diff --git a/.ipynb_checkpoints/Showcase_OnlineSensorBased-checkpoint.ipynb b/.ipynb_checkpoints/Showcase_OnlineSensorBased-checkpoint.ipynb new file mode 100644 index 000000000..3a624c825 --- /dev/null +++ b/.ipynb_checkpoints/Showcase_OnlineSensorBased-checkpoint.ipynb @@ -0,0 +1,1280 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook serves as a showcase for the functions written in the ``wwdata`` package, more specifically the OnlineSensorBased subclass. For additional information on the functions, the user is encouraged to use the provided docstrings. They can be accessed by entering a function name and hitting shift+tab between the function brackets.\n", + "\n", + "All information and documentation on the ``wwdata`` package, including how to install it, can also be found online at https://ugentbiomath.github.io/wwdata-docs/.\n", + "\n", + "An elaborate explanation on the functionalities of the package is accepted for publication in *Environmental Modelling and Software* and will soon be available on [ResearchGate](https://www.researchgate.net/project/Data-analysis-and-gap-filling)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Loading the necessary packages" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.404080", + "start_time": "2017-05-09T11:54:53.499498+02:00" + } + }, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'pandas'", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mos\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mlistdir\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 5\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mscipy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0msp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'pandas'" + ], + "output_type": "error" + } + ], + "source": [ + "import sys\n", + "import os\n", + "from os import listdir\n", + "import pandas as pd\n", + "import scipy as sp\n", + "import numpy as np\n", + "import datetime as dt\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "# seaborn is not a required package, it just prettifies the figures\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And now for the actual package..." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import wwdata as ww" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Check what version you have installed" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'0.2.0'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ww.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "pd.read_excel" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.587365", + "start_time": "2017-05-09T11:54:55.406913+02:00" + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Time', 'TSS_line3', 'NO3_line3', 'CODtot_line3', 'CODsol_line3',\n", + " 'TSS_line2', 'NO3_line2', 'CODtot_line2', 'CODsol_line2', 'TSS_line1',\n", + " 'NO3_line1', 'CODtot_line1', 'CODsol_line1', 'Cond_ns', 'Turb_ns',\n", + " 'Temp_ns', 'Ammonium_ns', 'Cond_es', 'Turb_es', 'Temp_es', 'NH4_infl',\n", + " 'NH3_line3', 'Turb_rz', 'Cond_rz', 'Temp_rz', 'PO4_mixinggutter',\n", + " 'TSS_efflPST', 'NO3_efflPST', 'CODtot_efflPST', 'CODsol_efflPST',\n", + " 'TSS_efflRBT', 'NO3_efflRBT', 'CODtot_efflRBT', 'CODsol_efflRBT',\n", + " 'Cond_line1', 'Turb_line1', 'Cond_line2', 'Turb_line2', 'Cond_line3',\n", + " 'Turb_line3', 'NH4_efflPST', 'PO4_efflPST', 'PO4_sandtrap',\n", + " 'NH4_splittingworks', 'PO4_splittingworks', 'Flow_line1', 'Flow_line2',\n", + " 'Flow_line3', 'Flow_total'],\n", + " dtype='object')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "measurements = pd.read_csv('./data/201301.txt',sep='\\t',skiprows=0)\n", + "measurements.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create Class object and format data" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.669059", + "start_time": "2017-05-09T11:54:55.589786+02:00" + } + }, + "outputs": [], + "source": [ + "dataset = ww.OnlineSensorBased(data=measurements,\n", + " timedata_column='Time',\n", + " data_type='WWTP')\n", + "dataset.set_tag('January 2013')\n", + "dataset.replace('Bad','NaN',inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Convert the values in the column containing time data to the pandas datetime format." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.780731", + "start_time": "2017-05-09T11:54:55.671616+02:00" + } + }, + "outputs": [], + "source": [ + "dataset.to_datetime(time_column=dataset.timename,time_format='%d-%m-%y %H:%M')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "use the time-column as index" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.788079", + "start_time": "2017-05-09T11:54:55.783330+02:00" + } + }, + "outputs": [], + "source": [ + "dataset.set_index('Time',key_is_time=True,drop=True,inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Convert the absolute timestamps to relative values. This can be important when data is to be used for modeling purposes later on, and needs to be written to text files." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.793662", + "start_time": "2017-05-09T11:54:55.790638+02:00" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "#dataset.absolute_to_relative(time_data='index',unit='d')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Drop any duplicates that might be present in the index" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:55.812335", + "start_time": "2017-05-09T11:54:55.796021+02:00" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "dataset.drop_index_duplicates()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Convert all or the selected columns to float type." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:56.047638", + "start_time": "2017-05-09T11:54:55.815534+02:00" + }, + "collapsed": true + }, + "outputs": [], + "source": [ + "dataset.to_float(columns='all')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:56.758532", + "start_time": "2017-05-09T11:54:56.050129+02:00" + } + }, + "outputs": [ + { + "data": { + "image/png": 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MBjZUKhWcnZ3N3pCTkxOqq6st0iiihuCF/t1HWa7EyK+HMJilRVNd35Ae7j2x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m+wytsx7THCf1Qjtcq20bjLk1GDIMwHTcYIW+ZWWRaU/4SNKlVVuFWWZbG6SGODIAiCsEVIY6MF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\nX78ugYGB8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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(18,4))\n", + "ax.plot(dataset.data['CODtot_line2'],'.g')\n", + "ax.set_ylabel('Total COD [mg/L]',fontsize=18);ax.set_xlabel('')\n", + "ax.tick_params(labelsize=14)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Filter data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Selecting data happens through tagging, so no original data is lost. When applying filter algorithms such as ``tag_doubles``, ``moving_slope_filter`` etc., a new pandas dataframe is created (``dataset.meta_valid``, see also below figure) that contains these tags. It is also based on this new dataframe that the plotting of selected and not selected datapoints in different colours happens.\n", + "\n", + "![validation](./figs/packagestructure_validation.png)\n", + "\n", + "The written output of the filter functions tells the user how many data points were tagged based on that specific function. When the plotting argument is set to true, the plot shows the aggregated results of the filter functions used up until that point." