diff --git a/CHANGELOG.rst b/CHANGELOG.rst index a5c80fe..46bf5a7 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -2,6 +2,14 @@ Changelog ========= +Version 2.0.0 +============= + +- New interface reading ASCAT Level 1b and Level 2 data +- Removing old interfaces to TU Wien data +- Restructure package and harmonize interface class names +- Update documentation + Version 1.2.0 ============= diff --git a/LICENSE.txt b/LICENSE.txt index 9fcdb44..8a35162 100644 --- a/LICENSE.txt +++ b/LICENSE.txt @@ -1,6 +1,6 @@ The MIT License (MIT) -Copyright (c) 2020 TU Wien +Copyright (c) 2021 TU Wien Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.rst b/README.rst index 7fe9e80..9087eb1 100644 --- a/README.rst +++ b/README.rst @@ -17,20 +17,20 @@ ascat .. image:: https://readthedocs.org/projects/ascat/badge/?version=latest :target: http://ascat.readthedocs.org/ -Read and convert data acquired by ASCAT on-board the series of Metop satellites. Written in Python. +Read and convert data acquired by ASCAT on-board the series of Metop satellites. Works great in combination with `pytesmo `_. Citation ======== -.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.596434.svg - :target: https://doi.org/10.5281/zenodo.596434 +.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4610836.svg + :target: https://doi.org/10.5281/zenodo.4610836 If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version. -Please select your specific version at https://doi.org/10.5281/zenodo.596434 to get the DOI of that version. +Please select your specific version at https://doi.org/10.5281/zenodo.4610836 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility. @@ -39,9 +39,7 @@ You can find additional information regarding DOI versioning at http://help.zeno Installation ============ -The packages you have to install depend on the features you want to use. The ASCAT soil moisture products are disseminated in BUFR, NetCDF or GRIB format. In order to read them you will have to install the appropriate packages which will be explained shortly. Unfortunately neither BUFR nor GRIB readers work on Windows so if you need these formats then Linux or OS X are your only options. - -For installation we recommend `Miniconda `_. So please install it according to the official installation instructions. As soon as you have the ``conda`` command in your shell you can continue. +ASCAT data are distributed in BUFR, NetCDF, EPS Native and GRIB format. Unfortunately neither BUFR nor GRIB readers work on Windows so if you need these formats then Linux or OS X are your only options. The following script will download and install all the needed packages. @@ -58,7 +56,7 @@ Windows: conda env create -f environment_win.yml -Supported Products +Supported datasets ================== This gives a short overview over the supported products. Please see the documentation for detailed examples of how to work with a product. @@ -78,12 +76,7 @@ Read ASCAT data from different sources into a common format supported by pytesmo Contribute ========== -We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes. - -Development setup ------------------ - -For Development we also recommend a ``conda`` environment. You can create one including test dependencies and debugger by running ``conda env create -f environment.yml``. +We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests for new features or bug fixes. Guidelines ---------- @@ -94,8 +87,8 @@ If you want to contribute please follow these steps: - Clone the repository, make sure you use ``git clone --recursive`` to also get the test data repository. - Make a new feature branch from the ascat master branch - Add your feature -- Please include tests for your contributions in one of the test directories. We use py.test so a simple function called test_my_feature is enough -- Submit a pull request to our master branch +- Please include tests for your contributions in one of the test directories +- Submit a pull request Note ==== diff --git a/docs/changes.rst b/docs/changes.rst deleted file mode 100644 index 257630a..0000000 --- a/docs/changes.rst +++ /dev/null @@ -1,2 +0,0 @@ -.. _changes: -.. include:: ../CHANGES.rst diff --git a/docs/environment.yml b/docs/environment.yml deleted file mode 100644 index 70e0700..0000000 --- a/docs/environment.yml +++ /dev/null @@ -1,14 +0,0 @@ -#this file is not used at the moment -name: ascat-docs -channels: - - conda-forge -dependencies: -- pybufr-ecmwf=0.82 -- netcdf4 -- numpy -- sphinx=1.6.6 -- pykdtree -- pandas -- pyproj -- python=3.6 -- ipython diff --git a/docs/read_cgls_swi_ts.ipynb b/docs/read_cgls_swi_ts.ipynb index 0e39607..c3250d3 100644 --- a/docs/read_cgls_swi_ts.ipynb +++ b/docs/read_cgls_swi_ts.ipynb @@ -9,10 +9,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": true - }, + "execution_count": 1, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -30,14 +28,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\u001b[0m\u001b[01;32mc_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc\u001b[0m*\r\n", + "c_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc\r\n", "c_gls_SWI-TS_201612310000_C0375_ASCAT_V3.0.1.nc\r\n" ] } @@ -46,166 +44,50 @@ "ls ../tests/ascat_test_data/cglops/swi_ts" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we can initialize the data reader" - ] - }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": true - }, + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ "data_path = os.path.join('..', 'tests', 'ascat_test_data', 'cglops', 'swi_ts')\n", "rd = SWI_TS(data_path)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "With this object we can read the data" - ] - }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " SSF SWI_001 SWI_005 SWI_010 SWI_015 SWI_020 \\\n", - "2007-05-10 12:00:00 1.0 70.0 71.0 71.0 71.0 71.0 \n", - "2007-05-14 12:00:00 1.0 71.5 71.5 71.5 71.5 71.5 \n", - "2007-05-15 12:00:00 1.0 82.0 78.0 77.0 76.5 76.5 \n", - "2007-05-16 12:00:00 1.0 82.5 79.0 78.0 77.5 77.0 \n", - "2007-05-17 12:00:00 1.0 77.5 77.5 77.0 76.5 76.5 \n", - "2007-05-18 12:00:00 1.0 75.0 76.5 76.0 76.0 76.0 \n", - "2007-05-19 12:00:00 1.0 75.5 76.0 76.0 76.0 76.0 \n", - "2007-05-20 12:00:00 1.0 86.0 81.0 79.5 79.5 79.0 \n", - "2007-05-21 12:00:00 1.0 84.5 81.0 80.0 79.5 79.5 \n", - "2007-05-22 12:00:00 1.0 81.5 80.5 80.0 79.5 79.0 \n", - "2007-05-23 12:00:00 1.0 81.5 80.5 80.0 79.5 79.5 \n", - "2007-05-24 12:00:00 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83.5 \n", - "2016-09-23 12:00:00 82.5 83.0 83.5 \n", - "2016-09-24 12:00:00 82.0 83.0 83.5 \n", - "2016-09-25 12:00:00 81.5 82.5 83.0 \n", - "2016-09-26 12:00:00 81.5 82.5 83.0 \n", - "2016-09-27 12:00:00 81.5 82.5 83.0 \n", - "2016-09-28 12:00:00 81.5 82.5 83.0 \n", - "2016-09-29 12:00:00 82.0 83.0 83.5 \n", - "2016-09-30 12:00:00 82.0 83.0 83.5 \n", - "2016-10-01 12:00:00 82.5 83.0 83.5 \n", - "2016-10-02 12:00:00 82.5 83.0 83.5 \n", - "2016-10-03 12:00:00 82.0 82.5 83.0 \n", - "2016-10-04 12:00:00 81.5 82.5 83.0 \n", - "2016-10-05 12:00:00 80.5 81.5 82.5 \n", - "2016-10-06 12:00:00 80.0 81.5 82.0 \n", - "2016-10-07 12:00:00 79.5 81.0 82.0 \n", - "2016-10-08 12:00:00 79.5 81.0 82.0 \n", - "2016-10-09 12:00:00 79.0 80.5 81.5 \n", - "2016-10-10 12:00:00 79.0 80.5 81.5 \n", - "2016-10-11 12:00:00 78.0 80.0 81.0 \n", - "2016-10-12 12:00:00 77.5 79.5 81.0 \n", - "2016-10-13 12:00:00 77.0 79.0 80.5 \n", - "2016-10-14 12:00:00 76.5 78.5 80.0 \n", - "2016-10-15 12:00:00 75.5 78.0 80.0 \n", - "2016-10-16 12:00:00 75.5 78.0 79.5 \n", - "2016-10-26 12:00:00 74.5 77.0 79.0 \n", - "2016-10-28 12:00:00 74.0 76.5 79.0 \n", + " SWI_060 SWI_100 SSF \n", + "2007-05-10 12:00:00 NaN NaN 1.0 \n", + "2007-05-14 12:00:00 71.5 NaN 1.0 \n", + "2007-05-15 12:00:00 76.0 76.0 1.0 \n", + "2007-05-16 12:00:00 77.0 76.5 1.0 \n", + "2007-05-17 12:00:00 76.0 76.0 1.0 \n", + "... ... ... ... \n", + "2016-10-14 12:00:00 78.5 80.0 1.0 \n", + "2016-10-15 12:00:00 78.0 80.0 1.0 \n", + "2016-10-16 12:00:00 78.0 79.5 1.0 \n", + "2016-10-26 12:00:00 77.0 79.0 1.0 \n", + "2016-10-28 12:00:00 76.5 79.0 1.0 \n", "\n", "[1603 rows x 9 columns]\n" ] @@ -225,17 +107,19 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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XAQDKG5YAAFoZD50vbnNHYzjTFZwIDywAkLC9bksYDB9uqk91SE5hOJS/fa2d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0LAbJ+j7dkHjWDVzrpes86PJRzZZ9cbF2VDuV0rv694OiFb+q9NOy1lnTwRZb6WaiaiMn9dO3G+\n6oiJxE3JrS91b9+6plr1vPYVtE7+tlerOvShRR1rWxBMq1vbKTOPOXnvsxlOlKqmsv3n9wuLx7Jg\nbCk/fOwTtuzrHTfnYMK24wi2XlPZVRhaHMKna+7cwuuNoGSfmYYvKvPXy5TDMuH9e+B3c+D5H8CI\n+aqm7+RboTh327i+BCcwUos9d+zgnGLAkz+3VUOL/ZNSMX14EYvGl7mvDV2jSQtDrB7LHjQK7R5/\nel7SIvqgcap/jC5U5m92cYzx8TU880mfT5DmRvUWABpDqeSvpdqObx83mZnDi5g3OjWC4taetVAL\nCFBvBUFaPPbuev6cRZbSUtbMxTE/hyGzlI57f8ekLYVBH6fOGcZ/P9zRpbr+hCUpsovPCWTWTLXk\n9ul9GQ60TWfuyOhaerY1S7/btHsgwXH71PWu1+QHDU+Ge9BYhqAI341PrSZMhGpZAP48DF2wKqIe\nzOtXf0RTLMGnO7P6Z/V9SAlv/okDXvs6O2QZFVNyu/52FNkmFJAp+8xmOpV+ifd65s8L3YC5F6t6\nwMVXwyf/UXKjF2+AaCtOsNLqFvLnHV8OmaAs8FsKVXrXF8JuQQDUTr+EAhFhzPZH2nX8ZTOH4Te0\nXsv+xRImuoz3WObPubb3xBW5adCLOHBaZvbckZA7kF1q96MwuizMmXOHc+9bW9le3X09SKN1qoQj\nUFDWyprKaXve6BLOOSh7T+HWEEgzfKkl1Q3+U8ue4K95qkP7T4emCW4+cya6Jrjqvg/cYGNPoiBh\nB8Pzs/cv7E44Ki+vt4UQEJdGBsG2ejPzJ6X6zW9bBP+9HAqHwEVPwLn3w+CprW/fh+A8B2ulPf/t\nYKP3AU/+OpL5S4euCZo0VVul2XbtpUJN3nwe8mcJdSMEiTF89Z2c+OqJPBr4Phsf+SnNsX7a8qFG\nOZpG84envN2SLGNyZSGPXr44w2XPIX/pmb7013WWbZ/bmP2izqNZTYRaaPKML6jseYWA+y5w7XDb\niwsXjCaWsPj3O13X9sGyZLJHZJYBO8XwpYUm73n+tmU1nPPekiSrmQBaYmA1IYdku5fukX0m+1Pi\nz3cj+QD5IkIj6vrUhGCVHAXAPQ89zEl/eJ1jf/tqjzda7jSa9sO/zoGnv8XL5nQeX/Bvioq7voee\nzyP7PHNeMhqbKjkUhLO4eKZf4oVtyA72OIKFcMQP4Ip3Vd3y/34Jv58D79+tItPZIK3uUH2mTMby\nnWBSC49K7/qaEG6tT6RiJu9aExm/7q/t6mdZlOfj2GmVPPLBZ71yP5Qk9qAhVb14D8AJxK3Yrcal\nqsCYrNLbYhoQJImE7Grdp40rPjcBgN+9sK7rd24j0aCCYqHi1lsJjBiUxwNfXkhpC27iLSGQlvmr\nk6nk71eJM9U/H92X8r4y1OkYhhaH+Okp03l/aw23vty9WdRsyHMyf70gV3T8HbzeFroQxHNm/nqB\n/G17W0nt/3W2Khc68274wguqRVg/hDNc1DuBjeZuMHxxIITIKCoSQlzYvkP1DobZBe2Dwh2XdehC\nuKYOvmg1m4Of5x7/Tep1cbIWzhRqMvIj4y7Gvn8jYuR89o08lq8k7mHtX7+U+8Hel1GjMn+Jws6n\nxB2paHqNX3oz+BrLHvjtur905NGsjFJak2mUjILT7oCqlfDENR1qhjlhcAELx5Xyj+VbuiyqZ0pJ\nOTaxDWc2nNU9ZNifdq68BC7cRvLXmoXzfV+cTx0h9PjA6kMH3Vvzl5L58+cTJMbm4OcpoY4CIjTa\ng7OuCbbLciLSz498d1G8512gcwGpHseWN+BPi5Hrn+eO8Bf5TuDbnPe52d1yKGd8SFgW3zp6Mh/+\n4CjW3nBsRquHbEh3RCzsLcOXtqB4JJx+p5qIlIyG/14Bty+BDS9lrttNmT/vOc23z1VLss/0zJ9T\nBmFacGP8HELNVUpu3w6cNXcE9c2JbnFWbg1LLbs2d3JmQ/vugBMwqrMlW81GfkYJRb0MYQiLbxv3\nprzfHdPmocUhzp0/kofe/4yNe7pn/DcbVGbK34bMX2eRnllqSMv8bZJD2FIwR0mv09AZVe1JM4ey\nbNZQfvvCOj7Y1rPSfte9tIey114MLlQBzgpP6YmuCaL4M9yNTUu2WC7U5di7TtVY33kk7FsPx/8a\nvvoWTFnWte5JPQxnzLawFYlOzV87C1fb+jT5vhDiNiFEWAgxWAjxGHBiu47US7hgwWj+8PnZnDZn\neOsr54CuCXb51PZFdak1aMGSIe7/0iZ/k7Wt1JfOhHMfoPSie3mu5Cxm7HqQyD/OgVj/yq5Y1Vuo\nkyGCbdDrt7ove1KRbouraSJlkralQV2W0iZ/M8V6rjf+iROSVuSvBcmnFxOOhCXfgA/+qSLrHcCF\nC0ezo7aZ5z/tmp4+CVNSLmqI+orByAxKeDN/6ZFM7+Qr3dY6F5zJ9MhBeVmX5/kN6mQYXzw72e7P\ncDN/3eH26bR6iFsp1+N7gcuYKLbTQMg+tgAE18e/AOA2du4Xzx/LhFd+ofoeGQFeO/Rf3LBvKdce\nPbnNmef2wm31kJBomqrt8xtai0ZIDvpF5i8dw+fCxc/AGX9XAa97ToZ/ngl7PM+aWAP4M9vCdCWc\nTGpLU4h0Au6sa1qS9+Qkdow8EV7/Xbt6Ws4fW8qIQaFekX4WSnvMGzS2R47nBPM2WipoXJCoTjFP\nuyz2Nf6YWAbApcaT7vtSym5rjv2VpeMJGBq/eb57sn/S6XMZ6v7MVPo5stA4L3a9+7pRBtlaMFuR\nAc9crCvCcD9eNo3BBQGuuu8DmnpQ6aVJO6nQQ4YvXiwYV8qfzpvDtUcnXZ81TRCVPkjzEEhYss2t\nYDqF+l3w2NfgjwerQNph31FS+3mX9JgjanfC+xyM6AXdm/kDDgU2AB8ArwH3SilPb9+hege6Jjhh\nxtBO9fnb1xjlmV1K9lle97H7/n2JpeQXJkmRZfcDCRPB9IXVTETTmHLhb/mJdRGBjc/CXSdC494O\nf5aeRmLfZrbLCorzOl8QX54f4KKFo7nnkoMylh00JvlgaHCkGjb5u93/G75kPMFguwdSEQ3tk+ks\nvQ7GHgZPfgN2rGj35z58cgXDikNd1vbBkpIyUUdzMHsk1Evw0rN23rGzrU1ZnXrXheOyE3ifIagj\nDyNeP2DcKB1Y3Sj7dOSJj3+0A+khf5qQjNaqiNnuv85v9pi1AEsKztVf4FTtfx1JRPcs6nbC3cvg\npZ/CtNOJXvIS33nLYHJlAacd2PFgWmvI1erBe7231VWy11o9tBdCwNRTVJP4I38CW5fDrQuUYqFx\nLzTXdrs0Md8m8201KBMkA3rO33UzvqEmoc9+t83H1TTBWXNH8ObG/T1qmmFZEiETWPRMfzRI1rd/\nasvAi2O7MHTBxbFr+UX8LJ6yDsbMMi3ryibv6SgvCPB/i0bz2Ic7WLWj62uRtWa7d2EvyBLDfp3X\nrOnu6yaCVOWNB2nx5luvuWOMlHZmdfu7sCczK9gWFIV83HzmLDbva+SGJz5tfYMugrCcPn+9Q2yO\nmTbEDYSCbZCIDxKpHgKmZXWv7LO5Fl74CfxuNqz4J8z7gmrbcOg3IdB6S6z+Ai+BbhT5nsxf+9DW\nGVEJcBCKAEaBUaK7wlB9EM1xi1U1BlLoDN+jXO4ujV3NtxJfdJ0tIZn58wsT6WkaO6w4RPGhl3NZ\n7OuYuz6209A9rw3vEGq2sl2WURLu/MAihOCHJ03lgCGZJifeQm0nYyKb1YOoWSriOUZTxjnD5K72\nFTdrOpx2p5JY3n+Bql1qBwxd47z5o1i+cZ9ycuwkTEtl/mI5yJ/RAvnryODZGFUPh1wEXheCBhlC\nIFWGYQDBIX/dMXNyfotPdtTxxo5M0jyT9UCSxJjo1BDmAG0rv/b/CasdtVE9jnXPwZ8Ww2fvwbI/\nwql/5h8rqtm6v4nrjp3crQ9xXw7yF/Z7JxjZj5/OW/qU4UtbYARg0ZUqUj33Ynj3b2oys2tlt5O/\ntmT+vBAieb4dCXMiXAlLroXVj8OGF9t87NMPHIEm4P53ey77F7csdKRbq9+T2CiVYuiNirMxNMGL\n1hxuNVXGz0tWHLjkpJvwxUPGURA0+PVzme7anYUvWk0cX9aett2JYcWhjHrKJgJs848H4JGnn+H3\nnlrHkFkPd50Efz4U1jzdoWMuGFfKFw8Zy71vbeX5VVUd//DtQDLz1/PXcTboQtCcLfNndlPNXyIK\nb94Gv50Fr/5KtQC7/G047heQn1lW09/hPYX1Ir/b3T7fBJ6WUh4DzAOGAq936Ij9FoImfxmlkc0A\n7JHKvc9bv2aJJBG09FT99aVLxrKqeAlXB3+CjNQoArj93e7/2P+PvfMOj6pK//jn3JlJJoUkEEJo\noXekSVFQQAEREQs27JW1u66uuura96e4lrWuumtbdXVVbNhQQEURCwIqSu+9QxJImXbP749z72Qm\nmSQzkyk3YT7PkydkcjP3cHNz7nnP932/b0OQElvpJjbHSPmri4yA4K/UDP6MHQ3NKHzPpJJcDtJN\nboT0CFOgsvLhrFeUmvH+lRErXFOGFpFm12Ki/vl0VfPncoaemBwBAV9dNX/hUmY4cVU34PG/pyao\nwLhfm1i7B7PJe7zrpZ76rWaQkSnUzqfLU3WvrZYBipkVgz+vW6k2r5+hNlgunwuDzqekwsuTX6zm\n6G4tGd0jvg/Uwhx1L/ZsHfw3HrjRFq6Q2yjSPkOR1RJOfASu/h46DAdXiWocH0eqav7CO17ThF8l\nNPvfapqA4ddA884w89Yajn+10TrXyegeBbyzaEvCHBPdXh0NHRmHuaE+vNjpVPkG3xeeWyNAWS47\n8r7vKDbpVX9nkvilfYIy3rlydFfmLN/F4k37Y/reae5iymw5Cc1zT7NpzL91jH99tkxXSqsPG08s\ndnNQOukpNrPZaC0hkRxRMhM8ZZDTDt48B356Iapz3zi+B73b5PCXd5ew+0D8HbSFNJU/a2Q5aJrA\nhQNZQ/mLcc2frsOS6fD0UPjsVmjdTz2vzngpYWncySAwi/FgoPIXp7TPcVLKl9QJZIWU8o/ArZGd\nqvHzf9m3+/9937nH8vYVw4N2MvSAnRdZLfhzOmzccWIfZuxtz/uDXlbBy38mwYpPsSzle7F5K9gi\nW5IX50WU2TMNYJtsia6lUVi5AVCtMwCyqKRQGA+maJya2g+BCdNg9efw7aMR/WiLrDROGdCW9xZv\npaQivAVNbfikcvt0O0OnYQYGfA57w4M/s/6gttYQmhBUYgT3nsZVk1offuUvrvvmUJxRFdSNdCnD\ni0qp/mZ8AbPyje6r/AsRabXgb996eHkCfPcUDLkM/vAFFKhajn/OXUNppYfbJvaK6yIUlMnS+1eP\n4LYTege9nhawcKhV+aumWzU65a86BT2VHfnlX6valTjS2jBviCztk6CfsQmh1MsJ02DPSljwfNjn\nnzK0iJ2lLr5etTuicUeLxyexoSOToPyZCCFC2t/vkbl00HbDQVVnHm/lD+DiEZ1omZ3Go7Niq/5l\neEuosNfM9okXX/55NPNvHQNUzRlnu+9ggutB4wjBQTJw4vbft5r0MXL/e9BhhAoguo9XKdez7ox4\nozjdbuOJswdywOXl1neXxL3Ps1/5s0g9myZU8Bey5i9W5RdrvoB/j4L3pir35PPfgwtnQNv4mJBZ\nicBn30GRrebZiuK4Gb5sFkKcL4S4C0AI0QFoWhJBHZhpimsdVUWt/fr0DqpTg6q0TwA9hPPS+D6F\njOzeknu+c7Hv7E+gVW9467yIHpAJxXD63Cxb0TyE8vfwGf2ZfuXwmJzKVP4cNoEPGxXZ7WnhVWme\nTpRrVKZwkYOxYC7oGfJ96mXoVOh3Jnx5f0RpSaCMXyo8Pt5ZFGZj5lrw+XxkCDe6I7R6mV6n8hf5\n+cpc6uFQm0GHJqpSa/E0rT/rqrTP+O7uazYHT2dfx1muO9ksC7nPcwGnee5T3wyYk7dSwJPeyeqL\n+nq7JZLf31NOk3vWKCvsSf8Ah1LgN+8r5z/zN3DaoPb0bZsYS/xBHZrXSHletQbeWgMAACAASURB\nVLPqeoW7CWKZJu8Npe3AuKUw3TWpD387pa9fJQl3raoMX6rcPiEgLb3HBOg2DuZOg4PhBXNjehWS\nn5WWMOMXU/mL99xQF5oQIdWQLdL4XRumP/Gs+TPJSrdz1THdmL9mL9+tiZ0vQZZeijstcQ3IuxRk\nU2C4T5qqailZrJBVvQO92HAIn39qHuFbSL5nBxx5paoPm/K62gD77kl499KIn4s9Cptx2wm9+GLF\nLt5YELs2UaGwmvJn0wTuEGmfvlj0+dv2s6pD/+9pqsbvtOfh8m+g29hG4qDWcAKXhGvtXdU/tiyM\nm/L3DDAcOMf4+gDwz8hO1Xg5I8Dc4FnvSczxDUIE7LIM7dScc4/oEJT2WV35A7XLd/dJfSh3+3h4\n/n64+GO1w/TpTTD7buuZbRgN3rfIgpDB35lDimo0co8Ws2DYtM93pReQ41UqX5axz5BJJTnCUKai\nrX8RAk56Agp6wbtToST8QO6wdrkM7tic177f4Lc4jwbdayiHtUzWganE1YO/aNImrj22GzZN0KMw\ndM2FJgQVTV35i/ODwWHX+Cz9eLJ7jmZc71a85DuhSuGrdmy5mWJrBedfdzl8+Ed45xK1oXLlPGWF\nHcAjs1YiBNx0fI8kDVIxpZaef4E0+pq/JHDp0Z25YHgnf6BcXOGu5ycUQlQpf2bNnz8oFwKOn6bm\nky/vC+v90uwapw9uz5crdiUkXc7j05Ou/GmCILdPk6XG3GH2SlP3dfwXt+cd0YE2uU4enrUyJopV\npcdHnjyAJz3xZi9Qs4ewiUfasOP1zxcDfUtxCSf0NFp+2Oxw4qNw3H2w9H3lwBuhV8BFwzsxsntL\n/vbxMtbGqY0GBCh/SdzECEQTQj3jqrXq8jbE8GXfenjnMvj3MbB9CUx4EK5dCP3PCr8GoIkQuPH5\nTdpI9Y/dkRsMhXvVjpBSXoOh9kkp9wPxLQKzEIFKzN+95zDVc3PQ96dfOYIHJvdDanUHfwDdWjXj\n4hGdePOnTfy2y6t2mAZfAvMfh/cvr+GQlFSMBu/baBl31zwz+DPzmSvT88nV9wESp1APwGwqyBeG\nG5mzATuJaVkw5TV1rd++qEY/mrq4aEQnNuwt5+vV0acm+Xxqp07YQl/TIFfDapNlNGkT4/oUsvaB\niTSrthDu1irbf46qtM+KiN/fyviD9Dg/GNNtGlKqxdyjZw4M+l71RdRBqRQ1XLF31ouIXcvh+TGw\n+BU4+ga4ZKbqjRnAki3FzPhlG1NHdqZNbkaSBqo4rF3Vhk+4qafZjcXt0wKY88HgDs3DOl4ENHk3\n3T6DFncFPeCIK2Hxa7B1cVjvedaQIry65L3FDcuuCAeX1wj+kmiU8d3avSHVEA/GfeuvmZQJETac\nDht/HNudnzcV8+WKhrc2KqnwkCcOIJ3h3VOxpnpPYRMfNuxUKX/puHBpmSroMxECjroeznhZ3b8v\nHgf71oV9bk0TPHLmAJwOGze89UsNA6tYoek+vNgto3zZNOWJIdwHgzY4db1mH8Z6KdsDn96i6vpW\nfAIjb4Lrf4Ejr0pKX0MrELhZVEy2qs3ftSLizZpwV0QeIYQNYxNbCFEAWEymih/mYry+nNpA1zBp\nc9Z63B/HdSc/K427P/xdPXgmPQZj74LfpsN/T/cXcCad4o2U23KwZeQ2qFVGOARaBQP8sMtGa+82\nfky/xv9aviilh9iiGojmdaz+FpHRsrtyMdy6MCJb8gl9W1PQLJ1XG2D8In1GsFmL8ldXC4cGp00E\nMOOao1hw+1g0ARXSNHxpasGfsSsa511zmybQpVoQ26rtNlcXifei0shFeWJqm2ogJSx6Bf59LJTv\nUfUS4+6pUTMipeT+T5aTn5XGlaO7JmWokVJ9hs5wWMMBrzGQbrfx3a1jePD0/mEdr4mqjY0q5a/a\nQaP/olyWZ/4lrMyWbq2yGdyxOW/9tDnutVIen5n2mbx7ZNeBypDZHN5qwV8iav5Mzhjcno75mTwy\na1WDMlwASsrd5FGWlDYPUHvw58GGHd1/j6VJD16tFj3jsNNUPVn5XnghMqO+whwnD0zux5ItJUHO\norFEw4svifdwdTQh2I2xUbf2C//rESl/roOqv+wTA5XxzqDzlAPy2Dvj7npsdQL3/70+qbLYdi2L\n/H3CPO5J4H2glRDiflSvvwciPlsjpXqj7drQRdXkIevYlchxOrhlQi8Wbyrmg1+2qh2bkX+Gyf+G\nTT/AyydElI4YN4o3scdeGDLlM9aYizTT6W11meqbViiqAuECUUwLcYB9Ijd4hy5a+p4Kw6+FBf+C\n394J60fS7BrnHdGBuat2s2FPdIYdusdU/kKnpNUV/NX2MIuGrHQ7rXKc2IRQATU0QeUvMTV/upRI\nKY00rrofcKZTsDjY8J31iKksgXcuhY/+CB2OgCvnq3qJEHyxfBc/rt/H9eO611CNrcK7V43gjalH\n+L+uHjCEO3enULTNy6ixEQfw3tUj+O9lRwS9JhB+xS/I7TMQZw6Muxu2LIDf3g5rDFOGFLFuTxkL\nN8bWdbI6bq+OHV9SLfKz0+0h0z49Zu/BgLTPRAk7DpvGDeN6sHx7KZ/8tr1B73WgZB8O4cOeHdrc\nLN7UlvbpxUj7NL5Ow4NX1LHO6TgcLpuj6gH/MwmWfxz2GCb2a8Pph7fn6a/WsGhjZKmj4aBJX0J7\nVdaHJgQ/6IZZ1/4N/tfDqvnzeeCnF1V7m6/uhy6j4eofVKlOTpv4DboRERhA+3SpvEN2r0RGWDYW\n1pNRSvk6cAswDdgOnCqlnB7RmRox5gJC1LP35g1I9awt7dPkjMPbM6B9LtM+XcFBow8bA6bA+e+o\nwO+F41Rvp2SyfyM7tEJyM+O/8DPdPvOz1XXz7xwF0FKUMkyswEUM5f5x9ygr9Q+vU2lwYXDusA7Y\nhODV7zdGdUpdr7vmr3qdXyDx6JMjgmr+mpbhiy9BNX9SqgBQIGqYkdSs+XPikTZEQH+eeKscgOrZ\n969RsGyGyjQ4/31oFrpfptenM23mcrq0zOKcYR1CHmMFBndszohuoftlAjVs9FNEx+EdmnN09+Dr\nrAX0+TMVIluov7MB50Lbw1Vdu6v+Pqkn9m9DVpot7sYvHp+OJpKr/Lm9ekjlr3rap0TWu/6IJScN\naEuPwmwem72qQa03yotVdoOjWe1/o/Gktr9/L3Yc+PyTcxpuPLUpfyYtu8HUL6CwL7x1vuotFyb3\nnNyHtnkZ3PDWr1XrvRihSWspfzZNsFm2UmVQAXWSyu2zjmLtZTPgmSPhkxshvytcNhvOfl2lj6fw\nExhAe3VD+fOUke3aEdH71PlkFEK0MD+AXcD/gDeAncZrhwTmzpynnsjaqwUEf/XkI2uaani+64CL\np79cU/WNLseo2htQCuC6uVGMOAZICSWbazV7iTWm8ieRnDOsA670ms52R2grKNJ200nGUBW1OVRO\nf1oWvHVBWIuTVjlOJvZrw/RFm/0N1CNBmjV/9lqUvzoWrLXtZDaEYLdPC5iQxJBEGb74pFQ1f1pN\n5U8PEdh5sINede/ENfbTddW+4cXxoPvU/DLyz3UWyr/502bW7i7jLyf0iqnanKLpIISoYfgScnGn\naTDxYTi4A755pN73zUq3c9KAtnyyZDsHKhvWVqcu3IbhS6KVv475mf5/u7x6LTV/xph8iVf+QP0e\n/zy+J+v2lPHez1ujfh9XqQr+0nOS02y7tmepF82o+TPTPt11K38mWS3hoo+g14mqt9xnt6k5tR6a\nOR08NmUgW/aXc99HSyP6P9SHJr34rKT8aQIQSGceVFQFf77agr8N8+GFcfD2hWpD/Jw31TOqaFji\nBt2ICNxc9uq6Uv6AFmXh16NC/crfImCh8Xk3sApYbfx7UURnasSYNTwV7rr/yHVRtZivT/kDZWd+\nxuD2vPjtOtYFukG1PgymzoHc9qoG8Nc3oxt4Qzi4E7yVrPe2JC8hyp/h8ulRD8NQyl/cyGmjAsB9\na2HGtWGtxC8a0ZEDlV7ej+LBqBsGM6IW5a+u+sp4KBk2LUD5a2JN3mWC+vzpUirlT4iav78Qt5MH\nG/jCNxqKmrI98L8pqq61xwS44huV7lkHB11eHp+ziqGdmjO+T2hl0KokQD9NYSBEVR28ucFRawuO\n9kNg4Hnw/T9h79p63/usoUVUeHx8vKRhaYd14fYmJ/ibdcMofrx9rH8MoeZ0rwxO++xc9gsfuy6F\n+U8GmMDEl/F9ChnQPpcn5qzG5a0/wAmF96BqGZGZl5zgr9a0T2nHLnz+R71K+wxznZOWqdrhHHk1\n/PCMClrCcG4e2qkFVx/TjbcXbuGz32N3X2tSD/KbSDbm4093tqih/AWlOO9cCq+fBf+ZCKXb4OSn\nVRlCzxMsY15jRQKv4eZ9FfR/Rhkz5pevqe1HQlLnSlJK2VlK2QWYA5wkpWwppcwHJgGzIhyzHyFE\nnhDiHSHECiHEciHEcENhnC2EWG18To49VAgcxsWu9NQT/EWQ9mnylwm9cNpt/O3jagWbue3U7keH\n4fD+FTDv0TjLA9UwnD7XuFuQlxF/5S9wR8imCdbrCV50dh4JY++GZR+Elc5xeIfmHNYuh1e/3xBx\nyp7U63b7BPj4uqOZef3IGq874pb2adyvTVb5i3PNn24ofyEeWqGMotzYgxZxcfnLXj8PnjtaZQ9M\nfASm/Dcs44V/fb2WPQfd3D6xd9wbuqdovIiAtM8aff5CMfZusDvh89vrfe9BRXl0b5XNm3FM/fT4\nZFIMX9LtNnIzVKBR6fWFVP6qG74UuDaSTzHMvlPZ3W/+Ke7jFEKpf1uLK3hzQXS/B1+ZWvxn5iYn\n+Ktts1QTOkdoK8j2qPGl4a7d8CXkG9hgwjTVcmDFJ/DKSWH1s7x+XHf6tcvl1vd+Y2dpbDZaVdqn\ndVyNzdRvn7M5VFTV7fqVv+LN8MHV8OxRyuNi3D3wx8Vw+AWx8XJo4lRP2CkliwpnYcyVP5MjpZSf\nml9IKWcCIyI6UzBPAJ9JKXsBA4DlwK3AF1LK7sAXxteWwMzJr/TUnfYZ5PZpr93tM5CCZulcP647\nX63czZcrdgZ/MyMPzn8X+p0FX9wHH98Avtjmi9eK0eNvtSef5glQ/sxFgzT+fVBP5430M/lJr5nv\nXUacLOePul71+Zl9p5qU6kAIwYXDO7Fq50G+X7c3otNIb92GL6Bs7Xu3yanxejyUP02AC2MsTazm\nz+/2GecgRvfX/CmmHt2ZNy8/EgjesxnXuxVgpH3GS/nzeeGrB9SCJC1L1akM+0NY12BHSSXPz1vH\npP5tGBSm5X+KQxO7pqmaE6oMX+qcnpoVwuhbYNVnsKruvWMhBFOGFvHr5mJW7qg/FT8alPInEUkw\nfEm3a1w8ohNvXzE8ZPDnrpb2KcxebpMeVwvqF49T64GK+JrijOzekiM6t+Dpr9bUm/kUkgr1bBSZ\n1jJ8OUJbAcAZe9VGrx1fUJ/msDnyKtU2aufv8OI42FO3+uKwaTw2ZSCVHh83v7MkJrXeGj5rKX/G\n/aw784KUP93n4ZQ9/4anBitn++HXqLYNR98AjuS2EWpMhNpgO5DTjfzy+AR/24QQdwghOhkffwW2\nRXQmAyFELjAKeBFASumWUhYDpwCvGIe9ApwazfvHA3MCqS/1QQSoC9Ie/s184fBOdC3I4r6PltU8\nhz0dJv9L/YEsehneOg/c0blMRkSxCv62ypbkZcVf+QtUTOyawCclL6adzz2eiwD41tfX/31XvFpM\nCgGnPgO5RTD9YqjHjfHkAW1pnung1e8iM37RzQe6FnlQHQ/DF5smkGiqZrWpKX/mwzXOyp9PV/qe\n+eu5Y1IfjuyiFjyBz/dzhnXgoTP645HVlL9YqfolW+HVk+Hrv8OAc+Dyr6FNeNb9AP+YvRKfLrnl\n+F6xGU+CSWRyxKFOmk3D41UborK+tE+TI66E/G6qXqqe/qqTB7XDYRNxM37xJKnmD1Rwe8/JfRnU\noXnIOd2v/Blpn5o0Np57nwzX/KhSDhf9R/U/WzI9bje+EIKbj+/J7gMuXvl+Q8Q/b6vcjw8tafb8\nM38PbYKhS3XNM3RVbqOhR++Y2fskuPgT1Z7gxXH1bhx3a5XNX0/swzerdkdtGheITXot5/YJ4HPm\nq1ZCBsM8ixi79w11va5bBMffn7QWII2ZkMFfs24Ulq2I6H3CXRGdAxSg2j28D7QyXouGzqiawZeF\nED8LIV4QQmQBhVJKMxF6B2CZYhOzsbbbW7fyF/jc82WG726VZte4+6S+bNhbzkvfbqh5gKYpafzE\nR2H1LGU1HG+b+OJNeJ35VOAkLyNxyp/5b58u8emSpbIznSrf4Ae9j//7cXW2yshTO3kV+5Ulfh1K\nq9Nh4+xhHZi1bAdbi8NvkVCf4UtdxMfwRb2nV0tP1fxFiVnzV1/aZ5vcDDQh8GBH6DFO+1w5E547\nCrb9ojaMJj+rrMnDZPn2UqYv2sJFwzvRIcCUwkrk17sRlYr+EoXDLvyNq+s0fAnEnqZS5fathR/r\nTq/Pz07nuD6FvP/zlqhrzurC7VV9/pKh/AUSKrXa7/Zp1oebyp+mQXozmPAAXD4X8jrAe1Phtclh\n1VJGw5BOLTimZwHPzl1LaYQGPPbK/ZSJ7KS106gtJnYb1zddV887TerIhmwQth8CU2dDRgt45WRY\n+n6dh59/RAeO7VnAA58uZ/XOhinbNqlHp1rGCVP992YWqJpzI/umu74OHQEnP6nu2xRREcpRuTSn\ne8TvE26rh31SyuullIOMj+ullNE2LLEDhwPPSikHAWVUS/GUahsx5J+tEOJyIcRCIcTC3bsT0yTZ\nTMtwR2B57MtsFdE5RvUo4Lg+hTz15erac8GHToUpr6uWBC8eV2+KQYMo3khldnuAhLh9mhOGlGoB\n4dWlP5UIVF8ek7g7W7XuB5Megw3z4Kv/q/PQ845Qk9jrP4S/gyfN3dwo8ttD9YRqKOZc4tWcTU75\n8wdYtvjcw1/ffAz92+eq4E8nZIyZZlf36+WjutCnbQ6CqrTPCdoCptmfb9ggvC7lOve/s5VJ1BXf\nwICzI36baTNX0CzdzrVjujVsPHFk1g2j+OxPNWthTVLKX+Jw2DT/M7GqyXsYmyzdj1PmQ18/BAfq\ntic/a0gR+8s9zFkW+81Ot0/1+avNeCuZeLDjkg4qykoAEKbyF7jx2WaAssOf+Ihq4/LMcHVNva6Y\nj+em8T0pqfDwwrz1Ef1cuqeEMlvN8oVk4y9zMJaZSvlr4LO1RRdl1Nd2kMocmv9ErROSEIK/n9Gf\nrHQ717/5S73CQl1YLu3TmAM8GQUgfVCuUn+7y/XsTS9SpQgpoibUBtvBnMif2WHd7UKIHkKIfwsh\nZgkhvjQ/Ij6bYguwRUr5o/H1O6hgcKcQoo1xvjao1hI1kFL+W0o5REo5pKAgMUXEptW5x6f+kB89\nc0DI4wJ/Jb6MyPva3HliH7y6ZNqndfSb6zURLv5YtSR48TjYvCDi84RF8SYOONsCJMTtM3DRYNME\nUoLXVzVx+ndCQaWRxJuB58Lgi+Hbx2DFp7Ue1r55Jsf1KeTNnzbXawhkIs20zzpq/mqj3iapURCk\n/DWxmj/NrKuL4lqHQ8f8LIqaZ+Ly6uw6UElBs5pGT/ec1IcrRnXhluN7AirYdmNHet08l/Y459i/\nij5o2btWtXD44RmVUjf1C9WPKkLmrd7NN6t2c92Y7uQlYLMnWvKz0+nV2nqLyUORNJvmX7T63T7D\nnZ+Of0DVvM65t87DRnYvoG2ukzd/2tSgsYbCr/zZrLNwBujXTqVIlpLJhi2qusYf/FVX0DSbque9\n9ifVfuCr+5WRxvp5MR3TYe1ymdivNS/OW8e+svBrlTO8JVQ6kpPyCZCVFny9JvRtDaheq6BSJgFs\nNFD5M8lsARfOgL6TYfZd8OlNtWYPtWrm5MHT+rFseymPzVkV9Slt0mup4M8MTtzNDHVv+UcAdJcb\n2JkRuUKVIphQwV9pszgFf8B04GfgDuDmgI+IkVLuADYLIXoaL40FlgEfAhcZr10EzIjm/eNBYBPW\n3m1yOH1w+5DHBW56RpPS1yE/kytGdeGDX7axcEMdwmr7IWrHLyNPmToYf1wxQ/dB8WaK09sAiQn+\nAm9ov9IasBvmSaTyZzLh72p39f0rYV/txbQXDe/EvjJ3+LbkxsNAiyIg0TSB06Fxx4m9I/7Z2jDT\nCDyaEzwqfXX3AZd/N78xI6Sh/NXTd7NB5xCwrbgCj0/StWXNNMv87HRum9jbb9Zjpn3KAMOXUI6g\n9bJkumravn8DnP0GnPD3qP6fPl1y/yfLad88gwtHdIx8HCkOSdLsgcqfei1kk/dQ5HdVhg+/vlGn\nc6VNE5wxuD3frtnDlv2xzUrw+HQcwoeIU1ZAtJhze6nMJEuq+n5BCOUvkGat4cyXlUGc7oFXJqnn\nVtme0MdHwY3H9aDC4+PZueFnHGXrJbgceTEbQ6Sk2YOXuGcYa7cHPOcC4BIqCBSxCv4AHE44/SUY\n8Uf46YU6fRrG923N2UOLeO7rtfwYoXGciU1GaVYTJ8zN5LJWAyEtG2bfDeu/oT272JWVCv4aSqjg\nz+fIYkdWZHX64d7tXinls1LKBVLKReZHRGcK5jrgdSHEEmAg8ADwIHCcEGI1MM742hIEqi31bWyW\nSlUrI6KsMbrqmK60yXVy94dL615853dVAWDhYao5+Y//jup8ITmwA3QPu21qlywRaZ9Vyp/07x4H\nBn/eAOVvoX1Q3McDqEn8rFfV6v6tC/2BUXWGd82ne6tsXvkuvLYPZqsHLYoNAoAVfzuBqSO7RPWz\noahK+0wHbwUVbh+jH/6KGb9E39zXKtjinPYJajI2swIy0+vfmBACDsgM0vZHmbbtLoMZ16han8LD\n4Mpv1a5/lLy3eAsrdhzglgm9SLdbZwc5Ghr/dkXjwWHTqmr+/MpfBG8w8s+Q3Rpm3gJ67WlvZw4p\nAuCdRVuiHmsoPD4dJy5EmnWcBjc8eCJHGEZRxWST7VHBW1XNXz1/n93GwdU/wMib4Ld34OkhsPjV\nOq9vuHRr1YxTB7Xj1e83htWmwKdLcuQBvM7kuQZXX0KZz7qP9BH8pPfwB9UaOjKWm8qaBuP/VuXT\n8PJEOLAz5KF3TupDhxaZ3Pj2rxHXVIKZ9mm94M+TlgfXLFAixX9PB2B3Vk339hSRUVtq/Wv9Xwn5\neq3vE+ZxHwkhrhZCtDH68bUQQkRt0yOl/MVI3ewvpTxVSrlfSrlXSjlWStldSjmuATWFMSfQXr+u\ngnYhBEe7Hmdo5TNRO8tnptm5fWJvlm4rrd/lLKslXPSRaoo582aYdWdMJnnT6XO7KMRhE2SmxX9B\nGEr5c/lqKn/FMotn0i6N+3j8NO8Epz0PO3+DT/4cModfCMGFIzrx29YSFm8qrvctzbTPaGr+4oEQ\nAiHAo6WDp4JKj49yt49tEZjYWBXNH/zFT70OnIydYQRPQgie8k7GUVFVsyzDVVl3/K76fP38Ooy6\nWbnM5RVFOmQ/FW4fj85axYD2uZzUv03U75Pi0EO5fRpN3k3Dl0gefOnN4Lj7YNtipQDWQlGLTI7q\n2pLpC7fENBvB7dXJwI1wWNPcaLHenbx9v4K7XPUjhPB6EjoyYOydalOoVR/48DrVSHtXHeUkYfKn\nsT3w6ZKnvlxd77EHKj005yDSmTxHR73a89rpqLp+5dKJU1dqsg0dPR6O0EOnwtn/gz2r4IVxsHtl\njUOy0u08NmUgO0oruXvG0ohPYcOHtFDap7mUkxLVr/qCDyBdpervyU4pfw0lVOmPlDLi0pFw7/aL\nUGme3wGLjI+FkZ2q8eIIUv7qfriVks1u8hrkLTipfxuGdW7Bw5+voKS8np2gtEzVvHnoVPjuSaUG\nNLTg22jwvlm2JC8zLSGNnoPdPmu6q3qkCpRWyqLENzTtMR5G3QK/vK52UUNw2qB2NEu38+r3G+p/\nPz16t894YRPCH/yZc0h5NH2dLIbNTPu0xS/tM1DtzQhjo0QAi2UP1va7oepFvZ7+nVLCTy/C82Og\nsgQu/ADG3NHgprgvzV/PjtLKJtPQPWX4kjgc9pqGLxG3oul/FrQfBnPuUfd1LZw1tIitxRXMXxO7\nNEa3T5IprBn8PXRGf+brh6nNq80/BLt9hkurXmpz6JR/qqDjuaPVdXZHnz7bIT+Ts4cV8eaCzWza\nW/f7lJSWkiHciCTa+VefDwYW5XH3Sco5fLMsoNCzFaRUyl+82gH1nKB+D95K5dOw4dsahxzeoTnX\njenG+z9v5aNfI+uiZtW0T/+1b9kNLv6Y+7wXUOm0jIl/oyXUHKvLyAtHwnX77BziI3Z5ZxYnMG88\n3H5cDVlHCSG456S+lFR4+MfsmjtFNdBsyvFr3L3w+7vw2mkNa/5qNHjfkKAG7xA8YYTqZmC6fbpk\nkgKmY26FLsfCpzcrK/1qZKXbOWNIez79bTu7DtSTEmMqfxZymdOE8Nf8mfd4Uwj+tASkfe4srdps\nCdxZrg1zbljVLUDBriv4qyiG6RfBJzdCp6PhyvnQ5ZjoBhvAnoMunp27luP6FPpTzRo7fdvm0Mmi\nbSqaGg6biN7wxUQImPiQqk37+qFaDxvfp5DcDAdvLYxdzz+l/Lks0WD6vCM6cOsJVTU7HVtkskDv\nha45YN1cNKlHZ3QmBAw6H65dCP2nKAOzZ46E1bOjHut1Y7pj0wSPf1G3SUlZscpssGUnb255bMpA\nv4EOqMtxyVGdAVguO6qaypLNyvAlnkZy7Q5XTqDZreHVU2HJ2zUOufbYbgwsyuOv7//G9pLws25s\n+NCT3K4kEHN/IlB11Vv24iXvCXHpU3yoIYRgQFEeA4qqamm9vhgrf0KI0+r6iGrkjZDABd2vW2rf\nnQwyfGngLnqftjmcf2RHXvthIyt2lNb/A0LA0X+C016AzT/CSxOgOMoHZfEmyG7N7krIy0hMMXyQ\n8mereVuaaZ9ukhQwaTY4/UWVavv2BVBeMyv5wuGd8Pgk//uxnutuLPRtcb2ipQAAIABJREFUcTQh\niRQhwCNUzZ85h5S56lGjGgF2Pb5un0CQ+104f/bmRkelV/J/nvOAqlTgGmz+CZ4bCSs+USly570D\n2bFxOX5izmoqPL6gRWdjJyvdztybj032MA4J0u1azT5/0Tz32g6Cwy+AH5+D3aEDCqfDxuRB7Zi9\ndCf7I3CbrAuPT8cp3GAB5e/+yf24cnRX/9dCCMpxcqDlIFg3FyF9DXO5zsqHU59RCpQ9HV4/A96+\nCErDNCkLoDDHyYXDO/LBz1tZs6v2HnXlJcqwPa1Z5M7nseK4PoV8dN3R/q8DvRiW6Ya51Y7f4qv8\nmTTvCJd9Dh2OhPf+AN88HCRN2m0aj00ZiFeX/PntX/2p1PVhw2uptE9z7RsY/Jk1wfFwKz8UmXHN\nUUwe2Nb/tVeXEZvG1Xe3n1THx6SIztSISbeHNykETiyxuMVvPK4HORkO7vlwadiKI/3PhAveU5P6\nC+Ng+5LIT1y8EZp3pLjckxCnTwheNISaIEyHz60yeQ8SsvLhzFfUtX3/yhr1lZ1bZjG6RwGv/7ix\nzr49VU3erTNh27SAtE/jVmsSyp9h5R1Pt8+9AYvRcBa/5hGVHr2qf2V1O3Bdh28fh5cnqB+45DM4\n6voIHTVqZ+3ug7yxYBPnDCuia0H4jeBTpDAJ7PNnrlOj3tkfcxc4suCzv9SauztlaBFun877P8fG\niMrt8eG0iPJXHXMa2d96BGxfQravuOF96MDIHPhWpYyv+gyeHqrM4vTI5vqrjulGhsPGP2bXrv65\nSpXyl56TxGd2NQKn5xWySDUdN4K/uNT8VSejuXJk7XcWfPl/8NEf/ZlAoNYQd03qw3dr9/LS/PB6\nKlqtybvmD/7gyAe+4I4PfgtIC0/ANT5ECBRJvD49YrezOn8TUspL6vhIoOtGcolGxYtF/UxeZho3\nje/JD+v28elvdTfDDaLzKLj0M6VWvXwCrPkishMXb4S8DhRXuBPi9AlVa1qJcSNXY57ej7s9F/GU\nN8mCc9FQmDANVn8O3z5a49sXj+jErgMuPl9ax+/Lr/xZx2JcEwK3MGv+1CxS5m78yp+/5k+Lp/Kn\n0j5vn9grKBWjNsy5odLj8wd/Ug9QMw7ugtdPhzl3KxfPK+ap+y6G/H3mCjIcNv40LuW+liI6HDYN\nT/W0z2ife9kFcOxtsPZLWDkz5CG92+TQv30ub/20OfzN0DrQfW7s6Kpu3mKYV3F/4QhA0rt8EXqs\n3Cjt6cos6urv1bwy82Z4YWzIcobaaJGVxmUju/Dpbzv4fWvobCjfQdW6IDOvVUyGHQsCb88KnOy0\ntzOCPxlbt8+6sKfDaf9Wv4PFr8IbU1TfZoMpQ4sY17uQhz5bGVbWlzJ8sVLwpz5LKdlRWsl/f9iE\nV08pf7Em0IvE44t8PkyF4TEkKO0zRu95zrAO9G6Tw/2fLKMiEiWmsI/KMW/eCd44C36p3U0tCJ8X\nSrYiczuwP5HKX8CNPLxrVY1AmrG74SKNV3zHs4fcmF3bqBk6FfqdCV/erxYrAYzuUUDH/Exe+W5D\n7T9vtnqwiNsnqAnbDP7MbfxyV+NX/uzSrVTjOO44mqqHWUtSH+Y8Uen14THTmE3lb+1Xyphh43cw\n6TGlNGfEtk/WgvX7mLVsJ1eO7kLLbOukHqdoXKTZNf+iw9zZb9DabuhUKOgFn98GntB102cNKWLl\nzgN1ll+EizRb91gg7bM65hxRmt8f0prRwrc7NspfIC26wPnvqXKGkq3w/LEw89agQKQupo7sTG6G\ng0dmhfYl8B1UpRHZza1j8lG9BddGR5fEpX0GDUQo9fXkp2DdXHjpBCjdZnxL8PfT+5GT4eBPb/5C\npafu57AdL9JKNX8Byp9J1IZQKWol8Fp6dT0+hi8pIidWxnk2TXDvyX3ZVlLJs1+vjeyHc9rCJTNV\nqscHV6mC+vp2TEu3gvThzinC7dXJS5DyZ6bLSSnp1qqZf4co3WHBW1QIOOkJKOgJ706Fkqr+U5om\nuODIjizcuL/WHVEMExIrKX8Om4ZLpIP0IY3xNQ3lz4tPi+91PmeYarXgCFGrGgpzanB5AkwcvJXw\nxX3w2mRw5sEfvoQhl8ZuIjGQUnL/p8tpnePksqMPGc+uFHHATPuUUsZmcWdzqKyK/Rvgh3+GPOTk\ngW1xOrT62yCFgfAYbpUWTPs0ZwkpbNB5JEB80hKFgH5nwLU/weBLVN3l08Ng2Yf1rhVynA6uHN2V\nuSt3s3BDzRp4UaGUv7QkGr5Up/p0utHRBYo34sSVnLq5wy+E896G/etVmc5O1eohPzudh8/oz4od\nB3jk87pN/1SbCutsJJvXOLAti/lveyg3vxRREXgtPT4ZcTZEvbOJEEITQoyIfGiHHiLo37G7yYd1\nbsHJA9ry3Ndr2bwvQptmZw6cOx36nw1f3W/kmNexqDfaPBxwqmLShLl9Vls0mGkC4dZbJpy0LDjr\nNdVWY/rF4K1K2ztzSBEZDlvtbR+M+gqblVo9aAK3MIIkY9e9KdT82aQXn4jvdZ52Wn/WT5sY9vFV\nhi8+PFItOJzTz4V5jypnvsu/gsK+cRnrx0u28+vmYv48vkdYbSlSpKgNc272+CS6lAgRg3KHrmOg\n1yT45hGlRlUjx+lgYr82fPTrNsobuDklvNZX/iSoMg4gR4anyEVFRh5M+ofKFsrMV6Zm/zvb7/xd\nGxeN6EhBs3Qe+nxljcWnVrmfMjLAQpuc1e/OjQ5lsmNHRyYrp6jbOLVJL3Vl1Lf2KwCO7dWKC47s\nyAvfrq+zxYkNH9JizuFAkGLpNfwRok4LT1GDwPrJmLt9AkgpdSD0NtwhxKwbRtV7TLDbZ2zPf/vE\n3tg1wf99sizyH7anweTnYORNKsf8zXPAdTD0sUaD931prQESlvZZ26QwtFPyegTVS0EPOOVp2PIT\nzLrD/3JuhoPJh7djxi/bQjrTCUNZExaasO2aoBKn+sLYEW8Kbp8O6UFPwHWOZNFrHury6HiNtE9x\ncIdKvzrlabWxEAdcXh9//2wFvVo347TD28flHCkOHRzGzrPHp+PTZXROn6E4/n61QTbn7pDfnjKk\niIMub2R18CGwea2r/PmvpASyE5g22X4IXD4Xxt8P6+epthDfPh5kShJIZpqda4/txoL1+5i3OjhA\ncbiKOaDlxH/MEVB9nt7gqHJYTWjaZ3Xa9FeBd26RcmL9+XVArfu6FGTx57d/rbXns91iTd7NKxy4\neezyqOAvVfMXOwKvpS+OaZ9fCCFOF02hC3CU9ChsltTzt851cs2x3fh86U7mrd4d+RsIAWPvhEmP\nw5o58J8T4cDOmscVbwIEe4Syk09U2qdJ9Rs4K906AVJI+k6GI6+BBf+C397xv3zR8E64vHrovlRm\nT7c4th+IFLtNw4X6XduKNwCNX/mTUmKXnrinfUZK4M7oQr0Hb3jHUHbJlyr9Ko689v1Gtuyv4PaJ\nvZt87cV9p/TlnSuHJ3sYTRozzdnt1fFJGXmPv9po3gmO+iP8Nh02fl/j28M6t6BzyyzebmDqp+Y1\n6gqtGPyZZRBIsDsTe3KbHUZcC9f8qHrbzrkb/jUaNv0Y8vCzhxXRLi+DR2YFq3/pnmLKbLkhfyZZ\nVL9Di7UWSumE5AdQue3hUqNMZ8bV8NU0Mhwaj08ZyJ6DLv76wW811FUppQr+4mhoFinmPBCozO86\noEzRmvpzJ5EEXkuPHgflz+AKYDrgFkKUCiEOCCHCaD53aBHU6iEO9/hlR3emY34m9360zN9fKWKG\nXAJn/w/2rIIXx8Ge1cHf378Rctqx36X+A4ly+6ztcjkaQ474cfdC0ZHw4XWwazkAPVs348guLXjt\n+41Bue8Awgz+LKb8eaW61i2nnwKomr9YuOolC58ucQgvepzTPiPGNHzx+NhJC273TkVvHt/6u+Jy\nN099uYZRPQoY1SM2fQKtzIXDOzHEylkDTYA0f9qnjh5L5Q/g6Bsgpx3MvKVGGwIhBGcOac+CDftY\nu7uWDJYw0Hxm8GfBtE/js5TEtU1NneQVwTlvwNlvQGUJvDQeProeKvYHHZZut3H92O4s2VLCrGVV\nG8oZ3lIqHRYL/qrfokJA634AsXNTbQjOXNXLdeB58PWD8MHV9G+dyQ3H9eDjJduZ8cu2oMOlVDV/\nSQ9cA9ACnm8muw+ov7VUzV/sSLMHpn1GHg+EFfxJKZtJKTUppUNKmWN8bS093wIETizxyG12Omzc\neWIf1uw6yKvf152LXyc9J8DFHytnxxePg00/VH2veBPkdWB/uUpXTFTap2nscnS34J5A9sbQF8bm\ngDP/o9L13rrA75Z28YhObC2u4IvlwQprVfBnnaDEpgnSvMELKSnBVUe/Qqvj1SVpeNEtdJ0huM9f\nonj6yzWUVnq4rQk1dE+RXPzKn0/Hp8d4Vz8tC8b/DXYsUaUK1Tjj8PbYNMHboTIrwsTmr/mznvKn\n+Q3QSLzyV51eJyoVcPi1sPg11RtwydtBhjCnHd6OLi2zeHTWSv9mZzO9BLcjtk7FDSVk8poR/CU1\n7TMQmwNO+Scc+1f49Q14/XSuPKIlQzo2584PfmfL/irfB5+UOPCqtl4WwbzGgWuHnaWm8meRa9wE\nyHFWrWs8vtg3eQdAKM4XQtxpfF0khBgW0ZkOMeKVIDu2dytG9yjg8dmr2G1I6VHRbjBcNhsyWsAr\nJ8OyGep1o8F7SYXKL09U8JeZZmfuTcfwyJkDgl5vNDtFOW3gjJdg31qlAErJuN6FtM118sr3G4KP\n1b2quayFJkK7TSNUq5jGXPfn09WDUbdq2qe3amc0ngLr5n3lvPr9Rs44vD2926T27FLEhrSAtE9d\nyoa1eQhF39Og41HKBbea2tQqx8mxPVvx7qKtUWfB2HULK3/GtdRlEtI+Q5GerWoxL58LeR3gvT/A\nq6fAnjWAen7ccFwPVu08yEe/bkNKSY48gM9preAvJIVG8Jf8JlJVCAGjb4FTn4ON32F7eQJPTmyJ\nBG58+1d/gK1Lqdw+LbTBaT7f3L7A4M9Q/lJpnzEjx1mVOebV9bilfT4DDAfONb4+SMoEpk5i6fYZ\n9L5CcNdJfaj0+nj48xUNe7MWnVUA2GYAvH0RzH9C9ZrJ68D+MjeZaTbS7YnbUerUMgunI/h8IScL\nq84fnUfB2Ltg6fvw43PYbRrnHdmR+Wv2smZXlVObkF5/c2+rYNcEc7NPAMDVpqqheGOu+/PqknQ8\nlnowQkCfv8D+TXEM/h76fCWaBn8e3zN+J0lxyJEW4Pbp02Xs63mEgAkPQmUxzH2wxrenDC1iz0EX\nX63YFdXb233WrfkzkZC8tM9QtOmv1gwnPqqawj87Qv1uvC5O7NeG3m1yeGzOKg5UVJIjypEZ1k69\nlpIA5c9az2QABp4D578LpVtpO/0kHh+tsWD9Pv79zToAdJ/EIXyWUv7MaWDRhqoNm1TNX+wJXCt7\n49jk/Qgp5TVAJYCUcj9gre10CxCYUhBPa5yuBdlcelRn3l64hV82FzfszbLy4aIPVWrH7LsAaaR9\nesjLSP6iudF5DB31J+h5onL/3PQDZw8tIs2u8cp3VWm6QveqxuMWwqYJKnUb9JyIcJf5X2/Mvf6U\n8metYngINHyJf9rnL5uL+ejXbfxhZBda51pAQUjRZDDTPj0+pfzFZWHXpr/qP7fgedgZ7HR9bM8C\nCpqlR5362RiUP0ukfVZHs8HQqao3YO9JMHcaPDsCbcM33DS+Bxv3lvP6V7+qYzOt0+OvVlr2YJ4c\nyNas+LTXaTBdjoFLPwfNztjvL+KmLhv5x+yV/L61BN0oIZEW6vNnPt++CNiUSSl/sacwx0mv1sqI\nMi59/gw8QggbxkaUEKIAaLzFQA3AvNj1Ee9b/Nox3Shols49Hy5F1xsoGzgy4KxXYdgV6uuC3pRU\nuBPu9BmKRjdVCAGnPqMsm6dfTD4lnNS/Le8u3kJppdHiQfdZTvlz2IRKJclogVZZtWNX5mrMyp+u\nDF9syb+PA/E3eQ+oiYg0Xz8cpJQ88MlyWmanccXorvX/QIoUEWCacbmMtM+4bdSNuQPSm8FnfwnK\nj7bbNE4/vD1frtjlX1xGgkO3rvJXlTkkraX8BdKsUJU6nP+ucrB+9WTGLL+DY9rDh9//BoDdQg3e\na8Vm5ypuZ0POkGSPpHYK+8DUOYj8rlyz/Q4ucc7lT2/9Qlmluoet1Ocv1DSwO6X8xZw0u8ZnfxpF\nhxaZcW318CTwPtBKCHE/8C0wLcJzNXp+u2c8H1xzVK3fF7V+EXuaOR3cOqEXv2wu5r2fazbDjRjN\nBif8HW5cDu0HK+UvQfV+ddIY54qMPJjymqpTeedSLj6yPeVuH+8u2gKotE8rKn9eXUJm86Dgr6GN\nlJOJT5ek4bGc8mfe0y5PfAPr2ct2smDDPq4f14Nsq7dMSdHoCHT7jGmfv+pktlAB4PpvYPmHQd86\na0h7dAnvGHNrJPiVP7sFgz8rK3/V6TYOrv4BRt6E+P19ni+9inP5DIC0Zi3r+eHkYm66SSnjmq0V\nE3LawCWfIrqO4Xbfv5i87wX+MXOp+p6Fgr9QZodm2mejMPBrZNhtAk8UAlC4bp+vA7egAr7twKlS\nyrcjPlsjp5nTUaMmLZCgJu8JiFomD2rHoA55PDhzhV9VahBCQE5bAPaXuxPW5qEuEnEd40LrfnDi\nP2DDPPqteppBHfJ47fuN6LpE073+5t5Wwa5pyi44LRvNV4kwhP1Grfz5lOGLtFlr5zywz59JrA1f\nPD6dBz9bQdeCLM4eWhTbN0+RgmDDl5i7fVZn8CXQqi98fodyqTboUpDNsM4tmL5wc8RpT2l6JR4t\n3VLGWyb+4A+sq/wF4shQfYSvmo+jzWFcYJ8DgDPX2sGfSaNpaJTeDM55EwZfwjX2Dxm7/A71uoWD\nv3S7xr4y5R5vwT+1Ro/DWLvFxfBFCPGalHKFlPKfUsqnpZTLhRCvRTPQQ4VE7CJpmuDek/uyt8zF\nU1+srv8HIqDEKspfY2bQeXD4RfDtP7i18zrW7Slj3po9COlDt4qttIHdTPs0FhppKMWvMSt/ZqsH\nabPWfexv9RCU9hlb3lywiXW7y7j1hN7+2qwUKWJJ9Zq/uC7sbHaVmVKyCeY/GfStKUOK2LC3nB/X\n74voLdOlC49mTVXN3PRsFMpfIAU94eJP2H7Mo/yUdQxtuw5M9ojCptFsM9vsMOkxPMfezXG2xYC1\n0z5b5VRtXqSUv9hjtwm88Wr1AARVwhr1f4MjOtMhQOA9H48+f6Ho3z6PKUOKeHn+Btbsir7hbSBS\nSoorrBH8WT4Voz5OeAjaDGDYL7czIGs/r363AaF7LKj8GWmfxkIjHbVTV9aI3T59uq6CP4ulfWpa\nTeUvlhyo9PD4nNUM69yCcb1bxeUcKVIkLO3TpPNI6HMqfPsP1Y/WYGK/NjRLt/PWT+Ebv/h0iVO6\n8NmsGVhVKX9S9X1rTAhBm2OmMvTmGWRkZSd7NGEhZSNbawiBY/SNbB7zFJXSQVrz9skekZ/qCQD5\nWVXBX6rmL/bYbRoeXcZW+RNC3CaEOAD0F0KUCiEOGF/vAmZEPdomSpDbZwLPe9PxPclIs3HvR0sj\nTn0JRWmlF58uLZL2Gd5rlsXhhLNeRQiN552PM3/lFipcbnSL2UrbNLV7ZCp/6ag04vJG3OfPq0sc\nwgsWS/usavIemPYZO+3vX1+vY2+Zm79O7N343HJTNBpM5c/l1fFJ6d/UiCvj/wYImHWn/6WMNBsn\nDWzLp79t9/enrQ+PTydDuPBaVvlTSEkji0qsSYcWoR1d49lfNREUjboQcdsmBo0/P9lD8VP9mdMi\nq2odmXL7jD0OTai0zwh/rs7gT0o5TUrZDHhYSpkjpWxmfORLKW+LfrhNn0TO1y2z07lhXA/mrd7D\nnOXR9TwKpKTcbPBugeCvKcwVzTvBaf+mVdlq/mZ/mbKKCssZvthtGl5dr1L+hLoHGrPyV1XzZ62d\nc3ORHFijHas1yPaSCp6ft46TB7RlQFEjaLCcotGSZqvq86cnQvkD1WD86Btg2Qewfp7/5SlDinB5\ndT78dVtYb+Py6jhx47Og2QtUq/lL0WA+uOYoZtRh1ieJo1ttnEl3WqtVSfWst8AMspTyF3vMjfu4\n1PxJKW8TQjQXQgwTQowyP6IZaFMm0YYvgVwwvCPdW2Xzt4+XNTidbH+5SvlLZp+/Vy8dxgOT+zVe\nw5fq9DgeRt3MmbavOVr7HZ/FlD+7FlzzZyp/FY245s9n1PxhsVYP8dz9fHTWKqSEm49PNXRPEV9q\npH0mamF31B8htwPM/Av41PzUv30uvVo34+0wUz89Pp0MXOgWTfvEX/OXCv9iQYustDo3w1KXOXZU\nnwYCM8jstiaynrMQDnPjPkLCNXyZCnwDfA7ca3y+J+KzNXES2eqhOg6bxt0n9WXTvnJemLeuQe9l\nBn/Ns5IX/I3qUcC5R3RI2vnjwjG3UdrmKHJFObrFlD+bJvD4Amv+moDyZwZ/dmsFf6HqgWOx+Fi2\nrZR3F2/h4qM6UVRLmlOKFLHC7PPnNvr8JarOHUcGHP9/sGspLHoZUKlmU4YW8dvWEpZuK6n3Ldxe\nnQzhRre48meyV2vJnMwTkjOYQ4RUWBIbqs8DR3ap6vWYSvuMPXab4dcQJ8OX64GhwEYp5bHAIKA4\nojMdYiQjg+Do7i2Z0Lc1//xqLduKK+r/gVow6yZSaZ8xRrPR7LxX2K21xGWzViG8Q9OClD+nYfjS\nmGv+fD4dB16E1ZS/OO1+Tpu5nByng2uO6RaX90+RIpBA5U+XCbZx730ydB4FX/4flCuXz1MHtiPN\npoWl/inlz41us2jwZ3w2N4WuavVfXsi7PmnjaarIwM9Naa2RRALXbJcc1YnurarWOraU22fMsWsa\nnnilfQKVUspKACFEupRyBZDKK6pOkgxfAvnrib3RpWTazBVRv8f+suSnfZo0tflYZBeg/eErCi58\nOdlDCcJm7h45mwOQJ5RzbGNW/nxeN5qQlkv7DFUbFalNc3W+XrWbeav3cN2YbuRawKU3RdPHNHxx\nJ8rtMxAhYMLfwXVABYBA86w0xvct5INfttVb+uD26jhxoTssGvwZ19LfhBzZdEogUjRpApU/mxC0\nyE4ZvsQTh03Er88fsEUIkQd8AMwWQswANkZ2qqZP4G2drOLhohaZXDm6Kx/9uo0f1+2N6j32G4Yv\nuRYI/pqW9KfIb9OBVu27JnsYQahWDzpkquCvOSr4a8x9/nxetYkhLJb2GbI2qgGxn0+XTPt0OR1a\nZHLB8I7Rv1GKFBEQ2ORdT5TbZyCFfWDoVJX6uX0JAGcP7UBJhYfPl+6o80fdPpX2Ka2a9ml8Nhd0\nja4VQWNDJt6noakSGPxpmqBZut0/V6QMX2KPMuuLU58/KeVkKWWxlPIe4E7gReDUiEfZxAmcnJN5\nj185uivt8jK4+8OleH2RF4KWVHjIcdqxW7Q5dGN15bIydk3D55OQ0QKAPHEAgDJX41X+pBH8Wa3V\nQ+ADMBYPw3cXb2HFjgPcMqEn6XZr1ZKmaLpomsCuicT1+QvFsbeBM0+Zv0jJiK75tG+ewdsL6079\ndHuV4YuwrPKnPvuDP1LBX1zwX9+U40usCHykCaHWa/mG+pcK/mKPw5iDY93n73EhxFlCiHbma1LK\nr6WUH0op3dENtekSuHOUzF2kjDQbfz2xNyt2HOB/CzbV/wPV2F/utkS9HzS9tE+r4i8aduYihY3m\n4iCaaNzKn+5xAaBZWPlLN+qmol16lLu9PDprJQOL8jixX5sYjC5FivBx2FS9iU9PgvIHkNEcxt4F\nm76Dpe+haYIzBxcxf81eNu8rr/XHPD5JBm6kw5rGSOb6wV+TJlNpn/EmFVzHhsDNeVMFNHv9pYK/\n2OPv0Rwh9Uk7a1AK33whxAYhxBtCiGuFEIOEENaUhZJI9R2PZHLCYa0Z3iWfR2at8tfwhUtxuYfm\nFqkbSvZ1PFSwmWmfQuBLz6M5B8lKtzdu5c+ngj+ruX0GPgCdDqXURev2+eK89ewsdfHXE1MN3VMk\nHodN+NM+k6L8ARx+IbTurxq/u8s4Y0h7hKBO9c/j8ZAuPIg0iwZ/xqXUpVnzl3oWxhMpUxvNsSJU\nBlx+tsq+SdX8xZ6qtM/IqK/J+9NSynOllJ2AEcB7QBdgOim3zxpYaXIWQnDPyX056PLy6OyVEf1s\nsaWUPwtd1CaMQ1PK39NfrqbMnkueOEBWmr1xK39G2qeVlb+0BqRW7z7g4rmv13J830KGdmoRi6Gl\nSBERaXZbleFLshZ2mg1OeAhKt8K3j9EuL4OR3Qt4Z9EW5WAcAp+rDABhVeXPX/RnfEplJaZoJFQ3\nfAFomVL+4obDpjbuY274IhT9gZOBU4DRKEXw0SjG2aQJ3Hm3QiDYs3UzLjiyI2/8uCms3kcm+8s9\n5KWUv0MKm6YhJTwyaxXrSwXZVJKVbmvUbp94zbRPa9X82QPsrtMdZtpn5Ku7x+eswuXV+cuEXjEb\nW4oUkZBmE3i8Oj5JctI+TToOh35nwvwnYf8Gzh5axPaSSr5ZvTvk4T63Sgm1rvJX3e0zVeseT1LK\nauwIzoALTvu0p1o9xBy7puH1xdjwRQgxG/gBuAZwAQ9IKQdLKSdIKe+NerRNlCC3T4soVjeM60Fe\nZhr3frgMGebWQHG5m+YWUf5SJIbA3nMebNjxke104PbqUZkGWQHdq1xrhcWCv8D0OGeUBi1rdh3k\nzZ82c94RHehSYK2ekSkOHRx2DbdPR9clcWpfGT7j7lUq4Od/ZVzvQlpkpdXa88/nUsGfZtXgz/gs\nq4r+LLKiaJqEuzZKUT+hav56tcmhZXY6jqRPEk0Ph00ZvkS6f1xfGL4O0IHuxkc3IUTLqEZ4CKBZ\nTPkDyM10cPPxPVmwYR8f/rqt3uO9Pp3SSq91lL9kD+AQITAdQ0NylG0p00pvZYBYQ3k9PbOsivRa\n1PAl4AHoV/4inLgfnLmCTIeNP47tHsuhpUgREWk2rcrtM9kpXbn7i1ZBAAAgAElEQVTtYOSfYcXH\npG2cy+RB7Zi9bCd7DrpqHCoN5U9Lt2jwZ7p9UvXZKmuKpkSgWmKVDfvGTuA0YP779MPb8cNtYyzr\nIN+YMc36Yl3zd4WUcjjK9GUuMBj4rxBikRDileiG2nQJVLStNI2cNaSIw9rlMO3TFZS56q7hKqlQ\naokVGrxD6oGXKALVqEzUYqmX6zdmpN+FbfZdyRpWwzAMXzSHxYK/gGsdjdvnD+v2Mmf5Tq48pqu/\nkD5FimTgsGm4vRJdSmukJQ6/Fpp3gpm3MuXw1nh1yfuLt9Y4zAz+bFYN/ky3T2Ni0KUM2lxOERtS\nrTRiT/U+f6DUwFTgFx9smoZPlxGr1+H+NlxAOVBh/Ls9cHhEZzoECNw5stJEbdME957clx2llTwz\nd02dxxYbwV/zLGssmEMtKKxzZZsOQQ5dqDTPGYXXMts3mIxfX4aSLUkaWQPwqXvZajV/wa0eIkv7\n1HXJA58up02uk8uO7hzroaVIERH+tM9kun0GDcgJx0+DPSvpsektBhbl8dbCzTUWRtJjBH9pWckY\nZb1UKX9GzV/KjTJFI0ELkfaZIn44jPWEpxZzq9qor+bvMSHEj8B24F6gGfAc0FNK2S+qkTZhAu9z\nq93zgzu24LRB7Xj+m/Vs3FtW63HF5cohMdciyl+KxBDk0GUEfx5nPv/xjUfzVsBjh8F/JsHi16Ay\nfPOgZGI2ebc5nEkeSTAh+/yFuWv30ZJtLNlSwk3je/rbRKRIkSzSbZoyfLFC2qdJzxOg6xj4ahoX\n9c9kza6DLN4UbE7uqVTPQGemRYM/47MMcPu02pqiKZEKrmNHqFYPKeKHqah6vJF5M9Sn/K0HrgYK\npJRjpZR3SClnSilTbR5CEOz2ab27/i8n9MJhE/zt4+W1HrO/zFD+LGz4Mrhj82QPockRSvmzp2Uw\nX+/Hz5PnwrG3Q+k2+PBaeKQHTL8YVn7mV9esiPAZrR4c1lL+Ah+IkdT8VXp8PPTZSvq0yWHyoHZx\nGl2KFOHjsCuzAT3Zbp+BCAETHgRPGZP2vEhmmq2G8UtpaSkAzsxmyRhh/YSo+UuFJ7FHTxm9xJyU\n8pdYTBMdbyyVPynlk1LKRVLKxun4kGCs8uyrjcIcJ9eN7c6c5TuZu3JXyGP8aZ8WCf6qzx2nH96e\ne0/pm5zBNGGCJmxjqWFPV4rZ/vS2MPoWuG4RTP1SNVVe/w38bwo82hM+vRm2LLJcMyrpM5U/a9zL\nJkIIv0oSSdrnq99vYGtxBbdP7G2dhXaKQxqHTavq82elW7KgJ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eAZADMrA3an9I49mA70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vLOEih9w7ZFdlGyxwdpOO8pasBSE98uLcHPmO7ZThoDu80O+vqu2WaMNgjuytqG5mzh9eYUtDFOjdKPpaRx6gpktUIQgoyqDINU1qknCaAqzXzxosG7ueRNLR55yGf8dOAIFzWfYje95tEPOI7IXbEbD60KQxKumRPfO/HQEvLzYin9UO0aX9lYX8LPgwABMU4/xJW25yfe7D1Zk1geevyTzmxGDpt76xN4Dwv883A8YU6S86HePud9bYr9OpEQDPfr6Zj9dmDuRkFzZMLy/ewv0frGN9bXZhhHzBH59fwkuLt3ZKHfLWeSt5duHmtKODm8bZmUneaoOGtgSvL0mJY/jebAO6Lrll3gq2m55+iVs57u5313Tj3t18uAGM7903n5qmGC+bKqa55o90RwBn9bYWNCkRAhQlvyN71rKQ1GVOJVT8dTcTby5Pydo7nVkdU4rdpscg2TN3C841JZ7U+cery2k2acTOyF4uEfz0yJ6UO04blxUY+cRbG6P2sfPU5+3X/0keDkCbKAQke4pl/DjwMILMdrX23V9sauCpTzdmnB8sYom+sTeAYG14XGPY0c/Wbm+xc9R8pOqoQFqbmfjJI59x+q3vZRzvytjdbHrWB5PqZ0Obuy+t297aqf5lteNg3CBJKZESpooNBOhYoCWWSLXBuXc7xTEGx0LRXbyzcht/emEpn66vB6yNSfa2kVJmCEJkw2CO7K2qMcRqLIp/rlH0cDfy7I746xtIKVEVM7KXx5sda1nQdD2nCKVP48zEd+5OsUBcxl4OfXHplib79WCJkHQHzia49701/OXlZbaKsFNwxSk2VUwr40UmsyQjZ48dp40tVc26ltR+pVSkHPFXJc/j6sQ5FMhW9lcW8Xj4Gi4JPMlssSzjXlabHf9/b3Ppfz/NPJ/H858TvrE3AOHlf9R1ycF/nsf37v24z59noKKvJMGTmm57kB79eENeb36cSKRtkg/68+t87Z/v5/x5a7M+GGmcuoShNPBy+Of8NnBXh9fHsrTBIOkq3YYXvbW9jcnTn23i2BvfsmtItYcdYYMTDhpLda5jrTtGi6YbhYfVQZCzZzE+kprMEgGWrv/jvhpnu9AckeWOIh5SwgcO2tyOME47gnMsWQIqVnkQp8PaqTJ5b+g63gj/OCMqlU7jhB1nvdnkQWsvxKB0PqHtD8ByORaA+0N/tK85VX0r414dzW9+ZM9H78EjTGXVtpnvQUv0kfKY9YYXprophi5hv8mVbKxv450V2Wvh5BOcC4pluH2xKbdoCqRiVoNFmtgJXUqKhDHmjlQ7drBki25KadT+WRM5mz3qnve8ZkdAOuVIl5kbE2ekb2V1MwCL06J7XtHAwbIYe2F0maFUavWvbEbcQ6HfsiZyNp+Hv4uCbkuMP/zReiZc/qztCc8VmjQMpYCq5HXkNBXZkxm/o5IG1kS+zprI1/ksfD5fhL/DyC2vZ9zjB/d9zCk3v9MHTzvw8fTnm+zXnXUC5LPToKfgNHjTjV9n8zj76p7KCgCOVNzrkBeNczAb1B2VnRkptvOMtg8/TfwAgI2hiRnXnB14nduDf+X24F/tYx212WApg+Ybe/2I91dt5653VgNGfpkF1xA231iqVuWFuedixJM6v35qkUsRazDgi00N3PTactcxayLIdePXmYVnc4Ox6f/WvhMoLwzy8Pz1OX92IOC9ldu57701Gcedxl5X8u5sGucgjOxpurQ9hcNEI6crb7rON8eSXP3UIrsGX7aIgJSSKcLIAzi4+j+9+MQDG56Uo7Qx6ByTEVMxN712ntewHcybyEKzCP0vHvucbc0xV2TvWOUDfhO4C5DsrSwBDCpTlai2jcJ/vG7Mk87cFi88/dkm13tdl0xOrmKB9hWGtuZvsXpnzp6mwxHKx5ypGgbdRJFac8tEK0Uixvitr2bc44UvtvDp+nr+8OziQUPp6ipueX2F/To9yjyhstDzM+epz/F99RmiicG3TnQWzu6T3pNeWJTqj07nYY0sBeC8wPN8T33GPp4e2JPInOpw5iva22f8X/AfVIhmvtTHoZllEsqHjuIniR/wmHaA69qj1fkcraaoyR3ZcoNle+MXJ+tHWJS5c/efyEUPpJQOvfLPrCTedEWx9rBsaxP3vLeWORMrOGG30d172AGEk256J2OD1xkZdzAWKlXJLa9lU72xUZowtJBTdh/DAx+so64lzpCirosg9CXOusPoZ9/cd4LruJPGGY13fkazDezBMhs6ICUU0Wa//0voNuB6+/2/317Nve+tZXhJmIsPm8rKmsxC4BvqWllW3cxwUQ9Am1rS2489YJFZANigce4uVjBBbOETOcUVVbZqu8XSNohGn3PfazAbexGbvim5dd5KqoYU2OduDd0IwB2au/bgmeo83tZnIOUxdm3IjqJzlzz4ieu9LiV/rrsEgIuWfxc4uTs/o99g6EFKk5qqc2foLwA0yQI0D193JJadtXHHW6s5ZsZI9hpf0VuPO+CR0CQKOgcqC9G0aa5z6XVI5y0zhF1+FTScXGsTN/TNQw5gOI2xdMdBwuV8dbzGECPZW1nC3soS3td3Me7lcX9dh5GlEbY0RqmqKPC4In/RmqVG3oGTyjhpk6HNsFBOso8PKQzxmHYQT2gHIFFYpE/gmuC99nkFHZ1MteH0Woj5zGxwwo/sDUB45ew1mmIanTH2rD482DxqXps73Y7s5fZbO0P9smTPR5UVcMbsKuKazpMeqk35BmdkrzXRsQhJNgzGrbZB44y5DzoWBStS1RzTeG/ldusCComioiGl5IDrX+dXTy6ihFbzbMdqgIMVGV5ok8b5ZPhq/h66hTfCP3bli1o5atEuRPYMcZ3B0SudBc0LgqonZXq6WOd6f2HgaR4IXUs81kpQSRmLnYGmS9YGjI1TXIl0cPUAhiOy55zzbwn9H0eqhoP18ZGX2McrW1e2e7vkIKSs5wIFHYGOput8XX2Fe0LXM776Fdc16ZE+Y1ym2ivRkIpcNce6vt7kM5xTVXv0QacD1Vo/LDwd/pX3500aZ3lhkEOmDWNIJ1hg+YBsfWZyqM5+/bY+w35dFDbmTh2FnyZ+wCPawa7PWe2q6e71IiOQMEi2z76xNwCQS2TEkr0vDucejLU8FulUqMGIzkb2OhON2tTQRlFIpTQSYJfRpcwcU8ZDH63P+w2l0zBu7WROD6QWm46UFfMRmjQMNxdiqchTgVkHKZrQaDMN5TuDN7A48h3+EfwHE694zr62xMz9U+QgWTW6gIz8PCR62ipalkiVrLBk8tOdMl4bpPRjE694jl89tag7jztg4JJj13VPKtMdob9mHANILniQgJoSKOkMdClZHzRyXmIifyMEVuslNR1dl6xWxtvnZoulAGws3MU+VpqogVgT2TCIg8jt4r3wxdwfvJakLhkhjM31kCZ3KoWXQ8FqYwBaUiUcZvz6RRZtbOidhx3AcOfsZb/OMpwFOsXp61CWz0vzmCIEqhCDivGwcEMDB/4pM5+2gCjXrPkGAC2n3IV0mDSRtFqFLRSQkKljZcJg4zzxyUaue36JfTx9zfEjez7aRWs8yXfv+SinumytacaYlwej0MxhqSwO5/wM1mCPdmEjP5CRTnP9XeDfTGgyvLS5Ruw64+neXB9lVHmBHdo/Y04VS7Y0sWhj7mImAwVW/iG4N4CdFXAAt4z0ILP1kDoUm0baUt1Q9bru0bfsKF6BOR5b40m75s8RqkGFO0790HWvHwaeAGB82xeQaD93arDieUc+yq8D9zCt+SMKpXtunKhkKm/mkiPlJTT0n/fXZbs8r+D89dub4/z5RWPzHKLjEila/XqbWtfZvFpNl/bfp0SrzdsBbtGHf/XUIlQ9xkR9rX2uSlSTDJWyqWhXLohfyvWJrxkn2uq8bgUMbgGMbBDojBD17KcuRkps+mskvt11nZdS7CiREpSTLW6KrFXOaEdCPKlz0f0LWLqlqV0HqbU/KaUVRUjm6zu5L/BgL1iMBkUxlDoHi7F351uruPS/n3iesxwPTD4cOfVo17l0VgjAgbG/c0PiqwDsLlbycOg3nKC8x+1vpvKS45ruptsOkjHvG3u9hFe/rOaVL6tdHoNsSOciL9vaDEi+rr7C6KQhBmKN287I3Fsd1qvT5zOc+T9FtPHNwCt8f7VBxck5stcJb83mhjZGlaWoTCfNGk04oPDQ/PzbUDoL0Sd1nSc+2cDnG+pzjuw5J0HnHDhYJkQLukwJtNypHQfA21+stvMfU7lQjkXBjCO0kXLIRIgxUjg2j1sW9upzD1Tc+56xyS6lhXMDL3Lp5l9QJg3P/v8lTwFgBKl2sjY7mYp1mf1Ma4eCk/dw/JzHFqRqfFr5pEmZWsKbZWqOqpPFyMbNBM3IXqyTJQV0iW3sBWUCGvOTtm4tFdua40zVDIrm29quAKhCohUMJaAqPK/vzWo50rg4mt2JN+j6Vw6YXpHqYwdPG8Yw6gEY0rrWdZ2Xo9ViNQAIR2RvR8V/P1zHsws385NHPm13zbT2eUOEEWV+r+BgntT242ltX+OCeEuG/0U3aZyKEEyPfsre8cwaw/mI3z/7Jau2ZebEA1RijtV9L0QJptbd60+f6VmaawuVvGfmPP408BBzlaVcHHjSdU1Sk65xPlio276x10uw+MItplrfpvq2rEaXpejnRJWo5g/Bf/Pr7T8HUpuczhSwtjrsYKNxOvN/Rjg30uQe2evMAN7UEHUZe2UFQY6dMZKnPt2UV4Z0QtMZ4xB4aIomueyhzzjvnvl2Hwx41O5x38Nh7OH0fvXww/YzNCkpMukzNbIMSNXxcUGm+pIWHgKkEuoBRgvD+20ZNNTmr7JhT8Bqj7gIUaEZr7/UDWrdCFFHJQ2U0mzTrNOHqdf+yLUwu+pYJbsUsR5IsMbYOLGVQpnaOFuiPz9OXMjNyZMAuC15Ircnj+dLvYp1cjiieatNA+1s3T1dSgqkY4O1/KVu/Ir+g3M220kxjOXrQhfTJI15MBmpSOXfYs6NbdnLG+VSmH2woSSQGkNKooVJEaMsypCo4ey01L7THdFlNLOnkqJ6Bja5SwcMNgdhLvi/1ww1U03PXDMLiTJW1DCabfY8VoFh7G0NjOZHiYttQ4VYo6cjTJdGyZQfb/oJv2m9tnd/TB8gPXqpoDNVbEDF6JNDhWnsFQ1zBQHOnDOOClNAb49x5a57NFAEwDjFcD5k7CE13fW3GSwOHt/Y6yUUhozcupZYkoa2BPtd91rWULRXVKXUTB4dotdBImpvcjpDx7H66GAz9pxKSdZAteR2tRyNuFyNwnhSZ1tzjFFl7ryVM+ZU0RRN8sKivins3hO48P4FNuUQDFoYQE1TzDZa01UT0+GMiOaabJ6PsOrsJaRKgywGoDBdsMWEJiUBkgRjxiaxhBa7AG4BRhuvl8ONi3dw77aVBymQHKYbnucVcgxNsoARoo5Xwz/l4dDv7PGZTuP0jOw5rnHOj7v++kXmXvtKxvX5BClhktjEm+HLuCv0J/v4RGHMOyvlaNtYXibH8sfk1zk2fj3Vshy1Zas9njvrndZ0SaHeyjvhA4iJMGxvX7hkoMK5VuwkNtBKhFsvPJl6c0xrBcNsY2+b6dRh8VNZ77cjll5Q9dS8p0brGGpG4IsT2/l45Rb2/N3LPL9wc4ax90Toar6ipkrWTFh1P+NFar0cLJvorsBSI3birtCfeDt8Ke9GLiHYZlBey4VhWLeoRvmFZtNJQawpw1jUzXtGnDl+eb4up+/TzlFf5OXwzzlHNZxPFZaxVzg0I73nwKlDAbjsCDcF1lrPLQwRzS4RnITu/tsMFgePb+z1EizVzOaYRlPUyK948Yutntee8I+3M46VilTn05q22hNjZxYbq8Pmuxrn+tpWZv/+FTv/0Rl8Gm4uPJowjb0OBuYpyts8H/oFemtuxem3NhqG9uhytyLdPhMrGVdRyEMf5U/NvZcXu/vftubUIm45HDpyJliRvT88u5gPVzvyMQbHfGhD16GYNpopoNWkZRY4InvOcajrKTrJ5uA4FKS9eIRNY69GlpMUAWjNLu2+I8AymFWpoZgG8did9qBalvOdwAuUixZ2VtZT0GLQBjOUNj3u6UW5sTbwTdH8Vv0bntzEa+GfAjBXWUqYOM+EruS20N8B2C5L+J++D8fG/shL+hz7c9VyCMHWrak6c51wEk4cWoSmG5G9mFpCnTIEmqs7/uAAhHP/N1VsQA6dhqoqlJjra7x8ot1Xlsgqw7Btym6Q7Ij2SdBh7Il4MxW6seYKJCtXGZGqD9fUuhwKE8RmJpk5uAsi+3BV4lwA3gj/mMsCjwCdS0mx8MayGs6/d35eCILVt8bZ59pXWbghU4jGUIBMvT9Tfd2ulQlQ2WJERIdgGHuNwjD2mjBrGUY9Inu6sQ4fFH0jdTDRsWbEQEa6k2o3xWDGzDT/tWmcRUMzisxff/puvPqTgxlW4ta5qCNl7G2RBhvnysD9ju/UXW3bGeX2gQzf2OslWN0jntQ65VU9Q32dSWITxY4aX6ue/L2jtED791q9rYXrX1hCNKE5jL38juw9tmAD25pjPPKxQcNxRp9+vr/hjdVNY+/9Vdspp4nz1f/Z0RUnfh/8N9OV9Sh1q3P67s2OsgtOKIrgq3uN5b1V21m3feBOqCtrml3vnZuX7Sb9Btr3/Ds/Y72+4y13+w3GyF6xaKNJpoy9k9V37fNWjUKJEe0cZtLqtoaMKEuZaKGAKL8N3g1AmwwTVYraVfrbEWBF9hR0imQL20Nj2H/KULaai66Fr79/At9WX6Ak7nZQeAmauo0944L0Iu75iqrkGvv1dlnCWFHDTCV1zKAeCr6U412f2yqHEIrVUqbVA4a32gut8SS3zFvhOqbpkoSmU6C3EgsUUy/K8jci7egGw0QDonQ0qiIoN5X4YsN2c6wngk/Dc6D6S/sz3uUEdiw4I3tKvJkyvY4vmAxAYdQYn1Km9iYCnXnhn9ifaQkMSdEPgUsDT6CidaktP15Ty8uLt3ZJPbqv8f6qWrY0Rrnx1WUZ55ZXN1PXmlp/rw/e4TpfFLMie8Z60awYNVqb7Mheo0fOnkQimZx0jOc8X28SadoKOwljD2gJ/1SKRuJqMQTCGaykSFBl8rBiikJuBfuko7z4HUmjRqmTbpxIy9kbLNF839jrJUiHcZarZ6CYVv4UvIP7Qn90GXuT1j6C0I3JraMJ8i8vLeXWeSt55rNNtlc73/NWLCzf2oSmS9egHrPtHQCCehyk5IrHF/LLwP38MvgARyvz0+4gKRYmxSHHSdBSr0yP7AF8ZfZYFAGPfDxwo3t/fmGp672z+1iRvZJwwJV/l97HnBuebBGCwWjsldJGM4VUm4bIMepHdqTOtRhIyTBheG83RIxN0FfVNzhTnccMc2MeI0hcRCA+cB0DfYEIqQ3OSLYRV4sIBRQ2YVBuntdS0alrgvdyzcbzXZ+3+una7S22E8uLxpnu5c1XhGWKklVENOXJNtGCdw285XIMAAe3vgiAlkWQ6oYXl/GntDlC0yVSSxCSMZKBYhplEUTzUybf2QuKRRuioMzlCIgP29UVJVqjjDPyahPGvJ9u7HV3nktqOsu25tcGfJiWMvRLW9egorNIMQqql7RaAnKpdpnrKLewSh/JvIqvpCiyJqaLtS6q9vw1tTk5pa2hng8Re6ufvbrEHRWfIVZRRjNvmEXnh5ApCBRONlBIlFnKKpIo1GtGRM+O7MUy1Tx1KdF1GKY7HDN5KqxkIeHINVbQmapsAqDCbLNK0UgsXAFkqrRbGFUeYUJloUt3IW6WYCggxs3Jk5gkNhPE6FNJ3Z2z50f2fLQLq38kNZlV+TG9c04VxsAcQrNNM/l94uuoQlIZNzwaHRl71iT4s0c/58L7jXIE+Z6zJ8wl+/lFW7jn3TX2JDqMOlht5ASoaBCtB0ARRhsdprhzJKcJh1EWy61swqZ6Y7M1siyz1tSosgIO2mkYj368YcB6fJ3eQ3AvylbOXkkk4PISpm9wnO+zRQgG6M/vMiwaZxMFxAjx58QZANwdNPKmrEiowEi2tyJ7S4vmAnBJ4EmuCd5r3y9KyChOnfBWFdtRYNU2AtiFlUTVYoKqwue6UdPtM30ya/Xh9jVFujsyrUtjDjz4z/O4+AFjfnNSt9NpnPmOsBlVuS95BBGRYJRwy93LLEv4S/psAOa0GSkC2UrN1DRn5qFquiSsGX+nZLCENhmEZH7K5CuOflBCG2qk1O0ICJW42ma1GAtIW0gpvd26O8/PW1rDUX97k/dXbe/44gGC05PP2q+PSbwKwKfqTDRUylrXAO4NcVgY60qLUsJh8b9SWzSFRstIMVEpmuyx+v6q7Xzltve4ZV7HeaHWWG+Mdlx6pL9hCja7nNNDaOR/4au4OXij/ftHmGvHA8lD7evCiQbuCP6Fk9T3aKaIpdXGPNjsiOxl5uyZKtJ6Cw0Bw3nGNnctxHyDs199e2edEAliMkiFGfGspJFkQSWQys89frdRrnsEVYV5PzuUI6aPAGBocZhzEpcDsFRWsUwfS1BoTDDzSZOadEXz8oEynAt8Y6+XYHWWuKZzzN/f8rwmqLib31ILa6DIjuwt0KcCMDy6hqdCV/GzVu8CuvY91cw/ab7TOJ3YUNdGaYERht9ZMYy3twP7GCfNOj4xaZwvFO4NijVBAIgcPdWbG9ooiQSyFrM/Y3YVmxuivLl8YNKcQgF3f3BOYttbjI1ecSTgWjgyjb1Mmlw6BsuEaEGXkhLRatNmtmJE9/ZVFwOpTd/jn2zklnkrGIbRnzZHJrNQn+B5z61Rlbr6es9zc/7wCn94dnEP/oKBgbqWOBMuT20WJ4tN9usICeKBIoKqwv3aERwTu447teM4Kv4n900c+bVSpig2r3xpeMzdapxmMWLHfv6Pz6doefmGsKnAuVkaG5pJilGv8Pz4j5kTvdl17UWHTrZfa6isqDyUSfFlfB4+j+I67xJA6ayPO4J/4Wdtf6Ol0WhzLVRMqwzaka58gwDOVl9lTeRsSkUrgaJyFEWwTDcinzJc4op6Vsty44VJW02f73Qp+da/P+Scf7traeYKq4buza+v6ODKgYMEqULUu4o1ALylzKVWFhNOGPOes52uDtwHwM3j/w8wFJ7TnRKVNNjtbrXJ4k0dr8nW+tXYlg/GnvGbCxzFva09yAHqF4zXjNIVlsjce/qu9nUFyQb2V78ADMaXhVTOXkNGlNnKAyyUrWyNTDIONgxc1lEucKrPVyUN9ddPmEaJuT+uEI2UVaaMu09+dSR/P3N3z3sNNWtUVxQFeU/flTnRm3lZn81yadTRtSiiCU13ORAHiyPbN/Z6Abou7eK3LR4F0i0EVLf3+Sz1NQASUuVIdQE6Cquk0ZFHtS1jlrKKo5Lz2v3uUCDToz2YjL3SggCRgDF5WqH8LwLGJFlbayzQliz5CeoHHKJ8an/WKbARasgtZ29TfZTRHlE9C0dMH0FFUYhH5g/MSTXd+HdOXM1mFDgcUF00zvT8PeeEm+7pniFWcaH65KCZEC3oUtoCLQCPawcCqQLrTo/jJ+vqGSbq0UJl6GqENVa9Lgw5/J8mvs8SWUUbYWpq6zy/r6YplpEHORiQTlkbK2pokCkvf0wtIqgKNFSWyHGUFhUSI+S+yReP2y8t77UTLhpnMrMj3v5G/pa7sGicTSEj2jlZGMbe6/ru1ODOc3SyD8IBhdXFuwNQKtoYuv0jz/un1987Uv2Y09W3bLXP1sIxtOj5G9mbwCauDf7Lfq/s+S1URfD1+JV8P34ZBCIutkK1bghhsPxlIFOwSpeSN5fV2BS8zsKaZ99avs1TuGMgQpEaa3QjKlIsotSUz6K4IESzKCacMNZgaz78z05vM0XZBGXj2F442XWf8+I/4d/JYwD4a+g2yuoN55a1RsVz0DbQ8ymyZ3qcnM7TUofhNk03IpnDTWPvEzmVyxPfBaAwmWIeBdA4aKdhADRRYJQO2L4yS+kFSaFspSVYQR0l0JDfNE7nOjs2YayPC8VUwiLBJ+HvGfoLxcPsa4YUhTwDHgAXHDKZ60+fySl7GI4ea/7cZDrSbg79HzcFbyQZj2WkaQwG+MZeL2Dx5kbmrzUGcHuJxOlm2Rhh1f2oZw9lBW3BcuopJiYDTI06ijG3U/TVq6PnPY3T0VBBVWFchbFZ3GOEEW3brhiD9c5XPgew86cA7nbIlVt10jQpiNTlRm/Y3NDGKI98PQuhgMKpe4zh5cVb2e5BiepvfLnZ3VecHiurbyrCraaZnhRd3ZTa6KXTmP4XvoqfBx9G1wZ+DkVnkIrsGX1NR+GB5GEMNftWeg7UMFGPVjgMIQR3mRsagDVyBI9qBwOCbbKU8uSOpcbpjCyPKA0zWtTabAWARKDYVi4GOH6m4dy6OnEOb2i7GQc3f26fl8gMYQLnhsDqn4NkfSYsY2gojKwyPPUnqO+zVZa7RAYshBzOw8KQyhJtrP2+pNnb4HU6cqycFYCdheFFby6dSqseQOapsXeyfN1+/bfE6VBehSoENQzhRX0OihCuvKC1mrlxbDQi0Fsa3L+7uwWWrX6pCLj1jfyI7inoLhpmU8kU9ho/hEaKCJlGiTHuJPut/6dx0am3ETDHtTU8X9X34m/Jr9j3mbLhCSBlAOeiGGtd0tg28Ncbi7gV13TKaOY89TlmK6l8RktkZISpKF4ty/mvdhgL9CkUaI3UyFL72l1HW68FK6iCL5/J+D4prfqYhrDSViph1esZ1+UTrD4h0Jlb+zSUj6NWMXL0hphlKZh2bE73CgUUzpwzLqOWsFV3D4wAgVz+smtNGSyObN/Y6wVsbvBaGCXpwuHOKIlAZ5hoJEaIsDC8VktHHA8IquUQJiUcC0PjJrIhNAiNPSesXJxdR5fy7T2MCbBWNYy9aIux8FiRvXQUmLLvi+V4ws1rc/q+7c1xhhWH273mjNlVJDTJE58MPC9ael+UHsaeLt3H06N362vbHOey0DjzXPUrHbo0BDGKSlIL7iZZSaVogkRbRtL2BLEVrXgkioAFcid+EP8RAB/o0+1rVsrRDE1uBm3ge6V7Ck7nU5gkE8QWNshhvFNg5KdEA6Wua0aXG9Gpe7WjOSdxOUuVyS6RAWtD44Tu4YUdLN7YsIwSExGaQ6k8xk1yqOe1zi5ZGArwrxUpifGyZu98KGcrFTjqc+2lLKNeFiELK2mTIUjkp7HXakaJ/508hhu10wF3PqcQqYLzJeEALboKVXvba+xXbnvPvjZCrNv9yvr48buN5vlFW1hR3dz+BwYAFKnRIlNR48aSKQRVhXrckb1KGlFkEo65Hibsz9yJxqZ82shUP4yRqvNa1GaMa6tNcinFkI+RPSnh5fDP+VXwP/wy+IB93sq/rRI11Mli4mbb1MkSirRGIhi/8Xl9b1e5qc2yElq3UdC0xvV9mm7kmhXoLcTVIpJShbo1kHTn7ecTrMj63soSyhI1UDGZNpEyzjapo3M29iykq3amU4zXvvNwWmmlwbGW+MZeL8BLGuCO4F/4KHyB/V5KSVzTuejQyQwtDvMD9X8ALAtMs69ZPcqQhd3KEAod6pw0bsj63cFA5p803+vsOaEIIzqlKgI+fRCABqUcgLq6WtNo9qbHWJG9bbIMJUdPdVKXBLLQAixMG1nCrKpyHp6/fkDnrhUEVdfE1Ro3vKOGZHMK6R5Wp8CQ28hxvM5R8CZfoEuJis5u44byh1NnACm6Bw0bXB7+UWxnV2UtWuk4eyF5QZ/L1Oi9rJapfIIaWY6CdOWgpWPC5c/y1KcDz2nQVTjX1Sfj51MoYlTLcmORBhoKJ7iMvfSaSJtlpYuK5GXsJT2MvYEqmNRZhGWUuFJAcyRFDb6p8Aee1zrbpSisUk8JM6N38ph2IBXNKz3Dnc5amQUOpdTJYhNNspBIUCVKCJFsM1SL8gwBaWyYf5v8pn3MaewpQtBg5n8NKw0TS2hQWAnr33cp5x6tfMiSyLnoK1/r1vNYf4Hv7D+BcEDh9jcGfrF6Fc2Vt1dfMpVwQKFeLyRsRvaSmp4SDyozaHIn7z6Gz685imN2Tc2BcUdEOpg0HIRWt+wUjTMPcvacaTrpDuglehVjhMHyODMwjxpZxp++YjAZ6iliQnIlJaKNu5NHcUH8EpeBcrd2HAAlDe6SDrqUhGQUFZ2EWszT8gDjRB6vzZbj2RbXO+UWomrK2Bv583TF9Y7hJd41JZoSU5ugbPFcU/Id/WLsCSEuE0J8IYRYJIR4UAgREUJUCCFeFkIsN/8d0vGd8gdHqgsYJhptr77ViQsDkj/pN/CL4H8BuKHsCvszepHhwd1qJY1baIeH7SVCF83z0gvOn2TVQCmSbVC7EsbMJqoYFJMiEaWCJgJovCT2S31ISvZXFvKb4D0A1FKCouVGudR0nQ5sPQDOnF3Fsq3NfDaA8zB2HlWCcz215rMvNjWy1lErMP03eNUxAxiFw2hph1qcj9B0SVBooKRyRFdJw0Bh2zLXYmDRr9tG74NTcymRRrXbbtFyOqhZ9uQAjBB3FVbfqaTBzrFtJcKTkVP5UfxC1o480mXsDS125+utTgxBNm7A2iZb8uJOOBfjwRbZi+gxYiKCCKao5JsY4Xmt05FTaNaWaqKQhfpEIskG+PR+z8/ZnxGpOXGyspk2QkSCSkoBMG5Eoe57bw33vLumKz+nzxGWcdqEUYuwMGSMY+caaUT2jPVxREmElrjGDctMKmeNIWozRyzhdrOIfah6Ubeex3IGDi0O87U543jik41sqh/Y4jeq1EAofC1+FZfFL2DzkNmEAgp1ehGl0U3cFLyR4vg2RlvGXukY+7OlkSAlEec8mGr8YMLoT1avtSjFSU3nR//9xLNEhTWfNOZB6QXhMNA+0afYr18IHclyOYa5yhLuD/4BgPn6NIKmcVgvSwynILBA3wkQrnstM9ehksbl/CpwH/spi/h14B52jn5GRDfW8XiwmHppGkV5bOxZauKjxHaSIgQlo4gpKWNPCRdl+2hWeBl7Tlr8cOrRdMkuYg33Bv9IpGVwrMd9buwJIcYAlwCzpZQzABX4GnA58KqUcirwqvk+L5G+0TjEUQJANhsKchZlYXzjAg7TDarIiuI9aQ4M4QfxH3F/8nD0QmPRsep8GaH+ACx+Kut3C4+4Yr7TOJ3RgYSmk9Qkk+Ua48D0E4iZxl4xbRyifAbAmwGHsRdv4bvqc/bbRlmEokV5b+V21te2X/dM0yUBpeNhcuKsUUSCCg99NLCEWkIBhfFiC78O3MPU2OKMyOMssYJpYh3/ejslDnLJg5+4rnEae06Kp5VYDqDkuepXOqSl6qgE7Gj5ZmnQkmiuduXslQhjs9ZaMsG1KKfDVlKLt0/dau8e+QbLKLY823WymIe0Q3hnQ5wn9QNQg2GXqFRFkdvYWyeHI2JNDDUNRV1Klle7N4HOKKvVVbOVGsg3hIkSUyKuOahBN/rRxYdOcV3rDGYWhVORmFf0vYwXK15t97uqhLseWCthSiPBVE6LWdrmyU83ccOLS/NC+CskY+hqhO/sP5EXf3QQ4B5fQgiuP303zjtgInMmGOvsy1GTel23BoCj1ZS4TbHonmHm7JXnH2TkYd7x1sAWEFLR0YXK+/ouPKEfSBKFoKpQK41C3yeoH3BK7b9s6XqGTHB9viiLkvWwtlV8uq7OXpOsPdGyrc08+emmjHUI8iuy51xqrbXyBW0O2+b8lNVyJEUixv7qF7yr7cKt2om2emejQ8BqvTT2gE77pFkPw5AJDK1dwHmB53kgdC3nBl7kN3W/oMAsVZMIFNFoOWny2BFba5aHGiHqaApWghDEAsUdfKp9OMe/s0zD5Ynvsl4fRqVoRNMl31Jf4iB1IUO3dU15d6Chv2icAaBACBEACoFNwMnAPeb5e4BT+ufRug9r0a2kgd3FCu4O/dk+11CzwaBwml6siXXv2OcSSgGqELygz+WXyfMIBY1JcqOZozFENNMmQ8gtKcGCXJDUZU58+IGOcppIJnWSuk4pZr2uiQcRFxF0FIpElFNVo8zFuuBEfpr4vnFNSw31OPMGQihalLPueJ8D/9R+ArMuMzneXiiJBDlu5iie+WzTgCpiL6Xk1dBPjcWg4aoMettT4at5Mdy+X8XpvGhwLLLOjY+6zVvaPV8hrbw6RbWFL9owKYaJVtuICRO36TiVQ4d5RtYtxM2SICQHnpBPb8HqbyWmCt3FiR/S7BB7CKoKITVlmIwsdYshrTS92BNNFcpYUnflUUFaZK8d+mZC01mypZEvNxv/bxuAgkrpCMk4SREioAoeSB7KEr2Kiw/fCYAfHOJWO9R0yfjKQk6aNZqCYGqDvUEOY0loBjRvdV2f3lZzHOIRAEPKyqksDtFgRQja6u3vaYoleT2tWPRARJg4SSXM1SfuQlVFYcZ5RcD4yiJ+dcIuNl3fKnNh5Yo6axsWx3uuPt6Y8gJO3n0M//1wPbUtAzOvSkqJioYUqf6k65JQQGE7qXzmQr2ZKlFDIlQOhRWue6SX/3EylX5+60P2fsmaKyz6oxcV2/Kx5UPOnmXEDqOOkdTyf8lT+EHiMvTikak+BjxZdTlFI6bYOX5NjvnRWnOO2sWgcR8xfQS6hMSQyQzf9kHGd1qRvUSghEbdnEvzOJ++oS1BIVGmi3U0BY19cIta1q17OutsXuiYQ/+rHcaD2mEUiyhavJViq3SXPnD2c91Bnxt7UsqNwA3AOmAz0CClfAkYIaXcbF6zGRie/S4DG1JKBDpvhy/lyfDVrnOP3v03/vX2atv4GtKSiqiMa/mCoMPLbe1hHtYOBuBDfRr/0Y5AttR2On8iH7yw7WGc2Mqnke8zc/MjJDSZMvYiRt2kqIhQTBsjRD3zI/uyJVjFNpM2t279WmIylRgeJYiqJxDkov4lc6JxgkHlbI4leW7h5k7/vt6CpksCwvidBURzUpbaeWRJ2j1Sr1dvSxXFLnHkkQZr3RvFfIdmqYsqqu1xbbWMvXirvRF5O3wpvw/eBUBx+Yh2HQNWAj5aWqH7tD/K4InrpaJulmOgSbo33EFVcc15pQVB1lx3vP3ecnRZG+5v3pm5wXGpcbZD37zhpaUc8/e3OPZG4//D//LGgE++F0gkgoAiuDJ5PsfEr+esuVWsue54isMB1lx3PN/Z3yhIr0vJGz87lP87a4806hxsF0MyjL30tqoS1dTKlFNs9LBKRpUV0GhH9hrs7wF46tPsQmEDBWEZI6lkV1N2MmEsR00jhTTLiJ0uMUrU8pY2g0X6BEqS3TT2zCa3pokLDplENKlx9zurs3+mH6FLI2dPKimHjKZLQqpir68AUigUiiha0JtW99pPDrZf7x27hdNi1wAwWmzDahTLOLJodukiWOAoqp4HapwSOExZwEeRi1CFZIVZ2zESVF3G3p++fQQv/Ogge5/RREoMp5Uwo8oi7DK6lDXXHc9uYw1D58llCRSP/UuhbqzPiWBxKrKXxzTOuKZzV+hP7KysNyJ7QH3QMA1WBSa399GscO7ndh1dxr6TUn8Ly4GhtG4nYmo8qMn22V/5gv6gcQ7BiOJNBEYDRUKIb3Ti898TQswXQsyvqRmYhax1CWPEdgpEprfuu4HnWfH5OzxrGgTlLStYEzAW6yKt3mXDWQZhI8WcHPstF8UvpVaWoqDZlJpckc9UTiGEHT2ZWfM/EqaUMQAFQwioCm2igLPVV5mqbKRVKSYUUKg1F6PWumpb4RQgKg2qWJiOvYOalCjthWscmDuxggmVhTzUzzX3HvxwHd++60OklOgS3tRm2ufCsW0MpYFHQ9cwXaQUSXcxi+UCHLqz28/i3BQ6pdpLhDEJLtfHENhuGHtXP7WI657P/yiftLx5SsCWak4SIC5V5i1aw73vGW1niQG1qiVQVNmBsWdF9tLk3Ae4wdEdpEf2mh0bGTC8/i7FzrQogLUpsvKBNnkoHbtqIrXjv9lcH2V4SZjbvrEnZ82toqEtQW3rwIyoWBBSIoXiEolKp/la05Mzwjm+0m1UV8sh0JRm7KX1uxLa2CodqfJFQ5k4tIhG6aZxWt/z2tJqV6R/ICJMnKSaXU3Znb9nvRFslpVIk5o+StSyRVZQLcspTWYXV8oFlhSW9V1Thpdw9C4jufvdNTQNwGiVphtCVc7IXjCgEAwovKHPso/piZgh8BP0rkmbXhLKErv6v+BNtlPb6o7WHJr0GMx2UfUB2Fbp0HXJbCUlolJDOQCThhalxL4AQsb4spyKTofYgxcexvOXHmi/twxhZ1TViSKTxpkMlKQihHkc2UskdfZWjP2EYq7JoYDCIbG/8NuK67t0z/bWaDuvvrWGiClYpSZbsl6fT+gPGucRwGopZY2UMgE8DuwHbBVCjAIw//XkiEgp/ymlnC2lnD1s2DCvS/odupSUkxpgX+rjuCN5nP3+nIbb+c0ziymlhcJoNR8VHGCf2+hI1j559zGcZhaA/ExOoYbyVL2bLAM4mzBBNJ6/NE5VEXYx0sJEHUlNUixNYy9SRkhVaKGAsDC8fWVaHUFVsQduYbLWNuwuil9ie6rL6HgQ67p0hf3bgxCCr86u4sPVta4IWF/jiscXMm9pDa8vrQYkB6mpGo0j6z/lVPUtZivLeCj0O/v4X4K32q/jSZ2aphj3vW8YNFJK5ogl/DpwDyWt6+zrrCL1q+Qo1FbDGL/3vbXclgcKcx3CFdlL/f2jhFm9uYZColwZSAleVJfOTL+D8XFH17Flx9NonINFTMQL1oZtvJkPdtohc9l/SmqjE1IVV7kYaxP8wHf35tLDp9JKhFighP2ULzhVecvzO5zRuXveW5P1WZpjSYaXhjlmxigOmmqsHVsbB3ZJAYGORBBsx+Fk9U+n7bbnOLe+2bKWQog3QTw1L6Ube4XEUlE8QJgCYWqReS+bxmnUTIwndV78Ykunf1NfQdclEeJoSnZjz2k4OzeBa+RI5LblFNHGKFHLajmSallOmda9yJ411J1/zQsPnUxjNMkDH6zz/Ex/QtMlgbTI3pmzqwirClFS7RpKNlFIDDXsnU+V7sSpNgtal4o2O49ROkSYADSPvFstn3L2gBaZiipbTpOxQwpZIcdwa/JEfj/i7/Z5axr8UN/ZPjZm9FjKC0OOa4ye84SW2jM6MTNpCAglA0UpYaU8ztlzph9FNGPPG1AU1shRxAIl2T7WLrwEWixYeahq23ZKTWd2wI/sdRnrgH2EEIXCmGkPB74EngbOMa85B8iuQjLAoUtJyCxQe078Fxwbv44/JL9hUxdWh43yCnsqRmHvdZFpLNIn8Mz4K2zFMDDC/T8+aifXvdtkKm/I+7u9nymazN/IXl1rnEphTFhBPUpC1xmbWAOhYlBUAqpw1e95vPQbhrFner+atm8mRILP9Yk8q+9jG4FDRceToF3mIUd8Za+xKAIe6efoHsB37p7PuDTRheLoZlvpy5rMICUCNEWtRk/EuOTBT/jVk4tYVdOMpku+F/gf5wZeZOfqlNCNJdVeLctR4vnrPfSCXSTeEdkD2C5LOFL9mOPUD/he4Fn7+Lbh+wCZRZgvOXwq5YVBhpeEU5G9NBrnYCkT4AXrt+2kbKAxMoaLj55FSTg1VoOqkpHTA7DflKGcu/8EAGqDIzlIXcjfQrdSJbZmXJtwtN/LizPPW2iKJuzvHm7mBlY3Dvy8PYlot/yLZbA4+9GsseWua6rNPKnqzWtpiRl9O53GuauyBk1xCOSUGKqfUcXcwJs0Tikls8aWM76ykKcHMJVzW3OMiEiQVNuhcTqmduc0v0yOQdSuZI4VVRg+nRrKKdUbPOlzucJqcef37ja2nAOmDOXOt1cPuHQLTUpUoSMVY+4aU15AKJAasx8GZgMQ0VooEDHULOqI6WNcd2w9ddMhZEf4zH7sxXiwDuWDGqcupatkhSV0VBRW0VG4PnkWawpn2OetyF4tpTyl7ccr6oGguunYluN5qRzn+Z1zkh8D8MHmRIpF0YEg2ECGsxzHSyPPB1LlxZylLToDaz9njXdn4altGDTZUN1yOxgQ8CN7XYOU8gPgUWABsNB8hn8C1wFHCiGWA0ea7/MSUkIQY9J21pVZIKcSl6pNiThRNYQGNkemcEL8Wj4bdlLGxi9dCdKZN+T93d4bx4EkGtJZrN3Wasu260IlqUl2av3EpowEFIWpupHzcFfyaJaHphNUBVHCtMow7y5cRpiEnTNleW/KRfsGipQSmaNAi4URpREOnTacRz/ekFGvrj8wSbjzB1WtLUNRbr6+E0NEE0No5JXgjzh6w99twYC4pqPpkmKz4HIomVo4LJqDUbewNRUNGwSwaJxCCbiM/S/kRMaKbdwQvN0+tnf0JtbvfB4ArWmbtT3HDeHTq4/i7L3HETPpw+mRvfRNzSAS47R/22Sxkboig64eDqbmtFBAyfD6WygvDFFWEKQmPN4+9lb4Mtc1UkqXMmp7aIomKTZz2UaUGvNoPkT2EMLlcEjHXuMNR82MMSnhgtIC9yax2qSQXXTb83zVFLhxRk5GUEupaGU/UuJfcurRAMQDRegIm8Zp5DELTp41mndXbqN6gLbh3GtfpYAYWjvGnpIlsrdMH4vQk/w08AgAZ550PNtkOSo6lXQ9UpKK7Ln/nhceMpmaphiPLcheQ7c/oGlGZA9hGC1WE1m0zF9EfsVj2oEUizaKRRQlS2QvncYJ8NfEVwAYss2olWa1jeWE8BZoSUX2BnJNWzB+T5GjnIlVCsHZFs61xTkPXpq4mGsLfppxz44cz6Ol4exqlgX23lNPDMzxmQuScaP9bkh8lRURgz1jsRw644R3whrnBUGjTx+0U4ohWCONObR83atEhEXj9CN7XYaU8tdSyp2llDOklN+UUsaklNullIdLKaea/3aPHN+fSLbxUNigyCWk6jghaKGAA1peBIycsVighNaIkSOlKsKmMPztzFn2MSdSioBub8PBf36d655fkjVKkM85e2Vta/lp0Fh0g3obarKVIr0JZpwO4JJu3yIrGF4StifUFsIUESUsErZIi2UwO4sIe8Fqy85OKl+dXUV1U4w3l/d/TqlTSS6JQkCLuoRVNspKNsqhFNPGb4N3A7DP9iftRV3TJbqUFJrKVEEt1e8KRJwYIQe1OH/pIhmw1DiF6vIgXp74Lkv0Kvv9cbFr2UoFxWbEKJ1uZ21cLjlsqiNnL43GOcgie2u3tzDh8mf5fEO9/dtGi+00RQxlTSctujQSIBJUPe8DEFAEzWnqa2HHuI0ldVfphfbQHEvawiVW8fatAzyyZwi0KO16sY/cZQQfXHk4Bzs2LUIIvr3fBMBoYyuyN0zUs3izWQjb0e+Gisz6oEqxcT9VVWlTiu3InpXHfNLuY9AlPPP5wBGkSkeHNE7na1dkzxjjM5Q11BdNpGriNLYLQ2XyP6FruTX4ty49Typnz31838mVzKoq5/Y3Vg0IJ6EFzVTjRHE7D6xIXVtco1EWUkIrlaIJTOpvOryi95bwXGmDke9tGW/WeI57tIPmiPoN9D2NlKlcZUjlKzudCk5nfnobeWkFtLcXsdhNMREhEAggUYjJIMksgYF8gJow5qoGiuw8TWsubM8B1h5sY89k0VkCVwBtRFgUmEGobYud+uNH9nxkRbgtRSWKO+iFAMvlGMJ6GyApoZX6gvG0xIxJa1RZxPZujS6zolbuDt0qvSN7a7e3ctsbK1lW7R2yH+gTY3uY3vqx/TqitzFBW2O8mWDw1gOKwmnJa/mftjefjz2L3586k1jCWCjaZJiIiBuGtTUZmv9GOjL2ZNeMvcOnD2docWhA1NyzjL3jY9cSJUJAa3XRN5frY2mVYYpElCqRMk5XbzE+9+QnG9F0KDIjezvVzrOviRAjLkJsMGsBUTuw60V1BroV2VMDNr0GoJlC7taOtt8vlhMAKDZrSaUv2Fb0RFEEhSUVBn2p1Z33056CZD7CkuR/9OMNJHXJTLGKMtFKU8hwajnzpMoLQ1kje2C0W5Nw52YMM2v2gbHZzFZT7wTlPY5QUnNHUzRJifl3CgdUKopCVDcNbK+3kJYcfftL9YjSzOjVL47ZmT+eNpN3rzicGtPYG+5oO2eu6NdUowTNe7v+2j6mRAwjO6gqtCrFds6exXaYMryYGWNKefrTgVt0OCwSRAllPZ8tsrdKpupvNYw7CoD1wpC/n6Zs4FhH7b10bGmI8ucXl3g6cbxy9sAYExceMpl1ta22eNtAQFLXCaKhK8aaaTWRNc9FkxrNFFBMGxU0ZDX2vDbmWxmCJgWhqDEfWq1l9csmD6qms896nR9I0KWk2OFY/dNXZnHnt2a79hPO16G0Me617XAagEfE/sS34r+w328yBezb1GJ7vogSRIt1rzZkf6GhNcGLHxuOgEZZSH2rYXxZjvyuRvasZracjOlR50/VmRQ0raVcGEZeUMvP9kuHb+z1AoKxlJc0gdsj9j9tHyIyymk7hSgRrQypqODUPcYwa2wZB+00zJ7MwmZHTPfutGIu6lly9j5bX+95PJbHxl6dcCtP7aYvNl4MM4rfBlWFBckJXJy4lNPnTqY4HOC9VcYC0kqEQmIuY89a/DtS47TYYZ2hcVrPc9qeY3n1y2pqmvo3cjBa1LJJVvCFnEAbYSOyJ1Ib3HVyuN1GFQ56UpWoZi+xlDveWo0uJUXmZwq0JtvDHyFOXERYanrBG9Z1rv7jQIbUvXP2AJ7W9uN9fTo3Jk+1j1kRo8uPTSXXTx5WxH4OMRKhBmgOlEOzW9Qilkz3YOc3j9My5qQ0fttjIcuAMA1fx88rKwi2W0ReEfBFnbFM1Vi5to5+2pbQSOo6O4t1zBBuZ8NNoX9wZ+gvTBPrkFLSHEvROAGGl4TzI7InlHYFWrKhIKRy1txxFIcDDBs+kqiIMN6R8+iM7M1Q1gCwcXTKkSFMJ0dQVWhRit00TvNxTp41hs82NPSrIFV7iBCnUQtmPS8cOyC3mFKIz0acyif6FAoOuACAdcoYNOeWSfNeP37yyKfc/PpKPvFYi+0W9/hzHjl9BFOHF3PrvJUDhqKo6xAiiVTdBnPQ7ADRhEazLEAVpk5B6RjP+3iNcYlCE4UEzeiNlMb9Pl5bl/15HO0y0EVaJCnF6tuSJ3L0riM5YpcRrn7mXFsiwXRjL7PNnNevkGN506GIaonexJRCmz0RI4SWyE9j5cZXU3lzE8aM5jcn7wqkjLP0FKdcYTkqshmNXypTXO9V39jzkQ2BeMrYi6cZe5aU+IRgHUOUKKHCMk7ZYwxPXXwAk4YVc/xuhkdxuEkzSt9oOgs7dwb5HNkLaMaG7N6IUaFjur7SiJAMmQCkFh7wbq9CooSJpyJ7Zu5UxKM0hhOpyF7nn/mM2WNJ6pInP+lfr/dYUcMms1ZZK2ECWhvFjsjefH0aLWYbDRWN1KiGKMM/g3/lsfBvmCw2EktoFBG1RVxY9Bhg0DjjIsR6OQxdjfDIcy/17Y/rRVjGnlDUjEW3lQhfi/+KvyW/ah+zjL3xlUWUmq8f/v6+FIZS419RoFGtyJDAv3Xeil75Df0Fq7kkkrZ4ktVmlGRT2V6AexNTVpB9Iw4GzbImalxvlVKpdFAOowmNpC55OPQb/he+Cms7bdVIAngo9DvaEhqaLimJpL5vRGlk4Ef2kIDodgF4RQ2wTqliD2W5LTDijDwV0cb6kUeih0r5TJ9ETDqk9lVBiyhK0Tj1VDmaE2aNQggGrFBLATEaEtlpws6RPXuCuxj4QyN/wneD1zF8jEHz0pUQqkOcRW/e5nnPRNKiI3rQMc01JT1nDwzH7gWHTGbJliZeGyAF643IXhIU9zi1ovHRhO4qAs7w6Z26f6MsJGAZe0iufHwhv3lmcdbrnWkqA738ghXZW6BP4brkWfbeRAjBDw42asS5I3vufupl7LWnDF5rCtLF1CLbKI7KIDKen8aKRNospMtOnMPOI43fZ+33uhrZsyJ62ZpygXD3YVUb2A7BXOEbe70BPUUvcEb2jp0x0q6vUhLdSgktUOCWyP7pUdP49OojGV1u0DidHfpb+46nzRJ5cNA4c/ECtuVx6YWAbmzI6oIGXXAE20gqYVupKlvCM0CLDFMs2giLBHHZSRqnbkUiOj+pTBlewp7jynlo/vp+9dJOFhtZoRu5Um0yjJpspVS08Y7Yg92jt7PXCeejhIpRhaRQxNgeNjyzkxQj+vRq+GfUb1lFEW08LczCuDVG7aACYuiBAiQKtYUTmSoGLp2r09BSdfacal3ZYNE4ITvlThGCxkBlRnHrfCgQ3BlYo0VK0FpqmaYYohObS3cDDKPXgtObnW3xluYdLRXdCoewki6NTXWpKTpUYZa8OU19276mXLTQbFK+nH+nEaXhAS/QAhIpBK3dFNgKqoLlVLG7sorbg38F3JG9QhEjGShCUQSnxn/LLrG77HMBVaFJOGmc0p4TR5UVsPfECp76dOOAiUalYJReCIYLs17hnNtnjCnjquNTG73Xl1QzpCgV0QoogkWkCjnLJf/zvGd7RcG91DidOHHWaMaUF3DLAInuaZpGUGhgRvYsIzUcSBkmTZbEP9hsm1zRQBHBhDFmpYTPNtS3e70uU2030OdNaTJirBIIzvnNMlicubiZOXuZ92yv5m+NbsyPUSVl7MUIoedpZC8cUO2SW0TK7eMBO7LXNWPPcsBm29c1JN05vgHdN/Z8ZIPD2PvHN+bar/925u52ZK8kUU0pza5ODIbXx1lXxdmhv3fQpJQap0OgJZeizPkc2bM40xuCkwDYmbWGsWfCOWEG04QMNsmh7KmsYLSo9aBx5mbsdXVSOXNOFSuqm1mwrr5Ln+8+JENoZsToKo6dMZJWwoSSzezKKpoppJ4SQgEFLZBarOvDYzPu0rxkHqqQbE9E+FSfhF69mNJIgLKAxvCKcgCawiMZKfJXUykdVmRPUVVy2XM56YGW1zt9XKpC0OBh7O08yp2TlvdqnBaNE1BaUr811RzCcanx+qmL9uftXxzqeTuLOrcFI/IyjAb+HLiNO4J/gUSrS6ClQjRyZeB+Tlbfcd3DkmoviTiNvQg1TbEBXfpCMQVauvuMqiL4u/YVElJlumLUc3OqmBbTRjJQSEAR6ChoDsn4kKrQRFGKxindtUdP2X0Mq7a1sGjjwBJoKguBKiQH7VKV9Zr0sfaNfVLKr5sboq5SSIoiuEy7lMviBq1TblvueU9rPfI09rLk7FkIqgrfP3gSH6+t48PV/T+ftrQZa28g5N4AOyPya+WI1IniztU+bpRFBOOm0rakw7lWgp13O9Aje1IatSut1BunsWdR98eUp9be9G2GVxTPay+yf/RGjo/9gRrNUEJNKhF7vkgQQCbd7bSxvo3v3P0RVz25kAc+WMdn6+sHXMkPMES0ysy8OSIpkS6rDboa2bPWZ69PH7/bKBKOPtgoC1F9Y89HNghzo/i5PpERo1NKP+GAQi0lxNQiRrWtIEQiI7KXDleYP6DwtX3NunuOyF4iB/WugTiYc8HG+jbammrRUNgUnkiMEAUi7qoH5Y7sGa8tL5mz/p71WlOCRNViRgu3UEY6uqrGaeH43UZTGFL7rebeQcrnBIROSWkF4yuLaJVhxrV+AcBGYSzQAUUQV1Ke7zUle/KsNpel+liOj/0BTQr2V43PtBBmuT4WbYtBsxlZKFFNr3lToNIlnJHvsEovoKhZi55PGV7MybuP5oeHTXF5uu87by7nHzjRpmJbEAIalCHQXA16ajwOdKGBrqKhNcFj7xtR4Je1veyNnDWcJg1N1eSaVVXOqLKC9FsARo7kA8lDuSV4Li0yzBixja8G3uRI9WMCdat5a0WKTjdMNPC9wLPsbdZHs9AcyzT2hpeE0SVs7yZFsjch0AHR7fk7oAiWR8u5Wzvajn46l41ComiBQs/IgaIImoVDjVN3RxiOnTGKoCp4aoAJtSiaWS6mwLscAGR69yNBlX+dM9t+71xbAopglTaMJ/QDWaqPRTZ4l0mwNqNeJUGsaF17eapnzK5iaHGIW+atzHpNX6G52dhnhEKGwWI9doUj4vmlHM/j2gHcM+H6du919Qm78KfTd3Mda6SQYNKK1Musc60FKSWlpqE50HP2dAnFoo0Wy9hz/M3rWw1Hc2Vxao0YVhLmuwek9otefcRrfG5kGF/IiWw3a8SpJGxHQxIllX9u4pN1dby2pJpH5m/gyicWcvLN77DL1S9w5F/f4NL/fsLtb6zkreU1/T4vRhMaRygfGzUeHcI/1n6sq3X2UutQ5ucri0IunYXP9Ym+seejHZiD67LEhRSEQzY/WwiBIgTbCyYyuc0Usygob/dWzgGvCoGiqoYiZzwV2bNyBLLfI3+NveNufItKGmhRy1ACITarhiKas3aSZ86eR5MkTW+1qihsD1dlFBwHo53iptfNWnjao060h+JwgONnjuKZzzbZhYz7EveGjMVXNG2iOKzSKkMEMJ7jFbEfYBjFcTW1yW4uGM1FiR9x6y7/4Qs5kbVyBKerbwFGztQyOZZgWw0lspmSxDaUYCFBVdAQGEKFaDbyOwYBpLlRE0Jk9TbPGlvOjV/bg58cNc11fMrwEn55/C4Zi7WqCOrVCpCaS5Ezn2tgekFgSI4/u3AzhWadqX9px3L4dEMt7pQ9DKrwP781O9stXIgR4srk+bQEh1ArS5murE19V6ye7U0pmlJ6XUkLTWYUwJmzZxVWH8giLUIaNM4TZo3u1n0sMYPtstT4m8RbSJp9fJLYREhoaMEiz8iBAJpFESSjkIiaNM7U+bLCIIdMG84zn28aUFHScllvvAiXtntdOqy6heBWSFSEsH9frSxFSVMfllLSFE2kaJweKrE2jbOd748EVc7dfyJvLKth0caGdq7sfTS1GsZeJOJWe3VGPBME+HHiQlYOOaDde33ngIkcsrM78tcgiwjFUwItufSeUnMMD/TC6lJKConSIo22c+4jLEeL0wAUQnDVCbu0m5PWntCeRXMP6nE7Qp1EtYMPqe82WvnZSw7gzZ8dym3f2JOLD53C+MpCPlpdyx+fX8I3//Uhe/3+Ffa+9hXOvetD/vziEp5buJk121r6rFRQNKGxh7LCCIioqXnbarOuOuHHVhj7ne8dNMk+FlAEX997nO3ceSh5CJtlBSvlaFszIt8R6PgSH52GNAZkEpWywiCXH7uzrdKnKoKagknMan7auDaNxtkeAoqCqgiaKaTQUdPMqx6NE4VBNW83lA1tCYYGG9mYKCagCOrNCc0Z2XOqMlnenn0nV/LGshq+lClazgvaXIrDAXQpaVFKKPGgHe78qxeYPqqU5y89MBXZ6wav7sw5VTzy8QaeXbiZM2ZnpxP1JmoDI5g4tDhFAQbb2xhQFBIOYy8ZHgIkbI/jGjmSSRj5e2/qu7GnYkRqZshlVMQ3groHkaBKnWJR7OrZhLf8dj4hZeirthfbyPFKTfy5FvO2oAhBvdlONG2B4uGu77LQnf42EFDZsIiFke/yg/iPbIGq/150GJhFv+dMqGDNdcd3+r6hgEILEfZUUoI2ItbolIdgSpa8Ua+cPYtCdfGDCzhzThVf2XOsbQAOFBh19gRz0sRDOgtrXtxuijjQsg1dL2eu+JKHzZqwmlro6e1WBEZkDyBab9A40zZaJ+8+mpcXb+WD1dvZb3L/j39dl5ylvGa8GbFr1uu8fm9xOIAQhvERDGSuLWDkmqnbPjLyGE2H7X8+WMevnlzE9FFGG3tFqWwaZwdD/Jv7jue2eSu59Y2V3Hz2nu1f3IuwaJyRAmOsWI/tFXXKZfOdrqDYSJEd2ZN4t1k6wkGF4nCALzb1ryHcEXRplCyyFdRd57I7kgOKQkLTPEsvtOe03yyNOWJrwWSO3nUkD31vHxJ3B1xpReBMT1EYV1nIuMpCjpmRKjVS1xLny82NLN7cyBebGlm8qZE3l2+zP1cUUpk+qpRdRpeyi/nvTiNK2q2X2hXI1lqGiGbY/3LXcdWus9e1WFVpJJix/qy49jgArnveYIT8Ink+SlLys8BDBPU2Y+Dm+brsR/Z6AZYn5bZvzc04pwjD2LPRQWTPCVUVqIqgiQKIpUQK2qNxqoogElTzOmevQjRRK0sJqgoN5tZOV1OGizOxucCccG79xp6cNbeKB7TDbFGbn5+0J2/+/FBURdCmFLpq4Djx5eZGfvTfT9jvOmOz0FUPEhhe4knDini4j2vuWRG817TdeaPyq5QWBFI1GoGoafgFVYGmprbLerDIPK7w8Pf35UV9jn2ukUI75/Rc8YxxcOpRFARV6hTDGz58kFA5pUxF9qoqCnn2kgP47ckzXNfkkivrhCIEdaq5aXfk7aXvb4aXZi8CnQ8obzaMsSPV+RRaqpjB7CIZuSKoKizQ3bLYSqzBrocEcG7gRQB+l/iG67qmWJqxt+gxdn30YBYOvYpvqi9zwwtfsu91r/Hdez7i5cVbB0xha4F01wfoIqw5zPL+07KNpK4zXnHkj5rOxIxnEIImYVJuow3ouswwkg7feQRFIZWnPhkYqpyalJSasu2M3iPjvNUPvPZvAVWhssgYg19uTjlVnW3zim4aYC9dZR+z6kuurDFq3XZ2fnCiNBLkm/uO57mFm1lV4107ty/Qakb2CszIXnsb+lxy29P7V6MsJKC18bvAvzldf5F0/5mXSI0Azt1/As8t3MKby2oyzg8YaDHCIkmzzDT22tMDGFpiiuF4dE4r1+9MD8fx53ISX49fweujvwcYba1JJWtkL9u+ZkhRiP2mDOW7B07ib2fuzouXHcQXvzmaZy4+gOtPn8lX9hqLEPD4go1c/vhCTrrpHXb99Ysc9bc3+NF/P+Gfb67k7eXbqG1pXxOhIwiTNk6h23nU3Zy99pBiiRm5y9WyHFUmobX/82e7Cz+y1wuwBldVZSZ9RFUEW8MpXjZjMw3CbAgoAlUIQ/3KNPZeXry1XdUuRRgTdDQxMDYvncXMIUlmty3jaW1fgqpCnW5sOtoiqaRw54RZYNJLCkMBpo0oAQSHxv7CaepbnDZpFhVFIQKKoE0UMkvZyIHK50BmlOFJh5R4etHNzkAIwRmzq7ju+SWsrGlm8rDs+SM9iX0VI6/uWW0fhGYa/A4PY6u5AAVVhWTAsREPFgD1CAHTR5XwlLYfu4o1rGMEIOzizLMwxQlmfoXIqx/y+LIk54TgyfDV/DTxfbzaNJ/gNPYAdh1dRl2LO0fEi6bVHlRF0CrMto6nNnDp3uz89h8a0t8Ap6tvc7qlilnaPRoiGH31czmZs3ndPiaiDZThNo5rZCn/1o7hV8H/AIb8uJUXWRoJGvXRXrkGIRRKhozgu+tv5pvj3uHBEZdx85IGXvlyPsNKwpy+51jOnFPFREduYV/Diux1F04aJwCt29BCE101Cwui1Z6bT0VAM+a81VaPLjMjYgUhlaNnjOS5RZv57Sm7unJY+wOaLqkUTWwr2omhHpvmpy/en3lLa7LO7VapC2f+jjPi/oy2LzcEbweHSIu19lhpAF6U1hSNs+O/6XcOmMi/3l7N7W+s4vqv7Nbh9b2BeKvRP0TY+PsXhNox9nJYJ9P7lxWX/2bgFZDwHMe5zic0SSiQ+ow1VV506BSeXbiZXz65kBd/dJCrxM1AgZI0nMlekT2tncjeqLIC1te2eTI8LGOvvMirZI3gHX0mUwPG30oIYaSudNLY80IkqDJzbBkzx6aEUnRdsr6ulcWbjCjg4k2NvL+q1rV3GlUWsaN/1r9VQ7xzg9Mh42ZAI+zeM3WXxtke0ucDSz2fxg1QVOnxifxBhyNECBEBTgAOBEYDbcAi4Fkp5Re9+3h5CpPGqaiZzasKwZbIhNSBcO6bf1URKIqgURYiY40I4Px753teO4JaGihCigIKQmre5uwdpH8AwIipexFQBc16EBRoLJ1qX+McoAUOz6M1GWyhklu0UzhdsYpoKrQJYwK+L3QdcEW7z9DVRGALp+05hj+/uJSH56/nimM7J03dVZyuvgnAh3IasxIakYDqonEaiqRahrEngka7SGm0a5QwVyfP5dv7TYB311BHMUmpUCDitASHUBQqIhJU2KKX2/e4IXg78Kc++JW9B2mV3VBS/Sld6TXZaRonqfpljoLM6VtCzZP+JVlX28r4yv4zPHKFs0abDYeaWlcRCijUSrdyqWyrZ4hwt8nvEt9EonB14hx+G7wHFd2mcRaFVVj0MNSvg7P+CzsdA4seI/zCFXx70bl8a873mDfmezzwaR13vLWK295YydyJFZw5u4rjZo5qd7PbG7Dq7HUX1ibbpnEuexFt5z2oEMZmvlYWs3HcSVk2Yc7IXr1RVN1jX3/y7mN4fMFG5i2t4ehdR3b7mbuDhrYEpaKFeLDE8/ykYcVMasfxVl4YpL7V7dxxqSkSonXSsRQ2r7W/b+mWJtf1njl7HclxOjC0OMyZc6p48MN1/OjIqVkFjHoTeosR0WhVjX5T2J6x14XI3iJ9out9uuM6qeuE0ghoQhjOyz+eOpMz//k+f39lOVce1zframegJAyHXrOXsadlTxEZXWbl+GXe03IkeDlTwgGFWFK3o9WqIrxz9mT3VMYtKIpgfGUR4yuLOHZmiga6vTnGl5ubWLy5wTYE5y2rsY3M4nCA6aNKHEZgGVNHFGdEjRVLlyKUZuyZDdMbrMr0vd5m29jbBKNmeXwif9CusSeEuAY4EZgHfABUAxFgJ+A60xD8iZTy8959zDyDVZBZzfS+CAFNASMsvTi8O7t04raqEAQUQTMF4MjZ88IHkYt5V9uF8/g1BXlM4yyLb0VHsPfXr+HhxxZTLo3QfmtxKhfPuQl3F7FOE8gQFtdb0Ka3X8zZie5OisNLIhw6bTiPfbyRnx41rVuRwtwgOVb5iJrgaNZHR3De+CFEggptJo1TQ0EXKqARSKNxYuZCSild4gSWXLFEYRtljKSOuFpMEUbUwN5EWk+QjCMCIfIVuu6O7IE7fwdgn0md8/QpiiBhSdprKYpL+gbHi/11z7truOaZxTx10f7Mqirv1Pf2OZJu+k6NMozOCbJ7I6QKOzL1pV7FWLENYo2Up5nLz+l7A3CvdjSVoolLA4/T1BanMKQSEMDbf4Phu8DUo40JeeZXYMoR8NrvUD68ncNKnuKwY66j+pSjefSTjTz80Xp+8shnXPP0F5y0+2jOnFPFzDFl7Soq9hQEOtL8njHlBWys71rNLCvPxY7szf8XFaGdqRSNrNeHcWD8Rm4unUpZlpy9Jhw0Tlnimeu2/+RKKotCPP3ppn439o75+5v8iyS60rU5qDgcyDD2lqQZc1qo2GbYzPrNSxn3aE+sJteuc/6Bk7j/g3Xc+dZqfnVCZ3YLPQPZVgdAecUwoJZDdhqe9drccvbc1yyQO7nepzdZIinB8Sd01jzde1IlZ80dx51vreLE3Ua7ok4DAapZ3y4qM2n5+0yq4IUvtjBpWKbzboRl7Hl0kl1HG+N3j6pyJg0tYtW2FIU9ElSJJXX7c4qwBFrcc4ZdP7gXImNgKIweMDXMAVNT9MtoQmPZ1iZXFPDRjzfQ8p6xL1UVwZRhxew6OhUFTJhRZcJuh01vbp/SHTSbpPkb6tf13pf2ETqK7H0kpbwmy7m/CiGGA+N69pHyH8KUVRcekb3GaJK731vLshH3UVZewa2duK+imDl7shCi3rLPQZK8G/4hAPupi1GlIBJU8jKyJ6WkIllDS8FQStQgQVXYuWaxklS3C2SJ7KVPltb7cFChVTpWEF0HRenVIrZnzqnilS+3Mm9pDUfuMqLjD3QRUkrOU58nLBIM3fcbvLvnYYwqi7C+ts32MNYERtl0mKAqiDsie9YCoEvpWgycVMMaWcZIUUdMtegikEybSvRYM2qge6IS/QmbxuksfeLoZ+9ebrRrZ6AIYQuWNLa0ctjvX+aKY6fbf4symnk3/EMeaLwemOn67Py1xqZrbW3rgDf2RJp6WYMo7bKx9+bPDuWgPxu0zaCqUGf24XWMpIQ2RLSB8rRx7uyLSWn8zVpjMSNPa9nzULMETrvD7TovKIfj/wKzzob/XQqPnMPwqUdx4XF/5oKDD+HD1bU89NF6Hluwgfs/WMfOI0v42pwqTtljjKsuao9DYufsvfzjg4h1kY4fNPuxk8o99d2fsZmZ1JqOGkV4b9iFgEYXjbPYW1hCVThht1H896P1NEUTLuXTvkZda4JgKIn0cLjmglwccslgiV2OwvN8F+rspaOqopCTZ43mwQ/XcfGhU1xF3vsCwqytOG7MGN65fHc76uSFXNrM2b8uOWwK//faCtf5oB51vZdpjhwp3W13+bE78+qXW/nFY5/z1MX794EjtRPQDWdB3GObfc5+Ezhy15GuOnsWImbUzsuZdNSuI3nn8sMYU17A3pMqeGNpDRfcvwBIOWStJlZMGqeQ7r1fd+sHdwWRoMpuY8vZbWy5fUzXJWtrLRqoEQV8Z+U2Hv/EENk6Qak2DP20yJ7VLrlQoTuL9DG7jVLa1BIKapZk+UT+oN2RIaV8Nv2YECIihCg1z1dLKb15hDswhLQKMme3pbdRhgx0npahiPYje5PFJoYJYwGKSxVh5uzlY2SvJa4xim20RgwvcVBV+F3iG/wicT6NQ/eyr3NO8E6xllDaxG/t7SIBlbjTg2MuaN1JqO8Ih04bxrCSMA/1slBLQpNME8Z3iL1/wOjyApP2ovC8tjc3JU/mvqGX2dcHVYWko86eZRCnN4WzFpyVt5cIGF7JDXWG5/A78Z/aYjh628BWSusQVk6FcNI4U/3JatfOQBXCpjg2NrewrTnOnW+vtjeAU8RGikSMYzffku1x8iKfTyYNY++25AlcGr+QH4mfd/leY4ek5shQQOFLOY7LE9/l5tIf0SQLSbTUUY5bwMI57i3Dr7UtRklYhbf+CuXjYdfTsnzhXnD+PDjmOlj7Lty8N+Ltv7L3uBL+eubufHDlEfzulBkEVYVrnlnM3Gtf5YcPfsI7K7b1iiS5YtbZA4O10NXNvppFuW6Sspl6YURERDZjD0GzlWsabTBonFn6/km7jyGW1Hnxi62e5/sSQbQuR/asjfBVx2enB8aLxxrrcLO3SIhnnT06rrOXjh8cMpnWuMbd767J+TM9BTVmzuORcsZ0MOflEtlzfn7GmMxIXCV1rvdeQ8r5CGUFQX578q4s3tzIv95e3eH39yWWbjJ+i+axzRZCeBp6kNrDZJtPrM8VhgIu9WCLBpmK7Fk0TneEurcje7lCUQQThxZx/G6j+NnRO3PXuXP54MojmH/VEdx33ly+OrPcuLATqU7dRprDPxRQqS6YBNVf9t0z9BI65QYRQnwXeBF4Vghxbe88Uv7Diuy1Z+wlNdmlXDCDxhkx6uyldcwhNHKc+r79voEiVEUYNM48LL3Q0JZglNhOrMgQdwioggaKeUg71EWpc9I4nQtOOgfcOhcOKkSSDmPZrHlmJT/3BgKqwul7juX1pdVUN0Y7/kAXEdd0SkQrtUWTXQnFoYBCDeXckDyT5YV72FHMgKKgqgq3JU/gIf1weyFNFw1xtmW6sddgFrd9Td+THycuMD4f6z8FuZ6AF40zFOie11hRIG4ae8LM2dP1VCHhAMZ3FmiZjhxrk+hF7RloEKax96/kcbwWOoRfnnVkl++lKIIhhUZ0xjC2Bf/VDiOmltJIIVurtzBENBsOMBOv/uRg5pqlCqIYn41HW9hX/RI2zof9L4F25mbUAOxzAVz8EUw9Cl79Ldx2AKx5h7KCIN/cZzzP/PAAnrvkQM6eO443l9Xw9Ts/4OAbXuf/Xl3O5oauUS29IKCHBFpS97g1eSIN0jDexopt1CuWsSc8N+yKAgmChqJq1BJo8f6ePceVU1VRMCAKrAdJkhRdE+6w2CLTRnrn/AG8WF1uvFj9huf5hGfOnvFvZ/6iO40o4ahdRnD3u2to7uN6rYF4g2GshLO3g31tJ42HsoLMqOtQud31Pp1t40W+OWbGKI7aZQR/e3kZa7e3ZF7QT3juc2MMHDVzDGfvnTsBznJW5ZIT7nRsRYJWLltKwCSBau9HLST7IbLXGQwtDnPg1GEcPMGc00N9Z+yld6+gIqgLjYEGbyZdPqHd3YsQ4sS0Q0dIKQ+WUh5Ivsvt9SZ0K7KXOZl9e78JlEYCJHS9S5QDRRHEZMhI3E+66VIvFF7NJYEn7fetMoJqJjPnI42zoSXOaLGdZLFRhNlpsDrbzpmn55zAwmmbc4uPHQmo7g21aexlk1vvKXbnV2ePRdOlTVPoDSSSOsW0kQy4cwGcmzhVEbY6a2FIRVEE1yXP5hr5Pfu6dK/iwdNSRLxqyo3vUjPl9GPm5lqm9c18gyeNs7vGnhDEpTtnTzqISsXCkDkPyETGZ611Pw9sPTBpnDEC3Pmt2ew7uXsqZladQ+fGJhgQ1MoShtLAUNFAPFjGJllBoyygqqKQh3+wL4BtBOrRBg5LvmUU2N79G5lf4oXS0XDmfXD2w5Bsg7uPgycvhBZjvthldCnXnLQrH1x5ODd+bXfGVRTy15eXsf91r/Htuz7k+YWbbUGFrkKg98gf3elYvD55Ft+J/8x+36iU26+zRfZ0KSFSbudwZYsKCCE4edYY3lmxzaVk2R8Ii4TtXOksgjnU8vr7F+b89+Uznue9SiLZapyd/JNeeOgUGtoSPPhB3+YOhRONtKklng982h5jXO87azxYYkevFKe2mSP1ba5rPCN7Hqbyb0+eQUhVuPKJhb2ajtEZBDD2KwdNG8W1p87s4OoUrL7XXs6nfW3Aud+xInvY/2pStZlmFuzI3kBfTCyHcRZjrzceP93JHVAVWtVio55mnqOj3cssIcRTQghLhuZzIcT9Qoj/AL4SZxYURbegSYFQMhWTCkIGpTKpyS55VlQBbVbGctLtQR6hV7vet2DQLgrytPRCS/1WIiIBZcai4vSUOjcvcyYMsV8r7UT2FEdkb6tDPdIy9rLNrT21dEweVsycCUN4+KP1vbYgGZG9NpJB9wTp3LQoiqCqwtgEjx1SgOpYHLLROA+dlkrMr5FGJEAxcwFuOnsP+5xt7CV6L3rZF7CMXdURAXIW5O4KVCVl7AnL2JOpBaYUw9hTPYw9m/7VrSfoG1i/LU6wR+SxbWPPWeBaUVghxzBebOVk9V1CxUM4KPZ39ozd7vpsoxnBktEmKqmH8nEQ7GTh9J2Ohgs/gAN+DJ8/BDftBQvutS3wSFDl5N3HcP939+HNnx3KRYdOYcnmJi64fwH7/vFV/vDsYlZUN3XwJd4wInvdz0NKn222kpozG1VjPOtZ6JlCmJ+PlCFNenY2GicYBdZ1Cc9+3r8194Iku2zsWWtze+ybWkr5UJ8Gtas4YEpKjMLq8p7Gnh3Z69y42L2qnP0mV3Ln26uIJfvOcVugNRENeAuf3PBVtzqh2knntbU+/7PoB8yM3klCqkyU7jSHjJy9LKvxyLIIvzh2Z95ZsZ1HPx4YURjVZGrEZefaxWIt5ZJWEvSI7Nk0zmxqnAM8smcj3gSBSPssjB5GepMHFEGrUmI8i5a5LucTOsrZ+z3wfeAiIcQ/gX8Dvwb+JKU8uw+eL/+w/iNmVj/Ni6EjEB5ewcKgSkKTbG6I5lSXJh2qImizJPQT7dOFVsjRqErKwMw3JGoNL6Y6xKBAOHMgnMZLtkKv1uQH8MPDpthc90hQ5W/J07k6cY5xsnW718dtSAl8cj/Mu77TvyEdZ8yuYtW2Fltwo6cRT+oUEkVvL7InBPedtzcPf39fAqpiG8FCCHuj4rWoPnfJgVx9wi7UmfL3qum5PN4huxyTVmQv3409o685vZ/dNfZCqkJcB5QAQjcMIl1Keyc+UdkMYCwuabA3iQPdGwsoesrY6wlqtDW+nXTtoCpYro8lIIz7N1fOIkkgQyjIiuwNja1ndGItFLkL9OaMUCEc8Wv4wdswbDo8/UMj0rd1seuycZWF/OSoabxz+WHc9e05zJlQwV3vrOGIv77Jabe8w8MfraelE1S8norsra9tdb23qNgANZrR3wrDgaxF1aXEELEx85vby/eZOqKE6aNKeeqz/jf2YtJ7begI1vriFV1xCjNtkMMyRFqsOSOe1Pl4bS1/fjEl7pDK2ev8M114yBS2NsZ4fEHfUGSTmk6R3kQilFkvGIw+8NRF+9s0605H9sxx3ZqUNFHIGjmS8bqx5k8T6/h94F9ILypjlq85e+445kwYwh+e+9Kuk9ifCAhjfYx2knlrGXC55AC7aZzpkT1LoKX7dfb6BbHmdimcvfH06ZE9RRF22ZH2xJjyAblYGy3Aj4CbgX8CZwHLevGZ8hp6tJHFTOT9KT/xPO+s05RetysXqIpC1FKSbMfYW6aPQUVDMWmc+Wjs6fWGhy5cWQW4N94hF33Buxs7a9EcunMqMhVSFZqSKg9rhxgHWgzqSNZom5TwxvUw71r44olO/w4njps5iqKQysO9JNQS13QKRQw96KZYOhdiVRGMKI0wd6KR12R56QUpY8JySt/2jb242pT83mV0KdNHlRqFWrFqgBmfsSShY2bUOd8je9YmQ3Espt1dHEMBxVBTLBpOoGWL8T2OyN5RQ42aVorMHKu6bex16xH6BCIZIykVdBRaeyBX2NrQFIdTtPiAorBMjrXfb5zxPc/PbpFGH/9D8gYqElth1lnde5jh0+Hc5+DkW6BmKdx+ILz8ayOH2gFVERy683Bu++ZevH/l4fzyuOk0tCX4+WOfM/cPr/CLRz9nwbq6DiP8Sg8VVa9tcZfDiDn07DcnDWOvNOJt7CnCnBsj5TadqSMK2Mm7j+aTdfX9mkMVROt6ZM+DSvfYBfsBcO935trH2mQYEq2uTaIVkYlrktNvfY+bX19pn+sOoWP/KZXsNraM299YmRPFr7tojiUpEy0kQ9lLGsyqKmekWf+vs8aeZZxYc8RmWUElxob6kdBv+EbgVXttttBe+ymK4I+nzaQ1pvHbZxZnv7CPMKbUGGMTR3SuJEQqZ69zkT1rH2St4VbpBcUjsqeIPHAcxps9xVl6laabdmtFQKuSUiLOZ3SUs/d74FngVeBQKeVJwGcYAi3f7IPnyzusKtubE6K/ZcaksZ7nnYtke/kA2aAqDhqnw9izoiwWNFQC6KaxpxBP6n2yQPQklEbD2CsaPgFwG8rOtss2aYUdkb2g4/qAKtAlRAkb6pFmZC9b6+xZvB3q1xqUgmd+ZBTY7CKKwgFOnDWaZxdu7pVk+8a2BAXEkGnGnqIIl8fPCdWO7KXOWRPqMTNG8p0DJtrXhgIKn+pTAFg+5hT7uBWltmWm8zyyp5k5e2oaFVsRcNbcqi7d0yp6S8Ukws2GsS/N/ydUFrKzYnjsQ7pX2+VJngVGZC9u0nmnj+pY2KEjWBvvoSUh17FVchTbZCmLRp1OsnSC52fXyhGs0kfyrrYL9+7+IMz6WrefByFgj6/DDz827vfO3+HmfWDpC56XDy0Oc/5Bk3jlxwfz2AX7cvxuo3jm802cdsu7HPW3N7nzrVVszxqJkEjRfRqnRSk8Ynpm2ZcDZu0MGIXGvXP2TGdDpAxMdcaO9vUnzTJEtZ7+tH+iewVBlRBJJowo79LnrfnMScXca/wQ1lx3PFNHpPp0uLAY4q22EVJEak1uL4LblWEshODCQyazZnsrzy3c3PkbdBKNbUnKaUZGytu9zopAhbMwbNKhCDh9z7E288bKxY8SIoLhlCgVRjtKD+pce003ZXgJFx06hac/28TrS6rbubL3UVFg/L5AJ+vNWnT1XPZrTkd3yC69kKbGmV56QcqBH9UDM7KXuX5YysK9oZ5+VFp9UEUII2cPoK132Fh9hY5WkROklAcB+wHfApBSPg0cDeRvEa1exIJ1dYBgz/HlnuedA7grapyKELZXVo+nqDlDcYeYkyh2grBFl+hLrn9PINi8magMUlRmbFBmOqSac2k7p6exOOIUcUl1+1pKoNWIqHg5jH53ygxG1bxjvPna/YawxpMXpBQzuoAz5lTRGtf4Xy/QnE695V0KPYw9SP3udPawF40znc5gIaQqbKaSCdEH2DjsIPu4VccrJdAS9/x8vkDqqWKvTqz64/H88bTdunTPcEA1BDvCxShmvq0uJbqEMHGoM6TDwzLT2LMje1365r6F0OIkRIg11x3P2CGZ/bCzsDbelY6yA9ubDYNy79jNvDPtyqyblyQBDov/lbMTV5EcMqXbz+JCYQWcfDOc+zyEiuDBM+G/X8+q3CaEYK/xFfzpK7P48JdHcN1pMymOBPj9s1+yzx9f5cL7P2be0mrXGqEYhfa6/ahWvnOJYx78UJ8GwBF7786a646nrMA7x1IIYdAPC8rtumsdbRZHlxcwd2IFT366sV8EM8aURwiLBGOHlnfp87PMAt2VRZkFsZ1osSJ7uk6V2MoXkfM4U30dgPveX5txvdUWXa0RdtQuI5k8rIhb5q3s9XZtjCYoEy1QMKTd6yzVyPRSR9mw6o/H85czZmVE9mIECROnhNS+Jl3oK5dffMEhk5k6vJirnlzUKcp0T0PXzO/20G5oD0VmusDoLKUZnHA6wC0jzxJtSeXsZZZeGNDGnq4bOdFr3/Wk3Vsqrg2tPZ9Dt9f4Iaz4w7H2e0UImoRF46zv8e/rS3Q0OhcJIe4DHgHesA5KKZNSyht79cnyFPtPGcr1p89k0lBvrrHTG+GVwN0RAqowqCOA7ojsHaJ+5rrOiOxpCJGaEPKt/EKkbRNbxVCbSnfmnFREJRclU+c1zk2Okz5bK0uQ7eTsKQJY8QpUToEpR8DR18KqefDBbZ34JW7sUVXOlOHFPDy/56mcAp0CESepZopQWBN8+kRv0zjbEWix4FT/ct4nYX4gZlKM8z1nL6VY1nNFesNBxXC4BAtRE8aGRpcSKSU/jN8JUmedWmUYe2nOBGtj1wUyQJ8jmYiiKT1XUDto99vUj2+MGgu9hoqiKDnVjHLOAT2K8fvB99+EI66BFa/CTXPh3ZtAy77RLA4H+NrccTxx4f68dNlBfGvfCby/qpZv3/URB17/Gn99eRnra1sNqnQP9EFLFbTQsTm8KH4pZ8V/iShORfuyCrSYkT0Ra0IxGSMd4eTdR7OypoXFm71rwvYm7IhQF4uq/+iInXjyov2ZOdabgjfvp4dwxPQRNOtBQBKUMSYLI9p2ffAO0s0Sa/ymcm+79FgoiuCCQ6bw5eZG5i31ru/XU2hsjVFKK0ph+8aetVZkS6fIBmt9tkr3RGWIsEhQKRyOaw9V547aLhRQuO703djU0MYNLy3t1DP1JOw+KDpn7O0/uZI7vjWb607vWMHT2ebWemyxmFRhlF5ITwvQdNklVlmfYOPHcOfhRk708Olw7J8yLqksNvYYWi85O5xaGooCbYqpf2Dm7N3/wVoOvWFe3gVPOhJo+QbwJ+AqKeVlffNI+Y0x5QWcOWdc1s2HM2LSFYVMRQi7dpQeS3nAxgt3EdsEKqpp7EXM3LV8y9srjm5lm5Ly7DjpmrkYe05jxCmu4YwK1skSB40zc/II6jFY87Zh6AHs9W3Y6Vh45ZoMcYZcIYTgzNlVLFhX32WVvmwoVowFpmpEpkfMinRmo3EqQmSts2fB2e7Ov8dn6+uBVGSPQZOz1zWBBy/YNM5QYSqypxsbwBMSLwHwaWgv4+KGdFU6A12NCPQltHi0y8WsvRDwECxwdk+nk6I9FPeWsQcQCMEBl8FFH8CEA+ClX8I/D4H1H3X40Z1GlPCrE3bh/SsO55av78mUESX847XlHPTn10HqPaIGHDcdiwXOepmU856+q1u8yYMxITAFWkw6XwmtHdI4AY6bMYqAIvqHymkbe10tQi/Yvao86/kJQ4sYUx5ho24QnIYmt1BByqgtwZ1Pb3Xd1DjuOk7efTRjygu4Zd6KbtylY7Q21aIISaCofRKXHdnrZmmaKCHGiO2cqzro0OnGXo6DYa/xQ/jmPuO5+901fLKun+h3ljCK0rl5J6AqHLnLCIaXdKwa7FyDrXFs7W/s0gtIcNTas3L2BhRatsPTl8AdhxvMiFNvh++8AMN2yrj0iOkjuOSwKVx53PRee5zfnTKDZy85AEUIWtKMvfrWBKu3DZx6jrmio5y9A6SUC6WUS7KcLxVCzOidRxuccCkXdsH4cqpxykTK2BtGPXWBYSzUJ3Bt4iwjsid0BIKI6c3Nt1p7ZYmt1AUzc0wgt2Rwp1EXTpNtt2DQOM3InsdCMrxugVHiwjL2hICT/gGRUnj8fE/PYy44dc8xBBTBQz0s1FIZMhaYcIEH1131juxZG2XheJ3Naeak6nj9CQZLnT3djqz13KoYDqiGsRcsQkk6qEqOjvdRxKgPx7r3XZ8dIKWjckJBop5E0FvBryuwHAwJR7TT6YxQhGi3FICFkkjPRRuzYsh4OPshOPM/xrzyryONPN8c8j1CAYXjZo7i3u/M5e1fHMaPDt+JgCKoKO5kqQgPXHX8dEoiAYaVZNISXeJNHu1oC7QUlANQJlpyooENKQpx8E7DePqzTTkpC/YkpFn+o6vGXi4oKwzxWdRYz6fHF7GvknL+7aMsNqjZJnoyXz6oKpx/4EQ+WlPHR2tqe+y+6Yg2GutiqLh9Y08zKcLdNfasteOcwMuOm6fTOGXODq+fHT2NESURrnh8YbfrXXYFdkStk8ZeV2GNXWu+tGicgF37GczIXheU4HsFugYf3gH/2BM++Q/se1EqFzrLnK4qgh8fNc0uydMb+OY+49l1dJmRsydMlp5p7HWXit1f6OgvfroQ4l0hxNVCiOOFEHOFEAcJIb5j0jv/B3RMLPZhY8LQIv52plGfpith6IAiiNqKhynv4XBRT1OwkhPj1/JP7USSUrEje5Y3N69q7WkJyrRamsLexl5ONM4sIi7OzY0R2XMrfjkxuuYdUMMwfv/UweJhcNJNsHURvPa7Dp/DC0OLwxw+fTiPL9jYJTpvNoSluTh65uxli+wZ/woBU4YbE9ue472pO84F3WtjaEf28pzGKbvLt/JAKKCg6RI9VEwg2YKKZtA4Nc1YlA+4jHVBM6/s84fcz0OPP06voDmWZBLraS6d3GP3tGjXiWQ2Yy83emt3S2fkDCFg+olw8YfG5mXBvXDTHPj84Zyt9jHlBVx6xFQqCwNMzJIS0BmcvPsYFl5ztGeZGicLxTtnz4xMFQ0DYILYkhNtFuDkPcawuSHKh71olHjCNvZ6z8DfdXQpK6QhRHNU23N8NfCmfe6O0F+5OnCf/V7PoHF2byCfOWcclUUhbnm996J7iWbjbxYprWz3Omsf01kaZzpa8HBqdCP3uyQS5HenzGDJlib++ebKjj/Qw1CsaFonc/a6gnEVhS6hNbAEWsy/iUPoJqnLgSH0te4D+OfB8NxPYeRMuOAdOPoPhiN9gEAIc0+jhjJKLwyEJuwMOqJxXgYcD2wGvgr8DvgxMBW4XUp5kJSyY56KDxesgdYVb58ihKEgCUiH3PdwUU9zMEXds9Q4BSljL69onE2bUdFpLRjleTqXshXZRFycXq1aWYKINUEy7skQGbHtPSMnJ5RmPE07BmZ/x8jNWfWGxyc7xplzqtjeEufVL3tONSysmw6AYKYPJlvOXmrjJphVVc5bPz+Ub+w9zvP+QVdkL7N9k6joUuS9sWfXdOzBGd3aDCXKJiKkxgSxBV1KpkQ/M8SUSkYRCxSxLjAB2tybY9ubOMBXmOptNYwR24lXTOuxewY81NecNpOhNNtxu5T2Jo3TC+ESY/PyvXlGMffHz4d7T4Jty3O/h+yZnD0LXsZcelmWdCiWQMuEA9DDZXxFfTPnzeIR04dTGFJ5qo+pnKIPIntHTh9BjBBLC/diYnIVAP/T9rHPfz3wKh+Hv8/OYl3K2LPK1XTzuwtCKufuP4HXl9bwxaaGjj/QBWimcFmkpH1jL9lDkb3Vusdan3TTYaXs3JR85C4jOH7mKP7vtRWsqmnu1vN1FqKPInsfX3UEz196oL2O23X0hEjVHXWItGi63r8F1Zu2whM/gH8fZdA3v3IXnPOMkaM3wKAIwf8WbjGonDGDpp1PLBsnOhydUso6KeUdUspvSymPllKeIqW8Qkr5dl884GBEewVbvfDkRfvzwPl7A8Zi3GIGU2UsZewNE/W0hYxJeVRZhKSdsydsieOeqHnVZ2gwZOjjhd7GXi40hGxJyC6BFgwvUrJ5Gze8mJnMXRCthsosUYqjfm+ce/KCLsnyHjR1GCNKwz0q1BKylBxDRRnnrPZIn+etCJ1ljFRVFGY1Kpxt5+3dF4YnLM9pnLJXaJxG+8YqDKn7qWIjrTGNLWvNsqVjZ6MqgmWBaXb/t5/HnCoGXK5FGtpWfQiAMmKXHrunJQpkKUqCO7InhMhJfKVXc/baw6jd4LyX4fi/wqbP4Nb94PVrc8trlT1TVN2C1yZP7YDGaUf2ggW07nw6RysfUZDIzcAoDAU4apcRPLdwc59S6YSds9e+mmZ3oCiCycOKWBtO5RUtKD/KdU2laGK6WJvK2etBwsA3951AcTjArfN6J2qltxprmlLYPo1zu1nDcVRZ90he1ZRnHCta8b+MY51tu1+ftAuRgMIVjy/sUzpxsTSNy0jn6ux1FpXFYYrCATvFwhpnQiEV2XPl7PVTQXUtAe/dDP/YCxY+Cgf8GC7+CGacNmDDZNZ8uDUWTtE4zXMD84mzY4AQd3csqGkemI6we1U5+00ean+2lbBReylmiHsESDJUNBIvMAqHhwIK4VDIjuyNGxLioMBiXvpsXc//mF6CNAUqtNIxnufTI3u/PG4639p3vOtYtsiec6KrlUZu27sLl/HIx5mS6arW5kmJBAyD6rQ7oHkrPPtT72vaQUBVOH3PscxbWs3Wxp6JhBVLMxcs7FWfxqRxpqtxmu+dSn3ZEOwgZw9M2kOeR/ak7IXInhVhLzL69CixnaZYkiLMthoyEUUIFreUQEs1G7fVs3xrE43RhG3cDOg8gaXPM/n1H7BNljF814M6vj5HWHRsJ93ZOXUqomOJfOhDGqcXFBXmnAc/nA+7nAJvXA+37gsrX+vgg70T2StyjPUOBVqEsI2U5l2/QVgkmbDpmZy/8+Tdx9DQluDNZb2rHmlBSgl679M4AUIBlU1tpmAaggkz98+4pky0OCJ7BnoiQl9WEOQb+4znuYWbWdMLghFWmQ0rVzMb/vnNvThu5khbEr+raJKZ62zRqudd77tiqg0vifDL46fzwepaHuoFBexsKJMNRmStl409CxG7xJZZI9YZ2dPckb0+N/ZWvwW3HQgvXglVc+HC9+GIX3sWTR9IsIZpI4WOnD3r3ABeiz3gG3v9gM4ae5mfFWjBYrvzjcDwwCULjZyKWEJHE0bO3kR9DcMfOoF7A7/nsM9/wspN2fPTBhISdeakXOpdnD49anf+QZP47ckz0q7JFp1KfbYOwyjSmjPbRUFH1eOeUTIbY/aEQy6HRY/C549kvy4LzphdhS7hUQ9DsysYYtVbLBqecc5qj3TvvUXJKsjB2At1QOMEQ1VN5LmxZ4/Nniy9YEb2osIwTApMAQfb2AsV0RrXWKcbEfpv/eVhjvzbm5x9x/sDO7InJbzxZ+SDZ7E8OYK7Z9xF5TDviHxXYI3XpMPYO3ZGqvitIkSHfVcIKAr1o7FnoXg4nH4HfOspQMB9p8Kj5xnUJi9InZ70IQc8RJqc84FnZI8UjThasTML9ClMXX1/zvlUB0wdSkVRiKd6oa6oFzRdMkqYNOhw7+b/hAIKK5uM/tmklpMIZ0bBymhJRZR6mAP2nQMmEFAVbu+FnDTFylHqoKj6UbuO5Jav79Xt72tOk394MHkoarwRtixyHe+Kw+uM2VXsM6mCa5/7kuoecqx2hBK9idZAaZ9FrSwGlyXEp5ilFwA3jVP2YWSvYSM8+h245wRItMDXHoBvPAZDe7jmaS/BMugaZVFmzl5/PFA34Bt7/QBLRSiXopnpsBZjLVgC0QaeCF3NO5FLjWNFhphJNKmhozJS1HJz68+gfj1te5zH4eonxO47ExJtWe8/UJCoXUe9LKKoxNsrlkvOXi6eFyuyp0Qza+0VkF3sxIX9L4OqveHZn0B956KnE4YWsffECh6Zv77bRXKllCn576LMPAsropeeW2FN/Lkk2Dujgl7N+8vjptMsC4w8yDyGtGsT9axAC0BMBpEIfh58iAvVJykSUeJShUCYWFJjmW44OF4K/RyQLNrYmKItDrQVJtYMD38LXv89n5Qfydnab/jGUZnRje7AMlDimmTp74/hs6uP4rwDJtrnc9m3FIcCOYuK9AkmHQIXvAuHXAlfPgM3zTZU6fQ0qn2P5+wZ93LOjbkItFgzkyYlNyZPp6h1Ayy4J6fvDKoKx88cxcuLt9DcB0WuE5rkMOUTEkrEyLfuRYRUYUekJAIlkBnduiz4mKv0Qk/u/YeXRDhj9lge+3hjj7FDLATj9cREGILdV4PNBemRvbu1o40XW1PGXlfXSCEEfzxtN2JJnWue+aLLz9gZqGhoog8UgE2MHWK035BCY3+pKBCXpoMr6VSG7YPIXjIOb//NEKb68n9w8OVw0Yew8/EDlrLpBSt334jsmTl7PVIMp++R0yoihPidECLgeF8qhLir9x5rcGOv8UO47Rt78cvjO5+Qag3SaHEVav0q9lBSalyixPB2RxMaGiplopUIcTjpHxSc/FdenvIrdm79mKZ/nwrxnqd99CT0+g1slpVZqSHdCaHvMjrl7W00FxjFNE4OUxbwfdWgKBVaxl66OEs61IBRF0Zq8MQFmRu2DnDG7CrWbG/lg9XdU6zTdEmlaEQTqqc31jIY0pVMU8Ze51TD5kzI9GJHQirNFCDieW7s2ZG9nszZM1Vxk7pR+wj4efBhTlbfodVUoktqks/lJD7Rp6AKSSXWAmM+zkCy9mpXw7+OgiX/o/6AX3NG9bc5be5kRpb17ObQcuwkNZ1wQKWsMOiKKucyF/RaQfXuIBiBQ34BF75nMASe+ynceQRs+tQ4L6UxT3c0/3QCKUVe7/NZBVpsNUnJG/pubBs616CixnITvTh599FEEzovL97StQfvBOKaTplooS1c2aNt54VQQGGdNFgUpVq9i03yjfgV9mvNbCcpe95f8/2DJqNJyZ1vrerR+4YSTbQqmekAvYVtlPHd+E/s9yvlaKQShOovXdd1dUqeOLSISw+fynMLt/DSF73fD1WpoXeyoHp3cPqeY7j57D05Z78JgDFu45Y6tqOEhabLnErVdBkrXjEo6q9cA5MONmqPHnqFp2jcQIelYN8kC5EZNM7+eqquIVeXYQD4QAixmxDiKOAj4OPee6zBj2NmjPSUwe4I1mJcGx6D2pQScXhZ2xOt0hB+iCZ0Y8NvwRxk+371R1yt/JCizR8g/3O67akYiFAaN7KxHWMvV1xy2BT++719XMdGOTajFnXEMk7+HbqBK4IPItApFaZBHM6Bc18xEY79E6x9G979R6ee8biZoygJB7ot1KJJwzhoC1Z4zkTWJBVKM/asjXNnpbNHlGZu6kOqoFEWouS5sWfX2evBqIpltMxf4xbzGSO225ROg4IjuDV5IgA3Bm9iGPW2tTdgglOr5sEdh0LjBvj6o/yx/ggUReGCQ3qenmPTOB2092CgYzqxE/0mzpILKifDN5+E0/9lFBS+41B4/nIjF1hqPUpFtPN2s7SZV/8SpHIkDSatYOmMH0NLDbx/a07fu+e4IYwpL+gTVc6EpqOiQx9stEOqwgpp5OAq6ARUhd8kvslF8Ut4W59pXydajDQBiezxXJ+qikJO3G0U93+wjvrWrpcqSEck2UA00HfGXmFI5RU9RQdNEiBWNomm9YtsJU17BljzDtR3fr383kGT2HlkCVc/9QVN0UTHH+gGFDRkH5LnhBAcv9so1xhPlUJKM/Z6YyGpWwv//Tr853SDfn72I3DWg8beKE9hMRFcOXvmuUGZsyelvAL4BfABcDdwvJTypl58Lh9ZYHWwZ1clCbRspUEW8mDyUM5P/JSCotTErOFY6AJGjlBxOMCUI77DxfGLkes/gvtO6ZKKZF8g2LK53chervjxUdPYZ5Kb0hhxRLBaiCARGYbvMBoYJqz8t6HkhN3PhuknwWu/h82f5fyMBSGVE3cfzXMLN9PYjQVI16FCNBINDvE+b0f20gVajH/Dwc4tTF4LRlBVaCGCiPetzHVPwxZo6cl8KZNC99v/Lc44FxbG391Krt8kjT57gPoF88KXpSTb+3uBkRLeuwXuOw2KR8D5r7NuyL48tmADZ88d1+NRPUgp78YdOXuFDkdZLvuWPimo3h0IATO/YqjTzf4OfHAb3LKvcc5DbKmrsCJP2fqR13HhiOxZuaxNQ3eHnU+Ad//PkE/vAIoiOGn30by1fBvbm3tXqTdl7PX+RjuoKjRi5HTPKzsFVRHcpR3Ls7rbwSjMWq69EdkDuOCQKbTGNe5+d02P3bNQbyYe7BtxEfCundtaPpW6NZ9x2F/eAIz2G5LcBvecCHccBlsz59KOvuO603ejuinKn17IVN/uSSho6KL/nEyKwBHZc9I4ZVbxui4h0Qbzroeb5xqCU4dfbQiw7HRUx58d4Kg1lWYbZREi2WbQU/O09kKuNM6DgBuB3wLzgJuEEKN78bl8ZEGL6WnYIg0KXZloZbtZPqCyOFVTyGXsOeSnz9p7HJ+XHcofii5Hbv4c7jkJWvu44G1HiLcQitezSQ7ttrHnBWdEVaIQU4tRY/Wua0pEKycp7xpvSnPs6kLAiTdCYSU8/r1O5UaeMbuKaELnmW6IGGhSMlQ0Eg15S2Vbxl4oja5pefnTI35dQSigGAItWn6XXtB7QaDFqxLIIn2C671l7G2Qw+xjRSI2MKgjiSg8eSG8eAVMOxa++wpUTuam15ejKIILDum5QupOjKswqHiThqaEkgqyqElmQ78qcXYGBeVw/F/gu69CmalEXJwpttRVpGpt5v4ZIVL7G1sVVgg47CqIN8Pbf83pPifvPhpNlzy3cHOnnrmzSCQlCjqyLyJ7ZoR5QvQBHhl+aYYo2Cmx3wIgLWOP3hnD00aWcMT0Edz97hp7j9AdJDSdEtlEMhdWSzcw1NyzrLnueM88/HuWhRmn1BAi5QQ9qOVFI+INcPfxKdpzjti9qpxv7zeR+95fy/w1vbf36WsaZzqEECQsNU6HYFqPFVWXEpY8BzfvDfOuNdaEiz+CA39iBxgGC5os8aDYwGXDdYRcp/wbgK9KKf8opTwb+CfQkWa0j16AVSvvMe1AWqUxoHbbaTJ3fXsOU4alZGxdNE7HwAsHVH5y1E78a9sufLj3TVCzFO4+AZp7rrB3t2HWGNskKyjtFWPP3e1rw2OpjLqFVUpos/OqGLoTOaOwAk65BWqWGJz1HDFrbBnTRpTw8Pyuq3JquqSSBqKhLJE9MzCSGdnrWs6eF4KqQlSGUPJcjdPeTPRojbNUv9saNERYLklc7LrG2kzXU8JZ8V8C8Kh2kKP0Qj+hcRPcfRx89gAccgWccR+ES1i3vZXHFmzk7LnjPGm9PYGDdxrGoz/Yl+/sn6IDOSnHuUQ7BzSN0wtj94Lz58E5/4Npx/XYba2xvtOI3KOFRlF1A1Y/VIUwiiDPOssQlmnoeN7aeWQp00aU8GQvUznjVmRP6TtjD4ypIt3xsM10xEaWGyUEjMhe74ziCw+dTH1rggc/7H6JpaZo0igZES7v/oO1g5cuO5hXfmyUabEiewfEbmT/6I1AKs0ibBl7Uufglhdh4kFw3osQKjYc1us/7NT3/uSonRhTXsDljy8kluyd+sMqWp84HNpDUpgBgGRaZK+7NM7tK+GBM+C/Z0EgYqgLf/VuKPNWT893NErT0bj+g15z2PQ2cjX29pVS2vFyKeXjQM9KrvnICYdPN7y8c3aqYp4+C4DyIZUcuvNwl6qa7kHjtHDSrDHsPLKEX3w+guRZD0HtKsND1ti7HtecYdbY28xQStI88o9dsC/Xnz7T61M5I92o2R4aRXnCnbBdLNooEW20lEzq/Miecjjs/QODirXilZw+IoTgjDlVfLa+nqVbupbvpuuSAhEnGfAuFSHtyJ572Fu/rrM0Ti8EFCNPQGj5beyliu/23Kzu3Aj+feR1/D15GqvkKC6MX8K34z8D3AyR9/RdWa2PIETCkSfQY4+TO9Z9AP88xHAMnXm/UWrENFz/8dpyAr0Y1bMwe0JFmhKsQ00yhzYpzTdjDwzhp4kH9qjRstvYcs6aW8VVx+de9N7I2XPTOO2+fMjlgIR51+V0r5P3GM3Ha+tYX9vamcfuFJK6joKO6AMap5MNIcksCbRRGikAItlmXtNLPE6MvMh9JlVw51uru23ANLYlKKelw7IL3UVFUYgpww3Hg0Ut3CCHsRGD2ZA09zEqxu/ZLfEpw7QtsOc5UDEJzn3OUJ6+9xSjlluOKAoH+P2pM1hR3cwtr/dOUXpF6v0a2QNIYBp7aQItXVYmjrfAq7+DW/aBte/CUb+HC94x1IUHMebLacaLrV/0GhW7t5HrbDhZCPGqEGIRgBBiN+CC3nssH9kQVBUmDS0iqAhuT55AgyykdtSB9vmqigJ+fOROaTTOkOseqiL4+THTWLO9lf9um2TUPWncBHcd26Wk5x5HoxHZawqNyJiU9hpfwZlzxnXr9ulCJI2BSkoT21FI5QSV0EoJrUY9w67giGtg2M4G7S2HnBaAU/cYQ1AVPPRR1/4GmpTGophlc2jZL+m5EZbwRfpGJRsOmDKUr82p8jynCEGUEEoyz2mcsudpnE5jryYwkr8nv8Klh+/Ec/o+zNP3ADKlxaOEiRCnl8p0dYyP7zEcQcFCg7Y5/QT71NrtLTz+yUbO3rv3onq5ICeBlnyhcfYyygqC/PG03Zg2MvfInpvGmToGQPk4mPNd+PR+qFnW4b1O3M2gxD/dizX3DBqn7JPInu4YkG1xLSOyJ1FYoY9G6knrQK9uFC88ZApbGqM8+cnGji9uB00tzRSKGKLQOyWgNxD0WH8sYy9grs27xM2yCdMNASvKq+Dc541/7/8KLM/NuQpw6LThnLz7aG6Zt4LlW3teUEylf2mcAFHFdPQ71Ne7FNmTEr54Em6aC2/dALueCj/8GPb7IagDPB+6B7BBDiNZMga2LesVkaW+QK47mTuAK8CIpUspPwe+1lsP5aN9hAIKzbEkn8kpzIrdSbIwVWD4rZ8fxiWHT81K47Rw6LThzJkwhBtfXU7r6L0NNbjWWoOqVbem939Ee2jYgI4gWjCiV26fbkDWKRVEZJtdnB6MyF6xaOu6sRcsgNPuMNr0f5fmtEuvKApx5C4jeOKTDcSTeofXp0PXJQF0pOK9sdWylF6wNiy5zv//+e7eXHf6bq5j+0wyNgVCQIwQihbN20RmIFU+o0dpnKl7WQb2qXuMcV2T3mJRQkb5lL5uSy0Bz/4UnrnEiC6d/5pB23PgH6+tMKJ6B/duVC8b9hhXDuTWb4t8Yy8DI0pzy6sxaJxG/7NpnM5GP/AnhjPgtd91eK+qikJmjx/C071I5Yz3oRpnUzSVH/fakmrPTXQSFUxjr7cpYAdOHcqMMaXc9sYqOwrbFbQ2GLlsgSLvlIDegJdoSMrYM9ovSNwQHXHuaUpGwrefM9ItHvyaUdctR1x9wi4UhwNc/vhCB5ujZ6CiZV2L+wr1wsy5NNVgwXQKd8bYq1kK954Mj5xj5BSf+zyc9k+j3XcgJMonw7blwOCO7BVKKdNJ0b1fHdWHJ0IBhZZ4qvm9Bm57NE4waFC/OGZnappi3PXOGqiaA+c8ZahS3nUcbFuR8Zk+Q8NGGtQKigr7Jlrw+gaj/d6L/NA+VkorRUTRgt6UyJwwajc4/FdG0eRPH8jpI2fMrqKuNcErX27t9NelInveC0zCVDMsSCv50RPiH3d9ey7vXXGYIfcsM+We8w16LxhXznFqbcQyolJpXxuVISIibh/uE5OvZZtBi/roDsNze/YjRi6qA2u2tfDEJxv5+t7jGd5PUT0rQp+LlzWduuwDXv3JIXx45eEdXyhSET1rQ+yq01U01OgnXz4NGzuuyHTy7qNZurWJJVt6R+wgoZk0zj6I7DmNPQA1m8Gi9a7MvwUhBBcdMoXV21p4flHX0zKiTQYbJVjSd5E9L2aJZm5RA8JYu4IySdKrUHlRJZzzDIzeHR7+Fix8NKfvrCwOc9Xxu/Dx2jru/2Btl5/dC6rs/5y9NmHWmXTsP3IuvRD7//bOOzyO6mrc792iLrnJXa7IvWCwDdgGY7BNj206gSSU0EJJISGBfCEJBBLzS8gHgVCcEOALIYRuerHBDmACwWAM7gYbbLnbWHJR2937++POrFbSSto+O9J5n2ef1c7Ozp49mpl7zz1tH7z+C7hvMmxdBif/Hi5fDAMmp0fYLKe28yGwe31DD16XEesIuEspdQjWXEMpdRaQJQleHY9cn4cDtQ0x+dHir+sib4je6Cu4EwZ2ZcaIHty/+HPTn6fPYXDRi2aS/vApsGN1ymWPicpN7FDd01KJMxo76NxsWxG2Zy8JYw9g0jUw8Bh45aemCXUbHDOkO7075SUUyhm0PHstGXu2tzCykiE0TOSSqdCVn+Old6f8cBgn0KgCmNvQaQ7jDATtqoZNvrfJZ6otz55tfKbdwbf1E5OfV/Gh8UyfcKvJHWuC7dW78tjBaRaoZeyqsvZ5++SVk/jnZUdF3TdaiFhHpyjXF9VQf+Db43nth1PDrz1KhU/MYGQ1zkgmXQ0FpbDg5ja/95QxphfYcx+nx7tXn8ECLU17tbXk2VMhs5/WOm0FWmxOHNWLwd0Lufetz5uFhcdK3X7j2csr6tbGnqkjWjXOgG7u2atXOc32A4zX6dvPGmPk6Uvho7/H9L1nHN6XY4aUcvura9haGXsF7bbIhjBOpRT7fV1N3zuLNpuqaw3Ln4C7J5iewYd+E65ZCkdeHnUs6CjUdBoMdfsprN/Zrgu0XA08AAxXSlUAP0Ry9hzD7/U0Kq8c7cKtI8LAa6UM7vUnDmd/bYD7FllJyr3GwEUvmb8fPgW2fZoSmeOiqoKtJN9jL1Z26M7Ntg3wbKdM7SLoSzCM08bjhTn3mZCiZ6+AYOsOca9Hcdb4Mv69bidb9sY38IRCtJqzZ3v2CpoYe3aIVirmIB5F+zD20hDGGc2z19bh7TDOjERxfvoUPHiimRhc8iqMPSfqbht3HeC5ZRV86yjnvHrQ4NmzdTlxYFcmHRJ9cpqWJsLtlBNH9WqU0xdZoMWu6NtMn7nFMPV62LDY9NpqhW5FuUwdUsoLn2xJeegcWMaecsazF807VY83fN/XOv1FljwexZXHHsLKrVUsXrszoWME9hvPXn6nGHvMpgBflH4gDQVabM9efXTPnk1uMZz/BBxyPDx/jakU2wZKKW6bM4ZAKMRNz61I2EBuimn/4axx5PUo1pZMgpq94W2teva2fWYiu565DEp6mxYws++Bou7R9+9A1JSYhc2uB79K+4JNOoi1qfoXWusZQHdguNb6aK31xrRKJrSI3+uhuj7Ss9d8n1pPhIHXyqA3rFcxpx/Wl4eXbGxY1eox3MRl+/JMW4aKj1IlettoDZWb2RTMjLF33cyh7Ixi7J3hfQeAUE6Snj0wyeOn3gGb3od3/rfN3c8e3w+t4eml8bVhCIZCJtylBc+ePa9qZuyFbb3kb2AeT0QYZxx9BrONhgE/XTl7ZvLS1JvavEBLTpMCLWmw+kJBeONX8PR3TRjU5YuMl78F7n5zPX6v4goHvXrQYOxFNltviWheAyE2orVeiDpXnHAxdOpvvHuh1v8ns8f1pWJvNUu/+rrV/RKhzuqzlwnP3iljejd6HTXvTPsa5+ylXSqYM64vvTvlca+9iBsnoWrzf8kvyZxnr8V8R8BnVeM0xl4Lnj2bnAL45j9h2Knw8k/g3bva/O7+3Qq4buZQFqzaziufbWtz/1jIhtYLHqU44C2G6r3hbVGNveq98PJP4YFjTNuob9xlDL2yCRmVN5up7mRy07vWfOnKpL1WjT2l1HWRD+AK4LKI14ID+L0equsajL1onr1aYku+B/jRjKFoDXctWNewsdshpqxxXolJzo2zj03CHNwDgRq+DHROS4+9pvi9Hr6mZe9dsIU2BnEz9mwYfRYs+l2beS39uxUw+ZBuPLF0U1wr38GAFVLUgrE3abAZuPP80QegVDg/GodxujdnT9thL6lsqq7a9uw1K9Ci/eSrurBXNuVU74XHzoV374QJl8B3nm+1ifeGXQd49uPNfOvIAfQods6rBw15eLURC18tEc1rIMSGUhGtF2xjL9rNwpcLx/3c5Pesmt/qMWeO7Eme38P8ZclVjYyGHcbpyYCxd93MoXz66xPCr6N5TAJ40FYYZ6/9q1msLof37m3TIE6GHJ+Hy44ZzAcb9rD0ywQah1vGgcrPXIGWpoXDICJnzzL2fNRT35pnz8aXC+c8AqPPhDd+aVqDtLFQdsmUQYzuW8Kvnl9B5cHkcizDxdKcNvY8ioOeYghUQ72JtGlk7IVC8PGjcPd4+GAejL/YVNkcf1FGFkvcxMkPfU7Am0/X6o1Oi5IQbY2AxdZjAiZss6/1uBKIvVFPE5RSnZVSTymlViulVimlJimluiql3lBKrbOeM3eXcRk5PhWu5gfRB5g6Fbux169rARcc1Z8nPtzE+h37G97oMtBUuSoshb+fDhvfTUbs2LB67GXKs+f3KnQrl0HSOXuRnPoHKO4Nz1zeqBRyNM6Z0I9Ne6r5z4bY2jYA4QlFS8befd86nPu/Nb5ZmfxQjCGFsWDCOO0CLS727NkTsVRW44xY9Q+0UKCl6XykhlxyaTD2UurX27kG/nI8fPEWnPa/5uFrfdX87jfXkePzcLnDXj1o6JcZi2cv6SbCHRhFROuFaAVaIhl7DnQfYXpxtVKUpDDXx8yRvXhp+daUL2QEQsbYy0SfPY9HUZzXME61mLNnhXF2q9lAqaqE126ER74BX6e2KEgk5x3Rjy4F/oT6yHnssL+8TqkVqhWieUXrLc/eLO8SIIYwzki8fpN3PO5bZpH1jV+2avD5vB7mnjGWPQfqmPvqqvh/QAQhq1iadthg8iio9loh2db/NFyNs+IjeHAmzL/a9Cy8fBGc9sdmxbgEG8WXqg/dar5yo2OvdWNPa32z1vpmoBQ4XGv9Y631j4HxQFkS33sX8KrWejhwKLAKuAFYqLUeAiy0XgtRaLoCVh9sfgOrjcPYA7jmuHLy/V7ueH1N4zc69zMGX0kfePRM+PytuOWNC6vH3hadKWPP6PIOvs1B3VxnoURbL0Qjvwucfh/s/txUuWqFk0b3ojjPxxNxFGoJBcyEoqVcleI8PyeNbl4uuSFgMflbmFKKWtuzV+/enL1QGsI4vS149m6eNYo/nH0oEJE/CZw2tjc15FCg6hNqxdEqa16Bv0yH2iq48EXj1WuDL3bu57mPK7LCqwcNYZy19bGEcYpnL1G8nobcyDaLOXm8MP2XsOdz03uvFWYf2oevD9bz9rrE8spaoj6gUWiUN3MT7e9PH8LDF09swbPnA2shTtkRA8feYIoh3TfZ9LJMQ3h2QY6Pi6cMYuHqHazaGl/lU19dJftVYUa9O9FUYPcLvsJn6gh4daBxD+G28Hhh1t0w8TJY8id4+fpWPaqj+3bi0qMH8c8PNvGfL2JfaG1KSJs8Q6dz9jxKsd9jGXu2tzZQx7nb/2gW+vZ+BXPuh0teMyH8QqtUeMvoWv1luy7Q0h+oi3hdBwxM5AuVUiXAVOBBAK11ndZ6LzAbeMTa7RFgTiLH7wg0TQKPtrIdj2cPTNL8ZVMH88pn21i2aW/jN0t6G4Ov62AT8rX29XhFjp1Kk6eWaWPvwdBpXFZvIpO36Qanckpy9iIZNNWUKf/wb7Dm1RZ3y/N7mTOuL698to3K6thCSoLB1j17LaHDE7i4PhYVjzKhh4C7C7SkoRpnpDc+bOyhuHDyQM4aX2Z9b8P+95x/OP7cAnwECAXqm72fEFrD4t/DP78J3azV3AGTYvroPW+uJ8fn4QqH+uo1JZ6cPSnQkjh+n9FdfTDU0DKktcti2MlQdoQJnWslb3fq0O50LvAzP8U99+w+e5ko0GJz3cyhTBvWo+UCLbaxZxUa4bAL4KolJjf2he+bcXVfanLFIrlw0kAKc7wNBdhiJKe+yoT/ZZBoxWQCTQw7TyKhkR4PnPJ7mPx9007m+Wsb+qhG4YczhtK/awE3PvMpNTGEiEcjpDW+rPDsKQ54SsyLg6bX3rGBd5n89fMw8VK49kMY9802LmjBpsJbRue6rfRnu+v6CMf6H/478IFS6tdKqV8B7wP/l+B3DgZ2Ag8ppT5WSv1VKVUI9NRabwWwnltOHOng5PgaT1yi5azUtZXEHIVLjxlMt8Icbn9ldfNCEEXdTVuGHsPh8fNh9UtxHz8mKjcT8uSwm5KMhXGCaUvwbmgMA2seY2VoQPj9ULLVOKNx/C+g5xgTPrF/R4u7nTOhH7WBEM9/EttkSNuVPuM09sJerBQsV3kiPXtuNvbSEMaZG9HrraHPXpPvbfIZ+zpWwRrr/SQGmNr9pgfVW7fCmLPNam6n2AI0Pt+5n+eWVfDtowbQvTi+haR0cUgPc232iqEiqBRoSZwca0GsPhiK3lS9KUrBjF/Dvq0mD6il4/o8nDKmN6+v2M7ButarFMdDQ85e5r0q0T17XpS1EKfCVX490Lm/yZE96XZTxfTPR8bcHy5WOhX4+dZRA3hx+Ra+3N166kAkeYEqanyZNfaiUa+bGnuaUCLRFkrBzFtg2o2w7FFTbbKFMOP8HC+/PX0MG3Yd4O4310Xdpy1CWuNV2ZCzB3t8VkXVKjOPGKy/NKGwJ/0uo2G67YEtPjNevu79QaMKp24g1mqctwGXAF8De4GLtda/TfA7fcDhwH1a68OAA8QRsqmUulwp9aFS6sOdO1Mb/uEWmoYkBaMU8Yg3jBNM36Vrji/nvS928/a6Xc13KOhqBqfeh5pJ42fPxP0dbVK5mZqC3oDKqGcv0usSuZoYykmDsefLhTP/YpqWPn9tiytEo/uWMKJ3ScyhnCHL2FNx9sJJZcBiowItLq7G6dW24Zy6c7BbUS6PXHIE0HC+Ne1XZje8f/HaowGTswcwKPgVj/lvxVO/n4T4eiM8eAKsftH0zjtjHvjzY/54tnn1AM4eX8Zjlx3J7HF92tw3msdFiA07D60+qCOqcbZxtxg4Bcpnwtt/bFQJsCmzD+1DdX2QN1ZuT5W4DU3VMxjGaRMtZ2+/zqO+eh8Q4dmzjQCPB466Eq58B7qVm4q4T15kCpWliO8ePQif18MD//4i5s/kB/dR63PeEKhsUjwtIc+ejVIw7QaYcTN89rTRcwtFxI4eUsqZh5fxwOIv4g6BBRPG6SPoeBinVyn2+Ky2CVbU1ODQV+zK7W9yGoW42OyNWBzNYPGiVBDPCLgMeBJ4FtitlOqf4HduBjZrrd+3Xj+FMf62K6V6A1jPUV0eWut5WusJWusJ3bt3zN4fkcbe6L4lzBjZs9k+dhhnHfFd0Ocf2Z+yLvnc/urq6JUg7calZRPNwPTJv+I6fptUVbA/1/yeTBp7kUQae7qVHoVJ0WMEzLwZ1r4KSx+KuotSinMnlPFpRSUrt7Q94OgEwzhtYzMVTizVqECLe6txemxjL8UD4uH9OwOwZW81fq+iOK/x/+qpKyfx05OGMbqvmWjVeYzhfKN6iMnelXSpWBz/l36xyDRKr9oMFzxlwojj+Gd/vnM/85dV8J1JAyktyg6vHpjrY/Ihpc0bfEchWvEHITb8lkc6EBnGGcv5M/2XZvV7yZ9a3GXiwK707pTH8ykM5awP6oyHcdo09eydN7Ef+ynAH7C8auGY+SaylQ4xnvbjb4JVL8K9R7Ua5h8PPUryOGt8GU99uJkdVbFFWxSF9lGfU5KS70+GPTrCuxgKoQgRimvaGoWjfwgn/94sfD1+PtQdjLrbL04dQad8Pzc882nUBfXWsAu0OF3R0qMU1eRDbidY9QIAg9nEzrxBjsrlVrb6+jotQsLEdNUopa4FtgNvAC8CL1nPcaO13gZsUkoNszZNB1YCzwMXWtsuBFqv3dyBiTRQfnHqyKgGi91UvUbFvnoPpsLdj08YyootVbz06dboO+WVwLeehoFHm0bhH/09ru9olcrNVOZk0thrPmlREaFy2hN/OGzMHHEFDD4OXvsf2LU+6i6zx/Ulx+vhiQ/b9u6FgiZESMVpoJw61nhGTm3SMyoRPEpRq+0wzmpq6oPsPVjX+oeyEI+2DGdvav//9iQ5ENL07Zzf7Nod0rOYq6aVh1/b13ExZrIYiud81NqUeP/7GVDUEy57C8qnxy3z3QvXkevzcvlU5ytwJooUaEkcW3d1wVDYVokpB7L3WBMu/J/7WsxH83gUsw7tw+K1O9lzIDX3ibpACB9BPA54LiIXFfL9Xq489hD26XwKVC0EAyhth3FGMQK8Ppj6E7j8LSgohX+ea0L9a+L3LDXliqmDCYRCPPjOhjb3rQ0EKWY/wdzOSX9vsnxNhLFXfxCPDqFTsSp55OUw6x5YvxAeO8dE2TShS2EOv/zGSD7ZtJdHlmyM6/ANrRccLtDiUeaa7Xs4bPkIlj5CX3aysyB7IjTcRA15bC0Yyp/0uU6LEjexjoA/AIZprUdprcdqrcdorccm8b3XAv9QSi0HxgG/BeYCM5VS64CZ1mshCpEGSkuDrt1U/b95sRVfiGTWoX0Z3quYO15f03JZ7JxCOP8JOOR4eP4a+O9f4/6eZgQDsG8ru73GYxtZ0jpdRJsE5tCQPxLMT2MZYo8H5txnwjpbyCHoUpjDCaN68tyyCmoDrSeLJ+rZG9armI1zT2VIz+RzNLwe1eDZq6/h7jfXcc4D7yV93EzjCxt7qT0HI6/X/Jy2/0/7lQljGuQxYW6hWI3P+hp47ipT4n3YyXDpAtM7M07W79jP859s4TuTBmSVVy9eYvJECVFpyNnTLeaatshxP4dgHfz79y3uMntcXwIhzcstLS7GSSAUIk/VoeIIU04VkeHCq35zEkpBJVaRrwM7I4y9VhTYa4wx+I6+DpY9Zip2bvh3UnIN6FbIaWP78Oh/vmyzh9y+6no6c8BE8ThMCA831V9kXtRXo9CE4qnG2RqHfxvO/Ct8ucS0looSbjzr0D5MG9adP7y+hs1fR/cARpVbkzWtF4IhDef/C/pPNsWAgN0F4tlLlL+MeIR5nOm0GHETq7G3CahM1ZdqrZdZoZhjtdZztNZfa613a62na62HWM+pC1pvZ0QaKC0Nugc9xRxb+0ce7HRt3Mf3ehQ/PWkYG3cf5F+t5Yv58+G8x2DoyfDSj+G9P8f9XY3YtxV0iB2e7hTn+TJSQS+6sWcGw3sCswnkpzlUuKQ3nHanWXVb/P+i7nLuxH7sPVjP6ytaz2vRIbv1gnOriR5FowItu/fXsWWv+wq1eHXAhAuleLCOnONVxuDx/Mh7KF/mDQu/1rHkEFZtgYdPgU8eMwUJzvk75CZmyN/9pvu9eiBhnMlg664+GGpoqh6r8dx1sGnQvPRh03ImCiN6FzOkR1HKQjnrg5o86uLKSU0VTXP2tIZPQ9a1s/mDhqiRtu4rvlyY8SsT2unNMT35XvlZiyGHsfC9aYdwoC7II+9tbHW/fVWV+FUwow3VW6Paim6gbr8xoFLZ5WzMWab5+pZlRscHGrdbUEpx65zRANz03GfNC9e1gKnGGYo/pSLFeJQyRb18uXDuo6Z3MrCnUDx7iaCUKZLmxtEkVmPvC2CRUupGpdR19iOdggkt09jYa/m0+1L3IpTgzea4YT2YOLALdy1c13qlNH8enPN/MGIWvPZzk5CfKFaPva26NCMhnBA9jDNHmd+7KjQgM/1URs2BcRfA23+Ar95v9vaUQ0rp2zm/zVDORAu0pBLTZ6+h9YLWcLAuEPMgmS34dD3BNITgRF6vWyrbNoK1x8ejvW5seN3WLfur901+3s41cO4/TEGCBIuTrN+xz3j1Jg+gm4u9eiCtF5IhHMYZCIWvY088+px6vTFY3ope000pxexxffhg4x4q9iZf1KkuYDx7+DLfC7KpXgaWFvKZHkSNyoUvl7QexhmNfkfAlW/DEZfD+/fDA8fA5g8Tkm1E7xKmD+/BQ+9uaHVMP1hlirN5C5019hZcdyxjyzpRoa1qkl9vNJ69FLbDAWDEN+Cbj8OutfDwqbCv8aJqWZcCfnLCMN5aszPmytjhpuoOh3EqpcK9MSnsBt9+lt8GLqAqv5+jcrkVra20WxcOJ7FeNV9h8vVygOKIh+AAkQZKi8aetT3RRtlKKX520nB27qvloXc3tr6zLwfOesjkZyy8Gd76XWI9SKxqUZuCXTNn7PmaXwK5lmfvALmZu6ZPmmvK4D97ebP8AY9Hcdb4Mt5Zv6vVUBI7jNNJY8/MdRRBTy7UV6MxjZhj6YWWTXh0gGAKK3GGjxvv6oGCLTkDeCo41bxupT8USx8xkxV/gQnbHHFa4oICf1q4nny/l8uPcadX7/+d2ZBpEK1KohAbOREVi+3L2BvPeVzcC476Hnz2FGxdHnWXWYeawgcvxDiZbo36QJA86h3x7BXl+jhiUFf+dtGE8Lay0k58mT8Kvny3oal6PAZLTqHpE/ed+SY8+8GZsPAWCMSf43jVcYfw9cF6Hv+g5YXDmirj3fIXdYv7+Mnwp28exvgBDQZmeY8iZh3ah7UhqwLijlUmZy/ZAi3RGDIDLnjSNBl/6OTwXMTmwskDObRfZ255YSVfx5BbGgqZapzOF2ih0UKr7jKIeYFT8TpQqdaN/PGcQ+nTqfmikRtHk1hbL9wc7ZFu4YTo5Phi8+xBchUWJwzsyowRPbh/8edtF9nw+uD0B4yHavFcY/TFa/BZN9iN9Z0zZuzltJKzV63zYqr0lxLySuD0eWawebV5J5KzJ5gB76mlm5u9Z2P32XM2jNPoK+jNhUBt+BSorkusOa1T+HSAkEqHsRff/gpAw6OBGeZ1KEq+TbAeXvqJyccYdAxc9qap9poE63fs44XlW/jOpIGu9eqdM7EfI3qbioLi2Uscf0SfvXAYZ7zz7cnfh7zOxkiJQv9uBRzWvzPPfVyRhKQGbff3dMCz5/UonrhiEscPb6iQrYB1+WNh22cUBK1smESMgMHTTCP2Q78Jb98Bfzketn0W1yHGD+jKEYO68pe3v6AuEH0Brm6/MfZyi9OYrx6FWYf24envTW62fTed2K2LYecqq/VCmootDZpqKo0f2Al/Oxn2NBSz8XoUc88YQ2V1Pbe9vKrNQ4VCQbxKx+7BTRNKQWQhUTvnNq7Fmg7MGYeX8cxVU5wWIyW0etUopV5QSj3f0iNTQgqNiUwCb2nQtS/lZK/p608czv7aAPctip5v0QiP11S4Gn8xvPO/JqwzHoOvcjPkdWJ7rT9jxl60XJ5N2uTp7Sc/sys4AyaZpPyPH4WVjS+vsi4FTDmklCc/3By9JQYNOXtOVKGzCRt7nlwIVIfrmh50m7FHgFAaPHvxLh4oK+ciYN+qQ03Crw7sgv+bA//9i2mpcP6Tph9mktxle/VcnqsXDJkJrfTZSxw7kqQ+Mowz3oElvzMccx2sfwM2vhN1lznj+rJ62z7WbGteGTEelN3f0wHPXlQUrM8/FNAM3G95NhM1AvI6wZx74bx/wv5tJmT77T+a4mYxctW0Q9haWcNzy6Ib1vX7TbmE/JLsaW21TpfBjtUo0uTZs+l/JFz4PNTtMx6+nWvDb43oXcIVxw7mqaWbeSdaH+II7JQKnQ05e1oz79+fc+kj/w0v1kgOc+w0XSjUWmfOCZBC2rpq/gDc0cpDcIDIkKSWBl17c6JhnDbDehVz+mF9eXjJRrZWxpBP4fHAaf8LR34P/nOvKdwSijGEr6oCOvWjsro+c8ZelBX/W+q/zS/qL2al7p+ZnL1Ipt0AfQ4zXpqqxtXpzpnYj4q91Sz5fHf0z2ZFzp4lijcX6mvCtr6bjL1QSOMnQCjN+RZv/vjYNvcxYTgQtCrQhXN+ALZ+YiZ7FR/CGX8xzdJT8L9ft30fLy7fwoWTB9K1MI2tRzKA3bxeOi8kji+i9UJSnoEjLofi3rAgetTHKWN64/Uonv8kSe+e7dnLEmNPARtzR4DHz4DqFdbGJE/I4afAVe+b54U3w0MntVgApynHDu3OqD4l3L/486j940IHvgagsFNmwzijYU+q14TKYOdqvIRSn7PXlD6HwUUvm5D5h05u5D299vghDC4t5OfPftpqtIodZeN0GKeds7dySxXvb9jTcP1KpEPMRM4R/V5TYsmFtl7rxp7WenFrj0wJKTRma0Rhh3SGcdr8aMZQtIa7FqyL7QNKwUm/gyk/gA8fhBeubT3XyKZyM5T0zaixV9aloNm2CrrzaHAmGk/SxnLceP1m4l5fA/OvamQonzCyJ53y/fyrhUIt4WqcDhp79iAS8OQ1TLpwVxhnIKTxEUyLZy+Swd2L2txHoQhpTcA29uwwzk+fggdPBB2CS16FseekTK67Fq6jwO/lMpfm6kXSMLkRay9Rwjl7ka0XEpks+vPNYtbmD2DNK83e7l6cy5TyUuYv25JUQSdPwFqU9GWJsacUdZ4c0+vMJhXnY2E3OPsROOOvprjIfVPg/XltLq4qpbhqWjlf7DzAayua9z/UNcbYyyvJAmPPel6ny6C2itLQrszUQuw5Ei5+xVSxfPhUqFgKQJ7fy2/PGMNXew5y58K1LX48FDb2HC7QgikWUx/U7KsJUFtvzg0J44ydyHtdjs+D1u04Z0/ILiIrabW0Yp3Kk7Ff1wIuOKo/T3y4ifU79sf2IaVgxs1w7M9MWOKzV7YdalK5mUBxX2oDIUoyZOzl+b1MH96jxfcduSeWDoETb4PP3zTheRZ5fi+nH9aX11Zsi5pDaa8mehw09uxVsKAnx1TjtAI5q+vdY+wFbc9eGo2984/sH9N+ds5Fg7FXB2/8Cp7+LvQZB5cvMivRKWLt9n289OnWduHVgwZjTwq0JI7f19B6wbbBElbnuG9Bt3KTuxdlAXD2oX3Y/HU1H321N8EvABWsNX/4M5+zFw2F5cgc0DwfLfmDKxh7Nlz1Hxg4BV65Hv4+B/a2Xrn5pNG9GFxayL2L1jczrD01ewngReW0vRiVbuzx1y7Skk8tOlN5cKXlxuDL6wSPzIYvTb/YowZ347yJ/fjr2xv4rCJ6R7JEe96mGvs6tQuk7T5grg3x7MVOY8+ee00m90regelZ0jCItRU7nKrY4muOKyff7+WO19fE/iGlTFPd42+CT5+Apy+J2jgcMP2DqvdQU9ALIGOePYDVSeaIpIUJl8CQE+GNX8KO1eHNZ08ooy4QYn60nlSW18fJAi0Nnj1TjZNwGGfsOSVOE9R2GGd6zsENvzuF26zeTbFQFwiFc/YO+fh2ePdOc35853koanmhIhHak1cPkLClFOCPDOPUSerT6zPjwc5VsPyJZm+fMKonuT4P81vIJ4uF7PPsWcZe/0np+5KSPnDBU6Zn6+YPTSP2j//RYs6816O44tjBfFZRxdtN8s+8tZVUqaKsilVbq8vCf2e0y1mXASZyorgXPHoGfLEIgBtPHkHXwhxueGY5gSiVpkPWQkY25OyFtA7LuHOfWSSW+2HsROrK5/GYPntZdG3ESpvGnlLKq5T6fSaEEWLjwskDw3+35I63T8ZUnZLdinK5bOpgXvlsG8s27Y3vw1N/AifcBivnwxPfgUBt832sHnv7czNv7FVVGyOpMKf5iqFj17RSMPseyCmCZy4Nl9ke1acTo/uWRG12H/bs+Zwr0GIXwgh4ckw1Tmu7m8I4g0FNDoG0DdRKqZgHC49S1AaCBLU5N321e01O7Gn/a1qepJA12/bx8qdbuWjKQLq0A68eNAzU4tlLHL/HrsapCSVaoCWSkbOh9zjTd6/JWFCc52fGyJ68tHwr9Qm2a/GEc/ayxbNnNbYuLE3zFymYcDF8713oOdqkATx+PuzfEXX30w8ro1dJHvcuWt9oe059JQc92dFZyz7L9lIMhWZhK0SG8+BK+sDFL0OXQfCPc2Dta3Qq8HPzrFF8VlHF397d0OwjdkqF0zl7HqUIhcy1C7Brv3j24qXx2KHbbxin1joIjFduNGXbKV6Popfl3WuxQIv9nML/2qXHDKZbYQ63v7I6/pyKydfAKX+ANS+bAai+SbEXq+3CXr+5oWcqjBPCzic6FzSf4GY8Zy+Soh4w627Y9im8dVt487kT+rFya1WzEJKGapwOevbsKl9aw+YP0Fb+iJsKtARCobSHccaKUlAbCLGNrjwcOIFl0/9uvHpp4E8L11GY4+PSo9uHVw/gkUuO4AfTh9C92J3tI7IBO4wzEAyFKwEnZewpBTN+DZVfwYd/a/b27EP7sPtAHe+ub73iYUt4gnbrhSzz7HkzdA52HQQXvWgKNq1fCPceZRZam5Dj83DpMYP4zxd7+Oirrxu211dR7S3JjKxt0GjaabWT0U5MRYt6GJ32HAmPXwAr53Py6F7MGNGTP76xlq92N+5/q7MkZw9lcvbsME4x9uInUleBkG6fBVoi+BiYr5T6tlLqDPuRTsGE1glX22zjpEvlOVmU6+Oa48t574vdzUI/YuKIy+AbfzID0GPnQN2BhvcsY2+3zxh7mfTs2YarP0o5Yscv6uGnwPiL4N27wiXLZx3alxyfhyeaFmrJAmPPXgXr+/UHAAysNpXMDrosZ8+ngmgHW1jYKAW19SFCePh14CIqSye0/aEEWLPN5OpdNLn9ePUADulexI9mDnVl2E220KjPnt1UPdnJ4iHHwaBj4d+/h9rGYfTHDutOSZ6P56OFqseAN5yzlx3GHlgLir4MLjh4vKYVyxX/hk79TETN05dC9deNdvvmEf3pXODn3rcaKnnmB/dR68sSz17kaWYZe2mvxtkSBV1NY/u+4+HJi1DLn+A3c0bh83j4n+c+bdy8PNzz1mnPnjn36sXYS5jIsSMQTLxwlNPEetV0BXYDxwPfsB6npUsooW1ircKZ6knO+Uf2p6xLPre/urrFfm+tMv5COP1+Y7g8eibUVJntVRWAYgemR1i6jb3hvRoGM/tXRLsBZsUc8cTfQtfBpshN9V46Ffg5eXQvnvu4gppIIyoL+uw11aEvZAaXapfl7OVkiWfPoxQ1gfQbynctXEtRro/vHj0o7d8luIuGnL3IMM4UHHjGr+Dgbnjvz4025/q8nDKmN6+t2JZQ+Lc3lGWtF5SyPHsOLKL0GA6XLoBpN8KKZ+HeSbBuQfjtwlwfF08exIJV28P9DYtC+6jP6ZR5WaPQ6DTrPhwAnekwzkjyOsG3n4GBR8OzV9B73eP87KRhvL1uF8981JBnmi2ePbvPXtjYs3P2smJi4z4CIbtIlfv0F5Oxp7W+OMojPbFEQkzY12pb0ZSpPiVzfV6umzmUFVuqeOnTrW1/IBqHngdnPgibPoC/nw7Ve6FyExT3Yq+1KJtuY++p703mnZ8dBzToMFqlJUfDOG1yCk07hqot8PL1gAnlrKoJNC6dHTQTI+VzMIyzySDi02Zwqa5LLP/GCQJBU6CFLDD2FITLZQPh6qapZPW2Kl7+dFu78+oJqSHcVD0YIqQ1SqVoEbHveBgxC5bcDQcaR4rMGteHA3VBFqzaHvdhw549X7bk7AHozHr2IvH6TcuLSxcYY+UfZ8ILP4RaU1n7wskDKMzxcp+Vu1ekDxDMzQ5jj2hhnE6PyTmFcP4TMGQmvPhDLuBlxg/owq0vrWS35TnToWypxmn67NkeqZ2WfNJUPTGMHnV2OAHiJCZjTyk1VCm1UCn1mfV6rFLqF+kVTWgN27PX0uTPNlLScVLOHteX4b2KueP1NQkn0TP6DDjn/0xj6P+bBdtXhnvsAZTkpfcmWZTra9ZjL2s9ewBl400bi0+fgE+f4qjB3ejXNb9RKGdDzp5zE3aPR+FRMH/Y7YAJCQI4WO8iz57VekFngbGHUuF8i3Rx14J1FOX6uPQY8eoJzfGH++yZpuop9QocfxPUH4S372i0+chB3ehVkhe96nAb+LPOs2ctKDpl7Nn0OQwuX2zCO5c+bCp2frmEzgU5nH9kf15YvpX12/bSSR0glNfFWVmjYXn2HAvjjMSfD+f+A0bMwvPajTwwcDH7awP85sWVAGhr4RUHUyrAnHsHagPhiuN2GGdSObcdmECoHRdosfgLcCNQD6C1Xg6cly6hhLax7ZJgS6GUqtkfKcPrUVx/4jA27j4YtSpkzIw4Dc57zLQW2PIRdCqjsrqeolwfPgf6mUSr2JdVF/UxP4ayifDSdXj2VXD2+H68u343m/ZYyeFZkLMHpiLnxiLT+60gaMJ03VSN026qrh00mm2MZ69Bd0n0mo7Kqq1VvPLZNi6eMjBqgSJBsO+LJowzxRPF7kNh3AXw37/C3q/Cm70exTcO7c3itTui9hRtVd5Qlnn2rLypjBVoaQ1/ninccvHLRrCHToHX/odLJ/XBqxR/fvUjAFR+Z2fltGh0puV3ZqFvKl/kj3VKnMb4cuCsh2DMOZS+P5e/D3qD55ZV8NaaHQ2evUz1BGwBpVSj1lK79lmePcnZi4sLrL64gZB7IpSaEuuMukBr/UGTbe5Zqm+HnDKmNwBd2pigpWsB5/jhPZg4sAt3LVyXXA+1oSfA+f8yldNKh1JVHchocRZo8I5GMzCzagHM64Mz5pnm9M9eyVmH90EpeNL27lm9fbwOtl4AM1E76CkEoCBoQoXcVI0zpDU5Kjs8ex4FNYH0DTB/WriOYsnVE1pBKUWO1xMO4/Skeh1u2g2AgkVzG22ePa4v9UHNK59ti/65Fsg6Yw+TN+W4Zy+SAZPhyndNq4b37qHnYyfw/RH7+GiNaSPgKejqsICGpuPvb3KvY1nJcc4IEw2vz9QgOPw7HLX5b/yh5Al+8cynVNeYBQone95C89zaXfuNXB4x9uLittPHcMLIngSClmfPheqL9ba9Syl1CNYClVLqLCDBhC0hFfzkhGF8fNPMFnNsVJPnVKOU4mcnDWfnvloeendjcgc75Dj40Wdw7E+prK7PaNsFaPCWRF/tyrKruutgOPl22Pg2fVb9jWOGdOeppZuNh1c7X6AFjB7rQx7ILaEgZFYVXeXZs3P2ssGzpxR1EcZeKj17K7eIV0+IDZ9XUR9IQxgnQKcyU6n5k3/CjlXhzaP6lDC4e2HcDdb9upZ6lUPqrdLECHv2HK7M2IzcItOv81tPQ20VV39+JT/xPQmAvyg7wjizIme+LTxeU2X8yCs5q24+3zvwZ/71vqlu6ryx11h/dkqAePbix+dVBEPaNFV3w3nZhFjvhlcDDwDDlVIVwA+BK9MllNA2Ho+KqZhCOlcgJgzsyowRPbh/8edxh9o0o7AUvH6qquvplJ/ZG6Q9f45aoCUbr+nDvgXDT4OFt3DpkINsqazhnfW7jMcP8PicnVR4vYpgKAQ5heRY+TPVLmu9YAq0ONwjifQuNTR49dpPXz0hPfi9HgIhU40zLfk+x/wYcorgzVvDm5RSzD60L+9v2MPWyupWPtxE1lAtAU/2eNEUqQ+/TinlM+Cq91BjzuIb3vcAyClKcwP4GGl6qmVtjzOl4KS5cPR1fMu3kAv2WBVmnc7Za2G7tF6IH6/H05Cz50L1xWrsaa31DKA7MFxrfXQcnxUcINx6Ic0rED85cRj7awPct+jztneOgcrq+oyHcdrWXrQKVVl5TStlVhLzu3D08hvoma954r+bwjl73izw7AVCGvz54WIJSYX6ZhjTVD1ocjIcJtpkJxWs2FLJqyu2cfHRg+hU4Hy4qpDd+L0e6qym6mkJASvoClO+D6tfhE3/DW+ePa4PWsMLn8ReqCVH1xHwZEcIJwBKpaGGborJ7wJnzGP7yX/lw8KplI1ITz/PeMnK8bcllIIZv6Jm6s8Z6zHhsE4vGLZUNVeMvfjxe1Q4Z8+N2ovVYHsaQGt9QGttZ3s+lR6RhFSQzmqckQzvVcLph/Xl4SUb41p9bQknjL1wzl6WhP3ERGE3mH0vnp2ruLP787y+chs1tVbD1CzI2QuGNPjy8Wu7z557PHshnV1hnJHoFLkI/rRwHcV5kqsnxEaOFcZpCrSk6UuO/B4U9oAFvw67wgaWFnJov84xV+XUWpNLLcFsKIZiYTx7WW/uAdDzyLOZcP0LFBV3dlqUqLihEmLe8T9j7bgbqNNeikv7OipLS9eqGHvx4/Uok7PntCAJ0ursVik1XCl1JtBJKXVGxOMiIIuWzoSWyIS7+UczhqK1KeGeLI4Ye63m7GUxQ2bAEZczace/OEIvZ922SgCUw4VFvKrBs5djFUtwU4GWbOuzl2pWbKnktRXbuWTKoMx70QVX4veZAi1BrdM3UcwtgmN/Cl++A+sXhjfPPrQPK7ZUsX7HvlY+bKgPavKoyy5jz2XDipA8Q+fcCDdW0H/YYY7K0VLItTRVjx+fNzKM0336a8uVMQw4DegMfCPicThwWVolE5IiU2GcAP26FnDBUf154sNNrN+xP+Hj1AVCVNcHMz4BzfGZyyB6n70sv6hn3Aylw/hT3jwK6/cQ0srxwgReK5EZfz452g7jdI+xFwwE8CqNcjgcFpqfk6lYVbxrgfHqXSJePSFGTNElbcI403lPPPxC6DwAFv4arJCp08b2xqPg+Ri8e/XBkGXsZUePPSF+3vrJNBb9ZFqz7VpbxTGyfUy2yMlz/hxsSVXSVD1+fJ6GAi1upNVZodZ6vtb6YuA0rfXFEY/va62XZEhGIRkydE1ffVw5+X4vd7y+JuFj2A3VM23sPf29yfxwxpCw0ecqcgrgjHl01pV80/smgSxIpfV5PGFjzx8yhXtqXFSgJRSwig1lQc5eqr0on1VU8vrK7Xz3aPHqCbHj93qsMM40G3u+HDj+F7DtU1jxDAA9SvKYfEgpzy3b0mY4ZH0wRJ7KMs8eWV6gJcsYVFrIwNLCZttFh/HT0rUqTdXjx+dV1FvVTN2ovlhnhh8rpa5WSt2rlPqb/UirZEJSNHj2MkNpUS6XTR3MK59tY9mmvQkdwzb2Mt16YUTvEn44Y2hUXbnimu4zjvpjf45fBQnifHnvcM6eSz17IctAVVmQs9d0UE52wnOXlat38RTx6gmxk2OHcYYykO8z+izoOdpU5gyaMWHWuD58tedgm2NLXTBELnWEvNmTZaKUCnsDNuQO4z++iQ5L5E407sjZyyYih48fzRga/ttV9QmyBNuz51LHXszG3t+BXsCJwGKgDGg7gF5wjIYCLZm7NV56zGC6FeZw+yurE0pId8qz1x7Im/pDPi84lIOqwGlRrGqcIfAX4NfGcKquDxIKueMuqeuzx9hL5cT6s4pK3li5nUuPHizXmBAXfq+H+qBOT1P1png8MP2X8PUG+Oj/ADhpdC9yfJ42C7XUBzX51KGzydijYZHmd33v5ddFv3RUHjcROWKEtBbvXpzY87/OBX6uOLahxY7YevHj9XjCBVras2evXGt9E3BAa/0IcCowJn1iCakik+dkUa6Pa44v570vdvP2ul1xf77KaWPPhRdwGI+XXlfO5+A3n3NakohqnHnhPnsANQF3ePfCYZxZmLOXzLLinQvWUZLn4+KjByYlk9Dx8HlMCFPawzhthpwA/SfB4tuh7iAleX6mD+/Bi8u3ErBCqaJRHzA5eyFfFhl7qsHYE1slPiKNu5D9ws3jdIaxhw+vUuT5veT7TeSPePbix+81i9hat++m6vXW816l1GigEzAwLRIJKSEcxpnhc/L8I/tT1iWf219dHbcnx2nPnhsv4EgKS7rQz+HqXxDZZ6+AHMuzB+4J5dSWsefxZ4FnL0VhnJ9VVLJg1XYuPWYwJXnOG7GCu2gI49SZqeSnFMz4NezfDu/fD5iee7v21/LeF7tb/Jids6ezydijIYzTrZX8sgHx6sWPvTBjn3NdC82Y5hVbL268HkVIQ6idN1Wfp5TqAtwEPA+sBG5Pm1RCysh0Im6uz8t1M4eyYksVL326Na7POm3sCamhec6eGaXd0mtPB9tfGOedC9ZSkufjoikDU3I8oWPROIwzQ2NK/6Ng6Mnw7p1Q/TXThvWgONfHcx+3HMppt17A73w4exgVaaholy8pZpbIyoe2Z8/ti7KZxJ7+2Zds5wIzt/KKZy9u/JaFbDdWdxtt9dm7Uyl1NvCK1vprrfVirfVgrXUPrfUDGZJRSAB7JceJ2+LscX0Z3quYO15fE65eFAtOFWixceNqTTbis2LbySnAS4hcKzCg2iUVObVVFEJlQTXOphPrRBa3P91cyYJVO7hMvHpCgvitSnShUBqbqkdj+k1QUwXv3Eme38tJo3vx2optLVb3Na0X6iGrPHsN1612qVcgGwhp035B9Bc7tmHsaeLZc11P4SzAXnitD7pzwaYt8349cDrwrlJqo1LqMasq52FKKVkayGJUsz8yh9ejuP7EYWzcfZB//XdTzJ+rrK6nMMcbXkHJNG68gLORsGevoBsAXaxaTm4L48wGz14qBuU7F6ylU75fvHpCwvi8HuqspuoZjRbpOQrGnmtCOau2MOewvuyvDfDm6h1Rd6+vrydX1YM/i4y9CGvPrcUdsoGQxHHGjaeJZ69LgRnTMuadb0fYY3EgGHJlKHZbffbu0Vqfr7UeCEwCngEOAZ4C9qZdOiFh7GvZqZCH44f3YOLALty1cB0H6wIxfaayut7REE4XXr9Zic+r2FJZzVOrTXGWbqoKIObzwGnsME6v33kvWLKtF5Zv3svC1Tu47JhBFItXT0iQHK9ViS7Txh7AcTdCKAiLb+eowd3oXpzL/GUVUXcN1FUDoPzON7S2aZyz587iDk4Reb/TVtV70V7sNM3Z62KFcYpnL3587dyzhzKMBWZbj2OBdcAdaZZNSIJwGKdDZ6VSip+dNJyd+2p56N2NMX2msrresRBOIXV4PYrNX1fz9Apj5JUoMwFzTc6e7dnLgjDOZJ3cdy5YR6d8PxdOHpgSeYSOiR3GGQzp9PfZa0qXgTDhEvjo73j3fM43xvbhrdU7w2H/kQQtYy/bPHtaPHsJEbm2lUg7p46OnZpnP3exwjilqXr8eNt5zt4bwH+Aq4Fa4Lda6/Fa65O01jdnQkAhMRo8e84xYWBXZozowf2LP2fvwbo293fa2JMV19QQXgHTpsxzsfUvdUsYpwqZSaTHm+uwJA15An6vedZxZO19smkvb4pXT0gBpkBLiKB2KARs6k9MHt5btzJ7XB/qgiFe+2xbs91ClrHnyaICLUpJy4VUYHL2xFiOj8Y5e8N7FVOS56Mo1+ekUK7EHw7j1K50L7e1bvwF5j41xHqUK6VK0y6VkAKc9ezZ/OTEYeyvDXDfos/b3LcqC8M4ndafG7EHlgBmQJmnbuUC7wJq6to2+LMBHTDGntfvvLFn6zLXZwzneBa371ywls4F4tUTksfv9VAXCFlhnA4IUNQDJl0NK55lrGcDA7sV8FyUUM5Q3UEAVE4WGXuosFdKu3Oe6BwRNzzJ2Yufhpw988eJo3rx0U0zyc/xOiiVO2ko0BJy5TXcVs7eFVrro4A5wCJgPPCoUmqpUuqR9IsnJEq4z57Dp+XwXiWcflhfHl6yka2V1a3uKzl77QP7phiIuL3c5v8bx77zHQi4wOCzcvY8Pue9YbaXNMcXXzznsk17eWvNTi47ZrB49YSkMQ2Fdeb67EVj8jWQ3xX15i3MHteX977Yzfaqmka76IB57cmmnL0Iz562NwhxE9IajeQ8xoOnSTqPUgqfNNlLCJ83ImfPhddwrP/1WuAgUG39XQYcni6hhOQJh3FmwTn5oxlD0RruWrCu1f2c9uwJqcE+52zPHsDc+vPoUfkJfLHIGaHiIZhFnj3b2LMG6FjXtsWrJ6SScBhnKIN99pqS1wmO+TF8/ibnln6B1vDCJ4177ula49nz5mSPsQcROXvancUdnKJxzp40Vo+Xpp49IXF8nvads/e/Sqn3ga3ALUAx8AAwTGs9JgPyCQmisiSME6Bf1wIuOKo/T3y4ifU79kfdpz4Y4kBd0GFjLwuU1Q6wV73qaQgVeTp4DDXeInjsbHjwBFj2GFghV9mGCtmevSwo0KLi9+x9/NXXLLK8epKbIaSCRk3VnbxNTrwUSsro8+H/Y0yfEp5vYuzV1x4AICe/0AnpoqKUamS0ZMOY7EZsQ0/0Fzv2WCzFN5PHF5Gz50Z1tjWD2IApztJda3281voXWuuXtdZ70y+akAye8H82O07Lq48rJ9/v5Y7X10R9v8qqrJZtYZyFMlmOm4acvQZjb7+/lHtHPwEn3AoHd8Nz34M7hsPL18P2FU6JGp2gaRHhzQZjz2Pn7FmevRiWtu9csI4u4tUTUoi92FAXCGW+Gmck/jzTiqFiKd/vu4blmyv5YmfDAmJllenpWVJU7JSEzVAQtlQkZy8+Im93JoxTiAclnr2UYYe/1odCrlxwaCtn709a6w+11u4ooyeEySbPHkBpUS6XTR3MK59tY9mmvc3er8wCY68pf/3OBEqLnA/lcxv2KRfQDcZeQY6XXZTA5Gvhmg/hopdg6Amw9GG4bzL8dQZ8/CjUHXBE5kjCnr0sCuPM9cfm2fvoq69ZvHYnl00Vr56QOuxV7Zr6kPMTx7HnQekwjqt4AJ8KMn9Zg3dv335j7HmyKIyzcc6eO/N9sgG7QIuoL3aa9tkTEidcZTzgzrxRydRsr2RB64WmXHrMYLoV5nD7K6ubeSiywdhrqqthvbJnddhN2Av/kZ69/BwvNXbrBaVg4NFw5l/hutVw4m+hphLmX228fS/9GLZ96oDkFlaBFjzOLzz4muTstcVdtldv0sA0SiV0NPzW+VcbCDpv7Hl9MP0mfHvWcn3Pj3n+ky3h8eTAAcvLl00FWojM2cuuMdlNSM5e/DTk7DkrR3vALtDSLnP2BPfStApTNlCU6+Oa48t574vdvL1uV6P3bGPP0T57TXTlWCEClxMtjLMgxxu9z15hN1NS/eoP4OJXYNjJ8NHf4f6j4S/Hw0f/B7XR8zzThd1nD6/zxp6tS38Mxt7SL41X7/Kph0j4sZBS/FYYZ029w2GcNsNPg77j+VbNY2zZ9TWfVlQC4Dm407yf38VB4RpjcvYiwjizQH1uQUdtvSAKjJWGnD3RWbI0tF7QrryG2yrQ0rW1R6aEFOJHhZ+z66w8/8j+lHXJ5/ZXVxMKNdzIs8GzN3Fg41M6G+Y0rsTSW2SBlny/l4P1rUSDKwUDJsMZ8+DHq+GkuSak8/lrjbfvxR/B1k/SLLglipWzhzd7cvZsY6+1le27Fq6ja2EO35k0IBOiCR2IHGtV23j2HBYGzP1ixq8prNnGRf6FzF+2hVBI06t2I/v93aAge6YnjTx70jogLiJvd9X1QcCdE22nUOLZSxnhapzB9unZWwp8aD03fXyYXtGEZGjoq+KsHE3J9Xm5buZQVmyp4qVPt4a3Z0OBltnj+vLejceHX8tqWGLYequ3Wi9s9fYhP8dLdV0gtgMUdIWjvgdX/QcueQ1GnGaqdz4wFeZNM3l+tfvSIzwNOXvZZOzZzy2VKFj65df8e+1OLp86WLx6QsqxJzq1gSzI2bMZNBUOOZ5r/fN5c9k6du6vpZxN7Csud1qyRijVOIxTbL3E+GKn8/ncbkNy9lJHuM9eyJ15t20VaBmktR5sPTd9DE7mi5VSXqXUx0qpF63XXZVSbyil1lnP2ROH4ULCF7nDckRj9ri+DOtZzB2vr6HeWiXJBs8eQO9ODbke2ag7N2CvIlaTx/frruaW7ndQkOOLHsbZGkpB/6Pg9PuNt+/k/weBWnjhB8bb98IPYcuyVIvfEMbp8ba+YwawjTxfG0uzdy5YS9fCHL59lHj1hNTTEMYZzI4wTpvpv6QoVMWcmmd5ZukmhqgK6roNd1qqFhFbLz4iIxnWbt8nOY9xYusqmy5Zt9LQeqEdevaUUsOt58OjPZL87h8AqyJe3wAs1FoPARZar4UECYdxZuEKhNej+OlJw9i4+yD/+u8mwBh7+X5vXP3E0k026s4NRIYpPR+aQpWvK/k5XlZsqeLjr76mOl6jD0wOzpFXwPeWwHffgJGz4ZPHYd6x8MCx8OFDKfP2eUL11OHLCrd4eLC2PXtRHHtLv9zD2+t2cYV49YQ0YYdxhnSWRTz0OYzgiDlc5n2ZD955gwJVi6/XCKelakJEnz3J2UuYddszm7vdHvBIzl7KsKMbQi5dcGhrZnAdcDlwR5T3NHB8lO1topQqA04FbrO+A2A2MM36+xFgEfCzRI4vZL+hcvzwHkwY0IW7Fq7jjMP7Ulld77hXrymyGpYYnib2ukKxdW81AKffuwSPgoGlhYzoXcLI3iWM6F3MiN4l9CrJa/u8VQr6HWEeJ/4WPn3SGHov/hBe+x8YcxaMvwj6HJbwrMoTqqceH84HcULQsu783pZ/y50L1tGtMIdvS66ekCYiCwRlW+Eq7/SbyF31Aj+vvwc8UFQ22mmRGmHCOK0CLWiU1MVLiDXb9xnPaHadfllNQzVOUVqy+CLGYDeqs1VjT2t9ufV8XIq/907gp0BkbfueWuut1vdtVUr1SPF3diiyNWfPRinFz04eztn3v8dD727MUmMvS5WX5azYUtXotVIm1wfg6uMOwefxsGprFcs37+Wl5Q15m50L/IzoVcKICANwSM8icn0thFPmd4YjLoOJl0LFUlj6kDH+PnoEeo01Rt+YsyGvJC75VShAoM11sMwQDJpJotcTvUDLhxuNV+/npwynICc7ZBbaH5HGXivrDs5QWs728nMYsv6fAJT0zzJjL+JvqcaZOBt3HSDf73xovZsIL57KOZc0keHrbryGY5odKKX8wPeAqdamRcADWuv6eL9QKXUasENrvVQpNS2Bz1+O8TbSv3//eD/eYcjWapyRTBzYlenDe3D/4s8p61KQdcaeGy/obGD55soW35s2rEejqqdVNfWs3rqPVVurwo/HPviSmnpjHPo8ivIeRY0MwBG9Sxo3u1cKyiaYR9jb9zC8dB28/gsYfSaMvxj6Hh7TP9Wj6wmo7DCcAlbFWn8L3pQ7F6yjtCiHb0munpBGIle1s3ERrMdpN1Fz59NUqWJ6ZFHbBWhcoEWID1ttpUU57Npfx77aQFbPabINsfVSh79pyJLLiHVGcx/gB+61Xn/b2nZpAt85BZillDoFyANKlFKPAtuVUr0tr15vYEe0D2ut5wHzACZMmCC30BbIxj570bj+pGGcfNfbrNpaxYwRPZ0WpxHZHgrrFiL12LQ5eEmenyMGdeWIQQ0GYDCk2bDrQCMD8L3Pd/PsxxXhfboX54YNwJGWATi4tBBfXifj6ZvwXdjykanc+enT8PHfoecYGH8hjD0H8jq1KK8nVJ89nr2Q7dmzq3E28N+Ne3hn/S7+55QR4tUT0kpOFodxAvg69+WTcb8kUHuQbAsJUkT02SP7x+Rswg5/HdKjmF37dzssjftwyzzQDXgjwzhdaD7HOkOYqLU+NOL1m0qphJpeaa1vBG4EsDx7P9Faf0sp9XvgQmCu9Tw/keMLBres6AzvVcLp4/ryzMcVWefZy8I5jStRxBdW7LW8eeU9ivjGoX3C2/ccqAsbfyu3VrFq6z7e+3wX9VaoY47Pw9CeRWHjb0TvgYyY8Uc6nXAbfPaUye17+Sfw+k2Wt+8i4w1sIpRHZ5Gxp5sYexEugjsXrKW0KIcLjpIIByG9NMrZy9L74vg51zotQlQat16QPnuJMLh7IR9s3EMwJH324iFbr1U34u8IYZxAUCl1iNb6cwCl1GAggZJ6rTIXeEIp9V3gK+DsFB+/Q6FctKLzo5lDeXH5VnqU5La9cwbJxnAlN6IUHN6/C59VVNGlIPGyJ10Lc5hSXsqU8tLwtrpAiM937o/wAu5j4aodPPHh5vA+fTvnM6L3GEYM/itHjvyKsdufo3jlc6hlj0KPUcboG3uOyQEEPKEAAZUdCw8hy7Pna5Io9cGGPby7fje/OFW8ekL6aZSzJzPIuFCqwSMvnr3EyPV5GdCtQHrtxYlEJ6WORjl7DsqRKLHOEq4H3lJKfYH5nQOAi5P9cq31Ikz+H1rr3cD0ZI8pGBo8Kdl/WvbrWsAL1x5Nr5I8p0VphAtUl5V4lClPbKOAX5w6knMm9KNf14KUfleOzxPO47PRWrNzXy0rIzyAq7ZW8ebqHdytAU6hNGcGl3T6iFn7XqfslesJvX4TwZFz8E+8BG+ojmCW5ezZZZ9ttYa9ekdKrp6QfvxZnrOXzShUQzVOSTxJCKVgaI9ivth5wJUTbaeQSzV1+CJTUFyo2JhmNFrrhUqpIcAwzNxttda6Nq2SCUmhmjxnO8N6Fbe9U4aRSU1i+Lwe6gINjUeVUuT4PIzu23KeXCpRStGjJI8eJXlMG9aQwVNTH2Tt9n1hD+Cirb24b+vR9K9dxze9bzJ7+Xz8nz7OoSg+95VnRNa2aJqzB/D+F7tZ8rnx6uXnSHU6If00DuOU+2JcNPPsif4SYWjPIl5d4bQU7iKcs+eamWD24nN5REOrxp5SaiKwSWu9TWtdq5QaB5wJfKmU+rXWek8mhBTix+OWpL0sRsbkxPB7FHURr7NFjXl+L2PLOjO2rHN4m9aair3HsGrr2Ty6eRtF65/nsF0vUNVtPEOcEzVMM2NP2xU4c8WrJ2QMv0/COBNFQYS1p7PmfugGbE+oAoZaC8JiLMeOXKqpo72HcT4AzABQSk3F5NVdC4zDVMQ8K53CCYnTYOu58bTMDmQFOzFMuEOqU3rTg1KKsi4FlHUpYObInnDCocBNTosVxi7QYq8q/mfDbt77Qrx6QmaRMM7E8SgVvo4lZy8+7CqmSsHQntkX/ZPtyLWaOiKjG9yo1raMPW+E9+5cYJ7W+mngaaXUsrRKJiSFlNxNHlFdYjQNd5BzMHHsCrX283MfV9C9OFf66gkZJbLHlHgL4iPf76Wm3ix+BYI6nH8rxMfAboX4vUoMGMERIu97bjwD2zT2lFI+rXUAUzzl8jg+K2QBbjwpswUZVBKjaeVIOQsT5wfTh9CnUx7Hj+jJ715ZTUjDlcceQp5fvHpC5pAwzsTJz/FysM4Ye8GQdn3uTyaJLGiT4/Nw9zcPz8r8/mxFFv1Th1IKv1eFWz25jbYMtn8Ci5VSu4Bq4G0ApVQ5UJlm2YQkiKevmRAd0V1iNF25Fj0mTp7fy7cnDWRrZTVgmslfcKT01RMyS6MwTjFW4qIgx0u1ZewFQqFGzZmF+DhpdC+nRXAVcqmmFq/HGHtuzBtt1djTWt+mlFoI9AZe1w0dfT2Y3D0hS5EqTMnjxgs6G9BN6ouLFpOnKNdHrs/DD6YPEa+ekHEkjDNx8v1eAiFNXSAknr0EkbE4MURvqcUsZIdcOadpMxRTa/2fKNvWpkccIVWEWy+48awUXE3TIAcJh02e4jw/H900k8JciZ4XMo/Ho/B6FMGQxivXc1wUWNfswboAgZCWMNg4sMcS0VhiyKmWWuwUFTfeAiVTuJ0inRcEp2jaOFjqEaQGMfQEJ/GHJzoyqsRDt8IcAHbtrxPPXpxIE/rkUJKzl1LcfO3KNKyd4pGkPcEhdBPfnkwOBcH92KXHxTMVHz1KcgHYsa/G8uzJtCtu5JRLCImqSS12PQI3pkfJXae9Ip69hLl86mCnRXA1zTx7MuAIguvJEWMvIXoU5wGwc18tgWDI1d4BwV3I0Jtawvc+F+pVjL12jlzs8fPzU0awce6pTovhWppG3sgpKAjux/bsyZgSHz0tz972qhrJ2YuTplEiQnzIqZZawjl7DsuRCGLstVNsN7Mb3c2Cu2nu2XNGDkEQUoc90ZECLfFRlOsj3+9lR1Wt5OwliMxjEsOOqpHcx9Tg5mtXjL12jozLQuZpPLJIGKcguB8J40wMpRQ9S3LZvq+WQEjj88q0K1ZsI0WGkMSwr1Ux9lJDOGfPheej3HXaOS48JwWX03RgkQItguB+GsI45XqOlx7FeeyoqhHPXpycMqY3AHPG9XVYEncSNvYkHDYlNIRxuu8aFmOvnSLjieAUxw/v0ei1zA0Fwf34fXYYp8OCuJAeJbns2GfCOMUzGjuDSgvZOPdUhvUqdloUV2KfayGx9VKCvVDjxjmNGHvtlDy/F4C6YMhhSYSOxm2nj2n0WuY2guB+7BAmMVbip0dxHlv2VgPuzvsR3EU4v1aMvZTg5hBs90outEqe3/xrq+uCDksidDRyfI1vK5KzJwjuJ0fCOBOmZ0kutQGz8OoV16iQISSMM7V4xbMnZBv5lmevul6MPcFZZHIoCO4nHMYpnqm4sRurg3j2hMwhYZypJRzGKTl7QraQJ8aekCWIrScI7scu0CK2SvzYjdUBvB6ZdgmZwROuxinWXirwubjXqNx12in5OcbYqxFjT3AYmRwKgvuxc/YkLDt+eopnT3AA+1wTb3xqcPO1K8ZeOyXPZxt7UqBFcBaZHAqC+8mRMM6E6d7Isyf6EzKDXaBFxuDUIMaekHXYnj0p0CI4jQw0guB+GsI45XqOl5I8X7hompsnjIK7sHP1ZIEhNYT77LnwHijGXjvFHlhqAmLsCYIgCMkRNvZk4hg3Sqlw3p5MvIVMEbJy9eScSw12vq0btSnGXjslXKBFPHuCw4gnQBDcj23seeV6Tgg7b8/v4l5dgrsIWsaeGz1R2YjfxUaz3HXaKYU5PkAm2oLzuPj+KAiChd9r5/84LIhLEc+ekGmCQWPsSehwanBznz2f0wII6WFAtwKumzmUOeP6Oi2K0MGRsC9BcD8Sxpkcdq89mXgLmcL27Mmif2oIt15wWI5EEGOvnaKU4vvThzgthiAIgtAOkAItySGePSHT6HDOnsOCtBPCTdVdeA+UU0AQhLQSCEpDV0FwOzleu/WCw4K4FDtnz67oJwjppqxLAQATB3Z1WJL2Qbgap8NyJIJ49gRBSCu1UhFWEFyPTzx7SdGzxHj27Ob0gpBuRvftxFs/mcbAbgVOi9IucHMIthh7giCkldpAyGkRBEFIEgnjTI4jBnXlf04ZwZGDxcsiZI5BpYVOi9BuCLdecOEtUIw9QRDSSk29ePYEwe34w2GcLpzpZAF+r4fLpg52WgxBEBLEHw7Bdt89UOIJBEFIOUeXl4b/FmNPENxPjk88e4IgdFzc3HpBjD1BEFLOQxdP5P5vjQegpl7COAXB7di5ZuLYEwShI+J3cXUq90ouCELW4vd66FqYA4hnTxDaAxLGKQhCRybs2XNYjkQQY08QhLSQ5ze3lxqpxikIriccxinGniAIHRCfhHEKgiA0Js/vBSSMUxDaA1KNUxCEjkzY2HOhb0+MPUEQ0kKezzb2xLMnCG6nOM8U7y7M8TosiSAIQubxujhnr921Xqivr2fz5s3U1NQ4LYqryMvLo6ysDL/f77QoQjsh35oUiidAENzPlENKeeyyIxnSs9hpUQRBEDKO38VhnO3O2Nu8eTPFxcUMHDgQ5cb/iANordm9ezebN29m0KBBTosjtBNKi3K4buZQTh3b22lRBEFIEo9HMfmQ0rZ3FARBaIdI64Usoqamhm7duomhFwdKKbp16ybeUCGlKKX4/vQhHNK9yGlRBEEQBEEQEsbOW5acvSxBDL34EZ0JgiAIgiAIQnPc3HamXRp7giAIgiAIgiAIqcCuxulCx17mjT2lVD+l1FtKqVVKqRVKqR9Y27sqpd5QSq2znrtkWrZUcttttzFq1CjGjh3LuHHjuPnmm5kzZ074/d/97neUl5eHX7/wwgvMmjULgIEDB7Jr164Wj/3qq68ybNgwysvLmTt3bnj7nj17mDlzJkOGDGHmzJl8/fXXAOzevZvjjjuOoqIirrnmmhT/UkEQBEEQBEFov/jCYZzuwwnPXgD4sdZ6BHAUcLVSaiRwA7BQaz0EWGi9diXvvfceL774Ih999BHLly9nwYIFXHTRRbz33nuN9ikpKWHHjh0ALFmyhClTprR57GAwyNVXX80rr7zCypUr+ec//8nKlSsBmDt3LtOnT2fdunVMnz49bAjm5eXxm9/8hj/84Q9p+LWCIAiCIAiC0H5paKruPnMv49U4tdZbga3W3/uUUquAvsBsYJq12yPAIuBnyXzXzS+sYOWWqmQO0YyRfUr41TdGtbrP1q1bKS0tJTc3F4DS0lJKS0vp1KkT69evp7y8nIqKCs4880yWLFnCnDlzWLJkCbfeemub3//BBx9QXl7O4MGDATjvvPOYP38+I0eOZP78+SxatAiACy+8kGnTpnH77bdTWFjI0Ucfzfr165P78YIgCIIgCILQwfB53Wfk2Tias6eUGggcBrwP9LQMQdsg7OGgaElxwgknsGnTJoYOHcpVV13F4sWLAZg8eTJLlixhzZo1DBkyhKOOOoolS5YQCARYvnw5EydObPPYFRUV9OvXL/y6rKyMiooKALZv307v3qbMfe/evcNeQ0EQBEEQBEEQEiPcesFhORLBsT57Sqki4Gngh1rrqljdokqpy4HLAfr379/qvm154NJFUVERS5cu5e233+att97i3HPPZe7cuUyZMoUlS5YQDAaZNGkSRxxxBLfccgsff/wxw4YNIy8vr81ja62bbXOjS1kQBEEQBEEQ3IDPY+XsuXDK7YhnTynlxxh6/9BaP2Nt3q6U6m293xuI6pbSWs/TWk/QWk/o3r17ZgROAK/Xy7Rp07j55pu55557ePrpp8OevSVLljBp0iSKi4upqalh0aJFMeXrgfHkbdq0Kfx68+bN9OnTB4CePXuydetWwISS9ujhWueoIAiCIAiCIGQFdhinC209R6pxKuBBYJXW+o8Rbz0PXGj9fSEwP9OypYo1a9awbt268Otly5YxYMAARo4cyZYtW3j77bc57LDDABg3bhz3338/kydPjunYEydOZN26dWzYsIG6ujoef/zxcBXPWbNm8cgjjwDwyCOPMHv27BT/MkEQBEEQBEHoWPhc3GfPiTDOKcC3gU+VUsusbT8H5gJPKKW+C3wFnO2AbClh//79XHvttezduxefz0d5eTnz5s1DKcWRRx5JZWUlfr8fgEmTJjFv3ryYjT2fz8c999zDiSeeSDAY5JJLLmHUKBOuesMNN3DOOefw4IMP0r9/f5588snw5wYOHEhVVRV1dXU899xzvP7664wcOTL1P14QBEEQBEEQ2hENYZzuM/pUtBwwtzBhwgT94YcfNtq2atUqRowY4ZBE7kZ0JwiCIAiCIAiNWbt9Hyf8778547C+/PHccU6L0wyl1FKt9YRo7zlajVMQBEEQBEEQBCGbsatxujFpz7FqnELr7N69m+nTpzfbvnDhQrp16+aARIIgCIIgCILQ8fB73OsfE2MvS+nWrRvLli1zWgxBEARBEARB6NB4w9U43efac6+ZKgiCIAiCIAiCkGb8dlN199l6YuwJgiAIgiAIgiC0hJ2z50JbT4w9QRAEQRAEQRCElvB53WsyuVdyQRAEQRAEQRCENOOTME6hKbfddhujRo1i7NixjBs3jptvvpk5c+aE3//d735HeXl5+PULL7zArFmzANMAfdeuXS0e+9VXX2XYsGGUl5czd+7c8PYnn3ySUaNG4fF4aNp/0P6+YcOG8dprr6XoVwqCIAiCIAhC+6YhjNN91p5U40wD7733Hi+++CIfffQRubm57Nq1iwMHDnDvvfc22qekpIQdO3bQo0cPlixZwpQpU9o8djAY5Oqrr+aNN96grKyMiRMnMmvWLEaOHMno0aN55plnuOKKKxp9ZuXKlTz++OOsWLGCLVu2MGPGDNauXYvX6035bxcEQRAEQRCE9oTfCuN0o2evfRt7r9wA2z5N7TF7jYGT57a6y9atWyktLSU3NxeA0tJSSktL6dSpE+vXr6e8vJyKigrOPPNMlixZwpw5c1iyZAm33nprm1//wQcfUF5ezuDBgwE477zzmD9/PiNHjmTEiBFRPzN//nzOO+88cnNzGTRoEOXl5XzwwQdMmjQpzh8vCIIgCIIgCB2LcE91Fxp7EsaZBk444QQ2bdrE0KFDueqqq1i8eDEAkydPZsmSJaxZs4YhQ4Zw1FFHsWTJEgKBAMuXL2fixIltHruiooJ+/fqFX5eVlVFRUZHyzwiCIAiCIAiCAEop/F4XWnq0d89eGx64dFFUVMTSpUt5++23eeuttzj33HOZO3cuU6ZMYcmSJQSDQSZNmsQRRxzBLbfcwscff8ywYcPIy8tr89ha62bbVBvLDIl8RhAEQRAEQRAEg8nbc9/8uX0bew7i9XqZNm0a06ZNY8yYMTzyyCPMnTuXu+++m2AwyGWXXUZxcTE1NTUsWrQopnw9MF65TZs2hV9v3ryZPn36pPwzgiAIgiAIgiAYfB6PhHEKhjVr1rBu3brw62XLljFgwABGjhzJli1bePvttznssMMAGDduHPfffz+TJ0+O6dgTJ05k3bp1bNiwgbq6Oh5//PFwFc+WmDVrFo8//ji1tbVs2LCBdevWccQRRyT+AwVBEARBEAShA+HzurEWp3j20sL+/fu59tpr2bt3Lz6fj/LycubNm4dSiiOPPJLKykr8fj8AkyZNYt68eTEbez6fj3vuuYcTTzyRYDDIJZdcwqhRowB49tlnufbaa9m5cyennnoq48aN47XXXmPUqFGcc845jBw5Ep/Px5///GepxCkIgiAIgiAIMTKuX2eG9Sp2Woy4UdHyudzChAkTdNN+cqtWrWqxKqXQOqI7QRAEQRAEQXAXSqmlWusJ0d6TME5BEARBEARBEIR2iIRxZim7d+9m+vTpzbYvXLiQbt26OSCRIAiCIAiCIAhuol0ae1pr17cW6NatG8uWLcvY97k5nFcQBEEQBEEQhOa0uzDOvLw8du/eLcZLHGit2b17d0x9/gRBEARBEARBcAftzrNXVlbG5s2b2blzp9OiuIq8vDzKysqcFkMQBEEQBEEQhBTR7ow9v9/PoEGDnBZDEARBEARBEATBUdpdGKcgCIIgCIIgCIIgxp4gCIIgCIIgCEK7RIw9QRAEQRAEQRCEdohyc9VKpdRO4MsYdi0FdqVZnPaM6C95RIfJIfpLDtFf8ogOk0P0lxyiv+QRHSaH6C850q2/AVrr7tHecLWxFytKqQ+11hOclsOtiP6SR3SYHKK/5BD9JY/oMDlEf8kh+kse0WFyiP6Sw0n9SRinIAiCIAiCIAhCO0SMPUEQBEEQBEEQhHZIRzH25jktgMsR/SWP6DA5RH/JIfpLHtFhcoj+kkP0lzyiw+QQ/SWHY/rrEDl7giAIgiAIgiAIHY2O4tkTBEEQBEEQBEHoUIixJwiCIAiCIAiC0A4RY08QUoBSSjktg9sRHQpOIudf8ogOBUEQso92Y+wppWYopcY7LYdbUUp1ivhbBuz48TktQDvA77QAbkcp5XVaBhfTbsZDB5FrOAmUUqXWs1zHCaCUGui0DG5HKTVBKdXDaTncSrbaIq4f3JRShymlXgGeBcqdlsdtKKWOVErNB/6qlLpEKZWrpWpPzCiljlJK/QO4RSk1RAbp+FFKTVJKPQn8QSk1UnQYH5b+bgHQWgedlsdtKKWOUEo9CvxOKTVGKeX6cTHTWBPEJ4HfK6WOlms4dpShQCn1T2A+yHUcL0qpw5VSCzDjsJx7CaCUGqWUWgL8CujssDiuI9ttEdcOakopr1JqHvAX4AHgMWCE9Z5rf1cmUUqNBf4MPAU8CRxPFp6k2YpSajRwN/AisB24HPiO9Z54R2PAWkG8B3gZ2AX8ALjEek902AZKqQuBR4BfKKXOsbaJlzkGlFIepdSvgL8Cr2C881cDhzoqmIuwDJW5wP003AevAfo7KpiL0IaD1stSpdT3QOYxsWCdf/8D/BN4XGv9HdtQlvEjbn4APKu1/obWei2IDmPBLbZI1ggSL9YF/QZwjNb6OeBp4DilVJ7WOuSocO7hCGC91vrvGF3mAV/Zb8qF3iZTgNVa639iLvSDwAVKqYFaay36i4nRwFqt9UPAHcAzwGyl1FDRYUx8hVmkOQmjP7TWAdFb21jjxJfARVrrfwC3AQMA8QzEiBUFsgiYqbV+BHgI0MBOJ+VyE5bB0htjKH8X+J5SqrPWOpRNk8VsxDr//MA7Wuu/QtjD4pMIpdiwjJWumOv2Hmvb6UqpMiDfei3jSQtYtsirZLkt4qobiVLqm0qpW5RSswC01k9qrautEzEErAUKHBUyi7H0d7NSara16QXgdKXUbcCnQBnwJ6XUzyB8IxUsIvQ3y9r0PlCmlCrXWh/AnIOVwGUg+ouGUupYpdSREZs+ASYopQZbOvwv8CFwBYgOmxJFf4uAbVrr14EvlVK/sbaLdy8KUfT3OLDMCl/fDewDejsjnTtoqkOt9ata66+VUscA/wEGArcqpWY6JWM2E6k/pZTH8uxtxehtI7AYuEEpdUg2TRazhSjX8O+BvkqpPyil/gv8BnhEKXWWMxJmP5E6tIyVg8BU4HhlQtqvAG4F7rT2kXE4gij3wGey3RZxhbFnrXxdCfwU2IDJC7hYKVUE4RNxNTAd452SlYgImuhvI/D/lFKXa623A8MxK2M/11ofBTwMHK2UmuSUvNlGFP39wQqf2wq8AzyklHoOmIAJh/UppfIcEjcrUUoVK6WewcSzX6GU6gJgTbD/BXzf2nUvsAAosFa7BVrWH6AAO7/nCuD7SqmeWut6J+TMVqLor6v1Vq3WOqS1rlVK+TELXmscEzSLaekcjPA+7cF4SSdhFnHOV0oNd0ba7COa/mxjTik1FPhCa70ZE2VzFfCkUirXOi87PK2MIQeAvwPjgB9rrU8D/g2cZOlVsGhFhzUYr/yfgde01icB/wOMVkqd7JjAWUYr90CllFLZbIu4wtizFDgJmGuFe12NUeZUW5HWTfJ94KyIzwi0qL9jlVIna603YPL0Nlu7LwV2ALWOCJuFRNHfVcBMYJzW+ibgSuARrfU3gPXAWOvmKTRQB7wJfAvYApwd8d7TwHCl1HRr8rMb6IvxkgqGqPqzDBWtlPJqrVdgFhvmAsgg3Yim+os2TowAtmut11qD+hGZFzOrafEctJ5XaK3fsvZdjCnysD/zYmYtrd0DtwBDlVLPYzxVi4Evtda1snATpkX9WWHY52it/21tWgB0R86/prR2Dt6LCdvsDqC1rsAsZot3uYGW7oHaGoc92WqLZK2xp5T6juUqtVdgV2Fc9T6t9QJM2OHRmJVYrNWvdcABRwTOMmLQ33JgmjIFMl4DfmUZzucBozAT7g5LjOffcUqpMmuS86y13/HAf7JlNcdJInTYWWtdiymEsQAT4jBBKTXM2vUTTDjdnUqpcsxCjgJynJA7W4hBf0Ot/RQm3wKt9aXAhUqpr4FDVQfO+YlDf3bIa1fgoFLqImAJMKajX8dxnoORnICZX+zLqMBZRqz6A4oxk8cvgPHWwmE/lYUl3DNJPOef1npPxEdnYu6JHd7Yi1WHWuv9wLWY8WOcMoWCZmCimToscZyDHivP1kcW2iJZNRGwPKG9lVJvARcCFwB3K6VKgE1ADxqqRf4LsxJbCmCtfhVh4t47JAnobyjQR2v9AFCBqUh3HnCJ1vrLjP8Ah0lAf8Owzj9lyre/BZwIPJotqzmZpgUd/lkpVaq1rtFa1wHvYbzH50DYO/UwJhTnRsw5+FOt9V4nfoOTJKg/DWil1ABlQkzexiSLz+1oOT8J6i9gffxE4JuY3JULtNYPdsTrONFzUJmQwxlKqaXAKcDPtNYdzjsfp/7OBbBy9q7XWv/QmnQDTNdaL3XiNzhJEuefRyk1VSn1MXAycIPWusqp3+EkiegQQGv9BPBba9tJwLe11h0urD3ReYxl8AUwizcDHRI/Kllj7CkThqQxSqrQWk/HhMtVYsrbP4GZbE9USnXSWm+03psTcZgfW2F1HY4E9VcFnGkd4kJMvsUMrfXKjP8Ah0ni/DvDOsQXwK+11tO11p9n/AdkAa3ocA+mJDEAWut1mHDh3kqpcqVUoXWT/H/A97TWR2utVznxG5wkAf31sfSXh/GEfo0JNT5Wa/1Z5n+BsyShPzuR/gXgm1rrS7TWyzMsflaQhA5zMeFe24Ffaa1naa1XZ/4XOEsS98B8oMY6hsfapyMaysncAzVm0fpXWuvZHfH8g6R0WKiU8mut/wX8j6XDFU78BidJ8hzMt96+LttsEccrtlkuz1sAr1LqZaAEq+CANiXEr8EUwhiJ6V8xBxO6+TvM4PKBfawOugqbjP6CmOpptmd0W6bld5oUnH/vW/vuwuRZdDhi0OH3gS1KqWO11out7c8qpUZgShYXAccBq6wVsw5FivR3vLVI80HUL2nHpEJ/SqnjtNZLHPoJjpOqa1hr/SkmxL1DkeJ7YIfyxkPK74EddbE1leegzKXbmf4c9ewppY7FWMZdMIUtfgPUY3KhjoBw8vctwO3a5ErNw1SLfN/63CIHRM8KRH/JIfpLnhh1qDE6/HXE587GVPt6C1PQpsN58iCl+utw3niQ8y8ViA6TQ/SXHHIPTB45B5OjI+hPOWmAKtOXZ6A2Tb1RSt2LWRWsBq7VWo+3Qhp6YELprtdab1RKdQYKtakW1GER/SWH6C954tThnzB5PBusz6G1ftsh0bMC0V9yiP6SR3SYHKK/5BD9JY/oMDk6gv6cztlbCjyhlPJar98F+mtTrMGrlLrW8qyUAQFt8qTQWu+ViTYg+ksW0V/yxKPDoDatPtBav+2GG2QGEP0lh+gveUSHySH6Sw7RX/KIDpOj3evPUWNPa31Qmz4ydlPgmcBO6++LgRFKqReBfwIfOSFjNiP6Sw7RX/KIDpND9Jccor/kER0mh+gvOUR/ySM6TI6OoD/HC7SAqX6DqaTUE3je2rwP+DkwGtggnpSWEf0lh+gveUSHySH6Sw7RX/KIDpND9Jccor/kER0mR3vWn9NhnDYhwA/sAsZaFvRNQEhrgiC5DQAAAQBJREFU/Y5blZtBRH/JIfpLHtFhcoj+kkP0lzyiw+QQ/SWH6C95RIfJ0W7152iBlkiUUkcBS6zHQ1rrBx0WyVWI/pJD9Jc8osPkEP0lh+gveUSHySH6Sw7RX/KIDpOjveovm4y9MuDbwB+11rVOy+M2RH/JIfpLHtFhcoj+kkP0lzyiw+QQ/SWH6C95RIfJ0V71lzXGniAIgiAIgiAIgpA6siVnTxAEQRAEQRAEQUghYuwJgiAIgiAIgiC0Q8TYEwRBEARBEARBaIeIsScIgiAIgiAIgtAOEWNPEARBEARBEAShHSLGniAIgiAIgiAIQjtEjD1BEARBEARBEIR2yP8HqegA0Ef6ds0AAAAASUVORK5CYII=\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -249,9 +133,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -259,21 +141,21 @@ "metadata": { "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.13" + "pygments_lexer": "ipython3", + "version": "3.6.13" } }, "nbformat": 4, diff --git a/docs/read_cgls_swi_ts.rst b/docs/read_cgls_swi_ts.rst index a5efdfa..affab09 100644 --- a/docs/read_cgls_swi_ts.rst +++ b/docs/read_cgls_swi_ts.rst @@ -1,8 +1,7 @@ - Example CGLS SWI time series ---------------------------- -.. code:: ipython2 +.. code:: ipython3 import os from ascat.cgls import SWI_TS @@ -12,27 +11,23 @@ Example CGLS SWI time series By default we should have the grid file from the SWI-STATIC collection and the unzipped SWI-TS products in one folder like so: -.. code:: ipython2 +.. code:: ipython3 ls ../tests/ascat_test_data/cglops/swi_ts .. parsed-literal:: - c_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc - c_gls_SWI-TS_201612310000_C0375_ASCAT_V3.0.1.nc - + c_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc + c_gls_SWI-TS_201612310000_C0375_ASCAT_V3.0.1.nc -Now we can initialize the data reader -.. code:: ipython2 +.. code:: ipython3 data_path = os.path.join('..', 'tests', 'ascat_test_data', 'cglops', 'swi_ts') rd = SWI_TS(data_path) -With this object we can read the data - -.. code:: ipython2 +.. code:: ipython3 data = rd.read_ts(3002621) print(data) @@ -40,131 +35,31 @@ With this object we can read the data .. parsed-literal:: - SSF SWI_001 SWI_005 SWI_010 SWI_015 SWI_020 \ - 2007-05-10 12:00:00 1.0 70.0 71.0 71.0 71.0 71.0 - 2007-05-14 12:00:00 1.0 71.5 71.5 71.5 71.5 71.5 - 2007-05-15 12:00:00 1.0 82.0 78.0 77.0 76.5 76.5 - 2007-05-16 12:00:00 1.0 82.5 79.0 78.0 77.5 77.0 - 2007-05-17 12:00:00 1.0 77.5 77.5 77.0 76.5 76.5 - 2007-05-18 12:00:00 1.0 75.0 76.5 76.0 76.0 76.0 - 2007-05-19 12:00:00 1.0 75.5 76.0 76.0 76.0 76.0 - 2007-05-20 12:00:00 1.0 86.0 81.0 79.5 79.5 79.0 - 2007-05-21 12:00:00 1.0 84.5 81.0 80.0 79.5 79.5 - 2007-05-22 12:00:00 1.0 81.5 80.5 80.0 79.5 79.0 - 2007-05-23 12:00:00 1.0 81.5 80.5 80.0 79.5 79.5 - 2007-05-24 12:00:00 1.0 81.0 81.0 80.0 80.0 79.5 - 2007-05-25 12:00:00 1.0 79.5 80.0 79.5 79.5 79.5 - 2007-05-26 12:00:00 1.0 81.5 80.5 80.0 79.5 79.5 - 2007-05-27 12:00:00 1.0 76.5 79.5 79.5 79.0 79.0 - 2007-05-28 12:00:00 1.0 80.5 79.5 79.5 79.5 79.5 - 2007-05-29 12:00:00 1.0 82.0 80.5 80.0 79.5 79.5 - 2007-05-30 12:00:00 1.0 83.0 81.0 80.5 80.0 80.0 - 2007-05-31 12:00:00 1.0 79.0 80.5 80.0 80.0 80.0 - 2007-06-01 12:00:00 1.0 75.5 79.5 79.5 79.5 79.5 - 2007-06-02 12:00:00 1.0 80.5 79.5 79.5 79.5 79.5 - 2007-06-03 12:00:00 1.0 85.0 81.5 80.5 80.5 80.0 - 2007-06-04 12:00:00 1.0 85.0 82.0 81.0 81.0 80.5 - 2007-06-05 12:00:00 1.0 84.5 82.0 81.5 81.0 81.0 - 2007-06-06 12:00:00 1.0 79.5 81.5 81.0 80.5 80.5 - 2007-06-07 12:00:00 1.0 77.5 80.0 80.0 80.0 80.0 - 2007-06-08 12:00:00 1.0 77.0 79.5 80.0 80.0 80.0 - 2007-06-09 12:00:00 1.0 77.0 79.5 79.5 80.0 80.0 - 2007-06-10 12:00:00 1.0 77.0 79.0 79.5 79.5 79.5 - 2007-06-11 12:00:00 1.0 76.5 78.0 79.0 79.0 79.5 - ... ... ... ... ... ... ... - 2016-09-19 12:00:00 1.0 73.5 76.5 78.5 80.0 81.0 - 2016-09-20 12:00:00 1.0 74.5 76.0 78.5 80.0 81.0 - 2016-09-21 12:00:00 1.0 75.5 76.0 78.0 79.5 80.5 - 2016-09-22 12:00:00 1.0 73.5 75.5 77.5 79.0 80.5 - 2016-09-23 12:00:00 1.0 72.0 75.0 77.5 79.0 80.0 - 2016-09-24 12:00:00 1.0 69.5 73.5 76.5 78.0 79.5 - 2016-09-25 12:00:00 1.0 71.0 73.0 75.5 77.5 79.0 - 2016-09-26 12:00:00 1.0 71.5 73.0 75.5 77.0 78.5 - 2016-09-27 12:00:00 1.0 77.0 74.0 76.0 77.5 78.5 - 2016-09-28 12:00:00 1.0 83.5 76.0 76.5 78.0 79.0 - 2016-09-29 12:00:00 1.0 92.0 81.0 79.0 79.5 80.0 - 2016-09-30 12:00:00 1.0 93.5 82.5 80.0 80.0 80.5 - 2016-10-01 12:00:00 1.0 90.0 84.0 81.0 81.0 81.0 - 2016-10-02 12:00:00 1.0 84.0 83.5 81.0 80.5 81.0 - 2016-10-03 12:00:00 1.0 72.0 80.0 79.5 80.0 80.0 - 2016-10-04 12:00:00 1.0 64.5 76.0 77.5 78.5 79.0 - 2016-10-05 12:00:00 1.0 57.5 71.5 75.0 76.5 78.0 - 2016-10-06 12:00:00 1.0 65.0 70.5 74.0 75.5 77.0 - 2016-10-07 12:00:00 1.0 66.0 70.0 73.5 75.0 76.5 - 2016-10-08 12:00:00 1.0 68.0 69.5 73.0 75.0 76.0 - 2016-10-09 12:00:00 1.0 67.5 69.0 72.5 74.5 76.0 - 2016-10-10 12:00:00 1.0 65.5 68.5 71.5 74.0 75.5 - 2016-10-11 12:00:00 1.0 60.0 66.0 70.0 72.5 74.0 - 2016-10-12 12:00:00 1.0 54.0 63.5 68.5 71.0 73.0 - 2016-10-13 12:00:00 1.0 52.5 61.0 66.5 69.5 72.0 - 2016-10-14 12:00:00 1.0 55.0 60.0 65.5 69.0 71.0 - 2016-10-15 12:00:00 1.0 56.5 59.0 64.5 68.0 70.5 - 2016-10-16 12:00:00 1.0 61.5 60.0 64.5 67.5 70.0 - 2016-10-26 12:00:00 1.0 12.5 42.5 59.0 64.5 68.0 - 2016-10-28 12:00:00 1.0 69.5 54.0 60.0 64.5 67.5 + SWI_001 SWI_005 SWI_010 SWI_015 SWI_020 SWI_040 \ + 2007-05-10 12:00:00 70.0 71.0 71.0 71.0 71.0 71.0 + 2007-05-14 12:00:00 71.5 71.5 71.5 71.5 71.5 71.5 + 2007-05-15 12:00:00 82.0 78.0 77.0 76.5 76.5 76.0 + 2007-05-16 12:00:00 82.5 79.0 78.0 77.5 77.0 77.0 + 2007-05-17 12:00:00 77.5 77.5 77.0 76.5 76.5 76.0 + ... ... ... ... ... ... ... + 2016-10-14 12:00:00 55.0 60.0 65.5 69.0 71.0 76.5 + 2016-10-15 12:00:00 56.5 59.0 64.5 68.0 70.5 75.5 + 2016-10-16 12:00:00 61.5 60.0 64.5 67.5 70.0 75.5 + 2016-10-26 12:00:00 12.5 42.5 59.0 64.5 68.0 74.5 + 2016-10-28 12:00:00 69.5 54.0 60.0 64.5 67.5 74.0 - SWI_040 SWI_060 SWI_100 - 2007-05-10 12:00:00 71.0 NaN NaN - 2007-05-14 12:00:00 71.5 71.5 NaN - 2007-05-15 12:00:00 76.0 76.0 76.0 - 2007-05-16 12:00:00 77.0 77.0 76.5 - 2007-05-17 12:00:00 76.0 76.0 76.0 - 2007-05-18 12:00:00 76.0 76.0 76.0 - 2007-05-19 12:00:00 76.0 75.5 75.5 - 2007-05-20 12:00:00 79.0 78.5 78.5 - 2007-05-21 12:00:00 79.0 79.0 79.0 - 2007-05-22 12:00:00 79.0 79.0 78.5 - 2007-05-23 12:00:00 79.0 79.0 79.0 - 2007-05-24 12:00:00 79.5 79.5 79.0 - 2007-05-25 12:00:00 79.0 79.0 79.0 - 2007-05-26 12:00:00 79.5 79.0 79.0 - 2007-05-27 12:00:00 79.0 79.0 79.0 - 2007-05-28 12:00:00 79.0 79.0 79.0 - 2007-05-29 12:00:00 79.5 79.5 79.0 - 2007-05-30 12:00:00 80.0 79.5 79.5 - 2007-05-31 12:00:00 79.5 79.5 79.5 - 2007-06-01 12:00:00 79.5 79.0 79.0 - 2007-06-02 12:00:00 79.5 79.0 79.0 - 2007-06-03 12:00:00 80.0 80.0 80.0 - 2007-06-04 12:00:00 80.5 80.0 80.0 - 2007-06-05 12:00:00 80.5 80.5 80.0 - 2007-06-06 12:00:00 80.5 80.0 80.0 - 2007-06-07 12:00:00 80.0 80.0 79.5 - 2007-06-08 12:00:00 80.0 79.5 79.5 - 2007-06-09 12:00:00 79.5 79.5 79.5 - 2007-06-10 12:00:00 79.5 79.5 79.5 - 2007-06-11 12:00:00 79.5 79.5 79.5 - ... ... ... ... - 2016-09-19 12:00:00 83.0 84.0 84.0 - 2016-09-20 12:00:00 83.0 83.5 84.0 - 2016-09-21 12:00:00 83.0 83.5 84.0 - 2016-09-22 12:00:00 82.5 83.5 83.5 - 2016-09-23 12:00:00 82.5 83.0 83.5 - 2016-09-24 12:00:00 82.0 83.0 83.5 - 2016-09-25 12:00:00 81.5 82.5 83.0 - 2016-09-26 12:00:00 81.5 82.5 83.0 - 2016-09-27 12:00:00 81.5 82.5 83.0 - 2016-09-28 12:00:00 81.5 82.5 83.0 - 2016-09-29 12:00:00 82.0 83.0 83.5 - 2016-09-30 12:00:00 82.0 83.0 83.5 - 2016-10-01 12:00:00 82.5 83.0 83.5 - 2016-10-02 12:00:00 82.5 83.0 83.5 - 2016-10-03 12:00:00 82.0 82.5 83.0 - 2016-10-04 12:00:00 81.5 82.5 83.0 - 2016-10-05 12:00:00 80.5 81.5 82.5 - 2016-10-06 12:00:00 80.0 81.5 82.0 - 2016-10-07 12:00:00 79.5 81.0 82.0 - 2016-10-08 12:00:00 79.5 81.0 82.0 - 2016-10-09 12:00:00 79.0 80.5 81.5 - 2016-10-10 12:00:00 79.0 80.5 81.5 - 2016-10-11 12:00:00 78.0 80.0 81.0 - 2016-10-12 12:00:00 77.5 79.5 81.0 - 2016-10-13 12:00:00 77.0 79.0 80.5 - 2016-10-14 12:00:00 76.5 78.5 80.0 - 2016-10-15 12:00:00 75.5 78.0 80.0 - 2016-10-16 12:00:00 75.5 78.0 79.5 - 2016-10-26 12:00:00 74.5 77.0 79.0 - 2016-10-28 12:00:00 74.0 76.5 79.0 + SWI_060 SWI_100 SSF + 2007-05-10 12:00:00 NaN NaN 1.0 + 2007-05-14 12:00:00 71.5 NaN 1.0 + 2007-05-15 12:00:00 76.0 76.0 1.0 + 2007-05-16 12:00:00 77.0 76.5 1.0 + 2007-05-17 12:00:00 76.0 76.0 1.0 + ... ... ... ... + 2016-10-14 12:00:00 78.5 80.0 1.0 + 2016-10-15 12:00:00 78.0 80.0 1.0 + 2016-10-16 12:00:00 78.0 79.5 1.0 + 2016-10-26 12:00:00 77.0 79.0 1.0 + 2016-10-28 12:00:00 76.5 79.0 1.0 [1603 rows x 9 columns] @@ -172,7 +67,7 @@ With this object we can read the data Since the returned value is a pandas.DataFrame we can plot the data easily. -.. code:: ipython2 +.. code:: ipython3 fig, ax = plt.subplots(1, 1, figsize=(15, 5)) data[['SWI_001', 'SWI_010']].plot(ax=ax) @@ -181,6 +76,6 @@ easily. -.. image:: read_cgls_swi_ts_files/read_cgls_swi_ts_9_0.png +.. image:: read_cgls_swi_ts_files/read_cgls_swi_ts_7_0.png diff --git a/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_7_0.png b/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_7_0.png new file mode 100644 index 0000000..605b015 Binary files /dev/null and b/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_7_0.png differ diff --git a/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_9_0.png b/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_9_0.png deleted file mode 100644 index f3232f4..0000000 Binary files a/docs/read_cgls_swi_ts_files/read_cgls_swi_ts_9_0.png and /dev/null differ diff --git a/docs/read_eumetsat.ipynb b/docs/read_eumetsat.ipynb new file mode 100644 index 0000000..3f4784d --- /dev/null +++ b/docs/read_eumetsat.ipynb @@ -0,0 +1,658 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e52304e8", + "metadata": {}, + "source": [ + "# EUMETSAT\n", + "\n", + "The following example show how to read ASCAT Level 1b and Level 2 data in various formats (BUFR, EPS Native, netCDF). The data has been ordered from the EUMETSAT Data Centre (https://eoportal.eumetsat.int)." + ] + }, + { + "cell_type": "markdown", + "id": "00d374f0", + "metadata": {}, + "source": [ + "## ASCAT Level 1b\n", + "### Read Level 1b BUFR file returning generic format" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "e74f67f4", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cartopy\n", + "from datetime import datetime\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from ascat.eumetsat.level1 import AscatL1bFile\n", + "from ascat.eumetsat.level1 import AscatL1bBufrFile\n", + "from ascat.eumetsat.level1 import AscatL1bBufrFileList\n", + "from ascat.eumetsat.level1 import AscatL1bNcFile\n", + "from ascat.eumetsat.level1 import AscatL1bNcFileList\n", + "from ascat.eumetsat.level1 import AscatL1bEpsFile\n", + "from ascat.eumetsat.level1 import AscatL1bEpsFileList\n", + "from ascat.eumetsat.level1 import AscatL1bHdf5File\n", + "from ascat.eumetsat.level1 import AscatL1bHdf5FileList" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "1be16c97", + "metadata": {}, + "outputs": [], + "source": [ + "path = os.path.join('..', 'tests','ascat_test_data', 'eumetsat',\n", + " 'ASCAT_generic_reader_data')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "e544da33", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(68.91681, 168.80144, '2010-06-09T01:39:00.000', 18872, 1, 215., [63.32, 52.36, 63.4 ], [-13.51, -11.38, -13.51], [ 6.68, 322.19, 277.56], [0, 0, 0], [1, 2, 3], [0.031, 0.036, 0.044], [0, 0, 0], [0.999, 1. , 1. ], 0, 0., 3, 1),\n", + " (69.00519, 168.60977, '2010-06-09T01:39:00.000', 18872, 2, 215., [62.86, 51.89, 62.96], [-13.42, -11.13, -13.12], [ 6.5 , 322.01, 277.38], [0, 0, 0], [1, 2, 3], [0.032, 0.033, 0.047], [0, 0, 0], [0.994, 0.998, 0.994], 0, 0., 3, 1),\n", + " (69.09337, 168.41656, '2010-06-09T01:39:00.000', 18872, 3, 215., [62.41, 51.42, 62.49], [-13.87, -11.21, -13.46], [ 6.33, 321.83, 277.2 ], [0, 0, 0], [1, 2, 3], [0.051, 0.035, 0.055], [0, 0, 0], [0.962, 0.966, 0.942], 0, 0., 3, 1),\n", + " ...,\n", + " (75.06332, 94.81529, '2010-06-09T03:20:58.000', 18873, 80, 211., [62.91, 51.42, 62.93], [-20.72, -18.1 , -21.4 ], [ 49.34, 95.85, 142.29], [0, 0, 0], [1, 2, 3], [0.054, 0.058, 0.051], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1),\n", + " (75.07438, 94.38296, '2010-06-09T03:20:58.000', 18873, 81, 211., [63.38, 51.89, 63.39], [-20.03, -17.17, -20.9 ], [ 48.89, 95.43, 141.91], [0, 0, 0], [1, 2, 3], [0.06 , 0.056, 0.059], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1),\n", + " (75.08462, 93.95003, '2010-06-09T03:20:58.000', 18873, 82, 211., [63.85, 52.35, 63.85], [-19.63, -16.91, -20.82], [ 48.43, 95.02, 141.52], [0, 0, 0], [1, 2, 3], [0.063, 0.058, 0.061], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1)],\n", + " dtype=[('lat', '" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_crs = cartopy.crs.PlateCarree()\n", + "data_crs = cartopy.crs.PlateCarree()\n", + "\n", + "fig = plt.figure(figsize=(12, 6))\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", + "ax.set_title('Level 1 BUFR example - Sigma0 Fore Beam')\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", + "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", + "\n", + "float32_nan = -999999.