From 27b95d72167c33c230ce2e8d42201dc5abb9a9ba Mon Sep 17 00:00:00 2001 From: Martin Schultz <m.schultz@fz-juelich.de> Date: Sat, 16 Jan 2021 17:35:05 +0100 Subject: [PATCH] Small fixes in user input last cell --- data_preproc_mapvis.ipynb | 248 +++++++++++++++++++++----------------- 1 file changed, 140 insertions(+), 108 deletions(-) diff --git a/data_preproc_mapvis.ipynb b/data_preproc_mapvis.ipynb index f79931c..5187e2f 100644 --- a/data_preproc_mapvis.ipynb +++ b/data_preproc_mapvis.ipynb @@ -67,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -80,7 +80,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -238,26 +238,26 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# specify date, variable and model level\n", "DATE = 30 # use integer index for simplicity\n", - "VAR = 'u'\n", + "VAR = 'q'\n", "LEV = 132 # use index for simplicity" ] }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "U component of wind (601, 1200) -27.909231 31.76069 0.19587262\n", + "Specific humidity (601, 1200) 2.408882e-05 0.023921737 0.0068351426\n", "lon: [-179.7 -179.4 -179.1 -178.8 -178.5 -178.2 -177.9 -177.6 -177.3 -177. ] [177.3 177.6 177.9 178.2 178.5 178.8 179.1 179.4 179.7 180. ]\n", "lat: [90. 89.7 89.4 89.1 88.8 88.5 88.2 87.9 87.6 87.3] [-87.3 -87.6 -87.9 -88.2 -88.5 -88.8 -89.1 -89.4 -89.7 -90. ]\n" ] @@ -285,12 +285,12 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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cel4I4E4AfwngVgC3H/59A8Gz2CCNJQ0O1v4N29oZs/jHLKG5ltKUTb0cBnTqlRDqKBilk8lQ/o/I95YbAn1lGFphqin3VYR+6fP3IP5nXXloac3mYNiqhap/njkP9gKFD/9blVKvBXAXgEcA/D6OLPZPAvAapdTX42hS8OW1z+II1a5+YQwhkZNqYa+NupPyvNR7cKfFRNm+VyySzyxCZaPGhz63bueI/pF1cbTYt7HT02MC0Ls+25PFUPlza2OjgwnMQo74X+F99wZJlB6t9SsBvNL6+CKOrP27wtUI9j4JSBVkPXC5N1BYfVta3kYIq9b7HSisSjnf632mQAoU7cAl+mrqS+j8BQ6TzVShXyK4W957JVL2IXFcDZBDtvJY5T2Ey8hJux2QVYAr4WINibnYlIjEmk25HATVCHpsIOMgOFqw1eHQYXAldZhrXcwR27krFXsX8rnkTDK5TAB6uOKKZVzgigj+AcjJfnxEfwyXYEo5+ZaalayPe63zQh96TtKFI3JP/h49ARi5B2+WsU9YDxH8gxHrfz2lg0fpAB+7P7Vw2MT+tfdcBAA8fOPJ6LUbNRMAajcYqdv9KS0/zlZ+F9QRt2Z691HuaiFXzdy8HDUBGGV8E9EvjEAEPzMk+k97Wh+61FosbcIfCIt/YMxmwtXhFOmHynUs10LLgZ5navjgkk8c96hslOwHGTEB6C3+RfQLvRHBz5Q9CH+qTU6mwC6NXe+7b02aSp7p4sINyuvSc+09F6Oi3yQ3lCBnIeGi5QCaK1JKaJ3XIV9/7nCshz3SxLVsatoax7IE1h5vBUEEP3P2cCIehaXD3LyYcxiWSYuBlcLav4l0l7C/9p6L2aLfvG9P0d+yLo8U+r2eVWKF5yoWU+AqCnuT6h7DdXKe0uZHWrpHjq9i5Rd6IoJ/AvawyZdK9APhUIWlcfcp0mWnhYISoV8CpegHaOtxqwGTm1jmlp6WcBSuHJhpg3FOGzevbS2AVx1DBSGGCP7JWFn8U1s7uA6KqYO2y43Htsj3PICI0oLI2WWNa73ZCyL2y+CWb7krensV+j0nO8K+EcE/MaMP+Wox+eC+xEm5PB0S/ili3/dZy0kAR7cBqgFThP44uNUp7swSRck3Rozo42dwj+V0SKWwHiL4F6PVJCDW8XC22FKSMmjkbkZ2uR7VRNPZvpsi/FP9+FvBYRCeQTiFmDESEzeBn7LpnxszpRUQ8VrCaqf3CmMRwb8DKGL9p3Y8o4W/Kd58vvMlg7v5ndRJVcmJi5SxwEPRfWqgtvJTTVJDddOuF6mrKjPCdQLAUaCG+os9M9oaL1yJCH+BAhH8O6RGlNsdj+se586fKn5Gzw4tJ9ZzLApQiXtTrBMviV9tkyL6S6z8rV17UiapOXXFdJ9aWey7SHm3VpMCbiJ6xCnZMxDqs7i7We4JKQuhhqUFf631ptVJrFyosazGBoiUZ7TouEzrrSlKW8dIr1nRyMmPkvdJcfHhKPpNWg1yKwv9HFqsCnDpB2d32WpNyUok5f1bPntFRPQLpSwn+KlOnmydBi6DoQ21S45LzLburFx5G7KW55ZFK3elnI68ZNNeCxcfjpt4hXpSN4274FQfcs412Cut+mOKfrJ2ZS/03dF7h2oQFx+hhCUE/4wH0Iw4OjwH6s2UHK0SXIS+6xktrf0+0T96A29r7HwS676f0nrAqR8TsT+G1v0k1SSAQ8CAWkT4CzlMLfi5ifgauE8AgHrrP0fRnwPXAWL0YTwzWPlX6itasfJkz4R7XeUCx77OR2paufbhtcw+tgp9mFbwrz6AcwgT16IDmb1j6nX2QUk+UcTmLrXy+0S/WFnngErszzD5m5HWltwVRbCLvbynILiYTvCvLvRtOAh/6k5ydtFvE3qX2s28JaIfCLeTmC9/jeivvb62nruE0d76jBIo3bk49Fk+OKaJA6tavgVBuMxUgn/PAzfXQbR0E5QpzEbEfO5liRy1SSxm7Y9F7hkVy526XHx5kOK/f+09FwEAD994Mvj3Wnz370HLcuUW455DGrggcfbXQspQSGEKwT+L0K+JbJEKhyXzFLeWVIvRZsXubV0akYcl71mzGpJq7QfiAnj7ew/hP7KOu0Q8lbBPfSblBICLX/5I8T+6v6SAKjRmL5dEClLemWvaBYEjUwh+7sTcI2xqB2EOot+kVOzb3xmNTxi3OFW2t7UfqHPz2egVyae0jqfUI997thb2qcRWFlLgIvRHwqmPHIXdz3AVyKX9/+iT3UfCYcwU5oK94Odu3S8J7ddjJYAKl5gPMXMnZAoEs95xdacaRYro77kikAN3sW9ipilH/HPLcxtuBotV4SiCW40PexL+M4+xwljYC36KyCMtsQfX0tjeXAWSaa33dTSuz1N917l2XtzrXQkpfv2p9TfnupI63VMQchT7NhRWf06I6E+nJEIPN+Hbq5+3hf8Km5G5jpHCfLAX/LPhEjc5kwCOhx+1tspwxRbIpkip9UkeNRCNiNmfW6dL8tMnIM0ydLXDGcS+SYrw59iHuJCVszA15520hnvfzT19IWZOu8AbEfwdMAffVD9p+3s2M1nIXOKWS6cWEx325y6hTOFvHhqkW4Qx7b2C0UOEhsrBbnezCf1cZhH9gAh/E67WaC79dQmjjCt2nsXSMHMeC3PAXvCv5laRGhVlu2aWQTtGimvQCHJFhs9CXjsBW2HpOUZqfS7JS7NcYt9dXexvmH0MVT/i2+dCwUxGjBG0Or+EU3+cA9VEkTp0csz11fWMWctAmAu2gn81oW+TI/x9tBogUzq9kg5KOrUwIdHf67CyHD/+Eqj2qvjy6Rz8ebQXoe8iV/yPcP3anrdn0U8x8U+9x8j+mDIiWk2dsfPAlyeU1vleZ89wNLAJY2Er+FtakjiRcgBSCyu/z8UmdbApHZS4dz41gweFxSlUDpQd+Og2VWt99okae2I0+j1bce09F4s28OaIffv/QHjvyt7Feg9SJ/4c+tmStpd6+nbuvWvdSqnzs3X5mO+62sn2QjlsBb9Ja3/j3EEqJS32hCX0jJP3nQgK/5Dopx5kW7uWcLc6UOQlRZnErP3mdbWMnlyXWv1dkyNXfrRcsRhJjuhv4dKT8zchnVXc+6jG1ZQ+KaXP5epW2oLV308oYwrB34KawYl62dFcPi8ZmEsEpimWXMuaNQMOtU8kR2IiOdVSFSKlHEoHsFBaWrv1+DAntj5Lskvcp7z7nt15cq36wnhWEf059DA8uPqKkadAC0JPphH8VFb+kQ3aTr+dFoqly1xCG4xabmBaidS62dLlgcrqv73LKNHvwnSVmkUInbj7PC7ddLr5c0pdewT+uKK8pLbt2d2rRq86CsKKTCP4KeDWAab4fI+YBGyUnl5IcVDMbBMFStFfK2i5+2z6LM7bBMPlDmfmrf1uKfnuEsWtrP4n7j5/xb8+Wk4IVonuJVwmp01vbYbbmMcRs39Z1dovdUEAdib4R5AqAjdSGmXvGOqlLjo1wrVVzOKWPpycrFJUoj/3DImc+x1f4fKvgvkETCyfQ2l++MaTpKI/JvBD11OK/15ugQJvOJVnjUGnx3gX6ldWaRsUQSVWnRDthakEf23D952Uaj+DitooBRwbVO5hIq0IPbc0tBolIfHfawChtvRTuvm4/PLPnT8VzRdfmyqNZrVZ/muFf67Yd32/VPTbbj2leUF5AJYcpiVsUPS7KWP/KsK8BfYqRmk+Ud1HuIxS6tkA/h2A6wD8NYA7tNY/Yvz92wD8IIBTWuuHap41leCnIKXTMIlZFFu63MQalDl5GdX4OPpUp6Snp9tL7kS11JXKRc17ukQjhej31dOctOZGs4pRK/xdYr12EpDDlu7tPWryorYvWdE6KpTBbWwIYdfV2SatMWNhrV6gPGVeuIJHAPxzrfVdSqlrAPyeUuqs1vqdh8nALQDuo3jQ7gR/LqkThFYH1bgacSx8mTRAfthllxpGzsfIgZTS0l+y2Tj0bFPolqTR9vWvsfz32LQbYqToB6Qf2juziH17gur6+wx1OdWwZI9FM7zbymit7wdw/+H/F5RS7wLwLADvBPC/A/h2AG+geBYrwa8uqWglzLGWxgZ8yo1to322R8LRyp/CiM2tVEuilKsAJZSIfru9laQ95ZmU0YV8EXBGh/l0TUxcae0t+muMESJA+ELVV7bub223Xaq65LtX6Bkp3gDU5DyDSvjPMiGaAaXUGQDPA/BWpdSXAniv1voPlKLRqqwEv0lNJUod8F3XzRDdwp702L+PaICziv5UQh2+i9TIS7Vl1Vv4m3XN1VZ8bW+GdpUDt4kAl9CcsTaSskdJBAQ/SoT6agdd5Yp+DuNyCpR7djjzoU88Aa/9yGcPePIvPU0pdafxwR1a6zvsq5RSTwLw8wC+FUduPt8J4L+hTAlbwQ+MsfjUWMS4MKpTmUH0l6TRFbKNCqqyosz72Cpa6O+xtmO+b44gOHnfiWHnAuS4CPUM/9kaqrrp28AeqmMcxRHHNPUm1wVvhNDP7add/Vmqi+72XZ9WmUX0b3BP36Q8pLW+OXSBUuqxOBL7r9Zav04p9V8AeA6Azbp/GsBdSqnP0Vo/UJoQ1oJ/o3clnFH0c2mko11NUig5lTZ1EBlZDpR5nxLNimICxM3yF2r3pX3ChRseVzRZ8U0UuFjzS8jZ68RJfHBKy15pGZ7Td+8UwR7bDOvav+X6OxekrvdFHSn6nwDwLq31DwOA1vqPADzduOYcgJt3E6Unp6HXbirkKvbNhsi9Qc4g/HPoGc61Fsql9NAgm+K7SnE2Qer3Ss4MyG3r5eHsLv/f9T6u9M4s7GOknqfARXxwSMMoOLnl9IjJH3t+6G+hCDi+MYQqKlbrOtoqMImAzwfwNQD+SCn1tsNn36G1/mXqB7EV/LVWdq6iXZibWQZ+ysE5d5AdMSjb7b1n+8+e1B6C91xZRmmTgFxMd6ScPOlZzyW++hzMaLxJrTtUIjzlO649XL5of7H7uVzkatqK7Kvpj9b6LQCCnbPW+gzFs9gKfmCca8020LZ+NoX1kzulp/S2SgNncv1je+5xKRX99oCWy/a9kPjt0UeU5PEt190d/PtZ85fTV5b5yftOHHuvkglA6aSB2wDPLT17hMuqbQuDguuerjrXoh6mvkuKu5DvulZpEuaCneC3Byjzd3MAnEUshzqnknSnNGZfaLLRg+aITb2ziH3gyvxJCYPXuyxdz3OV55Zue0NbLub3fOK356Q8l7MP3ATAL/ztz80JwDlcWfbmBCBFxNecRSAIJnY/xKFPzRH9qeOeT/S3xLdHIOQS5LvP9v1WcNZZQhqsBP9VGWPraPGaSotG4rLspjxnhvyihMPAlItrUhSaJI18R1+6zMlKap3LbSeUh3+15uwDN0Wt/cCVE4BN/Nv5uAn/1BWPmnzi1sdyS4+wHr4x1RTmI6IHpkKx+kG9B0vgAyvBH8N28WlZAbnuAbA7nlCnQ705iIIZQndSk5vvOSI+lpczTnpS4dpGXWzWfiDu6mNec4XV//ypR9t/7gblkSfu5hCzVLZyqRjdLwr8sMVzqzri8uGvvV8ppZpqFuPL3plK8AP+pfycCsddKIQGvdQlR85RL3r49bcQuiXh1CisQjWTJJdrUO5eAd99c/4+68QjpdxyfZtTLf6AIfwfuMnr5mVa8V1924z9Xc+IIKP7Q6E9nK3yQL90hSYwsbYWWj2YacV1z0wn+DdqKpf9XW4Dom8pkep+e4BC1NpQWGJi7li++9aK/u0etfcqJRTar5Woo9zomzJRzhH+psUfiFv9b7nu7mPfMeHWh5Xg81vmuFIpjKdkbPRFxdkj1P3uCn3Q6rAS/J84URZLu5beE4DcDUcp98u5fm+kbIBNhWqAKFktqI2SsSdXKtP9z9WPlEQASxWaJeUU2+BrMjoWeW9yLZGCH04x9SkoFf32/3MCYcxMznkyvTcwC+15zOgElHDtPRdJjqu/cIO64mf7jAp7t735u28nfgm220jsWk4Nt9fAM0Lstsrnc+dPXfFTA2W+lKQnNPCUto9UQ8E19+pHf1LJKdOSsjn7wE1BS/4Gpzj5vVlBeAl0UIylvnHRvDe3dpDC9l4lad+bYWEPsLLwp7AJ/ZpTKH2ivlbsl1gJqBoVtzosAAAgAElEQVSVNMw0eli4WoVb9UFh+Q/lR+mm41I/fnuSnJOfpng3/28aCHqeYFtaNikW/5mFiDCGVSz7Llq7v273n3XCSSn6pe+ZE7aCP2R143jkvKsTSLW4C+tQU56lgwmFlb5G9Pu+lyIuUiJh+Hxu7by2+wzfKuC191w81oekuvjUTMpKyinH2i99ibB3KNuC3efN0r6o09krWpHQHraC38fsYr9mJ7zrmbWHGu2h8ZrCk5tl33WPlDJp4aJEbenPJeVgmRA5kSJcoj+Gy5c8d+Ujt9xWtsgKQitauqNwHztbvDvXdxXymE7wx/BZ6XxL/bHvhUg9vc/EZTWwxbu5dBhaTluFFWLzU3awMSHZMq9coj80gFAI0tL67Jr0mqL/4RtPJu/16RVhIqWul+apWPoF4TKUwpd7ZB87ba3976WPmROWgr9FTP1e0X82sebrFFx+gaH/p+6qr7H0p8aTb9nRtRT9lFF69kBKfnHKT7sNmNF5bCu+aw9QS1ceF63zTjbbCcIRNS45obHavOfoCUBPY5MwN6wE/1WX0sV4jUVub4dExARASiPv0QnUbj5NxXf/HiI2ZYLGucPlPCAcT9dxH/8cN56R71lrTRRrvyC0Z7R/e6nrcItnCvxhJfg3QtZ4qqX3Hkv4LcRRaOVgxIbRFlBb+1NP9u2xEjBLZ2nnRWqEilaDX+pBaldcB/u643nvmvjnpDslnnUulHWEQvhz6RcEoYZWK19mG+vp9uN6l5z3K+kbQtfuyYg6K6wEv33wFnDZGt/LxzZnCdAngGKNvkRcb51V6N4rWfWorP2pYl84ji2yc8T+9nvpwJc6MYtdZ2JOAGz3HyB/kA4JCG5RLUJpmHW1SRByCY3JFPc2z8Rx7c0LPbdnW4v1B669hzHkpF3+kAh+pdRTAPw4gM8EoAF8HYA/BvBzAM4AOAfgK7TWHyq5f6gipQr0ksbkW66rtaRv/+b6BPo6lNRn5lzHZaCvsfbPKPZT8n3EJufS1Y9WK0eh9/fFrj97+NecvNQO9ClWw9K22qsN+vIi9/myV0aYFWpjWcrYXmMgoVyxc/VhKxgNheNQWfh/BMB/0Fq/RCl1AsATAHwHgF/TWt+ulHo5gJcDeFnJzVMbQYtNNaXLgKmivQUUS5fcXHyAeUR7D1rniUs0m4LZha/e9axLoYOqbrnubpx94KYrDl9LTVdo38cqK2vme5SUl4h9oZYeByP2xuXy04oSb4jZ+y0hncfU3kAp9WQAfx/ATwCA1vqS1vrDAF4M4FWHy14F4Mty7rtFuqkVCi2Fhm/ZK3cDrPmuFP7DVPTooFqyDR49JgqjJkfnzp+64qclm5i28/PM6QdZTMZCYt91TWqaY25D2w9VnwWMXWHjMtEXhN5QtV/fvWvYxmPfmGyL/dp3EZ/89aCw8P9NAA8C+DdKqb8D4PcAfAuAT9Za3w8AWuv7lVJPd31ZKXUbgNsA4OprnwrgeMPoNev3WbZSwnOVUrPU30uMx5b6e1lwS6zauUKUwi1hpGBq7cZkW8lNzpx+EOdwaqpJoq+8S/LOtWG4xAVPEISx1ETH2kR5aJUfoB2/XWLfR+y59plF4pu/DtUWfhxNGj4bwP+ptX4egL/EkftOElrrO7TWN2utb37MU59wRUW1LYctLYm1bja5u/NTZt+xGX3IdaeluDDTZeZbaANj7F1y4Lrc29I6ZJKaj63yyWVJv+W6u3HLdXfjzOkH8YzPe+/uxe3WT/WqE4KwAj1WKluTGqwjtok35fNr7tVZYj/Edi/X58IaUAj+8wDOa63fevj9tTiaALxfKfUMADj8+wGCZwFoY7nkuAyfstpg4rLE5wqOWrcEW9zXhg7z0XJQ4OCesuHKwxwLUUvRb/7Yn28uLhxJcf2huKdtoIhtjOuxMsLF/UoQVqbnKnhM7Kc8NybqRfSvQbVLj9b6AaXUe5RSn6a1/mMALwTwzsPPrQBuP/z7hpz7xgal1LjcOdRu7t0oGVBTNkLGGnMo/a4NeTGBQbH5tyUjotX0xlcGOXW1JJ/OPnBTlTC+5bq7cRauWPhxepTp5pq0Pa+2D9nu5cPXdkMWPV8Zu1wcU9we7dXS2S2pgjCKVDdjs33njL2u79vkuNuE+hoqMc/VwCNchsLCDwDfBODVSqk/BPBcAN+LI6F/i1LqTwDccvi9CebGuVkJpZ/SLcCeIMTuHftbadqoJhKtRMvMdclFbj5RWME3S3/LPRcmMdHd6rk19y4JfUmdBkEQ0rEnzjnEXHRzIvqExH6q26dY7vcFSVhOrfXbANzs+NMLKe6fw2jLVe3AuqXfdZ+W75UTks8XnWgUrSz9o+vSKChdXsxNvrG8pCjDmpWJluXdYkXSpOSee63fglCKN1gBQTsqHUdD43FshYAKse7PAauTdoUjfMLn2MmhnQbr2vjcPijv1yo6DQdR1MsKDLT1bz+LPnW2VvS3xnYHyHGd24MbmyAIaZQa38Syv0+oXHqEReDut58CtajkJLBmdl0rcfFpRY37DxVmPuSE/i2JZDJ60ioIe6TnOUCpiNjfL2LhZ0iqFa+l9dlnfXd9XjNJmCU+eWijpEmv6EEcVh5KyHHxqXlGS8z7104cSk79rXlGa9ciQViZkjbj2qhrtvWSsTM1QIcgmIjgJ4LajWQk5uEh2+8mM4j0ln79sb/PKqRaC2XzOb7DuyjuHaNUpOfkT279C12bW59SXQIFQejHNq62Gjtdcf5F9AsmLF16KDa+9oKLi8LMtOqURh3i0qo+mO/ie69Z6mKvWPgmZx+46VGxb58fYN7D93kOIw0AKXV+1kkpd1znkFAeOiiMg6JNcwt4kYO4As3Pshb+XhE39soMVv6NrR6sXm6zvZ8ZC5/iXiF8z/F9jzJtPnJcg3L6s9nqwQpQxFU3maVvHcGIsYd7mxo1cZB6OhcsLfwrHK/di5EdEaXlqkeH1bNOtbTyt3qPERtZqeL9h2jpwtPLDSoV7sJkZnpa7nPvu6fVhJpT4EvhrEm2CVBqvqQe1mV/xz7RV8T+fLAU/BscGxnHAbVFmnKO6DYP4KrpCFYT/a1p4U42SvSXCudUUW5fl/OeXER9zunjIVZqAz0YKaBjzw2lbWXRXwqnyRBV3P2WmEK/dnwXxjOFS489QIUiTaQeeV0CR7HfkpRNP6FJAMBz0FkhlvkKEXtsHo3XnyjGc4W46aaT+t0cK3/pZIlDiFDBDYf+y+XCkuNCtHeB5sqrlfKF+j1sS76wDlMIfpuQuFlB+OTS4wRegMfgR0Vr0d+7HlK+S83BVSm85Ml3Pfr/137ks4/9PUVAt1wRSCV38uD7PgVi3aeHU39Xk5aVxG0JvvDSs+ULZVov3KCObcIVob8+Uwp+YQyrhfma1dLfI82tRf/GJv5Dwp8jplgfbaGfsQ5zZ6Z+jvNqKldmG8tSz8QpxXTbiTFTvglXwkrwq0vKG/td6EPMPWS1cpktgk8sXvss72FjWv1rcU0eKBkt8EsR634aMwkaibs+BrufrTmQa8OlfUKinmIsTrXqS71aA7abdjltrtnYy4BJKRpzOqWRkwmqsh210Xx7JuWzZxW2L3nyXccmENtntROLmJtRy1WJ0rLlGPyAK9zGnFx8fSjH8XQ0KeONayxM/awkPa5T7HMwyzhW3iL29wdbwb/Rs6Paop6YPzZUAyelMKCK1tLKOjzLqsAmjDiIo5wytdObckBXKrOKfoBO5G+02kxci6+MudTlWVhJ2Piiqaz0jj1wtZ9QmxodJnv7N+e8h1Kxf829+tiPwBtWgv+qgC5sHV84dBy9PQHgOohydueYRfRvlJQxVb2gKEdT7InwuxJK9yEuhCZ9M5Mbi77HczgRCskZ+5tY/cvx9akztbuaMVnE/Zyw8uFPxddJ9RCVpugvEWatrX+cQzTO5mMaCgcbu7b2ub5n2XsOeoSlpd7A+9qPfPaSonujxapISnlybfc9qO1XZuubTEw/75J3mC1aDQVUewV7hgWnJPW9Xe3CFPumW5BMAvjDSvB/orK/7TkRKLXCmuKpNn53K1qH+Zx1YPUJ8Rb5Fbtn7O/UE79eUXt68ZIn35W9udeM4+8i1+Un5XruwqEFo0JQ9ghB7BJFJSef2uS4cLiuT8231YJqrPY+KVBv9g19JvCClUvPXmgt8EsnI6NdP2aYCNhuMlwFmbkSwNHVq3Uknd6kbtgVsR/G7gNKDAQU/UjPU0VnsoyuIoxTDjKbYTzKpaT87HYgwn5eWFn4RzFCELW2mFKEDRvBDMvLnPPSTBt1vV7Nyj+C1Mk+5zq2Nyjj3LsOPAKORH8PIeUL/bj9m9r3+izjs1jMQ2VZU86j2m1KmmvLZObVeeGIXVj4uVbSsw/cRGLtT7EucrTyCvtmNis/N9e7FbHjytufhb7X2iWnl8W/N+Z77WHjs5lO+91neYdRmCtfZvtctW2sxm4s/D7rhQhhfsxg5bcx6xFH6yzXer6Jfg6beEOn/sbi71PDefN9a2ravmmFbNWP1Fo6e210DMXkz7nedZ2ZxyuwwmnFoXegaAeuDcmzjdN7ZzoLvyv2q8SCFUZii2mu4poznKz9rsmHLepbH7IVQ+pYGq0EHJVFs8SNx2dlta8JUWvNDp3+OoMI9KVzhrS7cK2MUWL2N6FzigTeTGXhTxXzLn/IWRuywBuunR7XdIXoHa7TjNST8lzqTblCPaNXAykswzHRH3u/mvev8bmf0Sruik4E8HmXFqGfXa5uVG1mzyuRMzKV4C9ldbGfKi44NM7RHeoeoBL7IyzYnFx8RsOhvXImxTVls2S3HgNSor6Y11H2g7nv50oDhfDnwuhJYCmxfjunP9jcrlqK/ZJ0CWOZRvDnuOqYFpNY5S49QEsoo0es655wqz8zi32THsLf50aU6l40MmrRXgZYn3hLFS+jhF9OumL9YOxdU/YUuO4xoyj2kXKugJkHs449OXvFVhtrhXqmEfwpiBvPXIQ63pmsNNxE/0r0tvjn7CVwif1ttc3+W08Xn5naTikrvV+q1b/2ULFVRV/Ke1Fd05LccaTEsr5SuxHyWULwu3wgpWK74bb8NpPoHxWJJ+W49lkmHKVWcSr/fnMCYd+PYuPw6JURwL2cL7QjpX2mUCvKufihcyE0ruRea+Zty3bVynjUui/Y0nxv06cItUwv+MWqzxtX52UPjKOtTxQDttlRU04GUvw6Z+KW6+6uEv0bJeI/JOhbRgkasYE3RfTLpKCOWHSukn6Aoi+Mlbl9jdSD+GSp5/jUY8U4x3g12xgj+JlG8NsnFIrQL6e1lT92f26rDFRQv9NqYr835qqAb7LAKRyoPdC3biMz9Jmc0pjb3koNADmW+hwhGtsDwCmvZ2CWU4U3fPWX+xkyAh3TCP4Ncd+ZA5e1q2QA7DUQpaSpt6/+9rzVOmEKtxfbtz9HuHMS+Rvcytg+jVQop0b4hwR9idXZJ1L3JPpd+crNDWrUvjCzropBaT2mEvytxL5Ublp8+ekb8FpuVkshZyA2r/XVGUrx5rpXal21v7tiHY+J99HiPsWdxywnqkmefRLqHoQcd0o3WYZCfJYK1b3XC4q840BqnSpdnRLWYirBD7TroLZGs5eKHvI3beGL7no2J6smhf9tD2rqpykmY/cZGXJyFXLFfuizEK4JsS1oQhb72PdrJtyl4oijEKUwDFFO5koJufYI+XBfGdmLphHiPGZ0Akz0CX+s/VmO7J6Bc+dPea2/LToH32Qq51ktrSordoihlYEV35cLZx+46dGfGJSTytr24fp+bX9bkyZOVlQTijLLbX+p5RBz/+Gap71ZLS9c9enM6Qcf/QGO3Ci3H2G/sBL8wHFh31voc7XsUjEqtGPo3hQDWimhjUyuH5OV64oMDPNhCxlfu8qJRFIS6pFKUFHdg1rgjRL9W1lQnoa7mvgdRYs8zKlnvnFKRL5gwtalx9VBcXQF8VGaxpYWdtfnrh36FMvOvuVv3/ul+lRSLp+OtnS3rM8l7yYDQ5yYq9MWdjQGVZnH2kyKYE913wmdXsqRlNNXVyPlHbdrbJev1fOmNdR5GOrDa/rq7bsjwgULY2El+E+ceMT7N7Pyt45cEgqPlyKkauO5pz6HIg0uYU6Vt7H72BOMHidObs+bkZbpFrHvF/P2wJgi+l3fA9q68YTaRI7As/828pyM2ESl5HsUjPbnLymTWCSevW/kXQWuYYeF8bAS/D5GCjS7Qw5FPmkRnSX33UvS0GPFJGbxNwe/lgKjdtPrKETst8UW8SHrF4f8MoVb7QR49mglqemgFrKtRX9MgNuHZ+2RVd+7pF65DiN8yZPvEtEvPAo7wW93gCEf69ZWfsrrWqdjNVJjUOcM4q3cpWZdMQB4iFcOpOZDTX5RuvHYFvjS+5iMPvE6l1FC36Sl6M9Jd6pblmsVdbZy35gxzSlQiX3Ab+EXd559wk7wm8wspIQ4rqg95sCXMhD19D11DcwjVgxqRcbmZz6L2N8Gp57pnSVvUkn19fe1uVlFYQ+oRL/rvqWkrA74+s4Z/Pm51sWcvKPUN+ap4oLgg12Uno2UxiATgrlotVqR2vlTRdfwRe3pwfYOW2hVV4jVEJuQnVHQmlap1NCXo7DTFiujULSUHF/9UnJPHs0VXNfcq6/46QlXcRiDon+JRSnK/VygocXYYVvzQ648M/b/Qj2sLfzCesTctew9EdSWxVkPWKOaLM1k2QfcG2Y3ZnmPlLLb6rnvEKwNn+8+pVU21OZK2qJL4G+fuU5Pb8EMVusRSJ7Mia8fF399IQRLC3+OGJtFuM0e77iV/7vrp+SZM+dtLbllw9kyngpnsV+avylnjrjCYlJb413PaUVPa/9qfUTuyo/r/WcflzgSy89ZNIvQB6XUTyqlPqCUerv1+Tcppf5YKfUOpdQPUDyLpeBfZaOqazl11s51ZJnMZoWi7NBj7kOlz8o5EXYUvrRRiv3W72+3m94Ci8PGVtuKf+EGRWrZz5k0zNT/tuhzZ3p/box0SxuNHODVlH8L4EXmB0qp/xrAiwF8ltb6MwD8EMWDxKWHmNTDowC6QZbDoM4BTsv2rmhTuQN4TMxTTSx6COtcXGmiTk+Oe5PtSpQSs98l9s3/55wwnRN1hSMXblDHRNL22TX36qIJgHm/nHtw6idscvoIquhMvvtxzqfe+NzSfHWuR97VumemHsBlPiP1YEEhHa31byqlzlgf/08AbtdaXzxc8wGKZ4ngJ6JkwC05OKX0Wa7v9ejMSzo+X4i63ifx5kAdnrOX2A9hd+z24NIzek4LsV967fZ7KHZ/inBLjZKSEofdF3Ulp92EntdqQuGaCKSwNwtrKjWx+anCva5GqK6VTFYpxwqKPVk+ES8WfTKeppS60/j9Dq31HZHvfCqA5yulvgfAxwB8m9b6d2sTwlLwb9bQ1EbROiZ/jF7WNern+MLv5d6jxtIkg8qV+Oo8h83Gq1h2ciYqsXeuPU03ZbWvdjXAZblNTVOPvq3Wvafk+3voe0rKb9Rpu7EJ5yhSJpYrif6VRf5HHnncoDHslx7SWt+c+aWrATwVwOcC+HsAXqOU+pta6ypLBysf/idf/bFHK9wMG1tW2/BEvUTc6nk97pkb7jJWX1PuxcGqXwJ1JxpbWailpT9qqJxT6ibVJDxEzuSBEkrf/e1eNffj2HdTh/tN2QjuwjzEq2c+lbaRFqSuIpXWQW57FVcW+xNyHsDr9BG/A+CvATyt9qasBP9McBwsaigVyrlRRUL4BrucQYe6XHp1yqFBntvA4IJK9LcW+znkvFPKBDF2cjRl3aUS/a7vjbLAbs+mfL4ZWMH3k0KugcD+rg31WR+lon/L79bjXU659qh/FGI/pf5QhltuDfcgD4vxCwC+EACUUp8K4ASAh2pvytKlhzsrif3SUwFbilDXibtAeNmXW5lQrg5wtezblCwJh9xrZhL7JZRuVk0l5rbC7fRc3x4l1zv02qxMIS59oYZ7T+S595lcoN4fEnOTonLvaemSI0K/HUqpnwHwAhz5+p8H8EoAPwngJw+hOi8BuLXWnQdYRPD37DhX6STNzmfrbHz56Dsga8SAFYsw4Tu8yIZ6k20pHNLQGnMg8g0cXAaUnumIWQdLxKa9aZP6QK4epIj5rf9pNWmpfVdf3xj6vHdfkJN3nPzqTWonfjXfz52sh9oi1R4tTiukQhpa66/0/OmrqZ+1hODvBUexX9MRp3YudmdkD1otBgOfJSw2SOWkpdUgO8IFx2VFHLHRl0rQjxioUtJYU7aUVumUzbnmtb6/h9IUux81qe+01edWRoea/qwmPTXfHbXZdhS93vPaey4++v+Hbzz56P9LV+ZiE3DqMWn1jbhCHiL4I1APbhRHyuf6xVPBxZecsrNP6WC5rAbYpFoRKd2LetF7oKIS+/ZE1SXEXKETayYDPhFRY/2mbGOlE4eYC0Sr/og6gk9qOGSK55r3SIl8E6sjM0Yzqqn32/hsCn3gSrFfS2/RXwuX1VehHhH8HiiFfu6hHT5cbjgciLkElXynp98rtw7WRa/Jlm8D4cr0GNBCojz0u+s+rv9TEROjpWeH+P5m3y/1UKjW7SG2Xyg3mozvnATXdyhEPyUzif4tnSXnT1CL/ZqDuajDdm6ItX/fiOA3aDGAUmwA6iH0KQZQytNkfWcx9N47kJPfrSYjo/FNvlYgVeynloPL3c0McVgrnHJFt/18+28p+L6f8uzca0rCkrbefOyymqdaz0O/b1DsR7AnFPYEzVf3fCsCs5HTrlz57BP7Psxx3Rb1pSdA9yB35VSs+2vBKixnycEIVIKIo9i3Q5VxFVtbSLpYWVDHmG5Fbp2qCclHmY4ecExTKb0Gs1bnTXAKY0iFGXrT9Y4p/XSLU3hDIRZdqxQ544krIlkJsRWkmjMecsOUcsGuQ6H39Yn92CTgmnv1FT+uv7voFbLTRkT8fhELP9r56adc55r9253SDCLZRe1GMtd7t+oES+5bm5ZZY+/P4AIVY9SgZ1taS1asWk0gAP6bP1PTNcqy6nK5KsnLVm40rvvmjn+zuPjYQt81YUkdq12if3P12f5G6ecPtB33Kfq/FcaBvSGCnxgKq/7Gyo0p1U2Eq/CtSRfFqbyjmbmzHyH2Q+4aNW5qqW4gPn95ykg8MWtyCjn+8b7rLtygjllbW4t/yo2vtQaoUhes3GdwEP016aBYCTInAtfec9Er+n0TUC75KOwDMpcepdRVSqnfV0r94uH3T1JKnVVK/cnh36dSPWuDQhiNWqK0j4U3lx5ncX0JUbqknfJ5T1xpaOW+08o1qBWt09riZMeRy9kuF5XaE3q3+1K5XJSKD5e/eu2kgeK6jRZuPjm02P9A8d2a+jKbe0+IVN/9jU3YP3zjyWTL/ug6SMlM45RwGUoL/7cAeBeAJx9+fzmAX9Na366Uevnh95cRPq+aEa48tsi3mV3ox0g5eIZTZ0IdIainm1IPelj6YyI9ZRNajdAfWT45ByPFNmi22twaEpglbi0UVs/Nyj8jFBbfUFm7PqcIFz2C3I3ntfjE/cM3nsS191wMWvkBt6Wf0sp/y3V3kxo1qO8njIXEwq+UOg3gvwfw48bHLwbwqsP/XwXgyyieRcUI68TW0HM23M2K6/1mFrazYVp8Qz8UcC7XFqsEI0h128m5vgbfplofveqiibmKymECwNkibq84p8L5nULk1oUUS77t05/zbFc+5varrUJuSijPdaCy8P9LAN8O4Brjs0/WWt8PAFrr+5VSTyd6FgDeIsPE7kRXF/or0WO1hboejxqAR4XuDA1GKwj9nrhikueKQI4uIjHR39KqPaq/Tz3PIOU7IfYwnvmEvllvtnqVaulPJee0dOr+zte3zqK9hONUW/iVUl8C4ANa698r/P5tSqk7lVJ3fvzDf1WbnCR6iaILN6hsa740Jj609tXnUNYtLKyj343Sqs+hjEopLdMU62frPrTnxLWV5b+XGKZaLVldvOdu4s7xz3fdL2TpT7Xyc0Gs/GtA4dLz+QC+VCl1DsDPAvhCpdRPAXi/UuoZAHD49wOuL2ut79Ba36y1vvmxT3kCQXLc9IhcYLKJ/Y1c0d9TaISeVZNfJZMdbgKLY5p8UEX3oKJ13rkGoZWs+rXx3Uue0Yvck2qp8Am90e4+pVDn0R7cTTfMumCLe6oQm7minwspAn/1/YYrUi34tdav0Fqf1lqfAfBSAL+utf5qAG8EcOvhslsBvCHnvpRCYYTYd5Hbkc4kNnsw8vAXzuVAmSct8rdHPW7hq