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Maxima\n", + "Tag the data points that are higher then a certain percentile" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:57.347519", + "start_time": "2017-05-09T11:54:56.761091+02:00" + } + }, + "outputs": [ + { + "data": { + "image/png": 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89dZbWLp0KRQKRZMAV6vVQhAEeHl5QaFQAGgaBNfV1cGzPj+5uW0YX3s6Y2I+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Pjw4fJ82xUemUyGIU21q/LMKriQMD9zLHxhCQBu+JExrL2hvtrkNd79clWpTQ2Y8Nd2W9xWrHpz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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.get_highs('Flow_total',0.95,arange=['2013/1/1','2013/1/31'],method='percentile',plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## NaN values\n", + "Tag all NaN (Not a Number) values as 'filtered'." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:57.358210", + "start_time": "2017-05-09T11:54:57.350077+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "47 values detected and tagged as filtered by function NaN tagging\n" + ] + } + ], + "source": [ + "dataset.tag_nan('CODtot_line2')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sensor failure\n", + "Tag all datapoints that are part of a constant (within a given bound) signal." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:57.391744", + "start_time": "2017-05-09T11:54:57.361076+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2464 values detected and tagged as filtered by function double value tagging\n" + ] + } + ], + "source": [ + "dataset.tag_doubles('CODtot_line2',bound=0.05,plot=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Noise \n", + "Tag all data points for which the slope as compared with the previous point is too high to be realistic (i.e. the data point is noisy)." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:58.312987", + "start_time": "2017-05-09T11:54:57.394331+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "199 values detected and tagged as filtered by function moving slope filter\n" + ] + } + ], + "source": [ + "dataset.moving_slope_filter('index','CODtot_line2',72000,arange=['2013/1/1','2013/1/31'],\n", + " time_unit='d',inplace=False,plot=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tag all data points that are more than a specified percentage away from the calculated moving average. This function makes use of the ``simple_moving_average`` function, also written as part of this package." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:58.360928", + "start_time": "2017-05-09T11:54:58.315777+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2810 values detected and tagged as filtered by function moving average filter\n" + ] + } + ], + "source": [ + "dataset.moving_average_filter(data_name='CODtot_line2',window=12,cutoff_frac=0.20,\n", + " arange=['2013/1/1','2013/1/31'],plot=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:59.889452", + "start_time": "2017-05-09T11:54:58.363535+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "65.77546296296296% datapoints are left over from the original 8640.0\n" + ] + }, + { + "data": { + "image/png": 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Lly/H6NGjtcddtmxZsx6/Zs0aAMB3332HTp06AQCio6MxYcIEw785NdhDhIiIiIiMSxQh\nPXtGc4NARNTaiSLQvz8wcKDmXyu+9lVXV+PgwYPo168fpFIpioqKUFRUhOLiYjz00ENQKBT49ddf\ndR7Tr1+/Fj++uroax44dw9ChQ7XJEADo3r07HnjgAaO9PlaIEBEREZHxiCLcoodBmpEOVUAgiuPi\nzfZtKRGRSSQnA6mpmp9TUzXLVjqFbXFxMcrKynDw4EEcPHiw0X2uXr2qs1xbLdKSx5eUlKC8vBx+\nfn4Ntnfr1q3RnieGwIQIERERERmNNC0F0ox0zc8Z6ZCmpUDVt7+ZoyIiMqLQUCA4WJMMCQ7WLFup\nqqoqAJqhK0888USj+/j6+uos29vb3/Hjb9682WB7dXV1y4JuASZEiIiIiMhoVEEhUAUEaitEVEEh\n5g6JiMi4BAE4c8bsPUQMwd3dHU5OTlCpVBg8eLDOtitXruDChQtwcnK668e7ublBEARkZ2c3OEZe\nXp5hXkwj2EOEiIiIiIxHEFAcF4/inw5xuAwR2Q5B0AyTsbJrnp2dJkVQW5UhlUoRERGBo0ePIrV2\nGFCNd999F/PmzUNxcbHe4zX38RKJBFFRUTh27BgyMjK0++Tl5SE+Pt5Ar66R+Ix2ZCIiWyeKmtLw\noBCr+2NIRGRQgsBhMkREVsDd3R0AsHnzZhQWFmLcuHF48cUX8dtvv2Hq1KmYOnUqvL29ER8fjyNH\njuDxxx9HQEBAk8ds7uP/9a9/IT4+HtOmTcPMmTNhb2+PjRs3wtnZ2WhT7zIhQkRkDGwiSERERERW\nZtCgQRg1ahSOHDmCU6dO4aGHHoKfnx+2bt2K1atXY+vWrSgvL4evry+WLFmC6dOn3/aYzX18p06d\nsHnzZrz//vtYt24dHBwcMHnyZADAp59+apTXK1Gr1WqjHNkKFRSUmTsEi+Lh4cL3hGyKIc956dkz\ncBsVqV0u/ukQvx0li8RrPdkanvNka3jO6/LwcDF3CGRB2EOEiMgIapsIAmATQSIiIiIiC8QhM0RE\nxlDTRJA9RIiIiIiILBMTIkRExsImgkREREREFotDZoiIiIiIiIjI5jAhQkREREREREQ2hwkRIiIi\nIiIiIrI5TIgQERERERHdjihCevYMIIrmjoSIDIQJESIiIiIioqaIItyih8FtVCTcoocxKULUSjAh\nQkRERERE1ARpWgqkGemanzPSIU1LMXNERGQITIgQERERERE1QRUUAlVAoObngECogkLMHBERGYLU\n3AEQERERERFZNEFAcVw8pGkpmmSIIJg7IiIyAIuoEFEoFBg7dixOnDihXXfy5EnExMSgd+/eiI6O\nxrZt23Qec+rUKYwbNw5hYWGYPn06srOzdbZv3LgRERER6N27N5YsWYLy8nKTvBYiIiIiImqFBAGq\nvv2ZDCFqRcyeEKmsrMTChQuRkZGhXffXX3/h2WefRVRUFHbu3Il58+bh7bffxuHDhwEAV69exZw5\nczB+/Hjs2LEDHTt2xNy5c1FdXQ0A2L9/Pz766CO8+eab2LBhA86fP493333XLK+PiIiIiIiIiCyP\nWRMimZmZeOyxx5CTk6Ozft++fQgJCcHs2bPRpUsXjB8/HhMmTMDu3bsBAFu3bkVwcDBmzZoFf39/\nLFu2DFevXsWpU6cAAF9//TWmTZuGyMhI9OzZE0uXLsUPP/yAGzdumPw1EhEREREREZHlMWtC5PTp\n0xgwYAC2bNmis37UqFF44403dNZJJBJcv34dAJCUlIT+/ftrtzk5OSE0NBTnzp1DVVUVzp8/r7M9\nPDwcVVVVSElhN2giIiIiIiIiMnNT1SlTpjS6vmvXrjrLhYWF2Lt3L+bOnQsAKCgogKenp84+HTp0\ngFwux/Xr11FZWamzXSqVwtXVFdeuXTPwKyAiIiIivUSRTSiJiMhiWfwsM+Xl5Zg/fz48PT21CZSK\nigo4ODjo7Ofg4ACFQoGbN29qlxvb3hQ3t7aQSu0NGL318/BwMXcIRCbFc55sEc97MgpRBCJGAKmp\nQHAwcOaMxSRFeM6TreE5T9Q4i06IlJWV4dlnn0VeXh6+/fZbODk5AQAcHR0bJDcUCgVcXV3h6Oio\nXa6/vU2bNk0+X3ExZ6Kpy8PDBQUFZeYOg8hkeM6TLeJ5T8YiPXsGbqmpmoXUVBQfP62ZocPMeM6T\nreE5r4vJIarL7LPM6FNUVIQZM2YgNzcXGzZsgJ+fn3abl5cXCgoKdPYvLCyEh4eHNilSWFio3aZS\nqVBSUtJgmA0RERERGYcqKASqgEDNzwGBmmEzREREFsQiEyIKhQKzZ89GcXExvvnmG3Tr1k1ne1hY\nGBISErTLFRUVuHDhAsLDw2FnZ4eePXvi7Nmz2u2JiYmwt7dHSAj/EBMRERGZhCCgOC4exT8dQnFc\nvMUMlyEiIqplkQmRr776CsnJyVi+fDmcnJxQUFCAgoIClJSUAABiYmKQlJSEjz/+GJmZmXjttdfg\n7e2NQYMGAdA0a/3iiy+wf/9+nD9/Hm+99RZiYmLg7OxszpdFRERERERERBbCInuI/Pzzz1CpVJg5\nc6bO+j59+mDz5s3w8fHBmjVrsHz5cnzyyScICwtDbGws7Ow0+Z0xY8bg8uXLWLp0KRQKBaKiorB4\n8WIzvBIiIiIiGyWKcIseBmlGOlQBgawSISIiiyNRq9VqcwdhKdhsSBcbMJGt4TlPtojnPRmL9OwZ\nuI2K1C4X/3SITVWJzIDnvC42VaW6LHLIDBERERFZNzZVJSIiS2eRQ2aIiIiIyMrVNFWVpqVokiG1\nw2VEseE6IiIiM2BChIiIiIiMQxB0h8mwrwgREVkQDpkhIjIEuRyO32wA5HJzR0JEZLGkaSmQZqRr\nfs5IhzQtxcwRERGRLWOFCBHR3ZLL0bFPKCRKBdT2UhSe+B3o2s3cURERWZzaviK1FSLsK0JERObE\nhAgR0V1yPBgHiVIBAJBUqeA+LhpFp86xDJyIqD59fUWIiIjMgENmiIjuUuXIaKjtb+WX7fPlLAMn\nItKntq8IkyFERGRmTIgQEd0tLy8UnvgdVZ5eADi9JBERERGRNeCQGSIiQ+jaDUWnzrEMnIiIiIjI\nSjAhQkRkKPWnlyQiIiIiIovFITNEREREREREZHOYECEiIiIiIiIim8OECBERERERERHZHL09RP74\n4w+DPEGvXr0MchwiIiIislKiyKbTRERkcfQmRB577DFIJJK7OrhEIsGFCxfu6hhEREREZMXkcriP\njoR9bg5UAYEojotnUoSIiCxCk7PMPProo3dc4ZGUlISdO3fe0WOJiIiIqBUQRbiNHgH73FwAgDQj\nXVMpwhm5iIjIAjSZEBk0aBDGjRt3Rwd2cnLCDz/8cEePJSIiIiLrJ01LgbQmGQIAVb5+mmEzRERE\nFkBvU9W1a9fi/vvvv+MDDxw4EGvXrr3jxxMRERGRdVMFhUAVEKj52dcXRfsOcbgMERFZDL0VIiNH\njmzRgbZv346TJ0/iww8/BAB4eXnBy8vr7qIjIrImbBpIRKRLEFAcF89rIxERWSSDTbt7/vx57Nu3\nz1CHIyKyLqIIt+hhcBsVCbfoYYAomjsiIiLLIAianiFMhhARkYUxWEKEiMiWSdNSIM1I1/xc0zSQ\niIiIiIgsFxMiREQGoDNOPiCQTQOJiIiIiCxck7PMEBFRM3GcPBERERGRVWGFCBGRoQgCVD5+cNz1\nPSCXmzsaIiIiIiJqgt4KkZY2SM2tM8c8EZFNksvRsU8oJEoF1DIHFCYkA5xti