\n", + "valid = data['sig'][:, 0] != float32_nan\n", + "\n", + "sc = ax.scatter(data['lon'][valid], data['lat'][valid], \n", + " c=data['sig'][valid, 0], zorder=3, marker='s', s=2,\n", + " transform=data_crs)\n", + "\n", + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Backscatter [dB]')" + ] + }, + { + "cell_type": "markdown", + "id": "1738df7d", + "metadata": {}, + "source": [ + "### Read Level 1b BUFR file returning original format" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "d33f0c39", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(68.91681, 168.80144, '2010-06-09T01:39:00.000', 4., 215., 18872., 1., 1., 63.32, 6.68, -13.51, 3.1, 0., 0., 0.999, 2., 52.36, 322.19, -11.38, 3.6, 0., 0., 1. , 3., 63.4 , 277.56, -13.51, 4.4, 0., 0., 1. ),\n", + " (69.00519, 168.60977, '2010-06-09T01:39:00.000', 4., 215., 18872., 2., 1., 62.86, 6.5 , -13.42, 3.2, 0., 0., 0.994, 2., 51.89, 322.01, -11.13, 3.3, 0., 0., 0.998, 3., 62.96, 277.38, -13.12, 4.7, 0., 0., 0.994),\n", + " (69.09337, 168.41656, '2010-06-09T01:39:00.000', 4., 215., 18872., 3., 1., 62.41, 6.33, -13.87, 5.1, 0., 0., 0.962, 2., 51.42, 321.83, -11.21, 3.5, 0., 0., 0.966, 3., 62.49, 277.2 , -13.46, 5.5, 0., 0., 0.942),\n", + " ...,\n", + " (75.06332, 94.81529, '2010-06-09T03:20:58.000', 4., 211., 18873., 80., 1., 62.91, 49.34, -20.72, 5.4, 0., 0., 1. , 2., 51.42, 95.85, -18.1 , 5.8, 0., 0., 1. , 3., 62.93, 142.29, -21.4 , 5.1, 0., 0., 1. ),\n", + " (75.07438, 94.38296, '2010-06-09T03:20:58.000', 4., 211., 18873., 81., 1., 63.38, 48.89, -20.03, 6. , 0., 0., 1. , 2., 51.89, 95.43, -17.17, 5.6, 0., 0., 1. , 3., 63.39, 141.91, -20.9 , 5.9, 0., 0., 1. ),\n", + " (75.08462, 93.95003, '2010-06-09T03:20:58.000', 4., 211., 18873., 82., 1., 63.85, 48.43, -19.63, 6.3, 0., 0., 1. , 2., 52.35, 95.02, -16.91, 5.8, 0., 0., 1. , 3., 63.85, 141.52, -20.82, 6.1, 0., 0., 1. )],\n", + " dtype=[('lat', '" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_crs = cartopy.crs.PlateCarree()\n", + "data_crs = cartopy.crs.PlateCarree()\n", + "\n", + "fig = plt.figure(figsize=(12, 6))\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", + "ax.set_title('Level 1 BUFR example - Sigma0 Fore Beam')\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", + "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", + "\n", + "bufr_nan = 1.7e+38\n", + "valid = data['m_Backscatter'] != bufr_nan\n", + "\n", + "sc = ax.scatter(data['lon'][valid], data['lat'][valid], \n", + " c=data['m_Backscatter'][valid], zorder=3, marker='s', s=2,\n", + " transform=data_crs)\n", + "\n", + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Backscatter [dB]')" + ] + }, + { + "cell_type": "markdown", + "id": "e52fed39", + "metadata": {}, + "source": [ + "### Read Level 1b BUFR file using a timestamp" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9c12237f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(68.91681, 168.80144, '2010-06-09T01:39:00.000', 18872, 1, 215., [63.32, 52.36, 63.4 ], [-13.51, -11.38, -13.51], [ 6.68, 322.19, 277.56], [0, 0, 0], [1, 2, 3], [0.031, 0.036, 0.044], [0, 0, 0], [0.999, 1. , 1. ], 0, 0., 3, 1),\n", + " (69.00519, 168.60977, '2010-06-09T01:39:00.000', 18872, 2, 215., [62.86, 51.89, 62.96], [-13.42, -11.13, -13.12], [ 6.5 , 322.01, 277.38], [0, 0, 0], [1, 2, 3], [0.032, 0.033, 0.047], [0, 0, 0], [0.994, 0.998, 0.994], 0, 0., 3, 1),\n", + " (69.09337, 168.41656, '2010-06-09T01:39:00.000', 18872, 3, 215., [62.41, 51.42, 62.49], [-13.87, -11.21, -13.46], [ 6.33, 321.83, 277.2 ], [0, 0, 0], [1, 2, 3], [0.051, 0.035, 0.055], [0, 0, 0], [0.962, 0.966, 0.942], 0, 0., 3, 1),\n", + " ...,\n", + " (75.06332, 94.81529, '2010-06-09T03:20:58.000', 18873, 80, 211., [62.91, 51.42, 62.93], [-20.72, -18.1 , -21.4 ], [ 49.34, 95.85, 142.29], [0, 0, 0], [1, 2, 3], [0.054, 0.058, 0.051], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1),\n", + " (75.07438, 94.38296, '2010-06-09T03:20:58.000', 18873, 81, 211., [63.38, 51.89, 63.39], [-20.03, -17.17, -20.9 ], [ 48.89, 95.43, 141.91], [0, 0, 0], [1, 2, 3], [0.06 , 0.056, 0.059], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1),\n", + " (75.08462, 93.95003, '2010-06-09T03:20:58.000', 18873, 82, 211., [63.85, 52.35, 63.85], [-19.63, -16.91, -20.82], [ 48.43, 95.02, 141.52], [0, 0, 0], [1, 2, 3], [0.063, 0.058, 0.061], [0, 0, 0], [1. , 1. , 1. ], 1, 3263., 3, 1)],\n", + " dtype=[('lat', 'i4'), ('as_des_pass', 'i1'), ('sat_track_azi', 'u4', (3,)), ('f_kp', 'i1', (3,)), ('f_usable', 'i1', (3,)), ('f_f', '" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plot_crs = cartopy.crs.PlateCarree()\n", + "data_crs = cartopy.crs.PlateCarree()\n", + "\n", + "fig = plt.figure(figsize=(12, 6))\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", + "ax.set_title('Level 2 BUFR example - Soil moisture')\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", + "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", + "\n", + "field = 'sm'\n", + "float32_nan = -999999.\n", + "valid = data[field] != float32_nan\n", + "\n", + "sc = ax.scatter(data['lon'][valid], data['lat'][valid], \n", + " c=data[field][valid], zorder=3, marker='s', s=2,\n", + " transform=data_crs)\n", + "\n", + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Soil moisture [%]')" + ] + }, + { + "cell_type": "markdown", + "id": "be7747e4", + "metadata": {}, + "source": [ + "### Read Level 2 BUFR file returning original format" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "a6efced3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(64.74398, 105.99558, '2017-02-20T05:09:00.000', 3., 206., 22966., 1., 1., 63.31, 356.33, -13.78, 4.5, 0., 0., 1. , 2., 52.35, 311.8 , -12.86, 3.9, 0., 0., 1. , 3., 63.36, 267.25, -14.03, 3.8, 0., 0., 1. , 29.2, 3.6, -11.77, 0.08, -0.09, 0., 4.25, -13.02, -8.76, 36.7, 1.7e+38, 0., 16., 100., 100., 100., 3., 2.),\n", + " (64.81854, 105.79933, '2017-02-20T05:09:00.000', 3., 206., 22966., 2., 1., 62.86, 356.15, -13.87, 4.6, 0., 0., 1. , 2., 51.89, 311.63, -12.57, 3.7, 0., 0., 1. , 3., 62.91, 267.08, -13.74, 3.2, 0., 0., 1. , 30.2, 3.8, -11.6 , 0.08, -0.09, 0., 4.13, -12.85, -8.72, 35.4, 1.7e+38, 0., 16., 100., 100., 100., 1., 3.),\n", + " (64.89284, 105.60199, '2017-02-20T05:09:00.000', 3., 206., 22966., 3., 1., 62.41, 355.97, -13.54, 4.5, 0., 0., 1. , 2., 51.42, 311.45, -12.15, 3.7, 0., 0., 1. , 3., 62.45, 266.9 , -13.46, 4.1, 0., 0., 1. , 35.7, 4.1, -11.22, 0.08, -0.09, 0., 4.05, -12.66, -8.61, 33.4, 1.7e+38, 0., 48., 100., 100., 100., 0., 5.),\n", + " ...,\n", + " (58.81395, 38.96368, '2017-02-20T06:53:58.000', 3., 198., 22967., 80., 1., 62.91, 49.74, -10.56, 2.8, 0., 0., 1. , 2., 51.43, 96.24, -10.12, 3. , 0., 0., 1. , 3., 62.95, 142.57, -10.8 , 2.6, 0., 0., 1. , 80. , 3.6, -9.06, 0.09, -0.1 , 0., 3.98, -12.24, -8.26, 50.1, 1.7e+38, 4., 48., 99., 56., 99., 0., 0.),\n", + " (58.82597, 38.74857, '2017-02-20T06:53:58.000', 3., 198., 22967., 81., 1., 63.38, 49.53, -10.96, 3.7, 0., 0., 0.998, 2., 51.9 , 96.05, -10.23, 3.3, 0., 0., 0.997, 3., 63.42, 142.41, -11.1 , 3.3, 0., 0., 0.997, 78. , 3.7, -9.24, 0.1 , -0.11, 0., 4.03, -12.38, -8.35, 49.9, 1.7e+38, 4., 16., 100., 56., 100., 0., 0.),\n", + " (58.83763, 38.5333 , '2017-02-20T06:53:58.000', 3., 198., 22967., 82., 1., 63.83, 49.31, -11.88, 5.6, 0., 0., 0.943, 2., 52.36, 95.87, -10.71, 5.6, 0., 0., 0.953, 3., 63.88, 142.26, -11.85, 5.1, 0., 0., 0.929, 72.6, 4.2, -9.81, 0.11, -0.12, 0., 4.13, -12.81, -8.68, 49.3, 1.7e+38, 4., 0., 99., 56., 99., 9., 1.)],\n", + " dtype=[('lat', 'i4'), ('sat_track_azi', 'i4'), ('as_des_pass', 'i1'), ('sat_track_azi', 'u4', (3,)), ('f_kp', 'i1', (3,)), ('f_usable', 'i1', (3,)), ('f_f', 'i4'), ('sat_track_azi', '" - ] - }, - "metadata": { - 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import cartopy\n", - "from cartopy.mpl.geoaxes import GeoAxes\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits.axes_grid1 import AxesGrid\n", - "\n", - "data_crs = cartopy.crs.PlateCarree()\n", - "proj = cartopy.crs.Miller()\n", - "axes_class = (GeoAxes, dict(map_projection=proj))\n", - "\n", - "# image_list = [generic_image_bufr, generic_image_eps, generic_image_nc]\n", - "image_dict = {'bufr': generic_image_bufr, 'eps_native': generic_image_eps, 'netCDF': generic_image_nc}\n", - "for image in image_dict:\n", - " lon = image_dict[image].lon\n", - " lat = image_dict[image].lat\n", - " data = image_dict[image].data['sigf']\n", - "\n", - " style_label = 'seaborn-talk'\n", - " with plt.style.context(style_label):\n", - " fig = plt.figure(figsize=(10, 8))\n", - " ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1),\n", - " cbar_location='right', cbar_mode='single', cbar_pad=0.2,\n", - " cbar_size='4%', label_mode='')\n", - "\n", - "\n", - " ax[0].set_title('ASCAT generic reader example lvl1b - ' + image)\n", - "\n", - " ax[0].add_feature(cartopy.feature.LAND)\n", - " ax[0].add_feature(cartopy.feature.OCEAN)\n", - " ax[0].add_feature(cartopy.feature.COASTLINE)\n", - " ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - " ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - " ax[0].add_feature(cartopy.feature.RIVERS)\n", - "\n", - " ax[0].set_extent([-175, 175, -90, 90])\n", - "\n", - " sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=-50,\n", - " vmax=0, zorder=3, transform=data_crs)\n", - "\n", - " cbar = ax.cbar_axes[0].colorbar(sc)\n", - " cbar.set_label_text('Sigma0 of the f-beam')\n", - "\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### If we want to filter the data regarding one or more variables, we can create a simple mask. Let's try it for the land flag." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "\n", - "data, meta, timestamp, lon, lat, time_var = generic_image_bufr\n", - "\n", - "valid = np.ones(data[data.dtype.names[0]].shape, dtype=np.bool)\n", - "beams = ['f', 'm', 'a']\n", - "\n", - "for b in beams:\n", - " valid = (valid & (data['land_flag' + b] > 0.095))\n", - "\n", - "data_masked = data[valid]\n", - "lon_masked = lon[valid]\n", - "lat_masked = lat[valid]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let's plot it to see the differences." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "lon = lon_masked\n", - "lat = lat_masked\n", - "data = data_masked['sigf']\n", - "\n", - "style_label = 'seaborn-talk'\n", - "with plt.style.context(style_label):\n", - " fig = plt.figure(figsize=(10, 8))\n", - " ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1),\n", - " cbar_location='right', cbar_mode='single', cbar_pad=0.2,\n", - " cbar_size='4%', label_mode='')\n", - "\n", - "\n", - " ax[0].set_title('ASCAT generic reader example lvl1b - masked')\n", - "\n", - " ax[0].add_feature(cartopy.feature.LAND)\n", - " ax[0].add_feature(cartopy.feature.OCEAN)\n", - " ax[0].add_feature(cartopy.feature.COASTLINE)\n", - " ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - " ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - " ax[0].add_feature(cartopy.feature.RIVERS)\n", - "\n", - " ax[0].set_extent([-175, 175, -90, 90])\n", - "\n", - " sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=-50,\n", - " vmax=0, zorder=3, transform=data_crs)\n", - "\n", - " cbar = ax.cbar_axes[0].colorbar(sc)\n", - " cbar.set_label_text('Sigma0 of the f-beam')\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let's now use the multitemporal AscatL1Bufr class to read a file from the folder by giving it a datetime object. As already said, the usage of AscatL1Eps and AscatL1Nc is exactly the same." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import datetime\n", - "\n", - "generic_image_multi = multi_reader.read(datetime(2010, 6, 9, 1, 39))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Level 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Same thing as for lvl1b: import, path to data files, creation of objects" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import ascat.level2 as level2\n", - "\n", - "test_data_path = os.path.join('..', 'tests','ascat_test_data', 'eumetsat', 'ASCAT_generic_reader_data')\n", - "bufr_file_path = os.path.join(test_data_path, 'bufr')\n", - "single_file_path_bufr = os.path.join(bufr_file_path, 'M01-ASCA-ASCSMO02-NA-5.0-20180612035700.000000000Z-20180612044530-1281300.bfr')\n", - "single_file_path_eps = os.path.join(test_data_path, 'eps_nat', 'ASCA_SMO_02_M01_20180612035700Z_20180612053856Z_N_O_20180612044530Z.nat')\n", - "single_file_path_nc = os.path.join(test_data_path, 'nc', 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPB+ASCAT_C_EUMP_20180612035700_29742_eps_o_250_ssm_l2.nc')\n", - "\n", - "\n", - "single_reader_bufr = level2.AscatL2Image(single_file_path_bufr)\n", - "single_reader_eps = level2.AscatL2Image(single_file_path_eps)\n", - "single_reader_nc = level2.AscatL2Image(single_file_path_nc)\n", - "multi_reader = level2.AscatL2Bufr(bufr_file_path, eo_portal=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Now let's read the single lvl2 orbit files" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "generic_image_bufr = single_reader_bufr.read()\n", - "generic_image_eps = single_reader_eps.read()\n", - "generic_image_nc = single_reader_nc.read()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot it:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import cartopy\n", - "from cartopy.mpl.geoaxes import GeoAxes\n", - "import matplotlib.pyplot as plt\n", - "from mpl_toolkits.axes_grid1 import AxesGrid\n", - "\n", - "data_crs = cartopy.crs.PlateCarree()\n", - "proj = cartopy.crs.Miller()\n", - "axes_class = (GeoAxes, dict(map_projection=proj))\n", - "\n", - "lon = generic_image_bufr.lon\n", - "lat = generic_image_bufr.lat\n", - "data = generic_image_bufr.data['sm']\n", - "\n", - "style_label = 'seaborn-talk'\n", - "with plt.style.context(style_label):\n", - " fig = plt.figure(figsize=(10, 8))\n", - " ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1),\n", - " cbar_location='right', cbar_mode='single', cbar_pad=0.2,\n", - " cbar_size='4%', label_mode='')\n", - "\n", - "\n", - " ax[0].set_title('ASCAT generic reader example lvl2')\n", - "\n", - " ax[0].add_feature(cartopy.feature.LAND)\n", - " ax[0].add_feature(cartopy.feature.OCEAN)\n", - " ax[0].add_feature(cartopy.feature.COASTLINE)\n", - " ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - " ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - " ax[0].add_feature(cartopy.feature.RIVERS)\n", - "\n", - " ax[0].set_extent([-175, 175, -90, 90])\n", - "\n", - " sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=0,\n", - " vmax=100, zorder=3, transform=data_crs)\n", - "\n", - " cbar = ax.cbar_axes[0].colorbar(sc)\n", - " cbar.set_label_text('Surface Soil Moisture (%)')\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let's now use the multitemporal AscatL2Bufr class to read a file from the folder by giving it a datetime object." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import datetime\n", - "\n", - "generic_image_multi = multi_reader.read(datetime(2018, 6, 12, 3, 57))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.15" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/read_generic.rst b/docs/read_generic.rst deleted file mode 100644 index 273b76f..0000000 --- a/docs/read_generic.rst +++ /dev/null @@ -1,265 +0,0 @@ - -Example Generic Data Reader ---------------------------- - -In this Example we use the generic lvl1b and lvl2 readers to read files -in multiple formats (bufr, eps_native, netCDF). The datasets are from -the Data Centre of the EUMETSAT-EO Portal -(https://eoportal.eumetsat.int). Also simple plot scripts and simple -masking is shown. For the multitemporal class, where you can read -multiple orbit files, the process is only shown for bufr, but the -classes for the other formats work the same. - -Level 1b --------- - -First let’s do the import, set the path to the ascat_test_data and initialise the objects. The path for to the bufr ascat_test_data is split so we can use it for the MultiTemporal class. -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - import os - import ascat.level1 as level1 - - test_data_path = os.path.join('..', 'tests','ascat_test_data', 'eumetsat', 'ASCAT_generic_reader_data') - bufr_file_path = os.path.join(test_data_path, 'bufr') - single_file_path_bufr = os.path.join(bufr_file_path, 'M02-ASCA-ASCSZR1B0200-NA-9.1-20100609013900.000000000Z-20130824233100-1280350.bfr') - single_file_path_eps = os.path.join(test_data_path, 'eps_nat', 'ASCA_SZR_1B_M02_20100609013900Z_20100609032058Z_R_O_20130824233100Z.nat') - single_file_path_nc = os.path.join(test_data_path, 'nc', 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20100609013900_18872_eps_o_125_l1.nc') - - - single_reader_bufr = level1.AscatL1Image(single_file_path_bufr) - single_reader_eps = level1.AscatL1Image(single_file_path_eps) - single_reader_nc = level1.AscatL1Image(single_file_path_nc) - multi_reader = level1.AscatL1Bufr(bufr_file_path) - -Now let’s read the single lvl1b orbit files- -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - generic_image_bufr = single_reader_bufr.read() - generic_image_eps = single_reader_eps.read() - generic_image_nc = single_reader_nc.read() - -Simple plot script for all three formats (should lead to the same result). -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - import cartopy - from cartopy.mpl.geoaxes import GeoAxes - import matplotlib.pyplot as plt - from mpl_toolkits.axes_grid1 import AxesGrid - - data_crs = cartopy.crs.PlateCarree() - proj = cartopy.crs.Miller() - axes_class = (GeoAxes, dict(map_projection=proj)) - - # image_list = [generic_image_bufr, generic_image_eps, generic_image_nc] - image_dict = {'bufr': generic_image_bufr, 'eps_native': generic_image_eps, 'netCDF': generic_image_nc} - for image in image_dict: - lon = image_dict[image].lon - lat = image_dict[image].lat - data = image_dict[image].data['sigf'] - - style_label = 'seaborn-talk' - with plt.style.context(style_label): - fig = plt.figure(figsize=(10, 8)) - ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1), - cbar_location='right', cbar_mode='single', cbar_pad=0.2, - cbar_size='4%', label_mode='') - - - ax[0].set_title('ASCAT generic reader example lvl1b - ' + image) - - ax[0].add_feature(cartopy.feature.LAND) - ax[0].add_feature(cartopy.feature.OCEAN) - ax[0].add_feature(cartopy.feature.COASTLINE) - ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':') - ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5) - ax[0].add_feature(cartopy.feature.RIVERS) - - ax[0].set_extent([-175, 175, -90, 90]) - - sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=-50, - vmax=0, zorder=3, transform=data_crs) - - cbar = ax.cbar_axes[0].colorbar(sc) - cbar.set_label_text('Sigma0 of the f-beam') - - plt.show() - - - -.. image:: read_generic_files/read_generic_8_0.png - - - -.. image:: read_generic_files/read_generic_8_1.png - - - -.. image:: read_generic_files/read_generic_8_2.png - - -If we want to filter the data regarding one or more variables, we can create a simple mask. Let’s try it for the land flag. -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - import numpy as np - - data, meta, timestamp, lon, lat, time_var = generic_image_bufr - - valid = np.ones(data[data.dtype.names[0]].shape, dtype=np.bool) - beams = ['f', 'm', 'a'] - - for b in beams: - valid = (valid & (data['land_flag' + b] > 0.095)) - - data_masked = data[valid] - lon_masked = lon[valid] - lat_masked = lat[valid] - -Let’s plot it to see the differences. -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - lon = lon_masked - lat = lat_masked - data = data_masked['sigf'] - - style_label = 'seaborn-talk' - with plt.style.context(style_label): - fig = plt.figure(figsize=(10, 8)) - ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1), - cbar_location='right', cbar_mode='single', cbar_pad=0.2, - cbar_size='4%', label_mode='') - - - ax[0].set_title('ASCAT generic reader example lvl1b - masked') - - ax[0].add_feature(cartopy.feature.LAND) - ax[0].add_feature(cartopy.feature.OCEAN) - ax[0].add_feature(cartopy.feature.COASTLINE) - ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':') - ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5) - ax[0].add_feature(cartopy.feature.RIVERS) - - ax[0].set_extent([-175, 175, -90, 90]) - - sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=-50, - vmax=0, zorder=3, transform=data_crs) - - cbar = ax.cbar_axes[0].colorbar(sc) - cbar.set_label_text('Sigma0 of the f-beam') - - plt.show() - - - -.. image:: read_generic_files/read_generic_12_0.png - - -Let’s now use the multitemporal AscatL1Bufr class to read a file from the folder by giving it a datetime object. As already said, the usage of AscatL1Eps and AscatL1Nc is exactly the same. -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - from datetime import datetime - - generic_image_multi = multi_reader.read(datetime(2010, 6, 9, 1, 39)) - -Level 2 -------- - -Same thing as for lvl1b: import, path to data files, creation of objects -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - import os - import ascat.level2 as level2 - - test_data_path = os.path.join('..', 'tests','ascat_test_data', 'eumetsat', 'ASCAT_generic_reader_data') - bufr_file_path = os.path.join(test_data_path, 'bufr') - single_file_path_bufr = os.path.join(bufr_file_path, 'M01-ASCA-ASCSMO02-NA-5.0-20180612035700.000000000Z-20180612044530-1281300.bfr') - single_file_path_eps = os.path.join(test_data_path, 'eps_nat', 'ASCA_SMO_02_M01_20180612035700Z_20180612053856Z_N_O_20180612044530Z.nat') - single_file_path_nc = os.path.join(test_data_path, 'nc', 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPB+ASCAT_C_EUMP_20180612035700_29742_eps_o_250_ssm_l2.nc') - - - single_reader_bufr = level2.AscatL2Image(single_file_path_bufr) - single_reader_eps = level2.AscatL2Image(single_file_path_eps) - single_reader_nc = level2.AscatL2Image(single_file_path_nc) - multi_reader = level2.AscatL2Bufr(bufr_file_path, eo_portal=True) - -Now let’s read the single lvl2 orbit files -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - generic_image_bufr = single_reader_bufr.read() - generic_image_eps = single_reader_eps.read() - generic_image_nc = single_reader_nc.read() - -Plot it: -~~~~~~~~ - -.. code:: ipython2 - - import cartopy - from cartopy.mpl.geoaxes import GeoAxes - import matplotlib.pyplot as plt - from mpl_toolkits.axes_grid1 import AxesGrid - - data_crs = cartopy.crs.PlateCarree() - proj = cartopy.crs.Miller() - axes_class = (GeoAxes, dict(map_projection=proj)) - - lon = generic_image_bufr.lon - lat = generic_image_bufr.lat - data = generic_image_bufr.data['sm'] - - style_label = 'seaborn-talk' - with plt.style.context(style_label): - fig = plt.figure(figsize=(10, 8)) - ax = AxesGrid(fig, 111, axes_class=axes_class, nrows_ncols=(1, 1), - cbar_location='right', cbar_mode='single', cbar_pad=0.2, - cbar_size='4%', label_mode='') - - - ax[0].set_title('ASCAT generic reader example lvl2') - - ax[0].add_feature(cartopy.feature.LAND) - ax[0].add_feature(cartopy.feature.OCEAN) - ax[0].add_feature(cartopy.feature.COASTLINE) - ax[0].add_feature(cartopy.feature.BORDERS, linestyle=':') - ax[0].add_feature(cartopy.feature.LAKES, alpha=0.5) - ax[0].add_feature(cartopy.feature.RIVERS) - - ax[0].set_extent([-175, 175, -90, 90]) - - sc = ax[0].scatter(lon, lat, c=data, s=7, marker='o', vmin=0, - vmax=100, zorder=3, transform=data_crs) - - cbar = ax.cbar_axes[0].colorbar(sc) - cbar.set_label_text('Surface Soil Moisture (%)') - - plt.show() - - - -.. image:: read_generic_files/read_generic_21_0.png - - -Let’s now use the multitemporal AscatL2Bufr class to read a file from the folder by giving it a datetime object. -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. code:: ipython2 - - from datetime import datetime - - generic_image_multi = multi_reader.read(datetime(2018, 6, 12, 3, 57)) - diff --git a/docs/read_generic_files/read_generic_12_0.png b/docs/read_generic_files/read_generic_12_0.png deleted file mode 100644 index 7876c90..0000000 Binary files a/docs/read_generic_files/read_generic_12_0.png and /dev/null differ diff --git a/docs/read_generic_files/read_generic_21_0.png b/docs/read_generic_files/read_generic_21_0.png deleted file mode 100644 index 6b672d7..0000000 Binary files a/docs/read_generic_files/read_generic_21_0.png and /dev/null differ diff --git a/docs/read_generic_files/read_generic_8_0.png b/docs/read_generic_files/read_generic_8_0.png deleted file mode 100644 index 3869471..0000000 Binary files a/docs/read_generic_files/read_generic_8_0.png and /dev/null differ diff --git a/docs/read_generic_files/read_generic_8_1.png b/docs/read_generic_files/read_generic_8_1.png deleted file mode 100644 index 84e1309..0000000 Binary files a/docs/read_generic_files/read_generic_8_1.png and /dev/null differ diff --git a/docs/read_generic_files/read_generic_8_2.png b/docs/read_generic_files/read_generic_8_2.png deleted file mode 100644 index 808b9dc..0000000 Binary files a/docs/read_generic_files/read_generic_8_2.png and /dev/null differ diff --git a/docs/read_hsaf_cdr.ipynb b/docs/read_hsaf_cdr.ipynb index fdf15ba..74f3be6 100644 --- a/docs/read_hsaf_cdr.ipynb +++ b/docs/read_hsaf_cdr.ipynb @@ -4,27 +4,33 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Example H SAF SSM CDR products" + "## Example H SAF Metop ASCAT SSM DR products" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "In this Example we will read and plot the H SAF SSM CDR products H109, H110 and H111 using the test data included in the ascat package." + "The following example shows how to read and plot H SAF Metop ASCAT SSM data record products using the test data included in the ascat package." ] }, { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", - "import ascat.h_saf as h_saf\n", - "\n", + "import matplotlib.pyplot as plt\n", + "from ascat.h_saf import AscatSsmDataRecord" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ "test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf')\n", "h109_path = os.path.join(test_data_path, 'h109')\n", "h110_path = os.path.join(test_data_path, 'h110')\n", @@ -32,9 +38,9 @@ "grid_path = os.path.join(test_data_path, 'grid')\n", "static_layer_path = os.path.join(test_data_path, 'static_layer')\n", "\n", - "h109_reader = h_saf.H109Ts(h109_path, grid_path, static_layer_path=static_layer_path)\n", - "h110_reader = h_saf.H110Ts(h110_path, grid_path, static_layer_path=static_layer_path)\n", - "h111_reader = h_saf.H111Ts(h111_path, grid_path, static_layer_path=static_layer_path)" + "h109_dr = AscatSsmDataRecord(h109_path, grid_path, static_layer_path=static_layer_path)\n", + "h110_dr = AscatSsmDataRecord(h110_path, grid_path, static_layer_path=static_layer_path)\n", + "h111_dr = AscatSsmDataRecord(h111_path, grid_path, static_layer_path=static_layer_path)" ] }, { @@ -46,217 +52,19 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " corr_flag dir proc_flag sat_id sm sm_noise \\\n", - "2007-01-01 21:06:01.843200 0 0 0 3 92 3 \n", - "2007-01-02 09:18:16.848000 0 1 0 3 91 3 \n", - "2007-01-03 10:37:43.104000 0 1 0 3 93 3 \n", - "2007-01-04 20:03:56.275200 0 0 0 3 91 3 \n", - "2007-01-05 21:23:26.246400 0 0 0 3 97 3 \n", - "2007-01-06 09:35:41.251200 0 1 0 3 92 3 \n", - "2007-01-06 21:02:37.507200 0 0 0 3 99 3 \n", - "2007-01-07 09:14:52.512000 0 1 0 3 88 3 \n", - "2007-01-08 10:34:20.582400 0 1 0 3 91 3 \n", - "2007-01-09 20:00:33.753600 0 0 0 3 92 3 \n", - "2007-01-10 21:20:01.910400 0 0 0 3 90 3 \n", - "2007-01-11 09:32:16.915200 0 1 0 3 87 3 \n", - "2007-01-11 20:59:13.084800 0 0 0 3 99 3 \n", - "2007-01-12 09:11:28.089600 0 1 0 3 87 3 \n", - "2007-01-12 10:51:33.753600 0 1 0 3 87 3 \n", - "2007-01-13 10:30:58.147200 0 1 0 3 87 3 \n", - "2007-01-14 19:57:13.132800 0 0 0 3 85 3 \n", - "2007-01-15 21:16:37.488000 0 0 0 3 85 3 \n", - "2007-01-16 09:28:52.492800 0 1 0 3 86 3 \n", - "2007-01-17 10:48:11.232000 0 1 0 3 82 3 \n", - "2007-01-18 10:27:35.625600 0 1 0 3 98 3 \n", - "2007-01-18 20:14:26.217600 0 0 0 3 93 2 \n", - "2007-01-19 19:53:50.611200 0 0 0 3 89 3 \n", - "2007-01-20 21:13:13.152000 0 0 0 3 93 3 \n", - "2007-01-21 09:25:28.156800 0 1 0 3 89 3 \n", - "2007-01-22 10:44:48.710400 0 1 0 3 89 3 \n", - "2007-01-23 10:24:13.104000 0 1 0 3 46 3 \n", - "2007-01-23 20:11:03.782400 0 0 0 3 43 3 \n", - "2007-01-24 19:50:28.089600 0 0 0 3 51 3 \n", - "2007-01-25 21:09:48.729600 0 0 0 3 43 3 \n", - "... ... ... ... ... ... ... \n", - "2015-12-19 21:20:37.507200 0 0 0 4 97 3 \n", - "2015-12-20 09:32:50.611200 0 1 0 4 88 3 \n", - "2015-12-20 20:05:52.483200 0 0 0 3 90 3 \n", - "2015-12-20 20:59:46.867200 0 0 0 4 97 3 \n", - "2015-12-21 09:11:59.971200 0 1 0 4 89 3 \n", - "2015-12-21 10:52:05.635200 0 1 0 4 86 3 \n", - "2015-12-21 19:45:16.876800 0 0 0 3 89 3 \n", - "2015-12-22 09:37:37.459200 0 1 0 3 90 2 \n", - "2015-12-22 10:31:30.028800 0 1 0 4 90 3 \n", - "2015-12-22 21:04:35.616000 0 0 0 3 87 3 \n", - "2015-12-23 09:16:50.620800 0 1 0 3 89 3 \n", - "2015-12-23 19:57:43.113600 0 0 0 4 90 3 \n", - "2015-12-24 10:36:14.976000 0 1 0 3 89 3 \n", - "2015-12-24 21:17:05.654400 2 0 0 4 100 3 \n", - "2015-12-25 09:29:20.659200 2 1 0 4 100 3 \n", - "2015-12-25 20:02:29.961600 0 0 0 3 94 3 \n", - "2015-12-26 10:48:37.497600 0 1 0 4 90 3 \n", - "2015-12-26 21:21:58.118400 0 0 0 3 91 3 \n", - "2015-12-27 09:34:13.123200 0 1 0 3 86 3 \n", - "2015-12-27 10:28:01.891200 0 1 0 4 88 3 \n", - "2015-12-27 20:14:52.483200 0 0 0 4 86 2 \n", - "2015-12-27 21:01:09.379200 0 0 0 3 88 3 \n", - "2015-12-28 09:13:24.384000 0 1 0 3 85 3 \n", - "2015-12-28 19:54:14.976000 0 0 0 4 88 3 \n", - "2015-12-29 10:32:52.540800 0 1 0 3 86 3 \n", - "2015-12-29 21:13:35.616000 0 0 0 4 90 3 \n", - "2015-12-30 09:25:50.620800 0 1 0 4 88 3 \n", - "2015-12-30 19:59:05.625600 0 0 0 3 86 3 \n", - "2015-12-31 10:45:09.360000 0 1 0 4 91 3 \n", - "2015-12-31 21:18:31.881600 0 0 0 3 89 3 \n", - "\n", - " ssf snow_prob frozen_prob abs_sm_gldas \\\n", - "2007-01-01 21:06:01.843200 1 0 29 NaN \n", - "2007-01-02 09:18:16.848000 1 0 21 NaN \n", - "2007-01-03 10:37:43.104000 1 11 29 NaN \n", - "2007-01-04 20:03:56.275200 1 22 29 NaN \n", - "2007-01-05 21:23:26.246400 1 11 36 NaN \n", - "2007-01-06 09:35:41.251200 1 0 32 NaN \n", - "2007-01-06 21:02:37.507200 1 0 32 NaN \n", - "2007-01-07 09:14:52.512000 1 0 18 NaN \n", - "2007-01-08 10:34:20.582400 1 0 18 NaN \n", - "2007-01-09 20:00:33.753600 1 0 14 NaN \n", - "2007-01-10 21:20:01.910400 1 0 32 NaN \n", - "2007-01-11 09:32:16.915200 1 0 36 NaN \n", - "2007-01-11 20:59:13.084800 1 0 36 NaN \n", - "2007-01-12 09:11:28.089600 1 0 39 NaN \n", - "2007-01-12 10:51:33.753600 1 0 39 NaN \n", - "2007-01-13 10:30:58.147200 1 0 21 NaN \n", - "2007-01-14 19:57:13.132800 1 0 18 NaN \n", - "2007-01-15 21:16:37.488000 1 0 21 NaN \n", - "2007-01-16 09:28:52.492800 1 0 14 NaN \n", - "2007-01-17 10:48:11.232000 1 0 21 NaN \n", - "2007-01-18 10:27:35.625600 1 0 14 NaN \n", - "2007-01-18 20:14:26.217600 1 0 14 NaN \n", - "2007-01-19 19:53:50.611200 1 0 18 NaN \n", - "2007-01-20 21:13:13.152000 1 0 29 NaN \n", - "2007-01-21 09:25:28.156800 1 0 36 NaN \n", - "2007-01-22 10:44:48.710400 1 0 29 NaN \n", - "2007-01-23 10:24:13.104000 2 0 39 NaN \n", - "2007-01-23 20:11:03.782400 2 0 39 NaN \n", - "2007-01-24 19:50:28.089600 2 0 25 NaN \n", - "2007-01-25 21:09:48.729600 2 0 18 NaN \n", - "... ... ... ... ... \n", - "2015-12-19 21:20:37.507200 1 0 7 NaN \n", - "2015-12-20 09:32:50.611200 1 0 11 NaN \n", - "2015-12-20 20:05:52.483200 1 0 11 NaN \n", - "2015-12-20 20:59:46.867200 1 0 11 NaN \n", - "2015-12-21 09:11:59.971200 1 0 7 NaN \n", - "2015-12-21 10:52:05.635200 1 0 7 NaN \n", - "2015-12-21 19:45:16.876800 1 0 7 NaN \n", - "2015-12-22 09:37:37.459200 1 0 7 NaN \n", - "2015-12-22 10:31:30.028800 1 0 7 NaN \n", - "2015-12-22 21:04:35.616000 1 0 7 NaN \n", - "2015-12-23 09:16:50.620800 1 0 25 NaN \n", - "2015-12-23 19:57:43.113600 1 0 25 NaN \n", - "2015-12-24 10:36:14.976000 1 0 32 NaN \n", - "2015-12-24 21:17:05.654400 1 0 32 NaN \n", - "2015-12-25 09:29:20.659200 1 0 25 NaN \n", - "2015-12-25 20:02:29.961600 1 0 25 NaN \n", - "2015-12-26 10:48:37.497600 1 0 29 NaN \n", - "2015-12-26 21:21:58.118400 1 0 29 NaN \n", - "2015-12-27 09:34:13.123200 1 0 50 NaN \n", - "2015-12-27 10:28:01.891200 1 0 50 NaN \n", - "2015-12-27 20:14:52.483200 1 0 50 NaN \n", - "2015-12-27 21:01:09.379200 1 0 50 NaN \n", - "2015-12-28 09:13:24.384000 1 0 43 NaN \n", - "2015-12-28 19:54:14.976000 1 0 43 NaN \n", - "2015-12-29 10:32:52.540800 1 0 43 NaN \n", - "2015-12-29 21:13:35.616000 1 0 43 NaN \n", - "2015-12-30 09:25:50.620800 1 0 43 NaN \n", - "2015-12-30 19:59:05.625600 1 0 43 NaN \n", - "2015-12-31 10:45:09.360000 1 0 54 NaN \n", - "2015-12-31 21:18:31.881600 1 0 54 NaN \n", - "\n", - " abs_sm_noise_gldas abs_sm_hwsd abs_sm_noise_hwsd \n", - "2007-01-01 21:06:01.843200 NaN NaN NaN \n", - "2007-01-02 09:18:16.848000 NaN NaN NaN \n", - "2007-01-03 10:37:43.104000 NaN NaN NaN \n", - "2007-01-04 20:03:56.275200 NaN NaN NaN \n", - "2007-01-05 21:23:26.246400 NaN NaN NaN \n", - "2007-01-06 09:35:41.251200 NaN NaN NaN \n", - "2007-01-06 21:02:37.507200 NaN NaN NaN \n", - "2007-01-07 09:14:52.512000 NaN NaN NaN \n", - "2007-01-08 10:34:20.582400 NaN NaN NaN \n", - "2007-01-09 20:00:33.753600 NaN NaN NaN \n", - "2007-01-10 21:20:01.910400 NaN NaN NaN \n", - "2007-01-11 09:32:16.915200 NaN NaN NaN \n", - "2007-01-11 20:59:13.084800 NaN NaN NaN \n", - "2007-01-12 09:11:28.089600 NaN NaN NaN \n", - "2007-01-12 10:51:33.753600 NaN NaN NaN \n", - "2007-01-13 10:30:58.147200 NaN NaN NaN \n", - "2007-01-14 19:57:13.132800 NaN NaN NaN \n", - "2007-01-15 21:16:37.488000 NaN NaN NaN \n", - "2007-01-16 09:28:52.492800 NaN NaN NaN \n", - "2007-01-17 10:48:11.232000 NaN NaN NaN \n", - "2007-01-18 10:27:35.625600 NaN NaN NaN \n", - "2007-01-18 20:14:26.217600 NaN NaN NaN \n", - "2007-01-19 19:53:50.611200 NaN NaN NaN \n", - "2007-01-20 21:13:13.152000 NaN NaN NaN \n", - "2007-01-21 09:25:28.156800 NaN NaN NaN \n", - "2007-01-22 10:44:48.710400 NaN NaN NaN \n", - "2007-01-23 10:24:13.104000 NaN NaN NaN \n", - "2007-01-23 20:11:03.782400 NaN NaN NaN \n", - "2007-01-24 19:50:28.089600 NaN NaN NaN \n", - "2007-01-25 21:09:48.729600 NaN NaN NaN \n", - "... ... ... ... \n", - "2015-12-19 21:20:37.507200 NaN NaN NaN \n", - "2015-12-20 09:32:50.611200 NaN NaN NaN \n", - "2015-12-20 20:05:52.483200 NaN NaN NaN \n", - "2015-12-20 20:59:46.867200 NaN NaN NaN \n", - "2015-12-21 09:11:59.971200 NaN NaN NaN \n", - "2015-12-21 10:52:05.635200 NaN NaN NaN \n", - "2015-12-21 19:45:16.876800 NaN NaN NaN \n", - "2015-12-22 09:37:37.459200 NaN NaN NaN \n", - "2015-12-22 10:31:30.028800 NaN NaN NaN \n", - "2015-12-22 21:04:35.616000 NaN NaN NaN \n", - "2015-12-23 09:16:50.620800 NaN NaN NaN \n", - "2015-12-23 19:57:43.113600 NaN NaN NaN \n", - "2015-12-24 10:36:14.976000 NaN NaN NaN \n", - "2015-12-24 21:17:05.654400 NaN NaN NaN \n", - "2015-12-25 09:29:20.659200 NaN NaN NaN \n", - "2015-12-25 20:02:29.961600 NaN NaN NaN \n", - "2015-12-26 10:48:37.497600 NaN NaN NaN \n", - "2015-12-26 21:21:58.118400 NaN NaN NaN \n", - "2015-12-27 09:34:13.123200 NaN NaN NaN \n", - "2015-12-27 10:28:01.891200 NaN NaN NaN \n", - "2015-12-27 20:14:52.483200 NaN NaN NaN \n", - "2015-12-27 21:01:09.379200 NaN NaN NaN \n", - "2015-12-28 09:13:24.384000 NaN NaN NaN \n", - "2015-12-28 19:54:14.976000 NaN NaN NaN \n", - "2015-12-29 10:32:52.540800 NaN NaN NaN \n", - "2015-12-29 21:13:35.616000 NaN NaN NaN \n", - "2015-12-30 09:25:50.620800 NaN NaN NaN \n", - "2015-12-30 19:59:05.625600 NaN NaN NaN \n", - "2015-12-31 10:45:09.360000 NaN NaN NaN \n", - "2015-12-31 21:18:31.881600 NaN NaN NaN \n", - "\n", - "[5194 rows x 13 columns]\n" - ] - } - ], + "outputs": [], "source": [ "gpi = 2501225\n", - "h109_ts = h109_reader.read(gpi)\n", - "print(h109_ts.data)" + "h109_ts = h109_dr.read(gpi)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Time series plots of grid points" + "### Time series plots" ] }, { @@ -268,96 +76,126 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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F/QUm/f7sA/O1yxbSFSxhvOXzV8GGn/l3DAc5mzCocjcYGYISGHe9uh6NU6bqBd6oUrC1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MqJZwf/Nc1eSoS/8d+jvzQKptX8mEsJWH8ISxTS9EimceHrlO2BoWY3et3k/8uweMJAAHKmtjJZ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\nOefPrZ6/HNXjNOfPWpI+VXH9hSpTx04GewhyT7FxsTz86ehJr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"text/plain": [ - "" + "" ] }, + "execution_count": 4, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "import matplotlib.pyplot as plt\n", - "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "ax.plot(h109_ts.data.index, h109_ts.data['sm'], label='H109 SSM')\n", + "ax.plot(h109_ts['sm'], label='Metop ASCAT SSM Data Record (H109)')\n", "ax.set_ylabel('Degree of Saturation (%)')\n", - "ax.legend()\n", - "plt.show()" + "ax.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The SSM CDR H109 can be extended using H110, representing a consistent continuation of the data set" + "The SSM data record H109 can be extended using H110, representing a consistent continuation of the data set" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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TEPbg/bwKXaOgSyT/5dMdrp/95tKdzoUKDKI54sFjLWhtd78HFPaok2P6OnNU5MnXnGop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\n", "text/plain": [ - "" + "" ] }, + "execution_count": 5, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "h110_ts = h110_reader.read(gpi)\n", + "h110_ts = h110_dr.read(gpi)\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "ax.plot(h109_ts.data.index, h109_ts.data['sm'], label='H109')\n", - "ax.plot(h110_ts.data.index, h110_ts.data['sm'], label='H110')\n", + "ax.plot(h109_ts['sm'], label='Metop ASCAT SSM Data Record (H109)')\n", + "ax.plot(h110_ts['sm'], label='Metop ASCAT SSM Data Record Extension (H110)')\n", "ax.set_ylabel('Degree of Saturation (%)')\n", - "ax.legend()\n", - "plt.show()" + "ax.legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "A soil moisture time series can also be plotted using the plot function provided by the `pandas.DataFrame` object stored in the `.data` attribute. The following example displays several variables stored in the time series." + "A soil moisture time series can also be plotted using the plot function provided by the `pandas.DataFrame`. The following example displays several variables stored in the time series." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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DaQcoD0sZC5YRiEguInSkTK2IuS3haOJ4m2gy7qu8Ns/fegTbDsnnekrVaeJo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VOktcDmOsW/vQ11YJDkcy6rSK5Emv/O5pQpIaP6vNYRX6Yhl8+6ECabKtSyOcQsqirMebf6yCQ1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AzYxnB+ZcSLF3I0XHSW22qR1twKF1aGoyrQLqwQ2IxSgQKwI6W4F4EXj2C3Y8aztbUHyMGseS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\nHmJGXTktU3Jwy4shxBI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grBE3TlQ1pO6eL6kb+F4HHPX+/Wlgnoj8AngE+LdclLGQWJ7+\nGmOem3JRxkJiefrHsvSX5ekvy9M/lqW/LM+JzxY2GWdej4gCU4GnvYd7gL8EFgC7bKRo9CxPf1me\n/rI8/WNZ+svy9Jfl6R/L0l+W58RlI3HjLwmUAO3AIq8X5C4gqaov2440ZpanvyxPf1me/rEs/WV5\n+svy9I9l6S/Lc4KyhU1yQEQuBdZ6//uxqv7fHBepoFme/rI8/WV5+sey9Jfl6S/L0z+Wpb8sz4nJ\nGnE5ICIzgU8Cf6uq0VyXp9BZnv6yPP1lefrHsvSX5ekvy9M/lqW/LM+JyRpxxhhjjDHGGFNA7Jo4\nY4wxxhhjjCkg1ogzxhhjjDHGmAJijThjjDHGGGOMKSDWiDPGGGOMMcaYAmKNOGOMMcYYY4wpINaI\nM8YYY4wxxpgCYo04Y4wxxhhjjCkg1ogzxhhjjDHGmALyH88WYdHDk3THAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, + "execution_count": 6, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "h111_ts = h111_reader.read(gpi)\n", - "\n", "fields = ['sm', 'sm_noise', 'ssf', 'snow_prob', 'frozen_prob']\n", + "h111_ts = h111_dr.read(gpi)\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "h111_ts.data[fields].plot(ax=ax)\n", - "ax.legend()\n", - "plt.show()" + "h111_ts[fields].plot(ax=ax)\n", + "ax.legend()" ] }, { @@ -371,32 +209,43 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In order to mask invalid/suspicious soil moisture measurements, the confidence flag can be used. It masks soil moisture measurements with a frozen or snow cover probability > 50% and using th eSurface State Flag (SSF) information." + "In order to mask invalid/suspicious soil moisture measurements, the confidence flag can be used. It masks soil moisture measurements with a frozen or snow cover probability > 50% and using the Surface State Flag (SSF)." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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aWIfTwYH3iP6qCfopyzRhJB1++Gu5hqQxMXFm5wvN7LHDssvrOXpaJIRYQpzG\nAK1Rzd+9E/988F7ZtYTEJHz60zK/64xVmCHwvt5yFE/+tAuX9Wtnqs5Ur+9bdb0HfdunYc+JCnRr\n3QQOji2wMDIPjEWMf+l3bH9yguZ98/NIHX7diFj28IJf+WSjCVO91h8E09/LtvQ8rzjDg4lNBWcw\nO0D3glDhse934PvcIvRq2xQju7eS3Qs1eadHt7NAW5oB0atEmPbeRgC+3Hc0/vTxFs178tRTwWlL\nVHA+eoyClibusz+OxM3viANZXecBzKWhiAnU1HtQeKYavdr5OiXlGqOiUyo1cTTapiXh0LPiJGqS\n5FIlFVUSiXmFZWjXTC3JX7zzBNqlJyPDj4hOgaDO7cGhkir0bZ+uUSI0q5uTNHHi33opKAm5z3rI\nuN548+cUN1nBkNkQBEHz0DRrMkgQb4ywHsxGQ6PLsYNBBK1JYUdoms6utde5/bFgiXE0xsYAreO4\ntLIO1fUenNMyFVuPiL4dVfXmhAE0E3dx37Y4WFyFJkkuVNW7ZXsj2S9YPnHhxv5TleigiKwXCMoZ\nLgw0tMZd6dMuhV+nr5l4f1W9B81SIj+u/oLl52YFodwKq02ug3DgbHU9ymvc6NIqFQBQWiX6ktZS\n6yxcaY5cJjXqD43vjVeW7ZP+LfnERSsX5wdKK+tCIjyNihWd6NIW5RNNnHIytGriYzjiwceIxv2f\n5eDSV1bJwjcThk1y/GT5xFG/aaY3mTG+NAGdV1iGq+atwevL81XlPlhbgLEvrvSjF4Hhn9/twMRX\nV6O4Qj+HUrClaqQ6ktek1OtMr8zxRr/XTAviTYtE5pfHIADH11sKNe9Z9dOItzHUg2lNHFWOSfhq\nVNOYGGIajbPX1qBlwnTJS79jzAsrAABfeCPLmg1tnyIxcXIiZu1+uYn7z14T6mjQxI1/+Xfc/oE1\nbU8g0Bp3pQ8Xi8A1cw6yrG8aE/xhCPRMYOn6aqPIpWf8y7/jwn+vMFU21PuhWf9D5XKPxzxxMxTp\nGqwKsbUQFUxcksuB20Z1VV13e3iVehUABndpjj7t0/DmLUMAADUN0SMFCQaI7xbpO88L0mQmCb4d\nHEcRwYLsDyDf1FnEMk0QHy8TJVwkck6PNuHVurGwueA0AGtmX4FIbXq3E80sCZM2pEsLcJwv/L0v\nyTq85Xwws0/FG9FMzCSMfLf26YQoNsvE3TKyC4DoTvYtCELAUkOawGVt8BW16oiy9PhbCcseb/PR\nNALodqMiBcnBAAAgAElEQVQZMY2OltWI84+e50omTosRSfWmEaqu94hnmcaeeaikCoIg+B0sKdjY\nxAhVHyoIAvsMM0PgmjmDotW/KFzwZ8ura9AWHNLjXx9FZ1OJRhRX3ntGidru0Lx73s2DZf/WE8Y8\nPKGP9Fu53gkdFj2jGjg2Hjot+zeLth3mTW1lBVHBxAFAZufmqmsVtW6JSKEnQ9eWopq4tdeRf8qb\n61XPxgs+23gE3R9dhFNejRTZiFhRvehNml4TLIKQvkYYPhL9ryUjBO+Ww+E7zGiYJYxrGzymEp1r\nSSMHdBTD4nbwJqptnpqIzE7NsGZ/idgObzmy+Vn1iYu36GBk0zVKSq2nPDMriSLz0R3FmrhXl+Wj\n2yOLApLIllT4Dl/l2Ow4VobMJ39VPUMPP4vw1RphTyNKnG7DHJQ+1lq4at4a6bcyYNO+k2yHfqeD\nQ5LLYagNennpPlP7eDzi1vez8dTPu1TX1Zo4NYHb2FII+Aedma1xhBPNs8XaogqEvrvjg03o9sgi\nzPzG52sebLLEpbAG0RPG0HuHao57//ny0n2IB+w5oU4vxYoQ74/wKmpW/hRGLrPy2gaJsaA7R36n\n+BtRIcpBM2Pve/NfnVKYFTo4TvKHYS1EelGwpO70NUnjJ2mb1BNp/YESs80PCqyaSVaZ1NidrlJL\nqT7740j8+/pB+PiuEbKcRqN7tsbWI2dQVef2BTZhRl/z/f52xvnM9wZLdR4tkMwpDfqlx7yaHZIk\nRZCZaMTH3shkZuchC3RuQeW4amk0aU2ccv9XagfpFA5m89DFG+heny4twS1XjcfUiRciZ+M642cb\nyZAZ9ZPOd6lMC6KH1ESnqIkzQ/42lsFW4IO1BapryqEgdDJ9PS05Ad/cN4pZ55UDOwSpdbGNYE+p\nWPXXWrC5MGSaOFJvd681l54mjnaRiuF4O6bAUoKwBOD+fJaoGTqO4zChvzzSVVlNg0QE0pOBMBnE\nWTqeQZgO5cfl6MAm3musPHEAO0gCTSQSMy7C2Jl1Rg0lrG6QZpk+FgFxfo/WcDo4jOnVRnZ9dI/W\naPAIyC44rQpPrGVOOaQLWx0eq0zcK0v3YebX6jxayryFWtBl4kyOSZLXpzOazSmDAXrOL8yTp1cg\nKVeUoMdQKXwRBDmj3OARJKI7JswpQ9zEjWt+R6++/bBg8SoMGckWvjRG/JCrzit6z/82M8taiXaY\nmuiS/NeNdusYmJ0y1Lt5THx1FVbnFwe97gaencZBubcO7dqS/bxXOLT3hCgI2nL4DC55aWVUBeNg\n4Z1VB6XcqsFAsE10Y2ELNQJND5VVN+DCF1ZgV1E5bpi/Ht9vVe8DZtGvgxiQTm/MWTQ9QaxaLhE3\nIABYuuuk9HsdI70Vi3byh7mOGiYOAE4oCJXyGrdEbMgCdSSIzSZ29vEGWttDNmClmRYz2bdGfUxN\nHEUQ+8Lo++qONZhtsRUrsmEZLZDocmBtfgnFxLECmxi/PVaZuNeW5+PLzUdV1wntFggTZzYXGmE8\nYnVjNwt6KOkDAABOlrMd7OVm0Yp7gqASWpDisTofzaCqqgqTJk3CoEGDMGDAAHz55ZeYNWsW+vXr\nhyFZWXjpX49hz848vDr3Caz8dRGmThgDF9+ANow8ezTid8TkePaXPaprvyrmI4GVkyIl0SkyDtRA\nntedzXiwlvrE/u0tvC0wWBUiniyvxZ4TFZj1TV7Q26Jaq4zolHogycS/yRGJ8mcX7cbB4iqZRjUa\n8cyi3apcof6iaZILg89Ru+xYxRf3nCf91nJfiQ2oG7x6fzGOnK7GvBX52HjoNB78Mtf/2r2HkZ4m\njmbwlEL4WD2e/rVwt/T7IWr8WPOYRf/4EzU0qrig9GR5c77JKZQ4epqJa+Jl3lIoTVz2odMoPFON\nyUM6h6GlwcFXm4+ie5umGKrjzEj6rUw8Swc2ERR/ATlBx5ostCqXLBjCzFlN0BhsnKmqR0FptW4Z\nf+n5egsmeckJTgzPaIE1+0sw7byuAHxbn9XAJoEkxY5GkMAmtIDg8+wjqnL0ZryrqBzXvbUO6x8Z\nh2YpCaYZiQSvOWU8Mx6Afv80mTiZOaVamqmcduQd4TBNfT77eew5rWYIrICYpzbZIe75fVv2xcwR\nM3WfWbx4MTp27IiFCxcCAA4fPozHH38ce/bsQYOHR/beQqQ3a4YZf3sUO7dvxaNP/xs92qchyeVE\nvZuXAnioEGdr2Cz0GBorGl1iTgn49syhXVtgw8HTOk/5QIS34YDVT00CvJhZV81TE1Qpf/SgNH22\nGn49yeVAnZuXyhPiOd6FYjTev314UCJZn0flWZNbPkUvF6fXMroPTpPWNVaglyeOPq/UrgBBa0JY\nYYV0ZvXRn+BDUaWJ++OY7rJ/f7f1GJ5ZJHK2NEdPmDfanHLq/PX464JtYWhl8PDw19sx5U21Lwb9\nIckiUGvifAQyKZ1EpRKgNxWW2Rp9+JLJRBZvpBOnz/7BfNJMiakK0R46umdr7DlRgZJKUUtM/BFk\ngU1MvNzjEdDRGzRlZDe29DmW4GD4xD3yrVoKTRMaV7y+GtX1Hjz1k+i8b5aISPAOerwxwkrQ46H0\n99Vi4ngdTRzPax+G8cwQZ2ZmYunSpZg5cyZWr16NTp06ITk5GXfddRe++/Y7pKSkqJ4hQ9cuPVmz\nXs0Ri5Oh1FqPSgEiDSvCgNREpyqwiRbxy2JQQpGkWQtWPylxQTCzrqz2QjnGVi1lkrx7CRk/QkqZ\nNWePRpRW6qceUuJgMTvgDsHzUwZabgM9RWNNE8eaQj7m3nw9Vw7sgD9d1F11nVSvpxCgGbyJA0Qt\n+43DzwEQu/6GdG+N+sDaK/zpdlRp4sb0aq15j964CPPGylFT7+aRGEeRmhwamjgxT5z8i8vMgajZ\nxJKW0vm9iNPl8TKRUOzUXE3khBO11EFvNKfJ/VBJwi7o2RovYK8UpZJj6OKUb/6/S3ri9d/2y655\nBAHNUxNRVFaLTi0iO77BgFmfONb9I6ervPfMvYsQSNG4r+cVlqFVU3U0V39A9y+zUzPZPS2fOCNN\nXCRTDBhpzIzA8wJ2FJUBAAYyohdroXfv3sjJycGiRYswe/ZsjBs3DtnZ2Vi+fDm+WPAV9rz2Ot79\n8kfms8kJTvRo0xQHDIg+D8+jpp5H02RXvPBwmkS9XrAeKwFyUhNdOFVRK09SrbFts2oNJ2Fn9V1k\n7YVCw12rOvvFv6y13aVlKo6clluxkMBQSsI6loViOd5k82ZhlEt4eIZ1wSotbI9GDxSeN07VQc8A\ns2c6jReuG4jURBcOnKrCst0nVbSQHhNHj1mLVPEMJQnKo3Fm1rt5rN1fIgt+p4Q8tZd+fUwmzo92\nRRW3Qw+A8uO7nJzkG6MMQEHjTDU7R0YsgWZI9DVxxIxSvEanBqBHb8bYHqp30ETcNznyhMxtdaTR\n4YCZDVFVJkSbaP+OzdAsJQGr80tk75Vr4uTPsDZODx9fWXpcDE0cC6zbRFigJBq1NJREWBON2qOr\n5q3B+c/9FpS6aKKMDmbA84Jm0ll6TJTTTvSJYyOa0zUQ+Pu1i4qKkJqaimnTpuHhhx/GqlWrUFZW\nhiuuuALP//tF7Nulr+nXojvo9hwurcbBksq4StWgRdPX6KTNMEoxQiMl0YnqOhLYRO1bHE3wd+6Z\nEY5Y7fOqffJgKT5zSnXZ287PUF0jtBR5rT/EerThjxqBdrSg57LiL+TDF33zWG8uSq2lJhHRiVgR\n8BkJz/WYOJZGmTQnGrXELy3dizs+3CTlDmaB7pHevglYc+3RQ1Rp4mg0S0mQhYN3cBzyn7lCVW5E\nRks4HRzWewc2msOQm4XMnFLXJ85b3sD05B8T++LjDYdleSn0iI9YiPoZLiGi08Hh/B6tJMd+KbAJ\nVUa5FbGceT08Fe49+vYnyyCM6omyWvRpn8bUigPszZgwcUpJ8OierZHVpbkqzHaCBVOlSCOQFtJM\n3ClK83amul4zMie9jJXEocBraxRiIjqln8jLy8PDDz8Mh8OBhIQEvPzyy7jyyitRW1sLD8/j748/\nw3hKO1KaBGrIyAEdw8oMFbS0tnrrrvBMjen6UxO8KQZo322NsqxzPJxDLUvk7OZR6/YgPTnB8Dkj\nzWRlnTtgcp+sc9bnuuuCbrjrgm4AgIxZC5nPO2PMJ67ezRsSxEbo1zE9SK3xIZImfzXeVB16wf30\n1q2UMF52zevnrkFD/2VcL7y2PF92TUtMSOrXZeIokkG55SprFQQBp6vq0aqpfvCpUOJwiajhZqWp\nIrBi6nz8LGPv9GNKRZUmjoYyyIkyiSABHWofiA1Czyw4cNIiUGrilP0GFJHqFHUpGQs9Ii6a8u8Z\nLYlwyL9G92wtjS3rfUri2cmYq3SQiXiYoU28fpN3/28z/v7VNs0DjUUoKPMSEnRukSIFl6Drc3Ac\nOC667eSDMQ/pJXnsbI3kh3lCwx8OsB7YRHoujvZJJSZMmIDt27cjNzcXmzZtwpgxY5CdnY3t27dj\nw+atuPr6mwAA10y9GY8+/W/V81qEh/aIxcdYapnX6c2VPSfY+QtZSCXRKcG2aKAxd5E6IE6yK3zn\nEk2c3vr+Rgx88lf98t6xU6YDUGLAE0sCbtvAzqKpNTE900Lf9mkAgGHe1AOtvQQwse6JFSXyHR9m\nY9Ac/fE3gl6ADX9BL4twK5QHzlmCfo/rzyWiJWe1jaVBYwUro8FiUMi1wV1Ec/eOClccs5o4KYG9\nwKYN3vz9AIY+vQzHWIxPmGDqG1uYByv2FstSEgBxENiERrMUudRLazIoQ+3HUy4pAYKmJo5jpBjQ\ns3FXSmz0JIbJEWfifN/a9NcM4We/oKfPV5NpTqkoz9LEuT3a/kmxiCFdfD5KP+QWadp/6y1HpZau\nU/MUKrG3XBvt4LiY9uEwAyWTSpg4opVLZGg7Dc0pNYYsnjVxejDTbZfToWEmJKh+Rqk1oF/QXMNB\nmiupSS6VRsWKL3NqUmTOJbPRM0OBC3q2xs45E2TXbj8/A0sevNDQj+vr+87HmpkXY+bEPgBEfznA\nJ3SMlf107X5t8zWzCHaOOAARld2YoXPN+KvKg7Poa+KUe92fLuou0Yr3XdQDvz50IQYofLn1mGdZ\nmiaiGRTkfwmW7z4FACiKAiZOb9nQve1qIGQBgJwj8iTg/izJqGXilI78mkycIzo1cVe9sQazvlEn\nSTYDTmbaI/6tY/jEkUAmZCF9ttEX4l25dpQmknpEXFIYQzkHinB87a6tUqVgL2Sjo7+RKZ84yj/p\nuwCSaEYLlFK5sS+uYJazkieuS6tUiVGpc/vmu4Pj4OQ404FQIglBAB78YiuuU0SdfeTb7bjitdW6\nz24qkG/oE19dDUEQpMiUrIA4vIEmTjOwSSwMpgIny2uxq0ie2yr/VAUKT+unI6Ghpc1VrljWHkg/\nSuZu0VltLWmsQWtsgkXspyY40eAR0OAR/IoqrDSzDiWsdtlK8VIdcywlJvRvJ1k9EHAchz5eLZse\nmia50LlFqhTojdBGy3aLrgHR5ncUzZYWLMgCm0SwHVrQ9YmTGBIB5z+7HC8u2SuZN2o9p6TB+3f0\nMWwOB4fe7XxzUgqi49QeGadME+dtj/fvh+sK5O3VrCV8kLSFOqtdT7hPQNPipZWBx/AIiFrnOO4h\njuN2chy3g+O4zzmOS+Y4riXHcUs5jsv3/rXkUfrZ3SOx5MELVSZEGi43snxpgDVH61Ai71gZvtik\nTpJsBiyfOGWEKgfH4V/XDgAAZHmTWNKTQ3k4Kg8CPZ+4UJgeBBtORWANq2ron/98gemyHMdJ2jg2\n8SEfL0OfuDiAsitHT7MlZFqEQmWdW2XO06FZikQ811Pz3eGIfnNKAgECvs8twubDcobs8+yj2HVc\nP7kui+HiBZ8pdXqK2idHL9k3z7OJywSn6E8bbUScEU6W16r295p6D05bCGalOYX83PLOVNfHiTGl\ntibOSgRKpQUNDZIaiI52Gf0njTUEfYsKwlms5QMXbcs/BrZ3GeTmlNE3k80qNIrKajFvxX6J7tPS\n8inpmiszOxjWrZ8nzvdbz8+TRrTPEVq4b0b4pQzE6E/3/GbiOI7rBOD/AAwTBGEAACeAGwHMArBc\nEIReAJZ7/20a5/dszZQyaTkMchwnM9mycuDEArQiSTk4Dk2TXDi3QzrzwyvNVJS531bsLdaUxlvN\nQxNs0K/XWgck7Dwh6ljliivq8PBX21T+hABUan8jjPamvzATnZKlNRaZOEuvjGqYZZq1pHony2tl\nRMXonmISVaKJo4UWTk70DWUdSl9t9k9QEjIE8I1ZTKqb56UxTGKkTuFl5pQsnzh1nbETYtzXPqsM\nZ3lNA0oq1GkZAukxedaf/D+xAJYQYXvhWUtm4HpRAIlJfzW1H/t71Lyz6iBW7j3l38MmYFkTF6JP\nHgwrQBJPQLkXR3L9e3gB//wuD0dKfVp0I3/CaIOZAD3hBr1PkuBATD9+7196Bvy0vQgAsFtD2GjG\n4shXVrynn2KApYlTz8miszUyzWGo0ODhMeub7YZ+d3pNoMMheDR4EXpEFmwuxPGyGqzYewpvrzrg\nV/8CtZtzAUjhOM4FIBVAEYBrAHzkvf8RgGv9qfi1G7Nk/9ZiLJwKCX08+HqQSH/1bl4W9S+NYsQk\nZgK+/rt1pPIvXKdOZrlFoS0giIXEldLBpMO0P71wF77aUohfdhwP+H2X9G2LKUM6Y0gXkUhhmbz6\n2qYeQF4n3Hsswuxeo0XQniyvld0jQgZi+lOnIPScVDRWGg9/7Z/JcqgQEJPAeJjnfcQ1y1dVL7CJ\nhxeYY5ZgYu1EG8pqGyyVLyitQlGZ+jA2e0gyt0BB9kcTetHLohmsobn34y2WzlS98W3i9WmrrnP7\novz6ycU9s2g3bv9gk1/PmkG07NbBEKgqrVYIImnZsPXIGXy68Qge/HKrdG1dEHzfQomXpw6S/Tsa\nSc2DJVXSb/3olGrN1ycbjmiUFuFyOPDVvaNMtYOcWbrJvk0Smo9+l0eZMoYOWw6fwRebjuJvC3LZ\nBUw016omDgBmf7cDd3ywCXMX7QmvJk4QhGMAXgRwBMBxAGWCIPwKoJ0gCIRqPgGgnT/1X9pP/phe\nYBNeECSmJValoDQIQVtV75H1h7YvlnyzON9C1Ot7x+YpuHVUV9k1rdIhcQL2E1pnmE8TR8wp1XCY\nVNGbQdMkF16aOsiXQ09m+yxvJGv86MAmrSMYJjfc0Er5UVxRJ5uv7bzjmuSNQFfboE5wGwuBYYya\nyNIKE7CWr0cQJF9AliZOL7DJ6vwS7Dupjh6o1GLHAoK1IwVDE6difhX/jJ7dM3CkpyTgRJl5vz+9\n8SVRj+nEy1FohQYgPGZbLVKNUxYERxMnVqLMbxVttJK/jHNmp2YYnhH8PHBKTB7SWfbvaE/2bUb4\nYmXEUxOdppOik1ebN6cU/7K0gDuOlUubaijXJXFH2nlM3+1Brwl0d7XczoNt6RaIOWULiFq3bgA6\nAmjCcdw0uowginqYfeY47h6O4zZzHLe5uLhYdV8Z5l6r304HB7dHMIysE0tIpXwHaMKV1vCQnw6O\ngwBRqma0KSuHUGtBRNyckvqtaU7p0P/eHt7nPB/qs0o5XJqaOCLJjwFmJFggc0m5OZ8sr5VJqm4a\n0QUApYmjApsIAjTNKaMNRoTIC4v3at4ja52Ohipq08TriSxzSmoMz+0gz4X06Hd5mPFpjuoZkgIj\n2sczJK0zWSlrCyTftvCMQSCVKCTo/EWPtk2Zc8gfSOaU9R6fb3GUDhaZJmaPQr9Cg5uoPBi+VkSo\nuDq/RHY9kuuflafMXwgQNMdpXN+2GNunTRDewnyxhDQTOQTDDT0hnT/miazzRwvErFMvsIksxYD3\n95KdJ1URKEsq68KySxBLlwrKZ5eGZPJpcszos3kEzfzqdCbc0SnHAzgkCEKxIAgNAL4FcD6AkxzH\ndQAA71+m4bogCG8LgjBMEIRhbdqoF5k69xa750kJTtS5eYmpiQdzSqKJO15WK+sPPelpTZwYhU5e\nB0trodQQaR08WkFkogkubyMbiCZO0d8GD0+ZDAR/TtAjacYnzk0R44Tp3mshx1KkUVpZh9oGDwq8\n5hpGYzqiW0sM6dJcIhRo7UVKghMny+tQViOayA3q3ExiQMhBQQc2Iak24kETV1BapXmPjOmfL+kp\nXTt6uloaO7YmTvz70wMXoEWTRM26B53jSwlBkqfHUjqWYMmVtHqsrp7JxQEwHrdAmtq0adMAng4+\nKmrZBI0/kAKb1FOBTUwO1sT+7dGZEZ01VCBrMZRbjhmLl1AKVANNoB0YGCvOz74KAnvNzbq8L967\nfTg+vGOEX/XSeOfWYaprNM2Ve5TtmhJJkHODNa6hFp6Qc18/xQD7upb1DhBaM2ej5WhmftLrlRaS\nDDrHF4NBr5awmlNCNKM8j+O4VE7s3TgAuwH8COA2b5nbAPwQwDskaG1myS4Hahs8vtwnccDEEdOy\nH3OLZP2hNTy+ABtivjil1IW1DlRjqDFU0RhpSYkEhSZO2RU3L0iLUnkQjz+3bcDvlzvlcrKobKzE\n9HRgE0EQ8P7aAkx4dZUq2WO0YujTy/DQl7kY++JK1DZ4DDebejePRJdDYsYSXL7xapeehFMVdUj3\nSi+vyeok3fOlGKCYOEEc75hg4gzul9do+3YJEA8SFyVFueY/ayWNpV6eOMaUk9dNa/SdMbJXypoX\nnD0pECKAPKkUYFQqJLd626cgCOBjyIx11T61lYwe9JYosTCpoc0pTdbrdKjzokYV/JGgm+h8KD0b\nHv9hZ+gqNwn6m/rb1Z1F5Uz6cKDF4GV6YLWN7CVnq+uZyekjDb39XYs20gNdtmdbfWETObP88Ylj\nfUvpUkj3gMAXG9102pqIBrE6Yj3jzybnMi7ChiAIGzmO+xpADgA3gK0A3gbQFMACjuPuAnAYwFR/\n37H6HxdjzAsrAGgzcUkJDpkmTo+LjxX07ZCOX3d5c7nQgQtkTJxXEwdxXivpAhbBq1w0WtPFyXHY\nOWcC/v7VNvyy44TsfeGAmVcRQlcrOEODm5fqocfi+/tHo3/HdOYzltqo+MeGR8bpOvPyVIoBAUBe\n4VkAwNEz1Rhm0s480ljjNcep9/CGe01VnRvNUlJw1su00AF62qYn42R5LTq3SEG31k1wx+gM6R4Z\nOtrUUgC8eeKimYoTYaShLNNh4niBmIX76vDwAnivQMLFME0x40BO6iGQApuEmJk4MXcu6nb7T9wI\nAJxeBqkkwQlngwdCz17A3Dm6z1VVVeGB26bi5PEiJDiAxx57DDNnzsRtt92G777/ETV1dXjxrQ/R\nrWdvlJ05gyf+/gCKjx9Fk9RUvP322xg4cCAmXTQS7329CGnp6bgkqyf++tgzuOuO23Drrbfioism\nY/gFY6X3EabkhwWf4bfFP6OhpgonTxRh2rRpeOKJJ1BQUIAJEyZg5MiR2LJlCxYtWoR169Zh7ty5\nEAQBkyZNwvPPPy/V99BDD+HXX39F+/bt8cUXX4BlqRJpjOnVWmWeB+jTWE285pRVdW5pAzV7rDgc\nXFjN0MPxJjPakEi7NoQKLHPKQGgMev+bP30ohnVtgVZB9D1nNY1sqUohTrTAlDmlHzM978nLZOc5\nC5ImTudcsjK3wxHYxKg5ZlpLl1H69RPMurwv5q86yLwXbk0cBEF4QhCEvoIgDBAEYbogCHWCIJQK\ngjBOEIRegiCMFwTBb1UDbT6hNReSXU7UNnikCXHPx1tiLv+RFmrdHhkDwloQJH+WcsGyxkCliNPx\niWuS5JKlJYicH5f8vRmzFiJj1kK8t+YQAF9YYmXzGnieufC7tW5iuAGZgTKpY0qiU8rFp2VO6ZPk\nh4dICBSqOUQ2fhO0f0brJkh0OaQok/SItE1LwilvdMp26Umyw5sIKpTzTTSnVLxj1kJT/dBC9qHT\nyJi1EDuOlQVUDw2jZUKbpx07W4OMWQvxsze0My+wDzY3L8DlcGhqeAHj3I702DklLXbkZmF1vUcW\n4CKYWLx4Mdq064Cvfl2DHTt2YOLEiQCA1q1bY+nq9Zg6/U58NH8eAOC/Lz+LvgMGYuvWXMydOxe3\n3norAGDoiPOQu3kD9u/dje7du2Nr9noIANavX49hI86TvY82ed+xLQcfffYFtm/fjq+++gqbN28G\nAOTn52PGjBnYuXMnEhISMHPmTPz222/Izc3Fpk2b8P333wMQGdBhw4Zh586duOiiizBnjj7DGiyc\ntZBrDwA6Nbdu2kjMKenvbpaQc3LhjQYYymTfBGa6Hqc8nG7Ye7/qox5unpIQVAYOgCpvMQAs9yZN\nj1bLJb393WxeNhqkaFpyAjNSMg1yLrHiA/jawL7OMjP2+fAZNtNvmK1brxxrLjz0ZS7eWX1ItwzB\n9kLrtIjfmrhwgO6sFkefnCAycaJjqXg4VDd4VHnRYhF1DR6Zho01Bg6vOaVSS8EKb6o8MLWkMKQY\nLfmPVr5Ya6NyewTZwnc6OPRo00Q3Ga0VyH3i5OOq3Lh8fotiW+kgJ9Hq2A+o8/ZI0T69/2lh+nld\ncf/FPfGvhbtQ79WM0/OnXXoyfttzCh2aJasYE0kTR71a8EafDbZwZpn3EF67v8Ry3kAtGB0EtLBl\nn9cn8usthbhyYEdxfnDA0K5yzSwvCHA4NDS8AjGnZM+jZikJKu2fpMUO8aJu/+ijmve2ezXRXTs3\n1yzj9vBSgvS2rZvgUIm2PyGNzMxMbHjwIbwy9wncedN1GDNmDABg8uTJEAQB/QYOxvLFPwMAtm7a\ngJfn/w8AcMkll6C0tBTl5eUYdt752LJxHTp2Ogf33nsvXv/PWyg6dgwtWrRAxzYtcJyRviAt2YXz\nxoxFy5atkJKSiMmTJ2PNmjW49tpr0bVrV5x3nsj8bdq0CWPHjpU0bLfccgtWrVqFa6+9Fg6HAzfc\ncAMAYNq0aZg8ebKpPgcKq2kRtOabnrCPmFO6qaBTpt/HceEN+x/kV43IaIlsynSe48wxLfGqiZNA\n54rlKK0AACAASURBVFoLUldHdm8VnIoo7GP4r/+QW4RbR2UE/V2BgB5Dve3dH+tEK4J8o3MJ0J7b\nrEfCswz0+2dGe8lq+3dbjwXSKEPEQAgLEZrmlC4HeEFO4FQG0RmbhdX5xbjx7fVBM+9avvskbn0/\n23fBuwBqGjyyhcOStovGV4KKIGMRvMrntdYkGUti/gKE139Gztjor16fT5y8fbLAJhDQJNGJ83u0\nVj3vdxtlQWbk95TEtssbWVEab0oTF81ntPKb+8xT9XPKTBzQHu2bJSOJ8omj53G79CRU13tQVuNW\njRXLt1UAUHimBt9uPaYbot9f+DuzWYcaa4N/6qdd0m+WRmzl3mK8vHQf5v9+UBbQhcDDC3ByHFOq\naaSJY5lvJih84p5fvAevLtvHfD5aYGaZ8IKA/acq0bFrd3yx6Hf06tsPs2fPxlNPPQUASEpKggDA\n5XTC41acEYoXDB81Gluz1yMnez0uvvhitGjVCj//+L2XIWSvC6eDE32UZfe8e2mTJqb7Kq/b/AZR\nXtuAFxb7Z76q9Z7mGmHwnRyHtGRrglJlxGm99yrhYGjiQwkrDOOivOO4+6PNumUGd5ULK5xeaxcj\nxAsTV1PvwTXz1iDPq2nwnc0+BEOg2UonuFMgaGBMvmjy0T5VUYuJr67C8bM+jaHuHPYO9ZKdJ0LS\nHjOaOCs+cWu9OQQjmb/R3Ow0VyqYaaZih4nT+OCssKeVddYSw1rFnz/fig0HT+sGKbCCuz7ajFX7\nilVEc20DzyT6aIgaCh/TRhYN68BTR6dkgyyiBy/tLV2L3Ial/15J46g0p/T4ApvwgsiwBvNA1GMz\n6TmZmuiEw+vPxVNNjYU0A8oofL68e/ptJ+ZSSS6HFKCEno9t08TAPSWVdWqtpfev7B3Uz2CaPgY6\nG1hrjDU076/1mVJopQx5fXm+5ns8vBidk7X+zfgeKEHKEv/hN1cewKvLtN8fHTDuX72bR3W9Gzm7\nDiA5JQVXTr4BDz/8MHJyfCHyld9nyIhRWPjdV+AArFy5Eq1bt0Z6ejo6deqMM6dP48ihg+jevTuG\njBiF+W+8igsvvFC1I9GMyIZVK3G6tBQ1NTX4/vvvMXr0aFU7R4wYgd9//x0lJSXweDz4/PPPcdFF\nFwEAeJ7H119/DQD47LPPcMEFF5gbHgDlNW78d+UB0+XNQMvSwengmIJCva3B4eCQnCDujbRPtxk4\nuTD7xFl41YxPc5BnsC8lKCwOOA54//bhsmuv3pClei6UgU2yztHWggcb2wrPYlthGf61UBRo+fZ5\nX5lAjufkBCdmTzrXdDJqq6BTGbVJEwlwnzVN5PHV5kLsOVGB/60vkK7pmv15W731yFnT77Cy+qSA\nWzofVWtu6weGstAIiwhG3Wbn8Gs3qte6v4gdJk5jcIhpEH0/mGGR/YG/EQeVQVm2HjkjI/pYk4zz\nmpmQABJkErE0Z8ox1GLMiMsYbZIarUEltOLYHCiuxKcbRW3Rz9uKUFHnDtmBqJQmE7MhAF6TQRKU\nQxxDQRAoTVw0HAFsKL85zRTrodobQjzR6dPE0XOtbbpPCqVkPsimT7+Dlr65QpD/wt/Nm7V+lFeU\nhK4sObfJCUmYOFbfzZitAHKmOCGCeeJ4QcBJhn8JjdoGD05X1cmumfIf8v7du2cnbrlqHKZOGIM5\nc+Zg9uzZ7IIA7ntoFnbn5WJwVhZmzZqFjz76SLqXOXgounYX0z0MG3k+ThwvEpkqjWHjAAzIGoLb\np92IgQMHYsqUKRg2TB2avEOHDnjuuedw8cUXY9CgQRg6dCiuueYaAKLGLjs7GwMGDMBvv/2Gxx9/\n3LjjFlFT78Gry/ahwcPD7eHx6rJ9YrARBrSCNpTXNvilGaOtOwBrgU3Cq4ljXAuAylOuzwaPgHNa\npmL6eV2la5f1b6d6LpTnQy+DCIOhBKtbgfSUA3D3mO7o3iY0faKFGf286XCiSRDLChQT9OZZqI+c\nS6xgXARac1tPI2umCYt3HPeLBjfbPX3m2BxIBPpgIGYcx7TMhRKkSeK7H9n8J8B1b63367kGD4/k\nBKc0mXhB7rfCijbEecv9tK3IW4fgfdbYnFJ138tssBYXy8cuVKBfb/RaDwlsorj+p4+3SL83HhIX\ntFmi2RQ45k8AcibuhesG4vYPNomBTbyNpPi5qJDiaUGdSN2cJu7CXqKvT4fmKSiraUDR2RrZfKQ3\nMOUmT5g4er7R0Tv1zDPCDSYTp7i2Yu8pxX3fb72+NEl0osqr0fQIXk0ca116PxG5N2NsD3y39RiO\nl2kzSmTMI5FTs7Sy3pCJyz9ZCQEC+nXwz3919NjxGDnmEgDAQK/PXUFBAQDg2JlqZA4agkW/LvcK\nG1rg1fc+Rf+OzVQChbmvzZf2wiEjRqKgpBKtWqaq20+J5Nt26Ig33pgnSesBICMjAzt27JA9ctNN\nN+Gmm25Stb2ystKvPlvB67/l482VB9C6aRKSE5x4dVk+th01L5EHgG9zjjHzFrIYERopiU6Acm00\nu5odXHiJZqaptOC/tkjrsTtGZ+DjDYe9ZdSlQrndhVN+qPXpaAFdepD81f3F7Enn4umFu5n3po3q\nyrwORIdLhM9KxneNjG0kmmdOE8e+F6jJ5L2fiJYXBc9NCqgeJcwEgzFr7RXMORM7mjiN3YwERpBp\nsaJHQGIJLNMV2uGcrV3jAAHYXCBPNmkm2TcZp0SnA/eN7SHloWJNxEglpjb6lFbo0GAuHE6Hi0uh\npM1Du7aUElWXer8lvUlFwwGgBaUfAB3+v7tGkJiv7h0lJZ2+rJ9I0C3ecUK28bVN09bESX531LtJ\nPjlAX7IXbrA2c+UlpY9bZZ1bIhD1hAp3jO4m/RZTDHDMvnukusR//2NiX9w3tgcAYEAnXyoNWjDj\nS88R/nQsZghxsj4sm+9INlp6dYtzrE1aErq20vZTU5r7cfCZ8ym7IFBlAO38QNECkhKh3s1Lba3y\nI1IoGYd0r2/c6zcNNgz0QARcZDqaFayxotOGG4G4FGgRd93bNJX2QFaRePCJyysswxlv9FN6PRGQ\nOVFqIrgOfXbQCMYw3T2mu+a9DGqvkHKskXdHgSiW5Yaw5bBIExaeUQdh8odRsvIMIWVZEZUJlEt/\nYOdmGNtHP51KKAU5RlWbOF5k85CYjhsjsPkTO0ycxiolhA1NLEV6szcD1mRURgMkkAIRMJ4ReThB\nWrAEZpJ9KxcleQ9L4r9yr7Wkr+ECYWzNrO1QHYjKTVzpwO9ycNhDMcFiioHon6QehVCBDmwCAejd\nTjRdoZ10aaase5um6NMuDYt3nJARQE2TXNLBrdzkfe9gj4/eoWAZ0mHs37dga+Lo3wKTuCA5IPU0\ncfRaF1MMsAObEGaXXrNE+zRlSGdm3QneeqLVRNofHDldLf3W+57+0gD0d1yx/FdMnTBG+v/yi0bh\nwbun4Zbpt+LRp/9tOdJjtMIon6ZHIYwww4+lKM0pTbbFwXFh9ctmmlMGUJ/e2OhZyARzu4sUrpq3\nBjM+zdG8T3p/Gx3cTQNa6YFCzUg1SfKd6UTAE02BTXyRo314dVk+auo92HuSIYD3o+lWuksspPS8\nH5T0GEfeYSCECxUM6QAzJv1UGTPRQYOBuDGnrPfQTFz0LC4tsJqo5USe5HKiweNWEdWAOGkqat2y\n/gNayb7l/yY8I5m8iS4nAHfEtUPWzCmJ1N74mwfTNEVPm0abU4rv5WSEnQDITCsr69xRmRJDK8UA\n781516FZCg7OHYV/fp+Hz7OPAlAzJhMHtMfrv+XjZLno4/T+7cPAcRzapSfjUEmVqjzLJ45GgoYm\njhX5zgiBHvzsNvouajFJJZXiWOgJFej1y/MCHBYCm2Sd0xwH5l6Bg8Vs07xImlOGitaqqfcwgyVA\nuuZL8WHFv47+N6l37LhL0X/EhdK99OQElNc2RIE8PgAwxuzqQR2xs6hc8xHJH5PjZH/1kOpdp1JJ\ns9EpvRYn4QJ7Dol/6908eEEwzJVFQzfUugOAh31mB8sn7k8XdscH6wrkdVOaY0GAYX9EH0pByvfn\nD5TdsZqrMhKWGDcMOwdJLl+fyackUdAjTS/RbVAqB5R0IYE/S8maZYT412lFCqGI7BtwIyIAmqao\nd/OaNEAwfV1jRs7DabTUxXDSjwUmbvX+EtU1sqEpm0/Uslq53/JPqYk1TdNL+n1UGQ5g+jhEGkbM\nmRVfPSOfQCuQRdVS3FOOo9OhiKwm+J5/7PsdGPDEkqhMUK8ObOLT4PBeLZPDwUnmWYDaPPLyzPYQ\nBNGkkq6D+Aw5NXzitMZDi1CMxJo30sSJc1Pd3pd+3acqq0RPykGf+MQxNXEapplagVAA357J8rEN\nOSI0zU9V1GFnUbmYeoTxTbR2Bsn8iyYwNMwpo4KaswBB9lv9YbS0HoAoNCHz18fEGb+T1miYfYaU\nC68mTv0u8v7xL/+Ovo8ttlSf0gyQFkaN9qa+Ye1twbIeSU9JkJnP0hj93G+m+jN1/nqc+7i1fmuZ\nv5Fu7TlRYYmg1Sq571T43D1IewtKq6MquAlgHFhLKudHu89pkWq6rGQhokNSKj87B3nQt3DD7JDo\njZ2yT/2fsLZe/EH0Ue0aMA5s4tMCRNm6YmLTIXX0HFpq4nRwUt8I0aWlOWAxbHpM3CBvaGFyKJHx\nIqHxlVEyIwmjb8lbMKcMpvRDFmVQaRbAqQlqun284EuWTfJ4RUQrYgCteUCSlZNeVtb5CAOluWOf\ndmno3roJFuaJgXfIWJHgJmpNnPjXaiCdSIyewBgeuh1aPBLRyuoRpdcN7YyLvf4BbpJigHEi6uWJ\n0zLXJIy2VSl4JGGupdr7P1lnDR6LiaY53x/JJ07Ztlg4cCiwtkFlF5wODgkaQr0Xrx+ErY9fKv2b\nTDMz+6vSnNJMoCIiLArrFqnzLtp01yx6t0vDz3/2pYtY/8g46fe8m4dg6UMXMjVhwbIekVIPUXsS\n+VwllebMf62EoydQ5Rq1IEDRwrK/XqS6drC4ilEyOPBHeBDuPYEV2ATQbrvV5v30wAW4oJf5PLvk\n/GZp4tI0rI4iLQMz9olTm6yqyig6UdvAJgKC2dWYYeI0feKoSdK1lSgpuOPDTSitrGOWDyaun79e\nlsjXCljyBqVkPNmrwicmBFYcn1mbCAlE0al5svd9cpPATs1TTLQ89KA3ej1zHsCaX08wNwmayTCq\n1+ngFFJv85utv1h/oBQZsxYG5J+j0sR5lxphQsnco6XrSnMXjuMwcUB7aTOTmDiiibPoE6c5TAEM\nn79Db6SJc/O85tw4b+5yfKgwb6LBcRwGd2kBAGhw89rJvqXDUn1PS5PiUiT7DissrEEr34XeT1l7\nK6mrzu2x7NtA/k3qUNZOwvDHlh5ODmWfHByQpDF/rhvaWcZw+GVO6S2rp+0j4ECiMIdTE6dGvYfH\ngCeW+FWf08FhQKdm0r9pP+KURCd6tUtjPhcsTZzRvhpsHCqpQsashdh9XK4hI2vzPyv2U42zVnfP\nMKdGUI4YnVCcFmbSCPfW+vpv+d73yl+s1Q6rzcvs3My4EP1eHeFia+/Zr2Toicm63hSNZCyBb3IK\nQ1RzYH2KHSZOy5xSponzFdqsCPQRCuw/VSlL5GsFrMUlmVN6P2pSAgn+4GXiGPVo7fEsTca1gzvh\nyav6YfakfgCAMwoC/42bBuO5yZkhy7XiD77IPqJ73+cTZ4xgbqyCVSaOKs8yGQi2Jm7+KjHpb+5R\n/9eBVrJvXvBKdL39furqAVIZFqNx+YAOVB3iX5IrTpXs28AnTgv+ECeB0kc8Yw7Ifdm0nz1RXovv\nth7TrZ9Oyq2V7JsclixiT8t/kOSJU0YfjT4IzJ9m8On783HtxSNxyy23AJALyJijojEX6Ms+c0r9\nxgQ7gNKHH36IBx54IKh1GoHjOMkywwhEOGgusIlc22SKieM4uTlrGMDU5lY3aObNMwJZuz//+QL8\n784Rpp8L1lTy7d3mz61AsCjvOADgi03s8/sXr3l9LEB5tsy6vK/0W1OmGGZN3NnqBub1YGnirEJP\nuEigFpSJOY9DEZjKDEwziDrFzGrO6b4HKkyNvmgKGtA6GOlDgJ4w0R55jTUZafM1DkBKotg3Xwhi\nbVOEQZ2bYVthmXSd1X2ng8Pto7uB5wUkOh0oKhNDz5KiLZok4sYRXSz3JZQwOuTJZmFm0wym35mc\nQNdfuU6Og5tm4hhlWEFrAgGRgAXi9qTlE7dqnxiplEjSmqX6UgCwNm1WqHtiTqmZ7Nvit4rEamc1\nUe0T5z/IcifmlExNnORAzjCnNNTERY/ZNAuCzr9YoEdgwf/ew9uff4fzMntL19xuN1wul0Wzap+W\nSSsnJY1mKQmo0zCh0QNpWzigFfiFhoODaSYu2cuYmdLEJcoDm9CChpQEJzPHKwftPHFHSqvRpZV5\nX51AEMhyJuuT1saZQfA0cWpTsFAuf+IXXq1IXRGoOWVEzOYVL02lTIK16A76bFiTX4L8UxWytDGh\ngmlzyhCPJCvgFoHW9zYzD6LNcl2MQO1ruT+rtaousJQ0MaOJ0/KJowkbWisXjT5GNNjmlPJrkjkl\n8YnjgCeu6oeXrh8klSGbPDG9ItAjgh0ODs1TE1BGSW+iIdeJBKopV2S21y1qhVkP5sZlRfND8sRJ\n7WCYDAQ7yEQwwiCr/Bm83+XphbshCAJT6sRKAcBxHFo3FU1QyDMksImmT5zi3SO7iQm/tb5hJPyS\nmAmBFdEpA1lVZE3qaeKkMO+MF2lq4qQ8cdG9R2otV+a3pi7965GHUHikADOmX4+ObVth+vTpmHbN\nBPzzL39CXW0tZv3lXmRmZmLw4MHIXrcaAPDHu+9GVlYWsrKy0KZNG7z6wlwAwPtvvobhw4fj8otG\n4rUXngEAHD18GNdePBJz/vEX/GHcKPzp5smoralhNQUAMHbsWPzlL39BVlYWBgwYgOxsMZT6k08+\nienTp2P06NGYPn06amtrcccdd0htW7FihVTH0aNHMXbsWPTq1Qtz5syxOJBsMLWMXjg4TsobqoV3\nbx2Gv4zrJW1mZviNJgp/GFpIR+ZrG0UQEI4T/2dt9fd/ph26PhAwTXIDOD96+GndEjQmzvuX9uMN\npWklEQDUMphyJYLpqx4o3rttGGZ482wSKPcb5ZnFGkV6rkx7byPm+Ol2YxXKOapFHnVtGVrBhz+B\nTQAz5pShg+nAJlQrlJp5s3OZprezC9TxMawgZjRxWmPj0tTEhU7MFIy9j1WHMucZ8Tugk4EqpTmc\nV2KqlPAZMbHJCU5pgzVDANPRtfJPVqC8tgFDu7Y0fM4f0J/6x21FuGVkV80QzcrgLHoIZnRKeniN\nVOjKwCYi5BeCrTkmbQrkoFbOC7qbvMBek1ohoAmxRr6jliaObG7Kdt8w/BxsZAQDottz9HQ1zgnx\n4aR8pxIyTRwvBESgkKFxe7zJvhkMspgInH140OU52XWiiQstE7d6wT6UHJVHzm3w8LKcngcYTu5V\n3oNxT4ID9V6t1h6XA/VuHk3apyDzDn1txmPPvoJ1K5fj3QU/4YsP30H270vx3oJFcCUl4aP588Bx\nHPLy8rBnzx5cPG48fvx9M959911wHIfDhw9j4sSJuP6m6Vj3+284cugAsrOzUVBSiTtuvh6rVq1C\nQnobHDl0AM/Nexfz3nwLt0+7Gct++RF9/3inJtNeXV2N3NxcrFq1CnfeeSd27NgBANi1axfWrFmD\nlJQUvPTSS7K2XXbZZdi3T4xkmp2djR07diA1NRXDhw/HpEmTMGzYMFPfQQv011duEw4T5pTj+7XD\n+H7tsGLvKekZI6QkyJN900wcSXGT0SoVxRU+n3YOnGaeuLxjZaprwQBbW+lfXZOHdNI1K9NDsAKb\nsM6DQC0F9EA0cXVuOR3GmiJWtshQy+rGndsO485th/+uPCBdU26TNC2ibU4ZgsaZwNr9pbJ/nyir\nZZbTS3kRDOgFNtE0XeeiT9PGAt1GNf0SfkS9Jm7mRNH+WIsYYkWnBNT+PNEGlqaMvsZxvo2QEMas\nQ/LcDumY2L89zu/RCgDw1DX9AQBXDeqo+/7kBIcsco6VjfTSV1ZhypvrzT8QADYVnMEP27R9hywR\nokFNMaDvWzD+3LZSFFC9/F4EwdYcOyVC3f86WNJ53z2Bqb1NT05QXQPoOSz+u1PzFPRq2xS9FQ79\nvnw31tt7zX/WWiovSaf9PDmMGORAiSQy3g0kOqWGJk6LQKT3Rroll/ZrB0A7h1C0oJ7an+rd+m0V\noE1QXX311WjZTNSEbN20AddcdyMAoG/fvujQ6RwcPiQGWaitrcX111+PN954A527dMH6VSuw9vcV\nGDx4MK68ZDQO7d+H/HwxgECnc7qib/9McOBwbuYgFB096p1Q7G9x0003AQAuvPBClJeX4+zZs1Lb\nUlLEgFJr1qzBtGnTpLZ17dpVYuIuvfRStGrVCikpKZg8eTLWrFmjOx56MLMN3je2h4qJS05w4KHx\nvTWesGZOSUALfch5p6rHK6QIJ4HH1q5Yww4vg/ltjr7vqx6CpaVimVOGcjwTJSbOmqnYqXI200EQ\nicAWem/U0hyFcmxLLATtu+ntDaFriA4kM3+d+asObEJ84rRh5aw2owUONkxr4oLI7UW9Ju6+sT1w\nn0K9TYOWNgfbJ66itgG1DbzKvCMYYLXu6Jlq2cQjh5mkiWM887fL+ki/C56bBAC4dVSG4fuTE5yo\ntbjBRgpaTruANSYlmMInmYM448u8e9tw6bfSnFJ8Xl4++Jq4wM0plc/SG48gsIMNaUnvicSdbHLJ\nCU4sZYSKJhJCLQZIrztWI3EGupEyCT3qIh+oOaX34QY3j6RkF9M88nBpleaYsA6Up68dgH4dRR9F\nf3y3rGDMVDXBf6qiViYdHti5uarM9kLrocz10KRJE9nYaX33e++9F5MnT8b48eNx9LSYA+qPf34I\nT/7jQRw9XY2qOjf6dkjHutzdSEj0RahzOpyo89RKAajF5MkKXwmNNCRNmjQx1Qet54MF5RSaOKA9\nCs/UyK7t+dflzGet5IlTBjZJlGni2EwcR9WtHNdQgUUsWt1L/Q2CQiMUmrhhXVtg8+EzITWnJPu9\nUvhi9OmUmrtogF8pBiwwm9X1blTUuiXrFCMYCbRkZbWSfYeYFyZjZsUnDiY0cVaabbWP5s0pfVCS\nbZGwDI56TZwREjSiUwZDs3HhCysw/JllAdfDAmvCzPwmDw/QNv7E5MQhJ4CDgWQXZU4ZtFqDAxXB\nolPWijllMKPG0Ypew+iUDCmy8mAItiYuGCGlWSZWBGJz5R1vnsrWwgG+OWz0DbR84vQe695aJIS7\n+hngwO8UA4xvpvSJCwRkrNy8mGJAeSAWV9RhUd4JS3OH43xm2pGQVEYK5BsPGTEKP369AACwb98+\nnCgqREb3XvjPf/6DiooKzJo1S3rm/IsuwXdffILKykpwHHDieBFOnTql+56z3nx0Z6rlAoUvv/wS\ngKhta9asGZo1U5uEjhkzBp9++qnUtiNHjqBPH1FIt3TpUpw+fRo1NTX4/vvvMXr0aD9GQQeKRZCW\n5JL8WI2gF3hLCV9QCLGszJxSMrmWP8NxtJm1qSYFDDPalbPV/qdvMYtgBzaRmVOGcDC1mDgWImGC\n1lQjVxkTuj5abN2RlTPlujfXY+Tc5abLR5ELoSb0ApsQMBTu3vRL2oNnZVytjpM/Wl49l5NwIeo1\ncUbQ9IkLgqnQGR0NUKDQIq6X7T4l5YwhvZHyxAXx/cmJTikBrpm6I7lx6BEHVg6iYGriZOaURu91\ncAyHY6VPXHAlkGQtBMTEKf4t/w6CbE5se/wyTX84wPwclog1C991fL92eHvVQVzUu43pZ0IFerjd\nvBDQuqF94sTolHLqVskomAEHDglOB5wOLmY08WZgNFvI/RtuvQsvPP4wMjMz4XK58NTL/0ViUhJe\neuklJCQkICsrCwAwdfqduPKGW3HkYD5GjRqFBo+A5JRUfLPgc1PtUZrzJycnY/DgwWhoaMD777/P\nfGbGjBm47777pLZ9+OGHSEoSrUBGjBiBKVOmoLCwENOmTQvYH04JurUbHx2HtunJaGtSM2DF17iJ\njjllgovtNiD6xHnbKQiIDKkEKGeZViLfYCLYeeIg+HoRSm2MlVbT54qhJsZ7/81bhuC+T/0PavPR\nnSMw5c11psrqnaFa5pRWzt1dx/Vz4QYbl/VrF/JAYLwOE6dFz3GcPPBOoAgHzeqvJq5RmVMaQRad\nkvod7dEptRL9ki5w4KQP7fRdDBqSXQ6cMiGJ792uKfadrMTJ8jpkzFqInXMmBK8RJqE34X154oy/\ndzA1mblHfCZfRvW6HJxqsSsdkIM9X32h+v2vQ2VOSf0WBDlT3ExHCwdQEREN+ukz+2HfZ13mALRs\nkhh2p2j6fSWVIkMlN7UIUBNH8sTxYnRKpabTTPXE95V8KjJVk12OsBChVlBcUYvjGo74NFhkvCAI\n2F/sC6Lyy/rtAID7/p+8747Xo6jXf+Z9T0tPSG8kgQAJCRCqdCnSFVQUK4qK4lW5qFcRBRQBlWtF\n9FoQRVRAVEDEUITQWyChJJBKei8n5ZycnP7O74/d2Z2dnbo7+56T/B4+H/Ke3dmZ2dkp3/796lU4\ndNxgrG5sAQDUNzTg2h/+IjLjZKabK1asSNS3dttubNvdgU989r/w/Wu/gfU7WrG9pQP7jx2Eum27\ncd+s2Cf4k5+/POxD/Ly4JXz84x/HzTffnLh23XXXJf5uaGjA7bffnnrfSy65BJdccknquk/wfbc1\n62Jg55MNYcjMKdn41Ek0cSIIiddCtY71JxalNa7i6+m0DA+8vg5X/PX13P3wdWTxOT4Zsu5PE6+a\niaXfO0eb/ifrZ7Lt08A++vPGhHrL9BlANma3yGnaqyKJK2CVJ074+6XlQeAy/Xgnby7bsgun/+Rp\n3HnpO3DC5GFC/W7jZG1OyZXb1NQW5ckEzEKXfQsIvLbHm1Mmkn1zv3t7njgV+EnAJiFjTn2apb9O\nGAAAIABJREFUAyajU6rL3f3ZYxMTb5PB8dgHxLfUvbUY0VNbr8e9r91B01sukUgyNbSf3ETJd7h3\nH+aU4knEK4IqVB7YRAVm9txlGDdVagRdW4QEd13fNe9hKDej8WeuxMaisyvQxLEItMdM1Kdb4FEr\naO/Ymcqv/6pC0+XNzfYO+zLo5pbzl+CEaUAoJVYUrQ9TwfDzz3fC7yLgSxrPCDUbQRSfYwtIWtLo\nfOK87GcOuPfVtcYyuvX3pxdXeemHr2nEqqlQGn33PGMpy+fHI6ra4gWyvKLP9XXACH36B9M4ye76\n1Cj5BkW6z5OG2fnm2oKdfbLcpnkgfoqXw4jV/3p9ff66rcvFJResT2pRIyFprZy1uve/jg/Lpcfl\nnOn6dFoq7PlMnCKwSW/XxKlQ4vynYk1c6BPnsR0xOqVqsx3avz4h4eiRcWWRtSSbqUsEQFPeIxeY\nolPyKJdING7D+suD5PgWOpQVzJALxGeT0SndCAy2Tu01cW5msjoi24TsUmN9Xd05zSnZo10VGo39\njPGDo+TKNkPEBFu1IYHM9pKAievFlIZn5KX9iaYOZiL4P1/+b1x01km46KyTcOrxx2DGjBm4/fbb\n8dRTT2H/qYdi/Y44UMiW5vaqCMRkkAkv8kT9iyPh2jBxSXNK3qc9Dn6UfCYQ0rAzIHM3c0N8PZ2V\ng6+z2hezwur5/XOxxrkawWnfWJMMUiT7fnwwk3vmrNHWx573yRscYkjArtU4UjldUmQUzdwBuSRd\n881ssb1Al8ogywilXDwy1JEXYhqhJIIe9a+Xa4p1QRKPFzSJttjjzSn5Q4DPSeESwccVRQpZo7pJ\n/LsITVxtuWSdYJpvtshxVbYf/iu1PY/MKc34+LETvPUpmSdO/13KhESLXVW0KHPKXIo4zbOUum2g\njIkwhbVn/VYRhLIDs0RI1UOQq/oibvB5tH2JwCYcHcHatSGaGQFy1dlTMGvhJpwfph6pry31iE9c\nT9HgWdtl65WQMPy1bP6F+/P//uTnWL8zYNTGDu6DoZzAZs323QCAMYODdAIbwnKupos+kCUQwxWn\nH6C855J3MDKnDP/mBWvMxI3lkmMg4KJTVmkG2fg56QRNvs0g84JV8/vnVuDwfQNT4mppNXnImuSj\neP76qWVRWikdsubdk/Xj2ncfrCx32cn74XMn75e6PmZQA9bvbFPOx2r5G2aL1kpT/fNN0zLhuow5\ntAl6okJngZKHLJYJohLB2idOcq0+o5Jhz9fEcS/OT5jeGKrWBvym3Rj62fDJvn22wx+6uqr5teaq\nMXpu6Va8uKzRXJCD6j1lLdtq4s4/bEwUlc8HXAObmMbNtyaORERPdojP8kPtenjUMpMrg9lobDYl\nvy5DiTBNSXWJEqkZDW9OKfTnvzWEsAxs3XV2VSJNZkKgYnGgMSZucN9aXPPugyOTtYaaMtoLMqd0\n/Q47d3egtcMhHHuGz+zaJzbMbD+OBEmSslm0x75BqSnDUhouASU+cOQ45b2SgzllP405pUoTByL3\n6SoSNmOp27N9+S35UpDI9upirWoUzA0o7pyd39TUFy00fexADFG4OADAN8+dmhDGMHzy+InR77yB\nTVzQXaH4zdPLtW2bIHvGt59drDFN18sUASrLKN07FekmZW9OGUMMwEakpezAAju5Ys9n4rhdjufs\ne0Jj5AKVYy2/aS/a2AwAWBk65ftE2YKxYOAXuK32juHjv5+Nj/wuX8LJWKuU7m+kictgt54H/NCZ\nDpQabqxVklXfEiaVb5kLTFG5XA7Sy08/AMP61+HoiUO05YjmW+ueIcT9QIsY3YxDJA1Dzv0WN3iX\niJtAMtm3zCyl02KPY5YK4rdKmVN7QkNDAxobG52+36ptu7F08y5zwYygNCl5Hq4waU6AMOsH9jer\nLF10SL861JRKGNy3tpCcoiZQStHY2IhVO7JHUzZ9Ld1aZ2ewzV7TUFsKUgaE9fGWNEzAQEDw7kNH\nx22DF+70HKMstq3tSoHMVxbw2wfrt++IyDxUY9O4qwNX3/9m7vp90fJ5p5Pq+aJm6QOvr8Mfno9N\nYrOaJIrP6cwe80CmiWPCR1VOWZ0ARSV4qGoSeO6ji/1RCaFFyJa1zmxXh73AnFKlievd4bMP33dw\nFI2HR4nIwtEH//qMrlgiQcREG2KLb7YnNJza6JQ0aU758w/P8BIVzAWm71IqkYj5lSXIBvzn7LLd\nTHTQmlPCTXo3Y/xgzLnmDGM5VZ44vt30M0S6bkzIv5rM5pQ8XPw3gfgbdnVXwGhdvs9iGHsZmKZD\n/FZFBTYZN24c1q5diy1btkjvN7V1oqk11rotbO6DTWFS6TJJ5l9UoaapIVpzm4SE1PLyfbBlVztK\nJPBJ3dEM7NiAxPMLm/skntnZ2onmti401ZbQvrUezW1d2NnaiXJTA3bs7sTujmDsWhtqsL1PLQiA\nZTuDb75pZxvat9ZiM5eLSmxH1W5WNDQ04Beztzs9w+/9Cw1hznV7nIsmjhCSMJeslWjiQIBffvQI\nbN/9Ep5/uxFNbV2ccMfYhBdIBTTCNdf1nAW+aOuJksAVvoNp8VDV7EuT0tOB60yWLjJhw5ptu1Eq\nEYwdnH3Ni4K3LCk3ZDSf6KvqCzLmUKWJ+8yJk3DPK3qfyKbWpKBKJ4ids3Kbk59ZNq2mqImz+xay\nclljNuzxTByvfeOjU/Z2c0rVhCESYk0UBvtAuZTcCPXmatUdV4k1DQD5hik7iIb2q0NjSzKH1hkH\nj/TSNxlM36VM4hQDqkVuivaVuU+5CA2dJo56dS5niHziXAObIDvDmlWKJw1sIppTcmN0wv7D8Oun\nllnXz5uQ8f6+rAkb7a3KX6mhtoymNv95MGtrazFp0iTl/Z89tgQ/n7U0+nvlTefhnKtmAghMPndY\n5OZceP3ZkW8Ve1aHX3zkcPzmpWUYPagBt31yRuIee37lTeclrv/wkUX41VNrcO4ho/Crj03FHS+s\nxHf+9RZevfYM/O7Bt/DP1wMu8EunTsbXzjooeq5xVzvefePj+O750/DJGROV7ajazYOm9gVW5Xyb\nTp0zfRRmztuAqaMGWJXvW1eO+pBk4pKmq3w/k3niiocNE6f1icvY7seP3Rd/eWl19Lcvnzg+Su3r\nYbCRIrWaRWmoXPyBdRg9OPBFfd/hYzM9z89N6btKrp30wycB5Fvz4nQwjcK0MQPxlhBBkSK9jk6b\nMgJzV7kJgWwg08R9+Jjx+O3Ty9G3Psk4lkjwXXXT8saZC3HpSbGPom4v++hts/G3y47DMZP2seyt\n+5xy8d03YbIhSqoKe7w5JRAzcuUqMRsu30cV9lpVhUxyQaN79u2aEGji9AtGhvYeiGhHSKBZlS0Y\n1n/+Pe767LGpciygQyGwMKeMiirK+jZti0xQc9SRisbGDXLF0ZzSFrYmjrwWqVTqqcAmkmvc7/au\nSmJqnHjAMHz0Hftq67zj08dEv/n1HikpuEG38YljJisiw1eUOaUJ1fZbBIDV23ajs7viZK7CyjaE\n6QOYgNDEOOtMv32irbNbaZ7rYoUidvMPl8iTiOu0tu8+dAwW33g2Dhhpx8T14aT+CSFs5PeZ3lhE\nn7i8gS2yIBXYpABt0PXnT8eSG8+J/vbGxEn8bWw0p5UKlX570/Qu2rwtLwM6rH89ltx4Dj5zolrg\nZAPVOi/q7cWvaBqGEyWaKNkzJx8wPHunNJCt06vOnoIlN54TpWZhKJWIlTC7u0JT7lKqYWARgDu6\nKt60t3wt3TSou6W9KyHYpgDe1ORUli3rcUOy5ZDbO5i4cER4aXVRTvuuUBFaQxTJkQmQmpFso/Ap\nQS2VSGIj1Ofhin/3lJnqQdc8gm/dPz91PR0diChzdBQF03cpJZg4ednCzClzbFziZs9rPVs7u72a\n9zLExJpKwgX8562NmHLtI9E15mNTVbt4mKP8fer2V1L3+9frjR9qubnCE3D8YcjaddHEpZi4mp7J\nE+fjC7l+5+4KRVc3TQTRMIExv1GKhlLMDPOti33xYcZsQld3BVOufQTX/1uueTvomkek121QVkgK\nTcmRRYJMBzG4CUONqInjtpfe6BOnsxbIujWWSiThK+Rri62RfFeb/ePGmQsx5dpH0mVNTJxKE5fz\n+7GnfRDkdTWlzGfYS8uDYG2zl2+T7kfVmqemvdBSSVhYxHUZE0cIkfrDPbNkKwDgtTV6jeAHf/MC\nDrzm4bAyu34ceM3D+Phts7VlbD8ZX65SoTjwmocx7TuP4m9z1iTMvnl/Xxu4lmfYK5g4tj/x5pQ2\nUupqQBVghdmo7z88aaseRUOTOCL7XGh82HsTEuaUVZDep5O9Bn/f9+q6VNn4HeJ3ESXuz155qt8O\nCrAJbMKgEiD7Jqj9aOKST29qTua1KlITJ85N/rB9aknS36qUMbBJ3heQa+LU/QbM+XhUREUUoZa7\nZkOEsbUg+s/1hOYS8OPT5FpHd4Wio7uSYJBNYAcqY2qYJqOrW2+9EOUzc+uiE5gG5a6XVxtKukM1\nQlmlxDL0qStLlx5bG7J7ok9c9fVwrnni/PTQV8AJmb8N8+vU4e5wjol7jYl5cGFiBjbYe/WwanuS\nmQeAF0MmjjFzIorqnkgbGTWikgKqND1FoOxQL/PLXbxRH+Tq1dU7UtdM7klA/M3ygh8/Xpv9yJsb\nE2W0ihHZtYzfYK9g4piUief6i2A2Fm9sxsHffgQ7W+19SR6ct0F+gwYmTUP6JsPbyj4k2zC9BjYp\nBX5aZ//8GWNZvtWq5JYSXvPKe+cpizJinz/cRSYujyOxDUzalYQmTlGmKPNfE58+e3kjZlz/H6l/\nlPio6K/k27cGMGvigjLpvwlIZimv7rFH39qId3z/cakwRtpHhRadwaQN4pd4QhMXRUskWLOtFet2\ntKKzy/y+w8JoiT1gfSaFjviz8YfL1CYNNHEu5pTxmZL82xSdl4Tlb1BoyfLgyUWbcdSNj3k928Qj\npSiJPA9VEIU4CE8avE/crvau3OHxr/3nm5h41Uz864310vtSDYZoTlmAJk6Er3UrM6fc1eaQ1kNA\n5oi+kmtNkn6YhJpZI/n5Aj+asrGYtXBT8Q0r2jbdf3bp1tT1osyTswghRjhE+DXV7kKj8EMy7duP\n4K31O43P1GisrKqxlwJ7CRM3rH/ACPEDWoSk5i8vrbKSXvG49p/ycLoVSlEiJLUZyeZ8EdJH1s6S\nTYHUQzfh+HvViArlsvDSGpu01LHIxfTNc6bgs5yjrQy8NEol8Wp1nFcmEI7o0eFnjy/Bjt2deHNt\nesNizx4RJodVteETrEo1rUxTYxhEpyxG+/GdB97CpqZ2bN3Vnu6JmYdL/W3SBpUUc4Udhp8+cRK2\n7mrHWT97BjPnKwREHL7/vkNw7bsPTjl3V+uAEeFFE+dYvkIDTUJNBnMVxrzVRj5xSTZUfJ8ih/XG\nmQuwdVdHlDi8Gvj35Sfitxcf6bXOPrU10nGqjTRxyX+BpE/cIkMkTRv8+aVVAICr70ub6Kug8xEW\n4Y+J81ORzJyST7JtgviqpjWYl/5aa5jjJ04ehmvOm5qrDR+gkI/F9x5aWKX23c0pZdAdSw9fcZJ9\nhxzxt8uOw58/E/iB//DCQwEA9aE7zEeOGW+tpfXhSsFP2ZaObvzhuZXGZ46YkKSN+Kil2rXr8aDY\nK5i4/YYHUV1kG5VPZJkoKvOpCkUi/w1DECpdLMs0cc7NK+Gi5uYnYzWsGFyEN2xs+G6JUscifLcY\nLnvn/sp8JwzlhLRGXqYoc8o8YN/68+/cX9FG7iYkdco1cURSJnGfiwBaBGyHM0XsCBdqDXOFH1P+\nN1uvZ08fhUe/fDKmjx2Ip5fIw/jzGNSnFp85cZJcw98DJklefOIc+/3LJ99GY0uHk/SezT+2diNN\nnDFZvduiuIWL1GlCqu4CTFNFAdr0sYNw1rRR+RviYNLEReddol9I3Csa0pykok9chUqFmi0OzJEJ\nvo4ulTllVqHsog1N+NVTbyvvF/WZeKukS0/aLxLgVxumlBf96+UxD/JidWOSuc2iiQPMZv88po4e\naNW3LDhm0j44KQyqMmFoYLLNpuSx+w3FeYfmC0gnvpaPfLx6IV48L6olJ90rmLiRA4NwsbyktWct\npmOopL+Uxr48PBjhxh+mcXh6f3BSc3NFqzGuLgdXShOHtHZThavOmVIVaV5Zo3Jn8J3smzVpTfTI\nNMDh11aNZxHmlJFPnIOUu0SCnrgS96wa3VM6wY2sOdHcTixj9onjf3PmlNw+Mn6fvrjr0mNx/QXT\ntHVp28n8ZD70pCuLzHH8d584Ch85ZnzqOjPXY98rik5ZqWjnmatg46ePLSkk1YMtxOjJ1dDQnnvI\nKHzgyHGp62yMZYyyDx9fGVT1yT5xKjolDczRRfz6qWX+fOJ8aeIUdIhtahuxGx+9bTZ++MhidXRG\nFfOQ8wP+8qNHJP5mWuI/furofBU7Ij47qHQMTIGAsuKXTyYZZ9Nw2ioeeBrlwiPSa7MaYDQpP555\nBcXi4/95S23maks/8MX4J8S29Iq45E2W6uJTJ0zELR853KofDHt8njiguAUjwvSNX1i2FfsPT+Z6\nUGkHn1q8Gc3tXamPKWOuokTRHk9Y0QZaV3MyJ0rxVJjLe0aaOK5bJkKZQaVh8g2bwCbiqDa1deKV\nFdtw+tRs+e18JMdl/IjKXr6YwCaBYEMVVZMJP3iUCItO6dqWuUxsypwuLGOQRQJULGISMCRNyOLr\noua8VCL4xHET8e0H3tLWp0NP8FNezF4yPicb+zMOHinNIcmEQ2w/jgLEdFWs23dNa5AF/563HmdN\nG5W5nTbB17MazP3Z00fj7OmjU9drBb9DaXTKiv0Mmrd2B/rV16TO5KwQfcgqlEq1/1ua23PvjSUS\nMIneUgwo5ocq8JqImQrf/n+9sR7vOXRMim5RRhfOuf5njE+arx05YR+vuRatUWXBtgomeoy/PaRv\nLbaHfsfiY/zn++Kp+6NCKe5/LR1IrkiwPvCCedP8d7V80Aplxb8pxdf//gauPHsK3lwn948T6RSV\nEFYEf2vedWdiYEOguf3Oe9wFs3uFJo6Zs/n011qw3t3u/qO/m43zbnkuwVSeOmVEqlxzWyeWb20B\noDCnDFcYC8gxcWgQwfITx0907pMKLhIOvmw1JOlZNHGxmUWx5pMMl5822bpsMrCJWjPL46v3vI7P\n3DHH6Buggo2WyQT2rEqKW9Q4EwT5V5Jtxb9TgU2iPHEZ31bzHLsje1XZU12VSiJ9iFjGRGyrfOJU\njPQhYwcpfRZ16CmfuCJMAG3hkmKAMeORJi781xRQg/++tz27wrWLWkRrOuxCR3cFX7rrNfz8cXuT\nTBHD+gtBBHpqXiDeZ2TneBah1Pm/fB6n/+RpbRl1nq/09asE/zmVoOmeOWsse6jG1846CP3ra5Sm\np65QhS+3tQD5+j/kwcWu+Ovr+MvsVanrvcUSKivOnjYqvTY4iGtRRNWS0juU/eKpapplQEPS/POi\nowLrhA8fnbZSsMElmWjVYFQjy7PQ190KioFIBW5y2ODue20d/j53LY7+3uP41B/jdEF8U+IWkMXs\nO++Wm0sTRwgZDOA2ANMRvNunASwGcA+AiQBWAriIUuo/FTwHtkElDtica8jF6ZfH1l3tOGjkAIwb\n0gezFm3GQSPTUkAds8ns6QkBrjz7IFzx19cxuG+dd2lTKoy/TvWbkDpVxaDSuuT2VMTE6uB/zjwI\n/3PmQVZleS2KapzFcV0V2r63tGfzlWNEj2kz2dyUDtgR9YmazCmLAUtEr7uf6EdkTum/L7qgQrKD\nuqObYmj/emzf3YnBfWsl0SkNkkX+N6+JU5xmD15+orY+HXokxYDn+urKJet0MnUOgU26Q21Q5BMX\npWqoJF5Cx6TLfKMopbmFH+JeMV8hJbZBP09Mgg+wMWbnOD9KcRLd6kzabS0dxms6k++8a+sLp0zG\nZSfv7y1qoGrO2WridBD9tAA1E2MI7spBITi0fTwnfmMI5sPGs7O74vytO7sr2N7SgRGhG5At5OkC\n9M/wptqXnrQfbpwZBFwRH+tTG+8DhBAct//QXDTndedPw3Xnu2mV+Ai0fF90MM2HjTvbsH5HK1ef\numyWNSt+kw072xQlk0ie8/lmdV5N3M8BPEIpnQLgMAALAVwFYBal9AAAs8K/CwU7OLvtdwgj8owr\nBY20LzJ+jZcGiB+wkTso9hsWMIBZJO0muBwOMv+8IuF6bi3fsqtHfW1MKCfMKe00ceyZrNrlODql\nusyu9q5II6zrk8o8tShtTkmjVaNIr5kSYc8U0Rs1FydrrrMr9pnqkJjemRJ6KjVxnge7CH9GG3iR\nUCeYKPv6XDRxB48JnPmnjxkEIA4MYQpsAgDH7TcUADBqUJpIy7N/qta0TYAbWT1Aeg731LwA4n2G\n7Xmq6JQ+oapu6640E5d6lqr3wOfe3pq9UyGKCvvOwyQAsdl2dkv86npaQ1U02sNUS3fOds/V+I1/\nzMMx358V1WGL3z8n0ewbhlOWW1eGhBmgQ598QhQ8EzgEFFNcv+7BBTj+pieiv3VLyvYs4ecwvx/N\nWrQ5ihjtMs3zLvPMTBwhZBCAkwH8HgAopR2U0h0ALgBwR1jsDgDvzddFM5g5Ja+JyyuxyzOuFRoT\nXaaPKZfwB/8eMm4Qnv76KRlV03o4MXFVNqd09QNYvyOWfvSYmZgGNtEpxWEtl5IbmitshmF3B6cp\nkDTD1pDKr7OoBKGEyAPW8PfFfhDiPlY2BKvOJ84U2KRC007vZp84+W9fSX95iHtkNQgsGyJ8jIT5\n4cH3W9flG4TAL7a+skDgt/X010/Bu0J/uSjoRqViPFu+/Z6DAQAD+6Qj1ElNBa17FcDnV0pFV+tJ\nc0qN4CryietFTEA10u0UDRefKpc6VI/tBUMGQBTm2L8/EOQeBYJ0JS54cVk6iE5WOlf3XXtqD4iD\nscX9MJ3R7n31+3Kq8Td9F56myis4y6OJmwRgC4DbCSGvEUJuI4T0AzCSUsq8YDcCyBaZwQF1kdO5\nnEPOglyaOEq1RLjNQcSanzC0XyG+RzKTNGVf+BQDVTBncX1dQno26p0JNtEp7xIkemVLHxwVIsm1\n5nkTExZp4lQ+cZl6ZkaJEOgExLJk34s2NuM/C7IlWM06dVTmlOxqhabnpSkNStL3j9PEeWbiZJ++\nu0Jx9s3P4FO3v+y1LR4269RlyuuKHjlBzI3nNoYTQl9kIJknzoSG0DRJtvYqlKZM9W1f1+Wwn3jV\nTKu0JalQ49Yt+Eetxpwy9onTj9bSTc2YeNVMvLY69uCYeNXMzL7FOlQo7dHx8gEf56bMAOqbivx7\nG5vszM1UqIa/uw34/Ti7K7b9g8f/YBZmLdqcun5tjsBWPPhh7SlGm+1vPH28Yusuq2d9W3jo0N7F\nC2pV/dHXwdNUuYMg5Xi2BsARAH5NKT0cQAsE00kajKz0dQghnyOEzCGEzNmyxc0cREQcfphn4vzP\nRNsaKRCdQLJndLb01YKLFoUvWZXAJhnKx9++d2zyPJLmlHbPsO+TVdorSrV0bQCQDht7VmUCWNR5\nGjDlCgkXdRNAmNphdapAo3/tpK1dnM8UpfFTf7jkKABmc0qeUOff00WLZAvxvbsqFIs2NuPJxfn2\n47ww7Y+2e5A41nmGsIaLnJgIMS3piy4ICqXAuu2tqWsusCVYZH5dsv7w6EkiWRXYZMqoAZy/jH68\nnlwcELpiNMW5q/y75Vco7Y3HjRNMM8lmOvQm7Wi1YCsAlSESSDi0t17ha/XgG+sdagnysgVtqy1d\nxLQj1YJ4HhMQo1ly9IxjGzLY1tHUGvsZqqOw6mFjnWWLPEzcWgBrKaWzw7//gYCp20QIGR10jowG\nkBYfAKCU3kopPYpSetTw4cNzdEM+YPn3leTI7tzdmdKWMPxNjEZFuRxwGTVxRcMlInXSnDLZ9xv/\nvQCzFmbTgKjbc5vVCzY04Sv3vB4+67UrXpAIbGL5TE1Oc0pIBBsiTEStyZyyKIJPFthEF7q3KLNO\ngJvvFHh19Xb8z9/eiK7JPk1nd+wHx2vixg4OEpm6+GUlE39XRxPXG6DTHgPJ/V7H0Iimq3nGsIbT\nxJmWZCkyC0wTQ9t3d+DTXKQzANbUQ2xS6FZeh97xxQPEjHKoiQv7P33sIGufOPZtbM2PZd/SRoMJ\nuATp6L1YtLE5dx1FbBu98RznkYjY7fhsT77awaMHYmBDOp4hP95ZrX/yQia4Ngc2cRtNH+eo7fmj\nAy+U7TFzSkrpRgBrCCEsRN/pABYA+BeAT4bXPgnggVw9tOsLgORg+Pbv+PksdRjnK4Xwu8zMgkC+\nwZm6Vo0l5DKZ+bJi3297bgU+c8ccX90C4L6B3zhzIZZsSqrd//fCQzz2KB9sApuonrEJpCADa8V6\nGUjKsbmrTjHg3C0rEJJOMZC4L/xdpP8/5f79xO9fxr2vrkVzaA4n22MCIj+4XqE0kfoCkGviLjt5\nP649+QFWRJADsffVOLwPtwjSZNLE8Qy+rqQ4b/MMYS0fndIAnSbuLy+twrodSU2cu6DGrrydz6da\nWFIt3HXpO/Dd86dFayNmfkn0f9Yt01ip7DFcBE7PLrULStIbLGry4mt/eyN3HdUMVtJbeDvTfKpW\nFFWGg0cPtC5LIdHAc7+z0hx5Ifq9ElJEQC81skxjpSDHUFdv0cQBwOUA7iSEzAMwA8D3AdwE4AxC\nyFIA7wr/rgp0Ubfy1AUAtTX2I72ycXeUr0y2mFdvM9vnF23W4hadMkY1lnceyQR78kNH7+unMx5g\n4xOneia7OWWoicsTBpsaNHEFHaklQtTJviUzMKt0zeUpfqxigjJdrrO7gpVhyG1KOSft8L4ssMmn\nTpgUHcJ8O4lk396ZuHR91dDE2XwrUz/4+7o5XCeMdZ49tYYTqiQCq0jmY+QPLXkP2bs5s3AeNXGp\nZ9wfyY3jJw/DJ4+fGKcYkBCRfJ64XHuagNbObjwp+BrZMtWU0h6N5ukDPpiN3mBZ1JNlYjUOAAAg\nAElEQVToDa9/0KgBVuUC6zDZ9Xge26Zs8Q2Ztr0avuAMWdaC6gnTmpBF3s2KXEwcpfT10CTyUErp\neyml2ymljZTS0ymlB1BK30Up3ZarhxmRd2MRh1UkCESkJJoIiDBZNz74mxfj5zL2Ly+y5omrxoZd\nhcjKVUUWqUvExGWNTmlhepW4JekXu6/SxG3Y2Sq9nheySJO6Ycsr79Bt3rE1ZTrSpOw5UVNTiUzD\ngk7KfNsCgU+67cI1cUL3u6pgH2YTEdNkTmmboFg0Xc1nTulHEycLjGKryXD1pbF5294UnbI2lWIA\n0b+xj69JEydITSzwKcG81XbL7SFa1yu8BDYpgCToDYyRDl8788Dot+wcOPkAs4tQT7wjAZHuH/xy\nOVCS27gaiH3imGWdPS1YzbFMphiQN/zdC+xz5OXdcvNq4notstAjK7e2YLvEGby7QvHqar1jtPgt\nS4SAgGTa4KoSxt8pxYDanLII5Amn3luiV/FIMHGOz2TNfRiZU2oZFO6ezJwynLwq4rcoXzRTsu9q\n9QOIxyihidN4U4uEnejfI9PE8UycUhNXBZ+4nvDxkTE1JsGFrcZQFsU0K+q4yIn2PnHpgjJGuShN\nHL/ZvL25Gc1c4t+4bbGynts/ResDvie8Jk63x/NBEXi4ad3tBnhv0ED5eAff49BdoZi/bof0Xm85\n3k+bEgdd56OiM4wYWK9+OD6cqw5V0DBCgJU3nYeVN52HAQ3p1CjVANuft++OaXCT8DJLJHMVbKdx\nMrCV/KH3HT7WS59ssNcycVnWxyk/fgqn//RpAMmD4if/WYzn307n6NC2FxryZ1HRdlcqhR+lLkSh\nTzNVq/Z66NmiwI+1tU9c5OSbrU1GSNpEXjTdr/aYloiaoQiIuOS1Ig92yv0b/WaMnaS8yHRXBIJU\nysSF/wFJgihhclGIejr5BtXw8RGbkGm2TMwkY4xNxDYL9c/gI7BJV3c6gXuqrJaJk2ni7Prg2nue\nkXnXT5/BR383O1WmN/EhTNspzkMCEkenlGjEZcizXGyHpEJpr2EqssLH5/c9h77+jzfwlXvy++oV\nCf67f/4vc1P3tdEpC+iPtTZfdb1XTOSgD395KQggSIi9BUpPbWM+tNB5x37vZeIySnNlYZlfXyOX\nCvFIm3+FB4/hI8v6WY0AAyItqbPt5++ZTJ28oDfsJx6RCGxiueLy+sQxaM0pjXMz+FdF/BYliSaE\npAk5rgviXM3sE+fwGKWxBiZm5tLlxLXL3iMyp5SYpiY0cdx1/vzynWJAVls11rbYQkdXmmMzMZPM\nZ8o0/Rpqy+hXFzNyec5KNv42eeJ0OR5l7+sq6LM3v0z+PX/dTqGeXmZOGTHKaXNK28ickSlWDkGP\n7b4m5ombNKyfsmxvhY8t3HcQj5ckSa17G/gzXQxUBPQcU2EDiuoGo7GFbI26nO2VCjVHNs4h1JaV\nc6GBFt1wtnVZF+wVTFxsQhFDN7irGluw/7cewj9fW6csw9dl4wchOwwDc0r3xVKN6EAi96/rJ1/0\nl0++XVSXIuSRmPcKgZKApDmlpSbOV2ATnTmlYduqyBYWh6KEDQTp+bhmW3BQytZsXv5Gu0RpXIaN\nFysvWzPi9xJNw2olXHxges3aoYnr0e8q+MT1RIoB2d5q6gczSbTpLa+Ny7evENSUSCpPnAwsEJDs\nPf4xd236AcdhtyY2woJiP/hR6D3GlMlcfCJsk31X08drb/CJ8wHf+4ZOM9E7NEbmvcSG7qt2BEuA\nmVNWvVkrpOcRsdfEUYr3//oF7PethzK3b8vY8v383syF1vWLliG+sHcwcUIYb0A/UReHuVH+LSQE\nVaHDgqkSF2SJuC2Yb5w9BWdNC+ysO6vgnCKaU8okxAztndU9rXKZU3IPv3DVaXj8q+/M3Z+84Alw\n2zPIhgnTQeZjlYJl1eI++t+nTTbXnQOBT1zy2pJNwZqVJTfNnuybjbEa/L3ofWn6HoPI2PLhkgF5\nlFvCFUhq4uKyvn3iZKiOOWWyjXbNvqOCi5CLJ6ZsteAq1JRJWhMn6QpbL7ZCDtu3sVrTiXqDgjoh\nZDrFQM8RybVCsm8m2ggEogGMmrjw37RPnP17ufjEJf3Feyl1nAM2o+Zb9lNEECffMO4lOnPKAtaY\n2Nz1QmCNYf3ro7YDk2TvXcgNGeNrYpb5sbSxmPMBfp1vUCRhr2bU2r2CiZNBJwmJQ5naaZ86LQgN\nkbAIzCnlkYB48BnpT5g8LK6r4DkgbpS6sLK7O7oK68cX7pyL/xO0e772uDGD+2DyiJ6JtMQjkdjR\n9uUszYcMj+vDcSt+M8QMSLLPowb1MdadB4FPnCgUCQk8SlOmwHkDm/z6qWXqlAaSwCaxRk6iiRP2\ngcg0LPwisnQNJUIwqE9teF/O8Fcj1HJVTKUF2Eaa5GHrEwck109DTT5JaG2pFPZX3y4hgQTZNiiR\nq7WGTLDzw0cWyQoC0O/tvUoTxwWPAQQT6ugPO01cni3B9nP0xHqpBlrau3Di/z6BOSu3oaXDnPjc\n9zlgk4KppyGzqOBhpYkrcPqIeeOmjg5SEJCC280DWcR03z5xb6zdiRNuegJNbZ346WNLcMVfX3Ou\no7ct+72WidNN1CiPj46J444zG0KjuS3J6DDpoTEkcnh7W0u71pzEN0TzLB2jWmTekIfmb8SPHl2c\nuJbL7KkXOtQlzOLceLjMB2ScJ86uvGyeqqwpXTUCriCEpEwr4oh/wIgBDcl7Hj65SfvNZwdjXZO9\nvlhPShMnS9dAgJ9edBi+de4UHDJ2UHQ5oYmrQrLvnkhenGVvYXPDprds/C87eT+cOW2Uc1s8asok\nyBNn0XCJ2B/21oFNNHzMr55alq43/Jft7VK/yl5EkEQBYVKaVi6wCTVpzuWCp2J84uzr3JMwf91O\nrN3eih8+sthcGHvvOOgwpF9d9PuCGWNS97WBTapAoijbYOuo+C44I0VnwHy2uw7lLbOWYt2OVsxd\ntR23zFqKB17nLHsy0EofP7bn8xHvFUycbMHovoeNk3RCE2dBaDQJ4ZtJyMXZHtCl0OciaC/7Envt\nsdXYtqHFor3k31ppbZVXfO9jw/KBn0u2DGpe7ZLNHE+GypXcV/QlpiXdJkZ3dwUv3v822nenQ50n\n6idpQopp3yilqXZ9pBhQzXHK32fMW6Sdk2jihAG3STFQIoG5y+dO3j9BfCY1cem+7dyyG6/MXJGJ\n0ZcJO6rhE5eKTikJz21CV7hXiYIzXXtfOm2ykRFe/VYj3p67WXm/plxKCdhUvScgDmaPbnAtz84T\nFlQnqYEXzSkdK9dg7iMrsXLeVnPBELUKTRzzLwdsApuEz7h1VVqHCd2UYt7a2ISr6NUz78k12Lq2\nueBW3MduT0y10N1ZwQv3vY0Oiz3EBJl1hc1W6nPU0p9A/hW3NLWjvavi/Zvt2LQbrz66KlcdecxM\nqxkM587Zq6Pfr62ujgmnDnsFE3fhkeNw6LhB+NQJk6JrVuaUlkSLDVPVKpgdEBJIFk2E0QGhuV93\nhSbCWGeZzpUKxQv3vo17/3eOsexuob86RrXaAQ9y2Yz3Qg7wuaUxIWPbPdvktirE/l46c8r4nqwd\nUYsU1x0+79i1t+dsxquPrsYL96e1BjxKJE0A8ybQ1Yyox0ekjMwohXs8UtEpxWTf0uiU8hdIauLS\nW/WC59bj5QdXoKM1GyEiMn89kSeuo9tsriWCjbGowZfhNx8/EqccNBz96mqMZR/8xRt49HdvKu/X\nlUvo7LYTXRBiL+SwDw/upl1n5djeLjMBS60ljxvoS/9cjpm/mmddPp0nLm3BQCXrn4eaqbaHas/l\nteSsLzdygQ2OmrCPQyvuePaepbjnxlfMBRW45rypTu4FtvN3T9TELXh+PV77z2rMmbkyd12y9asb\nu2qQKIQA7z50dOr6fWFgMN/Mx/0/eRUv3r8s81kEyOgMszsSQ6MkqrwrssQfeGt9k/R6NV2L9wom\nblj/evzrSydizOA+0bW85pQ8bEx+0rltAsmiKLnd0tye+PvDx+wbPS/6BLiCbSadHeb+bt0V9INp\n/3QBBpx9NijFYws2RRJzV+xlPFySYbY1p4wEDdna3NwUONzyn66zu4LHFmyS+3nJNHFMqi3ZXIHs\nksROw0ZfIun1FPnEVdJbrQ9NnGqOy/zfFm5owqyFm6RjJpqCpfLESQhpVe9Nyb63rtkV9k1RgQay\nITOZUz6xaBPau9yZLh7i1+vIoIljRL5NX048YBj++KljvET3DMwp7RakS1Ar1+9nzRwKgU2YAIEk\nyiTRG1IMsHnIvhmJ/hcwDNr3VwieXKCqffiAZAJnUbjZt66Y6HO+cOlJ++Hb7z7YWM5ViLonBnTp\nDumdiodI4DpXhGpg2ZZdqWsESSZO/Ka+BfMd7d1xwxkhO8erqeXdA6cxgL2EieNx1IQhAOyCltgG\nNrGZ8KkwziRg4kQi5fxfPpf4mwnmuys0YqiyphigAsGowxH7BuP04WPGA9BHp3TtzROLNuOzf5qD\n/3tSr3FRoTf6teXB6VNHRL9tGQ6N+4sVfvvM8uB5bo7/YtZSfPZPc/D0ki2puuUHUVoizvfNdYMt\n14Sh1w2Ee4kQZWATStObLa/dykpQmNY4Rdzuxb9/GZ+5Y46U6VHniQv+ljETqjmRTPadvr9l7a64\ncxkgPqYbg1dXb8en/zgHP3hIEkDDpU2hiSw+cW2dIcFQ5UO3pkTQWUkmm1bNt8Cc0m8HnaNTRpq4\n4IdMm9ubCJco2Xc4D/mlkojWa6GJS+1ZDkeK6ruJ62NP1EC5+NZm9aduaS8uEJov0Hii5IZsHtis\nfV/7w+k/eVq6JHS0hnfrKg/vIk5NArMQu5dknFCCRfIuEnsdE/eP/zoeFx4xTjun2OTu7KZo3NUu\nL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a0ssAmtUGxdtyv0h8vOucr6U9GYU7pq4v7y0iqce8uzeOFtc8AQGWqFvTDJxPVQdMpy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Hf7kGD/2P9/j0Am8J7c5l9Y0nd6DlqK5w3vTafmbtdLvqmuPTmGsS7pRVde6yFKYlbuMr+/D0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\njDHGGGOMySLWiTPGGGOMMcaYLPL/sC6whMBhjWsAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, + "execution_count": 7, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "conf_flag_ok = h111_ts.data['conf_flag'] == 0\n", + "conf_flag_ok = h111_ts['conf_flag'] == 0\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "h111_ts.data[conf_flag_ok][fields].plot(ax=ax)\n", - "ax.legend()\n", - "plt.show()" + "h111_ts[conf_flag_ok][fields].plot(ax=ax)\n", + "ax.legend()" ] }, { @@ -405,42 +254,55 @@ "collapsed": true }, "source": [ - "### Differentiate between Metop-A and Metop-B soil moisture" + "### Differentiate between soil moisture from Metop satellites" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The `sat_id` field can be used to differentiate between Metop-A (`sat_id`=3) and Metop-B (`sat_id`=4) measurements." + "The `sat_id` field can be used to differentiate between: Metop-A (`sat_id`=3), Metop-B (`sat_id`=4) and Metop-C (`sat_id=5`)." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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dQ/ssCiGVUmi7gcuehkJ0mF7JeDn29wwcQd3mO3zFRjSpJJ17IUjxn/RvFCvu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\nnHXWWQBs2bKFgYEBe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"text/plain": [ - "" + "" ] }, + "execution_count": 8, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "metop_a = h111_ts.data[conf_flag_ok]['sat_id'] == 3\n", - "metop_b = h111_ts.data[conf_flag_ok]['sat_id'] == 4\n", + "metop_a = h111_ts[conf_flag_ok]['sat_id'] == 3\n", + "metop_b = h111_ts[conf_flag_ok]['sat_id'] == 4\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "h111_ts.data[conf_flag_ok]['sm'][metop_a].plot(ax=ax, ls='none', marker='s', color='C1', label='Metop-A SSM')\n", - "h111_ts.data[conf_flag_ok]['sm'][metop_b].plot(ax=ax, ls='none', marker='o', color='C0', label='Metop-B SSM')\n", + "h111_ts[conf_flag_ok]['sm'][metop_a].plot(ax=ax, ls='none', marker='o', \n", + " color='C1', fillstyle='none', label='Metop-A SSM')\n", + "h111_ts[conf_flag_ok]['sm'][metop_b].plot(ax=ax, ls='none', marker='o', \n", + " color='C0', fillstyle='none', label='Metop-B SSM')\n", "ax.set_ylabel('Degree of Saturation (%)')\n", - "ax.legend()\n", - "plt.show()" + "ax.legend()" ] }, { @@ -454,73 +316,66 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "It is possible to convert relative surface soil moisture given in degree of saturation into absolute soil moisture ($m^3 m^{-3}$) using the `absolute_sm` keyword during reading. Porosity information provided by [NOAH GLDAS](https://ldas.gsfc.nasa.gov/gldas/GLDASsoils.php) and pre-computed porosity from the [Harmonized World Soil Database (HWSD)](http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/) using the formulas of [Saxton and Rawls (2006)](https://dl.sciencesocieties.org/publications/sssaj/abstracts/70/5/1569) is used to produce volumetric surface soil moisture expressed in $m^{3} m^{-3}$." + "It is possible to convert relative surface soil moisture given in degree of saturation into absolute soil moisture ($m^3 m^{-3}$) using the `absolute_sm` keyword during reading. Porosity information provided by [Noah GLDAS](https://ldas.gsfc.nasa.gov/gldas/GLDASsoils.php) and pre-computed porosity from the [Harmonized World Soil Database (HWSD)](http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/) using the formulas of [Saxton and Rawls (2006)](https://dl.sciencesocieties.org/publications/sssaj/abstracts/70/5/1569) is used to produce volumetric surface soil moisture expressed in $m^{3} m^{-3}$." ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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r8dTYecKDYGGvGuQkrkIDqM30ORhAYVlPIYZfSKQ4LUi4zgFGIBjGAKJsGUDn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\n3psWWQfQTMb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kbM4qYAAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, + "execution_count": 9, "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "h111_ts = h111_reader.read(gpi, absolute_sm=True)\n", - "conf_flag_ok = h111_ts.data['conf_flag'] == 0\n", + "h111_ts = h111_dr.read(gpi, absolute_sm=True)\n", + "conf_flag_ok = h111_ts['conf_flag'] == 0\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "h111_ts.data[conf_flag_ok]['abs_sm_gldas'].plot(ax=ax, label='Absolute SSM using porosity from NOAH GLDAS')\n", - "h111_ts.data[conf_flag_ok]['abs_sm_hwsd'].plot(ax=ax, label='Absolute SSM using porosity from HWSD')\n", + "h111_ts[conf_flag_ok]['abs_sm_gldas'].plot(ax=ax, label='Absolute SSM using porosity from Noah GLDAS')\n", + "h111_ts[conf_flag_ok]['abs_sm_hwsd'].plot(ax=ax, label='Absolute SSM using porosity from HWSD')\n", "ax.set_ylabel('Vol. soil moisture ($m^3 m^{-3}$)')\n", - "ax.legend()\n", - "plt.show()" + "ax.legend()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.13" + "pygments_lexer": "ipython3", + "version": "3.6.13" } }, "nbformat": 4, diff --git a/docs/read_hsaf_cdr.rst b/docs/read_hsaf_cdr.rst index 068518c..963d106 100644 --- a/docs/read_hsaf_cdr.rst +++ b/docs/read_hsaf_cdr.rst @@ -1,15 +1,17 @@ +Example H SAF Metop ASCAT SSM DR products +----------------------------------------- -Example H SAF SSM CDR products ------------------------------- +The following example shows how to read and plot H SAF Metop ASCAT SSM +data record products using the test data included in the ascat package. -In this Example we will read and plot the H SAF SSM CDR products H109, -H110 and H111 using the test data included in the ascat package. - -.. code:: ipython2 +.. code:: ipython3 import os - import ascat.h_saf as h_saf - + import matplotlib.pyplot as plt + from ascat.h_saf import AscatSsmDataRecord + +.. code:: ipython3 + test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf') h109_path = os.path.join(test_data_path, 'h109') h110_path = os.path.join(test_data_path, 'h110') @@ -17,273 +19,94 @@ H110 and H111 using the test data included in the ascat package. grid_path = os.path.join(test_data_path, 'grid') static_layer_path = os.path.join(test_data_path, 'static_layer') - h109_reader = h_saf.H109Ts(h109_path, grid_path, static_layer_path=static_layer_path) - h110_reader = h_saf.H110Ts(h110_path, grid_path, static_layer_path=static_layer_path) - h111_reader = h_saf.H111Ts(h111_path, grid_path, static_layer_path=static_layer_path) + h109_dr = AscatSsmDataRecord(h109_path, grid_path, static_layer_path=static_layer_path) + h110_dr = AscatSsmDataRecord(h110_path, grid_path, static_layer_path=static_layer_path) + h111_dr = AscatSsmDataRecord(h111_path, grid_path, static_layer_path=static_layer_path) A soil moisture time series is read for a specific grid point. The ``data`` attribute contains a ``pandas.DataFrame`` object. -.. code:: ipython2 +.. code:: ipython3 gpi = 2501225 - h109_ts = h109_reader.read(gpi) - print(h109_ts.data) - - -.. parsed-literal:: + h109_ts = h109_dr.read(gpi) - corr_flag dir proc_flag sat_id sm sm_noise \ - 2007-01-01 21:06:01.843200 0 0 0 3 92 3 - 2007-01-02 09:18:16.848000 0 1 0 3 91 3 - 2007-01-03 10:37:43.104000 0 1 0 3 93 3 - 2007-01-04 20:03:56.275200 0 0 0 3 91 3 - 2007-01-05 21:23:26.246400 0 0 0 3 97 3 - 2007-01-06 09:35:41.251200 0 1 0 3 92 3 - 2007-01-06 21:02:37.507200 0 0 0 3 99 3 - 2007-01-07 09:14:52.512000 0 1 0 3 88 3 - 2007-01-08 10:34:20.582400 0 1 0 3 91 3 - 2007-01-09 20:00:33.753600 0 0 0 3 92 3 - 2007-01-10 21:20:01.910400 0 0 0 3 90 3 - 2007-01-11 09:32:16.915200 0 1 0 3 87 3 - 2007-01-11 20:59:13.084800 0 0 0 3 99 3 - 2007-01-12 09:11:28.089600 0 1 0 3 87 3 - 2007-01-12 10:51:33.753600 0 1 0 3 87 3 - 2007-01-13 10:30:58.147200 0 1 0 3 87 3 - 2007-01-14 19:57:13.132800 0 0 0 3 85 3 - 2007-01-15 21:16:37.488000 0 0 0 3 85 3 - 2007-01-16 09:28:52.492800 0 1 0 3 86 3 - 2007-01-17 10:48:11.232000 0 1 0 3 82 3 - 2007-01-18 10:27:35.625600 0 1 0 3 98 3 - 2007-01-18 20:14:26.217600 0 0 0 3 93 2 - 2007-01-19 19:53:50.611200 0 0 0 3 89 3 - 2007-01-20 21:13:13.152000 0 0 0 3 93 3 - 2007-01-21 09:25:28.156800 0 1 0 3 89 3 - 2007-01-22 10:44:48.710400 0 1 0 3 89 3 - 2007-01-23 10:24:13.104000 0 1 0 3 46 3 - 2007-01-23 20:11:03.782400 0 0 0 3 43 3 - 2007-01-24 19:50:28.089600 0 0 0 3 51 3 - 2007-01-25 21:09:48.729600 0 0 0 3 43 3 - ... ... ... ... ... ... ... - 2015-12-19 21:20:37.507200 0 0 0 4 97 3 - 2015-12-20 09:32:50.611200 0 1 0 4 88 3 - 2015-12-20 20:05:52.483200 0 0 0 3 90 3 - 2015-12-20 20:59:46.867200 0 0 0 4 97 3 - 2015-12-21 09:11:59.971200 0 1 0 4 89 3 - 2015-12-21 10:52:05.635200 0 1 0 4 86 3 - 2015-12-21 19:45:16.876800 0 0 0 3 89 3 - 2015-12-22 09:37:37.459200 0 1 0 3 90 2 - 2015-12-22 10:31:30.028800 0 1 0 4 90 3 - 2015-12-22 21:04:35.616000 0 0 0 3 87 3 - 2015-12-23 09:16:50.620800 0 1 0 3 89 3 - 2015-12-23 19:57:43.113600 0 0 0 4 90 3 - 2015-12-24 10:36:14.976000 0 1 0 3 89 3 - 2015-12-24 21:17:05.654400 2 0 0 4 100 3 - 2015-12-25 09:29:20.659200 2 1 0 4 100 3 - 2015-12-25 20:02:29.961600 0 0 0 3 94 3 - 2015-12-26 10:48:37.497600 0 1 0 4 90 3 - 2015-12-26 21:21:58.118400 0 0 0 3 91 3 - 2015-12-27 09:34:13.123200 0 1 0 3 86 3 - 2015-12-27 10:28:01.891200 0 1 0 4 88 3 - 2015-12-27 20:14:52.483200 0 0 0 4 86 2 - 2015-12-27 21:01:09.379200 0 0 0 3 88 3 - 2015-12-28 09:13:24.384000 0 1 0 3 85 3 - 2015-12-28 19:54:14.976000 0 0 0 4 88 3 - 2015-12-29 10:32:52.540800 0 1 0 3 86 3 - 2015-12-29 21:13:35.616000 0 0 0 4 90 3 - 2015-12-30 09:25:50.620800 0 1 0 4 88 3 - 2015-12-30 19:59:05.625600 0 0 0 3 86 3 - 2015-12-31 10:45:09.360000 0 1 0 4 91 3 - 2015-12-31 21:18:31.881600 0 0 0 3 89 3 - - ssf snow_prob frozen_prob abs_sm_gldas \ - 2007-01-01 21:06:01.843200 1 0 29 NaN - 2007-01-02 09:18:16.848000 1 0 21 NaN - 2007-01-03 10:37:43.104000 1 11 29 NaN - 2007-01-04 20:03:56.275200 1 22 29 NaN - 2007-01-05 21:23:26.246400 1 11 36 NaN - 2007-01-06 09:35:41.251200 1 0 32 NaN - 2007-01-06 21:02:37.507200 1 0 32 NaN - 2007-01-07 09:14:52.512000 1 0 18 NaN - 2007-01-08 10:34:20.582400 1 0 18 NaN - 2007-01-09 20:00:33.753600 1 0 14 NaN - 2007-01-10 21:20:01.910400 1 0 32 NaN - 2007-01-11 09:32:16.915200 1 0 36 NaN - 2007-01-11 20:59:13.084800 1 0 36 NaN - 2007-01-12 09:11:28.089600 1 0 39 NaN - 2007-01-12 10:51:33.753600 1 0 39 NaN - 2007-01-13 10:30:58.147200 1 0 21 NaN - 2007-01-14 19:57:13.132800 1 0 18 NaN - 2007-01-15 21:16:37.488000 1 0 21 NaN - 2007-01-16 09:28:52.492800 1 0 14 NaN - 2007-01-17 10:48:11.232000 1 0 21 NaN - 2007-01-18 10:27:35.625600 1 0 14 NaN - 2007-01-18 20:14:26.217600 1 0 14 NaN - 2007-01-19 19:53:50.611200 1 0 18 NaN - 2007-01-20 21:13:13.152000 1 0 29 NaN - 2007-01-21 09:25:28.156800 1 0 36 NaN - 2007-01-22 10:44:48.710400 1 0 29 NaN - 2007-01-23 10:24:13.104000 2 0 39 NaN - 2007-01-23 20:11:03.782400 2 0 39 NaN - 2007-01-24 19:50:28.089600 2 0 25 NaN - 2007-01-25 21:09:48.729600 2 0 18 NaN - ... ... ... ... ... - 2015-12-19 21:20:37.507200 1 0 7 NaN - 2015-12-20 09:32:50.611200 1 0 11 NaN - 2015-12-20 20:05:52.483200 1 0 11 NaN - 2015-12-20 20:59:46.867200 1 0 11 NaN - 2015-12-21 09:11:59.971200 1 0 7 NaN - 2015-12-21 10:52:05.635200 1 0 7 NaN - 2015-12-21 19:45:16.876800 1 0 7 NaN - 2015-12-22 09:37:37.459200 1 0 7 NaN - 2015-12-22 10:31:30.028800 1 0 7 NaN - 2015-12-22 21:04:35.616000 1 0 7 NaN - 2015-12-23 09:16:50.620800 1 0 25 NaN - 2015-12-23 19:57:43.113600 1 0 25 NaN - 2015-12-24 10:36:14.976000 1 0 32 NaN - 2015-12-24 21:17:05.654400 1 0 32 NaN - 2015-12-25 09:29:20.659200 1 0 25 NaN - 2015-12-25 20:02:29.961600 1 0 25 NaN - 2015-12-26 10:48:37.497600 1 0 29 NaN - 2015-12-26 21:21:58.118400 1 0 29 NaN - 2015-12-27 09:34:13.123200 1 0 50 NaN - 2015-12-27 10:28:01.891200 1 0 50 NaN - 2015-12-27 20:14:52.483200 1 0 50 NaN - 2015-12-27 21:01:09.379200 1 0 50 NaN - 2015-12-28 09:13:24.384000 1 0 43 NaN - 2015-12-28 19:54:14.976000 1 0 43 NaN - 2015-12-29 10:32:52.540800 1 0 43 NaN - 2015-12-29 21:13:35.616000 1 0 43 NaN - 2015-12-30 09:25:50.620800 1 0 43 NaN - 2015-12-30 19:59:05.625600 1 0 43 NaN - 2015-12-31 10:45:09.360000 1 0 54 NaN - 2015-12-31 21:18:31.881600 1 0 54 NaN - - abs_sm_noise_gldas abs_sm_hwsd abs_sm_noise_hwsd - 2007-01-01 21:06:01.843200 NaN NaN NaN - 2007-01-02 09:18:16.848000 NaN NaN NaN - 2007-01-03 10:37:43.104000 NaN NaN NaN - 2007-01-04 20:03:56.275200 NaN NaN NaN - 2007-01-05 21:23:26.246400 NaN NaN NaN - 2007-01-06 09:35:41.251200 NaN NaN NaN - 2007-01-06 21:02:37.507200 NaN NaN NaN - 2007-01-07 09:14:52.512000 NaN NaN NaN - 2007-01-08 10:34:20.582400 NaN NaN NaN - 2007-01-09 20:00:33.753600 NaN NaN NaN - 2007-01-10 21:20:01.910400 NaN NaN NaN - 2007-01-11 09:32:16.915200 NaN NaN NaN - 2007-01-11 20:59:13.084800 NaN NaN NaN - 2007-01-12 09:11:28.089600 NaN NaN NaN - 2007-01-12 10:51:33.753600 NaN NaN NaN - 2007-01-13 10:30:58.147200 NaN NaN NaN - 2007-01-14 19:57:13.132800 NaN NaN NaN - 2007-01-15 21:16:37.488000 NaN NaN NaN - 2007-01-16 09:28:52.492800 NaN NaN NaN - 2007-01-17 10:48:11.232000 NaN NaN NaN - 2007-01-18 10:27:35.625600 NaN NaN NaN - 2007-01-18 20:14:26.217600 NaN NaN NaN - 2007-01-19 19:53:50.611200 NaN NaN NaN - 2007-01-20 21:13:13.152000 NaN NaN NaN - 2007-01-21 09:25:28.156800 NaN NaN NaN - 2007-01-22 10:44:48.710400 NaN NaN NaN - 2007-01-23 10:24:13.104000 NaN NaN NaN - 2007-01-23 20:11:03.782400 NaN NaN NaN - 2007-01-24 19:50:28.089600 NaN NaN NaN - 2007-01-25 21:09:48.729600 NaN NaN NaN - ... ... ... ... - 2015-12-19 21:20:37.507200 NaN NaN NaN - 2015-12-20 09:32:50.611200 NaN NaN NaN - 2015-12-20 20:05:52.483200 NaN NaN NaN - 2015-12-20 20:59:46.867200 NaN NaN NaN - 2015-12-21 09:11:59.971200 NaN NaN NaN - 2015-12-21 10:52:05.635200 NaN NaN NaN - 2015-12-21 19:45:16.876800 NaN NaN NaN - 2015-12-22 09:37:37.459200 NaN NaN NaN - 2015-12-22 10:31:30.028800 NaN NaN NaN - 2015-12-22 21:04:35.616000 NaN NaN NaN - 2015-12-23 09:16:50.620800 NaN NaN NaN - 2015-12-23 19:57:43.113600 NaN NaN NaN - 2015-12-24 10:36:14.976000 NaN NaN NaN - 2015-12-24 21:17:05.654400 NaN NaN NaN - 2015-12-25 09:29:20.659200 NaN NaN NaN - 2015-12-25 20:02:29.961600 NaN NaN NaN - 2015-12-26 10:48:37.497600 NaN NaN NaN - 2015-12-26 21:21:58.118400 NaN NaN NaN - 2015-12-27 09:34:13.123200 NaN NaN NaN - 2015-12-27 10:28:01.891200 NaN NaN NaN - 2015-12-27 20:14:52.483200 NaN NaN NaN - 2015-12-27 21:01:09.379200 NaN NaN NaN - 2015-12-28 09:13:24.384000 NaN NaN NaN - 2015-12-28 19:54:14.976000 NaN NaN NaN - 2015-12-29 10:32:52.540800 NaN NaN NaN - 2015-12-29 21:13:35.616000 NaN NaN NaN - 2015-12-30 09:25:50.620800 NaN NaN NaN - 2015-12-30 19:59:05.625600 NaN NaN NaN - 2015-12-31 10:45:09.360000 NaN NaN NaN - 2015-12-31 21:18:31.881600 NaN NaN NaN - - [5194 rows x 13 columns] - - -Time series plots of grid points -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +Time series plots +~~~~~~~~~~~~~~~~~ A simple time series plot of surface soil moisture can be created using ``matplotlib``. -.. code:: ipython2 +.. code:: ipython3 - import matplotlib.pyplot as plt - fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - ax.plot(h109_ts.data.index, h109_ts.data['sm'], label='H109 SSM') + ax.plot(h109_ts['sm'], label='Metop ASCAT SSM Data Record (H109)') ax.set_ylabel('Degree of Saturation (%)') ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_7_0.png +.. parsed-literal:: + + + + + + +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_8_1.png -The SSM CDR H109 can be extended using H110, representing a consistent -continuation of the data set -.. code:: ipython2 +The SSM data record H109 can be extended using H110, representing a +consistent continuation of the data set - h110_ts = h110_reader.read(gpi) +.. code:: ipython3 + + h110_ts = h110_dr.read(gpi) fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - ax.plot(h109_ts.data.index, h109_ts.data['sm'], label='H109') - ax.plot(h110_ts.data.index, h110_ts.data['sm'], label='H110') + ax.plot(h109_ts['sm'], label='Metop ASCAT SSM Data Record (H109)') + ax.plot(h110_ts['sm'], label='Metop ASCAT SSM Data Record Extension (H110)') ax.set_ylabel('Degree of Saturation (%)') ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_9_0.png + +.. parsed-literal:: + + + + + + +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_10_1.png A soil moisture time series can also be plotted using the plot function -provided by the ``pandas.DataFrame`` object stored in the ``.data`` -attribute. The following example displays several variables stored in -the time series. +provided by the ``pandas.DataFrame``. The following example displays +several variables stored in the time series. -.. code:: ipython2 +.. code:: ipython3 - h111_ts = h111_reader.read(gpi) - fields = ['sm', 'sm_noise', 'ssf', 'snow_prob', 'frozen_prob'] + h111_ts = h111_dr.read(gpi) fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - h111_ts.data[fields].plot(ax=ax) + h111_ts[fields].plot(ax=ax) ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_11_0.png + +.. parsed-literal:: + + + + + + +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_12_1.png Masking invalid soil moisture measurements @@ -291,44 +114,60 @@ Masking invalid soil moisture measurements In order to mask invalid/suspicious soil moisture measurements, the confidence flag can be used. It masks soil moisture measurements with a -frozen or snow cover probability > 50% and using th eSurface State Flag -(SSF) information. +frozen or snow cover probability > 50% and using the Surface State Flag +(SSF). -.. code:: ipython2 +.. code:: ipython3 - conf_flag_ok = h111_ts.data['conf_flag'] == 0 + conf_flag_ok = h111_ts['conf_flag'] == 0 fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - h111_ts.data[conf_flag_ok][fields].plot(ax=ax) + h111_ts[conf_flag_ok][fields].plot(ax=ax) ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_14_0.png + +.. parsed-literal:: + + + + -Differentiate between Metop-A and Metop-B soil moisture -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_15_1.png -The ``sat_id`` field can be used to differentiate between Metop-A -(``sat_id``\ =3) and Metop-B (``sat_id``\ =4) measurements. -.. code:: ipython2 +Differentiate between soil moisture from Metop satellites +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - metop_a = h111_ts.data[conf_flag_ok]['sat_id'] == 3 - metop_b = h111_ts.data[conf_flag_ok]['sat_id'] == 4 +The ``sat_id`` field can be used to differentiate between: Metop-A +(``sat_id``\ =3), Metop-B (``sat_id``\ =4) and Metop-C (``sat_id=5``). + +.. code:: ipython3 + + metop_a = h111_ts[conf_flag_ok]['sat_id'] == 3 + metop_b = h111_ts[conf_flag_ok]['sat_id'] == 4 fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - h111_ts.data[conf_flag_ok]['sm'][metop_a].plot(ax=ax, ls='none', marker='s', color='C1', label='Metop-A SSM') - h111_ts.data[conf_flag_ok]['sm'][metop_b].plot(ax=ax, ls='none', marker='o', color='C0', label='Metop-B SSM') + h111_ts[conf_flag_ok]['sm'][metop_a].plot(ax=ax, ls='none', marker='o', + color='C1', fillstyle='none', label='Metop-A SSM') + h111_ts[conf_flag_ok]['sm'][metop_b].plot(ax=ax, ls='none', marker='o', + color='C0', fillstyle='none', label='Metop-B SSM') ax.set_ylabel('Degree of Saturation (%)') ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_17_0.png + +.. parsed-literal:: + + + + + + +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_18_1.png Convert to absolute surface soil moisture @@ -337,7 +176,7 @@ Convert to absolute surface soil moisture It is possible to convert relative surface soil moisture given in degree of saturation into absolute soil moisture (:math:`m^3 m^{-3}`) using the ``absolute_sm`` keyword during reading. Porosity information provided by -`NOAH GLDAS `__ and +`Noah GLDAS `__ and pre-computed porosity from the `Harmonized World Soil Database (HWSD) `__ using the formulas of `Saxton and Rawls @@ -345,21 +184,26 @@ using the formulas of `Saxton and Rawls is used to produce volumetric surface soil moisture expressed in :math:`m^{3} m^{-3}`. -.. code:: ipython2 +.. code:: ipython3 - h111_ts = h111_reader.read(gpi, absolute_sm=True) - conf_flag_ok = h111_ts.data['conf_flag'] == 0 + h111_ts = h111_dr.read(gpi, absolute_sm=True) + conf_flag_ok = h111_ts['conf_flag'] == 0 fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - h111_ts.data[conf_flag_ok]['abs_sm_gldas'].plot(ax=ax, label='Absolute SSM using porosity from NOAH GLDAS') - h111_ts.data[conf_flag_ok]['abs_sm_hwsd'].plot(ax=ax, label='Absolute SSM using porosity from HWSD') + h111_ts[conf_flag_ok]['abs_sm_gldas'].plot(ax=ax, label='Absolute SSM using porosity from Noah GLDAS') + h111_ts[conf_flag_ok]['abs_sm_hwsd'].plot(ax=ax, label='Absolute SSM using porosity from HWSD') ax.set_ylabel('Vol. soil moisture ($m^3 m^{-3}$)') ax.legend() - plt.show() -.. image:: read_hsaf_cdr_files/read_hsaf_cdr_20_0.png + +.. parsed-literal:: + + + + +.. image:: read_hsaf_cdr_files/read_hsaf_cdr_21_1.png diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_10_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_10_1.png new file mode 100644 index 0000000..1d81b2e Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_10_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_11_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_11_0.png deleted file mode 100644 index 6c3e77a..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_11_0.png and /dev/null differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_12_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_12_1.png new file mode 100644 index 0000000..f2a7231 Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_12_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_14_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_14_0.png deleted file mode 100644 index 52e7d49..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_14_0.png and /dev/null differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_15_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_15_1.png new file mode 100644 index 0000000..3d0b72e Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_15_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_17_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_17_0.png deleted file mode 100644 index 1c6d46d..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_17_0.png and /dev/null differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_18_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_18_1.png new file mode 100644 index 0000000..a830cd6 Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_18_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_20_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_20_0.png deleted file mode 100644 index 958f78b..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_20_0.png and /dev/null differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_21_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_21_1.png new file mode 100644 index 0000000..38ff661 Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_21_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_7_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_7_0.png deleted file mode 100644 index c59bd0f..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_7_0.png and /dev/null differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_8_1.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_8_1.png new file mode 100644 index 0000000..2b24edf Binary files /dev/null and b/docs/read_hsaf_cdr_files/read_hsaf_cdr_8_1.png differ diff --git a/docs/read_hsaf_cdr_files/read_hsaf_cdr_9_0.png b/docs/read_hsaf_cdr_files/read_hsaf_cdr_9_0.png deleted file mode 100644 index 4c13194..0000000 Binary files a/docs/read_hsaf_cdr_files/read_hsaf_cdr_9_0.png and /dev/null differ diff --git a/docs/read_hsaf_nrt.ipynb b/docs/read_hsaf_nrt.ipynb index 77bce84..f7c456b 100644 --- a/docs/read_hsaf_nrt.ipynb +++ b/docs/read_hsaf_nrt.