils import validate_index, validate_series +from pandas import DataFrame, DatetimeIndex, Index, Series, Timestamp, to_datetime +from spei.utils import infer_frequency, validate_index, validate_series def test_validate_index(caplog) -> None: @@ -50,3 +50,34 @@ def test_validate_series_df_2d() -> None: with pytest.raises(TypeError): df = DataFrame({"s1": [1, 2, 3], "s2": [1, 2, 3]}, index=to_datetime([1, 2, 3])) validate_series(df) + + +def test_infer_frequency_monthly(): + index = DatetimeIndex(["2020-01-01", "2020-02-01", "2020-03-01"]) + assert infer_frequency(index) == "M" + + +def test_infer_frequency_weekly(): + index = DatetimeIndex(["2020-01-01", "2020-01-08", "2020-01-15"]) + assert infer_frequency(index) == "W" + + +def test_infer_frequency_daily(): + index = DatetimeIndex(["2020-01-01", "2020-01-02", "2020-01-03"]) + assert infer_frequency(index) == "D" + + +def test_infer_frequency_no_infer(): + index = DatetimeIndex(["2020-01-01", "2020-01-03", "2020-01-07"]) + assert infer_frequency(index) == "ME" # Assuming pandas version >= 2.2.0 + + +def test_infer_frequency_non_datetime_index(): + index = Index(["2020-01-01", "2020-02-01", "2020-03-01"]) + assert infer_frequency(index) == "M" + + +def test_infer_frequency_invalid_index(): + index = Index(["a", "b", "c"]) + with pytest.raises(ValueError): + infer_frequency(index)