+9Lc4/6N9LaZ7rAhOBskQzh81fnLMBctMz/1YT/xesvHdtDd/H6S3jo+R/HQ8//+KN/c1n1t/pi1hkqNzC7zrnKtLewFmv+urSMw387gNcopb4ewH0Avjz1i7HIH5zFl9mpUNHCPzonD0fGCo5FmlhpUCqh1aDfIn+pI/q0tOaH2gdlnlCWH2U7TRU0rfuGlvd3+fRTHtjVu99M2bSdm6ZYZCdOceRjEdVCZ9ycwylcvD7eHnNWiGKrBBwP3UwV+2LdnxNSwa+1fjOANx/+/+cAXkh5f+7YbjwtiAl16kOduHTmPko2p82E+X49o7DYz1klPzlRczgVcLw+xMooJ0wjBfbpvfbnHFhN9G9QhmCN9Tuj3jFHdLquNcXt2cO/53B8fMzNxxR3oBSxLwjUsDxpl3L22HPZmUOD5bz60RNOlidqRrhSrJyfNrO0odR60GuD7eYm4RL4sYl56cS9do/RyftONBf9rShtjzVtudVZDrnENIJ5erV57Sby7dXBLd68a5Wg9J1z6g+XvnXLl5ClX6z788JS8M8El4ZKCacDsGoGGM6WxRRcmzZHQiH6c8LMjSDl1NuZ6tGIOmOK+JyTc0vaa+2Jvj7Rz13spxA7fGumemyS2nfY15kidhP4VP7qqRb7UeXhm+ikslIwhD1DcvBWTziI0A2Xv932I9Ax68C0IpSHdXELUZjszC8AACAASURBVFpK71VE34bKmgliySbN2Hd8fzM3hlPkXUnaXa5yrs3KuRt5ufVVobyhDN852hiRQq5oNcfykraR8zkwRx4KczOV4M8VBdKAyhklwFpNmLgNxDE4191RkZJaUjLp2PKhpG5RCV1fmnrGYq91u8lJb+67pU6QbNG/sYKlH5iv/wtRMzbZon+L7lVqwaZuL3bdHjEO26seYt1fh2lceriL/ZWs+iM6mZXyr5ZSf+feUG/oHeXuU9O31G6cta8fXbahuleStpr38eVzjptQzt987xiy8tsTgtHll8vMrj2l1Ih7M798m+dz7uXCLhOKflFEuwBMJPgFfrgGC24DCKe0pDCbYAD4lXkOJVGrfJFKtn9rRDy38LcmudFaemwWticCobpolp1vsuoqX9em3u3z2Hc5tYtY3d2uKblvT3oZBFL6Bl99S+kTc9sKdVhjF2LdX5spBD93/95jMX2Zp5cSKrFHbd3lNNCm0EPob6KlhZsClbWf02DuIsVPPiUvqOpnj6gpLTfPppLaz8TEV4+IK6G0UOFqJyl1mtsqYS7cV4JrN5GHDAe9EbG/HlMIfo6Mbowc2FsepHbCueK3R3hF00KZshGxdFJQI/xnE/ul11O3m55WddczXbRIh2ujb8w6XSq+cr+X43JUKuYo20dsNUS4TMqE8YpwnjhVvL+HQ7mI0F8X9oJ/T9ZyrsREHMUAZpazXeYzuERsUInC0dSuBrjey1c2Pa12vcS+j5AoHV13S/EJ8JYrSr50uFx0SghZwkv2bVCufF1xYFSFOJu1vvXEV/7m52dOP3jsEK9N9JeQWy6Urj4i9teGteAXsZ9PzqahVLYOrtRVwTwEJcTWadkTgRKLW+0gWyIeVhH7JtSnjgLhI+5XJSU0IoUwpHKtKV2dslePeke5CflUA/7DwXyY16b46FOI6FCbKIkbX+r+E8LeD7Ha5OHc+TTB3sNtz6SHH7+wLqwFfyk9fVpH+e/XvmNuJ91yqTGUZ6mTBRe5UVN8Vr2YiMhN0wh8Gw9j36GkpSiw94BQtsOWZcZh03uKJT4lD7icThvKw9S2bWIbPErT5Ps8dQIcE/s5fWVNv7o6KSfsbmV2zLp/sJC3zF9O5cb9IEXhStgKfk6VehS9o1yUEruHaZUIue5QUBNxIif6SkrZlOQvh9M+KZ9LuaHbxDegUtepFtZyjhZRV3jJ1A2evV13Usgpt9zyKC2/mtWXVMu+vToaEmIlotT3nZw8KRXDPURlzoQp5ZoeOmaU2BaNNh9sBX8pHCJWlMLdxYP63X0+/L5nU+dP7H4pEVkon2fjs8j3FlYlbhqpdcVnIYrVhx6DTa0Prm8CGXMDoPbpD6UntOozo9AvpeUkLGeFwCfSS3yrWwvBUJjP2H4drisMdrpc79hiP8VscCw7IQ5LwT9rZRq9IbD02T2sjbOWaU9SXW5SJwKlLhaxdISEXmld4lI/WkaX2fzHS77n+htVuy0V7CsI/dIwlbUukdv/R6/05Arv2nY60gd9E+e5wvzi9ZecaeYi9nvnqW9lVdx6+MNK8F+6dHVVhzKjdZ+7VX+jxjfaNziG7pX6HO5xpXPSVeJnb+L6bs39XPhE3mjhQkGrOlQSmg9wh6E0oRD91KLdNRnk0kZDLnmhfHRNvErCLuauegFtrfSbSKOytqdOYkqfRSUqb7nu7mSBHnre2QduyrpXS+y8oRTgqeXFxWgj+GEl+GsYMZjkuKSU+ID3gptPca7Yt//PKW9zqRX9raC05nOjVchNLhF3zPsB7drHCi4+W1/IrU9shYi04+QI5ZjY7+m6ZD/Ht/ep5p7C3Ewt+GfplDmLfU5QdS4z1IkQnES/Ld5mz1ublvH1W2K7hoRoHec/Vldb99P2xChlYmP61bsMB6n3WJ2clV3u+cHBEj8auxxdRsvUMm8REU1oy7SC345fPYJt2SynwnMV+7FBuVejDnUilBsauZbDxia0Rwj/ld12TCjrQAtRWxoHPCVevO9eJXmSYtHv4W6Zugm/JGoSddnuaRWBkhl9xbluUAb8/vil3xV4M63g3xgt3FJcecx/OcNpAPJ1khTpc4khruXTy9q/F5EPzNMWqUgV+9u/rfcy9NorEYoiQ/2sVowWuLHnm3nccvygzgP7vbhswOU0BgvrMb3gF9ZltkOUZoIytOYsmBZe6nqwWl5t5Lgiuiznvut8fyuJLBUSSRRl7cqDHueXtKCkL00JmSzU4zMOSv4KVEwj+GcUarOlmUPHUmvRcg3+s5WDDZWVPyakXNFhONSJVFLLmXN94JA2n0gujTaUQ48Nv7krDRzKxGa05X9VOPr5c+qHObsnCXGmEfyzwXGQGEVOZzViEBtVVj3CFbrCI+YQ2gzJZRAa3dZy86FHenMt271EhRm6scceClf9NX/PScOI8KK5B9L1hFs/kINMlsoR0T8vIvgTmbFTmxHfyas5cLKIuOiRtk3oU4rRkHgawWihH6Nl+iiW/UMClkP55uJr97af+faZ/Xffd1M+K0nXCESszQmHyZVMkuaHveDnPqi7mDHNq8Ghg3TRMj2lIj+XkXkqbSud1HLquWm9dd2xT7NNeW5rF7aae8YOJxwtwrj1r6VwdOVxkRqGd5VyEWhhLfi5DO45jYdLmmen9ETflM84kZK+FP/9CzeoLqFKe7l9cMdnHW+R9pKNrLmsKBDsiYz9f5drESexlJKWkaKfSz7tDd9ENhSqvLascg4ZFfjymNEJWIXtEJeZ4Zj+0RYsaqjPj7hwgyIR+z42UbT9vzUc62CMHqF3uRzENhspZ3dwFa4pKy85/eO586emFWuzpXvL69Z5vumO1DMohH3D1sLPpYKmDAatrHomvY6r52ThyoVzPH2TnDT6hB6V+06q/3ZsQ6TrmlyXipnoYdnPIafdcmknrTbB2nnh8td3pYVDntiE9hfkiv1W9HKfpNjftWcoxvbZJl7ClbAV/LNAOUiErHg9lvU3OIn+rYPh6pM/glqxH4qPXnOP3LbAUWD1YGvnvvbs6gdyTrOdrY3kxPpPxe7DUvq0TVxT9H894vWPcufZa7sNMYsQLgm8IBOsdRDBz4SUJfu9in6TULpGDUS9yqU2xCZQn0ejvz87sXbey3WHY9sGaC3tPtHd4t1DYUFb5nVIaLY4uJADHDYrrwDXMV5ox+4Evzmgph5E5INqYMoZ5HPSX0vLMIy5nc2IJfeYJTbnPrX3GCH2XVbSUvYu9IHj7bzVRHEPA3mOO1DrKDwpjHh2qtCnSlvufWqea77bSPE/+2Qq5pYpm3XXgqXgbyUOSq1nro5phNgfCQcRERL9oY6rx2ZKc3JAWaa2IOx1yFOPjah7InUFz0WvVT0u5Ij53H0AttWfql8L9TccJhwhKNOU+o6UedLT4i+iV5gZloKfC63DPM4i9nsT83+lnGyFxNQm3nMssb4yTb1HaFWhRwxzoQ1becbqB1WfwFVctqTlSbilq529DA8z0SIfWlv8ewj90RvHxbq/PuwEPzfr/oZ01vuEUoS5RL9M+vpC6UaTU3Y5G3Sp2Jvoz+mjQxvXQ1F8Ut08a0/opdr02/tkXQ71jcLiv4rA7XVI1976mllhJfjVpbFL1z03xZYM9LaVsGd6R0AZLcOGQqyVUCrwpDOlYYTYT73ebM+ulZ7V2/sIUoX8di3FNT1xCdftfVuINPOerkkL9YFQPkot/jMJ/dCKVk6IXh8peUF9rozQFlaCn5LYADty4CwVfa7vlYbwK2HELH5PloMRbjxCGdR7NVrdf+b2M9rFYSSUIUJdUOarvR+C2xkVqXAQ+yl1PhR1aub2LrRHTto1WMV6tvmdbz+UUHXeoY6NYoP0NljG4OxSIx33GmynIZd8b1bOnH6w6UZK6tCdW3/BabN6yz0JGxze06SVf39MzHMQ+xuhfj/lLIlecKs7QpxdCv6ZB9ISuIr+GBevv9S8A6MMl1lzj9poPC6kQ6ah1eTZ9ywfpXWtdz0whX6v6Cmp7ja1h8uNooVF3v5/bhqo+2dO+T2a2j0grZGympMlBX+LQZOKURZljpbsUR0YZV7U3ovajce2VAp02P70Nd+vuYY7Pr/xEnr2Ea0MDDVtsXeUn9gzav9ee33pd4A0Sz8ntvrYw/CVg4wt87Kc4A/Fsl5hMK2Bo+gPwW2JnZqS+mhvkrJdEoR9kNuWR9cNDoIl1kZiYZhrxGlN+zRFnzmhTz10zPcOpVbkFht9zQ2+KWU0uj7vFcn3uVlK8HM+uKaXS0AIynyg9qG1P3NZNlbqbHLLIiTuV8qXnoxujzY5daJ0stirrpRYUlPTZopf+/NafP1RyZksOfdKJWbx9d3b7j9q9knVfj9Gy8mhy8VsJqv/SGScmZ+po/SkDNhcxL7gxx5AOFgDW5JaJ/fWwXIMO2m2XfP/sYO0cuj9zr0ieeQKqZI0lb5LSQSgUHQUO00xYpb2kvSYn9W+Wy/s9OaUZ209Xk3ou8KgUt9bmJulLPw23MSDcJwRA02tL7bvXinXply/N/ccc/Wr1+Q4NLnI2aSbc3rydr35nVF91Cz1q6dwDVnOU4U0l3wNrQRQTjBq6N33r3pyrGvFl2oM2dtYtDrTWvg5x9nniuswn71ixjmvtSy7rL3mZ3vN75R3950tkSukgb71Ordc7bbHoU7MFLObOkQl5X1q09a6HGYp443W+UEh9nPcyVz1gur9Uiegs0anEmiZRvDPKlY5uvNQidBegsFefqc+kIeqTrnuM1t9LcVXz+26ltoeYnWUcqJQwqhypa77nEV/6nu6XAJrxHduWmYWSNzKP0c4u/Z3xd6lRuxTRiCq2X9Sunm8x7kOAm+WdOnhIrI4in2OlJwuWIuUDQ05m9FHx7E3CfURrfqP3AlML0Yu24eebbqkcAhJueqzc9JglkfPiDnbM7Z24gvmEIpiVGvZj01GagIppLTB2nYq7jnCFBZ+e+Mc5WAdi9nve96eXTU4QG3pFC7jahO+NlB6v9TvlTy3d9u03bdaiveWdX6ktbfW7SHXyl+7CrA9a/Z+qCRYgvnOVH7iOc/nTG1+2PV45rol8GNKC3+v8Jumj7f9k5s2blCls2eHtMKAwJGUum1/zr2e+97Htzk4931SJ0WptOq7cqHc8Be6/0bsUKHccJE57Kk/6dFPlxwQZacrFP50m1DnTExmpHUbFPbLFBb+VlCLlt6RRlZi1s55djjX1ZlX0OyN3DO/CxW1PtAtViA4WVNbrrBQ3rflZDCUTrsNxVZwBEG4EvYW/laChOK+nMVST3I211E+z1xWz8Fl3d1jWda42sxEykS8RJBzPuiPAurNwSOZRQCOzqcYvetEyeZWiUgjCG7YC36hHaluSimM6jhzRX/MHYtSzHKeSOxF7G+kpHvWd3PBbdJRe2o2hWCP3YNLfPpZRSgHN5SWE7vR7yasi1Lqnyml3qGUertS6meUUo9r8Rz2gn87qIYy3B61qKO+56y0jrQzS4fLWejX0POdWgvW2KFbQhtK+wCXu0dNfxKKDFTz/dWp7cNDB4LlQBHbPmdleq/lLbRHKfUsAN8M4Gat9WcCuArAS1s8aykf/lSRQB1JYxWBIJGHjqjJB198eB+S33FWqJfU77BCnuT6rKdcX7LJt9byL2KQjlC8+FA5UIt9KVOhM1cDeLxS6uMAngDgfa0esktcp6MK89Fioxul2BfyGSVka0KPuiiN/JP6/j1EP7eDmVrge8eU9x4tDO2IRyXfHVW+PmE/OtrS6DIV9oXW+r1KqR8CcB+AjwJ4k9b6TS2exd6lJxXKgS/VhUg4Tq/wb/YzU56bIsB6h1aUSUIeLU/JbVkWsbqR+2zq+4UY0aZ7PsflKjRj6McZhCp1GinyP3RYlyAQ8DSl1J3Gz23mH5VSTwXwYgDPAfBMAE9USn11i4Ts1sJvIuL+MhRWwxGWo5QTOUOuXFRWVUp3MfM+pZOJ2eq2K709V+Oo86y23CSs55WUrDhwEuWppL6n3e+V5E+vVRzKZ7TYvyGszaVLV1eftlzIQ1rrmwN//yIAf6a1fhAAlFKvA/B5AH6KOiFTCf7Wp1gKtPiEPyc3gVwhlXJ9i3pqC78SIShtpy/UgQbs++WUfcqEuAeUJ7OWQnk6bo/8bG1A6d0Xl+QZl/FCEBpwH4DPVUo9AUcuPS8EcGeLB00l+IF0MZVjqZvREtoS6vwYLTJ81LwjpaXfvhfFSc4zivsebTDmzsOlH6iZCLSA0ySdAkrR3xIzjanCvyR2PWfEml+PaBy+aK3fqpR6LYC7ADwC4PcB3NHiWdMJfiAspih9YWVFgSem+CgduCk6v5jLTa7oL/1u7F5CGq0HRJerTi2+NLs+rxU/LVbsKNpyzjN8fzefXxOak3IlJVW4ryxqZ5+sbMTae63xyXUv1wGTIvp5orV+JYBXtn5O9aZdpdSzlVL/SSn1rsPBAd9y+PyTlFJnlVJ/cvj3qfXJdROq4LUDq3kOgDQWOloNUrEBolUZhvYGtHAb8j13ZbHfsv1R37tnucxQ5qNFaUrcdtMPnhO5cetzYt2vIqhd9C5H+yDLnEMtSw7A9F1fo3tm6EuEcigs/I8A+Oda67uUUtcA+D2l1FkAXwvg17TWtyulXg7g5QBeRvA8qZQdGGUNCFnYTAsgRxeDUJ71WC1KsSLtue2E3HlKQnJyCd/K2RDhcklxXTMyNKQrXRQHO1FAcdAVJ3rueejJLOf65LiP2t/b4NzfCGGqBb/W+n4A9x/+f0Ep9S4Az8JRmKEXHC57FYA3g0jwm/SOpy/x+3lQE52Ce4eVO9mK+fxzf98e5ITibBm+tbTfqN2gy81q7aOVW8+MsdpbnwNQmielZTRLHVydWB8kB0WuC6kPv1LqDIDnAXgrgE8+TAagtb5fKfV0z3duA3AbAFx9bRuvH0rRs3V2e7eWtiLl1MuYbyvnDXk5G8lbPV/qbRm5fciIfDbbgtkOWkfpSZlwh9Jg+/Kbn5cyQuRT5W+uC4/5fLssWqygxPrYkSvEvZH+VJgFsoO3lFJPAvDzAL5Va/2R1O9pre/QWt+stb75qic+MXp9Cz/9VOxOU2a7dXAV5Sm49nXE6oPUl/7E9lDYf2sZBWnEPqDWLh2p7jACLS5hD9RP7OxVoZqyNNtI7j6EGeipPbiQuzdB4AWJhV8p9Vgcif1Xa61fd/j4/UqpZxys+88A8IHa51Aec08dpUXoQ8w6uNEz7nhtXeK8IjEzqeWSG753a/cz+bVS1K8aFxPfyoP93dVEYStC+bTlry3ee27ipV5JHHGYo42M98cRl9G5oIjSowD8BIB3aa1/2PjTGwHcevj/rQDeUPssSkpWCvZ29HaPDi43P2c5ZTPXCuJKp0SHOk7LKEup0TR6kvu+Wx9l/rTEtNz6YsaPaoOxd1+5P6fIcw5W+ZwyWrUsBYEKCgv/5wP4GgB/pJR62+Gz7wBwO4DXKKW+HkcniX157YOorQapG/Zkoy4vuJwaGoJamFLVfa51uEV+Ud6r5HwPqg26lKuRrSZMuatU2/V7sBCW9FcUFu0W/WTL4Ail6e0xDnDtN0ezettdDYooPW8B4Cv1F9be32YbSEtCS5UijV2gIEcU7akjLXnXXu1/ew7FhGtUP2I+t0Zgt3C5iaWlxt1ttHW6Fqr0U7sMlkzsYt+pObhNEIQ0yDbt9mRPYkioh/vA39q1YLUJa6/N0VShUWufSbl3aQTiljGekj6wtixS9wxQRWVqBYc2JAgUTCn4TaQxtoXzjnyf/zBXRqaRaxlSiPMeBgB7g27KM6lOWKaO+d+rHriEvqsNtEpPqL2NaIuloTZHQrXHylXGvpOOc+/dEo59JhfE8Dof0wt+QZiNlNBmnCdaVHAaMEzXHZuWB3FRfT8XV6ShFEKiLCbIfC5B9rtTu5/03pzLYbNrC1LzMOX9c8W+IAj1iOAXkuEiPu0BfAYrf4qA34PIb0XrlQJ7z0BqSM4WKwExUupQzd6EmOi3f2pxHchVA+d+YgSpE6LS/Lfr1yxiX/phYTVIT9qt5ar1jCJCArmbASkiV2zPbUXOYCFHmdNAHZnH9VmL8zxSSNlsWxMVqGW0nJIIPi3gKixduAwasWtTz0novfoQmlTWHBC24irKLMi4NCfsLPwyq06nd4x2zo08dwk55TulSB1eC1eYTKoVBd997Mg6MVasczmid2Vc+yBauCrZ96rd6Hvm9IM4c/pBXLz+krOezzQBE4