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Example H SAF NRT SSM products" + "## Example H SAF SM NRT products" ] }, { @@ -17,259 +17,224 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/shahn/conda/ascat_conda/envs/ascat_env/lib/python3.6/site-packages/pyresample/bilinear/__init__.py:49: UserWarning: XArray and/or zarr not found, XArrayBilinearResampler won't be available.\n", + " warnings.warn(\"XArray and/or zarr not found, XArrayBilinearResampler won't be available.\")\n", + "/home/shahn/conda/ascat_conda/envs/ascat_env/lib/python3.6/site-packages/pytesmo/grid/resample.py:30: UserWarning: resampling functions have moved to the repurpose package and will beremoved from pytesmo soon!\n", + " warn(\"resampling functions have moved to the repurpose package and will be\"\n" + ] + } + ], "source": [ "import os\n", "from datetime import datetime\n", + "import numpy as np\n", + "import cartopy\n", + "import matplotlib.pyplot as plt\n", + "from pytesmo.grid.resample import resample_to_grid\n", + "%matplotlib inline\n", "\n", - "import pytesmo.colormaps.load_cmap as smcolormaps\n", - "import ascat.h_saf as h_saf\n", - "\n", - "test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf')\n", - "\n", - "h08_path = os.path.join(test_data_path, 'h08')\n", - "h14_path = os.path.join(test_data_path, 'h14')\n", - "h16_path = os.path.join(test_data_path, 'h16')\n", - "\n", - "h08_reader = h_saf.H08img(h08_path)\n", - "h14_reader = h_saf.H14img(h14_path)\n", - "h16_reader = h_saf.H16img(h16_path, month_path_str='')" + "from ascat.h_saf import H08BufrFileList\n", + "from ascat.h_saf import H14GribFileList\n", + "from ascat.h_saf import AscatNrtBufrFileList" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 2, "metadata": {}, + "outputs": [], "source": [ - "### Reading H08 product" + "test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "H08 data has a much higher resolution and comes on a 0.00416 degree grid.\n", - "\n", - "The sample data included in the ascat package was observed on the same time as\n", - "the included H16 product.\n", - "\n", - "Instead of read you can also use the daily_images iterator.\n", - "\n", - "You just specify a day and it will read all the images that are in your folder for this day. \n", - " \n", - "This also works for the H16, H101, H102, H103 and H14 reader." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2010-05-01T08:33:01\n", - "\n", - "('The following variables are in this image', ['ssm', 'proc_flag', 'ssm_noise', 'corr_flag'])\n", - "(3120, 7680)\n", - "(3120, 7680)\n", - "(3120, 7680)\n" - ] - } - ], - "source": [ - "for h08_data, metadata, timestamp, lons, lats, time_var in h08_reader.daily_images(datetime(2010, 5, 1)):\n", - "\n", - " # this tells you the exact timestamp of the read image\n", - " print(timestamp.isoformat())\n", - " print(type(h08_data))\n", - " \n", - " # the data is a dictionary, each dictionary key contains the array of one variable\n", - " print(\"The following variables are in this image\", h08_data.keys())\n", - " print(h08_data['ssm'].shape)\n", - " print(lons.shape)\n", - " print(lats.shape)" + "### Disaggregated ASCAT SSM NRT (H08)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "In our case only one image is in the folder so the loop exits after this image is read.\n", - "\n", - "The data has higher resolution but it already comes as a 2D image.\n", - "\n", - "Let's plot it." + "H08 data has a much higher resolution and comes on a 0.00416 degree grid. The sample data included in the ascat package was observed on the same time as the included H16 product." ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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vSCbh4Eoef3wUu3atpnsPR/tBZMQ+1vw0m/882AMPWxKXD/+Ei3cQ+XEnad+h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1.69999998e+38],\n", + " [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ...,\n", + " 1.69999998e+38, 1.69999998e+38, 1.69999998e+38],\n", + " [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ...,\n", + " 1.69999998e+38, 1.69999998e+38, 1.69999998e+38]]),\n", + " 'corr_flag': array([[0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " ...,\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.]]),\n", + " 'lon': array([[13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792],\n", + " [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792],\n", + " [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792],\n", + " ...,\n", + " [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792],\n", + " [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792],\n", + " [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792]]),\n", + " 'lat': array([[70.99792 , 70.99792 , 70.99792 , ..., 70.99792 ,\n", + " 70.99792 , 70.99792 ],\n", + " [70.99375333, 70.99375333, 70.99375333, ..., 70.99375333,\n", + " 70.99375333, 70.99375333],\n", + " [70.98958666, 70.98958666, 70.98958666, ..., 70.98958666,\n", + " 70.98958666, 70.98958666],\n", + " ...,\n", + " [58.01041334, 58.01041334, 58.01041334, ..., 58.01041334,\n", + " 58.01041334, 58.01041334],\n", + " [58.00624667, 58.00624667, 58.00624667, ..., 58.00624667,\n", + " 58.00624667, 58.00624667],\n", + " [58.00208 , 58.00208 , 58.00208 , ..., 58.00208 ,\n", + " 58.00208 , 58.00208 ]])}" ] }, + "execution_count": 3, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "import numpy as np\n", - "import cartopy\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "plot_crs = cartopy.crs.Mercator()\n", - "data_crs = cartopy.crs.PlateCarree()\n", - "\n", - "\n", - "fig = plt.figure(figsize=(8, 10))\n", - "ax = fig.add_axes([0.05, 0.2, 0.6, 0.7], projection=plot_crs)\n", - "\n", - "ax.set_title('H08 example')\n", - "\n", - "blue = '#4b92db'\n", - "ax.background_patch.set_facecolor(blue)\n", - "ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb'))\n", - "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - "ax.add_feature(cartopy.feature.LAKES)\n", - "ax.add_feature(cartopy.feature.RIVERS)\n", - "\n", - "ax.set_extent([10, 47, 50, 75])\n", - "\n", - "data = np.ma.masked_greater(np.flipud(h08_data['ssm']), 100)\n", - "sc = ax.pcolormesh(lons, np.flipud(lats), data, zorder=3, \n", - " transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'),\n", - " vmin=0, vmax=100)\n", - "\n", - "cax = fig.add_axes([0.65, 0.2, 0.025, 0.7])\n", - "cbar = fig.colorbar(sc, cax=cax)\n", - "cbar.set_label('Degree of Saturation (%)')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Reading a Region Of Interest (ROI) of H08" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "H08 has a very high resolution and users might want to read only data for their area of interest. This can be done using the lat_lon_bbox keyword" + "h08_path = os.path.join(test_data_path, 'h08')\n", + "h08_nrt = H08BufrFileList(h08_path)\n", + "h08_data = h08_nrt.read(datetime(2010, 5, 1, 8, 33, 1))\n", + "h08_data" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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uBF3Cs3gJMg0pGDMMOJesRkpKKr8s/p5XRoyk7pvLKNGgOwB7P2nIrO8/pWvX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\nWq1aFc6dO8iXIZ9SvUZ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WAJ2BOkA/SZLqKBuVXqkvubWysmLy5E/QaNTRjdbS0pJZsyYT\nF5eAVpvPc89VVEX7DZ1Ox0cfTWTSpLGikE+FOnRo88SfBwWNIjU1rZSiER6r5NqI+AFRsixHA0iS\n9AvwCnChRK5WCIrMaQQG9lLdTmebN++gW7f+jB49EdAXCw4f/inHjp1SOLJHs7CwYMOGFXTp0l7p\nUIQSYGFhgbu7G0lJKaxevU7pcITiVwmI/df3cf+8prhCz2mUYCyCIAglLUaW5arFdTJJknYC5Y08\nvAzw74KdJbIsL/nnvL2Bl2VZfuef7wcAzWRZ/qAo8RaHQj2eKs4JJEEQBLWTZfnlEjr1LaDyv773\n+uc1xZlMcZ8gCIJgcAKoKUmSjyRJNkAgsEXhmAAT6z0lCIIggCzL+ZIkfQDsQr/k9ntZls8rHBZQ\nyDkNQRAEwbyJx1OCIAhCgYmkIQiCIBSYSBqCIAhCgYmkIQiCIBSYSBqCIAhCgYmkIQiCIBSYSBqC\nIAhCgYmkIQiCIBTY/wFzkCHLCl4h/wAAAABJRU5ErkJggg==\n", + "image/png": 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PPJOuXbtyzjnn8NprryHL/1+SZcKECdx+++1s37691XvP0G9hhn5Lq+fefPNNTj31VIYOHdri3O23386YMWNaJNz9/PPPOeOMM1q0//bbb0lJSaFt27b7/T4oisLMmTORJInNmzfj9/txOBxN59977z0KCgoOWKYqPz+f6667jvvuu4+UlBQuvfRSiouLm85Ho1G+//57qqur99uHSqU6tilAVFEO63UsUx+JqlR/kjvuuIOXX34ZrVaL2WymX79+3HPPPaSkpLBu3Try8/MRRZHVq1dTWVnJsmXLmq5dtWoVycnJXHDBBbRv355p06axdu1a5syZA8DKlSu56667OOmkk1q9dzCsIRqWQGp+fNu2bWzatIkPPvigxTVLlixh586dXHvttc2Ol5WV8dNPP/HWW2+1uGbVqlW/u/Fh48aNeDweHnroIUaPHs3KlSu56KKLePXVV4HG/HD7Wxv3az179qRnz56UlZXxxRdfcOqpp7Ju3Tr27dvH8OHDCQaDxMbGsnnz5hbpQlQqlepYpwZsKtURsGnTJqZNm4YkSRQWFtLQ0IDP5+Pee+9tsdgfoE+fPkBj0fZ58+bx/PPPYzKZms7v27ev6fFjnz59yMvL4/bbb6dXr16MHz+e8ePHc9FFFzUVVv+t++X8FsGaLMv873//Y+bMmcTHx7e45o477mDcuHEtZrrWrl1L+/btWzwOBVi4cOF+U4P8QqfTEYlEOOGEExg7dixjxoxh5syZQGNB+HXr1rWaS25/MjMzufrqq7n//vu55pprmD9/Pqeccgqnnnoqs2bN4tprr+WVV1456P5UKtWx499b+l19JKpSHRGSJLFw4ULi4uIYM2YMd9xxB5MnT241WPu1999/nz59+jRbgB8MBtHr9USj0aZj8fHxjBgxgoULF/Lmm28SjUY58cQTD2mM3333HWazmauvvrrFufnz57N3795WA8BRo0bR0NDA008/3ex4SUkJ27dvb1ZloTWdO3dmzpw5PP/884wZM4b6+nry8vIA+OKLL8jMzNxvLrn9EUWRcePGsWTJEsaOHctpp52GIAhMnDiRTz75hM8+++yQ+lOpVKq/O3WGTaU6Arp06cLw4cNxOByMHj0agPT09ANeU1hY2LTI/xfr16+nV69eXHjhhYRCoWbt9+zZw5VXXsmsWbM4/fTTEQThoMcXCoV49913mTdvHqLY/Oe0SCTCzTffzHnnnddqbU+9Xk/btm3xeDzNjs+bN4+ePXse1OPHX+8c3bp1a9Os3NKlS5sS8x6qrl278thjjzU7ZrPZGDx4MAsWLGh1zZ1KpTp2KShqHjaVSnX4Xn75ZX744Qc2bNjQ6vlfZsxcLhcPPvggjz32GLNmzWqahSsuLubUU0+lX79+rF69mn379uHz+YDGgGv79u0YjUZqamoYMGDAIY1t4cKFdOzYscXuT4CZM2ei1WoP+GjT4/EQFxfXos/evXsf0jigMc/bL0Xm9+zZQ2pq6iH3cSDl5eW/O+unUqlUxxp1hk2lOkIyMzN5+eWXueSSS7j44oub7cJ8/fXXWbRoET169KCuro7evXs3PaKExvQYI0eO5Pjjj2fs2LFceeWVnHjiicyZM4eRI0fy6quvcuKJJ/LCCy8wevToZsllf08oFOLTTz9l8eLFLc4VFxcze/Zs7rrrrgPO2Hk8nmZr2Hw+H+vXr+fyyy8/6HH8wuVyNT0SLS0t5fjjjz/kPg7Ebrfz3nvv8cknn2Aymbj66qsZNmxYi5lFlUp1jFEg+u+dYFMDNpXqSBozZgwLFy7kvPPOY9OmTfTq1Yvi4mJ+/PFHVqxYwdKlS5FlmVtuuQVJkvj8889Zt24dX331FVlZWZxzzjkIgkBqaio33XQTTzzxBPPmzeOxxx6jY8eOjBw58pBLNK1bt468vLxWk95ec801DBkypNlau4csG5jq6dH0taIolJaWUlBQ0HTsj649g+ZF3ysrK0lOTj7kPg7k/PPPp6ysDJPJhMPh4KKLLiI5OZmvv/76iN9LpVKp/ipqwKZSHWH9+/dn06ZN3H777WzcuJHc3FwWLlxIr169mh7VRSIRzjrrLJYvX05+fj4mk4krr7yyaZYrOTmZkpIS5s+fT11dHUuWLOHGG29k1KhRLXKkAUwtLgXgoZysFudWrVrF2Wef3eL4Z599xurVq5k9e3bTscnePSRYmrdzu91EIhHatWsHNAZrEydOZPz48S36nOzfA8Ajxrz9fn/C4TBms5nly5cTiUQOWJ/0j+jRowc9evRo+nrs2LHMmzePkSNHsmLFihZ1U1Uq1bFB4d+9S1QN2FSqP4HNZuOZZ57Z7/l77rmHrVu38thjjzVL5/ELvV5PQ0MDJSUlnHDCCVitVnJychg1alSr/QkKRMytf5Tt2bOHk08+udmxYDDIDTfcwKWXXto023WHuANCBuoqbWD9/7a1tbWkpqYiiiKzZs3i/vvv5/rrr28WFDWNQ/z9j9NwOEwwGOTCCy/kiiuu+NMfVYqiyIQJE3jiiSc47bTTWLJkSaubK1QqlervTF3UoVL9xZxOJ3PmzOGaa65pNVhzOBysX7+eHj16cMIJJzBgwADuueceLrvssv3ODunauzCk+pjk3tvsuCzL1NXV0alTp2bH77zzTuLi4jjuuOOAxpkxoz6EEBIRos3Xsnk8HiwWC5dccgmzZ8/m3nvvbTVYA1D8GuTA/oMhRVGIRCJMnz6dDh06MGjQoP22PZJEUeT666+nrq6OCy64oFnVCJVKdawQiB7m61imBmwq1V9s2bJlpKent5r2Q1EUXnvtNUaNGsVVV13FgAEDWn2c+Vs6bZRQQIMxNtDsuN1ux2KxNAv0du3axfPPP8/ll1/ebKNBMKRFk+JHNIeb9SFJEhs3bmTLli088MADZGRktDqGqcWlSE4JjXP/GyLcbjcmk4nvv/+eESNG/O77OpJ0Oh2TJ09mzZo1zWqZqlQq1bFADdhUqr/Axo0bmTVrFi6Xi2g0is/no6ysjOXLlze1URSF//3vf9TX11NRUUGPHj0OKlgDcNpNyGGJ+6LNZ9JqampapM24+uqrOemkk0hLSwNg+pYyercrxt9gxGQM8rC2fbP2+fn5PPHEE0ybNg2L5TcL3H5FCgpEEyLIuv1v42poaMBisVBeXt60U/SvZDKZmDRpEi+//LI6y6ZSqY4pasCmUv1JZFnmjTfe4LjjjuOEE07gjTfeoH379jidTvLy8rjlllt45plnUBQFRVF49dVX2bNnD9deey179uzhvPPOa+rrQfNG3khbzpTwrmb3mBwoYmppKfEJnsaFbL9RU1NDZmZm09fvvPMO27ZtY9y4cc3a1frNCFGBSLTl7JhGo9lvEuA7xB3crd3K5NpiQllBREMEMSww2b6v1fYOhwOn00lmZuZRW0eWnJyMTqdj+/btR+X+KpXqj1EAWTm817FMXXmrUh1hDocDq9XKJ598wn//+1/OO+88brzxRnQ6HZs2bWLSpEnMmDGDe+65h5EjRyIIAoWFhaxatYqVK1cycOBAJk6c2KKm54ad2SSmO3lGt4p9RSmNB41g6WCnrtJGXIobfM3HUllZSU5OTtPXTz/9NOecc06zvrUeqGywkduuin27U7ktVMKs1AOX1LrPsBmNJKMNa1AUiM1x4vPrCNUa0WT60O80M9VdisYnIHRxYzKEmOYtQJZl/H4/ubm5h/U9PlxxcXGUlZXRpUuXozoOlUqlOlhqwKZSHQFff/01a9euxePx8PjjjzNq1CjS09MZNGhQswS63bt3Z/LkyUyZMoUtW7YgiiLffPMNX375JcOGDWPGjBl06tSJbt26Nes/KguMLNjGN4UdqPfGomgUDOVawm3DOCtiSMh0Eok2nzAPh8MsX76cd999t+lYUVERZ511VrN27q5hsuOdlG5MRxMR0LqBAxQfmBP3E57NqWR3r2BffSJKWMQLaEwRjKlefHYjsk1GESBokvmlcNXk+mJoE8/Asx6h+LijO7nvdrubHgmrVKpjx7G+ceBwqI9EVf84Pp+PUaNG0b1796bSTkdKJBLhyy+/pLy8vOnYK6+8wplnnsnTTz/Nxx9/zNSpU1mxYgXz5s2jc+fOLfpo27YtycnJ7Nixg+uuu46tW7cyffp0rr/+ej799NNW85u5d8WxvjaDuDgvigCSIYKtby29c0uJSXMTjkhMDzQP8pYvX05eXh7Dhw8HGnd71tfXt1jTJtk1lG9MQ5PrQdEoiCGYvrWs1ff/UdZiKjan0r5XCWXr0jHHBBA0SuPsnqCg00ZITHMipfnR14uY0z1kxDmor4pBtIWIX6vB3lFCDB+dD12fz8enn36Ky+Vq9qhYpVKp/u7UGTbVMe3yyy/nk08+4d13322qTxkKhVi8eDFdunTh0Ucf5a677vrdfjZu3Mju3bsZOXJkq9n7ZVlmypQpvPrqq0050rp06ULHjh2ZP38+U6dObUosCzBt2jTq6ur2W9i8Xbt2fP/9982S1vbo0YPzzz8fm83WrO1kxz7SutTTM7GML1f2QIoLYbX6MWjDhGSJtBgXla7mY45EInzyySe88sorTcdWrVpFampqs7VjL83ahnCuFSEiELAbMHgEpBCErXA7O+meUUGM1s8+dzxl9XFEV+ajJAcp3JSFkhTG+PO6OVkWMJuC6KQoLr+BkEuHJt+PQROltD6OmEQv3r02BBmiBoiY/9rFJC6Xi6+++opFixbRr18/Fi9eTHx8/F86BpVKdXgU/t0zbGrApjpmeTwe3n33Xbp168Y333zTFLDFxsZisVgYPHgws2fPZu/evVx66aXNHk3+ori4mIkTJ/LDDz+QlpbGJZdcwmeffdY0K/WLiooKnnrqKWbMmEGbNm0IBAKsXbuW7du3c99997UoeZSamnrAouY5OTls3ry56esVK1ZQWlrKlClTWrSVnBKRqMguVxIF3fex1x5PqtWNSROmsC4Jsz5Em7gGqPz/azZs2EBSUlJTsfdoNMrkyZNb1O20d7EiZwQwmkMYRRmvPZZQXpD+7faSanCxyZ5OjNbP3p1pZLSrpaLaiNEcJKyLEi03oUuJQEDE4zagN4axGoKIgoI+NkiC1YvdYyJaYsadEEYTEPAnQSAjzKPWNvv93hxJdrudzz77jOXLlzN8+HC+++67ZiW2VCqV6lihPhJVHbM++OAD8vLyKCgoYNOmTc3OXXvttXz33XdMnDiRwsJCLrjgAgKBQIs+JkyYQDgc5qmnnmLmzJn07t2bL7/8skW7xMREYmJi8Pv9ABgMBgYNGsSVV175h+pTZmRksHv37qavFy1aRO/evVvsnLwttJvUgmos+iDxej/VXivOaiuFm7MIRSVijAGs+gCecPMNCg0NDbRv///pOaZOnUogEGDMmDFNxxa3+YL6UQEMphDntF1PQXIFUlBAqjBQaE+i0JXMvpoEMg0OcjtUUV6WgGKOotNGCXu1aDwCXr8eyRZCECEU0lBZa0OnjRAJSkiiTOjnJLraSh0I4MuOkvb1wReuPxxVVVXcfvvtxMTEsG7dOj755BM1WFOpjnGyIhzW61imBmyqY9aCBQvo0aMH8fHx1NXVNTt377334nA4MBgM/Pe//yU1NZXbb7+9WZvFixezZcsWLrvssqaKA6IotroY3WAw8NBDD/Hkk09SXV192GPPyMigpKSkKRdYYWFhixm5p+JXo9FFqWqIIRDRUhcw4fQZkLwSikahqC6RGH2AYFTDxLoBza71+/1YrY31pZYvX84LL7zAdddd16wM1KLtnejfZi9t4hv4sb4NxZ44hE5uImYZr1+PKCgMb1vIh0UFnJ2xDkEbRdRHyLHZSUu3E4qPEt5jIRrUIIgyOl0EvTFMOCJhsQYIRTTIUZFIbIRwQoSYrvWIAZGGTvv/2CksLKSwsBC73X5YedLq6uqYOXMmN954I2+99Vaz4FWlUqmOReojUdUx65eSS5IkEYlEmp3T6XQMHTqU7du307lzZyZMmNCUuPall14C4KeffqKgoKBZiou6ujratGn9cd3ll19OaWkpM2fOZMaMGcTFxf3hsdtsNhRFoaysjOzsbPbs2cMJJ5zQrE2ty4JGEyXB6qWqIYbBbYpwBIzk9iwm2eBhY2066SYne10J3CltZ+avkubGxcWxdOlSbr75Zl555RUmTJjQbCbw+3YfEVPWnh9/7ETvfrvYVJWGJMpEiyzYOtnpEF+HRowyKm4TtUEL39k7IFbrie9cR5nbhlaUwSgjpfiJenRE/Fo0GpmgT0tKkguDJkxpbTwokN+2gt1VSdj3xCFbI8jx+w/Enn76aTQaDW63G5/PR1JSEsnJySQlJTV7JScnY7PZmlVqUBSF8vJytm3bxhdffMFll112UOsXVSrVsUFdw6ZSHaOys7Opra0lPj6eaDTa4vzQoUOZPXs2Z511Funp6Zx++umsWrWq6XybNm0oKioiEok0PYqsra1ttnngt+6++27q6uq47777uPLKK+nUqVOzoOFgCYJAVlYWS5cu5dJLL6W6upqEhIRmbQJeHR2yqtlRlE5impMd9hQyrU62/tCWwlwfucn1bK1Pw+kztOj/+OOPZ9myZaxbt467776brKysZue9UT3+rXEIbXxYtAFOyt3JtxV5hHJ8nNtmPaWBOIKyhk3+bGJ1PgJRLcndaqhpiEGjixD06LAlNe5ODSmACNFCK7ZuDVSWxSH6JBLb1VNXlMDOHZlY09y4TFr0FVru77j/3ZmpqamMGzeOO++8E4/Hw86dO9m5cydFRUXs3buXjRs3UlFRQVVVFYFAoCl402q17Ny5E51OR+/evbn33nu5+uqrD/nPRaVSqf6uBEXZ/26tPn36KGvWrPkLh6NSHbzbbruNLVu20L9//6YM/r/m9XrJzMxsSt9QVlbGu+++y0knnQQ07vzs0KEDe/bsoXfv3mRnZ7Nq1SqKiorQ6/X7va8syzz++OM89thjxMXFcc011xxwg8H+/Pjjj3z00Ufs3LmT4cOH06dPnxbF0O/YVYYQgUB6hJRMO90TK/hmVweMphChbTaEDh6G5jSuhRu5d/RB3fdB80Ya6qxIdVqicRG0lhAhl47EdCepZjc6Kcr6omz+02c5e31JZBrs2CMmqgIx2LR+fijPI93mZG9dAglWL4oiUFkaT0yyB1kR8BdbEQMiSrYfvSGE8KMNT/sIQkjAVCZxb8/9B2wbNmzg1VdfRavVcuWVV3L99de32DX7C4fDwY4dO9i1axdOp5Phw4e3KHKvUqmODYIgrFUUpc+B2nTqrlde++Lw8if2yyn+3fv8Xalr2FTHHFmWufbaa3nzzTfJyMggOzub8vJyVq9ezfjx4xkwYACFhYWYzWZ27tzJtGnTmDZtGjt37mwK1qBxvdrGjRtxOBz06tWLUCjE/PnzDxis/XLdpEmTKC4uZsCAAbz99tt/6H3079+fuLg47rjjDs4//3w++ugjQqFQszb3t88kmBLFnOilpiSO5Xvb0S2rgpNydhBOD3FK3jaWFHZkSWHHg76vRR+kU24FhrYudDFBemWWkZDm4riUYuL1PiyaIBlpDRT7E2hnqmFhZSf8US2BqJaN9RlIkow/oiUSlKiui6HWbkVnCyJJMt5KC/EbBaIZATJf0+D36rEOq0EfG0CICsi6A4+tR48ePP7441x88cV88sknZGVlcckllzTbUfuL2NhY+vfvz/jx47n++uvVYE2lUv2jqY9EVcecSZMmsWDBAk4//XT69OmD2Wxm7NixjB7dOMPUv39/Bg0aRG1tLcnJyVx44YX77ctsNgPw/PPP77dNKBTiqaeeYuPGjUSjUV555RX0ej06nY7HH3+c3NxcSkpKyM4+cDmn3xIEgcsvv5w777yTL774gqSkJJYtW9YsqAQQ/SKKIpCa00CD28SuukQs2iDIAgv2dmJO/3coDiXyRKmT/zoO/IPj7ewkWRap9lgRfrAR6hpiY2U6ZmMQf1RLmsHJensmL+a/wbWFF1DkTqRXQhnfVuTRIb6OWoeFnpnl7HPG0Ta9Fk9IT43diijJ2KutCAK4T/Ng1UawXwMmWSQsi0SjIsZqkVDLFHetfl+6d+9O9+7dqa6uZtGiRQwaNIhu3bpx0003cfbZZzfbPKFSqf49jvWdnodD/dRTHVNcLhcvvvgit956K8OHD296XDZq1CiuuuoqZs6cyejRowmHw0fsns8++yxPPPEEkUiEjRs3cuONNzads9lsjBkzhtWrV/+hvlNTU7n88ss55ZRT2LFjR6uzROYyAUFQMOuCxFr8hEIavt/antMLNmL5ysqkDWfzdmnf373X7i7/I+TSUVVvIxIV0Z9YhzXWh0EfJvBtIvvc8Swo6YQoKIxZeQ1j0jeRbnLRzlTN6Oyt/LQ7hzM7bmRzVRoX5q7BH9Hi/DYFnS6CIgsYyrSIQYFQhRm9JoKnKJYeqeVEZZGkzwz4MqI8kJtxSN+flJQUxo8fz9y5c+natSu33XYb2dnZzJo165D6UalUqmOdGrCpjimzZ8+mQ4cOLXKfaTQaevTo0bQ7skOHDgfsZ9++fRQWFh7UPRcsWMCoUaMYN24cN910E++99x6fffZZ0/kePXo0K1XVmtuqS7hzR+vlngYOHMhjjz3Grbfe2mJzwGTPXjw9Amg1UYpKk+mTXEIkoCEtw84eTwJv3fUI2fH2xtQf76fSpf9/W/Q/taSUGfot1IetWBJ9pCU6CIS05MfXEIpIeLbE4+0QxvluJq4SG7t/yubcjut4r7QXejHC+2W9+LqyI7EJXt5b15duqZV8VtkNqy5I2vBSgn4twnYLmgIn7QtKEWSorY1Bl+1hQ1UGPr8OU02Y1B/EP7RBA0Cv1zNixAhmzZrFVVddxYMPPsj333//h/r6I5YuXcojjzzS6uYWlUr11/hll+jhvI5lasCmOmZs27aNxx9//ICPOFetWsXixYsPuK7sjjvuoHPnzpxxxhlNx4qLi9m0aRMNDQ04nU6WLFmCy+VClmVWrVpF9+7dgcZ1UxMnTuTSSy/lgw8+AKBnz56Ulpa2eq+PshYzXdoOgKzd/3uLj49vUfD9F4kJbiJRCZ05zC5XEqJD27gTU1B429mXGo+FO3p+xYd3zeKmnIFMKS8lps/dzE1YyVS5MSjVaSN8WtiN7Bsc6GfGkh7rxKoJIGy0IuR5mTv0NRp6RUFUOGHIZr6rbUtVrY21tZnUu80kmTz4NsRjivPxU2Eu5Q2xbN+cjawIaIuM6OyQF1/PrnX//1jYbAwS8OsIOgzsGafh1jFZfPDBB394NhIaH5d27tyZvn37tprg+M/yyiuvcM8999C1a1eWLVv2l91XpVKpfqEGbKpjgizLXHjhhZxxxhn7XSvm8Xh4/vnnef/992nbtm2L816vl5tvvpkXX3yRWbNmUVpaSklJCV6vl4KCAk466STS09NJTEzkwgsv5KSTTmLmzJnodLpmu0B79erFDTfcwFVXXcXNN99Mz549qaysbDH78kTsGlbtzaVjcg3EhbB2rz+k9/xYzDqQFGprbHgdRlDAE9IjaxT6d97Duak/EZC1fNHzJdZ4crlh79l0XqvBWCXwo7c9VcsyiQY1nDXiRwyaCLEWH5XPWpHvqsesDWEPmRl/7td0Ta/k2gUTSFsm8MopLxKr9VNlj0Fx6KgvjqNDUi21PgsnnLyROLMffUyQSKkZjU+g0mHD3LuexNFlFNYmoc91oySEEFxa3F4DgigjGiI8kpQDNM4m7q++6qFwOp3k5OSwevVqLBYLY8eObbFh40jy+XycffbZDB06lHHjxnHuuedSU1Pzp91PpVKpfksN2FTHhB07dlBcXNy0saA133zzDYMGDeLEE09s9fy4ceP45ptvmD59OikpKbRt25bvvvuOZ599lry8PJ566ilef/113njjDebMmYPFYuHLL7/kvPPOa9FXt27dePDBB/nggw+YO3cuCQkJVFVVNWvTL6mYblkV2INGeuSW0VBn5bnEH3/3vS5t+ynzUr7DZvCTlmonNtHD6d02Ie+xULcuhZgsFxoxik/W091Uyje+NthDJgYmFDHMtp2Mb9y8urE//nYhkpKcbPhPN7SPJ1DXYKVPSikltfH4IloMUpgt7nQKbGU8PPJdLP8p42tXFwpdyVhMQTrO83DugFVEZBGbwU+pN5Zkk4eQX0t6typkvYLVGKChzsqevSnEW3wEi630alMKcSGiUZGIX4sg/X/qoPT0dERRZO7cua2WCjtYdXV15OXl8fbbb9O9e3f27dvHhAkTgMaZ2CM9C3biiSeyfft2hg0bxuOPP47D4SA/P/8P7xBWqVR/hEBUEQ/rdSxTd4mqjgmSJKEoyn7XQMmyzOLFi3nttddaPf/GG2+wceNGHnvssaa0HVqtlnA4zPvvv9+sMLwoioiiyH/+858DjikhIYFbbrmFe+65h5iYGEpLS8nI+P9F9fOLuhCuNKFoFVK6FZGZXo9F2/os0D1ry/DmRpFiQ5wMpJlc+KNavGEdsiywsjoHoY2XtHgnZVvScMXa2eZLp5elmPHWOr5zhviouAfhLA3Gx2v4JPtTxm+8DMeGJLIf39X4PfKbWbq7A7YYH8lGLxW+GIrr4+maX4FWiNAzrozuplJcESPxeh/rRnThP5bdfFrUjUs6rqYqaGOjPZ3uOeXkWepYkmuktsaGqI2iMUWp2ZyMnBRiQ2kGWkOEkFuHoJWJtfnA+//vVa/X079/f/R6/QH/TA8kHA5jsVhYuXIlAwcOpFu3bvz3v/9l0aJFXHzxxQQCAf7zn//wyCOPHHLfv/bL36t+/foxZcoUotEoFouFq666ikGDBjFx4kR0Oh1nnXXWYd1HpVKpfs+xHW6q/hVKSkqYNm0aTqeTYDDY7NzixYtZsmRJUxLbESNGALBz505effXVpnZ33XUXl19+ebMca3a7naysLDwezx8uM5WZmcm5555LZWUlKSkpzc6dkrcNJSZCt87F7HHG0+AxsXlNHo9+VsoLSSv4ImcBM78v4/GPSwBQNArRgMRX27qw25lIqSeWOpeFJIsHt9+A0RCivC4WMShQ6oplWXk7euhLed2diFUT4Ob2X7PemUW118q1Oy9E/1Es4fQQa7e0oSFgpM5tJtbmJRjW8NPebJKNHvTaCPaImRWeDiTrXHzt6MwX27vyw548ck/Zy2pvW4ZkF7HJlcnK6hwSDD7yLHV8vLkHoYhEpzYVnJa/lZzEBvRtXQiSQjSoIdRgwJboQYmKTPM2L7guCAK9evXC4XBwzz33tCgrdjAEQcDpdLJ582by8/PZu3cvgiBQX1+P0Wjk4YcfZs6cOQSDwaZHpQ6H45A3DQwbNoxLLrmE4cOHt8jP17lzZ2655RYuv/xynn/++T/0PlQq1cFTABnxsF7HMnWGTfW39dprr7FhwwZWrFjRVFLKYPj/MkxLly7l888/p127dpx22mmceuqp3HHHHXzyySdNuzZTU1NJTk7GbrfTo0ePZv3b7XZyc3MJhUJNpakOxtOv7eP6S3Kbvh45ciQ9e/YkKSmpWbvjd5/JvrzlVLhjyI+vYVN1OtpsD3WpGhpqEyjX2jCOqqOiwoboAyEqoLWFiQQlGr7IIGPcPiRJprQ+DgSwGoJoNVE87aLEGAJkWRw8UT2CGr+Vqdlf8rWnC5enfccSZxd2u5PYflIAoyGMUR8m2+Kg3B6Ly9NYkF1vDLPHmUBuXAM/VLchFJV4vNP7LK7pRPY7GorPltGIMilaF8W+eDRilBvbfcNdq8ZQlmAjO72eHIudDdUZGKQI1W4rOm2UmEQXLr8eQQCPt2XJrF+Li4vj2muvRaPRsHbtWrp169asruuBxMfH8+mnn2K1Wnn99ddZv349r776KsFgkLi4OBITE4mLi2PcuHEsXLgQk8lEMBhEp9ORl5fHwIEDGTlyJKNHj95vouSFCxeyfft2nnjiCerq6nC73UiS1KzNL0HbY489xl133cX48eO55ZZbSE9PP6j3oVKpVAfr2A43Vf9Ymzdv5rrrrmPr1q2Ew2HmzZvHQw891HR+z549vPnmm3z++eeMHj2a9957j2HDhrF69WrOPPNMnn/+eQoKCigsLOT111/nuOOOa5ZsNRqN4na7ycrKIhwOH3SgMNm7h+Jzotxv2tR0TBCEFsHaL6q9VoZnFLKmPIuhmbvpkFRL96xywn4twd0xdIirRdRH0WV46da5mDirD1ucD2+Gwo6N2Qjf2xiUs4echAaqN6Tg8euxmQJU2WPwhPV0MFfTN74YnRAlqojsDKbhihi4KH0VnTKqCO6zMih1L1V+K1nxdsJ2PbE2L36ngXOz1pFhcuAJ6MmzNfB63UB27k2jdKSIyeanPmBipSOPrtYKjFKYdyr7oXi11O6Np7QynmJPHLIisLk8jXBEwuPVU1kWh89lQFFAkmQEcf+F3qExz5osy6xbt45AIIAsH7j9L/r06cN3332HxWJhwIAB7N69mzFjxlBRUdGUmy8rK4uvvvqK2267jccff5w33niD2bNnEw6H2b59O1OmTKFdu3a8+eabrd7j4Ycf5tRTT0Wj0ZCamkr79u1bbde5c2fuv/9+/vvf/7J27Vo6dOjAmDFj8Hq9rbZXqVR/3L85rYc6w6b6W1q0aBHdu3fnyiuvbDqWl5cHQCQS4dlnn+Wee+5hx44dPP7441xxxRV069at2UyZz+cjNjaW+fPnt9g44HQ6sVqt6HS6g55hu0PYwStD3+Dh4lPoFlsJhd1/9xqXX89XJZ3Ijrfz1e5OpMa7aBtTT8ecSoqqswnJGoQGHXFJLjbvzSQpyYkoKLTrW0L1+zk4+wdYvrs9cbFeErvXUl0bgzXOQU1tDFsrUkkyeHCHDZQF4qgPmsk0OhgVt4XaiJUTk3aSdYKdzfY0Khw2QvUGFBHCEYnUNAdPbxpCu9RaAOoCJjZWpBO7VoerrUJKjBtvqHHmaa8/kbDcOLNky3CiKAL6j2PpfF0Vi2o6YbEECIS0hF16BJ2MpI8SDOiIeDWIht9/BCmKIldddRUAzzzzDEOGDPndnaTDhw9n48aNVFZW8uabbzJ79mzi4+PRaDScfvrpAKSlNdYc7Nq1a1NAHhsby4wZMwBQFIV169Zx2223MWfOHJ5++mn69esHwNdff82aNWuaNjIcjHbt2tGuXTtcLhfPPfccV1xxBe+8885BX69SqVQHogZsqr+d4uJi7r///qb/xH/rq6++IiUlhQkTJpCfn8/VV1/dlCft1/x+P6IoUlxc3KKCgMPhICEhAWhcwK7V7j9J2qyvSonZF0RzY5TrXplI7rM7WfNOFh9Hd/GQ1Pqsyy+SrR5KNqVj6x7AZAzRO6GUoKzBGTASiZHZVJ5OQvt6nD4DglODx6on4NUhCAqBRDDuMHDtxZ/zaVUBba11rI7msGdrBsYMD+mxTpwhI5U+K6JgpXNsFX5ZS3EokUJfCr2sxXgjeiRRRq+NICT6Cbr1iGJj1YSkdA8NARPDsgr5YmlfpIBA4EQ3AzJKWV2Sg1YboVpr4aeabAa3LaLGa8HZYEGQZLwn+1n6ZS+k/MZZpEhQonOHMopqExEFhUC1idgsJyZdGJwH/BY1M378eAwGA4WFhWzZsoUzzzyz1XaSJDF58uSm/HdJSUns3r2bffv2Ne0SPuecc+jevXuL2dPCwkIaGhro378/vXv3pqCggEWLFjFy5EiGDBmC3+9n9erVXHHFFRiNxoMf/M9iYmI4//zzefLJJw/5WpVKtX+KIhzzOz0Phxqwqf525syZQ58+fejTp2VdTJ/Px6effsrChQu56aabyM/PbzVY+6VtYWEh2dnZLWbQnE4nsbGxAFgsFtxud9NjzXkp3zGhejAAM/RbMGBDu2EPUTmLQE4Y7ztW7sibz/u2frB3/wHbZP8e2ooyyZ1r0YpR3PtsfFLbk9SlGmKvLCGcbUcSFBweI5LU+CgwGhWRAxrqa2LQGkDwwRvFx+ELadGIMpElCeSdXkq9z4xFGyIQ1VBeFYeolUkzudntSCCcIHF58neEFImvQl3RiDLePTa0bgGNQcEhWHDUWLElubHoQyz+sB/EKlw9bgF7/El8ubUr5pgAgYCWbtmV2P1GSjyxBCMa2mTWYNKE2VWbRNiikJNgp6QmgRibn+370gGFhCQ3cpJAJCpxi/P3ZyF/LSamsdhocnIyXbp0IRKJ4PF4mv6sfuvXlSG6du3abGbOaDS2WLcIjbtUf70WUqPRcOqppzJ48GAWLlxISkoKF154IRaLpcW1u3fv5tVXX6VLly4MHDiQrKysVne5arXaPzUvnEql+vdRAzbV30Y0GuWdd95h2bJldOnSpdU2CxYs4Pjjj6dXr158+OGHPP744/vtz+/3U1hY2GoSXUmSmtZLtW/fnuLi4qZHrgCvpHyP3W8ifUwJ3tN6UvxyJuv6v0xAifJg7SBMQogVHxewNKGUh35TTgog0OMxbDtHUlSazPk91lAdtFKcEo9mjxlHB3B8m0MgLUJKpp1QnRExIKLEhgkHNehjA4T8Wqzd61G+SCAsi5h0YcocsYTiIDw7Df+ExjVmUVkkMcGNURfGpvVjt5vZQio31Z5HjCFASXkiOlOIhI511JTHIWhliAqkptupdVjwb4ontkzBmxulNBDPTmcyJmsAb5kVgGBbDfkJtUQUEY0oY9KE2bg5F0SI3yFQlRsD5QbsNi3JGXacXiP1dVZEjUykwgRph/I34P/FxsYSGxvLihUr2LVrF5deeukf66gVOTk55OTktDhutVo5++yz93tdKBTiySef5JJLLqGyspKHH34YvV7PgAEDGDhwYLOULna7nfj4+CM2ZpVK1Ug+xtehHY5/79yi6qiQZblFgtlfPPbYY0yaNIns7Gz69+/fapvS0lJOPvlktmzZgtVqPeB/il6vl927dzcLxH7tlxQP559/Ph9//HFTIldnyMBx8fuo25REzvcanG0kggEtXRZch0GQmJL0PTOLR+NrH0LyCUxuKObL3C9xFjxJbJ+7uJ2d5OurcO+O49yCtXxT0YGQrOGkdjtI6FlDuJ2fUKyMzhZEEmUwRhHTfUj1WhSPljZJ9Ui6KDopirOjgt1hRqeJ4KqxYKqE+iu8BOuM1Dit6KUIGkmmc2wVQVmDRh8lEhUxasPE6f10zKkk5NFhfDaOtKwGACRjhKqKOJRqA5FcP+2v2Y7kkehoqiIqi3RLqSK5bT1SQGBlZQ6D4wqJ0fqp9VpIMngwF0sk5zTgaguhIiuKCHl5VWTbHETCEjpTGNmtRZPuO+i/F/szYMCAQwrWKisreeWVV3juuefYt29fq2327t3LzJkzD3ksiqIQCAQYPHgwr732GpWVlbz44otIksSMGTOYPHkyb731FvPnz+fNN9/k+OOPP+R7qFQq1f6oAZvqLzVr1izS0tIoKioCaJa7SlEUkpKSuOiii5oVd49EIuzdu5evv/6anTt30qFDB6qqqrBarfu9j8PhQBAEysvLW51hKywspKCgMT/Y5ZdfTp8+fXj99dcBuMnely7bLyb9uyhfLysg9fEVGLYaObvXWp6xd+YFe08GJezBVKijzeBi7jzxU9L1ThoiFt6tP46wR0dVJAZZJ5Otr8cb1FHls7KwsDNJJg9GU4jUjrXkJdfhDeoQHVpESSGaGAYF9tXHI4dFfCEtUrqPlAQX4ahEWlYD8eeUYjUEyW1bTbzFR43bgj+sZW1NFkWuBEa02Unf1FIsuiAmTQiN0DiLWDlAg04TwZbgQaOLoLWEaF9QijXGz/b6FLRugZ9cuQxN2YUoyOg0EQQZEsxevrN3oJ2pFp9fx5Jt+WSeUkwoKhFJDhGJi6AkB6lxW9lQkonV6ifUYECKCRPyHtzO2wMRBIHVq1ezZs2ag2ofFxdH//79Ofnkk8nMzKShoaHFztPc3FxuuOGGQx6LXq9n4sSJXHTRRcyePRtJkhg1ahRvv/02NTU1zJkzh4yMDILBIGeffTbPPvvsId9DpVLtX2Pxd/GwXscyQVGU/Z7s06ePcrAflCrVwTjrrLP46quvSE9Px+v1UlNTw6WXXspLL71EOBymbdu2dOjQgcGDB7N161Y2bNhAaWkpKSkpdOnShUGDBnHbbbdx5plnEg6Hm+0i/bVNmzbx5ptvUllZybx585ql9AC49957mTZtGsOHD2fNmjV069aNHj16cPvtt5Obm9vUbrJnL4oMCNCuTRUaUSY/ppqgrOGbr3phroBzr1+MhEKixs3X9k6sLsmhc1oVnrCOopIUYuK9mHRhuidUsL42gxhDAEfAiMNlIhrQEJ/kxqgNE45K1DvNKBVGUrrUUFEajyA2zohlJNnxhnQ0NFgwWYIkWLxUNtjQaiME/DrSEp2NZaOiEvV+MzaDnz01ieh0EbwVFpJyGwjLElkxDgprkzAbQviDWjLjHBTXxROqMZLdsZreCaV8uq07CXEewrJE27h6ZEVgS0Ua4QYDikbGWKIl0DaEEhHQWUNoNpkJdfGjKIACclQEt6apfujh2rNnD6IoNvtz2R9FUXA4HE2JkF944QX69OlDz549m9aarVy5ku7du2Mymf7QePbt28eTTz7JKaecwgsvvPCH+lCpVM0JgrBWUZSWC5d/pX03ozLns5Y/gB+K0/K2/u59/q6O7XBTdcx49dVXad++PV9++SUzZswgLy+PK6+8kueee45ly5Zx3333IcsyK1eupFOnTrz22mvodDpmz55NTU0Ny5YtIykpieLi4qa8WxdddNF+71dcXIwsy7Rp06ZFsGa329m3bx+nnXYap512GldddRX5+fk4HA4WLlzYrO0jljaY92jJe0ehzmtmVpsPGRKzg+pADANO2oK9fxCTGCJR46YhakYjyERCEtVeKyUrs1CiArEmP6GoxC5XIt6gDlfAQKzBT9SuRzJE8Pj11Dis1DVYSI13oXMKjcGaRsFcqEXSRinZnYLDZUJx6PDUNa5dE0SFjkm1aPUREo1eREGhIWDCqg/gj2gxm4Kc3mYLpjQP8SYfobDEzppkJFHGH9QiKwK7y5IRRQUxLkRBXAU/VOURG+sjLEskmT0U2RPQCDJhnxZ0MkJAItg+AD4JyRBpzCcXrxC165CdOqJ+DUQFsBy5rP95eXkkJycfVO1Rt9vN/fff3/T1VVddRc+ePVmxYgVPP/000FgF42DzvbUmNzeXW265hc8///wP96FS/ZOtW7eO+fPn8/HHH/Phhx/icDiOUM//7lqi6gyb6k/3zjvvcN1113H11VfTvn37Fo8y9+3bx4wZM8jOzmbr1q1A41q3XwdaAwYMQKPRkJ6eTkpKCn379m220++3XnzxRVavXs0JJ5zA+PHjm517++230Wq1DBs2jAceeICHH36YUCjEzp07SUxMJDMzs1n7O4QdxCwwI0sCOq/CJdM/J0NrZ17lIPrEFmORAqxx5jIifhuLGrqwx5lAssnDtspUru36Ld/UdcQd0rOvNInMzHpcfgOuEhvWLBeuWjPpWQ34w1o8Xj0Wc5DAT/GEOvqhyoAYATkjQHqyg1qXhRhjY9AiCFCzL562HStwBIxoRZn2sbVsa0gh3eKiwhNDnq2BtfuyuKJgBQurOlFRb0O7xYy/TZjc7BqSjF522RNxu40kxHoAGmfg6pIIhhvLS0nWMIIoE602os/wEvA0PuYURAU5JIEsIPpFtOk+wn4NQq0eRaswKyX7D/5tad3cuXMZMGAAPXv2/EPXK4pCNBo9pIoWByLLMpdffjlz5syhvr6e0tJSOnTowEUXXdSULkal+rf5+uuvmThxIg0NDSQnJyNJEm63G6/Xy4svvsi4ceP2e+3BzbCZlMc/bXdYYzyj7eZjdoZN3SWq+tMVFxdjMBhIT09vdd1Zbm4uL730Etdeey0rV67E5XI1lZm69957gcZ0Cvfee+9+Kwr8lqIoOJ3OZkXdoXHn6JIlS1i4cCFjxozh2muvRZKk/aaAAJheMJ+tHTJZO7EHu67R0EVfTlXERkdrNVVBGxWBbE5L3IQjasIohZFEGZMmRKLNw0pHHu6QnvKGWDq2qUQUFOxfpxEz0I7HbcCW7KFybyJdOpWwLxJPhtVJYRc9QokJBBByfUTdOsr2JCG5JNx5EHDrISgi2kL4wjrsdjMFOeWsq8okHJbY5ddzRtvNfFxYwIC2e3llywC02ihhtw7LcQ34i22U1cciJCo4HSa0+gg1VTZS0xzsc8ZhM/mxf52GEgOKXUPP4wvZaUzC4zagNUYI1xtIzGmgflcCWqdIMDmKvMeMYpZR4sI8Ym59k8fhuOaaaw6qSPyiRYvo1q1bU9LcXwiCcMSCNWhM9jts2DDmzJnTVAZr5cqVTJ06lYKCAsLhMLm5uXzwwQdH7J4q1d/Zgw8+yEMPPcSECRMYOHBgsx+4N2zYwOWXX87ixYt58skn//C/xV9qif5b/XvfueovM3nyZK6++mruvPNOqqurW20jiiI9evRgwYIFXH755U2JR395RGmxWLDb7Qd9T0EQ6Nq1a7M8XdBYf7RPnz7MmzePDh067Dd9yK9VR2x8VFjA3jFmYmJ9XLr8CvJ1VfQ0FZNjrGNs0jqytPXsCyTyn+RlDEnejU3rx6AJUxcwkWLyIAgKFU4bJk0YX9cAgqCg1OvxFMViTvWwbVMOSRYP2zbmEKkyostzo6QFCDcY+CVO6XzcXkRRpqBtKdltaxAlmUhUxBrjZ1t1SlM5qIw4B58VdWv8vcFBWoITSZJJz2og9GM8sdsl9PoInqAesVpPqN6IKdZPw0/JiChoxSgJIyrQdmrMeLu1JgXh6zjkqEi43oCilanfmYhslIkYFYSQQCQ1BIoAoT/nI+XNN9+krq7ud9vpdDrMZvOfMobfuuSSS7jrrru49tprueCCC5gyZQpz586lX79+dOvWjW+++QZo/IHlsssuIyUlhZEjRx7Uo12V6lghyzIXXnghzzzzDPfeey/HH398i2UoPXr04KGHHuLbb7+lb9++TZvOVIdGDdhUf5ry8nIee+wxFi9ezE033USvXr3Ytm3bftunpqaybNkyzGYzY8aM4dxzz2X69OlA43+OL730EsFg8KDu3aVLlxY5taLRKPPnz+fMM8/k7bff5uKLL246dzs7W+3nQfNGnlk3lIvzf6LNcSU81PUjtBU6xnxxE7evHcsPDe34rLYn6/25dDGV86GjD2WBOE6K3cL5GWsYkbKDPY54Qh4drjozex3xyAGJ4Jp4rLlOLG0dhCMSiW3rKa5MwJTtRpPqR7cshk4ZVWCMIDVoSM1pYGtZGhmxTrZWpFJSnkiX9Cp8IR0upwlFEQgGdCTFeGhjbSDo0xKoM/Lh1wOo3JiKLAt4gzp8aTLO/gFiTX5qa21EzTLIYP4shlBOEBmBmkWZOP0GbKYA5HqJRCQ8A3wQkLCmuxFkAckvIHolohYZJTaMWKcj94soj8TlHtSfz6HKy8trqhHaGp/Px/r16xk6dGhT8t2jwWw2c/zxx1NfX8+oUaOYMWMG3bt3p7q6mltuuYWtW7fyww8/HLXxqVRH2rRp01ixYgX3339/s1yEvxUfH8/06dPp0KEDffv25e233/4LR/nPoAZsqj9FMBhk1KhRzJs3j+uuu46UlBS+++67A9aIdDqd7Nu3ryl/1ZAhQ9i7dy+LFi3i7rvvJj8/nzlz5uDz/X5+r4EDB9K5c+dmx3788UeSk5N5/fXXOf3001usNfoiZwFf533W9PWdO8oAuLLHD9SHzSzMn09UEYlYZBae/jgxy01srUwlTudjlaMNS+352DQ+it1xTFp9DtVhGx31lWTbHOCTECICOilKcrqDE0ZvQCPJuCqthHxa6gsTQYBgUENyrBtnB5kyl43sjHoM7Vx4g41rxwp3p9MlvQqdOcSGndl4HUasMX6ixWZyU+qwe03YQybkkERClgPLPgGNTyDB6sVZYwFRQWuIUOuycGKnHRAR0CYGqBkYJSbWR/3eODqfUUh+Qi2ioJAS5ybk0WExB1AEcFdaMSV5CSVFkOPCiLYQYkPj2EpO/nNWWOzYsYMBAwa0Wj5MlmWCwSAej4ctW7b8Kff/I3788UcWLVrEW2+9xV133cVll11GXl4e8fHxNDQ0HO3hqVRHxCuvvMJLL73ElClTDmrXtSiKnH322dxwww1cf/31XHHFFYdcESSqCIf1OpapAZvqT/Hpp5/i9Xq58847efDBB3nttdd49tln97sGbc+ePSxbtoyamhoGDhwINJb3ufDCCznvvPN44403+OCDD8jOzmbKlCns2bPnkMe0ePFitm7ditfr5bTTTms6fvKgWwm5dBilxg+O4q4v8Vn2QsQw3Nx+CV9WdGGbM5WzikaSoXFw3pAfeax6JAOuXIu4xcLXywuYkPo9A2xFzNvRn9K6OAzGEFvd6Yw1e9lRm4w10023TiXUbknCsSGJSn8MsiJgTfWgBCXSOldjsgSJ1Btw+Q2I8UFsP28wkGUBd5UF2aOlT+e9bK9KaVzgHxKR6rV4fXqkbC+l9XH4/DocQQOCqCAJCoIC2YNL8AT16GJCiGGBoEOPzeRndUUOOqdINCwiGiP4AzpO77+ehqCR7XXJ2L1GtGIUU6wfZ0UM+ioNRMHnMoCogEcDVQYkv4BskhuPHWE+n48vvviCcDjc7LjH07hJ4qOPPmLx4sUkJye32FxyNF166aWcc8453HvvvWRnN27AkGWZ0tLSpvx/KtWx7KeffuLmm29m0qRJJCYmHtK1Xbt25eGHH2bt2rX06tWLwsLCP2mU/yzqpgPVQamrq6O8vJyuXbsiSdLvti8tLSUjI6NpLYMoivutBxmJRJgxYwbnnHMO69evb/ZI6/jjjycxMZFbbrmFBx54gJSUFCKRCKtXr95vBYP96du3L+np6Vx22WXNZmu0gsTYXusBeCB1BR950iiIgU2uLrxx/skkzqlvzPAvBXnP0Q+TGCKo0eCPaul9yjY2v9uZ+3edxuP57zKj++dM33AGvdPKcISM3F7TnWSrG4s2xLaKVKLxEbLeg/ICGzk2O9sqUxF0USprbcgRCX2dhJCpEPVpqHLEoNVEMerD+MMiil6m1m9GUQSMliDegIbsjuXs2ZuCIdFHMKihQ1oNgYiGpBQnkigTjINdpSmNwZU5QmrHOjRSFE9QT2asg70dJTJjXZSUJpKZVscWRyol6zLQ5Hkac7TVxhOtNiIAYZuMolMQ3FowRBFDAkgKkl8gbBUQQkf2p9f6+npsNhuTJk0CGh9p+/1+9Ho906ZN45FHHmHs2LFHdDPBkXLccce1OFZWVobJZKJDhw4Eg0Eef/xxXC4X4XCYaDRKJBJpeqWnp3PKKafst+KHSnW03XPPPZx66qm0a/fHdm3abDamTZvGZ599Rr9+/Q7qGgXhmE9+ezj+fp90qr+d77//njPOOANFUejXrx+ff/45Ot2Bs9hv2bLlgOsZfq2urg6LxUJBQQF79+5tcT4/P5/HHnuMkpIS7HY73bt3/0Nlf0aPHt3s6zt3lJH+XYja7rncm/I9URTO3XUmJybt5Ja4vXxwSg07u8QjletIjXdR7zbzcI+PiBc93FE0jvK6WMymIM/d9BSXvXoDF9VdhdEcpFNqNbFaP2ckrqcwkEan2GoWLelNu+OK2VGUTtkwDen6IBuLsjDGBFAMYDYFsRqClAWSCDpMaMwRwhUmUjtXYfeasGa5CIY1iChEwyIGvYJojFDhsJHXppoGnwl/RMe2XRkgNCbb1WijdDqpiI0b2yDIINh1VHkS0Kf6CPm0OMpjiM90Yp+fjsEGe8Vk8EmYawW8VhP7whJRlw4kpXFDgSlK7AYtrvYymgYNUYOCdY+IN1NB4xOIGo/sDNv8+fPp0KFDU9CyZMkSHA4H5513HnPmzGmxsPnvrq6urmkTzLnnnsuuXbvIy8tDFEUkSWr26w8//MDcuXOJj4/nyiuv5Jprrmm1GP0v1q9fT/v27Q/YRqU6UoqLi1m+fDlPPvnkYfUjiiJjx44lPz+fu+666wiN7p9LDdhUByTLMhMmTOD8889n4MCBTJo0iW+++YZRo0Yd8LpQKPS7Qd0vPB4PVquVaDS63/+ETSYT+fn5hzz+/Vnc5gvY0YOSKyLs9KXyWCiWc2N/4rV2H/GFN5sH6zuQZXWQ1cWBKCjcnjGf89ZchVX0s8afx+Q2C/kqrjtb7GnMqTiJuONqMGpDnJS6ndJAPF8u6414osxXRZ0ZmrubuG61NPhMWBJ8xGQG8AT1CBoZjSQT8OmQRKVx16YlTGK8h5oqG9pUP3XfpKMd0ICjxoohNkBJdTxUG/A06JENMhFJYW9ZMhpDmLQkJ96QDrfbiKSJggDFzjiS8hpzvwWdBnTWIJGwhBIRkVwSDftiyT6tgop6G4pHh9YpEe7rwaqL4LabMO/W4O0cQl+sIwiEYkDRyciyiBQQ8KVC+9fs7Dkvngdzs373+36wZFlu8Yjz5JNPbvr9sRasQePfc4vFwvbt2/nmm2945plnMBqN+20vyzLr16/nnXfeYebMmYwZM4Zbb721xSPV//73v7zyyisIgsDYsWOZNGkS3bp1+7Pfjupf7H//+x+9e/c+YHnAQ3Eon+3yMZ789nCoAZvqgF577TWi0ShDhgxBFEVEUTyo9QopKSkHvXU7OTmZ6upqZFk+rAz0h2J62iIKf+hMxkn7WPhpPxQR+l1cRBdtgL6GYta422DT+dEIUZYWt+djay9ObrOdV2uOxxEyQgI8nb6am+jLqpocjksuRiNGqQraaG+s4eKznuaV2hNAgJFxWzBKIfZ5Gzc5bKtMJVJlREgIkhdfzz4xjobiWJLbNCBHRZw+A6lpDqprYxB6eRiavpevnF2IhCXMliBRUwhftYWYZA+yIuCrtZKaXg+Ay2lEjojIUQGhTo/StnFdXqDBiMYSRhQVrGYfAYMWT0RE0Mp4QzrMpiAOjw5BAcMPFjzZCsSF8bSPIHglwrEyxmoRRQKNQ4MiKmi8AhETVAyPR+s+cn82wWCQO+64g/vvvx+9Xg80LuL3+XwMHz78yN3oL7Zz50769+/PrFmzGDJkyAGDNWgMSnv37k3v3r2prq5myZIlnHDCCbRt25aePXsSFxdHYWEhS5cu5ZFHHiEcDrN48WKOP/548vPzuf7667ngggv+lo+MVce24uLig36Cojpy/r2hqup3ybLM/fffz9lnn40oijgcDpxOJ+3bt//da1NSUnC5XC2O79ixg3Xr1jV9rSgK1dXV+Hw+OnXqxI4dOzhQ9Y0jIbnvHQz+/FYqrgqx97F8Mr/xkfZjmBsWXcKusId8rZlO5gr8US1b7GnEmf30NBXzfVUesiIwLHEHb+zrS8HqC1hQ1IkuCZWsb8hg8ZvH8enmAp7dNpi36wcQq/XTM72cp/YN44ud3aj2Wil1xRKuMaLYwiiKwJ6GBOKMfpLbNFBTYyM5yUUkpKGyNB45KBEJSny5uRsmSxDtdhOCoKDVRNG4RCRJJhyWkFL8aMUoiiKQGO9B1MqkJLpAUAhHGtcbdu9YglynR5JkGuotJFk8SOYwMfFe6ktjcRbHggKhxAjRoY3515JTnYjGCFJARI6NEIpVCCbIWErBUCcQtipIAXC1lY9owKbX67n99tubgjWAdu3a0bFjxyN3k6Ng8+bNnHjiiXz00UfNZgsPRkpKChdddBFz587lxBNPxOv1snPnTlJSUrjnnntISEggNTWV8ePHM3fuXPr06cOMGTPIyMhg0qRJB7WzWqU6WJWVlU31ev9K//bi7+qPXqr9evbZZ4lEIvTp01jF4+uvv2bEiBEHzIf1i0gk0uKxVUlJCY8++iiKonDqqadSX1/P7t278fv93HrrrYwcORKHw4HX6z3gWpzp28owl8HUkzL322Z/3kpfRtHm8xnccwf5lipeGjOIjBQnllv16JJ0LPO1J2Qq4idXLkWORBw/JuPPjHDT3ovRxAfYJSYhI2DfkYCSHETxaNkVl4RGkAkd5+H0vB3scCWzaF9HInstRGIjnNJjM/UeM7V2K9GgRGbHaupcFkKlFtIzqymqTiTGEkDURjFpQ8Sl1bBjVwaCCHJIom1ONQYpwvbYGAKlMYhxIXRtPfgCOkzGEEPSd7PbnURpXRzxMT7ksIRjZTKaLh6M+jDeoA63To8QH8TrNCBqZOx+I0ZTCI/HgBQTxmAMYTUEqbVb8VZaIDaCWRfEnBakuDYDqUaLogF9nYg7t3GjAYDGD2KVSDD+kP8oWuVwOPj2228544wzmo5FIhFkWW5RMuxYUltbi9/vZ82aNbRv357U1NQ/1I9Op/vdjQg6nY6hQ4cydOhQdu/ezUcffUTXrl157bXX/tDaT5Xqt2pra+ndu/fRHsa/zrEdbqr+NEuXLuX222/n6quvRhRFotEoS5YsadqxdyAej4eFCxc2mzJvaGjgoYce4r777uP5558HGneAzpkzh6VLl+L1esnKyqJTp06tZqp/cEkZDywtY/rWxtxojnyFKRWlvzuWYYNu5r4VZdz/bRnTpe0YpDC+HbFckLyS1z4aTtHw/3F328859/2lWBdYeHDVKWwLptHDWsqNbb9h7Jk/kJlTR2a7GuQKE/6whgJrGSedsJ4T2u8mJt3F+ZlruC1vAalxLkp8cYiCQq/0MvoN2kFem2p+KM/D6zQg7TEypFMhZeUJ6LQRlIQgO4rSSYlzY7eb6ZJZSXFlApWuGAZ23YWoj6AxhYnKjf9M9TludA6J9CQHnVKqubDjGjKsTr7c3YVtpWmE3TpcPgNJSU4inbyEK004nGYSrV7sfiMGUwi8GuSwhLPegrfcgkYXxRbjw9tgorowEUkbRZfoR/BK7NmXwp59KWg8AqYqAdkgE0iWESICiI2zbMFY0DlhRrcjE0yJotgiWK+qquLVV189Iv0fDW63m5deeonBgwfz4osv/u76zyOpXbt2TJ48mVNOOYXTTjuNSZMmEYlE/rL7q/6Z3G73UdngonB4OdiO9Txs6gybqgWPx8P48eO5/PLLm7Zsr1ixgpSUFAYPHnzAazdv3szw4cPJy8vjhBNOaDo+b948xo0bx4033gjABRdcwEcffcTDDz/Mpk2bGDRoELfddhu5ubnN+nv8oxI0fhkz4MjTELY0Pi5VtAqyZv+PTgcNvInB70zi+JyT2TDlWU7rNoz7J3/JN95O1H+YyajxIY674jF2hBVu2Xwlw7IKqR8UYlDHIgKKll6GfbxadzzusIFYvZ+9DfE8OPpttEKEmTtPw+k2ckfPr4jXeXl8/Qg0uihJMR4uTfuBLf4s7BET25yNsyihiER2Rj3+JC3frehCt957KXbEkZLUmBC3anMKggANySb65JXQEDSytiyLwe2K2Fibzt69KejjAnRMrqG6V5Dyqjjy82v4oS6PGF0QjSZKyKlHYwkTiYjU1sVgKNITzg6j1UaRBJlQWINeF8FnjqIzh4iUm5D1CqF6A84YCSICggIhnxa8GjQ+kbg8Ow37YgnbZIKpMvoqDVIQoj08sNOCNzuKvk7Cl7bfP4ZDFhMT0+zvDUBmZia33XbbkbvJXygSiXDHHXcwYMAAampqsFgsf/mGAEEQGDp0KJ07d+aZZ55h0aJFvPPOOy0SS6tUB8vtdv9lJeBU/0+dYVO1MHHiRHJzc5sS2NbW1vLaa68xe/bs37326aefJjU1laFDhzatQdqxYwe7d+/m0UcfbWq3efNmLr30Urp3787cuXO54oorWgRr960ow5csEjGJeDI0RE1grBHQOwS0TrEx1UQrJtcXA3DikE1cmbyczs9ew/zN33Du2zfzv8IBHPfieqZWF7DQl8ENu8+je0oFuYZ6EOCHtR3ppi9jkKHxn8aFKSup9VkY32E16Ro7VjHATe2/4cLOazCIYZJ1LnJS6gl5dQxOKWLaxnEsr21Htr4BZ8BIyfoMOqdU4/AZ0WmiZCyLUu210i25kga3CYO2MSGsolUIRyXWrWhP0b5UshLs7HXHk2OzY4j3kx7rZGdNMpIok5NWz153PMlGD1VeK363vmmNmiKL6M0hwhYFQSMTKTFTXJ1AdrydcERCYwgTqjMix4ZBAdESJurWokiNwa9Uq0OwhNG5wLMuASxRhMQggkYmlBUiFKcQCUqEY2T0dRJSEB5od+QeVcqyzM0334zb3bgoLhAI8NRTTxGNRo/YPf5Ka9asoba2lsWLF2M0Gpk6depR2+GanJzM3XffTUFBAQMGDOCRRx75yzb5qP5Z/H4/BoPhiPW3cuXKg24rIx7W61h2bI9edcQtWLCA+fPnc9lllwGNyUqfeuoprrzySk466aTfvX7AgAHExcWxYMECbrrpJtatW8frr7/OtGnTmiXEveGGGxg9ejTDhg1r9R/+Q4vKiBghqoOwUcCVpyD5IXZ3FL0d6OJG39D6X18pNsS7rq7svL8rkiCTOLiS/lMnEk4KEyyM4UTrNtY2ZLHKnYdBimCWQlSGbMTEe0lq00APnYG+689hWOx2cjX1dE+sYEr8bt6sH8Bdu8aw1ZdBdTCGp/acyAZnNvEGP/GJbj7b05WkGA+BiJY9/iR6JJaRVlBFiSsWUVSo3JaC4b8VNLhMbKpOJznWzZD0IhQR9OleampisOTbkUxhiopT0IpRREEhWGlm3+5U2iTW0+AxEZYlyuyxbK5JI9nkQQmLbNmYi7GysWpBqNyM1MYLsoCQFkCjjVJYmoLfq0ORRVBA0jXWEI2x+ZFiQggaGWO5iJIWQPFo8afIhHMDCKKMHJZQogKIChFbBDkqIhtkonq4t+DIrisTRZFZs2ZhtVrx+XzodDoGDBhwUMma/44kSeKMM87gkUce4eqrr261vNZfSRRFzjjjDKZPn84zzzzD0KFDKSsrO6pjUh17FEU5Yv8mKysreemll45IX/90asD2L+bz+di+fXuzn7Kffvppxo4d2xRcLVq0CJPJxMMPP3xQfU6YMIHly5ezYcMGbr75ZubMmQPATTfd1NTm008/Zfv27c0S2c76qpS7N5Tx8MJSXr5vI/5kMFcpaPwQsglkLQ4TNYK9vYSzvUI4oCEU1/rsgGmNkS+72Hj1qccoDSfwaee3CMQJxK3TIrbxUhuJod5npsIfywO5H7PNkcInu7tjftuGy2/gTXc893T8HIBlvo6cHLeZTi9ew/KSxsfDRd4kluzqSH5cNa6wHosmSEO9hTPythCn9+P5PBWzJki63ok/rCUckXA0mDHkuGjwm8hMcCBJMp6gnoXF+YjpPhSgS24FbreRvJQ6EBVK6+NYv6UNmCMk5zTgChqIM/sxaf+/9l6lJwZDXABFJ+PLjWC0BBGTgk2PNqMhiXClCaFWT5esStISHUixIaIhCSRwlDRuIDFag3izZfSGMEgK+joRxaVF1MrglRC0CvglJGMEyyY9hkoNxpqD+itxyEKhELNnz2bq1KnIsty06eVY1LdvXy644IIWdWuPtpycHB544AHi4+Pp3r37Mb1GUPXX02q1h1wDdH+WLl3K2LFjD6qtokBUEQ/rdSw7tkevOiy/FEifNm1a07E1a9Y0W2MTDofp0qXLH/pp6oILLuDGG29k2bJlza6/7777OPfcc5sl1jXWRdG5IGlRCXV949G5wJ8oIIbBWhKloZMOMQRRA2h8AtaVRoyVIpMbiplcX8xtod3M/L6MmT+UIUag9INujPj2BhxREyM3TODGaz4irjCEZYmF2z+5AF9Ax9o17Vjs7UzV2jQu7vgTQ6b+SPbZm9nhT2e+vYCGiBkJmfeq+3HiqesIBbXE6AMk6LyM6riN5bvac1z8Pko8saSlOPimogOBqIbwMCe7PMn82NAGt8+Aq95MQqIbrSZKfnwNVc4YOsbXIoky7gYTSbEeQhVm6v1mBAHK7LEo4cZ/mhl5tRhtAWp3JVBVY6O6NobdmzPJS6xHEBRqdiYSYwxgTPJhSPDjrzSjKCBKMoIMCApap0jUFqHUFUuty0I0IIFHQtHKSPFBtNoowYAWRAW/wwgaBdNx9WCJEnXqQBYQNVFESxiNPoqne5BgSoS7jjuys2uyLOPxeNDr9eTm5vLoo4+qOcT+RFqtlosuuoibbrqJ2267jYsvvphgMHi0h6U6BsTFxWG32w+7H1mW+e677/jPf/5zBEb1z6cGbP9idXV1TJkyhblz5xIKhQgEAtTU1DTb3ZmUlHTQCXB/q127djz00EOkp6c3O7579266du3a7NgN43PRuRWKrs5B61OQgiBrGjPrmz5ahbtt42yaqQqM1RBIArm3m4Q1EpJHRCo34OwYJffsIkZethLTQiv6HUYe/HY0j3Z+nzxdDSWjtJx1w9fMPeslchIa+ObMR+ll3AdtvARlDWsbsmiz2sSiJ46nj3Ufj64+iStse/FEdCzc0Zm0RAdtLPUEZQ0rKtvQO7eU7sYS2sbUU+e0ULsrgc62Kton1rG+OJPCymQ0UrRxR6UmQrzJx/ebOxDZbSUkS1zT9ltiErxEoiLtupYRlQVESUZWBFIyHJiMIaoaYrAag+gyvOSk1XNK560oOoVdVUn4gzpkrYLDY8Lv0TMstxAhJkxcrBdFFsjrWt6YWy0rhC3Jg6PURtBpICOjAbQKGlMEFIGgT0tmsh0hIiC6NIj6CPaiOAiIJGXZMWW4MZhCaIuMxH1ibgzgvEf+EeXKlSt57733MBgMjBs37qArZagOT+fOnXnooYfYvn07ffr0Yc+ePUd7SKq/uczMTKqqqg67n++//56EhISm9dK/T0A+zNexTA3Y/oW8Xm/TY9DU1FRSUlJ4//33m/6D9Hg8TW27du3Kpk2b2L59+xG5d3l5OeFwuNWki5NPy0LrBXeWiC8FIr09xBdGqLplILmfRbBUKJirI6TMXUX23St4v+8LdL1qC9GUEG2mrqBbt2LOS/2Jha/3J367D3O5QuoykafKR3D5wqtI2ATzPh/OUndniuviGfrpJCZvP5veWWV8tq8bvrCOTfXpRIwCeiFMRpqdmbU92b4tC70xTEVNLDnGer7f0xan3USpO5ZnSk4kUechN6keQ43IJ+t7kmepo3dOKUKxCaM+jODUkGp24woaOK/vagafuIkdNck8XzSYBLOX2j0J7C5Pxr4lkcwEO3pthJraGBylNtql1lJTbSNYZaLea2ZFZRtMKR4EAUJeLYYUH4KgoNFHWLCjMzGxPkJhDfEJHsrtsY1F34MiLoeJjLa1KDJUbk1BiglBmQFBlFHCEnavCSUmghwbRqnXgwDoZOp3JBIosRLw6dB4QeOXsWzVEY05cqkhVq9ezbZt2+jfvz8TJkw4Yv2qDp7FYuG2226ja9eu9O3bl08//fRoD0n1N9azZ0927959WH00NDTw2muvNaV5Uv0+NWD7lwkEAuTk5JCVlUV9fWM5o1NOOYVHH30UURQ54YQTuPHGG2loaADAarVy4oknMmvWrCNy/7Vr15KVlYUgtP6Tjt4BESP4M6ONOxxPh8RTy4i5q5SIHjzpGnbN7suuV/pw4Zxb2fh6V4Z03EXxjIFs3pfBU3tOpM95m0h4uBTbxWXUFYjUB0x06VRCrxvWM/e8F/BHtbze9xU+Pf0JTs/awqrCNkTWxOIO6EmzuIg/u5Q1njbIisBQ63b6di/C7zAwqO0eVjbkkRzvQtQoVNXYcAcNVAetyIqArIOs7Dp2uFKw6fzoOjhx+wwo2sYdmI7tCXxa1I3lu9vTP3Mf2TYHAKnt6tDqI8gaKK2LI9bkJzOtAYxR6nxmkpKddOlagsdlwF5txawPYTUHkGp0hPdZCNUYEQQQRPD59fj8OgIhLQGPnoQ2djDIpKU4sHuNaMwRZL1MxKtFNigoigCCgterB6+EZIigSfUjRAVQBGS9jNYpInu0RA1QfqLQmCT3CP2g2tDQgNlsxmAwNJU+Ux0doihy5plncs011zBhwgQmT56s7iJVtercc8/lp59++sNVaRRF4YUXXuCCCy5g6NChR3Zw/2Dqp+O/zA8//IDJZOLGG2/kzDPPJCkpiYEDB1JWVsaSJUtYtmwZ/fv3b1Y+Kicnh/Ly8qav6+vrGTduHGPGjCEQCBzS/b///nuys7P3e96TCYG2IXS1Eu3e9SCEBSzaELu+akvd0BD2AUEMGR7aX74GX18f8kl21lVlIoUg4Ts9Fl2Q1R90Z2NlOoGIlk4D9nBf20+5I+cLtILME6UjGRKzgyQpwAXrrqCnqZhp/b/ksvMXoddEKHbGsWdLBl/t6Yw3qOOWzecSp/MxeeAC+tj2cXvWfPon7+OJfu+QmdZAitmNrIhMyFxB/5O3EIlK5JgbKPfZOL/dusYdmXFBqn0W5JQgoqCgN4RZU5nN1qpU9u5Ko2ZnIiGvDkupQGq8C7vXRNneJGLivbi9BmrrYthenorREkRnDRGWJTw+PdGECGndq8jsUEPIpSPq0BFn9aHTRQjsjkGQZOr3xSHWa6msisVnNxH1a1B0MqJXatzp6dIh1WmhyoAQFRBKjIS9WmRjFHwSugaJcDs/+moNoVgFja8xUhOCh//REQgEmD17Np06daKiokJ9FPc3UVBQwAMPPMAnn3zCiSeeSF1d3dEekupvpl+/fuj1+j+8XGbJkiU4HA6eeOKJQ7pOQd10oPoXiYmJIRwOk5eXx9ixY9HpdGg0GkaPHs0DDzxANBpl+/btzYIqi8WCw+EAGovB5+Xl4fP5qKys5PTTTz/oe0ciEV577TWGDBmy3zaCDPpiHbY9CsEEA206VrJlQy6nnruSjtlVjOq8lSvyV5C+MoYn+r6L/qNYLm//I2GrwlvTHyHZ6KHHmdsI77NQtTGFWp+F8kgcmwNZpBvsnJ+2mjs2jeWmvWcTCmm4d8doZm04CZvkQyPJxOgDiMkBLuv0I23iGsiOtdPBXMWjq07my+quPF01nBJfPDcsGU9+bA3VXivbG1J4aNso0gxO2sfWsmhnJ2K0Qd7Z3Yt4qw9RVKiojSU/q4pwWMLvNOB2Gjk+ew9pbeqQ9QrJKU7cvQI0eEyY9SH0CX5cFTFEIxJ4NMTE+An4dAiigstlJFRjZEiXndS7zVTW2xBEMKV6qNkbj6/eRNQkI9To0SQE0GR70ZnCIMnEJHoQtDIajwiigsYWROsRkAICii1MJDECPgljmQaNV0TrhbSP9Gg8EI2JELFFEWQwVB/+GjaDwcDkyZMRRRGTyYROp1Oz8P9NJCYmcu+992I0GikoKODHH3882kNS/Y2IosjJJ5/MqlWrDum6wsJC7r//fj799FPeeOONI5rL7d9ADdj+Bc4++2wSExMpKCjg+eefb6pe8GtDhw5l1apVzJs3D51O16zAu8ViaSrk/uKLL3LxxRdz5ZVX8t///pcNGzawYMGCgxrHSy+9RGxsLB06dNhvG40XTJXgyRQoGSWxd0caii3M4lf6s3NvGns9CRQYSngw4yueLh1G7Ks/8uzWwfzvnLmsDmRT6onlp8WdsZQIROIjrCj4kIUNXelmKGVRVSdKQon4K81sXdMGUVQw6UKM77Kal/YMIs9Wz7CUQvpkl/L8d8Nob62lqC6RF7cPQmcJcWnGj1T5rawtykbboGFY7HZ0mghtbA10T6nAG9HjieixxvjZWJmOz2XAG9SREONlUN4e3CE9NqsfJSIyuMNulha1p3p7MrpEPw0uE3JAQyQqUVkWhxwVQR9Fpw+T26EKR50FrSFC0KFHDmgQgyK7nYloNVGslgCCR0IQICHXjqCRQRaQYyNEwxJBp55QnRH8Gton1IFHQzgjBLKAxRwkkBEhkhVAiYgIHgmsEfztg4QTw4hBqBwXJJgAMVu16Ks1yFoF8cjs6G9KH9OrVy8yMzO54oorCIfDR6Zz1WHRarVcccUVnHnmmYwaNaopRY9KBXDxxRezatWqg/oha9euXTzwwAPMmTOHc845h+LiYgYMGPCH7vtvLv5+bI9e9bu2bdvGwoULmT59OgUFBXzyySetFo82mUwUFBTwv//9j969ezdbY6bRaJr+Ey0pKWmqSKDVahk1atRBLRrdunUrd9xxB+ecc84B26V/58VglzHUQdr30GlWObi15J5ThGjXMjxpJzduOJ+vfdl0sNay66n+hGqMXPL9FTzy7Hn0TijliYteJu+c3egrtQzadCbf72mLQYhwSuo2Vja0wZrpJr1bFZGQRHtbLVXBGPqnFKMRZNY6srkwZSXdOhcTjGromV5GOKAh6NRz9/rTubfNpwhOLWFblLs+Po+y0kS21KRS6Y1hWVk7anwWhmXuIiehgdQUJwlmLylmN65w40+S9VU29LEBfijKQ6ONos92o5GiyBUmUr+V0EhRjHEBshMb1xCGwxK1HguiNookynRoWwmSQjQmQrzBR4bNiaKAlOIn3eakviam8V+1JYKigOzXkJ7ZAOYIRGHjD+1ok18JfglzohdXYRyaBg1KVCQm0dtYJ9QvITi0aBo0uDtF0Ow1ovFB2AoRs0LEIuNt++cEVS+//PJRTy6rau6EE05g+vTpPPTQQ5x77rn4fL6jPSTV38CQIUPo0KEDDzzwQLONar+IRCKsWbOGBx98kNmzZzNu3DhKSkq444471Jm1P0gN2P7BotEo48eP59RTTyU9PZ3TTz+dZ599ln79+rXaXhAE7HZ7izQckiQ1/RSl0+maJUzs1asX33///QEXJ5eXl3PyySczduxYunfvfuBB/7iRmr6NdS2rBghESsrQukXyLHUYawQ+emAkvdLL6GEoY01dFtpkP0k/iSgREU+Owscr+5ClcVD2UluieoWT07eTldTA9H1jmRRfxOCE3Zj1IVx+A1Qb2FibgSgoLC9vS5XfSv/4PcxvKEBWBM6IW4coKNzSawmxyW7S4p2UR+JQbGHOH7SS9F6VDOq8i0BASzCqoWtyJWdnrmeTPR1/RIusCNS4LWzc2Ibt1SmUlSWQmm7HYgoiR0UkUcbvbPzgMrZxUXeaH502SrLNTVFpMlpzmGhIwufRk57sIBKVKNqYhTXWBwLIisCuqiRMujAajUyt10JMvBedKQQhEUFUEI0RqrclgyxgSPURTohQ+lMmol8kstWGziUghUBwaQhFJGSdgr5Kg5gURDY0PjINJUQJWxUCaVGiBhlFLyP8CZ8ca9asoaKi4sh3rDpsOTk5PPTQQxQXF9O7d28KCwuP9pBUR5koinz99dd069aNu+66i927d7Nt2za+++47Xn75ZSZOnMiXX37ZNKN21113HXagpiA0bvA6jNexTA3Y/sEmTZqE3+9n3LhxB9W+vLwcl8tFampqs+NOpxODwcCiRYuoq6trFtBlZGQgiiJr1qxptU+Xy8XIkSPp06cPo0aN+t0xiL27Ek0K0dArgsYjUP5RF7Ru2HFKArmn7KXtDdtZsTqf0+f/lzMyN7Fz8GvUnhjCHOfn0dGvE5vlZMyHt+A5w80ZI1bz1o4+hGWJeL2P/hvOpjwYi0ET5uK2P9G2ZynhbxL46alexJr8mDRhPi0tYOne9uxtiOfJshG0N9ewwZPNcakllOxOQUJmRKcdfLSrAFfAgCesJzupgWyrg1JPLHNWD6fKFUOG2UltvRVflQXMEUK1RvQxQXwhLfVVMWSn15MS48YU6ycj1omn1owkyTgazLgCBnSmMJIkozVE6JxVSTCsoU1iPdosD75CGxpThIaAiZQ4N56FKQQ8etxuI85aCyGPDn2CH0QFxadBTgiBTyJYbkaICERio/Tst5tgWhhZA8GkKGJygKBbjxgRCGSGiYZEbDtFInUGhIjQuCEhLIA5ihAQIXDkPzqCwaC6K/FvzGQyceutt9KnTx+OO+443nvvvaM9JNVRptFoeOutt5gwYQJPPvkk7733Htu2bSM/P58VK1awefNmpk2bhslkOtpD/UdQ04j/g3377becdtppTVUGAoEAPp+P+Pj4Fm1lWaayshJRFFvMsC1evJgLL7yQN998kxEjRmCxWJrOCYKA1Wpt2pQgyzJPPPEEK1asoLa2lj179pCXl8cFF1zwu+O9a3MZwskxGHZD2pAyyuoyOb/dOjYnZ7CVDmTIJdyR/iUTO8dycup2wrKGvuvPwWwL4HUauWXRRWgSAljb2REE2H6CkdAzWpLTPKxc2oUJp39NV2MZWxxpvFvci64JVbS/cC1frilA3JqK3LmaOKOPqmobgqAgCgoVgVi8ER3tzLVMGPQdtyy+iI6dymibVEeFK4ZrM77hlk3n4g/rSDJ50GdXU1IXz86GZBS3lsx2NVRuSkVJDcAWK660CDEpjY8Pql1WJFGh3NH4mDTo0mOMDeAqikW2RtHFBMl+UmT3yDYonTzICAQcBnQ5PsJ+LTUNMSgyRDtF0OgjSBqZqCgh6qNEd1kRs/zIAihBCbQK1gw3vl02pFwv6/dloq3XEEyJoG3QEDFoMO3SEUhW0McECTr1eLIVpIBI1BIlolEQQwJyWESQQPQf2YDN5/MxcODA/aZ7Uf09CILAGWecQV5eHhMnTmTnzp1Mnz79aA/rqJNlmUWLFrF161bGjh1L27Ztj/aQ/lL33Xcf9913319yr2N9Hdrh+Pe+83+B/v37s2zZMoLBIJWVldx+++3cdNNNlJaWtmi7YsUKkpKS0Gq1zQKy2tpaVq1axcKFC/niiy/o1atXi2tra2vp2LEjxcXFDBo0iGeeeQabzUbv3r25+uqrueaaaw46v5YvTWbA6E3UuK2EY2R+qM/jyrTltD+lCGfAyJiV19DG2sCK+jz+t3QIA1P2EYmKrB3xFMltGtCvNePdGk+a1UXlhO70blvC5vI0ug7ezWp7LtsC6YRlCbMuRLzOSy9LMeYUL516FFNZbyPL5CAt1UHIp6XYGUdQ1tDRUk2K1kkbfS2n91tPRBY5P+0nXA4TXzoKODNvI3FGH9vK09i7OQNJkonKArntq6h3mzG3d5CS6CLS0YcUE8LtMFHjtOKrtuCqsRDYG0PIp8OW5CEU1CCl+RENEeSoQMUtYfQ97IQaDDicZkRdlLBfAwERjS6CHJEQdFGiQQ1yVEAyRpDdWoS8xmoHgqAg+UQEGXx+HZG4COEKE0q9HrGNFzEgYsx3oK3SETECyQG0ay3oarREYqONu0clBckjoiSEkLwSxrLGlCBH0iuvvMLatWuPaJ+qP0/Xrl2ZMWMGjz/+OG+//fbRHs5R90s9zA8//JCePXsyffp0dcez6ohTA7Z/sPvuu4+EhASuu+46pk6dylVXXcXw4cOZP39+04eJz+djw4YNzJs3jxtvvLHF7NqiRYuAxschTzzxRIsdpqWlpQSDQdatW0fPnj1JS0tj5syZjBo1igEDBpCfn39QdUinlJdiG1RDykqBFQu681zBG6CV2fNjDv9ZdDnFzjhGpu/A+KOZja93peLdNmi8IguKOpGXWM8JP13J0oI3iZogkhxmVPJW8i/YyZaqVNqn1vJh28UEohp6/R975x0mWVXt7XefVKdydVfnnpzzDDPMADOSc5AkiAoIiEoQI/EaCAaQfL0IKgYQQaJIEMlJ4hAGhsm5p3Purlwn7u+PM3IvHyBpIvT7PPVAV9XZZ9V0VfU6a6/1+4WbuGXirRRsg6fbxlPwQ0yq7iaiOZimwytdI+haWc2f9/gTBw1fQWcpzuMdk4irZX6/8XO0l5MMlCKsLddSmc7zWNMkfCkoOAaVyTxaYxHXVSgUQ4R1h2SkTKFg0tWboDJRIB4rE4pZ6JqHmrTRMipe3EO6gnzORPaGcHpMjJCL22vieirZvijoEkX1QYBQJVIB03BIVBSIp0oI1cfJGZimg5Eu43aFkXkd3XTxDYmaV/EsDS3qIE0fUWVhd0WINivk2uLEN4Cd9hACCiM8pCZR4w5IiK8Kkjf6DZT6IkYOok2b15rqzDPPfM+LgSG2X2pra/ne977H6aef/g7dxs8ic+fORVEUTjrpJC655BLuvfdepkyZwjPPPLOtQ/tUIQFfKp/otiOzY0c/xH+ksrKSRx55hGeeeYbW1lYuvPBCbrrpJgqFAieeeCJf/epXOf3007n99tv51a9+xUsvvfQuyY1/W9R89atffVfDaHNzMz//+c85++yz+drXvsYZZ5zBl7/85Y9s2H1D+mXCXYIzxjxLzyFltCJ8d/mXwBXM3nMVX9rtZdxnK3nw5t3JjfEZnO6iHdaDPimD2xXm5IYXmVTdjSN9vnDUc1TXDfLn9bty++incG2NunCW/VccxoL0ek574hS+veEYoobNyOQAv16yF1PiHby6diTlss4Bw1ZSM7GXe/rn8kzHeE5qfIlDGpZx8aNfoLU9zdLOOianu3hg4zT2b1wFwNpCDROSPYR0N5j49BR8T6Gpr5JcOYSUgQuB5WqMTA7gWBqFfAh1XRiGlQhVlImliyiaT2REDpF0UBQfoh52NgSKJFJRJBEroagSaQdVtVw2TD5nUiwZjGnoQY24FDpj2AUDmXAg4mJ3hzFringxD/IqSIFUJL4bVN2sSgj1qBSGgVFdQvqAL5AqeJaKVCE30QEh0QoKXleY7Nwyzs7vngr7uPzzn/+kpaVlyOVgB2TKlCl8+ctf5vDDD6erq2tbh7PNSCQSnHDCCVx33XVUV1dz0UUXsf/++3PkkUfyla985W3nmCGG+CSI/2QtsfPOO8v3ayYfYsfG8zwGBgaorKxEURTuuusuvvWtb3HVVVe93SCaz+f52te+xgknnMDhhx/+9rFSSl5//XVuvPFGfvazn/Hiiy9SKBQ44YQTPlYsN6Rf5vhhr7C2XMvdK3birBnPMibUzcVXncQXz3qcxzon85Mx/+B7S47jkJHLqdJzFL0Qf3ptARWvGgxO8lGqLRCS9MNhCkdlKTbH2WOX5bQWknTn4qiqT9nSuXLWPTzYvxP7Vyzl+qa9qY3kUYTPxFgXL/WNZnSsj5c7R5FbVcG+eyzm9Z5hHDPyDR7rnMwPRj3O5esPoj8foVw0iMXLhDQXH4Gu+IR1mw2t1UQSZcIhh5RZojsXx7I1EGDnDVJVQaKjKx493UnUkIdnqaghD6H4RMI22eYkaBKlqOBH/GB4QJUITYInUEIuqVSR/rYkmB6q7qMZLnZbFKXawrMVVMOnuiJH2dWQksAofl0MPyTxdZ9Qn4o1ysLYGIJJeVxHxR80IOwFvxRFIjI6UpPIkI/eq+PW2qh9OlIB4cIvRw7/ZG/CTbz++uuMGTPmPf1lh9gx+POf/0xnZycvvvji257EnzVc1+Wwww6jvb2d8847j1AoRDab5bbbbmPJkiVcdtllfO1rX3v7wiSTybBu3TrWr1/Pxo0baW5upqWlhY6ODrq6uujt7UVKydixY5kxYwZz585lwYIFzJw580PtWuxoCCFel1Lu/J+eM3xaUn737nfLUn0Uzp3y2AeeZ3tlKGEbgr6+PiZPnsw3vvENZs2a9fb95XKZ//mf/+G73/0uoVAIANu2ufLKKxkYGOCqq67i0EMPpb6+nksvvZSampqPdf6rE4vYv2Elj7ROZm5tM/9cOAu1wmbG8DZ2q1jPbx/dn/SkXq6ZfBdfff5U9p20ilojyyv9I2l7bASlKWUUTRJ7Kcz9517BCC3ON1vn01JIsVt6Ay/1jcZUXZoGK8gORqhM5+lrSaEmbaY0dKIpPiMi/TzbPo6ypWM3x0iMH2CwOUmotkhDKoMiJLtXryOplnglM4rOYpy+QhRN9dm9fh3LM3WsXtuAYrpMGN7FhHgP3VacfivM+s5qdMMlZDhkBqIgQTrBl7Yoqxh1Rey8AXmNmrF99GcjhE2H4uokXtRHxB1kxqBy9ACDg4G9VChlYRd18AVC81FUiWgxcdIuQpVUVucYzATPFa4A00MZ1PFTTpCIqRI1beFZWuAhWmnhlYLEUhkInocACmpQh/eBTb6jRAPbqiurRn6yNx6Qy+XQdX1Il2kHx/M8Lr/8ciZNmvSZ7ml7r6QNAh3KP/7xj29fJA8MDGBZFlVVVaTTaSorK6msrCSdTr/9czqdRkpJU1MTGzZsoKmpiXXr1lEsFjn++OO5+OKL3zXRvyMzlLB9MEMJ2xAcddRR5HI5TjvttA987k033USpVOLRRx/FMAza2tqYOHEiN9100yeO41cVr5I2i/hSsK4vzYvz/silPbvyz9vm4+6aw5eC8dU9nD7sGV4vjmaEEZjX//qaLzDz1Ld4esVEqquzHDvyDf68ZhccR6UmlaNtZS17zFvOwtaR2JbGgjHr6S7HWNNew4iaftoHkzgdEWrH96IqPj2ZGGNreukuxFCQZAphptZ3UnR1JiW6aC5Wsvj1MUyetRFN8YloNm92NDKuqpfl7XXMH7WBsOrwzMZxhEM22Q0pxkxrozsXx/UUYqbF4OJq3GFlpKcgXYE2oCENiZ90UUMebnFToqVL1IiDV9agqIIvwPCJVBewygaxWIlMSxKpS0TIC5KqsoKIuuimi9cUxa+1EL3B1qqvy0CiI20hOkw804ewD7aCWlCQalA98yI+iiMwhhUod0fQsipqGdyYxKt0UAyPy/XxH/Ab/WDuvvtuKisr2XfffT/xWkNsWwqFAj/60Y8444wz+PGPf7ytw9lmvF/SJqUkl8sxODhIRUUFsVjsY01Fd3Z2cv/997Nw4UK++MUvcskllzBs2LDN/TK2Oh8mYRs2LSm/c9f8T3Se86c+MpSwDbFj8l5boe/HokWL+OMf/8iSJUuora0FgnH2qqoqDj/8cOrr69F1HV3XMQzj7f8XQrBq1SqWLFlCd3c3xx13HFOmTHnPc1zyaiv5yQ5n7vI0v318f/yUQ6jZQE7OM7G2m5RR4oSaF9k/7GJJh/2WfpGBQphSS5zYyCwzatt57bEpJHbuoW91FdSUUVSfZLxE34YK0qMHaIhlqTLzvLBxDK6jEo+XqIvnWNdVhab5lAZNUjU5Mm1J0iMGCOsOeStEOlLA8xWa1tSRGp5BVXzqojkGrTCVZpHOfJyEWWbdygaMmhKKkOw1cg0PvzEDs7JESHfJ9saCKpWtIBXQ4jb6ighIcKcWgv43K6hqSVcEJutmkFARccFVkF5Q6RK6j1AkMmNg1hco94VR4w5eX4josBz5nihaLPhZ+CANiVpQ8NIO5DVE0kbRfZACt6AR2ajj62CnfETaws8YhHpVyg0OZrtOtA2sCkBCYbjPlTUj3vN3OMRnl46ODi688EL+/Oc/c8QRR2zrcLYZruty6KGH0tnZybnnnvt20rY56e7u5oEHHuDFF1/kmmuu4Rvf+MZmP8fWZChh+2CGErbPIL7vs3LlSp544gnOPvtszjvvvHdshb7fMd/73vf4n//5n3fZSz3zzDNcfPHFlMtlLMvCtu23/+s4Dq7rMnnyZPbbbz9M0+SSSy7hG9/4BgsWLHjXee6++24WHrgzer+GYguchE9yVVD5yY73UaosVN0jpLvcO/v3nNN0NMteGkP1zG46OiqIrDE48JiFjAj1s6pYiy8V2opJljfXo4dd/PVRwhMzREM2nZ0pRgzrZbAYRlN9DNVjoBCmIZVhVLyfF1tGYxoOxaWVRKf3M7Wqk4nRLhb2j6I+kmVpXz39+QiVsSIV4SKm6vLG0tE0jumhvTtFOGphGi6FsoGVD6GHnUCSw1IRZQVp+hDyUAaMoEctbQXbpf2hIGHK60hFIhRQwy5eOUjkREZDzyk4I8ogQGZ1RMIhniiR6Y4FvW4CpK2g92tB31qF/b9bmjk9cCuwFBQnkO1QrMBdwgtLZNQLEkQJ+GAMqjgJH+EI/JiHNqjimZIr6j55wtbZ2cnKlSvZa6+9PvFaQ2wfvPXWW/z617/mX//6F9OnT9/W4WwztkbSBoH94PXXX09TU9MOLVD7YRO2b9317r8bH4UfTn14h03YhoRzPwN4nsc//vEP/vWvf/HKK6+wdOlSACZOnMg555zzvsma4zg8+eSTVFdX43keiUSCL3zhC+94juu6xGIxTjzxRI466qj3FOUFeOKJJ7juuut47rnnsG37fb+8Dj/8cF4d6EJxBHaVh9GnMjjZx+xRqBgzQHU0z4L0es5PL+Wq/tksfmsUDa9K2irSHD77TR4s78R9S2fyhelvMi++gZ++fBjSVjF6NOwKD3VEiWSkREh1mT6mlf5yhHzOxM8ajJ7QwQBh1jfV0p5KEtJd5ta18MRAlMG+KM93jqc4ySBjmxQcg87OFGNHdNFXjLK2qxqnpGGkS7S1VyI0H89XiP0uifv1HLFqi1zRxIg62EUNGfLR+jXchMCLu+g9Ol5KIGWQONETggoHZVBHqSnjDYZQcwpejY0M+SiNBbRVcTwz2EbFF+QyYdSCiq+CmraQuodXVhCeCJK0sIfea+CkHZSSiox6iH4tmAgNS4h4mM06tifQswIvBE6VA1LFD3uojoawgvXU8sd+O74DVVWHxHI/ZcyYMYOjjz6aww47jFWrVn1m+xM1TeOhhx7ikEMO4corr+S8887bIgMZU6ZMYdiwYVx++eVccsklm339IbYfhipsn3J83+fII49k0aJFzJo1i/HjxzNhwgTS6fQ7/lAuXboUKeU7rojvu+8+Xn/9dXp7eykWi9x4441vT4K6rsuxxx7LI488QiqVoqqqira2Ns4++2zOP/98NE3DdV3uueceLr/8clpbWznooIOYN2/ef2yU7erqYuHcN/lqzQt847mTGNHYR0h16StGyeZNpK8wqraX/x53F8e/+TU8X2Few0aeWjIZxfCYN3YjS++bSN1BLQyUIkys7KbOzPJ8xxiihk0yVGbx8pGEqkrYRR0zapOOF9AVj+5cnGIuhPQVsBSUmMPY+h58KSi7Orri0T6YpDqRpzcXxdA8CoUQvqugGh6m6SAlFAfDGDEbVfWxSjoVFQX611ZSO6GX7uXVCJ9AG62kIEcWkV0mXsQPBG5ry9ASJtQvKE8r4dsq0hMoIQ9Z0Kkb1YfjK2SWpnFrHRTdC4YFAGEp6FVlnB7zfwcKSipS9xElFbWqjO8oGOtNnHGlwNS9BG4EnHig8abYgaQHkqDy5giQ4MU91Lwa9MBJuLx+826HSimHErdPEVJKfv7zn3PKKafw/e9/f1uHs01xXZdDDjmErq6uLZa0rV+/nssvv5ympiYSicRmX39r8GEqbI1TU/LMuz73ic7z42kPDVXYhtg+OeWUU1i5ciWXXXbZ+17pNjU18dOf/pThw4dz9dVX47ouL774Ig8++CDPPvssY8eOpVgsvp1o+b7PF7/4RdauXcsNN9zwtjPC+vXrueWWW/jNb35DXV0dq1atoqqqikMPPZQFCxZ8KH22X9UO0phPcXrTCSgDBnatRltPBbSaxJsEhT0LtA2kOPrl03F6TebMXM9rd8xg3GEtjE/08NSGCcw5agUt+RTpSAHb12gvpbA9lb6uSvyMQbiuwLCKQcxql5wdorUvxb9zBWODiTXSQok6+I7Kxr5KRlf1sX/9Sh5qmYrnqBTvq2PSl9fRkU+Q64gzd/o6ukoxMiWTbCYCJRUz7ZDtjSEMj74NFdSM76NzYyVmRlCu9iHq4qoqFHVIuAhLxU+4KL5ACFBc0AwPRwqEBoru40nofy2YxHVqAzsqsTGCDPvIuIvwBL4f+H66eR0toyEF+FGJ2GRMIPM6qg12Xwgn4ePGg/ujLQpWZZC4RVsUCiM8tLyKGw1kRfQ+DSFBLQm0IlD/8d+T/z833ngj06ZNY/78T9abMsT2gxCCQw89lCuuuIJ4PM5Xv/pVnnjiCaZMmcKoUaO2dXhbFU3T+Mc//sFhhx3GFVdcsUWStjFjxjBp0iR++tOfctVVV23WtYfYfhiqsH2KufTSS7nhhhv42c9+9g67KYBSqUQ4HEZKyS9/+UsaGxt5/vnnOfDAA3n66aepr6/noosuek/j+NNOO42nnnqKn/zkJ4TD4Xc8JqVk1apVFItFRo0a9b5bpO9F47zzOfHlU5k9vJV+K8yGJY1QZeEVdeqH92NqDs1vNSAkGIMCX4fonD5qYzk29ldQE88zpaKTt/obuH7C7Zy+8ngUIensSzJ7RAut+SQ1kTyrumtwXYVErEyhbFCdyCOloL07haIFAwr5Ugi3NZDg8E0ftcJiRHU/6zfUIgyfxroBACrNIgNWmPaeFDWVOXrfrEGOLOHZCqGYjd0erCHSFn7OQEQdtBYTp9HeNPUJiivwUw6a6eJkQ6h5FWrKge1UNkhyZdKB4qaE1wciXlAF8wRmxSYf0mSZYl8EJewiczpG3yatJgF2tRv0zYV89D4NqYAf9hG2CLZDlaDip2cFVpVPaoVCbiSoFjgJSeUSyI4WuHEfxRJcNmrzaLBBMF0YiUSGKmyfMqSUvPDCCzz22GN0dXXhOA5SSg499FD+8pe/fOb02mzb5tBDD8W2bc4666zNvn5raysXX3wx69ato6qqarOvv6UZqrB9MEMJ2w5Mf38/vb29jBs37l0q8Y8//jjHHHMMl1xyCY2NjW/fL6Xkzjvv5IEHHuCAAw6gpaUFx3F4/fXX+cMf/sCzzz7LqaeeyiGHHPKe58xkMtTX1/M///M/JJPJT/wafvl4K3t/62V2j6+iWs1ya998pkXbOD3Zxm8zjWS8ML97YW+kIhl1L7QcqCIVqB3fS/+rNTjJYCtPKjIQgx1ug60wc8pGFi8eTai+gFPWCEdtbFtDCInTEUEaEiVhk07l6c9GMU0Hy9JwLY3po9poyabwfUFIc+lfUYUX8ZGGT7SyCIAQUCoE4rmKIomFLCxHo39FFWJYEc9Rka6CGvLwPYHM6uhVZaQEt6xDXkWaPqrp4ud1wq0apbE2WAqYHtJV0AY0jIygNNoJvEPTZdyijtB8pKsECV/EQzU9vIwBRjBNqlWU8dsj+GEfpaig2AIEaCWwxpaRJe1t83a/wkHtMvBi/qYhA4GWV4i1QjkdbJcqdmBbhQSk2OzTob7v869//Ys99thjyO3gU0pzczOGYRCLxbjuuuuIRCI88sgj77qQ/LSzZs0a5s2bx4033rhF1r/hhhsYP378Flt/S/JhE7bT7tzjE53noukP7rAJ29C34w7I448/zu67705DQ8PbPWE//OEPuf7667ntttvo7e3l+OOP55vf/Oa7krXbbruNN998k6effpp0Os2Xv/xlFi9eTCQS4Tvf+Q5/+9vf3jdZA2hrayMUCm2WPonz7LX86PxbGG928t1HT2C51cjDy6dy49rPcXzTXpjC4bHOyYz7i03D8H4Gz8jRMKWLcIfCvvWrSO3cw7f2ewxp+KRGZpi275pNL1TQkU9QPaYP31OIxiwUIXG7wmiaFzThR1z8QYO+gRiq5mNZGtGIhRFxWLJuGJ6noCiSXMlE1pdBlUQri+xU34ZVNrBWJlGbA2uoWMhCSkFPUyVuwkNRJHrIBSHxcjrhqAWmj6L6QbJWVFEqbPQ+DT9ngCsojnRQ+/RAxiOnBz1rGkgF1IjDqAmduJlQ0JPmK2g9OoorUPt1RIuJkrAxk2XUlIWiSKgpo+YVtKLAD/uE+oIhUZnT0fs0kAK/wkEM6vihYKoUBbTCJhX2CT7lWg/FBcXj7cdR3v8C7+OiKApNTU2USqXNvvYQ2wcjRoygrq6OWCzGueeeixCCBQsW0Nvbu61D26qMHTsW13UZHBzcIut/8Ytf5Pbbb2fFihVbZP0hti1DPWw7GJ2dnRx99NEcd9xxfPOb3yQUCrFixQoee+wxPM9j4cKF3H333cRiMebNm/f2cVJKbrnlFlavXs0LL7xAXV0dn/vchy8tv/rqq9x555388pe/BKC3t5fq6upP9Fp2Ht3MufedSOOsDoh6vJwdy5jGHoqOweLOBmxfw/vvOjr21ji4ZgkrD6yg7Q/V+Dq8MkvFflDlub7x/Gzvv3HZsoN4bcUo9H6N4XPa8KRC93MNMLVAYX0SP+JBzKU2kaO5zkAWNRKNOXJdMXzNx8kbZMoaiu4jPUG2O4YacVB1H+kLojUFChmTV70RaIZLOe0yY2IzS9YNo707hVAlSllBVJTxfcHY2l5Wt9biq5JizgRLweoLgysw+lQcJwQji5AJoQ9oqJZKucFFhF3I6viWSrRboOdAro7QVNICCZCSjtpuBEMCmkTGPIQm0ZvC6D3gzCvh+wLfUVEU8DXQ8gr5CQ6hTh2ztkgpZGK26ZRjCnpBwduUsOmDCooDfggoKmglsJMSv8pDzakg4JfDN99W6P/l5JNP3iLrDrH9oWkaZ511FjfffDO77rorTz31FCNGfDY0/RRFoaGhge7ublKp1GZfv6qqikMOOYRvfetbPPXUU5t9/W1NoDS05VsnhBDfB76+6ZRLgFOACHAnMApoAr4opRzY4sH8H4YqbDsYP/vZz5g7dy4HHnggpmkihGDKlCmcddZZ1NfXM3v2bFKpFI7jkM/nWbduHU888QRXX301a9eu5fnnn/9Idia+7/P73/+e/fbbj1//+tfccMMNzJgxg1WrVn3i13JMzWvUz+xEvaKKPSet5o2eRgbLYTrWVVHemGDDn8fjxBSsCWWurlvEQ4ufpPbyEMtP/w3nrFtG+bVKlr48hkmhTmrieUKdOuGJGZqWNVCwDcTMLE5BJ7FW0PiYQIs4bFzciKp7CAH5nIlRUcbtNxFlBc10odMklLIQqgySMNUnmSqiCEkqXaAmmUNTfUKpMsvbgs77UNjBzRlQV8bL6ggBLQMp/LKK0CSq4UHURY07EPVw4xKZcHGLgc6aU+lSHm2B4SP6DUJ9KnrMxqqUlKvAjUoUw0NkdPyEi9NgQ9RFasH0Z+INA3Vijtwsi2i0jFvSiaZK+KaPG/ewkz5mu47wwWmKIWwFa7iNNhBcrykumN0KvgFuFNQy+KbEN8CPbpoONeQWS9YAWlpauOKKK7bY+kNsXyiKwimnnMLs2bPZbbfdWL58+bYOaatRUVFBNpvdYusffvjhLF26lHvvvXeLnePTjBCiEfgOsLOUchqgAl8CLgCelFKOB57c9PNWZShh20F49NFHOeGEE7j11lvfpSD+xBNPcMYZZ7BmzRruvfdedtppJ+rr6znttNP43e9+R2trKwcccAAvvPDCh/b7fPrpp9l///2prq7mwgsv5IILLuC4447jxRdfZLfddvvECds1f2/mr527MLeqmcmXLSHvhgjdXEnf+krUCpvEuAH6Z3p07gahtSZnd84G4Me3/plpL3+Fq8ZO5bQvPszs+Ws4bekJ6KrHoYcuJPWnGDN22kDf+kqK/WGSbxgUGiE7UsXrDoMqiZg2QvcILzMZX9NDfK2KMajiFgxktYU1YCLyKp6lIaWgWA6ao31f4PkKYyr7MEMOo2p7iaRKJCNlRMgLHAo8QTxaRggCAducBm1hKGq4RS3oXUtbYCsIzSfcuslMPaOjdev4KpQbHFxLQ9aXkVPyaAVBPFEKhgR0H5BIXyBsBWl6ZGdblAZNNNMl0xMDX5DvCwQ0tVzQ52ZVe7hhGWyLGj5al4EX8dEKoBUFVoVEz4PigFUpwQ8sqoSlQEM5GHrYgtTX13PyySe/PaH8n3prh/h0IITg2GOP5YADDmCPPfbglVdeecfjnZ2d3Hjjjdi2vY0i3DKk0+ktmrAZhsGJJ57I2Wef/an7twOBJ5VPdPuQaEBYCKERVNbagSOAP296/M/AkZv71X2YoIbYzrFtm+OPP569996bU089lYaGhrcfy2az/PWvf+XRRx99hyzCK6+8gu/7H6uJ+x//+AfHH388X/jCFzj88MOpra1FCEFfXx8vvfQSX//617nllls+9vr/ZsWzY1k/PY3yZAqtBNmd4Iufe5ENhSo+V7mGO/SduX3KnxmhxZn5ypc58KzpZEeHGbYqT9/X53P/Dxw2Hqpyxj5P8OrgKOqNDM4Z/bzV1IiWV5Bpi8xsSSRZQn0yiVQkiTUqeauC8KDA2anAyvY6vIkueALpCRJVJfK9KYQPnqVg+wY1dRn6BmPUVGbp6k0wYEawLQ1d8yhmwlhlA9UI9NCUlE2uYOKUNFTTxZMgKzzIGIFfqC5JVRawHI1CZyyYIN3kcuAUdVAkSlHFB0TGwA5JRMrH6kgQ6tZwEgoy4qH3a6hlgVVDMBUqJF5XGAWQusRIl7H9EIoDSlbDD/molsCNycCjFNCzajBU4AKqxNcEoYFg0MDsDYRzZcxDNIe5cvSW9SrUNI2amhr6+vrYsGED8+fPp7Ozk5qamqFBhE85hxxyCPF4nAMPPJA777yTAw44AAga9E877TT+8pe/8PTTT38oWaAdAdM0t3gitcsuu/D444/zi1/8YkhM9yMipWwTQlwFNAMl4DEp5WNCiFopZcem53QIIT5c9WMzMvRNuANw5ZVXUldXxxe/+EV22203HMfh0Ucf5be//S2XXXYZhx9++HtqWH3UP3S+73P99ddz/PHH853vfIeDDz6Yurq6t+UWqqur6ejoYJ999iGZTHLvvfd+4BfPedZaXp94JxDIN/i+z68qXuW2K65il/2Wkc+Z1BzVTPnQDE7K44H7gtfxz65pxH4a55iLzuX3mXrqL1W56q+/JXnHKzQfHOfpi69Fz9pULFX4zRt7sPF347nhtb3o7EgxZUQHO+2+msbqAUYM66WYCeNEg2rT4HQ3mLycUsbrCCNaTPQ+DSVhI1RJdjCYrnQTHoQ8jLjNYD6MZ6kMFsIIVVLujjC+oZu+3jhm3EJdF2ZSfVcwtQk0Vg6SrCwE26SKxM8YSMNHH53HD0ky2QiFrihaRRkvBAiJ0maiFhW0fg2pBtUl35AYGSWobtkKZi/IlIMWc3BrbeyUH7gfFHWMDSZikwYbAuxMCLOyhD3CxuwSGP1q4BHqAJ7ATXhBUjqqhJOQ+Jqk3OBSqgkkU/QcxJsljf9UP9J76JOSTqc5/vjjAfjLX/5Ca2srnucNVdw+5ey+++6cfvrpHHvssdx5Z/B9sWDBAioqKliyZMmnSny3p6dni4vbCiE46aST+O///m+ampq26Lk2B57nfajnScCX4hPdgCohxGv/5/bN/3sOIUQFQTVtNNAARIUQJ2zeV/zx+HRcsnxKefzxxykUCvzmN7/htNNOo7m5mauvvpoxY8ZQKBQ49thjSSaTnHbaaZ/4XC+99BInn3wyjuNw3nnnMWHChHc9p6qqiu7ubhRF4aabbnrb8P29PEEB7mp8inki+EP7I2UlqWei7PX9l7A7xvN4YQIvvDSFaXM2sPyV0aijCvzX3g/SbKW5/ZkFiBqLF+78Nb8dmMs9HbPZ/08v8Wh+GqeuWMfNh45ip8mno5/tor0EP513P5e/eRz4cND0pTyyaAZGRRl/XSxITOIOXhjcZPClUJxgw6CBagmkAooFoRVhFBsKU+xgKCARyHjYXWHUooIKxGoy9GSDicxVG+tQDR/b0hg9v4U1PdWgSbySRtPqOqThIww/mPissPBtFdvSIOwGEhwhD5qi2DVOYOCuErgctIYDt4KCjl5XxCEC/iYP0E29trFomZJqYOc1tDEF3AETf1IBv6SDkKjdBjSWcVqjyIhPcYSHPqAGBvAqyJCP0a3jxny8ooZeFiAV9L5N/x4OlGrAHxQIH+IbCb66tjLnnnsuAA8//DCFQoFjjjlm6wcxxFZj9uzZnHPOOZx22mk89thjTJ8+ndGjR9PQ0MCf//xnzj//fIYN27KV3q1BfX09/f39W/w8I0aMYJ999uHUU0/lySef3OLn+7iUy+Wt/dnu/QBZj/2ADVLKHgAhxL3AfKBLCFG/qbpWD3RvhVjfwVCFbTulqamJ4447juOPP/5tcdpFixbR0dFBR0cHzzzzDD/84Q/51re+tVm2Ci6++GKmT5/OZZdd9p7JGkA8Hsd1XXp7e+np6cGyLCZPnvy+ay5qGcaKuydy57O7cfT4xVjHDPDA3+dz8uiXGGX08Osj/sSlo/7OlHkbOHb8G2ywqrlvwwyotvjLbn9gzz+dy82vzWf9ouHcdPsBnFO5jh43zh5/fwtv0ODeub9DteDCR46lONzHbDJ49MVZGBVl9NdihCcPgiph0MBOBImjllUJbTSINObwDUCAb0BqnY9mgchq1O3SDhIUzQt8O51AXDb3cjX4Aq+og6cgu0Ooms/69mrCIRuloGJ066iVFqGUhRpygySpLwSOgvQ2ZVwSVNPDrd1kyJ7TcZMu+vIIwhM4g4F8h2uriEoreA26JDQQDDDkcmFcR0WxFKzu4Bi5IQo5LdiaNSWyywQpgu3PiIsb9zEGFLSCQO/VsatcpAA1v2nwwBZBj5sKVloSa4PCcEl2tCA7ZttWtw444AAOPvhgBgcHyefz2zSWIbYskyZN4qKLLmJwcJC//e1vZDIZqqqqWLBgARdcsNV7vLcIqVSKcnkzmfF+AMcccwzLly/npptu2irn+6g899xzTJkyhe7uD5/7eCif6PYhaAZ2FUJERLC9tC+wAngAOGnTc04C7v9or/aTM5SwbaecfPLJLFiwANd1aWho4MUXX+Tll1/msssuY/ny5ZtFtPb/kk6naW1tZf369e/7ZSKEoLGxkaeeeorTTjuNM844432dDH4ReYsH599AdpZNYvQgt782D1WRWGmfXcPr+M4bX+K27t34yhunckrD84w2e+goJzlg5EruWfBbFpVG8dWjn+SGPf/CqJ1akRqc2bYLJyTWYPk6X5r/Moe/dAalGthjl+XstPM6Ju63Dj/qYWVDFKZYlMo61S+pmF0Kfsgn0hI4C1iVPsX2GL7uE+oV+Iaka57AyAYyGc2rawHwXQWhgFPlolRYlOs9UjU5YtUFjLiFr0lcS0UzPDKtSaQmcepspCdw7WAr0Y96yFhQ2fMtFQoaKIE+G0KiRpxgOlQBu1Ji9hII4MZcIEj2lD6DuhH99E8D840Ifn8IPxtMpWJ6CEvBNwOZDzevY2QUhAd+hY2WVREZHRlzKTc62I0OCInZrqFYAuEGnqFu3EOq4OsSPSfIjQB8cOKSD9+nu2VQVZVoNMqDDz7IypUrt20wQ2xxhg0bxpe+9CW+853vcNlll3HIIYdw9NFHc//9979rMGFHpFQqoev6VjmXYRh885vf5Nxzz6Wvr2+rnPPDUC6XOfPMMznssMM4+OCDOeecc7Z1SG8jpVwI3AMsIpD0UIAbgV8C+wsh1gD7b/p5qzKUsG2HtLe38+qrr7LvvvsSj8fZc889aW9v56tf/SrnnHMOoVBos5zH930eeOABHnjgAa666irq6ur4wx/+wNe//nV+9KMf4fv+u46ZP38+l156KeVymTlz5rznuj9c14rvC4771TkYEZtJ6R5q6gfJv5kmMXqQExZ9jXvm3sibnY18YcybXLnuQLqcJPtUrOChdVP5R3YWb+ZH8Me35jNW62ewHGb0H5p47F87Mev+73Lza/OZGm7luEmLqNutnbWZKvpKEbqLMWLpIjX1g5DXUDWfnr1tShMs1JKySbJCBOKwCpjdKuYARNoFKJK+WRJRCKYqQ70KquEjdA+pSPzBoB+tNpYLRHhtFaO2hPQV0okCZk0RvaGI2qfjlTTi8RLSF4FIbVEFVwRTo6aPsBS0pAW54LlGd/Ac3/ADz8+8RmhDCK+soWcU1JKgPxdBKoHsBjEXTA+/rIGlImRQqFMLCnrcxq528Sod9LYQigsy6UJZRdgKepeOG/WDvrWQxIsHAr3GgIqRDSpybhj8kAyOVSWXD9tych4fhRNPPJGdd94hBcqH+ISkUilOOukkPv/5z+8QPVn/if7+fiKRyFY737Rp05g1axann376Vjvnf+LfVbWFCxdyxRVXsNdee31oWzrJJ+tf29TD9sHnkfIiKeUkKeU0KeWJUkpLStknpdxXSjl+03+3/L72/8dQwrYdcueddzJt2jSklKiqyk9/+lMWL17MRRddtNkmpXzf58ADD+SMM87g7LPPZsKECRx++OGsW7eOJUuW0Nzc/J5q3LvvvjurV69mYGDgfStx3ogSuuax25feJBUrsXYwTdnROeHwp8mtq6DYGWOJ1cg1M+7iwZZpVIULvNg3htWlOvYbvYq4WuaNG2cC8Nu+Pbhj+k0c+vgSaqd2B4nWRoN7u+cw4EaoDhfYraaJXaub6GgLqn2969IoKRu7qFNZlQdfoJYEbszHqnPxQxKzQ6Vc72EloTAi2C4MtykgIbzOoDzWxnMUpKsEiVY8qHit66rCdlV008VzVEY19tDVk6CcN7B7wpjjsggF8gUTTffwG8uB72fUg5IKjvhfiQxNBtUxPegrk4ZPbpyHYgvKjQ5KQYVNFT7XVhENJYxBguQrq1FZm0XNK29XwKQCblEHW0EZCBwM7LSHUH0Ie0jDx2m0EF7QmyY8gVJS8XWJk/BRHDB7QSuDlheoZUGkbfv6injxxRe54447tnUYQ2wD9txzT/bee2/233//LSqLsaVZunQpY8eO3arn/OIXv8g///nPrXrO/x/Lst5RVTv//PM/ktf0EEMJ23bJ/fffz5w5c3j44YfZf//9t8g5brjhBlavXs1VV13FpZdeyo9+9CPOPfdcJk6cyJw5czjwwAPfU4m7oqLi7b61tra2dz2+cMI9fHnaaxzUuII58SYunvgApubSkMzw+uAI/AoHJFz85mEAKEgUIVnTU01EtXnyoTn0u1F+/+NrWbv3zSS1Ek1Oklt/dijzqjdiVJXQs7D6wXGMMvvoKsb4SsVL3PH8ruAKymUdo6GAlAJZ1OhvTiGyGnati59yESEPL+Zi7DxApFml1ODjhz3spAQFDl7wBgcdvZCamgyfn7oEpCDUbEBeg5CP22dit0WxeiJ4tsqGjTX4tkokUUYaPoXBMEL38PpC2EUd31XBVjCaDQj5KHEHRfdxcgbhmgJKKpiyFbZA6BKlpODHPBCg1pawq4NeMy3koa2OoFoQqi6i5xQy2UgwRCBA+AIv7qJHgy1PrSTwTB8Rc/AtFbVPDzxXbQWZcPGqHHxdIhWJaokgSUxL7BRBAvnvJHA7G0uaNm3af7ROG+LTzdFHH011dfUOOzXa19dHZ2fnVnd2CIfDuK67Vc/5f3n++eeZOnUqL7/8MpdffvlHqqr9//gon+i2I7NjR/8pxPd9Fi9ejKqqLFq0iP/+7//e7Odob2/nJz/5CaeddtrbFbtx48Zx2WWX8ZWvfIXrrruOE0444X1lQfbYIzDfbWlpecf9Ukr+vmImT3ZMRBGSSi1PnZrlR+MeYqeKVhZUrkNkNZBgFw3WWHX8fNJ97J5ew36jV/F831isOpeIagHwpl1mariVfcMeu537KtOjrdy8803c+b2rGHXIBjwEZ456lm8sO5Ejdnud2BoNsTGC8mYcWdQwKstI3ccYVED3ka5A6TMIJS2cVyso1fn4IYkoq4T6Bf68LG9cuRMx1aKrLYUjFfacugpfB5FwAmN2X1C7UCAcgchoKEUVofsUcyZq2EXt0VG6QohkkJhFEiXCNQXsWhe1X0MoErpNRFmllDXx84HbgVJho4cdqCsHSVROCxwYLAWzQ4OVMZyYJDvBxy7pMDGP7woUS4AmA19Q3cdvjmD0q4HdVMxDUQPdNS/qk1yqow0G269al06ob5MBvCFBEiR5IYkbkThJH7MHLpm5fU3lJRIJVFXlnnvuGZL6+Azyb7mKu+++m0WLFm3rcD4yTz31FGPGjNnqmnKapn1o6YyPyzXXXMOkSZPe8XspFAqcddZZHHrooRxwwAFccMEFpNPpLRrHp5nt7Pp5iLVr15LJZLj11lv51a9+RVVV1WY/x9e//nUWLFjA+PHj33F/RUUFFRUVH3j8Lrvswte+9rV3HS+lZExdD935GM92j4MaeKC4E/tVLkfFRxE+x+7+Mnc/tysSSc43yfphRhq9/HHlfA4YtZKrD7qHw+45m7594lxR+wa/aN2F/vQyuq04UyPwcHYmr/SPpOf2kdy0fzWm4dCYzHD/klkw3SL+Rghrfh6KBk5HJLCCGl8itCaMVenjRzzk2hil8RZaewhKoBXATkiizyUoV8A/W6fw5bmv4EqVjBPGabCJLjEpDPdR0xbdh4DMGahJG6/fQAiJokn8nhB6SeCOL0FvCD/pUGyPoZYVdDsYbvAGQxDyIeJCTkctCbykB2UNzxMYvRp+vY1f4aDoHn7WoNwYbKEqBTWYCB00sEIa2qCKkw5M5gUSyipuyiXepJOZIDGiNna/CYaPanpkd1IINYUwMsFAhJ2SQW9fhYuX9PAKGlpOQR8MtkPdrddm85EwTZNYLIbv+6jq1tWJG2LbU1lZyRFHHMEZZ5zBSy+9tEMJKz/33HOMGzduq57T931aWlrwPO8Ti53/J37/+98TjUbZY489mDp1Ktlslg0bNjB9+nQuv/zyzZKoSQneh+xD+zQylLBtZ/zrX/9CURSuuOIKvvrVr2729e+44w5ee+01rr766o+9hqqqHHTQQe+6P5/Ps+uUJu7omUNlpMh9G2bgLErxQmoK03deT1chzh51a7n5sN9xygOn8XDHVE4dMUi7k2JYxSCKkDhS4bLP3869PXP4WyHO3WOeYOpLx1Pz+zA3jJxCuNdnYLxCSIXEw1EUF/q9FJNf6SYzq5r2wyzoDQcKixU2oqjh94Rw4hIMH7Ndo/HpEr0zwgzOclAMj+SzJpkJEBqQiON66V1RxeuHCipfqGBqvJ2lqXpyk0HkNLwBAwRE6vL4voLvhZA5HU+ThIflKUbDmIYLA2G04WUK0sRTNby0Ryhu4XVEIe6gh10cKfB0BTVhQ0sY35Q4jRa4SuBOEFEQjsDs0HGjgeeoUlRBk4S6NfxxBUQp6FlLVhbINCcxuzQGZrooJQXPUVEKKn6Fj2crgSacE2x5WmkvGF6QIuitcxVi61RKdRKtGOi1XTx7+6qu/Zt/v//Wr19PZWXlFjHRHmL75pBDDuGZZ57h29/+Nv/zP/+zwyTur7766nuKnG8OyuUyq1evZsOGDRQKBUqlEgMDA2+rCvxbkHpL8d3vfpcrr7yS66+/njfffJNUKsWYMWMwTXOLnvezxFDCtp2x33778eijj7LvvvtukfVvvPFGjjzyyI/9IfovuYrLxMT3fOy2225jvXsIemWZrmwcKQXe1AJ+WcP2VTpaK9h/wlJu6NgHYQviusU+kQ3cnpnF78bdwavlYXz1rZO5YurfePWVCaydkObwWbdz9ay7mf37fnZ59HvsP2M5c+MbcKRKpVbg4sWHMTLdz4rPNULYRekzoKaMn9epeMGkf5qPnlWwq4MkRi1B295BtU3Z5P9ppcAzJeF+n+6Xqknt0of5bB0L1zaysDw2SKiExA97JKoLFPIhxMIk5Uk2arXFiJo+OjMJSrkQesymPGiiRSXlnih6wsK1VKQnsHrDEPFQuw08LehpU4sKnq4jQpt04toDOym7MnBawFJwoxJ8QbImT359ConEqnMQgyHQJWrCJtOchKiH4yiEK0t4q+O4hJARL6i09YRRrWDYwE4F5/UTEmN9CGu4g9ar4SSC6VCpiu02Wfu/LF68mAkTJgwlbJ9BNE3jxz/+Mddeey3z58/n+9//PkcdddRmm6DfEvi+z7Jlyzj55JM3y3rlcplVq1axbNkyVqxYQVNTE2PHjmWnnXZixIgRpFIpamtrOfDAA7fKkMM3v/lNLrvsMtauXbvFktLPOkMJ23bGqFGjGDVq1BZbf9iwYRQKhXfcZ9s2t912G3PnzmXatGkfuMZ1la/w7f5577r/jDPO4EfKSjxHpVgKo4cdfE9BWirdhRhjRndxY8deLOmsxxibI2Ob3DI4h3ubZ3LEtMVc8PLRrNvvJqa8eAIjH3LoGB5ixu+/jTm7H/XBSm79r+v5Q/eejA918nRuCgszY4iYNi3PjmDiXhvpyscZJIqQAjxBOR3IeCABGaj4F8a4KGUFqUn0ZhMvIhES9KxCOSXwphUolg3e6hxOpKJEWRjIjjCqD8KDfCmB2ZinMDKQ+fD6Qmz004FeWtoibDrI1gh+rUVDdYaOpjShqhJOSwx9eB67qOOmBEKV4AhoLENfKNiCrLPxpI7RoeAbKq4mUcoi2PaUkO2MB9ubyWCCVY34+G7ggUrMRToK0Y2CAjGUMQWwVSjoOJ0RdtppPYtWjMKLgVlVwirp+CUNK+2DpaBnBXZF0MtWbHi3nMv2yFFHHQXA4ODgUNL2GaSyspKLLrqIRx55hAsvvJBzzz2XO++8c7tNFpYsWUIoFPpEk5G+73PfffexaNEimpubGT9+PPPnz+eEE05g//333+KWV/8JRVE466yzuO2225gxY8YWO8+Hleb4NLLjbP4PsVn4/42HBwcH+elPf8qrr77K/fd/sHDz9MYONm6s5ufht95x/9q1a3l+3L3sN3oVs0e0IB2BU9LxXcFeM1aSeauKzkyCVX3VzGls4XtTnqJ9aR1ri9Us3OlOft+/O7XVWb7fMYdjx7/B2EtXUJ/KMOLiF7lr5h/p39VhdsjhuOqFfO25U7h3/UyKnsGRI99i7N4bWPv6CHK5MGrII7TWxOxWEQ4YGYFd4RNfHWyZqAkH4QQfeOGDcDfJemQgN1Lg9JqUO6KE2nWEkIieEMnVAq/KxqnwkKrEao6DJ6CgIZI20hcYjQX8rIGq+nhpB9106V5SA76gPGDiVzhYGROhSpSwi2K6CFvB7wlB1MVrsKCsBj6gFfJtFwSvxgkGD9p1CHlo6TJSEsiK9BsoXSGUNpNERZFQyqLm8y1owwr4nkJVOhf8ciS8sW44esIiVFXCKgainUpJgYSD0avihcGLeyiOQOxAvfzt7e1ce+21QwMIn1E0TeOwww7jF7/4BUcccQQHHnggCxYs4Oabb97iTfYflaeffvp9XWQ+LH/9619ZsmQJl112GT09Pbz11lv89re/5Qtf+MI2Tdb+zbe+9S02btxIe3v7tg7lU8lQhe0zxuLFi9+e8ly7di3XXHMNRxxxBPfff/+H2oZd3VtNuEXHTavc0fg0ecdg7WsjmL/POg6Oryet5vBQqDCKPLluAvFYmdc6hvP5Axdy//IZJNNliq5Bgz6AqC/xzMvTmPzEDFQLal91aLzyTf501wGoO2VwHJXKLzdw9PXziWgw41/fpK4yyzlzH+P+zpmMjvbxQPN0SpZOanIfA2sqUUoKbkTixn1qXlLo/pwHmiQ304GShuwwQZcoZQW7wsPsVnHiUKyX+BE/qMYpEjfh461LgApuGEQmcBCwGhz8mIsQklDEwQw5ZNansPKBbIbtqNTUZujuSaCPKOJbKkpvCF+XiKSN76hQVJERD2kGfqPSEYicgeIJwp2CYqOP2qfj6xKiPjICTkwBKVBXRXFH2Pg5nUhDnspYkda2NGVLx9sYpeONGPZIl1C6RN9ADDVpo2oedtFASoFT1jA2mFgjbKIjchSyJm5MQk0Z0R8CHy6v37qSA5+EhoYGLrroIlzXJZvNDk2gfYbZc8892WWXXXjxxRc5//zzcRyHb3zjG9s6rLd58cUXP9HAwRNPPMFrr73Gq6++SkNDw2aM7JOxbt06brvtNnp7e5k9eza2bROLxbbIuQLh3M9unWkoYfuM0draypNPPsltt91GqVTi0ksvpb+/n+HDh7Prrrt+4PHeoiR7Hb6IpQP1HFm9iOvW7YNXbXNM9WvsbfZzee/O6IrHDcNeYK/BWnqyMRxLo72U4vRZz1H2df68dFd+PHAEp01/ng47SXspxdR4Oy9ek+bWdXOZesAaRkf7eLZ9LJ3zI+i5wDJp77FrWNg+kpcyY9m/ZiVLco30tyaJ1BQoWTqy0kaNOIHsRU5nYJIgskGjXC1RHIFT5YBQ8FMOensIqQWTkKG+oKpUqheBHpoEtyaQ8dAGNQojfRRLoBXBKaj4URCGh6r6ZNelkFpgzK4WFMpFg2JXLLB1kgJ8EDVlGAgFemgRFzXtYGcNtEEVqQd2WX6FA3kNq1IgUw5eTkMrKKgRh/KgiagvE14epjyhTCJZwnI0Cn0Ram8IwzEKkSqbTJ1GqRYiMYtSSxwZd4mkSpRa44T6FdQZJYpdMaxRFuQ1CqUYUveRVRbS0gKdth2jd/sdKIrCM888w+DgIEcfffS2DmeIbYhpmuyzzz50dHSwdOnSbR3OO1i0aNHH7l9btWoVd9xxB88888x2kawtXryYv/zlLzz00EO0tLQwe/ZsKioqePbZZ5k/f/52Ue37NDKUsH3GePbZZ/nb3/7G/PnzmT9/PqqqcuSRRzJz5swPdfzcQ5bxyGszUeI2j8SnEw+VGT5ukFXlelrsSh5qmcp3xj/NgF9iblUzsVqL3WJrOH/JF5gabyepFTlx2kIeaZtCTC2T1AyuHh3o9jz0pkmPu4a/d+3EfY/simrBWcc+wq9f3Ydxf/R4qmECO41sRUHyQv9YsnYIJeZQ7IhB1MOMWcTDZXq6IoFDQIWHWlbxQz4VkwbobU8iVYnI6LjDysi8jhN1QGj4Gmh5BTfm46mQes2g0AhOygMfZNRDbFKRVU0X31VxXBWtoYg9YGJUljEbHLL9UTA9kBBPFdE1j4F1FZB0EJaKn9PxBeiDKr4RbMm6SQ8j6mC7CkqVBVkdxQpicfrDCN0HIfFm5pHZENnBCBQ1jAGVvm8PIJqSeJ6CbrrYfSZ2u4miSryiCimgwsYcVSRfMJG6D7YSbM2WVHwBoYoy5b7A41Sxd8yr13322WdbhzDEdkRtbS3r16/f1mG8zfr16+ns7PxYzf+Dg4Nce+21XHfddey0005bILoPh+u63HrrrVx33XWsX7+eXXbZhS984QtMnTp1q+rKeXx2e9iGErbPGOPGjeP8889/x30777wzjz766Ic6/vDmA3neaUbVfV58dRLz5qxharydnGfyXN84jh65mKJvcH3/zkyPtNLvRVlj1TGluovbVu9M7JE4fTt5VI/q57bmeVSFC0y7fS/+fvqV7GoWKPg9pBoKnD+mlmmN7ZyQWMKfVh7EmX+6hbVWHS3lSv51884UPlfAdxW0kAcDKn5WpZRWsAsx0H2EI4i0KNgpMPpVMlVhlJKKMaiglsHJm9g1DsITeKYM9Nk0FT/sow2quCbYVS6hbg075aFlNJwKD31AhTYTZWQR11YJmQ6irGD3hPHyUahxEBmN4VM6ae9LUmhPIhSJ6DOQmkSxBbGJA2TDEYwNJnbKR4vbxKNl8kJiD5ggwEu6qFkNs0VQHOnhegJpuugxG6ekU7lIZXCvEpmeGDNmNbFk/TDSNVn6cgb+8BIh06HcFuPfYuKZ9gSEfNJ1Wfq7ElBW8CscpCtwNsQg5qNWWrjhHfMr4dlnn2Xy5MnU1NRs61CG2A6ora1l4cKF2zqMt7nrrruYNWvWR05sXNflv//7vzn22GO3iMzTh6G3t5drrrmGm266iWg0ysEHH8zZZ5+91Qzsh/hfdsxv5yE+EcVikZNPPplIJMJXvvIVTjnlFK655hqWL1/OlClTPvB4mXCZ0djO2nCapd11vNHeSCpawvUVxsSi9DlRsq7J6wMjaBqohH+lqDi4HStvIEeCWmGj35SmVKGw+HMWWkpy4k/OYfDzBeYOa+abtc/ilDWWPTqeA+eeSnlaibt75tJvRYjpNrldS0RNh7Dh0LuqilgP5EcEiv6KJfArPLR2g1KdJDQgKI50EMWgB00qUK6SoEr0vk3N9zZ4djBFarZruBFJcbiP0HzcsCTaouJGwDNFULUrKviDIUTExbY1ZMiHkI8nQWQ1RNqiOxMPfD1TDiKnIatsKtN5+ptS5HJhtJCHVeuCKwi/HqF/qoYyqKMIiRfzEK5AuFDaNLEZrSxS7IzRMK6b1mKayLEd5Afj+DmdpoFKamozzKpq47HOqcjeEPqGME4tFDpiSMMPrkmLKv29MYyEhW2HCcfLlLJmYDjvg7Eswk+nb/9yHu+F4zgf2+pmiE8ftbW121Xj+z/+8Y+PVR277bbbiMViXH/99Vsgqg/H4Ycfjm3bnHXWWYwfP36bfs4kn+0p0aGE7TNGJpNh3333RdM0GhsbOf744znppJO49tprOfvssznttNNoaGjg8ccfJxaLccQRR7x7kZzG8q5aykWD4XX9qMIna5n0b0zxz7fm4dQ6VNcNYmge2Z4oYrxHUgqqq7Ncuvvf2Tfs8Zc5VTzSN41BO4w2yqc8V8O9fQR/ueRZJv/+DNZ/4zfMfe4M7pj1R45581ReWjSB6tH9rM3UcNCk5azJVrO2tYbqib0MNETQFImdDaGOK+LmQ4jxeXQhseo01J4QXszDjUi8uIeWUTH6FYqjHIQvULMqXiRIjMoJH71Xxwt7SE8gNYlVGfS56TmV/HQLvUPDrrSRRQ3P3TRxGvWRqgKuwM8ZlF0Fyip6uoyMOIRNh/7uODLk45U0ZMhDzal4cY/85EDA148oSFWiZjR808eL+7Bp/WJPFCVhkyuHmPjrMi0/ipCMlsgIUFWfwXyYZWodUoIiAQlyZAlVSFTVx+4No6XLuAMmocUh7Ake1sY4pBw8UyJ1SWmM/e7f9Q6AZVnss88+O5Ti/RBblnQ6zcDAAMVikUhk21p2FAoF3njjDb72ta99pONeeOEFXn/9dd54441tKgxsWRYHH3zwJ55wHeKTM/QN9xlicHCQz33ucyQSCb7//e/zpS99iZ/97Gf8+c9/pr+/n6uuuoqbb76ZCy64gJ6eHh566KF3rXFuaR0okgXDNzBhWBdfaHyD+VUb2LthLXvOWcGsPVYTXa2Teb0agPlT1xKqLtK9sJ6w4bBv2GPSCydyRLSFY6tf5Uv1r3JwzVLWbKjHOLqb8X89nXKjw8SbzyDxpVYO+9O5NCSySNPH8VXG1PXw+KNzaM8kmT2mhcF8GKfXxO4KE1mr4zoqRquB3R0matr4dtBnFkpYoEq0QRXPlNhJid6vIQUk1om3e7fUbNDLRcgPpjKLCr4BhUk2uQkuareBnfKReR3MYNLTGFDxyypqwsGPehB2wReImINT0vBdhdxg0FdnJGyE5qNoPp4pMXo19FgQJ7pPdH0wbRpuV0GCUmmBB2rcQfqCwc4Eq74dopQP0bsujVPSyBdCeJ5CydGDtZIu2fEenq0gmsNUxovgg9cVRk1ZFIZJ1HywJYoqUSyBUlLQIs5WfT9uLh588EEeeeSRbR3GENsRqqqSTqdZuXLltg6F+++/n5EjRxKPxz/0Mc3Nzdx0003cdddd1NXVbcHoPphYLEaxWNymMfwvwZToJ7ntyAxV2D5DnHXWWSSTSU477bS3qxHpdJof/vCHXHLJJYwaNYqzzjqL7373u+y///4ceuih7zj+wiWtMEZw8u7PsSzbwJo3RnBtqp66+kFGJgZYuGYUyddCFOZaLJiwjiojzyizj4PSS7k5tRv9xQhrnDw7NbRx4roj6S1F+dvUWxj0BQv2Xct0I8yBB89kzXW7cthBC/n7yzsTErBiXSNC95le1QFA59RBRlX005ZLoqo+RAPR2PDnBtAfrqJcBcaASqZYiT6iiJUJITwBYR/FVwn1KYFgrO6DIhmY6SFsAQqYvYJSXWAUL1yBG/eQhkQUVbSigjk+SyFjQkmDsooQ4CR9QkkLRZF4JQ2tI4RqgZyaxxoMwYCB6gQuAm5Gg5iHZ4M0PcIjBxnsim8aLIDSpDJayKMUNhG2QNM9LNPHLfzvR1XRfcywTWnQIJEqklufwot5eNEyUgrCiTK2qUFbGDfl0bk+jVJhBzpxayK4CR/qLZQOEz/tEBoUFBt83EwoGFLYwTj66KNxXXdbhzHEdkZdXR0rV65k9uzZ2zSO++677yNth/q+zzXXXMNFF13E7rvvvgUj+3CMHj2azs7ObR3GEAxV2D4zvPTSSzz44IOccsop79o6GjZsGNdeey0HH3ww11xzDRdccAHr16/nkEMOecfziqMc9KjDukI18yvWQW2ZxFsGvYtrWDNQhRryqDiiDTxBlZFnYqQTD8EYvZu7Jt3Bs7NvZrwe47UXJvCdYU9w8siX2Hvh6TxemMwzxYn8KVvL7m9ZXHLA33j4vl0YMb6Lyl26UEyXo6a/yaK/T2Vh60hGpAZY2txAfz5CqT3Q+xG2Qr4UIr+gGCRjPmhFgbIySmytDiEfo0dDaSjiGxBp21RRM10UKzA7F7agONzDj3iopotaYYEA4QrUsoI0JOU1CYyWEEpRwUiXQfeRAuy+MI6tYcQt3AYLOTUfDCV06vhhj2i7ILFGCapZWQ2R0RGeINOcRPgCBGgdIRpqB3H6gmlOqUr8dTGUghp4iAKhVBkj5FIZK+KbPvmVFYjaMkL3GeyO4w2GKLfGmFTfhawro6cszNoiquaTbMxgV3v4YZ9UsoBoKKF1GrgR0AoKV6ZGbfk34mbE932uvvpqstkshmFs63CG2M6oqalh2bJl2zQG3/d55plnmDNnzoc+prW1FSklP/jBD7ZgZB+ehoYG+vv7t3UYb+MjPtFtR2YoYfsM4Ps+p59+Osccc8z76uPEYjFmz57NIYccwo033siYMWPeNQUkFInnKFSF8iwrNOAPGmQneOjjs4Q0lwPHr6B5SQPfmPscL3aO5q38MHTh0ePFuTs3gePXHsXrts3LX7mab/31m1z6/KHYRZ1rnz2IP/3mUH7x6iH8+dG9uOj5I/nOlx+geW0te9atBeD5jjE4c/Por8YoXDaMKcM7sAsGatpC2mog42FpKIqEiIeQUG5w8ELgGWA2Gfga6EuiSAWK4x2UuINvqxgDCm6Ng4y74IPeq6OvDePZKtWvKhjVJdyUi5ZX8GpsfD2oxHmuQn3DAOGGPABSgu8L8AV2wQAJ4Zn9KDGH/NwS+fklhCdQygIZ9YKET5OIshII807M0NZZgZK0Mbp11LISeHumHKTpE6ksETZtrKJO66pa1IKKbCgHTgthB9V0+bdNQWs2iZ8xcDvDlAZMnKKOZetBJRHo21iBZ6u4FS72cIvLRg3fUm+/LYaiKBx22GEkk8ltHcoQ2yFz587l1ltv3aaOB6tWrcJxHIYN+/DDPGvXrv1QFoFbi4ULFzJmzJhtHcYQDCVsnwluuukmstksBxxwwAc+d/78+ViW9Z5XVNPHtrJg7Hqe7xjDU2smgBlUsor9YSxXI+eYKA1Ffv/65/hc/XpCissf18znkYEZ+FJwzeh7uLDpCDo9gTe2xKyJzehhFzWvcP6370DfYEJjmbkTN3BH687olWUe+vMC6DTJlwNT58JYl4ofb8SVCprpMGtEK2peJVKbx1wWxskbKCGX2vntaDEHJ+1QbvAo13oID+yURM8BlgLdJtITODEJtoLWo6NXl3FTHlatR3hNiJ5dfJyOCFq/ht0Y2EW5tTblWp9UokjXympK+RB6vxq4GqgS8hpqj45meGQzEXxLQw+5SB+8YWWSM3rRenTsbDBpqjcUQUKpNY4RcYi+HsaucfDSm3rifIEoK3ieQrEUIhK30GtK+BEP31PwczqKIvEHQqgJB5lyyGYiJIZl8SMeQpVIT1DOG4gqi2hNIZioHdDRBjTUrh2vOtXa2sqzzz7LxIkTh6ZDh3hPZs6ciaqq3HvvvdsshmeeeeYjT1YmEgn6+vq2YFQfHs/zeO2115g+ffq2DgUILoo9KT7RbUdmKGH7DHDTTTdx8MEHf6gpusrKSlKpFKtWrXrXYzOSbVQaBXIlM3juQp3EGpVQh05/b4x/LZ1AMl6isirPky0TWJ2roVAw+VbNUyTVIhc0H8VPRj7IF145Dc1w6SrESUVLRNoFP3rki8Tn9HLghOUseXwCG5uqcW0VZe9+LjnsLr435SmEkCgFldY/jGXVxjpkS4QV3TVEWwSjK/tJ7N6NOqAh2k1al9Tj9ZpMG9+KmrRR7EBvTXEEpeEuii2oWCYQtgIC8ARmj8BzlKAKJcHXASOwq/ISHsqAjjKgE0mW8Csc+no3NRG7Co3z2kikC+iaB3GXyPgMvi/QTZd0XYZyfxjfVZAZncFMFDmiBKpEOip2NhRU0eIunquQnewQqSih9upEqgtEUyViI7PYvWGUlVEKmTBOv4koKxgRh3hdnlJ/GLWqjLY6TDxZIpEskl+fQuiSYcP6gh4+S2ViYxeFgXCQ7Kngplx+OXLHq65BoGo/xBDvhxCCuro6ent7t1kML7300kcWy504cSIrVqxg8eLFWyiqD8/TTz9NPB6nqqpqW4cyBEMJ26eeX//616xevZpddtnlQx9z1VVXccUVV7zr/j4nii8V6pJZ0qk8dhyiXT7Dnyoz9ibJzpObsB0NVfi4L1Wwb/VKTpvxHOdt+AI5P8yRNW+wa0jjvOmPsWL+rWSer0FKOPaUp1l3zO8YWJUmrRdYftpvEKoknigRuqeCOzrmcfmiA7HyBgfs/gY984IGfd+QVMaKlKth3ZOjGSiE8WsshC9ofMYjMSJDazaJqntoeSXYNq2zUXMqwhV4oUBUFwlEXfJjPfyBEFKVKCUFa4QNZQWpS5CC1AqBrLYodkcD2QxHwRhQUEyXpuYack1JSkWD2NLABN7vDGMXdPrXVSJ8qKnJkhyRwfcEnqWCF/SzoUhCTSG0sIP0gn62Uk8EdWSBYkeMQtYkHS2QWK3y7yGn+tG9qLUl4pEypbJOJF3EMFyccSXKy1Nk+mIYw/OoIZeibVDZmEGEXdZ2VQcadDEbaXqIyI7XrL9q1Sqqq6s/0nt6iCG2BcuWLWPUqFEf6Zh4PM6JJ57IXnvtxT/+8Y8tE9iH5JZbbtnuPmef5SnRHTv6IT6QH//4x3z729+mt7eXpqYmNmzYQHNzM319fZRKJaSU7zomkUgwcuTId9zXNf03PPriLB54cyaWp9HTWkFhhE92uMLguXnUssuyR8fjvJFiVHKAk094jCW5YfyjYxoRzSGt5llbruW77XP51e8Cv8eaRQ7HjXqdH1et5Ki1B/DrI/5Ec6mSy/omUPGqQbFk0HdQmVSoxPTh7Qxr6OeRZdMQCQeKgddm56J6EusgsVEyqaYbRfdxoz69MzTKSyooWQbhkI0blWiNBaQv8MI+akkwOMnHSfr4IYnSZwSVtU2+oH6Fg9ZpYAyoaNnA73NwikTaKkZlGXyBNqBhjy+BBLU/ENCVvSEKM8oMdMVJj+8jniqhWAJCPqbuUCobSE+hrm4QHIE2rIAa8rCG28jWCF5RR5RURvwDzFDgxCCEZMPGGqQCVp2DtBX6clGcnEFve9C/lYyUKXVHCYUd/FGlwD7LF0hP0BjPEDFs9LCLkzdorBvA7TMRhs8VoY9vRr2tePbZZ7erJughhng/MpnMx+qx3G+//TjzzDM5/vjj+fGPf4xtb32NRN/3eeSRR5g/f/5WP/cQ782QrMennHQ6zS9+8Quqq6vRNA1FUXAch2KxSKFQwLZtIpEI0WiU+vp6Zs2a9a7pUIAHu2bQOLmL4bFB5iQ3og6X/PqtPbnvqOv5Y/98XqqYBwpYY8ssah7OoubhHDV5MRtzFZiqwy3tu7FLZRPPdYzha19/mGfKgqYvwBvZEYx/6EC8tMtB42zOu2cab+7RQHE4jKzu5+C6Zdy1cQ671W6gI59g7PAuBkoRMmoEY0OYwmSbvhqorMkxYIWRvkCtKuMUIrj1FoYMbJnmzF3Log3DEXYw7alNzWD3RNEryyDB7jdBl1TWZhnMRJB9IfzhJdyCjjYYVOFqJvXQn4vgr49B0sOvszBMF6szAmkHiipqWSC7QhCS9HQnSVQW8EOScKJMS0cldTUZ+pfH6O2qZvScNtpeGoaf8CHp4kV9QqkyyWiJ5mOS0B/FqCuiaR7FnElupoWQwfCHnQ0hfEF8hYaxfwYhJOGaAqWuKHq6jNsZxq+w8S2V1T3VyJVxkjv10FvW6HmlDmNiHqe84338y+Uy3/zmN7d1GEPsIKTTaW677TZOOeWUbbKFXigUPvYE86xZs/jpT3/K73//e26//Xauv/56DjrooM0c4fuzYcMGLMti+PAds2Xi08hQhe1TzhtvvMHGjRtpaWlhw4YNrFu3jubmZnp7e8nn83R1dfHss8/ym9/8hjlz5vDYY4+9a41zS+uxPZXrJ9zODxoe4/amnfnVy/tx3qzHOOSlM3nwtgW07K+xx6FvIh0VdW2YaLTMmlw1HZkEu1eswdRcVOGTWZ/i2xXrualrdzYc8gemxdsY/WCZUXfBBV0zOeyEFzBUj8plku5cnCW5YQzkIgw6EWqjOZq6qihZOp6lUphkE1kTfBmqwkdB4lsq3kAIN+GhGh52UUdNOLy+eiSyoJFcqVLTOID3VhIl6uC2RrHzBvG6POqARq5g4mcNSNl4JS1o9q+3SI7I0NWbwLE0vMYyhD18S8Uu6kHFTwHhB9ptobFZZMxFNV3Klo5aU6LYH2ZUQy8dG9NIDYwBwYY19SCgalwfIFGTNq6t0tNUSShmIbIaZshB1zwi8TKK5mNEHZIVRYTuMWpMF/nZZXo7kvQMxvClQEnYOAUdra7ElBEdVDVkALCH2fQNxoJkr9JDSoH0dqyPf39/Pz/5yU/wfX9bhzLEDsJXvvIVHMdh3rx5XH311Vv9/LvuuiuvvPLKxz6+oaGBCy+8kMMOO4zjjz+ez3/+87S2tm7GCN+f5uZm0un0djXUIxH48pPddmR2rG/sIT4yiUSCdDrNH/7wBw499FCqq6uJRqPouo6u6zQ2NrLnnnty6qmn8uCDDzJ37tx3HH9r/bNUV2eYmOzm1fIofrj+KPpaUxwy8y3KUmdYeoAFx75J7dRuFnaO4MxdniY2u4/TJzxHxjKZVtfJgvBaZiZaebhjCmOmtdHtFRm0wzxe0ui0khx746N07KazKlfLHW/MpTJSZM73FzEu3cvingbCps3aTBVjYr3MG9VEPGwxdkQXKODOylP1nE5PcyUtixtQQh4ICPWouDkDpc9AN1zUXp14XZ5CPfStqsKq9aDLxByZJVmVx1mUwgtJXEtFSdgouo9aUBFpC1nUyPRHA6uqgkZorYkaclHzKqIvhNIVQtoKwyd3wrgC7tJkUG1bG8HzFHxXQRg+G9bWEerUsCs8SvU+hD08Q9LTlQykSVpNVN0H08cqGEhDku2NoSqSRNgiZDrYeYNc3kQ3XbqywVSp0Hy0FVFcW8Mv6CghD89VWLZsBGVbpzxgohoeftZAD7lUj+onGrFQ9G0nd/BxqKys5Oc///mQBdUQHxpN0/je977HggULOPfccymXy1v1/Oeddx4PP/ww99xzD8uXL8dxPrqbiBCCz33uc1xzzTVIKZk6dSp33333Foj2nWzcuJGKiootfp4hPjw73p7IEB+Kv/zlL1x33XUsWLCARx55BM/z2H333bnwwgtJJBLouo6maR949bTy6bGIqTnWZKtRhKRtMMnECW38c9k0BsZHKNghHls+GYCZY1q5t2UW/d1xri3sy692voMfrziSwYYwd6/fiVxbnEh9nm9vPJJV/xrDzJP/xn91jOWh/FR0F/KOgRZ2qDHzPNk0ged3/R3ntR3A4p5GdMVjfb4KU3XpW15Fd9X/9nQMHFAivjBCYZSPbwXbl1aNhwh5+D6Ue8MQ87HeShHthfwIkJqPl/DxfIViv0l1syQ0qJAda6A3FrA6oggB4YhN0QqM2UWNhZks41SqeN1hzGEFfF9gd4dRSgotnZWouocyJYe2Jo5V6xLWPSxXJ1lRIKeFkZVlFFtFC3mYhkPWiiO0TUbzFRLFVoN+uPoyvhL0F/Y3pQjVFbE6IyiuQG010KdlKJd1vP4Q9WN76ShWgaVSM3yAiG7TtLoOTB/HVamoy5HNhpGqxClrDKypRi9A2AJ23mJvwc3KokWL6Orq4uCDD97q537ppZe49tprGT58OOFwGNM0MU2TUChEfX098+bNY/jw4dtVJWKI/0XTNPbee29++9vfbnWB5d12242bbrqJBx54gFtvvZViscg555zzkXTZ/k0kEuGkk05i7Nix/PznP+fYY4/dAhH/L21tbdtlwraji99+EoYStk8RlmVx3nnnUS6Xueuuu/jSl77EihUr2HPPPdl7770/VmWi3OgQXRSn04nTNDuNW9C5d5ebmNp0Ji+tGovaoxMemyNkuPhS0NFaQao2x8ljF/LthV9BbAzzy9jBnDjuFXKjTW59ax6/HHEf+kmSfxTGsU/jGnqsGD9f8E8uaD0MLx3EeNWse9jzlW9QES1RH8vSkU/g+CqTKwIF/+qKPD2dKezeMFOnNNPCaMLtCnbBwItIlPoiblkHT0DMDbYCwx72MFAMD+GoKIaHIiTxVAnPCDE4I7j6LQ+YKBISowfJNCeJNqs4MbATKpaiIaVAsRScDTHcpIdaYSP7QsisjlrrYJd0ZIWLYrqUMyaK6ZJtSiHSFnZJJxS1sbojyLQg1ZAllwvj94TQqi2kD26Fi3BUzHQJx9ZwfY1yfxgR8fAFuFUedncUqUgSjTkG8hGUkoLRodJdrMSsLSISDo21A7S2V+JaKn5eR7EUzCqbxKwcHW0VXBUfvVnff1uSUaNGbbM/HjNmzKCiooKWlhbq6+upqqriuOOOw/M8Xn31VS6//HI0TWPevHnMmzePsWPHDlUBtzM8z0NRlG3yezn66KM5+uhg0OqKK67g4osv5pvf/Cbz5s37WOvtuuuu3HzzzSxZsmSL6qO1tbUNiVJvZwx9q3yKOP3003nsscfYsGEDF154Ifvssw+nnnoq++6778f+ohKewJ+dI31AO+OusKl/SuOfxSp2mbCBqaPbSE7pZ88RaxmeGGRcvIeRo3qYlO6hy0kw7DYdrQgrNtZzwyt7cXb6NaSr8GJpFKqAryW6qNGzjI308GhhHJV6EcvTePWRqfy1e1d2adxI+6oahkcHGFhfQSpUoqWQws8ZdHekUCMOC3ZaRUsmRWFeCcUGdWKO5CqBuiqKEbWJNuTR20LopgsFFekL/IwBSiAmW+yLUFqRIrdvICabrM4HQrOaJNMfg4iHOy+HXeUh8hqyJQIy8B310g7CEcRiZYx+BSVpY2U3bZEqBAMQYTcwcbcFxuowuApWd4R4Qw6nO4znKVRX5FBqyiiqj6r7iE2TqnZZw83rqHmNcGUJ6QdXll5RR4k5hDp0YqZFuSOKl3QpDXch7FEaMDHCDvn76gnF7OD5cQeRtihmw/TnIuDvOFepa9asQUrJ6NHbJsGMRqPccMMNXHHFFRxxxBHYts2vf/1rPv/5z/PXv/6Vzs5ObrvtNqqqqvjtb3/LmWeeyd///vdtEusQ701/f/92US0677zzuOeee/jTn/7E0qVLP9Yamqbxuc99juuvv34zR/dOOjo6qKys3KLn+KhIGOphG2LH5/nnn+e+++7jnHPO4Rvf+MbHKrm/F3OmbiAVLTGtooP1x6TIHZvlreIIbh/9FNePuZv+3hgJrYwvBUmtRPOaWsqexgPrp3HslQ9jV0hOnLWQ6/a4jTl3fJ+qf+lc9dtjOXP9MXy3fS5lX+eFvjGsLdeyMltDIlSmakEHOyVayDsm39n3URb1DEcaPh35BF35OKHqIpPGtjOqpo8X3pqA5yvUVGbx98zgrotRGAaVK3yiT8UoDIZhbCDnoeVVktV5iLqIQR3ddBGGT+PzLorqIxXIr02hdRtomWBrNVmVx+oNg+khfAIdNCHxoh6oErXCJteUpNzg4ud1jLiNV2Wj92lo5v9qnHnRwHNUGdSIr1FxXBWzvoCi+PTnI6iqT21FFtdSMaI2yco8vqOilBVCI3KUM2bgeJDVSNbm8B0Fe6RFe0slalU52FYNeYwY3ktVQwbfUyjtkwuGLnIqvqME/W26h+cp1A4b2Czvj63BmjVrtrn5tKqqjBo1in322Ydzzz2XuXPnsmDBApYtW4aiKOy999784Q9/oLm5mTlz5gzJjmxndHR0MGLEiG0dBgD7778/F1xwAffff//HXmPPPffk3nvv3aK2W11dXaRSqS22/hAfnaGE7VPCBRdcwOGHH/6eXqG/un3j+x7345WtnDvQ9J6P/bXhGVb21JAthXj+L3NgXAHHCUzIf9g9I3iSpfJoyyQimkOfHWP61I2MivYhBFzzxn5ITXL/n/bg2499lTVf+S2qDaVdCjRGBlmeqWVkqJdJiS567Rir19cT0226M3EU4TMr2cJv7z6YXCnETlObSJolBvuiCGBjXyU9+RiR6gJx06KjM0WhM0Ziaj92o033zgI7BtgKnqOgaR5e2CeXDaP2GOgZBWVJDPIqGw8VeGvjQWJj+kTbwY35YCsUioF9lMhp+HrglOD3mKhFhWiijOwyUWtLQVVOgepEUKFza23cso5nq6i6T6RZpTzMITZukPzsMuXeMOVsiEx/jFjYwumM0NJchWp4uG0RHFcFIYmNyFKdyENZIZQqI1VJqWygh13Ia2gxB6/XRNoq0lIpOzoDg1FcW0UujxNLlBENJZKVBYaN7kEPuXhljXNzO33Cd9zWwXVdDjnkEKZOnbqtQ3kbIQRHHnkkhx12GPvss887XEGKxSIvvPDC21tgQ2wfdHR0bFd+mN/+9rdpbW1lw4YNH+v40aNHE41Gt1gl1/d91q5dS0NDwxZZ/5PwWRbOHeph+xTw5JNPsmLFCs4444z3fc4P17XimRJteAGnrCFzOnq6jEIUEXE5t28jk364iubTpwAw+qAN2I6BpnpYtk52lg29JnNnruPprvF8adhrHHHledT1+oiTHPKuQV0ow0OrpjJmUi8TqnrYrWI9GTfMbcp8Zk5r4ifd0ygem2FiaoCH35hBuLLETf58mlbVEW3ME0pYrPjneGI9cIO1J15JQx1fQlmTINLQyhtvjqF+fA/9+QhWV4SyJkk1ZImHynT6KZKNGTLLK9FGFPGFjr1zAQZCeGWNkqVByIdBA6lL7EoXKUG4gQCu1CSy2oK8TmaWTWS1gZNQcFyBkrRR8wp2tYs/vIR0FJRug1LBwA/5+JaG2q/hG5K+XJR4okQ+b+IVdKJVBQzdIztVIRqxsRyNyso8g2oUL2Og5hXykRB6fRGxPIY1yic+KkuxZKB1GehVeZrbqoIt0p4wxDycgRBKSQXDx3cU0CTjxnbQmQ2S9XDEptAZIz6nl7Kt41ka+bYKMvHgavzK1Kgt/p7cXPziF7/gpJNO+shq8VuDgw46iMHBQc4880yefPJJAAzDIJVK0dLSsl1swQ0R0NHRwaxZs7Z1GG9jmibHH388zzzzzMfe6t9rr7343e9+xzHHHLOZo4OXX34ZIQSNjY2bfe0hPj47drr5GadYLPKNb3yD4447jqOPPvp9J6A6vmhTsUJS/Tpob8TwSxp4grBp400sIDMGE/9YYNV1m65ABazprmZmRTv2K5WU8yGUQR21wsZQXfzf19JkVaMd1It2SheDhTCur3DTQ/tSX5Xh/rdmoQjJjUsX0GUnSK5WWfryGB5vn0R5eYqcE+Jb85+isWKQoxrf5Lt7P4aq+IQMl2i7JD8SZF8INewyuq4Xt87ilaengJB0rq7GaY0Sb8wFCYsv6CnEEDmNwooKqt6CykQRL+4hhETNqgjNx0hYQd+WJvHjHmq/hppXkZrESbuoZYHoC6FlVPQOg+JwD6nK4JgeE2eYhZpX0deGUfoMvERgqo4nQAoUR6CWBY6tUbZ06AmhlBRsW0MREkXz0VQfqzfMwJpKhOIHfXS6xOmMkIyUsNIequ5TLIbwijojd24lvyi9SUJEgbCH3m6gJhwS4wYYNr4b1fDA8Fm/rJFS0aC3P0YxF0JNWWQXV1EqGAjVx025SEUGTSA7EOeee+67XDe2J6LRKDU1NW//rGkaP/rRj7j99tuH9OK2Izo7O5kyZcq2DuMd7Lbbbp9IU23PPffklVdeYdGiRZsxKnjllVf4yle+wt577739TT5/wv61oR62IbYJ2WyW3XbbjcWLF3Puueey//77v+fzHh39ENqaMMpXehh15mqcGOgDQXXGebUCt89EKyi07pcgtNrED8HUQ1dTncyzIlOL4kDiTYO6FyVuXmdZbx3V397AC12j6WtJ0dJcRblosLGvkgV7LWWv2jUcMHU5bbkkV8z5GxtylXzt9Ic47/P307esCi/iMzw2yJ0bZ2OqLtc+dRCKCP6wWbbGzDPf4utHPsbsOeuYOryD9qeHo2g+6oQcRk0Jpcpi2NTO4INXVvGeryC7tiKwhRpeJv+FLIbmYlaWsEs60TZBKl3A7owE/yASREHFMyVezAu01GyBr4Fv+HjRIBa1qAQG7YoMEh1XgdoyngF+pQNSEHorQqQxhxGxcVIebtJDM1y8jVGUuhIy5eC3RdAUn+mNHeSakqhJG62xSCjkgiZRLIFMOvR0J4k05FFUn8pkHmVQI1s28cYXkZ1hZGMZ6Sq4w8r4niAzEKGtqwInGyKULCMTLr6j4rsqquFhGC6+LqHLRA+5wWSs7nNlxait8fbcLKxZs4a2trbt74/G/6Gtre1d27WnnXYaiqLw8ssvb6Oohvj/aWtr26ITlR+HyZMn09XV9bGPj0ajHHbYYZxzzjmfOBbXdXnggQf40pe+xP7778/BBx88tK2/HTKUsO2g3HjjjZTLZc4++2zGjBnzrj9q55bW8SOxkpxj4owtMbu6hTUDVdS85hFpF6hZFTkrR2K1imqBcEHOzKHlYfUdEyjYBstWDadUE1RlvJAg0qwx2Bdj8drhqIpPsiHLpLHtGGEHa8DkubVjufXVXUnoZbpXVPOL1YdgqB69TpxTk21EJwyCFLy0fjSDmSjLVg4HFa5duD9fHvsaF8x4lAmRLl4dHEVPKUplqMiIfTeiGR5yWRxFkXhZndbuCkob44ioQ2SvHhLjBhC2Qsi0KWRN2ntSSF+gaD75uSXySyuRYQ98UCwFtaiA4SNsBeEIQr0qXtRHuAK1FJive6Yk9FYELa8gqiz0mI3vqLgxH7U3sKuyZxaw1iawiwaoEkyP6kQet8LFc1QoaNS/4NPVWsHi5kYqx/Xjd5uk4wWKzXH2nrYCqRIMQLQbFLtiOGWN/kwMbXiBTDGM7yoo9UX8TOB1Kn0l2JLVJDKrIww/sMayFERGQzoCt2AQMy2MMTkUF+yiTlU6x5XhsdvmzfoxKZVKDA4Obusw/iM1NTXccsst7/jDq6oqv/zlL7nlllvo7u7ehtENAdDd3U2pVGLy5MnbOpR3EI/HP5aQ7v/l4IMPZvHixTzwwAMf+Vjbtrn33ns59thjqamp4bvf/S4Al156Kfvss892eaEkCXTYPsltR2aoh20H5dBDD+WSSy5hYGCAdDr9jsd+tKoVRoCmebzZ0YDvKbz8uzlULc7Ruo9KYayD0CT64jjZcT5GbRFeiaGpPrH9uqmN5tgrvZon4pNY86/RpD/fSlc2jlUy0FSf6PNR3CfqyOzrkl9dgZt00fs1lC6N6PRB/v7ELtTP6KJgG8xMtbF3fDnzzz+TA36wkFHje3iybzID5TCTxnfxxq92om+6wqMdU2hqq6amJoOq+AwWwgwWw2T7oyiGhxxdJmE4iGpJuWgQGlag1B/G0DxyL1ZTvUsP3d3JIGkBGqe2kymHKb+QpjjBRggwBlTslI+vSQh54AtkWcELS4wBBSchiXQIymlQywKrUmL2CvKVWtAr5gUf9sj4DLmWBFgaxHwUzUOqPtJTaO9JIUoqSsTFUyXteymg+Ehf0NcbR6st0bW8BiMneL5pLF5IInxIz+6mPx/BtYOhDrs7TOP4HnqIEdJdjJElCqUQqupTyJqI5jDaqAKKKvE7Yrh1NnplGbclSnzcAN3tKYThIytdlIwO1Vv7HfrJmTFjxrYO4QM56qijyGaz7L777jz33HPU1tYCgfbWokWLuPTSS/npT3/6nsNAQ2wdnnnmGQ455JCtLpr7QYRCIVzX/eAnfsAap59+OieeeCIXXngh++23H4ZhoGkaY8aMQVXVdzzftm3uv/9+br/9dp566inS6TS77LILF198MfX19Z8oliG2PEMVth2UyZMnc/zxx3Puuefyy1/+kuXLl7/92C8mDmOX8U0Ue6Joqo+iBtt8XfPieGGChnUhkTNzDJvYhVwTI9bmU2iLYWoOlaECD5/0Oaan2vFMSdnVOXnCQqQncMs6uV1LFKsFFFVSk/tI1uRxkx52tUt5WYpwp6B9ZQ3+k5W83j+cX7Xuz80/v5p7XppLk1XN+Fg39dEsO8WaGXb6WhbsuYyBUhgk6KpHXy5KKWviegpGLPD0VDpDZFqSNKQy+CUNq6iTWKHRtqEKY/YAvQOxIFkzJGpRYWNXmv7eGHZKYkRt1JCLXe2iVFjIkA8lDRTQcwKtIEBCpE2QHyHxDYlUwa+1cObkARCOgISD8CHXEcesLxCK2hB1iSdKhKMW8VSRkOkgkjZSBnJtVNhEK4vopou0VLyuMF7cRZmWxek3qRnbh4wFwwDWwCYfUwAFaiJ5dM0j35xAV3wipk2pKcHYYd0wqoD0FZyyhhhTwNxgYPcGbgYASlGFvIbwBdXj++jtj2+9N+dmwrZt/uu//ot8Pr+tQ3lfhBCcdNJJTJgwgd133/0dFcGf//znfP7zn+f888/nxRdfRModrIHwU4DjODzzzDN861vf2tahvAvTNDeLLMesWbP4wQ9+wB133MEBBxzAHnvswbx582hsbOTss8/moYce4gc/+MHb1oQ//OEPiUaj/PznP+eXv/wlRx111A6VrH2We9jEf/oS2XnnneVrr722FcMZ4sPgeR7f/va3ARgzZgx/+MMfaGpq4vrrr3/7Sv5HYmVg8N0UQY4ooWyIUD+3nY7+JMaiKKUaiV/hMGp4D925GNb6BNEWQW6sT8OzoBU9Wk90kR0mw2Z0ML96Awt7R5L/SyMzv/UWzzw5k9rZnexVu4bluXpqzSyKkPxz2TR2GtPCiifGEeoDNwJnnPwgD3VPp+xqFOwQ2ZericzrI6wH2wGtzWnUiEs0ahEN2XR2pFBCHv6AQXKVivBgcLJPatQglq2hbLJscpYl8ccVcPtNlKSNUCSyy8RPOSj9Bn7aJhyz+H/snXecHXW5/9/TT2/b+256JSRAQm+hieBVQUUu4qWoiOJVigoIghQVxALKRQUEuYCABRsgRZqEkkB6T3aT7fXs6Wf6/P4YjD8uCoGUTeK+X6/zyivnzHznmZ3Zs898v8/z+ZT7whB0oSQh2gJO1EYZkXECHp7qEeiXMBN+rZpgCygFAaPCQR2VsGJ+sitaAp4EXqWBMKLSOLOfrjW1uCGHeHWB3EgYdAlCNtpWDaPZRIsaGIMhUs0Z0sNREhUFRMEjsyGFUFfG0WWUkIXbFUJpLZCMlBjKRGBriMiMUUb7oyhR34JL3BgmdeAgmWKQcNAgkw3jjKqIcZO2umG6FjUhz8xSyga3NRaImoM3rOHJHmpVmRu8abvzNt0pDA8PU1lZOdZhvCue53HHHXfgui7PPPPMW2Y2/vjHP3LRRReRSCQ455xzqKqqor29ncmTJ487Iuxi/vd//5d0Os2LL774vvb/uy3Z9OnTufrqq982Y7UjFAoFUqkU999//04b8+94nsfmzZt54IEH6Ozs5KijjqKmpoa5c+dSVbVnTrd//OMff93zvHc0y0tOq/aOvmvHLLkePfz2dz3Onsr4t8VeyNe+9jWefPJJBgYGeOSRR2htbeXss88mGAxu28YsKcQiZbQpOZxRjYk3raH/5XrU18MUp5nIzUXamgfJ/qYBvawS7hbIT3DR6ouEfvMKh3z7NaT2IKFegaRW5vn+SRRNDev0UYb0CPLkPM3RUUTBY2HFWt4YauKxxfujhU2WdzbQcGQX+tF57BDc8tQHWbOhka0rGphZ0Yd2YJqYpjM71UumFGRC2wByR5BCLkBdJEdd/SgMaciVOubROUbnWXhBh8yWBNOqB/n7M4bVrJOMlog3ZnHKMk5GQ20sImQVIhMziJKLbUt4movSryAXREI9AmJJ8hOwuO9UYAfA1VxfYy3goqVBcAWsmItoCngiBCbmcDUXL+vbXXUPJFGyIlLIprgxAZ5AsFciVVnAmVpkZlsPqUgJAg7pkQjheJlcLkhVuIBbYaKqNm1Ng7iugNRSxDJlYppOU+UoTsAj0xOjoi6HrSuoqo3gwuBIFElysR2Rpqo0py5YiiDC5g31mCkHvawSTZYQ8jLxygJOWcYLuKRaMtuS3L2NyspKnnzySYaHh8c6lHdEEATOP/98+vv7+dKXvvSWz0499VTWr1/PSSedxFVXXcWXv/xlfvCDH3D55ZezbNmysQn434A1a9bw4osv8uCDD77vMb7yla/Q39/P3XffzZe//OWdFxy+N6imaWSz2Z06Lvj346RJk7jiiiv44Q9/yKc+9SlOOOGEPTZZ217GnQ7G2WvQdZ3vfe973HXXXVx88cWcccYZXHrppZx33nkcf/zxKIoCwLWLu1G7NIxnK9HLKtqQROHhJGaFQ3GGCSUJd1OErB5kdIFJ288ESnUeoV4R6bUoG39xIH946DACwyA4sGJpG6LgYbsi5TdSyKLL0S0bqdbyvDLSysZyDUVDJdwhYZYU5jT30DWSRE8HOe/0JxFsgchmGTduM6xHyI6GGcxHeKZ9Ks3JUQaebqTl0E5qqnL0F6P0dqfAFbBHA9jrY8gZGTlsIVUYbBiuIqyZ6GXV1yZzJEplDcEU8RSXgGYRas6Ty4RQNgeZ37wVKWTjBD0QPSQd5LyIMC2PtlXDC/vyHeEOCbkgoFTqlOpAGxKJbRb9zs+SgPhiHEKOb9UVcGFYw6yx0dYEcapMEDzMmSXSPXFEyWP15kYGRmKIORlpyF/mFATY1FeNNKRi2xLtHTXYRQVvYwTHFOkYqqA3E8eL29S2pBEEj4a6NJLoYSZcQsuCGIZMNh0mZwT44ytzcW0BHJCKom96b8oEGgtk0xGknIyckcjmg+h5bSxv3R0iGAzuUkX3nYWiKFxyySX8/Oc/f1uCqWka3/nOd1ixYgW/+MUvGBoa4oorruDnP/85v/71r8eXS3cypVKJn/zkJ/zwhz/cIdeXlpYWTNPkwgsv5J577qFYLO60GEVRpKWlha6urp025v9FlmUikcguG3+c3ct4wraX8OUvf5lUKsUdd9zBlVde+Y5PSqV634uyMNvAySt4Mwr09Cf9TkYPwlslRBvSw1ECUYPNH1P49kfvxzqwgCeDNKwgzM9S93yGwgE6lZNG6OmoJJMN8cmPPMfrSydStDU6Syk6BiuIyTrzaruxDiwgpFXqglkmXppGGZW4Z8MCmvfrRa/wOHnOClauaEWUXMpdUbwtIdaubSJ4xDCi4NE/kMB2RBqbRohMzBCqKSBMKmDHHJyyjDusoesKBV0jES/iOSKFYgBVtQl1ScijMolAGdOUkQZU9AaLl5ZNRegJIDggtJYwjs4j6eBsiuKoQElCMgTK9R5m0sXtCuGqHkalS77N82fgqi1KB5YRZQc37CDGTb8+TfYoTzbxDImKmhx2QQHNxRwJgOihbAziKh6J6SPIkoMgujijKtqEHAHNIl5dIJDQCczIIMr+0qs+GkBUHAaGYox0JygYKjyXoHbqEKX9y7i2iLZVQxJctBGJUNQgVF+ger9BgmETs6giih61NRkiEzPYURdZcVDD5u65UXcBRxxxBLFYbI+uZfs7iUSCY445hsmTJ3PSSSdx4403vsUJobW1lQ9+8IOIosj555/Pa6+9xsqVKzn77LM577zz+PznP8/NN9/MqlWrxpO4HeDuu+/miCOO4Oyzz96hcW677Taam5v57ne/S6FQ2OlSLZMnT94hLbZx/r0Y7xLdC3j66ae59957+cEPfvCuZrzXvtaN1+xRu6CP7pV1uEkLs6TwuQNe4PG+mYh4bJUriCdKiItTHH7KWtRWm7t7DsccDqIclMVJhyj2RvjYg7/new9+lPqFPQQnWgy+UM+rDa0k14gsqmxDkl1sXeH+VQfhjWi0zuilI6/RU0rQ95MItVo/wy/W0TdHZNJBnTz28lwCQyK6okDcJthSorQxTipYojcbJ1WZZ0IiTVwp83JvK54noKk28Qa/6zHUK1ISNYR6i5F230PTyWgYuSChMkh9AgMTolijGpLINsFcNxdGbC1iDgaRakvYM4vQEcbVPL/5QgI3ZiMUJETTb0CwGky8guzPwXvgmCJCTkGyBVzFBREE1aGpNk3PcIJsPoiWMMCDQNJCllyyWghGVQKyjaI6ZLviqFVlzPVxrEqLQFLH8wSKBY1g2MQwZOSw7R9L9F0cMiNh5BrI9yXxbIH6pjSjG4IM9Sfw6i3EggZpldgUA31zDEHxKNghnKSIIjsQsnE2RRFcYO9S9XgLv/vd72hsbOTII48c61DelfPPP5+TTz6ZNWvW8MQTT/Dd736XdDr9T+ufWltbWbVqFblcjkKhQD6f5ze/+Q0///nP8TyPk08+eY+VWNhTefnll9m8efP7krr4v1RXV/Pwww/z4osv8vjjj3PEEUfshAj/QWNjI1u2bNmpY+7r7O3LmjvC+AzbXsAVV1zBGWec8a7J2oppD5CfalM/bZCyqSAXBaIrVeKva/z0uWMpGBqT4sN4GRXHEdGrHZ5ePIvHVs8iJFvE10qUSyqC6oAIaTuCGfMoWCqdXZXYM4tsfaIV4YMjSJtDfHjSChrrR7jzkHuRa8p0bKhDi+vUBPI4jkjf8lr0Vgt9NMDmgUqqJowgF6GiKUN1dZbi5jhN+/fS3l9FMlwiPRzh1Q1tPN85kVJZxdgapTJSwEXg4BntqHkIDElYlkywvgDdQQJVJZyAR26yQ7HBozaeI1RdpGFOH2qnhpHTcBt1zKEgUoWBIju4PSGcsOt3hwpg1ZmgiwiOgFVr4oQ8wms01LSEpIuIowogEOwT0dIClGSI2uBB90ASx5ARBBBXRbAtieKGBIWyhpNVqWpN07uumi09lch5CVl2iM0eIVGTR08HsU2J6oo8heEQkuziuSAHbNSQheeBNKxi1xnU1maIVJboH4xjVLjIQwqCLVJfnUGsMqgIFnEiDnJtGS1uIIoupbLKxKZB7LBLePbebUb+yU9+cq9I1v5OfX09xx13HBdddBHBYJDFixf/y21FUSSRSNDY2Mj06dP5xje+QUdHB5deeil33nkn5XJ527bjs27vTDqd5u677+YXv/gF8Xh8p417xBFHcOONN+50aZC//vWvzJo1a6eOOc6+y3jCthfQ39/P5MmT33W7x7pn0NgyjCrZyJLL9KM2o1dAdrpDRdsobYk0zYE0jVMHCCgWnuoxfWYX2CI5U8OVobF6lIVT16NVlWgvV4II7asbEHMytakczM9SeKMCM+nw6Mb9GH2mjgeGD6G1aoTkSgkjG+DJNdP5QMsatLTAMbPWovUrCAKEVZNDP7GM/BuVZEsBJs7twnIlDm7roHN9DUrQV+S3OiMIgoeaEejoqsayJXRHplgP2gFprFENozOKU2Vh9IYRHAEiNl6VwfBjjdir4wznwzC9QDhVwnMFAjUlHEMi3x/BTdhEW7LYURdP8WfZAL82Dd/xoDjBxkq4KDkBt9JEyMqUGh3c/fMIpgBlCVH2YFjDswSsgoozo0h1Ko9Xp2OWFERdJBEsM++AzYTjOtKkPKX+CGVDIZ8PIigu3rBG/0AcNWYSD+mI3UEiYQOjoFEZLqLkBCqq8gAYhuwL5qoedtxBrSwzMOrLdWxY1EasLs+s+j4UxaGUDWIXFDqWNyK4+HZZezGCIPD000+zN3atNzQ08Nprr72nfURRJJPJMH36dEIh36Vj8+bNXHnlldsK4cd5K67r8j//8z+ceeaZ/9L5ZU9ixYoV9PT07BV6g3sKHuPWVOPs4eRyOaLRd9fRGhmM8YW255BFl6sm/4lV3fWEZqfxZJfTW5bSFh7h3lUH091TwWBfglBFifbnWolVFhgqRig2eXyofgWy4OA6IlNDA7iqS8UyAU+A3sEE2lNxRBu0YQlLl5lx6gae75hE3gggfHDED6Qs8/CiBcw+ZT1r07WkDhzEGgqgyTZbi0mUWVmSvwlTMDX61tSwuLuZYF0Rq6DiFhTcuE1b9QjCnBzR5Sp1sRwlWyE5d4j85iRK0sBVXcjLeGEH0RDAFaivyZCf6MDUAsbmGGZJoTgSIrQqgGVJiIqLFLMQihL68iRu3PZdDwBP8fBkDzEnI9gCOAJezMaYpCMpLlJJRBv2l7Q8ya9tkzcEccIOouYXxDekMkiiC4MBKEt4lQbdf23m9c3NFHv8wt94Y5ZQwCQS0QlEDWqmDCOpLrYpMdiRwmsuk8sGOWraBjZ11MJ+ed/A/c0mDHoDBKuLSAURqzdE8LUwdkHBVT0SoTIlW0EUPNSIiRY3UJoLTJrdTW08twvuzN3LpEmT9mhf0X+GbdssX76cD3/4w+953wsvvJCuri4ef/xx7rjjDr773e/y2c9+ls9+9rNcffXVb9FeHAf+8pe/YBgGP/zhD8c6lO3ipz/9KYceeiiyPF6ZNM72MZ6w7cEUCgXq6+spFovb1emz+oTbaVWG2NBexxf+fA5CVwDTkjnroFe484njePn6+UyoHSKWKpJYoSC+FuOTH30Ow5LJbUxy1KEreXDLgTzz1Dyc7hA/WnIsalpieL5DcuIoji6jH5dDn2Bg1NpoIYvVgzUkIiXKlkwmGyKcKiFGTVItGXqKMSxXZDjr66Bt7K2m/eUWWpNpRqeJeL+s5pCD1+JuivhPPiUJsSjR3DzEhs11GF0R8nMNNi1pZqQURhJdgq05YpEy4foCRG1EzUaZkkNUHPpW1SBX6LiuQHx6mmi8jDag4C3IIskuTlFBlFwES8CscpD7VX9WTYDQVt8M3gn5/8cVUIIWri7jjGhUrPKwQx5GTkNwBAINBdT9MwiKRySmI4dNejNxegcSRCZmSDVmUQI25Umm70MqQmMyQ7GkMdyTQDcVXE+gZCo4GRWvKCPELJycgii7LO5tQg5bGD1hioNhBnsTaFUlXNVjRs0AYnMJqSySn2pT2ZDBSVn0jsSpDBQp64rvmSp6eJ5Ax2AFdeG9P2FrbW1FkqQ9XuLj/0eWZVpaWrjrrrvesxl8ZWUlN910E+3t7ey3336sW7eOyy67jKuvvpo77riD73//+zz//PO7KPK9i+7ubn7zm9/wwAMP7PCy5aJFi/jDH/6wS23RXNfl0UcffUtN3JUbxpsPtod/Z2uq8YRtD2bVqlUA/OQnP9mup7C5v/gy5/zyIia0DtA6oxc74nJEUzsOIjSU6T7RZetIiuxgBCMB8z+6gs3FKk6duBq3wqRKLTApMcLC49/g4wsXMbFxkLbDt4IjkNmQoroug1H2EwqxLKJnA5S7o8QCOpXhIkdM3MykimE8VyA9FKVvRS2pYAkrryKFLCIRHU+A1aubmXRUB0On6Lzc3obXUsYyZCompJl5QAed62qZMrEPN2YzuWmAxIwRCm9UkC6EEAU/CSlmgkQTJZTNQWxbwjVkBA/fqskRyRUCSJKLFXUpZYNoio0SM6hJ5nBiNp7iYlVavt2UJ2DOLCM3FREMES/uC/o6tohUkJAqdUanCjiVFsG4jlJXopwPoK9JIGk2hVwAeyiIszVMTVWOfDaI6wloio0WMVBjBtH6PP1PNqFpNnJWwshq285FjJloAzKkVdQKHSunYZoyjiHjRRzEooRUkAmoFrPmbGFFTz0BzcJtLKNVlCnpKmqvSiyiIwsu9RVZzILKqRNX88GJq2mqHGXT6J4vPrs9LFq0iA0bNox1GO+JCy64gHvvvZcFCxawaNGi95S4ffazn+W5557jBz/4wTbbK4BPfOITPPXUU/z617/mwQcffM/J4L6Ebdv8+Mc/5rLLLmPu3Lk7NNZDDz3EBz7wAS677DImTJjA97///V3ys3366afxPI+JE//RCWRH/32v4Tjbx3jCtgezbt066urqSCaT27X9hz+4CGtima2r6tEuDnPAnHY6Cime7J7GkRM2EUyVsXQZKSejV7m8+Ox+2J7IH/50MKmKAsszDQQkC9cTSZthjqjazObXmoltlPAkj6GuJNq6IIlECVfziC9X8GIWhiMTkGwW9zYxXA7jeQKC5BLqEdjcW8Xxc9Ygih75rXHsGpNATQnTlZAUB2VTkFS8gKrZOK6I7sioNSVmxPvRYgYlSyWsmphNJu76KLqhoJsy4USZ8toEep2N1x5GzEs4SRszr+KOqthlhdzmBIHGgm9v9UoCVbXpG4kjKC5yyEYO2xBwoSghqzYB1U/UJMWFqI26LoiaEfAGApjNJkJeppwNYGQ1PFvAijm4gwHUkIVoC3h1Ornnq1FDFpmRMK4nYJYU3+x9Q5xim01xIExgkj/bFQqYFDpjMBjAnVYk0FjwTePfnBmThhXkYRmluYBXaVA2VHrycbyOMLOq+6iuyGMZMq4noMzMElJNXtw8kc6uStRelREzxMsDbXQNJxke2fusqf4Zp5xyCoceeuhYh/GeaG1t5dvf/jbTpk3jP/7jP2hsbOS73/0uprljUivz589nyZIlrF+/nh/+8IcYhrGTIt67eOSRR6ipqeGKK67YoXH+9re/8dnPfpZLL72U66+/nksvvZQf/ehHnH322Ts9afvBD37A0Ucfva3795vKakLd43+O3xVvXDh3nD2UTZs2UV1dvd3bP/zyAiTFxRNgw9cCrBuqZnJsiJim89JT+2HqMi33iQgOaGlfFHbTz6aR2OiRHopSH8qSNkK83NtKXznGvcsOZsGRazn1v15EqDSQsxLlegfjhQqOO2AV2QMM5H6N0BURNg1XkgyX0W2ZAyZ2kqooILigBS0W9zcRi5Txwg5SwEFVbDLlIG57GHtKicHeBBMrhzEtid6/NJP4Y5iXfnwQqUiJvqE4nZtqkAdU1BlZAi+HsdbG0TfFECcVEMsiggdu1AHBQ8jLELERcjJUGZiboziWRHGShao4OLoMroCs2jhlGQwRMW7C6iiK7CDETVTNAkPEqHTRax2csIOQlXFDfq2aoLrIYQsiDlpaxCiqBHsFQkuDFCdaeK7AnAndlLfEYFSlr6MSp8oiUFlGyknouoJgirieXyfnVpiYWQ1FdnAMiWRNntDiEFJLkfD0UYyCSjRWRhJdcoUA8qQ8i1ZPoi0+wklT19CcGsVaHad3KMGc5h7CyTJmo4nriSSDJeorsnxo5opddZvudn71q1/tdbNssizzoQ99iJ/85Cd8/vOf57bbbuPiiy/e4XEbGxt57bXXiEajXHvttXR2du6EaPce/vznP/PCCy/w4IMP7pDNl+u6XHDBBZxxxhlMm+ZbuE2ePJlrrrmGV155hY9+9KM8/PDDrFy5kjfeeIOHH36YH//4x9x33338+c9/fk/L9EuWLGHRokWceOKJ294zDIX8VOt9xz/Ovwfj1Y57MIqivKcnu5sr3izIrvX/+WFoCX/ZOB3HkEjtP4IgeGw5NUXLEw4HXb+EZ3snkR2qxJtaROwJUaUWGNb9WrlNw/4S2ktrJ7Fs7QyiR6SRZxUpljWMfIQXtk6kribD/FlbeaxtJhMqhtn8aguxWSO8vmICYtxEScGM6kG6c3GG2itAdZE3BjFn2tTFcqSbdKIRnYwpsba7FllzMKeZlGa6uLqMvLIata2AbkoIbTrFgTBCm0vlpBGGhmI4OQ0v5CBmRLRuBaPRQqopY6cDCBUGbl6BSovaZJ6MGqRY0vyO0JKMHZCJVRbI54LImkPVMoe+YAVejUm5oCFFLRxPAcVDKElIuoAX8wjFy0iiR34kjJiVMVIuouRiHVSgIZVBH07iOCLd+Thu0kINmbgdYcTKsl9bt1mgYIYI5KFUpaIELeyBIF7QoZAP4DkCddEcw+kkRUOiviqH7UgUNyZwkjaxygLFYoDq+gzL++spDUQ4aPZmOiYVCWo2I7rfUTi7rZvNuQrfu7QU5G/mBA7febfmmDJ//vy91mLn75ZBhmFw2mmn7ZQxw+EwTzzxBNdeey3XXXcds2fPZv78+cyaNWufVbl3XZf77ruPFStW8OKLL+5wM8ptt92Grusce+yxb3k/EonwjW98g4ceeojrrruO/v5+ZFmmsrKSWCxGuVymUChskxP50Ic+9K7Huvbaazn55JO3df9+1dyEpHhofQrEdug09nn+bk3178p4wrYH09jYSDr9/vWzvpw5kCvldTijGumuBEpKJ9acZesHYwQydYh4yLOyxIIG0aoRXhtuQRA8AopFuhRBC1l8YMIauqckGby+DSMlox/qQpVFSHLo7azgqVIAb0uITW4VyB7pkQgTp/ayZbAC0YL1j02i1OQQrC9QHg6RWjBAb3eKoSdbEI4tUjYUKip92QrbEQmoFvryJLWH9NI/GkMvaFS+qJA+zkHOSthxB91SwBV8oVtbwKh2qH5ZZLDFxdb9Lk/XkhAMkeBWmQElhueIqCETUXGJNmXJjkQgDGrQYlLlMIFLbIaemYwrer7rgCcgxU2kTSHMCgdPEPBsgdJAhGhdHjlsYssuapeGJWhYCZOOrTVIQRtRckmnI1CUcAMC4oQiVbECPVsqKRxXwMxpmHUg2SKaZtE4o5fhQgSeSxA8YYh1nbXEIgLRV4KsndtAVW2G5gO3sqGvGuelJG6jSyloYtsSSkqnYKvUJPMIgkdVsMiMRD/rMjWULV/KI6DYlM29W9bj/6e1tZWRkZHt6pze08jn89x6661MmzaNY445ZqeNK4oi1157LRdddBG33HILzzzzDLfffjtNTU3Mnj2b/fbbjylTpuwTHYmGYfDjH/8YXddZvHjxW2r73g/pdJrrrruOr3zlK/90li4cDnPuuee+4xhLly7l05/+NGeeeSY/+tGP/uXP2XEcXnjhBW688cZt7wmiX3dr19g7dB7j7PuML4nuwTQ3NzM6Ovqu23meR3t7O/l8/m2fObbIRw5eApqDY4mcNXExUtJgSnSIRLBMKR/A+nU1HYMVxDWddClEWDWxCwrV8Ty/W3wAr29tYsvpMHggNDwrgCFhr44TWyujl1XsiIu2MkRgYg5yCiO/y+biRwABAABJREFUbQKg6qhejNllQl0SwuIYgiHS159A0EWskzOEQwbxkE42HyS/tJLSqhT2q0nsiEfXmlqcrWFSlXlyJxeRFQerwkaMWhQ74qBLSDVl3KQFAQct4yD3a9TWZFHri4hZGXVUpDTV9DXdQiauKzCxbohSWQMBsgNRIkGDzcOVLF08CSvmJ2ueI+D1B/AGAjgTy8g5CafKQgw4KKMSli0Rj/pipnZbGSFlIEgeQsGvy3MsEc95U5S3oGJkNfpH4oSqipjpAEguWALuUIByV5Su4ST5vij5SQ4hxUQc1MhNdrEXZgl0KpiOxGjZfxpPHteHF7cwTZloWCccMtjQW0N3ZwWjxRBvdDTxxOv7URfOkS8F+GjzcuZVddGcePf7aG+hUCjwgx/8YK8rtL/llls477zz6O/v56qrrtolx6isrOTb3/42r732GsPDw3z7298mkUjwv//7v5x//vncdNNNPPbYY3R3d++VIry5XI5vfetbxGIxFi1atMPJGsAll1zCrFmzmDJlyvseY+7cuXznO9/h+eef56CDDvqXdlPPPvsssVhsW6nLZZktuGkNzxXQ+vf+ZHp38O9cwzZ+h+zBtLW1veMMWz6f54UXXuCvf/0r+XyeQCDA9773vbe0tVclCvxuxVzq6kfpX1/Fz39/Aon9h3mpv40Dq7sQmz26qlvwXJH1T08keegA0xIDVM0oMjPWy6N6gJb4KKu664nX5uiOxqhaJBP9z2629FaSjJdI5xXUQ9Jk0mGIWTjHl1GWJkgu7GNrqQp3ug6jKom1Iul5IlpNmXxXDC/okKjOE4+WGY0EkfMipRYbLP+Xygl55JdXYKV8g3bBFiAfQKgtQ1rzrbGKMlKFQf4zBcSyymA6imuJkLCxHAXwUAM2liVh51XavUrmNXWzJZtkqD9BZk0FdtJmypwuhooRMj0x1AodI2YjBW0QPFzVQ9Ic5I1BrLiL4Aq+FVXYxDZlHENCjZhIjQXMjihIoDYWsUQPLAmhIBFdqpA/DMSwRWhpkMJsEzkt48oeVk5DcCDUI7FFrMVL2Gj9CqYpU3nIAJ4nMJwN+zOlWohgxMBxREY6khywfztmTPK/jBAgCaYjsTlTyey6PiKSTk8psW2Je18gFou9ZYZib6GtrY2enh7q6+s566yzqKys5Atf+ALnn38+mqbt9OOFw2FOO+20bUuvPT09PProo/zlL3/hxhtvxHVdqqurCQaDBINBQqEQ4XCYyZMnM23aNGKxPWd9zvM8Fi9ezH333ccpp5zCz372sx2qWfs7b7zxBr/5zW/43ve+t8NjpVIprrrqKu69915OO+00Xn755bfF+Lvf/e6tnayKS7SmgGHK6PXjNWzjvDPCOz1lHXjggd7eqCy+r2CaJqFQiP/93/9FkiQKhQKrV69mZGSEZcuWsWHDBg477DDOPfdcbr31VgRB4L//+7+3dR59J7KMYllDEDziIZ3My9XodX7h/BH7ryOlFlky3MzQa7VYLTrxZIl8PkhVMs85rYtYV67D9QSe2jqVVKTEYCaKWVIRRxXkvIDZYCGFLJysipyREdqKuI5IIl4kINsM5SIENZPsSARRdaj5o0b/ISAaAk6FDYb/ZTZ9Rhdr2+sJxnWsjTFEE5ygh1eno2wOYtTYYAtIJRGprYjdGcYNueDiL3+GHARXINAtU26xkLIyTsxmQtsAfZk45tYIog1OvYEoeYTDOolQmaFchHI+gJiRiU3MkBmOIPerTDx4K+2DlciygyB4/tKj4mCaMoLoYQ4HkRIGzoiGp3oIkgemCKKHGLb8xg8P7KKKFtcx8hqC7CJKHpLs4G2MYMVc1JoSRiaAYAvIKR1lVRjm5pAlF+WxBOn9HRA9v1lBcikVNIJhg1IuiBywCIcMf1vRRbdlctkgh0zs4KUl0xBTBnOae5AFF1HwOL174Zjdx7uCXC7HPffcwxe/+MWd8od7d+M4DkuWLOHxxx9nYGCAs88+m0svvZT6+vrdcnzXdVm1ahVdXV1kMhkymQzZbJa+vj5effVVVq1aRWNjI0cddRSHHXYY4XB4t8T1f/E8j6VLl/Lwww8DcM011/CpT31qp4ztOA4HH3ww06ZN267as+3Ftm0uvfRSfvCDH/Dxj3/8LZ9NmzaNT3ziE8yaNYuvb+2CRh2hK4AddyDgcHNwLzb83UE+/vGPv+553oHvtE10aq134P/85w4d57mF33/X4+ypjM+w7QEYhvFPn7BVVSUWi3Hdddeh6zqDg4PMmDGDmpoaLrjgAk466SRuvPFGLrzwQmbMmMEXvvCFbcnao81PEi3EmRBPsyFdycBQDK/aIVBVQpEd1o9WkwyWGMpG0GZncNfHaWvrpluMM7SqivukBWiSTXPEX0qzHYmmilFidQbLOhqxxDeTkf4Qcv4fptaS4jA6GkZWHWTZoVAMIAVsPEeg73CPpqeg66MW4rCK4EJgUo61W+qQgjbuqhhOm46gOdAVwvMEjCoHdVjGlXw3AnFVBLfWAQeQwBNBLEsItoAxWUcoKFCrI3nQ/VojTCziJi3cN8VwE6kC+VKAIVvCtiW/s7RGJzMSQQrY2BGZdCmEuC6MEXepnjpMVajAuv4arKKCqDl4sotriUhlkUBDDn1jDKfaYs6ELjYOV6LIDtGAwfDqOqzpNonKAoWif32tvhBevYkguZhDQeSUgTsYwMppWM02YncET/IQjywjArLq+P6nnoCkOHieAIKHKHoEFZv+zRWo1WUCmoUSsLFdCbmqzGGtHWy5ZiqRr3eztruW0/edEjYAotEoRx999FiH8b6RJIkFCxawYMECOjo6ePzxx5kyZQonnHACd9xxx3vqDn8/iKLIfvvt9y9tkUzT5OGHH+auu+7igQceYN68eZx++um7LaH0PI+VK1fy0EMPYRgGV1xxBeeffz6SJL37ztuB67qcddZZFItFTj755J0y5t+RZZmmpiZWrFjxloRtZGSELVu2bOtCFZpLsDWEXWOihi3srjA07NRQxtnHGE/Yxph7772XCy64gMsvv5yrr776bZ8/9NBDZDIZUqkU2WwWWZYJBAJomsa5555LNpvlqquuorGxcds+P0m9SgPQl40xUvT1wGJLApQOK2JvjlCusNGjJvmyxnET1vPkM/MITcvQmUuQCpaQZg0x/Lc63FkFOodThEMGAxsr8aI2atikvibDgBqlPpGle30USQezwkVwRERc3FENU3GxdRE3aaGFTaz+CF7UJtRVouH3EczzhsmVAxiGDI6Ik5GJzktjdiSwPfCCLmrAxjQlhGklIn+NktnPwY6BoLh+opVVqFwqkJ4JdtImGLLQSzJiZ5Dg9Az2VMtvokhZGKYMApRerkSUoNxqgiESr8+RHQ0TTxXQZAfiRUYyEZJbPIbnQUC2WLm5kXhlgXgqi24pFEMqH2hdy6/duZQ6o7hJG8GF5R2NiCMqpYBLLmJBlYtbUKipGyQzGEVQHZS8iFdUie43wihhHEMC2fczFTUHIeyBIyCIQG+AE49+nT+vn4lriXimxGH7rWP5UD2Fokb/QAI8AVH0MC2ZymgRVbT58NSVvDTQhnLJEKYr0VyThr3b+/1tCILAfvvtxyuvvMK8efN2uin37qStrY0LL7yQTCbDI488wgEHHMCf/vQn5syZM2YxqarKWWedxVlnnUVvby+33HILV199NWeccQYLFy7c9mC4K1i9ejUPP/wwuVyOr3/963z+85/faYna37nkkktYtGgR11577U5vxGhvb2fDhg385S9/ecv70WgU13VxHAdZlnF7Q4ieAEUZsyBDanxJdHvw9vI6tB1hfEl0jGlpaeGkk07igQce4NVXX2XGjBlv+XzJkiX84he/4E9/+hPFYpGamhps28ayLKqrq7nooove8sfqusBKYkEdUfAYLYaojBSIqQY5U2Pr8gbqZg3Qu64awRVwojaCKaJU6Aiih6bYVEfzbO6qARfOmLeYnnKCgq2RUEssHWwk0x0nWpen0BnDCzuovQpmhYOck9DSgADlag+vyiAQNikPhvFkFyno655JRd/+qWKxTM1TPfT8KEQhH8DNqghRC68sE+iVsYNgVVhIeRlqdOT2IGbSgZCDNKJgJ22/pk11/eVIT/B7vgMOQkHGDbiocQNJcrFtEdcWEWWXVKzE4GCcWLJIritG89QBMqUgmmwTVk2GChFqYzn6czGMDTHEtiJWXwhSJjOa+uhIpwg+Fid7XJGqRIG+gQSxRIlcJoQSsHFdgWhEJ5sJ4TkCVc+pDB1tkqgokl+XJLkWhg+3QITamgz9fQnQJcSYiecKvvPBqELd9EF6Nlchp3QcS0ILWuhFFSHjT5XVTxtEEDz6hhNUJfPURXJkjACt0TTDegRR8NAdmU39VXxHfP/F1Hs6Dz30EEcddRS1tbVjHcpO48knn+TXv/41d999Nx/5yEfGOpxtvPbaa3zyk5+koqKCz33uczu9xm39+vU8/PDDDA0Ncemll77tu21ncdNNN3HLLbfwrW99i1QqtdPH/8lPfkJDQwNTp05FkiTOO++8bfdna2srX/jCF2htbeVr9kbkdr8uVhsSscPw7bbGdxl932V7l0QPuP2sHTrO88fdMr4kOs57Z/Xq1aTTaY466ih+//vfk8v5CvhLly7lnnvu4Q9/+AO5XI6DDz6Yz3zmM0yePPld63UCis1gNsphze28+ux+dM9RcLpDJKamSUxNE9N06g/YxOIVE32rKVvmpOa1PLpxP4pFjc2jIRrq0/RsqeRXryzAkz1CyTKBp2KUji2gpHTyPVESbRkyW+PbkiQ7ZOM1u0QiZcKuSL4/gpFWCaRF9AmOP1s2FMATPQQXQh/rIztaR3Gj4Lu7VfrJmprUMcshpJKIkpaRdAHbDmDUWoglCc/wNdEc2cXzRCTVwTX8pc1EY47MSBg8CFWUSEVKDCytxanXEUY0tNYcmaJvaRUL6gjNHlu3VqFETLyAQGW4iLskztZIHE/2iM9M+36fdWCWFbJmgIZElp6Twc4FMR2J5voROnsrwBYJBkxK6xJkIhpIHrG6PEPzZSjJZMUQXpVFMaui9KlYCYf+/oS/FJyXcTP+HyZJF1GyAt1bK4nUFbhan863Imspl1QaakcZXVeLemiaiGqwfmstCyZvYcnWZtKFEDe402Dk/9wQe19513viE5/4BI7jYNv2PiFZAXDCCSdQV1fHOeecQ39/P5///OfHOiTA179buXIlF1xwAV/96lc54YQTOPDAA2lqanpfM26WZbF582bWrFnDihUrGBoa4uKLL+YrX/nKLmnCALj11lv59re/zTXXXLNLkjWA0dFRXn31VRYsWIBlWXzve9/j8ccf5+CDD6a1tZXu7m5aW1v5rjyZyyq3EuyRcGV8X+NxxnkH9o1vuL0Qx3H41Kc+xSmnnIJhGBQKBaZNm8bhhx/O6tWrOeSQQzjnnHOYOnXqeyqqzpc17M4wzw7OxGuzkF0BN+iSXZsiNDnLhr5qKuJFpKJIvhzA6Anz8OgBiLJLcEWQ0iyd3nXViK6A+2YXp/1Sisx0l+iiCMUFJdTqMpmuOIIrYDaaeLboJ0xVeUYzYX82K2LhahLCsEo0UUI3FNyQg1iQEFyJ7GN1WGfkUVZGsYPg2QJyXsIuh8ARMKstBMlDXa/iiQKO7OEGXaSSiB11/UL/koiStLEGAniyR6YzDq4ASRNjS5T+epmmA3rY0ltJpC1LvjsKYQdTVChtihOZMoqg+LNukuhSthTKTTZ1rSM0RzO8urGNaKLEYS3tbMmnGHyqEfm4HuIhHb2kUihrqJJDPFkknw+SGw1xyBHr6MwnSb9YC3WgVOhY6QA1VTmypQDlGhkED09zEUoSruziJfylEG2LhjejgF5SEDyBYjqEGBH5Rmkq30+sxHFFSs0Oei6IZUvMbO3l1U2tqCHLT9b+TfnpT3/KgQceyPz588c6lJ3G7NmzufLKK/n617/OwoULd0hyYmcSCoX45S9/yZNPPsndd9/Nd7/7XSRJYubMmdTV1VFfX09DQwPV1dVvW8Y0TZMNGzawZs0a1q1bx6ZNm2hsbGTBggVccsklnHnmmQQCgV0S98aNGzn33HNpb2/n8ssv36W1eKeeeiq1tbXbJEdefPFFTjnlFJYvX05dXd1bTOXjDVmKuSRCawk3vWvOfV9jbzdw3xHGE7Yx4umnn6avr4/jjz+em2++mcMOO4xEIkEul+Ooo47ijDPOeM91G3dWv4TzYgtCyKPiDYmRwxzCIQNeDWGHQH4iARM8krVDSLMHMR2JQw7uoDGQ4eFHj6Q8p4yyOQgCuDKEt8rko0Hc6SaC6DJxXjdbfzmJlrM3sTTf7K9C2gLBbhmjwmW4J4Hggid5JOoKOK6A3pkinwkiDasERwU8GaT9sxS9GGyNIE4v4toigiEjFwXMhAeyhxSwkVUHJ6hiNppQlJBsASfsIIVsPF1GzovYhQhOwkHURZA8xISJ5wi4FSbCUIA+JYaQVcgD1RPSDG5JUd2aZtCNkx2J0NY0SOeyBk48+g3yVoCGOVleeWk6uYkBEhUFzpn4Mk8OziAkW3gLsmxZX8vMWZ3kwgEU2WFacoAXOyaibghSbrR4ZVMbYr9G/OARRkfDeI6fbA8MxfBcAWQPJaXjtb/ZdVehY+VVv3HCBbM3hOgKeKLHTbXNgF/EXBku0j5cQcOEIQKyxea19WwwZUJRHdvZufU9exvnnnvuLvtDP5a0trZy8skn85//+Z+8+uqre1Q37AknnMAJJ5yA67q89NJLPPfcc6xdu5Znn32WrVu3Mjo6Sk1NDaFQCMMw0HWdTCZDW1sbBx98MF/72tc46aSTqKzctXIztm1z7bXXcuutt3LiiSfy+c9/HkXZtR04/7f28IgjjmDTpk1ceOGF5HK5tzR6ZNNhJAmCmoW3fZbR4/wbM17DNkbce++9nHvuuUyaNIkLL7yQT37yk/T09GAYBl/84hfJZrN85StfeVcLnruvWEzfiXVUnNaFep5I+ecw8ngDuekWgV4FRwM7YW9b2hRfjSGZoB9awCyqHDB5K72FGLXhPGufnIQ5tQzDGpPndJHVg+TKGqVcgLkTu9iaTeL9qYJCky+7IRoCggeSDq4KePhJR5tOLFHCejmFPqtMJKJTWpvEDbhEtojk21y8uEUwamB0RRBMAckQsEMeoingKR6SLmBFXURDwE74PqHyqIydcBCcN+vVJA85LeOEXbyYBWUZ702XAsEQkSp1ACTJxfMEYpEy2XyQeLRMZnUFJx77Bk9umkZNMk/BUJmSGqZkK5Rshe7XGpl/zBqW/2YGkYWDRDUdVXSYHh/g18vnce68l7h7yWHMnthN528mUKwDr7VEJKyTy4QQZY/Qa0Hy+5sIWZnEWhEjAVYU5DKUJxtQloiulykvKOIMBPFEqFguMnKYCR7cHJ6w7TqXSiV+VLWR0XQYLWShyA5hzaS/N8nNkbZdd6PuBViWxbPPPssJJ5ww1qHsdBzH4Rvf+Ab/9V//xTe+8Y2xDme7KRQKLFu2jGw2SywWIxaL0draSjwe3y3HHxwc5Pe//z233HILoijymc985i2NWbuD3zY9xUe7jgegWCzyta99jWw2yw033EBzs/8wdpm+mXiySKmsYZXlcVmPd6kti0yp9fa//ewdOs5Lx9+819aw7TmPbP9mfPrTn6ZUKvGXv/yFu+66i6amJo4//vhtgosLFizgt7/97b/c/6rV3VxWbMeNh5B1j57nmuj8QYTRPzbQ+h/tBJM6qbUucw/fQEPbMKLq4K2I4S7IoVdC009koitVlv9tMnMru1n+2kRihwzheQJ10wcZKESZmhxElvzlx6XL28hsSpKZ7mJHXAQHlCJYcQe9xsGOuLiqhzoKlc9o5DIhrP2LuFkVa3ESu8ZEzonkD9DxEhZCTsHaGMMJuUiGgJl00NJ+suZEHKxmHcF5MyEsiUghGyfukFwmI5gCnuyhDsrYcQdP9BDTKkpaQixJRKqKKNW+dpnnCph5DUWxSacjVCUK6KYCjTqL+tr8/9sy8aBOezbFur4a9kv2UjF3kNd7mmj44FbShRCWIzFYjPDSQBt1taP8vms2sYoiK7c0kJ3uEJyeoTaVo1TWEBWX6lQO96gsFCQER+CKYxq5dm4jogXG9LJvrRW2sWIQCRt4cQvJEMgdX8SzRL+R4v8jGAwyvWIAQfLQh4MU8gEGNlaixfVdfavu8UiSRH9/P7a971n7SJLEhRdeyM0338yaNWvGOpztJhKJcPjhh/PBD36QI444gjlz5uzyZC2Xy/HFL36RadOm0dLSwu23387ChQv55je/uduTtV83PsPizmZuS70G+CLGX//615k8eTINDf/Q7ojGy5SXpzBzqm+JN84478B4wjaGaJrGWWedRV1dHbfffjttbW3U1NTwve99j8MOO4yXX34Zy/rnrd6uDLV1GTo+Emf4cAu92qU4GiTf6rFmcRv6SJDRKSIlW2E4H+bwyZvR20wOrO9CcMD6RhpJB6vSQhEcFhyyjopQEbU9QN9QHFHweH7dZErrEsiqQ1VbmpZZvXhxPx65rYBe5SKaIlJJRNRFXM2jXAulGgFB8vA6whB0/O3SCkatTWhVAIoyYpWOHXfQBmXMpINcFLFiHnggFiW8goJcFBAtAU8ABgPgCuSmuH6yNiTjSUDQ8Q3aXT95FE2BUsF/WhVX+8bXUtCmNBimoWaU/qE4saCOU5Y5qn4TvV0pLFuiLx2nPpLj3Fkv83zvJGrCeQ5o6OKwinZaKtJMig/jeCIDq6s5rKaDylCRpniGAyZ2MnFKL6WySn86hjUSwDFk+jdUcY05E6ks8t2Gpm3X7frpjQRDJnLQ4iZ1EtfNaMR+PoVniTgBF0uXESQPqfDWZU5BEPjbSr+OScpLCIKHUlfCMsarGkRR5Oyzz95nmg7+L01NTXzoQx/irLPO2uvsuHYXmUyG/fbbj6VLl/KJT3yCO++8kyuuuIKjjz56ly4lfz/++tve+6qxibQRZHZDH6fUrdr2fmNjI1dfffVbSl1cT8CeUKayPotT3jfv352N5wk79NqbGb9DxpCNGzeyYsUKLr74Yi6//HKmT5/OsmXLePzxx+nt7eWQQw75l3VsZoNF5uVqtByIpooV9VD7VaKdHtlJAnJBpu7IblavaWbOrC10FRLU/1nmJXkCbpNJXzpOy4oSk8/s5tXBVuKBMltHUhjVDiJQESpSiqhEq3LkygGGupOMlEUEEYJ9Iu5wFLfZQpA9PEv0GwR6FcwmEzcg+3VpzWWCq4MYKQ+5LOBEoVTvog1KWHoQtSjgqh6hHsmvXXMF1DwYKc/34Yz7S6IIfgeVnPW7QUVDwAm7foOBKfqdpYoKlojreri6hKC46HU25BXqWkc4YvpmHv3zoTTM76NnIInaqzA4Pcqx+63lxb/uxwnHv86zWyejOzKi4DGih7BdkVwgyEfqlrGxXIMgeCSnjfBs7yQ+2ryc54YmMyU0SGd2ApGwjuuKFPuDfLeiBYL+dfpOc9Pbrt015kz+/7rZbx70T57+I29/K5gqUx3Pk4sFUESHbDFIZbIAb7eQ/bfjjTfe4PXXX+czn/nMWIeySzjllFN4/vnn+e1vf8vpp58+1uHscXzlK1+hubmZiy66aLced0J8hJucpahvuqIUf1uHOEmjfbCJk49+nR4jwTsVLBSzQV/epz9BRV0Oirst9HH2QsYTtjGmUCjwwx/+kOuvv57LL7+cr3zlK8yePftd9/Nc0KsdPEnCTLi4QRen0sWabSGKHkZWo2NTLWLcRBQ88qYGMXGbFlr9b0Q2f0zE29SCZ4n0kUSwRDzZwxvR2DzUhFdhUBH1v0EC3f6tUndUN1vtBjzZQxDBs0TkiIXYEcRsNlB6NDzJw3UEoqkymcki4TUahUk2giHihhwMxUMsi5hNBsFNGkoB7LCAHXFxHBFX8xM1N+DiORKiKSCUBaxKC6kg4WoegiXgaS7Yb2Y+noCckbDDLoLhLymq1WXMdICBkRgPDxyANLFEWDGpqczRn1H9WcSNk2mb38X6bDUzagaYF+/kuaHJTI4NMaDH+MOmWVREixQNlTnVvXQX43xn4m/53KqzyBcCtERGsVyJ/at7eeHVGYjvon3puu77fuL/lj0NIf3WJ8QrC+ve11j7GtOmTdtjOil3BaIo8oEPfIBbbrllPGH7P7zyyiv89re/3Sl+oO+VrkKCQ2s7+P2yuRw3ew0vNNYhtxZQZQdRcHniT/P5ffVWbk61/IsRPAbTUSTNIZsPjq95vSt7v4H7jjB+e4whkydPpquri4GBASKRCBMmTNiuZA18tX/BEYhu8Uit9C+jFHCw8irxP4epeVFGThgEVgdZtnQC+VIA89QMba2DhFtzbPkPEDyY3toHnkB9U5q6CcPIURMvYeHGbGTNIV0IIS+OIhkQ6ofBvzTihh3ESoPwegVlRMbrC2BHXNRODTvs4jbqiFmFzEgYuV+j2OIgFSTkgki4QwHJw9VcPFNCKkN2hgOuX6tmVtmIpgiOgDooo+QEHM3DEwEPoptFgtVFgr2+dyeugKI4CAUJobUEYYdQfQElK2GmA3iSR31VhomNg9hFheFSGEHwIGKzcbSK+uoMo+UQm9fV05lN8FjvTPJGgMeW70eFWsQcCTC6qAZR9Hj9DzNZULmVTy05l2SwhGNKbMpWckRdO3/720xmzNnKd1r+MaP23HPPcdttt5FO+zYDDz30EJdffjnlcvl93S+CIPD0008zNDS07b0bvGkMDQ1x0003MTw8/L7G3RcIhUL09/e/RTJhX+PII49k9erVbNq0aaxD2WNwXZfPfvazfOxjHyORSOzWY39TWU1nTwXrcjWEUyX+umEKZtIhHtKpjeVoL1Qy6agODpjd/q8HcURUzaa1Zhgns2u058bZdxhP2MaYhoYGNE3jySeffJvLwTshiL4uWb5VYGSe4/tvCn7H7+h0gZEPlHEsCUcDtb6IWVApbo7T0VGD4wq+SwCwtr2euqY0UxJDhBQTZ1QjFNUJxHWswSCl0SClmTqeBOnDTDwJoutlvEENY14RJ+QilwVCPSJms0GoV8S1JNykBZ6AmgOpLCI4vn1Usc1CHZSRdF+7DQGkgoiZcpB0wBJwNb+BwY74tWmxzaJfz1aSyB5oEHg6BqIvH4LsUcwG8WQP1xGRAjblgkZgRoa6lhHiVQVyf64jpweoqc8wMhylaKhMbulnsC8BgOMK1E4YwUUgFSjREM1yxgGv8dTL+1HbkuZLn/wDli3BQVl+9cZBREM6HevruDkwkS+kF3Dk5g8jOLC2+x9q+47jcM899xAMBvnVr37Fyy+/zAsvvMDkyZO59dZb/2ktkuu6jIyMMDg4yCuvvMJ3vvMdXnnlFf7/Tm5RFNm0aRNbt24FoFwu8+Mf/5glS5aQz/97r40uX76cwcHBsQ5jl6GqKtXV1WzZsmWsQ9lj+O///m9M0+T4448fk+MfM309o+WQ7/ebVRFiFoODccq2wum1r5M1AwyVw/9036H9buewGRtRZIfBfBQxZu7m6PdOxmvYxhlT+vv7eeKJJ7jiiiu2ex9X9wVYJR0i7RKFNhArbeqfkeg7wkECRMnDnKAjbokg1ul4soxgCZgb4oSmZHGXxTEqXEaLQV5cM5O6WQPgCNi2hDkURK0p4XaEsSMiahaIlQkcnqf0WgXVrwkYsTD5Ng877OFoIPeruAoE2n1jd73KxYqAk7TxPAhtUTBSHq6Mv8ypS5gJCPYLFCZ7mCkXbUTCbNMRhjTciIPWIVNs9PAk8GI2guChp0A8MEv0pTj5aRaYIkLAxS7J4ArIURPTlhjJhTGHggSPzGHpGo4j4hkSubQ/yyYUJXLlAPktcbIRhwOmbqFgqWTNAK8vP5hvnPgo1y86hV+4h1AVKTA72cfhszbw3Q0ncnPlW5c4vt361lq1TZs2UVlZyf3338+ECRNYvnw5v/nNbzj00EM5+OCDueuuuzjnnHOQZZmXX36ZZ555hk2bNqGqKoqiUFFRwZlnnskvfvELHn/8cRobG9m0aRM9PT20tLSQTqdpbGxkeHiYmTNnbhMh/XfmtNNOG+sQdjmmae6TmnPvh5///Of86le/4oYbbtjtGnW3V7zCnFCemKwzOTnE0r4GpKTJ/NYtLO5sJlcO8Gp+ArOSfRwY3UJH3SraVp+7bf/vRJZxHrAuXU1rMs2KjU0EEjo4u/U0xtnLGJ9h2wM499xzOfjgg2lp+Vd1Dm9HGZUQRFBzvq5XaplE1SNBPAHqnxUILA0RezGItimAU2n5umWAaIp4okdxOEy50abiWQ1WR1FzAoroEBwQCWgWoS4/aXM1D7lCR68EvTOKen8Svd5meA7IukfDczau4mLHHfAE9GoXK+qhFN4M1AMx4z8XOAFA9LAqbOQivuK/AHolCIZIsEfE0SCyLICregi6SLkK5KK/LIor4BUVyhNNCiMh8lNs5LCFWPZFcwVHQCpIeK5ALKhjDgbxNBejrGAaCuabSuKzJ3STCpWYNWcLsaBO68xepJDF2sFq+n7fQmdXJamWDN9ZdiL/MWcZQ8MxNNnmsY0zuGXT8VxefHdT7scff5wzzjiDyspKVq5cSX9/P8cccwyapvHEE09QKBS44oorePrpp7nrrrv40pe+xIYNGxgdHWVwcJC1a9dy1VVXsWHDBs477zzmz5/PHXfcwYc+9CF++MMf0tnZyZlnnsnll1/OF7/4RZqbm3e5IOiezsjICP/zP/8z1mHsMnRdZ2hoaLvLJvZl/vznP3PppZdyySWXkEyOjeJsfynKMw/OJ22EmFk9gNgRZNNoJXMae8kNR+gpJXipZwLPjk7j151zqT7oSr6prOZnn3gYxxVZUWjkyimPoTsyUsBGTwfH5Dz2Jjz8ztodee3NjM+w7QZWr16NZVnMmTPnbZ57v/zlL3njjTe4+eab39OYboOOJEJmukiwXyLW4ZGZIlKqc9HSIuFuGJlvoQ4pBNpVXBnsiL8E6dSYyEMqjuYxOgME21+uHCmG0RakyW1I4k4zCW1QESwILg8xcoxONF5GnqGT+H0dZhSG5jsIlkS4U8QOgVHlm8ArRTASULFMoNAMTgiUIQWz0UQcVZBzvqq/VBYRLbDivlBuqckl2i5SbPAId4uUGlzMBn8GLbJZIj/N8S2vyjKIfuOBvCGEN8MXAY7X5cj2xAmHTIY3VSBV6359m+D5jRiii11SGC6HSQVKiIJH/9Jaauf2c3hbOyuH67CPGSVg+ZIff948k/ZCJc31I3RnEthFhSErCttRarJ06VIeeeQRgLcl4jU1Nfztb3/jlltu4c477+Tuu+/+l7NDsixzySWXbPv/QQcdRCKRQBAEvvrVrwLQ09OzrX5rd9fx7ElEo1GOPPLIsQ5jl7F06VJmzpy528Rn90Rs2+biiy/mvvvu44tf/CITJ+5+odkH6p+jUnBpCaf5y+ERPlb7Oj9cfyzi1DzDI1HmVvVw7eGP8kahhUsbn+DTv7uQH3/4bhaX2zi8sYN1p86nWDKo17JknDAjpTDNNWlG/9gAh+320xlnL2J8hm0Xc/3113PooYcyb948vv71r7/ls8HBQS6++GIuuOCC97zM4doi4pYggivg7Z+nVC0Q63B93bIZBdKHG2hxA2VaFr3VJPCmKbg6KiDKLmJTCcI2gYk5PNlDjFjkMyEyI2GcqIOQkylNMik1ugwfaSF3BSgUAgxmo+TbPKwY/swWUGxzMGocEMFVPawwWDEPWfeXbOWCL3QrZGVC3b6umh3yt/UkUHICVsrGi9hYEQj1+E4Gnuoi5mRwodjk+ubvOcXXfStKeKqLUengbA0TTZTIZUKgupTyGsmJowCYuoxpKBSzAY6dsBE1apIpBhksRtAdmeSsYXqHErzW08zk5DDec0lYGeWv3ZOJhnTa0xUMZqMc0rCFeVO3UlmR508tT7zjtbFtG8Mw3tGvUBRFLrvsMtavX/+elvJEUeSPf/zjW95raGjgxBNP5PHHH9/ucfZF+vv7tynI74ts3LiRo446aqzDGDM2b97MQQcdxF//+le+/e1vs//+++/2GH6UXMxgKUJINnl9pJGrZ/6JlaVGDq7bSl08R/SNACvTdczQejk0uonfZg4kOCHHU9lZ3LXuUDoKKXo+aREKGtz12uE8MzqdeKDMUCGCt3B0t5/PXocH3g6+9mbGE7ZdiOu63HrrrVxxxRWcd955rFix4i2fn3vuuRx44IHMnDnzvQ+eV3BCfqeo9FqUYrOHGRWJbhGQlkcIbtSwdBlrXRyty68p82S/fowhDac35Ju2vxyHhjJCbwBpWEGLmGiDMoItoEZNPNVDzChYjQZuXsHZGsYJuVgJxxewzYgQdAh3SMg5EbkkYMcdJF0g1+ovcYq2X6cW7BcpTHIQXJBLEO4UQQDRAsEUkYYV4u0e5YOL4EGoUya2SUCu0JELvkBvYFBCqiv7DggFeZtNlWHJuIZEMFFGVFxG+mM4JQWGNZyyTEPdKM88PwfX8QtPNcUmJFvURvLIHUGMrgjrRqoQj0lTd0Q39osphnsSmGvjzKnr5Y0757B0czPpbIRXut956dqyLFRVfe/XdDuwLItnnnnmbe9fffXVvPDCC1x00UVceeWVtLe/Q2faPsTIyAjXX3894Cc0r7/+diHTfYXu7u5/2+XQe++9lwMPPJCpU6dy1VVXUVFRMSZxjBZD1IbzFGyNibER7uw+gohkUB/IkAyUiZ3cx8Dqar68/hOYnsR/pV5CU2xmh7qJBAy+O+E3HDlxI/UXZDl61nqCkoUq+TZzhc2JMTmncfYexhO2XcjQ0BCZTIZAIMDzzz/PBz7wgW2fPfHEE7z66quceeaZ729w2a//cjWXwiQbN2mSme4hl8DRoDzRRO0IwMQiVtyl0OShZEUkA4K9IkpOILFSxoyD2BHCrTVwgi7C8ihmhQM1OmZJQc5Kfjem7bsZRDoF0FzQXL/J04HoChU7DE7AQ7T8hgIrZeME/Lo1a1qJ/HQLSQepKKKNCpRabEoNHqIBchHknIQb8Bg8EKR1YQpTLewAlKvBzmhYcQc76mCkXKyhAE7YwZM8PNHDrTEwh4OIZYnyUAinLKPFDaTRN1f8DZGeLZU07N+HKHlYlkR/OsbyxRPZPFJBaE6amXO3EFRs5tV0s2V1Pft9ZC3JZTJuW4lX1k5g9rmrkAcUQiEDcVmUHyUXv+2SlEolnnzySVatWrXLErbKykp+9KMfve39OXPm0Nvby+9+9zsuuOACbrzxRn7961/vk3ZNf8c0TdLpNGef7XsLLly4kKOPPnpsg9pFWJbFunXr3vId8u9AqVTizDPP5NJLL+Xiiy/mtNNO2+0NBv8/tbEcIcmkQi1iuRIh2SJjhejVE8xPdhBXdepmDTC/aiuq4JBxg8yp6qHkqkxKDhMWbF7rbUF+0GPwVJWlQw20D1aSKQRxU+8i4jgOAC7CDr32ZsYTtl1IVVUVCxcu5LrrrmPixIl84Qtf2PbZNddcw0c+8hGCwfdZaBp0fBWPoC/noW3REBzILCxhxVwkzcGosXEsv5hfLgvIJTATHpIJcgGMFNgRl8oVLsrWANGNEuUmm8gmCQYDVLyg+UlchUFos0KwVyQ73SG6WiG5RMETwKhwKbS4uDIEhkTssOebuecknIA//6ytDCGW/I5QwRLQKz2iG2RfHFeF/CQH0QElKxLqFbBiHuqAgpYBo8ZGLEngCf7sWln0zd0dAU/08FSPyLIAYtRErDRA8cATkEQXJ2kT6BdpnDRIQ+swIh5mUUFWHOySQsXUYdpSacpvpBg1ghQNlRefm03NlGE6shU4J2SgO4iguLz2p1ksOHItB9Z1kjh8gBmJgbddksHBQe68804eeeQR5s+f//6u67uwbt06zjvvvH/6maqqHHLIIVx88cW8/vrrdHR0cNVVV9Hd3b1LYhlr+vv7ee655/bpZdC/s2HDBpqbm6mpqRnrUHYrl112GatXr+amm25i2rRpYxrLHZUvMzE6wuqRWnpKcZ5fMwXdkZkQHOK1gWaios6Xm54iUwrybM9kFgS6eTQzjxc7JlIl59kv1o0ieJQ6o3y+8VnW3tTKSHuKiliRD05azVHTNozp+Y2z5zOesO1CRFHk8ccfZ3h4mMcff3ybzdTKlStZu3btjtWjeOBqHhQlkssU1Mybb7sCbtjBGdH8ZG4oQLnWrxUrtdpoIwK5uQbFSTZ6i4kXccg3iCTWexQmuMg5CScI1YthZK5DqEfEtUXKNS7VS00CvRK5aTbZSR5e3EbSBULdInbExUj5zQNO1AUR5JKAaIL1ps2So4JSADUrYCT9ZNET8WvfZHAV0Cv8WUMn5JFvcxGLEm7AhYiNXuv4JvIF0XczkD3EgE2xyUML+k+nFbVZsAQMXUGNGsSOGqT/9Tpqw3k6tlbT1jiEbUk0Nw0z1F7BhoFqKg/up2BolDbFCU8fpb8/wcK69RzbtAGptchhUzajzk+zuKuZFzsmkn2hhlf6/rEs6rounZ2dyLJMMpnkC1/4Ak899dT7v7bvQGNj41sS/3/FpEmTeOWVV/j0pz/NNddcwwsvvLBL4hlLmpub+fSnPz3WYewWVqxYsU83VPwrXnrpJU455RQikX/i1TYGdJUShFSTwWKExsYRMnqQ25YdzTENG5kT6GTIiVHKaxxR187Duf0ZNiLcMO/3BESLzyZWcFf6EPab20HGCXPI1M1Mn91JUzTDi7fNR3f+vbu8x3l3xhO2MeCee+5hwYIFO7RsJg0rxNZJpFZKmHFwNYhsEaA/gGALiKZAaJ2GVBZwE/6ymDooo1d7SIMqyrCM2qNCWcRcUMCMCkTbRZxKC0+C/uMsCLoU2xwkxSXUK7L1JAW92kVw/aVQMSNjxx1KTS4kTYQ3V9/krIQ24k89C45fr+bJfoeqXu36Xakhj8CwiOCBnBOxaw1/ZwHkgn9bipaA8Ka+rNyvog5JKH3+z0w0BLBEPFdEbij6wpXDGrlCEDFq4eYVzIJKX3cSt8l3Fqiuy9CTTuAMBxj8Wz1ELez+IEVTpVjSEE0B5/kUFdU57n/pUAaNKIlwmWWPzqBsqLibI6RiJey5Ba7S/1FLtGTJEr75zW9yyy23MGnSpPe/zL0dbN68mf3222+7thVFkauuuoqnnnqKe++9l76+vl0W11jgOA6XXHIJxeK+b8C4YsUKTj755LEOY7fiui4bNmxg0qRJYx0KAAekumgJpzEsGUn0aImOUjIV5rZ001tO0G5VUytn+M7Bv6VXj7My38A5NS9yaLCbU0MlkmKIDYUaVnbVUytnCMsmn2l4gZylMbzAYWtubORJ9iY8/r2Fc8cTtjHgj3/8I4cccsgOjRHsF4h2uyTX6eD6hftq3iM4KND4hEBwUMDRQEuDmJcIDEOoD6SygGgJ2FEXuQSBAQn5jQj5w8uYMQhsVjFSLvKQ4gvzJgw8D0ozdZy4jVpTgoCDXBLA8W9+NS0iDGm+ZIjmd3+aiTc11moc7BB+E0MOvLiNHQIn6vjbSvizbIaEU69jRx08AUTTN3xPrBcQohaCC3bUw6o3fRusnIBcVUYOWGiqTa43hhtwEQQPp6gQ2iIjjShEKkvUV2dYuqURSfQwSwpt03uxppYBgcpJI7jPpLCKCnaTTn6aRXokglpVZllfA7YrUn18N+ZgEGlynsvyc7nBfevSTCQSIRaLsWXLFl577bV37A7dURobG3Gc96auOX/+fL74xS9y991376KoxgZJkvje975HOPzPleT3FVasWEGxWPy3S9g6OjpQVXWPmV3bWqrgmPg6JNEv9XA9gaBis2aghoBkUSXn6LcTfGPpf7Cip57za17g5s6TOOqFizjwjY/zn1uO5vy65/n2Qb8j7wYZMcIkpBJFS6WhbZihTISvDnSO8VmOsyczrsO2m9m6dSu9vb1Mnz59h8bJT7UBmdHJAcykx+T/6aX9nAaMKgcjIVGz2KH3KAE7JJBYLeIEfCcoNQueBPFNAsMHOIiGiGCDY0gIIYi1gxX1Z+gE2SWyKERmjkX1izLpWWAKoPQrGG0GOALyoIpR4yAVRARHwK727VXUDr8zVc5LuIpvMVWqc5H7VKyEgzosI1pgVDqkVkiMzhDxNAHRfHOcOgMxozByuIGq2ZiVNmJZRBBdPMXFmVPCzqvIQwqFOgO1sgzrIrijYSQZ9FqX5OQ02VUVFGY4KAGbkqkgSB7tW2oQixKIUIqrlA8sIwJyexCz2kaQPJytYawag1DA5MKRg6GSf6lCnkgkyOfzmKaJLO/aX6n32x23cOFCfvWrX+3kaMaWFStWEI1GaWtrG+tQdhmZTIY777yT6667Dk379/KaXL16NbW1te++4W5izVANw/oRzKrooy04zCvpNtKFEFOrB3n+9elcespfmCinOaZtIy4C17Sfyn81vczaRD2K4PDA6oPImQGmxAZRBIfDUpv4Y2YuE2MjvPjSTC7+wJ/8A638/Nie6B7N3i9+uyOMJ2y7mV//+tfMnj17Wz3b+yXQJ6PmoNjgd2UOH12Pq/jaaJ7sUaqWCPX6NWNaziVT40+mGpUuUlFkNAVT7yrQeXIcK+pR+YLCyFyXzAyItouUakEY0sjub6H1KQwtcFBHJMR+heCsUayuGGLSJLHeIzNVwo44SLqImFEI9gm4GlQttxmcJ1Nu/LugroBcBsmUcFR/Zk3JSlhBfD25ooyrugi2iDSk4oRdxFEVbbmGMd1GqDZwCopv7C4EQPWbHYS0iimpUGX7DQlhCy+nMNwbJ9EjIM1yCQdM0lsTSEkTryyh1Jcw0wEk0cVzBZrq0oyETez2GFLSIDlzmOG1lQwbEsTe+rNfs2YNixcvRpIkNm7cSEdHB1deeSWhUGiHrumuZMOGDftcwXq5XN6nk5hiscgNN9zARz/6Uc4///yxDme309LSwsjIyFiHAcD/1j1PrBymOlhgxAhTtFUmRYc4vfZ1vrnoP6idMMLDmYP4UHwpy4Yb0C2Z62b+gRs2nEzRUJElB29QY97MLkasMNPCffyy82D+s/k1XjImIZoCA5YviLxv/ZaOszMZT9h2M0888QRz5ry7tdG7EeqDUh2YSZdQ95sr2x5IhoAVdcnM8FBHRewglOpE5CIoeTATAmoWXEWg0BqhYrXD8CyJ0elvTvMnLMrVGon1Ho4qUGhRcBW//syK+/VrZV31PT9djeEDXERbQLREHM0jvlGkVANWzGVkpoyrguAIJNYJ5Np8f1ElL/rJ5kSLYKfiy3vofpKH6OFEXDzJQyqJeBUGbl/Al/3QRYSYjZqRcertNxsvXAi6ILlQkCFqI4geyqiEPcEke4CLOBomHDGQiiJqrYVd7eI6AkrCIDsUIZQsUzA0dF3BTVp4psRIJoIbcPle7O2zN7fffjsf+tCHCAQCnHXWWZxwwgl7vPr8pk2bqKqqGuswdioLFiwY6xB2KZs2bcKyLG677baxDmVMmD17Nrqu7xEOHhHFoDU8wp/Wz+Yj05ezNltDzgwwL7yFxoYRypbCN6tW0mkbfLzldZ4fnoLuKnx50jOsLjUwP9LOPcnDeH5wEq4nUHYUJsWHqZAKHJNcxyvSdGqU7Jie497C3i5+uyOM17DtZtrb22ltbf2Xn3uexxNPPMHf/va3dxzHlSG11iW1QsSOgJ4SqHvZpu5lm8qlAuqob/ukZSDU+6ZQbb+LXBQIpAEBcs0SQ3MknIDf0elJ/m+CkoeRuR65hUWULDh1hr8c6IGoi3geGE0mVUsEwp0SgiUQ7BNA8ig0eWijIOkCdgisqEugXyK9n4sV97XTXAlKkywC3Qqi6dtixTf5kh9iSfJlQYqSX8s2qKHvX8ZO2NvcEvQaF9eQEBUXbViCsi/AG6ovEIwYeK6AMD2PU5KRNZvqijzFLTGk1iLGliieB7auYJUVlIiJ0RUhmwshtofAEgkvD+BY4tsM3sHXwyoUClx88cXcdtttfOxjH9vjkzXwl+IrKyvHOoydyt13383q1avHOoxdxqxZs7BtmyeffHKsQxkTRFFk+vTprFmzZkzj6J71c3RH4bFNMzl+8lqWj9ZTshX2T3TzfHYaH6pfyRNz7kFEZLOV4OXRiWwcqsJB5LnMNDTRpt+K863m33NARRdnNC7h5NQKbm96mmez0zgosAWn0mKLUcUWY996qBpn5zKesO1mQqEQhmH80888z+NnP/sZd999N1u2bHnHcbLzTLITRIJph5Y/55FLkJ4qMzrJrzUL9/iF+x5gxny3gVyLSHAQypV+96YT8hM5V/H85VRDJLpcw0h5RDpEvO4QTgBCqwLIRZHggG8cb+U0MEUGD3YpNbjg+dIdYlnEqTIptLjYCRuj2gEBjJRLxTIBwo5fnxZzoCRhVDqUGlwEyaNY78/EaS15X19O8JNHT/ZQVBstbvi2JBG/KUGwRFxL9P1RAVFyURUHVbEJhE1sUyZcUUKUPIZWViE3lDALKtTq2LqC3K8STZSwdV9PztElzGoLT/IoTHQQJZerV7xVv2zlypX853/+J21tbSxcuPA9F/+PJYVC4f1r/u2hfPjDH6axsXGsw9hlSJLEKaecwo033jjWoYwZZ5999i6TyNke/tL2Zx4bmElnNsGBTZ2UHZXGcAaAZZlGFvc3sbpQz8VdvqDxZCXDQCnCzNp+/jyyH/tFulhfrGHAivOFDZ/kdyv254crjiUmlvmfzDQ+WfEqf8rPYfqEXiYH+pkc6B+zc91bGO8SHWe3UVFRwcaNG98mseB5Ho888gjPPPMM9fX17yoNIeRlilMs+g4RcTWZYj24KlgxiG0SEG3fdcBVINzvW1IJnl83Fu320Ks8BAfsMHgKSLo/rh3290eAUK+AE4RSg4sd8ig123gKaP0y6pBvwO5JvnitlvGTK0Hy8AIOguIhZyWkkkj1awKZqZBapELSRCqLqFkRRFBrSwg52XdKiNq4q2J4KV9rzZN9EVxVsfE2RiDgEkyU0RqKxBuyCMMadswh2CchiJBtT5DrSACgahal0RCRoIETcXG2hKEoI8kuQk5GnpSnVFYJx8t4cQt5QAUBBNlDqyoRWhZE+j959d9N3FevXk1fXx/5fH5n3BK7hX2t3uupp55CVdW9YnZzRzj66KNZvnw5ixe/3Vnj34HPfOYz9Pf3v+sD7K7g9opXmBbu4/zGv7GwYQO2K5FQSiiCywdq12C6EofUbaExMMoJqVV8suNYfjB0NJ9qepUl61qZFe0hIFrMiPRx76qD+XLr05w0czVuX4gLf3c+IdHk/uFDEAWXhlCWm5aeyE1LT9zt5znO3sN4wrabufnmm/njH//IlVdeyS9/+UvANwu/4447ePHFFwG48MIL39V+JbZRpPp5mcCIQO8RQWJbPEIDHsEB/HqziIBSgMAoWCEBpQhKEWKdDrlWgXCngOCAJ0Cwz99WHfV1z9JzHUp1vok7E4t4qufLeLgCruxh1FlYLTrBLhnCDnJeJLbVZcLvTKSeAKLmIGT9DNGOORTqBeywS3ayh9wdwFU8zHoTqSRi9ocQ7Df9R4sSRsrF8wTMehNCDoIFueEIruqB4KGXVATBo1AMEJ6QJZAqU55iIKs2sbYMXszGsiTEV2NocZ2RvhhIHuEpGbygg1VQkcoCmmoRj5YpDIURFRenUUcQPeQBBWMohF4Jhck2X+3/R5t9LBbjM5/5DACnnnoqsVjsn1+cPZBisbhPJWzZbBZRFPH28YKWQCDAKaecwte//vWxDmVM0DSNs88+m0cffXS3HztdCrG6UE+7WcVhkQ10F+IcHtvA37rbcBAomBodhQq+VrmEieogByU6+P3KOeTdAILisirfwAR1kK3lCiTZ4cPhIlVqgZrpg9z+kTtZUWjkiPh6ZgR6WTtaw5f2/ytf2v+vu/089yZ8A/fxGbZxdhMHHXQQ6XSaZcuW8dxzz7FkyRKuu+46LMti6tSpHHvssUyZMuVdxylXQ7FGINrpL0m6soAdELCDvqNAuNfF0d7UOBMgNGhjxCA9RULNQDDtz7qpOX9WrVTnYVb4++CCXPSbAKyhAFJeBFdAsAS/qN8W8fIK+lQdBA+z0WRklognCEy6P03qhQBSScSVQYyZuAfnIOT4pvE1viOBPKiiZgSEuImbsInW5fFSJpIhEIrqSAEHUXHwJAinSlTMGEbUHLyCgqr4Cr35rhiV0SKS6qCng5iWjKQ5qKpN/UmdVEaLxKqKEHDIjYZRIiYYIrGZaXIdCUq6Sqy6gJtT8VwBRLDDLrhgxx3EgoRQ+dZptoULF1JXV7ddSfWeRGdnJ3V1dWMdxk7j9NNPZ9myZdxxxx1jHcou56STTuKNN97Y9kC3vfzyl7/kpptuel/Cwhs3buSqq67ii1/8Io899th73n9n8s1vfpN169axadOm3XrcyL0JVo/U0W/E+eHW45id6uOx9H4cVN/FqBXGcUUGClG+3n8kf8jOo+RonD5nKS+lJ3HQxK2cXf0SVVKRmKLz3CH/w9wln+ADseVc0PYCP+5eyMp0PdO0fraYldSG8/yuZ39+17P/bj3HcfYu9p6/OPsAnZ2dHHrooey///7U1tZy5pln8uSTT3Laaacxd+5curu7+a//+q/tGkvwQCn5/zoBKDT7orVq3n8V60Qky39PcCAzQaZyjY1sgB2EXItAtNtfFg31gZYW/K5M0a9lMybrOKqHmpbwVA87aaPkRDxT9BO4sK9tRsl3TBDnZOk5WmPjp5LoKWh43sINuLiWRLkvDAKISRNpVMYNOThBl3KNixK0EQM2+XQIzxVxog6l/giOIREMm1TPGELfFGNkTSXqhiCEbDxP4PC2dqRKnaFsBM8RkEIW5YKGY4kYhsLW4RRFUyWfDTJ3QhcVVTnssoJYFklvSeBFbSTJpdge95sdZBc5YKGOSv9ITiUPz3nrE5koihx22GE88MADu+AO2TUMDw+Ty+X2OVmPQw45hHPOOWesw9jlBAIBPvzhD3PllVdu1/YPPPAAU6ZM4bLLLuOee+7h3HPPfU/HO+ecc5g3bx5/+9vf6Onp4dOf/jSHHHLIuzZC7Sri8TgXX3wxDzzwwG6dUe051mNycoil6UY2b6nl1NRSPlrxOv3lKI9vnYEiOVwy5Sm+UfNXVmbq6ShXMCEwSGMww5TIAH8ancsEWWJyoJ/XjUo+1LIKCY+Tw1tZ2dHAvIpuEqLJnRsOQ8RDkRwUae+pix0rXE/YodfezHjCtpt48MEH2X///ampqSEcDnPhhRfy05/+lKVLl9Lc3MwDDzzAV7/6VQKBwHaNp6X9poJCnYik+00GeH9P0DyCIx5axn2zqQBkHYrVEnIRgiMeggf5RuHN2TVAfLO+bSsEBwWEERVX83BCHk7IRR2WMSscIhtlX8ZjRMEcCYLkL28W0yFcBZyYQ2mWjhMQCfZJoPt1bEJeRt4cxKm0EGQP0RIgamHpMk7Zr4cTZQcpauHJHqLiUC6qqLI/m+ZWGxgTdQTBIzsY4aXnZnHkhE2koiUEEWTVQRxR8UwRVbWxLV/nTpRd2kdTjAzEEPIy1OhIFX4nabEvAjU6XsQmGi0jrQ9jh/zYpKJIqEv0Z97+D9XV1QwMvN38fU+lp6cHRVEolUpjHcpORRAEXnnlFX7605+OdSi7nKOPPprFixeTTqffddtLL72UZDLJjTfeyOc+9zn++tf3tsz2xz/+keuvv54LL7yQM888kx/96EdMmzaNU089lRNOOIEVK1a839N431x22WVkMhmWL1++W453lbSW1in9RGWdjze8zhkHvEaXVcGNm3y3ifOnvIRuywzYcf5YmMwdEx+hLTjCX4Zmokk2IclkQ74K3XP4bf9cftl/GPctPZhPLvoMB7/wBRYtvJXLa55lohzh+7MfpiqQ5+Sa1Zxcs+92PY+z44wnbLuYUqnEWWedxUUXXcRFF13EmWeeybnnnsvvfvc7LrjgAo4//nguvfRSLrvsMlKp1HaP6wn44rYeSG/OmiGAXPJQ8x52AIyE6NtTZTwCoy6SBVrWxYwJxNv9pgQj6SGV/fFim6HQ5C+pegJIJV9bTbAFXMXDkz2KM0zMKovWx0xi6yWknETqVRXBEtFGfL9SrySTniYhWhDqlLBTNp7m4gQ91C4VyhKBAQEM6U1zOPz6Mc3BsURi1QVkzcF1RIZyEaSWIrXVWTxXJJ4sIYdt7FqDZ9dNJZ0P4ToCrivgVpjEqwuURkJoAQvdUHAtEVVy/ISxpoxriyRiJYIJHaVCxykq4AnksiGMKofAsECoR8ANur6bxP95IvM8j2effZaFCxfu3BtlB3FdlyVLlnD//fezcePGt3w2Z84cPvzhD/Ozn/1sjKLbNZRKJY466qh/i1m2UCjEtGnTeOSRR95128mTJ3PAAQcQi8WorKwkm91+fa+NGzdimuZbls8VReHkk0/mRz/6EalUisMPP5yHHnrofZ3H+0VVVb75zW9y//3347ruLj9eLKQzI+l3bL6eb2Flpp6frDuKSfFh+nIxBs0YYdWkSUkTlXRe0evJOUHOr3+BtdkaPhRbxq0THuZ3hTbunfQwC5LtRBMlTp+xlIpEge8OHsUzpWa+PjCHB4YPZvFAM08OTefJoR1zwPl3wK9je/+vvZnxhG0XsmTJEmbPns3GjRu56aabmDVrFgDJZJLPfe5zDAwMMHXqVL71rW8xYcKE9zR2aMhDzfnJmJoDuey7Gqh5DzMqYIUFXAkQwA4JhHt09JRAdoIIHmQmC7gqqFm/E1Q0ITzo4CpvKmokTVzNQzIEPNnDqrBR0jLiqIIcsej+nIUnghNxyUx3EaMmdgTsmAuaL/dRnGAj2KCMyKA5OFUmZsJF1EXK9R6e6DchCLoEGRXbkIglStiOiJkOgCsQCpg4toRhy2gRg0JRY0LtEGqnRjReJqBZKAEbTbNJVRTIDkUQNAdDV9D7Q+AJGLZMcuIoguAhyi4jgzH0oRBmXiWQKjN1Qi8NNaOIpkCpwaFc5xHeKiIYIpTe6kixePFidF3n4osv3kl3yY5TKpU44ogj+MAHPsB1113HvHnzOOyww94yG3HbbbexdOlSTNMcw0h3Hq7rcu2115LJZFBVdazD2S3Mmzdvu4rv//u//5sHH3yQP/3pT9uu9/YmOX/961+ZMmUKgvD2meVgMMhpp53GJZdcwmc/+9n3XFO3o5x77rmEw+HdoktXE87zdMdU1mRq2ZJPMT0+wKzqfkqOyhemPE/ODhJVDB4dnssNqz+AhEuFkqfkakyPD1AvQc5TOTm8mS5H5djwWhbUbyUiGRxfv46gZHFAoIv9w53c0fg8JzSsY0p0kCnRwV1+buPsvYwnbLsA13W54YYbWLhwIccddxyXXHIJ0Wj0LdvMnz+fM888k6OOOup9mYXrSQHRAsnwCKQdPBECGRdPhtCQg+D6S5xm1DdYLzYGiHY6VKyxkQxIrXERLQgO+UumerWHGRWRymBFPRhVcWI2Sk5AUP0veyfk4qou3kAApzPsNzRoDjXThnAdEWOijqj7t5RoC8hpGaXky4PgClCQUWtLvnxHwkJwBJyA34EqVfuzX2HN9Dt5VJdwogyAN6gRD5QRANuQ6c3GcacUMSyZ3HAEcyCI44iUdJXKuiyeKSIrDuGGAkJeJjcaoqSrsC7CxPohYqkiYsxECtoEVIv1qxvpHUogF0RiTTmqXvcoNXggesi5fyRstm1z//33853vfGeXe4a+F+6++25GRka49dZbue666zjjjDNYtGgRt9xyy7ZtEokEsViMTCYzdoHuRERR5NprryWZTI51KLuNAw88kJdeeuldk+6PfvSj/PznP+eJJ57g0UcfZfbs2dvdIPPSSy8xefLkd9xmxowZnHfeeXzkIx9h7dq12x3/jiKKIvfddx+//e1veeONN3bpsdb01KHIDjMS/Qzmo8wOdXFUaj0R2eDB7oNoL1Rwdv3LnFvzImdN9pdLDw1tYsSJsDJTR1IMUSUa3Dx0JP12jJt7T+LTlX/j2cHJJJUi+4W6eDAzn4RU5NFiBRFZ56PJ1/lo8vVdel77AuNdouO8Z0zT5L777uP3v//9WwRUBwYGOOaYY7jzzju55pprOO644/7p0+qOEhpySa01CPeaaKM2WsajVCViBwT0lO8SEBxx0bIglz30hEiuRSI9TcaMQaHeXy41Ev6SarRDwIgJhPr9WTJfAw30FgtKElq/gmALEHKQ60vIrQUSmxyUfpXRl2r8TlVdxg24eLaAE7HRRiHf5pE/QPfrx4Dg8xFCqTLSiIKUk3BTJnbEJRwyUEMWo4UQekFDCVkYhkx6U4rmmX0M5qOYuszcCV3Ux/3lUf9CiMiVOrGQjgdksmHqm9IoioMsOdRPHUSUXV9AuMEiJFsU8gG0gEU0WsayJQK1JZySjNWso5sKQ/MEnKgDYZtvT/iHMOv999/PhAkT+PjHP77Tr+eO4DgO8XgcSZJYtmwZDz30EH/+85+55557AD/RPP3007Esa7trJPdkdF3n+uuv3yfO5b1QWVlJVVUVjz/++Ltue/rpp3PZZZfx9NNPY9v2do1vmiaLFi1614QN/IaPv9e09ffvPrHXefPm8atf/Yqf/OQn21XP9374Ze0LpOIFjmteT9HWmFQxzHOZqTzSM4+ZkV5OqV/Jf9a/yjUrT+GZ/ExGrCj1yii/Th/Ew90HUBvM80RZ5f7sAawYreeIwCg5M8BKo4mtAxWcGFlN3gmwJl/Ha8WJ7K/1MCfYyfe7T+D73SfsknMaZ99gPGF7Hzz99NNMmzaN6667jk9/+tPb/oAXi0WOPfZYNE3jhhtu2KUq7J4IdkSiVKeSb1YRbY/EZgvpzYdvpehhBwXkkocTeFNzTYR4u59cOgFfaNcOg17tEEy7mDHITvbFcHF9myh5WEZO6Ri1vguA1qXi2BKWIdN9HLiqhzcnDwjIURNX9ZCKEvKojBkHuSCgbQ6gNhSR8xLZuRZ6TwS3xoCmMp4lkmrJENFMXFegIZlBlB2/GWEgCEmTzsEUouBRXZFn6eYmNq1qRBBdzIGg737gCQx2pHBskXishGHLOI5INGBQthRcR8Q2ZSpqs2zN+jMyhq5QHSn4HamOSDCpI3cHsHTZ15yzBW4OTtz28160aBFLlizhN7/5zS67pu+XI444gp6eHj772c9y3333cdttt3HyySdvm1W5/fbbWbFiBd///vf3Ku24f4Wqqntc0ry7mDp1Kq+88sp2bfulL32Jk08+mfvuu+8dt1u/fj1Llixh4cKFRCIRpk/fvjqqk08+mblz53LcccdRKBS2a5+dwYknnshxxx3Hs88+u0vGPyDZiW4pVKt5gpLF+sFqKlS/YWd5vpHFmTYqpDxnT32V+eHNTAv2orsKpySXMifVw5TwAA8NLaBSztMYzrLVhoRWZtCKcezkDXTZCX7dN4+NI5U80TODL7V/nIwTZn5yC/OTW3bJOY2zb7DnrOvsJXzzm9/k1ltv5VOf+hSHH3445XKZr371q9x99908/PDDxGIxzjvvvF2u0SXrHlZYxJUF/h975x0nVXX+//e9d3qf3dneC8suu9I7UkWxKxbsvUWx16j5GrvGqLHExJjYUGMvYKcoHaT3ZVmW7b1M73fu/f0xxF9MYgREEMP79ZoX7szcc8+cM9557jnP8/moIqiSQMIgIsaTUh2iJCBFVYSEStwsoRiSlaL+fAmdLxmsRdJUpLCAGBHpGKsiKAoJU9LgHUFFMSmAhG67GQwglgSICSY0kkLMp6O4vJ3o89m0a81gk0n06TF0SChHBIh69Uh+DZqwQLg4hthkIZEqo+vUkjCo0K1HV+Anq8BLS3sK5m165PIYO+uySM324vUbkbLjaKQE4YAeFjnQHd+GwRIjEkg6FtiL3Hj9SbslyZmMVN27nKh6BWSB1rAWkyWKRp/McYvEtAQ9RgQpKSdS25SBI89LMKRHlkVkq4LZEuXe8tLvjHVfXx8vvfQSs2fP/llKYwwdOpSmpia++eYbRowY8W/btWlpafh8vl/MipQoimRkZOD1en/xTgf/SkZGxh7rkel0uj0qUpg8eTKyLFNVVcUdd9yxV9v95513Hs8++ywnnHACCxYsOGCpAtdddx1nn30206dP3+dr7fOuFcQVCaMmzuVd4wB4LuUbunYOYUhWKx1RO0c5tiEKCp0RK+flrmJebyW1bhe1zkyW95bQbE5BKyTI1HuZ764kIOvpiVkIyTrOsNYxQN9KmpTghNRNTDd3MWbd+Wzty+TefnNojqfyx9pJVJk9vNY2mnJbJ1FFww+rcP7vonLob2v+GA6vsO0FO3bs4A9/+AP3338/48ePRxAETCYTxx9/PC+//DLr1q1j5syZB0RQVYyrKJKANqCg9yqI8X8EcMm8NoCYRSBmFbG2yOi9alJjLZ7Ma5PCkLlid3AnJ43XFQk0PgldlwZBEbCnJ++aFV2yKCEW0KHa4sRDWkwpYRo7U2k9RkGVVKRuLVhkIiVRYj1GxLCEsV1AipC0fcqIJAPBkiCKXU76l26x0VqdgSMlSLAsjtEWITu/l0BYT8KtBxWy7D4KsnopPW0nVc524nEJfWaIhCxSaHeT4fSjtJqSlRINZvTdIugVzNkByvM6UBQBOajDaQ4hCio6c4w0lx+7KczE8lo8jXbiQS39MrsRVJAT/z53L7/8MmeffTaTJk36yed1XxFFkTFjxqAoCq+88gonnXQS5513HnfccQdDhw5FluVfTP4awMKFC1m/fv3B7sYBx2637/etwHA4zAMPPMDVV1+91wGXKIpcc8019PX1ccYZZxyw79jEiRMxmUzU1NTs0/EPGjcRkbUkFJE8s4fnXSu4I16LURsnx+ElRRsikNBx7+YT0YsyRinOGn8hOlHm3KLVvFo/mgyjH70oIwoqcUVDlsGLiMoYex2p+iCfBXNRENkas/NlXxV6QcstZfNwB0x87R9An2xhbFY905ybGeRoxRM3HvI6YYf5aTm8wrYX7NixA1VVmT17Np2dnTQ1NZGWloaqqhQUFDBkyJADZv8Ts4poQwoJfdLhQIqpJLQgxQVEWUE2gCokPUXjZpGEVsDYqyDrkzZV3lIB2STirFHoHiokrZ8kFU1AxLVZoXWKirfbgjnPT7TOBrsL8STd/682EwQQNArEJKyNAm6HhBSUkLJDJNpMyGaIZslgSEBEg8EVRlEFtJYYQruZSHYcjSVOXJZAUom0Wmi3GkhJ8+NPFch2emnoSiXd6ccdMdLiszOyoJF1bbloNAo6UcYdNFIwqJUUQ5g1/iJUUSLF5ceij2LRxBBFFU2PBjlbQhQV0uwBujxWzKYoS5dWYi314m+x0uJxYC/yoJMS8E8WoR0dHVRXV++1ltXB4M0332TmzJmkp6czduxYZFlm/fr1DB8+nGg0+sMNHEKccsopQLLA51BynPixSJK0xzlpe4osy0iS9MNv/B60Wi233HILL730EgUFBeTm5qIoCj6fjwkTJvDmm2/ux94mEUWRSZMmsWXLlj3ewv0HT9jWUWzx4YvpKbL20R2x0NidwpSyHRjFOBvd2dg0YTL1XiwFMb7pKuT6kq+oDmez3ZOBVRvhqJwdaIUELREHLUEHI1Ma+aanAJMmzgBDK8s8pcxqHcP1+Qv4oHcYOzxpXKsZyVkpqzAboxxn20RdLJ0+jZkSbTeNWhdr+/LINB46/sQHi0NcmeNHcThg2wtOPPFEvvrqK2bPnk1VVRUjRoxgyZIlrFy5kp07d9KvXz/8fj9vvfUWW7du5Te/+Q0ul+sn6YtsFIibRCwdMgjJgEyUAVVFkJOiuQmDiN4tEzcnL8ZRu0jcnPQUdVardA+FSKpIwvz/iyYyv4mTMIhkrBDpHAPRiA5VShrCx0vCBFuspBS5iS5OxTDGS1jVoQjgGSljsUWI9tmJh7UY3AIxu4oQTZq4qyqE3QaEhIA924cvX4KYhKRR0M6zY5vmJtroJGpXkQSFeJ+BiE2LTifTUZPGyOG1RPQadrjTiLabMeX4WbGjGBIifZoEfSETgi6BWBBFTog07UonkqclXG/DWuGmL2Ai0+FDRCURF4nFJQaOqqPFZ8dY3Ic3ZCDqNWJzfFdcdtmyZRxzzDGYTKafZB73Bzt37uTvf/87TzzxBDfeeOO38jH/4Mwzz0Sj0WCxWA5SD38atm/fzueff85NN910sLtywNBoNPtdmqW0tJStW7cyduzYfW7DbDZz3XXX0d3dTU9PD4IgYDAYePjhh3nkkUe444479ntgffTRR/Pwww/v9XF9fhNGbYxAVE+j4KTVY8doiLO+OweHIXlTuaqvAIBOvxWzPsYzdVMwaOIU2Xqp9aUxwN7Bp82VXFW2BIsUozdupsLRSXvYzopgP0baG3jdPYL53koiCS2j0xu4zrWI7fFUelsc3G84kSvzlnCecyWPtR1LuaUDRRXQiIedDg7z/fzv3JruJ0aMGMGDDz7I2WefTUlJCRdffDHPP/88wWCQjRs3csstt1BTU0NbW9tP+iP/jyKChFZAkQQQQBdQcGzx7LarEpH1ELNLSDEFQVGT+W0KmDsSBDOF3RprIIaTQZU5K0D7JVFaTpXpGqGCRUbSJEjYZDwDEmT80YDOI9LX6EAe6SfYZUajS6Br1WFfoycW02Cr6gW/hmiqguKQ0blFRIOMxq0BAaw7NHj7zAhSMpjLdngJTAji9xqJFkZJc/norU1FtMZINQYRhOSq3y5PCp1BK4V2N6YcP8E+E1ZHGPMOLZKo4vcZ0VuSP2QGrYw9y0dXtw0yIsRliVhIS8fKbJo6UzBsMxKPa1i/tRCNpNDrsRALaZG0Cv6G7+ZE5eXlsXjxYtra2n6yufyxXHXVVXz44Ydcc801/xasQVLS45cWrAGUlZVx0UUXfavJ9ktzcvhP5OTksG3bNp555pn91uYll1zC/Pnz90tbaWlpVFRUUF5eTmFhIffeey/PPfccDoeD6dOnM2/evH0Wvp0zZw6nnnoq5eXlnH766UQiEXbs2PGdKv09oTKrA1UVEATwhI38tupTTi/ewJC0VuqaMuhn7yYQ09PP1k0orKPM0c3tpV8wI3ctNk0Ef9RAMJHcSemn72B6yhq0gsJVrkUMdzSyzpuPXoxj1sVI1QY5KqWavpiZQo0Vhxhi4qDt9IbMdMh2KrUmzklfyYubxpJr9mLTRPZpbP5nOGz+fpj9QUpKCrIsc/fddxMKhbjrrrt+0oDN3CFjcCvEbCJSTEWUIZwiEs6xIhuTxQeQFOqPOCVEGWSDQNwC3YMlEEh++UW+rexUVYh1GTFaotiKPKhRCZMxhjklhOiI0TJRT8KgYuiU0Gtl0CqImy0k9CreShlxuxnf1hTEBGgCIqJeJpqWQPHokAqCiEGJ0PCktpri1aFzSzRWZ2E0xBG1CoKg0t1jQ02NIWoUdi4qop+rB6FfAG/ISI7VS1vARklqL0ZHhIQiUHpCHX0tdozmGAKQ4fTR1ZiC0xjG5ghhXmNElpP+oHJRGMWrg+FeqDOTmuch3RRA7TCg+pOKwWJ6hNs7mr4d55EjRzJs2DCuuOKKn2wufwyKorBt2zYuuOAChg4derC7c0ARRZGUlBQEQeDCCy9Er9ezbNmyA+o3eaDJysrivPPO44YbbthvuWxXXXUVXV1de1x9ujdkZ2fz5JNP8rvf/Q6DwcAFF1xAcXExd911F62trXvczuOPP86FF16I0+nknHPOwWAw8NBDDzF06NC92s69LVDPhvpcyuzdTMiqY0haK6+3j+b1zycyf20VY/rXMclRw7TsakxSHK02QUjW0RhLozqYzRZPFkdm7qIzbOX04g38vXsMnoSJAmMPayMFaIUEM7MX8HlXFcNSm7k+ZT1pGj/jHTtYGZVplZ1kGbxMzN7JR22DCCgROuIOpvTbQa7BTao2uC/DfJj/EQ4HbPuJDz/8kKlTp/LAAw8wY8YMBg8e/JOeTxVBUFSkqErYJRI3CWgiKgmjuPs1kkEZyYpSKa4iRcHYCYIM8u5YUtGq6HtFSIsQabJiyg4Q9uvJtXmRAhKRqJaQxwg9emJ5MdTsCCnVStJRwK8hXhFCigiokorcL4yiA8UuE7cnEERQdQo6t0TMr0cxJe+ERY0CxgRyYRhVp1Du6kIQVJSYhODRoga0yGEt6oAAkYSGVFuQgtQ+RFRCMS11vamcXLKZPKeHNr+NlFwvqZYgE/LraGlLJbOwl54vcvA32EmM9+KcY0YyyGSlecEiU5DiRilMBo6+mD7pYxoRUduMJLw6xPTv3uWec845LFmyZJ8TnH9Kfve732E2m8nJyTnYXTloCIJAUVERgiCwdevWX1y+3r/y6aef8uyzz+6Vld1/Q6/X88477/Diiy+yYcOG/dLmPyMIAi6Xi9NOO42nn36aiy66iGXLllFWVsb555//g9ZZN910E4899hi//e1vOf744xkwYACnnnoqjz76KLfccste98dii7CkuZjmkJPemBl31Ii+RyAlz8OG9hwe23YMLREnc5v6k+v0YNLEqA2nY5Ri2HRRjGIMgyTzZVsFbSEbKwOlrPYUcZqlkSJ9F1evOw+XIYBdE2ZjzMhbXSMZamhkeagfJdpu5raUM82xmZsL51EjizikIDu8aQw2NxJX9z2X8H8G9Uc+DhKCIBgEQThDEISnBUF4VxCEWYIg3C4IQuWetnE4YPuRyLLMcccdh8Vi4f333+fBBx88INWEWn8cMQEIyQDM1hDD0hIlnCIhm0QiDhGdLxnQyUYBTVhFG1KIOpOVoq5NiaQxvE4l7lBQAlpIi6KutSN4teSYvCQsCaIhLZIhwRFD6xlS2oQgqgiXd5G5MFlJiiogVPjReDWIkoLiiH9r56TIyW2HaEYcQZtACmjQ6GRUVUBniSWdDTKCrG/JIe7TI2hUBFcUMSqQmelBVQRaPA66PRZ2daTRHrJSmtKLRlJY0FZGT8hMVNZQ4uhFRGVudQU6c4yIrCEx1oertJeQz0D3cUnT+HhCwu4M0hM0I0oKgbCehm3ZKBoVxRmHjAjIAim2797lGgwGKisr+fLLL3/yed0benp6eOSRR7j66qv/pxLvvw9RFLnyyit/MfIl30dnZycXXHDBfm1z4sSJvPXWWzz77LP09PTs17b/GVEUqaqq4tprr+WZZ56hqamJ8vLy79U33LRpEy+99BIPPPDA/tG1lBSm5O3YHYhFyTW6sesiDDhlB4oqkO3wkuvwkGtwc0npSrJNPmyaCIPMzSzpLEFWRJZ2F+OJGbiu+GtsuiiBhJ5Gn5MTrr+BJ3YeQ36Km6aAk9c/m8Qls39FgamP3zYmi2QkVO7s/zk1kWx2xdL5OlCBXzESjOko1PYy2brtx3/Gw/zsEAThXmAZMAb4BvgL8A4gA48KgjBPEISBP9TO4av8j0BRFM4//3yam5t58cUXue+++8jMzDwg5445k2WbYiyZlxaza1AlAV1AQYokg7O4RSBuTrofJLQCqvT/BXTFhIrOm1yJU5xxBJOM1RpGHhhE5xaZX9sfAG2jAYMxRnVnBu6IkTyXm3RTANkgoKTEEJoNRAN6NIUB5JiE3hpFjAto/BI5mW4Ii8mVNiX5/kSdBVSQoxIENQQ7LDitISRzMtBzOoIoBgW7IYzcYSTb7qUyu4PSrC5OyN5ChsGHWR+jr89Cb72TuCyRafDRFzJBQkBJCBg0MrlODxpJSQaU7Qb6Z3YxLaeacERHujlAaUY30Q4TOeWdoApIxuQKnKpX6KlL/bfxLisrY9GiRQdkbveUP/zhDwwcOJD8/PyD3ZWfBbIs8+ijj/6i5Ev+E1qtlmBw/2+dHXvssZx//vk/KLS7v7DZbFx33XVcfPHF/OpXv+KUU075t2DxvffeY/DgwfttNTEny83C1lIMkszajjxStUFOzthIpsFHP2cPVY52BtiTnqFrfAUcYW2hytzCBx1DGO5qptjSw3GZ27DpongSJhRVIJzQkmP1Er+8D0UVyDT6mZG9lmOmriW/qo2V3YWckbkWCZWOhJW/tYxnpaeYNI2f6baNFGu7yLb4uGbruTzScPx++Zy/ZA7RHLbVqqoOU1X1FlVV/66q6nxVVT9RVfVJVVVPAs7jWy2G7+dwwLaPLFy4kBEjRrBq1SpuvfXWA35XL+tFUFWstV6sLXEERSVm0yDKkNALKLuLEWSjgKKBYJaIP3d3kYEM3iINgfzdeW5RCbFTT2JxCmqDiaqptdhsYcpK24ilywS9RvRaGVkV6Q2aqetLJXFKH/i0aEoCSLoEhoVW9LUGon49GeXduAZ34Z6XhS4jDIKK4NMiahQS2VHw6Eh1BhCscaSASHeXHSUq4cjz4gsYceT4qOt0kdavl1Bcx47uNBp6U1jlLqLO7yIU0zK2dBf9BrQiCCrbfen4G+ykZ3pREiIFNjdtXjuhmJbcnF5MpV627MjjndohSJJCs9fB9qZMjFlJP1J9n0jCq6N7dSaiIUHGSoFbvQ3fGe8jjjiCpUuX7nPC9P4mkUjwyiuvMG3atIPdlZ8NGo2GGTNm4HA4DnZXflJ0Ot1PErABPPbYY9TV1bFp06afpP3/xNChQ3n88ccJh8OUl5d/a6mmKAqvvvoqkydP3m/n6vWbicS01HSmU+HqoiNm4732odg0yRSJ9X25+GUDnrgJnSizM5ROSyyF0zLXs6CpH2t78/iys4KOoJV3W4cyxN5MSNYzIWUHqaYgg12tvFqwGG/ChDtm4visrbjn5DDU0MTc7gqeb5uMSRNntGMXEgohRcKvGjg/ayUjMpoYltK83z7rYfYdQRAcgiC8JwjCdkEQqgVBGCMIQsrulbDa3f/usZGxqqqf/odzGARBsO1+vUtV1TU/1M7hgG0fWLBgASeffDJDhw7loYcewmw2H9Dz//HlehQtKBqBSLYVQ3sATTBBOFUCVSXqEIibkg4IUkxFlUA2Jp0O4uZkhWkoE8S4gBgTEOICUkGQQGUMCpKVdqKgoqgCki2G2KtlYEYb4biWdKufPLsHhyHMmGE1GPRxHPYgwVyIlYWRDDK9PjMd7Q5sR3US6zaiMcXBGUNviCOIKvYiD701LgqzezCU+iAqIhkSOAxhBEHF7zciRzV0ddu4MH8lqiog11toebGEclsnA1ydVFmTCcuhDgthWUtxVSvhmBadXiYkawmHdITCekIxHcGAHskUx26KEPYacJjCWO3JC7QkqkRzkyuM9A8gdOnpHKUi6BLc1tf47Zjn5+cjCALLli07oHP9fbzzzjvo9Xr69+9/sLvys2DHjh0sXbqU4uLig92VnxydTveDeV/7isVi4ZFHHuHll1/e73pv/w2TycQVV1zBtddey5133onT6USn02EwGBgwYMB+Ocdd1FDi6iHX6SEv1U29N4XGQAouQ5C35h5JSNYyPXsjZaZOBlub2O7O4ATnRhpCqTRFUxmS1cq8yne5t2gOlxQsZ5SrkbpQGr/J/YSP2gYRSyRTQRpkP192VvB/OZ8yyNjI0Zeu5JtwETfnzSXL6GWIvRm7FOKJnUfzZaCKd3tGYJXC9EYt1AbS98tn/SWjqj/usYc8DXyhqmo5MAioBn4NLFBVtR+wYPff+4QgCJcDXwKfCoKwx9o0hwO2feDuu+9mxowZHHPMMQfMiuVfEXYv9IRdGrwD7AgqWJvjKNpkoKZoQRtSiZsEEgawNSlIEVAliKYAKhR8HkLRqxgzgwjVFvTWKHJQR1vAht0QxiDJOGzJAG5Nax4en4mduzLZvqaQVGOILV1ZhMI6HIYwaYM7UeISiZhELKAjN7cXd8CEIT1EnsuN1RZGVQVESUFVQUmN0drnoNDZh2iNozfEiMhaol49FksYrUFG0iV4unoy8ZgGcsP0Hh0hqiTH+9O2KnbsykK0xejosxGK64hscxDpMbJ1bREuZwCnNUSGxc+4kl2MKGqi12uGqERrtxNvl4VQnxGnMURqphdBVIl1GlGMCpqgCCHNdxJUBUFg7NixPPLIIwd4pv8zzzzzDNOmTUMQDu0y9f2FRqPZb9tmP3cGDRrE73//+5+s/YsvvpicnJw9Mpnf31RWVvLEE0/wyCOP8Oqrr/Lggw/ut+94YVovFm2MfIubiKxNXuM0Mlu6sjh32hIs2hhrfAW81zSEBb0VlDm6+aB3GKGEjgnW7RilOFM2n8WCQCUxVcNk6zbyjX282pe0tTonZzVHO7ewMFTCh/3f47fNJxNTNRjFGH2yhSebj+EPWcvJ0HrxJkxkWXwkENAKCtevPpt0vf+w08HPgN2rXhOAFwFUVY2pquoBTgFe3f22V4FT96LNk/7lqamqqk5UVXU8cMKetnM4YNsLFEXhkUceoa6ujilTphzw8//t0S385dkdaANxhARooipSTCVmEfHnatGEZPSeBEICHLVxYtakPpsYB3+uSDgdDD2QMKokzAq1F2sREgKRFgvx0jAuaxAhKKGVEtRXZwNg1UWRckPYTRFyXB6q+rWACutXlXJ2yVqUOgvRhIZQTIvBmvTtzMp2097jIOLTE/YYqG9Nw+c2JQMvwNtjQRBVMp0+dvWmIkoKkbCOXp+ZKQOrCYb0pNqCJKISBp2MwRijKqcdjS7BF2sHsqUrC4Czhq0GAQblttEXMFE6tgFHjg/FLpNQBXo9FrqCFvqiJmrdLqSdJnSpYRJxkdz8XgRZpM1nIxTRIUhq0oNUgHhmDK1H4vepBd8Z/+nTp7N27VpmzZp1YCf+X3jsscdoaGhg3LhxB7UfPyeKi4vp16/fwe7GAWHGjBl8+eWXLFmy5CdpXxRF/vznP/PRRx/9pAUI34dWqyU1NRWd7gdTev6NXydqiQ95nO6Bf2JB8Rz8g55mbf+3eTZlFbIiUmruIiTr8YSMnJO9GlkRGZXdSFM4hZaAHbMUQxIVxjjrkFURvSgzyNZCbTQTqybCiTlbWO/JoymaypGGICt7C9nozmasq57GqIvqcA4OKciKqIVKWxvLAmWEFR16Mc4VOYs5tno6AC6NjzRDgNdrR7KmK49RBY2c6FzPFdk/rzzZnxsqBySHrRjoBl4WBGG9IAh/EwTBDGSoqtoOsPvfvVkOHSQIwmxBEAbt/nuTIAhvCILwOrB1Txs5HLDtITt27GDMmDG88MIL3H777Wi12oPSD0UvIZu1aKIKMauIoS+OtSmGpU3GX2hE54miDar4C7REnaANJJeJEobkqpy8e/dWCooIWgUhM4xiSuB0BOn2WRg6tI72PjsjhuxEVkVCcR2ipNDVkEJTWyqioDJwdB2KI87S3hLkrCiBqJ4Brk4c5jAuexBP0IjDHkTUJZC8GnIy3UhdOrQ6GY1GITe3F5s9RCCqJx6XkKMaEmEN8YiG5c1FCEJSjbx/QQdyQiTd6mfD9gKUhEBmQR+nF28gz+Lhva1DAFhTXUhZWjeZRh+ePjOSKY5NH8FhDxKLa8gxeSmwu1HLguSkeJjYv5ZurwUhJuBttZNQRLTVJoS4iBQQ0XTpeLjk3yvSDAYDl19+OXfdddcBm+9/5YMPPuDhhx/mjjvuOGA2aIcCsixz3XXX/eIlPQCsVitnnXUWV1999V6Lxu4pQ4cO5bLLLuPpp58+oFuj+4PVgSJOs9RwnHMzkqAQVTToJZkOr42dwXSKzD1UpXcQUbUYJJmtfZmUmTvJt7pREHAYwizoLud01xpsmgibfTmkaIJIQvJaelbmasIJLSdsO5Ncs4ewrGWLLxuDGEdBwK8Y+cQ9BJcmuWJWbOhiVziNJf7+hF/MZlsom/HGRnZ6XQxI60QnJbgsYzGehJkc6afZ6j7Md3AJgrDmnx5X/svrGmAo8GdVVYcAQX7E9ieAqqoPAlcBMwVBeAF4Cfgt8JiqqufuaTuHA7Y9YNasWYwYMYLi4mIefvhhCgsLD3gf/vpENYpei7YvjL47hCompTriFg2RVA2qkKz+jKQbsDbFSF/hxtaoEkoXQEnqrkXSFUL5SeP1hFlB8GhRugyYUsIMS2shIYts68wgw+kjIOvwRoxMy6km1+mhX3krjpQglfZ2JqXWMKKsgQJzH6P6NRCLS+xwpyEIKp07XIT9ejLNfrLTPSgmhdZ2J2PHJ8vVDfo47qAJQYBwVIteL1OS24XREaEwuwc5LmEyRrGbw9S2pTMovY1wXIe+Q4OqCvT5Tbyzcwg6MUFFbgenDdiIxhLHGzOwqq0AkzWpoebQR5AEFYshyrwVA9nSloXZFMUXNbChK7l6aGoRkfwiDnMY2+huEFUSaXEeKfp++QBRFA9aUvuaNWu49NJLueGGG/6nddf+ExqNhmeeeeZ/JoidMmUKoigyatQodu3a9ZOc4/HHHyclJYXXXnvtP4oRq6r6sxIpLht1M2qnAbsmzL0dR7Ermk6axsd2XwbTMrZxSslmjndtwq4J0Rmy0B5zIAoKBk2crpiVdW25ZOm9THbtwCDJvN8znNpAOjMyVmEWowRkHS9vHY1BiDHFXs3T/d6mzNxJc6OLgfZWXqsZycyUNazxF7HDn8aC3gqOMDXTHnMwv6k/N7gWcck9czjFuY6QKjIktYUySye3l36BJ2GiOpLNvOD+ydf7xaKSVIP/MQ/oUVV1+D89XviXs7QALaqqfrP77/dIBnCdgiBkAez+t2svex8EbgSeA14AzgF27E0DhwO2H6Cnp4cbb7yRW265hdNOO+2g5awpeg2yRUs03UzcaUBIqGh9MjpPHEOvDLu/i8F0Db4iHbFUE1JUxdqiIMWTemu2WhGNV0IKixjy/SjmBLqcIFpNgk292RzfbxtVGR30+CzsWFPAmIx6AomkQXLzonwCQT2euBGzGKXS1kaqNsj5GcuJxzUYNDKBiB5BhbQ0HwoC7vlZqFoFUauwsqkQRRUIhvRIooLPa6TU1UOgx4Q7bKLI1YteI4MqoNckCMV06A1xArKeUEyLaUgf0/pV0z+jC502QaPfSYM7ha9ak9tgjY1pRMI6+rl6KM7owRfTE0tIuIxBxo7czuSiWiRRwaiNoygiFlMUw6QeUjeDN5Ss8JVscTSG+PfOgaqqLFmyhKOOOuqAzPk/EwqFOOmkkzjvvPP+o/3UYSAWi/HZZ58d7G4cEERR5K677qKwsJBhw4Z9Z5u+q6uLxx9/nPfee+9HnUOSJD788EPq6up48MEH+eSTT/j888958cUXuffee7nsssu49dZbf7KAcW85QmfEXORlSXcJn288gvnd5czzVpGiD7EzlM4wc3Lb8oPGwRRY3bxbOwSNoHBC1haWdxRxUslW3pg/niW9pQyyt2DXhulv7aRPtlATyaI56GRcYT1P7DqGhCpwf8tJjDXt5Mzhayk1dHJiyVbOrz2TVF2Aq3IXkaYPsDWcS5bOw8CMNroVPdlaN56EiU/8A3k44xvWefJYGyzi1fZxhBI6VnuKDvYw/s+jqmoH0CwIwj8quo4CtgFzgIt2P3cRMHtP2xQE4UHgU5LFCpNVVT0Z2Eiy6GCPRRUPB2w/wPXXX8/QoUOpqKg4qP2I2bXELRKKTiDs0iJFFCKpWmSThL47RNQhoQ0qCKqKohGIpmgJpYvETSIp26M4qgXEOBh6BOTMKOFmK/a0AKoiJP00fWYWtxUzzbWFmyoXIDtkPtw0hGUdxfjjBvImNlH4nMjKjkLe7xjKEFMjPtnI7L6hDM9rwqSNEZclbCUefGEDEVnDgJN3UFbcjtUaRqNJUJLWQ7zXgJwQUWSJnT0uxJBEMKJDRGVXlwurNUyBzU2Zq5tIUMe4lJ343KakbZaiodnnwNNnpt1r4+r+i/F4TBgMcSSvhpPLNzHS2cAgZxunZ69nbFY9o1PqqfO4mLu5ErfHjFZMcGvFPDweE4Gwnq6RKhpJoavdgbbaiKb6P1f8KorCK6+8QkNDA7fddtsBnn149dVXcblcB0SU+VBFr9cTiSRXWH8u8is/JZIkcdZZZ3HjjTdy2223kZ6ezuDBgykqKuLdd99l5syZTJs2jc7Ozn0+R0ZGBps3b2bGjBnIsozX62XYsGHcf//9bN26ldtvv52HH36Y9evX78dPtm9sjoXZOPJNGrtTuGzkUn5f9D6PZqziKGc1I631OMQQRfouBqW1sa03g/7pyQWSRT1ljM2spznk5KRJqxnsaCGQMHCKcx12TQhvwsQKdzEtPjtmTZShqS1MNHZzWdZiOmQ7Q80NvNAwnjx9LyZNnPWePD5zD+KklPVIKGwJ5nBs6hYebDqRD3qH8efmSVQZm3ErUW7L/wK7JsxAeytlxg4uzzycw/Yz4TrgDUEQNgGDgYeBR4GjBUGoBY7e/feecqKqqhOAscCFAKqqzgGmAXtcLSX8tyXt4cOHq2vW/KA0yC+WpUuXcsIJJ/Dkk09is9kOWj+efrMRQUkGYjpfImk/JUDULqELJH+YEjoBQ5+Mp0SHoELclCw2iFtA0YGxK1k5GshTQQRzPw/eLgulxR20uB2kWEKcnLsJr2xignU7/7f9FCIxLccVVjPU3EB1OJsqYwt3fXQOibQ4Zw9ZTbUvk0JzLz0xCzv60si1eemNmMgxe1mzsIKcEa14Ikam5u7gk7pK9Lo44YiOREJE7TCiOOLoLDH0WplyVxebOrKQRAU5IRFvM2HM83Nkbj3BhI4Vu4owbDYiDwtwaukmPvx8LEcfs5Yvtg/gd6Pe59avz+a4IZtoDjqZ6KpFFBRWe4rINHjJ0XtY6y2gNWhDFFTaeu1otQlMhliy4EBQkUSVYION32X9uwhtLBbj2WefJRKJMHfuXNLTD3zp/ejRoxkxYgQTJkw44Oc+1PD5fDzyyCM8+OCDe+UzeSijqiptbW20t7czYMAATCYTkUiE119/nZ07d7J48eKfbBv9yy+/5IwzzuCxxx7D5XL9JOf4ISKDn2CkoYkEApuj2fx200lEfHrUhIDWGkMUVaYW1zDU0oheiBNS9HzRU0V/ayf1QRenpa1lfaiAld2FDEltYYSlns64ndpwOu6YCZ2Y4PL0RWyO5mEVw5jFKOtDhaxz53FCxma64jYGGptoizvRCgkmmWp5unsK56cu583eMazsLOCS4hW0xxwoqsDK3kJmZK9lrKmOD71DaYqksKK1kDRLgJl9ow7KGB5sZsyYsVZV1eH/7T364hw156GZP+o89efe/YPn2d/sLi5QASPQrKrqTfvSzuEVtu9BURSuvvpqZsyYcVCDNQBtIIGggrErSsIgomgETK0hEjqBiFMk4kz6h3qLdchGSOjB0KdicKukVidQJQhlgXdwHEWvIjtk9B86EHQKzSvyOKpwB5lmP2s8hYQTWuZ5q7i77DMC3WaqvRnsiGQSSOhZGyxEyYoi+DTU+DNo89uY19gfoxQnGNXRFbJg1MQJxPVccOLXtPQ6cBjCvLdxCP3SuilN6SUnxcPQvBYUZxy9Ncr1lV+T73AjCiqioOI0h4m3mRDTI5xcvIXFnwzGqomQCGnQjesjL8XN4o5Szj5hMTFFQ6ozwKZQPmOralncXMLW7XnEVYnn5h+DXRtGFFRerR2FRkzgDpoosfUwvqiOsNeAx2ciFtWS2GTH32nBXOj7t7FXVZXnn38enU7H8uXLD0qwNnv2bLZs2cLIkSMP+LkPRWw2G7fccguSJP1stut+agRBICcnh+HDh2MyJY2CDQYDl112GYMGDWLcuHE0Njb+QCv7xrRp0ygqKvpRK3k/lvOsffTTWtgczcYhBclLcXPnmM+4cex89HqZbKeXoKzn4c+mc9/6E5nbW8n6zUXMeWscIVlLY8xFfdDFjNy1lBi6+MpTgT9h4NHMxfS3dJJv7OPBxhN5t3Uo892VRFQd69x5jEhpJKpoeWX9GNriTjYF8kggcvLqX5Gj9+BRTJyfupyylG4kFKqMLehFmfrNOXzQMYTrdpyNXRNiuyeds0rWMcDZcdDG8DA/Haqqng88BvxmX4M1OBywfS9PPfUUoVCIqVOnHuyuIJtEtN44MUdy9Uw2ishmLa4NPqxNSYmPiFNE51fRe1SkCEScAv4CAW+hhCpC3KZCVETYbYDrPzGAICZXV5e2FpNh8NEbNrGiswiTGKNE28NvJ8wmx+SlJeIkXedDFFRURUB1xKmytRFLSFxbsQirJoIggE0fwRsx0hcxsdpdwM2DFjA6rYFjK7eypTGbInMv9Y0ZrN5ajKhJYNDFeXzBCVTa23HqghxbVI1OksGZvCN+a+loYg6VRU2l6GwxfD4jmSY/Vn2EJV0ltIdspJsDzG/vTyCux6iPc9OEL/mktYqRw2txx0wMNjdRld7Bho4c8p1uLFKMr7dUoDHFKc7oIREXieTEQZ/A12X5t7F/77336Onp4bPPPvv2h/BA8tlnn3HhhRcyc+bMX7xH5v7E5XIRDod58803/ycqR78PQRA4++yzGTVqFEceeeRPFsCmpqb+ZGK+e8LHIRPXtI7ina4RXLvmXMptXSz3luLS+Mh1eLi9+AtWt+Wx6Mzf47IHSdUFmTxsK5GqpN5kltbNNVlfcbx5O7XhDIxinApjK7N8pbg0fo6xbibT6GeUq5GuiIU32kZxdtYq3tk5hLndFZwxcD2fd1URTOj4tPMILitfwZ2pO4goWm6sOYu2oI21/kImGlt548PJXDF1AZ/3/4zjs7aysLc/RdY+MrReCg29B20MDxkOQfN3QRCOVFV1s6qq27/ndZsgCD+YnHxwMuh/5vT09PDggw9y6623/ixMtZM5aTo0oQSKXkQTUghl6xESeqy7AiR2b4MmdBB1JnVmVCG5HWrogViajBiWkl6bOhXJr0F1gtRqIH1ke9JJQJU4J3c1L+w6kg93DaQtx06RsZevdvUj0WnkulOeYlM0h/MGKSxo709TOIXj8qv5sruSTeuLGD5sJ91hM+G4hpMLttAQSuWJj09i8qRNLFhxBIIryofVgxD1MoIRhuY30+x34FNhQVsZWlFBIyUlCgzmGLGoFiklhpIQKEvr5qzM1TxXP4lGvxNRUCmzd+OOmbDtXkU7I3MtCz39+ayzinEZ9cxvKcPrNrGxLZuitF6CXWa6dHEsmhj29VoChRpqgzr09giKQUTuMILhu3lPS5YsYdGiRaxatQqL5d+DuZ+azs5OLrnkEn71q18xfPgBXcH/RWA0Grn77rsPdjcOOoIgcMYZZyBJEuPHj2fRokWUlpbu13NkZGTQ19e3X9vcW+7OnM+GaBptqU5SNAG+CZTyettozs1ehT9h5OTiLeyKW8mxevlyUyVFBV38btT73PPK+YSO1vJx2Re84ivhRMcGmuOprA4UUxdMY3LKdiKqlsXfDOC2Yz4hatPQFnawLljIkKxWNILCEaZm9EKcHYEMxqbu4oUt45g4ajvdso3jspMV8jXBDMZ8cAtqYZShxgaWRKAnbmHrwlKsQ3twaMOEFS2Hyw5+kZwuCMJjwBfAWpI6bwagFJgMFAC3/FAjBz8a+ZkRiUSYPn06w4YN+9kIcYoJ0IQVxLiKJpBAiiiYOmKgQjQ1ueoiJECRBAy9Kqau5G2Ezg2KBoSoSMKcAKuMEBdwlfeg0yTIGNJBz7IsWutdbPek8+jqY3EYwpxduo7V7w7EJEUZlteCFBY57Z2bGGlo4ljbJqz6CNV9GTSGUrg19wuun/olDV4nWilBeWo3ry0fR1vIxslTV5Gh8yG4opRkdSOICkpMQhAV7LowGilB4YA2fBtcRGQNgaielrZUqjI6SHP6cdiDzBy6kIH2Vt7uGIFBE8cbMhKI6vl68cCkoKU3jRHORl5pHkNbyE5nwMp7G4dyd/ln2FcaOCK7naPTq7ln4mwmZye15SwndVA2vJFjB26mLK0bjSaBao/ze0fht2Pe19fHyy+/zOzZsykoKPhP0/KToigKM2bMYPjw4YeDtR9BJBLhllt+8Dr4P8H06dMZNWoUV1999X5ve/LkyQfUf/SfKRl1CwYhxmOdU6iO5PBO2zDmuaso1HdzfvZK5vZVMljfmqxSV3W8WzwfR7qfozO3ky75cW1JcHbWKgAq9a1sjORTrm/jy+ZyGrxOvAkTu2LpnDp+Na1RJyc51lNpbUMvylyYvoxKSxtLvGWYpBijnLu4NWUb9w/9mHsbT2aAvpXumJW1nnwmOHaw7LQnEASV2mgmKVIIT9xEyvAujs/dxhkpq5niqD4oY3jo8ONEcw+W+fvubdATgHbgTOAB4GagH/AXVVUnqKq6+ofaORyw/RPBYJDJkycTj8e59NJLD3Z3vkVQVFQBZIuU/G+tgCoIJAwCOm8MS+tuYUsBAnkC4dSkw4EUA3+himJOoO/SoDHEMeb58QSNBIN6JmXUcvRJaxCiIjlmH0eV1zAlfQcpmgD2ozt4edaxfFNTxPjJmzh32hL+1DORpaEyRqY00tVtY5KzhgsWX8GHbYMw62I0rMxHIybILemiJ2gmKOvpjllJT/HTvCifRFzi7KGrkYM61nTmoRUTlNh6GXvUFibn1OLzGdGZYzh1IWIJiRHpTXzUOgiTFKXQ3Eubx47FEGVqTg3lwxt4d9cQjJo4X3f1QxRUhjubyLL6OL5qM0/WHU3/82rY1pnBel8+C9wVzNlZRU13GrkWLz1BM/Pr+lPdnkGm3Udu9ndXB5YuXcrkyZMZPXr0QZhx+OMf/0hTUxPnnXfeQTn/LwW9Xs9tt932s9ILO5iccsoprFy5ktra2v3a7llnnUVNTQ2BQGC/trsnDNYZGKMPkG1wk0CgfmMuZk2UFE2QWa1jOCZlK+duuQStkMCfMDJu02kMTm8joYrcUXM6FXdvJqpqqY0HeNczkr/Xj+D8D67l/gEfk2/zMLt5ICFFj0WKohUTPFR/Au/uGkJz2MlLHRP4pL2K2zLm4tQE+cZdzDuBdM62uJngqiVdCjHVsZVrcr5ifSCfBtlAQVYvIUVPm2wjnNBye+kXzGmsYl24kJCy9+4Ohzk0UFXVrarqX1VVvVhV1Wmqqp6qquqdqqou3dM2Dgdsu4lEIkyePBlBELjhhhsOmt7a9yGoYGwLEczWEbVJaD1h9N4E3lIzcbNIQgc6f9IvNOICU6eKJgSmdgEhIhLPjyDVmAl1WEixhDAYY2TpPHjiRq4+aj7f7EguxCdUkWytm+m5GzjpnGW4lmj5ev0Axlhq8cRNrPEU8sbGkYwv20kCkd+M/oRwTIteI6MUhdjy9wFUOdu5uOQbREHBGzcys/hrDMP7GFrUTGfUitYSo8DuJpbQ4I0Z6Qhb+bq1H0pcol9aN50RK5cWL+frxn607EzHKkZQVJGHBn7EZYXLWNxRytaaPM4tXU2Hz0bjlmzcYRO9cTPX5H7Ngk+HMcTVgqIKDMjoZG1rHl1hC2m2AGZ9jJ5IUrhXjmrQ62XqGzO4wT3iO+O9ZMkSLrvssoMx1UDS0eD4448/aI4avxQEQSAQCBwO2HZjMpmYOHEijz66N4oEP4zD4WDo0KGsW7duv7a7J4zdeDqLIg6Ot2xmRzCDR058k9GWOgbrW9CICv6EgWyLj5tdq9gZzWDZwA+4OXMuH/5pMj2b0sg1uPlj7STuaj6VT+oq0YgK501dQmvcyRjnLnrcFt5rGYJJipKl9fBh//d4dfDLBOJ6AnEdQ1Ja2B5P5/22IZRZOjnF3MZrfhdDjQ1sj6fTLVvpr3VTYOzlocYTCb6RTYWhldnuoZSYu9kSziMc1ZFAoE8+8KkXhxyHYA7b/uJwwLab119/Ha/Xy/XXX7/XwZqiKKxbt466urr91h9FUYjFYtx2223IehFNMI6ik5BiYO6IEc6xYN7eS0IPMatI6tYoCKANgCYInn4Cnorkt9PQLaFpMWDoAckZxR004rIGebl+DCm6ID1xC1Mrq1n66SCW9RazyFfOKGPys/QMVSkq7eAT92BuyJzHhZnLKczuocTcTXvMwYcdQ5iYXUdPyMylVSs48bIlDLS0UKrvoDdqwRfX80nPYI5wteOJGli8q5QLKlYRkrVMyqhlTX0+zW4HTmOIwpxuZFUkENfx0q6xZDu8SCGRpmgqHREbQUXPukABJ+VuZlhlPaX6Tk4v3sCYUdsJRZJ3pg/VnsDAo3awpisfT8xAkbmXRI2VXR1pZJr95Ns99Ld3ISsi/fI6CfSYIPLd/w0aGxsJhUKceOKJ+20+94aGhgbWr19/WCB3P6AoCrNmzTocsP0T06ZN47333tvvRQIDBw6ko+PAVzmelrcBBZHtsUz0oszJ5h6+cFexOZrNvQVzsEoR7iuYzcaYGacmCECalEAVYccFz3NL6kYuKv4GT9TAPQM/xe03scWXzYLeCjb7czih/1YuzF/JrJpRdMbtPOep4vdtx1Jo7uUIRxueuIkvPVUYJJnOmI2vIynkaXuJqRpWBYp5vXkUnwXL6Y1bmeiq5YSbF1Gi7eVIWy0iKiYpygklWzGJMZojeyzJdZj/QQ4HbLv58MMPGTdu3F7rNjU0NHD77bfz3nvv8eSTT/L73//+R4t2fvXVV7zzzjvodDpuueUWFF2y6CCaqkfRQCRFiyoJBCpScW4Po2ihr0KPkABtSEXv3b0i1yngL0sQzpGJuWS85QmUuIjLGqSly5kUutVE6I5ZSKgCkeIonQEroqDSTxviEudyjhjYwBOl7xJOaDn35ZvI0/TxUv832OzLYbi5HlFQqfGl8/eql3ll22jcsomuuI2X2sczMaWG4c4m7NowS3aUkm9xU5zRQ0fMRom1h23+LC4atJKQx8hxmduYkpF06Tgucyt9jQ4uyP2GseO2Md5aw+q6AnZEsuhv6mBeRzkZBh/PNkwBYLitkcsrlqEXZc4pWE2ZpZOBrjZchiBzdlbx8IzXuWXIvG+3Wj9bO4hxmfXJwRbg967v5qgtWbKEk0466aBoeF1xxRVUVVVxxBFHHDRNq18Soihy//33/8/ose0JmZmZVFZWcs011+x3L9KDUZE73LSLVYFitIJMgbGXK5uOItfg4bebTqIjYadQ28PdDdNZ4KtktLGOsBolU7LgGR7jaXchL3tLuMHZwFhXPXFV4i8jXuPXuZ9R2+ui3NLBTelf8WL9OPQ6mZaIE4Mgk673Y9NEWNldSLmlnXSdn8GOFnqjZn69cTqz3UOZavSjFZPjaxajjLfW8El7FSfYNjLLPQatIPN+wyCKdV0ca99EV9zGBPt/LCI8zD9QD4j5+8+WwwEbyYvM0qVLGTZs2F4d99VXX/Hggw9yww03UFNTw8yZM9m8eTM+37/ree0J9fX19Pb2MmrUKE499VQgeXG11oew7HCT0IsICRASKlI4qc3mLTFi3xXH1iQjGwTEuIq9LobWD8H+MdgdOxYVdYIAKakBWtudZLm8BIMGAgk9Dm2YrrAVSZdAUQROcqxnSSSLfloLrX47r/WNxRc3Es6Red8znBRRQ0fQilaQebzwfernFHPSN1dzev8NVHsy+JVzNVlGL32yhSVdJZyUsp6inG4y9H7GuXbxeXUly9uKODV9PVt92YzqX8/WQDbv7hpCVNagqCKTh2/lD9uPYsm2Mj51D6Iop5vXN47ELEZpaEpnoq2GeEKiLpjG02umsN6Xz/KOIlZ5i4irEiWmrqTfaEYnt688g9aok86wlerlxWgdUbZ5M9CJCR63frcmS1EUli5dylVXXbVPc/hjeOmll/joo494+umnueGGGw74+X+JvPrqq9TX1x/sbvzsuOKKK1i9ejU5OTnMnDmTbdu2/aj2Ojs7efPNNznyyCP3Uw//O30D/4hu2EMMHH0DDbE0OmM2DGKcjqidC9OX0RBK5c4jvmBFoJTNkVzuLZjDGxtGElR0PNE7iFs6htKvsANvwsgZ1u3EVZlFXcnK2ff6RhBUdUzOrcWl8RNRRY7P3cqfqt7gtsx5LHeXcIS5hRRNkDJ7N0ONDQQSBqKqlnpPClvHvMHchnIe7B7CZl8OR2duxyqG2RjKp2tpNrdefQ1vbRzOUl8ZU3JrWR8q5P3eEdyWuoEy7d7aUx7mUEMQhLGCIJwrCMKF/3js6bE/r0Stg8Tjjz9OQUHBXomifvLJJ3zxxRcsXLiQyspKTjnlFDZu3Mijjz66z+bg27dvJysri8GDB3/nedmsRbbYEWUVUVZRRRATKqqsIsVVwi4NqgjBbIG0DTJiPPkeIhKoIGgVmjZno40I+NwuyI2Sb3WTb3VjEmPsCrmwaGMMzmtlU2s2fsWITkjwki+DcZn1nOpYx3ypkueO+4hGWc9XYRen5GziueYpXJi9gtuufJfNoTyGmeu5xbWCGdvPYcGAjwFoiThZ5K/gV/mLmWhsZcLKq7lyyBIGGZsIKnpqetMYm12PQxtmaCaUmLop0PXwpyVH8ZvJs5nVPJo8g5svNh3BkLJG2mJOHjjyAx6qPo7JubXMXj0UyR6jK2zh2tKFtMRSqA+7sGvCOLQhSkzd9LN2U25sY1l3MX+e8QL37jyZGdlreWz9NPiXhZctW7bgdDoPuEjt+vXruemmm7jjjjsOulDzL4mxY8eSlZV1sLvxs8NisfDggw9SX1/PwoULGT16NCUlJZxxxhmcc845FBcX71E7iqLw+eefc//99zNixAiKig6MKMUV9nbcSoieBBxhaCGk6OiWbYy17uTJ5mM4PXMdKVKAo6xbeb17LP30Hbw64SVSpTC/cW1HQWHqnVeS9dQ6FODBnkG8Uf4622MOtEKCJ5qmYdNFiCr5bAtl0xczM5cjiChahjoaaYml0BuzoBdlXmifhFMX4uudZYwuqufatpGcUrIZpzbIUanVOKQQNdEsznGswTojwvCLdnHB3KuwSFEWPjAO08wWDJLMw93D6I2bOfBOxYcYh3B2gyAIrwElwAbgH8vbKjDr+475Z/7nV9gWLlzIE088wVlnnbXHx9TV1TFr1izeeecdBgwYwFFHHUVraysPPfQQ2dnZ+9SPlpYWjjvuuH8L1gBiNgkxllwqi1mSU6ZoRKIOCU1YTVpRWQT0buit0NJ2pB6dD6SgiL5XgrCENj9APDuK2N+PzhRnhzuNFWv780HdIMyaGDpRZu2WIuIRDcXaHvppu4mpmmTumKrjvrStpEsWuhJWynVd/GntRJ4rfpc7lp+BJ2EiR+fGJobZELVxTcFCbmofxrKIwua+LFb15DOrbQxj37+FWFDLX1ZNZJm/DEUVuXfAxyiqSH3QRb0/hfpwKrPaxnDSiPXM662kqS6d+Z39WX7MUwyxNzPVuoX/W3kqLw6axaruAmYf+wxWS4R0Y4B1gQKW9xYzf00V2wJZzNk6kPpwKu0RG/XRdJyGMP+341RuLJ6PXzHwqPTvsi1Lly7lzDPP3Kc53Ff6+vqYPn06M2bM+NlIyRzqKIrC/PnzKS4uPiw4/D0IgkBxcTGXXnopzz//PFOmTOGLL75g4MCBlJeX8+ijjxKLxf7jsY2Njdx8883k5+dz1VVXUVZWxgUX7LGH9Y/GrYTYGdcSQySiaNgUyGOEoZGaSBYaQeEvdeNJl/wcZUxg00R4ZNfxfOodxAOtJwBwX/cRNJ6X4BRLLb/vnsCRlhrWRTPoTtg40raDUms34521lJq68MRN5Bv70AoJjrNtYrixnlxdsqo8rGgZ5ajHGzNy77A52LVh9KKMXRNioy+Pt1qGUx3OZmVfMX/pHY9ejPO3rok8POU9oqqWyjs20fZlPqKgMslazWNZh71Ef+EMB8apqnqNqqrX7X5cv6cH/08HbE888QSnnHIKF110EWVlZXt8XHFxMdOmTeOBBx6gt7eXDRs2EIvFaGho2Kd+eDweXnzxxe/NfZONIlI4jqCoCApEHBLhNA2mrjgJrZD0GZWSwrkxJ6RUK0RcYNslICiAMYG63YrZHsFmjKDXysRliVPGruGsfutoDdlx6QOU9GtH06YHIKhqeatlOIPtzRxrjDEvrKE2HsAmRrh024X89chX6VO03DP6Ywp1PdzgbODO6tP40jeQuzecSlyVaJZTuaxwGc3bMrmn4GMqhzRwUtVmcnN7eWP5WJ5vmsDNy84iroqsbc4lENUTkvXEFImoosGqjTD72GcotPZx1Kqr+LxtABd+cykpqQFu33k6+VYPPkWPqsKymlLSdX6CcR1Th28hktAiSCqL6/qxYnkFm305nJq+nt/1f58NwQKiyr9XX4ZCIVavXs0VV1yxT/O4L7z++uuUl5dTWVnJ0UcffcDO+0snFArR09PzsxC+PhTQarWMHj2a66+/nr/+9a+cfvrpvP766xQXF/PnP//5O7luS5cuZejQoWzatImrr76aJ598kpNPPvmABcYPmTbhFE20yg4qtAbaZCe5BjdPdU7FIMbJMvq4qGglGVKEN/wpXO5azLi0XRxl20qxqYdnPfksvmMMj47+gJq4hZMc6/kmWEpE0XK8qY0dkSyWdxShE2Qawy4mOmoYbdmJXozzfMckFvor+LKnir64ic6wldd2juQIWytmMcogczMXpyxjbkcFV2d+xYyctWzw5LKpIYcVXYWs9hXSErSTo3HzWMZ6ns9dQcwO1R0ZrAj245PQ4dXgH0b4kY+DyhYgc18P/p81f1+3bh2TJk3ivvvuIzc3d6+Pj0QiXHHFFSxfvhyLxcJf//pXPv74Yx544IG9akdRFARBQBC+/4v01yeq8RebsVX78JfZkA0CUkzF0CsTyNEixcHcEqF1ohFVAwmDCqqAJggIEMlMgEnGZIsQi2mQNApGfRytmKAspZsx9jpW+4qY6tyKJKh0y1Z+Zd/FsqiWt3pGc7RzC/e8ej5PXfJXHqg7MekXGtPzWNl7rAkX82HbIH5VsJj3u4ZxhK2VCkMbVinMR73DsGkjfN1Wyq/LvuBPjZMwaGROSN/MHz45kXOnLWFJVwmDUlqZs2w4R4/eRKWllVXeInIMHkxSjFBCR1/cTG/UTIbBRzihY7C1GX/CQFyVsEoRXts5ksEZrciqiCioxBIaBtub+aytkluK53LrnAsYP24rHWErsYTENb3/rq0WCoV44oknqKio4O23397Lb8PeoygKN954I3//+9+ZOXPm4YrQ/YjH40Gj0RwUd4pfEqqqsmnTJt566y0EQeC+++7DZrNx/vnnc8kllzB27NiD0i/b8N9ytFFGQUFE5Jz6ZPFRkbmH42ybGKQL838dE9BLMtGEhoUtpZxZvJ7fuLbzhj+F480tnJ07htEbZTK0XqxShInGembuOpMTMjbzdW85Y511ZGi9nG1x839dVVyWsoIX+saxsL0fEVmD121C6NVzysRV7PClk6IPfXu+fuYuaoIZaASFFc2FnFy6hUJ9N03RVB7N2MinIQPdcjLt4TxrG1c2T6ben0LrxixMpV7uif5vXgv2yPy9KFfNuu+6H3Wexot+fcDN3/+BIAhfA4OBVcC3FTqqqp68J8f/onLYXn/9dd5++23ef/99dLr/LkA4c+ZMTj311H0K1gAWL15MUVERAwcORKPRMH36dJ544gl8Pt9e5SDNnTuXYDDI6aef/r3vCeaaEBLgHmRH1gvo/QrakIK7TAcCyAkQM5IrY5oQSVFdo0qkNIbUpUPjlRDTwui0CWRZItJnxFUQJMUQQkSlJpTFFGc1cVVDX8LAa48fT/yWL/njqilcM2IhzzZM4fMrH2N+qJRTczbyeUclywZ+AIjM9jpJMwaZ3T2EfFMfFztW8YpnJOlaH9kGD4GEgUK7m793jCahirxQ8g7HrrkKU5mX4eZ6hhQ2sMTfn9HDa2gOOViwcBD2AX0Y0+NYpCiFhh70oszXO8t4ftRX3LV9Omn6ANXeDE7I2Mw33mLyHW5kVURRRcY7a6gOZrO8t5hKZwf3bz+Rc45K6hKWmTvRi3H4p4AtFovxxRdfMGfOHKZOncobb7yxT9+HveXWW29lzpw5PPTQQ6SkHC7l35+sXbuWQCDAKaeccrC7ckgjCAKDBg1i4MCBfPPNN9x111309vZy7bXXMnTo0IPWr22RXP7enceW3kxOytuCTpRZsracy49bhEcxcVXjFM7PWM4JpggdiQAnOtczyRABNJxn7aP0rZu5edsnnGPbwaW7TuWxgg+4rv4MuoIWGiIuRjgauMHZwNPuQhZGPOTo3dxQfwZZRh8VKR00+FMwaGQmDazFrgkxNKuBkKKnUNfNxnABX3ZWcE7OajwJEyklQWr9aazqyWdKxg42x8LcvfVslg57hd/1DOdFVctY+06mpUTYlJbH8u6if/oZP8x/5BDOYQPu/TEH/yICtlWrVvHnP/+Z999/H7/fzwsvvMC11177ve/v7Oxkw4YNXHfdvkXqGzZs4O2332bBggVoNBp+/etf8+c//5lLL70Uq9W6V21NnTqVcDj8X98jqJDQgGwUMLfLCAr48zRI0WTxQSBXIJQpovNCzAGxtAQ6Vxg1JpGwKOhSwwjbLHhy45icIUxZPiy6KCn6EACZei9LvGXckTkXg6Dyiv4EeuJWJg/YTkTRkmfx0Jkw8H7HUK7IWUw/W7I44/+6qphi20qNLpsMrZelvn7ka6ws6S7hlbI3eaTzKBRV4Pacz/ljx1H8uvQznusdR1V6B6u/KeMZ6xR0UoJKeweKKtLY5+TMY5ZzY+pyRi+4nhmD1hJXJSqMbQzIaWehv4J7+n/CQ7UnYNDEWdTXn/aQFac+zIrqUmYf9SwdCSuPrzuaMwasxxM3cWXpUr7uLceuC2OWohy587RvxzUUCnH33XdTVFTEl19+ecBcDV555RVeffXVw8HafmbhwoU4HA6OOuqow7pr+xFBEBg9evRBc/34V4Ybd5GiCRCSdYw013GPq5pfG7x86RvIYxnrOanoK552F/LXeJS+hJmZji1Igo4n3UW89fg0zrh+BeNNtbzt78erxbNZHbUTiOsYm1lPus5Hsa6Lm9qH0RJ20ieb2RlMo9Hj5Lj0LegEGb1YSGMwhb6YGQmFr4IVfL1+ABXlLYxKaSBFH2aJpwyjFKMzYuOU9A1sD2dR7c/CpenHSQVbOH3H6fym8FOKtX7sgpZfd0yg1peGL3I43/KXjKqqiwRByAD+odS+SlXVPS4NPqQDtrlz53LjjTfS2dnJ+PHjue+++5g/f/4P5pLNnTuXfv367bWKfCKR4J133mHx4sW89tprQNKSZfny5Tz66KN7rZv11ltvMXnyZDIyMv7r+6I2EVUCVPAVapK+obtnLiEIKNrk33EbxO0K6BRifh2CXwNWGa02QbwiAAEdOm0CozaOQZJpCjgQheQP2yj7Lj4LDGBzIBfz9HbOc67kc/8RiIJCf3Mnc7xDODK1jueaJqMRFf6vqyqpwRbJJlvrZryxlW7ZyjWto/hV/iKe7J7Imq58BrtaiakSL+Qv4Jb2cZyRsprXomOZeuRGREEhW+9FK8rUKS5sxig9MQufBYtxpAbRizLdMQuvbzqVmUMXEkro8SRMDExtY01XHtNzNrDLkEaxsZuYInF/y0n0s3QhSgrvbx9MflofcVVka1cG98UrvzOmsizzwgsvMGLECD788MO9mrcfw8qVK7nhhhu44447SE1NPWDn/V8gJyfn223Q/5ZicJhDl5yRd9CdsLHEW8bbxQt4w59Ck9zIks4SKlM66EoESJcs9MQt2DUSd6Ts5K/eIq6wtzPetIOT7t3MtXVn8WiGkVxNLXFUZnWN48Pyd3jZW0ECgWcajkIQVCKylnxTsrigJKWXL7sr6WftxqaJcIS9jS+aKjgyZxeTHDUYh8fpb+pgna+AWreLfs4eKi1tALzdPpxxqbsoMPWy2ldEU8DB4JRW3uwdRW/UQiShYbCjhXSXn2p9FoQO5ggf5qdEEIQZwO+BhSQT6p4VBOE2VVXf25PjD9mM3KuuuoqzzjqLcePGcf3116PT6fjb3/7GwoULOeGEE/7rsXV1dbS0tHDNNddw991375F4ZF9fHw888ABNTU3ceeedXHvttRx//PF4PB7uu+++fRI5LSoqwul0/uD7bI1REnoB2Zj8WxNS0QYgboaYHcR4chXu2zz6kARRCVWv4EgLEA7pEEUVQaPg6bUQ+DKDzc3ZjHXVMyylmR2eNMxilDxtL0FZx9i0etZF8vHKRl7eMYa6UBoPpG8hrkpUOdq5NGcZ5zm/Ybi5nqeWT6Vc10EClTOt21jdlc8d35xOls6Ld3Ua82rKaZOd/K53IEMtjbzVM5q+qJlsg4e5NRVYpQjFum7W1+XhNIZYUNMfgNv7z2WGYzXeuJHbhs9FQuXL9gru/XgGZk2Ui4pXssZbyCZ3NlFFizts4vrs+UgoXFK5kuP7baPDa8MTM/1bsOb3+3nkkUeIx+O88sorez1v+0IikeDjjz9m+vTpXHjhhYerQX8CWltb6e7uPtjdOMxPxDs5X/G5bxBjDd2snjWI33ZXcp61jxRRy5KB71HnS+WTYAkfBc20Re3k6vpoTfjJ1CYdHUbotUz/y238qTSZo+oUTSwJp3N5xmLGrrqMDK2X/vp2LsxbiUZUGOJqYVFbKaelrUVRBWRF5MPqQXjiJqp9mVxSupJB5maWeMvI0XvYHMil0tJGmjmAQYrjTxjQizIuQ5APGgfh0gYwa6KMSG1iQ18OAy0t3J77ORlGP1OtW7nSuZo3i746mEN8aHBoW1PdDYxQVfUiVVUvBEYC/7enBx+yK2wlJSWEQiFmzZpFfn4+48aN484770QQBFauXElFRQWZmf+5GOPKK6+kvb2dmTNnctppp7F161YGDhz4vefatGkTf/zjHznzzDPZuXMnjz/+OJdccgmDBw/epzv5UCjEpk2b9niLoXeAAU1ERZCTpu4Jg4AiJQO1lO0yvgINoSxQRVCsCQRdAiWsQe+MoKqgRDSIxhhGS5Qr+i+nZ7CF3riZBb8bx6Q7VlCZ0kFQ0VMfTaM1aOfSjCWsCRcxzrqDzhwbRjFOVI0zwbKdbtnGFFMbv2o4BYsmytDyRj7xD+KN2uHcUTmX1UPepTXhJ0ey8snYNo7L2soLzeOp73CR5fJyWcEydugyWdJdgqoK6MU4bXEn/Qs6eKroXRryHHTJNu7deCKqIjC5qBZFFbBLITLNfiomdNIQTCVd58OlD7C0tgQy4ZLC5bTKTgbXnANAT7/3SbUGObdt0v8fx95evv76a+bNm8eJJ57ISy+9dEA8Y++66y7+9re/YTQaOfnkk5kwYcJPfs7/RbKysvZZA/EwhwbH2Tbyd18Fi379JEZBS0CRub97DK1hO50+KxFFy6ZYPme7vmGU3k+trGeyoY9nPWU0R1N5+6onKNFYeLCnnN+4tjPF2MPmmJ4bKr7mK08FG7uzybV5yTb5WNZWhEZSiChahjia+aJ1AFZrGHfMhCioeBNGXt45GlFUWRQqJd/Vx06vC6chzMmu9Sz396Ml7OSo1Gp8MQMWKYKiCtT4MxjlamSJux+7IumMte1kazSHx5qOwKEPc+rBHuTD/JSI/7IF2steLJwdsitst99+O+FwmGg0yooVK9DpdFxzzTXcc889zJkzh5KSEqZNm8acOXP+o1xGOBzm1FNPZejQoSxa9J+1bxRF4e233+ZPf/oTL774IoFAgHA4zOOPP86QIUP2edvF6/XS1ta2x+/XRFRiVoGEHkJZEDeBqkmuqPVWaLC0JUCFeHYUqVeDGkhKWsR6DcRlCZ01mcWqkRQW9pZhkmIEZT0jbllHVNEQTWjI0/ZSpO/m9Jz1LAuWka31sDGczx2Zcykw9nBf9zDWhQs50+IlVTTz69zPeDz3C+7Nm0OFoZWilD7SND6Gr5uBSZDoVYL8uvhzmiMpzMz/mkUTnmVMegNf9lbRE7PQ924e9478mL/VjaNA141NG+W4JdfSEEsjU+Pl0cEfIEkKp6aupZ++g3l9A7gxey4jrPWc2zaJ0q2XMLb2dB7Tl1K09VJSNl2Ldv2t347Z2NrTvzV07+jo4LHHHuO2224jkUgwe/ZsZs2adUCCNYDnnnuO6667jscff5ypU6d+57WvS2YfkD78L9C/f3/S09OZNWsWbrf7YHfnMPsRZchjnJy2ntpYJtc5mjAKWqKqjEU0kKnzcFRKNe8N+ytPb57CPa5qHGIYEYG5/iquaDye6xxNPJaxnr6EiWnZg3hp0USmZQ/i0Z5RpEshVvuLMEtR7iz7nCpbGyWmbh6p/JCjsnfwSc9gBhqbkEQFVYWhjka2tWdSH3IxOqsRiz5KQhZJKCJTMnawsSmH+mg6UUVDvSeFv9WNoyNgpT3mYIytjtEpu0jZ7Wm6piePbeEczGIUizZGobH3II/0zxwVUIUf9zi4fCEIwpeCIFwsCMLFwKfAZ3t68CG7wgZJn8B169Zx8skn069fPx566KFvV9X8fj+LFi3isssu44477uD444/nD3/4A1u3bmXr1q2MGTOGiooKampqaG1tZfv27ZSXl3/bdktLCy+99BJarZZ169aRmZnJJZdcwsMPP/yDFaj/DVVVMZvNnHbaaT/85t1IUUhpjdNbqUWMJ58L5KuIMQEpCi3HQNH7MVon6omly2Tm9xFXkheQuCwxobCO9d05SG+lsnGymawjvIiCyvSUNfylfTJ5Jjdf+QbQEnLSHTZzfNZW2uIO7FKYU9ZcySfD/0KhxsplzeP4VN/OeIObNjmVzREL28I5pGt9vNfvY65pmcSrR7zChNWXMzSzhY6wFZsuyrSsPmYH82kMpnCcazMOKcjxt2ykL2Hh8QHvMkof4W1BpXry37i9YxSPfHUSE4dVo9PKvNszggpzBzlGLxd89it+n1bw3wfrXwiFQvzud7/jtNNOY/78+djt9r06/scSCoWIRCIUFPyHfg99lInqIXvP9LNEEAT69++PyWQ62F05zH7i65LZHCdGGaDtY3M0h/eDVqYYO3GKJp52FzLKWMeV6y/AdMRnpNqCNMh+rth0BbeVz2VlXxGF5j5u7xxCubGNS22d5H5jYZxxMfe0VfOku4igquGklA2sCRaRp3XzbnAEdR4XpaWdNIZSOTp1KxFVhyCoHJ23g3WeAgZkdRCSdQx2NiMKCr6wgXavja+FfuSn9xFRtNR407mj7Euea5zE2blr+LB9MDv0GQy2N2GXQqxtzePc/msIJAx81jOQPJOb3rj5YA/3YX5CVFW9TRCE04FxJHPYXlBVdY+TqA/pX4tPP/2UKVOmcMIJJ3DNNdd8ZwvUarVy4oknUlpaSltbG6eccgoNDQ2MGTOGhx9+mMsuu4zzzjuPrq4u8vPzWbx4Maqqsn37dh577DHuv/9+pk2bxqpVqygoKKChoYF4PP6jtZ3i8Th33HHHXhnE+wsEOkZqiaQCKsgWEBKg8/7/vLWmy2Rki0rFk314l6WTb/OQSIikWQK0h2wcn7uN2Aw3M4as4bK0JaTpAzTE0piWuoVznSuwa8Ksbcjj+KytnGLdyBRzNbsi6YzIbubC7RcQUCIcn7KJZYEyxq2+jHe6R+CQgvjiBj5sGUTFvKt4MW8Zb7hH8/Gwv2CU4qTow7xbPJ+XvSXsiGSyy5vCxbYuKnWdmMUoD84/hQ7ZweWN03gkbzbPevqxorOIrJIednjSGJbZzNHObfTJZnJ0biYOr97r8f7Tn/7E2LFjeeaZZw54sAZw0003MWjQIIzGZALiB3nz+KbsPZb3e5/TzX6GGloZOPqwb+j+ZNSoUUSjUV555ZW9+v/sMD9PHs5cxOudSc03sxjlnk0nM2XdJUzZejI3OBsYZxB5bsjfGaZvZvmg91kZyWfDiLeY0z2EvogJsybKYxnrKdD28GnIwIt5y7jHlbyWnGLdzF1DjyVb4+EM+xo+9w2kv6WT8wpX8bvtx7CxPZuWWAoLPeWcmbuOxmAKR9ha2Vibj6yKxFWJDT25FDjcHF+8DYc+QkTW0hs30+W38knvILJMfhb0VqCoAhdlLuXV7aPZEszl0cEfsNadT56+F0/MQLGhizG2uoM51IcEqvrjHgcbVVXfV1X1ZlVVb9qbYA0O8RW2m2++mYsuuuh7DYfr6uqora2lvLwci8XCFVdc8Z1tTK1Wy+WXX86DDz4IJLXVUlJSuPrqq7n55pu/E5z179+fYcOGsWrVKiZNmrTPfdbpdPz5z3/eq2NiVpBikDCqaELJ/kvRf1SHqmj7JOJGDeZCH9V32hlUXMfWjkziYQ0JRSDP6WGbP4vxWbv4aOdAOvNs3Jf9GW/6hhCQDbzdPpxr875iY0Eux1k3szJSSFxNmmzqRRmrLsoFu07mpPSNBGU94QYb48oX8X9bTiHzaT0vvvpH6kpTWRCW2OzJ5nH5KL6eN5iRU7ZRtfJcnOYwXR4rI/MbqVh+PktH/4XLak5k3LAazra40QprmRcs43L7NhzFIVb5igkntEQSWmZ3D8GuDePS+jmx8dgfHKv29nbefvttTjvtNDQaDbW1tSxevHjvJ+pH8sknn/Dmm2/yySef8Nhjj/3b6+XGdu7qGsjD6Zt4P7h3UjCH+WHMZjNlZWWHq0V/Afy+ZwQhWUul1sSiYAp2U4TBrhaiioan3YXc4GxglD5CTVzD/T0VDDE14lPCvF28gIURgSN0AWrjKn2JHJ5tmMynznauT/8KraByf+vxCClOVoeLyNR4+I1rO6fXHc3ZGasYkdlMvqGPRd2luAwh1ngLqXW7EAWViZU1eGJGdoVdHJ29nQ92DaLY0kN32MxRWTVsD2RS5uompmjoixo5K3sNszsHs9hfTomrh1RdgFfbxzHQ3squcBoOXYR1/gKGWhs5vDb8y0MQhKWqqh4pCIKf75Y+CICqquoeibceEitsiqLw8ccfc/rpp3P77bd/+7zH4/mvJsWdnZ0YjUY++OADrrrqqv948R44cCCXXnopqampNDU1sX37dlJSUrj88suZOHEiM2fO5JVXXmHOnDns3LmT+fPn/6jPEolEeOedd/ZKJ0oTAkEGKSIQTU3aUCkSRFMVFINKwqhCUCLQa0JvibFhewEmQwwlJpFl9+EyBJEVka6olSJXL3pR5ptILp+3V5JAZExqPX9rm8DFWcuYseYK7ltzIhsD+ZzrXIEoKJRaeni1eDZLPGV44kYc/foYb6ol0G3m5D8tYEM0l7u3nsqVyy7k7KxV/DF7Fb85411uyfqSS/uv4MSczfxu6PsUGnsZnNWGFpErCpZycuoGPg0ZON3s5wp7Ox8ECni9eRR/yl2GRkxwReYiyiydBBM6+uvb/+sYdXV1ceutt/Lxxx9TX1/P/fffz8svv8yxxx6LXq//UXO2tyiKwgMPPMCXX37JFVdc8R2ttb6oCU/cyFBjIx98Mo7nvTl4E4cv0fsbSZIYO3YsbW1tPPnkk4d12Q5RnnetwCcb2dWXyk3tw7jEXkd/ZxdpugBpugBbg9m0Jvy0JeLM3H4uFilCUNFjE4083lfCh33D+cBfSj+thTMtXv5Q9g6Zeh+v9I2lWbZyU9ZcTv14JYoqcLLZz/PeHGzaCB/1DOEi19JvtyjHOneiERNoxQROXZAUXRCTJsZ2TwYtEQdWQ5RUbZBAVM/K3kIisoZySwftISsWbYxZzaPpDFqpC6SRbvRjEmME4jqKDN3oRZkicw/HOzdiFf+7JudhOCSrRFVVPXL3v1ZVVW3/9LDuabAGh8AK27Zt27jkkktoampi0qRJ/O1vf+P4449n0qRJjB8/nqeeeoqBAweSnp7OMccc851jBw4cSGdnJ2VlZf9V8+rYY4/l888/5/nnn+epp56isLCQqqoqBg8eTFNTE08//TQ+n4+RI0fulefof0KWZVwu117d+dsak0UHnqFxhKAECMTT4ggCGOwRwm4DQkxE06dBu93KwFN3sK07A1Rwh03opASllh6aQk7qOl08OPojAKZlVnOcdRMJRHJ1fRxr9HG7KvC3Ma9SrPHxSaCCFe2FBEN6+pvaGWXfRVTR8kDOp3gVDfUn/pXBq8/G127l4rFJN4H3OofzyMslDDq5mkSKyF/fO5b7z/k71ZEcVvYW8mTJu5xecyZX5i3hOFMnI1ZeTnPl1zRFU/lgxyD+b9CnzAlaWdZUTIbeT5G+mzJDO4XaPrb/lzF67bXX6N+/P/PmzWPAgAHfWoXdeeed+z5Z+8hHH33EqlWrSEtLY9SoUd95bXtdNkOGtzDXX8XtZ3zA9nA2g0yNB7yP/ytkZWVxxhlnIAgCfX19h4WKD0GOc25kjG0nZjGKUdDzm+zPWRIq5qmaKbwx+CXiKpRoLMzIW8cNzgaaZD9g5QzbBgpTrPyqZQwmMcrWcC52TQiTGOMY62bu2nkaQ1Jb+G36MuIoTNpyHourPiJN4+OdzpGsCPVjkLmZr1v68X7rEIalNnNC3lZqAhmUmrpoCKbij+lJ1YVIKAJv1g4jw+bHEzEiCSorE4VcnLeCN1pHMiy1GacmxDd9hYRkLePttVxf8BV/7xyNQYoTknW0R+xEElrOONgDfpifDEEQXlNV9YIfeu77+NkHbPfeey86nY4nn3wSjUZDa2srGzZsYNKkSbz99tu89tprbN68mddee428vDwqKiq+PdZisTB9+vQ9Ok9FRQX33nsvt912GyNGjPjhA/aBeDxOLBZjypQpe3Wcu79A6hYFTY+GhFFFtqpIfg0JcwKl2gpZcUR7DCFgIGVaGzW9aaRZAlgNUY7M3MXa3lwSCAxzNOGNGnjbPYr5LWWsG/Y2t3eOoS7g4rqc+ZxaexIX9l/F/XUnMSN3Ld6EiWeqkppFL3WNp8TUzW2pmzl66wVcmr+ch1ur8PWaUUUo0XcyUN/KDPsall9czBstI3micyqnnLycMy1eXlO1NPc6uV08ndGpDeRpezl9x+mUpXWzzl/AitZCth/5GlO2nsyVBUvQfWPhC0MF95TX4ZBCfBMu4vsy0P4hk9LR0UFdXR29vb1MnTr1B/X4fioqKiqw2Ww888wz33leN+whHlH0PLtrMp29Nq4bvJAPtg3i6NGb8R2Unv7yEUWR/Px8urq6ePbZZ7n//vsPb5MeQtxYMJ8X2yfQFrAhJ0ReMAeYnFbDak8Rx+ZXo0PBtHs+7VJScTakiiyJwHiDlZd8GVRaWplkauQ8ax9fhHUM1fVxf+cURqc1cJ5zJcNfu4UdF/2ZxVUfEVXjvNU5igyDjxXuYlL1Qa7v/zV/qRvPJ7VV3DpwHp+6K6nuzWB4RjM+g57WsJ1cmxeNXUEnyXSFLTh0ESzaCO93DMUTMVJpauWxzccwpXAHi5tL+GvkSByGMAZJpitspp+th7gqckP2XFpbjjqYQ/7z5+BXev4YviMKKgiCBhi2pwf/7LdEzz77bDZt2sTcuXO/FbwVxWS3JUni4osv5oknnmDIkCE/SjTzvPPO45577vnJgjWA+vp6Xn311b0+7uHSXHoGC6AICHEBQQYhDkJUJF4QQZAFhHYD5go37qAJf6OdlrU5FNjcZOo8uAwhFFVgvTePDFOAuU39STMHeCvgpJ+hg/dL5lEbzcQf09MVs1JgdXOseTt6MY5PMWASY0x01HCWfQ0rojpmlb/G49um8kjebD476hkmDdxOp2znNfdYvgxU8uDKE2jakEN5Whf3pa/hnPopXGDtwWqOMMG1kyJDN3/umMLjxe8xPnUn9f4UHqiazeN9JdxZ/BkzLL0ce95KPL1mblt9Jn/tmIh94/XfOz4bN26ksrISm83GkCFD/k0640BTUVFBVlYWGzZs+M7zxdoePuwaissY5L7hc5IJ08W7sIqRg9PR/yHS09O57777SCQSzJ8//3AxwiGCTYzQFzFyReFSih19aEQFd9zM4/mzOcG+kdn+QdTEk7nGT9Ukb4S3x9IZb4B3A8lbvLOs27ALWj4NGSjUuHmqdyxaIcEYy042RHI57djl9Ft4MQBv+nPINbopNPTSz9LFua4V5Gl7OTV/E+dVrOa15lEEInpGZjSxtS8TnZRAJyYIyVrW1OeTZ3TT1OdEJ8mk6QL443rKU7pY5O7P+f1XIwoqNw9YwLiMejoDVi7NWkJDm4vWkJ0Kcwc3bz/roIzzYX5aBEG4c3f+2kBBEHy7H36gE9hjbaeffcB22mmn8eabb9LV1cULL7xAXl4el156KZAUQv3444+56667WLlyJYWFhft8HqvVSlVV1X7q9X+mrKyMG2+8cZ+OjafK2HaBc5sAORESaXEqj2jEag+TVdiLodSHt9eCv8NCWmkv4ydvojVoY15XBZGEhjRdgOty5vNNTREzyxbRGzLz0NbjOMLQTJ0cYJKplhJbL3emL+LF/EV8HKjkj6um8H/Vp/CRZyjvdgzj5vozkFCZ8uktKIpIocaKX9FRbmnnj18fzURrNUeadzC+/07UzAg7etKYE3SRbfQwbfsJZJr9rPPmA3BPzmc0yKlkad0UWft4o3MM7zYOYajei4jIYxnr2XXMSzw/6jWeyf/0e8fF7XYza9YsZs6cuU/j+lMxYcIEampqvvNcpdbEnbmfopMSnGftoysR4NWCxYzW/+wXun8RiKJIJBKht/ew1tWhQOqI3/Baz1g+qXiPVE2AN4u+4sPSuUywbieuQm0sgy87K3imbSqXNI2nX2oPACsDpVzSNJ7xxlY+7R6IAgz88lr8ipHuhBlP3MjlriWM0ncxydTIda6lFL6QXLW52NbFH7LWohfj1AbSSRVDZEp+SvWdeGUjE9N3kuv04NCGKLX3MNzZhKyKWLQxJpXt4POmCsrTu/DFDCzrKkbZvRrUFbHQFrWjFRLM661kTU8eBXY31827kGkV2zjC0cbbjUO5vuSw08EPIag/7nEwUFX1EVVVrcDv/yV/LVVV1T3O2/nZB2wAxx9/PJ9++im7du1i0aJFNDU1UVhYSE5ODrfccgvr1q3jxhtvJD8//2B39XvZuXMns2bN2uftmML3IZwOERc4FhjRN+nYWp2Pt9tC75oMxuXUk5Lmx5wRpMdtYeHKKtxBE83zChhob+XT5kouX34REwfs4JHlJ9DbbmNAWidaQaE2nsKqSD7P533FtriV3/WWYxUj3DrqS0ZnNiTtVfRB6vtS6EpYefiodzmz33ombT2FmCrhlU3cMHkua0NF/GrreezypVKQ2YvLEmCpr4yPd1RR5WjnCEcbTxV8yBp/IX0JPetDBSzz9SNL7yXb4OXpAW/hVxS2xkNM33kMz3tzuGLJRSxc9tS346Cq6rerI7FYjMcff5xzzjmHiy++eD/M0ndpaGjgjDPO4Nhjj2X27NmEQqEfXJlJJBLcdtttvP322wwZMuTb51/JWIJPCXP26iuYkb6aS5rGM3rB9bzmd3FX1/e7bBxm/2KxWDjrrLMIBAL84Q9/2CNbusMcHMxCjOvSF/CrpqM50tDz7fNHG2UKNVa2h7MxaeIc59rMy/lLOCq1mncDdh7N2IhWTJApWZAVkUzJwsKj/8BDW48DoNTURUTVcEfrcdzXPo0cyUrVE5s4YcjRACgofNg6GE/UwFfBCl7pG4dVCqMVEnzVUUaVo53PGwdQbungo/qB5Bg8iKh8vbWccFSHogpMdO1AKyZo63bQ4EtBIyis6ixgeUcRXWEzWilBrtHDkKp6Coy9RBUNE7LqeK5+0sEY6sMcIFRVvVMQBKcgCCMFQZjwj8eeHn/I3drHYjFOPfVUjjzySE488UQkSTrYXdojcnNzGTt27D4ff+3FRdzmaUCIioSPiKKvNoKgkrpKS0IHrSE77j4zRkuU/jmdVAdyMXxiZ9hVG/igbhAX9v+G5kgKsiKx87gXeM5TyLOzT+D947qxShG+7KjgLW2UN0s/YmM4BsAAQytHGFqY76/knPSVBOSJFGp7ebF7PKWmLp7q9zaDdQY2R3sZZmjAoxgZWV7Hrmg6RxhauOLvVzP1lBqurFrGGbYNbI+n8nGgnKN2nUzTrpOpBN7VbeX68q9Z485ntamYzYFcRljrOdq1Dbds5ophS2FbybfjMGvWLD799FP69096jubn5/P000//qLn5PmRZ5sMPP0RRFBobGzn11FM5++yzefPNN1EUhW+++YY5c+YwdepUhgwZwhtvvMFLL71EKBTi4YcfJj09/du2fpW7EJtoZPHoP3NV/WlsqMnnyKpavnIn7XD2OInhMPsFq9XKtGnTkCQJVVUP57X9zHAMv4c/dhzFw7mf0hhwYhAkwmoUvxInXbLQlQjwWMZ6yIBXfOlE1Ti/srdyWfM4zrQs45HsefzJ059Ke7K6fHMsjXSrn/EGmOszE1J0RBJaXsj7GtDwQMYyTu9MFgiJJB0LtKKMVpA51bGO1eEioooGkzZGOKFlYEYbn7RWkW71s7KnkN6Amfy8HqzaKLXdaci7BbFz09049WFCspYMi59KewdGMca8tnK2+9Kx6aK8XD2GIldy1degiR+U8T5k+Hn4ge4zgiBcDtwA5AIbgNHACmCPEtuF/1buPnz4cHXNmjU/vpf7kRUrVnD66afz1FNPHXIX2UAgQCgU+s4P+d5yW18jUkBE3ysgxeCeUbn7sYcHn/iQxzGLUeZ7KjnRuR7fmvu+fa2jo4Mnn3yShoYGPvjgA7Zv387MmTOx2fa4KnqvGTlyJN3d3SQSCZqbmykvL2f69On89a9/RRRFqqqqWLduHbFYjPLyckaPHs2RRx75Hdur08ffDcC1bSMBaA/bOSltI0cYWvAretaFCynYcvlP9hkO8/00Nzcza9Ys7r777oPdlcPspmzUzRRpBJZGbdRGMznanBS51QoqHkXHsN1OMwElwsnVMwjFdYzJqOeejCU4xaREzrywhjyNl3KtmZd8GbTEUijSd5Op8XC0UebXnYOIqxJPZK4D4KhtJ/Fcv7dYG8ljkqmRC2vORSclKDC7ucC1jF3xdPK0vbzWPZaQrKcvamR0agPb/Zn0REw49BFyjR7yDH3M6yqntimDfvmd6MQEHUErR2buYkVnEZ6gEaspQpmzm4G2FrYHsqjzpWLVRRmV0sA3fYVc2vmfdUV/6cyYMWOtqqrD/9t79AW5atbdP05ovPGq23/wPD8VgiBsBkYAK1VVHSwIQjlwn6qqe5S8eMitsG3YsIG8vLxDLlgDWLNmDcFg8EdVL/4+pQBSgJ/v7u+PQrv+VmLABMC32wY5Eolw0003EY1GOe6447jlllv2uPr3x/Lggw9y5plnUlJSQkdHB7fffjvPPfccZ511FhMmTEAQhG+3Sv/VBeODvHlcnLGUM3dNZUdPGueWruaOlJ38truS5+omclLeFm5MWcdt1cP59QH5NIf5V3JycrjqqqsOdjcOs5tN5X9nhCizU9bST9tHocZNb8LIY83HMT1jPct9pZyUsoFR+i7ubJvGtKxtFOh6+WvTkTiz/r+eYV0sg6ONMqVfXYzNHmZIegsmMYaIwuN9TsqN7az0lfBR0Mwd605ncE4rdzZOxyDJLNP1Y8GAj2mS/XwWLMcgysRViQW+/1/gl2n0s8adzxH2NkosKlu9WTSFnDSFnGQa/TRbnDh0Eda35KAkRBqsqcQSEglZZKCrjY6wjaU9pWxvy2RATjuNHiebNTmcm/UN/I8GbHvGz8IP9McQUVU1IggCgiDoVVXdLghC/z09+GebwxYMBunq6qKrq4ulS5fi8XgAKC4uprGx8ZCs8po0adJBk5o4lKmpqSE9PZ329nbeeecdrr322gN27mOOOYbXXnuNrKws1q9fzyWXXEJaWhqJROLbmwaTyfRvwdo/VtWCih55t6fryr5iSt69ii9bK5icvZPptnXc0HIMywe/ecA+z2G+iyiKWCwWPvvss8Piuj8T3vMPxCAk+H3H0XzoG8KKUD9OTN9ERNVyc8Y8Nobyedk7mFyDhypDCx92DeXlsr/jU5Kis7XxAL+yt7I1HqIit4N1w96mL2rGLoUo1PZwg7OGi21dDLY2cao5SFV2O28XLyAQ1zHeuYNSUxcA+RoriirwtnsUOyMZfNFawcKaMqzaCAOsbaToQzi1QVI0QVL0IWRFZOO2AjZ2ZSNJCiFZi14vM7VfDSFZi1Eb5+T+mykw9lFq6WFbUxbnVq6m0eMkx+6lttfFvetOOphDf5ifnhZBEBzAR8A8QRBmA217evDPLmBTFIUrr7wSl8tFfn4+BQUFnHPOOWRkZJCfn8+sWbOw2+2sWrXqYHd1n5gzZw7V1Xvvifm/zJo1a5g2bdqP9nHdV04++WQ+/fRTKiuTd9iTJ09m5cqV3/v+fwRr9d5UHqw5AV9Mz7Siam7OnUvdmX9h5eD3eG/jEI7QGVm0rQytcMgtdP+i0P4/9s47PKpq68Pvmd7Te68EEmroXYqogCCgiBWwIaIoFrzYrl71WlEsiKLYLoJYEBAE6SI11FDSe+/J9H6+P+Ll8zZFRYaS93nOAzNkn/Ob7GHOmrXX/i25HKvVitvt9rWUS55r/A4xRncSvcRLgTGYvwTlEyFvocAejl5iY4M5g8G6PG73P0aYvI2BqmZejP0GFwKvN/ci7cebKXX7YxMdlLoCGRt2nM02GSOCcxmoKeLRgsnU/xTYzfKrosBl5qukzSxqiaeoIILZ/pXMCygB2mvjEpX1dNVUsL8xjkdTN/LV0HeosPhTbQ+guC2ItZXdqHH6sbs0gRMF0Uwf+CPpIbVMTMgGYEBUKVsKOqGSuqmp82dTaRptbjW5xlAkci/7muJ5s+tKck7EYLUpiApu9dWvvoNzgCiK14ii2CqK4l+BJ4AP4KelpDPgvLpTOJ1Orr32Wk6dOvUvzboFQcDtdlNZWclbb73FoEGDeP/995HJZPTu7ZOl6N9NWloaISEhvpZxQdDY2MiPP/7I7t27/2s/Tl9gsVgYMGAATz/9NPn5+f/R+WLykMe4tWwoH8f9gMmu5Hi/z07X0DxbOpY7Y35gstZE8eXL2GhT8ED/zT56JR38E6lUypQpU6itrcVgMKDRdLQK8xWtXjXDVe2Zzq1d1lHgMtNfbabZo2OavpGPjHIGKJ0829CPXHM4GomTPcZkclrC+C59BX0zi+ilbKPnnllcmXiKOSE7SZLpGK0uBzSkB9QyeNMDlFz1PhMKxrAmZRMAN/mdZJF8FEvbItjR0onClmD29/wSs9eOQ9lCn5Qyrt57N0/1/JYbIg/wUcUAbC45l0fncqw1in5xZdRa9Wyp7USLRUOjnxaFxMOWU53xCzRTZ9GDKCCKAptK0xgZW4DVpcDhkfF61WjG9z/CqbYwUgwN0OzDCbgQuEAT4YIgSIBsURQzAERR3Plbz3FeZNja2tp49dVX6d69O2VlZTz55JP4+/vz0zovADKZjPj4eKZNm8aePXv44osvWLJkCSUlJT5W/9tITU3F6XRiNpt9LeW8Jj8/n/vvv5/6+nq+++47unU7P6wvbr75ZiZOnEhMTMy/zGFJ+jIUmc8B8HHcD/Q6NJUr43PY53AjFzw8GZzDTVH7UQjtNhIO0cXsjdPZ05JMp123+OS1dPCvbN26lfz8fF/LuGT5MflrKlxBHHfaeKU5icWt0VR59Fi9UoptIfxgl7K9JY0Xm7rRQ1tGd0Ml0w31vBe9hyeT11HiFhmmMrHOnMD9GdvQSR0sbhzKjPIhLGmLYodd4OHwzTw75GtmlA+hk6GeZxvTAOiz/n42jXqdF7KuIHt1Z4L+0t5I/sr72g27N1s6MyN9H6tq+1Dt8kciiGgVTlbt7keg0kq9rT373zOwiokJ2bTZ1STqmjAEWEgObN8B2imuhsviChgcXcKumkRarWr0cgf+Cis7q5Iw2lXsq433ye++gz8fURS9wDFBEH53BbrPAjav18uGDRu4+uqriYqK4rPPPuOqq65i/vz5qFSq/zmuV69e+Pn58cQTTzB79mwWLlyIxWI5h8r/OF999RWNjY2//oOXMLW1tajVarZv384rr7ziazmnqa6u5o477uBvf/sbvXr1AtqzauP02Syrbi8W3m33srTrpxikNvorZXxZm8kDNZm8VTic8Zr29jlKQU7QYSkrEraRN+QTn72eDv6fG2+8kR49emC1Wn0t5ZLktYhDFNrDSJXL8JNa6aSsIURqYWHt5WS3RNJPaef92C3cE3iQyVoTjwfnsrQtgt12L6ubM/GTuFljCUcrcTDLr4oEVQOvhh/mzejN7G1NosoVwPXHZ7CttTMfxu7ipbAjDNbl8ZExlOLxS1naPIT1w95i5ZxXaXvJSWdVNbveeo/phZO517+cDHUlEWoj3p+McpvNGq7od4xghYVglQWTQ0WjU8uXhT3oEVxFqSWQTkENqKQuovRtuL0STC4VgQoLcX4teDzt5ykyBhNhMOJFIETb8UX+V7kAm7//jAjgpCAIWwVBWPvP40wH+8TWw+v1cuONN7Jt2zZGjRrF0KFDf1NTZrfbzVdffcWOHTsIDQ1Fr9fz4IMPXhA7R91u979YPnTwy6xduxaPx8Nnn33maykYjUaSk5N56KGHSEhIAODhxjLyJi5GLsgod5t4tnYM70XvAaDWYyZc2v7Ne0lbFDmWSNbnpbNi4FI+a+4PtN+kAL7a9ZwPXlEH/05NTQ1vvvkmzz//vK+lXHJ8E/s9WqmTKwKy6aqsY48tnpv1jSxpiyLLGI9XlOD0Srk5bA+f1g1kfPAx0hQ1fGvsgdWrQC54GGc4SqTMToNHTg+FihnlQ3g6cgMbLGmYPSr2tyZgdctxeyU8EreRdEUbtR4ZPRQqlpsCWdvQk88Tt7LeqmKsxs5XFj2TtSYSN89kQEoxGfpqVhZl0iOsCqNLRb1Vx7DwQmweOY3O9v/rGfoqXF4ZccpGPqoYQFltEFK5l5GJeailLr450Z2wECMqmQu3KEEpdVNSG0xSRAP+CjvXVf22XtMXC2dm6xEjRjz6B209Zj/sS1uPYf/t+TNdHvVJhi0nJ4dvv/2Wl156iYkTJ/6mYA3al0enTp3KjBkzKCsr48CBA6xf/7/bF51P3HPPPTidTl/LOK+w2+2YTKb/eN7pdJKXl0dycrIPVP0nN910E2lpaadboK2N3YTMKOXFpgy+MPtx3BlCmraGhPXtnmr/DNYAdrWkcLgpmsLLPuKmA7dRagliQ2H7JoaOYO38ISIigmeeecbXMi45Rgx6gKzKWO4P28Izr99Cs0eJSnCx2SZjll8VXlHC4pgtVP8tGbtXzpCAAlbX9+I7UzdyzOE8H5rNYF0efZRydljj6KFQ8VRDOlqZg09a+3CtPh+lxMWj0RswyB3E6VpYVjeEApeOQImLN1tjeeboOJ6PXcOStijGaux8agomVV7PtJIRFI9exv0Rm5nhf5g5nXZwvDGC/oHF6BQOjG4VpZYgbgzdS6NdSxdVNQ6vjOeyr0QiiChUbkYn5bKtNJX1RemMTMvDKwqUlIRhtKnIDKxgWHIB0dpWNLKOe8OvcgFn2ERR3PnfjjMd75OAbd68eYwePfoPF/f27duXp556Cmh3wLfbz/8m2q+99hpyudzXMs4rnnvuOebNm3f6sdPp5JtvvmHOnDkoFIrzwidr4cKFHDp0iDvuuON0JjdW3cwTk77gmDEaieBlhLqNGHkz0/ocIGXnrSwzhp0evzx+B8Hq9qX7vCGfsDr5e1xmBV333+CT19PBf8dms7Fx40Zfy7jkWGOOJzOqglqPjh/+8hqzXrqPF/PHMFrtxui14RYl7LFreOOdNxmraeOwKY4QlQm54KHcFMDkotEsqx3K0rYIdralkeuy0ODU8VbkAbJa4nivpScDNYWUuoLwk9vooy8hXGVkRVM/mr1y7vUvZ+fAxcgROWGJAuC1/JF0VagZFpjHmMju9FHKafUK3OFXw6S4Y/RWl/B4/HqGGfKYGp7FMVssEkHktZJRbKzqTHp4LS02DT0jKznSGI3TqKRrRA1qiQuN3ElyUg1XxObg8Mo4WBNLq1NDYVuwj2eigz8TQRBMP2v+bhcEwSMIgvFMx5/ztbl169Zx+PBhFi5ceFbOl5CQwLvvvsvzzz9/QWzLLy4uJjk5+Rfr9C41IiMjycvL47rrrqNnz5507tyZ7Oxs1q9f/4faeZ0tsrKyePrpp3niiSdOz9vD1mL6WUL5LLsPOoOdPZoUJmtNXKtro59qN0UxIRy3RNMj7zJi/FrJrwv9l1q1XXbomlzBLbVn3Eaug3OAw+Ho+EJ1jpH2ep7+inq6RlYSL3MBUobfsZ8kVT0TCsaQrG/g07id5Los2EUpt5ePIE1Xy9WGo4zfPofrexzk+dBsaj1mLCLIBQ+H7DFc5pfLSnMA7yZ+RbhUx3JTOKmKOmaFbm9fApU4aPNo+LBxCDGqZrY2dOKLlK/poqlmq03K/l7LARm7WlK4JqeAK665mcLrtRROXcI0/4NsMHfhnVNDGRxbzA+lSWjUTnqGVnLEFI1C6qHFrmZQeAlmj4Jkv0Z0CgcJ2ia2VyfTJ7ScNpcas0dJXlsocpkHs6v952j18YScz4hc0Ma5PzWAP40gCBOBvmc6/pxm2LxeL/PmzeOmm276zQGLx+Ohtrb2v5pbBgQE8PLLL/vMp+u3sG/fPozGMw6oLwn69+9PZGQk999/P0eOHOHbb7/l3XffPS+CNbfbzdSpU5k2bRpxcXGnn39Zk4hebmfV0HeJD2hmw9p+LDOGkbxiFmMO3M2JunC+OdQLj1dCXu2/Bmv7HG6GqOgI1s4zRFFEoVAwZswYX0u5ZEjvfz8mr5p9tgT+0TSAIIkWnUTFvJCdzPavpMLoz+OhPwKwy5pMD4WKQ2vTGaAtoMAZwufD3iVC0Qq038yerb6SafoqrtBW0OTRsa6xO6FSDSddVm7UN1Pr8aPUFcSStiiu09Uz27+SIIWZtdVdeSnhK/5hSmK2fyUNHgNyQUaWw8Xy+B2M1uaxcfWnRHSpI+nLu1hQPoEYeRMfZ36IwyPDX2fD4ZSxuzyRK2JyuC7uEDfF7MfhldHq1BCsNDMjeg9BchPJ/k1UWALYm5vEAH0hNW0GZBIvoWozeyvifTYXHZx7RFH8hjPsIwrneNPBgQMHGDt2LG+//TaCIFBYWMi6deuw2WxERUUxYcIE/P398Xq9VFdXU1RURHFxMcXFxeTl5QHtdURXX331WdPUge/xeDzccccdbN++nby8PJKSkujfv7+vZQGwePFi3njjDZ555pkLYlNLB7+fxsZG/v73v/Pqq6/6WsolQVr/B7j6h3soGvkhLtHNN5Yg7KKcYeoS2rwyuirUPFjbi1fDD7PVJkUrcbDd3IUAmYV3Cwbj2hvI0zP/wd/zrsRsU3Jf+nZm+BXxfEMmuxqSyAyqIEVdx+qaHhgUDnr7l5JrjmBJzDa+s/qTY4/CI0rwk1mpcARxpDmKzMAKrg3IQiu4MHkVeBBY39aDSnsAaqmTkf6naHbruMOvhs5L7yZ6cAUDg0uQCx5KbEEM988jXNZKhSuIV06MRqt2oJa76BNcTrXNHz+5jTq7Hn+FjR+Lk0iLrEUnd+IWJbQ6VKQYGhhZfGne385o00FsjBj5yP1/6Dql9z7ky00Hk372UAL0BoaJojjgTMaf0yXRrVu3otVqeeeddzh58iRer5d77rmHTp06sWHDBubNm0d0dDRlZWUoFAra2tr+ZXxwcDB1dXXnUvJZZ9OmTURHR592ze+g3bg0NTWV/fv3c8899/hazr+watUqRo0a1RGsXQIEBwfz4osv+lrGJcUL/b7mleYk7g3IJVzWhkVU0OBV8llzf4YbcgmQWZlRPgS7R87+o8nMHf49CsHNWxkr6NrLAcDkXqt4sLYXzW4dLzf1wIOEt1NX8K2pG8X2UEaH5vJQYBGP1nXnw9hdzKocSpjSyNMhJznkdCLFyypnX1TSds/EWrcBf4mV16sv55Go79hWm8ozKWu4TO3i1rLL8IoC25o789S0lVQ6A9nVlIxBYSdQbsXiVQKwqzWVwbHFJKgbkQseohXNtKo1FNtDCVGYONwaw+DEIiJUbeSZwrC65bTa1dTI/Xw5HR38+fy895gbKAUmnOngcxqwzZ49m8LCQuLi4nj55Zfp1asXEkn7quwNN9xAfn4+2dnZfPHFF6xfv55+/foxcuRI0tLSUCqVF8VNMyEh4Tfvir3YaWxsJD8/n8svv9zXUv6DU6dOMWnSpF//wQ4ueL799ltGjBjRYbtzjkiVKUiVNSHVtbDaEkiOLQqVxEVPdSm9tKXsMnXijsBdpATrSNo6g2GZOdS5DNwbUMyokxN5LHE9XgRGq9300pbiRcJRSyzVNn92KVOYpD9KtjOCIaoaFrVk8ELYMWZX9eP64Pa2ckvbIhiiKQQgQdnAguQD3Fx8NUdbo9HIXCgkbo7aY5kccwStxMHLzWn09SthyfKxvDTjQ96vHkqspoXjRdH4h5jZ3esTDjvkrGjuz8zQXfhLbNyTP41Go45QPxPDQgspswTiRSBcbSSnORx1sJNYTTPNTi0Ot6xjl+iZ4HsvtT/C+6Io7v75E4IgDALqz2Twn1rD5nA4sFqtHD58mGXLlnHnnXeSk5NDdnY2y5cv5/333ycrKwuHo/2bUmpqKqNHj2b16tW8+uqrPPjgg/To0QOVSnVRBGvQ3rw+KCjI1zLOK0pLS7HZbOzc+Zs7dfypeDwempubCQ7u2Ll1seP1enE6nSgUCl9LuWSQCzK+t+mo8Vioc/nxeHAubW41Bc5w6tx+KAUXckGkymNidKdc7grbTpXNn6fqu5Hq18BmYwYeJCw3BaKVODhqiaXSGoDVLWeGoZSTzjBS5fXMr7oSq7d9XgcYiuintPNlcx96qcuYfvJW/CUiJY4QdBIVq5O/J1hl4aGojfjJbUzQFZBvCafBYyBa3sx43UmscW56KBu4KWIvDq+MdSPf5NbE/fR+536OO2KQIrKsfgibLV0YFlrI7Z13Myy0kECZBbcoIVLVRr1NT4jGTLKmnlNt4RxvjCBMYyanKexXfmsdXOC8eYbP/Vf+tIDtoYceQq/XYzAYGDt2LG+++SYymYxBgwbh5+dHcXEx77//PhMmTECv15OQkMBbb72FTqdDr9fzzjvvnHc38LPBAw888B9LvZc6mZmZTJ48mbvvvpv6+jP6onFO8Hg8SCSS/7rRpYOLC7fbzaRJkzqya+eIzAH38WBtL96rGsabjYOpcfpzZd5VLD/aD7NHhUuUcn3AATwIPFQ+AbXUyRZTBnPCtwKwJLo9WPqisQ9BMjN6iZ1guZlnY9bwQMz3vN7SGakgYhHlDPPPo96p57jTxjhtOf8wxvN9YRqZCgX3Jm3j/ZberDzSB4CFLQl01VeysqUfcsFLliOYyUFZhEiN7DUl0+RVUjJuKV8au7Kyrh/XBh3gpeorUEpc/DjrVb66azQbCrpgdSvY2pDGcH0OADavgs9KezM2JBujW0W/wFK8osCX5b2obvPDZFIjEbyYTGqfzUkHfx6CIAwQBOFBIEQQhHk/O/4KSM/0PH/Kp9OpU6dYunQpixYtIigo6FezY06nk/z8fF5++WU+/vhjHn74YRYsWEBZWRnDhv1XY+ALltdee63jpvBvlJWVsXHjRv72t7+dV9kshUJBeHg41dXVp81yO7g4eeaZZ5g1axbR0dG+lnJJECiR4RUFVFI3ow0nAAiQW/gweRXfmDsxy6+KrTY9Cysu54OkLzju9OetypEEyswUW4M57rRxlf8xUuQt7LbFYfKqWXZ8IH8Zno9cMFKraKLAEUarTMON+mpqXP7oJW6uy5uGTu7kyuT2QGpDUzfujdiCpm/7Kk93VTkj1R4WtYjM8i8g3+UmTgZ9dt9F3pBPWNoWx/V7xuBxSPl8+BL6KOXk+RXTVVnBe63dWPjJO9z41jw0CU5GBZ3CKiqpdfrTXVNGmV8geomdwrZglBI3do+MPiHlaGUOtlalYvfI6Z9QAuUpPpuXDv40FICO9pjr59YeRmDKmZ7kT4kcli9fTteuXc/45qtQKMjIyOCFF15gw4YNrF69mhtvvJGRI0f+GfJ8Sn19PVVVVfTp08fXUs45ZrOZ+vp6EhMTAbBYLNTV1bF48WKefPJJHnzwQR8r/E8SExOprKzsCNgucp544gmUSqWvZVwylLnb27J9Y9FyzB7LVboTHBEl3FowlU1p61nUEs/cgFJ2B5aywZLETEMdnujthEjNTNHnEirV0RU3i1s7M0Gfw4q2Hvyl13fstntxYeB6XQvLTQITtNXIBRX1Tj27bXHcE7udYmco9U4DLtHN8vgdzK4ahFzwskxqJVBq5qSrgT0tSZg8KjRSByfNkcxM30O9x8w+YyIDE4qJ1zThoT0RMUybT7pcQ4r8KHZRZOf9r/JJWxcCZWbm7prG7D47WFnTlyhNG05Ryqz4nVi9SqqsfsSpG2lxaekeUs2JpgjuSdwO5edfLe/5hHABLnj81M1gpyAIH4miWPZ7z3PWl0S///573nrrLSZOnHj6Oa/XS01NDQUFBb84ViaTcfXVV/PQQw9x9dVXo9Vqz7Y8n+N2uy+4ZvVni2+//ZYFCxbw9ttvY7VaWbBgAUuWLGHAgAE88MADvpb3X0lMTDyvlmk7OLtYrVbeeustpNIzXpXo4A+yOGgfDxVPYZcdVjdmEiIzIRdErtQfZ1Paeo467cwNKAVAJ7Vzja6EW8uG8reCcSTK3CxsHARAgcvMLP9y3mwcTLKyFgkiz5aN49XyMTzT2Jkb9c0U/uSlbpDZ6aGqZIymmXxLOD205UiF9ttforqRIIWZl0+MRiqIJMqk/CV6PdvrU6iwBzLEr4Cb/I7Q4JVwffB+il7tzNMhJ+mvbM93WL1ylrRF4ULkgbJJfNDalYGaAt6eM5X0hCpG6U6ikHoYG3iMLS3pBMnMxCsa8CKwq6k9m9Zg15Hk38gH5YPP7WR0cK6xCoLwsiAIGwRB2PbP40wHn/WAbd68edxyyy34+/uzceNG/vrXvzJ9+nQeeOAB3nvvvbN9uQuO2NhYhg8ffknWReXm5vLBBx9gs9mYPXs2GRkZlJSUsHLlytO7hc83YmJiaGlp8bWMDv4kVCoVAwYM6ChTOIcMDilmUdIq5p6cysdxP/BG4WXESlU0ezTMKB/CFnM6NtHBopZ49BI7ARIN8ZomtnRdwZzyqwhVGHmqIZ0mr4qtNgV3BO2m2BnKjfpq5sV+z6iQXJ4MzmFudR9erLqK7gemYfYoUeDlhcZeDPHLY01DT74yBwAgEbwEy0w8nLGZZ/Ou4uWmHmgFN1u7rKO3roT+6hIerRzHTksqFa4gGq+z8mJzMgvquwGQqZSyvy2RCrealYnfkWMJ569lV7Ptw/fx3OfP1P13Eq1u5aAlgQUR3/GDKY39lmTS/Wq5KWIvO+pSCFOZiFG30D2wypdTc2EgCn/s8C3LgVwgAXiadluPrDMd/Ifukh6PhwMHDjB48GDCwsJ45513UKlULF++nPvuu4/S0lJ69+7NiBEj0Ol0553Hlq9Yvnw527dv97WMc45EIkEul7N7924OHDjAhg0bfC3pV0lJSeHkyZNYrVZfS+ngLLNnzx5KS0vJzMz0tZRLhh4D5tJbW8IuazK3J+3mqNPO4PBi6r025IKbdF01vTXFqAUlflIrJq+KR+p68nTISa7OnUwnXR2T9Nlc55+Fv8RBgSMcq1fKrqYUrsi5Bg8SAmVm5lT3JUNbydTQ/TyfsZrVx3pyV/4N7GuK5/Fdk3gxZg0bmrtxyOmkyhGA1aukzBHMXUm7SFA28HLd5dxYOhyF4GHqkdt5NPI7xuhyMXnU9IspY35gITMC9gCQsvU25BIP/ZUyuu2dTqkpkLGhxwGYsmo7rmYV4co2ohXN1Hs07G+MwyVKmRqwnxHqOl5O/YIScyAVtgC84vn5xbWDs0aQKIofAK6fGr/PBM7YJf53vzuysrKIj4/nqquuIiYmhtmzZ/Poo48yYsQIrr/+eoYNG8bBgwfZtWsXOp2O5557rqMO6Ceuvvrqi24zxZmQnp7Ohg0bkMlkpKenXxBZjRtuuIFBgwbxt7/9DbPZ7Gs5HZxF5HJ5h43HOeTH5K9Jkuk4Zo1FL7UDEC51M9iQz3O1o9qzVy4dw1UiN5cNY1n5QN7cPYo5QT+Q67KwqtMqRupOctwZxsLa0QRKROIUjZx0RrI6+XtcXiknbDGoBBdX+mfjEqU8l38V1a4AMlPKuCVmHw/FbaJXpzIWNw2mj6GEKKmTJFU9X5T1ZJT+JF2UVcgFD0mael6KWYdE8PJ8xmqybPEkyXRYvQrUUhcJ629nduH1JG+fTtHID3kveg8LWxL4sf+7bO2yjgJbGC7RzRRdKUEHpSw7MQC91E6pK5h+wWV005TzStUVVHtAikhmYAURKiORqo5s/kWO66c/awRBGCsIQk/gjHc6/a6A7f3332fUqFGMGzeOd955h0mTJtGlSxfuueceNm/ezJEjRwgLC+P555/nxRdfZMqUKYSFdfjL/BO9Xs/+/fsviGb1Z5OePXuyefPmC6qXqkQi4bPPPqNbt258/vnnvpbTwVnAZrOxZ88eevfu3bEr9BxRmP4hrS4NXrwkq+oYp6lhb1sSJ51+pCtqWRy1n62tXTjWGsVyUyCzwrbzQ8Y3DO6az93F15Em13LCqWFm1nRO2SNRStyESnXEy5updAZS6zHzQ8Y33BNwCrsoJ0rWyrq6bkTqjJi8Km6L+IE6t4FHTk5mfMgxopQtxCkauaf0GmIUzcT6taKROGny6FhSNpT5gYV82NIHheBhm7ELXVWVDMqehFzw0FlbAwL0CSrH29oe8HvxMi+ghGKXgiqPia7aSuSCjOcb+jN49gEKhn2MVuLgg/LBHL2xE0ctcTwTvZY91iRerxlNsqoOjyhwtC3WxzN1niOehcO3PCsIgh/wIPAQ8D5wxgXcvzlga2trY+7cuaezaT+nZ8+eLFiwgHnz5jF27FhCQ0N/6+kvGQoKCjCZTL6WcU5JTEwkNTWVO++809dSfhMSiYQbbriByspKX0vp4CxgMpmoquqoFTrXfBi7CwkSypxB/MOUhFrqop/Swt+qxuIS3Qz3z2VC+DE+qhzIIJWERS3xALyR+AUAQ1TQI6qKMJmRGpsfO+wCq1r7sKspmeNOfzbaFJS53bxTPIxN5gy6+NXir7DRVVXBDmNneqtLWJC2Ea3EwWhtDjn2KGZG7OKAOZHBAYX8aElltzmVayKP8VRDOsN0udS6/IhQtPG9KYMxkTn01hQzwy+HN4Z/xpZFA0npXMWsygE83dD19Ou8v+wa+qlLAFh1uA8Or4wddoE0eT33xW+l+CkVX34zhOdrruSV7NG4vVJ6qcrYWpFK6+yOxMbFjCiK34qi2CaK4glRFC8TRTFTFMW1Zzr+Nwdsn332GSkpKSQnJ//WoR38jFtvvZWAgABfyzjn3HbbbWzfvp0bbrjhgqoLS01NpaGhwdcyOvgDiKLIjh07CAwM5Nprr71ouqdcCJjdKiYXjQZgfmAhu1uTeTjse55t6Mdz0evYatcQJDXh8MrpFlDNtJIRSAQvaqmLJJnu9Hk+T9zKyydHIxFE9lpS6KstYnHilyyrHcrdW29FJXi5M2EXZreK7JZIRgWe4q3KkcgFDwNVVjQSB60eDbnOUErt7R1nrjBkk22OYm5AKXLBw5aGNFbkZGL0qlBJXGyuTyNDXYlS4qKL3ESD18N4jRWZXWRT2nqWRO/l6ZCT7HO4yXeG8XrcatLlGorcZqKim/CKEtLkJr429SBEaiIyoI2s21+jj6GErEHv8nniVvZYk/mm51KeXfOxT+bnguICzLAJgnCHIAgpP/1dEAThQ0EQ2gRByP5pWfSMOKOAze12Y7fbKSws5PHHH+fKK6/8vbo7+InPP/+cnJwcX8s45+h0Oq688krWrFlDbm6ur+WcMX5+fthsNl/L6OAP4Ha7qaysvORKEc4H0tTVzIrcTovXysKWBCYHH+RLYy8G6QvYaEnjCrWT4So72eYoumoqGRhQyL3+5bwXvef0OaaVtK/opIXW81XSZlJVNRyxxlPrUXJ7+E7eH7mMJq+SZw9exf3B+5kevYdmtw6JIJKmrubDtiTWNPfC5FWR54igyurPIWsCxa5QpofsZkzuWKIVzVwddow7M3azpHI4H5YP5PboH3n4yGQ6KWto9gpcvvpBmrwWwu4u4ZnGzrR4rRxyOrlpzT0UOcKIkurJcrh4o769UfzogBOUulXcF3CSU44oRofncsIlY7Z/JXUeD880dma2fyVPVI3jydIz7gPewYXFXNp3hAJMA7oBicA84I0zPcmvBmx79+4lNTWV3r17M2vWLIYOHUqvXr1+h94Ofs6AAQOIjIz0tYxzjtVqZfXq1WzZsuWCeh/t2bOHuLg4X8vo4Hdy4MABzGYzN910EyqVytdyLimuHjyfcFkbdlFBgETDVboTbGzphlLiYn1zd1ZVZvL3plTkgoxkTQPTDfV4RQkjTl59+hxZDhfJ2nY/xK+SNlPvMXONto0weRuZP20csYtyXqi8ivcHfkyWI4BvG3vQ5lEzIjiXbxp6ESIzMcQvH3+plTG6E9wVtQOrR8Hahh5oJE4iNUayTAnk2iLQSe0sSfqC55O/ppeqiisTT6GVOJh56hbuHLkVCQIZhmqeDM7hlsJJZCoUfD7xTdZXpAMw+9QNLIrMYne3r9ne1hm54OXB6qEcs8TQW1NMiNTOK81JrDN3ZV7gEXbYBd6L/Z6JYUfP+fxcaAjiHzt8hFsUxX9uOBgHfCKKYpMoiluAMzac/dWA7YknniAzM5Pw8HBqa2v/xRC3g9+PTqfDYDD4WsY5Jycnh6SkJAYMGOBrKb+JXbt2dZQBXMDU19d3ZEh9xA0lV/BG5SjWNfdgVuUAvjV1447QncwLKOHh8M3cF78Vq6c96PpLUD7PNHbmpCWSNP86oN0gt49Szt9CT/CpKZiU5bN4ru4y3muL4Q6/Gv7elIpW4uCz+v5Eq1t4u3okdq+cVF0dflIbI7S5JGibyLNHoBJcaCRO7i+YikuUoZS4idU0k2VL4MWo7+hvKGJvXQJBUjO5Tn+6yF2sautFpS2AU/Zo/FQ2VIKbFcZU/hZ6grTdN/N8/GoATF4lPUOqmFE+hK+6LmPgsckkfXkXu6sTyJAL7CxPZsOJroxWu3mj/jJWlmbSXVVOjx2zCJFaUAtKbjGU+2yeOvhT8QqCECEIggoYCWz52b+dcQPZX/VVKCoqYtasWafbCXXwx/F4PDz55JMsWrToknNYLyoqomfPM16yP284fPgwQ4YM8bWMDn4jZrOZqqoqxo0b52splywnasNRyDyMC80my5RAsS2YYVoBl+im2OXPRK2Fh9YPQj7Cw1BdLmMNx6hQB7Cirj8Dj01mT/ev6HVoKp93+4BnDk0nuXc5iyKzeLSuO4u8cv4SlM9Gm4ZMvzKOm6Lp7V/KEHU94bI2ch2R3Jt/PW5RQoyulePGKHr5lxGhMbGuuQcNdh1ur4QRhlOESnVEylsI0Zg5YYum0u7PZ8AzkRspswXx+u7RPDz4O76rz6B0fQL97lnEsYHLUApqkrbMID6yEadHxnfpK9BItCxM+5wtURl8X5tGo9fOS92/4oAliQX13TjRGs7enp/xg13J4eHvYJBoeLM1lnBZ29l3s7/Y8P1Oz9/Dk8BB2hu9rxVF8SSAIAjDgOIzPckvvjdEUaSqquqSXLr7M5FKpZdsO5zi4uILLrsG7YFmbGzHlvsLjdraWo4dO+ZrGZcsJenLyBn4D3b3/hB/qZVhfrk8Gb6VJ0snMLN8JDGyNgDGDj7MbQEHGK4SybIlMFFroYdfBXu6f8UuO0Tp28h3BfNyny/4e8LXjM2/kusD9hOtaGL4yQlcoXYyL6CEeruOeqeBLEcAHzUMQSVxEaCycVfcDxyujuayoFz6aYrQyBz0NxShkrq5L2YL65p7kvjVXSytHoZM4iXfHEaIwszogFN8aezK9JBdPDF0LXUuP0o3JNB78gmCJA4OOto/w1cNfZeNnVezq+tqCt1Q4rbSSe5ksC6Py8NzKXVp6a9qYkHwUR4N3k+KoZF8t5O9lhTqPB6OOu28seEqEhUdG5suRkRR/BaIAzqLonjHz/7pIDD1TM/zixk2l8vVYS75J1BaWkpDQ8Ml1wDe6/VSWFh4wZkG19fXYzKZOmxqLjCKi4tJSkrqWMr2If00RWy2yeiicDFQXYlekJHnUvJdpw0cddo56QxnsyWAO0N2IkdgnVWDVuJgaVsEM/wPc8ipIEbmYGzYcfwlVt6vH4bTK2VwUBGH7XG8cHQMbrucR4O7Y/MoeDT2O360pHKF2skxTQPrm7phdimodAUyJLY9kTE/ZzKhWjMHJfGk66sxetUM8itg4lWHWNvck3ClkUHafF4qu4JMbSkmj4pF1ZejkrowulQkji2mzBSAXZRw++FbyBn4D7aYu5AZWEiPrOvpGVZFrU1PmqEOryhhUWQW9R4rrzYOxC1KuSNwF910FaTLNdxdm8ZJUyQrErZx5PrX0UlUpyvTO/gfXJgZNkRRdAMt//bcb2os/osZNoVCQUxMDAcPHvwd8jr4X3i9Xrxer69lnHNKSkowGAykpKT4WspvoqqqCrlcjsXym/5vdeBD3G43K1eu7OhO4UM2J3xLT4WdLooWvjalEyxRMaPkavoo5UwoGEOV259uihru9S/nq7ZMpuTchNGjIlFez4aGruS69LhECRVuPX3UJaTIrcwN30ymXxlWjwK54OHOjN30TConxxjO3SE7+N6Ywbb6VNZbVRxoSaDMFMDt0T9idquIVTWzuzWZG+IPUtQYTJEpmJOmSBYWjWZVTW8OWJLopKkjQGbhmD2W0aG5OEUpXgRuDf+RnXkpZFdEIZN42Za+lkiphKz+7/NgbS9m+B1lxMmrub/TNpI0DZQ2BXKiNYKeujKOOu1UeBS4RSmhciO7bEn00xRz3Gnjh4xvWBS7lkUt8XTfdjefmoJ9PW0dnMf8ag3bggULmD17Ntu2bcNut9PS0kJgYCCdO3emW7dupKamnreNu89XEhMTL8mawLy8PPr27etrGb+Znj17MmnSJF5//XUWLFhwSS5lX0hYrVZkMhkLFizwtZRLlm/jNnJr8D4+NKbS5tagkTp4vrEH7yesIcsh58rQExQ6wnGJUl6rz2BR5G72NiVwo74ZkDAo+fufztR+iyp3O7ijeApLE78iRGZivO449xVfR6q+geFBeYzW5pAm16KUuGm0aDlhjyZa3YpM8FLhCmR3QyJvpq7k7tobcHpkdAqtp9pk4KqwkxS39qaHfyUjdSepdgegkrj4pHYggwMKOWmLJlBm4bWy0UjlXhLD26/396ZUOquqCJe1saG4C9U2f0LUFtY1dGd25DbWqTPo4ldHuLwVDxKeLR+H0akkXGMiXGWkzBHMlppOPJe6Gos3mLkBpXwV3sLGpgwm+WzWzn98vNPzdyMIwiBRFHcLgqAURdHxe8/zi5FWQUEBhYWFTJ8+nZaWFmw2G35+foSHh6NQKFi2bBmzZs1i6dKlHDt27H/6G3m9XkpLSzl06BCieAH+ts8yr732GoWFhb6Wcc6pqKige/fuvpbxu/jggw+QSqVs3brV11I6+BV27tzJunXrfC3jkuVopxX0MpRR4AgnXNZGZ3UVKco6BugKmFk8EY3ExXBNPlXOADxIGBtwjENO6OJXyzONnU+fp8+RawFYaQ7g1foR3BSxj522KFyilCVNQ/kweRUPhm7jsDGOh0smY/bamRGQxeT4YwRKLVzmd4pUXR1mj4pBIcU0ezTMS9gMQJtDRc+QKlZXd2dibDYeJDxfPpYyZzAFjjBUUhd51jD2NCSwoSYdldTNtV0OMzXyIIFSM0uzhtBDWYvJq2Je+lY0MgcqqQuZ4CXPEcHlUblsKUtlc1sGWbYE7B4ZSYYmotRt5BvbSysWJG8g1xGJyatmpTmATemfM8j/0rsvXCL802tt7x85yS9m2BQKBXv37kUmk9GrVy90Oh1KpZIDBw5w+PBhbr75ZsaPH8/GjRv56quvWLRoEb169SI4OBiJRIJEIqG6uprs7OzT/SPnzZtH//5n3Jz+omT69OlotWdsvXLRUF1dTXp6uq9l/C5kMhnz58/nscce4/LLL/e1nA7+B16vlyuuuOKSLDk4X8hui+KV+H2kyHV8ZAxlZ2snPozdxeiccQQqbYzfMYevhy1mZuCPPFB8LTq5k1djVzM9cDddFWpeaU7iocAi9vRYwdTiMUwJPYhW5iBFUUeczMudpVdT1BLE3roErog6xYiAHE5ao3ixsTd/Cz1BtKKZ4ZoiClwB7G5IJNWvAaXEzfLGAYQpjYwJPsE+YxLRqhYaHDpOmCJptGuxuhSYPCo+PTiATonVKDRuro8+yNamzpz6LoU192ziifoM6pwGiq/4gE9NCdysb2RkSW9ida0M8C8iU1XKNktnCi2hjIrLRylxc8ISxdSIg9S4/LF6FFSZ/EjWN/Be1TDqLHr29fiSW8uG8l1TVyrM/tzj6wk83xEvyA4lLkEQPgSiBEH4D6NcURTvO5OT/GLAZjAY/mvfx1GjRlFeXs769ev54IMPGDZsGC+88AJdunRh5cqV5ObmUlNTQ11dHRKJBEEQiImJYcqUKRfkktjZxOVy0djYeEm2pdLr9TQ1Nflaxu/m2muv5b777qOkpISEhARfy+ng33C5XDz22GP89a9/RaPR+FrOJYtXFFjaPITt1ckMDi+msC2YhS0JXB2RjcMrx50oweRVESk3Y5A70MicNHvltHrVgMhDgUUAyAUZj0R/x3pjd8qsgZRqg1hS340rg48zM7GObyxaYuQttHrU7HUn4S+38ZExlDq3gd22OPqry1mYsoqPmwZxqCkGURS4P20LcTIZLx2/nAczSvBXBOH2SjEoHERqjGyq6sxfBq5nY2MGSomb7U1phChNKFvgqYZ0dtYnU93gT23E92gkeq4tHsWjCd/xWcMA/KVW6j16bvI7wuHWONRSJxW2ADpp69pbXNWmEaK28Gb6CqJkFuaapzA8ooDJRaOptei5OW4/amksNPt2/jr4UxgHjAJGAId+70l+tYbtfxEbG8vdd9/NtGnT2LVrF/feey/Nzc3Y7XbUajV+fn4EBATg5+fH6NGj6devX0etG2A0Glm/fj3333+/r6Wcc0JCQsjPz/e1jN+NVCpl4sSJ7N69uyNgOw+Ry+U8+uijHcGaD+kz4D62148kVG7k04yP0Ahe/uIYz73+BQw+ej06pYPXk1exxtiTIcG5xGmbGajL59PmgfTXFTGnuhMzgn8kU6FgTnVfBhsK6KYuRyNxopK4cIkSWj0aPjUFU+fyY4S6kburhzA8IA9/aXtv4imGo6wxdWVWwfUMCymk2ubPxKhjhMna+EvZNWhkTnIHfcqY3LE4PDJWpi3n9cZBABhC7fzQmgrACxE7+Nocx3BNESO6dKfOYSDFr4FugdXsskWRZUlkZFAOVa5AjC4VTx4ej1rlwisK3JB8kHxLGF5RoMQWxO0BB7HG7GddfXc+bRyEUuLmoZhNBEqtrJb2IkcajkJwE6Y0+mzuLhguwKoqURQbgZWCIOSIovi7fYZ+d8D2T/z9/Rk/fjzjxo2jra0NrVaLXC7/o6e9aAkKCrrkgrXq6mrCwsKIj4+/4Hcc33zzzUyZMoUbb7yxo3n4ecTOnTtxu92MHDnS11IuaY47QygzB/J0+HY+bO3GQ4FFzArfwaN1fbE4FEyMzeaF6itZFreZky4XL4Ud4dnGNJJU9WxuTae/oYhny8eR6V/OMEMehY4w5IKHhwKLOOq0o5a6uNXvBP9oS2eC/hgGiY57I7Zwx9FbmJiQTbDczKvPTuO2v6xBI3NRaQ/g9oidPJU/gWazhlvT9uP3U2BXkBvF5b2P815LH3poyzlqiUUm8dBFV8MneX0xJKk5bo1meVVf7hq+jSaXnihFC9/WZjA18ABbKlMJ0UYyKLiYktZAVvV/D7soY4spgy11nbC75fQMriRIbuEfbd3JsYQzJuQkDq+cbY2dMPqr8JfY6K0tJkzextbmznhFCd18PIcd/Kk0CYKwGhhEe+j5IzBXFMXKMxl81lJegiDg7+/fEaz9ChaLhWeffRan0+lrKeeMZ599lgceeICqqir27NlDbW2tryX9bgYNGoREIqGsrMzXUjr4GRkZGXTp0sXXMi55PqodTKjaRJBEy9yAPDbbZFS5AwhVGFnT+z3KbEGUmwK4s3wkh+2xtHit/OOby1BJXIz2P8k+YxIzI39kqt9Bvm3qzl+C8vEgYPba6aFQEaVs5dXGAVyjP85WaydcopuPGoawtfd7LAg5RLkjkMee/IRtzZ1ZnPgl0aoWvmjqy6SYo9zeeQ+dVVW8sn8Mc6r70rNrCV4ENBInq+t7sbs+kUNNMbS4taSGNDA+/wpmBv1IUVkY9wfk8LfQAxxoi2dy5BH2W5MYElGMTOJld2MiE+OyCZG6kCKikTro7F9H/9BSjjRG82jwYSLkLVRa/Glxa7lKd4JhwfkoBDe7bcnYvXJuMpTS16+UZscZdynq4MLkQ2AtEAlEAet+eu6M+MWAzWQy/SFlHfwnWq2WG2+8EYVCgcfj8bWcc0JgYCDXXXcdMpmMfv360dBw4bp5SyQSUlJSqKqq8rWUDgCn08mnn36KwWAgIiLC13IueSx3BdBo1wHtNWilzhCu0zXhFSVES5WEKY1IJV4+jvuBRHk9GkFOytASBqqLOWGLZnboNsZrrARLJdwdvo0F9d1weOWUuNvXwe4PPI5XFDjlCiJTVcrfm7ryWtQOPmnrzstNPVBK3Bg9KqosBu4vu4YtdZ1ocmhZXdmdZGUt37dmMKxzPgXGEKLVrUgQeTd7CA9EbWJQaDG3xOwjXNFKhNrIqYoIph66HaXBwfTSMay2hBKnaebdgsGYPCp66sqwu2U4PDJSVbX8vW4kC6vHcMwYg0FmxysKiKJAjx/voM2jIcXQwIcn+3N/ybWEydo4bo9hXV03jljj+docQbNby4zoPb6cvguCC7T5+z8JFUXxQ1EU3T8dHwEhZzr4FwO25uZmli5d+kcFdvBvJCQkUF9fz5NPPnnR25y0tbVRXV3NfffdxxdffMGuXbvo2rWrr2X9IUaOHMmRI0d8LaODn4iJiUEm+8PVHR38QT6L3MHz6z/F6f1/n8I9bcm82JSGn9SKS/TQWV3No4nf4RBdbDWns7A5nS9T1pEm1/J0yEl2WtIAeKhqNMftMVjcSj7ZNhS54GVW5QA+N8VwoDGOVo+WPko5g7T5qAUlK0szuS3gAHcG7iZNWcv10Qe5Pmw/10UdYnbkNkZF5FHhCuJoYzTpumoGBRdj88oJUZh4pOcmvmnN5EhLNNtb0pikz+a2kB8ICLAgk3pRKVwMDCjE6lWwqy6JoZHtS5hLiodiUDhoMmv5qj4Ti1vJkIB8shsiyDGGE6NqpkdwJYIg4ie10klTy7TOhyhrDmBtQ08q7IFMDj9Mrikchyin1aUh2xrjq+nr4NzQIAjCTYIgSH86bgLOeCfeLwZsXbt25dixY5ekZ9ifTWhoKPPnzwfaW1VdrHz77bdcddVVJCUl+VrKWcHr9aLVatm/f7+vpVzy5OXlUV9fz/DhwzvqCX1MfL+HsbrlqAQPwSoLLza3twP7MHYX31Zl8GVVL1ZborF6FbhEGTPLRjMrIIuemlLmVg2l3mPm2uJRzA0oZXFrNCebIjB5VfwlbDv/mPA2pe4ABvkV0ENVzpupK/mirjcL6rvxSf0gvjD7MTt5J6ecAUiABwuuxS7K2dTSlU7KGt6oHEWNww+HV85VUSdpc6uZFZCFxa2gm6YCgK3VqaQYGlBLXSxuGkqrV81Tad8yLekg96bu4KQ5ik6KGgaEllLv0DNam0uQxoLbK2FQVAkhShM99BWcsEQxOiafeqsOleBCLnjJjK7guDWGYlsIXxd3Z3B0CV0NVRxqikEvsTMsMI+tzZ2RCF6SVXU+nMULBPEPHr5lJnAdUAvUAFN+eu6M+MWATSqVcvPNN7Nq1apLqubqXGEwGGhqamLVqlUXrW9UXV3dBdc79Jf44YcfePjhh5kyZYqvpVzyNDQ00Nzc4YFwrtmauJYvo7fi6vkKhekf8pwmG5coocGio8mj5tO4ndQ6/Lim8HK+MPuhkrm4KWY/KYpaBqqLOWWPJNOvjDuKJ3Pv/htweGVssCRSYfRnavFImt06OgfWcZXuBLcWTOWoPQ6XKCNRXk+czMv9hdfxVdJm5IKH3n6l5Ngj6aqsJFJmJMsRSYK+mSpHAMEKM9XuAN5M+JIEdSP1LgNyiZtSWxAVHgVR6jYkgpc2j4Z+YWWUmIOQCR5C5UY+qR/Ew4cns62+Ey8cHcP2khSOO2JweGRcFZzNDmsKN0fu47aoXSglbq4OPEK2OYoKSwAV1gB2d/uaL6t68WT4DmLULRxpiSZc2cbXvd6jxmag3B6Iya6kl6qK3a3JVFn8CJBbfT21HfzJiKJYLori1aIohoiiGCqK4kRRFM+4IFr4pSW53r17izt27GDChAmUlpYya9Ys4uPjz4buDv4No9HIwYMHGTFihK+lnFU+/PBDunbtyosvvuhrKWcFs9mMXq/n8ccfp1u3jv1cvqCxsZGSkhL69OnjaymXFCXpyzhmimZsUDYravoSr21mW0UKA6JKeTbie24rav8S0+ZUAVDfqicptBGLS8GO9DXYRAfFbg/pcg2LWuIBiJS3IBfcvFE6EotTQZtVzU2dsng8OJdDTifbzZ2ZG5DHKnModW4/sloTSNbWEyC3oJE4maov4KbCyTwa+x3bzZ2pdRgAMMjsZGpLSVQ0YPIqeaJgIjWNfnSPrSJ7fxIzx2yjza2mxu6HXm7nhfAfeLOlGz01pWwzpnOwMYa+wWVopE7a3GqC5WZOmSNQSNxUW/2YE7ONClcQH5UMYEBYCUqJG+9P+Y88YyiBSitJmgayWuLIrQ2jR1QVQUozeW2heEQJDUYdMzrtY2tDJ7r7VyEXPBxsicXiUjC35dJ8X1933XWHRFHs/Us/o4qKEWPvmfeHrlPw2Lxfvc75yi9m2FwuFx999BFxcXE0Njayc+fOc6XrksRoNF50NW1RUVHk5OT4WsZZY/fu3QD/sw1bB38+FouF1tZWX8u4JMltDmVTcwZXhp7gRGs496Tt5L3oPTR7BYYFF3BN+BHWdPmMqyOPkzv4UxbEridEbWFy0WjyXCLpcg3LTYHMDShlTXU3hqmraHAbUMrcZATXIJV4uSfwMBMKxrDHmsyd/id4oGYgqYo6uqvK6e9fjEQQOWKMZZZfFUtaenB5SA7hUjM5pgj66kvorK0hVGFkjymZw7Y4Vjb255GkTTzV+1taHSoWX/M+G6rT8ZPZ6G6ooJOmlhcbe1NhD+Cp3KsBkEs92DwKThojaXWp+aK0J15R4K3obSTpG/lH3UCGa/K5P3krJ1ojWHW0Nz/WJnK8NYJkfQNOr5Tjxij8FTau63QYyU/V7jq5E6XUzes9Pue4qb0DwpaqTkwP3Ie/ws6o8DxfTm8H5zm/GLAdP36cjz/+GIvFwo033sjNN9/8p4opLS3luuuuw263/6nXOR8xGAxMnDiR4uLii2qZx+v1XlQF4Xq9nsjISHr16uVrKZccoiiye/duoqOjGT16tK/lXHKcNEeiVzhYFP09QVIzmUGV1LsM2EQH9xZO5Z0jQ6lz+fFBa1ci5C0sM4Yx58Q0uuhr+CppM53lUm4uG8ZHlQN5pTmJxxLXMyXnJu7wq6GLXy0fxOxmWsoh3mvtRoy2hR1NnTjuVBIgs2IRFZi8KlyilAPNcTwa+R1vtsYSIW9lbkApr9aN5u8xaxihKaLCEUSt058oZSuNbj3puiry7BHcrG/kstACPEh4Ocleuf4AANgWSURBVPULrB4Fm+s7k2OJwOpVMNQvn6nxhximz6HJquWmoD1kFcaxb103Fqavotaq5+WmHuypSWBgQCGTD95Jvj2cWF0Ll3XJZUrsYcLVJuYG72RSyCEUUjfNDg2T/Q/Sw68ciSBidcuRSbwsqb4MiSByyhaFzSFnmyWFSSGHCJV3GOf+Khd2Ddsf4hcDNq1WyyOPPMKUKVO47LLL/tROBa2trTzyyCMAF9UN/reSk5NDdXW1r2WcNWpqai6qrgBpaWkXdHutCxmn00lOTs4lY4dzvjEiIIe+wWUUuKUUO0P4+mR37F45E/MmcV3kIXR6OzsaUuipLuUKbQV+Uivben3ITf77ebM1lt4HbqXu4XhKj0RzT8AppIKX9zotp9ZjRiqI7LAL7G+Op8QawvrD3dHInCyuHcEtAfs4aE3kgCWJy3Q53Bq1F5coQYqXCbpSFtR3I07dxN9qrqDCrWVm4I9015Rxb0AuB1ri6aMuZprfUXbZYUNVOnvNKczLncoVhmzSDHUEyS2sze1GlKyFEdoc9pmTmZm4h1eqrqBfSikhw6r5uH4ww0IL2VaXyrDIQnY0dWJUXD4SRIwuNZ21tfyjuC/RqhaWNA/iiWMTGORfSFf/au7Nm4bLK6O3rpQbow7g9EhxeyUYXSq+OJjJpKRjWL1K3ikbxmFTnK+nuYM/EUEQwgRB+EAQhO9+etxFEITbznT8edMravv27QCn/bouVcaNG3fBNkj/b/Ts2ZMVK1b4WsZZw2azdZhD+4CamhpcLhe33347CoXC13IuOR4TctnYlEFXTQVbzF3wk9q4o8ePDNXn8lDcJmIUTcT6t9A3sIyhKgd/qR7NcHUtI4/MYE7RVG4w5ODI86NitIaCG5agFpQkyoy8XHs5Vx29jTR1NU8UTMSLgMmtJDiqlShVKyMDc0iRt/u6FZlD8Jc4iZK1cNIRSakjBIfo5Tr/A0zzO8TogFN0VTgodQdwhbaCWRUjuCtqB69VjWFhwzCybAlE6duY5n+AHsGVVLsD6K6tIFbZxNL+H7PfmsTqtkxcohSNxIlEEJkTsYWyshAkgpe9TQkMCy1EJ3UA0FdfxLa6VAYEFFHj9GNiXDYSQcQrCsQFNfNB8UDkggd/pQ25xM1xazR1bgMqqZs+AWX0DShhaEZ7q7411d2YEnWYJE29z+b4guHCzrB9BGyi3TgXIB+4/0wH/2LAdrbqdLxeL7m5ub9Yn7VnT7th4KhRo87KNS9kHn744Qu6G8DP6dKlC/X19RdNzVFHwOYbDh06xNGjR30t45LlhrSDdDNUkq6sZorhKGnKak6Yoni19HJUgptvmjJZkvQFAXIL5R4788I2EyTR8mb6Cjalree63Ot5+9qlDLnyGMuMYQAsbR6AUuJmaddPSVHUsavral5K+IpP47exNP1TUtW1xMibMHptVDn8WRK/jqOOCKb/OIPdxhTMbgUPlF+NBwkeBEaoK3ihsR9yPGy2RnNr6I8srR7GjIhdjDCcop+6iLHB2bzTMByDzE6krIWvantR7ghiqzGdYdpcHF4ZGqmTrS2dMbqU7Lcl0b9zMWFKE5PCj3CgOQ6zR0mSrpESRyhhGjPFthD664pYmZ/J9roUvEgIVFoRRYG1ZRkYFHaq7QHYPHLMbhUml5Jqhx87GlK5M2wHB1tiAYhRNHOg5eJZjejgvxIsiuIqwAsgiqIbOOMlg19MZblcrj8m7Se2bt3K0qVLWbRo0f90I//nMmBHMTc899xzF01QkJeXR3x8PP7+/r6WclZoaWlBre5oH3OusFqt1NXVMW7cOF9LuaRJUDbwQfkgTukiCVOZGKbPobu+kisCW9hjTWZJ9F56HrydaEMbNxmO815rJnubE/gw6QuuKZxEtLaNzcauVFn9mBldx6KWeIbqc/l78VV0ivDyndWPV5qDKbUHoZG6GGPIxinK6KVs443mTI41RzGyegZR+ja+H/4muc5gVjX0ZVLIIard/tyTfxX7enzJ86HZDDl+Da93+pw3akYxNLDgJz80D6FSK1JlNTHyJnoojXxhSuWemG08nD2FBzpv5dGiScTrmznRGMGwyCLUUhe7mlI4URXBmJ4nsItyFBIPs4N3MjP3ZqbFZJGqq+NwSwzZshhGx+cxLWgvcsHLdnlnRgbm0EVZRYEzHH+plb3mZALkFq6LOkSbR8M1gYc4Zo9lfFg2JyxRnLBFc7I23NdTfd5zHnQr+CNYBEEI4qdcnyAI/YG2Mx38ixk2iURyVpp1r127FoDa2tr/WX8SHR1NcnIyixcvZtWqVRd8k/DfS3l5ORUVFX9qveC5JDQ0FKPx4imkPXnyJOHhHR+q54rS0tIOk2IfE9rnMUJkRm6J2UeYykQvbSkrG/qhlLgYqSlnW30nxuSOZXbKD6Qa6vlL9RgeD85lQex6NlgSkQgiU0IO8vWp7uQfjGNBfTc21nehk7yF++K38l5bZwKlZgZr85gTsh0JXh46OQWF4ObVxgEAbEtfy95e/+Ca8CN80tIPqeClt18p/lILYzVm/tppLUvaoqj3mFmStpzPmvvT3VDBCG0Opc4Q/KV2St3+vFx5JZ819ucLUyo9VGV83tCPOzv9SJ3Lj2GhhfjLbdyasA+l4CK3NZSbIvbyep/PeadoKDfoCxkTchKlINI3pIxSRwiVdn9itC20uDVkaCt5qmQCUVInh9riOGBM5EdLJ/Jt4XzZ0BujW8XWhjTG6HJRSlwESq10UtYwTJvP1YFHyDWHc1OnLB/Pdgd/MvNo7yWaJAjCbuAT4N4zHfyLGbbY2FiWLl1KQEDA/3SqF0URm81Ga2vr6WWvxMREVKp2L57a2lqcTidvv/02L774IosWLWLAgAEMHz4chUKBzWajvr7+tIHsypUr+fzzz+nUqRO9e1+QVil/iLq6uovK2kMul5+1TO35wKlTpzp6Vp4DWltbOX78OEOGDOlo6u5jQqQWDpvj+bY2g1hdCx6NQBddDYmKesZnzyCr5xfkuiykybVMa+6MW5TwTGNnsprjeDJuHRMSSnm9qQ+yIjVxGyxcOSmb50OzKXAJTNRaWC/UcM/hG/i+32IAemjL0cQ7GaUppLuqgnfrhzO3ug+dtdXsbk3m7ZiN9Ng8h4WDV3LKHg1UstecwoLgoyxpzWCWfwFD9HmsqOvP6soeTIjKptQVSJ4jghvC96EQPLR6NJxyRBGmNFJoDaO7rpwDxkQARmjz2CNJxBEip8wZTJisjQdStnJj4TUopB4OmeJQS13YPHK8ooTc1jAmRGZzyBTP8JAC5pZNIFrTQqtLzc7GFJYnr+ZLczwflQ8gQmPi5drR5LeFEBbbxjcNvYhUtZFrDCVYZWFnQzKdfTjXHfy5iKJ4WBCEYUAnQADyRFE84xvkLwZs/v7+PPTQQ8yfP58pU6YwZswYBEGgrKyMNWvWkJeXR2trKzKZDD8/PwIDA/F6vZSUlJzOmOXl5dGlSxcOHz5Meno6NTU1AHzwwQcIgoBGowEgMjKSOXPm0NjYyGWXXXZJOsl7PJ6LzgxUoVBcVF0y9uzZQ8+ePX0t46LH5XJdVJnZC5UN8Rt49dQt6JV2rgw/iV5i57OafjRatBALD6ZsYWFLAv3URcyoGYJblBCraeYyXQ73Bh7ik7YulMpbeCrkOJ+ED2TT158AsLAlgbeyRrDpskUESd0cGPAeT9cPY37ID1ylqeaHtlSOOcOQ4MXmkdPk0LIoMotwWSvNXjfFYz7gmcbOtLg0HGiL5/rQA7zXlkSisp5Ct4sGt4EZEbuQ4mWrMR27Uo5LlDJZa2JayQjS9dX00xYyTlvEey29cYoyolUtdFLVkCbXssMq4+uT3UmPqUEm8WL3yE4b3Nq8CkYbjrPXkoLdK0cu8dDo0pGgaSBS3kqZIohqmz9VFgMZATU8VTeYY81RdPGvo4e+nP1tiegVDk7aoknR1aOX2rk89jjrmnvSKu0ot7iYEQRBQ3uWLU4UxTsEQUgRBKGTKIrfnsn4X113mzVrFj/88AM7duzgwQcf5PHHH+f555+nX79+vPTSS8yZM4eePXtiNBopKSlBq9Uyffp0xo0bh9vtRqPRcPToUWpra4mPj6dbt25kZWVx55138swzzyCXyyktLSUyMpLrr7+eJUuWMH36dHQ63R/93VxwfPnll6xfv97XMs4qGo0Gu91+UdQmHj9+nGPHjpGZmelrKRctlZWVLFu2jJCQEMaOHetrOZc0OZ0/RSqI7On+FYOCiym0hlLiCMHoUNF8KhirR8H1uhYSFfU0e3UM889DJ3MwK+gHSl3BBEg09FYXEyg1I0HCLf32kLa73ctzV1MK/kFmUuQ6VjQNYI/Dj/66Ipa09OGK4zdxd8gOdhjTOGBJYqh/PrGaZlq8VvqoaomVacnYdwNPBucwyu8kcZpmqlwBHGyL55g1lpUtfQEIlxpJlLfSX1eIVuIgTGbktopB3B6+kzsDDtJPaWKDJZE4ZSNDNAVsr0/Bg4Q7KweyuqYH/xj0Ps12DfVWHbOjt6OSuNjXFI/RpeKYLQ6lxMWqk73ooy9hkD4fq0dJuKyVe8O2YnYpeCppHXHqJuoderalr6XIFES9y4DZrWRO9FbKrIEcao4h1xzObnMqk4OyyK8J9eWUXxhc2LtEPwScwICfHlcCz57p4F/MsNXU1BAbG8vw4cO57bbbOHDgAMXFxXTv3p1ly5YhlUrp3r07vXv3Zvr06UilUnJzczl16hT5+fmIokh0dDSzZ88mNPT/34iZmZk88cQT2O12pk2bxkMPPXTJbtUXRRFBEDh69CjXXnvtRbV8CO11kFqtlurqamJjY30t5w/x2GOPccUVV6DVan0t5aIlNDSU/v37+1pGB0CDU8/MkB+o9djprKqmzBZIX20RG9cMYuG8jwHYbJNh8qq5RluJlyYyVWU0eVW8mjuKhuT9rK/JIDOokh/MTtaWZZA76FMAVid/z81l7T2Ge+rK2GHsjEbqZLr/AZ4MzmFO9TB66cqYaahjaVsEwwy5vNmcyZPBOdxaNpQ+kRXUe8xcrnajlRxHjoej0lh2NSahkrpZkHyIBo+LRY3DyDWGMTPqR7QSB7NCd7C6LZO1biUxqmbiFI3k2CPZa0zir4nreLZ0LCtTvyBAoiHLIXJ/4hb+dmosSyqH08O/ki5+tRxrjmJ/bSxjYnLxWOTsMybSrNWSoGyg1BnCXVtmIEpFwhNM5FvCyNBXM7e6D7dE78PulTM0MpeNbd3oaajApZdi8qhYdaIXsZlN6LR2sPlsyjv480kSRXGqIAjTAERRtAmCIJzp4F/MsNXW1nLLLbdgt9vZtGkTFouFlJQUUlNTefrpp3n77be56667GDx4MP7+/uj1evr06cOtt97Kc889x/PPP/8fwRpAREQEffr0wel0kpCQcMkGa8uXL2fLli0AbNy4Ea/Xi1Kp9LGqs4/BYLgozICPHz9+0S1Zny84HA5eeOEFvF5vR83aeUKQwkyDx8A+exi1bj+eiNhIhSuInrdms6x6MBrBwRsVo4iXN/JiY2+qPV7S5HJavRoGRxUzTJvH1i7reCnsCH4yK37qf+1g82ncTuZU90UqeHkh7BhPBuewxpzODruAyaXC5FHzYnMyd/jVkK6o48ngHGaUD+GW0N0YXSpCpTqMooM3q0ZR4Q7i+uB9XBNxlFqznmqPi02WVOSCh+sjspisNbGsahD/aBpIVlP7F8dCayhf1vfG6lHQSVPH/LzJFFaGEiDRsMMu0EcpJ8ucyAfdP2Fs2HH2NcVzsDEWrdzJU52/xeGVMa3vfuSCl3qngRh5EyurenNZj1OM6XaSm47NwCCzs/TQEJRSN2WOYPRSO7Vufw40xmH1KhigLUAueJjQJRuABWkbz/k8d3BOcQqCoOb/d4kmAY4zHfyLGTZBEOjevTvdu3f/YxL/C0FBQQAUFRVdsh/Q11xzzelg9dFHH/Wxmj8PvV5Pff2FbwjZ0tJy0diTnE+IoohCoWDSpEmnNyt14Fu69Z+L1R5Pnj0CueDBLsqYkn0bV0afYvuhdF4evYKDtgRui9pFotyEUuLmb1VjWR6/g1qXP1f6Z5OpULDDLvBx/WCeityAK0LKMmMYMw11ADxRn0GBMYREdQMpO8ZRMPwj7vUvB+AHbQNTDMfxE+QsM8YxQmPipMvKh7G72GhTMDNiFzvsAnqJnEmhh9jW2pkkTT13+x8nplMTuc5ghmgK6aqqYFH15YzQrGFqxEEyVWUQDH4SNypBYKctivmbp1J8zXsoJS4+oT83lg4n06+MD+pikQlepu27nRnp+3gy4VtWNPXjeHMk29u6sD43nVk92uvkbgvcywu1l3Nj9AHKHMEEy01MTD/Ety09+HToUl6quJI+AWV8Wt2f7v5VPJ20lv3WJJo8OhKUDexqSyFc38qapl50GNj8AuIFb+vxFLARiBEEYTkwCJh+poN/McPm9Xr/kLJf4qqrrkKpVKLX6/+0a5zPLF68mMOHD18SXR1sNtvpzSUXMi6X66LxxztfEEWRp556irq6OlJTU30tp4OfKHIH4hEluEQpGaoK8i1hTI47yi0B+3h59Ao+qR4IQLNHx1FHCI8H56KVtW8ueqtwOCfs0QCYvGrkEg/xMj0V9kCe3ToBgGXGMALkFpptGkZoc1g58D0ATrqsAEz2O8TbTYNY2NyTXa2pxMv0JMqkAMx/8zYWlo6myhVAhSuAcmcw70XvIVBqwSBREyo1MVZjZ5M5HbngZVFsu63UdEP7l0aJINLgVfJBay/eKBnBNQMOstwUiMMrZ2X6RyRrG1hd2YNO2jpKTIFo1E6mGA6zvHEAd4fsIFbfgkFmY8WgpYzTZ3PCGMlr9SM4WB9Dg1uPVxQotIahElxopC5WNPdnYFARx4zRhKrMJCgbOOmIot5lYEn5MCqdgaRq6/i+NYObQvacoxnu4FwjCIIECAAm0R6krQB6i6K440zP4TOzL41Gw6effsrw4cN9JcGn3H777QwcONDXMs4JSUlJ7Nq1y9cy/jAGgwGz2exrGRcNzc3NANx///0d3nbnEZUZS3m7YgR6qY3b/A+jElyUPp5GZ1UVdrE9aDI5legldnJtkWxpS8fotZGqac+cfd5tGfMDC/HipdWjYXzgUdJ+vJm7Q3ZwRd9jpOyYToqijmV5AxgdlUcPhYpOMi+lbhPvNAxnlx2+NXUjWVXHnQFZ9NBXUO42oRaUrDQHsPnBl9naZR1FjjC6KuvY0ZACwB1+NTxRn0EfpZx1Vg2R8hYyFQqCpRp22WJ5sTmZZyvHkSyT00XenqbpG1KGRuLEILWztqYrmyyplNsC+Sb9H0zxO0RGQA23pbQHUfeHbaHUHYSf3Eaw3MzqtkwipRLeTfgarcxBp8B6NBInEYpWPAgct8dQZgnkmoBDDNPm8kjUdxhkdrY0dWF9XVdcXgkphgam+R+ki6qasQHHWFhxuQ9m/ALjAt10IIqiF5gjimKTKIrrRVH8VhTFxt9yjl8M2KRS6R8S2MH/xul0cvjwYV/LOCdkZGSwbds2X8v4wxgMhg6ribOEKIq8/fbbVFVVERgY6Gs5HfwMk0fF3+K/wSXKeKBiHKWuYK58bQdvlI7k05aBpCnq6BlUST9NMS+FHWGgvpD3WjPIUFfwYnMySTIdpW4TE/Kv4mZ9I8WOUPx1NtLlGhZH7Uens7HTnEZKcCOHmmN4oCaTGo+bUreBAfpCuivaq+77qUuo8iiwehVUe9Rk7LuB63UthEp1mL12/hJ0nCSZjlui9gLwSnMS84IPMCZ3LA1uPZGyFp5qSOep+m68kj+a+YGFfJ64FaUgxyq6ybeEoZE4KbSEopfYuDw8B5NXxeywbcwpG89bDZfRYNezoS4DiQAVbj92m1JQS128nz+QPFMYk/OuZX7VlVTZ/JEJXlZX9WBVVSYmlwqV4OIv0esZqfYgF7wsrhvBUL9cRgWdAmBm0I8cb45EikiVK4Aj1niGBhf4bN47OCdsFgThIUEQYgRBCPzncaaDfbYkeqnj9Xo5efKkr2WcEzIyMjhy5MgFb+0RFhZGU1OTr2Vc8NhsNlwuF4899hjR0dG+ltPBz4jv9zDX+B3muCOaw5Z4/hr1LdtaO/Physv5S+IGpgbs59bj0xlhOEW8zMUyYxjX6tqocvijF+yM02fzkTGUeJme6yMOALCjKZWm1v+3aRJFgX7aQt5N+BqrS8FrEYcIlkpY3dwblcRFncdDi0tLsSuY12tGEyZvo8Fj4ONeH7HP4WalOYA8twS5IOOky8oxaxyjc8bxUGARk3OuZ3hIATMNdWw1p5OsquP+4P3cnHCAo047i1ujKXebeL2xH/mtIThEOUFKM0trh9FdXc6qsky2mNOZGf4D8aomKs1+SASRh0onUe82EKFow+RWIRFEhgYWcF3kIeaEb0UpddPdUEGCoYnpMXvbO0Koy9hnS2KzTUa41EGgwsLisuFsbMzgkdiNpMnlPJK0ibFZs+ivLkIvbe852sGvcIFm2H5iJnAP8ANw6KfjjNs6/WIBlSiK2O32jkLgPwGDwcCtt97qaxnnBIVCccEHawDJyckXxW5XX7Nlyxa8Xi8TJkzwtZQO/o1MhQJQECet5JPK/jxqvobrww4w+pZT3PXdTHZNeJWDvVaxz+FmZtEkxoVms96q4rWIQxxyulEJXpIU9dxYOpzOuloWezQUNgVTMPwjAI467Rzts5KjTjuhUh27uq5mh11AjooZwbv4S8kkhofk80LYMV5sTubTuJ3MqhxAi1PDI9Hf0V8pQy7U4RIlLDcF4iWYu4J2kRSm46TLyjVRRwmUtpctTPPLIkWuY6MtgLkBpYCKo3Ynhx3hpGuqqA7w48mQvXxnDaOfqpIVxp70CK6i3qknxa+FY7Y4+oaU0erSEKI0k2+PYJT+JNGKJrRSB3nWMBZH7Wd8/tUEKq1cpTuBFJEeqvaNE3usyfhLrVS4goiUGemhLSdNXcMkfSHvNGfyvVHGdf5Z9I0q57A9jlUVvZgcc8Qn897BuUEUxYQ/Mv4XM2wymYzGxt+0xNrBb+DgwYN8+OGHvpbxp1NfX09ERMQFv8EiNjb2dPu1Dn4fVquVcePGdTRzPw+ZPOQxHqzthUN0oZOo+DZtNV8lbSZR0cAIdQXFk94jWKLiU1MwkVIbj8d+S7yigcWVl/FEfQbbzZ2RI/J61WgWRG2gyaWli6qKW1P280hdT7rsuYkeChVvtsbSQ/H/SYDDtng+bRzEg4XXMjd2CxmqSgAm6I+R5XDxcPhmxoUc44uW/7fUOWqPo5uyih2tnUiS6TB625dc7/Uv50Z9MwtbEjjpDGN8/hX8YEoDwOi1ESVv5s2yEfRQVnKoNobJ+ZPJsUfyVtNQAqUWfihPIlHdwGOV4wmUmbk9eBcHa2IwuxUkq+pY0dSPyVoT/fTFJKob2WEXuC1qF5cHnqDIFcSOplTWGntS7gyil6qUm/WNOEUZJq+Cm/WNSAUvWY4AguUmdDI7r9SMoY+hhOWVfekfWkqY7Iz7gF+SCLTvEv0jh0/1C8Kk/3KMFAThjByTfzFgUygUlJaW/sfzVVVVLF68mMrKyt+nugMAOnfuzOTJk30t40/HarXi8Xgu+BZVfn5+2Gwdrpa/l8rKSl588UXg/+tjvV7v6c0HHfiOo51WsLQtglfDD6MU5LR4rWy3txtEH7dH860liV12qPQ4mKKrosKt5ag9liXVlxGnbWZ+8EGqHP5Ue9R8lbSZF6qv5LWIQ/xgTqOfpog1+V0J9zMyuWg0Gyf15Ypr2jseHHI66aUuBeCNlM9JkzcxVmOn3mMmTa6l3B1ItFSJv9RKuqaKXJeFTIUCheDG6FUyO2w7D9b24rCzfRe6TXSw0aZgkj6bD6qG8GjsBpqdWpq8FgrcUl4pG0O8vpkmj5qr4k7xePx6rtRn81LYET6t6Mdnvd+nv7qITL8yRmkKOWqPpndEBRa3ki7Kasos7eVGQVITM/yz+WvR1bR6tHxZ15v52ZOwe2TkmCJIVdUiFbw8UJNJH3UJ/2gayIvNyegldlyijHBZKwDH6iOZ7V/J5eE5vBp+mPCOgO1i5zbgfeDGn46ltLeq2i0Iws2/NvgXA7bg4GC+++67f2lG3tTUxAMPPMCOHTuwWq1/SPmljlarxWg0UlFR4WspfyqpqakEBQUxfvx4Xn/9dV555RUKCwt9LeuM8Xq9HDlyBIlE8i//Fy4l/ujrdjgcREdH89hjj/FPY+/q6mqefvpp5syZc9G1ZLuQyBxwH38LPcEdfu19nmdX9SNAomH2zpv5e1MqITIjcfJG/CU2Nls6MS5nCmkKG3LBQ0+/CursBnSS9mXRU44olhnD+DRuJ8uMYdwTeJBImZnUsHq2pa/lq6TNVIwLoXKEjsTvb8MgOLF4lYwPPMLjZROJl+lZaQ6gwSvhI2MosbJmlIKc8RoreomNF2uuwOi14RRlPFs2jmP2GB4P/ZHhKpFZlQPYY9ewtHoYgRIZl4XkMUglYWLQIQpcShR4iNQYCVOa+NGaysm2CIaoYHHdCHbYBd5OXUGpK4jPmvtT7zTwzwruCFUbxxsjyHWE4/RIWdIWRVdFK49UXc6VESfxIrAs8RtmdtrL+8mfA9Dq0bDHmkIXTTW1bgO9dGW0uTVYvEpqXX5IBZG7/Y9zZ8qPbLQp0Eic7LZ7Gan2+OhdcAFxYdeweYHOoihOFkVxMtCFduPcfsD8Xxv8iwFbUFAQXq+X1atX4/V6ycrK4u677wbglltu6fBNOguUlpZSVVXlaxl/KjKZjAceeABRFPn666/5+uuvGTp06L/UtZ3Pdhlz5syhV69eiKJIc3PzvwQvLS0tF107sX/n22+/ZerUqb97vNfr5cknn6SpqQmFQoHH42HNmjU88cQTTJo0iRMnTvDdd99x8OAZ1952cBaJl/2/F+YuOzQ52jcIvDj4S462xTBWY2d1SyYSQWSiLo8PUz/DICiZbqhngLaAkUE5PFjbi8Wt0UzQFdNPXQLABF0xQRItxS5/1qVuxCW6+cgYSva8d+gz4QR4BCZkzSLbFtt+jeTv+XtTKkctsbxQfSWD1MVkKLwYvTaOOu0MVNVRa9NzR+k46l0Gvuu0gWa3jhNODRttCsYHHmFZ3RCuDztAsVtgqiGbhS0JFDjCKXWFUOQKZlTASWYE7GGS/ih3Ru1ko01BV30lp+xRdFWoSZI38kDIDk62RdDkVfJlXW8qbAFMijuG1avEKwr0UZew0ZJIpLINleDmg9JB7LEHIkVkUeNQ3KKEHqoyap3+TDdUcKXGSqKinp6aMuyinGaPlr3mZO4qG0ubR8NrZaOZoDvJ7OwbafF2JEEucuJFUaz72eN6IFUUxWbgV28kv9rpYMuWLQwaNIht27addqu/++67ueyyy/6I6A5+YvDgwb6WcE5Qq9Xccccdpx8/9thjrFy5ktDQUObOnUteXh7r1q07Lxt+V1ZWIpPJeO+99zCZTPz973/nrrvu4pNPPmHfvn3cfPPNF21NltVq5ZNPPvnd410uF1KplPvuu4/S0lJ27tzJ/v37CQgIYO/evaSnpwMwfvx4ysvL6d2799mS3sFv4JDTSaZCwV+Lx7O1yzoArtW1ESPfBMiwuJUESbwESJQcdEhZ2tyNBFUDr5wYzaKeK+mnKSZToWBpWzJpyhoWmhMIlFpIU1bTW2kFNCxq6cTOxhSOWRowu5UIZil2q5bNfmn01RQRJLUwTn8MvcTNLlsCKXIdS9qiSFdWIcHLcY+W+lVxrH38TR6p7Ue520SFPZAweRt1Lj8eCizCGnyEeHkjTR4tFW4l43XH+drUA73ERpDUzFF7HBstXQiUmvHSbgyc1ZrAVcHtraF2WDvhL7XyZuIXNHhUPBv3DTstqagkLsZoC7mjSw3rrP6M0BRx3BqNn9RK35AypIKXYdpc7BoZO+VpdJK3l3/kulzkOsMJl7URL2/ELsrZ1JDOoMAiZsXsJlamxyNK8JfIONZ3BXDhG4z/qZwHdWh/kF2CIHwLfPHT4ynAD4IgaIHWXxv8q8a58fHxbNy4EUEQiIqK4pVXXvnDwZrb7aa+vr5jSfUnVq5cye7du30t45zSv39/5syZw9SpU7n88su59tprWbZsma9l/VfS0tIYOXIkycnJAKSnp3PvvfeiVqt54403yM7O9rHCP499+/YBcOedd/7Hv5WWlvLGG29w11138dprr/3HhozCwkLmzp3Lrbfeyl//+le2bNmCSqXiySefJCsri/T0dNatW0d4eDj5+fkYDIZz8ZI6+DdK3abTfzco2tsavtjc/l4/ao9jbP6VzA3fTLhUx4fGeKJkFgbp84mRN7G01yeoBDd7rMm82Ny+K/LR/Enc7neKEJmR701dOeHUcMjppNQehEzi5cd3+vJF4hYUrRLkRgnb0tcy7/h19FCo0Eg8LGoYzhRdFeusGsJlrXxvzCBGZmGgysqNczZy0uXmybBd7LHHsigyC5XgYm5AHotbo6lwBXLUHku1O4DxGithUiktLi3bjF2weJW0uLW8mzuYQeoydrWl0uDWMyIwhzRFDQtbEii0hrG7LYWNljR2WVO5M+cm7KKcKbpSvjalU+Q2s8vUieVtmfTXFdFVVUmKuo5alz9bzOk0eAzc43+CYreMucE/sMHclXHaegqcYdR72jOZ40OP0VtTjFVsv/1epjuFQaLuyK5dGtwDfAj0AHoCHwP3iKJoEUXxVwOrX922V1RUxLhx40hLS+O222773RYfTU1N7N69mx9//PH0RoZx48Zxyy23/K7zXUxcfvnlF0Xrpt/CmDFjSE9PJyIiArVaTWNjI48++ihHjhyhZ8+evpb3L0ybNo0lS5YwePBg6urqePvtt7nhhhu4/PLLqa2t5bHHHuPee+/lhhtuoH///qdrtC4kqqqqaGpqIj09/V8Ms/Pz8wHo1q3b6eesVivZ2dm8//77zJ49m0WLFvHOO+/wyCOPcP3113Pq1CmqqqpoaGhgwYIFTJw4kU6dOv3X6xoMBurq6qirq2PkyJF/7ovs4L9y1BHORK2FleYAxoScZL1VRXd1OY/U9WSE4SSTww+TKBO5s3Ig70XvAfTEy5wUuc00eFS0ejSne4DaRAddOv+DTdYIrtW1saY5gHJlIC5RhkFm55hNS9Yz7wDgTrERsFnFR8ZQjvVdwW0Vg3grehu3Bu1mQe0gXos4RK7Lgr+0PZDZ71DRS13KPlsSqIvoo6rguFOKRNDjEN3M9q9kctFoai16Puj8KU819EUlcRGhaKO3uhirqKDK4c8r3b9knz0Wf7mNfpoipIjUe/TMCyhhq6qcWFkbFlHGJnMGu7t9zYzyIexU1nGTIZdjTj1dNRVYvEr0UhutHjVdVFV4RAmTdGVYRQ+FbhnfmzI42BrHgpj1HHQoAUiVNxKmaqHYLfB0+dXMi/6ePbb23qobbQqCJC5eqRrJdT55F1xAXMAZNlEURUEQDgJtoihuEQRBA+gA068MBX4lYKupqeHvf/87aWlp3H777b9ZnNVqZf/+/fz444+UlJTQr18/amtrUSgUZGZmXhI7JM8EjUZDTU0NCQl/yKLlgkKhUJCYmHj6cXBwMFOmTGHq1KlkZ2efV95/PXv25MUXX6S4uJiBAwfi5+fHVVddBcAnn3yC0Whk3rx5LFu2jB07dnDbbbcRGnpGu7TPG1asWMGhQ4dIT0/n/vvvR6fTUVVVxYED7eanx44dIysri5KSEux2OzExMXz22Wenl7CXLl3Ktddey913383IkSN5/PHHiY6OJigo6Bd/F0OGDCExMZHevXuTlpZ2Tl5rB//KRK0Fh+hiiLqc484g9IIdqeClj7aYzW0Z3BC4D4NEzSuRW3mztRNtbg3BchOz/KrYZomgl7qMZxq7Y/fK6aapoNrlzyR9NlkOFc9EfM87zf0AWF+azoDI0tPX9TNYCTzlIV7RAMBrUVuwil722VIJV7bxlUVPD6UZleDisCOcI9Z49FI7HgTerBvJ9JDdRMrMbGjuxuSY3dhEByFKM9MjdnPT8RnMT93Etbo2lpsC2W9LoquqgluDdtNDIbC0LZQUVS12Uc7mtgx21yayK6KAUIWRFH02sTIp3QLzebM1nttDd9Lq1fCjPZjP6voTqjTR7NJQrzVwmS6Hl8qvYFRILv2UuYRLdRx3yjjaFsPQwAJcooTeSgdDVHUUueG91gweCiyib0AptW4/DprisXiV3GTI5ZqcaZRXBXGd2hfvgg7+HUEQpLSb2laJojjup44EnwPxQClwnSiKLb/xnHcAdwKBQBIQBSwBzujbqvBLu78kEok4ceJEdDod48ePP2NRoiiyefNmVqxYgU6nQyaTcerUKcaPH49cLmfmzJkdTbR/xqlTpzhy5Ag33nijr6X4FFEUeemll0hNTeWzzz47K+dsbW3lmWee4ZprrmHIkCFn5Zw/Z+7cubzxxhunr/XXv/6VDz74gJEjR9KlSxfi4+PRarUIgnBe+9CdOnWK9957j8suu4zvv/8ejUZDbW0tzzzzDC+99BKxsbHcddddjBw5ksTERCSSs9eG+Msvv+Tee+9l4cKF5/Xv6KKl1wt4RQnX6totJb6xaEmSN+JESqZCwZzqvmwq6IzHKqf4yvd5prEzq1YMp/PYAr5I3MKilniGaXPpoVBx3GnjqCOGm/WNZDlcWEQFQ1UeWrw2Bn7yEHnT3zl92Z4Hp6L72J9db77L3Oo+JKobGKc/QZJMx267l0Gq9vfYK81JeBA43BrHuJBj3KxvJNdlIU2upcpjwiXC58aeDNQU0uTR8kHVEPoEtvcI9SBgdqvY1xTPBykr+NLUjXxLOA+Hb+aUM5RSZ/Dp7OByUyBpylpMXiXPFI1nRuwedrWlEqFsY7Auj9FqN0vbIih3BNFNU4HJqyLfFs4LYcc47rRxyB6Hv9RCf1Ud4VIdI05ejVTi5c6YXcTLG8lUStlqU3DKHs0Uw3GKXXo+ahjEtcFZ2L1yql0B9FKXUnXgxXP/HjgPuO666w6JoviLRazqiBgxYca8P3SdnL/P+9XrAAiCMA/oDRh+CtheAppFUXxBEIRHgQBRFH91Z+e/nfMo0BfYL4piz5+eOy6KYtczGf+Ln45qtRq32/2bdjHa7XbeffddKisrGThwIPv370en03HzzTeTl5fHwoULO4K1f6NLly506dLF1zJ8jiAI3HPPPTz11FNMmzaNRx555A8vj95xxx3s37+fNWvWcMstt9CnT5/T2bGzgUqlQqVSYbfbOXXqFN26daNTp05UV1dz7NgxGhoaMJvNDBo0iLlz5561655tQkJCMBqNzJ8/n2uvvRatVsuAAQPQarVcd911xMbGntUg7edMmTKFV199lddff52bbrqpoxH8OWa0uh6lIGNpWyx3+NUgF9p7X1a5/QAnb0UeYIHMzvOh7bWa9wYeYtbsLApcGpq8NsboTpIm17LP4aa/Uk2avJZcl4M+Si277R6+s2p4v/oK0gYV82JzMvMDC3mwtheRs9pYf7DdBuPqgMOEy0yESWRstskYrXazzNi+XJihrmCw0ogusJCTLiuJm+dQPHoZD9RkclPQXrrIReYHFuIQXSgFCxNTNzI+/wrWpW5kn8PNFy19+WvCWkyilKmGbJa4tGTZY/iwciAphgaaDDnIkdDm0ZCpULDZJuWxxPWnLTZGaEqodquwiV6+b0rH7ZXwt9AT7LAbMXnUzKocgMMr48PYXVR5TBx1BtHq0fJ00lq+M3bDX2rhkD0eD2V4kPCP0j5clXECf4mNaFUrMbJW/CUeDgsi/ZUyvvLVG6GD0wiCEA2MBZ6j3ScNYAIw/Ke/fwzs4AysOP4NhyiKzn+WzQiCIOM3LPL+4iewXC6nra3tN/mELV++HIVCQY8ePaisrOSll15iwIABrF27ljFjxnQEa/+GKIosWbLkvLa1OJfodDoef/xxWltbGTFiBGPHjsXj+f3eRA0NDaSmptK9e3fWrl3LjTfeyOLFi8+a3ueee45Ro0YBsHjxYubPn396aa+5uZklS5YwcuRI4uLizto1/yhtbW28//77fP311zidTt5//33mz5+PXC5Hq9UyYcIERo0ahVbbbpwaHx//pwVr/+S7776jX79+PPbYY6xbt+5PvVYH/4pd9LDaEkqMoomtNinpigbS5FquUDtZaQ5gvVWFn8zKDrvAE/UZBEg0bLbGMjv7RgyCkgJXCC7RjV2U80R9BnJBxiZzOm+2xjJIJWGsxs5NEXupMPrzbVV7IuHV8MOsP7iRZxvTuLNyIAaJHZNXwRpLJBrBSanbhMWrpN5jxuJVopO0l0hoBQ9fD2v//2t0q6h1G1ALSpYZw3igejBzqvuyz+EmQmNknVVDf2X7DtdBKgkNHi1P14zBT2ZjhLoCiSASrjDymbEzBomaMHkbj9Z1Z2VjP8JlJjbaFKQoaomS6smyJXDKJTA59BD1Vh3rrSqKnaHMDSjl75FbmRqyn2caO5NlD2ekyspVmmqMXhVuUcpotZvxulwKnOF8WDOE8TEnCJQKdFWo6a0tweqV4yfIWVnf12fvgQ7+g9eBR4CfN1QPE0WxBuCnP39P3ctOQRAWAGpBEEbTvlv0jD/wfvFTWKlU0traSk1NzRm1qKqtrWX37t0kJCRw6NAhHnnkEQIDA09n6Dq27P8noijSq1ev0zfHDiAgIICZM2fy5ptvUlpayvXXX4/X6/31gf/GwoULsVqt7N27l8suu4xHH32U+fPn8+CDD561oE0mk7FmzRpOnTrFpEmTMJlMXH755dxyyy0EBASwZs0adu7cyfDhw8/K9f4IoihSWFjI/Pnz0Wq1rFmzhueffx6r1UpRURHNzc3/Uld4LvH39+eNN97g8OHDbNq0ia1bt/pEx6XIrj2LeLP4MvooW1AJLqZk38ac6r64RDfX61oYq2lvSn7PkRv4LLsPy4xhDFKXcazvCuSCjM/q+vONJYjhKpEFIYdYUN8Nq1fB7X4FFLnNfGH2o8wZzOHMz6msCPqXa2e1xGFxK4iTOZALXkxeNZ82DmK3LY5ZfsX4SZRM1rbXY9d7zMTL9KgEDwOPTWZ22HbKnMEAzDTUcVvILkIVJo7bY3gveg8hUiO77V5kEg9bbVKGq0TStdVUOfzZZI3nqrATPB6ci9WrYFrJCPaYUrgxYB83h+whXa7hCrWTlyuvpMhtZntzGq0eNUctsYyKyGOYqhW7V856qwqr6OGAJYkSazAfVA1hYUsadR4PYzV2ohQtbLbJ2GxJwiVKmRa2jwHaAoIkWrbapLR6NFhEBe+1deajuC0cusC7wZwLzkJrqmBBEA7+7PiXLfCCIIwD6kVRPPQnyH8UaACOA3cBG4DHz3TwL9awhYSEiFFRUfTs2ZOamhpuu+22//mzdrudxx9/nIiICAoKCnjmmWdOFxtfd137vpdVq1adqa5LBo/Hg9vtRqlU+lrKeYnVauXxxx/n6aefZubMmWc05t133+W1116joqLitHXMsmXL0OnaDUE3btzIsWPHzrpRa3NzM1OmTMFoNBIWFoZcLmfp0qWkp6cTGxvL/Pm/NXt+digvL+edd96hsrISlUrF888/z+zZs3nwwQcpKipi5cqV59Umj8OHDzNy5Ehuv/12+vbtyDr4moeby7hryDYyVJWM1dgxem0YJP9aGe/Fi+Rn3///WWP2c15pTuKhwKLTj+dW90EtdfJC2LHTNWvlbhPNXjn7bEnM8mv/ot++1NpevfOF2Y9sawx9dcXEyJrpLJdS7nZgF6XUevTEyNpIlav5xBjO6rqemJxKXk75klJXEOM07V0T9jnc7LGmsLclibHB2Zi8KqxeBb3VJVS7AzhpjaKHtpxqlz+3+51ipz0IueCmi7yJV+tH0FtfwqKCEVwZfQqdzE6FPZAMbRVeUWCqIQ+doGCLTY9U8LK2uSfXBB7C4lWypqkXM0N3kaGwEiDR8H/s3XdcleX7wPHPmRz2EBBBEVEQt+JCFLdmrszUNLeZszTTzNHQ3JazNMs098iRmnvvhSsHoAwRBQHZ83Dm7w/yfOPnYhyWPO/Xi1dyzvPcz3WAOBf3c9/X1fJuD47V2sF5pQInaSrlxDp2p3pR/s7owvpWlmi5XcPmPqRga9gC5r9+DZtIJJoHDAQ0gAKwAnYDjYHWer3+qUgkqgCc1uv1L9/+/hoikcgBQK/XP8vrua+dYUtOTkaj0TBz5kwuXLhAQEDAK4/9448/qF27NpmZmQwbNuyFnWHGXDf0Nnn69CkzZswo7jBKLDMzMxwdHXN9S06n0zFp0iRD/1Jzc3M8PDywsLAgOjqaP/74g/379zNkyJACxxYcHMyQIUPo3LkzKpUKOzs7Dh06RGhoKAqFgqCgINauXYuzs7MhIdJoNPTv35+NGzcW+PpvotFouHz5MrNnz2bkyJFERkaSlJTEmDFjAFi0aBF79uwpUckagLe3Nzt37uS3337j4MGD3Lhxg/DwcBISErh+/Trr169n+fLlrFu3joiIiOIO9633g11lvrILoYuZEgBT0YvLWv6brJ3IlHArqyIAWXo18bp0AAZY/8PgRy0Nx81wOoOf5X3DrVMAV6klqToFAyxDmRJTj8kxDSgnzr7unnRz6phE0d36JgBaxKj1WmK1ZiyO7siO+CaEa2w5lSljiFUsofHl2FFjKy4SFU6SZJJ1WZxTwqm0mnxodZsHcQ6cSapOa7P7VDd5ipVYibsslkilDbczKmEjycBKbIq3SQzHkmvjKrWkutlTFCI1P9bcQVVFLO0tAjgf6U67f8coJzbnh/g6eMnjiFLb4iBPo4OphkClC7dinXGWppHw790CvV6EiUiGlViJuUiLk8SCodb/S2gFr1DIran0ev1UvV5fUa/XuwF9gZN6vX4AsA8Y/O9hg4G9uQ1ZlG2GSCSKA4KA+yKR6JlIJPo2t2PAGzYd2NjY8OGHH+Lq6srvv//OqFGj8Pb2RiQSIRaL8fX1pVatWoSEhPDPP/9w//59nJ2dmThx4gtj+fr65iWuMqNixYrMmzevuMMo0eLj43FxccnVsSqVirS0NNLS0pDL5Xz77beGcilLliyhZs2a9O/f/6WFYHMjJSWFbt26cfbsWSpXroyVlRXh4eGG2mUmJiZ8/PHHrF69moyMDObOnUurVq0MJWzCw8MxNTXlxIkT9OrVC1NT4+3hVyqVXLt2jbt376JWq/nnn3+oXLkyK1eupF+/fka7TlFo164dmzZt4tdff+XOnTvExcWRmJiIu7s7LVu2pEqVKjx48IDZs2czderUMlUSpzj8d1ZNJpISqkmjqjR7xjpck2pobxWpTWX5k17UtY4Ei0RMRDLDrJaPiQVuZvGGMW3FZpiLs/jMJiLH+JZiJRZiBd2sb9JcIWZPenk8ZOn0ME8HzAnVpJGiy+Kx2paG8nQy9FJ+q3QKmUjKuhRHelo84o4KbvtsYkpMC2Y6XiZJZ8aZTFu8FZH0t77OivjmeDs9wVSi4oHa8d/brjI2pmbfYo1TWdDd+gYg5Uh6NbzNw3knqAtHvA4QrknlYFoNaioiOZ5Wk1YuoVxVutLfMoFzSvjQ+hphahvupFdkquMZNqa6MbXcA8zEKjJ0EurITVmV7MK5On+xLNGNtuaBbEhqwrf2gURp3+42d6XcfOBPkUj0MRAB9M7DuZ8DzYHGer3+IYBIJHIHfhGJRBP0ev2S3Azy2oTN1dWVb775BoAPP/yQOnXqsHHjRiwsLNi1axe//vory5cv58qVK4Y3BJ1Oh1wuzxnp55/j4eGRh9dWdoSFhaFWq19ZWFQA9evXZ8yYMXz//ff06dMnR2HX/0+hUNC5c2cyMzOxsLDgn3/+oUqVKuj1epKSkli6dKmhY0F+bNy4kevXr+Ph4UFoaChWVlZ07tw5R0wLFy6kV69emJiY0KlTJ+rXr28ojPz06VMaNWqEUqnk8uXLRmnxlpWVxdq1a7ly5Qq1atWiS5cumJubs2LFCurUydVu8RKpW7dubywnVK9ePb766itmz55N+fLliyiysidYI6Hhf36tV5SYGBK1//YidZFY8o7DPawlGWxOteO7a9250moFNmIAKTMd7gHQYN5o+ow4wdRyD9Ch44/kGoy3DQegvjx7xre5QszfGWY801gB2bN00do01HoRSr2MHubppOmUbIh9h7+kSsY5nuSp2obdaeAiS6AOGtI0cn5J8uIL24csS3RiaVg7DtXejEykJTChPBOrHTOskbug1DHQMo53zA6g1OtJ1UsYGtGGr50PEaWxYH/1vVxQinGSijiX6MlQt1CeaZ7RwuwBVWUZ7Ekvj4MklZVxrTARa6hpFkWUVoqbLI5wTSofWwfxZ5obSboYRllHEq9LZ5B1ADLEfGsfyOrkCoQqHWlc2N/M0qyIG7jr9frTZO8GRa/Xx5PLemkvMQjooNfrDZsB9Hp9mEgkGgAcBQqesEF2AtaoUSOePn1K27ZtKVeuHH/99RcqlcowS/Ho0SO6d+/O999/j4+PzwtvqMLs2qulpaWhVCqLO4wSrV+/fpw5c4Zp06YxefJkjh49So0aNV55/IEDBwA4ePAgffv25cSJEyQkJGBqaoql5f/eXDQaDXPmzCEgIIAvv/wyV5ti+vfvz65du5BKpfTu3Rs7OzsmTJiQ4xixWIyPjw8qlYr4+HhDMq7RaDh//jzvvPMOdevWZfz48Xh7e2NtbZ2fL4vBX3/9RVZWFgEBASVqN2pRGDlyJHfu3GHr1q18/vnnxR3OW2tfcgMa/ptsAZiIZLhJX77jf4zNE8O/67dYSTmxOb8nVeOO/Jmh1tvOL38wzNCdypQx3jaceF065cTmDH7UkqbWYQyyCqGbGdxTxxGs1uEhs8BJYoGtWI2Z6Bl/Z5TndIo3Y51O4GMiJUKjY2q5ByTqMghQKYjVZq9f/cL2IbvSLamuiGKhZxj+WRa0tAhiZv177EizZsLThoyxP8PhFB9OpWn42j6ItSnl8TMNpal1GCfTPXCSJXMhK5N0nQluonScFMk80mi4r6zAu3YxmInN8DaJxlVqSfMK11mbUh5rSQY1ZBJ+iPfCWZ7IO+YheMhjSNKZARkk6fQkaOUcT6vF1HIPaGz6kE+sn7LrgdDr4C0k+2+y9pxer38mEr1kjcErvHbTQaNGjfRr167Fz8+Pb7/9lqtXr6JWq3Fzc6Np06akpaVx7Ngxzpw5w/Llyxk+fDhz584tdVXei0tERASVKlUqla2MioNer2fHjh08ffqU8+fP5+qcsLAwUlNTcXNzeyExWrx4MRMnTsTc3BylUklWVtZrZ+/ySqfT4ejoSNOmTVEoFNy6dQtnZ2cOHz6Mubk5o0aNYvPmzbRr146PPvrojT8HaWlphIWFERISQlhYGMnJyXh4eHD27FmuX79eoJnD0iwlJQV3d3dGjBhR4tqavU0+8JuOWq9BJpKSosvkmU5LVakF8bp01ifX5gvbhzmO//hxczrYBuBnGoGLJPsPpTuqTMMtwTomj6knVxlKdmxOteNkUg0aWj5ijM0TsvRq0vQqyonNOZwpp50iA5koe47hlkrJxgRf5pa/wk+JXrS3uEekxoYYjTUxamtG2N7ESmTCtjQnHmQ6sS2gER/V8qeuWQQfmKdyIlPCb09bM7XiAerLFUyM9uYrh7Oo0ZOqE+MlMydNp8REJGXCU18Gl7tAQxMJ38XWZVS5S9xRZe923ZfQgMfptjxNs6KR42M8zaNR67P7l35sdwEVYoJVDrhIk7iudMvujZpUm48dztFQLmdohB/jnY4ZZhWD1Oncu7y0iL6jJUuuNh04VdJXHVSwTQf3fshd4VxjEolEN/R6vXden/v/3jjD5uXlhUgkQi6X06tXL8PjsbGxTJs2jYYNG7J48WJGjhzJiBEjhGQtl7RaLevXr2fcuHEFnmEpK0QiEe+//z6jR4/mzp07ubrd97oyFT179iQhIYEtW7ZQuXJloyZrkD3T9ttvv3H27FnUajVfffUVH3/8seE6q1atYsKECdSqVYv3338fMzMzLl++jEgkwsvLC1NTUyIiIrh58ya3bt3i8ePHeHh4UL9+fQYPHoylpSUHDx7kxIkTb22yNn78eM6cOYOnpye1a9emfv36NGrUCGdnZ8MxVlZWrFixgrFjx9K4cWMGDRokdEwoBOOjGnMsvDpZUeY4V48l6bgTsnToNOICcx1vo0PHByGdqGsdySDbK6ypdIHJMQ14orIz7A6tI89ep9bb8gGnM51oLk7FP0tNYxMZfSxi8TGNoKrUgkx9FqYiE26qRASjoao0DZnIwrB2bkFkZ5xNkwjRqJlkF8ralMoMs4phY6oFiRpzyonN+T6uBpfiq/B7te24NojnE+unLEioxocxTejq8A/dHW6yP6U+leyuYyHJwlFiQbA6jcuZVYjXRnNfVZnO5qH87HyVn5KqUkkawCzHu+xKd+YD81R8//mAEVXOsdLlCrPjvGhveZd4rQUJWgu+sgvhWKYNzUzS2JZehVMaU6RiLb0dH9DD/AqbU53YnliZP1zPEavVABCvS8dTZsq9V34HBKVYPZFIlPKSx0Vk70TNlTfOsF27do1atWrxwQcfGN4gdTodM2fOpFu3bowdO5amTZvStWtXOnbsmNcXUSZFRETg6OhY4nbnlRZbtmwhIyODI0eOFHcoBXb48GFDMd/Nmzdz48YNnJ2dCQgIQKlU4uzsTOvWrenevTudO3c2rIUrC3755RdmzZrF4MGDefr0KU+ePOHx48c8efIEuVyOl5cX/fr1Y/DgwVhbWxMXF0e3bt1QKBSGnbAC49vjehS5WENz6xAWB7TjjwbrOZPuxSS7UJpPGMlvC5cw43F3drgfz3FeuCaV8hI5piITQxmPAxkKbMQZeMgyUKNnWHBfllX9E4VIR3mJnPUp7jhJk7iZ4UY/m6vMiuzCKKfT+CkgWJ2Ghyw7ubuv1htmqZ7P4n38uDnhqXYMrHiFIVaxAEyJqYerSTz+KVUITSnHiVo7kYmknFOCnyI7aQpWm9BQDvE6JU6S/yWP46Mak6A2Y0Wlw1zJsmTLs2b84XqOIHU6/srKiNGx71kDVrvt54bKjCRt9qaKdJ0JvooYfor3YZrDdS4qzWhnqmVHmjVnUqozoNxFtHox91UV+CfNlZahPYr6W1oi5HqGbWABZ9h+LPoZNmN545+h6enphIWFUbVqVcNjBw8eRC6XM2vWLOrVq0fz5s2FZO0NMjMzCQ0NpXbt2pw6dYqmTZsKza7zqWfPnnzyySfEx8dTrly5N59QQoWFhTFixAgGDBjA2rVrefLkCdeuXRNaM5Fdf++7775j7NixL7Rt0+v1xMfHExgYyPr165k2bRp+fn4MHTqUvn37sm3btmKKumzYWPkMQep0fnnWmrs+WziRqWCSXSj1/fuyaO7vBKnKv5CsAYbNCWk6Jc3//WM1Sm1LF2slkVo90550oVeFGzmO7WB+H1eJAjfZdbxk5syr+Ddt9kxiRZc/8JDBdZWKM+lefG4byqpkFzqY3ydaa0NEhpS+9ldo5JJClBbAjA9CO5CmluPqFI9GL6Z3xRtk6tVMjm7KkgrX8c9S4y4DZ0kma1K8iFNb0t7yLg4SNaAmUydjY+UzXFCa0MFUwx3LJ2xMtWegJXjJ4ricpUGjF3Mwwxk/0whOq21xk8XTwVRDhEbPLMe7rEyqirdpOGMim7PS5QpiUSBuUiUznnbgY4ezaPWF21FEULq98adj6dKl1KhRw/CXvU6n4+DBg/z000/89ttv6PV6Q2Fcwaup1WrOnj0LwODBg4VkrQAUCgUeHh4cOnSouEPJt5CQEJo2bUqzZs2Ijo4mNDSUs2fPlslk7d69F28CbdmyBUdHx5f22BWJRNjb2+Pn58eUKVNYsmQJTk5OTJs2jQkTJtCwYcOiCLvMan3vPWZFdsFKmsnixCpIRDpuqZRsq7+GdqZafBRR7En/X9HcO6pMgtTpRGiyd2PeVGUnazp0+JmFcFopwkwkwcU0CTtpGl4yc+6pMzicKUenh1BNFvtSGhCqSSNAXY5rPZfQyVRFkk5OJYmKsTYPECMmIqsczhIZdeRJdDFTEqCsiLVYwYrYNqxOrsCuqsfo4BhEP6sH1LaMxE0eh6lIRi9bf8I1qTQ2kVFObM4VZUWam4ZgJ02jkjSTMLUNDmIJqersuOvJVfyU5IqzLImTiTWoenwo46Ma42MiZYzzSfxMI/BXOrE7tiFKffacyNzojgx81ApnWSK3lJVZ6XIFgA/MU9Gi5yeXc+xPqU83i+Ci/FaWSkbodFBqvXGGbe3atfTv39/w+aVLl7CxscHPz4/z589ja2traHwdHx9PZGQk169fZ9q0aTnWmZRlUVFRSKVS4TaNEXl5eXHq1CkGDBhQ3KHky7Rp04iLi+PixYtIJBLOnDlTqmcL8+urr75i4cKFdOvWjS5duuDo6EhYWBiLFi3iww8/zNUYNjY2dO7cmc6dOxMfH4+dnV0hR122fZbQBBL+93n8vx9AjvVXL2ti7g84NZ7KggRPGpk+5EJ6Lb61DyRYrWOQ7SUUIh1rU6rhIE2llSKeK1k2XEr3oKI8gc1JjRlic5UwjQnRGgVe8jQcJRaMeOLLbxUvMtfxNoczLakkTaKcWEM/q7v0Dn2fUc6nOJhUj5V6Ce9Y3MVWbMatZFdamD3gz7TsNdde8uzk00ysQqcX0dsimSBVKi4SS7ZmViZWk8iPrntJ0UnZnZbdNksmkpKqDaGXrz9e8jgy9TKCVe7cz6oAwHK33exMqYOz5A6jHE9hLtLgIbPgnDK7REmQOp0qUjk/xbVgfvl//i15YmHk75bgbfLGGbaYmBhDUcrz58+zbt06VqxYAcDAgQOJiopi+PDhHDlyhOvXr3Po0CGePXuWo3xCafe8hld+BQcHExQUZLyABOh0ulK9BvCzzz5j1KhR/Prrr4SFhZWJchwbNmygVatWhj6hOp2OX375hXnz5iGXy1m7di3Tp09n165d9OvXj2bNmuX5GuXKlRN2XZdwz7SW9LK6RTtTLXt/aQ2Ah8wCmUhPz3+GM8wqhniNBXdUJoSqynPgcS085DE4ylJwlVpyPt2Tx+pylBdnzzeMdDxtGLuSNIlojSUatDhKLLJn1UyzF/VXlscRobFlXYojP1f+m2YKqGsSSVV5LOXE5pSXJhvaYcVq0wwlSLpa3uZkUg0UIjHBGgmWkkwitEqC1OnUUTymi5mSKlIzwjRaDsXWxt0klnqKCMxEEqwlGaxKaE601ooknQmHM+UE/ZvQBasdADARa9iRZs2JTAnTYusWxbegdCvkTgcl2Wtn2PR6PZmZmZiZmXHx4kU2bdrEoUOHDL9IK1asyMOHD5k1axbnz5/nypUrDBo0iM6dO+e6lVBpcOrUKVatWpXvXqitWrUyckRlW2BgIGfPnuXHH38s7lDyzc/PDz8/v+IOo8hotVq++uorww7Xu3fvEhERgUQioWrVqjnWyArebtob09D5jCdTn4XaHCbHNGBh+Zs4S2QcrL+G8VFtWObsT6gmA4noEcPddZxKq0Ebi0DCNam0Mg+islSHiUj+7xqy/5W32pXckG/tA7muEtFQnt0m60hKXdwU8bhIk4jXmvNEZYd/VhJhWY6IRXramd0HLNCRXahXIVbjKLEgQpPKX6l1qGYSTQfbALak1MBdHssH5qnsSS/PY3U5bCQZpOsSKSdRUk0qZrX7LvanV6W8NJn96Y7IRBrmOt4GIF6nYnVUKz6yv8SBDAVidJiIZNhJ03GXP6OhXM4z7eNi+q4ISoM33hIViUSEhISwdu1a9u/fz7Rp07h69Spz585l8ODB7Ny5k1WrVtGzZ0969uyJvb19UcRdpA4ePJjvc8PCwjhz5gxDhw41YkRl18mTJ9m6dSvLli1j8ODBbz5BUCIkJiYSHx/PkCFDWL9+Pe7u7piYmAg9hsuoUI0df6e5cGXCUhpcHE6WVkofuytMftCPC3V3E6xO456qPD3M0/GQhRCsNvm3Abwll7M02IqlHM6U46MIZ21KVYZZxRCkTudb+0CWJbrR1CyEUE0a7UwtaGea3Xt0V7oDBxPqUsM8GhdJMnUs4/+tD2fBgQwFMpGWJK0Z7vJYLmdpKCcWEae2oKlZ2r99VBM5lpn9lmkpVvKZTQQrkyryV2pD/GNc+bb6fhK0FkSpshvIe5jGUFUew9qU8lSXP0UiMuG7CkfQ6sFSLEEhkrAq2Z1W5kHUlytI1GXwx5Mu5K9pXhnxFsySFcRrp8FEIhESiYQffviBQYMG8euvvxISEsKkSZP47bffcHJy4rPPPmP06NG0bt36rUzW/kulUuX5HFdXV5o3b14I0ZQ9u3fvZu/evZw8eVJI1vJJp9Nx9epVlEol6enphIaG5uvnOq/s7e0pV64cUVFRDB06lClTpjBw4EB69OhR6NcWlDydTFXEqqxI1qnZ3HgNM5zOUEeexZRqhwHYm1qP+ibRXFDqsBWbZi/oj2wKgI+JlAMZCjqZqojQWOMgzd7M4CUz57pKRSPTMLR6MZczXQlSZ68Xu5yVfVu0hnk09tJULMUazmW6GuK5nFaNvhaJvGMWTqrOlCSdGRUkUmY53sXHRIpar2FZohsykZZ4XTrtTLWEa1I5FFub922vc6XBTs6k1sBSnEllkzjcFHHUMokkVmPFM40lCToLfEykrIpvRrJOiq3YDK1eTw+L+9iJ1SxIqMaAkA/Y4bmzKL8NglLmjTNsX3/9NVeuXOHAgQNUq1aNSZMm4ezsTO3atVEqlSQlJb31O9vc3NyIiIjgyZMnry3E+v/t3r2b5s2b4+npWYjRlQ13797l6NGj3Lhxo0ys9yos165do1mzZohEIkQiEebm5qjVamrWrImvry/t2rWjXbt2mJubv3mwPKpSpQpRUVFUrFiRKlWqCA3by7Bd5+Ygq76VULUZjUy0HM20p7FJLC0UcYx60o5VFS9xLNMWd1kSV7MUPNNasNLlCtNi6zLX8TZ+ikTAFLlIi7k4BR1ixIhpKJejQ0eLf3qzssZmknQmAGyK9+VDu6t4WcZQQ6YgQgOtTR+zLa0SD7Mc+ML+KosTa2EpVmImziJGY40EHR1MNcRqszc3fGYbRqw2A6Ve/28NOEsa2z3iQron7UwD8VBEU0sew1WlKx3MA5H8OxVkI8lAItJxWinic/srlBNn/7+VoddgIZIyOboVNcyfMtD5MueUtsX1LRGUAm9M2L755huOHj3K4MGD+fjjj3OsTVMoFK9N1h4+fIipqWmpTuj0er2h12dcXFyeEjYnJyesrKwKK7QyIyIiguXLl/Prr78KyVoBSaVSHB0dWbx4MRKJBJFIREpKCvfv3ycoKIhJkybx+PFj3N3d8fHxoXXr1jg5OSGVSvHz8ytQB4Hy5cuTmJhoxFcjKM0G2V7GQ2bB3xkWdDPL4ESmNe1MtfS1v8yUmHq4mCTiJk1iT1JDktRmdDO7xDcO/hzOtKSqNA0rMfwW04qNlc8A2evV2plqWZHkxsV6uwDFv6VELJGJtJiJVdSSZZenWhLbltEOp3nPPJpBsQ0ZkexqqB33fkhHPnK6QgdTDTp0HEx3Z4hVLA/UmYCIqlIFMomU1ckVsJAoGWx9lxOZVvS0DEGGBCuJEi9ZdlLmIYOaF3sxrtYp/o6pywHP7FJEsdo0nunEBGSVZ6XLFbL0aval29PQJI4LRf2NKEVE/36UVbn67bt161aaN2+e640EkZGRLFmyhIiICNq1a8fIkSMLFGRxiY2NZd26dSQmJlKvXr08b6SoV68eMlmu+7oKXuLWrVssW7aMjIwMvvjiC7p06VIosz9vi5SUFFavXs3Tp09z/LyKRCLEYjHXrl3DwcEhR+JlZWVF48aNady4MQBKpZIHDx4QFBTEjz/+SEZGBmlpadjb2/Pnn39So0aNfMWWnp7+1i+bEOTe89mvbmYZXM7S0M4UorVpWIrliEV6PrOJACyYX/4fwv9NvELUOpwkKWj/fdv+uPxZYrVpRGmltDGVM/hRa9ZXzq532TusPX3LX2Fvmi1LKlxnXUpF9iQ54mkazY8VLnE1yxSZKAMPi1i+tL8MZCdzf1U7CmR3UkjSmTDEKpYLSh1WYjEn02swyiaYtSnl+cT6KR8/bo7S6jblJOnYik15qk3HTpzGjjRbvBWRpOqkrG24jkrSTH4KaM2UmHqMKnceN6klybo0/EwjAQtMRDJ6WySzOLEOwp+kglfJVcJ2/vz5XNe78vf3Z/ny5WRlZdGuXbtSvdj+7NmzWFpacuLECTp27JjnhO3HH39kyJAhwqxQPmRmZrJz507OnTtHo0aNOHPmDA4ODqW6lIex3bhxg/T0dLy9vXn27Blz585l+/bteHh45KiBqNfred6CzsrKioEDB752XIVCQd26dalb938lBnQ6Hfv378fHx4dvv/2WTz/9FBMTk1zHGh8fz4ULF4Qi2wKDiKsL+cruCntqbMdcBLdUGtJ1ZtzJqoQEneG4NJ2SW1lOuEnTideZ0dxEjUykYF2KIx3MQ3GUWOIoyS7Eu7TSYfyzZDQ2kfFtxb/xlElZEF8RgCFWsUzJrMBAyzh2pdvyMMuRkAxHTCUqbMVmDHyUPVsXr0unnNicb590Z5rLAU4r5YCEOnJTKksDMRGZ0s8ygjSdnjWVLgCWXMy05lBqeSrIktgV7c3fnoeZHONHhlbGSPszLIxpy4ceN3iYYY+b1BIdOmK1ZkRqJQSrs//f1CLiC9uHL61fJ/iPMrzp4I29RI8cOYKLiwt//PHHG2+H3Lx5kxUrVmBtbU3lypX57LPPSnVNpJMnT3L48GGCg4Np1qwZHTt2pH79+rk+X6/Xl+rXXxwyMjKIiopi165dWFpasmrVKtq1a0dkZCRZWVnI5fLiDrFE+P3335k4cSLW1tZER0cjk8nw8/Pj3XffLdSC1WFhYaxbt47IyEgqVqyY4zkTExNcXFyoUqUK7u7ueHh4UL16dVxcXOjUqROZmZnUqVOHd999t9DiE5R+H/hNJ1idxohRn3Nqze8AJOoyuJJlgwwt7Uy17Do3hw/8pnNHlYlSL0Us0tPw398NKbpMfkmqw4dWNzmYVoMxNk9yjH85S4NCpOGGMrthfI3Vown85JccxyxOrMIXtg85p4RQlSPdLB6i1utxkmQXtj2WKSVdZ0IP8+xNDeeUYCPONDS335FmTXuzp5zJdEAm0vJYXY41Yb5M9DhOa9PHmIkkZOi1JOlEhtunAPfUGQRdXlI4X9gSLje9RM3KV9JX+6hgvUTvLH2Le4kGBARQvnz51yZrer2e48ePs3nzZiwtLbGysmLkyJGlPllp1aoV69evJyIiAlNTUzIyMvJ0fnx8PLdu3aJ9+/aFFOHb5d69e6xYsQKpVEqjRo3Yvn07CxcuxNnZma+//lpI1v61cOFC5s2bx7Rp03B3d0ej0aDRaIpk9tHd3Z3vv/+euLg44uPjczyXlZVFbGwskZGR3Lp1i9jYWGJjY0lJSaFhw4YMHjyYiIiIQo9RULrtOjcHgE+H/O/fOZ7/f8d94DedC8rsGbld6ZbUlacx1PoWZiIZZxKq50jYUnSZBGVVZohVLPXlMQD4f7yEOleGcafpFiC7P+mJZ148VtrhpohnvG0455TmpOgUeMnj2JrUiNF21yknNudEpgRfRQbuMhWbkhsQavKUHubpVJLF80Qjood5OvPiPUnUmOPfYAeZ+ix+T67JZzYRHEmzprdFMom6DDaleDHCOpRaMjOEEuuvV9rbSxXEGxO20NBQHBwcXvqcXq8nJCSEXbt2kZKSgoODA46OjowfP/6teHOVSCRYWlqSlpZGq1atOHLkCL6+vnk6/3UzmIL/OXr0KLt372bZsmU0aNCAbt26YWtri4uLC9WrV2fbtm2MGjWquMMsViNHjmTt2rXY2dnx3Xff4eLiAmRvJCjIZoD8sLe3z/V6NJVKhUwmQ6lUkpWVhU6ne6sKawuK36m0mvyjTMNakoGHzIKWd3twtvYe2pQLIlidxu7U+lQ3ecrCkA/+3ZCQrXdYe5KyFIZk7fu4Goyy9eePqjtwlFhwLFNKll5NdVkWZzKtCVbbUU0Rw+7UanxsHUk7Uxgf1YIJjicZbvMPALFaPUFZ7vS0eMSHYe2YXPEQDeXZRX5rmkTxmU0E11UqnmksWZuS/UeWn9kDNqRU4RPrp0X/xROUGm/8rRkaGvrCL2adTsetW7eYMmUKK1asoE2bNvTq1QupVMqECRPeimQNsl9nYmIibm5uTJkyhYcPH/LgwYNcn29ra0uHDh0KMcK3x7NnzxCLxfzyyy80b96cli1bsnLlSr7//ns8PT05d+5cgdqDvQ1MTU155513+OmnnwzJWmkgl8uJj49HJpMRERFh2HUtEBjDrnNz+No+iKHWofSzjONYphQfh0dsTrXDxzQUD5kFX9mFUFUWlyNZA9jhfpxjNfYD2btD21gE4iixIEyjYEpMPTxkiYgRMfZRDxykKbhJE7mUUg0nWTLif98+37X9h72pddidWg0AR4kFnc3D+EdlygCnSzhJsgBQiNSGsiMN5XI+tn7IQ6UDzrJE6ssV9LQMKcKvWikmtKZ6tUePHr2QsK1evZrQ0FAmTJjAp59+ilgsxs7OjunTpxf5X/qFKT4+HjMzM0Npji+++II///yTadOm5XqMRYsW0blz53zvrCsr+vbti5+fH5GRkfTq1YuKFSty48YNFixYgKurK5s2bcLGxqa4wyxSJ06cYPny5YSHhxMbG0t8fDytW7cudUsNUlJSWLhwIQsXLuSjjz4q7nAEb6ELSh0JOltsxBnMf/guJ2r+TaQ2lQ1JDbkhS+ZqijvtbAKoI0/mtFLEN8E98LSJpZw8Ay/TKIZZxfC7+1/cUVmQostAqzdhTLnz+Gc5o1A8NZT8yNRLmVr+FIfT3YnXPUOp19FKIaeTafi/kZiTosvksVaOnwIWJ5YnXmPBwywHqpg8AzAkekPC32F15YO0+WcgYVUuMcbmCcHqtGL46glKizdmV48fP6ZevXqGz8PCwrhx4wbBwcGUK1cOyF67kpyc/MIi5NLu1KlTtGvXzvD5uHHjmD9/Pk+fPqVChQq5GmPUqFFCaY9ckEgkuLq64ur6v+rjQUFBjB49mhUrVhRjZEXv9u3bfPLJJ4SFhfHOO+/Qo0cP7OzssLOzK5W7ZK2srJg/f35xhyF4i1mJs2imyE6GFlbbxbFMM1oo5DxW2tLf+jo1TSJxlyq5pZJyNKUJq702YSbS8UhjSWVpKvfUEm4oK/O++RMy9FqaK8SsSvbCTf6MTcn1GG97H5lIyjOtikcaS4ZYxQLmhGtSuasSU1maXVw3OxZTjqdVw8bqFl/YPgTgWGaCoQn9c63s7mMhVjDR4ziNFY/J0ptwT1W+qL90pU8pnyUriDfeEnVwcODp06ekpaURFBTEsmXL+PLLLw3JGoBMJsPJyYnw8PDCjLVIqVQqjh07xvTp0w2PmZub07NnTzZv3kxQUNAbW/pkZGTw6NGjt+YWcVF79OiRoTZYWXH69GlatGiBp6cny5cv57333qN27do4OzuXymQtIyOD+fPnl7pZQUHp8uDKYhJ1mdxRZXIjszKWYiWmIhPcTeN4rDGntkzDHZU1S552pJoihjtZzliKJYjR4Sq1RCHS4SBNQSaS4CixIFyTSm/LB0SpbRlqc5twjZJwTSqPNeZUl6URr0vnpyRXFCIR1WUaHCUWJOqyN6VFa9N4z/IfqkotGPioFScyJXQw1XBBqaPe1X5k6rNvkY6yjgTgPfNoojTZtdie7zoVCF7mjTNsw4YNo3v37uzfvx9LS0umTZvGuHHjchwjFosxNTVFo9G8YpTS59y5c9SoUQNvb+8cj8+ePZsvv/ySDRs2EBsbi4+PD56enjRs2PCFgq5JSUlcvXqVmjVrFmXob4Xo6GhCQkLo2LFjcYdSpBISEqhUqRLdu3cv7lCMQi6X07NnTyFhExS6BK2eWK0FqToFlmIV38fVoapJDM0VYk5kmtPOVEu7ymcNCZOpyAyFWEWsVoWzREZVqYpwjZJ0vRr/zKoo9TJamz3gmRYUIj3PtAqiNLbUkWdxJcuSOorH/JHkTUBaBb51PoCHLHuGzVZsQro+C/8sNRsrnyFCk0qaToaVWM+PdXawP92RruaxJOhUuEgsidKq8VOYMC22LnXNHiPcj3kNfdneJfrGGbZOnTqhUqlIT08nOjr6hWQNYPny5aSnp5ea3oBHjx6lT58+7Nmz56XP6/V6Dh48yKRJk154zsXFhS1bthAcHMyJEyeoU6cOFy5cYOjQoUyfPp2srCzDsc7OzgwZMqSQXsXbSa/Xc+vWLX744QeGDBlC//792bp1a3GHVSA6nQ5/f/9czUC7urry7Nmzwg+qiEREROSpnZtAkF9JOhMy9CbUUTzml2etaWMRSKrOlHvqDNqZagH4KcmVZ1oV61PcOaeEKI0N55QVWJ5Yi9b33iNcY8UzrTmDrKLpbB6Es0RMkMoRmQhC1Y70tkjmkQbE6HGXpvCZ7W3s5Wmcy6xKqCaNdSmOyEQSzEXQ2OR/qdd9jRgtIpqapNLbIhkpEsLV5lxQ6qgqtWBBQjXGlrtAXwuhdZvg1Yyyt/7QoUN06tSp1KzVqlOnDgBbtmzh8OHDLzzv7++PVCrl/ffff+04jRo1QqPR8ODBA0xMTAgODubevXuG548ePcrt27eNG/xbLCYmhq+//ppNmzYxadIk/P39OX36dHGHVWCTJk2iY8eO1KpVi9DQ0Nceu3XrVmrXrl1EkRUunU7Hli1b3rh0QCAwhoirC+lmloFMpGWC40mOptRmsFUYliLtvz1FoZIsnq0pDWhuGkKKTkG8xgI/xVN6Wd1iVtW91JSl4i5NYcyT5mToxViJTWlvGo9WD76KCFJ0mdSSm+AlT8JOLMNCrGCh0xXam4UwLeK9f9tYiVmfXJ87qkwAFsa2Y80zP+rLFViIs7uD7Ep3IElnhrlYxYlMCV/ZhRCsFvpO50oZ3iWar4RNq9Xy3XffcfXqVQA++eQTdu/ezaNHj4DsX9Rnz54tsW+2FSpUYOzYsVhaWrJ3714CAgIAOHLkCN988w2//fYbS5cuzVWtKKlUiqenJ2vWrMHBwYGEhATDc9WqVaN8eWERaW5ERETw3Xff0adPH8LCwhg+fDiXL1/G1dWVDz/8sLjDy7czZ87wxx9/MHfuXKpVq8a0adM4ffr0K5cPhISE5FgfWprp9Xq+/vprzMzMijsUQRmx69wcWiv0XMx0I0ZlxUWlGa5SS1yllgCk60zoanmbCI0tvooEelo84tzFZdy6tIxY/zk81sq5r7ZlrONJqkqzk6tkvZpzmZWJ0SqYH9eUKTENCVLZcFedvaJowlNf9qfVYLv7CSK1qdiIM/nKLoQqUhGrkyvws/NVxjqeYkpMPVYkuXFaKaKvRSJe8jhWxbYxzP61VpTybEJQ6PJVg2PatGls2bKF5cuXU6VKFSZMmMC8efP4+uuv+fDDD9m/fz9PnmRXl27ZsmWJLJJpa2uLmZkZgwcPZt++fVy9epUbN24wY8YMnj17lqs1RBcvXiQpKYnKlSsjl8v55JNPDDMomZmZ2NvbG0qCCF6kVqu5ceMGkZGRHDhwgLlz5/Lpp58C2f0s//77b5o0aVIif35eRalUcvfuXe7evUtgYCD79u2jS5cu2NvbM2DAAE6cOMFHH31EtWrVOHv27Avn9+nTh2+//bbU99yMjIzkt99+Y8aMGcL6NUGR2nVuDmbAO0DSwy45enMqwNBJ4ORLzg2/8gOuTSZTR25KsDqNcI0NKr0DvSxiOKs0Za7jbdre6863Dpd4qNGzK92WppZh+CjCuaOSUEUqY1liMz4td5b9aTX42PohIKOWzIzWVoF0MlWxLc2Wy1nPaChXsKriJU5kSqglT2ZLSh2uJ1emZyF/fUq7sryGLV8J2+nTp+nfvz/16tXj0qVLTJ06lerVqzNt2jTWrl3LkydP8PX1ZcSIESXuzTYjI4Ndu3Zx6tQpVq5cSbNmzbhw4QK2tracP3+eqlWr5nqs06dPG4qCAtSvX5/69euj0+m4f/8+V65cYeTIkYX1Uko1pVLJ0qVLDYWJ/f39qV69uuF5sVhM165dizHCvPv222+ZPXs2Dg4OVKxYEScnJ1q0aEGrVq0AcHNz4+OPP0atVjN+/HgOHjxI586dDefrdDrmz59PixYtiuslGIVOp8PFxYWJEycKyZqg1Kkrh1XJLoyyjmR+dFN8rMKYmebJKLsL7EiryKyqe7AQK9iZXAuJSIdWL8bP9CEeMlPUeg0Ly98kUSfB1yyEGK2aK0p7elskYyPOYFqsN7Mdb3E00wyZSMWudEt0ejHBai31FBHcSX27SmMJjCtfCVtMTAzlypVDKpXi5+dH06ZN2bJlCwsWLKBdu3YolUrGjRtXopI1vV7PpUuX2LBhA82bN+fq1auGYrbnz5/P15jTpk3j5s2btG3bFq1Wi0Qi4dq1a1y8eJFx48blqF8nyKZWqzl27Bh79uyhZcuWXLx4ERMTk+IOyyjGjh3LgQMHCA8PJz4+nsqVK9OyZcsXXp9MJqNDhw5s2rQpR8KmVCoJDg7m888/L+LIjef5colx48bh6OhY3OEIBHm2//xCBjSfyDmlgjWVLpCoy+CGPBZXqSXBkjRqypWAGTMdstcrH8uU4vbvLdcDGdbIRFoydNl9QkHBDZGGHxOqIhNp6WJ1i0tKiNdYAAl0NovDVGTCT0mufGYTQR2XQ5x71KnYXrugZMtXRvXs2bMc3Q/kcjlDhgxhxIgRBAUF8cknn5SoZA2yN0asXbuWDRs2sG/fPqN1HmjQoAGWlpaG9XuNGjVi+PDhAMLswv+jVCqZOnUqQUFB7Nu3j7179741yRpA+fLluXLlCsePH+f3338nNDSUDRs25DhGp9MZemn+/zZnZmZm+Pj4cO3ataIM26gkEgmTJ08WkjVBqRaj0+BjouFyloaTmeVpZ6pFh45glRM/xPmwICG7DdXmVDtDQdxYbRoOklRcpYn0tkjm3L8d2HwVMfx62496po9orhATrranv2UCaTol99V67qgy8VaEk6LLNBTfFbyGsOkg99LT01GpVC/UHIPsW4LTp0+nWrVqRgnOmHx9fZFKpYXSj9LGxobMzEzD58Ii65dbv349tWrV4tKlS/j5+RV3OIVCKpXSoEED2rdvz9GjR7lw4YKhd+ajR4/o27cvq1ev5uTJk7Rp0+aF83v06MGZM2cICgoy/BFQWuj1ev78809MTU2LOxSBoECC1Xak6LPwMZHio4giU5/FWaWEUdaRzHW8zVd2IaTplLxnHsWxTCnB6uxOB80VYqrJst9W/RSwMdUee4kZE+ofp7VCT6Q2lWRt9vvDd7G+mIs0vH9+NIBhB6lA8Cp5viWalpaGXC4vVbNHKpWK4OBg1Go19evXN/r4pqamOeqvCXIKDw9n8+bNpKSklOrZo7wqX748NWvW5NatW/j4+LB7926cnZ2JjIzkxo0bODk5vXBOjx49+P333/n222+xt7dn5cqVxRB5/qjVaszMzN6qfsKCsin92neENZlMuiSVNn9NwuGaiMsLVnEiU0IbUzVixOxMc+VUohdSsRYHeRqNLcJoaxqDrdiMeF065cTmeMijESPFzyyYTL0YhUhMTUUkaTolXzqc5bHGhNlN9gLZbbUWJFSj5E13lCzCpoM80Gq16PV6w22d0uDHH38kIyODBQsWUKtWLaOPb2pqaphFEfxPRkYG69at49atW4wfP56pU6e+VbdAc6NKlSqEhoai0WgICAjg0aNHWFtbv/J4Nzc3XFxcSEpKYvz48UUYacHJ5fJSt1FEIHiV7MK3Ms72/JHuQZPZlW6JBB1itNxSKVkd3oILdXezI80apV7GB+apbE6tSEPFYy5mujPMKgY3qRKwwFqsIUMvRob43/IdCn54VosWFvdpa/qYDcn1aK4I5QvbIPYV8+sWlFx5TticnZ1xdHTkwYMHeHl5FUZMRnX//n3CwsKIj48vtL/8zc3Nc9wSLQsCAgJ48uQJlpaWWFpaYmFhgVQqRavVotVqycrKYu3atdSvX/+tqi2WVx9//DEjRowgIiKClStXvpCszZ49m0uXLtG+fXsGDx6MRqPhzJkzrF27ttQUon5Or9fz6aefsmjRolLZ91Qg+K9QTRqpOin15ZZ8P/EPnKQpNPy3L/RjjR1fVD0GQG+LZCI0qbQL+IgTNf8mSA1DrJ4yNKIVqyplFw+xFEs4kuFCY8VjknSpuEotGW13hT+SvOlg+oAHGeXBLpR95xcU2+stFd6CdWgFka8Mpnv37ly8eLHEJ2xnz55lw4YNLFmypFBv0zg7O+comPu2W7duHQcPHkQkElGhQgUSEhIwNTXF3NwcqVSKRCJBIpHQt29f5s6dW2pmYguDj4+PoWNGq1at2L17N8HBwbRq1YrU1FSWLFlCx44d+eOPP9i5cydbtmwptbcURSIRc+fOLXOzqIK3061Ly/jAbzqnlSIUIjWP1bYodak0V4ixFGfiJEljR5pz9gaDzMqcqPk3NS4OwNUukdGVTvO18yGeaKGqVEaGXouE7DZUAEHqdMpLxCh1MsI1qSSrTNl1bk4xv2JBSZevd4ZPP/2Uxo0b06lTJ5ydnY0dU4HpdDo2btzI9evXOXz4MM2aNSvU61WpUoUTJ04U6jVKkp49e+Ll5cX+/ftJTU3F2dmZ2NhYEhISqF+/PuvXry+RG0+K0r179xg7diz+/v54e3tjYmJC5cqVcXZ2pkqVKvzwww9YW1uj0WioUqUKLVu2ZPr06VSuXBk3Nzdu3rxJkyZNivtl5FlmZiapqalUrCjUkxKUfv8/iYoGdgFWjb7jseZ56Q5wk8UBYr6v+zeLQjrQwzwdsCBSm0qsNo2ZT9+hd7mrxOvSuah0oNu/+9IG2V4hXS+hT2TbonxZpZsww5Y3np6ejBs3jlWrVjFjxowSN4Oyfft2wsPDuXnz5ksXdhubu7s727ZtK/TrlBRWVlb4+Pjg4+OT4/Hk5GT+/vtvevTowfXr18vUTMt/13SGhYXxxRdfYGpqyvLlyw3dLoYOHYr831sqGo2GnTt3cuTIEVauXEnFihUNM2uTJk3iiy++oGLFiiXyD6LXCQsLQ6PRCAmb4K2Wcm0mbk2/BOSsTSnPMKsYdOhwk8WxsdY6vnvWlAE2V5CJwEVqgbkki+qyRMqJLfGQPQPMua5S4STRE6y2KeZXIygt8p1pzZgxA2tra7755hseP35szJgK5OrVq5w/f57Dhw8XSbIG2Qnss2fPiuRaJZm1tTUfffQREomEMWPGFHc4ReaDDz7AxMSEGjVq0L17d7y8vDh79ix9+vTJ0ZrsebIG2eU/+vbty5dffolEIsHMzIxTp04BMGTIEKZMmcLs2bPR6XRF/noKwtfXl5YtWxZ3GAJBoQu/8gMnMiUMs4rhnjqDcVE+HEqtS3mJBGtpBm5SBfdUDgDUMX/CkmetAZgT1ZkuD97FQZxFuNqc9GvfFeOrKF1EZO8SLchHaZbvhE0ikXDhwgUGDhzIzJkz2blz5ysbWheVJ0+e8Ntvv7F169Yi/Qvfzs6O9PT0IrteSaRSqbh8+TKrV6/m4cOHZeqWaFJSEl27dsXX15ekpCRWr17NqlWrsLB4cxFMR0dHevXqhb+/Pzt37jQ8PnnyZNRqNcnJyYUZutFpNBp+/PHHUpdoCgT50dgkjROZEi5mVGVq+RN8ax+IlTi7DuFPSR6sfNKGdSmODLOKYUmF60Rr05jjsp8DnodwkMhR6kvXxiJB8SrQvUyJRMI333zDtWvXCA0N5bfffjNWXHmWkZHBjz/+yLRp02jXrl2RXvvmzZtl/hbQ2bNn2bhxI02bNuXatWtMnTq1uEMqMj/99BPHjx+nUaNGfPbZZ5iZmeWqeHJqairTpk3j3r179O/f39Bz9LlKlSoREhLyyvM1Gk2JS4ykUilt27ZFry/lf8oKBLkQrJHQzlTLJ9ZP6Xl7KFUOZne50enFfG4bygHPQzmSsiSdiPISBbHaNELUOpKufV9coZdeQqeDgvHw8ODEiRMEBwezefPmIi8iq9PpWLFiBT4+Pnz11VdFem2AlJQUQkJCmDlzJrGxsUV+/ZKgWrVqyGQy5syZg6enZ3GHU6Rq1qxJq1atuHjxYq7PuXXrFjNmzKBnz56cP3+eTZs20bp16xzHfPLJJ+zZs+elO5Dv3LnD4MGD+fzzzzl+/HiJSZB0Oh2enp5IJJLiDkUgKHTlxP97r7vSYCdLWm0FYJJdKB0C3sM/S80o60gAUnSZVJRIWJxQi2C1GeGaslnqSJB/RtstYG1tzdmzZ0lNTWXixIlcv37dWEO/0Z49e0hLS2Pz5s1Fds3/ev/99/nrr7/o2LEj8+fPL5YYipurqytpaWkv9McsC27cuMHly5epWbNmro9fsWIF33zzDatXr37lcSNHjsTb25tJkyaxdOlSw9dWp9OxdetWFi9ezO+//8727dt5+vSpUV5LQcXHx/P998KsgaBsuH5pueHfiboMotS2rEtxZGOqPRYyFZZiFdHaNILU6cx+5svW1CpMsgvg7+QGdDPLKMbISy+RXl+gj9LMqAWf3N3dOXHiBH/++ScTJkzg5MmTtG/fHjMzM5KTk/H09MTGxsZo18vKymLLli1cu3aNS5cuFVuxTisrK7p06UL9+vVf+wb8NhOLxdSpU4ddu3aVqduhOp2Ohg0b8t57771x3Z5Op2P37t0cO3aMbdu20alTp9ceb2JiwrZt24iLi2PZsmUsXryYRo0aER0djaWlJaNHjyY+Ph4zMzNSUlJKxI5SBwcHFi5cWNxhCARFZm1KeXxNw/CSmdPY9CGNTWScVorYWe0An0W2Z2L5Y3jJzFlY/iYAhzPNmF/+n2KOWlAaFUo9jj59+hAcHEzLli05cuQImzZt4q+//mLx4sVGu0Z4eDhfffUVKpWK27dvU7VqVaONnV/W1tZluqdow4YN2bevbDVWEYvFDBkyhEuXLr3QJzUyMpLdu3fz888/s3r1apYtW4a/vz/+/v5vTNb+y97enlmzZnHz5k3s7e0ZPHgwp0+fRiKRsGTJEipVqlRibkNHR0fn6dawQFDaDbOKQSbSsy7F8d92VuAhS0EmkjLQ/gIbEn0495/OhU6SFPyz1EKh3Pwo6Pq10j3BZtwZtv8yMzPjxx9/NHz+4YcfcunSJfR6fYEbx4eFhTFv3jxmzpxZovotmpmZGRaCl7TadEVBoVAQGRlZ3GEUuT/++IMdO3bw6aef8uzZMzp16sSdO3dYvnw5Xbp0oVu3boaCsv369cv3Hxeurq4v3PZ/+vQp1apVKzE/b3q9vsy1aROUbbvOzaFt8wn8k16JYNMwPGQW2IsV3FFl0lxhSnPFXcOxQep0bijdsf5nXDFGLCitiqQHzt69ezl9+jTz589ny5YtBAcH0717d7y9vXM9hlKpZNeuXaSlpXH9+nV++OEHPvnkk0KMOu/EYjEmJiYolcpc7RJ822zZsoV58+YVdxjFonfv3nh5efHuu+9y5swZYmNj2bJlC926dSvU68bFxVGpUqVCvUZeVKhQgQoVKpCZmYmpqWlxhyMQFImTF5bQArgd0pPb/3n8ZSt6rV/ymECQG0XyZ/m+ffuoVKkSqampHD58GK1WS1hYWK7Pj4qK4uuvv0apVNK2bVs2btxY4pK15ywtLYmLiyvuMIpFWlpaobcBK8nq1KnDO++8Q0JCApUrVy70ZA3g2bNnOYrzlgS3b9/ml19+Ke4wBALBW6gsF84tkhm2WbNm8cknnzBhwgSqVavGO++8w/nz51GpVMTFxfHo0SMcHBxwdXVFLpejVqu5f/8+t2/f5s6dOzx9+pTJkyfzzTfflJhbP6/So0cPjh07xscff1zcoRQ5nU5XahuXG8OuXbv466+/8PX1NermmldJSkri7t27jBgx4qXP379/HxcXFywsLNBoNCQkJODo6FjocdWqVYvatWsX+nUEAoGgLCmSd1dnZ2cOHDhAcnIyMpkMnU7He++9x9ChQ7GxscHDw4OnT5/y5MkTHBwcSExMxNXVldatWzNs2DA6duxYavpSTps2jdq1a9OlS5cia41VUpTlhC0iIoIRI0YwZswYNmzYkGP9ZmFZv349Xl5eOWbY9Ho9iYmJ2NnZcfPmTSQSCbGxsdja2rJnzx6mTJlS4DWkbyKRSLh37x4SiQQvL69CvZZAIChjSvksWUEU6burtfX/7t4fO3aMqKioHB0ClEolN27coGrVqpQvX74oQzMaNzc3xowZw/Tp06lUqRJTpkwptnIjRa2oEzadTkefPn04c+YMSUlJbN68mT59+hTZ9f9r0aJFeHt7k5ycjFwup1evXoV+zc2bN9OiRQsgu/6ZXq/HwsKC77//nkWLFtG3b18AgoKCcHd3Z8qUKWRlZbF//3569uxZqLPVarW60BNDgUAgKEuK7f6iWCx+oZ2TQqHA19e31CZrzy1cuJDY2FhSU1OJjo4u7nAKnV6v59q1a6jV6iJJ2M6dO8eZM2eYMWMGe/fuJTU1FY1GQ0pKSqFf+1WsrKzw9/dny5Yt/PLLL4V+6/7Ro0fcu3ePKlWqAHDlyhWCgoJQKBQsXbo0R6eBrl274uTkhEgkQq/XY2VlhUgk4ubNm6SmphZKfPXr16dy5cplusyNQCAwPmENm8DoFAoFtra2pKWlFXcohS4kJITffvuN/v37F+rareDgYEJCQujRowfm5ubY2Nig0Wjo3r0727dvL9bbsVOmTKFly5Z4e3tTrlzht5zZv38/tWrVYvny5XzzzTd07tw5V+eZmprSsWNHIPvrWb58eUxMTJDL5UaP8cCBA9jZ2dG+fXujjy0QCARljZCwFSIrKyvS09OLO4xC9+DBA9q2bcsff/xh9LF1Oh1z585l48aNPHnyhKysLLp160aHDh2YNGkSdnZ29O3bt9jXzpmbm9OhQ4ciu15ISAhOTk5MnDgx37N5z28fr1q1itq1axturxpDZmYmzs7ONG/e3GhjCgQCgbCGTVAorK2ty0TCFhMTk+s+mnn12WefsX//fgYNGkStWrW4e/culSpV4vr165QrV45169bRrl27Qrl2Sfbw4UPKly9vlFuvI0aMQKfTcfr0aZo3b45MJivQeCqVColEwoMHD/D19RXWsgkEAoERlOwaGSXEzp07WbNmTZ7Ps7GxKRO3RGvUqFEo7YjmzZvHnj17+Prrr6lbty4SiYR69eqhUqk4cuQICxcuLBXJmlKpRKvVGnVMuVxutPVhYrEYqVRKdHR0gf/ASEpK4ssvv0QmkzFs2LASX4ZHIBCUIgVcv1ba17AJv01fQ6lU0rNnT3r37s3w4cPzfH7lypU5e/Yst2/ffvPBpZi5uTkqlcqoY4aEhDB//nwmTZqUY13ctWvX+Prrr2nVqhW9e/c26jWNKTk5mV9++YW2bdtiY2PDtGnTjDp+y5YtuX//vlHH7Nu3L6ampgX6ebWxseGHH34QZtUEAoHAyISE7RXCw8Np1KgRp0+fRiaTcePGjTyPMXPmTL744guWL19OSEhIIURZMuh0OqO+QWu1WgYOHEinTp1e2El87949Q62z4l639jJnzpzh3XffxdnZmV9//RUPDw8mT57MmjVrUCqVbx4gl9555x0CAwPR6437J2NiYmK+ftYBTp48yeHDhwtlA4NAIBAAQvN3Qbbo6GiOHz/O2bNn2b17N+3atcPCwoKuXbvSoEGDPI8nlUoZP34827ZtIzExsRAiLhlkMplRk5F+/fqRmppKjx49XnguIyOjSLoI5EVCQgJ//fUXP/30E48fP6ZTp04sX748R0Fbe3t79uzZY6iNVlAeHh6IRCKSk5ON+vVwcnJiyJAhxMbGolAoXtr2KiQkhISEBJo0aZLj8YYNG6JWq40Wi0AgEAj+R5hhI/vWZ9OmTalSpQoLFy4kISGBzz//nF69ehEaGsp7771XoPFdXV2JiYkxUrQlj5OTE0+ePEGn0xV4rLVr13Lu3Dm+/PLLl86gZWZmlpiE7ddff6VatWo4OzuzZMkSWrVqxc8//0yPHj1eSHRatWrFV199RXh4uNGub2lpWWhrJM+fP09AQAB6vd4wi7d7927S09NRKBTo9Xp0Oh1Hjx41rM+Lj48vkpImAoGgbBJRttewCTNswLBhw9Bqtfzxxx85Co5C9k7P27dvU6dOnXyP36BBAw4dOlTQMEssOzs7zM3NOXbsGO+8806Bxtq4cSM9e/bEzMzspc9nZmbm6JhRXJ48ecLkyZMZM2YMderUeePOyvbt25OSkkKLFi04ffo01apVK3AMlpaWhbYLuWfPnkD2msE7d+4wdOhQbG1tUavVVKxYkYoVK5Kenk5CQgJisZjjx4/z559/MnLkSBo2bFgoMQkEAkFZVuZn2H799VdOnDjB2LFjX0jWADp16sTSpUsLdI3WrVsbfYF4SSISifD29mb//v0FHiszMxNLS8vXPl8Sdh6OGzeOFi1a4O3tnesyGD179qRNmzb4+fkRGBhY4BisrKwKfRdyw4YNDUV527Rpk2N209zcnL59+yISifDw8GDo0KFUqFCBp0+fFmpMAoGgDNPrC/ZRihX/O18xSk5OZvr06Xz66adYWFi89BhfX18CAgJ49OhRvq/TpEkTMjMzmT59+lu7YzQhIQF3d/cCj6NWq1+aOD/XsmVLpkyZUqz17c6cOcOpU6fy1S+0e/fudOrUidatW/PPP/8UKA4bG5tC/zqIRKJctYqrXLkyzZo1o0KFCixdupSMjIxCjUsgEAjKmjKdsE2ePJkaNWrg5eX1ymNEIhFqtRoHB4d8X0csFjNr1iyqVKnC9evX8z1OSZWUlMTt27fp1q1bgceyt7cnOTn5lc97e3vz8OFDvvnmmwJfKz90Oh1jx46lT58+r0zy36Rz58689957tGvXrkAzbSWxzp9IJGLBggXIZDKioqKKOxyBQCB4a5TZhC0wMJAtW7bw0Ucfvfa4jIwMTExMXrqm6v79++zduzdXDd7HjRvHxIkTCQgIyHfMJdXevXvp2rVrjnVZWVlZfPzxx+zevTtPY7m4uBAfH//S5zIyMvj2228ZOXIkkydPLlDM+fXzzz+TkZFB27ZtCzROhw4dDIlbfmfJbG1tS2wnjdDQUKPcIhcIBIL/KsubDspswvbZZ5/RqVMn7O3tX3ucVCpFo9HkeCwgIIAqVarQqFEjevToketdpK1atSImJqbEzYoUREJCAmfOnGHOnDk5Hl+1ahVr167lgw8+yNPrvX//Pra2ti997tSpU9SrV49Vq1bh5ORUoLjza8mSJQwYMMAo6+i6du2KlZXVC1+73HrZz2ZJ4eXlxYgRI3j69Cn+/v7FHY5AIBCUemUyYTtw4AC3bt2ie/fubzxWJpO9UFtq9OjRiEQi/Pz8aNCgAUeOHMnVdU1MTKhZsyZBQUH5irskOnbsGF26dHlh/dqePXuA7NvOebl1eOPGDWrUqPHC4zqdDn9/f/r161egeAsiJiaG6Ohoo/VNFYlEvPPOO+zatStf5z948CBX68uKU2ZmplFr9AkEgjKsoEVzhRm20uXy5csMHTqUgQMHolAo3nj8pUuXcHV1zfHYjz/+SM2aNQkLC2Pnzp15qgvWsmVLbt68mdewS6zMzMwXkrXo6GiuXbuGt7c3dnZ2eRqvR48eHD16NMdj169fZ9KkSUgkknwt9DeWy5cv4+bm9tpNEXlVp04dYmJi8rwB4cSJE1y5coX69esbLZbC4O7ujp+fX3GHIRAIBKXeW1mHTafTsXv3bgIDAzExMcHOzg4LCwsOHTrEnj17GDx4ML6+vm8cJzMzkw0bNrywDqtx48b5Xp8zfvx46tSpw4cffvjSKvKljYWFBU+ePMnx2M8//0ydOnUICAigQ4cOeRpv6tSptGrVynDb8fz582zevJlly5bRr1+/Yi3pERkZ+crbtfklkUho1qwZa9asYfny5bk6JyAggAEDBjB06NA8J8RF7fTp0yQkJBjqugkEAkFBiApen73UemsSthUrVvDkyRNEIhG7du0iKysLDw8PNBoNGRkZZGRkULVqVb7//nucnZ1zNeaVK1eoXbs27dq1M1qcbm5utG3blqNHjxbrbJGx1KtXj9WrV+d47NSpU6jVaqpWrYq3t3eexqtbty62trZcvHiRGjVqsG7dOg4cOECLFi2MGXa+PH78uFCK9vr6+rJ69WqWLl36xoT0+PHjfPjhh3Tv3p3mzZsbPRZja9asGampqcUdhkAgEJR6b0XCNnv2bFasWEHDhg3R6XR07twZHx+fAs/GXLx4keHDhxspyv/55ptvaNeuHd26dcPExMTo4xelSpUqERUVhVarRSKRkJ6ezu3btzE3N2f27Nn5GvPXX3+lW7duNGnShL59+5aIZA3gwoUL1KtXz+jjenp6otFoGDBgAD/99NMr2zutXr2aSZMmMWrUKBo1amT0OIzt2rVrWFtb4+HhUdyhCASCt0UpX4dWEKV+Ddu+ffv48ccfmTp1KoMHD2bo0KH4+vqSlpbGunXrGD16NL/++isRERF5GjcuLo7g4GAGDhxo9JgbNWpEnTp1OH36tNHHLmppaWk51gKuWbMGiUSCRqNh0KBB+Rrz5MmTeHl5ERgYyMiRI40VaoFoNBpu3rxJ7dq1jT728zp9MTExeHp6snz58hx9WTMyMpg0aRJTpkxh2rRppSJZg+ylCbntAiEQCASC1yvVCVtoaCiDBw/ms88+o0KFCjme27x5M2q1mr/++gsbGxs2bdqUp7HXrVvHwIEDC22d2dSpUzlw4IBRGqYXp9u3b9O4cWPDQvy1a9cC0LdvX+RyeZ7Hy8rK4pdffqFDhw6oVKoSs6h+wYIFuLq6FtqaMSsrK0aNGsWECRNYsmQJDRs2ZNSoUdSrV49y5cpx6NAhZs+ebZRuEkWlcePGuLm5FXcYAoHgLVKW67CV6luio0ePpk2bNtStWzfH4893KQYHB1O+fHnOnj1LYmJinsZOTk42SuX+V+nSpQu2trZcvXoVHx+fQrtOYbtz546hPMqNGzcIDw/H0tKS999/P1/jbdu2DZ1Ox4YNGxg7dmyJ6BsaHh7ODz/8wPTp0wv9WtWrV2fevHmcOHGCmJgYunbtiqen50sLN5dkOp2OiRMnMmvWrHx3hBAIBALB/5TahG3fvn3cvHmTxYsXv/Dc3r176devn6FGVXh4+BsL5P5/arUaU1NTo8T6KpMnT2b69OnUqFGjUBazFza9Xs+9e/dYvXo1586dY8yYMbRs2ZLDhw8X6LZd06ZN6dmzJ6NHjzZitPkTExND27Zteffdd4tstkgikdCxY8ciuVZhEYvFfPfdd0KyJhAIjEdPqW/gXhDFP32RTxMnTmTAgAEv1FJTKpVcunQpR6/JiIiIfCVsuanTVhBDhgyhW7duzJw587X9M0uqmJgYJBIJ1apVo1evXnh7e+Pr60u5cuXynYAOHjyYY8eOlYhkLTk5mTZt2lCjRo18zxiWVUFBQdy4cQO9Xs+6detKbEcGgUAgKC1KZcIWFRVFVFTUS28l+vv7U7duXZydndmyZQvnzp0jKioqX83btVqtMcJ9rZUrV9K+fXt+/fXXQr+WsQUGBlK3bl3++usvzM3N6dKlC7/99hv9+/cv7tCMYsGCBZibmzNo0CBEIlFxh1OqmJmZGf5IcnV1LfVrNQUCQckgrGErZZ7/ta7RaF5Y2H7hwgVat25No0aNiIuLIzk5mZSUFIYNG5ana1haWvLs2TOjxfwqYrGYn3/+mcqVKxMWFlaqFpVfv36dvn37smrVKtq2bcvjx4/JyMhg4cKFxR2aUYSFhVGrVq0SsY6utHF1dTV0CGnTpo2QsAkEAkEBlcp3oooVK+Lr68v8+fNJSkoiPDycpUuXMmHCBG7fvs2aNWuoXr06Cxcu5KOPPgLA3Nw8T9fIysoqsk4E5ubmjBo1Kt89JYtDWload+/epV27dly5coUWLVpw584dmjVr9tYkOE+ePMnzrXTBi44dO8bGjRuLOwyBQPA2KMO9REvlDJtYLObQoUOMGTOGSZMmATBu3Dg6duzI559/ToUKFQytcNq0aYNMJsvzmiqlUlmkGwGmTJnCypUr+fvvv+nQoUOhr58rqO3bt9OpUye2bdtG48aNMTc3586dO4VSaLi4REdHCwmbEbRv3764QxAIBIJSr9RNhSQkJPDxxx/Tq1cvevTowbFjx7h37x6zZs3i0qVLpKen51hDJRKJ8PPzy/OsT1ZWFiqVytjhv5KFhQV//vknjx8/5osvviA6OrrIrp1XISEhXLlyhZ9//pnNmzfTpk0bNBoNgYGBvPfee8UdntHEx8cbvXdoWSQWiwkPD+fPP/8s7lAEAoGg1Cp1CduGDRs4e/Ys1tbWDB06lJEjR7Jq1SqioqK4ceMGPj4+SKUFnzh85513GDRoEPHx8UaIOnfat2/PqVOnaNGiBdeuXSuy6+bVli1bmDJlCnfv3kWlUlGjRg0ePHiAi4tLrvu0lgYqlarUtw4rKWxsbEpNhwaBQFAyiRA2HZQq8fHxVKtWja5du9KpUycuXbrEkSNHOH78OAkJCUZrqN69e3eSkpLw9PSkS5cuiMVidDodOp2OqlWrMnPmTKNc52V8fHw4ePBgoY1fEE+ePCEyMpLPP/+cefPmUadOHUQiEXfu3KFly5bFHZ5RaTQaoyT/ArCzs8PGxoatW7fSt29fYdetQCAQ5FGpm2FLTEw0VH2XSqX4+fnxxRdfIJFI0Ol0RmvOLRKJGDx4MBMnTkSr1aJWq9Hr9YhEIn7//XdDCyZj0ul0hIeHc+PGDSwtLY0+vjGcOXOG999/HxMTEyIiIgyNyu/cucO7775bzNEZl1qtFhI2IxKLxZibmxdJuRyBQPAW0usL/lGKlbp3o8TExBeqp0ulUj7//PNCuZ6HhwceHh45HrO3t+fnn3/Oc6mQ19m7dy9DhgxBo9FgYWHB999/b7Sxjcnf358NGzYA/5uBysjIICIi4q1K2J6XjnneI1VgHN27dxdKfAgEAkE+lMoZtryW6DA2lUplmFkyFgcHB8RiMb/99hvLly/HxsbGqOMbQ1RUFFlZWbRp0wYAuVyORqPh7t271KpVq9i/L8akVCrzNLuWkZHBtGnT0Ol0HD9+3LDAfvfu3cTGxpKWlsbFixcB2LlzJ1evXjWcq1KpSE1NLVC8er2ePXv2kJaWxuXLl/n7778LNF5huXbtGj/99FNxhyEQCEqpsryGrdQlbMnJycWeGNy/f58mTZoYdUwfHx9q1qzJzp07jTquMfn7+9O6dWvDjluZTGZI2J4ncW8LpVKJTCZ743Hnzp3jwIEDmJmZMWbMGMOu5M6dOwPg7OyMqakpKpWKJ0+eANC6dWs8PT2JiYkhNjaWsLAwVq9eDWQneHfv3kWn07Fjxw50Oh0qleqNs1IikQgbGxs0Gg2enp40bdq0gF+BwlG/fn3Gjh1b3GEIBAJBqVPqErb09PRCb8r+nE6nIy4uLsdjycnJ+Pv7G6390vbt2xkwYABPnjxh5cqVHD9+vEjLieTF9evX+eCDDwyfm5ubk5GRwT///EPXrl2LMTLjy8jIeOUMm06nMxRtrlGjBr6+vkB2QWeRSISJiYnhtr2Pjw+WlpbY2dnRp08fIPuWuo2NDZcuXSIqKgovLy+++OILABo1aoSLiwuQnYSJxWLOnz9vuA2dnp4OQFxcHA8ePABg6dKlREZG0rp1a2xsbLCzs0MsFhMWFlZIX538k0qlXL9+XegtKhAI8qcMF84tdQmbSqXK1cxHQel0OpYuXcr48eMJCQkB4NGjR3z33Xf069ePmjVrGuU6Dx8+ZPPmzdSqVYsffvgBnU5HRESEUcY2puTkZCIiInLUWfPz8+PgwYOYmZnRokWLYozO+NRq9Qu1+3Q6HQEBAYjFYvr06YO1tTX29vb5rtXWo0cP6tevn+MxV1dXbG1tEYvFhh3Pbdu2ZeDAgajVaiZOnIhGoyE2NpbQ0FAge11YhQoVcowTERFh+Lktae7du0daWlpxhyEQCASlSqnbdFBUCduxY8dIS0tj6dKlfPPNN7i7uxMcHMxXX33F1KlTjXadL7/8kmXLlvHRRx/x4MEDBg8eTNWqVY02fl5lZWXx8OFDVCoV1apVM+zI3b9/P35+fobPAd59912mTp3K+++//9Ytzi9fvjzp6emGncEAqampHDlyBC8vryLv+SqRSJBIJPzyyy+IRCJq1qxp+KPhZbF4e3sDcOnSJWrUqFGi1kQac7OOQCAoW0r7OrSCKHUJm0ajKZKE7ebNm3z66aeMHDkSBwcHnj59Sv/+/Y2+2UAikdCzZ08CAwMZOnSoUcf+/54+fcr69euJiYkhLS2NtLQ0zM3NqVChAk5OTmRmZnL37l0qVaqEXC4nLCyMTp06YW5uzsWLF7l582aO8eRyOXPnzi3UmIuLhYUFMpmMjIwMYmJiOH78OCNGjGDChAnFGlde65dFRUVRvXp1Hj16xOHDhxk5ciSxsbFYWFjkSL6LgkajYf369dja2hpaxwkEAoEgd0pdwmZubk5SUhKurq6Fdg2tVktQUJChTEXv3r2NNnZgYCCffPIJQUFBWFhY0KZNG7p168aQIUP44IMPCrXh/M6dO/Hw8GDVqlU4ODjg4OBATEwM9+7dIzAwELlcTt++fXFycgKyW1ANGTKEuLg4Tp8+bVhbVVZYW1sTERFBtWrV6NixY3GHky/P1xyamZkZfp6PHz+Op6dnkXUe0Ol0JCYmYmdnh1arxdramoSEBEO/XLlcTnp6epH27hUIBKWQHtCV3Sm2UreGrW3btty6datQrxEeHk65cuWMnhTOmzcPHx8fXF1dmTVrFiNGjCAhIYGhQ4dSqVIl9u7da9TrPRcVFUVcXBwVK1ZEKpXSuHFj3NzcMDc3x93dnW7dujF58mQ+//xzQ7IGUK1aNc6fP09QUJDR1uyVJjKZjL179yKTyXBzcyvucApEoVAYfp4/+ugjGjVqxOnTpzl06FChXzswMJDNmzcjEokYMWIEarWa1NRUfv/9dyIiIsjMzGTBggXoS3lRS4FAIChMpW6GrWfPngwcOJBBgwYV2jUCAgJylEVIT08vUCkRjUbDoEGDOHfuHN999x2VKlUCsncLenh44Ovry+zZsw3FZ+3t7Qv8Gp47cuQIO3bsQK/XY2JiQu3atY029tuuSpUqRuucURI1aNAAlUqFRqNBLBa/sMnCGGJjY6lVq1aOhL9Tp04AjBkzxrAT97vvvgPIkbQ9fvyY48ePC2veBALB/5Thv+tK3Qxby5YtSUxMJCUlpdCuERoaSvPmzQEMnQc+++yzXJ2rVCo5ffo0q1evJjk5GYCuXbty+/ZtZs2aZUjW/uv8+fN069aN3r17s2vXLqO9jn379nHo0CEuXrxIYGAgf/31F8eOHTPa+G87U1PTt7r8hLW1NQ4ODvz999/s37/f6ONnZGSwbNkyVCrVS9fe/bdsiomJCb/88gt37txhw4YN+Pv7Y29vT+vWrQH4888/SUhIMHqMAoFAUFqUuhk2tVqNWq0u1AXTERERNGzYEMjeNQmwYsUKRo0aRa1atV57bt++fbly5QpmZmZs3bqVkydPUqFCBTIzM185S3fhwgVOnTqFk5MTnp6edO3atcDrxc6fP8+RI0e4ePEi1apVAyhza9AK6nknh7dd9+7d0Wg0xMXFodFoctwWz6/o6GgcHR2ZPXt2rjdK9OnTBzs7O5ydnbGxsUEqleLu7o5er8fR0bHE9tcVCARFpyzvEi11M2z379/H1tbW6E25AwICWLlyJatWreLJkyeGhM3c3BwnJyfq16/Pjz/++MZx7t27x6hRo/j+++85ffo0SqWSCRMmcO/evVeeo9frUSgUlC9fnmHDhrFx48YC9Vt88uQJ69atY+/evYZkTZB3zzs5vO0kEgkmJiYEBQVx+/Zto4z5999/c+fOnTztarW3t0csFmNvb5/j/2+RSETr1q25du0a165dM0p8AoFAUNqUuoTt8ePH2NnZGXVMf39/ZsyYQcOGDXF1daVv376GGbz09HSePXuGWCzG09PzteNs2bKFlJQUqlatilKpxMzMDIVCQUhIyGt3f7q5uXHp0iUA5syZQ2ZmJnv27Mn36zlw4ABDhgyhWbNm+R5DkJ2wabXa4g6jyLRo0YKOHTsSGhqKWq1+4/E6nY7169ej0+nIzMw0FMNVqVQMHz6cunXrGjU+R0dHypcv/8LjO3bs4NatW2RkZDBp0iQguyyPsZJPgUAgKAlKXcIWGRlp9O3/DRo0oHHjxkRFRfHHH3+wdetWw3MKhQKtVsv169cZOHDgK8dISUnhiy++YPjw4ZiYmAAYFnF/9dVXhoXWL+Pq6mqocWZmZsa+ffvYt28fSUlJ+Xo9kZGRtGvXLl/nCv7H2dmZ6Ojo4g6jyJ04cYKoqKhXPh8WFsbWrVvRaDQ4OzsjFou5fPkyBw8eBGD+/Pncv38/zzXj3qRcuXKGjg56vZ7z58+jVqtp3rw5VatWRaFQMHnyZCB7/eHz/3cLc72rQCAoYnp9wT5KsVKXsD19+rRQqrZXr16dU6dOvfC4RCJh7dq1DB8+nIoVKxoev3HjBh07dqRZs2Z0796dJk2aUL16dUOrIYVCQUZGBnv37iU+Pp5WrVq98tqWlpaGDQqQXU6jcePG+Z4hSE9PN/osZFnUt29f/P39y1y5iREjRuDq6oq/v/9Lb82XL18eb29v5HI5HTp0AKBNmzaGXqnffvstXl5eRo9r3bp1hISEkJWVhUgkIikpicjISJydnbG0tEQsFuPo6AiAl5cXnp6e+Pv7s2PHDqPHIhAIBEWtVCZsxiwuq9Fo+OGHH7h16xYbN2586TFDhw5l9erVOR7buHEjz549w8/PDycnJ7p168aYMWMMz8tkMnr06EGPHj3w9vZ+bckEnU7H3bt3DY29Ifv2T377LVasWJGjR4/m61zB/zRu3BhTU1NDz86yJCsri2vXrqHRaHjy5AnPnj0jMzOTWbNmYWJiQvXq1Ys8pnHjxuHu7s7UqVPJyMiga9eub6yP5+Pjw9ChQ0lLSysT6xEFgredSF+wj9Ks1CVs0dHRRp1h2759OyYmJly/fp327du/8rj/v5apefPmREdH4+DgQIcOHWjSpEmOpEwkEvHhhx+ybt26V7ac0mg0+Pv7s2/fPq5fv86SJUsMzyUnJ+e79lvnzp1ZvXp1mVp/VVj8/Py4evVqcYdR5BQKBaNHj0Yul3Pz5k3u37+PQqGgf//+xdY3ViwWI5fLmTNnTp52iYvFYjZv3sz169cLMTqBQPA2EIlElUQi0SmRSBQoEonuiUSi8f8+bicSiY6JRKLgf/9rW9SxlbqELTk5mcTERKOMdfXqVU6cOMHmzZuRy+UABAcHM2jQICwtLfH29iY8PJzdu3ejUCgMC5oB3n//fUaMGMHs2bNJTU195TXMzMwMY/9XSEgIkyZNYv/+/aSnp+Pn52fYeADZ3Qny27fU09MTExMTw5oiQf7ExMSwbds2zp8/X9yhFKt3332X5s2bIxKJcHd3N/ratLwyNTXN8zkjR46kadOmnDt3jj///LMQohIIBIVOb4SPN9MAE/V6fQ3ABxgrEolqAlOAE3q93gM48e/nRarUJWwLFy7k6tWr/PzzzyiVynyPc+7cOdatW8dff/2Fo6MjO3bs4N1338Xb25uEhATmzJlD1apV8fLyYujQoQwaNIg1a9YYZq0kEgkzZ87EysoqzwlkTEwMCxcuZPr06dy9e5c6depw+fJlvvjiCyD7Fml4eHiONXN5IRKJaNas2Stv8Qpy53kx2bi4ODIyMoo5muJz+vRp1q9fX9xhGEWdOnXo0qVLcYchEAhKKL1e/1Sv19/499+pQCDgArwHPP9FuB7oUdSxlbrCuU2aNOH27dsMGDCAyZMnM2zYMMNC/9zKyMhgw4YN7Nmzh9atW2NnZ4eDgwONGjVi+fLlWFhYANmFPLt06YJEIkGhUHDkyBHOnTtnqL4O2TtML1++nKe+o+fOnaNz586GNW8nT55EJBIZZtRUKhWZmZkFuvWrVquNNhNZVj3f9FGrVi0ePHiQ55+zt0X79u1zVeajNLCxseH06dM8ePCAESNGFHc4AoEgD0SAqAg3gYlEIjegAXAFKK/X659CdlInEokciyyQf5W6GTbIbqnz999/s2DBAtauXcuiRYuIi4vL9fnP+yf6+fkB2SU5ZsyYQY8ePQzJ2nPm5uYoFAoAateuzYEDB3I8P2PGDI4cOZKn+KOionIkePb29jluf167di3XpUvS0tJemGkMDAzkxIkTL2yUEOTNtm3bAGjatCkPHjwo5miKh0aj4fDhw0YvVF2cWrZs+cp1pQKB4K1nLxKJrv3n46V/uYlEIgtgF/C5Xq8vEbWBSvVv4UGDBvHBBx8wefJkJk+ezJIlS3KV6NjY2GBlZcWVK1fw9fXNddmGhg0bsmPHDn744YccY+V1EXaXLl2YN28eWq2W77//3pAQPrdy5UrMzc05ffo0tWvXztEMXq/X8/jxY27cuMGNGzd49OgROp2OSpUqUb16dRwdHfn7779Zvnw57u7ueYpL8D9xcXHExsbSpUsXUlNTC7UVWkn2vCBuca9bM6bnNebyu+RAIBAUo/w3AXouTq/XN3rdASKRSEZ2srZZr9fv/vfhGJFIVOHf2bUKQGyBI8mjUjnD9l/m5uasWLGCmjVrcv/+/Vyf5+LiQmBgIECuE7a6desSHx+fY9dgdHR0nnscVq1alenTp7Nz505WrFjxwvPz5s1j5MiRBAYGMmXKFMaPH8/vv//O2rVr+fTTT1mwYAEajYZvv/2WZ8+eERcXx+LFi/H09CQ1NZWpU6e+tsiv4M2+/PJLILuky71796hSpUoxR1Q8LCws6NmzZ3GHYVQPHjwgNrbIf9cKBIJSQJT91+kaIFCv1y/+z1P7gMH//nswsLeoYyvVM2z/1aBBA8LCwmjSpEmujq9QoQL//PMPAFWqVOHBgwfUrFnzteeIxWIaNmzIn3/+abiOWq0mKysLnU732lpr/1+VKlVo2rQpd+/efeG5ypUrM336dKZPn45Wq+XixYvs37/fkKQ1bdr0hWt169aNbt26vfaaWq2WwMBAatasmadYy5p79+6xbt06FAoFXbt2Zfr06cUdUrHZsmULFSpUoG3btmzbto0ePXq8MCNc2rRp0+atmjEUCMqSIljD1hwYCNwRiUS3/n1sGjAf+FMkEn0MRAC9CzuQ/++tedcuX758jsKzb1KtWjVDXaZOnTrh7++fq/PCwsJo3ry54XM/Pz8cHR05e/ZsnuJVqVS5mhGUSCT4+fmxYMECFi1aRLNmzfKdbC1fvpw6derQsmXL17YeKuueL0ZftWoVZ86cwdbWloCAABYuXEhwcHAxR1e0+vbtS5MmTdDr9chkMkPbtdJq3759QucDgUDwSnq9/rxerxfp9fq6er2+/r8fB/V6fbxer2+n1+s9/v1vQlHH9tYkbLa2tmRmZub6+JiYGFxcXAAYOHAgFy5cyNWuSgsLixy9CcViMfPnz2fbtm1s376dlStXsnfvXh48ePDSwrUhISGsWbOG0aNHU6FCBVatWpXrmAtq/fr1TJgwATs7O+rWrcvu3bvffFIZs2XLFi5evEiDBg0YPHgwHh4eVKpUCZ1Ox/Dhw/Hw8CAgIKDMlPmQSCRYWFiQmZnJhQsXClRKpyR455136NWrV3GHIRAI8qNo6rCVWG9NwpaVlZXrGbbQ0FD279/PyJEjgez2Na1atWLHjh2oVKrXnmtiYkJ8fDxz5swxtLrp0qULAwYMQKFQ0LFjRzQaDStXrmTz5s05zg0LC2Pu3LlUq1aNy5cvc+DAgSKdsYiKisLd3Z2BAwcycuRIhg8fzvDhw9/4msuK0NBQ+vfvD2CoO1alShUUCgUKhcLQn/XatWskJiaSkZGRp1nd0kalUhnWd5qZmbFw4cJ8Fa0tSUxMTEhISGDFihVlrkesQCAo3Up9wqbValm7di0zZ86kWbNmbzw+ISGBhQsXsmjRItq1a2d4fN68eaSnpzNu3DgOHjz40iQmPDyc27dvEx4eztdff52j1+eyZcvYtGkTU6dOZdu2bWzbto1r167lOD8qKoomTZrw888/v3G9nLGpVCoSEhIM5UPq16/PggULOHLkiHCLiOzyFV27dgVg9uzZ1KlTx/Bcenp6jnVbgwYNwsXFhdu3bxuq5r+NSe/YsWPJyMjg9u3bLF269K0p7WFnZ0erVq2KOwyBQJBnetAX8KMUK9UJ24kTJ/Dy8jKs6/L29n7jOcePH6ddu3YMGzYMnU7HokWL2L9/PzVq1ODixYvs2rWL4OBgxowZw5o1a7h37x7BwcGcPXuW2bNns3jxYv744w+A1xa2bd68OSkpKTnaVsXFxeHi4oJOp+Pnn38u0jd5vV6Pm5sb8+fPJzIyEsiO387OLk+3kt9WQ4YMISgoiPbt2zN16tQcz8XHx79Qnw+yZ2aHDBmCSqVi/PjxqFQqHj9+TFBQEJD9s5aQkEBGRkap2pV46tQpHjx4wOrVqzE3N6dGjRpvVZFZsViMi4vLa1vKCQQCQUlTqhO2wYMHExISgoeHB02aNOHy5ctvPCcoKIidO3fi4uLCmjVrmDRpEv3792fEiBGoVCpat27N+fPnuXjxIp6enmzbto3169dz/vx5wy3OtLQ0Onbs+NrriMVi7OzschT01Wq1mJiYcOvWLT777DNMTExo2rRpkfSqNDEx4d69e3Tp0oXvvvvOkKg+fPiQ3r2LfLNLiTJr1iw2b96Mra0tO3bseGFTR3R09Cv7uopEIuRyOcuXL0cul5OQkEBCwv/Wour1esLDw9m3b1+hvgZjcnZ2zjGjKJPJ3ro6dKdOnTJ0shAIBKWHSF+wj9Ks1N7jePToEZGRkQwdOpTRo0fTokULLl68SPv27V973tdff41IJCIgIIAvv/wSW1tbJkyYwM6dO+nevTuHDx/mwIEDeHl5sXz58hznBgQE0L9/f2QyGYMGDQKyk7CnT58ilUpxcnLKcbyvry+3bt0y1PCSy+U8evSITp060b9/fywtLblz5w5+fn6Eh4dTuXJlI36FXmRiYsLcuXP59NNP2bp1K0ePHmXx4sW57qpQ2mm1Wk6ePIlWq8XU1BS5XM5PP/1k2HwxZswYw7rE/3r27FmO4sUvI5PJAKhXr57hsec/i7a2ttSoUYOsrKwSvctSrVZz7Ngx3n333be67IVOp6Nnz57CGjaBQFCqlNoZtkWLFgHw7rvv0qpVK1xdXQ23nbRa7St/GYvFYkQiEbVq1cLNzc3QvH3SpElcvHiRgIAA3nvvPapVq8bKlStzvIF//vnneHt7o1Ao6NWrF+PHj8fExIQaNWrg6en5QouqmjVrEh8fb/hcJBJx584dGjZsyLVr1zh+/DiJiYm4u7u/NFEoLM7OzkycOJEjR44wfPjwIrtucdqzZw9ubm4MGzaM8ePHM3ToUHr37k1MTAwrVqzg008/Zfv27VSuXJmPPvqI48ePs3v3bgYNGkR6enqB+rqKxWJ0Oh3Tpk3LscO4pNi3bx9Xr15FIpGQkpLy0t3NbwutVsv06dNJTEx8q5NSgUDw9im1M2ynTp3C3NycPn36GB6Ty+VAdnP10NBQPv74YyIjI3Fycnpp+6jnhXDXrFljqOP2119/4e/vj7e3N2PHjmXOnDls2LCB5ORk/P39adu2LW3btsXExIRjx44xffp0ateuzY0bN+jTpw8TJ05k2rRpSKVS6tSpw++//24oqvv8jf/kyZNMnDiRWbNm5bmtlSB/lixZQtu2benSpctL36hbtmxJy5YtSU5OZvfu3YwcORKJREK9evWYM2dOgRfcSyQS5syZg0KhIDk5uUTNavr6+qLVahGLxfTt27e4wylUEonEMLMuEAhKoTI8M15qE7YHDx6gUqmwt7fHzs4OR0dHIiIiAGjdujW+vr4ArF27ljFjxiCTyZDL5eh0OqZOncqSJUuQyWTY2dmRkJDA0qVLsbS0pG/fvlhZWXHo0CE++ugjoqKi+OWXXwy3Qw8dOsSCBQsAyMjIwMrKCgBvb2+++eYb1qxZw4YNG6hcuTK1a9fG1NSUy5cv06xZM6Kjoxk0aBBfffWV0GmA7FtT//zzDydPnuTBgweEhYXx7Nkz1Go1Wq2WatWqsWTJEjw8PAp8rcjISDp16vTGWRVra+tCawyuUCgICAjg+PHjjBs3rlCukVc7d+6kW7duJfpWrTFdvnyZatWqFXcYAoFAkGelNmFTqVT4+fmxb98+kpOTycrKolGjRqhUKuRyuWG27ZtvvgFg9+7dWFhY0LFjR2bOnIlYLMbT05PNmzfj7+/P/Pnz6dSpk2H8Tp06ER4eTkhICPXr12fAgAH4+/uTkJBA9+7dDTHodP/rRFu5cmVmzJjBjRs3SEtL4/z581hYWLBlyxZ27tyJXq+nc+fOZTpZCw4OZt++fZw8eZIrV66g1+upWbMmTk5OVK9enWbNmiGVShGLxdy8eRNvb2/69evHjz/+aEiO8yMxMbFEzKrUrFmTqlWrFncYQPbtQblcblh/VxbExcUJCZtAUFrpQVTw5u+lluh1C28bNWqk//+1xEqKwYMH07lzZ8PuziFDhhAYGIidnR39+vXL9TgqlYpLly6xefNmrl69+srZnNu3b1OvXj2GDRvGmjVrgOw6VZs2baJ379506NDhhUQsPDycn3/+mT59+tCyZUu6dOlSJpO1q1evsnDhQi5fvkxKSgq1a9emVq1a1KlTBycnp1fOeun1ej788EMgu8PEpk2beO+99/J8/aSkJJycnPj999+LdSZJo9Fw8OBBunXrViLWT2k0mremtlpeJCYmcvPmTdq2bVvcoQgEgn/16dPnul6vb/S6Y6wsXPRN648p0HWOX/j6jdcpqUpt9rB+/XqSkpJIT0/H2dmZx48fs27dOk6cOMGTJ09yPY5cLqdVq1Z06NCBTz755JXH1a1blydPnrB69WrDYytWrODQoUP4+/szZcoUAgMDgexbfUlJSajVajIzM/nhhx/o1q1bgZK1X3/9lQoVKtCyZct8j1HUAgIC6NKlCx06dEAikTB+/HhWr17NhAkT6NixIxUqVHht4iISiXB0dMTFxYW0tDR69OjBxx9/nOc4li1bRv369Yv9tt/ztk4lIVkD+P3334ukpExJo1arDTPjpb3VlkBQ5pThwrmldobtuXPnzhEWFkaPHj2wtrZm8uTJnD17lokTJ+ZpnKysLAYPHoxarc5zYqXT6fjll1/47rvvqFq1Ko8fPzbsths/fjzz58/P03j/38GDB/noo4/4/PPPWbRoEUeOHDGs0SuJdDodX3/9NT/99BPvvPMO3bp1y3cdr+PHjxMUFMSwYcMYOXIkWVlZ/PPPP9StWzdX52s0Gtzd3Rk2bBi1atXKVwzG8nzzSUmh0WgQi8UlKqailJKSwsyZMw2bQQQCQfHJ9QxbvdEFus7xi98IM2zFxc/Pj8GDBxt23X377bcEBwcbqs3nllwuRyQS5esvbrFYzNixYwkNDaV9+/b89ttvpKSkkJaWVuBkDbITttatW1OrVi2GDBnCO++8Q+/evQ0dC0qChIQEduzYwWeffUa9evXYtm0b8+fP58MPPyxQ0VVfX1+uXbtG+/btSUpK4ueff36h3t3rfPPNN1hZWRV5K7CXmTBhQo6iusUtJiYmT7PRbxsrKysWLFggJGsCQWkiNH9/e1hYWLB48WKWLl2ap8bcBw8exN3dPU+3zQIDA9m4cSMxMTFA9g7DOXPm0LVrV8RisVFKdkRHR7Np0yYaN24MZJefWLx4MY8fP2bMmILdyzcGrVZL165dcXZ25rvvvuPx48d06tSJWbNm4ejoWODxzczMaNSoEb/88gsKhYKxY8fmetzTp0+zYsUKRo4cWSJuQ86fP79EbHx47uHDhyUq6S9qWVlZLFy4ELVaXdyhCAQCwRu9dQkbZG9IMDMzIzExMVfHHz16lPXr19O8eXM+/fRTbty48cZzdDodHTt25Msvv8Td3Z25c+fmO97na95eJioqClNTUzw9PQ2PWVhYEBcXh5eXV76vaQw6nY5+/foRHh7O77//zsyZM+nfvz9NmjQx7NI1hjZt2vDHH3/kafbz8OHDvPfee4wcOTJPM3KFRalUEhgYWCISR4DMzExatGhBs2bNijuUYiOTyejVq1eZ3HghEJRWIr2+QB+l2VuXsAUEBDBgwABSUlJyXZ0+ICAAOzs7IiMjuX37NqNGjeLUqVNMmzaN8PDwl54TGxtLQkIC3t7eTJgwgTlz5uSrmbtKpaJNmzbY29tTvnx5WrZsyYIFCwgICECr1RIeHo6dnV2Oc4KCgsjIyGDevHl5vp4xff7551y7do0vv/yyUBf016xZk/LlyzNlypQ3HqvT6fjjjz/o0aMH7777Lk2aNGHPnj1oNBqSkpIM38+0tLQinVmRSqWcP3++xHQRmDt3Lo8fPy7uMIqVWCzGxsaGb7/9Nkd5HoFAICiJ3pqEbcOGDVSsWBFfX1/i4+NZtGgRFhYWuTr3888/Z9WqVXzyySeMHTuWyMhI+vXrx7lz56hbty7jxo0jLS0txzkRERFs376dx48fs2zZMtRqNRkZGXmKWavV0q1bN1JTU1m/fj3Tpk2jXr167NmzBz8/P2xtbbl06RIODg45zqtWrRoikYhu3brl+ZrGcvz4cTZu3MjUqVMLvTG4SCRi6NChbN++nbZt2xIaGprj+ZiYGI4ePcrSpUtp1KgRX3/9NSNHjqRVq1bo9XqysrIQi8VERUXxfBPNhg0buHPnDllZWYadp5cvX2bnzp0A/Pnnn0RERJCZmcmuXbuA7P61wcHBAISGhpKZmWlIBN9EKpUybtw4goODOXr0qLG+NPn23XffUbFixeIOo9g5ODgwYcKEMrvxQiAodYRdoi9XGnaJPte4cWO8vb1p27ZtgX/5qtVqpFIpIpGI6Ohotm7dSnBwMF9//TV2dnYsWrSIx48fo1QqiY2NxdzcPF/X6dOnDwEBAUydOvWltxC3b9/OgwcPkEgkTJs2DYCnT59y7do1TE1NOXnyJFOnTmXYsGEFer15FRwcTKtWrejduzctWrQosuuqVCp27drF4cOHcXZ2xsTEhCdPnqBWq6lQoQLOzs7UrFmT1q1b5/o21/OETqFQkJqaSlZWFvb29gQEBFCxYkWkUilnz56lU6dO3Lp1i4yMDHx9fVm1apWhJtyvv/7KjBkz2L59OyYmJvTo0YMZM2bw6aefkpGRwYEDBxg9ejR79uwhIiKCFi1aULduXXbt2kWfPn2K/Dbp+fPncXV1xdXVtUivW1KpVCr279/P+++/X2JuWQsEZU1ud4n61B5ZoOscu/Jdqd0l+tYkbO3btyc+Pp7Y2Fg8PT355JNPjFrBPSgoiE2bNqHRaOjatSs+Pj7MnDmTb7/9lo8++ijP4y1cuJBly5Yxd+7cV85QZWRkMH78eCQSCS1atKBfv37MmjULFxcXQkNDCQsLY9KkSfzwww8FfXm5olKpOH78OBMmTKBBgwZ88MEHRXLd/0+j0RAaGopWq8XZ2Rlra+sS8Uar0+nQ6XRIpVJiY2Oxs7NDrVbz7NkzXF1diYiIQKFQ4OjoiEaj4ejRo7Rv356YmBgqVapUZHGeP38eT09PIiIiqFmzZqHPkJZ0er2evXv30qVLlzLV9UEgKElylbCZu+h9ahUwYfMvvQnbW3Mf4Pvvv6dr164sW7aMrKws9u3bZ9Txvby8mD17NvPnz6dFixZIpVLs7e159OhRnsbRarWMHj2aBQsW8MUXX7z2zdLMzIzBgwej1WoJDAxk2rRpxMXFsX//fq5fv07fvn1fW+y3oJRKJVu3bqVnz55UrVoVa2trxowZQ4MGDXj//fcL7bpvIpVKqV69OjVr1sTGxqZEJGuQvSbq+cyeo6MjUqkUU1NTw0yWq6urYYerVCqlc+fOaDQaVq9ejUajKdTY0tLSWLt2LQkJCVy7dg1HR0ceP35MXFxcoV63NBCJRPTo0YOEhARe9wesQCAQFKe3ZnuUr6+voZjsP//8w/Xr1wv1emq1mlu3brFp06Y8nff1119z7Ngx5s2bl6sSDy1atMDKyoqffvoJX19fpk2bZuiVunXr1vyG/0rJycls376dXbt2cfHiRZydnWnSpAnDhw/H2dm5zM/GGJuZmRkzZ85Er9ezatUq+vbtm+vNMrkRFhZGaGgorVq1ok6dOpiZmRl65hZn0l3S6PV6Vq9ezfDhw0vErmKBQPAiEaV/p2dBvDUJ23/p9fpCnXVRqVT8/PPPNGrUCDc3t1cep1QqWbRoEVevXuXJkydER0eTmJjI3Llz81SPq27dusyZM4cffviBGTNmUKNGDeLj40lMTGTixIk0a9Ys3+voILvo7bp169i9ezc3btzAw8ODJk2a0LNnzxd2qAqMTyQSIRKJ8PHxwdLS0ihjRkdHk5GRgZmZGY6OjsjlckMtv7i4OKKjo9HpdKxZs4ZvvvnGKNcszUQiEdOnT0ckEnHkyBGaNm1q1MRZIBAICuqtTNgKc4t+RkYGP/74I/b29hw4cOCVx4WHh9O6dWtsbW1p1KgRtWvXxsHBAXt7+3yVwHB0dGTWrFns27ePqKgoLCwskEgkdOjQAYBdu3bRs2fPXI+nUqnYsWMH69ev58KFC9SoUQMfHx8+/vjjXO+uFRhX/fr1uXPnDpaWlq/9Q+B1rl27hpWVFRkZGSQkJNC2bdsXZoykUimZmZm4ubkxcmTB1oO8TUQiEXq9Ho1Gg1wuJykpCXNzc2Fdm0AgKBHeyoStMGfYjh8/jomJCceOHXvlTsTo6GjatGlD06ZN6dWrl9GurVAo6NOnj+FztVptSBqHDRvG8ePHWb58+Svj0ul0nDp1ijVr1nDo0CEcHBzw8/Nj+fLlWFlZGS1OQf5lZWUV6GfXysoKpVJJ/fr1X3mMj4+P4d/G6EbxNhGJRHTp0gWAQ4cOYWlpSceOHYs5KoFAYCDcEn27aLXaQkvY6taty99//82nn35KZGQkKSkpdO3alU8++QQbGxsSEhIM64UKexelTCajc+fOHDx4EB8fH86ePUvLli35+++/KVeunOE4lUrFqlWrWLJkCZmZmfj5+TFjxgycnZ0LNT5B3jVqlP/NSzqdDldXV6E3ppF88MEHhi4kwu1RgUBQ3N6aXaL/5enpSWBgYKHsvHNzc2P06NE8e/YMZ2dn6taty59//omLiwvvvvsuPj4+uLm5MWDAgCLZvVi3bl0AkpKSmD59OhYWFnh7e3Pu3Dni4uKYN28elStX5pdffqFfv34sX76cPn36CMlaCbV//34OHjz4wuNBQUGGun9///13jt2M+/btIygoiLi4OKZPny5U7TeiwMBA1q5dW9xhCASC58pw4dy3coZtyJAhbN68ma+++gpfX18cHBxo0KCB0RZ0e3t74+3tbfi8ZcuWJCcnc+HCBdzd3WnZsmWRlZp4nniZmpoilUoZPnw4+/bt44MPPiA5OZkaNWowatQoatasWSTxCAqmevXqLF68mHfffRd/f3+ioqLo0aMHp0+fplevXojFYhwdHdHr9Rw4cIAuXbrg5eWFo6MjNjY2LFq0qLhfwlulVq1a1KpVq7jDEAgEgrcjYXvy5Ak+Pj6YmJjQuHFjWrVqxZgxY1i9ejXbt283HPfVV1/RsGHDQonB2tqazp07F8rYr/O8bdXp06cJDg5GrVYTFxeHk5MTTZs2pU6dOsJsWikikUho0qQJIpGIatWq4e7uDsCoUaMMx9jb25Oeno5arUar1eLp6Vlc4b719uzZQ/v27YWNOAJBSaAHyvANhLciYZs4cSK1a9emRYsWBAYGsmbNGrKysihXrhw9evTAxMSE7du3s2DBAn7++ee3aqG1RCKhW7duBAUFMW/ePKpVq0b58uW5d+8e/v7+HD58mHXr1vHpp58WaH2UoGi4u7sbkrTXlVQxNzcX6qgVMp1Oh0QiISoqCnNzc1xcXAgJCcHNzS3Xrc8EAoHAWEp9ayqtVouFhQXLli17bW2zhIQEwyzFli1b3qpfuHq9ni1btnDu3Dk6dOiAt7c31tbWhpINgwYNQqfTGXpfCkq2P//8k2bNmhVpuyrBq505cwZra2vq16/P7NmzmTRpEomJicjl8hybewQCQf7lpjWVtZmzvpnn8AJd58g/s0pta6oSk7UkJSXx8OHD/2vvzqOiuu+4j7/vMIyACIqIC+6iUUkoRmpwTYqtGGPzoI1m0bRG06RpzdqaSKuJTTQxdomNfdK0aUyq1mZrqsajVo1J3GqRECLIoqCIox0IAo4sA8zc+/xBnEcisjjLnYHv65w5p2z3fjBl5ju/5fujpKQEi8XiPDKnS5cuBAcHExQUxOjRo5usHQM4e/YsJpOp1Ua0ERERpKam8tJLL7F+/Xoeeughj/0u3qYoCvPmzWPixIlkZmayfv16Tp8+ze7du3nmmWe4ePGic+pU+L7Ro0e7bb2lcN2tt97q/N/Lli0DID8/H1VVSUpK0iuWEKKT8YmCbcmSJbz22muEhYURFhZGt27dnC9YDQ0NzkdBQQH//e9/GTVqlPNni4qK2nxqwJgxY7j11lvZu3cviYmJzh2WHcXgwYMZPHgwKSkpVFRUsGfPHpKTk6msrOSWW24hOTlZ74iiDWJjY6mtrdU7hmjBbbfdBsAHH3xAcnKyFNhCeIuf7/R0hdcKtpMnTzJ79myys7NJS0tzHpOzfft21q9f7zw9oCX/+te/WLBgAf/5z3/Izs5mx44d3HPPPVy4cKHNzXIffvhhPvvsM1auXMnatWs77IL81atXs3z5cmbNmsW7775LeHi43pFEG508eZL333+fX/3qV3pHES3QNI2wsLDrOrlECCHay2tr2JYsWcJvf/tbbrvtNj7++GMMBgMOh4OYmBhSUlKcB7e3xG63s3TpUn7+85/zzjvv8J///IfJkydz9OjRVtewXam0tJTFixcDjcf0bNiwoUOtaQP46quv6NmzJwZDh2y116F5+ixc4T719fXU1tbKGyIhXNS2NWx9tfExi1y6z7+zVvntGja3v5rX1NSQmpqKoiisWrXK+fnf/OY3aJrGJ5984iwi0tLSqKmpYfz48W26ttFoJCEhgYMHD5KXl8fatWuprq7GZrMREBDQ5oxRUVFs3ryZxYsXM3Xq1A5Z1BiNRsxms94xxHVQFIXc3Fw+//xzvaOIVhw6dIhdu3bpHUMI0Qm0q1JRVZXi4mI+/PBD1q9fj6IozsflY5h27drF6tWrAbjxxhsBqKqqIjc3lyNHjrBnzx4uXLgAwCeffMLo0aPbNZrw6aef0rVrV4xGI3379mXkyJEA7T4L02g0MmXKFBYtWtQhC7bTp0/z5Zdf6h1DXKfAwEBMJpPeMUQrvvOd7zB37lzOnj3L9u3b9Y4jRMemIScdtOaDDz5g06ZNbN261fm5BQsWEB8fT11dHdHR0cTGxpKamkphYSG333471dXVrFixgh//+MdUVlYSFhZGcHAwAQEBBAQEcPToUQoKCujTp0+7Ai9cuJB3332XlJQUFEXh/Pnz7fuNO4lvnsYg/EtMTAyqqlJfXy+Fm49TFIXg4GCio6P1jiKE6MBaLdhUVWXOnDlAY4uNp556ioULFxITE4PdbmfdunX87ne/IzMzkzFjxhAdHU1kZCRBQUGEhITQp08fevXq5RzF0jSNv/71r9x555306tWLixcvoqpqm0e5xo0bx7hx45wfJyUldahGuO60efNmJkyYwODBg/WOIq7Dhg0bGDhwoLSO8AORkZGoqorD4WjX8gwhRDvJSQfNO336NHPnzsXhcKBpmvOJSFVV3njjDVauXElwcDCLFi0iNja2TVObiqLwwAMPsGzZMqxWK1lZWaiqys9+9rPr+gVGjhzpnBYVTSUkJEhjTz82f/78DrcZpiO6dOkS3bp1Y926dTz11FNt3vwkhBDt0eKwVnl5OaWlpRgMBmexZrFYuOmmm3jppZe47777eP7557nxxhvbtQ7NaDSyYsUKxowZw5AhQ/jss8+or6937TcRVxk0aJDeEYQLjEYjH3/8MaWlpXpHEdeQlZXFG2+8AcALL7wgxZoQwmNafPs+fPhw9u/f7/zY4XCQlJRETEwM8+bNc2mxflBQEDNnzmTmzJls375dphE8ICsri4yMjA51qkNnYzKZaKn1jnCfmpoabDYbERER7Nixg9tvv73FN6JWq5WbbrqJ2NhYL6YUonNTOvHzYYsV1zd3Xm7cuJH6+nrmz5/v1p2VM2fOlILNAxISEqRY83OTJ0+WY8W85KOPPiI3NxdN05yjmjk5Oajq1YtmNE1jzZo1lJSUdMhd5kII39PmZxqHw8Hvf/977rjjDrc29WxoaLju9WuiZdu2bcNqteodQ7igpqaGn/3sZ80WDcK97r77biZOnIiiKCxYsABN09i9ezdWq5WioiIsFgs2m4133nkHTdNYsWIFvXv31ju2EJ1LJ27r0aaCzWKxMHnyZBoaGkhMTHRrAKPRyAsvvODWawqcm0SCgoL0jiJcEBISwiuvvCKjOB62bds2jh071uRzBoOBJ554gu7du3Pq1CnMZjNdunShR48eOBwO2RAihPCqVp9xdu/ezf3338+4ceN49NFH3f4kpWkaFouFiIgIt163MysqKqKqqoo77rhD7yjCDc6dO0dwcHCHPffWF8TFxbXYfPvK1irJycneiCSE+CYNUP17lMwVLb5tLy4uZs6cOfzwhz/khz/8oUfeUdbV1TVpyCtcV1tbS3V1td4xhJucPXtWdop6WHBwMLm5uXrHEEKIa2qxAqutrWX16tUebUwbHBxMamqqx67f2Zw6dYro6GhGjRqldxThJrfddpveETo8RVHkTY4QPs//16G5osURtqioKI8Wa3a7neXLl2O32z12j87mk08+oaqqSu8Ywo1ycnL48MMP9Y7RoUVFRTFt2jSOHz8ufz9CCJ+k66pZg8HAwoULZfGuGy1atAhVVSkrKyMyMlLvOMIN+vbtS3BwsN4xOoXc3FyCg4MJDQ3VO4oQojkywqaPs2fPyrZ4Dzhx4gSbN2/WO4Zwk5CQEDlY3Evuuusu+vTpQ21trd5RhBCiCV0LtoMHD3LmzBk9I3RII0eOZPHixVitVjIyMvSOI1z03//+l02bNukdo9PYtWsXBw4c0DuGEKI5nbgPm1fnIh0OBxUVFURGRlJRUcGcOXMwmUzejNBpGAwGKisrKS4u5uabb9Y7jrgOdrudwsJCpkyZwpQpU/SO02nMmjVLjgMTQvgcr46wFRQUOEcKdu7cSVpamjdv3+kMHDiQlJQUcnJyOHfunN5xRBs5HA6qq6upqalh+/btcsqBl23atImCggK9YwghvulyHzZXHn7MqyNsw4YN4/HHHwfgvvvu8+atO7WysjIAWQflJ3bs2IHdbmfWrFn8/Oc/1ztOpzNx4kRpUiyE8DleHWF75plnaGho8OYtBTBp0iRGjBihdwzRikOHDlFYWMiMGTOYNWuW3nE6rZCQENLT0/WOIYS4igaa6trDj3m9YAsMDOTgwYPevG2nd/bsWX7961/rHUO0IiQkBKPRSEBAgN5ROjVVVWUaWgjhc7xasEVFRVFVVUVeXh52u53Dhw/L4l4vGDRoEMuXL9c7hrgGu93OoUOHiI+PZ9CgQXrH6fT69esnmzyEED7H6209unXrxoMPPoiiKOTk5FBTU+PtCJ3OsWPHnOvYhO+xWq2cPn1a7xjia+np6WzcuNFt17tw4YKzL2JJSYnzb3Hfvn1UVla67T5CdAqduK2Hbn3YAgICePDBB+natateETqNmpoaKdh8lMPhICwsjPnz56Moit5xBDB69GjuuOOOVr/vzJkz/OUvfwHAYrFcdaTVe++9R0ZGBkFBQcTExADw+eefO3eglpSUEBYWhsVikSlYIUSrdCvYLly4wG9+8xu9bt+pJCYmEhcXJ2sHfVB1dTVLly6VpQE+JCQkhJqaGrZt29bi9w0YMMA5dXr48GGys7Opr693Pq9NmDCBUaNG0bVrV8aNGwfAjBkzSExMBODee+/FYDDw3nvvcerUKQ/+RkJ0EJ28rYduBVt4eDg/+MEP9Lp9p2O32zl27Bh2u13vKOIKYWFhrFixAkVR2Lx5M1arVe9IgsairX///tf8ekFBAenp6YwcORKA2bNnk5iYSGBgIFOnTgWgf//+bToD9tFHHyUmJgabzeae8EKIDkmXgm3z5s0UFRUxdOhQPW7fKRmNRn76059iNHq19Z5og9DQUFRVpU+fPnTt2pWysjKZItNZREQE3/rWtyguLm726waDodndvIqitPtkEUVRKCws5OWXX76urEJ0KrKGzTsqKirQNI2xY8e2+O5VeMZrr73GiRMn9I4hmmEwGEhKSiIgIIBNmzbJfycd7Ny5k3379gGwatUqcnJy+NOf/nTVdGVWVha9e/dm7Nixbrv30KFDWbZsmduuJ4ToeLxasG3cuJHs7GxuuOEGgoKCvHlrAaSkpDgXPwvf9fjjj3PDDTfoHaNDO378OOvXrwfg5Zdf5sKFC9xyyy3O0bEf/ehHjBo1irvvvpuQkBAqKyt57733AMjPz6ekpMSteRRF4dy5c+zfv9+t1xWiw+nEI2xenR977LHHvHk78Q0nTpyga9euhIeH6x1FtEBRFLZs2UJVVRXz58/XO06Ho2kaN9xwA927dwfg/vvvJyQkpMl6s8szAPHx8UDjJqkhQ4YAcNddd3kkV2BgICaTySPXFkL4P6+vYVuzZg1FRUXevq0AysvLpYu+n0hJSWHevHnX/fOqqlJaWgo09hW73Eri008/paGhgYsXLzqn+iorK6mrq3M9tB8oLy/nueeew2AwOM/W7devX6ubA3r27Mm3v/1tj2br27cvt9xyC9nZ2R69jxD+y8XRNT8fYfNIwVZaWtrkBUDTND755BPsdjsLFiyQbu46sNlszJ49m9DQUL2jiDbYu3dvqzt6y8vLgcbpvSNHjgDw1ltvYbFYMJvNvP3220Dj+rjLPd6u7AF29OhRAP75z3+SlZWF3W5ny5YtHbbFiKZpREREsHjxYgwG3TbIt6iuro49e/bIjlEhxFXc9qxVVVXF22+/jaqqfPzxx2RmZpKWlsbf/vY3FEXhf//7H9XV1URFRUmDUB288sornDx5Uu8Yoo3MZnOLfyc1NTWsXLkSTdMIDg52Tu/dcsstdOvWjYEDB/L0008DcPPNNzNs2DAAHnzwQQIDAxkxYgR33303AIsWLSIhIQGbzeYs7rZu3cqePXvQNK3DtIJ5+eWXMZvNREVF6R3lmoKCgnjyyScxGAzk5ubqHUcI36IBquraw48pLb2bHjZsmLZ69eo2XUjTNA4dOkRiYqKzdUR9fT1VVVVERES4Jay4fnV1dZhMJimW/YDdbsdgMLQ4CqRpGqqqemyKu6qqClVVsdvtPPfcc6xbt478/HyMRiPDhg1DVVUURfGr/z9ZLBZ69+7tF5nNZjN79uzhgQce0DuKEF4xd+7czzVNS2jpe8IDo7QJkXNcus8uy2ut3sdXuW2E7csvvyQiIqJJny+TySTFmo84efIkaWlpescQbXD48OEWz7I8cuQImzZt8uh6xNDQUMLCwoiIiGDt2rUAXLp0yXn80sMPP8ylS5fIyMhg586dHsvhLrt27aJ79+5+UawBREdHM3PmTL1jCOF7OvEaNrftEg0ICJAF7T6sa9euPrtuRzQ1efJkEhKafwPocDgYO3YsI0aM8Fqey3/XV2b685//7Fy478tTjNA4YllZWekXOzD37dtHREQEcXFxrFu3jscee4zIyEi9YwkhfIDbXsFvuukmhg8fTnp6ursuKdxoyJAhDB482LlzUPiu9PR0HA4H69at4/z586iqSk1NDWazmZUrV2I0GnUfub5c/Pfu3ZvIyEjnpger1Up9fb3b7rN9+3aqq6tdvs4999zjF29YRowYQWhoKAaDgeeff16KNSG+qROPsLn1GezcuXPSod2HHTx4kIyMDL1jiFYUFRVRW1vLnXfeSc+ePcnMzOStt96if//+PPHEEz43raeqKrm5uWiaxt///ndycnKorq5my5YtqKrKSy+9RHl5OWVlZRQUFFBbW8uLL76IpmlYLBbOnTvX5Hr19fXk5OQAuKXIWr58OefPn3f5Ot4QFRXlN1mFEN7l1oJtwIAB3HfffTQ0NLjzssJNpk2bRmJiYodt29BRzJkzhzVr1tCrVy+6dOnCzTffzEMPPQTgk02PQ0JCeOCBB1AUhUceeYT4+HjsdjvdunXDYDBw77330qNHD8rKysjLy8NkMvGDH/wARVE4ffo0+fn5Ta5XX1/Prl270DSNGTNmcOnSJSorK68734oVK+jXr5+Lv6X3mM1maeshhLhKiwXbpUuX2t1Qs6amhsceewyHw+FSMOEZr7/++lVnIwrfExwcjMVicX4cGBioY5r2Cw8Pp1u3bnzwwQcMHjwYRVEYOXIkM2fOJCAgwHn01vjx40lKSmLDhg1kZGTwxz/+keDgYJ566innSOLBgwev2Wz78vNMeno658+fx2638+GHH6JesX1f0zR27Njh2V/YTUwmE/fdd58c3SdEszRQXXz4sRYLNpvN1u6NBCEhIaxbt042IPiop59+miFDhrB//34ZafNhzzzzDEOHDtU7hkuGDx9OUlJSm743KSmJmJgYJk6ceNVzx1133UV8fDx1dXVomsYrr7yC1Wrl+PHjXG47VFNTg81mQ9O0q9qNGI1GrFar+34xD1u7di3FxcV6xxBC+JgWC7ZevXpx6dKldl2woqKCY8eOuRRKeM7lxqg5OTkyde3Dqqqq/H4DT48ePdq8OaJ///6EhYUxZsyYZr+ek5PD66+/jqIoJCcnExISwqhRo0hNTQVgypQpDB06lMDAQGbNmkVeXh6ff/450FiwzZ071z2/lBfcddddfjWFK4TXaKBpqksPf9ZiweZwOFi9enW7pjerqqowm80uBxOeoygKP/nJT/yizUFnZbVaZR3TFUaNGsXChQsBGD16NEajscXmwlcepG6z2XjuuecoKSnxWl5XREdHs337drfuthVC+L8WC7aAgABeeuklDAYDGzZsQNM09u3bx6ZNm5r9flVViY6O5s477/RIWOE+p06d4tVXX9U7hriGESNGMGHChHaPcHdUiqLQrVu3Nn9/TEwMN910E2+++SalpaWkpqbSu3dvDyZ0H03TuHjxohRsQjRH1rC18A0GAw6Hg969e2O32xk/fjxz5851rhm5Unp6On/84x89Fla4T3R0NPfcc4/eMUQLDhw4wNatW/WO4deSkpLo2bMnISEhekdpM4PBQM+ePdm/fz+qqrJ8+XIuXrzY5HuOHTvWZGOFEP7MHb0WO4M2nXRgNBpJTk4G/v9uta1btxIeHs60adOcC30TEhK48cYbPZdWuE1FRYVMifq4yZMnA40j1/7Q9NUXDRkyRO8I1+XKY6keeeQRwsPD2bdvH0ajkSlTprBv3z4GDhxIcXExcXFxOiYV4vqpqsqpU6eIiYlp+w914s1y1/0qMGfOHKZNm8aRI0f4xz/+AUBpaSmrVq2S3Yd+ICsri+zsbL1jiBZcLtKWLl3qV7schXtd3oAQFxfnfGF74oknCAsLY+fOndJCSfid7OxsSkpKqKqq4oMPPpCaoY2Ulv6hhg0bpl3eNn8ttbW1VFZWcvHiRUaOHElNTY1fTT90VBcvXsThcOh+hJFwXUVFBT169NA7hvBRl48v69+/v95RhGjR0aNHGTNmDPv376dfv36MHDnS+bW5c+d+rmla84cofy08IFIbH+raGvl/W99q9T6+yqV5FqvVSm5uLoGBgezatQtVVaVY8xFpaWmkpaUB8I9//KPJesPCwkLWrl3Lxo0bgcbDsYXv6tq1KwcOHNA7hvBRx44do6ysTO8YQrSorq6O7OxsamtrSUpKalKsibZxqWCrqKjAbDbTvXt3CgsLqa2tdVcu4aJJkyY5p0/69evXpOdanz59mDp1KrfeeisAL774opx+4MMCAgI4efKk9M0TzZo+fTp5eXns379f7yhCXJPJZOKBBx5o127vZsnh7+1XX19PeHg4d955J0ajkbVr1xIcHOzObOI6aZpGYWEhR44cAeDWW2/liy++oKysjK+++ory8nJCQkKc/72efvppBg8erGNi0ZKAgAAWLlzIpUuXKCgo0DuO8EHTpk1jwoQJescQolmapvHLX/6S0tJSvaP4tesu2NLS0pqczxcQEMCTTz7JhQsX3BJMtN/l9Yg7d+4kOzub+fPnO79msVgwmUzk5+eTm5tLXl6es5FoUFAQb7/9NllZWbrkFm1z7tw5Tpw4oXcM4YMiIiLIzMyUZsvCJ6mqSmpqKlFRUS5fS1NVlx7+rE1tPZozadIkbDZbk5YDa9askVYROnr22Wd55JFHmD59epOzFAHmzp2L2Wxm586dvPDCC1e1iZg+fTpRUVEcOXKE8PBwRo0a5c3oohUZGRmUlJQwY8YMvaMIH5Wfn8+gQYPk4HjhU/bu3UtZWZn0/XQDl9aw7d69my1btgCwcuVKPvvsM3dkEm1gt9ux2+2cP3+eP/3pTwD84he/oG/fvs7zQr+pf//+rFq1qtmeXv369cNoNBIWFkaXLl2or6/n1Vdfle3WPqJ79+6MHz9e7xjCh82bN4+ePXvqHUMIAMxmM2VlZUyaNImUlBQ3XdXF9Wt+/nrmUsH2/e9/33kM1axZsyguLpYXeC9Zs2YN+fn59OrVi+9+97sAhIeHN1uotcfo0aMZOnQoABMnTkRRFD799FPZhaazoUOHUlVVxenTp/WOInzYo48+Ks/BwidkZ2dTVFREUFCQjPq6yXVPiULj+X5GY+MlYmNjiY2N5ezZs5w8eZKkpCS3BBRNZWVlYTKZSE1NdRZnw4cPd/t9TCYTY8eOBRrXH6iqSmZmJjExMZSWlrJx40aeffZZlwtE0Xb/+9//qKur89vu/cLzVqxYoXcE0QnV1dVx5swZYmJi2L9/P5GRkUyfPl3vWB2O28+7CQ4OlmraA7Zs2UJGRgaaptHQ0ODVQikpKYnIyEgyMjKw2WwMHDiQZ555hurqag4fPuy1HJ3dt7/9bSZNmqR3DOGjzGYzlZWV8iZKeF1gYCDvv/8+0Ng2ymMN2zU69eHvLo2wNaempoaKigp3X7bTslqtmEwmxowZQ8+ePQkNDdUlh8FgYOHChc6PjUYjRUVFcmSSF505c4Zdu3bx8MMP6x1F+KCysjKqqqo8MuIuREusVitTp07FYDBIQ1wPcnvBFhUVRVhYGJqmUV5eLotgr5PdbicgIICMjAwsFotP7bCx2Wy8/fbbPPTQQ9K/zYsGDBjAd77zHb1jCB8VHx8PNB5LFx4erm8Y0ak0NDRgsVi8czPNv1tzuMLtU6JBQUFMnjyZwsJC1q9f7+7Ld0gOh8M5UrVx40ZOnDjB3r17effdd7ntttt8qliDxvVtcXFx1/z6jh07KCgoQNM06uvrvZis4zp69Cj5+fmMGDFC7yjChxUXF/P66687T50pLi7m0KFDAOzbt4/y8vLrum5NTQ1btmyRDQ0dnKqqfPnll+3u59erVy837gQV1+L2gu2ymJgYlixZ4qnLdyhms5k//OEPAEydOpWoqCiSk5N99g9AURSysrKorKxs9usDBgwgIiKCkpISli1b5t1wHUhtbS1PPPEEmqZhMpnkJBHRqoEDB/L0009TXl5OZWUlQUFBOBwOoHFk3GAwcPHiRefnWmOxWCgsLCQoKAhVVVEURc4e7uCysrKwWq2cOHGiXY26V65cSXV1tQeTNS5h01TNpYc/81jBZrPZ2Lx5s/xxN+PyqFNBQQHvvvsugwYNYvny5UBjP7Tu3bujKIpPb94YP348oaGhzZ5veeONN1JUVERkZCSrVq1CVVXefPPNJuvdLu86lXfszcvLyyM4OJhnn30WgG9961sy/SzaRFEUCgsLSU9PJyoqiilTpgAwY8YMunfvzvr16zlx4gRms7nJC+zlEfH6+nqWLFlCfX09FouFM2fOYDAYmD17NiUlJTz33HOoft4xXlztvffeo6SkhPnz5xMVFYXNZmvXGuV7773Xp1+zOgKPFGw1NTWYTCYiIyOdbT9Eo7y8PH71q1/hcDjo27evc92JP1EUhbi4OFRVZenSpc0On2dmZlJRUUFgYCCKohAbG0toaCjp6emYzWYuXbrEwYMHZUdbM2w2Gx999BE2m42IiAj5NxLtNmXKFGd/xm96/PHHGTVqFIcPH+bkyZOoqkp9fT0HDhxg27ZtmEwmfvGLXxAYGEh8fHyTFk29e/cmNTW12ebbwr8NHjyY7t27Oz+Oi4sjISGBTz/9tE1T6f369eOrr77yYEK+bn6ruvbwY27/qzObzaxevRqDwcC0adPcfXm/1tDQwIYNG0hNTeWLL76gurqaG264Qe9Y1y0oKIjnn3/+qndVWVlZTJkyhV69egGNBV5iYiIGgwGbzYbdbic8PJyJEydSVVWlR3SfpGkaBw8exGg0smTJEnm3KjzicrE1d+5c4uPj2b17Nx9++CGJiYl873vfAxoLs2u9UejSpQu/+93vZH1qB2I2m4mNjW122YXD4aCurq7Va+Tn5/Pxxx97Ip74mtsKttraWlRVpaCgwDmNI5oKDAzkxRdfJCIigry8vA4xrdC1a1d27NjBgQMHnNObDQ0NzU6VQuMZtJen9o4fP+5cHC0aC7aioiIpYoVXJScnM3v2bEwmU5t2lwYGBvK9731PZk86kL1793Lu3LlmvzZ16lR69uxJdnZ2i9eIj49n3rx5nojXhDfWsCmKMl1RlHxFUQoURVnq4V+pzdxSsJ08eZI//OEP2O12cnNzZbi8BZqm8etf/5qUlBT69Omjdxy3GDNmDPHx8fz973/n8OHDjB07ttXD49966y1iY2Odo3Cd3eXjv+bPn99kWkIIT1MUBZPJ1K6fiYuL49ixYxQUFHgolfCmBQsWtLgD3Wq1cujQoVbXHB86dIgDBw64O55XKYoSAPxf4HZgNHCvoiij9U3VyC1vkYYPH86TTz6JyWSiS5cu7rhkh6UoCvfffz+hoaHY7fYO8S61b9++QOOi5rCwsDb9TEpKCiaTqcP8G7jq8g48IfyF3W6/apZA0zQuXLhAZGQkqqrKm3c/sWXLFsaNG0e/fv2a/XpkZCQPP/wwlZWVhIaGXvM5e8iQIZ7fSOb5dWjjgAJN004BKIryDvB/gBxP37g1Lv81bd++nbS0NGehFh0d7XKojm7o0KGUl5eTmpraoXbRRkREtLn46tGjByEhISxbtozy8nL27NlDZmYmRUVFlJaWejip7ygsLCQzM5OkpCQZbRR+JSEhgREjRrB161a++OILoPG0hVdffZXq6mpSU1OvuTRC+A5N04iIiCAyMrLV7/3b3/7WYquP0NDQjtAsPxo4e8XH5q8/pzulpWpYUZR0L2YRQgghROdUpmlaiyfGK4qyC2i9smxZEHBla4O/aJr2lyvuMQdI1jTtwa8/vh8Yp2naoy7e12UtDodompbgrSBCCCGEENfSWkHnJmZgwBUf9wfOe+G+rZIFBkIIIYQQjY4CwxVFGaIoigm4B9imcybAA4e/CyGEEEL4I03T7IqiLAb+DQQA6zVNO65zLKCVNWxCCCGEEEJ/MiUqhBBCCOHjpGATQgghhPBxUrAJIYQQQvg4KdiEEEIIIXycFGxCCCGEED5OCjYhhBBCCB8nBZsQQgghhI+Tgk0IIYQQwsf9P4pCw06C/BPKAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "# the reader returns not only the data but also metadata and the longitudes and latitudes\n", - "h08_roi, metadata, timestamp, lons, lats, time_var = \\\n", - " h08_reader.read(datetime(2010, 5, 1, 8, 33, 1), lat_lon_bbox=[60, 70, 15, 25])\n", - "\n", "plot_crs = cartopy.crs.Mercator()\n", "data_crs = cartopy.crs.PlateCarree()\n", "\n", - "fig = plt.figure(figsize=(8, 10))\n", - "ax = fig.add_axes([0.05, 0.2, 0.6, 0.7], projection=plot_crs)\n", - "# initialize the readers with the path\n", - "ax.set_title('H08 ROI example')\n", - " \n", - "blue = '#4b92db'\n", - "ax.background_patch.set_facecolor(blue)\n", - "ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb'))\n", + "fig = plt.figure(figsize=(12, 10))\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", + "ax.set_title('H08 example')\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - "ax.add_feature(cartopy.feature.LAKES)\n", - "ax.add_feature(cartopy.feature.RIVERS)\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", + "ax.set_extent([5, 50, 50, 70])\n", "\n", - "ax.set_extent([10, 47, 50, 75])\n", + "ssm = np.ma.masked_greater(np.flipud(h08_data['ssm']), 100)\n", + "sc = ax.pcolormesh(h08_data['lon'], np.flipud(h08_data['lat']), ssm, zorder=3, \n", + " transform=data_crs, vmin=0, vmax=100)\n", "\n", - "data = np.ma.masked_greater(np.flipud(h08_roi['ssm']), 100)\n", - "sc = ax.pcolormesh(lons, np.flipud(lats), data, zorder=3, \n", - " transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'), \n", - " vmin=0, vmax=100)\n", + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", "\n", - "cax = fig.add_axes([0.65, 0.2, 0.025, 0.7])\n", - "cbar = fig.colorbar(sc, cax=cax)\n", - "cbar.set_label('Degree of Saturation (%)')\n", - "plt.show()" + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Degree of Saturation (%)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Reading H14 product" + "### SM-DAS-2 (H14)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The H14 product is a global product on a reduced gaussian grid with a resolution of approx. 25km." + "The SM-DAS-2 (H14) product is a global product on a reduced gaussian grid with a resolution of approx. 25km." ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\n", - "('The following variables are in this image', ['SM_layer1_0-7cm', 'SM_layer2_7-28cm', 'SM_layer3_28-100cm', 'SM_layer4_100-289cm'])\n", + "The following variables are in this image dict_keys(['SM_layer1_0-7cm', 'lat', 'lon', 'SM_layer2_7-28cm', 'SM_layer3_28-100cm', 'SM_layer4_100-289cm'])\n", "(800, 1600)\n", - "(800, 1600)\n", - "(800, 1600)\n" + "(800, 1600) (800, 1600)\n" ] } ], "source": [ - "# the reader returns not only the data but also metadata and the longitudes and latitudes\n", - "h14_data, metadata, timestamp, lons, lats, time_var = h14_reader.read(datetime(2014, 5, 15))\n", - "\n", - "print(type(h14_data))\n", + "h14_path = os.path.join(test_data_path, 'h14')\n", + "h14_nrt = H14GribFileList(h14_path)\n", + "h14_data = h14_nrt.read(datetime(2014, 5, 15))\n", "\n", "# the data is a dictionary, each dictionary key contains the array of one variable\n", "print(\"The following variables are in this image\", h14_data.keys())\n", "print(h14_data['SM_layer1_0-7cm'].shape)\n", - "print(lons.shape)\n", - "print(lats.shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The data comes as a 2D array. If the keyword expand_grid is set to False during reader initialization then only 1D arrays would be returned. \n", - "\n", - "This can be good for working with the data but for plotting the expanded grid is easier to handle." + "print(h14_data['lon'].shape, h14_data['lat'].shape)" ] }, { @@ -281,49 +246,57 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 6, "metadata": { "scrolled": false }, "outputs": [ { "data": { - "image/png": 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P6nXZl+8+tY9TQga/VBzxuTJrfMcLhvwvrzUEg0HncvJFt8bXVpW8vGH5/NN7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\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lLEgM0c/Hnj4WgLyjimjZOZfKpTDqihe4ebGb6y99j2BdPfFgsP1GluLwous6S+a/zBW9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\n4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EtKC3P5+D93ExYZezw5rXWLuVPftwc6pvpKJAwaUeX7X1bOm/JAl37XjJr+8b/VuVPf\nQ1GUQIckCIIgCIJwTg7s2sCbjw0jKbX53EZN2yaLZEGoDmLOwh9YOvPzSZff8OD2XRuWbMw9vNcy\n6vExWIJtgQ5LEARBEAThT62YO4m5k8fSodeQZ36Z/fWbgY7nQiEm44gRhj+14Lvxu1p26hcry3L2\n209cQ1FeTqBDEgRBEARB+B2fz8O34/6P5T9P9HcbeN2lIlkQqptIGP6HuVPftzds0qpxo6Ztfnjr\n8avZuWFJoEMSBEEQBEE4pbToBGP+eT2FuUdKOlwyJGXR9x8vC3RMFxyx07NIGM5mzpSx6trF31/f\npe/V93w77ll11jdvo8hyoMMSBEEQBOEil7ltNW8+OpT4pCaLmrTsEjPv2w9yAx2TcGESNQznaOlP\nX3x2xQ0Prdm/Y+3G7Kwd1juf+gBbWGSgwxIEQRAE4SKjKAqLvp/A8llf0eGSwU8sn/XVmEDHJFzY\nxAjDXzD/u3F7m7fvFWW1hW19/ZEhHNm3LdAhCYIgCIJwEXHaK/j0lXvYtma+u/uA6zqLZKHmqWr1\n3+obkTD8RXOnvOfZtGJ2x5ad+70x4aU7WTrzc8ReFoIgCIIg1LTs/dt5/ZHB6PT6zFadL41eMH3C\n5kDHJFwcRMLwN62cO/lfPQaO6L1h6Y+eT/5zN057eaBDEgRBEAThAqSqKkt/+oLx/76DFh36vLV1\n9fwWc6e+5wx0XMLFQyQM52Hh9x+tat11YJTeYNjz2sODObxva6BDEgRBEAThAuK0l/PJK3ezYckP\nnh4DR/ReOW/y04GO6aIjVkkSCcP5mjv1PeeWVfNatezU97WPXxrN4h8+FrtDCxcMZUwjlDGNAh2G\nIAjCRelw5hZee3gwer1hT+uuA6MWfv/RqkDHJFycxCpJ1WTl3MnPDhrxwNwtq+Yszdy+2nLb4+8S\nFhkX6LAEQRAEQahnFFlmwfRx/DL7G9r1GPTayrmTnw10TBer+lqkXN3ECEM1Wjh9wtqWnfuH20Ij\n17728BB2bVga6JAE4bzoHs+BR49QWV4MiBEHQRCEmlZamMvYf93Ins2/OHoMHNFJJAtCXSCJFX5q\nRv9hd96/Y93C8W26DZSuufP/MJktgQ5JEP6yQ3s3k7rg2j/8ne7xnFqORhAE4cK2ZdVcpk14jlad\n+i6KiksePGfKWLFTbIA1TZTUD+6t/nYH/5stqqp2qv6Wa4ZIGGrQ4JEPN8rJ2rGhvLQw7o4n3yOp\ncYtAhyQIZ+VxV7Fq3mSucrxKTDpkrz3z9yJREARBqF6uKjs/fPISWbs2KG26Dbxz6czPvw50TIKm\naaKkfnBP9bc7+KX6lTCIGoYaNO/bD3OuvPmxhPLS/M/e/7+b7hp47b0MGH4POr0+0KEJwhmaH2hE\nVSlIknbfmA1OwFn82zFJHUD2QUEgAhQEQbhAHdi9kW/GPE6DlGZHOvcd1nPetx/kBTom4Uzi0rpI\nGGrcnCljVWD0oBEPTNy+bsHiXRuXBt/2xBii45MDHZognOJ3g9kKVaUg+8EafWayYI2GE33FyIIg\n1Ka7By0C4LOFlwU4kppRWnQCa0g4ZktwoEMJCJ/Pw5xJY1i/9Ee1XfdBr6yYO+mFQMckCH9GFD3X\nkoXTJ6xt0aFvaHR8w/lvPjqMNQuniR2ihTrBVWXnoak9kH3Q7gbQ6UD9r5WBXaNEsiAEjiz7yTt6\ngL1bVrB360pO5GTh87oDHVaNOpksnPz+9PvD0/tze59PcVSWMWfyWG7rNY47+3/7u+POxmkvP7Wg\nQW27rsVQ7ulzHz99+UZAnj/Qjh/J5K1Hh3L04M6SHpeNaCGShTpO7MMgahgCYeC191y9d8uK6VFx\nScabHn6D8Cix/KoQGPaKEi4L6kBRljYdyVUO+bvB6wRJByndteOOrBG1C0LtKik4zr39HiB3+w6K\nD4BOD00HQGz6G+iNUYSEPs7QUU/S96rbAx0qQxIakdB6HJJkBs4cEfjvE/hzGS24e9AiFNmOpDOd\navOksmPjWP72DqzR0OO+KwiJHQ5A8eGX8LmOYzDH8tOhTb9rU1VVrm85DEtoRyyhHQBwla/HXbmF\nlyb9k1ad+/9pPLd2fx1FdgDwxYr/49bOtxMaf+Op+P6oT6f3W5Ht+D156PQ2dIYQFL8dRXag+O08\n+1FvmrfredbX5EIhy36W/PAJS2Z+RtvugyaGR8WP/nUmglBHNU2U1PdGV3+7V/6nftUwiIQhQIbc\n9Ki1KO/Iosxtq3tcO/o5uvYfjnRyArkg1ALZ7+OD525h0pPrKT8Ofo82unBiB7grtWNimmlfS4aI\nZEGoHT6vm7v6jefQyg84uhFy1mk/j06Dvk82ISL5QXT6kFPHj/+5FyZLUICi1Zw8OVZVD15nFsag\nlDNi9HtOnDpRNpgT+WzhZTTd04g212YQHNEHS2hHZF8JOoMNrzOLzd98QGgiNOlzC0Hh3VAVLz5X\nNhUnvmH3z+Uc3wwmK3S6DbLXQEUutLwKGna+HpM1HVXxUlW2gn+Ov5XivBw+fX4aofEjKdj7Nu5K\nSOs3DgDF70D2leAqX4fsK2HUv/pzxQ0Pn/F6+nwe7uj1Bl5nFt6qLABCYoejyA7MtlbojVGnju3a\n9ydUVWHel7uQfSWExo/EWbIIa9RlmILTkX0leBy7MQU3xV25FZ87G0ky4/eewGhJwefOBuChdx4F\nFfx+L5IkYTIHYQuLJLV5B2ITU2r4r1lzcrP3M2nskxhNJnvjFp0vXzh9wtqzP0oINJEwaETCEGAD\nht99494tK76Jjm9ovOmh1wmPjg90SMJFoJurESWHte99VdByKKx8D4IjoSxHSxgMZghvqJ2kAczI\nWhbAiIULkaqqqKrK3i2/8P5zfpwli5B9Jez+eRnlRyF/D/hcENUYej8WTnjS3eTtepuDy7WfNegQ\nC8C9r91GequuNGnZ+Yz2jx7chSLLNEpvWyMXZFRV5fDezezevJzJb2+iLGcjSR2exWhJQZHtHF79\nOHm7IKUbZK+HvbPPfHxyV7CEajVEzmItaT/5vmzcG9L6QUz6MOwFP7PzRy05+CN6IzTqprUHWlt6\nEzgKtIUKFFlrOyIZ2lyrxXc6v+cEelPU70YzZF8Jrop1+FzZ+D15lBwspHA/2GIhrV9/QuNHoqqe\nU4mHo2gO5ccyObpRGxFyV0JQBKT21P6OlXnazV0Oebu0Ec2TJB2ExGmJocEMkh663HHL75ISqH81\nHbLsZ/EPH7N05ue07TZwSnh04q1iVKH+aJogqWPvqv52r3pVJAzCX6SNNmQvyty2qsfwO/+PbgOu\nE6MNQo1qulvbfC2tv/bBvvYjCInXTjIO/aIdI+kg9RLoeEsGltCOmG2tmLhsZOCCFi4IN3V6ElfF\nOpxFxzEGgcmWhKv0ODt/1E4iZd8fP076g9qa6DTta/FB7Wtkinacs1hLdoMjQW/WTshVBXS/LvMx\nqeh1bov/FwCH2//10bOivKPs37GGt+57CcXvwmCOZfu0QvQmaNJHO+bwKpC92vMWZJ65iMC5Mpi1\nE/1zPdZk1Z4vNAGCo7T3dkwziGkKlrAMgsK7I0kmvFVZeBy78XsKCQrvgtnWClXxoioefO4c7Hkb\nyd8L9gLtRF/2aF/ddm1xhLCGEBoP1igtIdCb4OhGqCrR/n72/N8Sn7OxRmsxSpLWh6b9ITiqCYps\nx11eiNGqJyr1mVNJTn1LFnKz9/PN2Ccwmcz2xi06X7Zw+oT1gY5J+GuaJkjqmNurv92hb4iEQfib\nBgy/+4bMrasmhUXGGEc+9BoxCWJHXaFm7d2ygvs6j0Kn105ujm7UTtpOTknqNApaDXsEd+VWXBXr\nCArTihqm75oSwKiFQCopOEb+sUOkNGuHNST8fx7r83nI3reduzuMwF2pnXS6yrR/X2U5oDNqJ54V\nub+d9NcESffryXM6xLeGjje9xI4fXgRga/S5JQyV5cUs/3ki4/8xHgBLeBCyx8XB5dr75vSE4OTz\n/VnyU1uCI7XkIShCiwdJOzE/+bEv6UBvAJMNPA4tsSrNhorjv0/OTmcwgzlEa1NnAI/9t/8z/o6g\ncIhroV208NjBUQS2GGhzbRPCEkehyI5T9Q8Ao59RSW3WjtjE1FPLlKuqSv6xg8Q1aFwnli73ed3M\nn/Yhq+ZNoU23gZMjohNHiVGF+iktXlLH3Fb97Q57SyQMwnm49Jq7LM7Kspm7N/1y+WXX3cul14xG\nbzAGOizhAjE8vT9lRw/hdWr3V+uyeWJEaxa+bcdjh35Pfoa9cAbrP51PRS50vBUS2zyC7Cul4sTk\nUydFy92ipuHvUsZoFwLqYxH5hqUz+Pwt26n7z49PICImEZ1Ofyp58HndpG5qxrFN//ukszYlddCu\n/Kf0uA+TVZtL7/fk4XVm4bZvwWhJ4cd9C/7wsaqq0mBFCooCJ7bXbtwXE71RmzqlN2qJnS0WzDao\nKoOCvVpCFpoAzQZpIyaSHkzWcILCu6PT2zDbWmEwJwKBH4XYv2MtUz/8F1FxSUXJTdsMWvDd+G0B\nDUg4LyJh0IiEoY4adP39vQ5nbpnjrrKH3vzIm6Q0axfokIR67oa2dwDgKFxG/h7tZ+O2vsvro5+j\nMtdF+XHoPOqzU8f73Nm4K7eiN0ah09uwF85Ake3Y812ASBr+rpMJA1Rf0lATbQ5LbYvXWU75cWh1\nlfbvwlE8B7OtFUZLCqrqQfaWABAVN5br73mRyNgGzPv2fR6O/pPJ9rXMEgqJ7SB9AIQ3vARFtpO3\nawcntmvJjCUcml0WjjVqIB7Hbqbt+pnW2ek0vVTPgaUyMWlQkQeHV2hz74XaYY3WRjFO1nXojdCg\ng/b3jE7TEgvZC8ER2vQoY1ASlSeOY7SANSYDnzsbvTGK4Ii+AEzZ+GqtxO2oLGPmxFfZu2WV2rrr\ngNdWzp30XK08sVCj0uIl9Z1bq7/da94RCYNQTa68+TGpvCR/3M4NSx7o1PtKrrzlcYJtYYEOS6gn\nhqf3x+fOJqLhg5is6fhcObgrt+CtysLvyaPiuMymr2DgC0HsneNC9kD/p8cg+0rYM+tVctZr+zIk\ntH4Knd526uodBP4KXn11+om9pNOmYkQ11uaeAxzpeObJft7RLDI2D8TjAMV/ZpHoHwkKh4TWYI2B\n+JYQ3jADkzWd4Ig+p1bt+XTBwD+skRp92Wx8rhyqylZQlrPx1CiUuxKK9msFyM5i7Wp9cCQgaVeB\nT053cRZr04yOrP7bL0+1i0yB6KZasW9RllZX8EdC4iC+FTRor/V372yRINQlllDtPWIwazUpOh0o\nCjiLtPfEf49khTWAdiMgsV1/JJ2Zads+rtH4VFVl47KZzJj4Gk0yOmbGNEgdsHD6hBM1+qRCrUmL\nk9S3b67+doePFQmDUM2uuPHhtLycfQuP7N/R+Orbn6brpdei04k994RzM6rnu7gq1lN8cCN6o/YB\nqzdC9lqtODGikfaBfHwbXPXWLeiNkWz44gMchdoJaJvrmmCNGojeFFVvCw9rwzVNezLzgHZlvZfa\nCHcllB/TTmxQoXCfNlf/dNZobdpF2dHfilarSrUToJQe2nzuk/PDrTHgqdROzM82N17SaSvmtLtB\nj04fQs76cipPaKvumGxaHYEtNhxJZ8JjL8TnAkehdsLvdYKrQjspM1i0K7l5u/68+FZv1PrhdZ7f\nPHZBqC7BkRCXAUarVrOR3EX7+WuzxhJsC0NRFfR6A+FRccQ1bILRaP7fDf4Pxw7t4buPXsDjcnrT\n2/a4d+nMz7+qnl4IdUVanKS+VQPrfVz7vkgYhBpy6TWjbzuwa/0nRpPZfMP9L5Oc1jrQIQn1QPMD\njbCEasP49jytQDM48reT18a9tOH+rEXaqigjv3oJgzkRv+cEebte5MAy7Qpy88F6bDFXnrpafbEn\nDSM7PoLsLcHnzsYS2pEd03+mYJ+2yktMMz2Zc2Vkr1YU6vdA6RHtqvXpV0P1Rq14NCROW0mntlhC\ntVWELGHgLIHSw4Ev0BWEmhKXob33XOVaYp4xBDIGtz216d2gEQcZMPweouOTz7lNp72COZPfYcvK\nubTucunUiJiE2+dMeU+8iy5AImHQiIShnrny5sf0ZcUnvty1YemtHXpdwVW3PnXWlUqE2ufzuvl2\n3HOERcUSGZuENSQcW2gEUXFJBFlDqSwrIi6pSa0tn2v6vBG2WO0KsiVMu2rt92jTVy55OAN3RSbb\nv4Njm7Wr0P2eGnNqCsuOH+/GEgop3bXiZ4M5AVNw+kWdMNw9aBGlOWOw52cS2/xOvM4stkxZzYEl\n2u+Tu2onKSk9MsjdlkneLi1xUPxQfEBLzARBCBzt/amtCnVgqfazc6n/URSF9Uu+5+ev3qJxRoeD\n8cnpV8yf9mENrvElBFqTOEl964bqb/e6D0XCINSCK258uHH+sQPzD+7ZnD7o+vvpc9Wo8xpWFaqX\nx13FQ8PObTL32U68qxwV5127cvrc+VbDtOkjudt/WwrSGKQlECevfjfuDX0eewpTcDqKbKf40MtU\nHC/HGg2hicMuulGGLv/f3p1HR12dfQD/3lmzTNbJQiAhIWGVCIgWsEoVFFkFWVxYVFxAUV6hxeW8\neqzaWl5abV9AjDQgrZVNLEuRpYigFhQLgvgSCARCQBKSSTKQZJLM+pv7/vHMTCIlIDrDbxKezzlz\nkslM7jy/H5yc+9zlufW0xMjVQAfdeRxUBtRm8R021YUSAlc9JV3N+fcqxKbRrM7l9iEwxkLDX+5W\no6OZhtF/orVKETF9MeePN6DPz4dd8vePHvwC65fNBQBHl9wBj3+yfgnXl74G5KQIOe++4Ld739uc\nMLCr6M5x0+4+U1zwN6ulNH7Mw8/jxl/czfsbwsCMEZnwKEsu/8Yr9MriDBgjotFoq0FGTs+L1hv3\nuF1wOuyIjonD/b0fwf4VO1H0Mb32bf/FsFpK0SGrO7p9NgURsbRB0GZp2lhYWwYkZAGDnhsDU9Io\nuB2n8EXe71BbCsSlA30n0QmvrsYiAMB7u2YG/TrVNm3ox3A7TsFmWQdXYxHcDQqqjtOyBq+HOh5C\n0POKw+FTPpQx1jJ9JA2GdB9OfzfH/dco9B88Ht363AKtVtfi75WdOoYNy+ai/MwJb48bBi6MS0z9\nFZ+pcO3ISRHyf8YHv937F3PCwFRw++ips4sL9v5epzcYxj72IrpeP0DtkMLGjBE0ut68A79482DM\nHJ2D9pldcX3/IUhO6wiDMRLVljMYdt/T/7FUyOv1wt5Q94OXf9VYLXhu0rfBu4gfSEonPM5y6COy\noLitqCldAn1kJr7btxPVx4He9/aGx1mOws2VKNpO69azfk4HJqV0B1J7DIcpeSSEaJqt8jjPoq5i\nNcq+KURsGp3qmtKNZh8AoOrES9hQvO+qX2uoTBnwGioOL0PlMdrw63HQDEL73v2gj8hEbdmHKD9E\nh1vZLAiUqGWMhQedkcqvjpj7EnQRuThXQtVN49o/BI0uBpVFz2HVoa9hiku8ZDs1Vgs2L/8jDn61\nHbk3DdqYmNJhyuaVC2xX4xpY+OCEgXDC0IaMmvxLbY21YkHhgX89lZ7dQ4ya8itk5OSqHVZIORrr\nYau1IjYhGXq9Eeerz0JviEBMfBKEEHj8ro8A4Hsd4ObcjlOQXleg83s5itsK6XVi2acPB5KKqbfl\nQ2dMC9Sk/8tnUwFQkvGvze9j0/I/obbmjcu27aw/hLqK1ZBeF6LNQ2CI7gqNNgYanemS1xAqNWVL\ncGDFXlQUUMc4OglI6wX0Gp8Coyk3cM/e3/PfVzWuUJk2lKZhvIoNNss6AIDRlIvzZxbj+CeAq5GW\nEzVU0YyCzkgVjbgyEGPqy7md9iX0GvceAGD763TS1h0vrgokDPPWzkXnnv0uOwtfX3ceO9Yvwa4t\nK9C9zy0Hze063rNtTR4fPHONykkWcu644Lf7QD4nDExlIyfNirNWlv716De7x2R16y1GTprdphIH\nr6KguHA/vty2Cgf3bIcpJg6156tgty+66Ps9zrMQGiM0OtNFO90e51lI6fIdUBbzk2KT0gnpdcFZ\nXwC3/RQA4J3tr2P/rk1Yk9/pguuwBU6cddYXwHJkL3gdbxQAAAx8SURBVKqPA267/3V6SC8tf9Ho\nqLKNORuIbd8bEbE3wmjKvWjMXsUGr8f2vbMTLoxTcVnhrC+AIborhDAE4mio3o2i7VQStHnlnuRu\nQFIOkH4jkJDZG9Hmu9rE5ue7O2bDWafAlJIDfWQm3PbTcDUWw2OnZMCr0GZxf713xQ3UfEebJRlj\n6uhyB30dMG0KvkIeACD581jcNTMTaRk5yOjcCzfcMhzts7r94OISzROFzj1/VpKa0XnKtjV5X4bq\nGljrkJ0s5Nx7gt/uxKWcMLAwMXLSrIRzlWXvFn6z656srr3FiEmzWkUp1tKSQuzeugLRMQm4vv+d\nOF91Fru3rkTl2RJ43C6UnhgbOBPA30H3d5r9HWGtwXzFI/IXtnU1SemE234a9po9UNxWOOsLIRVA\naAGh0cJZp8DtoHr47gZfCUxBZTkTs4AOfVMQGX8zIuNuhlZvDrTp9dQHnl/4ea6GIjjqDuDEp7tx\n4jPazBsZTwmLq4HW6fvLfsZ1oO/TbwRSrxsMj7MctopCGGO10OrNEBpD4AyC1mRyv5cgNJQs6Yxp\ncDUUQWgMOHtwJ8oONpVCbekMAsbY1RUZTzOdAM3yAYB8rA5vzX4V/e8YB3NqxhW3WV97Djs2LPUn\nCsWp6Z2nbvswL4yOIGRqyk4S8vUxwW938jJOGFiYGfPw8/GVZ0++W3hg19jMLr3E8InPIKtrb7XD\natEn65Zg7dLXv7fnQErqsfmTAH8HW3qdgQ6xRhcD6XXBXrsH9VWbULhJQebNQFLnwSj5YicsR+jw\nLOmlw6si46jEqBC+jrlvFB8CgPQ94KtykwgYo4GMn+UgoePTIUkq/AkLAHg9NPtAn2+Ex1keWA5F\nMwGFsBymWQCArielOxCVAOgi4mE05UJnTIPOmObr0BvhVWzQ6s3wemzwKvVwNRbBUbcfHmc5vG4F\nXoXW7Fceo6TB46AkIbY9LUcSmqbDvTxOuk8CgJRN99CcDcSnA4aYSADAxlNHg36ffqqHBy5CfdUm\n1JYVwuMA4jvSEiuhMUJxW2Gv2QvFRffAXgNUFNBBZ5bCptkfxtjVldSZCjMMffU11LhouHf2ixvR\n86bbr+j8hObqaqrx6T+WYdeWFeiS2684NaPLw//8YFHrG/lgIcUJA+GE4RoyctKsuHNVZcuOffvl\n2OR2HcWd459Az5sGqV5V6dHBqwLfL9s5EVNvy4cQBmgNZrjtp1F57A00VAPxHSMRkzIeUQm3AaA1\n9t+s2ovS/bSWPJj0kVQxyF85yGACtLqmsny6iKZTeT1OQB8FDJz52iWXAHmc5YF9DlqDOTAy3zwJ\nUlxWeBWaFfAvV1LcVnq4rHDaiuGoo6UylUcpPv9DawDcDjqh1xhLyZAhKieQKFAC0R5CY4DXY4Pb\ncRqKi9qW0gmXzQ6Py5dQRQMRcekwRHWFs74AFQWVqDxKCYXQ0AOCEgV/wuB/LjSAIQq+EqzUFgBs\nrVRvCbCieDCp7zS4Gotw/lQpTn8FFH9Or0XEAu370L+51uArm+oEGq20d8PVwDMMjKktvS99XV77\nKvoNugem2IQf3Zal9CR2bliKfZ9/hG69BhSnpOc8xEuPWEuyk4T87ajgtzvlPU4YWJgbOXl2ZK3V\n8kbJsW+mexVFf+e4aeg36B7oDREh+8xD/96BvNceRdWp3kjIoDKcj79Qj+qKM3A77Vi98BRMySPh\nqDsAjdYEnbE9tHpzoKPttp/GuVPL8d1eWiJy9qB6o706I42km1KoxKZG15RERCfRz2NSAYMpHRGx\nN0IIQ1On322Fo7Y0sOwHoI6qPgLQR2shvQqkb++C/z2Km85LqK+kDrviphFvtx3QGimR0RkpadHo\naAlRfDp1hMsOUnJxeg99ltAAnQfT99K/P0ILpF4HtOuZDo02JjDL4b/3VccUWI4A9lqg3kK/o9E1\n3Qv/sgB9JMUgBOBxAc66pp/rIprukz/JkBIo6RvaJGJc18FUHrVcwXf76P9NsJNLxlhoLbD0x9D7\nZ6LHDQN/9GGXUkqcPPI1tq/7M4qP7EePPrd+aU7NmLb1g0VHghwua2OyzUL+ZmTw233wfU4YWCsx\navIvRYPt/JyyksKXLWUlsYNGT8XAEVNCcnK02+XAQKUbqoublrGYUoDsgbTER3pdLW5KBpo28Urp\ngsdZDnvNHjSeK8TxncC5k4D1pDq18P2HcsV1oM6yPtI3E6FtGvWPTqKOvp/iApwNgMdOnX7pbdrc\n7FVohFtxUzLibKCOt78Szw+5xqhEqhYiNNQ5bl72MzoJaJcLdBtCy4bKDthxZh8dQuYfRc+6hfZF\nmLMpkaktB6qO0QnFtWW+/RNBpNUDqT2B6EQg0bcv/M+H8pDaIQep6dnQ6Q0AgHY7qTxuxeCWk4zs\ng5mwlQPRyZScKC6KmTcoM9Y6Hbp5Ccbopv3H37LL8Z/a7FUUHNyzDZ+sy4etptrbObf/3xOS2z+1\nZeUCa4hCZm1MJ7OQvxke/HYfWsEJA2uFhoyfPs5SWjz/xOGvM968+ft1Iv1/eH+Mzocy4XFQh76u\n/OIdXp2ROt3tfPuxFRd1mnVGGpnudCt1xB111Gmtr6ITdd126gj6R+rDgdBQohCV6Fu2A+oQ+7/3\nOGn03dus063R02g/ADhtdF3+BOJaZIgGEjrSvhGvhyoS2Wt4/wBj7Mq9/H8dYIpNcHbs0uutuITk\nFzetmB/kIQ/W1nHCQDhhYN8z7P6ZPUefe7sg2O1GxAIR8YDOQKPZl3pfQiZ1FJvXuPc4W18H2r/f\nQWtomklQg85IswLhdP/a9QQiE+geeZyAtZiWXUUl0mv6KKDddbQno6oIsByhhJMxxq7EWtNjU3es\nX/qe2nGw1qtTopCvDg1+u1NXc8LA2oCRk2dH1p2v+u1E98o5wW7bPwoPUGfxh44c+zfPhtOMArty\n+kjfHo9o3yxSJOCooYpPjmb7HhKzgCgzvcftoGVRDdWqhs4YayU+Mj/dY+vqReFXpo21Op0ShXxl\nSPDbfWQNJwysjRkyfvq4sXVL1qodB2OMMdaS1frJv49JSHpl84r5XNeMBU1WopCv3BH8dh/9OycM\nrI0aet9T6WPOv3NG7TgYY4wxv/Wx04ZtX5u/Te04WNvECQPRqR0Aaz22rckrBfKEEEIMHvPo5PEN\ny95XOybGGGPXnpXaB+bHJab8evPKBban1A6GtW0yvPYAqoUTBnbFJE1LLQfeXT5i4jNpo6rfOqt2\nTIwxxtq+DfFP3PHxh4t3cpLArhpJlQuvdZwwsJ9ky6qF5cBCAQBDJjwxcmxt/ia1Y2KMMdZ2fGB8\n8NemuMQ/bF4x38mJAmPq4D0MLOhGTZ6tb7DVPHuv/b25asfCGGOsddqSMjtr04r/De1x8IxdRla8\nkC/9IvjtTv+ode1h4ISBhdSIic9k1J6zvDzZu2aa2rEwxhgLb/9ImHHXtjV529WOgzG/zHghX7o1\n+O0+sZkTBsYuas6cGd3Lyy0v31q1fpLasTDGGAsPR7o9OsFkil43b95C7pCwsJMZJ+SLtwS/3Se3\ncsLA2GXNmjX9psrKqhcGVm+YoHYsjDHGrq6CLlMfi42N+QsnCSzcqZUwCCGGAVgAQAtgqZRy3gWv\nC9/rIwA0ApgqpTwQ/EgJb3pmqliwIP9rAPcCwLPPPpVdWWl9bkD5midVDosxxliIHO3x+IiFC5ds\nVTsOxq7U1a6SJITQAngbwBAApQD2CSE2SimPNHvbcABdfI/+AN7xfQ0JThiY6t58M+8kgBnABzOe\nf35mXE1N7fQ+Jcv/0Pw9PATFGGPhTVzwfE+7Ce+YzQl58+fnF6gSEGPBoM45DP0AnJBSngQAIcRq\nAGMANE8YxgD4m6/U/VdCiHghRJqUsjwUAfGSJBbWhBApAK4HEKV2LIwxxi6rBMBhyZ0L1kYIIf4J\nICkETUcAcDR7ni+lzPd95gQAw6SUj/uePwigv5RyZrO4NgGYJ6Xc7Xu+A8ALUsqvQxArzzCw8Cal\nrASwQ+04GGOMMXbtkVIOUzuGcKBROwDGGGOMMcZYQBmAjGbP030/u9L3BA0nDIwxxhhjjIWPfQC6\nCCE6CSEMAB4AsPGC92wE8JAgAwDUhmr/AsBLkhhjjDHGGAsbUkqPEGImgG2gsqrLpJSHhRBP+l5f\nDGALqKTqCVBZ1UdCGRNvemaMMcYYY4y1iJckMcYYY4wxxlrECQNjjDHGGGOsRZwwMMYYY4wxxlrE\nCQNjjDHGGGOsRZwwMMYYY4wxxlrECQNjjDHGGGOsRZwwMMYYY4wxxlr0/y7sce7pklZYAAAAAElF\nTkSuQmCC\n", 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\n", 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ilXBI6g/J/SFzQgbSCBDyV+CpUk5foEkJB0MHb43aTqJlx+mWHIeKTR1bKQna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A6nyA4OVZyIjHRaUBgVBXdVBLNYxEiJaZzm81YsUI1USkwF6uuRZKmSbyC7XBRi8TIdShVWqi4X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A6N/cUgBP/3cV8kjQZ/eTlBcXEoiooGw28mb/sONo2fRtofi/lq7HKemVxCbhEc2JnHckcQ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eZVq6QsgfdcAgpfy7lHI8cJaUcvxXHkdJKV/e3nF2KMfrdPuWN9ZW7csOWEnnyLGnMPaw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\nuafWQYZUBBTtPdOUTTCLly36uwzyPsuxzj+Tim5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0bfKKK+YesQ4c5TUMhmGc0fOzwjCM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\n4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6ZM6ovMM4fFLokQQgghtYjZWIIvPxyH/VvX2Dr2HNp554alb4ld032HdkmiwHCv0pbP\nNKfv2tCk8QNdp8x//1lsWTOfTocmtQY/XQd+uk7sMggh5L6UmZGOKZP6QiqVnWrarqd20+ovdold\nE7k/0S5JPrIzbek7vYa+kJa+a/22jKO7/Z567TMEhUaKXRYhhBBCahje5cKvq+bg91++Q4uOvabs\nTFv6jtg13a9q6iJlX6MRBh/atGre3sZtHg4O0ITunTKpH07s3yZ2SYTcE8lr2cArWTCUFAKgEQdC\nCKlsRflXMeOfT+DUod9NHXsOfYDCAqkOONrhp3I8nDp2wrE/Ns1t1r4nN3Ds21Ao/cQuiZA7duH0\nIdT7dfANb5O8ll3F1RBCSO2WvisNK+b9C00e6LpZG1m37/plM+ikWJElx3DC7Od8327f95AuCMID\nvm+5clBgqER9h0/SZZ87tr+kKD/y6ddnIjahkdglEXJLNmsZdm1YigGm/yIsGcj+o+LtFBQIIcS3\nLGVGrPnyfZw7sZ9v1r7n2G1rF30rdk2ESY7hhNnjfd9u3/drVmCgNQyVaMP3n2f3H/lqdEnRtYWz\n3h7xTM/Bz6HHoPGQSKVil0ZIBckndbCXlc/TlF8EzADMheX3qfcQu/2SGAUSQkgt9efJA/hu+muo\nE18/q03X1Ac3fD87V+yaSEV0aZ0CQ6Vbv2yGAODZXkNfWHz0j1+3nDiwzf+pydMRFlVX7NII8RJ4\nQO4POMrYx9oEQJ8JyFUAJwGUAUB2WxpZIKQqjeu1GQCwcNMjIldSOYoKcqAODIbSz1/sUkThcNiw\nfsl07Nv2g9CiQ68Pd6Qt+bfYNRFyM7TouYpsWjVvb6NWXTVhUXEbP34lFXs2raATokm1YCkzYuL3\nHSG4gIZ9AHAsNAAA7wTsZsA8ksICEY/L5UTupT9xOn0HTh/eiZzsc3DYrWKXVak8YUEQbHimxw94\npscP3tvaW3ToF62DyVCM9UtnYGDygxhQNwGp9ZojtV7z234Ms7HEu6FBVRvXazPeGnUSP309VZTH\nF9uVrAxMe+VRXDp/XN/xkaGNKCxUc3QOA61hEEPPweMfO52+Y5U2MlY+YtJUBGtp+1UiDmOpHl0c\nrWDIBfy1QMklQH8BMOax0YU49+zKzF20doFULX3eFYxp0xnZ+1wwFwIcB8S1AaKbDIFUrkV47DI8\nOvp1dB0wRuxSMbhBb9jLzqFMz9anbjOX/18Z12szbKYTsJlOAgBWHvv6lu2N6bIAVsNhcBIFJNJA\n8C4jeKcRAm9HwZ+7sW8BEBoPtHs2EaHxr8JuPoerR2fDXMimEZ6I+/v/VUEQ8HTXhTDrt0Aq10IV\n1B4yZQwA4OUPZWjS5uGb1jMo5WE47TkAgFUZ6eitaYToZqlQBXWAVK694QjImC4LAAASaSCcthw4\nrNmQyrWQSAPAu0zej9+amYwGLR685c+ktnC5nNi65ktsXbsQzTv0WhysjXrWPROBVFPJMZww81nf\nt9v/g5q1hoECg0j6jXhFXZCbtTnjyO6Og5/9F9o9PAgcx4ldFrmPuJwOzP7XKMwbtQ+8C3Ba2UWP\nvFOApYTdp95D7D1NRyJVxWG3YnSHN3FuyzrkHgeuHGZfD40HWj8JRDUeBak8FJxECQBYuOUZKPxU\n4hUM4JFgHRxWNhrnsADBsYAmpjn8NK1RVrQDhtwLkCkAqQIIjOqDFUfmI+Z3HdRhQFRjILIxu6/D\nchGG3O04vR6QKYFGA6QIinkKAGAp+QP5GRm4fAi4dABQhwHJ3YGCP4Hii0BCFyChUwQU/ingJApI\n5Vq8+llnFOZm44fF8XBYspGx8RM2ktj3JW9YkMq13ufRf8RR9Bk2qcLP0+GwYXjzIXA59DDkXAEA\nhOiaQyINhH9oF8iU0d77tu+2EYLA4+f5m2EzuBAU2xY20wmogjpAGdAEDms2bMaTkKt0sBoOw24u\ngVQBuOyAX1As/DStAQBP/7MRIABOpx0cx0GhVCEgKBT1GrRCREx8Jf82K8/Vi2exZMbrkCsUxoRG\nbXpvWjVvr9g1kVujwMBQYBBZj0HjnjidvuO7sKg4+YiJHyE4LErsksh9IPmkDk47+9jlABr0AvbM\nZaMKpVfZ1/w0QHgK0OfDOQCARZsHiFgxqY0EQYAgCDid/js+erH83Jr9Xy1F8SWg4Cz7PDCShYXQ\nehG4tD8f+kxAoQY6Pv8GAOCJiUBKk3ZIbNymQvuXzp8A73JBl9K8Ui7ICIKAzNOHcPLQb3ir41zY\nTUBCZyAsqQ+cthwcW30MDgsgUwA28993HFMFA+H1WYffmFfxtpgWQEQDoE4LIP8MkLUbKDx/4zo4\nCbtfcBzA8yz8cxzAX7chp8sOaOoAjQewkQFOooDA272jFxJZICTSQPa8eBsEwQ6HJRtWQzqspRmw\nGoDc44DNBEikQOPUCGiingAA8C4TnLZcGK9tRMGfbJSS4wCrkb2OxHdkYcqQC5jy2ceXD7LXmevJ\nVUB0M0DhD0hkQIthzeEf0gUKdQo4TglBsAGoea9FLpcTW9bMx7a1i9C8fc9lwWExT9KoQs2RHM0J\nM57xfbsD/kuBgdwhNtpwcXPGkV0dB419G+17PE6jDaRS1Utnh6/5a4GkbsHYPrUEchX7g517gt1H\nKgeSugFdXpsDl10PhzUbS/e9K2LVpDYY1vxpmPK3w5ADKDWAv1aFMr0FJ34Erp0qXz9zOzTui9sG\n954yQXXYv9uyIiAgAtDEAHValrcrdW/zsfjyR3gu5Z8AgNOJdz56VpB7CWeP7cHiaYC97ByuHl2M\nzJ2s464OYx1qUz7gtAM2A9tAwGG544e5Y1I5CwmBkexno1CzkKBNYHX5adj6BoclG+bCEtgMQEg9\nFZQBTQGwoOCwZKM4uwT5ZwG7CbAZWe12Mxt5VGqA8GTALwjwD2GBgJMCOcfY/ZxWdtHBcJv7/HhC\nk0TGgpWuAxAYpYLA21Gmd8FPA4ToxkIq10Ku0tW4sHD14ll8N2MyFAqlMaFRm0c2rZq3T+yayJ1J\njuaE6WN83+6jUykwkLvUY9C4YRmHdy0JCg2XD584BeHRdKIuqVyn03dggHQ0mg2Jhcuhx7b/Wipc\n6ew3FYhuMhWFme/j0n6L94rl8RiaonS/0uddxrXLFxBfvwXUgcH/874Ohw0XzxzF6PpDYTMA1lLA\n7u5U6i+wDm5QLPv4djuY90ITDUQ2AloOL18YvOb0z7f1vYaSQvy2bjFmvzAXVgMgkbBRA/0F4Ep6\n+TS+6sRPw4KCfyib4sRJAHiuRQnsc4mcPRfPtMT8sxW3U74RTsIuLkjlrKNvMwJO293XqVADUU0A\ntZa1Y8oHAqOARgNUUGvZ+giOU3inoU2c0hL16rdAREw97zblgiDg2uXziKyTUC22LnfYrdi44nPs\n2rAMzdr3XBoSFjOaRhVqpqQoTpj+lO/bTZ1GgYHcg+4Dn/EzG4rXnjz4e+9HHn8O3Qc+C6lMLnZZ\npJZofFEHa2n5VIXMlhcxeWhT/PCGERIp0O2NqTDrN+PgN9tRVgx0/8coyFU6FF+ai6w9Jd7Fp+eb\nUmC4W/x0diGgJi4i37/tR8z/wABOooTA2/D+otYICY+BRCL1hgeH3Yo6v9XHtVMiF3udoDosKCR1\nBfyCI7yLiRXqFCgDmkDuF3/TrUsFQUD8wXjwrr9PKSK+J5UDYUlAYDQbEbKXsalQVgMbOYlrC4Qn\nAYoAFoiUgYlQqFOgCmrvDRSLtw8X9TmcPbYXyz//J7SRsQV1k5v1+nXl3COiFkTuCQUGhgJDNdVr\nyIROmRnp661lRs3Ilz5GfP0WYpdEarikE6yjGl4fyDnKvrbC8BlGhU8G72JznLu8+jykCi1cdj2U\ngU3AcUrwLiPM+i3I3r8RlmJ29Q+g0HC3PIEB8F1oqIw2+0ToUPgnC5exrVkYkKt0UAY0hUwZ7Z0D\nDwDhMQsxZPy7CI2ogw3fz8KksD0+qeFecRIgsiEbxVCHAeYCwFIKXD1cflU7oj6Q0PlhaKKGY976\nLhgQlYKY5lNRcP4d2AwuZO0BLu2vniMItZUqmI1clBWVT1HTdWDnwQREwPt6FRjJFpjL1VKUZLsg\nVQCaOio4yizwC4pFWAKbQllV51iYDMVYu/i/OJ2+S2jarseUnWlL/lUlD0wqVVIUJ3z6pO/bHfgp\nBQbiI/1HvsqV6K/NOb5/6wsPdO6P/qNeg39AkNhlkRqi0QUdHBY2tA+w+cXWUsDlZH+EeSebSqFr\nDzisbMpC55ffgNWQjvSl25F7HGgzBqjTchQ4iQJ+mlbetmvaPOLqQvalDnZzxa95pncAgPO5ip39\n3EvnELmm522377mS3miACoERg+GnaeVdyOqx4NeeN1wj9WSHj+C058Ks34ySSxZYilnHzGEFDFfZ\n2hZLCQucQTEAONbp9tOwq8KmfNYZv1g9sgIANhUnshGrL+/03xcWewRGApGNAW09Nh3nwg4KCNWJ\nXMX+nXnWWXESNnXJUuJ+TfvL4unASKBBHyChc1twnAKrTiyr1PoEQcCB7Wvx4+IpSGzYOiO8Tr0e\nm1bNy6nUByVVJimSEz4Z6ft2B82gwEB8rM8Tk5Jys89syjp7LOGxMW+hXffBkEjozD1ye1oV6mDM\nc2+bKgCCi22fenEP26oyIJL98c05CoxY0gcCb0P6UrYoNSCSHeamDnsIyoAmkMhY5/PbXRNFfU7V\nUY9AHbYaWYd/SJMhsJvPofRKCWzugHBpH9si9HYX9SrU7CqqpzMklf+9Y3QzUjm7IpvUjX1++SCb\n2hHbEpCp2ALWwAh2W1kxa9dcyDr9jjLWsRZ41jlzOYGizJs/NidhV4QdlqpZ2EvIrfiHsmCrUAMQ\ngBR35n7v+xnwDwgCL/CQSmUI1kYiMi4Rcrnyrh/r8oVTWPnFv2GzmO0pzTs+t23tom988iRItZEU\nyQnTKmGW2+BZFBhIJek+8Nmn/jyx70u5QqkcNuE/qJvUVOySSA1Qd78OHMc6fDYDkJdR8fbErmzb\nw1Pr2MLT4d+8D95lgs10EpcPbUTuCdYpTOkB+Ic2REB4f0ikAfj69zFiPJ1qo7dWB30m2yFGqQYu\nHWRbXyZ1A5o9HoHMXfmwm9kONXmngTI92xbTahC7cjaaFBAJqIJYUPAEBEJqo9B4wFTAgrJMCTTo\nzQL175+y2782PYkeg8YjLKrubbdpNpZi/dJPkb4zDU3bdl8eEh49Zv2ymbcZ6UlNQoGBocBQw/Qf\n+aq0uDDn6xP7tz3ZqlMfDHjyjVvuVEKqnsNuxfdz/oUgbQRCI2KhDgxGgCYE2shYqNQaGIoLEBmb\nWGXb56qX6aBNAi4fYIsJy/Tsj2dCJ6DHO3NgKdmHPXOXInMX6/B2nDAWANuZ5OyW+fDTALp2z8Ne\ndg6q4A4QePt9PcrQL1qHq0dZJ6RhXyksxS6c385OxAbY1KDw+kBsKzZ3/txWtmWkyw4UXbz5fvqE\nkKoR3xEIrQf8ubV8qtrtrP/heR77tq7Gum+mIaFhq/NRdVP6bFzxOf2PrsUSIzlh2jDft/v45xQY\nSBXo88SkhGuX/9x4/tShlF5DJqDLgNH3NKxKfMtmLcPE1N0QBBs7HMlpBO8yeXdnkcgCwHHuk2pv\nsSCvzFR6z2tXrl8U++h0wFIM7JpVfrVbm1C+laLVwEYTHpr0DninEQ5rNvQX1sFqAILrqhBcZxxk\nyhjwLiO+2TH+nuqqKTRrdFCq2aFYN5qe4x/K5lh7Dr37K6mc7Vt/o/nWhJCq4dkK1vO6x7ln9moT\ngO1hX6JFx97/8/vPHN2DtYunAIA1uUn7Z7euXVi5iyNItZAYwQlTh/q+3aFzKTCQKtRj0LgBly+c\n/E6fdyU49ak30brzAFrfUA1M6KuD07XQezKp3XwOLkcRBN4GTqKEVB4KuSoenEQBAN7w8Fee7/d4\n78skKP3UKDOWIC6x8Q33G3c67LBZLVAHBmFcr804v2Mctk1htx1rNx/6vCuoE98Ajf8YxaamRLB9\n1IPqsK0K9RfYEH7HF1IhU0SjrHgHjq3JQOlldp/6vYDwlHcg94sHUHU7kFSlIU2GoCjrALL3sQ6+\nwLOQVXqVLRYPjGadD89uU4SQ6i+4Lluj49l4YJEpFe0eHoz6LR6E1HOq3w1cvXgWPy2egtzL5/mG\nLTvNDgqNfI3OVLh/JEZwwkeDfd/usPkUGIgIuj465pULJw98LJMrFAOfeRspTduLXVK1MaEvu7ru\ncM4B7zRB4G1YtHUUJj6aiBhdCpq264nw6LpQKFUozLuM3kNf/NtUIZ7nYTEbbnv6V4k+D2+MOObt\n8Hu2nxR4OziJgr1xSgiCzXuKMscpoFCnVLiNd5rgtOV4v08q10Kq0IJ3muCwXERZ8Q44bbneLS4F\nwQapXAuFfwr8Q7pAIgsE7zTCmP8jDDnHoGu3EPayc8ja8wkOL2NrFhI6AXXbAeEpDaHW9oRcFQ+X\nQ8/a421wWLNhzFuHSwcAp4XtJhPZsA8U/sne5/vdnsm++FVVC50lOlw+yHYF0kSX7/ce2YjdXvgn\n63AUZ7PpRYSQ6ie6KZB/hgV+mft6jMvBXu8uHQBKRxxBQFDo/2yjRJ+HtKWf4ei+LWjyQLefQyPq\njEpbPstYBeWTaoQCA0OBoRbpP/JVaYn+2qyMwztfiE1oyPUf9RriEpuIXValspaZYCzVQxMSDrlc\nieLCHMgVfggMDgPHcXi66zeQKrRw2nLhtOV6pwYJPOvIuxx6SKSB3qv9EmkAZMoYcBIFnLZcuBx6\n8E4jJLJAKPxTvN+3+LenvKFiSJMhEHjWuQeAH89tB8BCxs60JVi/dDoun2nl7fTLlDGQykPBSZTe\njr7LoUdZ0Q4UX7oAp4UtSFUGRkCuiodMGQ2pXOs+6VThfe6cRAmJNIC9lwV4v+6ZAiUILKRIpIHl\nIxnXfb/nvp5gAAC8ywSXQw+H5SLM+u04swEovgwUXwSUgUBEA7YNqzoMCIhoCwBYfXK1T3+nYhna\ndKT3d27KLwEnAcx6wJTH1ioYctnP4V5OtCWEVK6Gfdl7G3s5RubO8sBwpvNKJDVue8tReJOhGNvW\nLsSuDcvQoMWDR7VRdR/btGoeHTxzn0oM54Qpg3zf7hMLKDAQkfUb8XKQPv/KN2eO7E6Nr9+c6zfi\nlVoVHHiXCxcy0rF30/c4+scWBAQGobS4APqcId77eDrivMsIl11f4WuejrSnA85CgQkSWYB7fUGg\nt5Pu6TwDgMI/BTJlNATBDoclGwJvg0Kd4t3n3pj/I3inEfaycyjTu2B3/8FaV7AX6bvWY+F7O6FQ\np1R8Lu77Ww3HkHscKL1SfgqzwF/3BkAiBWR+gCaq/CAqZUBDb60SWSA4rjwQyFXxcFgugneZ3MFC\n4W7XHSRkgbCZTkLg2aiEvewcpHItCs9vR/Y+1knOPV6+e442AdAmAbp2gDpcBbX2ESj8U2r84ufk\nUzpIFYBaC0gVbC2Hzejegtb93F12NpXBYWGHSd1sP39CSNWQytnaoehmQExz9rXfPwXeO6VDdFwi\n4pKaoeWDfRATX/+2N5e4PigkNW6TFRmXNGrTqnl7K/FpkBogIZwTpjzm+3aHL6LAQKqJfiNeDinK\nv/pVxpFdj8WnNOf6jni5RmzFeiUrA7s3LoM6MARN2/VAcUEOdm9cjvycLDgddpzZJwfHKSFX6bxX\n6z2dZd7FpurIVfGQyrUQeJs3IPBOozcweMICJ1F6r66zgMF6+WxakAKCYK8wHUgiLb+S7/leT3sS\nWfmVfN7JrtS7HHrvbRJpgPccA89Vfd5lAu80wuXQw2nLhdWYDrvRAquBBQeFmnVazYVsGkxpDsA7\n2NA6J2EhQqEGYlsDmphYKAOaXrdOQlthROH6kQSJLBBWQzoMOceQtRsoOFe+GJd3lrcPsD/M2kS2\ny09QLKAKYVN0/DSAKqQ5rIZjEFxAWm7NuwDX3qKDJhpQaqSQyrUo0+fDamAnAZuLKgYmQoj4NNFA\nlPvPWJy7q+WyA/9Y+hradR8EbWTcHbdpKi3Ctp8WeYLChcjYpDGbVs/b7cOySQ2WEMYJH6b6vt2R\niykwkGom9ak3g/NzMr/KOLxroC65Gddn+EuIT2kudg2DE9sAAAo6SURBVFk3tfXHhfhh0YcwFo31\nhgDPdCFOwsaWXQ497OZzANiVdABw2nJgM51EmT4fZj3r7AVEAnGt2baWVgNbpCrw7KApZSCgDgck\nEgAc6yBzXHlH2dNR5CTlb2yrzLaQyrXeej1BwFPfXzvpnmlQrC3F38KKZ0qSJ5yw+xvdYaP8+fIu\nI3iHCzYTO0+hKJu9Bwco/N0d+SDWkffXSiFTRkOmjPHWxTuNkCmjwbvYuginLRfWknwY89kfXKmC\n7eJjyGVX13kn+9koNYDSnZOspewAMMFVHioEwR1eZGzUIzjWfWAS4D3IrDoZ12szMnePQ/4ZdlJs\nQAQ7xEymYj+H4mwWzngX+xnYy9i6Bc8uUoSQqhffkb3GyFXlo7CLL32Axg90vaPzE65nKCnEb+sW\nY9eGZUhu0vZCZFzyU7+unFONzion1QEFBoYCw32k34iXg4oKri4+e2zvwPCoulyPwc+h8QPdRN9V\nKbVeeXhZl3UMT3b4CDbTSciU0XA59LhyeDssxWzP7OC45vDTtAbHKVBwbj7ObQWupFfOYVichA15\n+2sBqYzNg3U5WNiQyOE9DM1uYh31FsMSoQru4P1+78iFYIfLrveOOAi83bt4+fpRAJedhQJPkOCd\nJjjtOeCdFthNrBNrzGPz6p0WFmg4KatDImPTlSRS1vFXhQByP8A/xD1SEQDIlBEV1jM4rBdZQHG4\n4LCwXYCcDnYImULN2pH7q1Cmt8CsB66dZAGFk5TPCfa8enB/CVwSKash2D0iAQCbS8QLDy6XEz3U\nid5AUHoVuHjdRIOwJEAT4/6dOlk4MBewqUm0DSoh4kvozN4vvvoe2nZ7DAGakLtuK+9KJrb/tAgH\nd/yC+s3aX4iITRxNU4/IzSSEccIH/X3f7qhvKTCQaq7fyFdUpfq8T7LOHhnPu1zyHoPGoW23xyBX\n+FXaY57Yvw3z3h+LrP1AaD221uDlaR1ReO0yHDYLpj/zBSIbtfXuCKQK7gC5n44tVHaZYDOdQP6Z\nK8g7zebW52eIu/jUT8O2GOUkLCx4OskSKcDJgIBw1lFWa9nXXA42/91qAJxWtiDPbmIdbo5jnXuZ\nik37cdrZFXyHlT1HwcXCgcvBOvV2M7sybilhV9s8V/P9NGzExLPXuMKfPZ7xWvnpzpyEHcwm8Kx9\nl42FifBkILq5ChynhNNa4r2CZzcD+kx3J/sKm7/vaUfg2XulhtUtU7IgBbDnZjOysCL3B/wC2c9D\nIi0fwQGAzJaVGyJ6a3UoKwZKrgCGHDbCVB1OWiaE3L5Zee3Qa9hENGzZ6a4PuxQEAZmnD2HLj1/i\nwul0NGzx0F5tZNy4jSvnnPZxuaSWSdBywn/6+b7dJ5dQYCA1RP+Rr3JmY/Hkq1kZ/5d3NUvT7dEx\n6NR3VKWcHO2wW9Egoz54F7taLwisg5nQGQiNHwWpPNS9e5G9wrQdAN7pPABbh1BWvAO8ywjjNQsu\nHWDz70uviDfXXK5iHXWZgo1GyJTuAOGZ6sS5r8Rf/19NcE/7cYcBpxWwGtkVfId79IB3lX98p3Qd\n2M/ZXFgeFgD3eodWQGJXFiouHQSunai4PWjddmyaTngSCxOeK/I5xypvWk5oPBAcx8IFAKwsnofI\nOomIjE2ATM7+HegOsO1xs9vePGS0LtIh9zgLXxzH/l2YCsr3XSeE1CwnOixEqmzc317LbsVzajPv\ncuHoH5uw9ccFMJYU8klN2q0JCY95YcPyWfpKKpnUMvW0nPCfPr5vd/QyCgykBuo5ePygvCsXZp4/\ndSju0w4VL8F6XnjvRsJRHRwWNiJgKbn5/WRKoG5b1tHmXewKvETC1hnEtmIdQLuZzSW3mdh0EasB\nMOVX7ykjfpqKayI8AcFhEbeu6kymZAsb1WFsxKLkEhvZoJ8ZIeRO/d/xOgjQhNjqJjf7PCgk/O31\ny2ZW478YpDqiwMBQYCAV9B42sfGjRXNP+rpdTsIWzspV/3tLSrmKdRY5CesklhWxDiTtfX9v/rqQ\nW2zRTdlUJo5j25WWXmUjAX4adpvMj60r4KQsJBacpUPSCCF37oeAZ8ZsW7voW7HrIDVXvVBOeK+X\n79sds4ICA6kF+o18RWUoLvhguGO5z4/w9Sya9QSB271yXN06veTOeYKjOqx88TjvYDszlRVVDIbB\nddmiaZmS7c5UeJ7WHxBCbs8v2hcbblwx54zYdZCar14oJ7zb0/ftPr2KAgOpZXoOHj9ooGHhD2LX\nQQghhNzMCvnIjwNDwt5NWzaTxqSJz8SHcsK73X3f7tg1FBhILdVr6AuxqcVfXBa7DkIIIcRjrWZc\n7y0/LNgkdh2kdqLAwMjELoDUHJtWzbsCzOM4juMeTh07crB58RKxayKEEHL/WS59YmZQaMS/05bP\nMr4gdjGkdhNoKjRAgYHcBYENSy0Fvlrad/hL0f0LP88RuyZCCCG130/Bz3XfvHr+dgoJpMoI5aeL\n388oMJB7suH72bnAbA4Aej7+XL+BpQvWi10TIYSQ2mOl8sl/BwSFTktbNtNGQYEQcdAaBuJz/Ue+\nIjcbS14fYvl2iti1EEIIqZk2RLwSv37ZjMo9Dp6QW4gP5oR3Ovu+3fG/1Kw1DBQYSKXqO/yluNKi\nvP8bya8aJ3YthBBCqrd1IRMe2bRq3hax6yDEQxfMCe885Pt2n0ujwEDIDU2ePKFBbm7e/z1UsHaE\n2LUQQgipHk7XH/t4QID6x6lTZ1OHhFQ7uiBOePtB37f7/EYKDITc0ssvj38gP7/grU6FPz0udi2E\nEEKq1snkMc9oNIFfU0gg1Z1YgYHjuN4AZgGQAlgkCMLUv9zOuW/vC6AMwBhBEA77vlKGFj0TUcya\nteAQgCEA8PrrLyTk5+vfaJ+76nmRyyKEEFJJzjR8tu/s2Qs3il0HIXeqqndJ4jhOCmAugJ4ArgA4\nyHHcz4IgnL7ubn0AJLvf2gH4wv2+UlBgIKL79NN5mQAmACsnvPnmxKCSktLxLbKWTrv+PnQJihBC\nqjfuL5//EfX4F1ptyLyZMxecFKUgQnxBnHMY2gI4LwhCJgBwHLcCQCqA6wNDKoDv3Fvd7+M4Lpjj\nuGhBEHIroyCakkSqNY7jIgA0BeAvdi2EEEJuKQvAKYE6F6SW4DjuVwBhldC0HwDrdZ8vEARhgfsx\nHwfQWxCEZ92fPwmgnSAIE6+raz2AqYIg7HZ/vg3AW4IgHKqEWmmEgVRvgiDkA9gmdh2EEEIIuf8I\ngtBb7BqqA4nYBRBCCCGEEEK8rgKIu+7zWPfX7vQ+PkOBgRBCCCGEkOrjIIBkjuPqcRynAPAEgJ//\ncp+fAYzmmPYASitr/QJAU5IIIYQQQgipNgRBcHIcNxHAJrBtVRcLgnCK47jn3bfPB7ABbEvV82Db\nqj5dmTXRomdCCCGEEELITdGUJEIIIYQQQshNUWAghBBCCCGE3BQFBkIIIYQQQshNUWAghBBCCCGE\n3BQFBkIIIYQQQshNUWAghBBCCCGE3BQFBkIIIYQQQshN/T8E6rcMRJtrdwAAAABJRU5ErkJggg==\n", 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\n", 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POR5Kl7ftcWr6zUriPEmHuXfwxRtPcFr5Y4f9uHvicF6fxQVrGbLqTFL6wOav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\n8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PNXnECpLNE1xedAv8T5S1wyRYkn1suM7TmImckRbW3mrRfX8I74Bsz+t5HtH0FWoGnx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c8WNWPNDoWdmYJM2Z4MYwemrSup0HYr+f0oikL15DTpK/VcVKkzwV/bwwBMLXvc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\n9BvxDPOffZWvPFeQFPbx/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vL1R6tYtQ1kGGpd2Z6PjzSi5HAWo4ZGYomOpijzMPm7d+PN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eGgf30r72/v/P4jlvkht7EbMz/X6STrUFfh7YM64kGhdYvzrOwOOOwDISaOkVrOw8CknK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\nAABJRU5ErkJggg==\n", 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\n", 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0r5py5lX07Du0q7u111BTWUbWKwd97/qnWifjcLpISknnqDOuICM7r31dymuF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\nJsn8u6+hK3gUvmgEXySMLxwmOnQITjbLnHkDGVrjYbtFaJE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aoSM9Dyeb4+Jr96KlU/D4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JWRbo4VSdm1tfItOHaeYMlHd8n6y3rhHcHYmdCjGoSERwiXAUUjIDya9QC9jsb0RkFLl0JnD3x7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jkHWTKoio1hhLqXjkQRd863ceYUB3abxRNfuZKvfv/3KN064r34UmHV4r9x6/Dv029KMQ7f\nWNEzb7yMZSYJ1D+Cs3QFqaYr2fRKnfC+ssSOuGWIHvii9OalkRQ76v2mgGITfgixzgDOTH+PGhKA\nqYvPsuauxNRDpOL7kBUvqaggIaciBokING+B1p3gyRNBt7fASahJBIZ7lolAVnWI4Ll+PQycISoQ\neQPF3DpqYNOrn/66y6dC9Yp/ftzph8LhYvc92i74EUcKsRZC4clIigRIVkSVIR4Ur0+xwaDzxJzj\nQahZDTuG7OnhBY1oKKXskh1oapCa+ePJHyrIyo2bINYp2p3yB8/BNEKYeoh1Ty9l4DniGtUrxXUl\nSSR6n/R6D8bk24SBXlapmIuvSJwjSWI9bE6YevszBMID0JJ/AuDZqvuOeH3isQgfKBV0NnTgysli\nZKXF2o+ShPbXM3xyP5raJRrXb8bXrwxZUUTCIB/4DnP4/ch2wUGINDSKaoRuoMdj+Er64s7LQU/p\nyIqCzSbkXE3TIt4ZSLcMpZWdZIlkMESsRRCzVZdTVCIAV2E+ZiKJbNcwE6L6YCTFHLsTDRAtSHpM\nfD4tU7g2K3Y78c5ObC4XeiyOv385nbt2i2s4nCiajVB9A+H6ekzdwJ7hIxWNklFWirdvX1Snk0hT\nk+BDNDeDJJMMBckbNZJwQyOWYeDMyTlEKhXgazNKDmvtX9koEqHZk/yf8exefJHwq+9dROnAUT94\nZ94Tvz2R1+0zdKz1zRePfcLwX8NPbMIgSdIw4GkgC7Gf0wpcb1nWlsM5/6hbkhLxyNVur/8LlSwA\nDJswneunl7FxWR3n55fhqfyAl1cWnOxp/cciu6AvZsrCnulneb2d0oIslhj3cqXjh1gJO5ZjIjNs\nTewv8PPrbcMJVNcQ7wzwvZZCbF43lmkx6wiKRclEnOpt6/jhLaOp1/Npl21olsmKeRvIKyoDxA7Z\nGb/axYvP13HlMI1XdsJlg8bw4nKIRYI07FvEvaEBLP7JMl69zmBR10yaEwpPvvQ4O1QXdcv2nzD3\n6V4cO9w88PuMnf27nuqCor5H9ao/4skHf/ENrP7LqfQ/A0699dsYqQ7ef/AZqpcfOH/b/EPHE0F6\ngGEXQeWMPCxTKC5hgCSJFoj9awL0Hb8TWfWguSox9TCyrR09bhBpE1WE1h1wwZ8X8t6vz0WPQaA2\nRioOGYWQP0i0QhlJqDwLJt04hXhoHan0TnNnDfQdK7gCG14UO+UHQ7GJnf1UTCg3vXnXgd9ZJgw6\nV+y0162DAdNh11KOCJmlIoGJB0WVRNHE+pSfJuZeMAxsDnEdgJKJTjx5MSaFK1iTUQMIL4o8/3oC\n4f44fFC9DEZcfh75g0Ur0qbXnyG7vIHd7yyl8uyLhPpREKqXH6jCmLpI5v4VCodD02bxc7hFnLv+\nOTjvPtj2JmCJpEY3HKQMN0ZgFdsX7IGKI08YHE43T5w1n2XBs/jrUmhuF4G3PcNHIiWUkSRZJtnV\nhSMrC3dRAalwpKcNKRWNQjRKvL0D2SZUimRVwe7zYnO7ibS0YXO7MWUdPQH+TAftjUEyCzPpahOJ\nq2WZmHGdWGs7SDI2jwtJknsqFzN8TWh2B/M7nMguJ4l0q5CnqBA9EccyLSxDR/MK9SVJVelOabp5\nEqZhYKRSdFXvRZJkVKeDUF09dn8GmteDzeMh1taOKz+/h1fQvnUbiUAXALkjhpHZv5yufbUo9jI0\nj4ecIYPRfD4AIo2NXDrOic+f87nW/tx+del7vQnDlwlDxk6jaf+ua4ETmjB0G7f9G+Bh4A7Lst4B\nkCRpGvAIcFgW6EedMHR1tFw/eMzUox3mmMPt9bNjTQCH68AOxK3nlzL2tAu55Gt3kZ3f23x+IqFp\nDsL7GrjokkJmudupl12s3S7hH/ILZrj/jB5djiSNYoTnA/pVlvK1DzNJdHURbmhE87qJNLdgFfY7\n7EqRaZrMHv9dHFnXkTgnH0WpRg86iFiZ3PNwI5DH1ekE5Pxrv3PIuZcdZA/jdPuoGDqeCuC3z/Vh\n10erue/H9dy2sgzXWR7OkPbQOTmfG/+wD4DrpoqWijmTfsbqRx9n97Cao1y5XhwPWJZFrBOW/+EO\nTr31TiRZo3rFXagOQR4+/Xunc+qtHuye4YRaXqXq8QUcrsdTqAVad7YcQh5WbDFUDfqMUZBkDVMP\n9/gLgCAAm4aQSM0bBO/9+lwqpon2JMsQwTOIQNw0DvAMIm0rUewHklV/cTpIT4qk4OPIHyqu5cyE\n7QtEm1BhWkvAVwQNmyDUBDN+8ggv3nRkrcJ90/tl3clCNwbOEMG7kQJnCuzF4r43TxCybQ6RDDFR\nPP/bT1zBA85r6HPGGvKnrKHflKdRXKehhxejJxvxF0OkfSn9poyk6rF5FAznkITONMTxcSL4x2Gm\nW85SMdi/VihLlZ0qkoUxsycgSekqUWoLmfYtdAFbK47+7/rJxWPoNwEuPcPEJZtoo6BC1/jrTtKy\nqAkcWVkEa2qRVQVZ00h0iUBakmRMw0BxCF8YzedFddhxZGVhWaZo0dFsGIaJEU/QsL0Wf1kJXW1h\n3JkeYkHx4ZAUhfLwYkZPPg+Hs9tPQgU+tgEiSUiKQrSpCUdWFnqnOF9PJJBkGX//Crr21QjehCQL\nNSUgEQigOsVYqtOBze0io18/El0BZJuNgnFjaNm4iUQggLdvsWhvsmk4sjLpqt7H5WMczNsBit2O\nMzut6mWZVHS+xdBxZ2AfemQblb3f/19ODB49hQ3vLxhxsufxJYa7O1kAsCzrXUmSDlvm4qhZpB0t\ndVMGjz7taIc5rljQUsMzi33MvPa7PPC3uby5vbeF5ERj8auPYJkWyz+Ued+WRb1iZ+JQixwjxZ6u\nrxPhq/hcNRiGA4fWxl8vNRh51nASwaAwCbLb6Wpv/uwLpfHhyvlskuciW7W47C2EoqU0Whn832up\ntMrGJ5st/Stk5RYxYbroYX75sqe4zHU/fvcu+maso2jcCOyZfv745Gpi0RCrH338c4/fixMHSZL4\n0fwLMHV4/8Ffs2vpfZROupN9qwRBNhndiZHqoGnbLax5Uuic7q86vLFrVsGK+2HJLw4ci34G+1bD\nvvcMArUtRNoCPTyIQI2BrxD6jBqJzSFag5IR4bXQrezjzDwwfna5UPlx5/hRHX4sM4msiF387kPz\nCG+Hj5u4KaowhBs8U2HklXnkDIAJN5xHyQQxri44tCy//yaueOh3lE3+/Gtrc5KWohX3ZVm0EKXi\ngqxtGjDy8juJB6H/GVBxhoIz009mKagHxamzrr8TVyZkenewP1FOQP8WitTU44ORP2QCkTaIBzcy\n6DzoO3YKliXatSxLJCbdlYPDQfM2UO0i0dETMPKKCmyOUmTVS7hlKSv+eA/L77+HV3ceYdnlE7C3\nqoPWgISKRR8jrYe74lX0WAwjkWDkMAeaz4esaTj8fnIq+yGrNqweorPYQHHl5pDoChHv6BCqRimd\neDBMKhQm3imC8WhbB2YqRbitS5yfbj3y+DJxOD89ZjjLJXbjNa8Hxe7ASBOPzbQnApJMaH+dkH9N\nJFA0G6ZuYHO7kRSVeEcnjqxMVKcTI6ljczlxF+TjyMyka+8+HP4MMV4yJfgIPi8Ad3xrOk63j6vH\niE0/M5UkVFfHBQN1xkyZ2Suy8h+IsoGj6GhtUM+76rYhJ/K6/0ZOz9WSJP1EkqSy9PFfwGfUYA/g\nqCoM51/7ney6vdtdA4ZPPJphTgjsDhczZ3+X3/zkj3zzf37Iovv+xKkzrjrZ0/qPQWvxlTg1jUh7\nkPoWLzMzw3jkMJJs0Gn4sds62R4ezV7VwfZame8Pepe6pqnYnA6aP9yA5vHw/FKFW688vLayX93+\nCluYzdvBmyg0k3hNg/vecWLzQjIc4YqhR/bRlySJeavtrHk3wlU//Bb3/XkvY86s5KdTgjSdns9v\n/dNZHFRQ+m+nvaWOzFgERVVpa6zB7cv6XKXzXhxffPXO+7n+m9vYs1n4x7z3wK8pnwrZFRcRaX8b\nSdLS6kcbMVKH7pYfCerXi3agWEDcegsg3GJg9x0Irm1OEbBXzhBJg3zQl4qeFKZtzkwoHP5nmrd/\np4cf0V1lsOQkmttA0YR5mr8vrH/2wBjRDqFcZBoGdncL/SZDzQcL8OaJORgpIdNqGrB/7R3kVIA9\nXaQ9mO5mmaJ1R7WLORop0e6UjILmEnyFcLMYM5kUSY+igZUUSczmeb/G5kw/r8Ugp38ljZuq4CCF\np4ysfAA2vDiH4Ve8SEPb6QQiE3E6NuPOPptQ86sEGyCn/wSSkZ20bF+JmeZDmClRLTgcuHMPrdqA\nSDpszlIsK8medxdQPK4Y06jjbe1vHBunigNw7mqmAej2sB848lQ2bTUgFGHN6jZceTkgSUSbW4l3\ndGLqKZBk5LTyUSoSIR4IoDrtaWUlHSOZxEgmRaCebidSnU4sy8TSjTQp2kKSJYaM+dcbfprDydD9\n77DJN0W0K8Viwt/BpmGly26K3U4yHEZWBPnZNHRIe6J5ioowkjqSLBFrb8fmKk5LwCaxudwYqRSW\naeLMyeoxm/v6eeWHzOHM/iFWtnhRnU5eXhXixpl5x/It6MWXBIpqY+CIUwh1tX8TuO2EXfjfpyXp\nBuBnQDfLbUX6scPCUSUM0VDgGyUVQw9p+/kiQ5IkGnIu5BxtG/b/vo2qxxdQMeSEE9T/Y6En4jjz\ncliyLEjNQB/b1oVAUln47RcwrAJaFI25f4swcYKXULSU5867nVu8D9LSr4z2rdvJHNCf9ub9n8mX\nMQwd0/u/BJMK52S+wA0Lr2fcYFGaT0UiXDbwX57+mZAkiR9//1r6+N7hPsoAuPsdb/q3Ypdw3NR8\nMsxs/t+bCvOufw7d7MPPN06lf7nBe4/NZ8CwCUc3iV4cNRRFJSu3CLtnOKn4PsZcOyXdLnRAjcsy\nk4y4dSPrf3/0Nshd9eIoHC4C7uIxdrLKBqPYsunYt5JY50aMJCQiok3H5jgQxIaboatRkHLdOSPp\naniKLW8Y5A2MoWjQvC3GyMsHI6te8AnPh+Zte2jffegc2qvT7U+6SFoSYcF5SKSvY/dB81bBoeja\nPZPicRrrn40x5bbziAcF4UCQjGPIqpCE7W6x6lZ/inUaJIJQNMpPy44AzkzR8tPtgSClW6w0j5BC\nlSQ7RrKdyrNuQDpbY8+qA/NdEqmhPV5HefNPyMrMoSY0kgGebBLhzWjuSgafX0njpsepWSX4EaOu\ncvL6tz+hF+tTUDFN3KppYnMqRg8HRVa9yIqXobPupm3PfWyp3ESF23ckb/3ngiRJWIaBze3i9Gk5\nVNdL1O1uIxUOi0BfkkXwbwiysOp0EG1uEUF3bg7JcFj4HygKeiSKbNeEGZosoah2DBJIksQPLrB4\n783tKGqfz5xT6YDhRNa9wSZ1Qk+iYlgmkqKix2M4s7KQbTbi7e3Y/T4SgSCuvBwsy0R1OtJqSyqa\nx0O0pQXFLpIbWbORDIcxDYNQXf2BtqODsOwfT7E/83ziASGBZZkmD7++jZsvHnwcVr8XX3QMHDWF\n7euXz+IEJgwSoCpHryh6smFZVifw7SM9/6iKIuGutssrRx5BzfokInPgAFboA3nmLYlkIn6yp/Mf\ng0tH2tCjMTp37CJc38iaN9byk+uz8BQVMPH2QZx2Zz4RSUZPJIjG4a1UGe+Z9zP3gpf5+uwsVLsd\nV34uH2ij/+V1Usk4rzzyc1yOZs7JfIGa1lm01gdZ+G6MVERERcdCMWvx+hhzF4/k2gkZDAo1c65P\nHLOKo1xYIAKnctevmHf9c8xt+Trn/HIAH34Y4qFnOthZcA4vboyRjB9+YNOL4wPLstATDRjJdlR7\nITZnGZqrEs1VyfrnV6LmPUz9opGHuCcf9TVNsVsvyRpO/ym4sk7Hk5eHO9eJOwcaN8KORUIRydfH\n2dNm5M4RZmOuzNPx5l2KhNhNd/rFjrpqL0RWxOaNJGtYpkgAssshqwxy+sP59wmVJCQRHMsK7FpC\nT0tT2alOJn8LwjXXI8kaqlbE2Dl+YoFVPfKxkmRHkpX0a0n2JA2SrPH+gwaxgGilsnuG4U7Hf90q\nSc5MkSzUfSgSIm/eZVhWAs1dic1RiqJl89XTHz5kvbLzi/nzwp9it3UyJHchMetcZMWDZSZxZpxC\nVr8JGDo4M/1sfOnw/6b6jjtAjrYssR65A0W7l2LLZs3cebTufIaUfDo2ZzEt9fuO/s0/TPQfW4Kv\nrIQ1W+C7o0M4c7Jx5mT3GLgZiTjuogLR7pOdhd2fgSM7m3iHkH62dAPVYUdx2DFT+oE2pbYOJEWh\nou7vbFvTRVbeZycL3Rgy9nTOKwnjzM0FwOb1CP8GXe9RW5JtWpqc7UCPxVAdTpw52UiKSsPq1Zip\nJJZpYSQSJLoCGIkEsbY2fMV9RPtSoIs5kw9UYU3TZH/m+SIZysrsNVrrBYNGTaa2emvxBbO/1yt9\neZiQJOmNf3Uc7jhHVWForts7bNqsw65mfCHwrX0++AtMLF1F1uhP1mnuxbGH0+XlrOJ9LK7LJBUO\n4czN4X+e7eKuOTI500fz9C43i6okPPm5/GDwFjYnKygwkjRsnMPTGwLoiQQtH27EV1rCSy/ew/hp\nF9Nv0GhMw6CjtZ6aXZvY/uEKNlUtoWrbZmA1ifAm/rrvOiAkjIUsq8dc6GjQ2dZIIh4lt6DkEElV\ny7J49+9P4vb62b9nAE8O+jmVfWFKVowld29i+s9NPEWF/PA8k3uetPHs8gauOjUDRbXRWLsLze4k\np6AEze446jn24vDwhytWEtZ/i1t7Ix1kJ+nY9xA73ob8wSBHfsOgc77NkJleGjbex463hC/D5G9O\np2b1Ut5/8PCu484RwWhWmdjhtzlEUOrKFFr+/uKbiAfX484+G8V+N7IidrdNI4TNEcM0oHBYBb7C\nq1HtheiJRqbcfiey4mHJL+9h7B0bkWJ3sebJBdg9MPzS6ZipbTj94MwQLTeJMGheJ5VnxzCSgpyd\nDAupUsUGqkNBVrwoHhHlb3k1RuuuPZxxpx9Z9bDp1TpGXjEYWRVJiWUlsKwDrtiSZOeC379Iy0ez\niAeFO7ZlChKxadJijTsAACAASURBVIhESXND3vg78RX9GoB4cB3OjFPQEw2Y6mgMU8Mub/2n9cst\nLKUjlEuubwlNkXPo5/H2nG/3DEOSq6hZHTjExO7j6DdFmNxd+/R5rHtmAZYJY66dwrb5Kwk1QeXZ\nMOBMsLlEe9eed2DnIoAZDLkQbCfw77L+iR8SGXoLuYPKuXell669e7EMA1dBAZUD3eT6YeHLO5BV\nha491aJFSVFQNBUzmSSZ0tFjcVS3Cz0WI1Rbh7ekmCfnREnpMgvWHdl3ny8zF9I5mZlM4inuQ+fO\naDqJSSBrNmSbqCh4S4pp37qdaLNJ8/oNeIsF0Vh1OjDS/g6yzUb+mNE0rK7ClScSkXCwE49PkHZk\nWcZdWIBlWUQaGtE8Hux+P9eM8/7z5D4nLMuiaf9uNLuTrLw+6HoSm63X0O2LjvziCkzTkFKpxHRg\nyYm4piSBcnI4B8cKpwD7geeBD4AjSraOeAnOu/r2/m3N+239Bo767Cd/gbBvXA37xtX0GrqdBOQV\nlXF1+h99rL0DWVX5r19tZXnYxTkDk5QUWMQ6u9iRLKePmcAEHOXref26Z4g2N/dI9V3424dYkxzC\nE7/+Di9+GGVxYw67PGdgP/s+Jv3PRh7Y6aM1MArLcQ6bNkcwkkn0WIyyQTlcUHJ0Xg6b1yxlQbWL\nKnkkL22I8/zaUE+lKtDexOl3/ZCOsbcwYvYZXDE6ybxntxGSFWY+eBrzv/0HvnmZkzUBB8VDiskZ\nMZTXNls8/fsfkD9zBplnTeXRV7fxwPMfHu1S9+Iw8YePbscl/Q1J0kQLiuqlcRP4CkRrjt0zDFkV\nyUL1ctHbbvfA2qeX0rbr8K5RNlnIiNo9UDrJT2YJVM5Q8BTeTiK8mUQqE8s2ET3RQKDuEVStCFkR\nfyeqvZDCMX8jd8AUTCOEYssGKRvFlo2eaCQVr8HmgI1/GckHj4kgOBGCNXOXIivpHXRZOC2rdmjd\nGUNSRAuSaQjVpT6jweF3HuIXIUl2Iu2iGrDmiQBq/isMneU/pKLQDVFxEPfbtsxC0USSoMcDlJ3y\nO3Ir5+DJy8PmALs3j0DdI2ieYlSHH1n1orkqxesJvoTGBmTFy7XTdmN+wm6yrHjRkZDtI5BVL3bv\nMCRJw+mH0KdoIgw4S9x2JxPPXbeAHW/Bzrdh8X0rcWYKVaQRl1XgyCjGMpNkld3NmT8WbtUA2wfU\nUFRa+ckXOA4YOelsZJuKqkB5H4tgbR3hxmZUh51tG9tZsmA/514xEJvbhauggNxB5XiKi9C8PlSn\nE9VhFy7OpikEHiyTBy5IkUxlsGDdYcp9fQpm5nUCQmFJ0Wxk9q9Aj8bIHz8GNe2grNjtBHbtwde3\nL96+xeSOGIY7P08QoWUZR2YmGWVlFIwbgx6LUTB2NMlgEDOVYu7fqzE/trETrKnFNAwk9aiFHXtQ\nvW0dK4KlzNug88SiGuYuqvvsk3px0iFJEoNHTSHY2XpCd6sV5dgfJxAFwI+BYcD9wNlAm2VZyyzL\nWna4gxzxX1842PGN/kPH9ZpW9eJzQZZlrpzk46WqMF37alDtdt5cGGCBpiErJrMv9VIm1fNMezHr\ntkmUFgxh9XwLV56Qnwzs3sMCowxJUbCffq8g4Mkyit2OHk+Q6ArRVpxFJ27+8uGZGPF2UuEIsqYh\nL3sK+6nnHNX8s/P78uKVNv68x83/u6aNLdGRPPn7Fxgz5Xz82QV8UpdjCgnVdUD+xfpwJ9nVW2nL\nm8HsSX4eXmJQnG3y1yeasLldXDOtl9B3IiHZTwX9I0Ds+se7oOSKJswFBSTCm1n/7Dzh3JwjDM2w\ngHQby7QfCIMvMwU2l9ipB7GbburiqaoGsg28+RDK2knZqacjq17iyRwseSaKGcdlbyblqkwnAKWk\n4jUkwpvILbkPSzLwF9+EbjjE58uo7wnQV/7p8Z6kIC16g2mK68uqaFeKtAouhJGC/Wtg9xJw+EWv\nPoAUByMRo2jEI7z67Zs45Rvi8Ylf92MaIRGkN1+G038Kq/66ANMQycfoq4WT9Vs/reKMO/1YVgKb\nS/hPyGqCVDRGw0d34MgoJhVtwe7z90jJZve7i8X33YbDX4WRqGLU1RNIxfah2LIw5YEEo6XMPqOG\n55f163mf5q12cfN5QFUOzZP28mL7RXyv8m/IqpdYp5CDPRgXPr8Xj7MOl72ZXYsvP/D4r0F1iLlY\nVgLVXoSph3rmJckahmmj5JQXSUau4q3Qpo+LjB539K0YxgdbDRq3VBPqKuJ7907miScbqF/5Pq7c\nXFSXk7de2YllGFx6WSFvrfrkVh09FmfGObls2pPBPevgZ2M7j3puimpjkmsTq6OVdBu/mrqOJMto\nPh+WZZLsCmJzu4i2tGDqBqrTgSs/j3h7O3osjis/j1BNLe1bd6A6nThzc0CSadm4EWd2Ng+/to1b\nLh8GwCXlOk1anLd2C1WkY1FdAGiuq8Yx5DT2v7sCV+4/cyd68cXFwFGTWfvu6zNO1PUkSfCcvqyw\nLMsAFgILJWEKdA3wriRJP7Ms68+HO84RJwyRro6ZA4adcqSn9+I/GC5PBl+dngFAa2MtSxo7cGRn\no0eiPPpwIzWz+rFkwX5+dEM+v389xVVfH8Jrf6sjXN+At6QvmBYdO3aix2I4sjJR0sZFlmXiKy2l\nYXst90T7kgyGxBeaLGHqKUYdZbIAUFgygOcXd8GBOIaRp4j/W5IkIW1t4VwfdK6GTuCaCRk9z3tm\n9T1AOy5PBpUjTqES0cpx448epG1VC5cPVmDwUTKye/G50N5UQ8pwsy/0LRKSzOjsV6ickUd21nNk\nzJiO3TMM1TEPIwWDr15BfP+FbHkj0HN+2y6Y8ZNfsvyPd2H3pEnKlmh/cecWI0l2TCOUDqI96K2F\n2PMuxbKEhIyqRogncghWX4KqFRFs3EPb7ip8heAY1cyHL+QT74IxNy1EU7tQ5BSmKaoAeqKBQefC\nzsWAlK4xS938CEEwjrSJSgIckGPtViyS0xqm1ctj2H2wY9FNTPvFeqTOrwEgyXYUW7bgJ0gaeqKR\n8V8dydq5GzFTsGbuHqIde1BUSAQDuLIrMFLtgusgezC1OmzOYlKxOuzeClR7IVVPrAQLJOU2JFn4\nTDj9IlFTbNkko7uwy3YMYwKKEicZjx1iinj/K2M5yw6e5NcZmfM6lqX08DZiB94Wzr0XPM46nr94\nKre8PZcb5r9Gx+5rcXjH4s2/FFnNI5bMwWVvJpnyYSXe75lDV6ScpO4j07Od+Z0f4sk4/kTnj6Ob\nZ2UZBtk5Dt6uEi7LBRPGkQqJqqmvrJTgvhoGeFK4ptt4aV4M1e3CiMeJd3TizM3Bsiyuym7kqmyx\nHi8u/2wn5MNB34phrN4kPsPdSYNlGKLlU5aweYRMq2K348z1Eu8IoMfiJIIh8kYLAQFfv1Iijc24\n8vOINrfgLSkmo18pHdt3Em1tZdMHSxg+8UwACoor+Moxtk6IhDoJ1tSiR6PYPGWE6+vZsfF9Bo48\nLA+rXpxEDBg2kVcfvS/ngtnfk/7x7O+//GzkT4EkSeciKgIK8KhlWb/8hOdMA/4A2BBVg9M/ZSw7\nMBORLJQBfwRe+zzzOeKEobm+esDZl99ypKf3ohcA5BaWcFFGiL/vDpKKRNATCZYurMeekcEf3tDp\n2LqNf8T78fj1Xq78X0gGQ2g+L0Yigbe4mEhTI6lYnIyyUoxEAsswMJNJoq1t2NwuHO5Mvnqu6Idt\n+aDtmMzZ5cnA1dqc3v0Moiif/mckKwq1VR1c+C/UYGX5y90ceTKRu6CU1vOOzEQrHovw+5fnMj9m\nZxgRyp3bQXKSVXqHUOFxVWJzlDHm628Si+dhWSn8FU8xcIbo0W/aIqoGlplg8PkK9etFZJ5VKnwH\n7L5G4eacDGFzlPEC6xmywInD9zLD5rxLvOHrpOL7BNnaUYaR+TJe61xc2e1orkqcmWuhvyA2q8YK\nUIVfkax4kWwaa55ciiSJ3a+DO1KLx0DjljS52jzQjhQPwo63xWMA3vwYoWbBrwg1QukkWHf/GMbO\nGYxqL+xJGGTFg2mE0dyVdNY8jqTQIzPozRM/a14nqfg+LNNAsfmRZI1IG9StrcM0QE/sQVb3IEng\nLYJgA4y5tgLTCKVffymqvRDLKsUyk/TNW4xpanzzok4efetAAOd0eXm9cQW3ZUBt0EZC91Gz/B4m\n/+BN6t6byZJfCFL3wv8GEIaiiVQmhqlRMPghQi2vEml/G1vWbdiUMIlUJqaloMszSSXcuFMvoSjF\neJx1PL5oEp4D+f4JR2VwKVuUiagKuBwW0ZYWYc6Wk40ejRHcV0NGvzICssloM8rIi2WqEi6enytK\nLaauk+gMMOdBeOZW9zFLFkAkNKaewjIMZJtKRr8y9GgMT98+hGr3A6BHYziys3o8bxTNhiPTT8e2\nnZx6/kCq692EalMY8TieokICu/egeb0omo14Zyer7SXkN+wjr6jsmM37YPgyc2m12VDsGg5/BqrT\nwVvrahh49IJovTjOyM4vxmZ3kExEzwUWHO/rnQynZ0mSFOAviPahOmCNJElvWJa19aDn+IEHgHMt\ny6qVJOkT2xMkSXoK0Y40H/iZZVmfw6HmAI4oUjnv6tvLO1oa1JL+w47k9F704hA4XV6uHCF6X2VF\nIRkKE9xXQ6ytHbvfT7SljaQk4+lTxFXXV1A0oIC+Z5zGV24bTt9ppzP7JxcRbWklFYkSaWwEINnV\nRbS5hc4duyk2EhQbx1Dmphf/Fti/ezNjXL/hUs9D1CkOnPY25nVeQkv4coLWD4nJX2d728WYpg23\nsxHDdBCOiW3OklP/hqzAkItexOYsI9xikNUPBs6oINQiJFDNlEHUvZjaD2JsX7iNK1KlDJ7pZMCZ\nFcTqruzhJJh6GCPVjlNrw1f6AK+7Ogg3b8SuBpHTUqSaq1JUF/QW9ERDWrUo/UI+Rl9r3U2Pn0F3\nQtFzyEKtSFYg3CpuvfmilapuPYy7fiTrn9vWkyh0Ix5cRyywCk/edCA9hiqqFaoGqlYkqjH2PPR4\nAD3RSE7/CYy8cqTwbJDENYpGQbhFkL43vLgHxZZNq3Mxkfa3Ue1FGEmRLIVb/0FT53gaP7rmn963\n3MISvnLr61wmXSrei2kLAeg/7Rn6T4ehs0SF5/KHKpg9710kDBQ5SUp3C66K4sGhNpAyPGhqEMNw\nIEkGPrfwL3rwVS9PLzn5323dO927Vu8gxw/nfmUiqUiU/HwHt1zpZfCEMpLBEDbLIpMIVQkX738k\n891by/APqCDZ1cVjN+fx2M15vLnm+GxKWKaFpRs9VQY9EsVXVkr56H4MPm0wRjyBrKr4+/cj3tHJ\n2NPK8PfvR2mBRTJp4u9fTrS5hUhTE4rd3uNeXThhHLH2duatS7Fu+T+Oy9zXrXgTWVVQXS4SwSDB\nfUfv3t2LE4fK4RMJdXXMPhHXOknGbROA3ZZlVVuiJP0CcNHHnnMt8KplWbUAlmW1fMpYc4ABwHeA\n9yVJCqaPkCRJwcNdhyP6LxIJBW7oN2iU1ctf6MWxxOxTsrhuah7XThTbeno0hq+shIx+pdz+cgp/\nWQnV9RKGIb6o3ng7xtDBDt5bFWLIxTNIhsOkolGCtfsJ1TdiJJKkohG+/avtALzx1G/48L0FvPnc\n/dz/o6t54le389gvv8XmNcfOufV44pWd4ujFAXy8ujC2o5SxHaWHda5hpOhKXUkwPpmUJLElMIWz\njK/SZWSQ5XgKWU7R1/sRTq0d3XCIfnhHI/UbQDdFm8zqB6+irvUMik5ZRPNW2Pf+HorHQvnUPAJ1\nsFHN6An6E6EWjESsR1UoHmjBMpMkggGx065GqFs1i+vyV7BvtZhjbZVIAN578CukYtuQ1TywDWXj\nKw8JQzX5QIXBskQQn0rz+iUOqj7I4nbMtSPx5Iufs8pE4N+yQ7QtGSlY/+xGulWHJfkAmVmSNTR3\nJb6Caw5JQJwZgjMBoq3I7hmGM3Mkqr2QZGQnHz6/sSdRMZLQsFEYtzmzQP9GiK3eVXRJKrsz1qKb\nmTgyppCM7kS1FxLXfRQO/zP1e7f/03s3aNRkqlcsSFd+ZKLxQvavmQPA5tfFWjh8Y3BobVgo7F06\nSyQI/muRZDtI4v3btWQO6x4SbS+PL5rE3BW39RjGnWw4XB5km/iOfW9ZK2f0TfDHWwpxOSwCusyw\nCovKwV4ee9NAkgyuzvoAn9viL0+3MWawxBkXHGuLuUMhqzbCdfVEW9uINB4gkBjJJJ1B2PnBHlLR\nGJKqYHOIDaH1K2rRY3H+/lYIv08m1tYOkoweSwjJVMskFQ5jJJI4/Bno0Qgf1PfhrZceOObzL//e\nP8ioKCdzQH8s08JfUYHd7z/m1+nF8UH/YRMJd7WdeUIuJh030nOOJElrDzpuPuiqfRDKRt2oSz92\nMCqBTEmS3pUkaZ0kSdd/0vQty5Ity/KmD99Bh9eyrMPuuZQs6/O3f4077YIP8vv2n3DhnDs+97m9\n6MXhwjQMXlgXxjItvMVFmLrOsJGZ9O9qJhYJUp07gKZ2iUh7ENmukegMEG/vIFhbi2zTcGRlEmkU\nO1cZZSV07atl7cPtnP2bidx6Yx9+eff7ZJSWkAyF8Ox8lPOv/e4XXtI0e1Iu7atbT/Y0vrAY21HK\nuqzP3im0LIsHfvo13lr4EB5nHbrhZPOTp5JdDsXT3kVR4uztGke/jLWYpg2H1kbn3u+z4cUDSird\nwbIsi532WEAEww2zIqhYxCSZizxv8dELlzDi6tdY/9QlJCMw6ca7kbTRJFKZbHzyTCqmOTH1GLVV\nkFEo5E6NpAjiu/0RUjER0E+9/RmW/2EORgrsXmE2ZnNA6Skj2fjyRkxD5AcW4txTb7kT6PZlSGKZ\nCfREIy07Xmbf+6I9yXljAAPRJJtIly2muH7fkzAsD95I6gEfipomVncnJ4ogdpNOHnr8Jbp5FOl5\n2Bxi/s5M6LwqTIeuMEyKYQItikaBkURHwm0Z9MtY21MNeDN+Klf6X6EtOJw/zN1P6YDhPWu/6YMl\n/OYH2/jJRz/np2PfRZVjaLYgi+79ipifKaoZlee/Qaj2e/hKfoNmC5LS3eimE0VKEm74KW27NvLr\nxX9i/Omzjs0H8Bhj1+YqdvU5n649e7FMk2FTK9E0uG/CEi78/QB+e0M2BhIrulzcWLycp5unMsd1\nPSvlxwGoreo4bnNrqtvDkrpsYQoHXD1akJJXLnyezlE3k+gM4C4qpGPrdq782iDeWSsTamjCmZMN\nksRpYxXeXtyO5vNiGSaWZSJJMpIiE2lqxpGVRcP7qzFTqZ7EqZsIfSzw9IoWLNMio7yMwJ5q4h2d\nfOPSIcds/F4cXzTW7uQv99xgtjXVHvdmofLRY637lr53zMe9Nsu5zrKsT3QPliTpckSr0Y3p+9cB\nEy3Luu2g5/wZGAecCTiBVcBMy7KOy9biEVUYAu1Nw/oN/NcGWr3oxdFCVhSunZDB7El+ZhVHubgs\nSf8uoZ3odPsYGm2m7cmbKavwsn/pu6QiUbKGDCJr0ECyBlZiJBI4s7PJHzua086vILN/BZal8ORX\n7Ty/WCF70EBMPUUqEqXJewGP/333Z8yoF19U9N9USv9Nh5csmKbJsn88xfJ37sXWdTGEH+LDB0+l\n9BSRAGx8fBqWJRN7KwfLknFobURbn2TDi3VCLSMt1R7rEhKmsS6wX96BfnOIpnSyUGAkMZFI6j5G\nXP0aG569BCMJU257nlhgFdGWB1BT8xj1tUVIBevRXBVYBvhLFfIGiiTBlub6pmLiZyMJ7/52DqYO\nrmxIXhkkFYNUHHYu3sjpdzzPGXc+j3VjkNhNYXZfHWN54r9RnOOEDKljInbvBNzZMyifMpdp3/8z\np33nZ5RYQUwkMs0Uqxs1Jjv/D8sSyUW0cxkT5e+iajD5W9/GNGHkLevBgjG3rsA0IG/QgbWVOJBM\ndBOxu5OK8V+5mwIjySApjo6EiUSOkcIETAnygqOI1n2LaNP/oChx7JbJ0o5ZbE+Vcvc3VGZPuLun\n9SXQ0UxHze+4fECM/V1jsakRLEth2o9ew5EBmgsGnv8auuEgu/xnVC+9hM7QIHYvupzV989kz9uX\n0LxlIzkDRjJ26gXH8JN4bDFg2ATmXrQe1enETKXYs62d3dUJHq+fzuzr+1Lm2kqFawvV9bAwNoUL\n3U3stx6gtqrjuCYLIIjIsyf5uXq0qydZEHOeiGK3gyQTrmvAMk2G+FJ07BItX8lQmGhTM++uiuMr\nzBHu1YCZ0oV0qqJgz8gg2dWFv7ysx/1Z0WwcyQbnp6FvYD6a140kSSSDQTyFBTy76viuWS+OHfKL\n+xMNB+Tzrr5t0Gc/++ggYSEfh+MzUA/0Peh+cfqxg1EHvGVZVsSyrDZgOXDcWDifO2G4YPZ3bfX7\ndrjKvmT+C73498TlN/0EgOLTp6J5RM91IhBk7tcssgYNpGTqBBKBACsX1fLwV/1saZ/BNjmTWGcX\nia4uLNP6/+ydd5xU1fn/3+feudN3tlcWdlk60gRBQEEQQRR7CRqxYG8x1Rhj8jWmGBOjMTF2xRJ7\nR7FEEUVUeu+dXWDZPr3ddn5/3HVNfjEGdLFl36/XvGZ39s69Z+7O3DnPeZ7n80Fxa84X3DeAN5eo\nLFU+o4O6i//K9vVLeeae/+Psx3qzMHcptpWgfIjjoty4AQbPXIDLfJsBx89ApJ9GEbbjQqzB2Csu\ndCbA7YyaeTSjLzmZvpZTSjs15y0UoEXROCkwD0Ux+OD2U8nEnF6BrBmidtE8PvS+wofGb1n7xBR2\nzxlAy7btqG5Ihy2aNjv1/prXCRzgE1dmn9O/T7oNmBUir7ujhGQ5gjU82ngKdbqGjaDaZxJRVCzb\nR2LfnY6Mq1RJZPqwrek4pK2jugvZquRhC0GT4mZsWZa5mesRwk0mvgIh3Lg85e2r9jpH/eAmVt0z\nHGnD0r+Ow+WB/lNucmRkLRhwAgQKnSDh6OseZ9L1jzLqwhmM/8lL7F72O0wh8LQ3WPja77u31jBA\nPx2XpwJf3hhySk5Dk2uZIr7H4fZFFNkG216bSqBwMhcduxjLMhlzzBkECqdwWMETBES6o7fErcUY\n973HGfqdoaSypUS3TkFKld7HPEN49eHsWOCcpye2z+F9dvH8hle+9qIDf3+rGEVzoWganvw8elR6\n2NMkmKI1YFleVEXnuEEGxwfeRXMlKWjr06kT6wOlpJsjIScti4KaSs69fCDb0hrDxvekz+BS3DlB\nRhxRgZQ22YxJuF0VKdXYRKqhgUxLG+5QDno8geLS8JcWo3o8aH4/e3b8u6nf52XslLNAKKSaW8it\n6Um6zZGc3Ve39Ss9f13sH4qiUN13qEwnYmd9Kcc7CLf/wlKgjxCipxDCDZwF/P+uzLOBI4UQLiGE\nHzgc2PgFXuZncsAqSXo2c3xOXmGHE2MXXXyVqC6NmqaN1PsHMGign5uGv8G0PUNYoFQw4jBBVpdk\nkhVoXg87XVkOTYxjpW8Rlq4jFIHidqPZNumWVmr4AEdIoItvGtsG73/DYp/Bh3PKBdcxc3oO29tc\nZAtf4PDhLVQWv0s6shAr9VcsVw7SziIUN2bGEZQYe/k1KK4cRl14Ms712zF2yybWoXoKybNMVkQn\nYCvtXwapV1l4771IG/Iqodfxb+F11SJUiAsVHcGYGW+y7qmp+PMdZaVEk+OG/M8lSWbmE38HMw15\n3Z3gxh2Afsc9w8DjYyRb3+L1yIkUeyxsBMfmvMPie06iMAtNR0PpkJeAMJat4VMX0atoK0Ip5KOW\nk0krCpqUuNtXvDQpO4IFKR2jtpEXnIzLU046uogjr7oW24yz9LF7GX3xDe3ZCGesRb1uoKSvY+yW\njS/BExyML38attSpWwy5AyRZFKdkq/0rUyhuMrEVKK4gnuAg0tGF/GbbM2zZZfHsKTeTk0wTPbKF\nWMO5BAonc+mxe3nw7dM4/fJy3n45h9zADtJ6EZbt5j19KIPMJL7AEeSqO6hbAhtfOxvLgOoxsP2w\n9Xj9QTpPL+jg4/b6nAlzIEB0+06uOraKtzdrGJYfmS1FCJtR2iY+io/jMO9qAn3uo3HBDsoqD24P\nw39CCEHmxR8hjrie5k07YFQ1xX6b55Y0kmkL48nLY3GtjhbwY6ab8OTlYhsm3oJ8stEYroAfIQSe\nvFyKqsvYt24b3rxcFJeLd2oVLuikl+X2eDm+upkFVl8Se+sxkkl8Bfm8MD8CLOPIXm0MGT35ax9Q\n/i9T1XeYaNm3azLwq4N5HCFB/ZKDSCmlKYS4GvgHTsXoLCnleiHE5e1/v1dKuVEI8SawBkfq4sHP\nq4C0PxzwJyGViE6t6jOkK/zu4mtDMLeACa7tHb+/ftXjPDdXIT8HsobjSFqUL4koLqy8xxgo0rSu\n34AeTwKQCYdx5wSZcOIFX9Er2H+aW02aW7+YU2sXcPSpFwHwyvO7eOiZGJorSTJTjpYzsV3tpxxP\ncBBuf19HXtVXjearxszuw+Uux+VxbsLdH8WVg6oVEpA2Q13XM0n5CUf7HLnsQ69cCgKaNoHe/Ave\nueUSGtZB2SM+SmwDK3oPg7/7GtF9TvbA0qF1xydKRqmw4y6tJ50sg55yXJon/uRRCmtAShXLaGW3\nvBsbQVYo+KTN6sg4YjMSbHkL9q2FbPgRwNn+723fR8ossYanOUQ/jSmBvzExeBcBaaELhRLbSVd8\nLKsarX8URXVcsDOx5ShqEM1XzYhzZpBonoOlt35iHifcpKMLUbVC3IG+IHzYUkFKFdXjfKN9nIq3\nBaTbeyZUrZBQ2dm8wd9YpD7OZaaXF868jxPuu4Rr5pVQ4/4FnuAgdNmPrD2Qiye/yMiJp5CJLacu\nMYiYXkJLqjcn5txHoW8nre/3ZNucSaT+qcLkrcRmvP5PlJ++SRzh3oKUNorm4tZHmzm3T5K0UMgN\n7EBKhYyRzyjfCkwrwJ6WCVw/86strRk54WT8JUUALFipcNesBmzDMXfTYzGCFeVU9Ckj2K0CX3ER\n6bY2Mm1hN3s4owAAIABJREFU3MEgmZZWItu2k41Eadq6B6GqHRmHf1Zk6gw8vgCbb51CTo/uVE0+\nGqGqVE0+muIhg1hjDOOhOftp597FV0JVnyEkom2HfNXjOFhIKV+XUvaVUvaSUv6u/bF7pZT3/tM2\nt0opB0opB0kp7/i0/XyshvQpt4OrkpROxkZ1qx4g/vuWXXTx5eH1B+nZ1sgjc4dz35vTOx7fuLye\n70xRqOkGE9RNrDN78us3VITqwluYj22YpJqaSTU1f+0bngGOz2/h+PzO8ZP4X0bTPPzt8TCq283V\n3wkSMYrI6EUkMxXYrkNRPEOQUkfVCknrRSiuIFl7ICJwOpqvGk9wMBtf/yvz//TJe61f4HaUwPF4\nQyMw0rUsvP9efPZDCOEYpq18agljr7gQIeDQs49jqLgat78vpF6lZatTDuUNORPvtl2O0ZrruxHC\n0xOMuexyhALjvncTySZ45w/ns2Vkkjdix/Fm8mqSwqkD725mGcsVAJRZOoc8FaFtJ8z56Wzmx44h\nG36EswPXkWh+jW3qE2zWXiAVnk86uhAbQa5tkkVxAgQ1iKI6q/5CcRNvfJGcktMQigcjvQtPcBA5\nJafh8pQz6sKTGf/9W8jEVwBO+RI4AQqAEX+drCMO1fGl45KSgLTYlb8ZgLXp68lagj26i3Nf/YhY\n5ghev/Jpzp5ik3WdRyo8H1Kv4nO3kLUHcuOV0Fb7V7JCwS1tXNtLiDU8jb73E4PGd32vsX1oLbsO\nq/1GfL7/E0VlPcCW2IaJ4tJwSxtdKPxi6Whi6R5oriSpbCkCi6jiYkN44kEby3y9jPn6Z5dFdu91\nCC2PzkTRXNQu28RPZ5Zw3cXlzh+FQrKhgRsOi1JS4iG+ey/5vXuhaC6MVNLpaRAK0pakmpvRY3H0\nWByXz4twqcSjrZ32WpKxMNWXPk/dO++x9cXZmOkMVlbHV1iIlc3i8vq6ypO+xnTrOYDG+l1firPi\nV1CS1Gl8ijrSl6OS1G/I6Pgxp10W/NiBsYsuvq5IKanftZn6ui009j+X0nIf+TmSQb0l9966Ek8o\nhLRtpO18Bs4Z3bmSerZtE4+0EMov7nBu7eLrw8u73GTCEUJV3Tn3eIUC2yTXNqnU6hHC4sfv9+fW\nI3eQ1fPxelrIC2yl9oNT0bxOSZAnAL0m3OD0AmiFmNl6hOLpMDpTtUJUdyXv/mkG2swIhySPwl1y\nO4YZJOCtZ8Ftp2JboLpg+FUfse6RsRhpKB/S3ktx0VLW633I+zCPPhOvwZMzivrVM9i10Gk0tnTH\naVpPg23A6EvOREqdXWIW2fam4sMKnqBl+6+py99EP+k4OBvpXWzzv4eCxEbQOzUBM7uPuvxNlJGg\ngSDxRws44sobMNK1zso+w1CNd4g3vkhhz59hW3Eso5Vswsl+S1tHKG58uWNIRxd2HEfzVbPs0dlY\nJiCh90WNtCkaJqIj01Dl3k1Q3sMN6+5g4+pWUo1N/OGaatoUjfc2ufjViPc6XK7TkXlIWydQOJlU\n1pE/3fn2VNJh6DVhVMf/9rl1z32J76Qvh8du/xH+427FTKd55OJCvJ4WhLBwKRk0V4J56dGMYg+b\nbWcyv3lp5L/s8fPxTtrZ/yRfw2dut3fnJj5K9UZaFiMn9OCj1zYSe+sn5B735w5lpZevaWBZeji3\nPB5Gj8UJVfcg3dKGbRod+7F1vSN4UDUNyzC46LiaTns9816eRWLUNez94CMAzj66hPczNTSvXYe0\nJdX6PHJyCxk+bhqa9s3odftfwbZtfnTmII4+eWb160/dedCMNHoPGy5vn7eg0/d7cmHwP6okdSZC\niJCUMiaEKPi0v0sp9yslecBBTsOenYFuPQ96U3oXXXxhhBB069mfkUedRM3eV2kJ21zUO87cxQou\njwcjmULRNGxDxzb0Tj22bds8fse1JAcOpnR0Maah887LD2EYXQZyXxfMTJaqYTUIVeWxOSYvr3Oz\nIOrnI7snc1J9mXiYzUuxap5ozuORfb3BWIY3BNVjHqXk6G30OfYZNG81qs+53rs8FY5bsWsIeMah\np7aQjsyj8IJWXtrkdQzKMhWEU05T6Pjv34SqwVE/uh019QcOPXsGoy6cwa7D4lR9txGjfjJHFjzH\nISc+5UiiShVv7gDmjc2QM3QzRb17UVgD3Q9z/Bc0XzW2GaeHcSYakkGuHxPb9zR1+ZuwEXiCg1C1\nQqStY72UT5406Z2agNvfl5K+tzJAuQZ/6kSGhe5n9MWXY6Rr0UKnO74IStoxPAsNRyhup0ch8Ump\n7Md+DanwfDKx5ejJLWzzv8d65RE8MyOUXtxK8NIwWaFgtjvNdW+twUawU+9Bi/5Lpg3QsU0Tf2kJ\nj6zy8cQCDY8brOg9pLOl7GmeiAicjtvfB2nraGqCDbFPgoSbn76WZ1Y/vV/Bwu7t6//N32FUoopT\nx0Y4vf/UL/bGOkgcdeJMwtt2oLT7H8X0EvICW0lmynG7Yhyb8w6m5SMgLcYXPHvQxlGcJynO++8L\njS7NjbQsVK+HVAZ+/IO+HHP65UjLcUQXqsoJt+Ty1jY30paobjexXXXYuo4QCoqqgi2xdBN3KAeh\nKPjLSjn+kM4tyZx48kzKK4OUHTYcgLyiMk6qTGFls9iGzpbMYXywIZe/3vdBpx63iy+OoihUVPWV\nmVTyoEqdfWxl803NMABPtt8vB5a13y//p9/3iwMa87HfubKnnkmJ/OKKA3laF1185QwcPh6AR3bm\nsHf9Tp77sR93ToBMOEw2Fu/UYzXvq+WOn03njdlXU9NNcoS6jTef+RutNTNYNv9VzE4OTrr4fAxn\nJdG4JL57D4qmsXltC+E4zF7k4uW5Bo89uJ03P7DYuFOQysDPVvySPyUy7GmeSG5gBy/FTkQS5K3o\nNKSdRXEFmRe7BMMKYCdfx+3vyyrrdmJC5eYhP6Xa/0dKcj/g4d0hTn/8KFYmruGIK68lE1vBZvEw\nthVnvX0nk0MP0KN4HuuK60iF55ONzUfLmYhpeQkUTuZC6WX9/f0w9Xq6T3yHuiUwYJrTy5BbcT7L\n/z6P1lmFbJk7C81XTWxWAQqSZOvbLLxvFvXBD9CTsOvBEtz+vgSKTibZ+na7YVoFRnpXRw+HnX4X\nzVuF5kqip5x67njTiyRb3+44j0K4O5rAheLG5akgv8dVAAzQT2d0/uMkhYJLSuLiE8l0rcLZxyHK\n97jiVS+PL/agut24/D62rdxNIpZl+dIwa5VH8bpbMKSGy3K+2/asvIRwoj/lIsrczFpWFNXSZ9Ao\nZ5L5H7Btmy1rF/HsfTfx66vauPLsf219XhKs5aWP8nhh05ud8O7qfKr6DKagXx9sy2Lmw072oC1+\nCBWFH7I5Mh7LdpORXkpsnfvfnHzQxmHazu2/ESooZsnNhyNUlQHVkvq4Qp9BozhnTAHThzqawbZp\nsnjudh45zySvporcmmrMTAZpWdiWBYrA5fPQo38ZBf36YiRS6JlMp76eZ9dkGJatZYx7M3k1PXlq\nWbzDXdpXWIgnL5f8Pk7JVDaT6tRjd/HF6VbdT6STsSO+6nF8nZFSntB+31NKWdN+//Ftv9N1BxQw\nGHpmYmlljewqr+jim8jUUCNVZZJfXOIEvIrbTXJfA7ahc9qwz59qTqfirF70NnfdeD4P33oNl58R\nZOXyG4mlqpikNHDexfdy8Z0385eZBdQWTOWKE95j8+qPOutldfE5qek/HGvO9QAk9tSjuFysXKez\nb1sT0rLJ7dWTmioXqQx8MHc3u/ZCOOZc+8Lx/kSSgqwZYmreq7ySuZZXojNJCgW/pwl3oC+rYpeS\nFgpjcu5FKB5cnnKMzC7G9zT46YkKaaGwNn09ltHKYN/v8QQHMZBLSYXnYxu1jAu9A4HziNo/xLJ9\nZI18klxAyaDnGf/9myiquRHNepPDr3mHfSXNLLx3FqubTyB0YRujLjyT6jFHkk2sZfDplZSRwDbj\nSBsMBNq5EYafMxQ9tYXo3ns7goTl2jOsNG/hg9QPAfDkjMIyWjHSG1G1AqTUWfzgbAAWPzgbt7+v\nk1WRnwTBihokHVnEYO163P6+rG07G0WCKQSlMt2x3Y5sLwZyKZqvirYNG2naEyUTjiBUlZ5DevD0\n9AVcPj3kNGNHX6YgsI2G+MUYyuGUDbyJZr2MRpnLuKP+f/NTB8s0WLN4Ls/ddxPXnn0oV5/Um1t/\nEmP2Qzqm5SUU2HFQ3lcHk8nFzRiJBNKymHlHLUHfbva1jebWRUGSmXLu3BhCFwqm+dUvSvj8OYyd\n/B2wJa+/+++Z1e8McuPbeC9GMsXpv92HbUtcbg1/STGe/Dxsw0RaFlZWZ+/OMEJV6Tu2P6WVnVOO\ntG39Ul5++BamD/WhaZ4OVan6RUtY2lSNbVoU7nka27QQQgEpWbf03U45dhedR0m3GrKZ5EGXN1Sk\n7PTbV4EQ4iQhxJ/abweUmTkgWdVsOjWqtFv1AQ2uiy6+LgghiL6/huS0QzjpxgaEoqBoGqnmFvRs\nHoGc3APeZ2vjbu785Xn0v/xVEoEMviGDWWr04aYbk9xyQwHjC1/lwvtvY/1ehaIyF8HulYz+QW8U\n1UVg50Y8Xj+R1kYUIeh1yEgAIq2NbF27iEwqQTaTpLVpL6lEjNaGWry+IFf/5rHOPjX/s0z77g+I\nhZt5oy5I85p1FA8ZhJYTQEobM5li8waJtG2y4QjN4QjBMUPYI3KICxcfrVGI95pEcwSK86Cm2OLk\n/Jc4+dETeOmcWRyi/RzLaMUyqvEEBzkKS55yJnpeZ2H4WBpUN6d6fovUnCZlI/Ys3tAILKOV1tTJ\n5PhrkVLl92ur2NtUTX4IrhiepBqLTfoxjMr/B4raG7eMMazgSXaNgwahMirnXjIx2OCdQ/K+PLJX\nJBiXOQkl0JcR5+awYlYBh517NK7gYFStAJengnR0IZq3CtMQ2O3KRUvilzPC+ztUrZAFf7sRT5CO\nxuVFD8xGCHj/L7cy+pKTAVDUnPZMSw6ar4plqWsZIi/Bai9BUiQ0Ch+2gGHuG3F5Kngy+hgnWmvI\nrakktqsWM53BTKWI13rwTI5x86+XMfaMwzluwD1M8s/BsAK0xQZSnrcBn7SxhcAGYuFmvP4cNq5c\nQN22tbQ17mbBW2ciptmY2SoU1y+wzThmtt5RwXIlccnOXan+MgjlF/PWr9Zxyj2DcOeESKSDFIQ2\nMOv4JWT0IiYN7k3EcpFOxNDyiw/KGIYbjfu9bfO+XeRnM7iVEC1zl1BSUf0vfz92+lW8tsOHFvDT\nsGwFeTU9STU5TvaB8jLSLa0omsb5051r89wldJrS1XuvPIw25peYho5LczJk6rI/kd9nJqrHQ/Oa\ntdSWTYB0mkw4jMvv5/31MGJcpxy+i06ipKIn65e9W3UwjyFwdE2/6QghbgFGAk+0P/R9IcRYKeXP\n9+f5B5RhyKYTg4orarrSC118YwkVlPDgm4LqCWMx02kUl4u8ntXMXvX56mJfe+LP9L34ZQB6Tp3C\n7395KFeeNosf/N9h3Pmul7NeOpPbf72cbiWSlXGn5AJgzOkjWdBaye4eo1ia6sfbG328/PAf2LVl\nNbP+eA2nXnchP/2/y2ip/i5y1LWUX/okeRNvxTv6xs46FV20E8ov5rSPhd+kJN3iqLBEtu9EqCqK\npiFtiVAULBueWu/jtqei7NvRzJuvN/Dhq+vpXmIzSu5DT65m9vlzkLbOMvOWDoUhM7sPRatCKHnU\ntUyk2k5SZWWIGt/hl0un8NOPphCRv+HMl75PS+ZK8j2P47IWEI73JxwT9CiXtEYkO11eVhr9eGOX\nl7qWdiUcYxnhurvYtRBG5L5POHNcx2tbeVqGAttkvftFR/5UuBl72eW4/X3bexJGoLor8ecfxQr9\n11jAWPWnBKTFqJx7HelYxcPoiy8kG6fDtG7Y9Eo+XiD755Ik20qwUTyCntzCCO/v2MD96EJgC0dG\n1UaQRWGueTN6agtT3dt5YM9Q9Hic4ccOps/Ro9CCAWzTYn54Gnk1NWzdmiIrBHpiIarQCXj3kbUH\nAlCstuCWNiceU8V13x3B7ddu5u/3TWfu6xchhOWce/UwhOJG81U7423vt/imcveL5e3qbk2ssSvR\n5Fp0M5dEupIySyctFDKpxEE7/pux0v3etuDUuzFTaaxMluLyf5/T5eQ6Ls6W7kiumpks7lDIKUky\nPml8vv8+p591pP3Zjdb7S6S1kcDkP+AOBknGP2kOL+nWk1CP7viKCsnr1QstEEALBDBTKcxUih9e\nPqFTjt9F51HSrSdtTfXfTL3kL5/jgclSyllSylnAVGC/swwHFjBkUv1LujIMXXyDkbZFbOcuwrv2\nEurRHTOdxkhniNbWsXbxO/++vZSkk7H/KK23ec0iAuWOaoi/vJTfPlBPXu/ezHqsicaVa5h2pM2o\nU0YyXsYYGcxw7BhQPR5Wzd/OyEm92bJkJy6/j0BpCYm+FzHonMmcOes9Fmx1cf3LNqrHi8sfYPZZ\nXgr696Wgf9+Den7+V9HcXgobn6Ft8xb8xcW4fD6CFeUdNfF5vXoibZtdH61k2eurSNbvI93UTKa1\nFaEo1LcqXPCowvTZNxJJ9MEQg6lXPaxOfI9lqWsRihtbKly38AzK85dSkr+ctRkvluVlQn+TLeta\nufTFAAAP7C5HaoejqDl0L5nLI9NeJOCFiyebPPhkmNueS7Fjr+D5thDvR6ewNfFDXCX3Y5uwPnIk\nIfVxCF7OYPt8vlf+A0bmzSUrFLyh4az0vc679p/Ius7DkzOowyFZKG622R6OCd7Fu/afOCz/LVR3\nJbbppBQ8wUEcefUNjLlsBmMum4EvdwyK4jRbb+B+Wuy/sd6+k03qkyhI1on7WZn5OWmhkEUhIlyU\nWAZRxUVYceGTNr/Zcjczny3hjee34Sss5K0/P8vWeUv4bUF/Xr++kbhQ8ZUUkWpsYqK8HCNTi6IY\nmLZz3ioLPqQodxVVucsxEezYuxRDnYqq6JhmgOboMHQjhCp0TLsbpuXFMpxg0LbdHZKv3zRycgvJ\nrarEnRvi9/ftYWH8clyKU+o1Iu9hADasWIBt70ejwedgamj/MwwA3sICxyjzP5Qyn3Won3NG53H6\ncC/JhgaSDQ34SopR3W4C5U5wMn2oj+iipi88dnCu6Q/+/kps08JIpsgtKOn42/jjz2VQZhGppmYn\nsxiJkGlrQws4Qextf/v374guvlqKynsQbtmnTDvnBwdVwkpBdvrtK+Kf5SAPqKzigAKGeKQlp7Ck\n8kCe0kUXXytUl8aEkkaMZIpARXl7I12Cgr59WCNHULt1bce2Dbu38ff3m3joxc1cOa2a5+67iWib\n86UlpeSdlx9i4OWvk25pRdqSeO1uhFB4+eYRZFrbkLbk4Qsv5frBtTzblsvPHmjg+ad3Eywvw+UP\nsOy9nSiaCz0aQygKQnXhV2ymVaf55bD3MLNO3a+vqIATHothJlOYya6mu4PFqRfdQFVqLs2r12Km\n07gCfixdR1FVbMsiVF2FNM2OIEK2T8ikbbNxF5z5nXJ+5Q6iKDqZbBGPPRenyr2bsUWzsUUPTpl1\nNCMGSKRU+Ud8Et8tWsBFz+dz/5uCxN76jtKnljD8dvUUVHclzdFhTPxVf37UbzW3P7QPACORJB5O\nM+/tZmwEZd46Vtw9jr4XNtDbOodYw1OYrTeSiS1HSh07s5ij8h5j18K/MtbzGxQpeSV1KJHk4WSN\nfDJGPs/FLuKs/DeZn7iSSTnziKeqMS0vMeNEDDEYgKjxHTx5JyIUN6pWyOhLZzD64hkMkBdQKC5l\ngLwAcLIIioSAtBlf8GxH6VCPvFlkheCkvFdQgOUf1tO2cTM733yL6M5dFPRzguFrdyzh1Lt7c6Rr\nA5lWR+1P81URLDqBgPo2+d43OP/V0ayJHIWZ/BCZeJxCVytB3250I0QsVYUtVTQ1idne+wGgCOf/\npbhKMKwAhhX4Mt5WB4XClQ9hptLOSjyCSLIPm+0yPohexOO3PcElv/k+D91y1VcusNDy3CW4Qzm4\nQzn/cm39NIKh/I7PVHz3HsLbtmNlspx1qL/TxiOl5OWHb6Fo6h0YiTjnHfWv2RJFVYlFHPlWzecl\nUFqCbRj/ku1Ys3hup42niy+OpnkIhgowDf3Qg3WMb4FK0sf8HlgphHhECPEojkrS7/b3yQfUwxBp\nbdTySz69wayLLr4plFX24qxuEttq4w8PvkWvE49n+6uvUzhwAE/N3wnsdCT8Skso6FNAfu9ejPvV\nGqTXy+s7dCYmt7Pg9cdJ9roQJZvFymbREwkUl0r56FEcd+WLPHDfNH5x3152xkYw9tQ3mfLLy5CW\nhWkYCP2TS4VUBKGqHsR37wHgodlZnpy+hg2xUbh8jlHTeSe4eOItBVfAT6a1DT0rv9EmVF9XhBAc\nfcpF3P+7y0gW30Gouge2aZKT6yXaYmHrOlowByMRx+XzYRkGLo8H2zSp3dzKrg02k6Y3ccLvapky\nfTBCxDnl5jTVY8/i3CN13CGNgDT5y9YJhAKSC987CtWbwUgk8RU79eZCVdmxOUx+RQGnbj4FM5Xm\nnRvncevGk7H17aTiTqlJoLwUb2E+zVLl/rqBNI/J8BvXxSTVW/EpN3DjlmcIxwSnjzaoSmdZFvfz\n9+WT0Db5UVwxnp25Fct281xkEGcIg1gS2uRAHv3Iw6McS35I0hIZRqwtiSd4COnwSIYMDfGr4bXM\nlXcy0bMUt/0amn84mejbWEaro/QkYIj6YzRvFe+nfsiL0XNoSAiqci1eSl1Da1xg5ATYbWkIVWXf\nkqVUjB5F25at5PfujVCcVehsNM5ZDxVjmyleueS3uLzTmHrnWP5+fpz7antz9hSbeulhqH880vZB\nwjGJ83mbCPj2YZgBVEVHCAul/T5rhnD5x2OYKpbtJpbs+ZW9174og0cezbbNTvBYIE18+g2M1ArR\nvFXcsq2BCivLD196gdnvK0zSOqeM5/NQdOYD3D41y5VPpFDGHcP29+Z09Gp9Krbdse6aV9OTk3pk\n6Myp1UdvPUO0+jw0n4/Thmqfus3ICSdTt8nG5fNxhHsrxceM5c7HljilcrrOO6skQw7vtCF10QkU\nlFRII5s5FFh0cI7w1TUpdyZSyqeEEO/h9DFI4Dop5X5fIPY7YBBCuF0ut8gr2P/6xS66+LoihEB1\naZx3zkBeeGc5vU86AVfAT+mIQ9HjcdzBINloFAAzlcaTl+uok9g2Ly1M4ut1IcLlwsykaVyxEndO\nyJn4bNhEoLycc055GBTBuGuvoK0pwaYPtxCs7Ea8tg4AaVkIVcVbUMDho3JwjRmAqsIHizM80Xw4\nWUNw/mk2x7i28XKilExbGD0axUilePQfzuf7wmm9UNUDivm7+C8IIZh40ky2lFcgLQtFVTEtcAcD\nNK/egZFKUThwAA1Ll+MvLsLSnZVHK5sl1dTC92ZXYxkGCxdGkJbFX37Sl1+/lmblPi+PnfQhuhGi\noKwPt7/rwzRMx7lXc6GoKlrAj5nOoLhcxNqSvDD9Ns598/847Ymp2EaSRy526r3PvWsfqcYmMm1h\n7lpj8MJ1+eT23cbZz9+HtCx+OfVhUhlobUqzL+Xh/nkuzFSURy8OcfnLGi6flz9uGM2AasneZsFG\nbz9aIoLfbqmiKF+ybVuGX41yVqYLAtuwbC8NmR78+gPBGRuO5KTJCteuGM33hxzCvOYg5wdfxJN/\nAcmoigebVdbtjHC9j4Hg+MC7PJ05GnAyDx43nP3iFBJ768lG4yAluTU98ZeUkGpqQtoSl8+L4lJp\n27SJJXdvw0iXc8SPK/HkRVlk92JEdxNdCo72LUI3Q0ipkuN3atylVBFCx6OFyehFAGT1fEzLR8hf\ni2EGSLc//srib27Q7fb6cPlA2pIBBXOx0n258f4x1AwYwR/vDlKnuNm+R9CwagOtNSkKS7/8ygDL\nNDDTGS6bZZDTozvrt0NrvA+9PuM5Zx4e4oUVGWzL5JRqnc4MFgwjS33lGQSAZGMjPv+nelghhGBq\ntxhPzN3MU5EIsLcj85FbXU18zx4irY3kFXbNhb4uFJZ0I5tJHXSlpG8qQogqICKljEop9wkh4sAp\nQB8hxN/kP8vcfQYH8mmsDOUXfabOdRddfNOo7DmAEZW7O36vffsdvHlOiZ+n/f6cMQVU1D5H87oN\nNK9ZS7C8jKZVa9i3eClNK1chLRs9HsPKZtk9/33OuGosM+64grxevQi3JGlcvhKAeJ2TRfg4WHAe\n283ChRHmz2tm3tvNDB3k5dnHd9DQCh+sUTj/hX4UemxGjc7Hk5fH+NOG4S8upnjoEJ5aFCER3S+D\nxi4OgNLKXkS37yIbjZFuaSWdyKAoAtXjwV9cRGLvPspGjsAyDKS0eeBHPYnV7ca2TG4/RfCH6wZi\nmyaRbTtQANswePftBqbdUsTM2f24ZQ6Yhsm08Qr3nRxj2tE+jju+GKGq2IYzyRKqyuRbziCdyJBp\naUUogitmK1z9hheX34fenmkYPHkYl84p48q5xzD1CIWSEg9z9viZNMJmzGFeZv8jRWxnLYqqcvnL\nGn85BW45NsvqdRmeejVNKg03z7ZYuCJL3Z4sdfvaFY3aa2wT6Uri6W7Ozy1RhFBIZQR7d6e47k03\nbTHB46nHWBc5io1JN93sFGMK57AkOp6AtLi/bhKqCmNcW5i7RMHf3otR1qcbWtDPoJnnYSSSbHtl\nDqrHQ2TnTmzDoHXjZkZPn8DeVVdz4v1XMOOawxCKwtIdKoPNKJO8SwHQjVzSehGm5fu3/2PQtwev\nq568wGL8nkYsfQ8Yy76xvQv/P6e3tzOtfW46G+bcSs2AEQAsM/1siblYtDhGoLyMBenOc0U+IIRA\n0ZwFjXjdbvREEiubJZ2M/cenBHJymTGumAuO7vxKBmlLfCvv5LT+fOb+N6/+iMde24Vt6PiKi9Hj\ncRS3Gy0QIF5fj6Xr7Ni4vNPH18XnJ7+4m9Azqc+KRb8w3/AehmeBAIAQYhjwHFAHDAXu3t+dHMjy\nZEVpj3hBAAAgAElEQVR+UbkEulSSuvhWceTUs0mn4nh9bjZFJdtcKsk99fhLinDn5AAmlTUD2GD6\nMZIp6hctQQiBNE2C3SvJtLZiZjLs/XAh0rJ57s4P0GMxgt0qiGzdjjsniJnOECgvxUimsDIZhOLE\n6qrHgx6NEezeDUVVWb0hi6WbtEQEZYUSI5nkxPx3KbOmETqmkPlLdIKV3Ui3tBLfs4fn04WcOzHU\nlWnoRJwmyAiRbdvxFxehejyfZJmSjgNs64aNNK5YSbBbN6pyI3hyy/EVFhAVLjLCcahVPR6+96ct\nSNOkaPAgXF4P6ZY2xh1dhmXDhaV3c/RvJ3HvVUGue1fDHfCRkRJ/aTF6LI6ZzaK3mwpK08LSdWad\n2YpuhJj5aIpsOEtWF/iCXloak7y8I8UR44pYsiLFK39bSE5lJVY2S9GQQ2hdtwFpS34wuyeKx41t\nmWDbbNqS6ZjUGfFEh+79VbMV7jwZTNuDKQT1qgfIYGYyLFnvo6g0wORRNnuaYUggS413E3XqUF5s\nKySf06lSnAWr115twOXzsnzAQEb0t5nqXsb87HC6lUiadnoJFIbY+OQzVB0zCU9eLiVDXIR6VpFu\nbeWcbV7OWPcuC//8OhmzN+MvH8khhS+xrHUqBYrjfC2lQlu2gjKXMwkVwkKiIrCQUkVR3EgrC8Z6\nFE9fEkYVyUw5ryyy+TasfU0f5uPBxQ8ycMR4Pi6wuf2EKRSedBeqx423oAAjkcA0rA7p0C8L55rk\nZOB8hYVEt+8gr08vtq2bzeDDJ/3H5ynKwanudnu8nDDjh/91u3c2+MjrVcOeBR+S37cPQlFwedyY\nWZ2cigoiO3cyf52f4UcelGF28TnILSyjuX7nQZNW/RbIqvqklPXtP88AZkkpbxNCKMCq/d3JgXwy\ny0IFxV3BQhffSnz+HIQQDBg+jlHmajS/D2l9ojJSWXMIAOHNW7Da+xZUj4dUYxNmKo23wFEC8RUX\nEd+9h2wkSqqpGSOVQtU0FJdKNhLF5fXgLy3BW5CPv7SEnO6VmJkMTStXE6vbTaY1jMvnYdP8NezY\nK8i0hXmv7SRumeejtgE0r4emlatINjRgmxaX/GQE3hFdzuudzSmHOJc6l89H8+o1mOmM8/8tKkR1\na2h+Pz0mTqR48CCm3FgA0uaJC5oJSIs/Pd5GqqkJoQjMdBpvYSHRnbVEd9VimwYL5jWwaoOJbcYp\nGNCXRVYQd8DHsWNs0k3NHDUC4nvqEUJBCIHL7+cPJwvSTc20GMUYUiPd0oplGOxeX0f9sjVkwxH2\nfriQRYtjSFtSMnQItqEjpc3mZ19A9Xhw+bxEtu+kbcPmjl4B27KwDUcr1ZOXixCON4kQgmvmqGSF\ngk9JMusDRxI40xYm1pYkHDFpjggsC25/10dGL2TtbpWNu8CyoEnVeH+vh2knljFmTB7nD0xRkWPz\nYfZQXlrkYuN2y2kqt+Dc2y8m2K2czc8+T9PqNQBofj+hU1pQPR6WhM/htk0TaBMuXomcRK3Lw9up\nIzAtH2m9iBLfDpKZ8n/LHFi2hmk5ZUear5qG8Eh0M4Rbi31rAmwhBENHT0bTPhGIKelW036N0km3\ntGJmsqRTnetm/zHPrf9sOerpQ31MH+qjeNNjKC7nnG/0HUnjnh3/UXnuYFG7ZQ3rl733X49bdMhA\nXF4v3bT3nd8HD8Ll831SXSEluT2rD+5guzggcvOL0bPpg2M80s43PMPwz3P3o4F3AKSUBySldiAB\nQ/k/y4910cW3ldLKGs4c7Oa0Pjan1jhfiEIIZkwsA0U48oCKwMxkKB3hCDMY8QTFQwaBEJipFHoi\nQfGQwYSqqigY0A9PXh4uv1M2YZsmtmliZbJEd+x0JqGaRqqhEaQjpaq4XOxbtw0t4OcXf9yApgnW\nL6pj6+zXyESiSFvizglyz+8W8tfr3+pyju5kAjm5zDiqFNeiWwlWVNC0chVmKo2RSOAvLcFMZzAS\ncfRYHNvQUTSNcx4p5qp76rEyWSzDwLYsAqUlToN0u+KV6nbTuHwFd06O8lzypwwfIHhudpRo7R5m\nv5Hg5HMGcEbePv58dXdKDh3C1GML+f3pGhf8ahVmNsvPXlO48jkdadsIRcGIJ2hcsRJL16kYPYq6\nd+eTaWll35KlBMrKsHWDUI/uRHfuJBuJkltTTW5NNdKW2JaFtKyO16y4XNiWBbaNpetIy+K6uX6y\nVoB0RlJa7iNQXorm9yMtiwUrBeu2C8YOkRhmkF7dJGWFsHGnYOlGBY8bKgtt6hoEW10+nlngwgbG\nDrEJBFykGpvwe6FbscQ2DEb84GpGX3YWQig8//MyZv56DemWVs4+5REWLY7x81s34kaiScnyHe1K\nVVLlLXMI9XYBpuXDtrWOx5ujw2iJDqMlPoHm6DDygtsI+vbw4EsHz6Pg60C3ngOwLQtfUSGPXJTP\nxGk9CQTz/vsTDyIjjzoJ1esl1dhENhrlzW0+HpvfQCad/FKOHws3835jGe9uDHDX48s+e9vde4jv\n3cs519zC2eMLSe5rILfGkVWecc1hX8p4uzgwQgUlJOPRLi+G/8w8IcSzQoi/APnAPAAhRDmw31Jq\n+x0waJpWkZN3UAO4Lrr42vBpmuEe77/L+8V2Oc2WZiZD64aNZMMRFr54BNK20AJ+XD4v0rYxkkmk\nZRHZsQsrk8VMp7FNg/jeelo3bsbKZmlavZaW9RsByO/Xh7zevUAoqJpGy5adtG3ZiicvDyFER4Yh\n3dqKy+fjH8vhr7M+IpWIsmfnRhbPe5EVH7xGMh49uCfqW4zb6+OUmT9jTM52fnXHZPRYjFjdbrKR\nCNmYs5JvZtLYlkV8jzPJMNMZPPl5PPjjXgihkIlEsXUdT14IRVVJN7eguFTepYCGVsH8N+uYOT3E\npReV84eTBddU30FpzjMA/HFijDsuvJcLfvoRSJtHf1yDmUoT2bbdmdRnsyiaRs/jjmXHnDeI7aqj\nesokVK+HwoEDQBEEu1Wgejx48wtw5wQRQpDYuw9su2PFVHVrmKl0R7AgpUSoKtKyGNBL5Y9rQ/Tu\nDk1NWfKLAuiJJEJVMTJZsjp8sAquej3Alt2CvU2CcFywaUuGrXWCR17OcN8xD9DHTDN9nMk4z0qK\n/TbTx5mcO7OaPWt3sLVO8MvpAeoXLmb64TprZz1CyL4e29A5+6eTGTDjbEaODFHQvy/Ld7sYYKb4\n2aD3WZQdzAq1kNoGQYXShhDWv/z/iv1PoKoZVEXH7YoRT1VhWd6vpAH4y2TUhFPItIUZfGghO1Uf\n47tlD1rv4ZmH7F+mxqW5ObqkESur4/L5sHWDQFkZz69I09q456CM7Z+Z8/jtCEXpMGLb396vYG4B\nZjZLdGctOd0rmXXze7Qs/DlT+nTJW3+dyM0vJhFr+3TZq05A4DjVd/btS+QHwIvALuBIKeXHOsFl\nwA37u5P9zssGAoGqnLyiAxlgF118a5GWja+4CNuyKB42lKaVq1C9Xq6+63yO/O6T9JhwVIeGf3TH\nLjLhsFMW4nFjpNJY2Sz7lizF5fVg6QY1044jsnMX0R07yal0JjQun5f6jxbiDoUYd94kdvesZvur\nr+PJyyPV2Eg2FuPqP57EgzfPd+rVDYNXt7uJ1bnwFYxH2jbHH9OLxpTCh7fdyfAjp+H1dy3CHCjV\n/Yax8OE3gVISe+uJ1daR072SUHUPItt3ABAoK8dIxJFA06o1nLfSJlG/j0xrG97CArwFBY5jbDpN\nqKqaO29cwGM3HUpyag821UH/HjZPPPkhBSXHIBQFRdnNR289Q+GA8bRt3sqk6y9l5h1ruPVHvVmb\nGcWDf1yENy+PxpWrSDc1Uzn+SLSAH08wQGxnLUJVcQeDhOv3OdmrSBTF7Xyf/vnq7vzgLzsJVnZD\nKAq2aRKv201urxqkdFb7M21h3KEcfnfYgzREplKcu4pbAidQWWIz+10v0rKQlo1l2RjxBFpOkNWb\nJSDJhiMIVaW5VUP1eLjy3Yv569jfMFQrRCrd6JE6hFZFo0YzCVV1Z8PGJJf3sjj76sNpk5J7XrqI\nIacJykaFGFhqctzpGjtVi8Oq3JxQ8Ay7m45hR3wERwaXsDg1kkGlEtty05DsT/fc5ShCJ5mpIDfQ\ni2win6T0kREKbmlz//MNfMvjBdxeJ5O5YWOSaX2/nNIrKSW1W9fg9vgoLK381MWVkm49YXcEadto\nAT/JhgasbJbXNvk4zdtGMPfTVYu+KG89dy8tOSeTk0w5XifRKA8+0wLA2cdXUlr5SVP4I3N3c/G0\nf+2dPfeEKp5fmCAbieAJ5XDdHbMJ5Xctnn6dyMkvIh5tO6jWBl+h0doXRjp1eE9/yuMrD2Q/+32C\nVVUtDYbyD2TfXXTx7cN2LhpCODXl2XAEIxFHqAoVo0dz19WPESgrxVdUROv6DST3NZAJh1E0zelt\niMWJ1dXRtnkz0jIxUmm6jR1N85q1+AoLKR46GCOVJBuJsv2VOVRPOYbE3r2sW7iLiyebHP+94ykb\nOZx0axu2rvPEfevIqawkv18fANKtbZQeOhTbtBCKwq+vX8Ddv3iLZXu6kxnYi8Y9O77Ck/fNpdfA\nwzjz8BAAZjpN8+o1TjmSaRHZtp1Y7S5idbsxszq+gnzKxxzOyw8cT9GQwahuN1Y2S3iL0/8y57ow\nr/7O6c9TVyyltL6R8KJmqvsNI5RfTE5uIYGcPCaffhngSLbO/d091C9czBXXfkA4LmhcvpK6ee9h\nGyaDL57pKMAUF3PaRJv8fn1wh0JYuk6wWwXSluRUOqowt54MPmlx+/d7YptmR5Nzbs9qbF3HSKZQ\n3W5aNmwk09rGm9EL+PXKSl6JH8/AHjaTlCg1PVSEqpKT76NlzTqiO3fh9ylkwxEiW7cDjpldpi3s\n9FbsTpEwT+HlxOXE62+jJnsSubbJ0Mw0LjhOYGUyPNEQ4sz8PXy36Fniisold13GGRcP557nU9zw\nhouEraAAe5on4nGHKRAxkpkKfNKmzNLxeVrI01pIpCuxpZtkphzdDKG5kgSVBC4psRH/Mjn8NnPZ\naQM5qSLB5qURNi+NHPTjxaOtLGco7+4r4flVOj+bMZK//fI8YpGWf9nOSCXZPX9Bu6eBgaKqZGMx\nnl30n5WTPi+GkeXJv/2c7XIsLo8HdyjUITbhycvDk5fHy0sy/9LTcMEx3f9tP/lF5VxyYh+OPcQp\nT+0KFr5+eH1BTENHCHFQ3J6/RcZtX4gDGXNxMHRwVgC66OKbQon6DlJKtGAAT36+M3GqrKR4yBDG\nn9iPgv79KBp0COmWFrRgkNaNm8hGYxiJBLZhEKurI7J9O5m2NqRlI4SgbNhAR1WpooKWtes7ttMT\nCba+NJsekyZyzAnV3DvH4of9tlFT46fyyLFcduuZCEUh3dpKdKcjA6j5A2TawuT16olQXU7zo26g\nejw89qvZPP1mPbu3r/uqT+M3kkBOLlfMGO78IhTqFy0huW8f7txcciorKejXl55HH/Gpz1XdGlWT\nJ/HSbY60ylNzsyxYnqKorMdnHnNS3ySq22lCtrJZVLfGA99/hGB7AKDH4+x6ay7Na9fRsm49sSQU\nF2mU9S7nyLEhPPl56IkEqeYWpG1jIxw/BCS09zFY2SyBwhB7P1xIsqGB8LbtBEpLSLeFOdy1hRH9\nJRvqFCZpq7hyjsbytzaiR2PEw2mkLdGCQfau2kw2GiUbiWAbTsbC5fGgBQJkWsP8YP4Qbr1pKWc+\n+TjuQF8GyAsws/s43nszsyb0YNHiGMW5qwjH+xOQNpNK0+SHJKrbzfNnz+NE/2ImBD6gOG8Vtq3x\ngVrGUtmdmFDJCAVVybDB7kazXgZAt6L3Ccf7URx6h/KCRbQp344m568rObmFbH/lNRqXr0BaJhXH\n3Il26M94fnECQ890bNcrO5+8XjXOZ6exEeFytfdteWjYva3TxmMaOnffOJOW4ElY2Sy2aZJubUX1\nOM37gdJSAqWlhHp0/9Ty00+jqs/gTw0ouvjqEUIQyMkDKPyqx/JtZr8DBtu2/W7Pv2tdd9HF/xLx\nSAtCVRw51HiMQFkpez9c+P/YO+/wOKr763/ulG1a9e4iufeOjSkmNqbYFGMwvbcQAqGEQJxefgSS\nEFoIeQk9AUJvpptmGzA2xrj3IttyUZd2tdLWKff9Y3ZXkk0xYFOcPc+zj7SzM3d2R6u591vOOZSN\nHcNzNz1D/dJlbJ71EnVLlqHqOlJKjPZ2glVbCNfXY8U6Jk+ZJJfWLV9LuK6e+iVL6XboeKx4nNC2\nanodczSK7ijyzF8QworFeWhnP64c3MbNP+3LW3NCjJ06FF9xEf5u5eT16UPz2rUEt2yhac1aGlc6\nijNCUdKkW4AXP2inqW77N37tDgToLg/XXXUUE0Y6C3nF5aJgwABenOksOo7y1nHe4UWcWBzkvSUR\nLpvWn2suOYyzjy4HYNbcXTz5Xm+ysnP36nx9hzgky+P/cDn3vHo5N/5lAmYkSqSujorJkxhy/jmU\njRtLfv++RBqbWLBSoaa6lYbqRhYujdOnQmXCWYfhycvFNgx++ZpCXCgoUmIlEqguF0W9yqhbsd4h\nQZsm7pxssnv0ILtHNwwziyXrBXNfreLCF4eBbePOzyfe2koi1EY85ATDVjyOp6AAFIVQdTWJ9nYC\nm6swo1GkZTHjcBN/9268ct0mfPkTOfnhW8ipuI2G8OUs6NbGrPP/RUPwINzmfZRZCZpUnXy3zYXT\nXTzeNJWYkU8o3JtIrBSPq5mn3xIMMiO0KSpDvasQwmKwqCUqFEzLg5Qquf7NbHznKj5umYpbSj5c\n8s0QbP8XIYTg/DP6Y5sGO97/gMKBA8ip6Imi6zw+v9nhxwCHHDWDSEMDsaZmsnv2wOX3o+g6dsKg\nbkfVPns/9z+3hlj+OcSDQbJKS1E0jcDGjYS2VRNtaiK4dSvhulrOGJ1Z0xwoSCa091PAIFH3w+Pb\ngBDCK4QY+FWO/XJVkb2MxDPI4EBFNPtMsCXxYJC8Pr1p27ED2zDY+ubbJFpDYEuklCRaW2lasxaA\ncG1dlwU7OBwIzef0+W6fMw/dn0U81Eq0JUC4rh7FpdNeW0fJqFEYkQhGOMLQYTmEwrAIP1lJNbQV\n87ehuFxIy6Jx1WrMaIzWbdW07dyFv3t3Eu1hjHDYUe1JKvfYiQSPzcq0Jn1VqKrGhKln85OLDk5v\ne/7DQs47/LM5XnmFpZwxzPWV+rRvuP74Ls9/8cvp/PKXJ1NQ/TiJ1lYSIcc0MKu0hOrFa4m3tqK6\nXLRV72DTpgi7GgTZFT258tcH07x2PSqSbGnyjwtyEKpKNCZpWLECRVVRdBdtO3elg4mblleydU09\nOb17obpcKLqOKycb3ZeFt6SIboceTFZZGXqWj3ggiL+8jHiozVFhShgEN1cRaWjgnv/UE21q5vAr\nwDKaeeHqRubfcQqblDxm5L1AQhyKz92AN28yJoLDYyexrkalJSyIJ8C2XcxqqyCacNYDM4+KsoBs\npro/RtecQCDbV82IvPcAx4/BJTYQGhPARrBscYb8v79RXuE4ySmqRvU7c2jdVo0RjqB7vTz5cSuW\naaC7PMRbQ3SfcDhG2FGTs00nmFjWPvhzx4/2LyXa/4vdlbdtXEF7TS2egnzHPHNzFe27apCWjRmN\novv92IbD+TxQ5HUzIJWE2S8Bw4HSkiSEmIbjuzA7+XyUEOLlvT3++9hGlUEG3wqMRIx49d0AWAkD\nIxwhp7KSsnFjcfn9TlCgCHSfD6FpxAIBRyoVhxQoFBWRnKCEqjgGbkKguFxYsRhlBx1EVmkJ7twc\nzHCE5jVrCFZV0bZjJ1nlpbhdsGp1mKaA4PezLFw52UjLIrBxM7Zh0n3CYRQNc/wipG0Trq1F83jw\nd+9OPBBwDJyiUcxolHhriMba6m/nQh4g0F0errnoEM49ZP9KVmq6ixHxenYuambnoua04k1j+RlE\nGpoI19WhebwUDBxA2agh+IqL0wujRKiNcKCdnn1yeOaldjx5uVzx13WYKCSEwq3THFWkwkGDyCov\nI9HeTk5lBUIRTD+lnF0NEk9BPmY0RkmhQ8TXPG785SVEm5qJtQRAEXiLix1fhUQizZeIBVow4wmE\npvHaFY8x56YGHvvLeJ5uvYKLXhnL25NijIocTczIJ2E4FRfT8jA8dwHN6lNc1ecjpuitnJy9HU2N\nUpFt8UhtD/68cgyjcz9gmIji1gOAE1DoahhNjeGSCx3TNjWbBlWnRdH2uu0kg6+HG66d4vwiBL7i\nYrJKS7BNEzMe57/zm7qottlGAjthoLp053vl9Xzu2DlZkpysz8/KhgKNPDe73vFAiUSINjcjVAWh\ndahEJVpD2AmDK84c9dU/aAbfOXizciSQs7/GV6Tc549vAX8EDgaCAFLK5UDvvT04E15nkMFeoD0U\nYPZTd+PufQ1CCLK7dyNcW8us589n+smPIG2bvicex9Y338aIRNL8BAAU4ZClhY2dMJ3nKSgC2zRQ\nVI26xZ/QfcLhZJWVE9yyFVdOLkY4jKKp2IbBksVhSisLmP16LZ7CfKRtE9i0GW9hITUfLaJg4ECi\nzc3YCYOE5Rg1xVoCGJEI3qIiok1NIBSkbSEUlfXL5lNcvt/MMTPYzwjX13P5acP4zUUnUTbxDhqW\nr6B0zChQFDx5uSguF96iQsK19VDpzAmu7Bw8BQUEFY0b33KRn69jxaLkD+yHUFVUlwtp2wzopQKS\nc6ZIdKmioZBrx7jjHTdCVTENE0VVMRMJrJjjSB2qrqZo6FDiwRCa24XmLcZbWEAsEGRL25XMfNNN\nrwoXcQOmHCo5JWcryx/8mKKLDsErLXr6bsWOQWvih1TkPUxT+BSHqJz3Pu+3nMGmoIbPAyO7mSgi\nwbC89/ggdBSalLixGevbRnPbEPI91STMHLYEpjBMhnlraezzL2QG+wwPvbGFX8ycxo6qNTz+7EJU\nt5uPnjuY8TM+wYxEeDo+lp/fcDzPP3ATnsN+Rd3SZeT06E60uTmtDvdZMJY3fOr2UKCRR1/dRqja\nabPUPB6EqmBEomher9MWl6xiIARCEViJ+KeOlcH3F15HAXC/BQwHCAwpZetuCZS9jlwyFYYMMvgC\nRCNt3PPAQja3jHCIoqZFuLaWfidNY8YZTyKEwFtY6BiqmRbYMh0sKLruBA+qAikXXUVNat0r6YnM\nSjiZ2LpPliAUwRE/vyIZKJh48gtoXLka1eMmGLLxFOZTWuohtHUb4br6ZCtSlGBVFTkVPR3tfZfu\nSF9KR+YyHnQye9K20j/nr9hT+jCD7w+uOGMESMmA857FisXJH9APV04ObTt3Ub9sBbHmAJH6BqKN\nTax4bTFali9dBWhWdGzDpKk+jKJrCFVNK4DZpsnGrSbVtYJgWLCuRkUBalQ3Uw51vqt2wiDS0Eh7\nbR1mLIZtGHjyC4g2NWFbJro/m9at2wht34m0bWpUNxMPdjFhhM3Jow1O8u/ifSppvTRMnoxR5NvM\nu4k/oPvGUJS7nI/bfkxp/mI8epDawJH0sdvJyZJUFlgclz8LcLqK24RKWFEZnfsBRttccvVnUF09\nUExHLTATLHzz+Odji+nZdyi9shdjJQzGTfuAQWeeRsmY0bTX1nH/c6s5bMqZAORU9ETaEqEotNfW\nfSUDyjefuYdwXT2a14vqdkRyUi2gibY2pGmllZCEqiAt25E4Nvbar+oL8cDLG/bZWBl8NXh8fsH+\nrDB8v52eU1gjhDgHUIUQ/YUQdwN7/U+XCRgyyOALULXmEydLJSWaz0v+gP74SkqoevV1bMupGMRa\nWqhZ8BEI0UWmz7ZMlGQ5XNqW0zub5B9IKRGa6rQqCcG4a36EbSRoWLGKpf+dRZ8Tj6ds3EH4u3dz\nJDsjUdqqd9BatY0dGxrYPuc9zFjcWewJQaShgbolS4k2NWFEoiRPiisnG9s0QChOMKOoSMt5D3/5\ny4vf7MXMYJ9i17b1eIuL0Lwegpu3ENi0mewe3TEjEeKtQYz2MPkD+1MyZiQ9ylRGj8wi2tjEP142\nsBIJzEiUWMCR3ZTSprRIoGgaWX6dLbscJ2fTgu1tKqEkZ7hfHzeh6u3k9etD0fChaD4vLRs2AtCw\nchVCUTBjUeLBVn5306Gc9sMxrAy4GFBs0teM8fQiF9fM6cn4RIh1NSpuV4C4kc8Db6lsazyKaLyU\n4b7lbGycgmH6sW0XQlgsWOlMV5GW2cxrncKOwCFkSZsSK4FiLkMoLqxEM5GW2QB8sCRjrvVN49Lj\n+nDV+eMAOPmSXwOgejyse/IZ2nftItHaSmDjZh57aj2t1dsxwhGEpqJ5vCBt5teUfeE5pJQsVspY\nrJSxffMqavVjQEqQTqLGNg3nnqooKLpTMXOCYidBI1RHBCIei36pzyal7HJvB3jvtcfoNr4QV04m\nsf1tw+3dfxWGA4XDAFwNDAXiwJNACMfUba+QCRgyyOBzIKXkjfkxpG2DLTEjURJtbUQbG1HdLofk\nbNlpfW8hRJdWJCXJWXD2UUERSMt2Fuy2I20pbYui4UNZ/I/7cefn4+9WjuZ2U7PgIzSfl+1z5uLy\n+zGjMTSvF0VTadm4CdXjIbd3L6y4k/EFiAecnm5pW+lqQjwYdBRspFPpSL/H5PnjsczC6vuK9cvn\nU7f4EyKNTbhysom3hmhYtsIxYDMtYsGOnvHBvSX9KyQnnz/UIaP6sxCKQs/+xUwa70bakrp601nw\nW+DzQFEe9CiRbNnlODiHIoL8bLjimv5YiQQ1Hy6kZf1G8vv1JVxfT/GwobTt2Ik0TXIqK8i3Dc4r\n3czp+TsZYkQYVfAED015gEuOMuhZ8g6jyw3yXE+S7aumdw9B7+KXUOOPAlDk2YHH3YRLD+Fz13Pn\nD+ZzbNYHaDlnMDnnAVzS5uiClxjpvxvbaifa+hEAf3r0VP4976Jv48+RQSfcdfecLtyRrPJyzFgc\nRdfIqaggsHET0eZmdK+XrLJShKrh8vu/8H7077eq2bm5iTm3PMgzr9cSbW5Jft8NbNNwFva2hUmN\nhXMAACAASURBVKJrmNFU4kRiGyaa14tQFDSvl8ffrcG27fS44bZW6nZ+ulJTuC3I/S+uY/S4rupm\n66KjueW2dVx+/UiCzfVf8UplsC+g6a795sMAHBAqSVLKiJTyN1LKcVLKscnf97oMm+EwZJDBZ2BH\n1WqeemVnOhvvKSxA9Xgww5G04oa07bR6mBACoSpkdetG2/YdCITTaiSEEyiYTjVCaBrYVroFBJKt\nS6azWGvZsMEhQ+suPAX59DxyIoGNmwnX1oKi0LhiJVllZWSVlRILBJCWiS0liqphGwZmNIqial2y\nYdHmZidgkbZTFYF0W5RpGLg/n2+YwXcUNds2EE2UOL3asVjSgdnCsiyMcBjN66H2o0VUHnMUl5Xe\nxIzHf0qvvtl48vOINjbhLSpk19YADQ0+PDl+rCT3pjhPUloImgqL1gjiCcGqZU1MnVJIUwCWbxQ0\nLFtBbu9ehOvqsU2TWCBAcNNmcvv0xldSgqcgn0Oy7iImJ+LTlwLwcuvlDDQj1Fsqv/74NF6/+3UK\nB5/DnN98wv8NOJPnWp/k1Fw/sdZHcZtt4P8xpuVFj9+DYvuJt6/G7R+GqWVTnnMfsdZadG8vpNFM\nbrcLuOv5I+gzaP+S0DPYO0gp8Xcr5/wTKrn3wUW4sv2obhdmNOqY/ZUUIxQF1eNJy67edV1falQX\nNYuaP3NcIRTqPlmKt7iIePL+lzofkL7PgSP+IIRA2hKEwIhEEMmf8aoQ9z4d48qzR9Pa0sBdvz6b\nvENuJq+3H9tI0C34Gh6vHyMRY0VtXyomT+K3/23ltEHO/d40EngK8hl3/HCWb4T21R8zduK0/XhF\nM/g8qJqOoiiub/t9fJchhBgA3AD0otP6X0o5eW+OzwQMGWTwGXj61V3Yhom0TDwFBZSOGU3NR4tI\nhNqcSchKBgtSgupUGKRl07Z9hzOAvVsGIUl+lrYzwYnkMbZp0bTakWCNNjSi+7NQNJ2s8jKkaVG/\ndDmxlhY0jweEwEoYtG7Z2nG84QQalpVIb0sHC9JRwUkFE52DCKEq9Jhw+F57AmTw3UN2XiGiScUM\nR8jq3o1oY1M6wxptbiYeDKK63bTt2EnYOonJP8hm3TaRVNGqx1tU6LjttoZQ9EJ8XoVw2CRuaFi2\nZFcjDOgJgTbJqAGFaKqkshzCMUF29+7UL19Bdo/uSFtSNGQwRiRC+64aqt+dg7Qlg94t4q/PH8zi\n5YcQN2Dm0Fp+Nr8b1/4gyuxdXq64+TiWbxKsaCxjo34681cqzDisFjNei8z+NR4tgJQqcf1a9NhN\nKFo2ttWO5i7HttpRXYWg9YZ4DffPPoGs7EzR/LsE27LILSgBoGX9BvzdutG6dRsuv59IQyPuvDxi\nzc1oXi+evL27D5mxKLGWFhRNS96fbYcbBk5AEosjVKe6oGg6diKBguNHI6VE0TXnnp0az0jwyKzN\nZI/6HbGmZloVR8HOKDuSeEuIkpEj0AJLqFmwkG6HHZo+TlE1fv2rEfzxV/OINrcwYUDmu/dtQtV0\ndF3fL8YaQoLy7dgm7Gs8C9wLPAhYX/bgzDc8gww+BS0Nu5zsl9uFlBIrFqNlw0bshPGpEo2pNqPO\nC3IpO8jPaSK0Iqg4anJaKSm1v206LUVC07ASTmk9XFdPaMcOjPYw0rKJBQJEG5vSY6aOVfRkNSH5\nXFq2EyiYZvo97N57C1AyaiQ735/PI/NqiYZDn7pPBt9tVK352MmmKoJoQ6PzPZK2U2EyLYdon1xY\n3bFhJPMWxQmEINrYRLw1iG1Z3HiyQ3hWVYVgfSvFhRqNzSbxBBTnQTgG8SQ/NJ5wvnvzF8UoHVTp\nSKjaNsGtW7HicYRQ8JWWIm1Jz4lHUHHkRAAmDTK5fcJL5InfcdBgSaFtcNgIyTOPb2PJ8+/Ty7eW\nv858jz+OWcGkPxzBJR/MwrI8KCKBCP8/vJ4GbLMNaceRdhzbakcoLnRPL6RUefTD61GUzHT2XcIv\nf3ES11x0CAATRoaJNDQSCwRw5+ZghMNOpj8cJhZsJR4KYcbjXPW39Z9bXQDwFRdTPHxYumKhZ/sR\nioJtmU6woCgOb0F1AgOhackWTYfLYBsmtmEy8/rjufLs0Sz78A383bvh7959j3NllZZSt3RZ+nmq\nugCkv2+TL5wEQH5x+de9ZBl8DWiajqqq+82J7wAhPZtSyn9JKT+WUi5JPfb24EyFIYPvPcaP9ZMl\nLXYpbjYsDu6TMefMeggrfhDgLMD1Aj9SOpr04do6ZxIynOBBgrNYTykjaWrajMh5qWPRLhSV7e/O\n6Sqt2mk/TBOpCBRNJd4aTGfPHLK0TE6GVvp9iU6vOcc7vbup4EURCrZpIYRToheqkqxy2NQvWYZQ\nFWoWfsQd75sIIfjhpWPJKyjF5ck4oH7XEQo0UrO9ionXnsnGZ1/ANg3cuXkY7e2oHjdmJILLlU2k\nsYkbr+jBn59uxp2fRywYQtF08gcMYNxINzMf3k5hf0deV/W4OWiQTdxQ6Vtg8vYqDVUFy4K6ZsjP\ngY1VAs3rIdQSJlxbh7eoECsWI7hlK9HGJrK6d8PfrRxfaQm75i8gS/ZiRY3G1NxGvHmHMLa6hk3r\nW+k7rD+3XVaKVxZxzC9W8ejN45h8zUKEovDPo7axzBjI+MDf0p9X0bKxzTbc/mGEm9/GWzqThAX/\neXtExlP0O45Djj6NeYteJNbSQuHgQYDDrbINg3hrK9HmZjx5uXiLixkxLoeVi0OfOZZQVcL19ZQf\nMp4tr76R5i0oquaITiR5CanWS83jSVeDU1yvzlixYDbKQSOZcbCXwmknpLdLKQk215F79MGfGYze\nd/VvCPW9iBmTcunZd1h6+23/eIvc3o6UcVnwZRLxCEPHHkm/oQej6Zmume8bxLe3wN/XeEUIcSXw\nIg7xGQApZcveHJxJyWRwQGCz6qXINgj2+mIn0C9CsLme5QvfxLacrJQ7L89R1QgEiDQ2AQ6pOFUx\nEEJ0tCZBcoGerAJ0ItVhyw4egxDYptUhuWrLdDsRtkPQ8xYWomhq+lxCU/esTCQ6pAGFojgTZjJY\nSLVNpYKV1DEyFdxIh7CdamkCePDhJdx+52z+cvMLLF/wJlZy0s3gu4c5sx6mZPSNrH3sCQaddToI\nBSMcxltUiOp2o2h6ks+isjTowZ2Xy5ZX38CTl8O4w4rxlRaT5YFzL+hJe1MrmgrjRrrZ1SiY94kk\nLFR8Hhg7SFK1sY2cLGgLQ44Ppwc8EMTfvRv1S5fhKShIy1pee/tJ3HvHRMxoFG9hIQu3aJxc0sa8\nO64CoLWlEUXA2nqNF6t9PLAxmwuvPxQNibeokJf/OpynWyoZ41qHv/hEhOJmWehwhHCRVXgsRqwa\nteAmEoYjiJIxZfvuQ1U1Zv5yGkJRiQVbSYTa0vcjd24uqq5jhCPcN3Ng2sX+8xBtauZHZ2Q7Ig4p\nYQnbSqolJZMjyfufFY87wYKRcJIrQqTvd4YRx+h7ObrPx4I3n6K1pZ6XHvkbf7v9dZ74KMDLq+Gx\n9z+bzLypdRRWwmBeTUl6m2F0eDxEGxvZEh9PQ/Y0Xpsf5/a/v8Utt76afv2uhz78Elcxg8+DaRpY\nlvXlpK/+93Ah8HMcKdUlyccne3twpsKQwfceiz5p56E3tgCOrN/XxbuzHiR3xG+d0rVlonk9GOGw\no0ZkGOkFPtCVp5AkPQNpojSdAoeU26g0LeRuixyhKh3eDJaNtC1H7lIolI0ZRd2SJV1akRRNTWfN\npG2n+3M7Q0qJ5vFgGQkUoXQoM6UChk5k7S7HJXXL35gbZvb7rzKycjsTjj+X7NzCr31tM9h3iIZb\nkbbNsIsvIFxXnyTKa9imiep2k92jB4GNG1E9DqM90dZO98MPJdLUwka1gAG9VN6ZEyDR3o4nL4/2\nUJwtu9w07GxlzJgc1m1zKgvPvetI9q6uysHngU0fbWDQ4QPYYZgYW7ZRPv5g8vv3o31XLaFt1Tx2\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FGU4/7It791VV49Lj+nCUt44JWh0Tpp7Nr351CtMn55Hdszu+YkeeWtG6tod6vFmc0C+O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\nw7chVEgV35KKZjuk7+WSa7+f6/IPivXdT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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -331,103 +304,78 @@ "plot_crs = cartopy.crs.Robinson()\n", "data_crs = cartopy.crs.PlateCarree()\n", "\n", - "for layer in h14_data:\n", + "layers = ['SM_layer1_0-7cm', 'SM_layer2_7-28cm', \n", + " 'SM_layer3_28-100cm', 'SM_layer4_100-289cm']\n", + "\n", + "for layer in layers:\n", " fig = plt.figure(figsize=(12, 6))\n", - " ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs)\n", + " ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", " ax.set_title('H14 {:}'.format(layer))\n", - " \n", - " ax.add_feature(cartopy.feature.LAND)\n", - " ax.add_feature(cartopy.feature.OCEAN)\n", - " ax.add_feature(cartopy.feature.COASTLINE)\n", + "\n", + " ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", " ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - " ax.add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - " ax.add_feature(cartopy.feature.RIVERS)\n", + " ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", + "\n", + " sc = ax.pcolormesh(h14_data['lon'], h14_data['lat'], h14_data[layer], zorder=3, \n", + " transform=data_crs)\n", "\n", - " sc = ax.pcolormesh(lons, lats, h14_data[layer], zorder=3, \n", - " transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'))\n", + " cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", "\n", - " cax = fig.add_axes([0.92, 0.1, 0.025, 0.8])\n", - " cbar = fig.colorbar(sc, cax=cax)\n", - " cbar.set_label('Liquid Root Zone Soil Moister')\n", - " plt.show()" + " cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + " cbar.set_label('Liquid Root Zone Soil Moisture')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Reading H16 product" + "### ASCAT SSM NRT (H16, H101, H102, H103)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The products H16, H101, H102, H103 come in the same BUFR format. Since the default filenames are slightly different the following readers should be used:\n", - "\n", - "* H16 - ascat.h_saf.H16img\n", - "* H101 - ascat.h_saf.H101img\n", - "* H102 - ascat.h_saf.H102img\n", - "* H103 - ascat.h_saf.H103img\n", - "* H07 - ascat.h_saf.H07img - discontinued product\n", - "\n", - "Otherwise the format and API is identical.\n", - "\n", - "The ascat repository includes one H16 file with the timestamp 2017-02-20 11:00:00. We can either read this file alone if we know the exact timestamp or iterate over all images on 2017-02-20." + "The products H16, H101, H102, H103 come in the same BUFR format and the default filenames are slightly different." ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\n", - "('The following variables are in this image', ['Estimated Error In Sigma0 At 40 Deg Incidence Angle', 'Slope At 40 Deg Incidence Angle', 'Topographic Complexity', 'Surface Soil Moisture (Ms)', 'Inundation And Wetland Fraction', 'Wet Backscatter', 'Snow Cover', 'Rain Fall Detection', 'Frozen Land Surface Fraction', 'Mean Surface Soil Moisture', 'Estimated Error In Slope At 40 Deg Incidence Angle', 'Soil Moisture Sensitivity', 'Soil Moisture Processing Flag', 'jd', 'Dry Backscatter', 'Soil Moisture Correction Flag', 'Soil Moisture Quality', 'Orbit Number', 'Estimated Error In Surface Soil Moisture', 'Backscatter', 'Direction Of Motion Of Moving Observing Platform'])\n", - "(637,)\n", - "(637,)\n", - "(637,)\n" + "(2016,) (2016,) (2016,)\n" ] } ], "source": [ - "# the reader returns not only the data but also metadata, longitudes and latitudes\n", - "h16_data, metadata, timestamp, lons, lats, time_var = h16_reader.read(datetime(2017, 2, 20, 11, 15, 0))\n", - "\n", - "print(type(h16_data))\n", - "\n", - "# the data is a dictionary, each dictionary key contains the array of one variable\n", - "print(\"The following variables are in this image\", h16_data.keys())\n", - "print h16_data['Surface Soil Moisture (Ms)'].shape\n", + "h16_path = os.path.join(test_data_path, 'h16')\n", + "h16_nrt = AscatNrtBufrFileList(h16_path)\n", + "h16_data = h16_nrt.read(datetime(2017, 2, 20, 11, 15, 0))\n", "\n", - "# it is only a 1D array to plot the data we also need latitude and logitude information\n", - "print(lons.shape)\n", - "print(lats.shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the SSM data as individual points" + "print(h16_data['sm'].shape, h16_data['lon'].shape, h16_data['lat'].shape)" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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GABjc/YhaMhNPL2/c3d1J2LOcw4s/Ijlyg55hXlTSwTX06du73HMwX4iXlydG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nJ+xzyuHt/IP+Pnk5x8kn79elGrln6r0by8fEJCWgEwecrrTJ40+r6irsOHjzHqfyZhaNyY9Jot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\nTkSuQmCC\n", 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\n", "text/plain": [ - "" + "
" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -436,27 +384,22 @@ "data_crs = cartopy.crs.PlateCarree()\n", "\n", "fig = plt.figure(figsize=(7, 6))\n", - "ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs)\n", - "ax.set_title('H16 example - Original data')\n", - " \n", - "blue = '#4b92db'\n", - "ax.background_patch.set_facecolor(blue)\n", - "ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb'))\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", + "ax.set_title('H16 example')\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - "ax.add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - "ax.add_feature(cartopy.feature.RIVERS)\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", "ax.set_extent([130, 175, -10, -42])\n", "\n", - "data = h16_data['Surface Soil Moisture (Ms)']\n", + "sc = ax.scatter(h16_data['lon'], h16_data['lat'], \n", + " c=h16_data['sm'], zorder=3, marker='s', s=2,\n", + " transform=data_crs, vmin=0, vmax=100)\n", "\n", - "sc = ax.scatter(lons, lats, c=data, zorder=3, marker='s', s=2,\n", - " transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'),\n", - " vmin=0, vmax=100)\n", - "\n", - "cax = fig.add_axes([0.92, 0.1, 0.025, 0.8])\n", - "cbar = fig.colorbar(sc, cax=cax)\n", - "cbar.set_label('Degree of Saturation (%)')\n", - "plt.show()" + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Degree of Saturation (%)')" ] }, { @@ -468,23 +411,23 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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Ri1WkpqaRknKG/v1HM2jwxQDYufqgzHmI3fn9Lzc0IoLJBDfffDUODg5V/m6m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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], "source": [ - "import pytesmo.grid.resample as resample\n", - "\n", "# lets resample to a 0.1 degree grid\n", "# define the grid points in latitude and logitude\n", "lats_dim = np.arange(-80, 80, 0.1)\n", @@ -493,59 +436,52 @@ "# make 2d grid out the 1D grid spacings\n", "lons_grid, lats_grid = np.meshgrid(lons_dim, lats_dim)\n", " \n", - "resampled_data = resample.resample_to_grid(h16_data, lons, lats, \n", - " lons_grid, lats_grid)\n", + "resampled_data = resample_to_grid({'sm': h16_data['sm']}, h16_data['lon'], \n", + " h16_data['lat'], lons_grid, lats_grid)\n", "\n", "fig = plt.figure(figsize=(7, 6))\n", - "ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs)\n", + "ax = fig.add_subplot(1, 1, 1, projection=plot_crs)\n", "ax.set_title('H16 example - Resampled to 0.1 x 0.1 grid')\n", - " \n", - "blue = '#4b92db'\n", - "ax.background_patch.set_facecolor(blue)\n", - "ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb'))\n", + "\n", + "ax.add_feature(cartopy.feature.COASTLINE, linestyle='-')\n", "ax.add_feature(cartopy.feature.BORDERS, linestyle=':')\n", - "ax.add_feature(cartopy.feature.LAKES, alpha=0.5)\n", - "ax.add_feature(cartopy.feature.RIVERS)\n", + "ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa')\n", "ax.set_extent([130, 175, -10, -42])\n", "\n", - "data = resampled_data['Surface Soil Moisture (Ms)']\n", - "sc = ax.pcolormesh(lons_grid, lats_grid, data, zorder=3, \n", - " cmap=smcolormaps.load('SWI_ASCAT'),\n", + "sc = ax.pcolormesh(lons_grid, lats_grid, resampled_data['sm'], zorder=3, \n", " vmin=0, vmax=100, transform=data_crs)\n", "\n", - "cax = fig.add_axes([0.92, 0.1, 0.025, 0.8])\n", - "cbar = fig.colorbar(sc, cax=cax)\n", - "cbar.set_label('Degree of Saturation (%)')\n", - "plt.show()" + "cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0,\n", + " 0.02, ax.get_position().height])\n", + "cbar = fig.colorbar(sc, ax=ax, cax=cax)\n", + "cbar.set_label('Degree of Saturation (%)')" ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" + "pygments_lexer": "ipython3", + "version": "3.6.13" } }, "nbformat": 4, diff --git a/docs/read_hsaf_nrt.rst b/docs/read_hsaf_nrt.rst index 96acda0..e613bf1 100644 --- a/docs/read_hsaf_nrt.rst +++ b/docs/read_hsaf_nrt.rst @@ -1,327 +1,276 @@ - -Example H SAF NRT SSM products ------------------------------- +Example H SAF SM NRT products +----------------------------- In this Example we will read and plot images of the H SAF NRT products H08, H14 and H16 using the test images included in the ascat package. -.. code:: ipython2 +.. code:: ipython3 import os from datetime import datetime + import numpy as np + import cartopy + import matplotlib.pyplot as plt + from pytesmo.grid.resample import resample_to_grid + %matplotlib inline - import pytesmo.colormaps.load_cmap as smcolormaps - import ascat.h_saf as h_saf - - test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf') - - h08_path = os.path.join(test_data_path, 'h08') - h14_path = os.path.join(test_data_path, 'h14') - h16_path = os.path.join(test_data_path, 'h16') - - h08_reader = h_saf.H08img(h08_path) - h14_reader = h_saf.H14img(h14_path) - h16_reader = h_saf.H16img(h16_path, month_path_str='') + from ascat.h_saf import H08BufrFileList + from ascat.h_saf import H14GribFileList + from ascat.h_saf import AscatNrtBufrFileList -Reading H08 product -~~~~~~~~~~~~~~~~~~~ - -H08 data has a much higher resolution and comes on a 0.00416 degree -grid. -The sample data included in the ascat package was observed on the same -time as the included H16 product. +.. parsed-literal:: -Instead of read you can also use the daily\_images iterator. + /home/shahn/conda/ascat_conda/envs/ascat_env/lib/python3.6/site-packages/pyresample/bilinear/__init__.py:49: UserWarning: XArray and/or zarr not found, XArrayBilinearResampler won't be available. + warnings.warn("XArray and/or zarr not found, XArrayBilinearResampler won't be available.") + /home/shahn/conda/ascat_conda/envs/ascat_env/lib/python3.6/site-packages/pytesmo/grid/resample.py:30: UserWarning: resampling functions have moved to the repurpose package and will beremoved from pytesmo soon! + warn("resampling functions have moved to the repurpose package and will be" -You just specify a day and it will read all the images that are in your -folder for this day. -This also works for the H16, H101, H102, H103 and H14 reader. +.. code:: ipython3 -.. code:: ipython2 + test_data_path = os.path.join('..', 'tests','ascat_test_data', 'hsaf') - for h08_data, metadata, timestamp, lons, lats, time_var in h08_reader.daily_images(datetime(2010, 5, 1)): - - # this tells you the exact timestamp of the read image - print(timestamp.isoformat()) - print(type(h08_data)) - - # the data is a dictionary, each dictionary key contains the array of one variable - print("The following variables are in this image", h08_data.keys()) - print(h08_data['ssm'].shape) - print(lons.shape) - print(lats.shape) +Disaggregated ASCAT SSM NRT (H08) +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +H08 data has a much higher resolution and comes on a 0.00416 degree +grid. The sample data included in the ascat package was observed on the +same time as the included H16 product. -.. parsed-literal:: +.. code:: ipython3 - 2010-05-01T08:33:01 - - ('The following variables are in this image', ['ssm', 'proc_flag', 'ssm_noise', 'corr_flag']) - (3120, 7680) - (3120, 7680) - (3120, 7680) + h08_path = os.path.join(test_data_path, 'h08') + h08_nrt = H08BufrFileList(h08_path) + h08_data = h08_nrt.read(datetime(2010, 5, 1, 8, 33, 1)) + h08_data -In our case only one image is in the folder so the loop exits after this -image is read. -The data has higher resolution but it already comes as a 2D image. -Let's plot it. +.. parsed-literal:: -.. code:: ipython2 + {'ssm': array([[1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + ..., + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38]]), + 'ssm_noise': array([[1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + ..., + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38]]), + 'proc_flag': array([[1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + ..., + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38], + [1.69999998e+38, 1.69999998e+38, 1.69999998e+38, ..., + 1.69999998e+38, 1.69999998e+38, 1.69999998e+38]]), + 'corr_flag': array([[0., 0., 0., ..., 0., 0., 0.], + [0., 0., 0., ..., 0., 0., 0.], + [0., 0., 0., ..., 0., 0., 0.], + ..., + [0., 0., 0., ..., 0., 0., 0.], + [0., 0., 0., ..., 0., 0., 0.], + [0., 0., 0., ..., 0., 0., 0.]]), + 'lon': array([[13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792], + [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792], + [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792], + ..., + [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792], + [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792], + [13.00208, 13.00625, 13.01042, ..., 44.98958, 44.99375, 44.99792]]), + 'lat': array([[70.99792 , 70.99792 , 70.99792 , ..., 70.99792 , + 70.99792 , 70.99792 ], + [70.99375333, 70.99375333, 70.99375333, ..., 70.99375333, + 70.99375333, 70.99375333], + [70.98958666, 70.98958666, 70.98958666, ..., 70.98958666, + 70.98958666, 70.98958666], + ..., + [58.01041334, 58.01041334, 58.01041334, ..., 58.01041334, + 58.01041334, 58.01041334], + [58.00624667, 58.00624667, 58.00624667, ..., 58.00624667, + 58.00624667, 58.00624667], + [58.00208 , 58.00208 , 58.00208 , ..., 58.00208 , + 58.00208 , 58.00208 ]])} + + + +.. code:: ipython3 - import numpy as np - import cartopy - import matplotlib.pyplot as plt - %matplotlib inline - plot_crs = cartopy.crs.Mercator() data_crs = cartopy.crs.PlateCarree() - - fig = plt.figure(figsize=(8, 10)) - ax = fig.add_axes([0.05, 0.2, 0.6, 0.7], projection=plot_crs) - + fig = plt.figure(figsize=(12, 10)) + ax = fig.add_subplot(1, 1, 1, projection=plot_crs) ax.set_title('H08 example') - blue = '#4b92db' - ax.background_patch.set_facecolor(blue) - ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb')) + ax.add_feature(cartopy.feature.COASTLINE, linestyle='-') ax.add_feature(cartopy.feature.BORDERS, linestyle=':') - ax.add_feature(cartopy.feature.LAKES) - ax.add_feature(cartopy.feature.RIVERS) + ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa') + ax.set_extent([5, 50, 50, 70]) - ax.set_extent([10, 47, 50, 75]) + ssm = np.ma.masked_greater(np.flipud(h08_data['ssm']), 100) + sc = ax.pcolormesh(h08_data['lon'], np.flipud(h08_data['lat']), ssm, zorder=3, + transform=data_crs, vmin=0, vmax=100) - data = np.ma.masked_greater(np.flipud(h08_data['ssm']), 100) - sc = ax.pcolormesh(lons, np.flipud(lats), data, zorder=3, - transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'), - vmin=0, vmax=100) + cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0, + 0.02, ax.get_position().height]) - cax = fig.add_axes([0.65, 0.2, 0.025, 0.7]) - cbar = fig.colorbar(sc, cax=cax) + cbar = fig.colorbar(sc, ax=ax, cax=cax) cbar.set_label('Degree of Saturation (%)') - plt.show() .. image:: read_hsaf_nrt_files/read_hsaf_nrt_7_0.png -Reading a Region Of Interest (ROI) of H08 -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +SM-DAS-2 (H14) +~~~~~~~~~~~~~~ -H08 has a very high resolution and users might want to read only data -for their area of interest. This can be done using the lat\_lon\_bbox -keyword +The SM-DAS-2 (H14) product is a global product on a reduced gaussian +grid with a resolution of approx. 25km. -.. code:: ipython2 +.. code:: ipython3 - # the reader returns not only the data but also metadata and the longitudes and latitudes - h08_roi, metadata, timestamp, lons, lats, time_var = \ - h08_reader.read(datetime(2010, 5, 1, 8, 33, 1), lat_lon_bbox=[60, 70, 15, 25]) - - plot_crs = cartopy.crs.Mercator() - data_crs = cartopy.crs.PlateCarree() - - fig = plt.figure(figsize=(8, 10)) - ax = fig.add_axes([0.05, 0.2, 0.6, 0.7], projection=plot_crs) - # initialize the readers with the path - ax.set_title('H08 ROI example') - - blue = '#4b92db' - ax.background_patch.set_facecolor(blue) - ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb')) - ax.add_feature(cartopy.feature.BORDERS, linestyle=':') - ax.add_feature(cartopy.feature.LAKES) - ax.add_feature(cartopy.feature.RIVERS) - - ax.set_extent([10, 47, 50, 75]) - - data = np.ma.masked_greater(np.flipud(h08_roi['ssm']), 100) - sc = ax.pcolormesh(lons, np.flipud(lats), data, zorder=3, - transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'), - vmin=0, vmax=100) - - cax = fig.add_axes([0.65, 0.2, 0.025, 0.7]) - cbar = fig.colorbar(sc, cax=cax) - cbar.set_label('Degree of Saturation (%)') - plt.show() - - - -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_10_0.png - - -Reading H14 product -~~~~~~~~~~~~~~~~~~~ - -The H14 product is a global product on a reduced gaussian grid with a -resolution of approx. 25km. - -.. code:: ipython2 - - # the reader returns not only the data but also metadata and the longitudes and latitudes - h14_data, metadata, timestamp, lons, lats, time_var = h14_reader.read(datetime(2014, 5, 15)) - - print(type(h14_data)) + h14_path = os.path.join(test_data_path, 'h14') + h14_nrt = H14GribFileList(h14_path) + h14_data = h14_nrt.read(datetime(2014, 5, 15)) # the data is a dictionary, each dictionary key contains the array of one variable print("The following variables are in this image", h14_data.keys()) print(h14_data['SM_layer1_0-7cm'].shape) - print(lons.shape) - print(lats.shape) + print(h14_data['lon'].shape, h14_data['lat'].shape) .. parsed-literal:: - - ('The following variables are in this image', ['SM_layer1_0-7cm', 'SM_layer2_7-28cm', 'SM_layer3_28-100cm', 'SM_layer4_100-289cm']) - (800, 1600) + The following variables are in this image dict_keys(['SM_layer1_0-7cm', 'lat', 'lon', 'SM_layer2_7-28cm', 'SM_layer3_28-100cm', 'SM_layer4_100-289cm']) (800, 1600) - (800, 1600) - + (800, 1600) (800, 1600) -The data comes as a 2D array. If the keyword expand\_grid is set to -False during reader initialization then only 1D arrays would be -returned. -This can be good for working with the data but for plotting the expanded -grid is easier to handle. +Let’s plot all layers in the H14 product -Let's plot all layers in the H14 product - -.. code:: ipython2 +.. code:: ipython3 plot_crs = cartopy.crs.Robinson() data_crs = cartopy.crs.PlateCarree() - for layer in h14_data: + layers = ['SM_layer1_0-7cm', 'SM_layer2_7-28cm', + 'SM_layer3_28-100cm', 'SM_layer4_100-289cm'] + + for layer in layers: fig = plt.figure(figsize=(12, 6)) - ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs) + ax = fig.add_subplot(1, 1, 1, projection=plot_crs) ax.set_title('H14 {:}'.format(layer)) - - ax.add_feature(cartopy.feature.LAND) - ax.add_feature(cartopy.feature.OCEAN) - ax.add_feature(cartopy.feature.COASTLINE) + + ax.add_feature(cartopy.feature.COASTLINE, linestyle='-') ax.add_feature(cartopy.feature.BORDERS, linestyle=':') - ax.add_feature(cartopy.feature.LAKES, alpha=0.5) - ax.add_feature(cartopy.feature.RIVERS) + ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa') - sc = ax.pcolormesh(lons, lats, h14_data[layer], zorder=3, - transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT')) + sc = ax.pcolormesh(h14_data['lon'], h14_data['lat'], h14_data[layer], zorder=3, + transform=data_crs) - cax = fig.add_axes([0.92, 0.1, 0.025, 0.8]) - cbar = fig.colorbar(sc, cax=cax) - cbar.set_label('Liquid Root Zone Soil Moister') - plt.show() - - - -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_16_0.png + cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0, + 0.02, ax.get_position().height]) + + cbar = fig.colorbar(sc, ax=ax, cax=cax) + cbar.set_label('Liquid Root Zone Soil Moisture') -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_16_1.png +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_12_0.png -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_16_2.png +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_12_1.png -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_16_3.png +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_12_2.png -Reading H16 product -~~~~~~~~~~~~~~~~~~~ -The products H16, H101, H102, H103 come in the same BUFR format. Since -the default filenames are slightly different the following readers -should be used: +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_12_3.png -- H16 - ascat.h\_saf.H16img -- H101 - ascat.h\_saf.H101img -- H102 - ascat.h\_saf.H102img -- H103 - ascat.h\_saf.H103img -- H07 - ascat.h\_saf.H07img - discontinued product -Otherwise the format and API is identical. +ASCAT SSM NRT (H16, H101, H102, H103) +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -The ascat repository includes one H16 file with the timestamp 2017-02-20 -11:00:00. We can either read this file alone if we know the exact -timestamp or iterate over all images on 2017-02-20. +The products H16, H101, H102, H103 come in the same BUFR format and the +default filenames are slightly different. -.. code:: ipython2 +.. code:: ipython3 - # the reader returns not only the data but also metadata, longitudes and latitudes - h16_data, metadata, timestamp, lons, lats, time_var = h16_reader.read(datetime(2017, 2, 20, 11, 15, 0)) - - print(type(h16_data)) - - # the data is a dictionary, each dictionary key contains the array of one variable - print("The following variables are in this image", h16_data.keys()) - print h16_data['Surface Soil Moisture (Ms)'].shape + h16_path = os.path.join(test_data_path, 'h16') + h16_nrt = AscatNrtBufrFileList(h16_path) + h16_data = h16_nrt.read(datetime(2017, 2, 20, 11, 15, 0)) - # it is only a 1D array to plot the data we also need latitude and logitude information - print(lons.shape) - print(lats.shape) + print(h16_data['sm'].shape, h16_data['lon'].shape, h16_data['lat'].shape) .. parsed-literal:: - - ('The following variables are in this image', ['Estimated Error In Sigma0 At 40 Deg Incidence Angle', 'Slope At 40 Deg Incidence Angle', 'Topographic Complexity', 'Surface Soil Moisture (Ms)', 'Inundation And Wetland Fraction', 'Wet Backscatter', 'Snow Cover', 'Rain Fall Detection', 'Frozen Land Surface Fraction', 'Mean Surface Soil Moisture', 'Estimated Error In Slope At 40 Deg Incidence Angle', 'Soil Moisture Sensitivity', 'Soil Moisture Processing Flag', 'jd', 'Dry Backscatter', 'Soil Moisture Correction Flag', 'Soil Moisture Quality', 'Orbit Number', 'Estimated Error In Surface Soil Moisture', 'Backscatter', 'Direction Of Motion Of Moving Observing Platform']) - (637,) - (637,) - (637,) + (2016,) (2016,) (2016,) -Plot the SSM data as individual points - -.. code:: ipython2 +.. code:: ipython3 plot_crs = cartopy.crs.Mercator() data_crs = cartopy.crs.PlateCarree() fig = plt.figure(figsize=(7, 6)) - ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs) - ax.set_title('H16 example - Original data') - - blue = '#4b92db' - ax.background_patch.set_facecolor(blue) - ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb')) + ax = fig.add_subplot(1, 1, 1, projection=plot_crs) + ax.set_title('H16 example') + + ax.add_feature(cartopy.feature.COASTLINE, linestyle='-') ax.add_feature(cartopy.feature.BORDERS, linestyle=':') - ax.add_feature(cartopy.feature.LAKES, alpha=0.5) - ax.add_feature(cartopy.feature.RIVERS) + ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa') ax.set_extent([130, 175, -10, -42]) - data = h16_data['Surface Soil Moisture (Ms)'] + sc = ax.scatter(h16_data['lon'], h16_data['lat'], + c=h16_data['sm'], zorder=3, marker='s', s=2, + transform=data_crs, vmin=0, vmax=100) - sc = ax.scatter(lons, lats, c=data, zorder=3, marker='s', s=2, - transform=data_crs, cmap=smcolormaps.load('SWI_ASCAT'), - vmin=0, vmax=100) - - cax = fig.add_axes([0.92, 0.1, 0.025, 0.8]) - cbar = fig.colorbar(sc, cax=cax) + cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0, + 0.02, ax.get_position().height]) + cbar = fig.colorbar(sc, ax=ax, cax=cax) cbar.set_label('Degree of Saturation (%)') - plt.show() -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_21_0.png +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_16_0.png Or resample orbit geometry to a regular 0.1 deg x 0.1 deg grid for plotting -.. code:: ipython2 +.. code:: ipython3 - import pytesmo.grid.resample as resample - # lets resample to a 0.1 degree grid # define the grid points in latitude and logitude lats_dim = np.arange(-80, 80, 0.1) @@ -330,33 +279,28 @@ plotting # make 2d grid out the 1D grid spacings lons_grid, lats_grid = np.meshgrid(lons_dim, lats_dim) - resampled_data = resample.resample_to_grid(h16_data, lons, lats, - lons_grid, lats_grid) + resampled_data = resample_to_grid({'sm': h16_data['sm']}, h16_data['lon'], + h16_data['lat'], lons_grid, lats_grid) fig = plt.figure(figsize=(7, 6)) - ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], projection=plot_crs) + ax = fig.add_subplot(1, 1, 1, projection=plot_crs) ax.set_title('H16 example - Resampled to 0.1 x 0.1 grid') - - blue = '#4b92db' - ax.background_patch.set_facecolor(blue) - ax.add_feature(cartopy.feature.GSHHSFeature(scale='low', facecolor='#efefdb')) + + ax.add_feature(cartopy.feature.COASTLINE, linestyle='-') ax.add_feature(cartopy.feature.BORDERS, linestyle=':') - ax.add_feature(cartopy.feature.LAKES, alpha=0.5) - ax.add_feature(cartopy.feature.RIVERS) + ax.add_feature(cartopy.feature.LAND, facecolor='#aaaaaa') ax.set_extent([130, 175, -10, -42]) - data = resampled_data['Surface Soil Moisture (Ms)'] - sc = ax.pcolormesh(lons_grid, lats_grid, data, zorder=3, - cmap=smcolormaps.load('SWI_ASCAT'), + sc = ax.pcolormesh(lons_grid, lats_grid, resampled_data['sm'], zorder=3, vmin=0, vmax=100, transform=data_crs) - cax = fig.add_axes([0.92, 0.1, 0.025, 0.8]) - cbar = fig.colorbar(sc, cax=cax) + cax = fig.add_axes([ax.get_position().x1+0.01, ax.get_position().y0, + 0.02, ax.get_position().height]) + cbar = fig.colorbar(sc, ax=ax, cax=cax) cbar.set_label('Degree of Saturation (%)') - plt.show() -.. image:: read_hsaf_nrt_files/read_hsaf_nrt_23_0.png +.. image:: read_hsaf_nrt_files/read_hsaf_nrt_18_0.png diff --git a/docs/read_hsaf_nrt_files/read_hsaf_nrt_10_0.png b/docs/read_hsaf_nrt_files/read_hsaf_nrt_10_0.png deleted file mode 100644 index ae4d8c7..0000000 Binary files a/docs/read_hsaf_nrt_files/read_hsaf_nrt_10_0.png and /dev/null differ diff --git a/docs/read_hsaf_nrt_files/read_hsaf_nrt_12_0.png b/docs/read_hsaf_nrt_files/read_hsaf_nrt_12_0.png new file mode 100644 index 0000000..10df992 Binary files /dev/null and b/docs/read_hsaf_nrt_files/read_hsaf_nrt_12_0.png differ diff --git a/docs/read_hsaf_nrt_files/read_hsaf_nrt_12_1.png b/docs/read_hsaf_nrt_files/read_hsaf_nrt_12_1.png new file mode 100644 index 0000000..0f7f084 Binary files /dev/null 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Wien soil moisture time series using the test data included in the ascat package." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "import os\n", - "import matplotlib.pyplot as plt\n", - "import ascat.tuw as tuw\n", - "\n", - "test_data_path = os.path.join('..', 'tests','ascat_test_data', 'tuw')\n", - "sm_path = os.path.join(test_data_path, 'ascat', 'ssm')\n", - "grid_path = os.path.join(test_data_path, 'grid')\n", - "advisory_flags_path = os.path.join(test_data_path, 'advisory_flags')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Read surface soil moisture data nearest to this lon/lat coordinates and plot the data using pandas builtin plot functionality." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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BsoOWy/t84+fInphtWcgcOHcgbpqhNk4CxuSOQfbEbMv1JoLsidl4/ZfXk90MXzB2w1jf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RAAAg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\nOR5ZtgzPvvOdAJJ5wdpCqHTicmGuxX3VqA3RjJ4Z2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ZUhVjyQ6lsSbQOGrsHIgPf7ot/S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rH5VTvvTF/8aEo49Wr7UWA/FcNqdvDn540g8BAFstckoAWHfllQCAoAE55UB9ALc/f3v+hiU6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\nKSMzue62k4GDZvZ54Flgkb6jpFI62ciwCt3fTjKzNcBK4CrgLjM7FngbOIH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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ascat_ssm_reader = tuw.Ascat_SSM(sm_path, grid_path, \n", - " advisory_flags_path=advisory_flags_path)\n", - "lon, lat = 14.3, 45.7\n", - "ssm_data_raw = ascat_ssm_reader.read_ssm(lon, lat)\n", - "ssm_data_raw.plot()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Read the same data but mask observations where the SSF shows frozen and where frozen and snow probabilty are greater than 20% and plot the data using pandas builtin plot functionality." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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b0/oa4qF1rxd54rwsj5HsMzYz5zV+PGe1OQt9M/pqRqnMPSH1xR/zIuczxxYC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\ncQqFQqFQKBQKhUJxGPH/FFBAbn9s2JUAAAAASUVORK5CYII=\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ssm_data_masked = ascat_ssm_reader.read_ssm(lon, lat, mask_ssf=True, \n", - " mask_frozen_prob=20, mask_snow_prob=20)\n", - "ssm_data_masked.plot()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot raw and masked SSM data in one plot to compare them using `pandas` plotting functions." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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RWbu1LBMGYV30xHV21I6PDmHVZ9+pDOoHUt5Pm2fe0MARrPrsOzEypJFF0EHJ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xkkbj2A/QD+gRByCyHko4SQcQBLOeeqQdceAOXGNBUWEYKxdvGjJjuJUxMnxSvcpqTWhFH9s7gP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\ne5FTCk6qwomrBI455himTJnC2LF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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "ssm_data_raw.data['SSM'].plot(ax=ax, label='raw SSM data')\n", - "ssm_data_masked.data['SSM'].plot(ax=ax, label='masked SSM data')\n", - "ax.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/read_tuw_ascat.rst b/docs/read_tuw_ascat.rst deleted file mode 100644 index fc3bd6f..0000000 --- a/docs/read_tuw_ascat.rst +++ /dev/null @@ -1,67 +0,0 @@ - -Example TU Wien Soil Moisture time series ------------------------------------------ - -In this Example we will read and plot TU Wien soil moisture time series -using the test data included in the ascat package. - -.. code:: ipython2 - - import os - import matplotlib.pyplot as plt - import ascat.tuw as tuw - - test_data_path = os.path.join('..', 'tests','ascat_test_data', 'tuw') - sm_path = os.path.join(test_data_path, 'ascat', 'ssm') - grid_path = os.path.join(test_data_path, 'grid') - advisory_flags_path = os.path.join(test_data_path, 'advisory_flags') - -Read surface soil moisture data nearest to this lon/lat coordinates and -plot the data using pandas builtin plot functionality. - -.. code:: ipython2 - - ascat_ssm_reader = tuw.Ascat_SSM(sm_path, grid_path, - advisory_flags_path=advisory_flags_path) - lon, lat = 14.3, 45.7 - ssm_data_raw = ascat_ssm_reader.read_ssm(lon, lat) - ssm_data_raw.plot() - plt.show() - - - -.. image:: read_tuw_ascat_files/read_tuw_ascat_4_0.png - - -Read the same data but mask observations where the SSF shows frozen and -where frozen and snow probabilty are greater than 20% and plot the data -using pandas builtin plot functionality. - -.. code:: ipython2 - - ssm_data_masked = ascat_ssm_reader.read_ssm(lon, lat, mask_ssf=True, - mask_frozen_prob=20, mask_snow_prob=20) - ssm_data_masked.plot() - plt.show() - - - -.. image:: read_tuw_ascat_files/read_tuw_ascat_6_0.png - - -Plot raw and masked SSM data in one plot to compare them using -``pandas`` plotting functions. - -.. code:: ipython2 - - fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - ssm_data_raw.data['SSM'].plot(ax=ax, label='raw SSM data') - ssm_data_masked.data['SSM'].plot(ax=ax, label='masked SSM data') - ax.legend() - plt.show() - - - -.. image:: read_tuw_ascat_files/read_tuw_ascat_8_0.png - - diff --git a/docs/read_tuw_ascat_files/read_tuw_ascat_4_0.png b/docs/read_tuw_ascat_files/read_tuw_ascat_4_0.png deleted file mode 100644 index 86db1c2..0000000 Binary files a/docs/read_tuw_ascat_files/read_tuw_ascat_4_0.png and /dev/null differ diff --git a/docs/read_tuw_ascat_files/read_tuw_ascat_6_0.png b/docs/read_tuw_ascat_files/read_tuw_ascat_6_0.png deleted file mode 100644 index 8ce0f72..0000000 Binary files a/docs/read_tuw_ascat_files/read_tuw_ascat_6_0.png and /dev/null differ diff --git a/docs/read_tuw_ascat_files/read_tuw_ascat_8_0.png b/docs/read_tuw_ascat_files/read_tuw_ascat_8_0.png deleted file mode 100644 index 1b4a337..0000000 Binary files a/docs/read_tuw_ascat_files/read_tuw_ascat_8_0.png and /dev/null differ diff --git a/docs/read_tuw_vod.ipynb b/docs/read_tuw_vod.ipynb deleted file mode 100644 index 7149477..0000000 --- a/docs/read_tuw_vod.ipynb +++ /dev/null @@ -1,101 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Example Vegetation Optical Depth (VOD)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this Example we will read and plot Metop ASCAT Vegetation Optical Depth (VOD) using the test data included in the ascat package." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "import os\n", - "import matplotlib.pyplot as plt\n", - "import ascat.tuw as tuw\n", - "\n", - "test_data_path = os.path.join('..', 'tests','ascat_test_data')\n", - "sm_path = os.path.join(test_data_path, 'tuw', 'ascat', 'vod')\n", - "grid_path = os.path.join(test_data_path, 'hsaf', 'grid')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Read VOD from grid point and plot the data using pandas builtin plot functionality." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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G20d8LT2+UWmo5GQASAiK8CIAWLTR+aoRRmlonUReM/ZMBvHigr3K/S8kwnn/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Y9NUrv1ouU0apBMU4SacDyrRTg7ETTLuBAc6zFCo1IIE7tqsIZDuWtXJYbtBsz6onh5IdiwdblU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\nTXV5KTVa8C8xuOiMZ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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ascat_vod_reader = tuw.AscatVodTs(sm_path, grid_path)\n", - "\n", - "gpi = 2199945\n", - "vod = ascat_vod_reader.read(gpi)\n", - "\n", - "fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n", - "vod.plot(ax=ax)\n", - "ax.set_ylabel('VOD (-)')\n", - "ax.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/read_tuw_vod.rst b/docs/read_tuw_vod.rst deleted file mode 100644 index 6b1f79c..0000000 --- a/docs/read_tuw_vod.rst +++ /dev/null @@ -1,38 +0,0 @@ - -Example Vegetation Optical Depth (VOD) --------------------------------------- - -In this Example we will read and plot Metop ASCAT Vegetation Optical -Depth (VOD) using the test data included in the ascat package. - -.. code:: ipython2 - - import os - import matplotlib.pyplot as plt - import ascat.tuw as tuw - - test_data_path = os.path.join('..', 'tests','ascat_test_data') - sm_path = os.path.join(test_data_path, 'tuw', 'ascat', 'vod') - grid_path = os.path.join(test_data_path, 'hsaf', 'grid') - -Read VOD from grid point and plot the data using pandas builtin plot -functionality. - -.. code:: ipython2 - - ascat_vod_reader = tuw.AscatVodTs(sm_path, grid_path) - - gpi = 2199945 - vod = ascat_vod_reader.read(gpi) - - fig, ax = plt.subplots(1, 1, figsize=(15, 5)) - vod.plot(ax=ax) - ax.set_ylabel('VOD (-)') - ax.legend() - plt.show() - - - -.. image:: read_tuw_vod_files/read_tuw_vod_4_0.png - - diff --git a/docs/read_tuw_vod_files/read_tuw_vod_4_0.png b/docs/read_tuw_vod_files/read_tuw_vod_4_0.png deleted file mode 100644 index 17a866b..0000000 Binary files a/docs/read_tuw_vod_files/read_tuw_vod_4_0.png and /dev/null differ diff --git a/environment.yml b/environment.yml index 7fc99ea..32ed33c 100644 --- a/environment.yml +++ b/environment.yml @@ -8,12 +8,13 @@ dependencies: - netCDF4 - pykdtree - h5py +- xarray - pybufr-ecmwf - pip - pip: + - cadati - requests - tqdm - lxml - - pygeobase>=0.4.0 - pygeogrids>=0.3.0 - pynetcf>=0.2.2 diff --git a/environment_win.yml b/environment_win.yml index 1be422c..2ac9a76 100644 --- a/environment_win.yml +++ b/environment_win.yml @@ -8,11 +8,12 @@ dependencies: - netCDF4 - pykdtree - h5py +- xarray - pip - pip: + - cadati - requests - tqdm - lxml - - pygeobase>=0.4.0 - pygeogrids>=0.3.0 - pynetcf>=0.2.2 diff --git a/setup_env b/setup_env new file mode 100644 index 0000000..79124f0 --- /dev/null +++ b/setup_env @@ -0,0 +1,8 @@ +wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh +bash miniconda.sh -b -p $HOME/conda/ascat_env +export PATH="$HOME/conda/ascat_env/bin:$PATH" +conda config --set always_yes yes --set changeps1 no +conda env create -n ascat_env python=3.6 +conda env update -f environment.yml +source active ascat_env +python setup.py develop diff --git a/src/ascat/base.py b/src/ascat/base.py deleted file mode 100644 index a32c478..0000000 --- a/src/ascat/base.py +++ /dev/null @@ -1,103 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -import os -from datetime import datetime, timedelta - -from pygeobase.io_base import MultiTemporalImageBase - - -class ASCAT_MultiTemporalImageBase(MultiTemporalImageBase): - """ - Base class for the lvl1b and lvl2 MultiTemporal data readers - """ - - def __init__(self, *args, **kwargs): - super(ASCAT_MultiTemporalImageBase, self).__init__(*args, **kwargs) - - def _get_orbit_start_date(self, filename): - """ - Returns the datetime of the file. - - Parameters - ---------- - filename : full name (including the path) of the file - - Returns - ------- - dates : datetime object - datetime from the filename - """ - # if your data comes from the EUMETSAT EO Portal this function can - if self.eo_portal is True: - filename_base = os.path.basename(filename) - fln_spl = filename_base.split('_')[4] - fln_datetime = fln_spl[:-1] - return datetime.strptime(fln_datetime, self.datetime_format) - - else: - orbit_start_str = os.path.basename(filename)[ - self.filename_datetime_format[0]: - self.filename_datetime_format[1]] - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) - - def tstamps_for_daterange(self, startdate, enddate): - """ - Returns the possible timestamps of the given daterange as a datetime - array. - - Parameters - ---------- - startdate : datetime.date or datetime.datetime - start date - enddate : datetime.date or datetime.datetime - end date - - Returns - ------- - dates : list - list of datetimes - """ - file_list = [] - delta_all = enddate - startdate - timestamps = [] - - for i in range(delta_all.days + 1): - timestamp = startdate + timedelta(days=i) - - files = self._search_files( - timestamp, custom_templ=self.day_search_str) - - file_list.extend(sorted(files)) - - for filename in file_list: - timestamps.append(self._get_orbit_start_date(filename)) - - timestamps = [dt for dt in timestamps if ( - dt >= startdate and dt <= enddate)] - return timestamps diff --git a/src/ascat/cgls.py b/src/ascat/cgls.py index a20d191..950d672 100644 --- a/src/ascat/cgls.py +++ b/src/ascat/cgls.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -25,13 +25,17 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -import pynetcf.time_series as netcdf_dataset -import pygeogrids.netcdf as netcdf +""" +CGLS SWI interface. +""" import os import glob import numpy as np +import pynetcf.time_series as netcdf_dataset +import pygeogrids.netcdf as netcdf + class SWI_TS(netcdf_dataset.GriddedNcOrthoMultiTs): @@ -40,30 +44,33 @@ class SWI_TS(netcdf_dataset.GriddedNcOrthoMultiTs): Parameters ---------- - data_path: string + data_path : string path to the netCDF files - parameters: list + parameters : list list of parameters to read from netCDF file - dt: string, optional + dt : string, optional datetime in the filenames of the cells. If not given it is detected from the files in the data_path. - Automatic detection only works if the files follow the CGLS naming convention. - version: string, optional + Automatic detection only works if the files follow the CGLS + naming convention. + version : string, optional version number of the files If not given it is detected from the files in the data_path. - Automatic detection only works if the files follow the CGLS naming convention. - grid_fname: string, optional + Automatic detection only works if the files follow the CGLS + naming convention. + grid_fname : string, optional filename + path of the grid netCDF file, - default is the standard grid file (c_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc) + default is the standard grid file + (c_gls_SWI-STATIC-DGG_201501010000_GLOBE_ASCAT_V3.0.1.nc) in the same folder as the data - read_bulk: boolean, optional + read_bulk : boolean, optional if set to true then a complete 5x5 degree cell will be read at once providing speedup if the complete data is needed. - fname_template: string, optional + fname_template : string, optional Filename template. Has to have three slots for {dt}, {version} and a slot for the {cell} number that is available for further formatting. The has to be without the .nc ending since this is added during reading. - cell_fn: string, optional + cell_fn : string, optional cell number in the fname_template. """ diff --git a/src/ascat/download/connectors.py b/src/ascat/download/connectors.py index 60aa52c..acc53f8 100644 --- a/src/ascat/download/connectors.py +++ b/src/ascat/download/connectors.py @@ -31,7 +31,8 @@ import requests import logging from ftplib import FTP -from datetime import datetime, timedelta +from datetime import datetime +from datetime import timedelta from tqdm import tqdm diff --git a/src/ascat/download/interface.py b/src/ascat/download/interface.py index bc1a158..a5c5d0d 100644 --- a/src/ascat/download/interface.py +++ b/src/ascat/download/interface.py @@ -25,6 +25,9 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +""" +Download interface. +""" import sys import datetime @@ -36,6 +39,19 @@ def parse_date(s): + """ + Convert date string into datetime timestamp. + + Parameters + ---------- + s : str + Date string. + + Returns + ------- + data : datetime + Timestamp. + """ return datetime.datetime.strptime(s, '%Y%m%d') diff --git a/src/ascat/eumetsat.py b/src/ascat/eumetsat.py deleted file mode 100644 index a1b13c8..0000000 --- a/src/ascat/eumetsat.py +++ /dev/null @@ -1,249 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -""" -Readers for data downloaded from EUMETSAT data centre (UMARF) -""" - -from ascat.read_native.bufr import AscatL2SsmBufr -from ascat.read_native.bufr import AscatL2SsmBufrChunked -from ascat.read_native.nc import AscatL2SsmNc - - -class AscatL2Ssm125(AscatL2SsmBufr): - """ - ASCAT A Level2 Soil Moisture at 12.5 km Swath Grid BUFR files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'M0?-ASCA-ASCSMR02-NA-5.0-%Y%m%d*.bfr' - file_search_str = 'M0?-ASCA-ASCSMR02-NA-5.0-{datetime}*.bfr' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (25, 39, '%Y%m%d%H%M%S') - super(AscatL2Ssm125, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - -class AscatL2Ssm125PDU(AscatL2SsmBufr): - """ - ASCAT A Level2 Soil Moisture at 12.5 km Swath Grid PDU BUFR files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_125_ssm_l2.bin' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_125_ssm_l2.bin' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (63, 77, '%Y%m%d%H%M%S') - super(AscatL2Ssm125PDU, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - -class AscatL2Ssm125PDUChunked(AscatL2SsmBufrChunked): - """ - ASCAT A Level2 Soil Moisture at 12.5 km Swath Grid PDU BUFR files from EUMETSAT - in 50 minute chunks. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - chunk_minutes: int, optional - How many minutes should a chunk of data cover. - """ - - def __init__(self, path, month_path_str='', chunk_minutes=100): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_125_ssm_l2.bin' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_125_ssm_l2.bin' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (63, 77, '%Y%m%d%H%M%S') - super(AscatL2Ssm125PDUChunked, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format, - chunk_minutes=chunk_minutes) - - -class AscatL2Ssm250(AscatL2SsmBufr): - """ - ASCAT A Level2 Soil Moisture at 25.0 km Swath Grid BUFR files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'M0?-ASCA-ASCSMO02-NA-5.0-%Y%m%d*.bfr' - file_search_str = 'M0?-ASCA-ASCSMO02-NA-5.0-{datetime}*.bfr' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (25, 39, '%Y%m%d%H%M%S') - super(AscatL2Ssm250, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - -class AscatL2Ssm250PDU(AscatL2SsmBufr): - """ - ASCAT A Level2 Soil Moisture at 25 km Swath Grid PDU BUFR files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_250_ssm_l2.bin' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_250_ssm_l2.bin' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (63, 77, '%Y%m%d%H%M%S') - super(AscatL2Ssm250PDU, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - -class AscatL2Ssm250PDUChunked(AscatL2SsmBufrChunked): - """ - ASCAT A Level2 Soil Moisture at 25 km Swath Grid PDU BUFR files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - chunk_minutes: int, optional - How many minutes should a chunk of data cover. - """ - - def __init__(self, path, month_path_str='', chunk_minutes=100): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_250_ssm_l2.bin' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_250_ssm_l2.bin' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (63, 77, '%Y%m%d%H%M%S') - super(AscatL2Ssm250PDUChunked, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format, - chunk_minutes=chunk_minutes) - - -class AscatL2Ssm125Nc(AscatL2SsmNc): - """ - ASCAT A Level2 Soil Moisture at 12.5 km Swath Grid NetCDF files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_125_ssm_l2.nc' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_125_ssm_l2.nc' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (62, 76, '%Y%m%d%H%M%S') - super(AscatL2Ssm125Nc, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - -class AscatL2Ssm250Nc(AscatL2SsmNc): - """ - ASCAT A Level2 Soil Moisture at 25 km Swath Grid NetCDF files from EUMETSAT - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - If the data is stored in subpaths per year or month then specify the string - that should be used in datetime.datetime.strftime to get the subpath for a file. - Default: '' - """ - - def __init__(self, path, month_path_str=''): - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP?+ASCAT_C_EUM?_%Y%m%d*_250_ssm_l2.nc' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP?+ASCAT_C_EUM?_{datetime}*_250_ssm_l2.nc' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (62, 76, '%Y%m%d%H%M%S') - super(AscatL2Ssm250Nc, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) diff --git a/src/ascat/download/__init__.py b/src/ascat/eumetsat/__init__.py similarity index 100% rename from src/ascat/download/__init__.py rename to src/ascat/eumetsat/__init__.py diff --git a/src/ascat/eumetsat/level1.py b/src/ascat/eumetsat/level1.py new file mode 100644 index 0000000..a521d06 --- /dev/null +++ b/src/ascat/eumetsat/level1.py @@ -0,0 +1,446 @@ +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation +# All rights reserved. + +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# * Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# * Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# * Neither the name of TU Wien, Department of Geodesy and Geoinformation +# nor the names of its contributors may be used to endorse or promote +# products derived from this software without specific prior written +# permission. + +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND +# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +""" +Readers for ASCAT Level 1b data for various file formats. +""" + +import os +from datetime import datetime +from collections import defaultdict + +import numpy as np + +from ascat.read_native.nc import AscatL1bNcFile +from ascat.read_native.hdf5 import AscatL1bHdf5File +from ascat.read_native.bufr import AscatL1bBufrFile +from ascat.read_native.eps_native import AscatL1bEpsFile +from ascat.utils import get_toi_subset, get_roi_subset +from ascat.file_handling import ChronFiles + + +class AscatL1bFile: + + """ + ASCAT Level 1b reader class. + """ + + def __init__(self, filename, file_format=None, mode='r'): + """ + Initialize AscatL1File. + + Parameters + ---------- + filename : str + Filename. + file_format : str, optional + File format: '.nat', '.nc', '.bfr', '.h5' (default: None). + If None file format will be guessed based on the file ending. + """ + self.filename = filename + self.fid = None + self.mode = mode + + if file_format is None: + file_format = get_file_format(self.filename) + + self.file_format = file_format + + if self.file_format in ['.nat', '.nat.gz']: + self.fid = AscatL1bEpsFile(self.filename) + elif self.file_format in ['.nc', '.nc.gz']: + self.fid = AscatL1bNcFile(self.filename) + elif self.file_format in ['.bfr', '.bfr.gz', '.buf', 'buf.gz']: + self.fid = AscatL1bBufrFile(self.filename) + elif self.file_format in ['.h5', '.h5.gz']: + self.fid = AscatL1bHdf5File(self.filename) + else: + raise RuntimeError("ASCAT Level 1b file format unknown") + + def read(self, toi=None, roi=None, generic=True, to_xarray=False): + """ + Read ASCAT Level 1b data. + + Parameters + ---------- + toi : tuple of datetime, optional + Filter data for given time of interest (default: None). + e.g. (datetime(2020, 1, 1, 12), datetime(2020, 1, 2)) + roi : tuple of 4 float, optional + Filter data for region of interest (default: None). + e.g. latmin, lonmin, latmax, lonmax + + Returns + ------- + ds : xarray.Dataset, numpy.ndarray + ASCAT Level 2 data. + """ + ds = self.fid.read(generic=generic, to_xarray=to_xarray) + + if toi: + ds = get_toi_subset(ds, toi) + + if roi: + ds = get_roi_subset(ds, roi) + + return ds + + def read_period(self, dt_start, dt_end, **kwargs): + """ + Read interval. + """ + return self.read(toi=(dt_start, dt_end), **kwargs) + + def close(self): + """ + Close file. + """ + self.fid.close() + + +def get_file_format(filename): + """ + Try to guess the file format from the extension. + + Parameters + ---------- + filename : str + File name. + + Returns + ------- + file_format : str + File format indicator. + """ + if os.path.splitext(filename)[1] == '.gz': + file_format = os.path.splitext(os.path.splitext(filename)[0])[1] + else: + file_format = os.path.splitext(filename)[1] + + return file_format + + +class AscatL1bBufrFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SZR'): + """ + Initialize. + """ + sat_lut = {'A': 2, 'B': 1, 'C': 3} + self.sat = sat_lut[sat] + self.res = res + fn_templ = 'M0{sat}-ASCA-ASC{res}1B0200-NA-9.1-{date}.000000000Z-*-*.bfr' + + super().__init__(path, AscatL1bFile, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'res': self.res} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[29:43], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) + + +class AscatL1bNcFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SZR'): + """ + Initialize. + """ + self.sat = sat + res_lut = {'SZR': '125', 'SZO': '250'} + self.sampling = res_lut[res] + fn_templ = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP{sat}+ASCAT_C_EUMP_{date}_*_eps_o_{sampling}_l1.nc' + + super().__init__(path, AscatL1bFile, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'sampling': self.sampling} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[62:76], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) + + +class AscatL1bEpsFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SZR'): + """ + Initialize. + """ + sat_lut = {'A': 2, 'B': 1, 'C': 3} + self.sat = sat_lut[sat] + + self.res = res + + fn_templ = 'ASCA_{res}_1B_M0{sat}_{date}Z_*_*_*_*.nat' + + super().__init__(path, AscatL1bFile, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'res': self.res} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[16:30], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + if self.res == 'SZF': + merged_data = defaultdict(list) + for antenna in ['lf', 'lm', 'la', 'rf', 'rm', 'ra']: + for d in data: + merged_data[antenna].append(d.pop(antenna)) + merged_data[antenna] = np.hstack(merged_data[antenna]) + else: + merged_data = np.hstack(data) + + return merged_data + + +class AscatL1bHdf5FileList(ChronFiles): + + def __init__(self, path, sat='A'): + """ + Initialize. + """ + sat_lut = {'A': 2, 'B': 1, 'C': 3} + self.sat = sat_lut[sat] + + fn_templ = 'ASCA_SZF_1B_M0{sat}_{date}Z_*_*_*_*.h5' + + super().__init__(path, AscatL1bFile, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[16:30], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + merged_data = defaultdict(list) + + for antenna in ['lf', 'lm', 'la', 'rf', 'rm', 'ra']: + for d in data: + merged_data[antenna].append(d.pop(antenna)) + merged_data[antenna] = np.hstack(merged_data[antenna]) + + return merged_data diff --git a/src/ascat/eumetsat/level2.py b/src/ascat/eumetsat/level2.py new file mode 100644 index 0000000..9104dbe --- /dev/null +++ b/src/ascat/eumetsat/level2.py @@ -0,0 +1,350 @@ +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation +# All rights reserved. + +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# * Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# * Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# * Neither the name of TU Wien, Department of Geodesy and Geoinformation +# nor the names of its contributors may be used to endorse or promote +# products derived from this software without specific prior written +# permission. + +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND +# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +""" +Readers for ASCAT Level 2 data for various file formats. +""" + +import os +import numpy as np +from datetime import datetime + +from ascat.read_native.nc import AscatL2NcFile +from ascat.read_native.bufr import AscatL2BufrFile +from ascat.read_native.eps_native import AscatL2EpsFile +from ascat.utils import get_toi_subset, get_roi_subset +from ascat.file_handling import ChronFiles + + +class AscatL2File: + + """ + ASCAT Level 2 reader class. + """ + + def __init__(self, filename, file_format=None): + """ + Initialize AscatL2File. + + Parameters + ---------- + filename : str + Filename. + file_format : str, optional + File format: '.nat', '.nc', '.bfr', '.h5' (default: None). + If None file format will be guessed based on the file ending. + """ + self.filename = filename + self.fid = None + + if file_format is None: + file_format = get_file_format(self.filename) + + self.file_format = file_format + + if self.file_format in ['.nat', '.nat.gz']: + self.fid = AscatL2EpsFile(self.filename) + elif self.file_format in ['.nc', '.nc.gz']: + self.fid = AscatL2NcFile(self.filename) + elif self.file_format in ['.bfr', '.bfr.gz', '.buf', 'buf.gz']: + self.fid = AscatL2BufrFile(self.filename) + else: + raise RuntimeError("ASCAT Level 2 file format unknown") + + def read(self, toi=None, roi=None, generic=True, to_xarray=False): + """ + Read ASCAT Level 2 data. + + Parameters + ---------- + toi : tuple of datetime, optional + Filter data for given time of interest (default: None). + roi : tuple of 4 float, optional + Filter data for region of interest (default: None). + e.g. latmin, lonmin, latmax, lonmax + + Returns + ------- + ds : xarray.Dataset, numpy.ndarray + ASCAT Level 2 data. + """ + ds = self.fid.read(generic=generic, to_xarray=to_xarray) + + if toi: + ds = get_toi_subset(ds, toi) + + if roi: + ds = get_roi_subset(ds, roi) + + return ds + + def read_period(self, dt_start, dt_end, **kwargs): + """ + Read interval. + """ + return self.read(toi=(dt_start, dt_end), **kwargs) + + def close(self): + """ + Close file. + """ + self.fid.close() + + +def get_file_format(filename): + """ + Try to guess the file format from the extension. + + Parameters + ---------- + filename : str + File name. + + Returns + ------- + file_format : str + File format indicator. + """ + if os.path.splitext(filename)[1] == '.gz': + file_format = os.path.splitext(os.path.splitext(filename)[0])[1] + else: + file_format = os.path.splitext(filename)[1] + + return file_format + + +class AscatL2BufrFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SMR'): + """ + Initialize. + """ + sat_lut = {'A': 2, 'B': 1, 'C': 3} + self.sat = sat_lut[sat] + self.res = res + fn_templ = 'M0{sat}-ASCA-ASC{res}*-*-*-{date}.000000000Z-*-*.bfr' + + super().__init__(path, AscatL2File, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'res': self.res} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[25:39], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) + + +class AscatL2NcFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SMR'): + """ + Initialize. + """ + self.sat = sat + res_lut = {'SMR': '125', 'SMO': '250'} + self.sampling = res_lut[res] + fn_templ = 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOP{sat}+ASCAT_C_EUMP_{date}_*_eps_o_{sampling}_ssm_l2.nc' + + super().__init__(path, AscatL2File, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'sampling': self.sampling} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[62:76], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) + + +class AscatL2EpsFileList(ChronFiles): + + def __init__(self, path, sat='A', res='SMR'): + """ + Initialize. + """ + sat_lut = {'A': 2, 'B': 1, 'C': 3} + self.sat = sat_lut[sat] + self.res = res + fn_templ = 'ASCA_{res}_02_M0{sat}_{date}Z_*_*_*_*.nat' + + super().__init__(path, AscatL2File, fn_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H%M%S'), + 'sat': self.sat, 'res': self.res} + fn_write_fmt = None + sf_read_fmt = None + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[16:30], + '%Y%m%d%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) diff --git a/src/ascat/file_handling.py b/src/ascat/file_handling.py new file mode 100644 index 0000000..166edb0 --- /dev/null +++ b/src/ascat/file_handling.py @@ -0,0 +1,851 @@ +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation +# All rights reserved. + +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# * Redistributions of source code must retain the above copyright notice, +# this list of conditions and the following disclaimer. +# * Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# * Neither the name of TU Wien, Department of Geodesy and Geoinformation +# nor the names of its contributors may be used to endorse or promote +# products derived from this software without specific prior written +# permission. + +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND +# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; +# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, +# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR +# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF +# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + +""" +File search methods. +""" + +import os +import abc +import glob +import warnings +from datetime import timedelta +from datetime import datetime + +import numpy as np + + +class FilenameTemplate: + + """ + FilenameTemplate class. + """ + + def __init__(self, root_path, fn_templ, sf_templ=None): + """ + Initialize root path, filename pattern and optional subfolder pattern. + + Parameters + ---------- + root_path : str + Root path. + fn_templ : str + Filename (glob) pattern. + e.g. '{date}_*.{suffix}' + sf_templ : dict, optional + Subfolder pattern defined as dictionary (default: None). + Keys represent unique meta names of subfolders and values define + real folder names and/or (glob) pattern. + e.g. {'variable': '*', 'tile': 'EN012*'} + """ + self.root_path = root_path + self.fn_templ = fn_templ + self.sf_templ = sf_templ + + @property + def template(self): + """ + Name property. + """ + if self.sf_templ is None: + filename = os.path.join(self.root_path, self.fn_templ) + else: + filename = os.path.join( + self.root_path, *list(self.sf_templ.values()), self.fn_templ) + + return filename + + def build_filename(self, fn_fmt, sf_fmt=None): + """ + Create filename from format dictionary. + + Parameters + ---------- + fn_fmt : dict + Filename format applied on filename pattern (fn_pattern). + e.g. fn_pattern = '{date}*.{suffix}' + with fn_format_dict = {'date': '20000101', 'suffix': 'nc'} + returns '20000101*.nc' + fmt : dict of dicts + Format dictionary for subfolders. Each subfolder contains + a dictionary defining the format of the folder name. + e.g. sf_pattern = {'years': {year}, 'months': {month}} + with format_dict = {'years': {'year': '2000'}, + 'months': {'month': '02'}} + returns ['2000', '02'] + + Returns + ------- + filename : str + Filename with format_dict applied. + """ + fn = self.build_basename(fn_fmt) + + if sf_fmt is None: + filename = os.path.join(self.root_path, fn) + else: + sf = self.build_subfolder(sf_fmt) + filename = os.path.join(self.root_path, *sf, fn) + + return filename + + def build_basename(self, fmt): + """ + Create file basename from format dictionary. + + Parameters + ---------- + fmt : dict + Filename format applied on filename pattern (fn_pattern). + e.g. fn_pattern = '{date}*.{suffix}' + with fmt = {'date': '20000101', 'suffix': 'nc'} + returns '20000101*.nc' + + Returns + ------- + filename : str + Filename with format_dict applied. + """ + return self.fn_templ.format(**fmt) + + def build_subfolder(self, fmt): + """ + Create subfolder path from format dictionary. + + Parameters + ---------- + fmt : dict of dicts + Format dictionary for subfolders. Each subfolder contains + a dictionary defining the format of the folder name. + e.g. sf_pattern = {'years': {year}, 'months': {month}} + with format_dict = {'years': {'year': '2000'}, + 'months': {'month': '02'}} + returns ['2000', '02'] + + Returns + ------- + subfolder : list of str + Subfolder with format_dict applied. + """ + subfolder = [] + + if self.sf_templ is not None: + for name, v in self.sf_templ.items(): + if fmt is not None: + if name in fmt: + subfolder.append(self.sf_templ[name].format( + **fmt[name])) + else: + subfolder.append(self.sf_templ[name]) + else: + subfolder.append(self.sf_templ[name]) + + return subfolder + + +class FileSearch: + + """ + FileSearch class. + """ + + def __init__(self, root_path, fn_pattern, sf_pattern=None): + """ + Initialize root path, filename pattern and optional subfolder pattern. + + Parameters + ---------- + root_path : str + Root path. + fn_pattern : str + Filename (glob) pattern. + e.g. '{date}_*.{suffix}' + sf_pattern : dict, optional + Subfolder pattern defined as dictionary (default: None). + Keys represent unique meta names of subfolders and values define + real folder names and/or (glob) pattern. + e.g. {'variable': '*', 'tile': 'EN012*'} + """ + self.file_templ = FilenameTemplate(root_path, fn_pattern, sf_pattern) + + def search(self, fn_fmt, sf_fmt=None, recursive=False): + """ + Search filesystem for given pattern returning list. + + Parameters + ---------- + fn_fmt : dict + Filename format dictionary. + sf_fmt : dict of dicts, optional + Format dictionary for subfolders (default: None). + recursive : bool, optional + If recursive is true, the pattern "**" will match any files and + zero or more directories, subdirectories and symbolic links to + directories (default: False). + + Returns + ------- + filenames : list of str + Return a possibly-empty list of path/file names that match. + """ + return glob.glob(self.file_templ.build_filename(fn_fmt, sf_fmt), + recursive=recursive) + + def isearch(self, fn_fmt, sf_fmt=None, recursive=False): + """ + Search filesystem for given pattern returning iterator. + + Parameters + ---------- + fn_fmt : dict + Filename format dictionary. + sf_fmt : dict of dicts, optional + Format dictionary for subfolders (default: None). + recursive : bool, optional + If recursive is true, the pattern "**" will match any files and + zero or more directories, subdirectories and symbolic links to + directories (default: False). + + Returns + ------- + filenames : iterator + Iterator which yields the same values as search() without + actually storing them all simultaneously. + """ + return glob.iglob(self.file_templ.build_filename(fn_fmt, sf_fmt), + recursive=recursive) + + def create_search_func(self, func, recursive=False): + """ + Create custom search function returning it. + + Parameters + ---------- + func : function + Search function with its own args/kwargs returning + a filename format dictionary and subfolder format dictionary + depending on the passed arguments. + recursive : bool, optional + If recursive is true, the pattern "**" will match any files and + zero or more directories, subdirectories and symbolic links to + directories (default: False). + + Returns + ------- + custom_search : function + Custom search function returning a possibly-empty list + of path/file names that match. + """ + def custom_search(*args, **kwargs): + fn_fmt, sf_fmt = func(*args, **kwargs) + return self.search(fn_fmt, sf_fmt, recursive=recursive) + + return custom_search + + def create_isearch_func(self, func, recursive=False): + """ + Create custom search function returning it. + + Parameters + ---------- + func : function + Search function with its own args/kwargs returning + a filename format dictionary and subfolder format dictionary + depending on the passed arguments. + recursive : bool, optional + If recursive is true, the pattern "**" will match any files and + zero or more directories, subdirectories and symbolic links to + directories (default: False). + + Returns + ------- + custom_search : function + Custom search function returning an iterator of path/file names + that match. + """ + def custom_search(*args, **kwargs): + fn_fmt, sf_fmt = func(*args, **kwargs) + return self.isearch(fn_fmt, sf_fmt, recursive=recursive) + + return custom_search + + +class MultiFileHandler(metaclass=abc.ABCMeta): + + """ + MultiFileHandler class. + """ + + def __init__(self, root_path, cls, fn_templ, sf_templ=None, + cls_kwargs=None, err=False): + """ + Initialize MultiFileHandler. + + Parameters + ---------- + root_path : str + Root path. + cls : class + Class reading/writing files. + fn_templ : str + Filename template (e.g. '{date}_ascat.nc'). + sf_templ : dict, optional + Subfolder template defined as dictionary (default: None). + cls_kwargs : dict, optional + Class keyword arguments (default: None). + err : bool, optional + Set true if error should be re-raised instead of + reporting a warning. + Default: False + """ + self.root_path = root_path + self.cls = cls + self.ft = FilenameTemplate(root_path, fn_templ, sf_templ) + self.fid = None + self.err = err + + if cls_kwargs is None: + self.cls_kwargs = {} + else: + self.cls_kwargs = cls_kwargs + + def __enter__(self): + """ + Context manager initialization. + """ + return self + + def __exit__(self, exc_type, exc_value, traceback): + """ + Exit the runtime context related to this object. The file will be + closed. The parameters describe the exception that caused the + context to be exited. + """ + self._close() + + def _open(self, filename): + """ + Open file, i.e. create io class instance. + + Parameters + ---------- + filename : str + Filename. + """ + self._close() + + try: + self.fid = self.cls(filename, **self.cls_kwargs) + except IOError: + self.fid = None + if self.err: + raise + else: + warnings.warn("IOError: {}".format(filename)) + + def _close(self): + """ + Try closing file. + """ + if self.fid is not None and hasattr(self.fid, 'close'): + self.fid.close() + self.fid = None + + @abc.abstractmethod + def _fmt(*args, **kwargs): + """ + Filename format and subfolder format used to read/write + individual files. + + Returns + ------- + fn_read_fmt : dict + Filename format. + sf_read_fmt : dict + Subfolder format. + fn_write_fmt : dict + Filename format. + sf_write_fmt : dict + Subfolder format. + """ + return + + def read(self, *fmt_args, fmt_kwargs=None, cls_kwargs=None): + """ + Read data. + + Parameters + ---------- + fmt_args : tuple + Format arguments. + fmt_kwargs : dict, optional + Format keywords (Default: None). + cls_kwargs : dict, optional + Class keywords (Default: None). + + Returns + ------- + data : dict, numpy.ndarray + Data stored in file. + """ + if fmt_kwargs is None: + fmt_kwargs = {} + + if cls_kwargs is None: + cls_kwargs = {} + + fn_read_fmt, sf_read_fmt, _, _ = self._fmt(*fmt_args, **fmt_kwargs) + search_filename = self.ft.build_filename(fn_read_fmt, sf_read_fmt) + filename = glob.glob(search_filename) + + data = None + if len(filename) == 0: + msg = 'File not found: {}'.format(search_filename) + if self.err: + raise IOError(msg) + else: + warnings.warn(msg) + elif len(filename) > 1: + msg = 'Multiple files found' + if self.err: + raise RuntimeError(msg) + else: + warnings.warn(msg) + else: + data = self.read_file(filename[0], cls_kwargs) + + return data + + def write(self, data, *fmt_args, fmt_kwargs=None, cls_kwargs=None): + """ + Write data. + + Parameters + ---------- + data : dict, numpy.ndarray + Data to write. + fmt_args : tuple + Format arguments. + fmt_kwargs : dict, optional + Format keywords (Default: None). + cls_kwargs : dict, optional + Class keywords (Default: None). + """ + if fmt_kwargs is None: + fmt_kwargs = {} + + if cls_kwargs is None: + cls_kwargs = {} + + _, _, fn_write_fmt, sf_write_fmt = self._fmt(*fmt_args, **fmt_kwargs) + filename = self.ft.build_filename(fn_write_fmt, sf_write_fmt) + self.write_file(data, filename, cls_kwargs=cls_kwargs) + + def read_file(self, filename, cls_kwargs=None): + """ + Read data for given filename. + + Parameters + ---------- + filename : str + Filename. + """ + self._open(filename) + data = self.fid.read(**cls_kwargs) + + return data + + def write_file(self, data, filename, cls_kwargs=None): + """ + Write data for given filename. + + Parameters + ---------- + filename : str + Filename. + """ + if not os.path.exists(os.path.dirname(filename)): + os.makedirs(os.path.dirname(filename)) + + self._open(filename) + self.fid.write(data, **cls_kwargs) + + def search(self, fn_search_pattern, sf_search_pattern=None, + custom_fn_templ=None, custom_sf_templ=None): + """ + Search files for given root path and filename/folder pattern. + + Returns + ------- + filenames : list of str + Filenames. + """ + if custom_fn_templ is None: + fn_templ = self.ft.fn_templ + else: + fn_templ = custom_fn_templ + + if custom_sf_templ is None: + sf_templ = self.ft.sf_templ + else: + sf_templ = custom_sf_templ + + self.fs = FileSearch(self.root_path, fn_templ, sf_templ) + filenames = self.fs.search(fn_search_pattern, sf_search_pattern) + + return sorted(filenames, reverse=True) + + +class ChronFiles(MultiFileHandler): + + """ + Managing chronological files with a date field in the filename. + """ + + def _parse_date(self, filename): + """ + Parse datetime from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + timestamp : datetime + File timestamp. + """ + raise NotImplementedError + + def _merge_data(self, data): + """ + Merge datasets after reading period. Needs to be overwritten + by child class, otherwise data is returned as is. + + Parameters + ---------- + data : list + Data. + + Returns + ------- + data : list + Merged data. + """ + return data + + def search_date(self, timestamp, date_str='%Y%m%d*', date_field='date', + return_date=False): + """ + Search files for given date. + + Parameters + ---------- + timestamp : datetime + Search date. + date_str : str, optional + Search date string (default: %Y%m%d). + date_field : str, optional + Search field name (default: date) + return_date : bool, optional + Return dates parsed from filenames (default: False). + + Returns + ------- + filenames : list of str + Filenames. + dates : list of datetime + Parsed dates of filenames only returned if return_date=True. + """ + fn_read_fmt, sf_read_fmt, _, _ = self._fmt(timestamp) + fn_read_fmt[date_field] = timestamp.strftime(date_str) + + fs = FileSearch(self.root_path, self.ft.fn_templ, self.ft.sf_templ) + filenames = sorted(fs.search(fn_read_fmt, sf_read_fmt)) + + if return_date: + dates = [] + for filename in filenames: + dates.append(self._parse_date(filename)) + return filenames, dates + else: + return filenames + + def search_period(self, dt_start, dt_end, dt_delta=timedelta(days=1)): + """ + Search files for time period. + + Parameters + ---------- + dt_start : datetime + Start datetime. + dt_end : datetime + End datetime. + dt_delta : timedelta, optional + Time delta used to jump through search date. + + Returns + ------- + filenames : list of str + Filenames. + """ + filenames = [] + + for dt_cur in np.arange(dt_start, dt_end, dt_delta).astype(datetime): + files, dates = self.search_date(dt_cur, return_date=True) + for f, dt in zip(files, dates): + if files not in filenames and dt >= dt_start and dt <= dt_end: + filenames.append(f) + + return filenames + + def read_period(self, dt_start, dt_end, dt_delta=timedelta(days=1), + dt_buffer=timedelta(days=1), **kwargs): + """ + Read data for given interval. + + Parameters + ---------- + dt_start : datetime + Start datetime. + dt_end : datetime + End datetime. + dt_delta : timedelta, optional + Time delta used to jump through search date. + dt_buffer : timedelta, optional + Search buffer used to find files which could possibly contain + data but would be left out because of dt_start. + + Returns + ------- + data : dict, numpy.ndarray + Data stored in file. + """ + filenames = self.search_period(dt_start-dt_buffer, dt_end, dt_delta) + + data = [] + + for filename in filenames: + self._open(filename) + d = self.fid.read_period(dt_start, dt_end, **kwargs) + if d is not None: + data.append(d) + + if data: + data = self._merge_data(data) + + return data + + +class Csv: + + """ + Read and write CSV file. + """ + + def __init__(self, filename, mode='r'): + """ + Initialize Csv + + Parameters + ---------- + filename : str + Filename + mode : str, optional + File opening mode. + """ + self.filename = filename + self.mode = mode + + def header2dtype(self, header): + """ + Convert header string to dtype info. + + Parameters + ---------- + header : str + Header string with dtype info. + + Returns + ------- + dtype : numpy.dtype + Data type. + """ + dtype_list = [] + for substr in header.split('(')[2:]: + d = [] + for substr2 in substr.split(','): + if substr2.endswith(')'): + substr2 = substr2[:-1] + if substr2.endswith('\n'): + substr2 = substr2[:-4] + substr2 = substr2.strip() + substr2 = substr2.strip("'") + if substr2 == '': + continue + d.append(substr2) + dtype_list.append(tuple(d)) + + return np.dtype(dtype_list) + + def read(self): + """ + Read data from CSV file. + + Parameters + ---------- + timestamp : datetime + Time stamp. + """ + with open(self.filename) as fid: + header = fid.readline() + dtype = self.header2dtype(header) + data = np.loadtxt(fid, dtype) + + return data + + def read_period(self, dt_start, dt_end): + """ + Read subset data from CSV file for given interval. + + Parameters + ---------- + interval : (datetime, datetime) + Time interval to extract data. + + Returns + ------- + data : numpy.ndarray + Data. + """ + data = self.read() + + subset = ((data['date'] >= np.datetime64(dt_start)) & + (data['date'] <= np.datetime64(dt_end))) + + if np.sum(subset) > 0: + data = data[subset] + else: + data = None + + return data + + def write(self, data): + """ + Write data to CSV file. + + Parameters + ---------- + data : numpy.ndarray + Data. + """ + header = data.dtype.__repr__() + np.savetxt(self.filename, data, fmt='%s', header=header) + + +class CsvFiles(ChronFiles): + + """ + Write CSV files. + """ + + def __init__(self, root_path): + """ + Initialize CvsFileRW. + + Parameters + ---------- + root_path : str + Root path. + """ + fn_templ = 'prefix_{date}_{now}_postfix.csv' + sf_templ = {'Y': '{year}', 'M': '{month}'} + + super().__init__(root_path, Csv, fn_templ, sf_templ=sf_templ) + + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. + + Parameters + ---------- + timestamp : datetime + Time stamp. + + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d_%H%M%S'), + 'now': '*'} + + fn_write_fmt = {'date': timestamp.strftime('%Y%m%d_%H%M%S'), + 'now': datetime.now().strftime('%Y%m%d_%H%M%S')} + + sf_read_fmt = {'Y': {'year': timestamp.strftime('%Y')}, + 'M': {'month': timestamp.strftime('%m')}} + + sf_write_fmt = sf_read_fmt + + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + + def _parse_date(self, filename): + """ + Parse date from filename. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[7:22], + '%Y%m%d_%H%M%S') + + def _merge_data(self, data): + """ + Merge data. + + Parameters + ---------- + data : list + List of array. + + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) diff --git a/src/ascat/h_saf.py b/src/ascat/h_saf.py index 08040b3..9dca5a3 100644 --- a/src/ascat/h_saf.py +++ b/src/ascat/h_saf.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -25,99 +25,73 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -import sys +""" +Readers for H SAF soil moisture products. +""" + import os +import glob import warnings -from gzip import GzipFile -from tempfile import NamedTemporaryFile -from datetime import datetime, timedelta +from datetime import datetime +from collections import defaultdict import numpy as np + try: import pygrib except ImportError: warnings.warn( 'pygrib can not be imported GRIB files (H14) can not be read.') -from pygeobase.io_base import ImageBase -from pygeobase.io_base import MultiTemporalImageBase -from pygeobase.object_base import Image - -import ascat.read_native.bufr as bufr_reader -from ascat.read_native.bufr import AscatL2SsmBufr -from ascat.read_native.cdr import AscatNc +from ascat.utils import tmp_unzip +from ascat.file_handling import ChronFiles +from ascat.read_native.bufr import BUFRReader +from ascat.eumetsat.level2 import AscatL2File +from ascat.read_native.cdr import AscatGriddedNcTs -class H08Single(ImageBase): +class H08Bufr: - def read(self, timestamp=None, lat_lon_bbox=None): + def __init__(self, filename): """ - Read specific image for given datetime timestamp. + Initialize H08Bufr. Parameters ---------- - filename : string - filename - timestamp : datetime.datetime - exact observation timestamp of the image that should be read - lat_lon_bbox : list, optional - list of lat,lon cooridnates of bounding box - [lat_min, lat_max, lon_min, lon_max] + filename : str + Filename. + """ + if os.path.splitext(filename)[1] == '.gz': + self.filename = tmp_unzip(filename) + else: + self.filename = filename + + def read(self): + """ + Read file. Returns ------- - data : dict or None - dictionary of numpy arrays that hold the image data for each - variable of the dataset, if no data was found None is returned - metadata : dict - dictionary of numpy arrays that hold the metadata - timestamp : datetime.datetime - exact timestamp of the image - lon : numpy.array or None - array of longitudes, if None self.grid will be assumed - lat : numpy.array or None - array of latitudes, if None self.grid will be assumed - time_var : string or None - variable name of observation times in the data dict, if None all - observations have the same timestamp - """ - zipped = False - if os.path.splitext(self.filename)[1] == '.gz': - zipped = True - - # for zipped files use an unzipped temporary copy - if zipped: - with NamedTemporaryFile(delete=False) as tmp_fid: - with GzipFile(self.filename) as gz_fid: - tmp_fid.write(gz_fid.read()) - filename = tmp_fid.name - else: - filename = self.filename + data : numpy.ndarray + H08 data. + """ + data = defaultdict(list) - with bufr_reader.BUFRReader(filename) as bufr: + with BUFRReader(self.filename) as bufr: lons = [] ssm = [] ssm_noise = [] ssm_corr_flag = [] ssm_proc_flag = [] - data_in_bbox = True for i, message in enumerate(bufr.messages()): if i == 0: # first message is just lat, lon extent # check if any data in bbox - if lat_lon_bbox is not None: - lon_min, lon_max = message[0, 2], message[0, 3] - lat_min, lat_max = message[0, 4], message[0, 5] - if (lat_lon_bbox[0] > lat_max or - lat_lon_bbox[1] < lat_min or - lat_lon_bbox[2] > lon_max or - lat_lon_bbox[3] < lon_min): - data_in_bbox = False - break - - elif data_in_bbox: + # lon_min, lon_max = message[0, 2], message[0, 3] + lat_min, lat_max = message[0, 4], message[0, 5] + else: # first 5 elements are there only once, after that, # 4 elements are repeated till the end of the array # these 4 are ssm, ssm_noise, ssm_corr_flag and @@ -132,355 +106,242 @@ def read(self, timestamp=None, lat_lon_bbox=None): ssm_corr_flag.append(message[:, 6::4]) ssm_proc_flag.append(message[:, 7::4]) - if zipped: - os.remove(filename) - - if data_in_bbox: - - ssm = np.rot90(np.vstack(ssm)).astype(np.float32) - ssm_noise = np.rot90(np.vstack(ssm_noise)).astype(np.float32) - ssm_corr_flag = np.rot90( - np.vstack(ssm_corr_flag)).astype(np.float32) - ssm_proc_flag = np.rot90( - np.vstack(ssm_proc_flag)).astype(np.float32) - lats_dim = np.linspace(lat_max, lat_min, ssm.shape[0]) - lons_dim = np.concatenate(lons) - - data = {'ssm': ssm, - 'ssm_noise': ssm_noise, - 'proc_flag': ssm_proc_flag, - 'corr_flag': ssm_corr_flag - } - - # if there are is a gap in the image it is not a 2D array in - # lon, lat space but has a jump in latitude or longitude - # detect a jump in lon or lat spacing - - lon_jump_ind = np.where(np.diff(lons_dim) > 0.00418)[0] - - if lon_jump_ind.size > 1: - print("More than one jump in longitude") - - if lon_jump_ind.size == 1: - lon_jump_ind = lon_jump_ind[0] - diff_lon_jump = np.abs( - lons_dim[lon_jump_ind] - lons_dim[lon_jump_ind + 1]) - missing_elements = int(np.round(diff_lon_jump / 0.00416666)) - missing_lons = np.linspace(lons_dim[lon_jump_ind], - lons_dim[lon_jump_ind + 1], - missing_elements, - endpoint=False) - - # fill up longitude dimension to full grid - lons_dim = np.concatenate([lons_dim[:lon_jump_ind], - missing_lons, - lons_dim[lon_jump_ind + 1:]]) - - # fill data with NaN values - empty = np.empty((lats_dim.shape[0], missing_elements)) - empty.fill(1e38) - for key in data: - data[key] = np.concatenate( - [data[key][:, :lon_jump_ind], - empty, data[key][:, lon_jump_ind + 1:]], axis=1) - - lat_jump_ind = np.where(np.diff(lats_dim) > 0.00418)[0] - - if lat_jump_ind.size > 1: - print("More than one jump in latitude") - - if lat_jump_ind.size == 1: - diff_lat_jump = np.abs( - lats_dim[lat_jump_ind] - lats_dim[lat_jump_ind + 1]) - missing_elements = np.round(diff_lat_jump / 0.00416666) - missing_lats = np.linspace(lats_dim[lat_jump_ind], - lats_dim[lat_jump_ind + 1], - missing_elements, - endpoint=False) - - # fill up longitude dimension to full grid - lats_dim = np.concatenate( - [lats_dim[:lat_jump_ind], missing_lats, - lats_dim[lat_jump_ind + 1:]]) - # fill data with NaN values - empty = np.empty((missing_elements, lons_dim.shape[0])) - empty.fill(1e38) - for key in data: - data[key] = np.concatenate( - [data[key][:lat_jump_ind, :], empty, - data[key][lat_jump_ind + 1:, :]], axis=0) - - lons, lats = np.meshgrid(lons_dim, lats_dim) - # only return data in bbox - if lat_lon_bbox is not None: - data_ind = np.where((lats >= lat_lon_bbox[0]) & - (lats <= lat_lon_bbox[1]) & - (lons >= lat_lon_bbox[2]) & - (lons <= lat_lon_bbox[3])) - # indexing returns 1d array - # get shape of lats_dim and lons_dim to be able to reshape - # the 1d arrays to the correct 2d shapes - lats_dim_shape = \ - np.where((lats_dim >= lat_lon_bbox[0]) & - (lats_dim <= lat_lon_bbox[1]))[0].shape[0] - - lons_dim_shape = \ - np.where((lons_dim >= lat_lon_bbox[2]) & - (lons_dim <= lat_lon_bbox[3]))[0].shape[0] - - lons = lons[data_ind].reshape(lats_dim_shape, lons_dim_shape) - lats = lats[data_ind].reshape(lats_dim_shape, lons_dim_shape) - for key in data: - data[key] = data[key][data_ind].reshape( - lats_dim_shape, lons_dim_shape) - - else: - lons = None - lats = None - data = None - - return Image(lons, lats, data, {}, timestamp) - - def write(self, data): - raise NotImplementedError() - - def flush(self): - pass + ssm = np.rot90(np.vstack(ssm)).astype(np.float32) + ssm_noise = np.rot90(np.vstack(ssm_noise)).astype(np.float32) + ssm_corr_flag = np.rot90( + np.vstack(ssm_corr_flag)).astype(np.float32) + ssm_proc_flag = np.rot90( + np.vstack(ssm_proc_flag)).astype(np.float32) + lats_dim = np.linspace(lat_max, lat_min, ssm.shape[0]) + lons_dim = np.concatenate(lons) + + data = {'ssm': ssm, 'ssm_noise': ssm_noise, + 'proc_flag': ssm_proc_flag, 'corr_flag': ssm_corr_flag} + + # if there are is a gap in the image it is not a 2D array in + # lon, lat space but has a jump in latitude or longitude + # detect a jump in lon or lat spacing + + lon_jump_ind = np.where(np.diff(lons_dim) > 0.00418)[0] + + if lon_jump_ind.size > 1: + print("More than one jump in longitude") + + if lon_jump_ind.size == 1: + lon_jump_ind = lon_jump_ind[0] + diff_lon_jump = np.abs( + lons_dim[lon_jump_ind] - lons_dim[lon_jump_ind + 1]) + missing_elements = int(np.round(diff_lon_jump / 0.00416666)) + missing_lons = np.linspace(lons_dim[lon_jump_ind], + lons_dim[lon_jump_ind + 1], + missing_elements, + endpoint=False) + + # fill up longitude dimension to full grid + lons_dim = np.concatenate([lons_dim[:lon_jump_ind], + missing_lons, + lons_dim[lon_jump_ind + 1:]]) + + # fill data with NaN values + empty = np.empty((lats_dim.shape[0], missing_elements)) + empty.fill(1e38) + for key in data: + data[key] = np.concatenate( + [data[key][:, :lon_jump_ind], + empty, data[key][:, lon_jump_ind + 1:]], axis=1) + + lat_jump_ind = np.where(np.diff(lats_dim) > 0.00418)[0] + + if lat_jump_ind.size > 1: + print("More than one jump in latitude") + + if lat_jump_ind.size == 1: + diff_lat_jump = np.abs( + lats_dim[lat_jump_ind] - lats_dim[lat_jump_ind + 1]) + missing_elements = np.round(diff_lat_jump / 0.00416666) + missing_lats = np.linspace(lats_dim[lat_jump_ind], + lats_dim[lat_jump_ind + 1], + missing_elements, + endpoint=False) + + # fill up longitude dimension to full grid + lats_dim = np.concatenate( + [lats_dim[:lat_jump_ind], missing_lats, + lats_dim[lat_jump_ind + 1:]]) + # fill data with NaN values + empty = np.empty((missing_elements, lons_dim.shape[0])) + empty.fill(1e38) + for key in data: + data[key] = np.concatenate( + [data[key][:lat_jump_ind, :], empty, + data[key][lat_jump_ind + 1:, :]], axis=0) + + data['lon'], data['lat'] = np.meshgrid(lons_dim, lats_dim) + + return data def close(self): + """ + Close file. + """ pass -class H08img(MultiTemporalImageBase): +class H08BufrFileList(ChronFiles): """ - Reads H SAF H08 images. The images have to be uncompressed in the - following folder structure path - month_path_str (default 'h08_%Y%m_buf') - - For example if path is set to /home/user/hsaf08 and month_path_str - is left to the default 'h08_%Y%m_buf' then the images for March 2012 - have to be in the folder /home/user/hsaf08/h08_201203_buf/ - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should be - used in datetime.datetime.strftime - Default: 'h08_%Y%m_buf' - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on - the harddisk. This string is used in datetime.datetime.strftime and - in glob.glob to search for all files on a day. - Default : 'h08_%Y%m%d_*.buf' - file_search_str: string, optional - this string is used in datetime.datetime.strftime and glob.glob to find - a 3 minute bufr file by the exact date. - Default: 'h08_{datetime}*.buf' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d_%H%M%S + Reads H SAF H08 data. """ - def __init__(self, path, month_path_str='h08_%Y%m_buf', - day_search_str='h08_%Y%m%d_*.buf', - file_search_str='h08_{datetime}*.buf', - datetime_format='%Y%m%d_%H%M%S', - filename_datetime_format=(4, 19, '%Y%m%d_%H%M%S')): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.filename_datetime_format = filename_datetime_format - - super(H08img, self).__init__(path, H08Single, - subpath_templ=[month_path_str], - fname_templ=file_search_str, - datetime_format=datetime_format, - exact_templ=False) - - def _get_orbit_start_date(self, filename): - - orbit_start_str = \ - os.path.basename(filename)[self.filename_datetime_format[0]: - self.filename_datetime_format[1]] + def __init__(self, path): + """ + Initialize. + """ + fn_templ = 'h08_{date}*.buf' + sf_templ = {'month': 'h08_{date}_buf'} - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) + super().__init__(path, H08Bufr, fn_templ, sf_templ=sf_templ) - def tstamps_for_daterange(self, startdate, enddate): + def _fmt(self, timestamp): """ - Get the timestamps as datetime array that are possible for the - given day, if the timestamps are - - For this product it is not fixed but has to be looked up from - the hard disk since bufr files are not regular spaced and only - europe is in this product. For a global product a 3 minute - spacing could be used as a fist approximation + Definition of filename and subfolder format. Parameters ---------- - start_date : datetime.date or datetime.datetime - start date - end_date : datetime.date or datetime.datetime - end date + timestamp : datetime + Time stamp. Returns ------- - dates : list - list of datetimes + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. """ - file_list = [] - delta_all = enddate - startdate - timestamps = [] - - for i in range(delta_all.days + 1): - timestamp = startdate + timedelta(days=i) - - files = self._search_files( - timestamp, custom_templ=self.day_search_str) - - file_list.extend(sorted(files)) - - for filename in file_list: - timestamps.append(self._get_orbit_start_date(filename)) - - timestamps = [dt for dt in timestamps if dt >= - startdate and dt <= enddate] - return timestamps - + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d_%H%M%S')} + sf_read_fmt = {'month': {'date': timestamp.strftime('%Y%m')}} -class H07img(AscatL2SsmBufr): - pass + fn_write_fmt = None + sf_write_fmt = None + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt -class H16img(AscatL2SsmBufr): - - """ - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should be - used in datetime.datetime.strftime - Default: 'h16_%Y%m_buf' - """ - - def __init__(self, path, month_path_str='h16_%Y%m_buf'): - - day_search_str = 'h16_%Y%m%d_*.buf' - file_search_str = 'h16_{datetime}*.buf' - - super(H16img, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str) + def _parse_date(self, filename): + """ + Parse date from filename. + Parameters + ---------- + filename : str + Filename. -class H101img(AscatL2SsmBufr): + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[4:19], + '%Y%m%d_%H%M%S') - """ - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should - be used in datetime.datetime.strftime - Default: 'h101_%Y%m_buf' - """ + def read_period(dt_start, dt_end, delta): + """ + Read period not implemented. + """ + raise NotImplementedError - def __init__(self, path, month_path_str='h101_%Y%m_buf'): - day_search_str = 'h101_%Y%m%d_*.buf' - file_search_str = 'h101_{datetime}*.buf' - fn_datetime_fmt = (5, 20, '%Y%m%d_%H%M%S') +class AscatNrtBufrFileList(ChronFiles): - super(H101img, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - filename_datetime_format=fn_datetime_fmt) + def __init__(self, root_path, product_id='*'): + """ + Initialize. + """ + fn_templ = '{product_id}_{date}*.buf' + sf_templ = None + self.product_id = product_id -class H102img(AscatL2SsmBufr): + super().__init__(root_path, AscatL2File, fn_templ, sf_templ=sf_templ) - """ - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should be - used in datetime.datetime.strftime - Default: 'h102_%Y%m_buf' - """ + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. - def __init__(self, path, month_path_str='h102_%Y%m_buf'): + Parameters + ---------- + timestamp : datetime + Time stamp. - day_search_str = 'h102_%Y%m%d_*.buf' - file_search_str = 'h102_{datetime}*.buf' - fn_datetime_fmt = (5, 20, '%Y%m%d_%H%M%S') + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d_%H%M%S'), + 'product_id': self.product_id} + sf_read_fmt = None + fn_write_fmt = None + sf_write_fmt = None - super(H102img, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - filename_datetime_format=fn_datetime_fmt) + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt + def _parse_date(self, filename): + """ + Parse date from filename. -class H103img(AscatL2SsmBufr): + Parameters + ---------- + filename : str + Filename. - """ - Class reading H103 Metop-A ASCAT soil moisture in BUFR format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should be - used in datetime.datetime.strftime - Default: 'h103_%Y%m_buf' - """ + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[4:19], + '%Y%m%d%_H%M%S') - def __init__(self, path, month_path_str='h103_%Y%m_buf'): + def _merge_data(self, data): + """ + Merge data. - day_search_str = 'h103_%Y%m%d_*.buf' - file_search_str = 'h103_{datetime}*.buf' - fn_datetime_fmt = (5, 20, '%Y%m%d_%H%M%S') + Parameters + ---------- + data : list + List of array. - super(H103img, self).__init__(path, month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - filename_datetime_format=fn_datetime_fmt) + Returns + ------- + data : numpy.ndarray + Data. + """ + return np.hstack(data) -class H14Single(ImageBase): +class H14Grib: """ Class reading H14 soil moisture in GRIB format. - - Parameters - ---------- - expand_grid : boolean, optional - if set the images will be expanded to a 2D image during reading - if false the images will be returned as 1D arrays on the - reduced gaussian grid - Default: True - metadata_fields: list, optional - fields of the message to put into the metadata dictionary. """ - def __init__(self, filename, mode='r', expand_grid=True, + def __init__(self, filename, expand_grid=True, metadata_fields=['units', 'name']): + """ + Parameters + ---------- + expand_grid : boolean, optional + if set the images will be expanded to a 2D image during reading + if false the images will be returned as 1D arrays on the + reduced gaussian grid + Default: True + metadata_fields: list, optional + fields of the message to put into the metadata dictionary. + """ + self.filename = filename self.expand_grid = expand_grid self.metadata_fields = metadata_fields self.pygrib1 = True @@ -488,8 +349,6 @@ def __init__(self, filename, mode='r', expand_grid=True, if int(pygrib.__version__[0]) > 1: self.pygrib1 = False - super(H14Single, self).__init__(filename, mode=mode) - def read(self, timestamp=None): """ Read specific image for given datetime timestamp. @@ -504,25 +363,12 @@ def read(self, timestamp=None): data : dict dictionary of numpy arrays that hold the image data for each variable of the dataset - metadata : dict - dictionary of numpy arrays that hold the metadata - timestamp : datetime.datetime - exact timestamp of the image - lon : numpy.array or None - array of longitudes, if None self.grid will be assumed - lat : numpy.array or None - array of latitudes, if None self.grid will be assumed - time_var : string or None - variable name of observation times in the data dict, if None all - observations have the same timestamp """ - if self.pygrib1: param_names = {'40': 'SM_layer1_0-7cm', '41': 'SM_layer2_7-28cm', '42': 'SM_layer3_28-100cm', '43': 'SM_layer4_100-289cm'} - else: param_names = { 'SWI1 Soil wetness index in layer 1': 'SM_layer1_0-7cm', @@ -536,7 +382,7 @@ def read(self, timestamp=None): for i, message in enumerate(grb): message.expand_grid(self.expand_grid) if i == 1: - lats, lons = message.latlons() + data['lat'], data['lon'] = message.latlons() data[param_names[message['parameterName']]] = message.values # read and store metadata @@ -546,211 +392,110 @@ def read(self, timestamp=None): md[k] = message[k] metadata[param_names[message['parameterName']]] = md - return Image(lons, lats, data, metadata, timestamp) - - def write(self, data): - raise NotImplementedError() - - def flush(self): - pass + return data def close(self): pass -class H14img(MultiTemporalImageBase): +class H14GribFileList(ChronFiles): """ - Class for reading H SAF H14 SM DAS 2 products in grib format. - - The images have to be uncompressed in the following folder structure - path - month_path_str (default 'h14_%Y%m_grib') - - For example if path is set to /home/user/hsaf14 and month_path_str is - left to the default 'h14_%Y%m_grib' then the images for March 2012 have - to be in the folder /home/user/hsaf14/h14_201203_grib/ - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the H SAF FTP Server then please specify the string that should be - used in datetime.datetime.strftime - Default: 'h14_%Y%m_grib' - file_str: string, optional - this string is used in datetime.datetime.strftime to get the - filename of a H14 daily grib file - Default: 'H14_%Y%m%d00.grib' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_str - Default: %Y%m%d + Reads H SAF H08 data. """ - def __init__(self, path, month_path_str='h14_%Y%m_grib', - file_str='H14_{datetime}00.grib', datetime_format='%Y%m%d', - expand_grid=True): - - self.path = path - self.month_path_str = month_path_str - self.file_search_str = file_str - - super(H14img, self).__init__(path, H14Single, - subpath_templ=[month_path_str], - fname_templ=file_str, - datetime_format=datetime_format, - ioclass_kws={'expand_grid': expand_grid}) - - -class H25Ts(AscatNc): - - """ - Class reading H25 soil moisture climate data record (CDR). - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - fn_format = 'H25_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H25Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H108Ts(AscatNc): - - """ - Class reading H108 soil moisture climate data record (CDR) extension. - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - fn_format = 'H108_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H108Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H109Ts(AscatNc): - - """ - Class reading H109 soil moisture climate data record (CDR). - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - fn_format = 'H109_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H109Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H110Ts(AscatNc): - - """ - Class reading H110 soil moisture climate data record (CDR) extension. - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - fn_format = 'H110_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H110Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H111Ts(AscatNc): - - """ - Class reading H111 soil moisture climate data record (CDR). - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - fn_format = 'H111_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H111Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H112Ts(AscatNc): - - """ - Class reading H112 soil moisture climate data record (CDR). - """ + def __init__(self, path): + """ + Initialize. + """ + fn_templ = 'H14_{date}.grib' + sf_templ = {'month': 'h14_{date}_grib'} - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): + super().__init__(path, H14Grib, fn_templ, sf_templ=sf_templ) - fn_format = 'H112_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) + def _fmt(self, timestamp): + """ + Definition of filename and subfolder format. - super(H112Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) + Parameters + ---------- + timestamp : datetime + Time stamp. + Returns + ------- + fn_fmt : dict + Filename format. + sf_fmt : dict + Subfolder format. + """ + fn_read_fmt = {'date': timestamp.strftime('%Y%m%d%H')} + sf_read_fmt = {'month': {'date': timestamp.strftime('%Y%m')}} + fn_write_fmt = None + sf_write_fmt = None -class H113Ts(AscatNc): + return fn_read_fmt, sf_read_fmt, fn_write_fmt, sf_write_fmt - """ - Class reading H113 soil moisture climate data record (CDR). - """ + def _parse_date(self, filename): + """ + Parse date from filename. - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): + Parameters + ---------- + filename : str + Filename. - fn_format = 'H113_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) + Returns + ------- + date : datetime + Parsed date. + """ + return datetime.strptime(os.path.basename(filename)[4:15], '%Y%m%d%H') - super(H113Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) + def read_period(dt_start, dt_end, delta): + """ + Read period not implemented. + """ + raise NotImplementedError() -class H114Ts(AscatNc): +class AscatSsmDataRecord(AscatGriddedNcTs): """ - Class reading H114 soil moisture climate data record (CDR). + Class reading Metop ASCAT soil moisture data record. """ - def __init__(self, cdr_path, grid_path, + def __init__(self, cdr_path, grid_path, fn_format=None, grid_filename='TUW_WARP5_grid_info_2_2.nc', static_layer_path=None, **kwargs): + """ - fn_format = 'H114_{:04d}' - grid_filename = os.path.join(grid_path, grid_filename) - - super(H114Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) - - -class H115Ts(AscatNc): + Parameters + ---------- + cdr_path : str + Path to Climate Data Record (CDR) data set. + grid_path : str + Path to grid file. + grid_filename : str + Name of grid file. + static_layer_path : str + Path to static layer files. + + Attributes + ---------- + grid : pygeogrids.CellGrid + Cell grid. + """ + if fn_format is None: + first_file = glob.glob(os.path.join(cdr_path, '*.nc')) - """ - Class reading H115 soil moisture climate data record (CDR). - """ + if len(first_file) == 0: + raise RuntimeError('No files found') - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): + version = os.path.basename(first_file[0]).rsplit('_', 1)[0] + fn_format = '{:}_{{:04d}}'.format(version) - fn_format = 'H115_{:04d}' grid_filename = os.path.join(grid_path, grid_filename) - super(H115Ts, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) + super().__init__(cdr_path, fn_format, grid_filename, + static_layer_path, **kwargs) diff --git a/src/ascat/level1.py b/src/ascat/level1.py deleted file mode 100644 index 4a0d3e8..0000000 --- a/src/ascat/level1.py +++ /dev/null @@ -1,1075 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -""" -General Level 1 data readers for ASCAT data in all formats. -Not specific to distributor. -""" -import os -import numpy as np -from datetime import datetime - -from pygeobase.io_base import ImageBase -from pygeobase.object_base import Image - -import ascat.read_native.eps_native as eps_native -import ascat.read_native.bufr as bufr -import ascat.read_native.nc as nc -import ascat.read_native.hdf5 as h5 -from ascat.base import ASCAT_MultiTemporalImageBase -from ascat.utils import db2lin, lin2db, hamming_window - -byte_nan = np.iinfo(np.byte).min -ubyte_nan = np.iinfo(np.ubyte).max -uint8_nan = np.iinfo(np.uint8).max -uint16_nan = np.iinfo(np.uint16).max -uint32_nan = np.iinfo(np.uint32).max -float32_nan = np.finfo(np.float32).min -float64_nan = np.finfo(np.float64).min -long_nan = np.iinfo(np.int32).min -int_nan = np.iinfo(np.int16).min - - -class AscatL1Image(ImageBase): - """ - General Level 1b Image for ASCAT data - """ - - def __init__(self, *args, **kwargs): - """ - Initialization of i/o object. - """ - super(AscatL1Image, self).__init__(*args, **kwargs) - - def read(self, timestamp=None, file_format=None, native=False, **kwargs): - """ - Read ASCAT swath files. - - Parameters - ---------- - timestamp : str, optional - Time stamp of file (default: None). - file_format : str, optional - File format: '.nat', '.nc', '.bfr', '.h5' (default: None). - If None file format will be guessed based on the file ending. - native : bool, optional - Return native or generic data set format (default: False). - The main difference is that in the original native format fields - are called differently. - - Returns - ------- - img : pygeobase.object_base.Image - ASCAT swath image. - """ - if file_format is None: - file_format = get_file_format(self.filename) - - if file_format in [".nat", ".nat.gz"]: - img = eps_native.AscatL1bEPSImage(self.filename).read(timestamp) - if not native: - img = eps2generic(img) - - elif file_format in [".nc", ".nc.gz"]: - img = nc.AscatL1NcFile(self.filename).read(timestamp) - if not native: - img = nc2generic(img) - - elif file_format in [".bfr", ".bfr.gz", ".buf", "buf.gz"]: - img = bufr.AscatL1BufrFile(self.filename).read(timestamp) - if not native: - img = bfr2generic(img) - - elif file_format in [".h5", ".h5.gz"]: - img = h5.AscatL1H5File(self.filename).read(timestamp) - if not native: - img = hdf2generic(img) - - else: - raise RuntimeError( - "Format not found, please indicate the file_format. " - "[\".nat\", \".nc\", \".bfr\", \".h5\"]") - - return img - - def read_masked_data(self, usable_flag=2, land_flag=0.095, **kwargs): - """ - Read ASCAT swath files and mask unusable observations. - - Parameters - ---------- - usable_flag : int, optional - Allowed usable flag (default: 2). - land_flag : float, optional - Sea/land flag threshold (optional: 0.095) - - Returns - ------- - img : pygeobase.object_base.Image - ASCAT swath image with masking applied. - """ - orbit = self.read(**kwargs) - - if type(orbit) is dict: - img = {'img1': {}, 'img2': {}, 'img3': {}, - 'img4': {}, 'img5': {}, 'img6': {}} - - for single_img in orbit: - - valid = np.ones( - orbit[single_img].data[orbit[ - single_img].data.dtype.names[0]].shape, dtype=np.bool) - - valid = (valid & (orbit[single_img].data[ - 'usable_flag'] < usable_flag)) - - valid = (valid & (orbit[single_img].data[ - 'land_flag'] > land_flag)) - - valid_num = orbit[single_img].data['jd'][valid].shape[0] - masked_data = get_template_ASCATL1B_SZF(valid_num) - - for key in orbit[single_img].data.dtype.names: - masked_data[key] = orbit[single_img].data[key][valid] - - img[single_img] = Image(orbit[single_img].lon[valid], - orbit[single_img].lat[valid], - masked_data, - orbit[single_img].metadata, - orbit[single_img].timestamp, - timekey='jd') - else: - valid = np.ones( - orbit.data[orbit.data.dtype.names[0]].shape, dtype=np.bool) - - for b in ['f', 'm', 'a']: - valid = (valid & (orbit.data['usable_flag' + b] < usable_flag)) - valid = (valid & (orbit.data['land_flag' + b] > land_flag)) - - valid_num = orbit.data['jd'][valid].shape[0] - masked_data = get_template_ASCATL1B_SZX(valid_num) - - for key in orbit.data.dtype.names: - masked_data[key] = orbit.data[key][valid] - - img = Image(orbit.lon[valid], orbit.lat[valid], masked_data, - orbit.metadata, orbit.timestamp, - timekey='jd') - - return img - - def resample_data(self, data, index, distance, window_radius, **kwargs): - """ - Weight selected data based on neighborhood (index) and - distance information. - - Parameters - ---------- - data : numpy.ndarray - Selected swath data subset. - index : numpy.ndarray - Index information. - distance : numpy.ndarray - Distance information. - window_radius : float - Size of window. - - Returns - ------- - res_orbit : numpy.ndarray - Re-sampled orbit data. - """ - # target template - template = get_resample_template_ASCATL1B_SZX() - res_orbit = np.repeat(template, index.shape[0]) - - # get weights - weights, _ = hamming_window(window_radius, distance) - # total_weights = np.nansum(weights, axis=1) - - # resample backscatter - sigmas = ['sigf', 'sigm', 'siga'] - - for sigma in sigmas: - data[sigma][data[sigma] == float32_nan] = np.nan - - weights_exc = weights.copy() - weights_exc[np.isnan(data[sigma])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[sigma] = lin2db(np.nansum(db2lin(data[sigma])[index] - * weights, - axis=1) - / total_weights_exc) - res_orbit[sigma][np.isnan(res_orbit[sigma])] = float32_nan - res_orbit[sigma][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # resample measurement geometry - measgeos = ['incf', 'incm', 'inca', 'azif', 'azim', 'azia'] - - for mg in measgeos: - data[mg][data[mg] == float32_nan] = np.nan - - weights_exc = weights.copy() - weights_exc[np.isnan(data[mg])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[mg] = (np.nansum(data[mg][index] * weights, axis=1) - / total_weights_exc) - res_orbit[mg][np.isnan(res_orbit[mg])] = float32_nan - res_orbit[mg][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # noise estimate - noise = ['kpf', 'kpm', 'kpa'] - - for n in noise: - data[n][data[n] == float32_nan] = np.nan - - weights_exc = weights.copy() - weights_exc[np.isnan(data[n])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[n] = (np.nansum(data[n][index] * weights, axis=1) - / total_weights_exc) - res_orbit[n][np.isnan(res_orbit[n])] = float32_nan - res_orbit[n][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # nearest neighbour resampling values - nnResample = ['jd', 'sat_id', 'abs_line_nr', 'abs_orbit_nr', - 'node_num', 'line_num', 'swath', 'as_des_pass'] - - # index of min. distance is equal to 0 because of kd-tree usage - for nn in nnResample: - res_orbit[nn] = data[nn][index][:, 0] - - # set as_des_pass as string - # res_orbit['dir'][data['as_des_pass'][index][:, 0] == 1] = 'D' - # res_orbit['dir'][data['as_des_pass'][index][:, 0] == 0] = 'A' - - # set number of measurements for resampling - res_orbit['num_obs'] = np.sum(distance != np.inf, axis=1) - - return res_orbit - - def write(self, *args, **kwargs): - """ - Write function. - """ - pass - - def flush(self): - """ - Flush function. - """ - pass - - def close(self): - """ - Close function. - """ - pass - - -class AscatL1Bufr(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level1 images in bufr format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: '*-ASCA-*-NA-*-%Y%m%d*.bfr' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: '*-ASCA-*-NA-*-{datetime}*.bfr' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - msg_name_lookup: dict, optional - Dictionary mapping bufr msg number to parameter name. - See bufr.AscatL1BufrFile - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='*-ASCA-*-NA-*-%Y%m%d*-*-*.bfr', - file_search_str='*-ASCA-*-NA-*-{datetime}.*.bfr', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(26, 40, '%Y%m%d%H%M%S'), - msg_name_lookup=None, eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL1Bufr, self).__init__( - path, AscatL1Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False, ioclass_kws={'msg_name_lookup': - msg_name_lookup}) - - def _get_orbit_start_date(self, filename): - """ - Returns the datetime of the file. - - Parameters - ---------- - filename : full name (including the path) of the file - - Returns - ------- - dates : datetime object - datetime from the filename - """ - # if your data comes from the EUMETSAT EO Portal this function can - if self.eo_portal is True: - filename_base = os.path.basename(filename) - fln_spl = filename_base.split('-')[5] - fln_datetime = fln_spl.split('.')[0] - return datetime.strptime(fln_datetime, self.datetime_format) - - else: - orbit_start_str = os.path.basename(filename)[ - self.filename_datetime_format[0]: - self.filename_datetime_format[1]] - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) - - -class AscatL1Eps(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level1 images in eps format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: 'ASCA_*_*_*_%Y%m%d*_*_*_*_*.nat' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: 'ASCA_*_*_*_{datetime}Z_*_*_*_*.nat' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='ASCA_*_*_*_%Y%m%d*_*_*_*_*.nat', - file_search_str='ASCA_*_*_*_{datetime}Z_*_*_*_*.nat', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(16, 30, '%Y%m%d%H%M%S'), - eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL1Eps, self).__init__( - path, AscatL1Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False) - - -class AscatL1Hdf5(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level1 images in hdf5 format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: 'ASCA_*_*_*_%Y%m%d*_*_*_*_*.h5' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: 'ASCA_*_*_*_{datetime}Z_*_*_*_*.h5' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='ASCA_*_*_*_%Y%m%d*_*_*_*_*.h5', - file_search_str='ASCA_*_*_*_{datetime}Z_*_*_*_*.h5', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(16, 30, '%Y%m%d%H%M%S'), - eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL1Hdf5, self).__init__( - path, AscatL1Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False) - - -class AscatL1Nc(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level1 images in nc format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: 'W_XX-*_EUMP_%Y%m%d*.nc' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: 'W_XX-*_EUMP_{datetime}*.nc' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - msg_name_lookup: dict, optional - Dictionary mapping nc msg number to parameter name. - See nc.AscatL1NcFile - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='W_XX-*_EUMP_%Y%m%d*.nc', - file_search_str='W_XX-*_EUMP_{datetime}*.nc', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(62, 76, '%Y%m%d%H%M%S'), - msg_name_lookup=None, eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL1Nc, self).__init__( - path, AscatL1Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False, ioclass_kws={'msg_name_lookup': - msg_name_lookup}) - - -def get_file_format(filename): - """ - Try to guess the file format from the extension. - - Parameters - ---------- - filename : str - File name. - - Returns - ------- - file_format : str - File format indicator. - """ - if os.path.splitext(filename)[1] == '.gz': - file_format = os.path.splitext(os.path.splitext(filename)[0])[1] - else: - file_format = os.path.splitext(filename)[1] - return file_format - - -def eps2generic(native_img): - """ - Convert the native eps Image into a generic one. - Use different convert-function for szf and szx data - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Converted image. - """ - if type(native_img) is dict: - img = eps_dict2generic(native_img) - else: - img = eps_img2generic(native_img) - - return img - - -def eps_img2generic(native_img): - """ - Convert single eps image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Generic image. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL1B_SZX(n_records) - - fields = [('jd', 'jd', None), - ('sat_id', None, None), - ('abs_line_nr', None, None), - ('abs_orbit_nr', None, None), - ('node_num', 'NODE_NUM', None), - ('line_num', 'LINE_NUM', None), - ('as_des_pass', 'AS_DES_PASS', None), - ('swath', 'SWATH INDICATOR', byte_nan), - ('azif', 'f_AZI_ANGLE_TRIP', int_nan), - ('azim', 'm_AZI_ANGLE_TRIP', int_nan), - ('azia', 'a_AZI_ANGLE_TRIP', int_nan), - ('incf', 'f_INC_ANGLE_TRIP', uint16_nan), - ('incm', 'm_INC_ANGLE_TRIP', uint16_nan), - ('inca', 'a_INC_ANGLE_TRIP', uint16_nan), - ('sigf', 'f_SIGMA0_TRIP', long_nan), - ('sigm', 'm_SIGMA0_TRIP', long_nan), - ('siga', 'a_SIGMA0_TRIP', long_nan), - ('kpf', 'f_KP', uint16_nan), - ('kpm', 'm_KP', uint16_nan), - ('kpa', 'a_KP', uint16_nan), - ('kpf_quality', 'f_F_KP', byte_nan), - ('kpm_quality', 'm_F_KP', byte_nan), - ('kpa_quality', 'a_F_KP', byte_nan), - ('land_flagf', 'f_F_LAND', uint16_nan), - ('land_flagm', 'm_F_LAND', uint16_nan), - ('land_flaga', 'a_F_LAND', uint16_nan), - ('usable_flagf', 'f_F_USABLE', byte_nan), - ('usable_flagm', 'm_F_USABLE', byte_nan), - ('usable_flaga', 'a_F_USABLE', byte_nan)] - - for field in fields: - if field[1] is None: - continue - - if field[2] is not None: - valid_mask = (native_img.data[field[1]] != field[2]) - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - if 'ABS_LINE_NUMBER' in native_img.data: - generic_data['abs_line_nr'] = native_img.data['ABS_LINE_NUMBER'] - - fields = [('sat_id', 'SPACECRAFT_ID'), - ('abs_orbit_nr', 'ORBIT_START')] - - for field in fields: - generic_data[field[0]] = native_img.metadata[field[1]].repeat( - n_records) - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def eps_dict2generic(native_img): - """ - Convert dict of eps Images into a dict with generic Images - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : list of pygeobase.object_base.Image - Generic images. - """ - img = {'img1': {}, 'img2': {}, 'img3': {}, - 'img4': {}, 'img5': {}, 'img6': {}} - - for szf_img in native_img: - n_records = native_img[szf_img].lat.shape[0] - generic_data = get_template_ASCATL1B_SZF(n_records) - - fields = [('jd', 'jd'), - ('sat_id', None), - ('beam_number', 'BEAM_NUMBER'), - ('abs_orbit_nr', None), - ('as_des_pass', 'AS_DES_PASS'), - ('azi', 'AZI_ANGLE_FULL'), - ('inc', 'INC_ANGLE_FULL'), - ('sig', 'SIGMA0_FULL'), - ('land_frac', 'LAND_FRAC'), - ('flagfield_rf1', 'FLAGFIELD_RF1'), - ('flagfield_rf2', 'FLAGFIELD_RF2'), - ('flagfield_pl', 'FLAGFIELD_PL'), - ('flagfield_gen1', 'FLAGFIELD_GEN1'), - ('flagfield_gen2', 'FLAGFIELD_GEN2'), - ('land_flag', 'F_LAND'), - ('usable_flag', 'F_USABLE')] - - for field in fields: - if field[1] is None: - continue - generic_data[field[0]] = native_img[szf_img].data[field[1]] - - fields = [('sat_id', 'SPACECRAFT_ID'), - ('abs_orbit_nr', 'ORBIT_START')] - for field in fields: - generic_data[field[0]] = native_img[szf_img].metadata[ - field[1]].repeat(n_records) - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img[szf_img] = Image(native_img[szf_img].lon, - native_img[szf_img].lat, - generic_data, - native_img[szf_img].metadata, - native_img[szf_img].timestamp, - timekey='jd') - return img - - -def nc2generic(native_img): - """ - Convert the native nc Image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Generic images. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL1B_SZX(n_records) - - fields = [('jd', 'jd'), - ('sat_id', None), - ('abs_line_nr', None), - ('abs_orbit_nr', None), - ('node_num', 'node_num'), - ('line_num', 'line_num'), - ('as_des_pass', 'as_des_pass'), - ('swath', 'swath_indicator'), - ('azif', 'f_azi_angle_trip'), - ('azim', 'm_azi_angle_trip'), - ('azia', 'a_azi_angle_trip'), - ('incf', 'f_inc_angle_trip'), - ('incm', 'm_inc_angle_trip'), - ('inca', 'a_inc_angle_trip'), - ('sigf', 'f_sigma0_trip'), - ('sigm', 'm_sigma0_trip'), - ('siga', 'a_sigma0_trip'), - ('kpf', 'f_kp'), - ('kpm', 'm_kp'), - ('kpa', 'a_kp'), - ('kpf_quality', 'f_f_kp'), - ('kpm_quality', 'm_f_kp'), - ('kpa_quality', 'a_f_kp'), - ('land_flagf', 'f_f_land'), - ('land_flagm', 'm_f_land'), - ('land_flaga', 'a_f_land'), - ('usable_flagf', 'f_f_usable'), - ('usable_flagm', 'm_f_usable'), - ('usable_flaga', 'a_f_usable')] - - for field in fields: - if field[1] is None: - continue - - if type(native_img.data[field[1]]) == np.ma.core.MaskedArray: - valid_mask = ~native_img.data[field[1]].mask - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - if 'abs_line_number' in native_img.data: - generic_data['abs_line_nr'] = native_img.data['abs_line_number'] - - fields = [('sat_id', 'sat_id'), ('abs_orbit_nr', 'orbit_start')] - - for field in fields: - generic_data[field[0]] = np.repeat(native_img.metadata[field[1]], - n_records) - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def bfr2generic(native_img): - """ - Convert the native bfr Image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Generic images. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL1B_SZX(n_records) - - fields = [('jd', 'jd', None), - ('sat_id', 'Satellite Identifier', None), - ('abs_line_nr', None, None), - ('abs_orbit_nr', 'Orbit Number', None), - ('node_num', 'Cross-Track Cell Number', None), - ('line_num', 'line_num', None), - ('as_des_pass', 'as_des_pass', None), - ('swath', 'swath_indicator', None), - ('azif', 'f_Antenna Beam Azimuth', 1.7e+38), - ('azim', 'm_Antenna Beam Azimuth', 1.7e+38), - ('azia', 'a_Antenna Beam Azimuth', 1.7e+38), - ('incf', 'f_Radar Incidence Angle', 1.7e+38), - ('incm', 'm_Radar Incidence Angle', 1.7e+38), - ('inca', 'a_Radar Incidence Angle', 1.7e+38), - ('sigf', 'f_Backscatter', 1.7e+38), - ('sigm', 'm_Backscatter', 1.7e+38), - ('siga', 'a_Backscatter', 1.7e+38), - ('kpf', 'f_Radiometric Resolution (Noise Value)', 1.7e+38), - ('kpm', 'm_Radiometric Resolution (Noise Value)', 1.7e+38), - ('kpa', 'a_Radiometric Resolution (Noise Value)', 1.7e+38), - ('kpf_quality', 'f_ASCAT KP Estimate Quality', None), - ('kpm_quality', 'm_ASCAT KP Estimate Quality', None), - ('kpa_quality', 'a_ASCAT KP Estimate Quality', None), - ('land_flagf', 'f_ASCAT Land Fraction', None), - ('land_flagm', 'm_ASCAT Land Fraction', None), - ('land_flaga', 'a_ASCAT Land Fraction', None), - ('usable_flagf', 'f_ASCAT Sigma-0 Usability', None), - ('usable_flagm', 'm_ASCAT Sigma-0 Usability', None), - ('usable_flaga', 'a_ASCAT Sigma-0 Usability', None)] - - kp_vars = ['kpf', 'kpm', 'kpa'] - - for field in fields: - if field[1] is None: - continue - - if field[2] is not None: - valid_mask = (native_img.data[field[1]] != field[2]) - if field[0] in kp_vars: - generic_data[field[0]][valid_mask] = \ - native_img.data[field[1]][valid_mask] / 100 - else: - generic_data[field[0]][valid_mask] = \ - native_img.data[field[1]][valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 0, 0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def hdf2generic(native_img): - """ - Convert the native nc Image into a generic one. - - Parameters - ---------- - native_img : list of pygeobase.object_base.Image - Native image. - - Returns - ------- - img : list of pygeobase.object_base.Image - Generic images. - """ - - img = {'img1': {}, 'img2': {}, 'img3': {}, - 'img4': {}, 'img5': {}, 'img6': {}} - - for szf_img in native_img: - n_records = native_img[szf_img].lat.shape[0] - generic_data = get_template_ASCATL1B_SZF(n_records) - - fields = [('jd', 'jd'), - ('sat_id', None), - ('beam_number', 'BEAM_NUMBER'), - ('abs_orbit_nr', None), - ('as_des_pass', 'AS_DES_PASS'), - ('azi', 'AZI_ANGLE_FULL'), - ('inc', 'INC_ANGLE_FULL'), - ('sig', 'SIGMA0_FULL'), - ('land_frac', 'LAND_FRAC'), - ('flagfield_rf1', 'FLAGFIELD_RF1'), - ('flagfield_rf2', 'FLAGFIELD_RF2'), - ('flagfield_pl', 'FLAGFIELD_PL'), - ('flagfield_gen1', 'FLAGFIELD_GEN1'), - ('flagfield_gen2', 'FLAGFIELD_GEN2'), - ('land_flag', 'F_LAND'), - ('usable_flag', 'F_USABLE') - ] - for field in fields: - if field[1] is None: - continue - generic_data[field[0]] = native_img[szf_img].data[field[1]] - - fields = [('sat_id', 'SPACECRAFT_ID'), - ('abs_orbit_nr', 'ORBIT_START')] - for field in fields: - generic_data[field[0]] = np.repeat(native_img[szf_img].metadata[ - field[1]], n_records) - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img[szf_img] = Image(native_img[szf_img].lon, - native_img[szf_img].lat, - generic_data, - native_img[szf_img].metadata, - native_img[szf_img].timestamp, - timekey='jd') - - return img - - -def get_template_ASCATL1B_SZX(n=1): - """ - Generic Level 1b SZX template. - - Parameters - ---------- - n : int, optional - Number of records (default: 1). - - Returns - ------- - records : numpy.ndarray - Array filled with default values. - """ - metadata = {'temp_name': 'ASCATL1B_SZX'} - - struct = np.dtype([('jd', np.float64), - ('sat_id', np.byte), - ('abs_line_nr', np.uint32), - ('abs_orbit_nr', np.uint32), - ('node_num', np.uint8), - ('line_num', np.uint16), - ('as_des_pass', np.byte), - ('swath', np.byte), - ('azif', np.float32), - ('azim', np.float32), - ('azia', np.float32), - ('incf', np.float32), - ('incm', np.float32), - ('inca', np.float32), - ('sigf', np.float32), - ('sigm', np.float32), - ('siga', np.float32), - ('kpf', np.float32), - ('kpm', np.float32), - ('kpa', np.float32), - ('kpf_quality', np.float32), - ('kpm_quality', np.float32), - ('kpa_quality', np.float32), - ('land_flagf', np.uint8), - ('land_flagm', np.uint8), - ('land_flaga', np.uint8), - ('usable_flagf', np.uint8), - ('usable_flagm', np.uint8), - ('usable_flaga', np.uint8)], metadata=metadata) - - record = np.array([(float64_nan, byte_nan, uint32_nan, uint32_nan, - uint8_nan, uint16_nan, byte_nan, byte_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, uint8_nan, uint8_nan, - uint8_nan, uint8_nan, uint8_nan, uint8_nan)], - dtype=struct) - - return np.repeat(record, n) - - -def get_template_ASCATL1B_SZF(n=1): - """ - Generic Level 1b SZF template. - - Parameters - ---------- - n : int, optional - Number of records (default: 1). - - Returns - ------- - records : numpy.ndarray - Array filled with default values. - """ - metadata = {'temp_name': 'ASCATL1B_SZF'} - - struct = np.dtype([('jd', np.float64), - ('sat_id', np.byte), - ('beam_number', np.byte), - ('abs_orbit_nr', np.uint32), - ('as_des_pass', np.byte), - ('azi', np.float32), - ('inc', np.float32), - ('sig', np.float32), - ('land_frac', np.float32), - ('flagfield_rf1', np.uint8), - ('flagfield_rf2', np.uint8), - ('flagfield_pl', np.uint8), - ('flagfield_gen1', np.uint8), - ('flagfield_gen2', np.uint8), - ('land_flag', np.uint8), - ('usable_flag', np.uint8)], metadata=metadata) - - record = np.array([(float64_nan, byte_nan, byte_nan, uint32_nan, byte_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - uint8_nan, uint8_nan, uint8_nan, uint8_nan, uint8_nan, - uint8_nan, uint8_nan)], dtype=struct) - - return np.repeat(record, n) - - -def get_resample_template_ASCATL1B_SZX(n=1): - """ - Generic Level 1b SZX template. - - Parameters - ---------- - n : int, optional - Number of records (default: 1). - - Returns - ------- - records : numpy.ndarray - Array filled with default values. - """ - metadata = {'temp_name': 'ASCRS010'} - - struct = np.dtype([('jd', np.float64), - ('sat_id', np.byte), - ('abs_line_nr', np.uint32), - ('abs_orbit_nr', np.uint32), - ('node_num', np.uint8), - ('line_num', np.uint16), - ('as_des_pass', np.byte), - ('swath', np.byte), - ('azif', np.float32), - ('azim', np.float32), - ('azia', np.float32), - ('incf', np.float32), - ('incm', np.float32), - ('inca', np.float32), - ('sigf', np.float32), - ('sigm', np.float32), - ('siga', np.float32), - ('kpf', np.float32), - ('kpm', np.float32), - ('kpa', np.float32), - ('num_obs', np.uint16)], metadata=metadata) - - record = np.array([(float64_nan, byte_nan, uint32_nan, uint32_nan, - uint8_nan, uint16_nan, byte_nan, byte_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, uint16_nan)], - dtype=struct) - - return np.repeat(record, n) diff --git a/src/ascat/level2.py b/src/ascat/level2.py deleted file mode 100644 index ecbe842..0000000 --- a/src/ascat/level2.py +++ /dev/null @@ -1,867 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -""" -General Level 2 data readers for ASCAT data in all formats. -""" - -import os -import numpy as np -from datetime import datetime - -from pygeobase.io_base import ImageBase -from pygeobase.object_base import Image - -import ascat.read_native.eps_native as read_eps -import ascat.read_native.bufr as read_bufr -import ascat.read_native.nc as read_nc -from ascat.utils import db2lin, lin2db, hamming_window -from ascat.base import ASCAT_MultiTemporalImageBase - -byte_nan = np.iinfo(np.byte).min -ubyte_nan = np.iinfo(np.ubyte).max -uint8_nan = np.iinfo(np.uint8).max -uint16_nan = np.iinfo(np.uint16).max -uint32_nan = np.iinfo(np.uint32).max -float32_nan = np.finfo(np.float32).min -float64_nan = np.finfo(np.float64).min -long_nan = np.iinfo(np.int32).min -int_nan = np.iinfo(np.int16).min - - -class AscatL2Image(ImageBase): - """ - General Level 2 Image - """ - - def __init__(self, *args, **kwargs): - """ - Initialization of i/o object. - """ - super(AscatL2Image, self).__init__(*args, **kwargs) - - def read(self, timestamp=None, file_format=None, native=False, **kwargs): - """ - Read ASCAT swath files. - - Parameters - ---------- - timestamp : str, optional - Time stamp of file (default: None). - file_format : str, optional - File format: '.nat', '.nc', '.bfr', '.h5' (default: None). - If None file format will be guessed based on the file ending. - native : bool, optional - Return native or generic data set format (default: False). - The main difference is that in the original native format fields - are called differently. - - Returns - ------- - img : pygeobase.object_base.Image - ASCAT swath image. - """ - - if file_format is None: - file_format = get_file_format(self.filename) - - if file_format in [".nat", ".nat.gz"]: - img = read_eps.AscatL2EPSImage(self.filename).read(timestamp) - if not native: - img = eps2generic(img) - - elif file_format in [".nc", ".nc.gz"]: - img = read_nc.AscatL2SsmNcFile(self.filename).read(timestamp) - if not native: - img = nc2generic(img) - - elif file_format in [".bfr", ".bfr.gz", ".buf", "buf.gz"]: - img = read_bufr.AscatL2SsmBufrFile(self.filename).read(timestamp) - if not native: - img = bfr2generic(img) - - else: - raise RuntimeError( - "Format not found, please indicate the file_format. " - "[\".nat\", \".nc\", \".bfr\"]") - - return img - - def read_masked_data(self, correction_flag=0, processing_flag=0, - aggregated_quality_flag=100, - snow_cover_probability=100, - frozen_soil_probability=100, - innudation_or_wetland=100, - topographical_complexity=100, **kwargs): - """ - Read ASCAT swath files and mask unusable observations. - - Parameters - ---------- - correction_flag : int, optional - Correction flag (default: 0). - aggregated_quality_flag : int, optional - Aggregated quality flag (default: 0). - snow_cover_probability : float, optional - Snow cover probability (default: 100). - frozen_soil_probability : float, optional - Frozen soil probability (default: 100). - innudation_or_wetland : float, optional - Innundation and wetland flag (default: 100). - topographical_complexity, float, optional - Toographical complexity flag (default: 100). - - Returns - ------- - img : pygeobase.object_base.Image - ASCAT swath image with masking applied. - """ - orbit = self.read(**kwargs) - - valid = np.ones(orbit.data[orbit.data.dtype.names[0]].shape, - dtype=np.bool) - - # bitwise comparison, if any bitflag is set by the user and is active - # for the datarecord the result is bigger than 0 and the not valid - valid = (valid & (((orbit.data['correction_flag'] - & correction_flag) == 0) - | (orbit.data['correction_flag'] == uint8_nan))) - - valid = (valid & (((orbit.data['processing_flag'] - & processing_flag) == 0) - | (orbit.data['processing_flag'] == uint16_nan))) - - # if any probability/flag is too high the datarecord is not used - # nan values are not considered since not all formats provide all flags - # and the values are set to nan there to keep a generic structure - valid = (valid & ((orbit.data['aggregated_quality_flag'] - < aggregated_quality_flag) - | (orbit.data['aggregated_quality_flag'] - == uint8_nan))) - - valid = (valid & ((orbit.data['snow_cover_probability'] - < snow_cover_probability) - | (orbit.data['snow_cover_probability'] - == float32_nan))) - - valid = (valid & ((orbit.data['frozen_soil_probability'] - < frozen_soil_probability) - | (orbit.data['frozen_soil_probability'] - == float32_nan))) - - valid = (valid & ((orbit.data['innudation_or_wetland'] - < innudation_or_wetland) | - (orbit.data['innudation_or_wetland'] - == float32_nan))) - - valid = (valid & ((orbit.data['topographical_complexity'] - < topographical_complexity) - | (orbit.data['topographical_complexity'] - == float32_nan))) - - valid_num = orbit.data['jd'][valid].shape[0] - masked_data = get_template_ASCATL2_SMX(valid_num) - - for key in orbit.data.dtype.names: - masked_data[key] = orbit.data[key][valid] - - img = Image(orbit.lon[valid], orbit.lat[valid], masked_data, - orbit.metadata, orbit.timestamp, timekey='jd') - - return img - - def resample_data(self, data, index, distance, windowRadius, **kwargs): - """ - - Parameters - ---------- - - - Returns - ------- - img : pygeobase.object_base.Image - ASCAT swath image with masking applied. - - """ - # target template - template = get_resample_template_ASCATL2_SMX() - res_orbit = np.repeat(template, index.shape[0]) - - # get weights - weights, _ = hamming_window(windowRadius, distance) - - # resample soil moiusture variables [%] - sm = ['sm', 'sm_noise', 'mean_surf_sm'] - - for n in sm: - # account for nan values: remove them from calculation by setting - # them to np.nan and using np.nansum later on - data[n][data[n] == float32_nan] = np.nan - # the weighting also depends on nan values of the data - # if we don't use a data value we have to exclude the - # corresponding weight from the total_weights calculation - weights_exc = weights.copy() - weights_exc[np.isnan(data[n])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[n] = (np.nansum(data[n][index] * weights, axis=1) - / total_weights_exc) - # set the empty values to nan to keep consistency and avoid - # 0 which could also be an actual value - res_orbit[n][np.isnan(res_orbit[n])] = float32_nan - res_orbit[n][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # resample dB variables - fields = ['sigf', 'sigm', 'siga', 'sig40', 'sig40_noise', - 'slope40', 'slope40_noise', 'sm_sensitivity', - 'dry_backscatter', 'wet_backscatter'] - - for sigma in fields: - data[sigma][data[sigma] == float32_nan] = np.nan - - weights_exc = weights.copy() - weights_exc[np.isnan(data[sigma])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[sigma] = lin2db(np.nansum(db2lin(data[sigma])[index] - * weights, - axis=1) - / total_weights_exc) - res_orbit[sigma][np.isnan(res_orbit[sigma])] = float32_nan - res_orbit[sigma][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # resample measurement geometry - measgeos = ['incf', 'incm', 'inca', 'azif', 'azim', 'azia'] - - for mg in measgeos: - data[mg][data[mg] == float32_nan] = np.nan - - weights_exc = weights.copy() - weights_exc[np.isnan(data[mg])[index]] = np.nan - total_weights_exc = np.nansum(weights, axis=1) - res_orbit[mg] = (np.nansum(data[mg][index] * weights, axis=1) - / total_weights_exc) - res_orbit[mg][np.isnan(res_orbit[mg])] = float32_nan - res_orbit[mg][np.nansum(weights_exc, axis=1) == 0] = float32_nan - - # nearest neighbour resampling values - nnResample = ['jd', 'sat_id', 'abs_line_nr', 'abs_orbit_nr', - 'node_num', 'line_num', 'swath', 'as_des_pass'] - # index of min. distance is equal to 0 because of kd-tree usage - for nn in nnResample: - res_orbit[nn] = data[nn][index][:, 0] - - # set number of measurements for resampling - res_orbit['num_obs'] = np.sum(distance != np.inf, axis=1) - - return res_orbit - - def write(self, *args, **kwargs): - pass - - def flush(self): - pass - - def close(self): - pass - - -class AscatL2Bufr(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level2 images in bufr format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: '*-ASCA-*-NA-*-%Y%m%d*.bfr' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: '*-ASCA-*-NA-*-{datetime}*.bfr' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - msg_name_lookup: dict, optional - Dictionary mapping bufr msg number to parameter name. - See bufr.AscatL1BufrFile - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='*-ASCA-*-NA-*-%Y%m%d*-*-*.bfr', - file_search_str='*-ASCA-*-NA-*-{datetime}.*.bfr', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(25, 39, '%Y%m%d%H%M%S'), - msg_name_lookup=None, - eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL2Bufr, self).__init__( - path, AscatL2Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False, ioclass_kws={'msg_name_lookup': - msg_name_lookup}) - - def _get_orbit_start_date(self, filename): - """ - Returns the datetime of the file. - - Parameters - ---------- - filename : full name (including the path) of the file - - Returns - ------- - dates : datetime object - datetime from the filename - """ - # if your data comes from the EUMETSAT EO Portal this function can - if self.eo_portal is True: - filename_base = os.path.basename(filename) - fln_spl = filename_base.split('-')[5] - fln_datetime = fln_spl.split('.')[0] - return datetime.strptime(fln_datetime, self.datetime_format) - - else: - orbit_start_str = os.path.basename(filename)[ - self.filename_datetime_format[0]: - self.filename_datetime_format[1]] - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) - - -class AscatL2Eps(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level2 images in eps format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: 'ASCA_*_*_*_%Y%m%d*_*_*_*_*.nat' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: 'ASCA_*_*_*_{datetime}Z_*_*_*_*.nat' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='ASCA_*_*_*_%Y%m%d*_*_*_*_*.nat', - file_search_str='ASCA_*_*_*_{datetime}Z_*_*_*_*.nat', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(16, 30, '%Y%m%d%H%M%S'), - eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL2Eps, self).__init__( - path, AscatL2Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False) - - -class AscatL2Nc(ASCAT_MultiTemporalImageBase): - """ - Class for reading multiple ASCAT level2 images in nc format. - - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month then please specify the - string that should be used in datetime.datetime.strftime - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. - Default: 'W_XX-*_EUMP_%Y%m%d*.nc' - file_search_str: string, optional - this string is used to find a bufr file by the exact date. - Default: 'W_XX-*_EUMP_{datetime}*.nc' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d%H%M%S - msg_name_lookup: dict, optional - Dictionary mapping nc msg number to parameter name. - See nc.AscatL1NcFile - eo_portal : boolean optional - If your data is from the EUMETSAT EO portal you can set this flag to - True. This way the the datetime can automatically be read from the - filename. Otherwise it needs the filename_datetime_format class - variable set correctly. - """ - - def __init__(self, path, month_path_str='', - day_search_str='W_XX-*_EUMP_%Y%m%d*.nc', - file_search_str='W_XX-*_EUMP_{datetime}*.nc', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(62, 76, '%Y%m%d%H%M%S'), - msg_name_lookup=None, eo_portal=False): - - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.datetime_format = datetime_format - self.filename_datetime_format = filename_datetime_format - self.eo_portal = eo_portal - - super(AscatL2Nc, self).__init__( - path, AscatL2Image, subpath_templ=[month_path_str], - fname_templ=file_search_str, datetime_format=datetime_format, - exact_templ=False, ioclass_kws={'msg_name_lookup': - msg_name_lookup}) - - -def get_file_format(filename): - """ - Try to guess the file format from the extension. - """ - if os.path.splitext(filename)[1] == '.gz': - file_format = os.path.splitext(os.path.splitext(filename)[0])[1] - else: - file_format = os.path.splitext(filename)[1] - return file_format - - -def nc2generic(native_img): - """ - Convert the native nc image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Generic images. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL2_SMX(n_records) - - fields = [('jd', 'jd'), - ('sat_id', None), - ('abs_line_nr', None), - ('abs_orbit_nr', None), - ('node_num', 'node_num'), - ('line_num', 'line_num'), - ('as_des_pass', 'as_des_pass'), - ('swath', 'swath_indicator'), - ('azif', None), - ('azim', None), - ('azia', None), - ('incf', None), - ('incm', None), - ('inca', None), - ('sigf', None), - ('sigm', None), - ('siga', None), - ('sm', 'soil_moisture'), - ('sm_noise', 'soil_moisture_error'), - ('sm_sensitivity', 'soil_moisture_sensitivity'), - ('sig40', 'sigma40'), - ('sig40_noise', 'sigma40_error'), - ('slope40', 'slope40'), - ('slope40_noise', 'slope40_error'), - ('dry_backscatter', 'dry_backscatter'), - ('wet_backscatter', 'wet_backscatter'), - ('mean_surf_sm', 'mean_soil_moisture')] - - for field in fields: - if field[1] is None: - continue - - if type(native_img.data[field[1]]) == np.ma.core.MaskedArray: - valid_mask = ~native_img.data[field[1]].mask - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - if 'abs_line_number' in native_img.data: - generic_data['abs_line_nr'] = native_img.data['abs_line_number'] - - # flag_fields need to be treated differently since they are not masked - # arrays so we need to check for nan values - flags = [('correction_flag', 'corr_flags'), - # There is a processing flag but it is different to the other - # formats - ('processing_flag', None), - ('aggregated_quality_flag', 'aggregated_quality_flag'), - ('snow_cover_probability', 'snow_cover_probability'), - ('frozen_soil_probability', 'frozen_soil_probability'), - ('innudation_or_wetland', 'wetland_flag'), - ('topographical_complexity', 'topography_flag')] - - for field in flags: - if field[1] is None: - continue - - valid_mask = (native_img.data[field[1]] != ubyte_nan) - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - - fields = [('sat_id', 'sat_id'), - ('abs_orbit_nr', 'orbit_start')] - - for field in fields: - generic_data[field[0]] = np.repeat(native_img.metadata[field[1]], - n_records) - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def eps2generic(native_img): - """ - Convert the native eps Image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Converted image. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL2_SMX(n_records) - - fields = [('jd', 'jd', None), - ('sat_id', None, None), - ('abs_line_nr', 'ABS_LINE_NUMBER', None), - ('abs_orbit_nr', None, None), - ('node_num', 'NODE_NUM', None), - ('line_num', 'LINE_NUM', None), - ('as_des_pass', 'AS_DES_PASS', None), - ('swath', 'SWATH_INDICATOR', byte_nan), - ('azif', 'f_AZI_ANGLE_TRIP', int_nan), - ('azim', 'm_AZI_ANGLE_TRIP', int_nan), - ('azia', 'a_AZI_ANGLE_TRIP', int_nan), - ('incf', 'f_INC_ANGLE_TRIP', uint16_nan), - ('incm', 'm_INC_ANGLE_TRIP', uint16_nan), - ('inca', 'a_INC_ANGLE_TRIP', uint16_nan), - ('sigf', 'f_SIGMA0_TRIP', long_nan), - ('sigm', 'm_SIGMA0_TRIP', long_nan), - ('siga', 'a_SIGMA0_TRIP', long_nan), - ('sm', 'SOIL_MOISTURE', uint16_nan), - ('sm_noise', 'SOIL_MOISTURE_ERROR', uint16_nan), - ('sm_sensitivity', 'SOIL_MOISTURE_SENSETIVITY', - np.float32(uint32_nan)), - ('sig40', 'SIGMA40', long_nan), - ('sig40_noise', 'SIGMA40_ERROR', long_nan), - ('slope40', 'SLOPE40', long_nan), - ('slope40_noise', 'SLOPE40_ERROR', long_nan), - ('dry_backscatter', 'DRY_BACKSCATTER', long_nan), - ('wet_backscatter', 'WET_BACKSCATTER', long_nan), - ('mean_surf_sm', 'MEAN_SURF_SOIL_MOISTURE', uint16_nan), - ('correction_flag', 'CORRECTION_FLAGS', uint16_nan), - ('processing_flag', 'PROCESSING_FLAGS', uint16_nan), - ( - 'aggregated_quality_flag', 'AGGREGATED_QUALITY_FLAG', ubyte_nan), - ('snow_cover_probability', 'SNOW_COVER_PROBABILITY', ubyte_nan), - ( - 'frozen_soil_probability', 'FROZEN_SOIL_PROBABILITY', ubyte_nan), - ('innudation_or_wetland', 'INNUDATION_OR_WETLAND', ubyte_nan), - ('topographical_complexity', 'TOPOGRAPHICAL_COMPLEXITY', - ubyte_nan)] - - for field in fields: - if field[1] is None: - continue - - if field[2] is not None: - valid_mask = (native_img.data[field[1]] != field[2]) - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - fields = [('sat_id', 'SPACECRAFT_ID'), ('abs_orbit_nr', 'ORBIT_START')] - - for field in fields: - generic_data[field[0]] = np.repeat(native_img.metadata[field[1]], - n_records) - - # convert sat_id (spacecraft id) to the department intern definition - # use an array as look up table - sat_id_lut = np.array([0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def bfr2generic(native_img): - """ - Convert the native bfr image into a generic one. - - Parameters - ---------- - native_img : pygeobase.object_base.Image - Native image. - - Returns - ------- - img : pygeobase.object_base.Image - Generic images. - """ - n_records = native_img.lat.shape[0] - generic_data = get_template_ASCATL2_SMX(n_records) - - fields = [('jd', 'jd', None), - ('sat_id', 'Satellite Identifier', None), - ('abs_line_nr', None, None), - ('abs_orbit_nr', 'Orbit Number', None), - ('node_num', 'Cross-Track Cell Number', None), - ('line_num', 'line_num', None), - ('as_des_pass', 'as_des_pass', None), - ('swath', 'swath_indicator', None), - ('azif', 'f_Antenna Beam Azimuth', 1.7e+38), - ('azim', 'm_Antenna Beam Azimuth', 1.7e+38), - ('azia', 'a_Antenna Beam Azimuth', 1.7e+38), - ('incf', 'f_Radar Incidence Angle', 1.7e+38), - ('incm', 'm_Radar Incidence Angle', 1.7e+38), - ('inca', 'a_Radar Incidence Angle', 1.7e+38), - ('sigf', 'f_Backscatter', 1.7e+38), - ('sigm', 'm_Backscatter', 1.7e+38), - ('siga', 'a_Backscatter', 1.7e+38), - ('sm', 'Surface Soil Moisture (Ms)', 1.7e+38), - ( - 'sm_noise', 'Estimated Error In Surface Soil Moisture', 1.7e+38), - ('sm_sensitivity', 'Soil Moisture Sensitivity', 1.7e+38), - ('sig40', 'Backscatter', 1.7e+38), - ('sig40_noise', - 'Estimated Error In Sigma0 At 40 Deg Incidence Angle', 1.7e+38), - ('slope40', 'Slope At 40 Deg Incidence Angle', 1.7e+38), - ('slope40_noise', - 'Estimated Error In Slope At 40 Deg Incidence Angle', 1.7e+38), - ('dry_backscatter', 'Dry Backscatter', 1.7e+38), - ('wet_backscatter', 'Wet Backscatter', 1.7e+38), - ('mean_surf_sm', 'Mean Surface Soil Moisture', 1.7e+40), - ('correction_flag', 'Soil Moisture Correction Flag', 1.7e+38), - ('processing_flag', 'Soil Moisture Processing Flag', 1.7e+38), - ('aggregated_quality_flag', None), - ('snow_cover_probability', 'Snow Cover', 1.7e+38), - ('frozen_soil_probability', 'Frozen Land Surface Fraction', - 1.7e+38), - ('innudation_or_wetland', 'Inundation And Wetland Fraction', - 1.7e+38), - ('topographical_complexity', 'Topographic Complexity', 1.7e+38)] - - for field in fields: - if field[1] is None: - continue - - if field[2] is not None: - valid_mask = (native_img.data[field[1]] != field[2]) - generic_data[field[0]][valid_mask] = native_img.data[field[1]][ - valid_mask] - else: - generic_data[field[0]] = native_img.data[field[1]] - - # convert sat_id (spacecraft id) to the intern definition - sat_id_lut = np.array([0, 0, 0, 4, 3, 5]) - generic_data['sat_id'] = sat_id_lut[generic_data['sat_id']] - - img = Image(native_img.lon, native_img.lat, generic_data, - native_img.metadata, native_img.timestamp, - timekey='jd') - - return img - - -def get_template_ASCATL2_SMX(n=1): - """ - Generic Level 2 SMX template. - - Parameters - ---------- - n : int, optional - Number of records (default: 1). - - Returns - ------- - records : numpy.ndarray - Array filled with default values. - """ - metadata = {'temp_name': 'ASCATL2'} - - struct = np.dtype([('jd', np.float64), - ('sat_id', np.byte), - ('abs_line_nr', np.uint32), - ('abs_orbit_nr', np.uint32), - ('node_num', np.uint8), - ('line_num', np.uint16), - ('as_des_pass', np.byte), - ('swath', np.byte), - ('azif', np.float32), - ('azim', np.float32), - ('azia', np.float32), - ('incf', np.float32), - ('incm', np.float32), - ('inca', np.float32), - ('sigf', np.float32), - ('sigm', np.float32), - ('siga', np.float32), - ('sm', np.float32), - ('sm_noise', np.float32), - ('sm_sensitivity', np.float32), - ('sig40', np.float32), - ('sig40_noise', np.float32), - ('slope40', np.float32), - ('slope40_noise', np.float32), - ('dry_backscatter', np.float32), - ('wet_backscatter', np.float32), - ('mean_surf_sm', np.float32), - ('correction_flag', np.uint8), - ('processing_flag', np.uint16), - ('aggregated_quality_flag', np.uint8), - ('snow_cover_probability', np.float32), - ('frozen_soil_probability', np.float32), - ('innudation_or_wetland', np.float32), - ('topographical_complexity', np.float32)], - metadata=metadata) - - record = np.array([(float64_nan, byte_nan, uint32_nan, uint32_nan, - uint8_nan, uint16_nan, byte_nan, byte_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, uint8_nan, uint16_nan, - uint8_nan, float32_nan, float32_nan, float32_nan, - float32_nan)], dtype=struct) - - return np.repeat(record, n) - - -def get_resample_template_ASCATL2_SMX(n=1): - """ - Generic Level 2 SMX template. - - Parameters - ---------- - n : int, optional - Number of records (default: 1). - - Returns - ------- - records : numpy.ndarray - Array filled with default values. - """ - metadata = {'temp_name': 'ASCATL2'} - - struct = np.dtype([('jd', np.float64), - ('sat_id', np.byte), - ('abs_line_nr', np.uint32), - ('abs_orbit_nr', np.uint32), - ('node_num', np.uint8), - ('line_num', np.uint16), - ('as_des_pass', np.byte), - ('swath', np.byte), - ('azif', np.float32), - ('azim', np.float32), - ('azia', np.float32), - ('incf', np.float32), - ('incm', np.float32), - ('inca', np.float32), - ('sigf', np.float32), - ('sigm', np.float32), - ('siga', np.float32), - ('sm', np.float32), - ('sm_noise', np.float32), - ('sm_sensitivity', np.float32), - ('sig40', np.float32), - ('sig40_noise', np.float32), - ('slope40', np.float32), - ('slope40_noise', np.float32), - ('dry_backscatter', np.float32), - ('wet_backscatter', np.float32), - ('mean_surf_sm', np.float32), - ('num_obs', np.uint16)], metadata=metadata) - - record = np.array([(float64_nan, byte_nan, uint32_nan, uint32_nan, - uint8_nan, uint16_nan, byte_nan, byte_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, float32_nan, float32_nan, - float32_nan, float32_nan, uint16_nan)], dtype=struct) - - return np.repeat(record, n) diff --git a/src/ascat/read_native/bufr.py b/src/ascat/read_native/bufr.py index e0b8eae..ae15711 100644 --- a/src/ascat/read_native/bufr.py +++ b/src/ascat/read_native/bufr.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -25,100 +25,57 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - """ -Readers for lvl1b and lvl2 data in bufr format. +Readers for ASCAT Level 1b and Level 2 data in BUFR format. """ import os -from datetime import datetime, timedelta import warnings -from tempfile import NamedTemporaryFile -from gzip import GzipFile +from collections import defaultdict import numpy as np +import xarray as xr +from cadati.cal_date import cal2dt -from pygeobase.io_base import ImageBase -from pygeobase.io_base import MultiTemporalImageBase -from pygeobase.io_base import IntervalReadingMixin -from pygeobase.object_base import Image +from ascat.utils import tmp_unzip try: from pybufr_ecmwf import raw_bufr_file from pybufr_ecmwf import ecmwfbufr from pybufr_ecmwf import ecmwfbufr_parameters except ImportError: - warnings.warn('pybufr-ecmwf not imported, BUFR format cannot be read') + warnings.warn( + 'pybufr-ecmwf can not be imported, BUFR data cannot be read.') -class AscatL1BufrFile(ImageBase): - """ - Reads ASCAT L1b data in BUFR format. +bufr_nan = 1.7e+38 +float32_nan = -999999. +uint8_nan = np.iinfo(np.uint8).max - Parameters - ---------- - filename : str - Filename path. - mode : str, optional - Opening mode. Default: r - msg_name_lookup: dict, optional - Dictionary mapping bufr msg number to parameter name. - See :ref:`ascatformattable`. - - Default: - - === ===================================================== - Key Value - === ===================================================== - 4: "Satellite Identifier", - 6: "Direction Of Motion Of Moving Observing Platform", - 16: "Orbit Number", - 17: "Cross-Track Cell Number", - 21: "f_Beam Identifier", - 22: "f_Radar Incidence Angle", - 23: "f_Antenna Beam Azimuth", - 24: "f_Backscatter", - 25: "f_Radiometric Resolution (Noise Value)", - 26: "f_ASCAT KP Estimate Quality", - 27: "f_ASCAT Sigma-0 Usability", - 34: "f_ASCAT Land Fraction", - 35: "m_Beam Identifier", - 36: "m_Radar Incidence Angle", - 37: "m_Antenna Beam Azimuth", - 38: "m_Backscatter", - 39: "m_Radiometric Resolution (Noise Value)", - 40: "m_ASCAT KP Estimate Quality", - 41: "m_ASCAT Sigma-0 Usability", - 48: "m_ASCAT Land Fraction", - 49: "a_Beam Identifier", - 50: "a_Radar Incidence Angle", - 51: "a_Antenna Beam Azimuth", - 52: "a_Backscatter", - 53: "a_Radiometric Resolution (Noise Value)", - 54: "a_ASCAT KP Estimate Quality", - 55: "a_ASCAT Sigma-0 Usability", - 62: "a_ASCAT Land Fraction" - === ===================================================== + +class AscatL1bBufrFile: + + """ + Read ASCAT Level 1b file in BUFR format. """ - def __init__(self, filename, mode='r', msg_name_lookup=None, **kwargs): + def __init__(self, filename, msg_name_lookup=None): """ - Initialization of i/o object. + Initialize AscatL1bBufrFile. + Parameters + ---------- + filename : str + Filename. + msg_name_lookup: dict, optional + Dictionary mapping bufr msg number to parameter name. + See :ref:`ascatformattable`. """ - zipped = False if os.path.splitext(filename)[1] == '.gz': - zipped = True - - # for zipped files use an unzipped temporary copy - if zipped: - with NamedTemporaryFile(delete=False) as tmp_fid: - with GzipFile(filename) as gz_fid: - tmp_fid.write(gz_fid.read()) - filename = tmp_fid.name + self.filename = tmp_unzip(filename) + else: + self.filename = filename - super(AscatL1BufrFile, self).__init__(filename, mode=mode, - **kwargs) if msg_name_lookup is None: msg_name_lookup = { 4: "Satellite Identifier", @@ -149,227 +106,226 @@ def __init__(self, filename, mode='r', msg_name_lookup=None, **kwargs): 54: "a_ASCAT KP Estimate Quality", 55: "a_ASCAT Sigma-0 Usability", 62: "a_ASCAT Land Fraction"} + self.msg_name_lookup = msg_name_lookup - def read(self, timestamp=None): + def read(self, generic=False, to_xarray=False): """ - Read specific image for given datetime timestamp. + Read ASCAT Level 1b data. Parameters ---------- - timestamp : datetime.datetime - exact observation timestamp of the image that should be read + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). Returns ------- - data : dict - dictionary of numpy arrays that hold the image data for each - variable of the dataset - metadata : dict - dictionary of numpy arrays that hold the metadata - timestamp : datetime.datetime - exact timestamp of the image - lon : numpy.array or None - array of longitudes, if None self.grid will be assumed - lat : numpy.array or None - array of latitudes, if None self.grid will be assumed - time_var : string or None - variable name of observation times in the data dict, if None all - observations have the same timestamp + ds : xarray.Dataset, numpy.ndarray + ASCAT Level 1b data. """ - # lookup table between names and message number in the BUFR file - - data = {} - dates = [] - # 13: Latitude (High Accuracy) - latitude = [] - # 14: Longitude (High Accuracy) - longitude = [] + data = defaultdict(list) with BUFRReader(self.filename) as bufr: for message in bufr.messages(): - # read fixed fields - latitude.append(message[:, 12]) - longitude.append(message[:, 13]) - years = message[:, 6].astype(int) - months = message[:, 7].astype(int) - days = message[:, 8].astype(int) - hours = message[:, 9].astype(int) - minutes = message[:, 10].astype(int) + + # read lon/lat + data['lat'].append(message[:, 12].astype(np.float32)) + data['lon'].append(message[:, 13].astype(np.float32)) + + # read time + year = message[:, 6].astype(int) + month = message[:, 7].astype(int) + day = message[:, 8].astype(int) + hour = message[:, 9].astype(int) + minute = message[:, 10].astype(int) seconds = message[:, 11].astype(int) + milliseconds = np.zeros(seconds.size) + cal_dates = np.vstack(( + year, month, day, hour, minute, seconds, milliseconds)).T + data['time'].append(cal2dt(cal_dates)) + + # read data fields + for num, var_name in self.msg_name_lookup.items(): + data[var_name].append(message[:, num-1]) - dates.append( - julday(months, days, years, hours, minutes, seconds)) - - # read optional data fields - for mid in self.msg_name_lookup: - name = self.msg_name_lookup[mid] - - if name not in data: - data[name] = [] - - data[name].append(message[:, mid - 1]) - - dates = np.concatenate(dates) - longitude = np.concatenate(longitude) - latitude = np.concatenate(latitude) - n_records = latitude.shape[0] - - for mid in self.msg_name_lookup: - name = self.msg_name_lookup[mid] - data[name] = np.concatenate(data[name]) - - data['jd'] = dates - if 'Direction Of Motion Of Moving Observing Platform' in data: - data['as_des_pass'] = (data[ - "Direction Of Motion Of Moving Observing Platform" - ] < 270).astype(np.uint8) - - if 'Cross-Track Cell Number' in data: - if data['Cross-Track Cell Number'].max() == 82: - data['swath_indicator'] = 1 * ( - data['Cross-Track Cell Number'] > 41) - elif data['Cross-Track Cell Number'].max() == 42: - data['swath_indicator'] = 1 * ( - data['Cross-Track Cell Number'] > 21) - else: - raise ValueError("Unsuspected node number.") - n_lines = n_records / max(data['Cross-Track Cell Number']) - data['line_num'] = np.arange(n_lines).repeat( - max(data['Cross-Track Cell Number'])) - - # There are strange elements with a value of 32.32 instead of the - # typical nan_values + # concatenate lists to array + for var_name in data.keys(): + data[var_name] = np.concatenate(data[var_name]) + + # There can be suspicious values (32.32) instead of normal nan_values # Since some elements rly have this value we check the other triplet # data of that beam to filter the nan_values out - beams = ['f', 'm', 'a'] - for beam in beams: + for beam in ['f', 'm', 'a']: azi = beam + '_Antenna Beam Azimuth' sig = beam + '_Backscatter' inc = beam + '_Radar Incidence Angle' - if azi in data: - mask_azi = data[azi] == 32.32 - mask_sig = data[sig] == 1.7e+38 - mask_inc = data[inc] == 1.7e+38 - mask = np.all([mask_azi, mask_sig, mask_inc], axis=0) - data[azi][mask] = 1.7e+38 - - # 1 ERS 1 - # 2 ERS 2 - # 3 METOP-1 (Metop-B) - # 4 METOP-2 (Metop-A) - # 5 METOP-3 (Metop-C) - sat_id = {3: 1, 4: 2, 5: 3} - metadata = {} - metadata['SPACECRAFT_ID'] = np.int8( - sat_id[data['Satellite Identifier'][0]]) - metadata['ORBIT_START'] = np.uint32(data['Orbit Number'][0]) + mask = np.where((data[azi] == 32.32) & (data[sig] == bufr_nan) & + (data[inc] == bufr_nan)) + data[azi][mask] = bufr_nan - return Image(longitude, latitude, data, metadata, - timestamp, timekey='jd') - - def write(self, data): - raise NotImplementedError() - - def flush(self): - pass + metadata = {} + metadata['platform_id'] = data['Satellite Identifier'][0].astype(int) + metadata['orbit_start'] = np.uint32(data['Orbit Number'][0]) + metadata['filename'] = os.path.basename(self.filename) + + # add/rename/remove fields according to generic format + if generic: + data = conv_bufrl1b_generic(data, metadata) + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + for k in data.keys(): + if len(data[k].shape) == 1: + dim = ['obs'] + elif len(data[k].shape) == 2: + dim = ['obs', 'beam'] + + data[k] = (dim, data[k]) + + coords = {} + coords_fields = ['lon', 'lat', 'time'] + for cf in coords_fields: + coords[cf] = data.pop(cf) + + ds = xr.Dataset(data, coords=coords, attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + if len(data[var_name].shape) == 1: + dtype.append((var_name, data[var_name].dtype.str)) + elif len(data[var_name].shape) > 1: + dtype.append((var_name, data[var_name].dtype.str, + data[var_name].shape[1:])) + + ds = np.empty(data['time'].size, dtype=np.dtype(dtype)) + for k, v in data.items(): + ds[k] = v + + return ds def close(self): + """ + Close file. + """ pass -class AscatL2SsmBufrFile(ImageBase): +def conv_bufrl1b_generic(data, metadata): """ - Reads ASCAT SSM swath files in BUFR format. There are the - following products: - - - H101 SSM ASCAT-A NRT O 12.5 Metop-A ASCAT NRT SSM orbit geometry - 12.5 km sampling - - H102 SSM ASCAT-A NRT O 25.0 Metop-A ASCAT NRT SSM orbit geometry - 25 km sampling - - H16 SSM ASCAT-B NRT O 12.5 Metop-B ASCAT NRT SSM orbit geometry - 12.5 km sampling - - H103 SSM ASCAT-B NRT O 25.0 Metop-B ASCAT NRT SSM orbit geometry - 25 km sampling - - H104 SSM ASCAT-C NRT O 12.5 Metop-C ASCAT NRT SSM orbit geometry - 12.5 km sampling - - H105 SSM ASCAT-C NRT O 25.0 Metop-C ASCAT NRT SSM orbit geometry - 25 km sampling - - EUMETSAT ASCAT Soil Moisture at 12.5 km Swath Grid - Metop in BUFR format - - EUMETSAT ASCAT Soil Moisture at 25.0 km Swath Grid - Metop in BUFR format + Rename and convert data types of dataset. + + Spacecraft_id vs sat_id encoding + + BUFR encoding - Spacecraft_id + - 1 ERS 1 + - 2 ERS 2 + - 3 METOP-1 (Metop-B) + - 4 METOP-2 (Metop-A) + - 5 METOP-3 (Metop-C) + + Internal encoding - sat_id + - 1 ERS 1 + - 2 ERS 2 + - 3 METOP-2 (Metop-A) + - 4 METOP-1 (Metop-B) + - 5 METOP-3 (Metop-C) Parameters ---------- - filename : str - Filename path. - mode : str, optional - Opening mode. Default: r - msg_name_lookup: dict, optional - Dictionary mapping bufr msg number to parameter name. - See :ref:`ascatformattable`. - - Default: - - === ===================================================== - Key Value - === ===================================================== - 4: "Satellite Identifier", - 6: "Direction Of Motion Of Moving Observing Platform", - 16: "Orbit Number", - 17: "Cross-Track Cell Number", - 21: "f_Beam Identifier", - 22: "f_Radar Incidence Angle", - 23: "f_Antenna Beam Azimuth", - 24: "f_Backscatter", - 25: "f_Radiometric Resolution (Noise Value)", - 26: "f_ASCAT KP Estimate Quality", - 27: "f_ASCAT Sigma-0 Usability", - 34: "f_ASCAT Land Fraction", - 35: "m_Beam Identifier", - 36: "m_Radar Incidence Angle", - 37: "m_Antenna Beam Azimuth", - 38: "m_Backscatter", - 39: "m_Radiometric Resolution (Noise Value)", - 40: "m_ASCAT KP Estimate Quality", - 41: "m_ASCAT Sigma-0 Usability", - 48: "m_ASCAT Land Fraction", - 49: "a_Beam Identifier", - 50: "a_Radar Incidence Angle", - 51: "a_Antenna Beam Azimuth", - 52: "a_Backscatter", - 53: "a_Radiometric Resolution (Noise Value)", - 54: "a_ASCAT KP Estimate Quality", - 55: "a_ASCAT Sigma-0 Usability", - 62: "a_ASCAT Land Fraction", - 65: "Surface Soil Moisture (Ms)", - 66: "Estimated Error In Surface Soil Moisture", - 67: "Backscatter", - 68: "Estimated Error In Sigma0 At 40 Deg Incidence Angle", - 69: "Slope At 40 Deg Incidence Angle", - 70: "Estimated Error In Slope At 40 Deg Incidence Angle", - 71: "Soil Moisture Sensitivity", - 72: "Dry Backscatter", - 73: "Wet Backscatter", - 74: "Mean Surface Soil Moisture", - 75: "Rain Fall Detection", - 76: "Soil Moisture Correction Flag", - 77: "Soil Moisture Processing Flag", - 78: "Soil Moisture Quality", - 79: "Snow Cover", - 80: "Frozen Land Surface Fraction", - 81: "Inundation And Wetland Fraction", - 82: "Topographic Complexity" - === ===================================================== + data: dict of numpy.ndarray + Original dataset. + metadata: dict + Metadata. + + Returns + ------- + data: dict of numpy.ndarray + Converted dataset. """ + skip_fields = ['Satellite Identifier'] + + gen_fields_beam = { + 'Radar Incidence Angle': ('inc', np.float32, bufr_nan, 1), + 'Backscatter': ('sig', np.float32, bufr_nan, 1), + 'Antenna Beam Azimuth': ('azi', np.float32, bufr_nan, 1), + 'ASCAT Sigma-0 Usability': ('f_usable', np.uint8, None, 1), + 'Beam Identifier': ('beam_num', np.uint8, None, 1), + 'Radiometric Resolution (Noise Value)': ('kp', np.float32, bufr_nan, 0.01), + 'ASCAT KP Estimate Quality': ('kp_quality', np.uint8, bufr_nan, 1), + 'ASCAT Land Fraction': ('f_land', np.float32, None, 1)} + + gen_fields_lut = { + 'Orbit Number': ('abs_orbit_nr', np.int32), + 'Cross-Track Cell Number': ('node_num', np.uint8), + 'Direction Of Motion Of Moving Observing Platform': + ('sat_track_azi', np.float32)} + + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) + + for var_name, (new_name, new_dtype) in gen_fields_lut.items(): + data[new_name] = data.pop(var_name).astype(new_dtype) + + for var_name, (new_name, new_dtype, nan_val, s) in gen_fields_beam.items(): + f = ['{}_{}'.format(b, var_name) for b in ['f', 'm', 'a']] + data[new_name] = np.vstack( + (data.pop(f[0]), data.pop(f[1]), + data.pop(f[2]))).T.astype(new_dtype) + if nan_val is not None: + valid = data[new_name] != nan_val + data[new_name][~valid] = float32_nan + data[new_name][valid] *= s + + if data['node_num'].max() == 82: + data['swath_indicator'] = 1 * (data['node_num'] > 41) + elif data['node_num'].max() == 42: + data['swath_indicator'] = 1 * (data['node_num'] > 21) + else: + raise ValueError('Cross-track cell number size unknown') + + n_lines = data['lat'].shape[0] / data['node_num'].max() + data['line_num'] = np.arange(n_lines).repeat(data['node_num'].max()) + + sat_id = np.array([0, 0, 0, 4, 3, 5], dtype=np.uint8) + data['sat_id'] = np.zeros(data['time'].size, dtype=np.uint8) + sat_id[ + int(metadata['platform_id'])] + + # compute ascending/descending direction + data['as_des_pass'] = (data['sat_track_azi'] < 270).astype(np.uint8) + + return data + + +class AscatL2BufrFile(): - def __init__(self, filename, mode='r', msg_name_lookup=None, **kwargs): + """ + Read ASCAT Level 2 file in BUFR format. + """ + + def __init__(self, filename, msg_name_lookup=None): """ - Initialization of i/o object. + Initialize AscatL2BufrFile. + Parameters + ---------- + filename: str + Filename. + msg_name_lookup: dict, optional + Dictionary mapping bufr msg number to parameter name. + See: ref: `ascatformattable`. """ - super(AscatL2SsmBufrFile, self).__init__(filename, mode=mode, - **kwargs) + if os.path.splitext(filename)[1] == '.gz': + self.filename = tmp_unzip(filename) + else: + self.filename = filename + if msg_name_lookup is None: msg_name_lookup = { 4: "Satellite Identifier", @@ -418,424 +374,245 @@ def __init__(self, filename, mode='r', msg_name_lookup=None, **kwargs): 80: "Frozen Land Surface Fraction", 81: "Inundation And Wetland Fraction", 82: "Topographic Complexity"} + self.msg_name_lookup = msg_name_lookup - def read(self, timestamp=None, ssm_masked=False): + def read(self, generic=False, to_xarray=False): """ - Read specific image for given datetime timestamp. + Read ASCAT Level 2 data. Parameters ---------- - timestamp : datetime.datetime (optional) - exact observation timestamp of the image that should be read - ssm_masked : flag (optional) - set to True to filter data by ssm values - + generic: bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names(default: False). + to_xarray: bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray(default: False). Returns ------- - data : dict - dictionary of numpy arrays that hold the image data for each - variable of the dataset - metadata : dict - dictionary of numpy arrays that hold the metadata - timestamp : datetime.datetime - exact timestamp of the image - lon : numpy.array or None - array of longitudes, if None self.grid will be assumed - lat : numpy.array or None - array of latitudes, if None self.grid will be assumed - time_var : string or None - variable name of observation times in the data dict, if None all - observations have the same timestamp + ds: xarray.Dataset, numpy.ndarray + ASCAT Level 1b data. """ - # lookup table between names and message number in the BUFR file - - data = {} - dates = [] - # 13: Latitude (High Accuracy) - latitude = [] - # 14: Longitude (High Accuracy) - longitude = [] + data = defaultdict(list) with BUFRReader(self.filename) as bufr: for message in bufr.messages(): - # read fixed fields - latitude.append(message[:, 12]) - longitude.append(message[:, 13]) - years = message[:, 6].astype(int) - months = message[:, 7].astype(int) - days = message[:, 8].astype(int) - hours = message[:, 9].astype(int) - minutes = message[:, 10].astype(int) - seconds = message[:, 11].astype(int) - dates.append( - julday(months, days, years, hours, minutes, seconds)) - - # read optional data fields - for mid in self.msg_name_lookup: - name = self.msg_name_lookup[mid] - - if name not in data: - data[name] = [] - - data[name].append(message[:, mid - 1]) - - dates = np.concatenate(dates) - longitude = np.concatenate(longitude) - latitude = np.concatenate(latitude) - n_records = latitude.shape[0] - - for mid in self.msg_name_lookup: - name = self.msg_name_lookup[mid] - data[name] = np.concatenate(data[name]) - if mid == 74: - # ssm mean is encoded differently - data[name] = data[name] * 100 - - data['jd'] = dates - - if 'Direction Of Motion Of Moving Observing Platform' in data: - data['as_des_pass'] = (data[ - "Direction Of Motion Of Moving Observing Platform"] - <= 270).astype(np.uint8) - - if 'Cross-Track Cell Number' in data: - if data['Cross-Track Cell Number'].max() == 82: - data['swath_indicator'] = 1 * ( - data['Cross-Track Cell Number'] > 41) - elif data['Cross-Track Cell Number'].max() == 42: - data['swath_indicator'] = 1 * ( - data['Cross-Track Cell Number'] > 21) - else: - raise ValueError("Unsuspected node number.") - n_lines = n_records / max(data['Cross-Track Cell Number']) - data['line_num'] = np.arange(n_lines).repeat( - max(data['Cross-Track Cell Number'])) - - # There are strange elements with a value of 32.32 instead of the - # typical nan_values + # read lon/lat + data['lat'].append(message[:, 12].astype(np.float32)) + data['lon'].append(message[:, 13].astype(np.float32)) + + # read time + year = message[:, 6].astype(int) + month = message[:, 7].astype(int) + day = message[:, 8].astype(int) + hour = message[:, 9].astype(int) + minute = message[:, 10].astype(int) + seconds = message[:, 11].astype(int) + milliseconds = np.zeros(seconds.size) + cal_dates = np.vstack(( + year, month, day, hour, minute, seconds, milliseconds)).T + data['time'].append(cal2dt(cal_dates)) + + # read data fields + for num, var_name in self.msg_name_lookup.items(): + data[var_name].append(message[:, num - 1]) + + # concatenate lists to array + for var_name in data.keys(): + data[var_name] = np.concatenate(data[var_name]) + # fix scaling + if var_name == 'Mean Surface Soil Moisture': + data[var_name][data[var_name] != bufr_nan] *= 100. + + # There can be suspicious values (32.32) instead of normal nan_values # Since some elements rly have this value we check the other triplet # data of that beam to filter the nan_values out - beams = ['f', 'm', 'a'] - for beam in beams: + for beam in ['f', 'm', 'a']: azi = beam + '_Antenna Beam Azimuth' sig = beam + '_Backscatter' inc = beam + '_Radar Incidence Angle' - if azi in data: - mask_azi = data[azi] == 32.32 - mask_sig = data[sig] == 1.7e+38 - mask_inc = data[inc] == 1.7e+38 - mask = np.all([mask_azi, mask_sig, mask_inc], axis=0) - data[azi][mask] = 1.7e+38 - - # if the ssm_masked is True we mask out data with missing ssm value - if 65 in self.msg_name_lookup and ssm_masked is True: - # mask all the arrays based on fill_value of soil moisture - valid_data = np.where(data[self.msg_name_lookup[65]] != 1.7e+38) - latitude = latitude[valid_data] - longitude = longitude[valid_data] - for name in data: - data[name] = data[name][valid_data] - - # 1 ERS 1 - # 2 ERS 2 - # 3 METOP-1 (Metop-B) - # 4 METOP-2 (Metop-A) - # 5 METOP-3 (Metop-C) - sat_id = {3: 1, 4: 2, 5: 3} - - metadata = {} - - try: - metadata['SPACECRAFT_ID'] = np.int8( - sat_id[data['Satellite Identifier'][0]]) - except KeyError: - metadata['SPACECRAFT_ID'] = 0 - try: - metadata['ORBIT_START'] = np.uint32(data['Orbit Number'][0]) - except KeyError: - metadata['ORBIT_START'] = 0 - - return Image(longitude, latitude, data, metadata, - timestamp, timekey='jd') - - def resample_data(self, image, index, distance, weights, **kwargs): - """ - Takes an image and resample (interpolate) the image data to - arbitrary defined locations given by index and distance. - - Parameters - ---------- - image : object - pygeobase.object_base.Image object - index : np.array - Index into image data defining a look-up table for data elements - used in the interpolation process for each defined target - location. - distance : np.array - Array representing the distances of the image data to the - arbitrary defined locations. - weights : np.array - Array representing the weights of the image data that should be - used during resampling. - The weights of points not to use are set to np.nan - This array is of shape (x, max_neighbors) + mask = np.where((data[azi] == 32.32) & (data[sig] == bufr_nan) & + (data[inc] == bufr_nan)) + data[azi][mask] = bufr_nan - Returns - ------- - image : object - pygeobase.object_base.Image object - """ - total_weights = np.nansum(weights, axis=1) - - resOrbit = {} - # resample backscatter - for name in image.dtype.names: - if name in ['Soil Moisture Correction Flag', - 'Soil Moisture Processing Flag']: - # The flags are resampled by taking the minimum flag This works - # since any totally valid observation has the flag 0 and - # overrides the flagged observations. This is true in cases - # where the data was set to NaN by the flag as well as when the - # data was set to 0 or 100. The last image element is the one - # standing for NaN so we fill it with all flags filled to not - # interfere with the minimum. - image[name][-1] = 255 - bits = np.unpackbits(image[name].reshape( - (-1, 1)).astype(np.uint8), axis=1) - resampled_bits = np.min(bits[index, :], axis=1) - resOrbit[name] = np.packbits(resampled_bits) - else: - resOrbit[name] = np.nansum( - image[name][index] * weights, axis=1) / total_weights - - return resOrbit - - def write(self, data): - raise NotImplementedError() - - def flush(self): - pass + metadata = {} + metadata['platform_id'] = data['Satellite Identifier'][0].astype(int) + metadata['orbit_start'] = np.uint32(data['Orbit Number'][0]) + metadata['filename'] = os.path.basename(self.filename) + + # add/rename/remove fields according to generic format + if generic: + data = conv_bufrl2_generic(data, metadata) + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + for k in data.keys(): + if len(data[k].shape) == 1: + dim = ['obs'] + elif len(data[k].shape) == 2: + dim = ['obs', 'beam'] + + data[k] = (dim, data[k]) + + coords = {} + coords_fields = ['lon', 'lat', 'time'] + for cf in coords_fields: + coords[cf] = data.pop(cf) + + ds = xr.Dataset(data, coords=coords, attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + if len(data[var_name].shape) == 1: + dtype.append((var_name, data[var_name].dtype.str)) + elif len(data[var_name].shape) > 1: + dtype.append((var_name, data[var_name].dtype.str, + data[var_name].shape[1:])) + + ds = np.empty(data['time'].size, dtype=np.dtype(dtype)) + for k, v in data.items(): + ds[k] = v + + return ds def close(self): pass -class AscatL2SsmBufr(MultiTemporalImageBase): +def conv_bufrl2_generic(data, metadata): """ - Class for reading HSAF ASCAT SSM images in bufr format. - The images have the same structure as the ASCAT 3 minute pdu files - and these 2 readers could be merged in the future - The images have to be uncompressed in the following folder structure - path - month_path_str (default 'h07_%Y%m_buf') + Rename and convert data types of dataset. - For example if path is set to /home/user/hsaf07 and month_path_str is left - to the default 'h07_%Y%m_buf' then the images for March 2012 have to be in - the folder /home/user/hsaf07/h07_201203_buf/ + Spacecraft_id vs sat_id encoding - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on the - HSAF FTP Server then please specify the string that should be used in - datetime.datetime.strftime Default: 'h07_%Y%m_buf' - day_search_str: string, optional - to provide an iterator over all images of a day the - method _get_possible_timestamps looks for all available images on a day - on the harddisk. This string is used in datetime.datetime.strftime and - in glob.glob to search for all files on a day. - Default : 'h07_%Y%m%d_*.buf' - file_search_str: string, optional - this string is used in datetime.datetime.strftime and glob.glob to find - a 3 minute bufr file by the exact date. - Default: 'h07_{datetime}*.buf' - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - Default: %Y%m%d_%H%M%S - msg_name_lookup: dict, optional - Dictionary mapping bufr msg number to parameter name. - See :ref:`ascatformattable`. - - Default: - - === ===================================================== - Key Value - === ===================================================== - 4: "Satellite Identifier", - 6: "Direction Of Motion Of Moving Observing Platform", - 16: "Orbit Number", - 17: "Cross-Track Cell Number", - 21: "f_Beam Identifier", - 22: "f_Radar Incidence Angle", - 23: "f_Antenna Beam Azimuth", - 24: "f_Backscatter", - 25: "f_Radiometric Resolution (Noise Value)", - 26: "f_ASCAT KP Estimate Quality", - 27: "f_ASCAT Sigma-0 Usability", - 34: "f_ASCAT Land Fraction", - 35: "m_Beam Identifier", - 36: "m_Radar Incidence Angle", - 37: "m_Antenna Beam Azimuth", - 38: "m_Backscatter", - 39: "m_Radiometric Resolution (Noise Value)", - 40: "m_ASCAT KP Estimate Quality", - 41: "m_ASCAT Sigma-0 Usability", - 48: "m_ASCAT Land Fraction", - 49: "a_Beam Identifier", - 50: "a_Radar Incidence Angle", - 51: "a_Antenna Beam Azimuth", - 52: "a_Backscatter", - 53: "a_Radiometric Resolution (Noise Value)", - 54: "a_ASCAT KP Estimate Quality", - 55: "a_ASCAT Sigma-0 Usability", - 62: "a_ASCAT Land Fraction", - 65: "Surface Soil Moisture (Ms)", - 66: "Estimated Error In Surface Soil Moisture", - 67: "Backscatter", - 68: "Estimated Error In Sigma0 At 40 Deg Incidence Angle", - 69: "Slope At 40 Deg Incidence Angle", - 70: "Estimated Error In Slope At 40 Deg Incidence Angle", - 71: "Soil Moisture Sensitivity", - 72: "Dry Backscatter", - 73: "Wet Backscatter", - 74: "Mean Surface Soil Moisture", - 75: "Rain Fall Detection", - 76: "Soil Moisture Correction Flag", - 77: "Soil Moisture Processing Flag", - 78: "Soil Moisture Quality", - 79: "Snow Cover", - 80: "Frozen Land Surface Fraction", - 81: "Inundation And Wetland Fraction", - 82: "Topographic Complexity" - === ===================================================== - """ - - def __init__(self, path, month_path_str='h07_%Y%m_buf', - day_search_str='h07_%Y%m%d_*.buf', - file_search_str='h07_{datetime}*.buf', - datetime_format='%Y%m%d_%H%M%S', - filename_datetime_format=(4, 19, '%Y%m%d_%H%M%S'), - msg_name_lookup=None): - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.filename_datetime_format = filename_datetime_format - super(AscatL2SsmBufr, self).__init__(path, AscatL2SsmBufrFile, - subpath_templ=[month_path_str], - fname_templ=file_search_str, - datetime_format=datetime_format, - exact_templ=False, - ioclass_kws={ - 'msg_name_lookup': - msg_name_lookup}) - - def _get_orbit_start_date(self, filename): - orbit_start_str = \ - os.path.basename(filename)[self.filename_datetime_format[0]: - self.filename_datetime_format[1]] - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) - - def tstamps_for_daterange(self, startdate, enddate): - """ - Get the timestamps as datetime array that are possible for the - given day. + BUFR encoding - Spacecraft_id + - 1 ERS 1 + - 2 ERS 2 + - 3 METOP-1 (Metop-B) + - 4 METOP-2 (Metop-A) + - 5 METOP-3 (Metop-C) - For this product it is not fixed but has to be looked up from - the hard disk since bufr files are not regular spaced and only - europe is in this product. For a global product a 3 minute - spacing could be used as a fist approximation - - Parameters - ---------- - startdate : datetime.date or datetime.datetime - start date - enddate : datetime.date or datetime.datetime - end date - - Returns - ------- - dates : list - list of datetimes - """ - file_list = [] - delta_all = enddate - startdate - timestamps = [] - - for i in range(delta_all.days + 1): - timestamp = startdate + timedelta(days=i) - - files = self._search_files( - timestamp, custom_templ=self.day_search_str) - - file_list.extend(sorted(files)) - - for filename in file_list: - timestamps.append(self._get_orbit_start_date(filename)) - - timestamps = [dt for dt in timestamps if ( - startdate <= dt <= enddate)] - return timestamps - - -class AscatL2SsmBufrChunked(IntervalReadingMixin, AscatL2SsmBufr): - """ - Reads BUFR files but does not return them on a file by file basis but in - bigger chunks. For example it allows to read multiple 3 minute PDU's in - half orbit chunks of 50 minutes. This speeds up operations like e.g. - resampling of the data. + Internal encoding - sat_id + - 1 ERS 1 + - 2 ERS 2 + - 3 METOP-2 (Metop-A) + - 4 METOP-1 (Metop-B) + - 5 METOP-3 (Metop-C) Parameters ---------- - chunk_minutes: int, optional - How many minutes should a chunk of data cover. - """ + data: dict of numpy.ndarray + Original dataset. + metadata: dict + Metadata. - def __init__(self, path, month_path_str='h07_%Y%m_buf', - day_search_str='h07_%Y%m%d_*.buf', - file_search_str='h07_{datetime}*.buf', - datetime_format='%Y%m%d_%H%M%S', - filename_datetime_format=(4, 19, '%Y%m%d_%H%M%S'), - msg_name_lookup=None, chunk_minutes=50): - super(AscatL2SsmBufrChunked, self).__init__( - path, - month_path_str=month_path_str, - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format, - msg_name_lookup=msg_name_lookup, - chunk_minutes=chunk_minutes) - - -class BUFRReader(object): + Returns + ------- + data: dict of numpy.ndarray + Converted dataset. """ - BUFR reader based on the pybufr-ecmwf package but faster - - Parameters - ---------- - filename : string - filename of the bufr file - kelem_guess : int, optional - if the elements per variable in as message are known - please specify here. - Otherwise the elements will be found out via trial and error - This works most of the time but is not 100 percent failsafe - Default: 500 - max_tries : int, optional - the Reader will try max_tries times to unpack a bufr message. - Some messages can not be read even if the array sizes are ok. - Most of the time these files are corrupt. + skip_fields = ['Satellite Identifier'] + + gen_fields_beam = { + 'Radar Incidence Angle': ('inc', np.float32, bufr_nan), + 'Backscatter': ('sig', np.float32, bufr_nan), + 'Antenna Beam Azimuth': ('azi', np.float32, bufr_nan), + 'ASCAT Sigma-0 Usability': ('f_usable', np.uint8, None), + 'Beam Identifier': ('beam_num', np.uint8, None), + 'Radiometric Resolution (Noise Value)': ('kp_noise', np.float32, bufr_nan), + 'ASCAT KP Estimate Quality': ('kp', np.float32, bufr_nan), + 'ASCAT Land Fraction': ('f_land', np.float32, None)} + + gen_fields_lut = { + 'Orbit Number': ('abs_orbit_nr', np.int32, None, None), + 'Cross-Track Cell Number': ('node_num', np.uint8, None, None), + 'Direction Of Motion Of Moving Observing Platform': ('sat_track_azi', np.float32, None, None), + 'Surface Soil Moisture (Ms)': ('sm', np.float32, bufr_nan, float32_nan), + 'Estimated Error In Surface Soil Moisture': ('sm_noise', np.float32, bufr_nan, float32_nan), + 'Backscatter': ('sig40', np.float32, bufr_nan, float32_nan), + 'Estimated Error In Sigma0 At 40 Deg Incidence Angle': ('sig40_noise', np.float32, bufr_nan, float32_nan), + 'Slope At 40 Deg Incidence Angle': ('slope40', np.float32, bufr_nan, float32_nan), + 'Estimated Error In Slope At 40 Deg Incidence Angle': ('slope40_noise', np.float32, bufr_nan, float32_nan), + 'Soil Moisture Sensitivity': ('sm_sens', np.float32, bufr_nan, float32_nan), + 'Dry Backscatter': ('dry_sig40', np.float32, bufr_nan, float32_nan), + 'Wet Backscatter': ('wet_sig40', np.float32, bufr_nan, float32_nan), + 'Mean Surface Soil Moisture': ('sm_mean', np.float32, bufr_nan, float32_nan), + 'Rain Fall Detection': ('rf', np.float32, None, None), + 'Soil Moisture Correction Flag': ('corr_flag', np.uint8, bufr_nan, uint8_nan), + 'Soil Moisture Processing Flag': ('proc_flag', np.uint8, bufr_nan, uint8_nan), + 'Soil Moisture Quality': ('agg_flag', np.uint8, bufr_nan, uint8_nan), + 'Snow Cover': ('snow_prob', np.uint8, bufr_nan, uint8_nan), + 'Frozen Land Surface Fraction': ('frozen_prob', np.uint8, bufr_nan, uint8_nan), + 'Inundation And Wetland Fraction': ('wetland', np.uint8, bufr_nan, uint8_nan), + 'Topographic Complexity': ('topo', np.uint8, bufr_nan, uint8_nan)} + + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) + + for var_name, (new_name, new_dtype, + nan_val, new_nan_val) in gen_fields_lut.items(): + if nan_val is not None: + data[var_name][data[var_name] == nan_val] = new_nan_val + data[new_name] = data.pop(var_name).astype(new_dtype) + + for var_name, (new_name, new_dtype, nan_val) in gen_fields_beam.items(): + f = ['{}_{}'.format(b, var_name) for b in ['f', 'm', 'a']] + data[new_name] = np.vstack( + (data.pop(f[0]), data.pop(f[1]), + data.pop(f[2]))).T.astype(new_dtype) + if nan_val is not None: + data[new_name][data[new_name] == nan_val] = float32_nan + + if data['node_num'].max() == 82: + data['swath_indicator'] = 1 * (data['node_num'] > 41) + elif data['node_num'].max() == 42: + data['swath_indicator'] = 1 * (data['node_num'] > 21) + else: + raise ValueError('Cross-track cell number size unknown') + + n_lines = data['lat'].shape[0] / data['node_num'].max() + data['line_num'] = np.arange(n_lines).repeat(data['node_num'].max()) + + sat_id = np.array([0, 0, 0, 4, 3, 5], dtype=np.uint8) + data['sat_id'] = np.zeros(data['time'].size, dtype=np.uint8) + sat_id[ + int(metadata['platform_id'])] + + # compute ascending/descending direction + data['as_des_pass'] = (data['sat_track_azi'] < 270).astype(np.uint8) + + return data + + +class BUFRReader(): """ + BUFR reader based on the pybufr-ecmwf package but faster. + """ def __init__(self, filename, kelem_guess=500, max_tries=10): + """ + + Parameters + ---------- + filename: string + filename of the bufr file + kelem_guess: int, optional + if the elements per variable in as message are known + please specify here. + Otherwise the elements will be found out via trial and error + This works most of the time but is not 100 percent failsafe + Default: 500 + max_tries: int, optional + the Reader will try max_tries times to unpack a bufr message. + Some messages can not be read even if the array sizes are ok. + Most of the time these files are corrupt. + """ self.bufr = raw_bufr_file.RawBUFRFile() self.bufr.open(filename, 'rb') self.nr_messages = self.bufr.get_num_bufr_msgs() @@ -859,14 +636,17 @@ def __init__(self, filename, kelem_guess=500, max_tries=10): def messages(self): """ + Read messages. + Raises ------ - IOError: + IOError: exception if a message cannot be unpacked after max_tries tries Returns ------- - data : yield results of messages + data: numpy.ndarray + Results of messages """ count = 0 for i in np.arange(self.nr_messages) + 1: @@ -894,9 +674,9 @@ def messages(self): kvals = ksup_first * kelem max_kelem = 500000 self.init_values = np.zeros(kvals, dtype=np.float64) - self.cvals = np.zeros((kvals, 80), dtype=np.character) - # try to expand bufr message with the first guess for - # kelem + self.cvals = np.zeros((kvals, 80), dtype='S1') + + # try to expand bufr message with the first guess for kelem increment_arraysize = True while increment_arraysize: cnames = np.zeros((kelem, 64), dtype='|S1') @@ -956,42 +736,3 @@ def __enter__(self): def __exit__(self, exc, val, trace): self.bufr.close() - - -def julday(month, day, year, hour=0, minute=0, second=0): - """ - Julian date from month, day, and year (can be scalars or arrays) - (function from pytesmo) - Parameters - ---------- - month : numpy.ndarray or int32 - Month. - day : numpy.ndarray or int32 - Day. - year : numpy.ndarray or int32 - Year. - hour : numpy.ndarray or int32, optional - Hour. - minute : numpy.ndarray or int32, optional - Minute. - second : numpy.ndarray or int32, optional - Second. - Returns - ------- - jul : numpy.ndarray or double - Julian day. - """ - month = np.array(month) - day = np.array(day) - inJanFeb = month <= 2 - jy = year - inJanFeb - jm = month + 1 + inJanFeb * 12 - - jul = np.int32(np.floor(365.25 * jy) + - np.floor(30.6001 * jm) + (day + 1720995.0)) - ja = np.int32(0.01 * jy) - jul += 2 - ja + np.int32(0.25 * ja) - - jul = jul + hour / 24.0 - 0.5 + minute / 1440.0 + second / 86400.0 - - return jul diff --git a/src/ascat/read_native/cdr.py b/src/ascat/read_native/cdr.py index 6d1c639..4413a5c 100644 --- a/src/ascat/read_native/cdr.py +++ b/src/ascat/read_native/cdr.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -26,24 +26,20 @@ # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import os -import glob import warnings -import numpy as np import netCDF4 - -from pygeobase.object_base import TS +import numpy as np import pygeogrids.grids as grids - from pynetcf.time_series import GriddedNcContiguousRaggedTs float32_nan = -999999.0 -class AscatTimeSeries(TS): +class TimeSeries: """ - Container class for ASCAT time series. + Container class for a time series. Parameters ---------- @@ -92,33 +88,30 @@ def __init__(self, gpi, lon, lat, cell, data, topo_complex=None, wetland_frac=None, porosity_gldas=None, porosity_hwsd=None): - super(AscatTimeSeries, self).__init__(gpi, lon, lat, data, {}) - + self.gpi = gpi + self.lon = lon + self.lat = lat + self.data = data self.cell = cell self.topo_complex = topo_complex self.wetland_frac = wetland_frac self.porosity_gldas = porosity_gldas self.porosity_hwsd = porosity_hwsd - # kept for backwards compatibility - self.longitude = self.lon - self.latitude = self.lat - def __repr__(self): - - msg = "GPI: {:d} Lon: {:2.3f} Lat: {:3.3f}".format(self.gpi, self.lon, - self.lat) + msg = "GPI: {:d} Lon: {:2.3f} Lat: {:3.3f}".format( + self.gpi, self.lon, self.lat) return msg -def load_grid(grid_filename): +def load_grid(filename): """ Load grid file. Parameters ---------- - grid_filename : str + filename : str Grid filename. Returns @@ -126,7 +119,7 @@ def load_grid(grid_filename): grid : pygeogrids.CellGrid Grid. """ - with netCDF4.Dataset(grid_filename) as grid_nc: + with netCDF4.Dataset(filename) as grid_nc: land_gp = np.where(grid_nc.variables['land_flag'][:] == 1)[0] lons = grid_nc.variables['lon'][:] lats = grid_nc.variables['lat'][:] @@ -139,7 +132,7 @@ def load_grid(grid_filename): return grid -class StaticLayers(object): +class StaticLayers(): """ Class to read static layer files. @@ -194,10 +187,10 @@ def __init__(self, path, topo_wetland_file=None, cache=cache) -class StaticFile(object): +class StaticFile: """ - Class + StaticFile class. Parameters ---------- @@ -252,7 +245,7 @@ def __getitem__(self, gpi): return data -class AscatNc(GriddedNcContiguousRaggedTs): +class AscatGriddedNcTs(GriddedNcContiguousRaggedTs): """ Class reading Metop ASCAT soil moisture Climate Data Record (CDR). @@ -298,8 +291,8 @@ def __init__(self, path, fn_format, grid_filename, static_layer_path=None, self.slayer = StaticLayers(static_layer_path, cache=cache_static_layer) - super(AscatNc, self).__init__(path, grid, fn_format=fn_format, - **kwargs) + super().__init__(path, grid, fn_format=fn_format, + **kwargs) def _read_gp(self, gpi, **kwargs): """ @@ -330,32 +323,34 @@ def _read_gp(self, gpi, **kwargs): mask_snow_prob = kwargs.pop('mask_snow_prob', None) mask_ssf = kwargs.pop('mask_ssf', None) - data = super(AscatNc, self)._read_gp(gpi, **kwargs) - lon, lat = self.grid.gpi2lonlat(gpi) - cell = self.grid.gpi2cell(gpi) + data = super()._read_gp(gpi, **kwargs) + data.attrs = {} + data.attrs['gpi'] = gpi + data.attrs['lon'], data.attrs['lat'] = self.grid.gpi2lonlat(gpi) + data.attrs['cell'] = self.grid.gpi2cell(gpi) if self.slayer is not None: - topo_complex = self.slayer.topo_wetland[gpi]['topo'] - wetland_frac = self.slayer.topo_wetland[gpi]['wetland'] + data.attrs['topo_complex'] = self.slayer.topo_wetland[gpi]['topo'] + data.attrs['wetland_frac'] = self.slayer.topo_wetland[gpi]['wetland'] snow_prob = self.slayer.frozen_snow_prob[gpi]['snow_prob'] frozen_prob = self.slayer.frozen_snow_prob[gpi]['frozen_prob'] - porosity_gldas = self.slayer.porosity[gpi]['por_gldas'] - porosity_hwsd = self.slayer.porosity[gpi]['por_hwsd'] + data.attrs['porosity_gldas'] = self.slayer.porosity[gpi]['por_gldas'] + data.attrs['porosity_hwsd'] = self.slayer.porosity[gpi]['por_hwsd'] - if porosity_gldas == float32_nan: - porosity_gldas = np.nan + if data.attrs['porosity_gldas'] == float32_nan: + data.attrs['porosity_gldas'] = np.nan - if porosity_hwsd == float32_nan: - porosity_hwsd = np.nan + if data.attrs['porosity_hwsd'] == float32_nan: + data.attrs['porosity_hwsd'] = np.nan if data is not None: data['snow_prob'] = snow_prob[data.index.dayofyear - 1] data['frozen_prob'] = frozen_prob[data.index.dayofyear - 1] else: - topo_complex = np.nan - wetland_frac = np.nan - porosity_gldas = np.nan - porosity_hwsd = np.nan + data.attrs['topo_complex'] = np.nan + data.attrs['wetland_frac'] = np.nan + data.attrs['porosity_gldas'] = np.nan + data.attrs['porosity_hwsd'] = np.nan data['snow_prob'] = np.nan data['frozen_prob'] = np.nan @@ -363,15 +358,17 @@ def _read_gp(self, gpi, **kwargs): # no error assumed for porosity values, i.e. variance = 0 por_var = 0. - data['abs_sm_gldas'] = data['sm'] / 100.0 * porosity_gldas + data['abs_sm_gldas'] = data['sm'] / \ + 100.0 * data.attrs['porosity_gldas'] data['abs_sm_noise_gldas'] = np.sqrt( por_var * (data['sm'] / 100.0)**2 + data['sm_noise']**2 * - (porosity_gldas / 100.0)**2) + (data.attrs['porosity_gldas'] / 100.0)**2) - data['abs_sm_hwsd'] = data['sm'] / 100.0 * porosity_hwsd + data['abs_sm_hwsd'] = data['sm'] / \ + 100.0 * data.attrs['porosity_hwsd'] data['abs_sm_noise_hwsd'] = np.sqrt( por_var * (data['sm'] / 100.0)**2 + data['sm_noise']**2 * - (porosity_hwsd / 100.0)**2) + (data.attrs['porosity_hwsd'] / 100.0)**2) else: data['abs_sm_gldas'] = np.nan data['abs_sm_noise_gldas'] = np.nan @@ -387,54 +384,16 @@ def _read_gp(self, gpi, **kwargs): if mask_snow_prob is not None: data = data[data['snow_prob'] < mask_snow_prob] - if (topo_complex is not None and - topo_complex >= self.thresholds['topo_complex']): + if (data.attrs['topo_complex'] is not None and + data.attrs['topo_complex'] >= self.thresholds['topo_complex']): msg = "Topographic complexity >{:2d} ({:2d})".format( - self.thresholds['topo_complex'], topo_complex) + self.thresholds['topo_complex'], data.attrs['topo_complex']) warnings.warn(msg) - if (wetland_frac is not None and - wetland_frac >= self.thresholds['wetland_frac']): + if (data.attrs['wetland_frac'] is not None and + data.attrs['wetland_frac'] >= self.thresholds['wetland_frac']): msg = "Wetland fraction >{:2d} ({:2d})".format( - self.thresholds['wetland_frac'], wetland_frac) + self.thresholds['wetland_frac'], data.attrs['wetland_frac']) warnings.warn(msg) - ts = AscatTimeSeries(gpi, lon, lat, cell, data, topo_complex, - wetland_frac, porosity_gldas, porosity_hwsd) - - return ts - - -class AscatSsmCdr(AscatNc): - - """ - Class reading Metop ASCAT soil moisture Climate Data Record (CDR). - - Parameters - ---------- - cdr_path : str - Path to Climate Data Record (CDR) data set. - grid_path : str - Path to grid file. - grid_filename : str - Name of grid file. - static_layer_path : str - Path to static layer files. - - Attributes - ---------- - grid : pygeogrids.CellGrid - Cell grid. - """ - - def __init__(self, cdr_path, grid_path, - grid_filename='TUW_WARP5_grid_info_2_2.nc', - static_layer_path=None, **kwargs): - - first_file = glob.glob(os.path.join(cdr_path, '*.nc'))[0] - version = os.path.basename(first_file).rsplit('_', 1)[0] - fn_format = '{:}_{{:04d}}'.format(version) - grid_filename = os.path.join(grid_path, grid_filename) - - super(AscatSsmCdr, self).__init__(cdr_path, fn_format, grid_filename, - static_layer_path, **kwargs) + return data diff --git a/src/ascat/read_native/eps_native.py b/src/ascat/read_native/eps_native.py index 9b72065..d109a2c 100644 --- a/src/ascat/read_native/eps_native.py +++ b/src/ascat/read_native/eps_native.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -25,22 +25,20 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - """ -Readers for lvl1b and lvl2 data in eps format. +Readers for ASCAT Level 1b and Level 2 data in EPS Native format. """ -from __future__ import division import os import fnmatch -import lxml.etree as etree -from tempfile import NamedTemporaryFile from gzip import GzipFile from collections import OrderedDict -from pygeobase.io_base import ImageBase -from pygeobase.object_base import Image +from tempfile import NamedTemporaryFile import numpy as np +import xarray as xr +import lxml.etree as etree +from cadati.jd_date import jd2dt short_cds_time = np.dtype([('day', np.uint16), ('time', np.uint32)]) @@ -52,70 +50,99 @@ int_nan = np.iinfo(np.int16).min uint_nan = np.iinfo(np.uint16).max byte_nan = np.iinfo(np.byte).min +int8_nan = np.iinfo(np.int8).max +uint8_nan = np.iinfo(np.uint8).max +float32_nan = -999999. -# 1.1.2000 00:00:00 as jd +# 2000-01-01 00:00:00 julian_epoch = 2451544.5 -class AscatL1bEPSImage(ImageBase): - def __init__(self, *args, **kwargs): +class AscatL1bEpsFile: + + """ + ASCAT Level 1b EPS Native reader class. + """ + + def __init__(self, filename): """ - Initialization of i/o object. - - SZF - beam_num - - 1 Left Fore Antenna - - 2 Left Mid Antenna - - 3 Left Aft Antenna - - 4 Right Fore Antenna - - 5 Right Mid Antenna - - 6 Right Aft Antenna + Initialize AscatL1bEpsFile. + + Parameters + ---------- + filename : str + Filename. """ - super(AscatL1bEPSImage, self).__init__(*args, **kwargs) + self.filename = filename - def read(self, timestamp=None, file_format=None, **kwargs): - img = read_eps_l1b( - self.filename, timestamp) + def read(self, generic=False, to_xarray=False): + """ + Read ASCAT Level 1b data. - return img + Returns + ------- + ds : xarray.Dataset + ASCAT Level 1b data. + """ + return read_eps_l1b(self.filename, generic, to_xarray) - def write(self, *args, **kwargs): + def close(self): + """ + Close file. + """ pass - def flush(self): - pass - def close(self): - pass +class AscatL2EpsFile: + """ + ASCAT Level 2 EPS Native reader class. + """ -class AscatL2EPSImage(ImageBase): - def __init__(self, *args, **kwargs): - """ - Initialization of i/o object. + def __init__(self, filename): """ - super(AscatL2EPSImage, self).__init__(*args, **kwargs) + Initialize AscatL2EpsFile. - def read(self, timestamp=None, file_format=None, **kwargs): - img = read_eps_l2(self.filename, timestamp) - - return img + Parameters + ---------- + filename : str + Filename. + """ + self.filename = filename - def write(self, *args, **kwargs): - pass + def read(self, generic=False, to_xarray=False): + """ + Read ASCAT Level 2 data. - def flush(self): - pass + Returns + ------- + ds : dict, xarray.Dataset + ASCAT Level 1b data. + """ + return read_eps_l2(self.filename, generic, to_xarray) def close(self): + """ + Close file. + """ pass -class EPSProduct(object): +class EPSProduct: + """ Class for reading EPS products. """ def __init__(self, filename): + """ + Initialize EPSProduct. + + Parameters + ---------- + filename : str + EPS Native Filename. + """ self.filename = filename self.fid = None self.grh = None @@ -269,9 +296,6 @@ def read_product(self): self.scaled_mdr = self._scaling(self.mdr, self.scaled_template, self.sfactor) - def _append_list(self, new_element): - return - def _scaling(self, unscaled_data, scaled_template, sfactor): """ Scale the data @@ -323,8 +347,7 @@ def _get_eps_xml(self): """ Find the corresponding eps xml file. """ - format_path = os.path.join(os.path.dirname(__file__), '..', - 'formats') + format_path = os.path.join(os.path.dirname(__file__), 'formats') # loop through files where filename starts with 'eps_ascat'. for filename in fnmatch.filter(os.listdir(format_path), 'eps_ascat*'): @@ -553,112 +576,395 @@ def ipr_record(): return record_dtype -def read_eps_l1b(filename, timestamp): +def conv_epsl1bszf_generic(data, metadata): """ - Use of correct lvl1b reader and data preparation. + Rename and convert data types of dataset. + + Parameters + ---------- + data : dict of numpy.ndarray + Original dataset. + metadata : dict + Metadata. + + Returns + ------- + data : dict of numpy.ndarray + Converted dataset. + """ + skip_fields = ['utc_localisation-days', 'utc_localisation-milliseconds', + 'degraded_inst_mdr', 'degraded_proc_mdr', 'flagfield_rf1', + 'flagfield_rf2', 'flagfield_pl', 'flagfield_gen1', + 'flagfield_gen2'] + + gen_fields_lut = {'inc_angle_full': ('inc', np.float32), + 'azi_angle_full': ('azi', np.float32), + 'sigma0_full': ('sig', np.float32)} + + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) + + for var_name in data.keys(): + if var_name in gen_fields_lut: + new_name = gen_fields_lut[var_name][0] + new_dtype = gen_fields_lut[var_name][1] + data[new_name] = data.pop(var_name).astype(new_dtype) + + return data + + +def conv_epsl1bszx_generic(data, metadata): + """ + Rename and convert data types of dataset. + + Parameters + ---------- + data : dict of numpy.ndarray + Original dataset. + metadata : dict + Metadata. + + Returns + ------- + data : dict of numpy.ndarray + Converted dataset. + """ + gen_fields_lut = {'inc_angle_trip': ('inc', np.float32, uint_nan), + 'azi_angle_trip': ('azi', np.float32, int_nan), + 'sigma0_trip': ('sig', np.float32, long_nan), + 'kp': ('kp', np.float32, uint_nan), + 'f_kp': ('kp_quality', np.uint8, uint8_nan)} + + skip_fields = ['flagfield_rf1', 'f_f', 'f_v', 'f_oa', 'f_sa', 'f_tel'] + + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) + + for var_name, (new_name, new_dtype, nan_val) in gen_fields_lut.items(): + data[new_name] = data.pop(var_name).astype(new_dtype) + if nan_val is not None: + data[new_name][data[new_name] == nan_val] = float32_nan + + data['sat_id'] = np.repeat(metadata['sat_id'], data['time'].size) + + return data + + +def conv_epsl2szx_generic(data, metadata): + """ + Rename and convert data types of dataset. + + Parameters + ---------- + data : dict of numpy.ndarray + Original dataset. + metadata : dict + Metadata. + + Returns + ------- + data : dict of numpy.ndarray + Converted dataset. + """ + gen_fields_lut = { + 'inc_angle_trip': ('inc', np.float32, uint_nan), + 'azi_angle_trip': ('azi', np.float32, int_nan), + 'sigma0_trip': ('sig', np.float32, long_nan), + 'soil_moisture': ('sm', np.float32, uint_nan), + 'soil_moisture_error': ('sm_noise', np.float32, uint_nan), + 'mean_surf_soil_moisture': ('sm_mean', np.float32, uint_nan), + 'soil_moisture_sensetivity': ('sm_sens', np.float32, ulong_nan), + 'sigma40': ('sig40', np.float32, long_nan), + 'sigma40_error': ('sig40_noise', np.float32, long_nan), + 'slope40': ('slope40', np.float32, long_nan), + 'slope40_error': ('slope40_noise', np.float32, long_nan), + 'dry_backscatter': ('dry_sig40', np.float32, long_nan), + 'wet_backscatter': ('wet_sig40', np.float32, long_nan), + 'as_des_pass': ('as_des_pass', np.uint8, None), + 'aggregated_quality_flag': ('agg_flag', np.uint8, None), + 'processing_flags': ('proc_flag', np.uint8, None), + 'correction_flags': ('corr_flag', np.uint8, None), + 'snow_cover_probability': ('snow_prob', np.uint8, None), + 'frozen_soil_probability': ('frozen_prob', np.uint8, None), + 'innudation_or_wetland': ('wetland', np.uint8, None), + 'topographical_complexity': ('topo', np.uint8, None), + 'kp': ('kp', np.float32, uint_nan)} + + skip_fields = ['flagfield_rf1', 'f_f', 'f_v', 'f_oa', 'f_sa', 'f_tel'] + + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) + + for var_name, (new_name, new_dtype, nan_val) in gen_fields_lut.items(): + data[new_name] = data.pop(var_name).astype(new_dtype) + if nan_val is not None: + data[new_name][data[new_name] == nan_val] = float32_nan + + data['sat_id'] = np.repeat(metadata['sat_id'], data['time'].size) + + return data + + +def read_eps_l1b(filename, generic=False, to_xarray=False): + """ + Level 1b reader and data preparation. + + Parameters + ---------- + filename : str + ASCAT Level 1b file name in EPS Native format. + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). + + Returns + ------- + ds : xarray.Dataset, dict of xarray.Dataset + ASCAT Level 1b data. """ - data = {} eps_file = read_eps(filename) ptype = eps_file.mphr['PRODUCT_TYPE'] fmv = int(eps_file.mphr['FORMAT_MAJOR_VERSION']) if ptype == 'SZF': - image_dict = {'img1': {}, 'img2': {}, 'img3': {}, 'img4': {}, - 'img5': {}, 'img6': {}} - data_full = {'d1': {}, 'd2': {}, 'd3': {}, 'd4': {}, 'd5': {}, - 'd6': {}} + if fmv == 12: - raw_data, metadata, orbit_grid = read_szf_fmv_12(eps_file) + data, metadata, orbit_grid = read_szf_fmv_12(eps_file) else: - raise RuntimeError("SZF format version not supported.") + raise RuntimeError("L1b SZF format version not supported.") + + data['time'] = jd2dt(data.pop('jd')) + rename_coords = {'longitude_full': 'lon', 'latitude_full': 'lat'} + + for k, v in rename_coords.items(): + data[v] = data.pop(k) + + if generic: + data = conv_epsl1bszf_generic(data, metadata) + + # 1 Left Fore Antenna, 2 Left Mid Antenna 3 Left Aft Antenna + # 4 Right Fore Antenna, 5 Right Mid Antenna, 6 Right Aft Antenna + antennas = ['lf', 'lm', 'la', 'rf', 'rm', 'ra'] + ds = OrderedDict() + + for i, antenna in enumerate(antennas): + + subset = data['beam_number'] == i+1 + metadata['beam_number'] = i+1 + metadata['beam_name'] = antenna + + # convert spacecraft_id to internal sat_id + sat_id = np.array([4, 3, 5]) + metadata['sat_id'] = sat_id[metadata['spacecraft_id']-1] + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + sub_data = {} + for var_name in data.keys(): - for field in raw_data: - data[field] = raw_data[field] + if var_name == 'beam_number' and generic: + continue - # separate data into single beam images - for i in range(1, 7): - dataset = 'd' + str(i) - img = 'img' + str(i) - mask = ((data['BEAM_NUMBER']) == i) - for field in data: - data_full[dataset][field] = data[field][mask] + if len(data[var_name].shape) == 1: + dim = ['obs'] + elif len(data[var_name].shape) == 2: + dim = ['obs', 'echo'] - lon = data_full[dataset].pop('LONGITUDE_FULL') - lat = data_full[dataset].pop('LATITUDE_FULL') - image_dict[img] = Image(lon, lat, data_full[dataset], metadata, - timestamp, timekey='jd') + sub_data[var_name] = (dim, data[var_name][subset]) - return image_dict + coords = {} + coords_fields = ['lon', 'lat', 'time'] + + for cf in coords_fields: + coords[cf] = sub_data.pop(cf) + + ds[antenna] = xr.Dataset(sub_data, coords=coords, + attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + + if len(data[var_name][subset].shape) == 1: + dtype.append( + (var_name, data[var_name][subset].dtype.str)) + elif len(data[var_name][subset].shape) > 1: + dtype.append((var_name, data[var_name][ + subset].dtype.str, data[var_name][ + subset].shape[1:])) + + ds[antenna] = np.empty( + data['time'][subset].size, dtype=np.dtype(dtype)) + + for var_name, v in data.items(): + if var_name == 'beam_number' and generic: + continue + ds[antenna][var_name] = v[subset] + + elif ptype in ['SZR', 'SZO']: - elif (ptype == 'SZR') or (ptype == 'SZO'): if fmv == 11: - raw_data, metadata = read_szx_fmv_11(eps_file) + data, metadata = read_szx_fmv_11(eps_file) elif fmv == 12: - raw_data, metadata = read_szx_fmv_12(eps_file) + data, metadata = read_szx_fmv_12(eps_file) else: raise RuntimeError("SZX format version not supported.") - beams = ['f_', 'm_', 'a_'] + data['time'] = jd2dt(data.pop('jd')) - for field in raw_data: - if len(raw_data[field].shape) == 1: - data[field] = raw_data[field] - # split data if it is triplet data - elif len(raw_data[field].shape) == 2: - for i, beam in enumerate(beams): - data[beam + field] = raw_data[field][:, i] - else: - raise RuntimeError("Unexpected variable shape.") + rename_coords = {'longitude': 'lon', 'latitude': 'lat'} + + for k, v in rename_coords.items(): + data[v] = data.pop(k) + + # convert spacecraft_id to internal sat_id + sat_id = np.array([4, 3, 5]) + metadata['sat_id'] = sat_id[metadata['spacecraft_id']-1] + + # add/rename/remove fields according to generic format + if generic: + data = conv_epsl1bszx_generic(data, metadata) + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + for k in data.keys(): + if len(data[k].shape) == 1: + dim = ['obs'] + elif len(data[k].shape) == 2: + dim = ['obs', 'beam'] + + data[k] = (dim, data[k]) + + coords = {} + coords_fields = ['lon', 'lat', 'time'] + for cf in coords_fields: + coords[cf] = data.pop(cf) + + ds = xr.Dataset(data, coords=coords, attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + if len(data[var_name].shape) == 1: + dtype.append((var_name, data[var_name].dtype.str)) + elif len(data[var_name].shape) > 1: + dtype.append((var_name, data[var_name].dtype.str, + data[var_name].shape[1:])) + + ds = np.empty(data['time'].size, dtype=np.dtype(dtype)) + for k, v in data.items(): - longitude = data.pop('LONGITUDE') - latitude = data.pop('LATITUDE') + ds[k] = v - return Image(longitude, latitude, data, metadata, timestamp, - timekey='jd') else: - raise ValueError("Format not supported. Product type {:1}" - " Format major version: {:2}".format(ptype, fmv)) + raise RuntimeError("Format not supported. Product type {:1}" + " Format major version: {:2}".format(ptype, fmv)) + return ds -def read_eps_l2(filename, timestamp): + +def read_eps_l2(filename, generic=False, to_xarray=False): """ - Use of correct lvl2 reader and data preparation. + Level 2 reader and data preparation. + + Parameters + ---------- + filename : str + ASCAT Level 1b file name in EPS Native format. + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). + + Returns + ------- + ds : xarray.Dataset, dict of xarray.Dataset + ASCAT Level 1b data. """ - data = {} eps_file = read_eps(filename) ptype = eps_file.mphr['PRODUCT_TYPE'] fmv = int(eps_file.mphr['FORMAT_MAJOR_VERSION']) - if (ptype == 'SMR') or (ptype == 'SMO'): + if ptype in ['SMR', 'SMO']: + if fmv == 12: - raw_data, metadata = read_smx_fmv_12(eps_file) + data, metadata = read_smx_fmv_12(eps_file) else: - raise RuntimeError("SMX format version not supported.") + raise RuntimeError("L2 SM format version not supported.") - beams = ['f_', 'm_', 'a_'] + data['time'] = jd2dt(data.pop('jd')) - for field in raw_data: - if len(raw_data[field].shape) == 1: - data[field] = raw_data[field] - elif len(raw_data[field].shape) == 2: - for i, beam in enumerate(beams): - data[beam + field] = raw_data[field][:, i] - else: - raise RuntimeError("Unexpected variable shape.") + rename_coords = {'longitude': 'lon', 'latitude': 'lat'} + + for k, v in rename_coords.items(): + data[v] = data.pop(k) - longitude = data.pop('LONGITUDE') - latitude = data.pop('LATITUDE') + # convert spacecraft_id to internal sat_id + sat_id = np.array([4, 3, 5]) + metadata['sat_id'] = sat_id[metadata['spacecraft_id']-1] + # add/rename/remove fields according to generic format + if generic: + data = conv_epsl2szx_generic(data, metadata) + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + for k in data.keys(): + if len(data[k].shape) == 1: + dim = ['obs'] + elif len(data[k].shape) == 2: + dim = ['obs', 'beam'] + + data[k] = (dim, data[k]) + + coords = {} + coords_fields = ['lon', 'lat', 'time'] + for cf in coords_fields: + coords[cf] = data.pop(cf) + + ds = xr.Dataset(data, coords=coords, attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + if len(data[var_name].shape) == 1: + dtype.append((var_name, data[var_name].dtype.str)) + elif len(data[var_name].shape) > 1: + dtype.append((var_name, data[var_name].dtype.str, + data[var_name].shape[1:])) + + ds = np.empty(data['time'].size, dtype=np.dtype(dtype)) + for k, v in data.items(): + + ds[k] = v else: raise ValueError("Format not supported. Product type {:1}" " Format major version: {:2}".format(ptype, fmv)) - return Image(longitude, latitude, data, metadata, timestamp, timekey='jd') + return ds def read_eps(filename): """ Read EPS file. + + Parameters + ---------- + filename : str + Filename + + Returns + ------- + prod : EPSProduct + EPS data. """ zipped = False if os.path.splitext(filename)[1] == '.gz': @@ -703,6 +1009,7 @@ def read_szx_fmv_11(eps_file): n_node_per_line = raw_data['LONGITUDE'].shape[1] n_lines = raw_data['LONGITUDE'].shape[0] n_records = raw_data['LONGITUDE'].size + data = {} metadata = {} idx_nodes = np.arange(n_lines).repeat(n_node_per_line) @@ -711,62 +1018,58 @@ def read_szx_fmv_11(eps_file): raw_data['UTC_LINE_NODES'].flatten()['time']) data['jd'] = ascat_time[idx_nodes] - metadata['SPACECRAFT_ID'] = np.int8(mphr['SPACECRAFT_ID'][-1]) - metadata['ORBIT_START'] = np.uint32(mphr['ORBIT_START']) - - fields = ['PROCESSOR_MAJOR_VERSION', 'PROCESSOR_MINOR_VERSION', - 'FORMAT_MAJOR_VERSION', 'FORMAT_MINOR_VERSION'] - for field in fields: - # metadata[field] = np.repeat(np.int16(mphr[field]),n_records) - metadata[field] = np.int16(mphr[field]) - - fields = ['SAT_TRACK_AZI'] - for field in fields: - data[field] = raw_data[field].flatten()[idx_nodes] - - fields = [('LONGITUDE', long_nan), - ('LATITUDE', long_nan), - ('SWATH_INDICATOR', byte_nan)] - for field in fields: - data[field[0]] = raw_data[field[0]].flatten() - valid = raw_unscaled[field[0]].flatten() != field[1] - data[field[0]][~valid] = field[1] - - fields = [('SIGMA0_TRIP', long_nan), - ('INC_ANGLE_TRIP', uint_nan), - ('AZI_ANGLE_TRIP', int_nan), - ('KP', uint_nan), - ('F_KP', byte_nan), - ('F_USABLE', byte_nan), - ('F_F', uint_nan), - ('F_V', uint_nan), - ('F_OA', uint_nan), - ('F_SA', uint_nan), - ('F_TEL', uint_nan), - ('F_LAND', uint_nan)] - for field in fields: - data[field[0]] = raw_data[field[0]].reshape(n_records, 3) - # valid = data[field[0]] != field[2] - valid = raw_unscaled[field[0]].reshape(n_records, 3) != field[1] - data[field[0]][~valid] = field[1] + metadata['spacecraft_id'] = np.int8(mphr['SPACECRAFT_ID'][-1]) + metadata['orbit_start'] = np.uint32(mphr['ORBIT_START']) + + fields = ['processor_major_version', 'processor_minor_version', + 'format_major_version', 'format_minor_version'] + + for f in fields: + metadata[f] = np.int16(mphr[f.upper()]) + + fields = ['sat_track_azi'] + for f in fields: + data[f] = raw_data[f.upper()].flatten()[idx_nodes] + + fields = [('longitude', long_nan), ('latitude', long_nan), + ('swath_indicator', byte_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].flatten() + valid = raw_unscaled[f.upper()].flatten() != nan_val + data[f][~valid] = nan_val + + fields = [('sigma0_trip', long_nan), + ('inc_angle_trip', uint_nan), + ('azi_angle_trip', int_nan), + ('kp', uint_nan), + ('f_kp', byte_nan), + ('f_usable', byte_nan), + ('f_f', uint_nan), + ('f_v', uint_nan), + ('f_oa', uint_nan), + ('f_sa', uint_nan), + ('f_tel', uint_nan), + ('f_land', uint_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].reshape(n_records, 3) + valid = raw_unscaled[f.upper()].reshape(n_records, 3) != nan_val + data[f][~valid] = nan_val # modify longitudes from (0, 360) to (-180,180) - mask = np.logical_and(data['LONGITUDE'] != long_nan, - data['LONGITUDE'] > 180) - data['LONGITUDE'][mask] += -360. + mask = np.logical_and(data['longitude'] != long_nan, + data['longitude'] > 180) + data['longitude'][mask] += -360. # modify azimuth from (-180, 180) to (0, 360) - mask = (data['AZI_ANGLE_TRIP'] != int_nan) & (data['AZI_ANGLE_TRIP'] < 0) - data['AZI_ANGLE_TRIP'][mask] += 360 + mask = (data['azi_angle_trip'] != int_nan) & (data['azi_angle_trip'] < 0) + data['azi_angle_trip'][mask] += 360 - data['NODE_NUM'] = np.tile((np.arange(n_node_per_line) + 1), - n_lines) - - data['LINE_NUM'] = idx_nodes - - data['AS_DES_PASS'] = (data['SAT_TRACK_AZI'] < 270).astype(np.uint8) - - data['SWATH INDICATOR'] = data.pop('SWATH_INDICATOR') + data['node_num'] = np.tile((np.arange(n_node_per_line) + 1), + n_lines).astype(np.uint8) + data['line_num'] = idx_nodes.astype(np.uint16) + data['as_des_pass'] = (data['sat_track_azi'] < 270).astype(np.uint8) return data, metadata @@ -792,6 +1095,7 @@ def read_szx_fmv_12(eps_file): n_node_per_line = raw_data['LONGITUDE'].shape[1] n_lines = raw_data['LONGITUDE'].shape[0] n_records = raw_data['LONGITUDE'].size + data = {} metadata = {} idx_nodes = np.arange(n_lines).repeat(n_node_per_line) @@ -800,63 +1104,66 @@ def read_szx_fmv_12(eps_file): raw_data['UTC_LINE_NODES'].flatten()['time']) data['jd'] = ascat_time[idx_nodes] - metadata['SPACECRAFT_ID'] = np.int8(mphr['SPACECRAFT_ID'][-1]) - metadata['ORBIT_START'] = np.uint32(mphr['ORBIT_START']) - - fields = ['PROCESSOR_MAJOR_VERSION', 'PROCESSOR_MINOR_VERSION', - 'FORMAT_MAJOR_VERSION', 'FORMAT_MINOR_VERSION'] - for field in fields: - # metadata[field] = np.repeat(np.int16(mphr[field]),n_records) - metadata[field] = np.int16(mphr[field]) - - fields = ['DEGRADED_INST_MDR', 'DEGRADED_PROC_MDR', 'SAT_TRACK_AZI', - 'ABS_LINE_NUMBER'] - for field in fields: - data[field] = raw_data[field].flatten()[idx_nodes] - - fields = [('LONGITUDE', long_nan), - ('LATITUDE', long_nan), - ('SWATH INDICATOR', byte_nan)] - for field in fields: - data[field[0]] = raw_data[field[0]].flatten() - valid = raw_unscaled[field[0]].flatten() != field[1] - data[field[0]][~valid] = field[1] - - fields = [('SIGMA0_TRIP', long_nan), - ('INC_ANGLE_TRIP', uint_nan), - ('AZI_ANGLE_TRIP', int_nan), - ('KP', uint_nan), - ('NUM_VAL_TRIP', ulong_nan), - ('F_KP', byte_nan), - ('F_USABLE', byte_nan), - ('F_F', uint_nan), - ('F_V', uint_nan), - ('F_OA', uint_nan), - ('F_SA', uint_nan), - ('F_TEL', uint_nan), - ('F_REF', uint_nan), - ('F_LAND', uint_nan)] - for field in fields: - data[field[0]] = raw_data[field[0]].reshape(n_records, 3) - # valid = data[field[0]] != field[2] - valid = raw_unscaled[field[0]].reshape(n_records, 3) != field[1] - data[field[0]][~valid] = field[1] + metadata['spacecraft_id'] = np.int8(mphr['SPACECRAFT_ID'][-1]) + metadata['orbit_start'] = np.uint32(mphr['ORBIT_START']) + + fields = ['processor_major_version', 'processor_minor_version', + 'format_major_version', 'format_minor_version'] + + for f in fields: + metadata[f] = np.int16(mphr[f.upper()]) + + fields = ['degraded_inst_mdr', 'degraded_proc_mdr', 'sat_track_azi', + 'abs_line_number'] + + for f in fields: + data[f] = raw_data[f.upper()].flatten()[idx_nodes] + + fields = [('longitude', long_nan), ('latitude', long_nan), + ('swath indicator', byte_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].flatten() + valid = raw_unscaled[f.upper()].flatten() != nan_val + data[f][~valid] = nan_val + + fields = [('sigma0_trip', long_nan), + ('inc_angle_trip', uint_nan), + ('azi_angle_trip', int_nan), + ('kp', uint_nan), + ('num_val_trip', ulong_nan), + ('f_kp', byte_nan), + ('f_usable', byte_nan), + ('f_f', uint_nan), + ('f_v', uint_nan), + ('f_oa', uint_nan), + ('f_sa', uint_nan), + ('f_tel', uint_nan), + ('f_ref', uint_nan), + ('f_land', uint_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].reshape(n_records, 3) + valid = raw_unscaled[f.upper()].reshape(n_records, 3) != nan_val + data[f][~valid] = nan_val # modify longitudes from (0, 360) to (-180,180) - mask = np.logical_and(data['LONGITUDE'] != long_nan, - data['LONGITUDE'] > 180) - data['LONGITUDE'][mask] += -360. + mask = np.logical_and(data['longitude'] != long_nan, + data['longitude'] > 180) + data['longitude'][mask] += -360. # modify azimuth from (-180, 180) to (0, 360) - mask = (data['AZI_ANGLE_TRIP'] != int_nan) & (data['AZI_ANGLE_TRIP'] < 0) - data['AZI_ANGLE_TRIP'][mask] += 360 + mask = (data['azi_angle_trip'] != int_nan) & (data['azi_angle_trip'] < 0) + data['azi_angle_trip'][mask] += 360 - data['NODE_NUM'] = np.tile((np.arange(n_node_per_line) + 1), - n_lines) + data['node_num'] = np.tile((np.arange(n_node_per_line) + 1), + n_lines).astype(np.uint8) - data['LINE_NUM'] = idx_nodes + data['line_num'] = idx_nodes.astype(np.uint16) - data['AS_DES_PASS'] = (data['SAT_TRACK_AZI'] < 270).astype(np.uint8) + data['as_des_pass'] = (data['sat_track_azi'] < 270).astype(np.uint8) + + data['swath_indicator'] = data.pop('swath indicator') return data, metadata @@ -898,6 +1205,7 @@ def read_szf_fmv_12(eps_file): n_node_per_line = raw_data['LONGITUDE_FULL'].shape[1] n_lines = eps_file.mdr_counter + data = {} metadata = {} idx_nodes = np.arange(n_lines).repeat(n_node_per_line) @@ -907,42 +1215,43 @@ def read_szf_fmv_12(eps_file): 'time']) data['jd'] = ascat_time[idx_nodes] - metadata['SPACECRAFT_ID'] = np.int8(mphr['SPACECRAFT_ID'][-1]) - metadata['ORBIT_START'] = np.uint32(eps_file.mphr['ORBIT_START']) + metadata['spacecraft_id'] = np.int8(mphr['SPACECRAFT_ID'][-1]) + metadata['orbit_start'] = np.uint32(eps_file.mphr['ORBIT_START']) - fields = ['PROCESSOR_MAJOR_VERSION', 'PROCESSOR_MINOR_VERSION', - 'FORMAT_MAJOR_VERSION', 'FORMAT_MINOR_VERSION'] - for field in fields: - metadata[field] = np.int16(mphr[field]) + fields = ['processor_major_version', 'processor_minor_version', + 'format_major_version', 'format_minor_version'] + for f in fields: + metadata[f] = np.int16(mphr[f.upper()]) - fields = ['DEGRADED_INST_MDR', 'DEGRADED_PROC_MDR', 'SAT_TRACK_AZI', - 'BEAM_NUMBER', 'FLAGFIELD_RF1', 'FLAGFIELD_RF2', - 'FLAGFIELD_PL', 'FLAGFIELD_GEN1'] - for field in fields: - data[field] = raw_data[field].flatten()[idx_nodes] + fields = ['degraded_inst_mdr', 'degraded_proc_mdr', 'sat_track_azi', + 'beam_number', 'flagfield_rf1', 'flagfield_rf2', + 'flagfield_pl', 'flagfield_gen1'] + for f in fields: + data[f] = raw_data[f.upper()].flatten()[idx_nodes] - data['SWATH_INDICATOR'] = np.int8(data['BEAM_NUMBER'].flatten() > 3) + data['swath_indicator'] = np.uint8(data['beam_number'].flatten() > 3) - fields = [('LONGITUDE_FULL', long_nan), - ('LATITUDE_FULL', long_nan), - ('SIGMA0_FULL', long_nan), - ('INC_ANGLE_FULL', uint_nan), - ('AZI_ANGLE_FULL', int_nan), - ('LAND_FRAC', uint_nan), - ('FLAGFIELD_GEN2', byte_nan)] - for field in fields: - data[field[0]] = raw_data[field[0]].flatten() - valid = data[field[0]] != field[1] - data[field[0]][valid] = data[field[0]][valid] + fields = [('longitude_full', long_nan), + ('latitude_full', long_nan), + ('sigma0_full', long_nan), + ('inc_angle_full', uint_nan), + ('azi_angle_full', int_nan), + ('land_frac', uint_nan), + ('flagfield_gen2', byte_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].flatten() + valid = eps_file.mdr[f.upper()].flatten() != nan_val + data[f][~valid] = nan_val # modify longitudes from (0, 360) to (-180,180) - mask = np.logical_and(data['LONGITUDE_FULL'] != long_nan, - data['LONGITUDE_FULL'] > 180) - data['LONGITUDE_FULL'][mask] += -360. + mask = np.logical_and(data['longitude_full'] != long_nan, + data['longitude_full'] > 180) + data['longitude_full'][mask] += -360. # modify azimuth from (-180, 180) to (0, 360) - mask = (data['AZI_ANGLE_FULL'] != int_nan) & (data['AZI_ANGLE_FULL'] < 0) - data['AZI_ANGLE_FULL'][mask] += 360 + mask = (data['azi_angle_full'] != int_nan) & (data['azi_angle_full'] < 0) + data['azi_angle_full'][mask] += 360 grid_nodes_per_line = 2 * 81 @@ -950,8 +1259,8 @@ def read_szf_fmv_12(eps_file): orbit_grid = np.zeros(viadr_grid.size * grid_nodes_per_line, dtype=np.dtype([('lon', np.float32), ('lat', np.float32), - ('node_num', np.int16), - ('line_num', np.int32)])) + ('node_num', np.uint8), + ('line_num', np.uint32)])) for pos_all in range(orbit_grid['lon'].size): line = pos_all // grid_nodes_per_line @@ -984,63 +1293,11 @@ def read_szf_fmv_12(eps_file): set_flags(data) - data['AS_DES_PASS'] = (data['SAT_TRACK_AZI'] < 270).astype(np.uint8) + data['as_des_pass'] = (data['sat_track_azi'] < 270).astype(np.uint8) return data, metadata, orbit_grid -def set_flags(data): - """ - Compute summary flag for each measurement with a value of 0, 1 or 2 - indicating nominal, slightly degraded or severely degraded data. - - Parameters - ---------- - data : numpy.ndarray - SZF data. - """ - - # category:status = 'red': 2, 'amber': 1, 'warning': 0 - flag_status_bit = {'FLAGFIELD_RF1': {'2': [2, 4], - '1': [0, 1, 3]}, - - 'FLAGFIELD_RF2': {'2': [0, 1]}, - - 'FLAGFIELD_PL': {'2': [0, 1, 2, 3], - '0': [4]}, - - 'FLAGFIELD_GEN1': {'2': [1], - '0': [0]}, - - 'FLAGFIELD_GEN2': {'2': [2], - '1': [0], - '0': [1]} - } - - for flagfield in flag_status_bit.keys(): - # get flag data in binary format to get flags - unpacked_bits = np.unpackbits(data[flagfield]) - - # find indizes where a flag is set - set_bits = np.where(unpacked_bits == 1)[0] - if set_bits.size != 0: - pos_8 = 7 - (set_bits % 8) - - for category in sorted(flag_status_bit[flagfield].keys()): - if (int(category) == 0) and (flagfield != 'FLAGFIELD_GEN2'): - continue - - for bit2check in flag_status_bit[flagfield][category]: - pos = np.where(pos_8 == bit2check)[0] - data['F_USABLE'] = np.zeros(data['FLAGFIELD_GEN2'].size) - data['F_USABLE'][set_bits[pos] // 8] = int(category) - - # land points - if (flagfield == 'FLAGFIELD_GEN2') and (bit2check == 1): - data['F_LAND'] = np.zeros(data['FLAGFIELD_GEN2'].size) - data['F_LAND'][set_bits[pos] // 8] = 1 - - def read_smx_fmv_12(eps_file): """ Read SMO/SMR format version 12. @@ -1066,84 +1323,146 @@ def read_smx_fmv_12(eps_file): data = {} metadata = {} - metadata['SPACECRAFT_ID'] = np.int8(eps_file.mphr['SPACECRAFT_ID'][-1]) - metadata['ORBIT_START'] = np.uint32(eps_file.mphr['ORBIT_START']) + metadata['spacecraft_id'] = np.int8(eps_file.mphr['SPACECRAFT_ID'][-1]) + metadata['orbit_start'] = np.uint32(eps_file.mphr['ORBIT_START']) ascat_time = shortcdstime2jd(raw_data['UTC_LINE_NODES'].flatten()['day'], raw_data['UTC_LINE_NODES'].flatten()['time']) data['jd'] = ascat_time[idx_nodes] - fields = [('SIGMA0_TRIP', long_nan), - ('INC_ANGLE_TRIP', uint_nan), - ('AZI_ANGLE_TRIP', int_nan), - ('KP', uint_nan), - ('F_LAND', uint_nan)] - - for field in fields: - data[field[0]] = raw_data[field[0]].reshape(n_records, 3) - valid = raw_unscaled[field[0]].reshape(n_records, 3) != field[1] - data[field[0]][~valid] = field[1] - - fields = ['SAT_TRACK_AZI', 'ABS_LINE_NUMBER'] - for field in fields: - data[field] = raw_data[field].flatten()[idx_nodes] - - fields = [('LONGITUDE', long_nan), - ('LATITUDE', long_nan), - ('SOIL_MOISTURE', uint_nan), - ('SWATH_INDICATOR', byte_nan), - ('SOIL_MOISTURE_ERROR', uint_nan), - ('SIGMA40', long_nan), - ('SIGMA40_ERROR', long_nan), - ('SLOPE40', long_nan), - ('SLOPE40_ERROR', long_nan), - ('DRY_BACKSCATTER', long_nan), - ('WET_BACKSCATTER', long_nan), - ('MEAN_SURF_SOIL_MOISTURE', uint_nan), - ('SOIL_MOISTURE_SENSETIVITY', ulong_nan), - ('CORRECTION_FLAGS', None), - ('PROCESSING_FLAGS', None), - ('AGGREGATED_QUALITY_FLAG', None), - ('SNOW_COVER_PROBABILITY', None), - ('FROZEN_SOIL_PROBABILITY', None), - ('INNUDATION_OR_WETLAND', None), - ('TOPOGRAPHICAL_COMPLEXITY', None)] - - for field in fields: - data[field[0]] = raw_data[field[0]].flatten() - if field[1] is not None: - valid = raw_unscaled[field[0]].flatten() != field[1] - data[field[0]][~valid] = field[1] + fields = [('sigma0_trip', long_nan), + ('inc_angle_trip', uint_nan), + ('azi_angle_trip', int_nan), + ('kp', uint_nan), + ('f_land', uint_nan)] + + for f, nan_val in fields: + data[f] = raw_data[f.upper()].reshape(n_records, 3) + valid = raw_unscaled[f.upper()].reshape(n_records, 3) != nan_val + data[f][~valid] = nan_val + + fields = ['sat_track_azi', 'abs_line_number'] + for f in fields: + data[f] = raw_data[f.upper()].flatten()[idx_nodes] + + fields = [('longitude', long_nan, long_nan), + ('latitude', long_nan, long_nan), + ('swath_indicator', byte_nan, byte_nan), + ('soil_moisture', uint_nan, uint_nan), + ('soil_moisture_error', uint_nan, uint_nan), + ('sigma40', long_nan, long_nan), + ('sigma40_error', long_nan, long_nan), + ('slope40', long_nan, long_nan), + ('slope40_error', long_nan, long_nan), + ('dry_backscatter', long_nan, long_nan), + ('wet_backscatter', long_nan, long_nan), + ('mean_surf_soil_moisture', uint_nan, uint_nan), + ('soil_moisture_sensetivity', ulong_nan, float32_nan), + ('correction_flags', uint8_nan, uint8_nan), + ('processing_flags', uint8_nan, uint8_nan), + ('aggregated_quality_flag', uint8_nan, uint8_nan), + ('snow_cover_probability', uint8_nan, uint8_nan), + ('frozen_soil_probability', uint8_nan, uint8_nan), + ('innudation_or_wetland', uint8_nan, uint8_nan), + ('topographical_complexity', uint8_nan, uint8_nan)] + + for f, nan_val, new_nan_val in fields: + data[f] = raw_data[f.upper()].flatten() + valid = raw_unscaled[f.upper()].flatten() != nan_val + data[f][~valid] = new_nan_val # sat_track_azi (uint) - data['AS_DES_PASS'] = \ + data['as_des_pass'] = \ np.array(raw_data['SAT_TRACK_AZI'].flatten()[idx_nodes] < 270) # modify longitudes from [0,360] to [-180,180] - mask = np.logical_and(data['LONGITUDE'] != long_nan, - data['LONGITUDE'] > 180) - data['LONGITUDE'][mask] += -360. + mask = np.logical_and(data['longitude'] != long_nan, + data['longitude'] > 180) + data['longitude'][mask] += -360. # modify azimuth from (-180, 180) to (0, 360) - mask = (data['AZI_ANGLE_TRIP'] != int_nan) & (data['AZI_ANGLE_TRIP'] < 0) - data['AZI_ANGLE_TRIP'][mask] += 360 + mask = (data['azi_angle_trip'] != int_nan) & (data['azi_angle_trip'] < 0) + data['azi_angle_trip'][mask] += 360 - fields = ['PARAM_DB_VERSION', 'WARP_NRT_VERSION'] - for field in fields: - data[field] = raw_data['PARAM_DB_VERSION'].flatten()[idx_nodes] + fields = ['param_db_version', 'warp_nrt_version'] + for f in fields: + data[f] = raw_data['PARAM_DB_VERSION'].flatten()[idx_nodes] - metadata['SPACECRAFT_ID'] = int(eps_file.mphr['SPACECRAFT_ID'][2]) + metadata['spacecraft_id'] = int(eps_file.mphr['SPACECRAFT_ID'][2]) - data['NODE_NUM'] = np.tile((np.arange(n_node_per_line) + 1), n_lines) + data['node_num'] = np.tile((np.arange(n_node_per_line) + 1), n_lines) - data['LINE_NUM'] = idx_nodes + data['line_num'] = idx_nodes return data, metadata def shortcdstime2jd(days, milliseconds): """ - Convert cds time to julian date + Convert cds time to julian date. + + Parameters + ---------- + days : int + Days since 2000-01-01 + milliseconds : int + Milliseconds. + + Returns + ------- + jd : float + Julian date. """ offset = days + (milliseconds / 1000.) / (24. * 60. * 60.) return julian_epoch + offset + + +def set_flags(data): + """ + Compute summary flag for each measurement with a value of 0, 1 or 2 + indicating nominal, slightly degraded or severely degraded data. + + Parameters + ---------- + data : numpy.ndarray + SZF data. + + Returns + ------- + data : numpy.ndarray + SZF data with updated flags. + """ + # category:status = 'red': 2, 'amber': 1, 'warning': 0 + flag_status_bit = {'flagfield_rf1': {'2': [2, 4], '1': [0, 1, 3]}, + 'flagfield_rf2': {'2': [0, 1]}, + 'flagfield_pl': {'2': [0, 1, 2, 3], '0': [4]}, + 'flagfield_gen1': {'2': [1], '0': [0]}, + 'flagfield_gen2': {'2': [2], '1': [0], '0': [1]}} + + for flagfield in flag_status_bit.keys(): + + # get flag data in binary format to get flags + unpacked_bits = np.unpackbits(data[flagfield]) + + # find indizes where a flag is set + set_bits = np.where(unpacked_bits == 1)[0] + if set_bits.size != 0: + pos_8 = 7 - (set_bits % 8) + + for category in sorted(flag_status_bit[flagfield].keys()): + if (int(category) == 0) and (flagfield != 'flagfield_gen2'): + continue + + for bit2check in flag_status_bit[flagfield][category]: + pos = np.where(pos_8 == bit2check)[0] + data['f_usable'] = np.zeros(data['flagfield_gen2'].size, + dtype=np.int8) + data['f_usable'][set_bits[pos] // 8] = int(category) + + # land points + if (flagfield == 'flagfield_gen2') and (bit2check == 1): + data['f_land'] = np.zeros(data['flagfield_gen2'].size, + dtype=np.int8) + data['f_land'][set_bits[pos] // 8] = 1 + + return data diff --git a/src/ascat/formats/ccsds.xml b/src/ascat/read_native/formats/ccsds.xml similarity index 100% rename from src/ascat/formats/ccsds.xml rename to src/ascat/read_native/formats/ccsds.xml diff --git a/src/ascat/formats/eps.dtd b/src/ascat/read_native/formats/eps.dtd similarity index 96% rename from src/ascat/formats/eps.dtd rename to src/ascat/read_native/formats/eps.dtd index 9c5e6d2..7fbc8b9 100644 --- a/src/ascat/formats/eps.dtd +++ b/src/ascat/read_native/formats/eps.dtd @@ -6,7 +6,7 @@ Revision 1.1 2003/02/28 10:49:19 melson Initial revision -Copyright (c) Eumetsat 2003, 2004 +Copyright (c) Eumetsat 2003, 2004 --> diff --git a/src/ascat/formats/eps.xsl b/src/ascat/read_native/formats/eps.xsl similarity index 96% rename from src/ascat/formats/eps.xsl rename to src/ascat/read_native/formats/eps.xsl index 331fc26..fa4f8bf 100644 --- a/src/ascat/formats/eps.xsl +++ b/src/ascat/read_native/formats/eps.xsl @@ -10,7 +10,7 @@ Initial revision - Copyright (c) Eumetsat 2003, 2004 + Copyright (c) Eumetsat 2003, 2004 --> diff --git a/src/ascat/formats/eps_ascatl1bszf_6.4.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_6.4.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_6.4.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_6.4.xml diff --git a/src/ascat/formats/eps_ascatl1bszf_6.4m.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_6.4m.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_6.4m.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_6.4m.xml diff --git a/src/ascat/formats/eps_ascatl1bszf_6.5.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_6.5.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_6.5.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_6.5.xml diff --git a/src/ascat/formats/eps_ascatl1bszf_6.6.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_6.6.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_6.6.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_6.6.xml diff --git a/src/ascat/formats/eps_ascatl1bszf_7.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_7.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_7.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_7.0.xml diff --git a/src/ascat/formats/eps_ascatl1bszf_9.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszf_9.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszf_9.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszf_9.0.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_6.4.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_6.4.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_6.4.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_6.4.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_6.4m.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_6.4m.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_6.4m.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_6.4m.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_6.5.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_6.5.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_6.5.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_6.5.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_6.6.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_6.6.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_6.6.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_6.6.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_7.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_7.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_7.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_7.0.xml diff --git a/src/ascat/formats/eps_ascatl1bszo_9.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszo_9.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszo_9.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszo_9.0.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_6.4.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_6.4.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_6.4.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_6.4.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_6.4m.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_6.4m.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_6.4m.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_6.4m.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_6.5.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_6.5.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_6.5.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_6.5.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_6.6.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_6.6.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_6.6.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_6.6.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_7.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_7.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_7.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_7.0.xml diff --git a/src/ascat/formats/eps_ascatl1bszr_9.0.xml b/src/ascat/read_native/formats/eps_ascatl1bszr_9.0.xml similarity index 100% rename from src/ascat/formats/eps_ascatl1bszr_9.0.xml rename to src/ascat/read_native/formats/eps_ascatl1bszr_9.0.xml diff --git a/src/ascat/formats/eps_ascatl2smo_0.1.xml b/src/ascat/read_native/formats/eps_ascatl2smo_0.1.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smo_0.1.xml rename to src/ascat/read_native/formats/eps_ascatl2smo_0.1.xml diff --git a/src/ascat/formats/eps_ascatl2smo_3b.xml b/src/ascat/read_native/formats/eps_ascatl2smo_3b.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smo_3b.xml rename to src/ascat/read_native/formats/eps_ascatl2smo_3b.xml diff --git a/src/ascat/formats/eps_ascatl2smo_4.xml b/src/ascat/read_native/formats/eps_ascatl2smo_4.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smo_4.xml rename to src/ascat/read_native/formats/eps_ascatl2smo_4.xml diff --git a/src/ascat/formats/eps_ascatl2smr_0.1.xml b/src/ascat/read_native/formats/eps_ascatl2smr_0.1.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smr_0.1.xml rename to src/ascat/read_native/formats/eps_ascatl2smr_0.1.xml diff --git a/src/ascat/formats/eps_ascatl2smr_3b.xml b/src/ascat/read_native/formats/eps_ascatl2smr_3b.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smr_3b.xml rename to src/ascat/read_native/formats/eps_ascatl2smr_3b.xml diff --git a/src/ascat/formats/eps_ascatl2smr_4.xml b/src/ascat/read_native/formats/eps_ascatl2smr_4.xml similarity index 100% rename from src/ascat/formats/eps_ascatl2smr_4.xml rename to src/ascat/read_native/formats/eps_ascatl2smr_4.xml diff --git a/src/ascat/read_native/hdf5.py b/src/ascat/read_native/hdf5.py index 9e70573..3fb6886 100644 --- a/src/ascat/read_native/hdf5.py +++ b/src/ascat/read_native/hdf5.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -27,231 +27,234 @@ """ -Readers for SZF data in h5 format. +Readers for ASCAT Level 1b in HDF5 format. """ -from __future__ import division -import numpy as np +from collections import OrderedDict + import h5py +import numpy as np +import xarray as xr -from pygeobase.io_base import ImageBase -from pygeobase.object_base import Image +from ascat.read_native.eps_native import set_flags -# 1.1.2000 00:00:00 in jd -julian_epoch = 2451544.5 +class AscatL1bHdf5File: -class AscatL1H5File(ImageBase): """ - Read ASCAT L2 SSM File in netCDF format, as downloaded from EUMETSAT - - Parameters - ---------- - filename : str - Filename path. - mode : str, optional - Opening mode. Default: r - nc_variables: list, optional - list of variables to read from netCDF. - Default: read all available variables + Read ASCAT Level 1b file in HDF5 format. """ - def __init__(self, filename, mode='r', h5_keys=None, **kwargs): + def __init__(self, filename): """ - Initialization of i/o object. + Initialize AscatL1bHdf5File. + Parameters + ---------- + filename : str + Filename. """ - super(AscatL1H5File, self).__init__(filename, mode=mode, - **kwargs) - self.h5_keys = h5_keys - self.ds = None + self.filename = filename - def read(self, timestamp=None): + def read(self, generic=False, to_xarray=False): """ - reads from the netCDF file given by the filename + Read ASCAT Level 1b data. + + Parameters + ---------- + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). Returns ------- - data : pygeobase.object_base.Image + ds : xarray.Dataset, numpy.ndarray + ASCAT Level 1b data. """ - - if self.ds is None: - self.ds = h5py.File(self.filename) - while len(self.ds.keys()) == 1: - self.ds = self.ds[list(self.ds.keys())[0]] - raw_data = self.ds['DATA'] - raw_metadata = self.ds['METADATA'] - - # store data in dictionary data = {} metadata = {} - if self.h5_keys is None: - var_to_read = list( - raw_data['MDR_1B_FULL_ASCA_Level_1_ARRAY_000001'].dtype.names) - else: - var_to_read = self.h5_keys - - # make sure that essential variables are read always: - if 'LATITUDE_FULL' not in var_to_read: - var_to_read.append('LATITUDE_FULL') - if 'LONGITUDE_FULL' not in var_to_read: - var_to_read.append('LONGITUDE_FULL') - - num_cells = raw_data['MDR_1B_FULL_ASCA_Level_1_ARRAY_000001'][ - 'LATITUDE_FULL'].shape[1] - num_lines = raw_data['MDR_1B_FULL_ASCA_Level_1_ARRAY_000001'][ - 'LATITUDE_FULL'].shape[0] - - # read the requested variables and scale them if they have a - # scaling factor - # encode() is needed for py3 comparison between str and byte - for name in var_to_read: - variable = raw_data['MDR_1B_FULL_ASCA_Level_1_ARRAY_000001'][name] - if name.encode() in \ - raw_data['MDR_1B_FULL_ASCA_Level_1_DESCR']['EntryName']: - var_index = np.where( - raw_data['MDR_1B_FULL_ASCA_Level_1_DESCR'][ - 'EntryName'] == name.encode())[0][0] - if raw_data['MDR_1B_FULL_ASCA_Level_1_DESCR']['Scale Factor'][var_index] != "n/a".encode(): - sf = 10 ** float( - raw_data['MDR_1B_FULL_ASCA_Level_1_DESCR']['Scale Factor'][var_index]) - variable = variable / sf - data[name] = variable[:].flatten() - if len(variable.shape) == 1: - # If the data is 1D then we repeat it for each cell - data[name] = np.repeat(data[name], num_cells) - - data['AS_DES_PASS'] = (data['SAT_TRACK_AZI'] < 270).astype(np.uint8) - - for name in raw_metadata.keys(): - for subname in raw_metadata[name].keys(): - if name not in metadata: - metadata[name] = dict() - metadata[name][subname] = raw_metadata[name][subname] - - # modify longitudes from [0,360] to [-180,180] - mask = data['LONGITUDE_FULL'] > 180 - data['LONGITUDE_FULL'][mask] += -360. - - if 'AZI_ANGLE_FULL' in var_to_read: - mask = data['AZI_ANGLE_FULL'] < 0 - data['AZI_ANGLE_FULL'][mask] += 360 - - if 'UTC_LOCALISATION-days' in var_to_read and \ - 'UTC_LOCALISATION-milliseconds' in var_to_read: - data['jd'] = shortcdstime2jd(data['UTC_LOCALISATION-days'], - data['UTC_LOCALISATION-milliseconds']) - - set_flags(data) - - fields = ['SPACECRAFT_ID', 'ORBIT_START', - 'PROCESSOR_MAJOR_VERSION', 'PROCESSOR_MINOR_VERSION', - 'FORMAT_MAJOR_VERSION', 'FORMAT_MINOR_VERSION' - ] - for field in fields: - var_index = np.where( - np.core.defchararray.startswith( - metadata['MPHR']['MPHR_TABLE']['EntryName'], - field.encode()))[0][0] - var = metadata['MPHR']['MPHR_TABLE']['EntryValue'][ - var_index].decode() - if field == 'SPACECRAFT_ID': - var = var[-1] - metadata[field] = int(var) - - image_dict = {'img1': {}, 'img2': {}, 'img3': {}, 'img4': {}, - 'img5': {}, 'img6': {}} - data_full = {'d1': {}, 'd2': {}, 'd3': {}, 'd4': {}, 'd5': {}, - 'd6': {}} - - # separate data into single beam images - for i in range(1, 7): - dataset = 'd' + str(i) - img = 'img' + str(i) - mask = ((data['BEAM_NUMBER']) == i) - for field in data: - data_full[dataset][field] = data[field][mask] - - lon = data_full[dataset].pop('LONGITUDE_FULL') - lat = data_full[dataset].pop('LATITUDE_FULL') - image_dict[img] = Image(lon, lat, data_full[dataset], metadata, - timestamp, timekey='jd') - - return image_dict - - def read_masked_data(self, **kwargs): - """ - It does not make sense to read a orbit file unmasked - so we only have a masked implementation. - """ - return self.read(**kwargs) + root = 'U-MARF/EPS/ASCA_SZF_1B/' + mdr_path = root + 'DATA/MDR_1B_FULL_ASCA_Level_1_ARRAY_000001' + mdr_descr_path = root + 'DATA/MDR_1B_FULL_ASCA_Level_1_DESCR' + metadata_path = root + 'METADATA' - def write(self, data): - raise NotImplementedError() + with h5py.File(self.filename, mode='r') as fid: + mdr = fid[mdr_path] + mdr_descr = fid[mdr_descr_path] + mdr_metadata = fid[metadata_path] + var_names = list(mdr.dtype.names) - def flush(self): - pass + for var_name in var_names: + data[var_name.lower()] = mdr[var_name] + + if var_name.encode() in mdr_descr['EntryName']: + pos = mdr_descr['EntryName'] == var_name.encode() + scale = mdr_descr['Scale Factor'][pos][0].decode() + + if scale != 'n/a': + data[var_name.lower()] = (data[ + var_name.lower()] / (10. ** float(scale))).astype( + np.float32) + + fields = ['SPACECRAFT_ID', 'ORBIT_START', + 'PROCESSOR_MAJOR_VERSION', 'PROCESSOR_MINOR_VERSION', + 'FORMAT_MAJOR_VERSION', 'FORMAT_MINOR_VERSION'] + + for f in fields: + pos = np.core.defchararray.startswith( + mdr_metadata['MPHR/MPHR_TABLE']['EntryName'], f.encode()) + var = mdr_metadata['MPHR/MPHR_TABLE']['EntryValue'][ + pos][0].decode() + + if f == 'SPACECRAFT_ID': + var = var[-1] + + metadata[f.lower()] = int(var) + + # modify longitudes [0, 360] to [-180, 180] + mask = data['longitude_full'] > 180 + data['longitude_full'][mask] += -360. + + data['time'] = np.datetime64('2000-01-01') + data[ + 'utc_localisation-days'].astype('timedelta64[D]') + data[ + 'utc_localisation-milliseconds'].astype('timedelta64[ms]') + + # modify azimuth angles to [0, 360] + if 'azi_angle_full' in var_names: + mask = data['azi_angle_full'] < 0 + data['azi_angle_full'][mask] += 360 + + rename_coords = {'longitude_full': ('lon', np.float32), + 'latitude_full': ('lat', np.float32)} + + for var_name, (new_name, new_dtype) in rename_coords.items(): + data[new_name] = data.pop(var_name).astype(new_dtype) + + if generic: + data = conv_hdf5l1b_generic(data, metadata) + + # 1 Left Fore Antenna, 2 Left Mid Antenna 3 Left Aft Antenna + # 4 Right Fore Antenna, 5 Right Mid Antenna, 6 Right Aft Antenna + antennas = ['lf', 'lm', 'la', 'rf', 'rm', 'ra'] + ds = OrderedDict() + + for i, antenna in enumerate(antennas): + + subset = data['beam_number'] == i+1 + metadata['beam_number'] = i+1 + metadata['beam_name'] = antenna + + # convert dict to xarray.Dataset or numpy.ndarray + if to_xarray: + sub_data = {} + for var_name in data.keys(): + + if var_name == 'beam_number' and generic: + continue + + if len(data[var_name].shape) == 1: + dim = ['obs'] + elif len(data[var_name].shape) == 2: + dim = ['obs', 'echo'] + + sub_data[var_name] = (dim, data[var_name][subset]) + + coords = {} + coords_fields = ['lon', 'lat', 'time'] + + for cf in coords_fields: + coords[cf] = sub_data.pop(cf) + + ds[antenna] = xr.Dataset(sub_data, coords=coords, + attrs=metadata) + else: + # collect dtype info + dtype = [] + for var_name in data.keys(): + + if len(data[var_name][subset].shape) == 1: + dtype.append( + (var_name, data[var_name][subset].dtype.str)) + elif len(data[var_name][subset].shape) > 1: + dtype.append((var_name, data[var_name][ + subset].dtype.str, data[var_name][ + subset].shape[1:])) + + ds[antenna] = np.empty( + data['time'][subset].size, dtype=np.dtype(dtype)) + + for var_name in data.keys(): + if var_name == 'beam_number' and generic: + continue + ds[antenna][var_name] = data[var_name][subset] + + return ds def close(self): + """ + Close file. + """ pass -def set_flags(data): +def conv_hdf5l1b_generic(data, metadata): """ - Compute summary flag for each measurement with a value of 0, 1 or 2 - indicating nominal, slightly degraded or severely degraded data. + Rename and convert data types of dataset. Parameters ---------- - data : numpy.ndarray - SZF data. + data : dict of numpy.ndarray + Original dataset. + metadata : dict + Metadata. + + Returns + ------- + data : dict of numpy.ndarray + Converted dataset. """ + # convert spacecraft_id to internal sat_id + sat_id = np.array([4, 3, 5]) + metadata['sat_id'] = sat_id[metadata['spacecraft_id']-1] - # category:status = 'red': 2, 'amber': 1, 'warning': 0 - flag_status_bit = {'FLAGFIELD_RF1': {'2': [2, 4], - '1': [0, 1, 3]}, - - 'FLAGFIELD_RF2': {'2': [0, 1]}, - - 'FLAGFIELD_PL': {'2': [0, 1, 2, 3], - '0': [4]}, + # compute ascending/descending direction + data['as_des_pass'] = ( + data['sat_track_azi'] < 270).astype(np.uint8) - 'FLAGFIELD_GEN1': {'2': [1], - '0': [0]}, + data = set_flags(data) + data['f_usable'] = data['f_usable'].reshape(-1, 192) + data['f_land'] = data['f_land'].reshape(-1, 192) - 'FLAGFIELD_GEN2': {'2': [2], - '1': [0], - '0': [1]} - } + data['swath_indicator'] = np.int8(data['beam_number'].flatten() > 3) - for flagfield in flag_status_bit.keys(): - # get flag data in binary format to get flags - unpacked_bits = np.unpackbits(data[flagfield]) + skip_fields = ['utc_localisation-days', 'utc_localisation-milliseconds', + 'degraded_inst_mdr', 'degraded_proc_mdr', 'flagfield_rf1', + 'flagfield_rf2', 'flagfield_pl', 'flagfield_gen1', + 'flagfield_gen2'] - # find indizes where a flag is set - set_bits = np.where(unpacked_bits == 1)[0] - if set_bits.size != 0: - pos_8 = 7 - (set_bits % 8) + gen_fields_lut = {'inc_angle_full': ('inc', np.float32), + 'azi_angle_full': ('azi', np.float32), + 'sigma0_full': ('sig', np.float32)} - for category in sorted(flag_status_bit[flagfield].keys()): - if (int(category) == 0) and (flagfield != 'FLAGFIELD_GEN2'): - continue + for var_name in skip_fields: + if var_name in data: + data.pop(var_name) - for bit2check in flag_status_bit[flagfield][category]: - pos = np.where(pos_8 == bit2check)[0] - data['F_USABLE'] = np.zeros(data['FLAGFIELD_GEN2'].size) - data['F_USABLE'][set_bits[pos] // 8] = int(category) + num_cells = data['lat'].shape[1] - # land points - if (flagfield == 'FLAGFIELD_GEN2') and (bit2check == 1): - data['F_LAND'] = np.zeros(data['FLAGFIELD_GEN2'].size) - data['F_LAND'][set_bits[pos] // 8] = 1 + for var_name in data.keys(): + if len(data[var_name].shape) == 1: + data[var_name] = np.repeat(data[var_name], num_cells) + if len(data[var_name].shape) == 2: + data[var_name] = data[var_name].flatten() + if var_name in gen_fields_lut.items(): + new_name = gen_fields_lut[var_name][0] + new_dtype = gen_fields_lut[var_name][1] + data[new_name] = data.pop(var_name).astype(new_dtype) -def shortcdstime2jd(days, milliseconds): - """ - Convert cds time to julian date - """ - offset = days + (milliseconds / 1000.) / (24. * 60. * 60.) - return julian_epoch + offset + return data diff --git a/src/ascat/read_native/nc.py b/src/ascat/read_native/nc.py index 93b2110..79ec76a 100644 --- a/src/ascat/read_native/nc.py +++ b/src/ascat/read_native/nc.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -27,328 +27,282 @@ """ -Readers for lvl1b and lvl2 data in nc format. +Readers for ASCAT Level 1b and Level 2 data in NetCDF format. """ import os -from datetime import datetime, timedelta import netCDF4 import numpy as np -import pandas as pd +import xarray as xr -from pygeobase.io_base import ImageBase -from pygeobase.io_base import MultiTemporalImageBase -from pygeobase.object_base import Image +from ascat.utils import tmp_unzip -ref_dt = np.datetime64('1970-01-01') -ref_jd = 2440587.5 # julian date on 1970-01-01 00:00:00 +float32_nan = -999999. +uint8_nan = np.iinfo(np.uint8).max -class AscatL1NcFile(ImageBase): +def read_nc(filename, generic, to_xarray, skip_fields, gen_fields_lut): """ - Read ASCAT L1 File in netCDF format, as downloaded from EUMETSAT + Read NetCDF file. Parameters ---------- filename : str - Filename path. - mode : str, optional - Opening mode. Default: r - nc_variables: list, optional - list of variables to read from netCDF. - Default: read all available variables + Filename. + generic : bool + 'True' reading and converting into generic format or + 'False' reading original field names. + to_xarray : bool + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray. + skip_fields : list + Variables to skip. + gen_fields_lut : dict + Conversion look-up table for generic names. + + Returns + ------- + ds : xarray.Dataset, numpy.ndarray + ASCAT data. """ + data = {} + metadata = {} - def __init__(self, filename, mode='r', nc_variables=None, **kwargs): - """ - Initialization of i/o object. + with netCDF4.Dataset(filename) as fid: - """ - super(AscatL1NcFile, self).__init__(filename, mode=mode, - **kwargs) - self.nc_variables = nc_variables - self.ds = None + if hasattr(fid, 'platform'): + metadata['platform_id'] = fid.platform[2:] + elif hasattr(fid, 'platform_long_name'): + metadata['platform_id'] = fid.platform_long_name[2:] - def read(self, timestamp=None): - """ - reads from the netCDF file given by the filename + metadata['orbit_start'] = fid.start_orbit_number + metadata['processor_major_version'] = fid.processor_major_version + metadata['product_minor_version'] = fid.product_minor_version + metadata['format_major_version'] = fid.format_major_version + metadata['format_minor_version'] = fid.format_minor_version + metadata['filename'] = os.path.basename(filename) - Returns - ------- - data : pygeobase.object_base.Image - """ + num_rows = fid.dimensions['numRows'].size + num_cells = fid.dimensions['numCells'].size - if self.ds is None: - self.ds = netCDF4.Dataset(self.filename) + dtype = [] + for var_name in fid.variables.keys(): - if self.nc_variables is None: - var_to_read = self.ds.variables.keys() - else: - var_to_read = self.nc_variables - - # make sure that essential variables are read always: - if 'latitude' not in var_to_read: - var_to_read.append('latitude') - if 'longitude' not in var_to_read: - var_to_read.append('longitude') - - # store data in dictionary - dd = {} - metadata = {} - beams = ['f_', 'm_', 'a_'] - - metadata['sat_id'] = self.ds.platform[-1] - metadata['orbit_start'] = self.ds.start_orbit_number - metadata['processor_major_version'] = self.ds.processor_major_version - metadata['product_minor_version'] = self.ds.product_minor_version - metadata['format_major_version'] = self.ds.format_major_version - metadata['format_minor_version'] = self.ds.format_minor_version - - num_cells = self.ds.dimensions['numCells'].size - for name in var_to_read: - variable = self.ds.variables[name] - - if len(variable.shape) == 1: - # If the data is 1D then we repeat it for each cell - dd[name] = variable[:].flatten() - dd[name] = np.repeat(dd[name], num_cells) - elif len(variable.shape) == 2: - dd[name] = variable[:].flatten() - elif len(variable.shape) == 3: - # length of 3 means it is triplet data, so we split it - for i, beam in enumerate(beams): - dd[beam + name] = variable[:, :, i].flatten() - if name == 'azi_angle_trip': - mask = dd[beam + name] < 0 - dd[beam + name][mask] += 360 + if var_name in ['sigma0']: + continue + + if generic and var_name in skip_fields: + continue + + if generic and var_name in gen_fields_lut: + new_var_name = gen_fields_lut[var_name][0] + fill_value = gen_fields_lut[var_name][2] else: - raise RuntimeError("Unexpected variable shape.") + new_var_name = var_name + fill_value = None + + var_data = fid.variables[var_name][:].filled(fill_value) + + if var_name == 'azi_angle_trip': + var_data[(var_data < 0) & (var_data != fill_value)] += 360 + + if len(fid.variables[var_name].shape) == 1: + var_data = var_data.repeat(num_cells) + elif len(fid.variables[var_name].shape) == 2: + var_data = var_data.flatten() + elif len(fid.variables[var_name].shape) == 3: + var_data = var_data.reshape(-1, 3) + else: + raise RuntimeError('Unknown dimension') + + if var_name == 'utc_line_nodes': + var_data = var_data.astype( + 'timedelta64[s]') + np.datetime64('2000-01-01') + + data[new_var_name] = var_data - if name == 'utc_line_nodes': - utc_dates = netCDF4.num2date( - dd[name], variable.units).astype('datetime64[ns]') - dd['jd'] = (utc_dates - ref_dt)/np.timedelta64(1, 'D') + ref_jd + if len(var_data.shape) == 1: + dtype.append((new_var_name, var_data.dtype.str)) + elif len(var_data.shape) > 1: + dtype.append((new_var_name, var_data.dtype.str, + var_data.shape[1:])) - dd['as_des_pass'] = (dd['sat_track_azi'] < 270).astype(np.uint8) + num_records = num_rows * num_cells + coords_fields = ['lon', 'lat', 'time'] - longitude = dd.pop('longitude') - latitude = dd.pop('latitude') + if generic: + sat_id = np.array([0, 4, 3, 5], dtype=np.uint8) + data['sat_id'] = np.zeros(num_records, dtype=np.uint8) + sat_id[ + int(metadata['platform_id'])] + dtype.append(('sat_id', np.uint8)) - n_records = latitude.shape[0] + n_records = data['lat'].shape[0] n_lines = n_records // num_cells - dd['node_num'] = np.tile((np.arange(num_cells) + 1), n_lines) - dd['line_num'] = np.arange(n_lines).repeat(num_cells) - return Image(longitude, latitude, dd, metadata, timestamp, - timekey='utc_line_nodes') + data['node_num'] = np.tile((np.arange(num_cells) + 1), n_lines) + dtype.append(('node_num', np.uint8)) - def write(self, data): - raise NotImplementedError() + data['line_num'] = np.arange(n_lines).repeat(num_cells) + dtype.append(('line_num', np.int32)) - def flush(self): - pass + if to_xarray: + for k in data.keys(): + if len(data[k].shape) == 1: + dim = ['obs'] + elif len(data[k].shape) == 2: + dim = ['obs', 'beam'] - def close(self): - pass + data[k] = (dim, data[k]) + coords = {} + for cf in coords_fields: + coords[cf] = data.pop(cf) -class AscatL2SsmNcFile(ImageBase): - """ - Read ASCAT L2 SSM File in netCDF format, as downloaded from EUMETSAT + ds = xr.Dataset(data, coords=coords, attrs=metadata) + else: + ds = np.empty(num_records, dtype=np.dtype(dtype)) + for k, v in data.items(): + ds[k] = v - Parameters - ---------- - filename : str - Filename path. - mode : str, optional - Opening mode. Default: r - nc_variables: list, optional - list of variables to read from netCDF. - Default: read all available variables + return ds + + +class AscatL1bNcFile(): + + """ + Read ASCAT Level 1b file in NetCDF format. """ - def __init__(self, filename, mode='r', nc_variables=None, **kwargs): + def __init__(self, filename): """ - Initialization of i/o object. + Initialize AscatL1bNcFile. + Parameters + ---------- + filename : str + Filename. """ - super(AscatL2SsmNcFile, self).__init__(filename, mode=mode, - **kwargs) - self.nc_variables = nc_variables - self.ds = None + if os.path.splitext(filename)[1] == '.gz': + self.filename = tmp_unzip(filename) + else: + self.filename = filename - def read(self, timestamp=None, ssm_masked=False): + def read(self, generic=False, to_xarray=False): """ - reads from the netCDF file given by the filename + Read ASCAT Level 1b data. + + Parameters + ---------- + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). Returns ------- - data : pygeobase.object_base.Image + ds : xarray.Dataset, numpy.ndarray + ASCAT Level 1b data. """ + gen_fields_lut = {'longitude': ('lon', np.float32, None), + 'latitude': ('lat', np.float32, None), + 'utc_line_nodes': ('time', np.float32, None), + 'inc_angle_trip': ('inc', np.float32, float32_nan), + 'azi_angle_trip': ('azi', np.float32, float32_nan), + 'sigma0_trip': ('sig', np.float32, float32_nan), + 'kp': ('kp', np.float32, float32_nan), + 'f_kp': ('kp_quality', np.float32, uint8_nan), + 'num_val_trip': ('num_val', np.float32, None)} - if self.ds is None: - self.ds = netCDF4.Dataset(self.filename) - - if self.nc_variables is None: - var_to_read = self.ds.variables.keys() - else: - var_to_read = self.nc_variables - - # make sure that essential variables are read always: - if 'latitude' not in var_to_read: - var_to_read.append('latitude') - if 'longitude' not in var_to_read: - var_to_read.append('longitude') - - # store data in dictionary - dd = {} - metadata = {} - - metadata['sat_id'] = self.ds.platform_long_name[-1] - metadata['orbit_start'] = self.ds.start_orbit_number - metadata['processor_major_version'] = self.ds.processor_major_version - metadata['product_minor_version'] = self.ds.product_minor_version - metadata['format_major_version'] = self.ds.format_major_version - metadata['format_minor_version'] = self.ds.format_minor_version - - num_cells = self.ds.dimensions['numCells'].size - for name in var_to_read: - variable = self.ds.variables[name] - dd[name] = variable[:].flatten() - if len(variable.shape) == 1: - # If the data is 1D then we repeat it for each cell - dd[name] = np.repeat(dd[name], num_cells) - - if name == 'utc_line_nodes': - utc_dates = netCDF4.num2date( - dd[name], variable.units).astype('datetime64[ns]') - dd['jd'] = (utc_dates - ref_dt)/np.timedelta64(1, 'D') + ref_jd - - # if the ssm_masked is True we mask out data with missing ssm value - if 'soil_moisture' in dd and ssm_masked is True: - # mask all the arrays based on fill_value of latitude - valid_data = ~dd['soil_moisture'].mask - for name in dd: - dd[name] = dd[name][valid_data] - - longitude = dd.pop('longitude') - latitude = dd.pop('latitude') - - n_records = latitude.shape[0] - n_lines = n_records // num_cells - dd['node_num'] = np.tile((np.arange(num_cells) + 1), n_lines) - dd['line_num'] = np.arange(n_lines).repeat(num_cells) + skip_fields = ['f_f', 'f_v', 'f_oa', 'f_sa', 'f_tel', + 'f_ref', 'abs_line_number'] - dd['as_des_pass'] = (dd['sat_track_azi'] < 270).astype(np.uint8) + ds = read_nc(self.filename, generic, to_xarray, + skip_fields, gen_fields_lut) - return Image(longitude, latitude, dd, metadata, timestamp, - timekey='utc_line_nodes') - - def write(self, data): - raise NotImplementedError() - - def flush(self): - pass + return ds def close(self): + """ + Close file. + """ pass -class AscatL2SsmNc(MultiTemporalImageBase): - """ - Class for reading HSAF ASCAT SSM images in netCDF format. - The images have to be uncompressed in the following folder structure +class AscatL2NcFile: - Parameters - ---------- - path: string - path where the data is stored - month_path_str: string, optional - if the files are stored in folders by month as is the standard on - the HSAF FTP Server then please specify the string that should be used - in datetime.datetime.strftime Default: '' - day_search_str: string, optional - to provide an iterator over all images of a day the method - _get_possible_timestamps looks for all available images on a day on the - harddisk. This string is used in datetime.datetime.strftime and in - glob.glob to search for all files on a day. - file_search_str: string, optional - this string is used in datetime.datetime.strftime and glob.glob to find - a 3 minute bufr file by the exact date. - datetime_format: string, optional - datetime format by which {datetime} will be replaced in file_search_str - nc_variables: list, optional - list of variables to read from netCDF. - Default: read all available variables + """ + Read ASCAT Level 2 file in NetCDF format. """ - def __init__(self, path, month_path_str='', - day_search_str='W_XX-EUMETSAT-Darmstadt,' - 'SURFACE+SATELLITE,METOPA+' - 'ASCAT_C_EUMP_%Y%m%d*_125_ssm_l2.nc', - file_search_str='W_XX-EUMETSAT-Darmstadt,' - 'SURFACE+SATELLITE,METOPA+' - 'ASCAT_C_EUMP_{datetime}*_125_ssm_l2.nc', - datetime_format='%Y%m%d%H%M%S', - filename_datetime_format=(62, 76, '%Y%m%d%H%M%S'), - nc_variables=None): - self.path = path - self.month_path_str = month_path_str - self.day_search_str = day_search_str - self.file_search_str = file_search_str - self.filename_datetime_format = filename_datetime_format - super(AscatL2SsmNc, self).