QVYCf4c+EsQoV0WnX+ORvBKNxpWgkv3/kQUv9pifm2l+Z3almZdbCVe5edjpxn1Ljp+E7DDuE6zCv2DEp3ohJa7hmIbUSmfm6LPCxJpysdrScM0re6kXyZl+kFPyAVUDii1opfK6BbiLNVffq5ttkW/vQU16aEIi1JO8e6JZbf41CFNq0V8CttSOZY92dG8pM/rHz4P3GCrxDgiN3Arr3nIh6+8WSX57UoJ4rTJbf7+Hz1Q3+rQTq7NfH5tlOdejziFO/SZ1HtnWnxnREW4FRG+JvnPJPygK8WrDLBEITRLGHhB2SisHHtPReHPZtKtMwQQi8ltGYJOZZa37OlLdQRE+Hb56kReLZNi677cZkozlBnUlx1RoThzKGneKXIA989zPfwlcm586dw7vyp6jSkpokCLu1REFqwjOAX1oKyUy858TGEDAr7wReth1Igz1KfWgitmHgPfU8sv3FqyozLpKlVOkpC0grz9FfCcVgL/lX9l1ekRTn5OvqQBa/1ICX1sZ4ZrMnUot53v5TnUBzqRfU+VL7k1HHfOVv1R5O78Tn0/ZL7zFYu0scLq8LKh98kt9FJI71Ma1/+FFrF9U4dvGwf1i0WOHerIJVvOFdmEPu9aJkXvnvXROjZyBXivc6+EPz0Xp2hfmbvvptzHyoIpbAS/NvBW9LYynn4xpNL+PFvmB19bACJ+VbbwkOESD9E6B+Rmw+tr+eOS+jN3lZzDyKjhkI8p7pJtjwngBrRHenYBj3Juzlg59IjFaeczarfU/SH3K4oN/Gmiv1UuFv6BWFmSsSZtMl+5J5psDIS/KCM1lH7BHrYCX6BHy7/39T9FT0mcKUdT64okcloGTIYhBldr1zlExJ6ue2m1G98+16rk2V7wjHtKenhluZebG1C+i5hJUTwL8poH/4Q3DZj73VQE3jTQ2y03mfj+syeTKS67K0EF6t5bCKSms5eZeeqO9R5abcJEf3CKrAX/KnH0e8RyugbvehZVmLBGs8sdZOj+wLnfq022ov9fU75vkdKViD21HfO0o8JQgj2gj8EN0txT0ZYIWqfYZcVxcFVMXee1IFsr/Vo77hEvojPti4opquOD1e/sEJ/z10k14bgFPbF7O1xb7AS/J+QfqWKVqK/tlGn+vrnDug518bEhbA/uAj72VbpNmJC0Oe64/vdxDzt2O4XpL3ywTcx7LVnQSYj41lhIr4XWIXlFNIIiYMVTg+MWe1LIyqkDg6xMwRMMSLMCRexvwdiQt/XLkN92QoRQkaH52xJq3cLrUBQPbPVGTKrInk1D6ws/DZSkY6Tkicr5Ztt2aMW2T7LYcpzVsrnvcDNT99kD/UpN+9bn0I8gtlEvq/MuLYjCsSYI6wIW8E/Y0fempF5Qulr3/vZVJS6XphnIvjuMatbRwwO5Sb0I1XM5ojeldvLSqJ59ESG+vnSdwmrwUrwbyftrtCRj2bUJt5RA3FJ5+z6Tu59UiIlPXzjyWPXpPxfoGUGcVVb/iPfMUfs54biNNuZmUecV2xWJBZdabbwnDntTfpmYXbEh39hWvrz+8T+LPS03mz5YvuY+vIrtG/BdZy57ClYi9rynMk3fKa0toD7u5dMzmZnpnFMEHJgZeEHpLEJ5aQKpNh1pasUoUlQC2tUaNVAEHqSeuZFrWhcxaLP8eRdFy6xH0t363cLlX9t3ZA+9AjXGDi7kU9gKPhzkMoWh2uozlaE0lW7FyBFbLgEuM9CljI4bddwruuc01YKx4O4OKapVNylfsd8Z9d7zyKcXXAry1I4vEOvOrBiXxdie1/7X2FOWLn0SBz+NrRw7fG5nYTcVHpNElo8x7bQhwaY0k7Rd99ct4eeeW0OBFwngbVwdTspsb72JpQe82+jfME5wLV+Af5yMENh9ia1TuWydzG79eExy/7Kff3qsBL8wmV8nQ/nwWEF7A2BtdTeI7esXSsMIztnLoMoBytkLjl5Z/cLI/2uc/M6dr30d3wxffxHYNb70nrCpY8aSa4FP/V8HIEXU7v0APtsrJzFS8pBOVwJif0Sdxwblwgz7zOzsJmhfFcjxco6uq/Ifb7tojNzm0hl5nccXb9ctE7THjWHsAZLWPj3ssTEsXN1MWNZuDbXmrg+D4l1DiKsdyQiruVOtVIzszDjyioT3hK4vy/39AFzpHEvyESIP9Nb+DdmrWy90u1bslvlAJsS7LjeVEI8V+zPvHmPq8hvgb2Po8X9UzaochA5ofdvuYl3VmZp4zOk0ceWx6Pr0l7HU4E/ywj+Gem98z20GSc3DXbEm5kmDq60pg50owcTbsTq0OgJAbWAMYUb5QQxtoIUI7QBtkUepKQnZXIi7WluuJQft4nKLGMhMFdahTqWcOmZhVDDMl0ifNdRbZBqGUmHs2sHRcfms7yG/m5fG7sHBfa79o7a0/OZPriJABelacxxPaMmt66mbCDmYJltzarvt+p7heA8zgmCj2UEf+/G10rYxERp68511Y6M2opBWQ49BsxeoVm5wEnsu/zUqdK3R7E1I1JO9GyTRE5tnXOfKAjLCH7O1IS6GoVrQsMhzOPsuAapXtZNTtb3lvQUALaYt63Zrd1rUuFsQeearlGMDKk6C752NDrPzDj2MxjPOGkOoT3iw19JrEHP2KBiaU45cpsTvdKXengQB4vUTHsuUhm9MdKexLU6x4HaDag1o0UYZ0Ljx8i6vE1eOfRVMXyHFbZGAmAIszGF4I+J6hGzaHvTqotVG7+9Z23TnwAAIABJREFUWddm1fcOMcPA6GKVspo1/1MICS/XJJOjwG6ZJu5W1BlZuT1REgq8IfVS4MYUgh/g33hWnt3b7zbTu7ZIZ2rM/VSL/4zM6KY2O7NYXHuyjQvcxwcfnNsH9X6TVvQIghAiFARjJDON00IfphH8IaRijyEWdUhwM7vwF7EvcCC20jgrI89byIk4NhKuK1k2o+rlSu1BoGMJwb8xQvj7nrmXBhdybRqdB6OfD9CJ+xTrbg8LMIc83TuuFSa77DnvH6HCPjhPaEevelPbh3Gs36Prp9lORqdFGMsUgn+mSrq3RpXyriM6m5Jn9bAY1YaRazGgicV+LuSQOKEVIwRz6HTpmms50arvdI2rqUE3pD/fH1MIfoE/qT60rTuZ0olFjjjKGXBaDEzmSa+UUVyE+Vl534gwFuoTplPuFfr7bMKfeuyLnXLeMy3CHLCNw18TN7pl/NuUE3GFy/TKo17PqbHQxwYv+zkt0xJjpjMXZhr0uSCx3gVgbD0YaTQZBZU22bMbsVCOWPgzMJfCpHFdZrR1YQ9l4YsMZH5eM2hzjTRBzcgNkaMIRZVaSUwJ5fSuB62eN0O79rnhpLjiiPYQalhC8Le05gtt4Jq3qQNG7sBiX58qOlP9WnPvG4Jr2Qhp+MIUziCGhHGkrqqHrkkNLpBD6HnmBH62+u0S8HsxvAhjYCv4cxsvhQ+5aze7zKh54SqfWnyHF/nqoEu8+3DdJ8Uqb6eph6/+jIONWKjTyYlXLvm6DyhEsmsjLdX+oljfuiKc+1thbtj68NukNIKQ6K/Z4FL6nT1zzb06aYmy5rRiTmXiO6QmxUfW54vvsriZ125/6zHwccprIR9KoSWshdmnbH1O6DDB0lj9VNGl9lA3pb8VWsDWwp9CKAa8iTSeMdSWTc+NuEB8QIoNNC0j8lD56q9EbX6vnI9ioRdaMaJuzeq2IwicmFrwC7ywBX5OfHeurlOUB2fVfreV6DfTxrEMbGrC8ZnuB3sRxb73FPEkbMxywq4gCOWI4BdIMMM4zhDKsQSKgbBUZLUehGWQXxMR+0IqLeqE9CuCwIepBf8M1kghj5GnAHIXQTJ45sG9PFsj9UVoRW7dktOhBWE8Uwt+gRdUIp3zRC7VJUQGrvaM2FMhCHuhNkRni+cJglCOCH5BCJAaU3pmcTnbZrjZ0isIM0IVT59D37hCPy0ItexC8K/qUy60h6vPvSAIAjX2ZHq1ifUWcpS6f95jMABhPnYh+AER/UI7enbwOVa1PQw8qwmSGRGhsy7Up+auRuiAMYo2Ie1KoGSag7dMRLzPQcrhWysSOriGAteBXBTXzgRVxCQZTNtghpJNOXxO4MFq7SH0PqV9Y8mGZddzYu3CPrm4ti2Z95O2uE+aW/iVUi9SSv2xUurdSqmXt36eMJbaE405ktM5hkRkSsdORckpvLMM9lTpnOV9BWE2RgjKkiAKua44Ned/+H43nx1Ki+s7teeRCDzopZObWviVUlcB+NcAbgFwHsDvKqXeqLV+Z+y7YhUSZqRHJ5raJnLbzh7bWsoETQZGPxLnX+hBrzZqWuOpNUgr9yhfOqXfmoManZxLawv/5wB4t9b6T7XWlwD8LIAX+y7WJ45cdVpVVHEFEkoRAbMPXOUsZe+G4vTo0cQsnVzS2YJWYYV7tpdQ+VFZv2fZo1KycZjy3bjnD2OydHINrQX/swC8x/j9/OEzL1Jp2tJj0nPhBrWMOw8VIhrbUxqu0/6O6z5SfvXMGhpxtvSmECuL2r0/lHlGeWjXimVJBZW7kpBNtk4upfWmXZfqu0JxKqVuA3AbAFz1N55y7OJVNx0KAiCdJSWSl2E29yWK/nSFvM55h1XGoR7lNkLsb9euUEYjyd3YO9MkXl1So+rH05RSdxq/36G1vsP4PaqTqWgt+M8DeLbx+2kA7zMvOLz4HQBw8jmnnS/pa8gXblDZFmuKyDF7jT4jCDMQi76zJ7cdOy9GvCflRKMFXNNFCaeoVr77pNSRkM/+HsqxJ748nkHcM+MhrfXNgb9HdTIVrV16fhfA31JKPUcpdQLASwG8sfampstIb+G9TTBKXGNkD8HcUA8oOR1nSdSd2eAefWf2vB85UI/Ou1CUlO132595L8LGfG+znFqJ6tq9H5wnj6uzlzbRmSY62UVTwa+1fgTAPwXwqwDeBeA1Wut3tHxmT3IEvG+iMGISIBOPOak59Zd7R00tsjY/fOqTQ2cUGtzSPCo9vjrGvW3UkusWQ3Gf1thpEf99YVZ66uTmB29prX8ZwC+3fo6QR2u3pL24PfVY4uQm2HpDER6PMg99Zb6nMJ6uPAjlsW2VHS36qa7Lvdfe23IqtRt199AGhXXopZOnPGm3FArf/RXoIcT3IPZzGLkMPZvfZUzg54rNHvjE7Ez5Xou4WhwntJpQs2LnYoW8L3FzLP2+IOyNaQQ/h8GkVMT6JgqxCQQnKzmntHBilgFmdNspwSWWzL0MHPI+ZZOhOYFJ8ZOmZHvejOXPDftQpto8TfGRL4lS07JOcWhzPjinrSVnTj8IADh3/tTglAjcmUbwA+ucvpuyUtBiNSFHtG/PF5HfDi6ilQM1eTEq8kzJtbP3XRu18dtn7cvtA5libkw19y9hr/1J7L1XzZdN7Nv/F/EvuJhK8O+F0IpAjQDP+e4W8tRMi/l883PXfWVFQGjNbGKRMyv7mbe2eNdY5YU8XIYBzvltinCgXIjb98m5/tz5U97vy8RgX0wp+EusQyI+88hxQ5rJNakWaqt8bKOn6++rCbI9U7LRd8aVodDmylb1uVce9XClEeYjV6S3uk/o++IOtC+mFPwbW0dbcgBXL1Ldd1IEcc0egpzv+tLssu6nsIrYb4kIhjCrT3JmKv/SdPbahzUiH2cpO0pa1dnQfXvlc6t3O3P6wai4ppoo5JDyTJkUzM/Ugn8lek5YfO441GnY0z6A1AHCtzq10smRpf7ZsXCXq5MjMnKu7R3wwPc8qkObqP3mhTJa5XXKfVvX5xH1aITQz4HKPUkYxzKCn7OVfyQcDvoS9sVsG3CF/pTUEfPgLKkn+2WW1bCQ7/wKyCbh+Wh60m4uJ048gjOnHzy283zlRtOSFhZ7mTCMj/88w2AHzJNOTpRG/+mJGRo19PcQUjeEUlapOy5dc+78qSnFs+i0OWAl+E18FWj7fPub2fh9riMjXUpGHfblsuyPEusrThJKxFaOO08tF6+/dIVF1PwReCNx8+NIPRYoaWVozPHXN6+dVfgLvGEr+HNIEf0juXCDyk5XyXc2cgT2du2KorwXueIsx/fad70Inn2SWtdy6mRNXdomJ+ZPL6QNCNS4hH8tNcJdRL9AyVQ+/KmNj6s/f0m6tu/kHpiVQ4+8Wik0p4tSv9IeosVOW87hSLHrfKsWrlUMsVoLAG0YS6lXQmtSIuvEqBX9o9xlbrnubufnZx+4qXNKBAqmtvCbjWAla4/vIKsVqHkPbnsIzBjqIyNWUD/PdgeiuKeQT8xXviY8Zuzch9S0lTyb4j6CMDvc3XZ8Yl+Yl2kEv2+GO9NGkVKxmuPes7IVfaV3W8Wf3uXGMTqG9kqYor8kzKkNpzKgEvuUk1NBEIRVmUbwpyAdPm8orPMrif5cOFtDV5nA7Bnu9avm70JbZjK8bdgBQDZcVvfR78d1NUBWAeZiCcEfaoyzCMTNij9LeoXLjBJKIZHDWbwJ9aQKYHNlIOTG06u+lDxLxDx/OIrREDEBz1Vgc0rTJvZF9M/DEoJ/g7vIKRHznHzWKVhtQrNtPmxd93z+3K1Fv8RU50et/33utYKwV0yBPdrK3xt7Y+7ZB2569EeYE1aC/8lXfwy3XHc3yYxxr9by1SYI3DbqhqAWURxEWcxVx/W32IFM4v6zb6T8BY5s4t5086EU+RT9+chJh63LNuG//SuWfv6wEvwmVMKfG3uchJjUHCTGVfy7QgxSdO4jQg5ymGQI+bjqIPeIOLOI/r1ZdveA7RqT6rdfWxdcbTB2yJdvr0EPfNb8TZ+JtX8u2MfhX7FSbaLfFK8Uceo5iuFauJ6p4MKML04hZmJhGVvh8vmuid0f+12Yl9Xj4JuW3hz/ad8Jqq5rOPll74mSfK8pq1hbkYml0Bq2Fn7hiL2vCNhIfghCPZTnK6SEYfVNgu1zH1qkk4pUQZZyHfVprkI9vcph1gmyaXh1+fKvZphdEfYW/pRKtM26Z7M2mdbrXCFrrwjMYgUH1j91d+/M1g6FML7TlHO/3+t7Iwm5gZg+4q5rKCz9vmfJKsJxcgR+y/zb88ZgoS/sLfwr+vHb7E38lr7v3vJJEFIICfGRG2Rrwm9yEfumGKsVfaP8sIV54Dgxk8g868Be8KdgdqSpAwWXAYVC/M5k3RfScIXfrKmz5v3E+r4mMeHfGio3IS5984YvJju1gK+9Vwtr/nZuwt77DKqNsyV1m+MkQJiTJQR/iJCPKLeBpQQR+zygHhBb+DRTD9wrtJ8ZCZVhizL23dMWg+Y1Mf/+1eBovadOz0qivyZvKPI1lJf2qhK3eiXMCysf/o888rgrlo5q3Xn2MtisxMx7EwCpc8BawoArZhjOlD0TI8qEe1jQWmYRY2Ih5kXKGBHa7yEIpbAS/DbUfmOugVE2GPYntml3NpHfCm51k1t6hMvEyqZ0Iuo72bn3Bl6uUIvp2s27VOmRdp5GSvhVQeDCsi49qw0sqyGifk5i7UqEwjg4+r8L/eghOKV9l1GyB4Cbdd91WJlMcuZiKcHPrYEI+axg+efiJ9/quyIq16BnObpOAl4JKvEzg4AS0e/eIE15TgMFlIJ8u892T8roVUI/WLv0CGFmEcA+SuLxm+/MLUxnK1GTe8+VhZUwnpjrkER1qYMq2k5vIeY6oXtlatyvYt91TQpy9ozEBDn1GQQi+ueAleC/dOlqko1Qe+lwBIETIvLWJ6eMa/39Z6R2/OKySh3bE2KLe1fY372Mw2aZ50wCfKLe94yc9NReIwe2rQkrwb8hJ8/Fmd26H8I8gXhGertKjGAvg/lslBx2RVmH9iTuBSnvDZ8wptAvlBuxU/ttEfprwlLwm8wS+kygpUT0l7gIUbN1qj18llMG216RdTgN/BzqwUg4TMY4pEEQNnwagmv4y033xCz+drp7CXVO/b2QDivBry4pp1DKFf2rbxDbC6min+NqwKj65ztgrsQVIwT3NrbViVWFP+e8NxFhkEdM6FEScr3pWW6tXYByXGc44Uqjz/uh9ftIO14DVoJ/w3ViY0j033Ld3eQx+4U+7N0aW0OOkA9daw60q3XsnDd5c0HOV3CT0l4oMSOhuKCcCNg+96P6gFA6WuKzjHOz9Kewpd13ZkYq0gesD0vBb2LO/u1GaZ7EmyL6fcfDC2MptdBztOybuCxX3C3jqWkb9Q45E0QR+Pm0EH6c67uP3uNCy0gooQ229jU96fHMFAGfE9GGk4uxmdbUvBS9s2/YC/4NW/j7Gp1UfGE0m6j3news8GHGFaZWoV9X7BNdq8Wp1/egp2tJ73fruZ+phNS8dx041UL0107oQn3Zim1byGe6g7fMirtXNx7ulm1hDbgNEq3q/TX36kd/Zqa2vDiKshrs/IidD0BR37lYf4H4+/ZKQ87nlITKYrYzDnyY+Tib4ULoD2sLv8//9uR9J3AORw3urHH9ufOncDLj/rPHid7yZHahItDhs6bFhE6NK0fv9hPakJvTFlZqN1RlYFplZyInvbO92wpwsvJzEeutyannM650CvmwtfDbg7FvcDaPet5DR+4SO9JQ+dJ6UsllEOVA7gbd2gnDKFr3czkbwaX+8aPWss+hDbSq47liP5SXezyBdoWV0D3DSvBflTF2bA3R/IldPzvS0OZkq3suF4OWz+tBz2dduEFdIdJzrfmp1888qIkAF1Jx1fPt9xb1P2U/hblXr6ZvcUXh4Sy+S9JGNakrKfOZ+8g9w86lh6oSpTQG14ZKThMD3zKb7zNpgHwwl7C51asYqasSHN4ptc77LP7iFnclVHW1dWx1s31xqIcbo8M7puaFS/Bxo6buUIl7ivbg2+Rbk0YKse8q95Brj+96YR7YCf4Qocq1klvLXt5ToGHEhIKTyGoB93bWSvBSbfxdvX7EGBG+MSXPRwu0mQwhZrS1WigngpzzTOANK5cewc/ojnpWRuZbz3jXOfHzXYOYy+2Iq3sItRiXtkUP17qzKtRiv9eEl3M9aZE2c89hCaFyrl3tDCF95BqI4DfgMnO2fZVzvhf6vebeo9jSm5rmmTom6gEldj/77z7RH4NLO/ExU/2mQjbQ9iO1/vfyGfelZ5a+0Ky3Uof9lPa7KfUgd5wV5mQql569kxp5REJsHcFhwCvppEtD2NnH1AO4Yvk8hRkGXKpy5VA/erG5EoREKEU4VtfG9JZ+/KPgEmYylgcldbz12OHKOw55uTK2JsjZ87enfnJ1phf8exG2Oe+5d9HPtYNKPemzZvDbuw/1Xut8qN6k+A3PVF+4pLW2raasAHCZWOwRTnlPUedTNYE9froio0mwgzkRlx4mpJ47kIpE7TliJgFIJfZ9v6d8Zy9sg58sYws1xEJCj47EspHrFiljxxG1Qpsy4lUIM/JOqOxi5Rr7e4rbsMAXEfzwb2ScHV8nP1tnvsoAFBMHPaNWcLGSUpK7Chb6fbb6ltt3mXWxZV2g7lO51ltO6RKXt3pc7pElULlmtsY3xqaEABfDyTyI4GdAr451Rqt/TXr32gGVxs9PdTkaRe+J3yxtpUTsu/7fgtpTX+17caZ3eFT7mlnq697gWm9rxsdNS0idm4vpBf+KFY76nczZ915EMOf3jJ0Q3XKA4Dr4xGjdzn333wY1188sbG4l278jVjJnrXe51Lxn6qnxoefMVC9nYuaVV9/qpdSV/TH9pt0auLnw5J58J7iZOb9a1skayz5nSsu7dsALbW7jRq8QkcJxag/hsvf27GXyNIKewr40LLKPnP4nJ0JP6JTy2Ywfe2d6Cz8Qrrw+3/zZRU4NM/vczZruUbgGkZXqvtSFediLUG3xnjnWfx8izOqoyf/Wdb9lPxiqNzIez8WyFv7Z4vyODnM1+vm5+PYjSOdzmVBc/tj3OLUXX52sKesWbnOhZ+25XpqhYinOmJiZW667G2cfuOnY562F/Cz9+ihy8r9FHXadX8EJOxynMCdLWPhXp0dnLUtzY2gprEMx+fcsunrX81aDJIXVtwWxk1O5pbcFoXe85bq7k68NIX02DaP2THFtvyGkzs3NMhb+ma1ooeg5s75TKqFwiK5Vh9jyonDEXsIh5tBqoJql3vVeuQk9K2fFabuO+vChUVZL08Kf+k4istqwQr8Wo0XdmVlv7ZllLfwlDZlL4+/lF8d5EJHOpI5ay9GIWNAmsUgSuRvUONf1Wji5X9WECG3JiDpgvtu2aXo2sd/q2RzGWg5paE3LujNjxLK9s6zgB+Zv0C1EL6fG6bPu70nst6ijVAJw9HIzldhfHU79nM9PnzqNqXU8Jkha9zVmGzIjJbmiJu2hrq5CqG/scaCdIJRQJfiVUj+olLpbKfWHSqnXK6WeYvztFUqpdyul/lgp9cX1SV2bnGPPKa4ZQevBdVaLQ+7A0NL3c6VBarZ60BLfik2P9pJyEFzuYXGz1dPtHc+dP4Vz50/h5H0nvGGYQ78LNPQ4cI47EmFnf9Ra+M8C+Eyt9WcB+P8AvAIAlFKfDuClAD4DwIsA/KhS6qrKZ0VxdY4zNDyT0mgfttg1/3UNIqM2LkoH46bHKZ0xqyiXtmKu9Nj1RepPHS3LuMcG9FrM+tO7Ll1zr35U+Nv9s71PaUbDhTAXe1xR3ztVm3a11m8yfv1tAC85/P/FAH5Wa30RwJ8ppd4N4HMA/FbN82LUVNzRYqfVxpqW96/BVVauzcu56ebaecUOzqF0w+n5vVZwCrk5O6GybdFeSg+JCm0q9rWZ0P051oPTv/4xAMDDN54cnBKhFZwOSQsFBAF4thGhHZQ+/F8H4FcO/38WgPcYfzt/+OwYSqnblFJ3KqXufOSjf0mYnMukLhdvh3T5DusaSclx2FzEb46VtibNXN7XhvJMiNEDSAo171frby0D2HhqN4u7fmxidYxDPQgZXK6952Lv5OyCWL1p8TzucB0Xhf5EBb9S6j8qpd7u+Hmxcc13AngEwKu3jxy3cvbAWus7tNY3a61vvvrxTyx5hyRKGiY30Z8Dl0bOJR3cmLlutaJWpHEQeaPgIDzsfQIc0jSKkEul0Aa7vkkfexkZhwUgwaVHa/1Fob8rpW4F8CUAXqi13nq28wCebVx2GsD7ShOZQmmFnmVQ8p2EGxtMYkt6raDqYEalnysl8cipYpinPqf0WTXnUYwOXbjigDrre82Qbp9Lz577uzOnH3z0/64oRiFGjuPcTiYXBB+1UXpeBOBlAL5Ua/1Xxp/eCOClSqmTSqnnAPhbAH6n5lk+cnaac470UBJXfE8DA/cBvIRS9zGugwun9iQcUVImM/QtoYnlzH0Ft3znnJe+8JexPpWqn+LaD/vgXJZCH2p9+P8VgGsAnFVKvU0p9WMAoLV+B4DXAHgngP8A4J9orT9R+azlWSXuPvV7mBF+YlGMuA2YAM0AQy2me/u6puLbzF3yvVmh2kNEdTItxzbFWWxxzK9Ser1LjnXf7LNCdbxVv2a2z1Bb5dSvbqzUTwr5VAl+rfWnaK2frbV+7uHnG42/fY/W+kat9adprX8ldJ9SfAc3hRjRQeRC0cmOGqh7dCi+Z6wcVzjFLSd2EEzsOi6sWoa5hMSEa3Uo19IptCGl/pqbdlfut1LJdeEJkXIoVinSnoSeKKWeq5T67YNB/U6l1OfU3K8qLOfeaekbPYMf6gaHdHJIQ2u4WH05spJV1abXHgxgnXxMeY8RfcbDN548FqFnlTyvJUX0lxxSuFHbf84o9l2x9ve8T2RCfgDAd2utf0Up9d8dfn9B6c0ow3JOQ4kbg21Rs/9tDdel9R7ENirvQexT0GOJe4/0qH+h/KXM+1naUm38/dHvKXH40+h1IGGsDc3Yv3E+h0dIRgN48uH/16Iy+M0yFn4zDFrrznzGxi+sySiLvd0GVl054ERKv0MRMUQsgOO49p6LMhkw4DDWckhDKnLI1nJ8K4BfVUr9EI4M9J9Xc7OpBf+q4n4bcKWBXsYsa1OQjLbUCQIl1P0NRYjU/7+9s4/d7Ljq+/cQdzctMoZihwVv4g3Gxk0oQiS4qC0NL3ZCUcG8K5VaUkC4oUmhSDTFtSihYCnlLaLQlroQAaI0DaIhVkMwdhAgqkRJgABxMMImtrs4JjZtXVPq3dqZ/vE81569e+feeZ8zc78fabW/5+2+zJ05850zZ85oaWM+9r4Hm7km6LWJfS3PHijjVLDb2/R3jjAgOkD08ZzzzezD5SLyPuv17caY26cXInI3gFMLv7sVwBcB+DZjzM+LyNcC+AkAq6ny1+ha8APpD1Dr6N2Vd3+PuDK39FQ2W57XUM9szbjuLVpfR8t6oEkQ5UZbG8sl9ks/M01lFsvI9XqLHLa1hX0eod4NymPGmJe6Plzb60pEfhrAtx5f/hyAH0+5kF3G8PfEng3vFiwbQg6UWkfRSxtrJXZGFFk9PPMcdV2rs48Qi4cBvOz49xcC+MOUg3Xv4V+ipww3OdHmkSNlaenlb+3V10BOG0PxUYY99gMpaC6vGvYuZ1YfQjLwTQB+WEQuAfAkgJtTDjak4CdkNFps376W410LtQe4uQURRUUZNAtXkofcAwCtNo7sF2PMbwB4Sa7jUfAPROtpbXay67QQ7SQNu05z9qwPaIfi6KHc5vYzRfSXFvitZmC5/o+4oOBXTk+NlsK/Dhw4hOEr2uffm9djevfdtJwNsp9pC9vTewhpz9deih7b5pq96klHkHIMs2h32p481HhxGo/0wFIHVLLu9tLhhbZ3LeKml/L1Qcu9tHi2MX2OJnq+duIPnzMBBvLw9+5l2Tt8fmHUHKhqHxSvebJcKV1Djpmb0gK5xgzQFK7QWuxr9Fz2kjyB9paQfTGMh78V2sVQL3CzMZ30Vr/tzdliBU3PdbCWAC9ZL7Z2C7X/TVC8hjFSeeVOSdt6EFuKkZ45iWMYD78NK3af2IuNRn2GS15RDZ7SOb0JfZvUujNq3euJngdd2mH9XkejPc4F4/r3zZCCPwTNDXuvDZIdkpuehTjx58zpRy9674GzVzS4EjISmmxrbmGdMyvO0nE0awVCfNi94CeEkFpsiYYloW9/Fir6W27ORsowF+0+jiFNQr8kpev7yN5/Mj6M4c/A3re1n7PXmYnSULiNzZrYD/nOGhrEyshrdVz3VjKbT6/9RG9M9tfXDmu316w3+2MowR/TiWhvlL2ytfCOPIuPCGM9HZtUIW+zVZ9ain677S8tvs1xXG3Ywqqk6F/6V/KcWtEwqCVEI0MJfkC34c/BCMZ7hHsYnVKzViSdnIODmqwtxk8V/1psSo3rCCkjLeXiopQjI7ftirGHtJ9EG8MJ/hhSjc7Jh04UM1yxecQ1kNODp4GWBrzmudlRlUFTuea4ltBjMKTlQMz19r7BVws0tTetsE7tiyEF/+ihPaMI6F6wvTv2/7k6FFfdKzmQdMFOcjy0zdaMLjJiFtX6Ho/Cvz7zthPSljS1OxesT/uBWXoseliB36vYHzW3/shZUEa9L3JgaT+I2N+G/j4XWm3K1nX55kPXen856aHfJWQEhhf8rowJ9uf2a43Gx7VVey9buE+0FP0ugRIjXHLWj7X6Vrseaqv3I6GlbDXat1hGFcOj3lcLcjtkRmk7ZJ8MK/i3ssSsiX6NuK63N9FfCx/D7CO0fTqL0E4lVHSV9Jy6roPe/bxoENojz0b1zGTDtfdBvtCm+DOVVeuyoY7YB0PG8IeSw9C27sx7obRRyR2v7HuseZx/yO9awTqrBw276GqrD640k9NnIzHa/SzRqn7Fnrfm2hdtbY+MyW4F/5Ru6UJEAAAgAElEQVQ9pkexv4fOIRQtCxPta9BwPTG09jYtoeX5prBVrnPRf+Ope3HjqXuzXkOp7DyhdSYkxj30t6Qta3VhhHYciuue91YOpD3DhvT4siT6Q6bf2WjDsb38qZ336OWfW3xrKq/Q0KnU342ChtmAHLiy2VDs989WH8rwsrr4lDfDesZntx5+m6mS25VdU6rELXruBEc3MDEerZYeslp1OyTVXexnPWKL+bseuQ53PXJdtXP7LFYvmZ2HKSf3xVSfarRhLXaiRSKGkHOy/Y0NBf8RH9FfM3tLKEtxrqRfWgwsa5wvdH1DSg7sXlnz4Gvx7mtzehB9sI4s0yqsyfec1BDjsvuQniXsMJ9patIl/vcgQEg+UuvLyJ1oSohPL+XiGy5YU9jHlJ2W7CIh9FRPCGmJHd6zNAAYfWZ+VCj4HcxFP8lPDk9CLwOv0OvLKU58zl3Lu1/iu67v99ZuNaTuXGKENIt2Bq2erjsFDak+a9bpM6cfveC1PWjeyzOfk1L+PmtpKPz7goJ/QHx3cRyJuUHXKJx82dofYCvGv0Qn26NHVyvzWUOXCK01mF16tqM8763sKL3fnwsNYn9C60C2NhrKYE8DXnIxFPwraDKaxB8NhjWVJfHlSymxP/3NDiMduwxdf8/fi3muZ04/6h0eVGqwWJqU63XV594HPFr6LdqLdVwhwz5omNVkZp++UCf4OVWUlz02yB5FS0u2Zgx83mOnrot5eIMvvoukp+fd2imSc1+BXsIDe2DJSVC6XKeB7bzuz23TWp2t+eyn68ol9l3vz8ueg7D9ok7wa2O+cKVHz8/S1u25BgEpA7TWYoHkY62jtDs2iqlxaOVIKFWHfEVUT7a/FWsis5UNaO34qrkmK+X7oezRqdgr6tJyTjvgaqc34TIX1i6h7drKfukzivUypITzpJyrFK1ipntro6WI9fa7WPKY1qJFHvPW1zAaNW3AyYdOJGuKEQd4rMP7hB7+BEZqNGsDAB9PPEf5umndaXEaOR1NMyR7b+sxM717mylY8/KXqsv24FZT+Wq6lhLQ+dcHqjz8TytuEyN3cD5iPvf5SswQ2Kn3eiVnxzBt3mVPpbcsm5abzdj3zvoRd16Nu4y3pue6VBqNGZJGWCPINkhiUSX4e6e3hlhKyNc855yROuCcsZpzT1uJ87c6Zsg5e6ofWsIbW4bwzNFoY30G0j3Vu1S2ymP6PHeZuELXpj5n/v8S84xZmmbVcjPqfRE36kJ6tIeGtF54lJsSAtz2omzt2EcuZKtehew3EFtHR6nba4weYlRzp97a7VqrCNN4TTVpef9LYn/0Nk5IKOoEv2YuHIjo7HQ04eNRyYlWIZCLnJ3XVv7xPaA949Y0WJ6voanpdFgqm/mAvgUjOF601z9fWj8Dn0XpvkkrWhHq6Ml53t7rH/FHpeDX7uVfgo1GB6OLfpuc97mXMqtBiX0KlmbJSu4u7XO9GkTTWnsP2XSsJT2KrpHthcZn0XrtAxkDlYIfuLAz0Sj+D9e0H3GpmbkxHFH0lzTyvZbVJOgmD1+suFvKER5a3r4x3KHHndvBNa+6T73fKqsexYTL29+D2O+JnuzEyM++xE7qPbZ7Ek4Xi3Y153xn5gpdtM5E0xMjlJU9nZ+abz52YXNIGaaUd+kMI73bMZctPnP60Wf+Ta9JGJrtROnBa44+vsRaq5xouAZSHrUe/h7gYlSSmyUv7d5j7WsQU56pi6JjRMSWrdkKcbH/toVS72LfxqcMUmeF9kQPtqaH5+jypNfcaHGNpbAhev/HogsP/4RWYa0x5Ij0yWRg7Q1qiD+1vLc5OuZSMyyuOmOLoi2BpCUlaChLZbp2r7bnvxWa23gPYr8kJcJnemGEfUvIhXQl+DXTY+c4Cpo7zBRGva9cuIRcSQFXQqSXyEtub5Rl16MHzl5xkWd/Lc/+KHZta4Bje/5rDgA0t3EKvYvz8udgrVzn52hVP/jsx4QhPZFcdv+5Z/5+/OqTAOLS1Pmsvi+R9aN37LCIUY2TXZ9GvcdS5MrQUrvcS02h+4aK5WQ+WGg9Q2sv8F7CFfJUI/zHVc9KPKO92BKt4Shb16TxmskYqBf82j1Mk9ifCBH9c8M7N1BbC332ahh63Tk1lNYCae+0qlul8rOXWDPgQpvYn9gS/Tbz781f1xhQhqRj3HIMjWwrtRO7bwSfGcmJesGvlbnQt/ER/a6GHJvxY6/in5BRabUxU+o+KFrF/kSI6F+jdp7/mgvLyTK+M8quNhvalkeewSb1US/4e9yEC6gfjlF7up6Ugc9tmxAPbQ/ZO7boaTavldifD462bG5O0T8dj+wXW5iXmJmj6Cc56GLRrjYPkS8tByrac6ynXFsv4icXmp9jCvP86L7f3yO123PM3ieaPPs+NiKnSN9z3SxJT2U66p48I97TXlHv4Z8ovelMSVqO0Je8g61CBexzT3/HXsPIXo+coVp2h6nJC7kVH02W0RrG19q5sYSPtz+Xp39ilFmlkiyV91KZ9bBngqY2SMgW3Qj+id5CfKbQntai3/V+boMVsygp5hr2IPaXXoegVURrva7e0CL+l+xxTe++b9YTV1vKLfqJG1c5+5R/zGCqp3C4NVo7uJachC0dhySO7gQ/QNGfkxzp4LTdU6/EdGhr3rK5kNmj93Ev99xK2GgK49liTfjnFP1rs2paZ9xyUnLwpKk912pvLftXjZqFxNNFDP8SmjuWJXoaoADLRmYpjriFMRjRAIV0klux75pFBT2p5WixbmeywzEx/61wxVqXaCvzAbfrs94JXY+Teq6Uz2sx7VY9/xeCxr5O+/pA4qZLD39P2J3gobH3M2IOyRFdi17KLpYlD1ZqB2Z7L1vGw2rpiEentre/F6E/Z8l7WSK8Z9R6r/m+bDuauz3YxyrpyNPY12m8JuJPFg+/iHy7iBgRudx67xYRuU9E/kBEXpHjPHN662im6x1hNT/FfhlyCPGlYzxw9ooL3tfcWZN06IXrg17bYevrDj1/ibagfdZ+adal9XMjbUn28IvI8wHcCOAh670XAXglgBcD+BQAd4vItcaYp1PPN0dzPP/WgKTX+DiK/fxMYnzugU8x0FuLFUvsHEp0wYV1briINxxN5aIpnr8Esfpg6RnFruXaOj/tSl/kCOl5I4DXAXib9d5NAN5sjDkH4EMich+A6wG8K8P5LkKD6I+dbYjdcnsv7KVcSsb32h3HmpjRHPtP0vANa9jLBn61NubywUeApVxLrrasSezvhVDRX/MZjWobRiZJ8IvIlwH4Y2PM74hcIHivBPBu6/XZ43vFuDhWvuw5ctOrt78UeyqLEkZ6box9Rf/aNaUKhxIi6sZT9wIA7nrkuqzHJQdGSWto42tbtHj6U6/B9/drufC1sjRYmp7b6DMAKbBs9smm4BeRuwGcWvjoVgD/HMDLl3628N6iCheRmwHcDACXXPYJW5fjxdYmXS7hHvr9kmjebCQnrk3B9kROYeFbX2LOmaNO5rrXSejbr31F/14H1z7ifalstOT7z0Hoc6/t6W9J6/OXptfBq6+9qu3dn9KNk37YFPzGmBuW3heRvwrghQAm7/5pAL8lItfj4NF/vvX10wAedhz/dgC3A8Bzr3x+Vtd8aGVsXXmXGvYII3HfWPE9irASLHVqOcs2tU5q8ZyOREwbi93wrrZoynHOlPpfo76yPcSjrY8MdSi2IrXcWuslEk50lh5jzO8ZY55njDljjDmDg8j/bGPMIwDuAPBKETkpIi8EcA2A92S54sFZ6th67gx6vvbRSTH2tXJuLzH37ofQo4dvDddz8Hk+OTbdy8mUWcjOMGT/H5N5KFe2Ik2CksST0/FhC95pH4o1EZyyV8Vodou0ocjGW8aYewC8BcAHAfwSgNeUyNAzMku52EcTz0vbdO+RnOE8pb37c2puuLPF1kDALpveO1DfMtci+pfE/Pwz32vzFfG56z1Fv15cM1w17NJcxK/VdUJakk3wHz39j1mvbzPGXG2M+XRjzDtynWcPTJ2taxHV/B/pm1K59wG/bCS5aF0XQxfu9ir6Y9detCJVuMecr5TQougnNjXDWmrZq17tItmGO+1mZqmj8Um9uZZVZQvmU++f2Dhh+1lrWACtLZ5W07XkIFa8ry24duXqz7G4eU3sp9LKe8o1KDrxtT29Lt4lJBUK/gxsdTwp08+tsqmUYromhvNcSC6xH1OWuQWM61gt6yM7+ANbwj+n6B+5XVP090MJJ4S9AFf74lWmLiYTFPwJ1OrQYjsXrRspUXylseal1Yzd8cbWad8Fu5rqe08seftD22sPdTEHFP3+rLXbnEJUwwxjyc00Qwfgdrn7pi7eS/vdI0UW7e6B3hqFho6pV6G6RY51FSH583OjoW6kQu9VGLGLebd+M0J7DqG1uNTMjafu9Rqg+35PK650mycfOtHUuZWrTOmgGwcK/k7otWN54OwVz/wDxjMeLuEUIqJdgwS73FqRuzOe7rPkIGNeZj3XuZKL82NFvyvTzl7R0E61Mfcsh/4mha16XcIeXPqguehfS3oeQJFydBfSM59yrr0LZMuOLXUKeSvEZ+3YS2nOQjs5DYtKcxGSEnGtnNbi3V351XOJi5C6FLKTbc7z+rAX734p0b9Wn9baaM/ttwQM8TlAsXlA+060Pv3I1GfvdXfy0ejWw7+Wz7lUxUw9rqbOIDQMJaeXseep/1qpULXs7GmLaY0d+Vzsh3r3tXv/a3iOW9ulkdIL793Tn2ojcs4oangWJTz9TM9JYlHl4Tcn1htHiEjM6flPEafzjiw1g06vXqQePQS5ytnlRa0p6u3z91h/Ju565DpvQcAOy59Wix3tuugKa/P57dZ3a9KrjU4lp0Mg54wicGH9rp2WU6On3w6xnffLPmWzVIa99e97RJXgB8o0Rlee6a3vl0RDNoGaaDUGe+mYR7pPlxBY25OAbKPRJrkGAaXD3VJZusYlQbyXcLQYcot+ciBV7JN6iMjXAHg9gL8C4HpjzPuszz4TwL8H8HEAPgrgc4wxT64dT53gB8qJQ1f8f8k0WmvEdlBaPEiaOtgQNJRdCqGe0FRCvOotSBH6WgeiE7Xraq09PHKtRVr7XJttWmpHtqitlboyNyVtQ6zoL903PXGVNF+Yu8ZSXbvrkeuKiX3tdrRjPgDgK3EQ9s8gIpcA+BkAf98Y8zsi8okA/t/WwVQK/tLUyjDhu7DTZZh8hR031timd5G/xej358No3qmWz7TUHh41w9hqD4xj8U1dCdS38fa1sX+5kClMZy785++XCOdZEuxzR6DreW3ZydAQJIr9chhjfh8ARC56Hi8H8LvGmN85fu9PfY7X7aLdkciRwhHQuahSAxrFsMZr0sQ8neva94BxxH7JNJyx5LgmLfeUul9GKqmiuaWNn85d+xq092tPXCXPCOSasfpLNs+2m3Pb+cDZK5zZDe1jue6BMfvRXC4i77P+3ZzhmNcCMCJyp4j8loi8zudHu/Tw16BV58a4R52kTDEvTc3uiXm5zdtWrNhnhxWOr+dfg7j3ocVu5KkhcjVtvH2tS+fULsZdlFgrOBfKGhbqzsMd5977lglNavOcJw0uu/9ci1M/Zox5qetDEbkbwKmFj241xrzN8bNLAPxNAJ8D4M8BvFNEftMY8861C6HgV0LOuFOK/mfRIjw0hhL44rM9e80sQD5laU+za+h4fdBSV33p7Xq3aCH+Y6lt4+1z9dS3aFnvVoq17HdzMW/bxFFmREfAGHNDxM/OAvg1Y8xjACAivwjgswFQ8PdErsVGo4l+H6O9tDlYz/TwDJfqas1Odq1T64VR6utIpKb83HqmORbC17IP2m2Qi5i+NDSjnwa2FuD2aBPJJncCeJ2I/CUA5wG8DMAbt35Ewa+QUAHg6jxqdAilsiHEiKCehNOWKA5ZLBey6HuNpXOuiZIWXlBXR9xjp9ZTfd07JTL/aM9+NRq9ZpXzweXpv/TBC8NYHr/6pNNW9jITuidE5CsA/AiAKwC8XUTeb4x5hTHmf4rIDwF4LwAD4BeNMW/fOh4FP1EDBdCz+A7U1jqw0aaze/K6rTHSM9kbPpl/aj7flrOAPQxWYp9F7c25cuC63sevPvmM6J+Lf5sewyBHxxjzVgBvdXz2Mzik5vSme8HfU9xlC2p5+YFlgemK7W7ZSWokRpxv1Xff44XMDk3vtV6w6evR19Rx7b2Oj8qa/duCXv52zEX9Urru3kQ/IWsMlZZTU0q72oMPDXGWMelFtTyv0qzd41RXQurMluBOEftbn7UW+72xlzq+d7bauKvdaLDdI7NmryaR31O2mVxcdv+5C/7Z9BgiSbYZSvDbsJMlmpnXzRz1NfQYoZ7FLWFSs71p8tyvQRtEOPOsh6X2uAexPw/fCf2cjEH3IT1btNxmvXbYisbp4Wmh1N6FT876F1qvctaJXAuEa7A2KKjRyWssk17wrbOjeMdjbfco91+SPbTDpfj7uZfejuWPYQ8Do9HpWvCHhpDQ09KGPRjcVvhm+klFo7B44ipRmXGC9T2OmPoaks2qBSGpgjU6bNbo7Xpj0B7Hv2T/1sJxJk9+jPBfy/lP+mDYkJ4lWnfENQYcGju9vZNrce38WLXE/tK5bUq0K99jLu1uuSX2S3ZarW1Mj9x46t4s9XU6jmsReitxGlInaL+JLylx9o9fffKCf7mPT3TSreCP7Vin37VaMMpZBpLKWr1tKWxaMYl8H68+xf4+0NAGYkMZQ0R/y/vUUMa+pOwErtGrTTFOYugypCfH4sal17XEeOmY9vlUaw87tu6VkCn/kM26csK6sw3Fvj6m9tCq/o5eJ2qF9OR4fqnPYkv0+4S75AoNotgnsXTj4a/hkbePX/pcJQYX9jEp0vQTmoazpYAYYWaqlKdudGHXO5PDw949ehKqWmfEaL9xwTPTjo9tOfeC81lsUC8Zyog+1Av+FmE39vnm+eJdswM12dpddQRxNhKuOhOyaVzNTDw2Ph1urfqW0llqnJYnB2qKuvnMp2Z6EbskjB5skW+IJOkLlYJf+4ZM8+uLvdZYoTRlHNoS/j15SPZOSl0vLVx6H0Aybl8/pe2UHd5j/7M/1zgA0G6/Q6/Pt0/Sft+p9CD6l9CcsYhsoyqG/8SJp7ruQEM8tvb3Uu557ffTNdwVfXRSgpwCuqRIueuR67yutVSbXUqlG5omj2KfzFmL7deY5nOE9JchZZlS7lv9oaY2qzXlJz3746JK8I9E6bz/9vHXznPyoRP48ENXOoVPTgOozaD2SEgZxooAV4c6Fzs9ePbXOk2K/X7QKGhbL/q1sdcfaCOmfJbuR0M51yZW9K/tQVKKLXt65vSjeLDStZA4KPgLYovyVgJhMii2UbEb7prAdHUuS4a5B3GomRr1ZKtDtT9/4OwVz9SZNUOf43pDB4pTnZ6uy76+GpvDUOzno6aAtbOV2f9rFNEuNAv/GEqIfJc90dpuexL9pG9UxvCPRMm1CL7HnQug+QAgVKzPOxuK/W22nlVoPQnt8EM6Vs1if8J1XRT7ZI15iuJehfPSOgTij7Z2HGu3tITfaCtPssxuBL/WRVmpxIr+XMzFPsW/m7XsT0us7RoaQqzYXyOX2K9xnlS0JxEgcfi2oxH7jZ7I2ado7p96FP20i33BkJ4B8F0vsGZQQkJKJgGp2XhqxqeMUzZOi/H6Tc/SFfo1kcu4tw5180X79fVObyE1pC72OrWltjhaH9Q6vCdk8EDb2B9DCP6tDmM+hctpUDe2EHOV05qRpRFYJ1TsA2UzXCwJfSBM7IduW0+xT2xqh9jE9AF7X1xak5AMd7HH19y2U0Q/ELcTr4/Qr7E+ipSlK8FPT5CbHFmBLojrx3rmHzb8OpQSFy6hD/hPLafsI6GdHq7RJsTpQdKYBgwcBOTHZVNC2+Pawt0eNqdMSdmZIvxD0D5wIhejTvCXEPV7GSikin7byKwZG4r9NLYM5SQmXCLCFQYRsitujNDX3knmordObC/2TTOjzBy3FHE57UtvbXiJ1Dz9ttd+SfxrWfBL6rGbRbvEj3MvOL8q/EpnbSEHQlJo+mbrWBP7OSjx/GsPMnqrwyOJ/Rr3YreVFIGeYzF9C9a823sZ0PdELufaE1fJRf9ywDrTF+o8/KUZwQuzRq4Nv0IMTW8iaRR867JdH0ptUjVCHejtHnwF5ug2z5elchgtr/0aa/2ChnU1a33XfOZh6Xu9tV9ftOzIy5n9/lEn+Jm1IZ3Su/za5yFxlJo6dz33lA6jVuYeko/eRP4oNl/T7rw2PmJ/+ltre86VLKJW/5iTye62Ev5bGf601hlyIeoEP0DRrx027jSm8svhVSst8LcoWRfm91ZysfgIdVqbyHQxF8Uj2npNMf1LNiLF2z//7dzzntKWYsT4CG3XlxbCf8vm7qn8e0el4Af2LfpD0xwuUcKLwYadl5Rn5BOPby/U2orZ9OlA5oa/ptgvRc91WougDGG+v0QtWpSVBtGf0o58wmiW3k/tv7bsos81jU6NMB+G8IyHWsEP7FP0u4xnCcO59jtSj9BUdEtify0FW44FWjWN/147cdKGUfuYntuRb9+lySFWG9sm5xT/FPrjolrw742tadaaop/UYWuh2vQd+z0foV865VqpQSHrqh5GWRjZ2sveMy3bI/suf3KIfwr98VEr+Ef1uqRQK5MCF+HUxdWx+TyDGrmUa3UE7Nz14BO+EWojlnaQLm3nW4v9Vot4R21LvfdLNcKRfMV/Drve+/PYG2oFP3ETKshjPCUa0rT1zlaZ22VrL+RdC+XRkJ6tBFtlVeK+WbfrMhe9tcX+Utsa0bE0ktif9109O6Pm1712H7meIb32xIaCXwkxgryG4evZwLbE53kuDap8M2PUonSH0eq+Rq3TaxlUQghZOBlDC7HfitazDKQ9oe1lnslNG6Paz9HhTruRzHcsXNvBsNY1hHLm9KNeDVer0dFMiEFcC5+wn3EJL/faYt8a+JTTqLMauXGlX8xtm7R39iFifzQxrs1Wl7gebfe4hm8fW+r3JdB2PcQfevgzEGKAShrArYbo+jxU9LPB+xESShVTL+be91Bh3Frs+zC/p5K5+HsltI61HOSX9OwviXfarf7pcfFu7rrWOhUp284YUPBHMPfsa6HktcwbPEN9/MjZWdm5l5dEb0huZl+x7xLYpZ//iF593zILEakxdWu09TlbQh8Y517XWKoLS+2o9wGz5mdZ49pqxP77no/0xa4Ef43p261Fl60o6XEg9VkS/qVE8proj2UtRnVEsT8Rah+2djUtcS1avfvznXl9hP5eGL0dldpIcrRQt9yx/xruieRDreDXuumW72JMNhRSg5hOXUMoj6sdjSRSbLbsRsnQr5rHc7Ek0pfSdPoQuiB3zRbXDjEqQajYn3/Wk8dfY7+q+ZpyOGXIOKgV/BrIKdxH8u6Ti6nxfHOI4bnY983jP/fyb12LZhFRuz0s7Z7dOia3NkviN1YQz8vLroua610J1srCl7UwQU3EtNvSazi0962xM3ja74vEsRvBH9q5TI1i6pxT0mZS7I9NL2K/5jWELq7VcH8puOLifTaw6olW9mRL2GoTq6W9+6VDeEZZHG/33Zx5P+CyUSyb8VEt+JfCemJCfWzjG7OjaWzn3LpTZwMuT09iv3YoTysRX9tjGSr2SXjZuOqSRlFaUuz7Cv1LHzTRu3DnbrejCu1R7mmU+yDbqBb8cyZDGhvf3ypOtgVsxHnpvU6UEvtLx40VGr4seR9beXx7rxeh5Lzf1IXnPs94JDu4NcuR2sZ7n2ULhfHtZG+oF/wub4mv6J9+v9a4tYTfEJ20rBMlO+EUYb4mLraER44BQc5yiY3z3bIpo5PrGYQex3cw5/MscyaHqOXZ9xH6pQfdoaR6+WN/v4d2SIgv6gX/GvM0ba7PfTPrkDq4yjr3Aml6YQ5oyMpjU3pAsCUIc9Q/nxSaNaidZ72VF1hj6I5NrYw8dvlra9elsGPwJ2JtO/t5smeSBb+I/GMArwXwFIC3G2Ned3z/FgDfCOBpAN9ijLkz9Vwu1oztXhu41rhJ35kWkocSoqC00EiJP47Ft95psSe+aRdThXJJgb8UypNL2Ne0I7UW6E5lVGMGTcsAa23Re6m1d4SMSpLgF5EvAHATgM80xpwTkecd338RgFcCeDGATwFwt4hca4x5OvWCQ3jg7BXdpBzLjVbhvJbxKMc1L+2CrLUstkgVWz17AGNFf6l2rkk8hGZL0sDWc+nVPlPs+xPq0AnZu4IL5gnZJtXD/80A3mCMOQcAxpiPHN+/CcCbj+9/SETuA3A9gHclns+LuZHcC70K21zQyNfhiaskajBx2f3nAACPX33S6/v2OXyETE6horUulbJprucZKyBbC/iU8I+5iF8KGa21azvgJ/ZzzYi1fm4TMWmwa7H3fpb0S6rgvxbA54nIbQCeBPDtxpj3ArgSwLut7509vncRInIzgJsB4OTzLg2+gNG3FN+CxueAVoEWy0je/Unoz1/7Cn/g2ftxCZtcQkVzPSqx8dqc0usnNLIl3n3EfUy6Z5/jjSb2GYpDSDs2Bb+I3A3g1MJHtx5//wkAPhfA5wB4i4h8KoAlC7RosYwxtwO4HQAu/fRTQSrFV+z32Alt0bPQX8qIlKNzLEGPnU/NFJw+zIX9ZfefCxL7EyXj+nt8zjGUKsMRbeycHF5nHztnh6LWEPpA++e3l/ZHSEs2Bb8x5gbXZyLyzQD+izHGAHiPiHwUwOU4ePSfb331NICHE6/Vi8lwjbJT4BI9i32bKZ6/9P3kOod9jJIdVI0ZqhCxkHsAoU3s94DmWcuR7Gxr4bkHse9bxntdf0dIKVJDen4BwBcC+FURuRbACQCPAbgDwM+KyA/hsGj3GgDvSTzXBWwZDRqJPkgV4qU7aNf1ldq3YXSxH4Nmsb9nUaLlnreewdaA36cN+7TL1PLwFftrhC521/IMJ5bKeWTnHZrmrCQAAB9RSURBVCE1SRX8bwLwJhH5AIDzAF519PbfIyJvAfBBHNJ1viZnhp7WXhiig5B6UGomobcN20YU+63EAMV+O0IHxrHtMzQj0lq5uOxPrkw8oe219TO02Spnin5C0kkS/MaY8wD+nuOz2wDclnJ8Upd5Nopam8m0QlPe/7UOLyZF5fT9GNGuQehrR3OITUlCRVdIOa0du3Z55z7fkp2Z756b4tUPheI5Hk39BiEhdLfTbi+e1B7ItaV8L2isO77CIkT029+zU2j6/F6T2Nfo3Z8/r1rnP/eC800HGSWFfspvclHz3HOhD4S1u63vtti4jhCin+4E/96hZ+GARvEeio/IyCXAexIAvte6F7G/db7cYjXlvvYi2pdYK7e5vUqN1U9Bm3e/9XOLobSX33bGjT7TTupBwY9+YnEp9vfFXAzEeO40eex9CLm/GgspXefRZCtCQ2FKXHuoaAuplz0MVn3K1C6jVu1SU70F8q6RGJVJ/FP4k1R2K/h78yrUFvuajUtO734OT03M9eSuf7l3Sk1ZA6CFVHHgekY9iY4a11pipqq2yE8Ng6k5W7fF0n1orLOxYV9a7oWx/KQ3diX4fTIBAPqMYy2jolnk7w2XOLDft+Pz56QK/fnrnoR/KaGf49gjMYrQX/q7R3qYCQHSnR2aRH8ppr6Y3n2Sk24E/5YXtTePvQZ6NCIlYvdjPTUh1xJSP32Fx9L3SnX6a4OLnOdIpVT8+egCw5cS9Rgomy526di9i/uc1HR05eqntTjnSnv5e+yjiV7UC36XqCol8FsbEOJHKS+PXd9SN+uZKFFXW3jzSor+1PuhVz8/mjaBS6l3exD3W+WowSGWeg17bYdbTH0Rw4vIFmoF/5KgKm20aFD6oEQ9WKpvLvFfWuxvCeu1zn1ehzV09Gu09uoDY8Tqp1CqjuQIOduDWNdA6bqu3Q71ygjZ6kg9VAn+8+cvqe7Rn9hL575EL4uPWhq32ud2iaUQsT+9p7Gz1RBvvHehD5S3qynPmWLfH+be3xe5+iOm/9wXqgR/K/bUwdvYRqOU6J8bplzn6OGZpYqpueh3deg9lMVEblESc+8M39HvcaXYDyO1XYWESMaEUy45HnyesX1f9u81tNNWTjJ69Uks6gV/yY5Jg9HQxJohybWoNXWBrFahUjIsYo2adThWhJXyPOYS+3uzA1rb0ATFfhi52teWkLfrTYz4tkV/bGKC6V61if8a5Oqfbzx17zPe/JxefQ5E9KNa8JfomHo0DhpCbkIWBm01fA33k4uW4il0s58UNIn9pft2CXmG7VxIr2J/9A3nYsndvlyif63ehIjvqU3GJgBYGgC0Ev++CR5ynYOQVFQL/qnxcnV/fpEca0jWrqO0cdIkVlpfi3bPfk2vvutZ0Jt/oERdrZESNuV4Pe4fEUqpNrbVblLF/3wgbt9H6POahzyGiP+c7eLDD135zPlabOQYAmP194tqwT/hm3lk5M5cg9jP9fvQe9Hk5agp9F3T2SGxtrmvYY2SiwZd9+xzjyPbhRb4bgoXQ0od8lmgXmsgcNn95/D41SeLHb+HBbo+sf5LG/3FPps18T///MDyeS67/9wFr32f46UP/gU8cZVEiX/frISu8mw9a66pjyZuuhD8c9iBk5q08OZvif25cZ8b3Jpiv7T4iG3vtBN5CRFiOcR/CNOzXpsVtq+j9EZyJcV+C0J2VV5aaBvSFn2ezVyUAxeW+dLvl37jQ8gA4NnzHu7bFv9r+NprjbsMU+z3Q5eCf2/kGrn32DBbLtZtKfTtTk+zZ7+1p9Hl1dXWKbYkR2iklpmeGOzrscuixu7RIzJPAbok9OffsYXqyYdOXPT5vI5uPZvHrz55kRC3X+cecIUez772yfOfA9q1fSEi3w/gSwGcB3A/gK83xvwv6/MXAPgggNcbY35g63gU/MpJEfs9CnwN5BRGPoZ+7TdLYr/01G1ourzSbHm15vHF7BSXidmToReh7/Pc7c9TF4+2JmRx85IgXzvu2jG2zm9fx1aIzURse10S/b7fP3HvWZy/7vRFnwNxMwFrZXvpgyaLA0WjXaPGKM5dAG4xxjwlIv8KwC0A/pn1+RsBvMP3YF0J/hChU7IiahcVozTCFt79mHOtGfO10IatwcGWZz93GI82oR+D5nbZGz6iThMxed6BtEWj2vC1RT7k3LQvxhFSgkn0z8U+EB/ys0XKzukTGu3aKDpDM8aYX7ZevhvAV08vROTLAfwRgP/jezz1gj/Wm2n/LlfFbJ2ZxQffe205ePJZYFRb7OcW+qHfD+kAW8TraxN3tZjq6d46t1x1tSYh7bGkXXGVT0+DCVtghuTMT1kUbT8Tn9+7BHrL9ROubEaxbUaj0Af2Zw+V8A0A/jMAiMjH4uDpvxHAt/seQK3gzxm2cOb0o8kVtAex70to2ZYQPSF5/UsS8lw1ddgjx+m37uRa18lSrNUZrXXBB99rX5oByHk/W8caaSZhiVixHyr012gRu6+xTZSCQj+Ky0Xkfdbr240xt08vRORuAKcWfnerMeZtx+/cCuApAP/x+Nl3A3ijMebPRPzrn0rBr6nDbb0gMCTdVunGmGPg5IOPdz9HWJUmse8bZzuy0G+JJpuTim8dGVF0LrEk7Kd7TxH9I+4TsLSTbQla3vda7H/IgGHt+Y/kIATGEPry5HmcuPdsi1M/Zox5qetDY8wNaz8WkVcB+DsAvsgYMzWcvwbgq0Xk+wB8PICPisiTxpgfXTuWSsE/x1XZSnfSWhrt0o5+Pg2wRPnkFv3zAU3LrDwuanROseLBd5FdretJpbV3v3e22k1KvahdJ3Ltuut7XB9iF1W6nsvWup7WaLsem9BFu/PfAnGZfbQK/RFEObkQEfliHEJ3XmaM+fPpfWPM51nfeT2AP9sS+4Bywb9VgX0HAqENYavRttrKG9DRqEt5+muK/ZBzpGTy8PEkpXoKc3fKNXfJBeJydedmaVA9f187OUMjgLYzPLnrdMisVsxAwydDkI/N0ZY1KOR6NF13KFpDdzTYRtKUHwVwEsBdx9CddxtjXh17MJWCv+VOsCFCcM+NMKcosn+vybNvE9sRr3Ukvh3IVvhSLpFQW+j7fl6bXkT+UluJqQeaQrd8rj937P0c32OH1tucWW9IHnJ49XsjtA5qs897whjzaR7feb3v8VQKfhuX2JlX2prx3DnOV4PW222Hon2wlRJ3m9phbJVNiugv2Zn10E56w1UXQp+/NhETu5NvC0rV69b3RdY3EKtJjjoWO8Ck3R4TtYLfrqg+lTZmce0eGsOStzLnIGBPKU8nQrJthHoLXbnE58dZSv8WKvpLd2Q9tZMeyCH0S87i1NrJNyeh5ZFSp0uuryiBtutZonQKzpQc+T7tweXMrO3AXLseMg4qBX8u8VdCRI7QILZEus+AoGehn/Oca+I/5+JC29O0Fd7TmhHaSCt63Qm3pwH7RM0Nj3oT+3slpI2krttw/b6V2Cfjo0rwy3n39ts++KY2XNv9dI1ehExqaEzONRAp3o/eSBFUo5RHL21EG5pSxOZg6Ro1bUi11VZLhuxozMyTK02oxnvzpYQWmM/clqpXOWYFyPioEvyxzI1KiTzj2htTrGBMyTjkG2rl2n0Q8B+k2ZScVm/JvJy0ZezQ3gZGRVMdWGPrOpfaujaxv1THl2Y8U5wivTzPUJbKVZsNc1G6/yltO+fHd4WIbsGsQGMzhOAP9U5oCHvIieYQKNdxYzqBPU11asroQeNflpILsm18vMshtjH2mloKQNf9ueq4K7wxdvdxrQK45P4MWu95YmTH39SPhM60xwh/Lf0VcTOE4J9YE/6jifyJEo0sdyy667gh9Cb259cbMxsC+HWWMefyQXvn1gsxHe6cpXqQuuHa0neXwh1Txdq0F0XpBZZrhAp9X3z2JJk/49YzHHO2nvPI/epIYj+GrZkAn1AhCv1+GErwT/RuhGrjOxW/RqlOrGVqspbY1xyTSSTlnkfs2EqxVc7nXnA+24DMpx64BgGucIv599Zep3LZ/eeaiP6le/ep477ZzNZEf63Zm1jsstlKR6ltg8BYamZmqomrruVwlu1pLd7IDCn4c9JLY48llxEuMSXcs9gP3Sdi+n5ICtrcdTNmDcfo7cNFjjUztfAVOD0vuFwixa7U3L/ERwz7PMOc+zCM6DQbVehPzNeAhVz/lpOIwn4MKPgd9NbYtwjtDKZp+BRyblc+usHJHbMfcryYur43sR/zbHorn3mdyTEAyGFHYogV+zmFfkidySGwQ7IgjSjol4i5z97abW7WkmyQvqHgn6GtsW8JK19hFzKlqkXs5zQ2pdYl+DI9R1dWJJ9NlexrzlFPY4V+rvP3wNpzCc320nvnmRrTXyucJ0bshwj9G0/di7seuW71O5qe9fy57UHsU+iHs3T/FP9jQcF/pFVj94mPS0mdaeMr+qeOOVb45/Tsp7B2ry06v7nB9N2Mp3UHnav+jYQtotZ2QQb66ShTFhBrIHQANpE7fEfr825tR2pAoV9u9lVT5jgSBwU/2or90M9SG1zI4trHrz4ZLPpbZeJISRGosSP0uZ8lwx5SP0Lr0mgd45wSnVmpDjI1naZPuE6OdjHZkNJ2oabYn3v3pwW7FENuSg8QY+vqiDZtxHsieaDgb4TdOWxtTlUKn7R+PqK/tsgv2XmEeNVTPPCp91CrjrDzcDM9w7mATn02uQehW+k3S19HSfsQK/RzQbG/jW0nc9ru1Lo5om0rvbaKXv6+oeBvwFKD0dyIWubPtontLGLSD5b0/KduEFcjRdqInaEL33ILrX/zOuQ7QJyE0VYWFV/RnoLWGbCta6LY18NS6s+cGYVC2ZNtKwFFf79Q8KNuxhE2lHoe8dROYk2gtZiirr09+x7wWSy9RmhmlEsfNJsbHK0d1+fcuXENXGrje7+l67Gdc5/2PA7XgLVknd6DfdvDPZJ4KPgrUrtzWOuYW3jtUjduAdpk28nhJd0i1GOZKwxsrx2Ez4ZIQJxX3/69L6Xqca4wCu0ifyK0Pj9w9orNOP7YTbXIOjX7IG12zqfuaLtmG3r5+4SCvyI1Golvx1yqAy9txLWFF4R6YmNCJHJsba6589DMlmfbfp4+Yn9JgNdqMxoz6yxRO9OKS9CvQbHTD5psn4Z64xrgxrQD0hcU/JXhFtVjEOKRX9vMKBafwaOmjk4TS+WWMlsS6tVvNWjVEJazRi+ZVmir+0GTDQypNzmvu+au0UQ3FPxHWu8c2vsUmTbPu4sSawG26s30OTPrtKVU+fdS9220iP+eMq30bJ/3hjYbqLnu0LO/Hyj4LVqL/pzU7NBzLY4tcWyfc5Q+90Ss8LfrJb36fsx3BN4qN99N0CZ6FPkuQu8l1Z7knOWqgWaxRi5kFPs3r3OpIWtnTj+aVdizTfQJBf+M3kX/UmdaQvzXEuL251vnbJXjuUadyWFgfY/RS/33uZ/Y8Jw1RhL7MWi4f4p9YqPZZpW23T73vpRZKqbM2B76hoJ/gTUBFzrytr+vIX4/xwK+Vl53jXHHS6wZVPtZp2zctXXuGDR3mnNK5c5fQ4PQJX3VU1IW1gX//mbrs7WypNAfAwp+B74VPKQhaGo0rcWLVvEeWy6+m6lpDA3pqdOk0N83PdVVUgbWgYvJkaJZkz4hZaDgJwT1RJ0m8dhTxxnaGaXMZGl6RuRZeqqvJD+9Pv/SCTliyqXE7DLRDwV/RWIafqqR0zpqz7UhEAmjx04zpQ6zQ+ufVnU2dCH3HNa9dHq0V0vk8MCHnMt3Y0GyLyj4K9IiD+/SDq2+59E6WCBuRukgAdY/0qY++9Q7H2eFxvC9HhjJhi1hZw5L6X9HLyeSHwr+BGqO2nMRYiRq549vic8OuFuDp5qMauz3UNeIH1o31IqdmeQAYJlRbdkWvvu31L4G2uBxoeD3pHbMW0rqLO20DuVZeobza9I4mNNYF3yyUIUeh+ilRB3MVYdSz+1DTtsVcqyRBgca7dho+DjrXM+h901AiRsKfk+WDG6uqd+18+TcgGMPxHaMPr9rYQQ1Pm9XOcTsR7B0LIaZ6aRUXewlp35LR8XSuXsZBGi0YSOyZH8p3okNBb8SfI137QFAD8ail45viR47w7VOxMejZM9e1bx/Tl/vj1zPt/Ws5BKaM630aNd6J9Rj73LQ0CaOS3eCv7cKWtoYlwr9KVmmKRl6anRuvl6SkI3U2AGmh27E1kmWfR5a7EIeU2c09wcl8Fl/VAO2szTOnH406Pv27rm+aFqHRuqjSvCbEybKaGjYwbY1uYR/rTLT0EGVgh1fPlK3lCd5cT2PGg6HNfFf0m5p9O7PaeXtZxv0I1TME1KCJMEvIp8F4McAPBfAUwD+kTHmPcfPbgHwjQCeBvAtxpg7E681GI0LL2MIuQ/GRK/jM0M092SGhK+M0AH6eHJLZHDyOVaO8t1bna9BrlDDEjuc74mawn8EW1eSkiLfx7vvu/t7Llgf9JPq4f8+AN9tjHmHiHzJ8fXni8iLALwSwIsBfAqAu0XkWmPM04nniyZm1fooncoo95HKWoxj6O9GFfuhhIY72cTUy5SwEraDOtQM1ypND979JUqH+ezR1vmiUei7yKV5WB/6IFXwGwAfd/z7MgAPH/++CcCbjTHnAHxIRO4DcD2AdyWeLxmX53apwmpZ4a7hGnql98wiLQi9t9iyiG1fPgMMtpn65MjQpIlexX5p7/7Itm8EUp4Pn+3YpAr+fwLgThH5AQAfA+CvH9+/EsC7re+dPb6niq3Krb1DIm5ouPog16CabbUevawTSqEnsV8zbp92tT4xi3MJWWJT8IvI3QBOLXx0K4AvAvBtxpifF5GvBfATAG4AsGSBFi2oiNwM4GYAeM4nfrznZdcnp6HT1OGNuM6BkJEYqW73bGNa0yrRwUj1rwYPnL2Ci3SJSjYFvzHmBtdnIvLTAL71+PLnAPz48e+zAJ5vffU0ng33mR//dgC3A8DJF55W5VYpGQ6ioeNbSj8J9NMpsyNy45PRREP5+dY1TZm4SrQTDc+CPEtK6uDU82qBdTKeyStP4U80kRrS8zCAlwH4VQBfCOAPj+/fAeBnReSHcFi0ew2A9ySei2RkzZhrjodmJ+RHyPNtQa30jiXI0R56uM+9M4nvksJfk8AHWC9zY4fj+Ih/hu+QkqQK/m8C8MMicgmAJ3EMzTHG3CMibwHwQRzSdb6mZYYebdQS0LmMd8uwH3ZAY9HbfhE52Xtd7vGZAReK8hziX4vI33t9rE2omI9Jdatp9pboI0nwG2N+A8BLHJ/dBuC2lOOPQG/i3uc8Ne4p9X5c3hR6UOpQasOsXkXjnhnpmWkR62tQ7PVLysxni52wSV+o2ml3RNgAwwktM984SQ1if2QPTK2BYK8CcuRn76LXZ9ULe6pLo5O6eR3rAtmCgn8H5BQa2jrwXhZFLe3mC4xhpFMX3obS2+LyOaMv9u31uWhF4zMm+eAmjqQWXQr+lA5ljw1pa6fYtTLpKWZfgwffhWsdhPZpWM0LVEsdtyfBWuP59FQevaLZBpBy+PbDhORAleCX81K8c9EusFqgpUOPeS6aRb6LeVhKbQ95CD2H0BA/+HzLwv6GuBilbtCG9IEqwV8Lin597Ol5xBrHFG9Qqzrf03Nlp6WXnuoRIVu0CrMdMayX+LMrwc9Og421R2LEvet9toFlSrYLdrLhsJ6S0Vhqw7ZNDnXo5NzLJGTBMGd9+6Ubwc8OIAw2SL2UrMu5N7TaSz2K7cRqpsN1McIzon0nI7PWRl0DgYmUNXih1+Z7LM2bcxI3qgS/OWFo+CPpvcHFCNXRs52EkrM8ch2rp0Vp84XV2q93wvc6tdiIXsqVkFykeMVz7Gmy5sHP0R7ZpvtAleDXTG7P6dZxyQGK+mVCy0VDPespFWkP1xhKi2w8I5YjIb0Qa3N7ctQQfyj4N9jqBDUIqVr4bCvfw06UvTJKXWNnopOt2TQ+K0LCKWm3twR9jnj+nhw1ZJ1uBH+Oaa2c5xwVH1G/hHahr9VY7bGO2bAz6QM+H0L8qWnXc7ZN3+tO3RWYtKEbwb9GqPdp6/sji7BYQd8rGgzRyPWJEEJI3/j0UdwRuH+GEPxAWIz9ViVdSpM1Cto98bloZYhGrDM1YMgIIYSE07LPod3uC1WCP+dOuzlXnodMX1HwlUGbUeFzzg89SKRXzpx+NPq3Pe4WTtzsrW/Y2/32jCrBn0JJYRBy7NazA72l6JujWeBpLbORabF2hxAgTcTHnofiv1/YPxDtDCP4tU0tad6NTut1aYPlpBttbZ70TS2Bv3UNFP39MGIfMWriDjKQ4AfC0v3FNlTtAqN3A1RCxPVeJoSQA7lE+ZKont7TIPyJXkbvTyjcx2UowW9TqlGWOG7oiDqlQebK0lPSKIxuUEk+mB5uXzxw9orignzNw17i3PTo9wH7JdI7wwp+X1wCuKSgTRXdLVJrctRPesCnU+agoG98BLJLmKeKa4rzfUKxT0Zg94K/hZB94ipRmQ+fop7sgZAUvqRPKMwJIeRCdi/4W0FxTYgumBGIELLEvP3T4096hIKfEEI2CO3gOUAgZFx6T39N9gkFPyGEZGaro+eAYH+ELPhlSNIYhLZzDhBISSj4CSGkMjEdOwcJOimRucf3mBwYjEWONs5BA3GhSvCbE6ZIp8YGQAjpndx2jAOINDTk65+ugcKfTLBdj4OIfA+AmwB8FMBHAPwDY8zDInIjgDcAOAHgPIB/aoz5la3jqRL8pQhpABwcEEL2AHcqTkPDRl0U+oQMzfcbY74TAETkWwD8CwCvBvAYgC89iv/PAHAngCu3DrYLwe8LxT4hZEQo7MtB0U0IKYEx5n9bLz8WgDm+/9vW+/cAeK6InDTGnFs7nirBL+eFopsQQjKTy65y4EAIIfUQkdsAfB2AxwF8wcJXvgrAb2+JfQAQY/RsACUijwJ4sPV1ZORyHKZeSH5YtuVg2ZaDZVsGlms5WLblGK1srzLGqJzyEpFfwqG8a/NcAE9ar283xtw+vRCRuwGcWvjdrcaYt1nfuwXAc40x32W992IAdwB4uTHm/q0LUSX4R0NE3meMeWnr6xgRlm05WLblYNmWgeVaDpZtOVi2xBcRuQrA240xn3F8fRrArwD4emPMf/M5xscUvD5CCCGEEEJIICJyjfXyywDce3z/4wG8HcAtvmIfUBbDTwghhBBCCMEbROTTcUjL+SAOGXoA4LUAPg3Ad4rIdx7fe7kx5iNrB6PgL8vt218hkbBsy8GyLQfLtgws13KwbMvBsiVOjDFf5Xj/ewF8b+jxGMNPCCGEEELIwDCGnxBCCCGEkIGh4M+AiHyNiNwjIh8VkZda758Rkf8rIu8//vsx67OXiMjvich9IvKvRUTaXL1uXGV7/OyWY/n9gYi8wnqfZRuIiLxeRP7YqqtfYn22WM7EHxH54mP53Sci39H6enpHRB44tvH3i8j7ju/9ZRG5S0T+8Pj/J7S+zh4QkTeJyEdE5APWe86ypD3wx1G2tLWkCRT8efgAgK8E8OsLn91vjPms479XW+//OwA3A7jm+O+Ly19mlyyWrYi8CMArAbwYh7L7tyLynOPHLNs43mjV1V8ENsuZeHAsr38D4G8DeBGAv3ssV5LGFxzr6uQI+A4A7zTGXAPgncfXZJufxMU2crEsaQ+C+Uks9z+0taQ6FPwZMMb8vjHmD3y/LyKfDODjjDHvModFFD8N4MuLXWDHrJTtTQDebIw5Z4z5EID7AFzPss3OYjk3vqbeuB7AfcaYPzLGnAfwZhzKleTlJgA/dfz7p8B274Ux5tcB/I/Z266ypD0IwFG2Lli2pCgU/OV5oYj8toj8moh83vG9KwGctb5z9vge8edKAP/dej2VIcs2nteKyO8ep6GnKXxXORN/WIb5MQB+WUR+U0RuPr73ScaYDwPA8f/nNbu6/nGVJetyHmhrSXWYltMT3+2PZ3wYwAuMMX8qIi8B8AvHrZCXYsp3my4psmxdZciydbBWzjiEQX0PDmX1PQB+EMA3gOWZA5Zhfv6GMeZhEXkegLtE5N7WF7QTWJfToa0lTaDg98QYc0PEb84BOHf8+zdF5H4A1+Iwcj9tffU0gIdzXGePxJQtDmX4fOv1VIYsWwe+5Swi/wHAfz2+dJUz8YdlmBljzMPH/z8iIm/FIfThT0Tkk40xHz6G9q1uQkNWcZUl63Iixpg/mf6mrSU1YUhPQUTkimnRjYh8Kg4LSP/oOEX6hIh87jGDzNcBcHmyyTJ3AHiliJwUkRfiULbvYdnGcezUJ74Ch8XSgKOca19f57wXwDUi8kIROYHDwrw7Gl9Tt4jIx4rIpdPfAF6OQ329A8Crjl97FdjuU3CVJe1BIrS1pBX08GdARL4CwI8AuALA20Xk/caYVwD4WwD+pYg8BeBpAK82xkwLeL4ZhxX8fxHAO47/yAxX2Rpj7hGRtwD4IICnALzGGPP08Wcs23C+T0Q+C4cp5AcA/EMA2Chn4oEx5ikReS2AOwE8B8CbjDH3NL6snvkkAG89Ztu9BMDPGmN+SUTeC+AtIvKNAB4C8DUNr7EbROQ/Afh8AJeLyFkA3wXgDVgoS9qDMBxl+/m0taQF3GmXEEIIIYSQgWFIDyGEEEIIIQNDwU8IIYQQQsjAUPATQgghhBAyMBT8hBBCCCGEDAwFPyGEEEIIIQNDwU8IIYQQQsjAUPATQgghhBAyMBT8hBBCCCGEDMz/Bzuheft5pTjqAAAAAElFTkSuQmCC\n", + "image/png": 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\n", "text/plain": [ "<Figure size 1008x792 with 2 Axes>" ] @@ -318,13 +318,13 @@ }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "272d2099bfe849d6843863d674ef5491", + "model_id": "d6666a2b6a92443fbb4b3f1ba320b7d7", "version_major": 2, "version_minor": 0 }, @@ -422,123 +422,155 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "(1261, 2)\n" + "ename": "KeyError", + "evalue": "'u'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m<ipython-input-12-17bb67ead1c8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 38\u001b[0m \u001b[0;31m# longitudes and latitudes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mnc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvariables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mVAR\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 41\u001b[0m \u001b[0mval\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mDATE\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLEV\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'long_name'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: 'u'" ] } ], "source": [ - "# inspect polygons\n", - "clev = cs.allsegs[6]\n", - "# for i in range(len(clev)):\n", - "# print(f'\\n\\nPolygon no {i}:')\n", - "# print(clev[i])\n", - "print(clev[14].shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [], - "source": [ - "# transform data to range 0..1\n", - "vmin = val.min()\n", - "vmax = val.max()\n", - "sval = (val-vmin)/(vmax-vmin)\n", + "\"\"\"Plot ERA-5 model fields as contours on ipyleaflet maps\n", "\n", + "In this code version, the original ERA-5 grib files have been processed\n", + "an re-arranged so that there is one file per variable containing several \n", + "time steps (see era5_processing.md for details).\n", "\n", - "# create locations vector\n", - "# locations must contain triples of lat, lon, value\n", - "locations = []\n", - "\"\"\"\n", - "for j in range(50, 550):\n", - " for i in range(0, 1200):\n", - " locations.append([lat[j], lon[i], sval[j,i]])\n", + "The trick to overlay contours on ipyleaflet maps is to obtain the \n", + "polygon paths from matplotlib's contourf function and pass these\n", + "to ipyleaflet's Polygon method. A few hickups of this approach are \n", + "discussed in https://stackoverflow.com/questions/65634602/plotting-contours-with-ipyleaflet/65655648#65655648\n", + "\n", + "Author: Martin G. Schultz, JSC, Jan 2021\n", "\"\"\"\n", - "for j in range(50, 550, 3):\n", - " for i in range(0, 1200, 3):\n", - " locations.append([lat[j], lon[i], sval[j,i]])" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "583184daea28497084e69d2afcde408d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Map(center=[0.0, 0.0], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_out_t…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from ipyleaflet import Map, basemaps, Heatmap\n", "\n", + "import numpy as np\n", + "import netCDF4 as nc\n", + "import matplotlib.pyplot as plt\n", + "from ipyleaflet import Map, basemaps, Polygon\n", + "\n", + "# === user inputs ===\n", + "PATH_TO_NC = '/p/scratch/deepacf/schultz1/'\n", + "filename = PATH_TO_NC + f'era5_20200215-17_{VAR}.nc'\n", + "# specify date, variable and model level\n", + "DATE = 18 # use integer index for simplicity\n", + "VAR = 'u'\n", + "LEV = 132 # use index for simplicity\n", + "# === end user inputs ===\n", "\n", - "zoom = 2\n", - "center = [0., 0.]\n", + "# coordinate processing\n", + "# vertical levels (just for information):\n", + "# test vertical coordinates (print lev)\n", + "with nc.Dataset(filename) as f:\n", + " hyam = f.variables['hyam'][:]\n", + " hybm = f.variables['hybm'][:]\n", + "## for i in range(len(hyam)):\n", + "## print(f'{i:4d} : {hyam[i]+101300.*hybm[i]:.3f}') # pressure of model level in Pa\n", + "\t\n", + "# longitudes and latitudes\n", + "with nc.Dataset(filename) as f:\n", + " v = f.variables[VAR]\n", + " val = v[DATE, LEV, :, :]\n", + " name = getattr(v, 'long_name')\n", + " lon = f.variables['lon'][:]\n", + " lat = f.variables['lat'][:]\n", + "# convert lon coordinates to -180..180 and re-arrange data for clean contours\n", + "lon[lon > 180.] -= 360.\n", + "l180 = len(lon)//2+1 # index of 180 degrees longitude\n", + "lon = np.concatenate([lon[l180:], lon[:l180]])\n", + "# val = np.concatenate([val[:,l180:], val[:,:l180]])\n", + "val = np.hstack([val[:,l180:], val[:,:l180]])\n", + "## print(name, val.shape, val.min(), val.max(), val.mean())\n", + "## print('lon: ', lon[0:10], lon[-10:])\n", + "## print('lat: ', lat[0:10], lat[-10:])\n", + "\n", + "# create the contour path information\n", + "cs = plt.contourf(lat, lon, val.T)\n", + "plt.close() # make sure plot is not displayed in Jupyter notebook\n", + "\n", + "def split_contours(segs, kinds=None):\n", + " \"\"\"takes a list of polygons and vertex kinds and separates disconnected vertices into separate lists.\n", + " The input arrays can be derived from the allsegs and allkinds atributes of the result of a matplotlib\n", + " contour or contourf call. They correspond to the contours of one contour level.\n", + " \n", + " Example:\n", + " cs = plt.contourf(x, y, z)\n", + " allsegs = cs.allsegs\n", + " allkinds = cs.allkinds\n", + " for i, segs in enumerate(allsegs):\n", + " kinds = None if allkinds is None else allkinds[i]\n", + " new_segs = split_contours(segs, kinds)\n", + " # do something with new_segs\n", + " \n", + " More information:\n", + " https://matplotlib.org/3.3.3/_modules/matplotlib/contour.html#ClabelText\n", + " https://matplotlib.org/3.1.0/api/path_api.html#matplotlib.path.Path\n", + " \"\"\"\n", + " if kinds is None:\n", + " return segs # nothing to be done\n", + " # search for kind=79 as this marks the end of one polygon segment\n", + " # Notes: \n", + " # 1. we ignore the different polygon styles of matplotlib Path here and only\n", + " # look for polygon segments.\n", + " # 2. the Path documentation recommends to use iter_segments instead of direct\n", + " # access to vertices and node types. However, since the ipyleaflet Polygon expects\n", + " # a complete polygon and not individual segments, this cannot be used here\n", + " # (it may be helpful to clean polygons before passing them into ipyleaflet's Polygon,\n", + " # but so far I don't see a necessity to do so)\n", + " new_segs = []\n", + " for i, seg in enumerate(segs):\n", + " segkinds = kinds[i]\n", + " boundaries = [0] + list(np.nonzero(segkinds == 79)[0])\n", + " for b in range(len(boundaries)-1):\n", + " new_segs.append(seg[boundaries[b]+(1 if b>0 else 0):boundaries[b+1]])\n", + " return new_segs\n", + " \n", + "# set-up the map and overlay contours\n", + "zoom = 4\n", + "center = [50., 0.]\n", "# map = Map(basemap=basemaps.NASAGIBS.ViirsTrueColorCR, center=center, zoom=zoom) # loads current satellite image\n", "# map = Map(basemap=basemaps.NASAGIBS.ViirsEarthAtNight2012, center=center, zoom=zoom)\n", - "map = Map(basemap=basemaps.CartoDB.Positron, center=center, zoom=zoom)\n", - "# add heatmap\n", - "\n", - "# heatmap arguments:\n", - "# locations \t[] \tList of center locations\n", - "# min_opacity \t0.05 \tMinimum opacity the heat will start at\n", - "# max_zoom \t18 \tZoom level where max intensity is reached\n", - "# max \t1.0 \tMaximum point intensity\n", - "# radius \t25.0 \tRadius of each “point” of the heatmap\n", - "# blur \t15.0 \tAmount of blur\n", - "# gradient \t{0.4: ‘blue’, 0.6: ‘cyan’, 0.7: ‘lime’, 0.8: ‘yellow’, 1.0: ‘red’}\n", - "\n", - "heatmap = Heatmap(\n", - " locations=locations,\n", - " radius=3,\n", - " max=1,\n", - " max_zoom=3,\n", - " blur=0.\n", - ")\n", - "map.add_layer(heatmap);\n", + "map = Map(basemap=basemaps.Esri.WorldImagery, center=center, zoom=zoom)\n", + "# map = Map(basemap=basemaps.CartoDB.Positron, center=center, zoom=zoom)\n", "\n", - "map" + "# add contours as polygons\n", + "# hardwired colors for now: these correspons to the 8-level default of matplotlib with an added orange color\n", + "colors = [\"#48186a\", \"#424086\", \"#33638d\", \"#26828e\", \"#1fa088\", \"#3fbc73\", \"#84d44b\", \"#d8e219\", \"#fcae1e\"]\n", + "allsegs = cs.allsegs\n", + "allkinds = cs.allkinds\n", + "\n", + "nclevs = len(cs.allsegs)\n", + "for clev in range(nclevs):\n", + " kinds = None if allkinds is None else allkinds[clev]\n", + " segs = split_contours(allsegs[clev], kinds)\n", + " polygons = Polygon(\n", + " locations=[p.tolist() for p in segs],\n", + " # locations=segs[14].tolist(),\n", + " color=colors[min(clev, 4)],\n", + " weight=1,\n", + " opacity=0.8,\n", + " fill_color=colors[clev],\n", + " fill_opacity=0.2 + 0.6*clev/nclevs\n", + " )\n", + " map.add_layer(polygons);\n", + "map\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'geojsoncontour'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m<ipython-input-1-3cf6325828cf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mgeojsoncontour\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'geojsoncontour'" - ] - } - ], - "source": [ - "import geojsoncontour" - ] + "outputs": [], + "source": [] }, { "cell_type": "code", @@ -564,7 +596,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.8.5" } }, "nbformat": 4, -- GitLab