__init__(path, AscatL2SsmNcFile, - subpath_templ=[month_path_str], - fname_templ=file_search_str, - datetime_format=datetime_format, - exact_templ=False, - ioclass_kws={ - 'nc_variables': nc_variables}) - - def _get_orbit_start_date(self, filename): - orbit_start_str = \ - os.path.basename(filename)[self.filename_datetime_format[0]: - self.filename_datetime_format[1]] - return datetime.strptime(orbit_start_str, - self.filename_datetime_format[2]) - - def tstamps_for_daterange(self, startdate, enddate): + def __init__(self, filename): """ - Get the timestamps as datetime array that are possible for the - given day, if the timestamps are + Initialize AscatL2NcFile. - For this product it is not fixed but has to be looked up from - the hard disk since bufr files are not regular spaced and only - europe is in this product. For a global product a 3 minute - spacing could be used as a fist approximation + Parameters + ---------- + filename : str + Filename. + """ + if os.path.splitext(filename)[1] == '.gz': + self.filename = tmp_unzip(filename) + else: + self.filename = filename + + def read(self, generic=False, to_xarray=False): + """ + Read ASCAT Level 2 data. Parameters ---------- - startdate : datetime.date or datetime.datetime - start date - enddate : datetime.date or datetime.datetime - end date + generic : bool, optional + 'True' reading and converting into generic format or + 'False' reading original field names (default: False). + to_xarray : bool, optional + 'True' return data as xarray.Dataset + 'False' return data as numpy.ndarray (default: False). Returns ------- - dates : list - list of datetimes + ds : dict, xarray.Dataset + ASCAT Level 2 data. """ - file_list = [] - delta_all = enddate - startdate - timestamps = [] - - for i in range(delta_all.days + 1): - timestamp = startdate + timedelta(days=i) + gen_fields_lut = {'longitude': ('lon', np.float32, None), + 'latitude': ('lat', np.float32, None), + 'utc_line_nodes': ('time', np.float32, None), + 'inc_angle_trip': ('inc', np.float32, float32_nan), + 'azi_angle_trip': ('azi', np.float32, float32_nan), + 'sigma0_trip': ('sig', np.float32, float32_nan), + 'kp': ('kp', np.float32, float32_nan), + 'soil_moisture': ('sm', np.float32, float32_nan), + 'soil_moisture_error': ('sm_noise', np.float32, float32_nan), + 'sigma40': ('sig40', np.float32, float32_nan), + 'sigma40_error': ('sig40_noise', np.float32, float32_nan), + 'slope40': ('slope40', np.float32, float32_nan), + 'slope40_error': ('slope40_noise', np.float32, float32_nan), + 'soil_moisture_sensitivity': ('sm_sens', np.float32, float32_nan), + 'dry_backscatter': ('dry_sig40', np.float32, float32_nan), + 'wet_backscatter': ('wet_sig40', np.float32, float32_nan), + 'mean_soil_moisture': ('sm_mean', np.float32, float32_nan), + 'proc_flag1': ('corr_flag', np.uint8, None), + 'proc_flag2': ('proc_flag', np.uint8, None), + 'aggregated_quality_flag': ('agg_flag', np.uint8, None), + 'snow_cover_probability': ('snow_prob', np.uint8, None), + 'frozen_soil_probability': ('frozen_prob', np.uint8, None), + 'wetland_flag': ('wetland', np.uint8, None), + 'topography_flag': ('topo', np.uint8, None)} + + skip_fields = ['abs_line_number'] + + ds = read_nc(self.filename, generic, to_xarray, + skip_fields, gen_fields_lut) + + return ds - files = self._search_files( - timestamp, custom_templ=self.day_search_str) - - file_list.extend(sorted(files)) - - for filename in file_list: - timestamps.append(self._get_orbit_start_date(filename)) - - timestamps = [dt for dt in timestamps if startdate <= dt <= enddate] - return timestamps + def close(self): + """ + Close file. + """ + pass diff --git a/src/ascat/tuw.py b/src/ascat/tuw.py deleted file mode 100644 index f5a205d..0000000 --- a/src/ascat/tuw.py +++ /dev/null @@ -1,689 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -import os -import warnings -import zipfile -from datetime import datetime - -import numpy as np -import pandas as pd - -import pygeogrids.grids as grids -import pygeogrids.netcdf as ncgrid -from pynetcf.time_series import GriddedNcContiguousRaggedTs - -from ascat.read_native.cdr import AscatTimeSeries - - -class Ascat_data(object): - - """ - Class that provides access to ASCAT data stored in userformat which - is available from the TU Wien FTP Server after registration at - http://rs.geo.tuwien.ac.at. - - Parameters - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains txt files with information - about grid point index,latitude, longitude and cell - grid_info_filename : string, optional - Name of the grid info txt file in grid_path - advisory_flags_path : string, optional - Path to advisory flags .dat files, if not provided they will - not be used - topo_threshold : int, optional - If topographic complexity of read grid point is above this - threshold a warning is output during reading - wetland_threshold : int, optional - If wetland fraction of read grid point is above this - threshold a warning is output during reading - - Attributes - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains txt files with information - about grid point index,latitude, longitude and cell - grid_info_filename : string - Name of the grid info txt file in grid_path - grid_info_np_filename : string - Name of the numpy save file to the grid information - topo_threshold : int - If topographic complexity of read grid point is above this - threshold a warning is output during reading - wetland_threshold : int - If wetland fraction of read grid point is above this - threshold a warning is output during reading - grid_info_loaded : boolean - True if the grid information has already been loaded - grid : :class:`pygeogrids.grids.CellGrid` object - CellGrid object, which provides nearest neighbor search and - other features - advisory_flags_path : string - Path to advisory flags .dat files, if not provided they will - not be used - include_advflags : boolean - True if advisory flags are available - - Methods - ------- - unzip_cell(cell) - unzips zipped grid point files into subdirectory - read_advisory_flags(gpi) - reads the advisory flags for a given grid point index - """ - - def __init__(self, path, grid_path, - grid_info_filename='TUW_W54_01_lonlat-ld-land.txt', - advisory_flags_path=None, topo_threshold=50, - wetland_threshold=50): - """ - Set path and threshold - """ - self.path = path - self.grid_path = grid_path - self.grid_info_filename = grid_info_filename - self.grid_info_np_filename = 'TUW_W54_01_lonlat-ld-land.npy' - self.topo_threshold = topo_threshold - self.wetland_threshold = wetland_threshold - self.grid_info_loaded = False - self.grid = None - self.advisory_flags_path = advisory_flags_path - if self.advisory_flags_path is None: - self.include_advflags = False - else: - self.include_advflags = True - self.adv_flags_struct = np.dtype([('gpi', np.int32), - ('snow', np.uint8, 366), - ('frozen', np.uint8, 366), - ('water', np.uint8), - ('topo', np.uint8)]) - - def _load_grid_info(self): - """ - Reads the grid info for all land points from the txt file provided - by TU Wien. The first time the actual txt file is parsed and saved - as a numpy array to speed up future data access. - """ - grid_info_np_filepath = os.path.join( - self.grid_path, self.grid_info_np_filename) - - if os.path.exists(grid_info_np_filepath): - grid_info = np.load(grid_info_np_filepath) - - else: - grid_info_filepath = os.path.join( - self.grid_path, self.grid_info_filename) - grid_info = np.loadtxt( - grid_info_filepath, delimiter=',', skiprows=1) - np.save(os.path.join(self.grid_path, - self.grid_info_np_filename), grid_info) - - self.grid = grids.CellGrid(grid_info[:, 2], grid_info[:, 1], - grid_info[:, 3].astype(np.int16), - gpis=grid_info[:, 0].astype(np.int32)) - - self.grid_info_loaded = True - - def unzip_cell(self, cell): - """ - Unzips the downloaded .zip cell file into the directory of - os.path.join(self.path, cell). - - Parameters - ---------- - cell : int - cell number - """ - filepath = os.path.join(self.path, '%4d.zip' % cell) - unzip_file_path = os.path.join(self.path, '%4d' % cell) - - if not os.path.exists(unzip_file_path): - os.mkdir(unzip_file_path) - - zfile = zipfile.ZipFile(filepath) - for name in zfile.namelist(): - (dirname, filename) = os.path.split(name) - fd = open(os.path.join(unzip_file_path, filename), "w") - fd.write(zfile.read(name)) - fd.close() - zfile.close() - - def _datetime_arr(self, longdate): - """ - Parsing function that takes a number of type long which contains - YYYYMMDDHH and returns a datetime object - - Parameters - ---------- - longdate : long - Date including hour as number of type long in format YYYYMMDDHH - - Returns - ------- - datetime : datetime - """ - string = str(longdate) - year = int(string[0:4]) - month = int(string[4:6]) - day = int(string[6:8]) - hour = int(string[8:]) - - return datetime(year, month, day, hour) - - def _read_ts(self, *args, **kwargs): - """ - Takes either 1 or 2 arguments and calls the correct function - which is either reading the gpi directly or finding - the nearest gpi from given lat,lon coordinates and then reading it - """ - - if not self.grid_info_loaded: - self._load_grid_info() - - if len(args) == 1: - return self._read_gp(args[0], **kwargs) - if len(args) == 2: - return self._read_lonlat(args[0], args[1], **kwargs) - - def _read_gp(self, gpi, **kwargs): - """ - Reads the time series of the given grid point index. Masks frozen - and snow observations if keywords are present - - Parameters - ---------- - gpi : long - grid point index - mask_frozen_prob : int,optional - if included in kwargs then all observations taken when - frozen probability > mask_frozen_prob are removed from the result - mask_snow_prob : int,optional - if included in kwargs then all observations taken when - snow probability > mask_snow_prob are removed from the result - - Returns - ------- - df : pandas.DataFrame - containing all fields in the list self.include_in_df - plus frozen_prob and snow_prob if a path to advisory flags was - set during initialization - """ - cell = self.grid.gpi2cell(int(gpi)) - - gp_file = os.path.join( - self.path, '%4d' % cell, self.gp_filename_template % gpi) - - if not os.path.exists(gp_file): - print('first time reading from cell %4d unzipping ...' % cell) - self.unzip_cell(cell) - - data = np.fromfile(gp_file, dtype=self.gp_filestruct) - dates = data['DAT'] - - datetime_parser = np.vectorize(self._datetime_arr) - - datetimes_correct = datetime_parser(dates) - - dict_df = {} - - for into_df in self.include_in_df: - d = np.ma.asarray(data[into_df], dtype=self.datatype[into_df]) - d = np.ma.masked_equal(d, self.nan_values[into_df]) - if into_df in self.scale_factor.keys(): - d = d * self.scale_factor[into_df] - dict_df[into_df] = d - - df = pd.DataFrame(dict_df, index=datetimes_correct) - - if self.include_advflags: - adv_flags, topo, wetland = self.read_advisory_flags(gpi) - - if topo >= self.topo_threshold: - warnings.warn( - "Warning gpi shows topographic complexity of %d %%. Data might not be usable." % topo) - if wetland >= self.wetland_threshold: - warnings.warn( - "Warning gpi shows wetland fraction of %d %%. Data might not be usable." % wetland) - - df['doy'] = df.index.dayofyear - df = df.join(adv_flags, on='doy', how='left') - del df['doy'] - - if 'mask_frozen_prob' in kwargs: - mask_frozen = kwargs['mask_frozen_prob'] - df = df[df['frozen_prob'] <= mask_frozen] - - if 'mask_snow_prob' in kwargs: - mask_snow = kwargs['mask_snow_prob'] - df = df[df['snow_prob'] <= mask_snow] - - lon, lat = self.grid.gpi2lonlat(gpi) - - return df, gpi, lon, lat, cell - - def _read_lonlat(self, lon, lat, **kwargs): - """ - Get nearest grid point and read data. - - Parameters - ---------- - lon : float - Longitude. - lat : float - Latitude. - - Returns - ------- - data : numpy.ndarray - Read data. - """ - gpi, dist = self.grid.find_nearest_gpi(lon, lat) - return self._read_gp(int(gpi), **kwargs) - - def read_advisory_flags(self, gpi): - """ - Read the advisory flags located in the self.advisory_flags_path - Advisory flags include frozen probability, snow cover probability - topographic complexity and wetland fraction. - - Parameters - ---------- - gpi : long - grid point index - - Returns - ------- - df : pandas.DataFrame - containing the columns frozen_prob and snow_prob. lenght 366 - with one entry for every day of the year, including February 29th - topo : numpy.uint8 - topographic complexity ranging from 0-100 - wetland : numpy.uint8 - wetland fraction of pixel in percent - """ - if not self.include_advflags: - raise RuntimeError("Error: advisory_flags_path is not set") - - if not self.grid_info_loaded: - self._load_grid_info() - - cell = self.grid.gpi2cell(gpi) - adv_file = os.path.join( - self.advisory_flags_path, '%d_advisory-flags.dat' % cell) - data = np.fromfile(adv_file, dtype=self.adv_flags_struct) - index = np.where(data['gpi'] == gpi)[0] - - data = data[index] - - snow = data['snow'][0] - snow[snow == 0] += 101 - snow -= 101 - - df = pd.DataFrame({'snow_prob': snow, - 'frozen_prob': data['frozen'][0]}) - - return df, data['topo'][0], data['water'][0] - - -class Ascat_SSM(Ascat_data): - - """ - Class for reading ASCAT SSM data. It extends Ascat_data and provides the - information necessary for reading SSM data - - Parameters - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains txt files with information - about grid point index,latitude, longitude and cell - grid_info_filename : string, optional - Name of the grid info txt file in grid_path - advisory_flags_path : string, optional - Path to advisory flags .dat files, if not provided they will not - be used - topo_threshold : int, optional - If topographic complexity of read grid point is above this - threshold a warning is output during reading - wetland_threshold : int, optional - If wetland fraction of read grid point is above this - threshold a warning is output during reading - - Attributes - ---------- - gp_filename_template : string - Defines how the gpi is put into the template string to make the - filename - gp_filestruct : numpy.dtype - Structure template of the SSM .dat file - scale_factor : dict - Factor by which to multiply the raw data to get the correct values - for each field in the gp_filestruct - include_in_df : list - List of fields that should be returned to the user after reading - nan_values : dict - Nan value saved in the file which will be replaced by numpy.nan values - during reading - datatype : dict - Datatype of the fields that the return data should have - - Methods - ------- - read_ssm(*args,**kwargs) - read surface soil moisture - """ - - def __init__(self, *args, **kwargs): - super(Ascat_SSM, self).__init__(*args, **kwargs) - self.gp_filename_template = 'TUW_ASCAT_SSM_W55_gp%d.dat' - self.gp_filestruct = np.dtype([('DAT', np.int32), - ('SSM', np.uint8), - ('ERR', np.uint8), - ('SSF', np.uint8)]) - - self.scale_factor = {'SSM': 0.5, 'ERR': 0.5} - self.include_in_df = ['SSM', 'ERR', 'SSF'] - self.nan_values = {'SSM': 255, 'ERR': 255, 'SSF': 255} - self.datatype = {'SSM': np.float, 'ERR': np.float, 'SSF': np.int} - - def read_ssm(self, *args, **kwargs): - """ - Function to read SSM takes either 1 or 2 arguments. - It can be called as read_ssm(gpi, **kwargs) or - read_ssm(lon, lat, **kwargs) - - Parameters - ---------- - gpi : int - Grid point index - lon : float - Longitude of point - lat : float - Latitude of point - mask_ssf : boolean, optional - Default False, if True only SSF values of 1 will be allowed, - all others are removed - mask_frozen_prob : int,optional - If included in kwargs then all observations taken when - frozen probability > mask_frozen_prob are removed from the result - mask_snow_prob : int,optional - If included in kwargs then all observations taken when - snow probability > mask_snow_prob are removed from the result - - Returns - ------- - AscatTimeSeries : object - :class:`ascat.AscatTimeSeries` instance - """ - df, gpi, lon, lat, cell = super( - Ascat_SSM, self)._read_ts(*args, **kwargs) - if 'mask_ssf' in kwargs: - mask_ssf = kwargs['mask_ssf'] - if mask_ssf: - df = df[df['SSF'] == 1] - - return AscatTimeSeries(gpi, lon, lat, cell, df) - - -class Ascat_SWI(Ascat_data): - - """ - Class for reading ASCAT SWI data. It extends Ascat_data and provides the - information necessary for reading SWI data - - Parameters - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains txt files with information - about grid point index,latitude, longitude and cell - grid_info_filename : string, optional - Name of the grid info txt file in grid_path - advisory_flags_path : string, optional - Path to advisory flags .dat files, if not provided they will not - be used - topo_threshold : int, optional - If topographic complexity of read grid point is above this - threshold a warning is output during reading - wetland_threshold : int, optional - If wetland fraction of read grid point is above this - threshold a warning is output during reading - - Attributes - ---------- - gp_filename_template : string - Defines how the gpi is put into the template string to make - the filename - gp_filestruct : numpy.dtype - Structure template of the SSM .dat file - scale_factor : dict - Factor by which to multiply the raw data to get the correct values - for each field in the gp_filestruct - include_in_df : list - List of fields that should be returned to the user after reading - nan_values : dict - Nan value saved in the file which will be replaced by numpy.nan values - during reading - datatype : dict - Datatype of the fields that the return data should have - T_SWI : dict - Information about which numerical T-Value maps to which entry in the - datastructure - T_QFLAG : dict - Information about which numerical T-Value maps to which entry in the - datastructure - - Methods - ------- - read_swi(*args,**kwargs) - read soil water index - """ - - def __init__(self, *args, **kwargs): - super(Ascat_SWI, self).__init__(*args, **kwargs) - self.gp_filename_template = 'TUW_ASCAT_SWI_W55_gp%d.dat' - self.gp_filestruct = np.dtype([('DAT', np.int32), - ('SWI_T=1', np.uint8), - ('SWI_T=5', np.uint8), - ('SWI_T=10', np.uint8), - ('SWI_T=15', np.uint8), - ('SWI_T=20', np.uint8), - ('SWI_T=40', np.uint8), - ('SWI_T=60', np.uint8), - ('SWI_T=100', np.uint8), - ('QFLAG_T=1', np.uint8), - ('QFLAG_T=5', np.uint8), - ('QFLAG_T=10', np.uint8), - ('QFLAG_T=15', np.uint8), - ('QFLAG_T=20', np.uint8), - ('QFLAG_T=40', np.uint8), - ('QFLAG_T=60', np.uint8), - ('QFLAG_T=100', np.uint8)]) - - self.scale_factor = {'SWI_T=1': 0.5, 'SWI_T=5': 0.5, - 'SWI_T=10': 0.5, 'SWI_T=15': 0.5, - 'SWI_T=20': 0.5, 'SWI_T=40': 0.5, - 'SWI_T=60': 0.5, 'SWI_T=100': 0.5, - 'QFLAG_T=1': 0.5, 'QFLAG_T=5': 0.5, - 'QFLAG_T=10': 0.5, 'QFLAG_T=15': 0.5, - 'QFLAG_T=20': 0.5, 'QFLAG_T=40': 0.5, - 'QFLAG_T=60': 0.5, 'QFLAG_T=100': 0.5} - - self.include_in_df = ['SWI_T=1', 'SWI_T=5', 'SWI_T=10', 'SWI_T=15', - 'SWI_T=20', 'SWI_T=40', 'SWI_T=60', 'SWI_T=100', - 'QFLAG_T=1', 'QFLAG_T=5', 'QFLAG_T=10', - 'QFLAG_T=15', 'QFLAG_T=20', 'QFLAG_T=40', - 'QFLAG_T=60', 'QFLAG_T=100'] - - self.nan_values = {'SWI_T=1': 255, 'SWI_T=5': 255, 'SWI_T=10': 255, - 'SWI_T=15': 255, 'SWI_T=20': 255, 'SWI_T=40': 255, - 'SWI_T=60': 255, 'SWI_T=100': 255, - 'QFLAG_T=1': 255, 'QFLAG_T=5': 255, - 'QFLAG_T=10': 255, 'QFLAG_T=15': 255, - 'QFLAG_T=20': 255, 'QFLAG_T=40': 255, - 'QFLAG_T=60': 255, 'QFLAG_T=100': 255} - - self.datatype = {'SWI_T=1': np.float, 'SWI_T=5': np.float, - 'SWI_T=10': np.float, 'SWI_T=15': np.float, - 'SWI_T=20': np.float, 'SWI_T=40': np.float, - 'SWI_T=60': np.float, 'SWI_T=100': np.float, - 'QFLAG_T=1': np.float, 'QFLAG_T=5': np.float, - 'QFLAG_T=10': np.float, 'QFLAG_T=15': np.float, - 'QFLAG_T=20': np.float, 'QFLAG_T=40': np.float, - 'QFLAG_T=60': np.float, 'QFLAG_T=100': np.float} - - self.T_SWI = {1: 'SWI_T=1', 5: 'SWI_T=5', 10: 'SWI_T=10', - 15: 'SWI_T=15', 20: 'SWI_T=20', 40: 'SWI_T=40', - 60: 'SWI_T=60', 100: 'SWI_T=100'} - - self.T_QFLAG = {1: 'QFLAG_T=1', 5: 'QFLAG_T=5', 10: 'QFLAG_T=10', - 15: 'QFLAG_T=15', 20: 'QFLAG_T=20', 40: 'QFLAG_T=40', - 60: 'QFLAG_T=60', 100: 'QFLAG_T=100'} - - def read_swi(self, *args, **kwargs): - """ - Function to read SWI takes either 1 or 2 arguments being. - It can be called as read_swi(gpi, **kwargs) or - read_swi(lon, lat, **kwargs) - - Parameters - ---------- - gpi : int - grid point index - lon : float - longitude of point - lat : float - latitude of point - T : int, optional - if set only the SWI and QFLAG of this T-Value will be returned - mask_qf : int, optional - if set, SWI values with a QFLAG value lower than the mask_qf - value will be masked. This is done for each T value independently - mask_frozen_prob : int,optional - if included in kwargs then all observations taken when - frozen probability > mask_frozen_prob are removed from the result - mask_snow_prob : int,optional - if included in kwargs then all observations taken when - snow probability > mask_snow_prob are removed from the result - Returns - ------- - df : pandas.DataFrame - containing all fields in self.include_in_df plus frozen_prob - and snow_prob if advisory_flags_path was set. If T was set then - only SWI and QFLAG values for the selected T value are included - plut frozen_prob and snow_prob if applicable - """ - df, gpi, lon, lat, cell = super(Ascat_SWI, self)._read_ts(*args, - **kwargs) - - if 'T' in kwargs: - T = kwargs['T'] - if T in self.T_SWI.keys(): - if self.include_advflags: - df = df[[self.T_SWI[T], self.T_QFLAG[T], - 'frozen_prob', 'snow_prob']] - else: - df = df[[self.T_SWI[T], self.T_QFLAG[T]]] - else: - raise RuntimeError( - "Invalid T value. Choose one of " + str(sorted(self.T_SWI.keys()))) - - # remove rows that have to small QFLAG - if 'mask_qf' in kwargs: - mask_qf = kwargs['mask_qf'] - if mask_qf: - df = df[df[self.T_QFLAG[T]] >= mask_qf] - - else: - # mask each T value according to qf threshold - if 'mask_qf' in kwargs: - mask_qf = kwargs['mask_qf'] - for key in self.T_SWI: - masked = df[self.T_QFLAG[key]] <= mask_qf - df[self.T_SWI[key]][masked] = np.NAN - df[self.T_QFLAG[key]][masked] = np.NAN - - return AscatTimeSeries(gpi, lon, lat, cell, df) - - -class AscatVodTs(GriddedNcContiguousRaggedTs): - - """ - Class that provides access to ASCAT VOD data stored in netCDF format. - - Parameters - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains a netcdf file with - information about grid point index,latitude, longitude and cell - grid_info_filename : string, optional - Name of the grid info netCDF file in grid_path - default 'TUW_WARP5_grid_info_2_1.nc' - - Attributes - ---------- - path : string - Path to data folder which contains the zip files from the FTP server - grid_path : string - Path to grid_info folder which contains txt files with information - about grid point index,latitude, longitude and cell - grid_info_filename : string, optional - Name of the grid info netCDF file in grid_path - default 'TUW_WARP5_grid_info_2_1.nc' - grid : grids.CellGrid object - CellGrid object, which provides nearest neighbor search and - other features - variables : list of string - """ - - def __init__(self, path, grid_path, - grid_info_filename='TUW_WARP5_grid_info_2_1.nc', - variables=None): - - grid = ncgrid.load_grid(os.path.join(grid_path, grid_info_filename), - subset_flag='land') - - self.path = path - self.grid_path = grid_path - self.grid_info_filename = grid_info_filename - - self.variables = variables - - if self.variables is None: - self.variables = ['vod'] - - super(AscatVodTs, self).__init__(path, grid) diff --git a/src/ascat/utils.py b/src/ascat/utils.py index a4d9e35..a9da5ae 100644 --- a/src/ascat/utils.py +++ b/src/ascat/utils.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -25,7 +25,33 @@ # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +from gzip import GzipFile +from tempfile import NamedTemporaryFile + import numpy as np +import xarray as xr + + +def tmp_unzip(filename): + """ + Unzip file to temporary directory. + + Parameters + ---------- + filename : str + Filename. + + Returns + ------- + unzipped_filename : str + Unzipped filename + """ + with NamedTemporaryFile(delete=False) as tmp_fid: + with GzipFile(filename) as gz_fid: + tmp_fid.write(gz_fid.read()) + unzipped_filename = tmp_fid.name + + return unzipped_filename def db2lin(val): @@ -176,3 +202,73 @@ def get_window_weights(window, radius, distance, norm=False): weights = weights / w_sum return weights + + +def get_toi_subset(ds, toi): + """ + Filter dataset for given time of interest. + + Parameters + ---------- + ds : xarray.Dataset + Dataset to be filtered for time of interest. + toi : tuple of datetime + Time of interest. + + Returns + ------- + ds : xarray.Dataset + Filtered dataset. + """ + if isinstance(ds, dict): + for key in ds.keys(): + subset = ((ds[key]['time'] > np.datetime64(toi[0])) & + (ds[key]['time'] < np.datetime64(toi[1]))) + if isinstance(ds[key], xr.Dataset): + ds[key] = ds[key].sel(obs=np.nonzero(subset.values)[0]) + elif isinstance(ds[key], np.ndarray): + ds[key] = ds[key][subset] + else: + subset = ((ds['time'] > np.datetime64(toi[0])) & + (ds['time'] < np.datetime64(toi[1]))) + if isinstance(ds, xr.Dataset): + ds = ds.sel(obs=np.nonzero(subset.values)[0]) + elif isinstance(ds, np.ndarray): + ds = ds[subset] + + return ds + + +def get_roi_subset(ds, roi): + """ + Filter dataset for given region of interest. + + Parameters + ---------- + ds : xarray.Dataset + Dataset to be filtered for region of interest. + roi : tuple of 4 float + Region of interest: latmin, lonmin, latmax, lonmax + + Returns + ------- + ds : xarray.Dataset + Filtered dataset. + """ + if isinstance(ds, dict): + for key in ds.keys(): + subset = ((ds[key]['lat'] > roi[0]) & (ds[key]['lat'] < roi[2]) & + (ds[key]['lon'] > roi[1]) & (ds[key]['lon'] < roi[3])) + if isinstance(ds[key], xr.Dataset): + ds[key] = ds[key].sel(obs=np.nonzero(subset.values)[0]) + elif isinstance(ds[key], np.ndarray): + ds[key] = ds[key][subset] + else: + subset = ((ds['lat'] > roi[0]) & (ds['lat'] < roi[2]) & + (ds['lon'] > roi[1]) & (ds['lon'] < roi[3])) + if isinstance(ds, xr.Dataset): + ds = ds.sel(obs=np.nonzero(subset.values)[0]) + elif isinstance(ds, np.ndarray): + ds = ds[subset] + + return ds diff --git a/tests/test_cgls.py b/tests/test_cgls.py index c62827b..de1ddd0 100644 --- a/tests/test_cgls.py +++ b/tests/test_cgls.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without diff --git a/tests/test_eumetsat.py b/tests/test_eumetsat.py deleted file mode 100644 index c9288ed..0000000 --- a/tests/test_eumetsat.py +++ /dev/null @@ -1,553 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -""" -Test data downloaded from EUMETSAT UMARF -""" - -import unittest -import datetime -import numpy as np -import numpy.testing as nptest -import os -import sys -import pytest - -from ascat.eumetsat import AscatL2Ssm125 -from ascat.eumetsat import AscatL2Ssm125PDU -from ascat.eumetsat import AscatL2Ssm250 -from ascat.eumetsat import AscatL2Ssm250PDU -from ascat.eumetsat import AscatL2Ssm125Nc -from ascat.eumetsat import AscatL2Ssm250Nc - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_ASCAT_A_L2_SSM_125_BUFR(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_125', 'bufr') - self.reader_A = AscatL2Ssm125(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm125(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 5, 57)] - assert sorted(timestamps) == sorted(timestamps_should) - - timestamps = self.reader_B.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 5, 9)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([3., 0., 0., 0., 0., 0., 0., 0., 0., 1.8, 3.3, - 4.8, 4.3, 2.5, 0., 3.8, 5.8, 1.5, 2.4, 4.1, 2.3, - 2.7, 5.6, 5.5, 4.9]) - - lats_should = np.array([62.60224, 62.67133, 62.74015, 62.80871, 62.877, - 62.94502, 63.01276, 63.08024, 63.14743, - 63.21435, 63.28098, 63.34734, 63.41341, - 63.47919, 63.54468, 63.60988, 63.67479, - 63.7394, 63.80372, 63.86773, 63.93144, - 63.99485, 64.05795, 64.12075, 64.18323]) - - ssm_mean_should = np.array([21.3, 21.3, 21.4, 22.4, 23.4, 24.5, 26., - 27.1, 27., 26.6, 27.1, 27.6, 27.4, 26.7, - 26.5, 27.5, 28.2, 28.4, 28.8, 29.2, 30., - 31., 31.3, 31.9, 32.1]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([29.2, 30.2, 35.7, 38.6, 37.5, 37.6, 40.5, 44.5, - 40.7, 39.7, 41.5, 38.8, 34.5, 36.8, 39.4, 41.2, - 42.4, 42.9, 39.3, 30.5, 26.7, 26.5, 26.7, 23.9, - 26.2]) - - lats_should = np.array([64.74398, 64.81854, 64.89284, 64.96688, - 65.04066, 65.11416, 65.18739, 65.26036, - 65.33304, 65.40545, 65.47758, 65.54942, - 65.62099, 65.69226, 65.76324, 65.83393, - 65.90432, 65.97442, 66.04422, 66.11371, - 66.1829, 66.25177, 66.32034, 66.38859, - 66.45653]) - - ssm_mean_should = np.array([36.7, 35.4, 33.4, 32.5, 32.5, 32., 31.2, - 29.4, 28.7, 27.6, 25.8, 25.4, 25.5, 25.3, - 24.4, 23.4, 22.3, 21.3, 20.4, 20.4, 19.9, - 19.7, 20.3, 21.5, 22.9]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_ASCAT_L2_SSM_125_BUFR_PDU(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_125', 'PDU') - self.reader_A = AscatL2Ssm125PDU(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm125PDU(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 4, 18), - datetime.datetime(2017, 2, 20, 4, 21)] - assert sorted(timestamps) == sorted(timestamps_should) - - timestamps = self.reader_B.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 5, 9), - datetime.datetime(2017, 2, 20, 5, 12), - datetime.datetime(2017, 2, 20, 5, 15)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([3., 0., 0., 0., 0., 0., 0., 0., 0., 1.8, 3.3, - 4.8, 4.3, 2.5, 0., 3.8, 5.8, 1.5, 2.4, 4.1, 2.3, - 2.7, 5.6, 5.5, 4.9]) - - lats_should = np.array([62.60224, 62.67133, 62.74015, 62.80871, 62.877, - 62.94502, 63.01276, 63.08024, 63.14743, - 63.21435, 63.28098, 63.34734, 63.41341, - 63.47919, 63.54468, 63.60988, 63.67479, - 63.7394, 63.80372, 63.86773, 63.93144, - 63.99485, 64.05795, 64.12075, 64.18323]) - - ssm_mean_should = np.array([21.3, 21.3, 21.4, 22.4, 23.4, 24.5, 26., - 27.1, 27., 26.6, 27.1, 27.6, 27.4, 26.7, - 26.5, 27.5, 28.2, 28.4, 28.8, 29.2, 30., - 31., 31.3, 31.9, 32.1]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([29.2, 30.2, 35.7, 38.6, 37.5, 37.6, 40.5, 44.5, - 40.7, 39.7, 41.5, 38.8, 34.5, 36.8, 39.4, 41.2, - 42.4, 42.9, 39.3, 30.5, 26.7, 26.5, 26.7, 23.9, - 26.2]) - - lats_should = np.array([64.74398, 64.81854, 64.89284, 64.96688, - 65.04066, 65.11416, 65.18739, 65.26036, - 65.33304, 65.40545, 65.47758, 65.54942, - 65.62099, 65.69226, 65.76324, 65.83393, - 65.90432, 65.97442, 66.04422, 66.11371, - 66.1829, 66.25177, 66.32034, 66.38859, - 66.45653]) - - ssm_mean_should = np.array([36.7, 35.4, 33.4, 32.5, 32.5, 32., 31.2, - 29.4, 28.7, 27.6, 25.8, 25.4, 25.5, 25.3, - 24.4, 23.4, 22.3, 21.3, 20.4, 20.4, 19.9, - 19.7, 20.3, 21.5, 22.9]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_ASCAT_L2_SSM_250_BUFR(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_250', 'bufr') - self.reader_A = AscatL2Ssm250(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm250(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 5, 57)] - assert sorted(timestamps) == sorted(timestamps_should) - - timestamps = self.reader_B.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 5, 9)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([1.8, 0., 0., 0., 0., 4.6, 2.8, 4., 4.1, 4.2, - 4.7, 5.4, 7.1, 7.1, 8.2, 9.2, 14.5, 15.4, 14.3, - 17.7, 25.5, 36.9, 37.8, 39.4, 24.1]) - - lats_should = np.array([62.60224, 62.74015, 62.877, 63.01276, - 63.14743, 63.28098, 63.41341, 63.54468, - 63.67479, 63.80372, 63.93144, 64.05795, - 64.18323, 64.30725, 64.42999, 64.55145, - 64.6716, 64.79042, 64.9079, 65.02401, - 65.13873, 67.85438, 67.91597, 67.97556, - 68.03314]) - - ssm_mean_should = np.array([21.3, 21.4, 23.4, 26., 27., 27.1, 27.4, - 26.5, 28.2, 28.8, 30., 31.3, 32.1, 30.6, - 27.8, 28.9, 29.5, 32.1, 33.8, 32.9, 28.9, - 41.1, 40.8, 34.4, 31.]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([28.8, 31., 35.8, 38.7, 39.3, 38.9, 39.6, 40.7, - 40.9, 35.5, 28.7, 25.2, 25.8, 27.2, 26.3, 29.1, - 30., 27.1, 25.5, 23.9, 25.7, 44.9, 38.7, 36.7, - 40.6]) - - lats_should = np.array([64.74398, 64.89284, 65.04066, 65.18739, - 65.33304, 65.47758, 65.62099, 65.76324, - 65.90432, 66.04422, 66.1829, 66.32034, - 66.45653, 66.59144, 66.72505, 66.85734, - 66.98829, 67.11787, 67.24605, 67.37283, - 67.49816, 70.48423, 70.55154, 70.61658, - 70.67934]) - - ssm_mean_should = np.array([36.7, 33.4, 32.5, 31.2, 28.7, 25.8, 25.5, - 24.4, 22.3, 20.4, 19.9, 20.3, 22.9, 23.7, - 23.5, 22.2, 22.2, 22.4, 25.3, 27.8, 27.7, - 30.7, 30.7, 31.6, 33.6]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_ASCAT_L2_SSM_250_BUFR_PDU(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_250', 'PDU') - self.reader_A = AscatL2Ssm250PDU(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm250PDU(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 4, 18), - datetime.datetime(2017, 2, 20, 4, 21)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([1.8, 0., 0., 0., 0., 4.6, 2.8, 4., 4.1, 4.2, - 4.7, 5.4, 7.1, 7.1, 8.2, 9.2, 14.5, 15.4, 14.3, - 17.7, 25.5, 36.9, 37.8, 39.4, 24.1]) - - lats_should = np.array([62.60224, 62.74015, 62.877, 63.01276, - 63.14743, 63.28098, 63.41341, 63.54468, - 63.67479, 63.80372, 63.93144, 64.05795, - 64.18323, 64.30725, 64.42999, 64.55145, - 64.6716, 64.79042, 64.9079, 65.02401, - 65.13873, 67.85438, 67.91597, 67.97556, - 68.03314]) - - ssm_mean_should = np.array([21.3, 21.4, 23.4, 26., 27., 27.1, 27.4, - 26.5, 28.2, 28.8, 30., 31.3, 32.1, 30.6, - 27.8, 28.9, 29.5, 32.1, 33.8, 32.9, 28.9, - 41.1, 40.8, 34.4, 31.]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([28.8, 31., 35.8, 38.7, 39.3, 38.9, 39.6, 40.7, - 40.9, 35.5, 28.7, 25.2, 25.8, 27.2, 26.3, 29.1, - 30., 27.1, 25.5, 23.9, 25.7, 44.9, 38.7, 36.7, - 40.6]) - - lats_should = np.array([64.74398, 64.89284, 65.04066, 65.18739, - 65.33304, 65.47758, 65.62099, 65.76324, - 65.90432, 66.04422, 66.1829, 66.32034, - 66.45653, 66.59144, 66.72505, 66.85734, - 66.98829, 67.11787, 67.24605, 67.37283, - 67.49816, 70.48423, 70.55154, 70.61658, - 70.67934]) - - ssm_mean_should = np.array([36.7, 33.4, 32.5, 31.2, 28.7, 25.8, 25.5, - 24.4, 22.3, 20.4, 19.9, 20.3, 22.9, 23.7, - 23.5, 22.2, 22.2, 22.4, 25.3, 27.8, 27.7, - 30.7, 30.7, 31.6, 33.6]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=0.01) - - -class Test_ASCAT_L2_SSM_125_NC(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_125', 'nc') - self.reader_A = AscatL2Ssm125Nc(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm125Nc(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 5, 57)] - assert sorted(timestamps) == sorted(timestamps_should) - - timestamps = self.reader_B.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 5, 9)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([3., 0., 0., 0., 0., 0., 0., 0., 0., 1.8, 3.3, - 4.8, 4.3, 2.5, 0., 3.8, 5.8, 1.5, 2.4, 4.1, 2.3, - 2.7, 5.6, 5.5, 4.9]) - - lats_should = np.array([62.60224, 62.67133, 62.74015, 62.80871, 62.877, - 62.94502, 63.01276, 63.08024, 63.14743, - 63.21435, 63.28098, 63.34734, 63.41341, - 63.47919, 63.54468, 63.60988, 63.67479, - 63.7394, 63.80372, 63.86773, 63.93144, - 63.99485, 64.05795, 64.12075, 64.18323]) - - ssm_mean_should = np.array([21.3, 21.3, 21.4, 22.4, 23.4, 24.5, 26., - 27.1, 27., 26.6, 27.1, 27.6, 27.4, 26.7, - 26.5, 27.5, 28.2, 28.4, 28.8, 29.2, 30., - 31., 31.3, 31.9, 32.1]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][ - :25], ssm_should, atol=0.1) - nptest.assert_allclose(data['mean_soil_moisture'][:25], - ssm_mean_should, - atol=0.1) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([29.2, 30.2, 35.7, 38.6, 37.5, 37.6, 40.5, 44.5, - 40.7, 39.7, 41.5, 38.8, 34.5, 36.8, 39.4, 41.2, - 42.4, 42.9, 39.3, 30.5, 26.7, 26.5, 26.7, 23.9, - 26.2]) - - lats_should = np.array([64.74398, 64.81854, 64.89284, 64.96688, - 65.04066, 65.11416, 65.18739, 65.26036, - 65.33304, 65.40545, 65.47758, 65.54942, - 65.62099, 65.69226, 65.76324, 65.83393, - 65.90432, 65.97442, 66.04422, 66.11371, - 66.1829, 66.25177, 66.32034, 66.38859, - 66.45653]) - - ssm_mean_should = np.array([36.7, 35.4, 33.4, 32.5, 32.5, 32., 31.2, - 29.4, 28.7, 27.6, 25.8, 25.4, 25.5, 25.3, - 24.4, 23.4, 22.3, 21.3, 20.4, 20.4, 19.9, - 19.7, 20.3, 21.5, 22.9]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][ - :25], ssm_should, atol=0.1) - nptest.assert_allclose(data['mean_soil_moisture'][:25], - ssm_mean_should, - atol=0.1) - - -class Test_ASCAT_L2_SSM_250_NC(unittest.TestCase): - - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'eumetsat', 'ASCAT_L2_SM_250', 'nc') - self.reader_A = AscatL2Ssm250Nc(data_path, 'Metop_A') - self.reader_B = AscatL2Ssm250Nc(data_path, 'Metop_B') - - def tearDown(self): - self.reader_A = None - self.reader_B = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - """ - timestamps = self.reader_A.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 4, 15), - datetime.datetime(2017, 2, 20, 5, 57)] - assert sorted(timestamps) == sorted(timestamps_should) - - timestamps = self.reader_B.tstamps_for_daterange( - datetime.datetime(2017, 2, 20), datetime.datetime(2017, 2, 21)) - timestamps_should = [datetime.datetime(2017, 2, 20, 5, 9)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader_A.read( - datetime.datetime(2017, 2, 20, 4, 15)) - - ssm_should = np.array([1.8, 0., 0., 0., 0., 4.6, 2.8, 4., 4.1, 4.2, - 4.7, 5.4, 7.1, 7.1, 8.2, 9.2, 14.5, 15.4, 14.3, - 17.7, 25.5, 36.9, 37.8, 39.4, 24.1]) - - lats_should = np.array([62.60224, 62.74015, 62.877, 63.01276, - 63.14743, 63.28098, 63.41341, 63.54468, - 63.67479, 63.80372, 63.93144, 64.05795, - 64.18323, 64.30725, 64.42999, 64.55145, - 64.6716, 64.79042, 64.9079, 65.02401, - 65.13873, 67.85438, 67.91597, 67.97556, - 68.03314]) - - ssm_mean_should = np.array([21.3, 21.4, 23.4, 26., 27., 27.1, 27.4, - 26.5, 28.2, 28.8, 30., 31.3, 32.1, 30.6, - 27.8, 28.9, 29.5, 32.1, 33.8, 32.9, 28.9, - 41.1, 40.8, 34.4, 31.]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][ - :25], ssm_should, atol=0.1) - nptest.assert_allclose(data['mean_soil_moisture'][:25], - ssm_mean_should, - atol=0.1) - - data, meta, timestamp, lons, lats, time_var = self.reader_B.read( - datetime.datetime(2017, 2, 20, 5, 9)) - - ssm_should = np.array([28.8, 31., 35.8, 38.7, 39.3, 38.9, 39.6, 40.7, - 40.9, 35.5, 28.7, 25.2, 25.8, 27.2, 26.3, 29.1, - 30., 27.1, 25.5, 23.9, 25.7, 44.9, 38.7, 36.7, - 40.6]) - - lats_should = np.array([64.74398, 64.89284, 65.04066, 65.18739, - 65.33304, 65.47758, 65.62099, 65.76324, - 65.90432, 66.04422, 66.1829, 66.32034, - 66.45653, 66.59144, 66.72505, 66.85734, - 66.98829, 67.11787, 67.24605, 67.37283, - 67.49816, 70.48423, 70.55154, 70.61658, - 70.67934]) - - ssm_mean_should = np.array([36.7, 33.4, 32.5, 31.2, 28.7, 25.8, 25.5, - 24.4, 22.3, 20.4, 19.9, 20.3, 22.9, 23.7, - 23.5, 22.2, 22.2, 22.4, 25.3, 27.8, 27.7, - 30.7, 30.7, 31.6, 33.6]) - - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][ - :25], ssm_should, atol=0.1) - nptest.assert_allclose(data['mean_soil_moisture'][:25], - ssm_mean_should, - atol=0.1) - - -if __name__ == '__main__': - unittest.main() diff --git a/tests/test_h_saf.py b/tests/test_h_saf.py index f365c90..143b48a 100644 --- a/tests/test_h_saf.py +++ b/tests/test_h_saf.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -29,219 +29,109 @@ import sys import pytest import unittest -from datetime import datetime, timedelta +from datetime import datetime import numpy as np import numpy.testing as nptest -import ascat.h_saf as H_SAF +from ascat.h_saf import H08Bufr +from ascat.h_saf import H08BufrFileList +from ascat.h_saf import H14GribFileList +from ascat.h_saf import AscatNrtBufrFileList +from ascat.h_saf import AscatSsmDataRecord @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") class Test_H08(unittest.TestCase): + """ + Test H08 reading. + """ + def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'hsaf', 'h08') - self.reader = H_SAF.H08img(data_path) - - def tearDown(self): - self.reader = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - 2010-05-01 - """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2010, 5, 1), datetime(2010, 5, 1, 12)) - timestamps_should = [datetime(2010, 5, 1, 8, 33, 1)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2010, 5, 1, 8, 33, 1)) - # do not check data content at the moment just shapes and structure - assert sorted(data.keys()) == sorted( - ['ssm', 'corr_flag', 'ssm_noise', 'proc_flag']) - assert lons.shape == (3120, 7680) - assert lats.shape == (3120, 7680) - for var in data: - assert data[var].shape == (3120, 7680) - - def test_image_reading_bbox_empty(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2010, 5, 1, 8, 33, 1), lat_lon_bbox=[45, 48, 15, 18]) - - # do not check data content at the moment just shapes and structure - assert data is None - assert lons is None - assert lats is None - - def test_image_reading_bbox(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2010, 5, 1, 8, 33, 1), - lat_lon_bbox=[60, 70, 15, 25]) - - # do not check data content at the moment just shapes and structure - assert sorted(data.keys()) == sorted( - ['ssm', 'corr_flag', 'ssm_noise', 'proc_flag']) - assert lons.shape == (2400, 2400) - assert lats.shape == (2400, 2400) - for var in data: - assert data[var].shape == (2400, 2400) + """ + Setup test data. + """ + self.root_path = os.path.join( + os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h08') + def test_read(self): + """ + Test read file. + """ + filename = os.path.join(self.root_path, 'h08_201005_buf', + 'h08_20100501_083301_metopa_18322_ZAMG.buf') -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_H07(unittest.TestCase): + h08 = H08Bufr(filename) + data = h08.read() - def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'hsaf', 'h07') - self.reader = H_SAF.H07img(data_path) - - def tearDown(self): - self.reader = None - - def test_offset_getting(self): - """ - test getting the image offsets for a known day - 2010-05-01 - """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2010, 5, 1), datetime(2010, 5, 1, 12)) - timestamps_should = [datetime(2010, 5, 1, 8, 33, 1)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2010, 5, 1, 8, 33, 1)) - - ssm_should = np.array([51.2, 65.6, 46.2, 56.9, 61.4, 61.5, 58.1, 47.1, - 72.7, 13.8, 60.9, 52.1, 78.5, 57.8, 56.2, 79.8, - 67.7, 53.8, 86.5, 29.4, 50.6, 88.8, 56.9, 68.9, - 52.4, 64.4, 81.5, 50.5, 84., 79.6, 47.4, 79.5, - 46.9, 60.7, 81.3, 52.9, 84.5, 25.5, 79.2, 93.3, - 52.6, 93.9, 74.4, 91.4, 76.2, 92.5, 80., 88.3, - 79.1, 97.2, 56.8]) - - lats_should = np.array([70.21162, 69.32506, 69.77325, 68.98149, - 69.12295, 65.20364, 67.89625, 67.79844, - 67.69112, 67.57446, 67.44865, 67.23221, - 66.97207, 66.7103, 66.34695, 65.90996, - 62.72462, 61.95761, 61.52935, 61.09884, - 60.54359, 65.60223, 65.33588, 65.03098, - 64.58972, 61.46131, 60.62553, 59.52057, - 64.27395, 63.80293, 60.6569, 59.72684, - 58.74838, 63.42774]) - - ssm_mean_should = np.array([0.342, 0.397, 0.402, 0.365, 0.349, - 0.354, 0.37, 0.36, 0.445, 0.211, - 0.394, 0.354, 0.501, 0.361, 0.366, - 0.45, 0.545, 0.329, 0.506, 0.229, - 0.404, 0.591, 0.348, 0.433, 0.29, - 0.508, 0.643, 0.343, 0.519, 0.61, - 0.414, 0.594, 0.399, 0.512, 0.681, - 0.457, 0.622, 0.396, 0.572, 0.7, - 0.302, 0.722, 0.493, 0.747, 0.521, - 0.72, 0.578, 0.718, 0.536, 0.704, - 0.466]) * 100 - - nptest.assert_allclose(lats[25:-1:30], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - 15:-1:20], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][15:-1:20], - ssm_mean_should, - atol=0.01) + assert sorted(data.keys()) == sorted(['lon', 'lat', 'ssm', 'corr_flag', + 'ssm_noise', 'proc_flag']) + for var_name, var in data.items(): + assert var.shape == (3120, 7680) + def test_read_files(self): + """ + Test read files. + """ + h08_files = H08BufrFileList(self.root_path) -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_H16(unittest.TestCase): + dt = datetime(2010, 5, 1, 8, 33, 1) + data = h08_files.read(dt) - def setUp(self): - data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h16') - self.reader = H_SAF.H16img(data_path, month_path_str='') + assert sorted(data.keys()) == sorted(['lon', 'lat', 'ssm', 'corr_flag', + 'ssm_noise', 'proc_flag']) + for var_name, var in data.items(): + assert var.shape == (3120, 7680) - def tearDown(self): - self.reader = None - def test_offset_getting(self): +@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") +class Test_AscatNrtSsm(unittest.TestCase): + + def setUp(self): """ - test getting the image offsets for a known day - 2010-05-01 + Setup test data. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2017, 2, 20), datetime(2017, 2, 21)) - timestamps_should = [datetime(2017, 2, 20, 11, 0, 0) + - timedelta(minutes=3) * n for n in range(8)] - assert sorted(timestamps) == sorted(timestamps_should) + self.root_path = os.path.join( + os.path.dirname(__file__), 'ascat_test_data', 'hsaf') - def test_offset_getting_datetime_boundary(self): + def test_h16_read(self): """ - test getting the image offsets for a known daterange, - checks if exact datetimes are used + Test read file. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2017, 2, 20, 11, 3), - datetime(2017, 2, 20, 11, 12)) - timestamps_should = [datetime(2017, 2, 20, 11, 3, 0) + - timedelta(minutes=3) * n for n in range(4)] - assert sorted(timestamps) == sorted(timestamps_should) + dt = datetime(2017, 2, 20, 11, 15, 0) + h16 = AscatNrtBufrFileList(os.path.join(self.root_path, 'h16'), 'h16') + data = h16.read(dt) - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2017, 2, 20, 11, 15, 0)) - - ssm_should = np.array([0., 3.6, 7.8, 8.2, 12.3, 14.7, 21.6, 26.7, - 30.6, 32.2, 43., 50.5, 46.3, 47.6, 58.]) + sm_should = np.array([0., 3.6, 7.8, 8.2, 12.3, 14.7, 21.6, 26.7, + 30.6, 32.2, 43., 50.5, 46.3, 47.6, 58.]) lats_should = np.array([-28.25222, -28.21579, -28.1789, -28.14155, -28.10374, -28.06547, -28.02674, -27.98755, -27.94791, -27.90782, -27.86727, -27.82627, -27.78482, -27.74292, -27.70058, ]) - ssm_mean_should = np.array([32.8, 35.1, 37.8, 39.2, 39., 38., 36.2, - 39.6, 43.8, 45.6, 46.1, 47., 43.7, 46., - 46.7]) + sm_mean_should = np.array([32.8, 35.1, 37.8, 39.2, 39., 38., 36.2, + 39.6, 43.8, 45.6, 46.1, 47., 43.7, 46., + 46.7]) - nptest.assert_allclose(lats[798:813], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - 798:813], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][798:813], - ssm_mean_should, + nptest.assert_allclose(data['lat'][798:813], lats_should, atol=1e-5) + nptest.assert_allclose(data['sm'][798:813], sm_should, atol=0.01) + nptest.assert_allclose(data['sm_mean'][798:813], sm_mean_should, atol=0.01) - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_H101(unittest.TestCase): - - def setUp(self): - data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h101') - self.reader = H_SAF.H101img(data_path, month_path_str='') - - def tearDown(self): - self.reader = None - - def test_offset_getting(self): + def test_h101_read(self): """ - test getting the image offsets for a known day - 2010-05-01 + Test read file. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2017, 2, 20), datetime(2017, 2, 21)) - timestamps_should = [datetime(2017, 2, 20, 10, 24, 0) + - timedelta(minutes=3) * n for n in range(8)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2017, 2, 20, 10, 42, 0)) + dt = datetime(2017, 2, 20, 10, 42, 0) + h101 = AscatNrtBufrFileList( + os.path.join(self.root_path, 'h101'), 'h101') + data = h101.read(dt) - ssm_should = np.array([26.1, 31.5, 49.5, 64.3, 80.3, 87.9, 24.5, 18.5, - 20., 12.9, 6.3, 3.1, 3.5, 5.7, 2., 0., 4.6, 8., - 9.6, 11.8]) + sm_should = np.array([26.1, 31.5, 49.5, 64.3, 80.3, 87.9, 24.5, 18.5, + 20., 12.9, 6.3, 3.1, 3.5, 5.7, 2., 0., 4.6, 8., + 9.6, 11.8]) lats_should = np.array([56.26292, 56.29267, 56.32112, 56.34827, 56.37413, 56.39868, 51.98611, 52.08869, @@ -249,47 +139,27 @@ def test_image_reading(self): 52.58802, 52.68512, 52.78127, 52.87648, 52.97073, 53.06402, 53.15634, 53.24768]) - ssm_mean_should = np.array([22.8, 27., 31.8, 38.3, 44.3, 52.4, 24.8, - 27.8, 24.7, 23.9, 22.8, 25., 25.6, 26.1, - 25.9, 26.9, 28.5, 27.8, 24.3, 22.7]) - - nptest.assert_allclose(lats[1800:1820], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - 1800:1820], ssm_should, atol=0.01) - nptest.assert_allclose( - data['Mean Surface Soil Moisture'][1800:1820], - ssm_mean_should, atol=0.01) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_H102(unittest.TestCase): - - def setUp(self): - data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h102') - self.reader = H_SAF.H102img(data_path, month_path_str='') + sm_mean_should = np.array([22.8, 27., 31.8, 38.3, 44.3, 52.4, 24.8, + 27.8, 24.7, 23.9, 22.8, 25., 25.6, 26.1, + 25.9, 26.9, 28.5, 27.8, 24.3, 22.7]) - def tearDown(self): - self.reader = None + nptest.assert_allclose(data['lat'][1800:1820], lats_should, atol=1e-5) + nptest.assert_allclose(data['sm'][1800:1820], sm_should, atol=0.01) + nptest.assert_allclose(data['sm_mean'][1800:1820], sm_mean_should, + atol=0.01) - def test_offset_getting(self): + def test_h102_read(self): """ - test getting the image offsets for a known day - 2010-05-01 + Test read file. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2017, 2, 20), datetime(2017, 2, 21)) - timestamps_should = [datetime( - 2017, 2, 20, 10, 24, 0) + timedelta(minutes=3) * n for n in range(8)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2017, 2, 20, 10, 42, 0)) + dt = datetime(2017, 2, 20, 10, 42, 0) + h102 = AscatNrtBufrFileList( + os.path.join(self.root_path, 'h102'), 'h102') + data = h102.read(dt) - ssm_should = np.array([45.8, 43.5, 41.7, 42.7, 38.6, 31.1, 23.4, 21.7, - 23.6, 26.8, 30.5, 30.1, 32.7, 34.7, 35.8, 38.3, - 46.2, 53.7, 46.2]) + sm_should = np.array([45.8, 43.5, 41.7, 42.7, 38.6, 31.1, 23.4, 21.7, + 23.6, 26.8, 30.5, 30.1, 32.7, 34.7, 35.8, 38.3, + 46.2, 53.7, 46.2]) lats_should = np.array([43.16844, 43.21142, 43.25423, 43.29686, 43.33931, 43.38158, 43.42367, 43.46558, @@ -297,62 +167,40 @@ def test_image_reading(self): 43.67243, 43.71326, 43.7539, 43.79436, 43.83463, 43.87472, 43.91463]) - ssm_mean_should = np.array([50.8, 44.5, 36.3, 29.9, 28.7, 29.1, 30., - 30.1, 30.8, 33., 34.9, 35.7, 35.2, 34.2, - 32.9, 32.9, 34.5, 32.7, 30.6]) + sm_mean_should = np.array([50.8, 44.5, 36.3, 29.9, 28.7, 29.1, 30., + 30.1, 30.8, 33., 34.9, 35.7, 35.2, 34.2, + 32.9, 32.9, 34.5, 32.7, 30.6]) - nptest.assert_allclose(lats[0:19], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - 0:19], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][0:19], - ssm_mean_should, + nptest.assert_allclose(data['lat'][0:19], lats_should, atol=1e-5) + nptest.assert_allclose(data['sm'][0:19], sm_should, atol=0.01) + nptest.assert_allclose(data['sm_mean'][0:19], sm_mean_should, atol=0.01) - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_H103(unittest.TestCase): - - def setUp(self): - data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h103') - self.reader = H_SAF.H103img(data_path, month_path_str='') - - def tearDown(self): - self.reader = None - - def test_offset_getting(self): + def test_h103_read(self): """ - test getting the image offsets for a known day - 2010-05-01 + Test read file. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2017, 2, 20), datetime(2017, 2, 21)) - timestamps_should = [datetime( - 2017, 2, 20, 10, 30, 0) + timedelta(minutes=3) * n for n in range(8)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2017, 2, 20, 10, 30, 0)) + dt = datetime(2017, 2, 20, 10, 30, 0) + h103 = AscatNrtBufrFileList( + os.path.join(self.root_path, 'h103'), 'h103') + data = h103.read(dt) - ssm_should = np.array([20.4, 15.2, 4.2, 0., 0.7, 6.8, 14.2, 21.9, - 23.7, 17.4, 14.8, 19.8, 15.4, 17.1, 28.9, - 28.5, 23.9, 18.1, 25.4]) + sm_should = np.array([20.4, 15.2, 4.2, 0., 0.7, 6.8, 14.2, 21.9, + 23.7, 17.4, 14.8, 19.8, 15.4, 17.1, 28.9, + 28.5, 23.9, 18.1, 25.4]) lats_should = np.array([8.82896, 8.85636, 8.88373, 8.91107, 8.93837, 8.96564, 8.99288, 9.02009, 9.04726, 9.0744, 9.1015, 9.12858, 9.15561, 9.18262, 9.20959, 9.23653, 9.26343, 9.2903, 9.31713]) - ssm_mean_should = np.array([14., 14., 13.8, 13.5, 13.3, 13.1, 12.8, - 12.6, 12.6, 12., 12.1, 12.6, 13.2, 14.1, - 13.9, 12.4, 10.9, 10.3, 10.7]) + sm_mean_should = np.array([14., 14., 13.8, 13.5, 13.3, 13.1, 12.8, + 12.6, 12.6, 12., 12.1, 12.6, 13.2, 14.1, + 13.9, 12.4, 10.9, 10.3, 10.7]) - nptest.assert_allclose(lats[0:19], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - 0:19], ssm_should, atol=0.01) - nptest.assert_allclose(data['Mean Surface Soil Moisture'][0:19], - ssm_mean_should, + nptest.assert_allclose(data['lat'][0:19], lats_should, atol=1e-5) + nptest.assert_allclose(data['sm'][0:19], sm_should, atol=0.01) + nptest.assert_allclose(data['sm_mean'][0:19], sm_mean_should, atol=0.01) @@ -360,338 +208,267 @@ def test_image_reading(self): class Test_H14(unittest.TestCase): def setUp(self): - data_path = os.path.join( + """ + Setup test data. + """ + self.root_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'hsaf', 'h14') - self.reader = H_SAF.H14img(data_path, expand_grid=False) - self.expand_reader = H_SAF.H14img(data_path, expand_grid=True) - def tearDown(self): - self.reader = None - self.expand_reader = None + def test_read(self): + """ + Test read file. + """ + dt = datetime(2014, 5, 15, 0) + h14 = H14GribFileList(self.root_path) + data = h14.read(dt) - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2014, 5, 15)) - assert sorted(data.keys()) == sorted(['SM_layer1_0-7cm', + assert sorted(data.keys()) == sorted(['lat', 'lon', + 'SM_layer1_0-7cm', 'SM_layer2_7-28cm', 'SM_layer3_28-100cm', 'SM_layer4_100-289cm']) - assert lons.shape == (843490,) - assert lats.shape == (843490,) - for var in data: - assert data[var].shape == (843490,) - assert meta[var]['name'] - assert meta[var]['units'] in ['dimensionless', 'unknown'] - - def test_expanded_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.expand_reader.read( - datetime(2014, 5, 15)) - assert sorted(data.keys()) == sorted(['SM_layer1_0-7cm', - 'SM_layer2_7-28cm', - 'SM_layer3_28-100cm', - 'SM_layer4_100-289cm']) - assert lons.shape == (800, 1600) - assert lats.shape == (800, 1600) + for var in data: assert data[var].shape == (800, 1600) - assert meta[var]['name'] - assert meta[var]['units'] in ['dimensionless', 'unknown'] -class Test_H25Ts(unittest.TestCase): +class Test_AscatSsmDataRecord(unittest.TestCase): def setUp(self): path = os.path.dirname(__file__) - cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'h25') - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = H_SAF.H25Ts(cdr_path, grid_path, - static_layer_path=static_layer_path) - - def tearDown(self): - self.ascat_reader.close() + self.gpi = 3066159 + self.cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf') + self.grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') + self.static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', + 'static_layer') - def test_read(self): - - gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi + def test_read_h25(self): + """ + Test read H25. + """ + self.h25 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h25'), self.grid_path, + static_layer_path=self.static_layer_path) - np.testing.assert_approx_equal(result.longitude, 19.03533, - significant=4) - np.testing.assert_approx_equal(result.latitude, 70.05438, - significant=4) + data = self.h25.read(self.gpi, absolute_sm=True) + assert data.attrs['gpi'] == self.gpi - assert len(result.data) == 7737 - assert result.data.iloc[15].name.to_pydatetime() == \ - datetime(2007, 1, 7, 10, 49, 9, 4) - assert result.data.iloc[15]['sm'] == 22 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 6 - assert result.data.iloc[15]['frozen_prob'] == 0 - assert result.data.iloc[15]['snow_prob'] == 127 - assert result.data.iloc[15]['orbit_dir'].decode('utf-8') == 'D' - assert result.data.iloc[15]['proc_flag'] == 0 + np.testing.assert_approx_equal( + data.attrs['lon'], 19.03533, significant=4) + np.testing.assert_approx_equal( + data.attrs['lat'], 70.05438, significant=4) + + assert len(data) == 7737 + assert data.iloc[15].name.to_pydatetime() == datetime( + 2007, 1, 7, 10, 49, 9, 4) + assert data.iloc[15]['sm'] == 22 + assert data.iloc[15]['ssf'] == 1 + assert data.iloc[15]['sm_noise'] == 6 + assert data.iloc[15]['frozen_prob'] == 0 + assert data.iloc[15]['snow_prob'] == 127 + assert data.iloc[15]['orbit_dir'].decode('utf-8') == 'D' + assert data.iloc[15]['proc_flag'] == 0 np.testing.assert_equal( - result.data.iloc[15]['abs_sm_gldas'], np.nan) + data.iloc[15]['abs_sm_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], np.nan) + data.iloc[15]['abs_sm_noise_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.1078, significant=6) + data.iloc[15]['abs_sm_hwsd'], 0.1078, significant=6) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0294, significant=6) + data.iloc[15]['abs_sm_noise_hwsd'], 0.0294, significant=6) - assert result.topo_complex == 9 - assert result.wetland_frac == 41 + assert data.attrs['topo_complex'] == 9 + assert data.attrs['wetland_frac'] == 41 np.testing.assert_approx_equal( - result.porosity_gldas, np.nan, significant=5) + data.attrs['porosity_gldas'], np.nan, significant=5) np.testing.assert_approx_equal( - result.porosity_hwsd, 0.49000001, significant=5) - + data.attrs['porosity_hwsd'], 0.49000001, significant=5) -class Test_H108Ts(unittest.TestCase): - - def setUp(self): - - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'h108') - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = H_SAF.H108Ts(cdr_path, grid_path, - static_layer_path=static_layer_path) - - def tearDown(self): - self.ascat_reader.close() + def test_read_h108(self): + """ + Test read H108. + """ + self.h108 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h108'), self.grid_path, + static_layer_path=self.static_layer_path) - def test_read(self): + data = self.h108.read(self.gpi, absolute_sm=True) + assert data.attrs['gpi'] == self.gpi - gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi - - np.testing.assert_approx_equal(result.longitude, 19.03533, + np.testing.assert_approx_equal(data.attrs['lon'], 19.03533, significant=4) - np.testing.assert_approx_equal(result.latitude, 70.05438, + np.testing.assert_approx_equal(data.attrs['lat'], 70.05438, significant=4) - assert len(result.data) == 8222 - assert result.data.iloc[15].name.to_pydatetime() == \ - datetime(2007, 1, 7, 10, 49, 9, 4) - assert result.data.iloc[15]['sm'] == 22 - assert result.data.iloc[15]['ssf'] == 2 - assert result.data.iloc[15]['sm_noise'] == 6 - assert result.data.iloc[15]['frozen_prob'] == 0 - assert result.data.iloc[15]['snow_prob'] == 127 - assert result.data.iloc[15]['orbit_dir'].decode('utf-8') == 'D' - assert result.data.iloc[15]['proc_flag'] == 0 + assert len(data) == 8222 + assert data.iloc[15].name.to_pydatetime() == datetime( + 2007, 1, 7, 10, 49, 9, 4) + assert data.iloc[15]['sm'] == 22 + assert data.iloc[15]['ssf'] == 2 + assert data.iloc[15]['sm_noise'] == 6 + assert data.iloc[15]['frozen_prob'] == 0 + assert data.iloc[15]['snow_prob'] == 127 + assert data.iloc[15]['orbit_dir'].decode('utf-8') == 'D' + assert data.iloc[15]['proc_flag'] == 0 np.testing.assert_equal( - result.data.iloc[15]['abs_sm_gldas'], np.nan) + data.iloc[15]['abs_sm_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], np.nan) + data.iloc[15]['abs_sm_noise_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.1078, significant=6) - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0294, significant=6) - - assert result.topo_complex == 9 - assert result.wetland_frac == 41 - - np.testing.assert_equal( - result.porosity_gldas, np.nan) + data.iloc[15]['abs_sm_hwsd'], 0.1078, significant=6) np.testing.assert_approx_equal( - result.porosity_hwsd, 0.49000001, significant=5) - + data.iloc[15]['abs_sm_noise_hwsd'], 0.0294, significant=6) -class Test_H109Ts(unittest.TestCase): + assert data.attrs['topo_complex'] == 9 + assert data.attrs['wetland_frac'] == 41 - def setUp(self): + np.testing.assert_equal(data.attrs['porosity_gldas'], np.nan) + np.testing.assert_approx_equal(data.attrs['porosity_hwsd'], + 0.49000001, significant=5) - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'h109') - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = H_SAF.H109Ts(cdr_path, grid_path, - static_layer_path=static_layer_path) - - def tearDown(self): - self.ascat_reader.close() - - def test_read(self): + def test_read_h109(self): + """ + Test read H109. + """ + self.h109 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h109'), self.grid_path, + static_layer_path=self.static_layer_path) - gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi + data = self.h109.read(self.gpi, absolute_sm=True) + assert data.attrs['gpi'] == self.gpi - np.testing.assert_approx_equal(result.longitude, 19.03533, + np.testing.assert_approx_equal(data.attrs['lon'], 19.03533, significant=4) - np.testing.assert_approx_equal(result.latitude, 70.05438, + np.testing.assert_approx_equal(data.attrs['lat'], 70.05438, significant=4) - assert len(result.data) == 11736 - assert result.data.iloc[15].name.to_pydatetime() == \ + assert len(data) == 11736 + assert data.iloc[15].name.to_pydatetime() == \ datetime(2007, 1, 7, 10, 49, 9, 379200) - assert result.data.iloc[15]['sm'] == 27 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 5 - assert result.data.iloc[15]['frozen_prob'] == 0 - assert result.data.iloc[15]['snow_prob'] == 127 - assert result.data.iloc[15]['dir'] == 1 - assert result.data.iloc[15]['proc_flag'] == 0 - assert result.data.iloc[15]['corr_flag'] == 16 - assert result.data.iloc[15]['sat_id'] == 3 + assert data.iloc[15]['sm'] == 27 + assert data.iloc[15]['ssf'] == 1 + assert data.iloc[15]['sm_noise'] == 5 + assert data.iloc[15]['frozen_prob'] == 0 + assert data.iloc[15]['snow_prob'] == 127 + assert data.iloc[15]['dir'] == 1 + assert data.iloc[15]['proc_flag'] == 0 + assert data.iloc[15]['corr_flag'] == 16 + assert data.iloc[15]['sat_id'] == 3 np.testing.assert_equal( - result.data.iloc[15]['abs_sm_gldas'], np.nan) + data.iloc[15]['abs_sm_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], np.nan) + data.iloc[15]['abs_sm_noise_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.1323, significant=6) + data.iloc[15]['abs_sm_hwsd'], 0.1323, significant=6) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) - - assert result.topo_complex == 9 - assert result.wetland_frac == 41 - - np.testing.assert_equal( - result.porosity_gldas, np.nan) - np.testing.assert_approx_equal( - result.porosity_hwsd, 0.49000001, significant=5) - - -class Test_H110Ts(unittest.TestCase): - - def setUp(self): + data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'h110') - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = H_SAF.H110Ts(cdr_path, grid_path, - static_layer_path=static_layer_path) + assert data.attrs['topo_complex'] == 9 + assert data.attrs['wetland_frac'] == 41 - def tearDown(self): - self.ascat_reader.close() + np.testing.assert_equal(data.attrs['porosity_gldas'], np.nan) + np.testing.assert_approx_equal(data.attrs['porosity_hwsd'], + 0.49000001, significant=5) - def test_read(self): + def test_read_h110(self): + """ + Test read H110. + """ + self.h110 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h110'), self.grid_path, + static_layer_path=self.static_layer_path) - gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi + data = self.h110.read(self.gpi, absolute_sm=True) + assert data.attrs['gpi'] == self.gpi - np.testing.assert_approx_equal(result.longitude, 19.03533, + np.testing.assert_approx_equal(data.attrs['lon'], 19.03533, significant=4) - np.testing.assert_approx_equal(result.latitude, 70.05438, + np.testing.assert_approx_equal(data.attrs['lat'], 70.05438, significant=4) - assert len(result.data) == 1148 - assert result.data.iloc[15].name.to_pydatetime() == \ - datetime(2016, 1, 3, 19, 34, 28, 99200) - assert result.data.iloc[15]['sm'] == 48 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 5 - assert result.data.iloc[15]['frozen_prob'] == 0 - assert result.data.iloc[15]['snow_prob'] == 127 - assert result.data.iloc[15]['dir'] == 0 - assert result.data.iloc[15]['proc_flag'] == 0 - assert result.data.iloc[15]['corr_flag'] == 0 - assert result.data.iloc[15]['sat_id'] == 4 + assert len(data) == 1148 + assert data.iloc[15].name.to_pydatetime() == datetime( + 2016, 1, 3, 19, 34, 28, 99200) + assert data.iloc[15]['sm'] == 48 + assert data.iloc[15]['ssf'] == 1 + assert data.iloc[15]['sm_noise'] == 5 + assert data.iloc[15]['frozen_prob'] == 0 + assert data.iloc[15]['snow_prob'] == 127 + assert data.iloc[15]['dir'] == 0 + assert data.iloc[15]['proc_flag'] == 0 + assert data.iloc[15]['corr_flag'] == 0 + assert data.iloc[15]['sat_id'] == 4 np.testing.assert_equal( - result.data.iloc[15]['abs_sm_gldas'], np.nan) + data.iloc[15]['abs_sm_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], np.nan) + data.iloc[15]['abs_sm_noise_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.2352, significant=6) + data.iloc[15]['abs_sm_hwsd'], 0.2352, significant=6) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) - - assert result.topo_complex == 9 - assert result.wetland_frac == 41 - - np.testing.assert_equal( - result.porosity_gldas, np.nan) - np.testing.assert_approx_equal( - result.porosity_hwsd, 0.49000001, significant=5) - - -class Test_H111Ts(unittest.TestCase): - - def setUp(self): - - path = os.path.dirname(__file__) + data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) - cdr_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'h111') - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') + assert data.attrs['topo_complex'] == 9 + assert data.attrs['wetland_frac'] == 41 - self.ascat_reader = H_SAF.H111Ts(cdr_path, grid_path, - static_layer_path=static_layer_path) + np.testing.assert_equal(data.attrs['porosity_gldas'], np.nan) + np.testing.assert_approx_equal(data.attrs['porosity_hwsd'], + 0.49000001, significant=5) - def tearDown(self): - self.ascat_reader.close() - - def test_read(self): + def test_read_h111(self): + """ + Test read H111. + """ + self.h111 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h111'), self.grid_path, + static_layer_path=self.static_layer_path) - gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi + data = self.h111.read(self.gpi, absolute_sm=True) + assert data.attrs['gpi'] == self.gpi - np.testing.assert_approx_equal(result.longitude, 19.03533, + np.testing.assert_approx_equal(data.attrs['lon'], 19.03533, significant=4) - np.testing.assert_approx_equal(result.latitude, 70.05438, + np.testing.assert_approx_equal(data.attrs['lat'], 70.05438, significant=4) - assert len(result.data) == 13715 - assert result.data.iloc[15].name.to_pydatetime() == \ - datetime(2007, 1, 7, 10, 49, 9, 379200) - assert result.data.iloc[15]['sm'] == 28 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 5 - assert result.data.iloc[15]['frozen_prob'] == 0 - assert result.data.iloc[15]['snow_prob'] == 127 - assert result.data.iloc[15]['dir'] == 1 - assert result.data.iloc[15]['proc_flag'] == 0 - assert result.data.iloc[15]['corr_flag'] == 4 - assert result.data.iloc[15]['sat_id'] == 3 - - np.testing.assert_equal( - result.data.iloc[15]['abs_sm_gldas'], np.nan) + assert len(data) == 13715 + assert data.iloc[15].name.to_pydatetime() == datetime( + 2007, 1, 7, 10, 49, 9, 379200) + assert data.iloc[15]['sm'] == 28 + assert data.iloc[15]['ssf'] == 1 + assert data.iloc[15]['sm_noise'] == 5 + assert data.iloc[15]['frozen_prob'] == 0 + assert data.iloc[15]['snow_prob'] == 127 + assert data.iloc[15]['dir'] == 1 + assert data.iloc[15]['proc_flag'] == 0 + assert data.iloc[15]['corr_flag'] == 4 + assert data.iloc[15]['sat_id'] == 3 + + np.testing.assert_equal(data.iloc[15]['abs_sm_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], np.nan) + data.iloc[15]['abs_sm_noise_gldas'], np.nan) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.1372, significant=6) + data.iloc[15]['abs_sm_hwsd'], 0.1372, significant=6) np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) + data.iloc[15]['abs_sm_noise_hwsd'], 0.0245, significant=6) - assert result.topo_complex == 9 - assert result.wetland_frac == 41 + assert data.attrs['topo_complex'] == 9 + assert data.attrs['wetland_frac'] == 41 - np.testing.assert_equal( - result.porosity_gldas, np.nan) - np.testing.assert_approx_equal( - result.porosity_hwsd, 0.49000001, significant=5) + np.testing.assert_equal(data.attrs['porosity_gldas'], np.nan) + np.testing.assert_approx_equal(data.attrs['porosity_hwsd'], + 0.49000001, significant=5) def test_read_2points_cell_switch(self): """ @@ -699,25 +476,17 @@ def test_read_2points_cell_switch(self): This did not work in the past when the static layer class was closed too soon. """ + self.h111 = AscatSsmDataRecord( + os.path.join(self.cdr_path, 'h111'), self.grid_path, + static_layer_path=self.static_layer_path) gpi = 3066159 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi - gpi = 2577735 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi - + data = self.h111.read(gpi, absolute_sm=True) + assert data.attrs['gpi'] == gpi -def test_hsaf_ts_class_init(): - """ - Test for initialization of the classes that change nothing but the setup code. - """ - - path = os.path.dirname(__file__) - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - H_SAF.H112Ts('Test', grid_path) - H_SAF.H113Ts('Test', grid_path) - H_SAF.H114Ts('Test', grid_path) + gpi = 2577735 + data = self.h111.read(gpi, absolute_sm=True) + assert data.attrs['gpi'] == gpi if __name__ == "__main__": diff --git a/tests/test_level1.py b/tests/test_level1.py index ce72852..8fbbf62 100644 --- a/tests/test_level1.py +++ b/tests/test_level1.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -26,139 +26,130 @@ # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -Tests for level 1 reader. +Test ASCAT Level 1 reader. """ -import numpy as np -import numpy.testing as nptest -import unittest + import os import sys import pytest +import unittest from datetime import datetime -import ascat.level1 as level1 +import numpy as np +import numpy.testing as nptest -float32_nan = np.finfo(np.float32).min +from ascat.eumetsat.level1 import AscatL1bFile +from ascat.eumetsat.level1 import AscatL1bNcFileList +from ascat.eumetsat.level1 import AscatL1bEpsFileList +from ascat.eumetsat.level1 import AscatL1bBufrFileList +from ascat.eumetsat.level1 import AscatL1bHdf5FileList + +float32_nan = -999999. @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL1Image(unittest.TestCase): +class Test_AscatL1bFile(unittest.TestCase): def setUp(self): data_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', 'ASCAT_generic_reader_data') - name_b = os.path.join(data_path, 'bufr', - 'M02-ASCA-ASCSZR1B0200-NA-9.1-20100609013900.000000000Z-20130824233100-1280350.bfr') - name_e = os.path.join(data_path, 'eps_nat', - 'ASCA_SZR_1B_M02_20100609013900Z_20100609032058Z_R_O_20130824233100Z.nat') - name_n = os.path.join(data_path, 'nc', - 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20100609013900_18872_eps_o_125_l1.nc') - - name_e11 = os.path.join(data_path, 'eps_nat', - 'ASCA_SZR_1B_M02_20071212071500Z_20071212085659Z_R_O_20081225063118Z.nat') - name_e_szf = os.path.join(data_path, 'eps_nat', - 'ASCA_SZF_1B_M01_20180611041800Z_20180611055959Z_N_O_20180611050637Z.nat') - name_h = os.path.join(data_path, 'hdf5', - 'ASCA_SZF_1B_M01_20180611041800Z_20180611055959Z_N_O_20180611050637Z.h5') - - self.image_bufr = level1.AscatL1Image(name_b) - self.image_eps = level1.AscatL1Image(name_e) - self.image_nc = level1.AscatL1Image(name_n) - - self.image_eps_fmv11 = level1.AscatL1Image(name_e11) - - self.image_e_szf = level1.AscatL1Image(name_e_szf) - self.image_h5_szf = level1.AscatL1Image(name_h) - - def tearDown(self): - self.image_nc = None - self.image_bufr = None - self.image_eps = None - self.image_eps_fmv11 = None - self.image_eps_szf = None - self.image_h5_szf = None - - def test_image_reading_szx_all_formats(self): - self.reader_bufr = self.image_bufr.read() - self.reader_eps = self.image_eps.read() - self.reader_nc = self.image_nc.read() - - nptest.assert_allclose(self.reader_bufr.lat, self.reader_eps.lat, - atol=1e-4) - nptest.assert_allclose(self.reader_eps.lat, self.reader_nc.lat, - atol=1e-4) - nptest.assert_allclose(self.reader_nc.lat, self.reader_bufr.lat, - atol=1e-4) - - nptest.assert_allclose(self.reader_bufr.lon, self.reader_eps.lon, - atol=1e-4) - nptest.assert_allclose(self.reader_eps.lon, self.reader_nc.lon, - atol=1e-4) - nptest.assert_allclose(self.reader_nc.lon, self.reader_bufr.lon, - atol=1e-4) - - matching = ['jd', 'sat_id', 'abs_line_nr', 'abs_orbit_nr', 'node_num', - 'line_num', 'as_des_pass', 'swath', 'azif', 'azim', 'azia', - 'incf', 'incm', 'inca', 'sigf', 'sigm', 'siga', 'kpf', - 'kpm', 'kpa', 'kpf_quality', 'kpm_quality', 'kpa_quality', - 'land_flagf', 'land_flagm', 'land_flaga', 'usable_flagf', - 'usable_flagm', 'usable_flaga'] - - # lists with no data fields or different definition - bufr_none = ['abs_line_nr', 'abs_orbit_nr', 'as_des_pass'] - sig = ['sigf', 'sigm', 'siga'] - - # BUFR files contain less accurate data so we only compare to one 0.1 - # accuracy. + name_b = os.path.join( + data_path, 'bufr', + 'M02-ASCA-ASCSZR1B0200-NA-9.1-20100609013900.000000000Z-20130824233100-1280350.bfr') + name_e = os.path.join( + data_path, 'eps_nat', + 'ASCA_SZR_1B_M02_20100609013900Z_20100609032058Z_R_O_20130824233100Z.nat') + name_n = os.path.join( + data_path, 'nc', + 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20100609013900_18872_eps_o_125_l1.nc') + + name_e11 = os.path.join( + data_path, 'eps_nat', + 'ASCA_SZR_1B_M02_20071212071500Z_20071212085659Z_R_O_20081225063118Z.nat') + + name_e_szf = os.path.join( + data_path, 'eps_nat', + 'ASCA_SZF_1B_M01_20180611041800Z_20180611055959Z_N_O_20180611050637Z.nat') + + name_h = os.path.join( + data_path, 'hdf5', + 'ASCA_SZF_1B_M01_20180611041800Z_20180611055959Z_N_O_20180611050637Z.h5') + + self.bufr = AscatL1bFile(name_b) + self.nc = AscatL1bFile(name_n) + + self.eps = AscatL1bFile(name_e) + self.eps_fmv11 = AscatL1bFile(name_e11) + + self.eps_szf = AscatL1bFile(name_e_szf) + self.h5_szf = AscatL1bFile(name_h) + + def test_read_szx(self): + """ + Test SZX data in all data formats (BUFR, EPS Native, NetCDF). + """ + self.bufr_ds = self.bufr.read() + self.eps_ds = self.eps.read() + self.nc_ds = self.nc.read() + + for f in ['lat', 'lon']: + nptest.assert_allclose(self.bufr_ds[f], self.eps_ds[f], atol=1e-2) + nptest.assert_allclose(self.eps_ds[f], self.nc_ds[f], atol=1e-2) + nptest.assert_allclose(self.nc_ds[f], self.bufr_ds[f], atol=1e-2) + + matching = ['sig', 'inc', 'azi', 'kp', 'kp_quality', + 'swath_indicator', 'f_usable', 'f_land', 'sat_id', + 'line_num', 'node_num'] + + # BUFR contain less accurate data so we only compare 0.1 accuracy. for field in matching: - if field not in bufr_none: - # BUFR filters sigma values below -50 dB so for comparison we - # have to mask those values in nc and eps - if field in sig: - sig_mask = (self.reader_eps.data[field] < -50) - self.reader_eps.data[field][sig_mask] = float32_nan - self.reader_nc.data[field][sig_mask] = float32_nan - self.reader_bufr.data[field][sig_mask] = float32_nan - - nan_mask = (self.reader_nc.data[field] == float32_nan) - self.reader_eps.data[field][nan_mask] = float32_nan - self.reader_bufr.data[field][nan_mask] = float32_nan - - nptest.assert_allclose(self.reader_bufr.data[field], - self.reader_eps.data[field], atol=0.1) - nptest.assert_allclose(self.reader_nc.data[field], - self.reader_bufr.data[field], atol=0.1) - - nptest.assert_allclose(self.reader_eps.data[field], - self.reader_nc.data[field], atol=0.1) - - def test_image_reading_szf_all_formats(self): - self.reader_eps_szf = self.image_e_szf.read() - self.reader_hdf5_szf = self.image_h5_szf.read() - for szf_img in self.reader_eps_szf: - nptest.assert_allclose(self.reader_eps_szf[szf_img].lat, - self.reader_hdf5_szf[szf_img].lat, - atol=1e-4) - - nptest.assert_allclose(self.reader_eps_szf[szf_img].lon, - self.reader_hdf5_szf[szf_img].lon, - atol=1e-4) - - matching = ['jd', 'sat_id', 'beam_number', 'abs_orbit_nr', - 'as_des_pass', 'azi', 'inc', 'sig', 'land_frac', - 'flagfield_rf1', 'flagfield_rf2', 'flagfield_pl', - 'flagfield_gen1', 'flagfield_gen2', - 'land_flag', 'usable_flag'] + + if field == 'sig': + nan_mask = (self.nc_ds[field] == float32_nan) + self.eps_ds[field][nan_mask] = float32_nan + self.bufr_ds[field][nan_mask] = float32_nan + + valid = ((self.eps_ds[field] > -25)) + + nptest.assert_allclose(self.bufr_ds[field][valid], + self.eps_ds[field][valid], atol=0.1) + else: + nptest.assert_allclose(self.bufr_ds[field], + self.eps_ds[field], atol=0.1) + + nptest.assert_allclose(self.nc_ds[field], + self.bufr_ds[field], atol=0.1) + + nptest.assert_allclose(self.eps_ds[field], + self.nc_ds[field], atol=0.1) + + def test_read_szf(self): + """ + Test read SZF formats. + """ + self.eps_ds = self.eps_szf.read() + self.h5_ds = self.h5_szf.read() + + for antenna in ['lf', 'lm', 'la', 'rf', 'rm', 'ra']: + for coord in ['lon', 'lat']: + nptest.assert_allclose(self.eps_ds[antenna][coord], + self.h5_ds[antenna][coord], atol=1e-4) + + matching = ['sig', 'inc', 'azi', 'sat_id', 'as_des_pass', + 'land_frac', 'f_usable', 'f_land', 'beam_number', + 'swath_indicator'] for field in matching: - nptest.assert_allclose( - self.reader_eps_szf[szf_img].data[field], - self.reader_hdf5_szf[szf_img].data[field], atol=0.1) + nptest.assert_allclose(self.eps_ds[antenna][coord], + self.h5_ds[antenna][coord], atol=0.1) - def test_image_reading_szx_eps(self): - self.reader = self.image_eps.read(file_format='.nat') + def test_szx_eps(self): + """ + Test read SZX EPS. + """ + self.reader = self.eps.read(generic=True) lat_should = np.array( [68.91681, 69.005196, 69.09337, 69.18132, 69.26905, 69.35655, @@ -187,23 +178,26 @@ def test_image_reading_szx_eps(self): 0.0341, 0.0399, 0.0418, 0.0408, 0.0421, 0.0347, 0.0424, 0.0451, 0.0523]) - jd_should = np.array( - [2455356.56875, 2455356.56875, 2455356.56875, - 2455356.56875, 2455356.56875, 2455356.56875, - 2455356.56875, 2455356.56877169, 2455356.56877169, - 2455356.56877169]) - - nptest.assert_allclose(self.reader.lat[:25], lat_should, atol=1e-5) - nptest.assert_allclose(self.reader.lon[:25], lon_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['sigf'][:25], - sig_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['kpf'][:25], - kp_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['jd'][75:85], - jd_should, atol=1e-5) - - def test_image_reading_szx_eps_fmv11(self): - self.reader = self.image_eps_fmv11.read() + t_should = np.array( + ['2010-06-09T01:39:00.000', '2010-06-09T01:39:00.000', + '2010-06-09T01:39:00.000', '2010-06-09T01:39:00.000', + '2010-06-09T01:39:00.000', '2010-06-09T01:39:00.000', + '2010-06-09T01:39:00.000', '2010-06-09T01:39:01.874', + '2010-06-09T01:39:01.874', '2010-06-09T01:39:01.874'], + dtype='datetime64[ms]') + + nptest.assert_allclose(self.reader['lat'][:25], lat_should, atol=1e-5) + nptest.assert_allclose(self.reader['lon'][:25], lon_should, atol=1e-5) + nptest.assert_allclose( + self.reader['sig'][:25, 0], sig_should, atol=1e-5) + nptest.assert_allclose(self.reader['kp'][:25, 0], kp_should, atol=1e-5) + nptest.assert_equal(self.reader['time'][75:85], t_should) + + def test_szx_eps_fmv11(self): + """ + Test read SZX EPS format version 11. + """ + self.reader = self.eps_fmv11.read() lat_should = np.array( [61.849445, 61.916786, 61.983864, 62.050674, 62.11722, 62.183495, @@ -232,23 +226,26 @@ def test_image_reading_szx_eps_fmv11(self): 0.035, 0.0325, 0.0288, 0.0292, 0.0431, 0.0363, 0.0435, 0.0282, 0.0309]) - jd_should = np.array( - [2454446.80208333, 2454446.80208333, 2454446.80208333, - 2454446.80208333, 2454446.80208333, 2454446.80208333, - 2454446.80208333, 2454446.80210505, 2454446.80210505, - 2454446.80210505]) - - nptest.assert_allclose(self.reader.lat[:25], lat_should, atol=1e-5) - nptest.assert_allclose(self.reader.lon[:25], lon_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['sigf'][:25], - sig_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['kpf'][:25], - kp_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['jd'][75:85], - jd_should, atol=1e-5) - - def test_image_reading_szf_eps(self): - self.reader = self.image_e_szf.read() + t_should = np.array( + ['2007-12-12T07:15:00.000', '2007-12-12T07:15:00.000', + '2007-12-12T07:15:00.000', '2007-12-12T07:15:00.000', + '2007-12-12T07:15:00.000', '2007-12-12T07:15:00.000', + '2007-12-12T07:15:00.000', '2007-12-12T07:15:01.876', + '2007-12-12T07:15:01.876', '2007-12-12T07:15:01.876'], + dtype='datetime64[ms]') + + nptest.assert_allclose(self.reader['lat'][:25], lat_should, atol=1e-5) + nptest.assert_allclose(self.reader['lon'][:25], lon_should, atol=1e-5) + nptest.assert_allclose( + self.reader['sig'][:25, 0], sig_should, atol=1e-5) + nptest.assert_allclose(self.reader['kp'][:25, 0], kp_should, atol=1e-5) + nptest.assert_equal(self.reader['time'][75:85], t_should) + + def test_szf_eps(self): + """ + Test read SZF EPS format. + """ + self.reader = self.eps_szf.read() lat_should = np.array( [64.45502, 64.42318, 64.39127, 64.35929, 64.32724, 64.29512, @@ -271,167 +268,165 @@ def test_image_reading_szf_eps(self): -7.59996, -8.976448, -9.36595, -10.800382, -8.289896, -9.127579, -9.410345, -7.238986, -8.335969, -7.897769]) - jd_should = np.array( - [2458280.67917396, 2458280.67917396, 2458280.67918378, - 2458280.67918378, 2458280.67918378, 2458280.67918378, - 2458280.67918378, 2458280.67918378, 2458280.67918378, - 2458280.67918378]) + t_should = np.array( + ['2018-06-11T04:18:00.630', '2018-06-11T04:18:00.630', + '2018-06-11T04:18:01.479', '2018-06-11T04:18:01.479', + '2018-06-11T04:18:01.479', '2018-06-11T04:18:01.479', + '2018-06-11T04:18:01.479', '2018-06-11T04:18:01.479', + '2018-06-11T04:18:01.479', '2018-06-11T04:18:01.479'], + dtype='datetime64[ms]') - nptest.assert_allclose(self.reader['img1'].lat[:25], + nptest.assert_allclose(self.reader['lf']['lat'][:25], lat_should, atol=1e-5) - nptest.assert_allclose(self.reader['img1'].lon[:25], + nptest.assert_allclose(self.reader['lf']['lon'][:25], lon_should, atol=1e-5) - nptest.assert_allclose(self.reader['img1'].data['sig'][:25], + nptest.assert_allclose(self.reader['lf']['sig'][:25], sig_should, atol=1e-5) - nptest.assert_allclose(self.reader['img1'].data['jd'][190:200], - jd_should, atol=1e-5) + nptest.assert_equal(self.reader['lf']['time'][190:200], t_should) @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL1Bufr(unittest.TestCase): - - def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'bufr') - - self.image_bufr = level1.AscatL1Bufr(self.data_path, eo_portal=True) - - def tearDown(self): - self.image_bufr = None - - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_bufr.read( - datetime(2010, 6, 9, 1, 39)) - - assert lon.shape == (267648,) - assert lat.shape == (267648,) - - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'M02-ASCA-ASCSZR1B0200-NA-9.1-20100609013900.000000000Z-20130824233100-1280350.bfr') - orbit_start = self.image_bufr._get_orbit_start_date(filename) - orbit_start_should = datetime(2010, 6, 9, 1, 39) - - assert orbit_start == orbit_start_should - - def test_tstamp_for_daterange(self): - tstamps = self.image_bufr.tstamps_for_daterange(datetime(2010, 6, 8), - datetime(2010, 6, 10)) - tstamps_should = [datetime(2010, 6, 9, 1, 39)] - - assert tstamps == tstamps_should - +class Test_AscatL1bFileList(unittest.TestCase): -class Test_AscatL1Eps(unittest.TestCase): + """ + Test read AscatL1bFileList in various formats. + """ def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'eps_nat') - - self.image_eps = level1.AscatL1Eps(self.data_path, eo_portal=True) - - def tearDown(self): - self.image_eps = None - - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_eps.read( - datetime(2010, 6, 9, 1, 39)) - - assert lon.shape == (267648,) - assert lat.shape == (267648,) - - def test_image_reading_szf(self): - szf_dict = self.image_eps.read( - datetime(2018, 6, 11, 4, 18)) - - szf_dict['img1'].lon - assert szf_dict['img1'].lon.shape == (1383552,) - assert szf_dict['img1'].lat.shape == (1383552,) - - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'ASCA_SZR_1B_M02_20100609013900Z_20100609032058Z_R_O_20130824233100Z.nat') - orbit_start = self.image_eps._get_orbit_start_date(filename) - orbit_start_should = datetime(2010, 6, 9, 1, 39) - - assert orbit_start == orbit_start_should - - def test_tstamp_for_daterange(self): - tstamps = self.image_eps.tstamps_for_daterange( - datetime(2010, 6, 8), datetime(2010, 6, 10)) - tstamps_should = [datetime(2010, 6, 9, 1, 39)] - - assert tstamps == tstamps_should - - -class Test_AscatL1Nc(unittest.TestCase): - - def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'nc') - - self.image_nc = level1.AscatL1Nc(self.data_path, eo_portal=True) - - def tearDown(self): - self.image_nc = None - - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_nc.read( - datetime(2010, 6, 9, 1, 39)) - - assert lon.shape == (267648,) - assert lat.shape == (267648,) - - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20100609013900_18872_eps_o_125_l1.nc') - orbit_start = self.image_nc._get_orbit_start_date(filename) - orbit_start_should = datetime(2010, 6, 9, 1, 39) - - assert orbit_start == orbit_start_should - - def test_tstamp_for_daterange(self): - tstamps = self.image_nc.tstamps_for_daterange(datetime(2010, 6, 8), - datetime(2010, 6, 10)) - tstamps_should = [datetime(2010, 6, 9, 1, 39)] - - assert tstamps == tstamps_should - - -class Test_AscatL1Hdf5(unittest.TestCase): - - def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'hdf5') + """ + Setup test data. + """ + root_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', + 'eumetsat', 'ASCAT_generic_reader_data') + + self.bufr_szr = AscatL1bBufrFileList( + os.path.join(root_path, 'bufr'), sat='A') + self.nc_szr = AscatL1bNcFileList(os.path.join(root_path, 'nc')) + self.eps_szr = AscatL1bEpsFileList(os.path.join(root_path, 'eps_nat')) + + self.eps_szf = AscatL1bEpsFileList( + os.path.join(root_path, 'eps_nat'), sat='B', res='SZF') + self.hdf5_szf = AscatL1bHdf5FileList( + os.path.join(root_path, 'hdf5'), sat='B') + + def test_szr_read_date(self): + """ + Test read date for SZR formats. + """ + dt = datetime(2010, 6, 9, 1, 39, 0) + + bufr_data = self.bufr_szr.read(dt) + nc_data = self.nc_szr.read(dt) + eps_data = self.eps_szr.read(dt) + + for f in ['lat', 'lon']: + nptest.assert_allclose(bufr_data[f], eps_data[f], atol=1e-2) + nptest.assert_allclose(eps_data[f], nc_data[f], atol=1e-2) + nptest.assert_allclose(nc_data[f], bufr_data[f], atol=1e-2) + + matching = ['sig', 'inc', 'azi', 'kp', 'kp_quality', + 'swath_indicator', 'f_usable', 'f_land', 'sat_id', + 'line_num', 'node_num'] + + # BUFR contain less accurate data so we only compare 0.1 accuracy. + for field in matching: + if field == 'sig': + nan_mask = (nc_data[field] == float32_nan) + eps_data[field][nan_mask] = float32_nan + bufr_data[field][nan_mask] = float32_nan + valid = ((eps_data[field] > -25)) + + nptest.assert_allclose(bufr_data[field][valid], + eps_data[field][valid], atol=0.1) + else: + nptest.assert_allclose(bufr_data[field], + eps_data[field], atol=0.1) + + nptest.assert_allclose(nc_data[field], bufr_data[field], atol=0.1) + nptest.assert_allclose(eps_data[field], nc_data[field], atol=0.1) + + def test_szr_read_period(self): + """ + Test read period for SZR formats. + """ + dt_start = datetime(2010, 6, 9, 1, 39, 0) + dt_end = datetime(2010, 6, 9, 2, 0, 0) + + bufr_data = self.bufr_szr.read_period(dt_start, dt_end) + nc_data = self.nc_szr.read_period(dt_start, dt_end) + eps_data = self.eps_szr.read_period(dt_start, dt_end) + + for f in ['lat', 'lon']: + nptest.assert_allclose(bufr_data[f], eps_data[f], atol=1e-2) + nptest.assert_allclose(eps_data[f], nc_data[f], atol=1e-2) + nptest.assert_allclose(nc_data[f], bufr_data[f], atol=1e-2) + + matching = ['sig', 'inc', 'azi', 'kp', 'kp_quality', + 'swath_indicator', 'f_usable', 'f_land', 'sat_id', + 'line_num', 'node_num'] + + # BUFR contain less accurate data so we only compare 0.1 accuracy. + for field in matching: + if field == 'sig': + nan_mask = (nc_data[field] == float32_nan) + eps_data[field][nan_mask] = float32_nan + bufr_data[field][nan_mask] = float32_nan + valid = ((eps_data[field] > -25)) + + nptest.assert_allclose(bufr_data[field][valid], + eps_data[field][valid], atol=0.1) + else: + nptest.assert_allclose(bufr_data[field], + eps_data[field], atol=0.1) + + nptest.assert_allclose(nc_data[field], bufr_data[field], atol=0.1) + nptest.assert_allclose(eps_data[field], nc_data[field], atol=0.1) + + def test_szf_read_date(self): + """ + Test read date for SZF formats. + """ + dt = datetime(2018, 6, 11, 4, 18, 0) + + eps_data = self.eps_szf.read(dt) + hdf5_data = self.hdf5_szf.read(dt) + + for antenna in ['lf', 'lm', 'la', 'rf', 'rm', 'ra']: + for coord in ['lon', 'lat']: + nptest.assert_allclose(eps_data[antenna][coord], + hdf5_data[antenna][coord], atol=1e-4) + + matching = ['sig', 'inc', 'azi', 'sat_id', 'as_des_pass', + 'land_frac', 'f_usable', 'f_land', 'beam_number', + 'swath_indicator'] - self.image_h5 = level1.AscatL1Hdf5(self.data_path, eo_portal=True) + for field in matching: + nptest.assert_allclose(eps_data[antenna][coord], + hdf5_data[antenna][coord], atol=0.1) - def tearDown(self): - self.image_h5 = None + def test_szf_read_period(self): + """ + Test read period for SZF formats. + """ + dt_start = datetime(2018, 6, 11, 4, 18, 0) + dt_end = datetime(2018, 6, 11, 4, 19, 0) - def test_image_reading(self): - szf_dict = self.image_h5.read( - datetime(2018, 6, 11, 4, 18)) + eps_data = self.eps_szf.read_period(dt_start, dt_end) + hdf5_data = self.hdf5_szf.read_period(dt_start, dt_end) - szf_dict['img1'].lon - assert szf_dict['img1'].lon.shape == (1383552,) - assert szf_dict['img1'].lat.shape == (1383552,) + for antenna in ['lf', 'lm', 'la', 'rf', 'rm', 'ra']: + for coord in ['lon', 'lat']: + nptest.assert_allclose(eps_data[antenna][coord], + hdf5_data[antenna][coord], atol=1e-4) - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'ASCA_SZF_1B_M01_20180611041800Z_20180611055959Z_N_O_20180611050637Z.h5') - orbit_start = self.image_h5._get_orbit_start_date(filename) - orbit_start_should = datetime(2018, 6, 11, 4, 18) + matching = ['sig', 'inc', 'azi', 'sat_id', 'as_des_pass', + 'land_frac', 'f_usable', 'f_land', 'beam_number', + 'swath_indicator'] - assert orbit_start == orbit_start_should + for field in matching: + nptest.assert_allclose(eps_data[antenna][coord], + hdf5_data[antenna][coord], atol=0.1) - def test_tstamp_for_daterange(self): - tstamps = self.image_h5.tstamps_for_daterange(datetime(2018, 6, 10), - datetime(2018, 6, 12)) - tstamps_should = [datetime(2018, 6, 11, 4, 18)] - assert tstamps == tstamps_should +if __name__ == '__main__': + unittest.main() diff --git a/tests/test_level2.py b/tests/test_level2.py index e005aff..06d4934 100644 --- a/tests/test_level2.py +++ b/tests/test_level2.py @@ -1,4 +1,4 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation +# Copyright (c) 2021, TU Wien, Department of Geodesy and Geoinformation # All rights reserved. # Redistribution and use in source and binary forms, with or without @@ -26,108 +26,53 @@ # ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -Tests for level 2 readers. +Test ASCAT Level 2 reader. """ -from datetime import datetime -import numpy as np -import numpy.testing as nptest import os +import sys import pytest import unittest -import sys +from datetime import datetime -from ascat.read_native.bufr import AscatL2SsmBufr -from ascat.read_native.bufr import AscatL2SsmBufrChunked -from ascat.read_native.bufr import AscatL2SsmBufrFile -from ascat.read_native.nc import AscatL2SsmNcFile -import ascat.level2 as level2 +import numpy as np +import numpy.testing as nptest + +from ascat.read_native.bufr import AscatL2BufrFile +from ascat.read_native.nc import AscatL2NcFile +from ascat.eumetsat.level2 import AscatL2File +from ascat.eumetsat.level2 import AscatL2NcFileList +from ascat.eumetsat.level2 import AscatL2BufrFileList +from ascat.eumetsat.level2 import AscatL2EpsFileList -float32_nan = np.finfo(np.float32).min +eps_float_nan = -2147483648. +bufr_float_nan = 1.7e+38 +uint8_nan = np.iinfo(np.uint8).max +uint16_nan = np.iinfo(np.uint16).max +float32_nan = -999999. @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL2SsmBufr_ioclass_kws(unittest.TestCase): +class Test_AscatL2BufrFile(unittest.TestCase): def setUp(self): - data_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', - 'hsaf', 'h07') - self.reader = AscatL2SsmBufr(data_path, - msg_name_lookup={65: 'ssm', - 74: 'ssm mean'}) - - def tearDown(self): - self.reader = None - - def test_offset_getting(self): """ - test getting the image offsets for a known day - 2010-05-01 + Setup test files. """ - timestamps = self.reader.tstamps_for_daterange( - datetime(2010, 5, 1), datetime(2010, 5, 1, 12)) - timestamps_should = [datetime(2010, 5, 1, 8, 33, 1)] - assert sorted(timestamps) == sorted(timestamps_should) - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - datetime(2010, 5, 1, 8, 33, 1)) - - ssm_should = np.array([51.2, 65.6, 46.2, 56.9, 61.4, 61.5, 58.1, 47.1, - 72.7, 13.8, 60.9, 52.1, 78.5, 57.8, 56.2, 79.8, - 67.7, 53.8, 86.5, 29.4, 50.6, 88.8, 56.9, 68.9, - 52.4, 64.4, 81.5, 50.5, 84., 79.6, 47.4, 79.5, - 46.9, 60.7, 81.3, 52.9, 84.5, 25.5, 79.2, 93.3, - 52.6, 93.9, 74.4, 91.4, 76.2, 92.5, 80., 88.3, - 79.1, 97.2, 56.8]) - - lats_should = np.array([70.21162, 69.32506, 69.77325, 68.98149, - 69.12295, 65.20364, 67.89625, 67.79844, - 67.69112, 67.57446, 67.44865, 67.23221, - 66.97207, 66.7103, 66.34695, 65.90996, - 62.72462, 61.95761, 61.52935, 61.09884, - 60.54359, 65.60223, 65.33588, 65.03098, - 64.58972, 61.46131, 60.62553, 59.52057, - 64.27395, 63.80293, 60.6569, 59.72684, - 58.74838, 63.42774]) - - ssm_mean_should = np.array([0.342, 0.397, 0.402, 0.365, 0.349, - 0.354, 0.37, 0.36, 0.445, 0.211, - 0.394, 0.354, 0.501, 0.361, 0.366, - 0.45, 0.545, 0.329, 0.506, 0.229, - 0.404, 0.591, 0.348, 0.433, 0.29, - 0.508, 0.643, 0.343, 0.519, 0.61, - 0.414, 0.594, 0.399, 0.512, 0.681, - 0.457, 0.622, 0.396, 0.572, 0.7, - 0.302, 0.722, 0.493, 0.747, 0.521, - 0.72, 0.578, 0.718, 0.536, 0.704, - 0.466]) * 100 - - nptest.assert_allclose(lats[25:-1:30], lats_should, atol=1e-5) - nptest.assert_allclose(data['ssm'][ - 15:-1:20], ssm_should, atol=0.01) - nptest.assert_allclose(data['ssm mean'][15:-1:20], - ssm_mean_should, - atol=0.01) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL2SsmBufrFile(unittest.TestCase): - - def setUp(self): data_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', 'ASCAT_L2_SM_125', 'bufr', 'Metop_B') + fname = os.path.join( - data_path, - 'M01-ASCA-ASCSMR02-NA-5.0-20170220050900.000000000Z-20170220055833-1207110.bfr') - self.reader = AscatL2SsmBufrFile(fname) + data_path, 'M01-ASCA-ASCSMR02-NA-5.0-20170220050900.000000000Z-20170220055833-1207110.bfr') - def tearDown(self): - self.reader = None + self.reader = AscatL2BufrFile(fname) - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read() + def test_read(self): + """ + Test read. + """ + data = self.reader.read() ssm_should = np.array( [29.2, 30.2, 35.7, 38.6, 37.5, 37.6, 40.5, 44.5, 40.7, @@ -146,59 +91,32 @@ def test_image_reading(self): 27.6, 25.8, 25.4, 25.5, 25.3, 24.4, 23.4, 22.3, 21.3, 20.4, 20.4, 19.9, 19.7, 20.3, 21.5, 22.9]) - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][ - :25], ssm_should, atol=1e-5) + nptest.assert_allclose(data['lat'][:25], lats_should, atol=1e-5) + nptest.assert_allclose(data['Surface Soil Moisture (Ms)'][:25], + ssm_should, atol=1e-5) nptest.assert_allclose(data['Mean Surface Soil Moisture'][:25], - ssm_mean_should, - atol=1e-5) - - def test_image_reading_masked(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - ssm_masked=True) - - ssm_should = np.array( - [15.6, 10.8, 15.3, 15.9, 19.8, 27., 27.8, 26.8, 28.6, - 35.6, 36., 32.3, 27.6, 31.2, 36.8, 13.4, 18.7, 23.1, - 24.5, 22.1, 17.1, 17.9, 17.8, 21.1, 23.]) - - lats_should = np.array( - [54.27036, 54.3167, 54.36279, 54.40862, 54.45419, 54.49951, - 54.54456, 54.58936, 54.6339, 54.67818, 54.72219, 54.76594, - 54.80943, 54.85265, 54.89561, 56.95692, 56.98178, 57.00631, - 57.03053, 57.05442, 57.07799, 57.10123, 57.12415, 57.14675, - 57.16902]) - - ssm_mean_should = np.array( - [24.4, 22.2, 21., 19.6, 18.7, 19.1, 19.1, 19.9, 19.9, - 20.1, 20.9, 21., 19.6, 17.3, 16.9, 25.6, 25.6, 24.9, - 23.6, 22.9, 22.4, 23.2, 24.1, 24.5, 26.1]) + ssm_mean_should, atol=1e-5) - nptest.assert_allclose(lats[10000:10025], lats_should, atol=1e-5) - nptest.assert_allclose(data['Surface Soil Moisture (Ms)'] - [10000:10025], ssm_should, - atol=1e-5) - nptest.assert_allclose(data['Mean Surface Soil Moisture'] - [10000:10025], ssm_mean_should, - atol=1e-5) - -class Test_AscatL2SsmNcFile(unittest.TestCase): +class Test_AscatL2NcFile(unittest.TestCase): def setUp(self): + """ + Setup test files. + """ data_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', 'ASCAT_L2_SM_125', 'nc', 'Metop_A') fname = os.path.join( data_path, 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20170220041500_53652_eps_o_125_ssm_l2.nc') - self.reader = AscatL2SsmNcFile(fname) + self.reader = AscatL2NcFile(fname) - def tearDown(self): - self.reader = None - - def test_image_reading(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read() + def test_read(self): + """ + Test read. + """ + data = self.reader.read() ssm_should = np.array([2.96000004, 0., 0., 0., 0., 0., 0., 0., 0., 1.82999992, 3.32999992, 4.78999996, 4.31999969, @@ -223,99 +141,53 @@ def test_image_reading(self): 30.97999954, 31.27999878, 31.8599987, 32.05999756]) - nptest.assert_allclose(lats[:25], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][ - :25], ssm_should, atol=1e-5) + nptest.assert_allclose(data['latitude'][:25], lats_should, atol=1e-5) + nptest.assert_allclose(data['soil_moisture'][:25], + ssm_should, atol=1e-5) nptest.assert_allclose(data['mean_soil_moisture'][:25], - ssm_mean_should, - atol=1e-5) - - def test_image_reading_masked(self): - data, meta, timestamp, lons, lats, time_var = self.reader.read( - ssm_masked=True) - - ssm_should = np.array( - [33.39999771118164, 27.06999969482422, - 20.649999618530273, 18.28999900817871, - 24.229999542236328, 24.939998626708984, - 23.639999389648438, 20.3799991607666, - 14.15999984741211, 10.059999465942383, - 9.539999961853027, 9.019999504089355, - 9.420000076293945, 12.279999732971191, - 21.529998779296875, 33.880001068115234, - 39.57999801635742, 35.34000015258789, - 38.88999938964844, 44.459999084472656, - 46.66999816894531, 40.12999725341797, - 38.39999771118164, 43.959999084472656, - 33.43000030517578]) - - lats_should = np.array( - [65.11197384, 65.17437784, 65.23645384, 65.29819884, 65.35961083, - 65.42068783, 65.48142683, 65.54182483, 65.60187983, 65.66158983, - 65.72095083, 65.77996183, 65.83861883, 68.62952883, 68.66132883, - 68.69261383, 68.72337983, 68.75362483, 68.78334683, 68.81254383, - 68.84121383, 68.86935383, 68.89696283, 68.92403783, 68.95057683]) - - ssm_mean_should = np.array([26.85999870300293, 25.90999984741211, - 25.670000076293945, 25.81999969482422, - 24.65999984741211, 22.6299991607666, - 20.389999389648438, 18.94999885559082, - 17.68000030517578, 16.28999900817871, - 15.130000114440918, 14.739999771118164, - 15.5, - 26.51999855041504, 31.529998779296875, - 36.09000015258789, 40.36000061035156, - 42.61000061035156, 45.529998779296875, - 47.939998626708984, 47.45000076293945, - 44.689998626708984, 41.12999725341797, - 37.59000015258789, 33.09000015258789]) - - nptest.assert_allclose(lats[50000:50025], lats_should, atol=1e-5) - nptest.assert_allclose(data['soil_moisture'][50000:50025], ssm_should, - atol=1e-5) - nptest.assert_allclose(data['mean_soil_moisture'][50000:50025], - ssm_mean_should, - atol=1e-5) + ssm_mean_should, atol=1e-5) @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL2SsmNcFile_vsAscatL2SsmBufrFile(unittest.TestCase): +class Test_AscatL2NcFile_AscatL2BufrFile(unittest.TestCase): def setUp(self): + """ + Setup test files. + """ data_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', 'ASCAT_L2_SM_125') fname_nc = os.path.join( data_path, 'nc', 'Metop_A', 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPA+ASCAT_C_EUMP_20170220041500_53652_eps_o_125_ssm_l2.nc') - self.reader_nc = AscatL2SsmNcFile(fname_nc) + self.reader_nc = AscatL2NcFile(fname_nc) fname_bufr = os.path.join( data_path, 'bufr', 'Metop_A', 'M02-ASCA-ASCSMR02-NA-5.0-20170220041500.000000000Z-20170220055656-1207110.bfr') - self.reader_bufr = AscatL2SsmBufrFile(fname_bufr) - - def tearDown(self): - self.reader_nc = None - self.reader_bufr = None + self.reader_bufr = AscatL2BufrFile(fname_bufr) - def test_image_reading(self): - data_nc, meta, timestamp, lons_nc, lats_nc, time_var_nc = self.reader_nc.read() - data_bufr, meta, timestamp, lons_bufr, lats_bufr, time_var_bufr = self.reader_bufr.read() + def test_read(self): + """ + Test read. + """ + data_nc = self.reader_nc.read() + data_bufr = self.reader_bufr.read() - nptest.assert_allclose(lats_nc, lats_bufr, atol=1e-4) + nptest.assert_allclose(data_nc['latitude'], data_bufr['lat'], + atol=1e-4) nc_bufr_matching = { 'slope40': 'Slope At 40 Deg Incidence Angle', 'sigma40_error': 'Estimated Error In Sigma0 At 40 Deg Incidence Angle', 'utc_line_nodes': None, - 'jd': 'jd', 'wet_backscatter': 'Wet Backscatter', 'swath_indicator': None, 'frozen_soil_probability': 'Frozen Land Surface Fraction', 'wetland_flag': 'Inundation And Wetland Fraction', # The processing flag definition between BUFR and netCDF is slightly different - # 'proc_flag1': 'Soil Moisture Processing Flag', + # 'proc_flag1': 'Soil Moisture Processing Flag', 'proc_flag2': None, 'abs_line_number': None, 'sat_track_azi': None, @@ -333,142 +205,100 @@ def test_image_reading(self): 'topography_flag': 'Topographic Complexity', 'snow_cover_probability': 'Snow Cover'} - # 'Direction Of Motion Of Moving Observing Platform'] - # BUFR files contain less accurate data so we only compare to one 0.1 - # accuracy. + # BUFR contains less accurate data so we only compare to 0.1 for nc_name in nc_bufr_matching: + bufr_name = nc_bufr_matching[nc_name] if bufr_name is None: continue - # flags and probabilities do not have the same NaN value so we mask - # the invalid values for comparison - if nc_name in ['snow_cover_probability', - 'rainfall_flag', - 'topography_flag', - 'frozen_soil_probability', - 'wetland_flag', - 'snow_cover_probability']: - valid = np.where(data_nc[nc_name] != 255) - data_nc[nc_name] = data_nc[nc_name][valid] - data_bufr[bufr_name] = data_bufr[bufr_name][valid] + if nc_name in ['mean_soil_moisture']: + valid = ((data_nc[nc_name] != uint16_nan) & + (data_bufr[bufr_name] != bufr_float_nan)) + elif nc_name in ['snow_cover_probability', 'rainfall_flag', + 'topography_flag', 'frozen_soil_probability', + 'wetland_flag', 'snow_cover_probability']: + valid = ((data_nc[nc_name] != uint8_nan) & + (data_bufr[bufr_name] != bufr_float_nan)) + else: + valid = ((data_nc[nc_name] != eps_float_nan) & + (data_bufr[bufr_name] != bufr_float_nan)) - nptest.assert_allclose(data_nc[nc_name], - data_bufr[bufr_name], atol=0.1) - - -@pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -def test_AscatL2SsmBufrChunked(): - data_path = os.path.join( - os.path.dirname( - __file__), 'ascat_test_data', 'eumetsat', 'ASCAT_L2_SM_125', - 'PDU', 'Metop_B') - day_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOPB+ASCAT_C_EUMP_%Y%m%d*_125_ssm_l2.bin' - file_search_str = 'W_XX-EUMETSAT-Darmstadt,SOUNDING+SATELLITE,METOPB+ASCAT_C_EUMP_{datetime}*_125_ssm_l2.bin' - datetime_format = '%Y%m%d%H%M%S' - filename_datetime_format = (63, 77, '%Y%m%d%H%M%S') - reader = AscatL2SsmBufrChunked(data_path, month_path_str='', - day_search_str=day_search_str, - file_search_str=file_search_str, - datetime_format=datetime_format, - filename_datetime_format=filename_datetime_format) - - intervals = reader.tstamps_for_daterange(datetime(2017, 2, 20, 5), - datetime(2017, 2, 20, 6)) - data = reader.read(intervals[0]) - assert len(data.metadata.keys()) == 3 - assert data.data['jd'].shape == (23616,) - assert data.lon.shape == (23616,) - assert data.lat.shape == (23616,) + nptest.assert_allclose(data_nc[nc_name][valid], + data_bufr[bufr_name][valid], atol=0.1) @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL2Image(unittest.TestCase): +class Test_AscatL2File(unittest.TestCase): def setUp(self): + """ + Setup test files. + """ data_path = os.path.join( os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', 'ASCAT_generic_reader_data') - name_b = os.path.join(data_path, 'bufr', - 'M01-ASCA-ASCSMO02-NA-5.0-20180612035700.000000000Z-20180612044530-1281300.bfr') - name_e = os.path.join(data_path, 'eps_nat', - 'ASCA_SMO_02_M01_20180612035700Z_20180612053856Z_N_O_20180612044530Z.nat') - name_n = os.path.join(data_path, 'nc', - 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPB+ASCAT_C_EUMP_20180612035700_29742_eps_o_250_ssm_l2.nc') - self.image_bufr = level2.AscatL2Image(name_b) - self.image_eps = level2.AscatL2Image(name_e) - self.image_nc = level2.AscatL2Image(name_n) - - def tearDown(self): - self.image_nc = None - self.image_bufr = None - self.image_eps = None - - def test_image_reading_all_formats(self): - self.reader_bufr = self.image_bufr.read() - self.reader_eps = self.image_eps.read() - self.reader_nc = self.image_nc.read() - - nptest.assert_allclose(self.reader_bufr.lat, self.reader_eps.lat, - atol=1e-4) - nptest.assert_allclose(self.reader_eps.lat, self.reader_nc.lat, - atol=1e-4) - nptest.assert_allclose(self.reader_nc.lat, self.reader_bufr.lat, - atol=1e-4) - nptest.assert_allclose(self.reader_bufr.lon, self.reader_eps.lon, - atol=1e-4) - nptest.assert_allclose(self.reader_eps.lon, self.reader_nc.lon, - atol=1e-4) - nptest.assert_allclose(self.reader_nc.lon, self.reader_bufr.lon, - atol=1e-4) + name_b = os.path.join( + data_path, 'bufr', + 'M01-ASCA-ASCSMO02-NA-5.0-20180612035700.000000000Z-20180612044530-1281300.bfr') + name_e = os.path.join( + data_path, 'eps_nat', + 'ASCA_SMO_02_M01_20180612035700Z_20180612053856Z_N_O_20180612044530Z.nat') + name_n = os.path.join( + data_path, 'nc', + 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPB+ASCAT_C_EUMP_20180612035700_29742_eps_o_250_ssm_l2.nc') + + self.bufr = AscatL2File(name_b) + self.eps = AscatL2File(name_e) + self.nc = AscatL2File(name_n) + + def test_read_all_formats(self): + """ + Test read. + """ + bufr_ds = self.bufr.read() + eps_ds = self.eps.read() + nc_ds = self.nc.read() + + for coord in ['lon', 'lat']: + nptest.assert_allclose(bufr_ds[coord], eps_ds[coord], atol=1e-4) + nptest.assert_allclose(eps_ds[coord], nc_ds[coord], atol=1e-4) + nptest.assert_allclose(nc_ds[coord], bufr_ds[coord], atol=1e-4) + + matching = ['sm', 'sm_noise', 'sm_mean', 'sig40', 'sig40_noise', + 'slope40', 'slope40_noise', 'dry_sig40', 'wet_sig40', + 'azi', 'sig', 'inc', 'sm_sens', 'snow_prob', 'frozen_prob', + 'wetland', 'topo', 'sat_id', 'proc_flag', 'agg_flag', + 'corr_flag', 'line_num', 'node_num', 'sat_id', + 'swath_indicator'] - matching = ['jd', 'sat_id', 'abs_line_nr', 'abs_orbit_nr', 'node_num', - 'line_num', 'as_des_pass', 'swath', 'azif', 'azim', 'azia', - 'incf', 'incm', 'inca', 'sigf', 'sigm', 'siga', 'sm', - 'sm_noise', 'sm_sensitivity', 'sig40', 'sig40_noise', - 'slope40', 'slope40_noise', 'dry_backscatter', - 'wet_backscatter', 'mean_surf_sm', 'correction_flag', - 'processing_flag', 'aggregated_quality_flag', - 'snow_cover_probability', 'frozen_soil_probability', - 'innudation_or_wetland', 'topographical_complexity'] + # rounding issues in sat_track_azi leads to different as_des_pass + # 'as_des_pass', 'sat_track_azi' # lists with no data fields - bufr_none = ['abs_line_nr', 'abs_orbit_nr', 'aggregated_quality_flag'] - nc_none = ['azif', 'azim', 'azia', 'incf', 'incm', 'inca', - 'sigf', 'sigm', 'siga', 'processing_flag'] + nc_none = ['azi', 'inc', 'sig', 'corr_flag', 'proc_flag'] - # BUFR files contain less accurate data so we only compare to one 0.1 - # accuracy. + # BUFR contain less accurate data so we only compare to 0.1 for field in matching: # difference between the files should not be the case if field == 'sig40': - mask = self.reader_nc.data[field] == float32_nan - self.reader_bufr.data[field][mask] = float32_nan - self.reader_eps.data[field][mask] = float32_nan + mask = nc_ds[field] == float32_nan + bufr_ds[field][mask] = float32_nan + eps_ds[field][mask] = float32_nan - # difference between the files should not be the case - if field in ['snow_cover_probability', 'frozen_soil_probability', - 'innudation_or_wetland', 'topographical_complexity']: - mask = self.reader_eps.data[field] == float32_nan - self.reader_nc.data[field][mask] = float32_nan - self.reader_eps.data[field][mask] = float32_nan - - if field not in bufr_none: - nptest.assert_allclose(self.reader_bufr.data[field], - self.reader_eps.data[field], atol=0.1) + nptest.assert_allclose(bufr_ds[field], eps_ds[field], atol=0.1) if field not in nc_none: - nptest.assert_allclose(self.reader_eps.data[field], - self.reader_nc.data[field], atol=0.1) - - if field not in bufr_none and field not in nc_none: - nptest.assert_allclose(self.reader_nc.data[field], - self.reader_bufr.data[field], atol=0.1) + nptest.assert_allclose(eps_ds[field], nc_ds[field], atol=0.1) + nptest.assert_allclose(nc_ds[field], bufr_ds[field], atol=0.1) - def test_image_reading_eps(self): - self.reader = self.image_eps.read() + def test_eps(self): + """ + Test read EPS. + """ + eps_ds = self.eps.read() sm_should = np.array( [69.11, 74.23, 74.12, 75.95, 76.23, 80.74, 83.45, 84.94, 84.28, @@ -489,128 +319,85 @@ def test_image_reading_eps(self): 115.63427, 115.17735, 114.715836, 114.24969, 113.77889, 113.30343, 96.66666, 96.049965, 95.42956, 94.80551]) - mean_surf_sm_should = np.array( + sm_mean_should = np.array( [77.97, 77.57, 79.2, 78.38, 77.85, 79.81, 80.72, 81.23, 82.43, 82.11, 81.93, 82.55, 83.41, 81.84, 81.43, 81.28, 80.37, 79.6, 79.43, 78.02, 77.49, 42.42, 41.69, 42.99, 47.51]) - jd_should = np.array( - [2458281.66458332, 2458281.66458332, 2458281.66458332, - 2458281.66458332, 2458281.66458332, 2458281.66458332, - 2458281.66458332, 2458281.66462674, 2458281.66462674, - 2458281.66462674]) + t_should = np.array( + ['2018-06-12T03:56:59.999', '2018-06-12T03:56:59.999', + '2018-06-12T03:56:59.999', '2018-06-12T03:56:59.999', + '2018-06-12T03:56:59.999', '2018-06-12T03:56:59.999', + '2018-06-12T03:56:59.999', '2018-06-12T03:57:03.750', + '2018-06-12T03:57:03.750', '2018-06-12T03:57:03.750'], + dtype='datetime64[ms]') - nptest.assert_allclose(self.reader.lat[:25], lat_should, atol=1e-5) - nptest.assert_allclose(self.reader.lon[:25], lon_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['sm'][:25], - sm_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['mean_surf_sm'][:25], - mean_surf_sm_should, atol=1e-5) - nptest.assert_allclose(self.reader.data['jd'][35:45], - jd_should, atol=1e-5) + nptest.assert_allclose(eps_ds['lat'][:25], lat_should, atol=1e-5) + nptest.assert_allclose(eps_ds['lon'][:25], lon_should, atol=1e-5) + nptest.assert_allclose(eps_ds['sm'][:25], sm_should, atol=1e-5) + nptest.assert_allclose(eps_ds['sm_mean'][:25], + sm_mean_should, atol=1e-5) + nptest.assert_equal(eps_ds['time'][35:45], t_should) @pytest.mark.skipif(sys.platform == 'win32', reason="Does not work on Windows") -class Test_AscatL2Bufr(unittest.TestCase): - - def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'bufr') - - self.image_bufr = level2.AscatL2Bufr(self.data_path, eo_portal=True) - - def tearDown(self): - self.image_bufr = None - - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_bufr.read( - datetime(2018, 6, 12, 3, 57)) - - assert lon.shape == (68544,) - assert lat.shape == (68544,) +class Test_AscatL2FileList(unittest.TestCase): - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'M01-ASCA-ASCSMO02-NA-5.0-20180612035700.000000000Z-20180612044530-1281300.bfr') - orbit_start = self.image_bufr._get_orbit_start_date(filename) - orbit_start_should = datetime(2018, 6, 12, 3, 57) - - assert orbit_start == orbit_start_should - - def test_tstamp_for_daterange(self): - tstamps = self.image_bufr.tstamps_for_daterange(datetime(2018, 6, 12), - datetime(2018, 6, 13)) - tstamps_should = [datetime(2018, 6, 12, 3, 57)] - - assert tstamps == tstamps_should - - -class Test_AscatL2Eps(unittest.TestCase): + """ + Test read AscatL2FileList in various formats. + """ def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'eps_nat') - - self.image_eps = level2.AscatL2Eps(self.data_path, eo_portal=True) - - def tearDown(self): - self.image_eps = None - - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_eps.read( - datetime(2018, 6, 12, 3, 57)) - - assert lon.shape == (68544,) - assert lat.shape == (68544,) - - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'ASCA_SMO_02_M01_20180612035700Z_20180612053856Z_N_O_20180612044530Z.nat') - orbit_start = self.image_eps._get_orbit_start_date(filename) - orbit_start_should = datetime(2018, 6, 12, 3, 57) - - assert orbit_start == orbit_start_should - - def test_tstamp_for_daterange(self): - tstamps = self.image_eps.tstamps_for_daterange(datetime(2018, 6, 12), - datetime(2018, 6, 13)) - tstamps_should = [datetime(2018, 6, 12, 3, 57)] - - assert tstamps == tstamps_should - - -class Test_AscatL2Nc(unittest.TestCase): + """ + Setup test data. + """ + root_path = os.path.join(os.path.dirname(__file__), 'ascat_test_data', + 'eumetsat', 'ASCAT_generic_reader_data') - def setUp(self): - self.data_path = os.path.join( - os.path.dirname(__file__), 'ascat_test_data', 'eumetsat', - 'ASCAT_generic_reader_data', 'nc') + self.bufr_smo = AscatL2BufrFileList( + os.path.join(root_path, 'bufr'), sat='B', res='SMO') + self.nc_smo = AscatL2NcFileList( + os.path.join(root_path, 'nc'), sat='B', res='SMO') + self.eps_smo = AscatL2EpsFileList( + os.path.join(root_path, 'eps_nat'), sat='B', res='SMO') - self.image_nc = level2.AscatL2Nc(self.data_path, eo_portal=True) + def test_smo_read_date(self): + """ + Test read date for SMO formats. + """ + dt = datetime(2018, 6, 12, 3, 57, 0) - def tearDown(self): - self.image_nc = None + bufr_data = self.bufr_smo.read(dt) + nc_data = self.nc_smo.read(dt) + eps_data = self.eps_smo.read(dt) - def test_image_reading(self): - data, meta, timestamp, lon, lat, time_var = self.image_nc.read( - datetime(2018, 6, 12, 3, 57)) + for coord in ['lon', 'lat']: + nptest.assert_allclose( + bufr_data[coord], eps_data[coord], atol=1e-4) + nptest.assert_allclose( + eps_data[coord], nc_data[coord], atol=1e-4) + nptest.assert_allclose( + nc_data[coord], bufr_data[coord], atol=1e-4) - assert lon.shape == (68544,) - assert lat.shape == (68544,) + def test_smo_read_period(self): + """ + Test read period for SMO formats. + """ + dt_start = datetime(2018, 6, 12, 4, 0, 0) + dt_end = datetime(2018, 6, 12, 4, 13, 0) - def test_get_orbit_start_date(self): - filename = os.path.join(self.data_path, - 'W_XX-EUMETSAT-Darmstadt,SURFACE+SATELLITE,METOPB+ASCAT_C_EUMP_20180612035700_29742_eps_o_250_ssm_l2.nc') - orbit_start = self.image_nc._get_orbit_start_date(filename) - orbit_start_should = datetime(2018, 6, 12, 3, 57) + bufr_data = self.bufr_smo.read_period(dt_start, dt_end) + nc_data = self.nc_smo.read_period(dt_start, dt_end) + eps_data = self.eps_smo.read_period(dt_start, dt_end) - assert orbit_start == orbit_start_should + for coord in ['lon', 'lat']: + nptest.assert_allclose( + bufr_data[coord], eps_data[coord], atol=1e-4) + nptest.assert_allclose( + eps_data[coord], nc_data[coord], atol=1e-4) + nptest.assert_allclose( + nc_data[coord], bufr_data[coord], atol=1e-4) - def test_tstamp_for_daterange(self): - tstamps = self.image_nc.tstamps_for_daterange(datetime(2018, 6, 12), - datetime(2018, 6, 13)) - tstamps_should = [datetime(2018, 6, 12, 3, 57)] - assert tstamps == tstamps_should +if __name__ == '__main__': + unittest.main() diff --git a/tests/test_timeseries.py b/tests/test_timeseries.py deleted file mode 100644 index ebbcce8..0000000 --- a/tests/test_timeseries.py +++ /dev/null @@ -1,222 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - - -import os -import unittest -from datetime import datetime - -import numpy as np - -from ascat.read_native.cdr import AscatSsmCdr - - -class TestAscatNcV55R12(unittest.TestCase): - - def setUp(self): - - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'tuw', 'ascat', 'ssm', - '55R12') - - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - - ioclass_kws = {'loc_dim_name': 'gp', 'loc_ids_name': 'gpi'} - - self.ascat_reader = AscatSsmCdr(cdr_path, grid_path, - ioclass_kws=ioclass_kws) - - def test_read(self): - - gpi = 2329253 - result = self.ascat_reader.read(gpi) - - assert result.gpi == gpi - np.testing.assert_approx_equal(result.longitude, 14.28413, - significant=4) - np.testing.assert_approx_equal(result.latitude, 45.698074, - significant=4) - - assert len(result.data) == 2292 - assert result.data.iloc[15].name.strftime( - '%Y-%m-%d %H:%M:%S') == '2007-01-15 19:34:41' - assert result.data.iloc[15]['sm'] == 52 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 7 - assert result.data.iloc[15]['orbit_dir'].decode('utf-8') == 'A' - assert result.data.iloc[15]['proc_flag'] == 0 - - def test_neighbor_search(self): - - gpi, distance = self.ascat_reader.grid.find_nearest_gpi(3.25, 46.13) - assert gpi == 2346869 - np.testing.assert_approx_equal(distance, 2267.42, significant=2) - - -class TestAscatNcV55R21(unittest.TestCase): - - def setUp(self): - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'tuw', 'ascat', 'ssm', - '55R21') - - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = AscatSsmCdr( - cdr_path, grid_path, static_layer_path=static_layer_path) - - def tearDown(self): - self.ascat_reader.close() - - def test_read(self): - - gpi = 2329253 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi - np.testing.assert_approx_equal( - result.longitude, 14.28413, significant=4) - np.testing.assert_approx_equal( - result.latitude, 45.698074, significant=4) - - assert len(result.data) == 2457 - assert result.data.iloc[15].name.strftime( - '%Y-%m-%d %H:%M:%S') == '2007-01-15 19:34:41' - assert result.data.iloc[15]['sm'] == 55 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 7 - assert result.data.iloc[15]['frozen_prob'] == 29 - assert result.data.iloc[15]['snow_prob'] == 0 - assert result.data.iloc[15]['orbit_dir'].decode('utf-8') == 'A' - assert result.data.iloc[15]['proc_flag'] == 0 - - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_gldas'], 0.2969999, significant=6) - - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], 0.03779999, - significant=6) - - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.2364999, significant=6) - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.030100, significant=6) - - assert result.topo_complex == 14 - assert result.wetland_frac == 0 - - np.testing.assert_approx_equal( - result.porosity_gldas, 0.539999, significant=5) - np.testing.assert_approx_equal( - result.porosity_hwsd, 0.4299994, significant=5) - - def test_neighbor_search(self): - - gpi, distance = self.ascat_reader.grid.find_nearest_gpi(3.25, 46.13) - assert gpi == 2346869 - np.testing.assert_approx_equal(distance, 2267.42, significant=2) - - -class TestAscatNcV55R22(unittest.TestCase): - - def setUp(self): - - path = os.path.dirname(__file__) - - cdr_path = os.path.join(path, 'ascat_test_data', 'tuw', 'ascat', 'ssm', - '55R22') - - grid_path = os.path.join(path, 'ascat_test_data', 'hsaf', 'grid') - - static_layer_path = os.path.join(path, 'ascat_test_data', 'hsaf', - 'static_layer') - - self.ascat_reader = AscatSsmCdr( - cdr_path, grid_path, static_layer_path=static_layer_path) - - def tearDown(self): - self.ascat_reader.close() - - def test_read(self): - - gpi = 2329253 - result = self.ascat_reader.read(gpi, absolute_sm=True) - assert result.gpi == gpi - np.testing.assert_approx_equal(result.longitude, 14.28413, - significant=4) - np.testing.assert_approx_equal(result.latitude, 45.698074, - significant=4) - - ref_list = ['orbit_dir', 'proc_flag', 'sm', 'sm_noise', 'ssf', - 'snow_prob', 'frozen_prob', 'abs_sm_gldas', - 'abs_sm_noise_gldas', 'abs_sm_hwsd', 'abs_sm_noise_hwsd'] - - assert sorted(list(result.data.columns)) == sorted(ref_list) - - assert len(result.data) == 2642 - assert result.data.iloc[15].name.strftime( - '%Y-%m-%d %H:%M:%S') == '2007-01-15 19:34:41' - assert result.data.iloc[15]['sm'] == 55 - assert result.data.iloc[15]['ssf'] == 1 - assert result.data.iloc[15]['sm_noise'] == 7 - assert result.data.iloc[15]['frozen_prob'] == 29 - assert result.data.iloc[15]['snow_prob'] == 0 - assert result.data.iloc[15]['orbit_dir'].decode('utf-8') == 'A' - assert result.data.iloc[15]['proc_flag'] == 0 - - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_gldas'], 0.2969999, significant=6) - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_gldas'], 0.03779999, - significant=6) - - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_hwsd'], 0.2364999, significant=6) - np.testing.assert_approx_equal( - result.data.iloc[15]['abs_sm_noise_hwsd'], 0.0301000, significant=6) - - assert result.topo_complex == 14 - assert result.wetland_frac == 0 - - np.testing.assert_approx_equal( - result.porosity_gldas, 0.539999, significant=5) - np.testing.assert_approx_equal( - result.porosity_hwsd, 0.4299994, significant=5) - - def test_neighbor_search(self): - - gpi, distance = self.ascat_reader.grid.find_nearest_gpi(3.25, 46.13) - assert gpi == 2346869 - np.testing.assert_approx_equal(distance, 2267.42, significant=2) - - -if __name__ == '__main__': - unittest.main() diff --git a/tests/test_tuw.py b/tests/test_tuw.py deleted file mode 100644 index 2185951..0000000 --- a/tests/test_tuw.py +++ /dev/null @@ -1,115 +0,0 @@ -# Copyright (c) 2020, TU Wien, Department of Geodesy and Geoinformation -# All rights reserved. - -# Redistribution and use in source and binary forms, with or without -# modification, are permitted provided that the following conditions are met: -# * Redistributions of source code must retain the above copyright notice, -# this list of conditions and the following disclaimer. -# * Redistributions in binary form must reproduce the above copyright -# notice, this list of conditions and the following disclaimer in the -# documentation and/or other materials provided with the distribution. -# * Neither the name of TU Wien, Department of Geodesy and Geoinformation -# nor the names of its contributors may be used to endorse or promote -# products derived from this software without specific prior written -# permission. - -# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -# ARE DISCLAIMED. IN NO EVENT SHALL TU WIEN DEPARTMENT OF GEODESY AND -# GEOINFORMATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, -# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; -# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, -# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR -# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF -# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - -import os -import unittest -from datetime import datetime - -import numpy as np - -from ascat.tuw import AscatVodTs, Ascat_SSM - - -class TestAscat(unittest.TestCase): - - def setUp(self): - self.ascat_folder = os.path.join(os.path.dirname(__file__), - 'ascat_test_data', 'tuw', 'ascat', 'ssm') - - self.ascat_adv_folder = os.path.join(os.path.dirname(__file__), - 'ascat_test_data', 'tuw', - 'advisory_flags') - - self.ascat_grid_folder = os.path.join(os.path.dirname(__file__), - 'ascat_test_data', 'tuw', - 'grid') - - # init the ASCAT_SSM reader with the paths - self.ascat_SSM_reader = Ascat_SSM( - self.ascat_folder, self.ascat_grid_folder, - advisory_flags_path=self.ascat_adv_folder) - - def test_read_ssm(self): - - gpi = 2329253 - result = self.ascat_SSM_reader.read_ssm(gpi) - assert result.gpi == gpi - assert result.longitude == 14.28413 - assert result.latitude == 45.698074 - assert sorted(list(result.data.columns)) == sorted([ - 'ERR', 'SSF', 'SSM', 'frozen_prob', 'snow_prob']) - assert len(result.data) == 2058 - assert result.data.iloc[15].name == datetime(2007, 1, 15, 19) - assert result.data.iloc[15]['ERR'] == 7 - assert result.data.iloc[15]['SSF'] == 1 - assert result.data.iloc[15]['SSM'] == 53 - assert result.data.iloc[15]['frozen_prob'] == 29 - assert result.data.iloc[15]['snow_prob'] == 0 - - def test_neighbor_search(self): - - self.ascat_SSM_reader._load_grid_info() - gpi, distance = self.ascat_SSM_reader.grid.find_nearest_gpi( - 3.25, 46.13) - assert gpi == 2346869 - np.testing.assert_approx_equal(distance, 2267.42, significant=2) - - -class TestAscatVodTs(unittest.TestCase): - - def setUp(self): - self.ascat_folder = os.path.join(os.path.dirname(__file__), - 'ascat_test_data', 'tuw', 'ascat', 'vod') - - self.ascat_grid_folder = os.path.join(os.path.dirname(__file__), - 'ascat_test_data', 'hsaf', 'grid') - - # init the ASCAT_SSM reader with the paths - self.ascat_VOD_reader = AscatVodTs(self.ascat_folder, - self.ascat_grid_folder) - - def test_read_vod(self): - gpi = 2199945 - data = self.ascat_VOD_reader.read(gpi) - lon, lat = self.ascat_VOD_reader.grid.gpi2lonlat(gpi) - np.testing.assert_approx_equal(lon, 9.1312, significant=4) - np.testing.assert_approx_equal(lat, 42.5481, significant=4) - - assert list(data.columns) == ['vod'] - assert len(data) == 4018 - assert data.iloc[15].name == datetime(2007, 1, 16, 12, 0, 0) - assert data.iloc[15]['vod'] == np.float32(0.62470651) - - def test_neighbor_search(self): - gpi, distance = self.ascat_VOD_reader.grid.find_nearest_gpi( - 3.25, 46.13) - assert gpi == 2346869 - np.testing.assert_approx_equal(distance, 2267.42, significant=2) - - -if __name__ == '__main__': - unittest.main()