4iIiIjIIulNiCxc\nuBASiaTZB1Kr1S3an4iotRCVItKKUtA3LhESpQIAIFEq4HgwDpVTZ5g5OiIiIiIiaozehMibb77J\nBAcR0W2IShHR24YhoyQdA+264YRMBolSCbXMAZUjo80dHhERERER6aE3IRIdHQ13d3eTBKFQKDBx\n4kS8+uqrGDx4MADg8uXLeOONN5CQkIBOnTph8eLFGDp0qPYxp06dwn/+8x/k5OSgV69eeOedd9Cl\nSxft9o0bN+Lzzz9HWVkZHn74Ybzxxhto27atSV4PEdmOtKIUZJRopts9VX0RR/ZvQ79EuSYZwuEy\nRESAKLLhNBERWSS9TVWHDBmCRx55BO+99x6OHTuGmzdvGiWAyspKLFy4EBkZGdp1arUac+fOhaur\nK7Zv345HH30Uzz//vLZPydWrVzFnzhyMHz8eO3bsQMeOHTF37lxUV1cDAPbv34+PPvoIb775JjZs\n2IDz58/j3XffNUr8RGTbgtxDEOCqmW43wDUQXQOHaIbJMBlC1DyiCOnZM4AomjsSMgZRhFv0MLiN\nioRb9DD+PxMRkUXRWyHyww8/4OTJkzhx4gS+++47qFQqhIeHY9CgQRg8eDB69eoFO7u7m6QmMzMT\nixYtglqt1ll/6tQpXLp0Cd988w0EQYC/vz9OnDiB7du3Y8GCBdi6dSuCg4Mxa9YsAMCyZcswZMgQ\nnDp1CoMHD8bXX3+NadOmITIyEgCwdOlSPPnkk3jllVfg7Ox8VzETEdUlyATETY5HWlEKgtxDIMj4\n7SdRs9XcLEsz0qEKCERxXDwrCFoZaVoKpBmaKjppRrqmUqRvfzNHRUREpKE3oxEcHIwnn3wSn3/+\nOU6fPo1169ahb9++OHr0KKZOnYoBAwZg7ty52LRpE7Kysu7oyU+fPo0BAwZgy5YtOuuTkpLQo0cP\nCHU+FPXt2xeJiYna7f373/pj6uTkhNDQUJw7dw5VVVU4f/68zvbw8HBUVVUhJSXljuIkImqKIBPQ\n16s/kyFELdTYzTK1LqqgEKgCNFV0qoBAzbAZIiIiC6G3QqQumUyGAQMGYMCAAXjhhRcgiiJOnjyJ\nkydPYtOmTXjnnXfg5eWFwYMHY/ny5c1+8ilTpjS6vqCgAJ6enjrrOnTogGvXrjW5XS6X4/r166is\nrNTZLpVK4erqqn08EZGh1c40wyoRouarvVmurRDhzXIrJAgojotnDxEiIrJIzUqI1CcIAqKiohAV\nFQUAuHLlCk6cOIGTJ08aJKiKigrIZDKddQ4ODlAqldrtDg4ODbYrFAptrxN925vi5tYWUqn93Ybf\nqnh4uJg7BCKTupNzXlSIiPh8BFILUxHcMRhnZp2B4MAP/WQ9zHat93ABEs4CycmQhobCgzfLrZOH\nC9C1U9P7iCKQnAyEhpokacLPN2RreM4TNe6OEiL1eXt7Y9KkSZg0aZIhDgdHR0eI9ZpuKRQKtGnT\nRru9fnJDoVDA1dUVjo6O2mV9j9enuLj8bkNvVTw8XFBQUGbuMIhM5k7P+eOXf0FqYSoAILUwFcfT\nT6OvF8fIk3WwiGt9tx5AhRqo4N+cVk3fbDMm7iVjEec8kQnxnNfF5BDV1eyESK9evSCRSPRul0gk\ncHBwgLu7O8LCwjB79mx07dr1joLy8vJCamqqzrrCwkJ4eHhotxcUFDTYHhAQoE2KFBYWIjCwZsyq\nSoWSkpIGw2yIiO6WqBTxUvwL2uXurv4IcmfZPxGRjiaSHmy8SkRE5tLsaWKefPJJtGnTBpWVlQgL\nC8Ojjz6KJ554AgMHDtTOEjNw4EB4e3vj559/xqRJk+642WpYWBhSU1NRXn6rYuPs2bMIDw/Xbk9I\nSNBuq6iowIULFxAeHg47Ozv07NkTZ8+e1W5PTEyEvb09QkJ4k0JEhpVWlIKs0kzt8oqhH7GHCBFR\nPU010GXjVSIiMpdmV4g4OTlBpVJh69at6NWrl862S5cu4R//+AfCwsLw9NNPQy6XY+rUqVi1ahVW\nr17d4qDuv/9+eHt7Y/HixXjuuedw5MgRJCUl4T//+Q8AICYmBuvXr8fHH3+MqKgoxMbGwtvbG4MG\nDQKgadb6+uuvIygoCJ06dcJbb72FmJgYTrlLRAbn4+IHmZ0DlNUKyOwcEOAWZO6QiIgsR+0wGR8/\n/Q102XiViIjMpNkVIps3b8bMmTMbJEMAoGvXrpg+fTo2btwIQDOk5bHHHsOZM2fuKCh7e3vExsai\nqKgIEydOxK5du7B27Vr4+PgAAHx8fLBmzRrs2rULMTExKCwsRGxsLOzsNC9nzJgxmDNnDpYuXYon\nn3wS9913HxYvXnxHsRARNSWvLAfKak3PImW1AnllOWaOiIjIQogi3KIi4DYqEm4TRqH4+70o/ulQ\n4z1CBEE0fEs+AAAgAElEQVQzTIbJECIiMqFmV4hcv34dLi76G9A4OzujuLhYu+zm5qad8aU50tLS\ndJa7dOmCTZs26d1/6NChGDp0qN7tzzzzDJ555plmPz8R0Z0Icg9BgGsgMkrSEeAayP4hREQ1pIkJ\nkGZphhRKszIhzUiD6oEIM0dFRER0S7MrREJDQ/Hdd981mP0FAG7cuIEtW7YgKOhWqfjvv/8OX19f\nw0RJRGShBJmAuMnx+CnmEOImx7N/CBFRU0QR0rNnNNPsEhERmVmzK0QWLFiAJ598EtHR0Zg4cSL8\n/Pzg4OCAv/76Cz/++CPkcjk+++wzAMC8efNw+PBhvPbaa0YLnIjIUggygdPsEhHVowrvA1V3f0iz\nMqHq7g9VQJBJp9clIiK6nWYnRPr27Yuvv/4a7733HtatW6edWQYAevTogXfffRf9+/fH33//jaSk\nJDz99NOYOnWqUYImIiIiIgsnCCg+8Iu2WSqn1yUiIkvT7IQIAPTu3Rvfffcd/v77b2RnZ0OlUsHX\n1xedOnXS7tOhQwccP37c4IESEVkyUSkirSgFwY5+aJ+Vw5kSiMh21c4sU3MdrE161E6v2+hMM0RE\nRGbQooRIrQ4dOqBDhw6GjoWIyCqJShHR24bhijwdSesd4JavYDk4EdkmUdQ/LIbT6xIRkYVpdkJE\nFEV8+OGH+PXXX1FQUIDq6uoG+0gkEiQmJho0QCIiS5eYn4CMknTcXwB0z9dMwctycCKyRbcdFlOn\nYoSIiMjcmp0QWbp0Kfbs2YPQ0FCEhITA3t7emHEREVkFUSli0ZHnAQDJHkCGpxQB+SqWgxORTeKw\nGCIisibNTogcO3YMTzzxBJYuXWrEcIiIrEtifgIuXb8IALjhCPR+WoXoCh98OHcvnFkOTkS2hsNi\niIjIitg1d0d7e3sEBQUZMxYiIqt3wxH43jUPqZU55g6FiMg8aofFMBlCREQWrtkJkUceeQS7d+9G\nVVWVMeMhIrIqAW5BkEp0i+26u/ojyJ1l4kRERERElqzZQ2YWLFiA2bNnY/To0Rg+fDjc3d0hkUh0\n9pFIJPjnP/9p8CCJbFK9aQvJMuWV5UClVmmX3xq8DNNDZ0KQ8f+MiIiIiMiSNTshcuDAAfz222+o\nqqrCV1991eg+TIgQGUhT0xaSRQlyD0H39v7IKs0EAGy48AWmh840b1BERERERHRbzU6IrF69Gt7e\n3nj55Zdx7733cpYZIiO67bSFZDEEmYAVwz7CxF1jAQBZJZlIK0pBXy/+fxERAZrZuNKKUhDkHsLq\nOSIisijNTohcu3YNr7zyCqKioowZDxGB0xZamwC3IMjsHKCsVkBm5wAfFz9zh0RE5sChjg2IShHR\n24YhoyQdAa6BiJscz6QIERFZjGY3VQ0KCoJcLjdmLERUq2bawuKfDnG4jBXIK8uBsloBAFBWK5BX\nxhlmiGxOzVBHt1GRcIseBoiiuSOyCGlFKcgo0VQ8ZpSkI60oxcwRERER3dLshMiLL76I7777Djt2\n7EBpaakxYyIigNMWWpEg9xAEuAYCAAJcAznDDJENamyoI/H6SERElk2iVqvVzdkxJiYGV65cQUlJ\nCQDA3t6+QR8RiUSCxMREw0dpIgUFZeYOwaJ4eLjwPSGbcjfnPMfIk7Xitd5A2AxbL0u7PvKcJ1vD\nc16Xh4eLuUMgC9LsHiJ+fn7o0qWLMWMhIrJ6N5Q3LOqDPxGZiCCg+Pu9cDwYh8qR0UyG1CHIBDaa\nJiIii9TshMjKlSuNGQcRkdUSlSKitkYgqzQTUokUKrWKzQOJbI0owm3iGFaIEBERWRG9PUQiIyNx\n6NChOz7wwYMHERkZecePJyKyFon5CcgqzQQAqNQqAGweSGRr2EOEiIjI+uhNiFy+fBkVFRV3fODy\n8nJcuXLljh9PRGTNfF382DyQyIbUTpcOgNOlExERWYkmh8wsWbIEr7322h0duLq6+o4eR0RkbcI9\n+6Br+264VHoRANBZ8MG+mEMQKgHpH2c0N0YsnSdq3WqmS5empfB3XhT5PhARkVXQmxAZNWoUJBKJ\nKWMhIrJKgkzAoceOIzE/AYAmQSJUgjNOENma2unSbRln2yEiIiuiNyHCJqpERM0nyAQ80DlCuyz9\n40yDfgI2f6NERK1eY71UeO0jIiJLpbeHCBER3Tn2E7Bs8nI5vknZAHm53NyhELUqvPYREZE1afa0\nu0RE1DhRKSKtKAVB7iG3ptkVBOTt3YurZ+LQqX80nFkybjHk5XL02RAKZbUCMjsHJMxIhldbL3OH\nRdQ6sJcKERFZEVaIEBHdBVEpInrbMIzaEYnobcMgKkXt+of2jcHgjPl4aN8Y7Xoyv4PZcVBWKwAA\nymoFDmbHmTkiolamtpcKkyFERGThmBAhIroLaUUpyCjRjJfPKElHWlFKk+vJ/EZ2iYbMzgEAILNz\nwMgu0WaOiIiIiIjMwaITIqWlpXjxxRdx//3348EHH8QHH3yAqqoqAMDly5fx1FNPITw8HKNGjcLR\no0d1Hnvq1CmMGzcOYWFhmD59OrKzs83xEoiolQtyD0GAq2a8fIBrIILcQ5pcT+bn1dYLCTOSsXL4\nWg6XITIRUSnirPwMq+WIiMiitDghIooiRNE0f8zeeustyOVybNq0CStWrMDOnTvx5ZdfQq1WY+7c\nuXB1dcX27dvx6KOP4vnnn0dubi4A4OrVq5gzZw7Gjx+PHTt2oGPHjpg7dy6qq6tNEjcR2Q5BJiBu\ncjx+ijmE7yfsRVpRCkSlCEEm4PsJe7Fy+Fp8P2Hvrd4iZBG82nphasgMJkOIjEEUIT17BhBvDSFs\nbGghERGRud22qWphYSE2btyIY8eOIT09XVuh4eDggMDAQIwcORKPP/44XF1dDR7c0aNH8d577yEw\nUPMt69ixY3Hq1CmEhobi0qVL+OabbyAIAvz9/XHixAls374dCxYswNatWxEcHIxZs2YBAJYtW4Yh\nQ4bg1KlTGDx4sMHjJCLbJsgEBLmHIHrbMGSUpKN7e3+8/cBy/PvXJcgqyUSAayDiJsczKWJBGm2E\nS0R3TxThFj0M0ox0qAICURwXj7QbDYcQ9vXiVLxERGR+TVaIHDhwAFFRUfj000+Rn5+Pfv36ISoq\nCsOHD0doaCguXryIlStXIioqCkeOHDF4cK6urvjxxx9RUVEBuVyOY8eOITQ0FElJSejRoweEOs26\n+vbti8TERABAUlIS+ve/9YfWyckJoaGhOHfunMFjJCOp9+0SkSUTlSL2/bEZbn+mw7kSyCrNxNS9\nk5FVkgmAPUQsDb+tJjIeaVoKpBma5Ic0Ix3StBQOISQiIoult0Lkjz/+wIIFC9C5c2csXboUgwYN\narBPdXU1jh07hvfffx/PP/88tm3bhuDgYIMF9+abb+Lll19Gnz59UF1djYEDB+K5557D8uXL4enp\nqbNvhw4dcO3aNQBAQUFBo9vlcrnBYiMjauTbJXaqJ0slKkU8uikCm1dkYl4hkNIR6D8LuOF4ax/e\nAFiWxhre8ttqIsNQBYVAFRAIaUY6xK5+KO3upx1ayKosIiKyNHoTIuvWrUPHjh2xdetWtG/fvtF9\n7OzsMHToUPTu3Rvjxo3D+vXrsWLFCoMFl5OTgx49emDevHkQRRH/7//9P7z33nuoqKiATCbT2dfB\nwQFKpRIAUFFRAQcHhwbbFQpFk8/n5tYWUqm9weJvDTw8XEz/pBcvAHW+XfLIzwG6DjB9HGSTWnrO\nX8y7AMeMTIQUapZDCoFRCl9sd8xFYIdAfDLmE/Tv3B+CA28ALEW4Uw90ad8F2aXZCO4YjAcC77f5\n/x+zXOstmSgCyclAaCgT8i3l4QLx1FE8vXwg9sqy4bt/HM7MOgMPh07o6t3J3NFp8ZwnW8Nznqhx\nehMi586dQ0xMjN5kSF3t2rXDI488gj179hgssJycHCxbtgyHDx/GPffcAwBwdHTEU089hcmTJzdo\n7KpQKNCmTRvtfvWTHwqF4rZ9ToqLyw0Wf2vg4eGCgoIy0z+xpx/car5dUgUEotjTDzBHHHRHrLk3\nw52c8552fqjw74aUjhcRUghkesrw1lO78XT139r3oKJUjQrwHLYEolJE1LYIZJdmo7Pgg21jd9v8\n/4/ZrvWWilWKd+2s/AK2CprZ/VILU3HgwlE4SZ0s5u8Cz3myNTzndTE5RHXpTYiUlJSgc+fOzT6Q\nn58fCgoKDBIUAPz5559wcXHRJkMA4L777kNVVRU8PDyQnp6us39hYSE8PDwAAF5eXg1iKSwsREBA\ngMHiIyMSBBTHxUOalgJVUAg/iFoRebkco3dEIrcsx2YaiQoyAW9Fr0b/0rEILQCSPZTYqMjDA50j\nzB0aNSIxP0Hb2+WymIeM4jTONEM6GuuBoerLIVUtUdszpLbJ9EtHX8A1eSZGiJ54d/Z+eHh0M3eI\nREREAJpoqqpUKrUVF83h4OAAlUplkKAAwNPTE9evX0d+fr52XVZWFgCgW7duSE1NRXn5rYqOs2fP\nIjw8HAAQFhaGhIQE7baKigpcuHBBu52sgCBoPoAyGWI1RKWI0dtHILcsB4BtNRIN9+yDezz9cdpH\n0zvkpaMvsFGnlahQVZg7BLIwtT0wAEAVEKhJzFOLCJVAfPf/Yv+oPVgx7CNck2fizOfAj2vyIRve\nDzdK2NONiIgsQ5OzzJhTeHg4AgMD8fLLLyM1NRWJiYl444038MgjjyA6Ohre3t5YvHgxMjIy8Nln\nnyEpKQmTJ08GAMTExCApKQkff/wxMjMz8dprr8Hb27vRxrBEZBhpRSnIFXO1y50FH5tpJCrIBKwY\n9pF2Oask02aSQdYm3LMPurjcq13+969LmLwiXTVVisU/HeJwmTtRM+TIe9xYDJ+2EL2dgzBC9NT2\nWQrIV+HqmTjzxkhERFRD75AZAMjNzcUff/zRrAPl5OQYJKBaUqkUn332GZYtW4b/+7//g0wmw8MP\nP4wXX3wR9vb2iI2NxWuvvYaJEyfCz88Pa9euhY+PDwDAx8cHa9aswfLly/HJJ58gLCwMsbGxsLOz\n2PwPkdULcg9B9/b+yCrVDEeQ2clu84jWJdyzD7q7+iOrJBPdXf1tJhlkjSqrKrU/1yavOMsM6ait\nUiS99PWLqj/kqH1WDt6dvR8ZW/ohIF+FLE8HdOofba6wiYiIdDSZEFmzZg3WrFnTrAOp1WpIJBKD\nBFXLy8sLq1atanRbly5dsGnTJr2PHTp0KIYOHWrQeIhIP0Em4O0HlmPqXk2l1l/XLyExP8G2emmo\n6/1rYtbc0NZUfrq4F9fKr2qXpRIpfFz8zBgRkfURlSKitw1DRkl6g35RdafdrR1y5CEIuHE8BXG/\nbkOyB/CQA+Bs5tdAREQENJEQmTVrlinjIKJWwEnqZO4QzCatKEVbHZNVavqqg6ZuUEhDXi7H/EPP\n6KxTqVXIK8thY1WiFkgrSkFGiaYKpLZflPZ6p6cxuugAjM15E6psJaRn38S5/7vA3zsiIjI7vQmR\nRYsWmTIOImoFOgs+sJfYo0pdBalEhgC3IHOHZBKiUkSFqgLdXf1xTZ6Jhyt8Eexo2qqDJm9QCACw\nN+tHqOuV7/i5dOHwJitg8dVPomhTM6PVnUUmwDWw4e9QI0OO9mb9CJVaCQBQqZXYm/UjnurJL9+I\niMi8mhwyU1dVVRUyMjKQn58PtVoNLy8v+Pv7Qypt9iGIqBUTlSIm7ByNKnUVAM0HXlv45r1uZUbP\nNt1w9TsfuFzKhWrvGJM2ZLztDQrBt13DJNW0HjMt8wabtOr+jvkKvtg36bBlXVdqmojWDhFplY1Y\n6yV8BJmAuMnxLUpS1f/9a+z3kYiIyNRum80oKSnBqlWr8NNPP6G0tFRnW7t27fDwww/jX//6F9zd\n3Y0WJBFZvpNXfsXVG1e0y97OnW3iprxuZYZT5kW4XNKsl2aka24gTNSY8U5uUGzNIO8hcHNwQ7Gi\nWLvO0d7RjBFRc9T9HcsVczF6RySOPnHKYs7x+k1ETfl7bxJ3mPCpX9UzyHsIurbvhkulF9G1fTcM\n8h5i/NiJiIhuo8mEyPnz5/Hss8+iqKgIwcHBmDBhAjw9PSGVSpGfn4/ff/8dW7ZswcGDB/Hxxx+j\nV69epoqbiCxM7nXdmaaeDZtnMTcsxuTj4geZnQOU1QqkeUqR6SmBf74SWZ4OsO/up2kcaGPl9C1l\nquEQgkzA9xP2YvjWwdp1/b3ux1n5GSaRWsLE53OQewh8BV/ttN65ZTkWNSSssSairUljCZ+SXiGI\n2hahnVXrwORfdH5/9PU0+vHROBzMjsPILtH8fSMiIougNyFSVFSEOXPmwMHBAV9++SUGDRrU6H6J\niYlYuHAh5s+fj507d7JShMhGjek+Hm/8uhjKaiVkdjJMDJxs7pBMIqM4DcpqBQBNg85/jgKgBn7v\nrMD2yhz0FZ1NUk5vrU1VTR33zaoKneXxux6GqlplVe+ZWYki2j8UAYfMTCj8/VG6/xejJ0UEmYDt\nj+zGkM39oKpWQWbnYFkzAwkCir/fC8eDcagcGd3qkp6NJXwS8xOQVVLTRLoks8GMYpl5CXD7Mx3O\nHrd6GgW5h2DizjFWd40iIqLWzU7fhm+//RZlZWX44osv9CZDACA8PBxfffUVysrKsHnzZqMESUSW\nz1nmDB/BFwDgI/jCWdb6J1UUlSIWxT8PAHCuBBLXyxD/NfDxPsDf1R9B7iGNfrtqDI01VbUG9eNO\nzE8w6vPVVhvUUlWrtM9tLe+ZOSmTE+CQqbkRdsjMhDLZuP9ftYpu/q39v1JWK5BXlnObR5iQKMJt\n4hi0WzAfbhPHAKJo7ogMq2bWmOKfDmkTusU3i/TvL4oYOvUF/LYOOPM50LNNNwS5h1jtNYqIiFo3\nvQmR/fv3Y9y4cejWrdttD+Ln54dHHnkE+/fvN2hwRGQ90opScOn6RQDApesXjX5j2xyiUsRZ+RmI\nSuPcoCTmJ+BSqeY1hxYA/vmaGRRCCoF9PT4CAPzuXgGFvz8AGLWcPsg9BN3ba56ne3t/q+nfUjdu\nAFhwZL7R/r9qvTv0v+gs+Oiss7iqAwuVYV+E6pqfq2uWTaG2aTAAi2sabKqkp1nVzhojCJCXyzEr\n7kmdzXV/n6RpKdqkWUghEHBNgRvKG9qZuADNNapCVWH033UiIqLb0ZsQycvLw3333dfsA4WGhiI3\nN9cgQRGR9XFv00FneeGR58z6Ybd2KMaoHZGI3jbM6LEkewApHTU/qwICUdLNB0O/G4iHfhqL+2cB\nV3bvMf7sE5J6/1oBQSZgYb9XtMvZ1//CySu/GuW5as+JqXsnQyqRop2snXabKasO5OVyfJOyAfJy\nuUmez5C6n8/TfnCwA9DjQoFJnre2/8vK4Wvx/YS9FjXUonZICWDcpKelOJgdh2pU6az7+dI+7c+q\noBCIXTXJxZSOQJxTHkbviMTEXWMBNfDNmG2ABJi4a6xJrs1ERERN0ZsQkUqlUCqVzT5QZWUlnJyc\nDBIUEVmW5lRanLhyXGf5r+uXzFoSbYry7AC3INjXtGK64QjELPJD3JfL8P261/HQT2ORW3ODnVSR\niT/udTJqMiStKEVnTL+1lKOLShFLf31VZ139Br2GUvecyC77C9eV17XbvNreY5KqA3m5HH02hGLB\nkfnosyHUqpIiolLElJJYbYWIGgAejDTZc0/cOQYLjszHxJ1jLOMmWhQhPXsGABoMKWl1al+rKGKw\n9wMNNl+7cfXWgiCgMO4QJr3gi/6zAPcOvtprYVZpJvLL5dprFYfOEBGRuelNiPj7++OXX35p9oF+\n+eUXdO/e3SBBEZHlaG6lRbhHH51lmZ3MrEMQTFFin1eWgyqotMslUhUezn4Vjx+Zgctinna9r4uf\n0W+2LXlIQVPSilJQcFO3yqBXxzCjPFfd96i+csUNozxnfQez47RNeJXVChzMjjPJ8xrCkZyDsLt8\nq0JEAkB6Oa+phxhMownOOjfpJieKcIuKgNuoSLhFaZqJ1g4paXVqpt11GxUJt+hhSM053WCX9L9T\ndZadXb2w4qXfsH3KIeybdFjn2jSyS7RVXquIiKh10psQGT9+PI4fP46DBw/e9iD79u3DsWPH8Pjj\njxs0OCIyv8T8hNtWWohKETP26f7+K6uVZm18KMgExE2Ox08xhxA3OR4ADN5PpHbKXQCwl0hx9caV\nBvv4Cr7YF3PI6CX+ljykoCn1h1oBwP7sn43yXLXnxProDQ22lanKjDZUp67636439m27JRKVIl6K\nf8Fsw7HqJ/yCHf10btJNnRSRJiZAmqWpcpBmZUKaaP6eScZSv0dK/rE9uD9P00i61qG8A9p+SvU5\ny5x1rsVebb10lq3lWkVERK2T3oTI5MmTER4ejgULFiA2NhbFxcUN9ikuLsbKlSvx8ssvY/DgwRg9\nerRRgyUi09LeBNXo7tp4s860ohTkirlwroT2g7K+fU1FVIraqR4BIGprBEbtiETU1gidpMjdNF6t\nO+VulVqFAJm39vV3bd8N3z+yB0f/8Ru82noZ5kU1oe6QgtHbR1jNUIwjOYcarHvEf6LRnk+QCSgo\nb7zvhbGG6tRVdPPvJpctVVpRCooqi/C7N5Bak8Mq6NwBqvA+TT/QQOonONtn5Rivkak5K08skE6P\nlM6d8dTnv2pnkKmbFFn3x6fan+tXFgJAX6/+ADSJ6dplJkOIiMjcpPo22Nvb45NPPsHChQuxevVq\nrF27Fn5+fvDw8IBUKkVhYSEuXryIqqoqjBgxAu+//z4kEivq5EdEt5VWlIKs0kzt8oqhHzX6ATbI\nPQQ923TDlrUXEVIIZHhKoTyy3fAfdkUR0rQUTdPCJkrTRaWIqG0RyCrJRHdXf7w9ZLn2dWSVZiIx\nPwEPdI7QfmjPKElHgGsgEuacbX4oShELDs/XLjtXAuc2yOB8ESjr6oO/4+IgOgC7Mr/HyC7RRk+K\n1B1SkCvmYvSOSBx94pTF33D4tms4rKq40rgzl3i09Wx0vb7hNIakqSqSQVmtNPuwspYIcg+Bl9M9\nkOMa+j2jmVVp3j+WY5QJh4gIMkF7U117ky7NSL+jRqZ1E6Y6vyM1w0Nqj6uvJ4gqvA9U3f0hzcqE\nqms37WNb5ZAZQUDxpq1wG/cQpJcvw71mdUih5jw4XTPBTHtHV+1DGhviFOQeor3ehjn5Y1+PjyAL\n7dM63zMiNHGdISKLordCBADat2+P9evXIzY2FiNHjkRFRQUSEhJw+vRpXL9+HQ8//DA+++wzxMbG\nQuAfNKJWp26Zuq/giwC3oEb3E2QC/tNxOkIKNcsB+SqUJh5vdN+6WlSdUW8ce1Pf3ibmJ+g0GE2U\n65azV6gqADT80J6cn3z7OGqkFaUgu+wv7XJoAeB8MRsA4HIpD1XJiSZtnhnkHqIz9WVuWY5VNCsc\n5D0EvoJuUmBR/PNGa5opKkUUlOc3uu2xPRMM+v/U2Pn9R0EilNWahuXKaiV+yT1isOczJkEmYFnE\n+wA0DYRP+wDSdm7Gf+I61Ro6s/MIwh03Mm2qL1Kzp9AVBBQf+AXF3+8B7OzgNnGsWYbumIQowjVm\nLKT5ur831QDy6/TS79q+m/bnxnoa1V5vnSuBzSsy4T2uFb9nZPNMPdMdEd25JhMitUaMGIHVq1fj\n6NGjSE5Oxp9//omjR4/iww8/REREhLFjJCITaOzmrbYvha+LH3LFXL2zO8jL5ZiW9Y522tnUjkD7\n8KZ7I7T0w0Kzb1RwK+FRa/35z3SWnaSaT/H1P7SHeoY2GUNdtd+Y10r2AEq6dAKgmXrz5zY5cKhQ\n4P48wKHCNM0zpZJbRX9d23ezimaFgkzAu0M/1Fl3qfSiUZI5tefc4mOL0FgzjCp1FfZm/Wiw54rc\n+gBG7YhE5NYHtOd3/WE5zx2abTXDm9pITTyTXJ0kqEvUA3jw85CaBGMPbVLkThqZNjUDlSooBKru\n/pqfO/tA5dNEBY8gAE5Ot3qJGHrojoWQpqVAltewea4dgOHZt5bLFLdmbaod4vT9I3uwdMh/kJif\nAB8XP811tgDa5LnFv2fmGD7FIVutQv3rTGJ+6+0zRGTtmpUQUalUOsu1Q2NycnJQVlZm+KiIyKTq\n3rwN+qYPDmTHaW/g8spytFMm6muqejA7Dtcdq9B/FjDgn0C/WUCaounZJ1o6La7OOPbblMjfrJcQ\nKarU7dPQWfDRlrJ+P2HvreZ+Ds2/sRJkAv49+G3t8g1HYP+G97TfWA/oNAhnPgd+Wwf8/jnwUEfj\nNs9MzE/QqVi5qbpp1OczFFEp4vXjrzRY38be8Dffdc+5mkljG1iTsNIg3+SdvPKrtsnkpdKL2oat\nw/10p6mtRrXBkjCm5mTkBEndJGibrIsIlGs+iyirlY2+Z82tOAtyD0F3V03So9FeR9WaiYWll/Pg\nNmFUkzemLbkuWSuVjx+qZTIAur81agBnNDlg2MNe59wWlSIS8xOwKP55TN07GRN3jcXEb4Zis9dL\neHr0MlR06woAUPj733rPLC0RIIpwjRwCt1GRcBraFzdKTJC4rD97kaW8F9RiPi5+kEpk2mVjVj4S\n0d1pMiFSVVWFlStXYvjw4VAoFA22f/DBB3jwwQexYsWKRrcTkXWoe/MmL7+GqXsna7/Vbs50riO7\nREMqkWlL6W84Ai8dfaHJP/4tnia2BSXyF0uydJYd7dvoLB/JOaStTpm4c8wdje8VlSLeOblUZ52q\nrRNUfftDdASWf/WY9lvQ4ELA9aJppietdfXGFW2S6W4axxpbYn5Co7NTTNw11uDx1r0R7tq+G7q0\nu7fBPpdv5Bnkm7zkwj91lnOv50BUipi297EG+6rVjSdnLImoFPHv40u0y13a3YtwT+M2VK2bbCi9\ntzOSPW5tq997prZv0KgdkYjaFnH7c0dd798a0rQUSC/dOh+lWZlNVzDcxdAdayHNy4GdUjPMq25d\nlQTAQ0WaYVNVqMKUvZMgKkVtJdbEXWO1v9vOlcCulVfQ9x+z8OAzr8J/YjYG/BO4fxYgOqJFQyJN\nRUF6cvsAACAASURBVHX8EGSXLgEAhNyrWLriAaNfQ21p9qLWLq8sByq1UrtsrMpHIrp7ehMiKpUK\ns2fPxqeffgpHR0cUFDTsyt+nTx94e3tj/fr1mD17NqprvlUhIuvS2Owal0ovIjE/ocHsDo0lDrza\neuHc/13A3LDnteuySjKxK/N7vR8gG5sm9rY37s0ska+sUtRbvlUtIbNzgG87vxZVpzQmrSgFV8t1\np9mt/cY8rSgFcU552iFEKR2B5Mb7eBpMuGcfnRv82iEz1jqOubiyCFtTNxs83mr1rb9TeyYewLhu\nExrsU3/IVUvJy+V477f/aJftYIfhfpH1KlRu+f3a6bt6PlOo32DZoUIBx4QE49641k027I+Hp6em\nR0XX9t0wyHuIzq4N+gY1kdRKzE/AtfxM3J8HXMvP1B0y4+MHtfTWt7qqrt1uX/Vxh0N3rIUqKERb\n0VGXWiLBJr9bMxBmlWjey8bO87rDZEIKAZ+Sapz2AZIqNI9pyZBIUyn5Q3cabtds+Z0lSy2t8oVM\nIsg9BF3b3eqrYy3DWIlskd6EyKZNm3Ds2DE899xzOHDgADp37txgn5kzZ2LPnj146qmncPLkSWze\nvNmowRLZIlN8uz+g06C7PoazzBkj731I21hPZifDgiPz9d6E150mduLOMZCXyw124+7i4NLo+seD\npuL4P05jkPeQBtUpolLEb3m/Nft565fD1v3GPMg9BPd4+muHEE1+8V74+xh/elK7Opf02qqDlg5N\nMrW6jWDrW3xskUGTOHWrUS6VXkRGcRr63XN/g/3udijIwew4VOHWUNNqVGPK3knwcfFDB8cODfZ/\nuuczd/V8phDkHgJfwRfArW/776QpZouvZzXJBmdXL/z4aBxWDl+LHx+Na5CYrZ/E0pfUEpUi3oib\nrx3OlrhehmDHW9Um0rwcSFS3vtUt+3C1Zr0t39AKAlZ88ATerjfqb/dTkcivc6mVSqTwcfFrcCMI\naHos6SSIa6p9fGv2t8ShR669dJNuaR2BSyWXbv/AugmQFg6BqZ29CKjpYRPQeCNzshJ1SqrqJuOJ\nyLLoTYjs3LkTERERmDdvXpPT6drZ2eHll19GeHg4duzYYZQgiWyVKb7dF5UiZux7vNFttb02bhdD\n3RLpvLJcANDOpKGvmVj9G/WD2XEGu3GfGDhZJzlQa0vaN5iyZxIA6FS9AED0tmEYuH5gs9/n+uWw\nK4ev1blJe/uB5Wjn7o3TPsBNR70znBtMWlEKLl2/Ver/1/VLSMxPaPnQJBMSlSIm7RrX5D7GTuI8\n3HW0znJnZ5+7Hgoy2Lthv5iskkzkleXgqUaSH8WK4gbrWsrYiVNBJmDfpMPwdfFr2BQzMUH/t+By\nORy/2QDI5Xd1PROVIib8MAoL/j97Zx4XVb338c8wM6wHWWQYQQRBBFFTxNTcMzQXzAXFcq0ntdLM\nm+ntmvXUU93bquUty1vaZnrdzY3cwzV3xC1EBGR3AFkP68wwzx+HOXPWWZiB0M779fIlZz8zc5bf\n7/v7fj+fpEWY9MtYi9tydYSMpBQlw+POXfr8w4u08MowZcjxOuZdI9tcKcefQZauGGc7seeVRXZG\nRw9TQFNn0CGvKgeEksBzPeex1q12AR0g7jefmla5qfDrlGPUc7MNlh4phsQiz58Kjt72BU6FAIez\nfjW/Eaf0R3H2jG0lMASBst0HoO8UTGnYxMf9Za+5B5200lRWOWh25V1JWFVCoo0iGhDJysqyyUEm\nNjYWmZn8OnAJCYnm0xqj+2mlqcglcwWXbU/batU5MNcxBkKYCOmJcDvqI0NGO6zj7qH04GkMGMmo\nuEOXAvVV9wOhJJr1PQd5BkPpRGWIKJ2UtCWxpkaD4Vsew8zEBBRWF9DHbOnMjEjfKHT04GfyWVPy\n9Gdh7tozIih62Uy42SgdiSDkk2xtl3s191CtrbbrOKV193nz5DI5XOVu2PDHD7xlQiVrtpBVkYl+\nP/fC2J2xGLF1UIsFRdTuapx45hw+nLkdBoUpyOe5eIFpFJwZNNBo4NcnCu2WLIJfnyhk3T7T7OdZ\nSlEyXbJjvIeZlNeVs6bfOr1c8HsoqyvFTRVwqylRJ93PCRVdGM8KgkDZrkRUfr4GZbsSocjLYZVy\nuH/xGaB5MFyBHMmI9v3x+WHT9G1foF/cIqx78kfWeq5yN5BaEj/eWM/bB1NjytelPX57+neo3dWm\nFdpa6RFB4J1PJmHAPCDmReq8/dxVZjfhlv44nzll82EVeTmQ5+bQ+2gL5UMStiP2TrYZsWCzVIol\nIeEwRAMirq6uNgm9ubu7Q6lUWl5RQkLCaiy6ITjoGF5Kb8Fl6659TVslAuKBCmZwQwhjbTkTbkdd\n7a52WMc9rTQV2ZV3RZefyTuF0/kncTr/JDQ1GtTqaunv2dpgzLXiFDr4o23U4lpxCkgtiTHbR9Cu\nPEa6eLXMb8fEqMni56aij2nMdGAGf9oSkb5RCPAINLuOrlFndrktJOUcMzsNAHqDzm6LZF9XflmM\n3qDHxN1joam5x5ovgwxKJ2ccyT6E0/knbQ5maGo0eGxTH9yvo1IesivvIinnaPNP3gKEkkCfOl/I\nGO5zirxcQetZ2faN9HoynQ7djiY3O+hZSBaKLiO1JP73FNupqLC6AClFybysmeIaSg/NmPfaaGjE\nteIUxs5I+MTHod2SRfCJj4MuKJjOGDEA8Fi9En59uv/lgiIjawLRjRHn069eB5UqDIezD7LW23Nn\nFy9bzYh/U/Cjvasfdk7ch7yqnDavaTS7/yt0EAcAxoaON7s+M8PIoHSGx9df0Jo0ui7h0EVbzj5r\ni+VDErZjfCfLZVTwmDlwYjViYsNtUIRYQuJBRjQgEhoaipSUFLHFPJKTkwV1RiQkJOykKS5Zp62z\ne+RaDG2jSYTUox7on0f9X9FQgfSyNIuBCuOL/6Ohq+Dnyh9B83bxoTs/5lL7HdVxj/SNQhevcNHl\nqy5/TNlA7hmP3j9GUo4mDSQSZyRaHYy5U5bOm04pSkZ5aR79/cllcmqheNWhwzA6mJTUFsPfzR//\nHb+jzQVAuFRrq6GpNnUsVW585dnsyrsOy65RcUZ3Ve4qnhitQqbAyJDRdh1HKNACAJUNFbx5Bhiw\n9MQrtDWpVQ4pDBIz9sLAsUo5lHXAthO2Ek2NBptSN6AwuD10fn6sZQYnqjlhUCihC6IyLkrK2dk3\nmrK7zQp6ZlVk4uVj8+lpuUzOyvZJK01FaUMpb7tXf3uZ5zoT12UCehYDkU2d+8j7QDtGyQxP3DMv\nB2WHjqN64WL6NpbptHBJfDCtkpuLskcMGsKpZ2pDeDj8hsQBACaGx7PWmxgeL/r8lUGGjkQQ6ipK\n8Obnw/Dsj7H4+6cDWsfOtpnU6dmlV7MOTBN0xaJpKv2p/HwNZFrqvSrTaamMoyMnrct+aYPlQxLN\nI5/Mg95gsgtPL0uzaXsxseG2KEIsIfEgIxoQmTBhAg4ePIjLly9b3ElycjIOHjyIkSNHOvTkJCT+\n6jCdHfKr8zBuZ6zDR9TSSlNRo68BQHXijWKDF9dR02fyTlkMVBgFUpefWkqXkTAxbsfUEIjdOgRD\nN/dvEX0UQkng08dXW7VuIyihM03NPby4/0Wrj2HMxGBOy2tqWd+fa50egHCGjKNhlv0U1RZh6t4J\nbX70NTFjLxqhp6endOVr2TjBCUGewuVPtuLKEUv1cfUFoSSwP/4IPXrt6dwONXYGHsXKtazB1mvF\nGOTxqAeGZwHDM4H68pJmH18MTY0GMRt6YEnSIkTv7I87O7bAIKcCfgYnJ8iaXOZkOi0U6VSjnwxm\nD5K8V7wZ1dpqm4Oem1M3sqb1Bj3r+o70jUKIZ2fedjlV2QDYrjM12mrc4Ah8+veNpbfRBQXDoHSm\nPpfSmQruEAQa+vZjn4OqhW2j2hoEgYrDJ1F24BgqDps69mX17EBUWX2p6PNXU3MP5ffzcHEdcGad\nDjmrgR2rc+E3OrbNjnBH+kaBcGJfqysvfiy8srGEoboa+pDOJnHUrhGonxhvW2CjrZUPSfwpiGUL\nSVlEEhKORTQgMnXqVERGRmLevHn4/vvvUVlZyVunsrISP/zwA1588UWo1WrMmjWrRU9WQuKvBlWD\nahoJza3KcXjHmjmax7VG7FFMZVNcKjRvC8rsjBfWFPAETfPIXJ4dY1ZlJq3f0BL6KD4uvjZvk1eZ\nZ/V5pJXeYk3nk3noUcT//gCTk0JLwi3TaIlrxdFwAwebb/3MW6cRnJKGZkJqSbx9+g16OtQrjC4p\nulB4DkU11Ch1WX0pHtvUx/wosAUGBg42655jjnbOXjZdKz6uvvCoB5K/AY7/BBzfAPzw4TWHdzCP\nZh+iM8m0jQ04KLuFkpRbqPx8DcrX/cRat6KCKm9JLGfblnYggZ/OfWHbgUkSL94LwUvnAf8q02zu\n9S0kVivE5tSNPIHPnEZTLYgiL8c0sq9tgCKvKXvE1ZW9I+70XwGBTnpZXSkrq7CQpHSTov1j0ME9\ngLW52r0DehU70c9Il6ZYKJGV02ZHuAklgUi/7qx5ORXZ/BUZJQx+fbrDJ3480NiIsl37pSyPNoYx\n001T0/KZSdx2iM3tErFsISmLSELCoYgGRJydnbF27VpERkbik08+wWOPPYZx48bh2WefxezZszFu\n3Dg89thj+Pjjj9GpUyf8+OOP8PYW1iGQkJBoPgq5SbywJXRECCWB3ZMP4N1BH0DTqb2gNeLbp1eY\nbUAwNUQ6enSksy6MdG4XikjfKJ7WCLMhbWi0XrPIEqSWxNP7JjVrW1e5ZctVTY0GX1xZxZrnIndB\nZqAb7/sL8Ag0OSm0IL8XnGZN+7ur25SjjBADAwfD380kqljRUC64Hrc8qTkws60AYNXjX9C/ybl8\ndsfdAANGbB1kV1DEVW5dh5l5DwBAN2/bfrOuPpHony9DBGOg3idX4/AOJtc5Z1DgEECtpka+OUU7\n8sXzce36QSiDw1HoQc2rlwNrDwBzF61BUupu6/RSSBI+Iwah2wuvYO0BIGe1KSgS4BFI22WP3v44\n3vl9hehumHo6T4aMAWAS+Kx3paxijaV8FV2CpZFXG9AUZbCy4j5JWgFSS6JaW00HGY0sjF6Ma6pG\n+hlZ31RR2BAe3qa/5xlRs1nT07pN563DLGEw2jYrskzPD6vFLyWhzBYlqyITfTZEYUnSIsRs6NHi\nQZE9d3aZnbYKsWwhKYtIQsJhiAZEAECtVmPz5s349NNPMWzYMJAkicuXLyMlJQW1tbUYM2YMPv/8\nc+zcuROdOnUytyub0Wq1+PDDDzFgwAAMGDAA77zzDhoaqFGb/Px8PP/884iOjsbYsWNx4sQJ1rbn\nzp3DU089hd69e2P27NnIzhaI5ktIPACkFCWzxEHfG/yhwzvWxnKXd35fAUU7H3z4SQLLGhEALhdf\nbGpAdBdsQDAFUt8b8hFv+dSIZ+jR3EMJx7EpbjuvPGfW1ji8eeofdnVCjZwtOIOi2iKbt/OoB/7x\n2SDcyjafEZOYwdYPkEGG+IgEhAfFYPrfw1nfX3GN7edhK6SWhL+7mi5Xksvk2Df5UJvXECmuKUJR\nrel66twuFCM7PclbL9ynq93H4roaMa11o9V9eevX6GowePOjzWowc4MvYgiVqF0oOodhmwdYXe6U\nmZ+CXvfYwUR9xyCHdzC5zjmldfdNo+Jz57BkcjpVAb3GTsPrL36DgGpAKzNlA3QrMWDVz3MQv2c8\nYrcNMfs5FSnJUGTfpadd9EBcU2ysuLYY1dpqVtaZEB8NXYUj007S98KZArbrh86gw7XiFLqU78lf\n45CXmMgfeXWzHCh9aLChUx5T6sLKilPnlCCtNBVHsw+xAuN+birERySA8FbT2TnBr1L/958PkC4t\n9WHsZ3LEFAQ2uYV4OXtjSNBQ3jrMEgYWtbXWi19KQpktCqklMXZHLC3UrW1ssFtA2xLTo2aZnZaQ\nkGgbmA2IAIBMJsNTTz2F//znPzh58iRu3LiB69evIykpCZ999hnGjh0LmczxioGffPIJjhw5gq+/\n/hpr167FqVOn8NVXX8FgMGDhwoXw9vbGjh07MHnyZCxevBi5uZR1Y2FhIRYsWIAJEyZg586d8PPz\nw8KFC9HY2GjhiBISbQ9j+rGROl2tyJrNh9mhyKi4g04B3Vmq+oBp/FfbqOUFA4wQSgKRvlF47/f/\n5S378eZ6WisEoD4Htzznkfx6rLu+FgM2RWNfxp5m619oajR49lf+CJ4lmJ1Tv7EjkV1wQ3RdbqnH\nmthvoHZXg1AS+GXWSfQeu4D+/nQGneh35ghILYnYrUMwMzEBjU3OYMHtQqByF9Y4MCdq29pwtSHG\nhT6FyRFTeev5OPvYfSxz9sMBRIDgNrrG5jnOUJbMzhbXEypRA6gSswOZ+y0fiCQx7JlFWM2wQ61S\n+aD0YBJ71NABo87cgFKkbxRrVJyLqgFQNMVplAagoOl0mJlnWRWZPPtcFrXs551WBiQ2xcZ0Tc+i\nIM9gKGTCDneuMlfEdZlA/9aaGg0+OP8+b73cyhyWHfCt+hzeyKsuOga60DB62vPtNx7ODquNnfLI\nwQlI96eyGI2/ravcDSNDRtP3gFymQGL8Eajd1fhg2EqT/W7TLXKnFTSW7EXuRKWzVDSUiwZKqz7+\nDGXfbYChyXHRoFQCdXVWi19KQpmOR1OjwffX1+FI9iEcyExEaT07sMvNfHM0Knd/fDd6Axb2Xozz\nM1MQ6hVmeSMJCYlWx2JA5M+gsrISmzdvxvvvv4++ffsiJiYGixYtws2bN3Hu3DlkZWXhvffeQ3h4\nOF544QX06dMHO3bsAABs27YN3bp1w/z58xEeHo4PPvgAhYWFOHfu3J/8qSQkbKO6XIM9//07nUoP\nABnlGQ4/DtV5oxpwSiclbT8rBtepg0lKUTKyq+6y5skgQ0kt1dNLL7+NPXd2ITFjH26qgFsM2Ytv\n9pvKBuYemo3HtwxsVqc9MWMvdAbbrVq5ndMV344RPX4vVTQUTVZ6CpkCwzqNYC3fnb6DNe3p7Gnz\n+VjL2YIztMWlUc0+qyITP9/8kXf+TFFbRwvZNgfuaNmzPZ/H2LDx8OYEQJ7aPbpFU5uj/WPg68K3\nygUAT0U7m/eXV5XDcm5iYiyR8ayXYcWz2wRL1ABg8W8LLH5mRVoqvHPZ6+xb/jSgNpUhOWrUWSig\npHN1gzWFbloZMPh/wMs8AygNClG4WRmcg6ncVciryoHOoBXcvM5Qh7E7nqCv86PZh2DglPMFenRE\nXJcJ6OodAY96YEp5J3RzERDFJQhUrTLpnygy7jyUHVZbO+Ue3mp8sepZ1m+7PW0L1O5qJM+5ic9H\nrMHvMy6htO4+SC0JVwVVSuZRD1z6lgpAX12nEP7O2wgpRcksK3Vdow5bmMFc4z0WPx6eb6+ATEtd\njzKtFu3eNukW6bqYLw2ShDIdi6ZGgz4/dcfyU0sxMzEBy5IW89a5dM98Nqg9GN+3cw/NwZHsg6KD\nFBISEn8+bTIgcvnyZbi5uWHQoEH0vPj4eKxfvx5Xr15F9+7dQTBGbvr27UtbBF+9ehX9+pnU4N3c\n3NCjRw9cuXKl9T6AxENNqwhykST8Rsfi0NoKOpUeANZf/4/DO7HpZWnQNlINOG2jFq4KVwR4BIqu\nX6ers2n/BhjoEVyFTIElSYuw6852VLsAL8WZ1ou8bxohByiHiC2p/7XpWAAEXW7EYIq/3uQ4T/zu\nVSk6ek11wqjgg86gQx6jsZxWmoriumLW+lUNVWgp/igRzmR55/cVvJIEZjZQSwjZ2kqoVxjOz0zB\nqzHL6NEzQklg1Qi28KbeoLc7tZnUkhi1fRjPhhWgOvsHph6DTMAf+ZML/wJg233PzKYIbRdGX5PM\nLKRL653QW90HhhMpeOa1MF6gwJrPrIuMQm2QycmlXg50G8jOsBHt4Doga8R9zy6LjtI6AANelONu\ne/AyzwAg9b74NaiLjoFOZYoSKWEqmQEo1yBLDkR5ZC59H3NHg9XuHXAo4TjU7mrsHrUNOZvU2LE6\nF0FxcYLfiy465qHvsDanUx4YEMX6bY2/idpdjYnh8ZiVOI2VIQgAjxYA3ZoG67uU6OCSYr9wcmuS\nX5VP/826x/JNVtMGuRxyxnTVirfN6z1IQpkO5Wj2IVawtLaRn2F7uIUsygH++3bbrc3Nbr+1pcxO\nCYmHkTYZEMnJyUFgYCD279+PuLg4jBgxAh9//DEaGhpQXFwMf392lLV9+/a4d+8eAIgu12jars+9\nxIMD03qyJQW5FGmpILKoTjYzlb6oRiM48m8P3BHaOl0tDiecgKtMuGZ+8bEFojof0f4x6CTQQTE2\nSriZG5c6QnSEHABWnF5mU/mMpkaDt07+gzUvzKsLa9por9rVOwJnZybj1ZhlAMBznqh2AWpFSpSY\nJRFKJ2dWp0xIlHVAwECrzt9WSC2Jr698Kbo8qyKTFfSI9I2iM4BaQqC3OYR6hWHFY2+zUon7BzzG\nWy/Su5tdx0kpSkZGOaXrwbRhZZ7HyqH/5m13uyINp3JPoM9P3bEkaRH6/CSso8OEUBLYNSkRn49Y\ng73xh5A85w/MjJzDykKKKNaj8OIhqFRheGneRl6gALAuO8WgN2WiuOiB+iyG+xFJArW1LPtPnW97\nuHy/Dj6xQ2zKGhHKLqqZPstihsjsyUBM7DzR5d9d/0b8/iYIlO0/AoOCysbSKxX4lSEn89bpf+Bk\nbpLFc79bngUAtKuVkc9GfAm1uxqklsQHX4+Hbw71u4pmRvwVOqzN+Ix5VTkscWBmgPhswRlWp5Au\n++RcODmMbdoa0f4xLPFnABjaaRj9ty4yir7HmMj0eugDTIML3i/8D5BlQSNLEsp0GCNDRgMiIVvj\n9dq/3SMtdnymgx8ALD+1lBeMt4a2ltkpIfEworC8SutTXV2NvLw8bNy4Ee+++y6qq6vx7rvvQqfT\noba2FkolewTY2dkZ2qYUxdraWjg7O/OWGwVZzeHj4w6FQu64D/IQoFK1XKr/g8je5G0s68nz909g\nbshcxx9oSH+gWzfg1i1keQF3vUyL3vl9BdbfWIsL8y+gA9HB7kPVZbGzF+qcqtAzJBwze8/Adynf\n8dbXQ4+Je8Yg/ZV0EM7sRpsKnvhp8o94YsMTVh3bGIToUUwFQ4Q6hXMPzUaYTxjWP7Ue/Tr24x3T\nCNlAYszPj6PWwA5iVDZUsKYHBPXHm0PfRA//HiCcCXQP7oL9d3fjTukdurbdyIrTyzCh1xjeMTPz\n/mBdB9Xy+1CpqIZP4hW+ivyRgv14tMsjoufeXE7+cRhlDeIlB17OXhgS0Z8+rluDDLKmMLjMCVD5\neTr8nBzBjaxLvHnrUr/C0G4Dmn2+3qQ7e9rLnfd825axiTXtUU9dm3N3TIbOxZgRpMUJzSG83P9l\n0WORDSSmbI3D7fu3EdE+ApdfuIxBYQOw+9oGpPpRQZHb/nI8MmYKCF9PPK4aiGlR07AtdRtrP/OO\nzMHVsKvo1aGX8IEy/wAKTdlI+b4Kep8gSWDYE8CtW0BEBJCYCEVtLVRD+wOM96Ei/TZw8yZUAwaI\nf3mgrnlmx7aoMQeh/QcAd+4AK1dCv30b5PfZ12K9DPgtDHjVPwS4KbzfsvpSal8qkeOregO5uUBi\nIn4NN0BzfD69KKsiEycKj5o9bwD4KXU9pj86Fd5e7GsgoH17qFSeuJt2CW9tMQVL6kI6wmdIf+FO\nqcoTCBXWnHlocJMBRR7UZ7WiY740Zi4Wz/sCkfeBtPaA8qW5UKk8cY+8x9JzCvcNR50T9b651JFa\nN/I+kKFSoMekGdR124pY275RwRNXF6ag77d9UVBVgEDPQIzrOQoqoml7fTVQL5A5GR4O+YIFwNKl\nAKgAiWriGCA9XQp4tAJ6shq8yBtMmXpRJcDtvf+CW+oCEL72t6W4qOCJdRO/ZbWHMsrvIJW8gnER\n46zej+CzV+x5aemcpDa9hIQgbTIgolAoQJIkPv30UwQHUyOvr7/+Ol5//XVMnjwZJGc0q6GhAa6u\nVF2qi4sLL/jR0NBglSVwWVmNgz7Bw4FK5Yni4pZL9X8QGdB+OJROztA2NkDp5IwB7Ycjq6CQHm2O\n9o9xmLNHyYbv4fbkIISWA8d/Ytfe51bmov+3A3DimXN2H6+7Zx/W9KO+g1FcXIVZEXMFAyIAcI+8\nh9O3L6Cvuh9vWWeXbvB382e5vKjc/FEs4vrCDUIIkVmWiSc2PIGu3hE8QUwjlzUXWWnMRnr79cGx\n3CP0dDsnH4S5dEdthQG1oK7vw1NOYkvqJqw4/XfWttkV2TjyxwkM6TiMNd/fKRhdvSOQXn4bXb0j\n4O8UTN8rvnJ+w+qD0x9g6/VtLLcLeyG1JF7c86L5dRpI3C28B3VTVsyR7EO4U0plSdwpvSP42Vob\nUksirTQVkb5R9HdTXsF/Fv9y6xcEfhqICeGTMa/XS6jT17K2sURnl27o4hWOjIo76OIVjs4u3XjP\nt4lhCThfcB4Au9Gc6qdj3X/F5RVmn42n80/i9n2qAXv7/m0c+eMEhqmfRIObEv3ma9GrxAlfvHwK\nPnoP1DbtZ2nMCl5ABACG/TAcV579Q/hz+gfDp2sEFOm3UROghu7XQ6ht2qfi8kX43GrKFrl9G/qX\nFkCeyx+F13WNgKJHD4vPen+nYHTxDkdG+R108Q43XfPt/IH3PgFefxu6S2egOXcQ0Z9Rzw0XAzBQ\nF4AQd3GXIKWTEh769uaPL/cAJkzDvpOvs2a3U7ZDtG8/bAP/e2Nytegqgj4Lwrbxu1nzPfS+KC6u\ngvv1fLp8AwCc8+6h+O49thbLX4UmPQxF+m3oukZYlSXieuE2wpq+v8j7QMGF2yh2C8W3KT+wsgJn\nd3sew9RPwglOqHZpRN8XqIDjpKfexDzGvdAa2Nq+kcMDh6acwMhtQ1FQVYDotX1wdNopqBs94DO0\nP6tUxkjZJ6uh6xgEPzDyFO7dQ9npC1QWiESL8tN14ZJbVqZekR5nD+5E+Kg51AyShCItlSoVY/rZ\n4gAAIABJREFUsyNoZXyvBXkGI9QrjJVVO2HzBPw+87LVAquiz14bkdr0bKTgkASTNlky4+/vD4VC\nQQdDACA0NBT19fVQqVQoLmbX55eUlEDVVGesVqvNLpeQsAemUFzynJvwUHogdtsQxO8Zb5WNpC1c\nvbwLncupv5llM0Zyq3Ls1oAgtSRm/TqNNc9or1lWL5554Obkho03fxIsnSGUBLY+tRtyGZVtpXRy\nxv74wxjecQRvXRlk2Dh2m6igJTMNGzCvexHpGwUPOb8BM6P7bNb04r6vCZ7zvF4vYnDHwbxlfz/x\nKu83NedYkieS+p1RwS/TaC6klsSeO7twv+G+2fX00GPX7e30NlxRObGSIFvJqsjEB+fes9kyWSwV\nONo/Bu2U/HKRKl0VNt3agBHbBtmcPkwoCRyZdhIHphwTDUw9EzWDttcUc4ABgE8vfmDzfU49O/7A\nP8eswbdvpiEksCdreahXGCaHJ/C2q2gox9mCMyIfylTeUH3mCtw7mhrYLC2ITp14wRCDQoGyTdup\nDi9glZ6IVq9l/c89F8Xjo9Fx0ftoCKeypapCg7D65ZMYGDgYHgrhzoW2USt8zwhonDzGuT9JLYnV\nySvNnrMRvUGP2b8+zZqXlHMMAHDILRcFHqb5Tno9XI62rB1nW6U5Tie5lezfL78oHaSWxNoUfjmf\nh9ID+ydTtkjGYHhs98kOOPOW50jWQWhqqPJsTc09jNw2FNqbyYLBEF3XCOiiY6Aovc8q2tAHBD6U\n2jNtETE9Ma5emFd0k7aQgwSomXpVE34ZjUYDW8hZDz3ido2y7R3SlOhSp61Dtba6WeclISEhjmhA\nZNy4cTb/i4uLE9udTURHR0On0yEtLY2el5GRAQ8PD0RHR+PWrVuoqTGNIF6+fBnR0dEAgN69eyM5\n2dTpqK2txR9//EEvl5CwFa6YlYfSA/7uauy6vR3/OvsuqxMo5u7RHDo+OsasvobR+tIeUoqSWXX1\nCpnCokghQImTbbq1AQM2RfM6waSWxAuHn4PeoIe/mz9OT6dU3E/k82v9DTCgoqECl+Zcx6a47SyR\nU6YApVFY1glOZs/PiWMB7uXshRHBI3nCnWK81P8l3rwMEUvIam01bpWm8honz/Z8XnT/jsAYRFiS\ntMiq9Xff3ol/X16FpJxjKKwpdPj5ZFVkYsCmaKxOXil4PZhDTOSVUBLYM/mgxe3Ty28jKcdyyYS1\nEEoCp2dcxFex3/Iazcz7r0ZXLR6kABXQMV5noV5hiPaPAUAFRWZGzaEzdrgsH/Cm4PzzBWZc0sQ0\nB5haEDv2waCkSkmNCeT6TsHQDWwKMPTrZ7ETkJRzDDlV2QAowWNjMEHofCoOn0TZgWOoO3YBHt6U\nHfUnwz8T/Qi+rpyAqEjHZERwLHxdfOnVGtGIIo6eiwwyQR0jAKjRszOPSmqLQWpJdFB3xeDngYam\nx49eqUD9yNGi5/sw0xxRVfXQCchqb0o47v3pt7h+9wzuNT1v/KuAuVdk+OrQCoze/jjqGtnlJcYg\nvCOEflsKUkvijVPLWPM0Nfdw0x8s/RBdSGeU7dpPZ9boIqNYds1OxcVAtdShdSgi182t+38Irs7V\nC0upoZSaHWV7zNSryqrIRHblXd46JbXFVg9opZWmIqOC2l9+dR7G7YyVdEQkJByMaECEIAh4enra\n9I9wUE1k586dERsbizfeeAM3btzApUuXsHLlSkybNg0DBw5EYGAgli9fjvT0dHz77be4evUqEhKo\nkbUpU6bg6tWrWLt2Le7cuYM333wTgYGBGDiwZUQNJR5uuCPYWRWZGLgpBjMTE/DO7yvw3Y1veNsI\nuXs0h32aYzyRTyNPhozF/w3+l137B/iCqkzHlGj/GIR4dra4j/fOvC3qZFJUW4TSuvtYdfFj0e0T\nM/eCUBIYFTIaZ2cmo50zJZgiNELfiEZREcW00lRU6djpoLsnHQChJASFO4WY1G0SXGWurHnuCg9e\n4IkS1+3eJK7LFtkM9QpD0rTf4dPUcTOOUnXxDqc7xvbA/H6t4UrJZfzr/LuYe2g2b5mbQlg41xbW\nX/vG7LQ5mG4s3ABfD7+e6OoVYXEfcw/NsSoIY85lhgmhJDA2bDzcvf1F7z8AuFOWLri9EWNwz8mG\nRMxQrzAsi1nOm59WKtywt0hTsERReh8yLVVKagwZKrIyqQ5AWiqlMwLznYBz+WfMTgsdlxmkGRs2\nHu1d/QRX35y6kfV7iHVMCCWBZf3eYG3LDJD4urTHuZlXcOKZc+jm0138/JpYeekjjN7+OMK9uyLP\nT4FOS4D5E51w+8zJh6NcpjkBhmaIqnp4q+H6+ff0tPPdu/C5Sd0f/lVAzmpg/R4DclYDFbm3Uaur\n5YtSO2h0vqVIKUpGfWM9a567wh3hQTEoO3KSCoLs2o+ypN+hGzLM9L0RBGqeM4kKy3RauCTubc1T\nf7ghSXiPGAifsbFo9/hjSMk6aco0VPcV3cyYnVTtYnqWO8r22JrMSxlkVg0+AdR7MsDdJM7riOxg\nCQkJNqIttW3btmHr1q02/3MUn3zyCSIjI/Hss8/i5ZdfxqhRo/Daa69BLpfj66+/RmlpKeLj47Fn\nzx6sWbMGQUGUCEFQUBC+/PJL7NmzB1OmTEFJSQm+/vprODm1yeogiTYOdwR73M6RdMqsObIqMu0q\nj9DUaPDppQ9ZL20mh7MPYGZigt2Bl+Iadh2OXCanX9KEkkDSM79jU9x29PbrI7Q5ACDx7l5WB5Pb\nyfV1bY9ttzeLbt+9val0INQrDGdmXIKXs5foCP3rJ14T/MzcUeaORBBCvDqLHlcIwpnAhK7xrHmN\nhkZeFkhixl6WVXFiBruB28OvJy7PuYEDU47h9wknsFm9DHtH7XCIfgjz++XyXI+5WDVc3HUGMJUh\ndYKvQwI0bgq2UKWXi2W9JiPmSo8A4PlHXhDcrrNnKGt6bbL5zwxYdpnhrltcWyR6/wGAn5tw5x5g\nj+hlVAhnGIkxqBPbGrbzfWBJ4n3L7hRmYDb0jZkixga/LjKKEnBG00h3ba1gZ/SxjoPMTluCUBI4\n/sxZBHjwBUlXJ69klT8xXTt0XcJZHZPbZbdY25YySvvcle5QufuDUBL47HG2dbMYVJbRMegMOhR5\nAuv7NOKWUrxc8IGBJGknIY/HeqEm34rrxxhAAWx2OnElfFnTXXy6oot3OOLSKfcjgPp/Tq4v3BRu\nLFHqvKoch43OtxRCndx5jyygnlkEAd2QYexACAN9OFtDR9/Juo6whGX0RxOhzKYy11xycvD1SlPp\nsrerde+iIM8mETMHuEiRWpJXQiaEAQZcKDxr1T6rtdUoqmUPurQFhzgJiYcJh0YJMjIyHLYvgiDw\n4Ycf4vLlyzh//jzeeOMN2j0mJCQEGzduxPXr15GYmIghQ9gNyOHDh+PgwYO4evUqNmzYwNIiedCR\nvMhbF2bns6NHR9yvo1IWuNoWQtijz3A027r6dXsDLyOCY1mfRW/Qs+r5jZkbc3qYLwNhlpVwO7m/\nF5wW3U7hpOCVmKjd1fh61HpBG1wAqNaRguUK3OPkk3nNGkVZ2o8t3Finr+VpVajc2fVL3GmA+h66\nuQTD58nH8cyClXAZ0R/V5fbbNBu/X6NdsJH2rn54e9D7CPUO5W1j/I39q0xlSEe+KofMztRtUkvi\nv6kbWPMCPAJF1radp6NmwMPJgzf/blUWa3pD6g8WrXCzytnbcLOjbOW9s2+LPoeDPIPpsg1bS9uY\nFp/dC4HML4HROy7Ab0B084MijIZ+SfJNdoOfIICLF1G2az8AwCd+vOAIff+AgVC7U4LBIZ6dMSJ4\npM2noXZX48yMy5jfk1+all5+2+KzjNSS2Je+W3R5HplL7+PRgP7YOFZcbNWYwdXVOwKd2j08bQQj\nirNnoGi6XtyLSuA8PMbs86e6XAO34X3hMzYW3rGDbc7Q0EXHsIJYyr6DcSThJDpOeQn1TeZ99XLg\n506l6EgE8TLDHDU631Lws+lkmN+bfx0LoRs4mC6b0YWGmUrVJOym9OQ+1vRj+VS76EDmfrx9+g2R\nrdj4uDKCeXbYHhuzEJefWmrV+qdyT1q13pbUjdAb9PT01K5PO0ycXUJCgsLqgIhOp8OXX36JadOm\nYfz48SztkNGjR2PIkCEYP358S57rXx7Ji7z1YXbuX3uUSmUX0rYQ4h7ZfL2GkSGjIeeYQDE7tcxg\nzJrkf1vsDIpxryid9Vm6KgMFO29CnWwmfq5+rO0IJYG+6n4glAQGBQ7hra9yU+GjoatwZU6qoJ7C\nwMDB6OIVLjpCL1SuEK1iZzsEe4Y0axTFXekBgK1FUlCdb1YzQozCi4fQpYgaCe1S1IDCi44RaiSU\nBJ4MGcOa9+2oH0AoCXQk2JY9zOv13HpTGVJkcaPd55NWmoqSOnaWUbKGb5krhqUyFkJJYP/UI7zt\nuAHJRjRic+pG0WCxpkaDpSdeYc3Lq+ILIRqJ9o8R1aEw7fOeYMCN1JKI3x2H3KocdCI6YdekRJsa\nr4SSwOdPrIFHPeUuZbwSZQDcN2+0ej/8HTc19NVqfoOfIAA3NygyqKwW7gi98TNpau6hE9EJ+6cc\naXaDnFAS8PcQLkdZenwxSC3l8kCfS8Yd+lzSSlMtCgkzae8uLNYMUMHYXRP341DCcfRSRdOlbUon\nJbr6RFp9jLYKV0Q3oLIRF/b9W3BdUkvivU+Hgcil3lnKrCzoTotoxIhBEFTpyIFjKDtyEiAIEEoC\nTw9fiuBXgecnAMGvAhpP4GDWr/zMMAeMzrckXX0i6WvECU5ImnZGVAuIB0Gg7Nhp6rMdO93mPtuD\nTGJ/P1oXyQBgwyPU36/9tpjO0hPCWMooh9xh9/vZgjN0FqI1yGXWdcGKqtntu/K6MpvOS0JCwjJW\nB0S+/PJLfPXVV8jPz4der0dWVhY8PDxQV1eH7OxskCSJZcuWWd6RRLMREyCUaFkIJYEgz2C6Q2XO\nfYLJ0hOLseS3RTY7bwDUSOrRaSfhpaRSPjsZfOlObc5qdjDmt9wj6PVjBC4VXrD5OLLUG6zPsko9\nX7CjE+0fw3OCYXZKzame3yi5zpu3qM8SPP/IfNEGJdMRZOdT+3jLG/T1vI7veU766dxHXmxWp43K\nzjHw5j93YAYdeOKWGnGnjXhFD8GtpsqKW0w1ewewP5NdpnMq/wQAfqYM83oNrQCyKIkWpPsrENDP\nPuHIIM9gyDjBoy1pG60O0FlTxlKnZ2daiQUk/315pWiwmFvSBADhPuJWsISSwIlnzqGPSrykyMvZ\nS7AGnPmcziVzRV2HzDEwcDD6lrhAxdCeNAComT7L5n1ZC1P8URcaxhqhd8RnYhLm3UVwvjHjTSxb\nINI3iqVrxA2Mqd07sMrAuLX3TIpri+CmcAOhJJBelsYqgbP387UF6uMmQMdp4a29ukbw3sy6fQZj\nT7ED+GXXbQ8AC42uq93VmDPiDfwQAxQxXC6ZQXNz27cV8qpy6GukEY2855JFmgRWFWmpbU4f5UFG\nR5axgsZEUyJFvcH08Gyn9OJt1wjK+UUPPa4Vp9h9HqSWxOvHX7Vpm61pm60a2JzRfY7ZaQkJCfux\nOiDy66+/om/fvjh+/Dh++OEHGAwGfPTRR/jtt9/w5ZdfQqvVwsuL/9CRcBzmBAj/qrRWCRGzhMWc\n+wQXMScWS5BaEjP2T0WFlvLdDcgvpTu1xnpsYzDGox7ol2dAwpaROJV7wqZjLL33LeuzGKJ6Cq5L\nKAkcmHqMHlXhdkqdampFR8v3pu9izXOCE+Ij+PaiQsfsq+6HoZ2G44MhbGvNf51/l9fx5aa9m+vw\nmmNkyGhwM0QAqqNkvA7iukxgjSjHdZkguK+cxvt4tKns59H51LQjMNruMjFmjIwMGQ0Z49HOvV4f\nm0edz451b8LD2z7hyPSyNBg4wSO9QW91yZc1cDVTxAKS1ToqKCcULOaWNDnBCb1U5p3HCCWBz0as\nYc3zdTYFBSsaKjB2xxO8Z0+kbxS6eFOlA128w5v1nCaUBDr0G0X/bsWuwKsfjARCzYsC20V1NZ1V\nIM/NYTlhOOIzMWGlqAshki1g1DWK8OoG/yrgj6+oZ1DyN9Qz6YOhn7A62ISSwFsD/0/wEIEeHRHp\nGwVSS7Icm5ROSqvFDts0ajU2frscuqZHWb0c+EMFbLjxPXu9rEw8Hvs0EtjSLPB9xDaNGHM82/N5\n1vPSmud/W8Pu9hdXNFajabOOOg8So8b93WJ77LHAQWbFrW+W3LD7PNJKU5FfnW/TNqSuCgcy91tc\njxt8K6t/CDSOJCTaGFYHRO7du4cxY8ZAqVSiQ4cO8PX1pe1tR40ahYkTJ2LLli0tdqISlgUI/2ow\nS4hGbRuG0/knWywwwiz74GpbKD19sLiP+ZrR9Vf/Y9PxzhacQWFNAT1dFKyiMw2M9dipfsBdL3Zg\nYs6Op3Cz5IZVQaK00lSk6wpZn6WdT0fR9UO9wnD1uTR8NHQVlrqP5XVK79fcZx3X+PvsyfyFtZ9P\nh6+2PtW4CaERW27Hd2DgYJbV6cDA5tVpq93V+L+B/xRcFundjV4nec4f+HzEGiTP+UP08wR5BqPB\nzRkXgoAGN2eHdbSu3z2Djml5rHKttPJb9Lldey4Nyx59A3GhE6B3dWP9xkWeVBnSNxk/tcr9Yo5o\n/xh08WrqaHsJu/AYn3vfjaa0SiwFJIXU+7kd8EY0Ir0sDZbo4dcTSdN+x9ORM/Hr5KO0EKSRPDJX\nsEHb2NjI+r85hHfqS/9uoUsAok/L6g64JO6FTKcDAMh0Or4ThoHzvx1E+8fAz5Xfc5HLGOnrItkC\nhJLAosh5uPAtEFxJzYsoBYbeFQ60lNSWCJ7DL02lTClFySxbTG2j1qpr40FAX10BRdPv5aIHOlcA\nR+8eMt33JAmf8aPgxLlOC70VkA+xXSNGDGufl20Ze9tfXNFY33GxbdZR50EiJLAnfln/tqgbGABc\nK07BsWmn4d903YW2C4Mccnr5xxf+2eyyYyORvlFop2xn83avJS22eOwgz2BavwkA/n7iValkXkLC\nwVgdEHFxcYGLi+lJExwcjLQ0U6OhT58+yM3NdezZSfAQTDP9i8JM486ouIP4PeN5WQOOyiAprWOP\n7Fe7ALHxb+PnafuR/OxNvProUtYLi0tmRYZNL9zTeWyxrQm9Z6PxRAq2rF2GS7/tw6TFAeg3n2rg\ncgMT43bFWqUzQ5U7OLF0OrhZB1zU7mo8/8h8PB3/Ia9TOuvANNZxhexhneCEJ0PHWv09GEmIfIY3\nTy5TsDq+hJLA/id3YbN6GfY/ucuue6RI5Ld69uAMkFoSpJZEXlUOJobHm23cU2nWbDcFe6ku1yBq\n8nReyQgzCKF2V+P1/m/gh7EbcSDhmKAWS3blXYu6KGL3j6ZGg02pGygnn3adedvdKLlm1b3HLI06\nMu2k6G9GKAkEElSwTkxs14gBBl4KdLR/TLPFXnv49cSXsWshc5LxbJ0BYNGxl1gZYClFyciqpKaz\nKpsvejw9ahbqXOS4EATUucgxParlymUAvvMFczqtNBVVeXfwP8lAVZ5trjliGAz8yApL1NmMZewU\nfTeEcH6Kxyt9BANqYplid8opHSJ7xK/bOp7RA3nP6SslyRj830dRXJwJlz27oChml/vdcwc2rl3q\n8LIVtbsaM6PmPJDBECP2tL9YZWCdOtHZWG3RUedBo4M6XNQNDADu1RSirL4U52ZewYEpx3Ds6dN4\nuY+pvEVv0GNzqh36TE3IDLb7VNQ31pl1CyS1JMbvHMVyN2SK2EtISDgGq+/eyMhInD5tqk0PCwvD\n1atX6eni4mLBBo6EBBNHlrgI2Y8yswYcKULLtXQFgGGdhmNIx2EglJR43NFpp+DmxFWipzqsVWeP\nYPA3kVYFRTQ1Gqy9yrYRrayrgEoVhtgpbyMiajiGTV6Bahfh0XKn6lr0zwMKNOZ1ZvKqcmAAe2TQ\n2k6XShWGN94fJdgpNf4GQr+PtSPzXITqtfUGHWtfxcWZUI54FM8sWAnnEf3scnThOt/Qx6gtQkpR\nstXXVZBnMJROlDuW0sn+DBFNjQY/bF2MrkXUSD6zZCSfFBYJ7eHXE+dnpmBh78VY9ihbdX9Zk4il\nEGL3j6ZGg5gN3bEkaREGboqBvlHP23Zp0t8Qu22IqFhqc4j0jYKfC3Wxm7PDBfiiu4SSwOGEE7Tg\nbBdv4WwUa4/PxIBGPPXLaPozlnEE77jT1qJ2VyPluVv4fMQapDx3q8U7kuacMKJ07ZG7Gvh+L5C7\nmpq2h7TSVNyv52duyCCjnrXc8gJOUETZIwa69uxzmNPnJcGO6sDAwTyhYQC0NSZXoFDl5u8QO+q2\nQL/wkXjq1Q6857T+XgGIQdFot2QRDAqTeHeOJ9B7ARDebeifdMYPMcwysB376IBjW3TUedAwJ5Bt\npFZXywpoVTSUs5aLvT8FEQjWphQlo0JXbmYjcYpqNPjl9k7BZSlFyciuusuaJ5fJH46yPgmJNoTV\nAZHp06fj8OHDeO6550CSJMaMGYPr16/jnXfewYYNG/DTTz+hZ09h/QGJhwQzI3ZWbe5glxxjCuuu\nifvp+nZmba8jRWi3p21lTfu6tufVEKvd1Vg5gq3iz3L4WNeIfVctj0JsERipGBr8OGt6csQUeCt9\neKPlALuEJthJvOPC1AXwdvFG0rTf6ZITa3h1+LuCnVLjb0AoCeyalChosWkrQgEpwDS6S2pJ/OM/\no+hAQXiRFnfP8YU0rSXUKwwLer0iOB+A1deVIzNEqEBED6yqOWC1hg3zvP9v8D+xsM8rdNowABRW\nF4pmiXDvH2OmQ2LGXpa4YB7JzwwsbyijsyYyyu8gKeeo4DFseSYQSgKJU4/Sqc5yyDEwQLiMRCgr\nQO2uxqnpF6hslATxbBRzx3+l72uCy4pqNPR1kFfF/j6407bQqqPqZpwwfI6fhnNT3MtZT03bQ6Rv\nFELb8Z81BhgQv2c8tDeTWeUFvBF0gkDZr8dgkFPXQr0TEO+8VfD6IZQE3hv8IWueQqagdX+4+gGT\nusQ/NBmYhJLAp3Hr6ee0Rz0wPAu4+C0QXEGtI9PpUPL2O5j5ciC6LwI8O9keLJSwkiZhVZ8ZUyHP\nzYFOpULZtz9KQqt2Yo1eGNc2OdInyuy0KBaCtZbgitMbWXpisaDWnFAGGyuTrhVoLa0+CYk/E6sD\nIuPHj8dbb72FvLw8uLq6YtiwYZg6dSq2bt2KDz74AC4uLvjHP/7Rkuf6l+dPfSjZ+RIAWsYlh1AS\nGNJxGI4knOTV9jpydD6V02ju599fsNE8Nmw8y66TKwBJ3MmyeKx0zui2h5LAiOBY1jxCSeDUzAvw\nc1WxRsu5xyu6bME6sSmpq72rH0K8Ols8NyYhXp2hcvPnzf/3iK9BKAmQWhKTfhmLdTdM+imhXmHN\namxznVOM1DU1FtJKU5FEFLMCBZVd7BtB6UAE8Ob9c8jHvNFmsWAN4Fgh5KPZh6BtbBAsGXGTu1n9\nvTZyMjqMI+VcgjyDoZAp6emXj74ATY0Gtbo6wfUBvuuHkRcPPy+YHWXrMyHUK4yVNfHB0E9568gg\nQ7g3v4FsLOMyBuuaw5jQcYLzVW7+9G8b5NmJtYw73aYR0e2oHzkaBiV1LRiUStSPtM+diFASeK7n\nPMFl+WQe9jtn0vfyLT+gMFjgHgsNQ9LRLZSd6xLgXGOmqLDzW6fYbZN/P/E1HWTiZoPN621/ALct\nEe0fA3cnDzo4f/wnIJhTbiQPCcc/V1zCjhnNCxZKWI8iJdlkKV1cDL9RwyQtETsZGDjYbMkyAN57\nO6siw+y0GFwtGGOwtqtPJPxc+RmETN4c8A5OTD8Hd7m7wFID4naN4rXvuYEcgHoPtpapgqMHMiUk\n2io2FbzNmjULR48ehaIpxfKf//wnDh48iC1btuDw4cOIjHSMl7cEH+ZDafjmAXYLQNmK2EvAFlrS\nJUeotteRo/NPhIxiTU/oOln0PE48c05UAPJesOXhfF3T6LuRJ0PGCjZQ1e5qXJh9Fbsm7kdP30cE\nj5fT0ZO3nZG00lRkVDRZnlbYXpOaVpqK4toi3vz1N77l7d/Iqse/aFZjm+ucYuSlI3OhqdEg0jcK\nHfzD6UDBlKXBeKSzfSKU8REJPGX6N04uw8GsX1nzknLEg06EksDGuG14NWYZNsZts6ujwRX2ZWbn\n7Jywz6p9p5WmoqTOVKogl8lFHXLyqnKgM5iuxcLqAozbGYu9IjozYna4AKAz6ASdZ5rzTGBmTQiV\nUhlgwKTdY3laQo5o1HG1hIxM6GJ6Hvi4+rCWcacfSDw8oA+kNFz0gR0BDw+7d2luVHfB2Vfpe/nR\n+cDhEuGAaGjEYJx+IgJFnuLXT1ppKkugGgC8Gb+Jyt2ftvIN8ewMlTs/yPsgQ2VWHWEFy7nI83Il\nfbI/CaOQsaQl0nyMJctCpXFGuO/paP8+ZqfFELIENw7+GN+tRit6P1c/etAopF1nzO31ItTuarw/\n5GPWPo0DCbXlxbx2WLR/DJ3Ja8yONOeY42haYiBTQqItYvVdNX/+fJw/f543v3PnzoiOjsb58+cR\nHx/v0JOTMMF8KOWSuXhy+/BWjdQKvQRspbVdcpglIaFeYajV1YLUkrQgpLVBJVJL4osrn9HTMsgw\nrNMI0fUJJYGnukzCV7HreKP5pfIG0e2MxzqR8xtrXlT77maPNaTjMKg9qNER7vHmnlko+jnttdIU\ny7i5WHgOpJZEpG8U3dEAKLtF2kHCRtTuaqyJ/YY3X9uoRWLGXhBKAutHb4DS04dydHF1btZxuMdc\nPuB/WfNyqrKRUcYO8ng6iyvLa2o0GPzfflidvBKD/9vPrkDmpXsXBed/MORTPBrQ36p9MAMQnkpP\n7Jt0yKxDDjNDBAByq3Jwpfgyb10nOGGufKCgHa4Rys6Yjb3PBCGdGoAqBWKKmTqqURfpG4UAd37m\n0Hc3vqGF8axxznkgYJRIKlKSoci+CwBQZN+FIqV5QrFMeqmi6Y4Dl0Y00kG/ejeF4LX68Ua4AAAg\nAElEQVQDWHf9RPpGoaMHu6PEHHVNK02la/Szq+4+lA3+Hn49sfBpk8V6DidOrg9vnkW5hO3oomOg\nYwgWG5X3JC0R+zCWRMZ3nSa43Gj7bCSAYItse1sbuBawBOcO/hhgwOcj1uDC7Gs4PysFB6YcQ9LT\nv9PPp8kRU9DO2QuAwEBCHVuLkVASOJJwEp+PWAM9qOzOjIo7zRbrtpWWHMiUkGhLiAZEGhoacP/+\nffrfqVOnkJmZyZpn/FdcXIxTp07hzp07YruTsBOqIW56gBdWF1h0iHAoAi+BtoSmRoPvr6/DkexD\n0NRocFlzEdXaarq1kVuZg/g94xG7dQgtCBmzoYdVHVSuLaMBBquyTcaGxcHHxZc1mv/t9a+RVZEp\nWvqUVpqK+w2mUWgnOFkldBofYWoEMI+na9Rh1+3t4hvaYaUp9h3kkjl0p6Jeb0oT0DZq7crSGRsW\nx9K/MOLp7AlNjQYjtw9FeQMlkNicjBchjAEjJhtSv2dNl9QW89Yxkpixl86y0Bm05n8LC/yauY83\nT+Xmj2eiZlq9D2PGisJJgSptFSbuGSd6D3AzRACIpgQ3ohF14eFmtU1KaoS/J3tGpo0d4jcHvMNb\nVlZXSv/tqEYdoSTwUjRfWwYAsiqokg1CSWD35AP4fMQa7J584MEcceeWSNY63omFEnW2/ODZO/Gg\nWQ0VS9cPoSRwMCFJVFDX0cLHbZVxvZ/Brz/8iwqWvwDcbnIoru8cwhLQlWgFGDbHMgB6fzXKdiW2\nuXbVgwahJPCP/isEl90SyLxgaqa9dfof1g8yckoLI32jeCU7wUQILbjPfT5RQY4TAPhlzgcPfCL4\nuUaGjIYcJgHkpWYE0R1Jaw9kSkj8WYgGRCoqKvDkk09iyJAhGDJkCGQyGd577z16mvlv2LBh2Lhx\nI/r0sS7lTMJ2CCWBmd3nsOb9wdG1aPmToATBmisApqnRYOCmPpj631gs/LAniov5AlLNQVOjQZ+f\norD81FLMTExA9E/dMHZnLMbsGEFH7XUGKi01qzKTFoTUNjYIpvFzYXasACDAI8CqDhWhJHBwKjvb\no9GgR9yuUaKp+1w9iv2TD1slqDg2LA5BhLBWwfvn3hbVb7CnZCbSNwqdCH7nwaiAfrbgDO7VFLKW\nucr59bDWQigJfCigGVHVUIXEjL3QG0zaGExNB3uwptzBXOp/p3bs7+ebq181qxGjqdEgMYsvEru8\n/1s2N1CSco5B10jdD+buAWYQIbRdGD4augqL+iwR3e/GvJ1m7XAn74lrkQYcoSTQt0M/3vw3T5ka\nuI5s1MVHJAhmNhhtoEktiUm7x2JJ0iJe6c6DArdEEm5u0HWhgoO6LuHQRduf9SImrMolrfyW3ccy\nJ6jbEtbYbZX4mP/B/R7hKPIERv/NDze3/4zK385KHfFWRJGWCkU+29FEXqSBIt129zUJPqFeYTg/\nMwVxnZ9izX8scCBrmlAS+CejdCWrovkW6dXaal7Af+3VNRbPc+dT+3hlzv+uPSworppelgY9dKzz\nba1sNqmcTuKvgGhARKVS4eOPP8a8efMwd+5cGAwGDB8+HPPmzeP9e+GFF/DGG29g9erVrXnufzm4\nqfnOchHPyZbCDmFVUktixNZBIMs0uLgOOLCmFIrHY3A2/ZBdHQZNjQb/d/pNOuABgO4Y55N5ULmx\nh6kDPALp1Emlk7NoKjaT1Pvsl05CxAyrXwxCbiXGjAKh1H2uPsVFzQWrjkMoCZycfh6rhn/BW6Zr\n1CExg9+ZtnfUnFAS+Hfs17z5RgV0rvUpAGxP22LTMbi4CgiMDQgYyAs8fDRspUNe3tH+MazMLC5y\nyNFLFS26fGDgYAR4mLYvqM5vViPmpxvfCc7njnpZgtSS+DL5c9a8SO9ugusaXYI+GroKDY0NWH5q\nKT48/77ovmt0NXDx9MWFpuoErrhqeX1ZizXgov1joHZjj9Ddq2E76DiqUad2VyNx8hHefKMNdEpR\nMjLKmwKN5a2X2uxIeCWS0TEoO3KSyhA8ctIhHWhCSeDY06fx7qAPzK7H1M6x93hCvz83CG1OJPlB\nh1ASODKNEiD/bd41+A+fKAVDWhnmvcXMj/J8+QVA07racA8roV5h+HLUNwhp1xkApd8xInikxe2E\nHF0sQWpJjNg8EK71etY7b0HvRRa3zSGzBUXSf7rxvcVtOxJBUvmKhIQDUZhbOHLkSIwcST1ECgoK\nMGvWLMTEPKD10A8BUzuOw4G8N3FdZUCtixPiIxJa9fhCwqq6vvyRWSZGZ4fUkj9QUluM/oz0wIji\nRsz+IQH3e4TjyDTble2zKjIxaFNfuq5SiOnd5uCrK6uhhx5yyLF7EhVw2Jy6EdOjZlmVfVHCEQ6t\nbLDNa97HzZc13U7ZDpXaSnTx4ut2MEtMhKbNQSgJzO7xHH7N3IdjuewOm8qdL+ZqLJ8wfhfN6ShS\nHVE1NLWmhpzaXY1I3yhklvNV24VKUOxl1q/TsHHcNta8nn69HLJvQknglZglWHH674LL9aCCP2LX\nEaEkcDjhBMbtjEVuVY5VgSchN5T0UuHRQ+6olyXSSlORX80endyfuVdQg4TUkojfHUdrbwBAfaO4\nwwwAzOrxP/ju3CpcXEfd56l+pkaeDDJeOYIjnF8A6nv+W99lWHF6GWv+suN/w5kZlxw+svVoQH+8\n0f9tfHjhPdb85jSo2yRNJZKKtFRK16Cp02zpeW/zYZQE4iMSsDLpLUQVN+Kmip9ZVFp33yY7cFvh\nOlj9XnC6RY/3Z2MMDEn8STTdWy57dqHdElOnWVFYAN9xsSg9cU4KUjkAQkkg6enfzb5f6jjP63tk\nIW8dS6SVpqK2soT3znN3FnKSYUMNyMlQ7WKgBxIAYH/mHizrv5x1zsYSn6yKTAR4BOLg1CQpY0NC\nwoFYLar62Wef0cGQW7du4dixYzh58iTS0/mjwBItAEkibEI8zq434OI6oJ229VSmjdgqrEpqSYza\nPgxjd8bitRNUlgQ3PfCmiirX+PDc+zYJTpJaEnE7RpoNhgDAF1dW0evooceNkmuYuncCVievxKzE\naVZlp7R3ZQcT+nUYYPV5UttTI45GJXE9WQmA0l3g0sOvp9lpa1j6KN/+WiizQlOjwZDNlODnkM3N\nE/wklAQW9vkba57eQH2uqoYq3votUT6QT+bhx5vsDApupo09nC88a3a5pRFltbsav045hs9HrMGu\nSYlmGzGklsSobdQ9M2rbMPr7erH3y7x1OxJBVo16MREqc9qfuUdUz4YZDAHEbXWNOMudeTXRRnFV\nAwxILzMFdhxt53deQFOpsLqAztCwVUzZEj1Vj/Dm1elqsfzkUnpaIVM0W0j4T4cgoAsKhsueXajJ\nF9c9spdCTRrOr2sUdCdqjVHQQYFDoHCixoaszRqUkLALgkD9xHi6DM2IPDcHLts2S/a7DsJSVmBe\nFXtwYNmJv9n8fvB1bc975w2p9LHaMS1pGv+9lVOVLZhN6SRzYv0vISHhOGy6q06fPo2RI0di8uTJ\nWLRoEV588UVMmDABI0eOxKlTp1rqHCVAZWe4ZlB1hVElQIRG2MayRbFRWJWZOg5QDd0excDjz/J1\nBtZdX4voH7tZ/TJKK01FSb2Ih6AZFh9biNymGnFr3CYuFV7AqssfseZZrUbexK3SVEFLUqEa0F6q\naFo4Sw6F2XIMMbgWk4DwyEdixl6GnopWsKzGGuIjEiCXyenpklrKOk7IzjXIU9wWzxrcBAI7AFBV\nX8matiWzxhyklkSy5pLZdbgjzEL7mPRLk6bEL+Y1Jc4WnGHpuhg782VNYrFGlj26HKemX7B5hEio\nzEms8cV1CTJnq2vE09kTK57dJiquWsi4Dh1t5/dk6DjRZZoaDWI29LBJTNkSQtfirfup9PMFoLSL\nmEGgBwqNBn4xPdBuySIEPBqNZ390TOCKS48i4QAaANZzpSUgtSSe3zEJMTk6BKM9Tk+/YFXWoISE\n3RAEVYa2aTv0AaayynbLl8IndogUFGkFuPpfBhiw/MRSlji/peddUs4x3kDf89P+bfW7uYdfT3w3\n+mfefK7eWlppKt2ezifzMG5n7AOpTyUh0VaxOiBy5coVvPTSS6itrcXLL7+MVatWYeXKlVi4cCHq\n6uqwYMECXLt2rSXP9S+NLigYjUpK+6JeDuT7yP+ckSyOurY5mOnjzM7U8Z+Au15Uw5fZqdJDb7UL\nR7OdAKpJ1gh3TUON2dU/ufghb55Yp1yMxwIHCo6ae7t480YR8qpyaOEsPXTNEvi7fI/fgV96YjFP\nqItbRiNUVmMNanc1jiacojsvRqcGtbua96L3cfUV2oXVRPvHCDqdGC3sjDQns0aItNJU5JLiv4Fc\nZvk+TClKZgU5jLoWpJZkNbhILYnXjwuLlt7kCCg7y12anS7b1SeSpVavdFKK3k/MLB+ha/idgf9k\n/O5KxEckYFDkGJQcOIrl78Zi+EvurBIIpp6Go+38xobFwd+N3Zl1ghPK6sqagn8m4UxHBJO7+kTC\nifMK/fYaX1PnQcXl6CHItNR35qwH4tIdE7jiouwRg4rOHQHwA2g5Vdkt6qZ28c5R7Fx5F+fXA4e/\nvI+7BVIbRqIVIQjoRo1G5VffsmYrsjIdYm0tYZ5wb74gemLW3iZx/iiM3RlL26mL0aldMEsHZPzf\n1OgXblvm5ojgWHjI2e9zbtYrld1pEs7PrcrBnbxk2hpdQkLCPqwOiKxZswZqtRr79+/HokWLMG7c\nOMTFxeGVV15BYmIiAgIC8PXXD09jsK2hSE+Dk5YazXfRAwMqvSxs4Xi4HThL3Ci+Tv/N7UydWy88\n0ny9yLoGaXMCBUIj3M/sn4J9GcIlAwAwocsk1rSfm4pl2WgNI4JH4o6/M2/UXC4g4eMIgb9nez4v\nON+SUJdQWY211OlraTFbplPDiOBYWjeEa3fZHChNj9d480eGPEmLl4Z6hWFgoGNsJJmddiEWRb9q\n84jy6yeWQFOj4ZWLcPU9OhJB9PflwhFQ5k7bAjPoBojbIaeVpqK03mQBLVTuFuEbiZRnb+HzEWuQ\nPOcP+rvoFtIfSxf8guWxH7P2Ge1vciIzati8GrMMG+O2OaQemuv+0ohGzD00G2uvfmmzmLIl8qpy\neGVvFQ0VrCBJSLvOdl/zfxb1g4awXLnPB7SQLS1BoOzwccQu8BB0JxISZ3YUtedPILLpEo+8T01L\nSLQ2uugY6Dralz0pYTtJOcdY08ySUL3RmbAiE0t+WyTo/AJQWb0KmQLVLsDlIDk2P3PI5ndZtbYa\n1Xp2G7SSkfVqbB/smLgPnZqev5HKjhg6Y3GzTA4kJCT42JQh8vTTT8PHh18u4OXlhYSEBCQnSxHt\nlqKOZFu/1lSWtmrKnK31/jdLbrAEB5mdqSwvILSC+puZIu1RD+Qc34Lfbu62eD5ijfLp3WaLbiM0\nwq01NGDuodmiowCDg4ayprc/tadZZQrrpvAtSe/XlyAp5yhrXe4LmjttDUY7Ny5Ma1JSS+Kt08tZ\ny23NfGEiNtpPKAkcSTgpaHfZXOIjEngj87MOTENhdQE6EkHYO9n2BokYRqcVbxdvweX9Ax+zuI+u\nPpGs1P98Mg/fXfuGVy7C/A47EZ1YomljQsdBLjPqHCjtElQW0hERskPmzhNSw3dTuEHtrsbMqDmC\ngaEOBNv5pYDMp+8zSsOmf5OGTX+7y1jSSlOhqb0nuCy78i7+M+o7vBqzzGFlEZG+UVC5+vPmL+qz\nBAt7L8Z3o39G0tO/P7DCd4ob1+jwkgxA0s+AT0XL2NJ6eKsxZcZqXjAEMG9rbS8dOSV83GkJiVaB\nIFB2MAn6pqCIo6ytJczDdKczVxK6J2MXBmyKxqncE7yBwfSyNNrlUA898km2Lok1CGUs7r6zAzdL\nbrDa3jP2T8Xy/m9B5eYPr6x8uozeaHLQUtg6GCoh8SBidUDEYDBAoRA3pVEoFNA2ZTBIOJ6CYrZj\nh6uWSplrLR9ybr2/JSvJNafeZ5WmMDtTT8x34400M19GvRLmILvghvjOAdG6/G5m0u6FRriNZFVk\nCqZmcwMSKcXNC/r16dAXcCdwIYg9Asotb+Hax3KnrUXmJOPNMzSaTP5SipJRWG3SGlG7q+0aySaU\nBA4lHMeBKcdwKOE4qxPoaA97tbsaywf8r+CyfDLP4ZoNeVU5KK/nOwt1cA+wKhMlryqHzp4BKKHN\n1ckroXRyBmAKIDG/wxPTz9OddlJLYkbiVOgNOqjcVDg9/aJdHXpCSeApTubTv869ywtICFkkV7uA\nvoaZGSxicFX8/3X+XTr4eDT7kEPLWCJ9o+Dnwi+nMrI06W9YnbwSM/ZPdUjDjlASmN97AW/+1rRN\n+PrqF/jIjEXxA8FFtpiwfw1w+XsFurk4OEOkibFhcWjvws6Ic4JTs3SUrCVw2GSkNVXxpflS0xIS\nrQ5JQpGXg9KDSQ61tpYwD/PZIiYGzmTKvqfw+JaBlOj5dkr0nOss1hynsUjvbrx5BhgwcvtQnC04\nQ7e9Myru4OVjL6C4tojVnrXG5KC5OFr8XEKirWJ1QKRnz57YtWsX6uv5Snq1tbXYuXMnevTo4dCT\nkzARUsceOuvQJH3RnJKK5hDpG4UuXiZF9L+feFX0wVhcnIn33zzAi7QbO1O9e43hjTRzX0Yrvhlj\n9sFbVlfKmxfqFYb4iARRy0ShEW4mzx6YzuoUkloSX135N2udaFXzggZppam8lEgAGB/GFh51hKiq\nGPOOzMGlwguCy0pqSlCtrbZr/44OfJhjetQsXnlESxHkGQw5+OKO92oKUVxTJLAFG+49ahxN0jY2\nYGHvxSznGaHvkClOXFxb3KwRKC7csqqjOYd4YqN9OzzK286Y6cLNYBGjuIbfqsyqyERKUTJGhoxm\nlLEo7S5jIZQEEqceFV1e3iRMyxSrtRchrRpNDZWl0hJ6G63JtQkDeT5YQWU6eGU4PkMEoH6/n8dt\nZc1rRGOLZKQYuZVzAa7GWKUMuFEiaYhItDIaDXyHP0aVPox7ArqgYCkY0kowB0/MDZgxS2nul2Sj\nfx5wT0O9R7iZtc3JtN2fKSxorzfocacsXbBst9oFmPxaEAr27bfK5KC52DoYKiHxoGJ1QGThwoXI\nyMjAhAkT/r+9O4+Lql7/AP4BZliPsjOKCLKLoOKC5pJLmuaaS3otS7ulV7OyvWzx1+I17XbNyrTS\num1apmaulZWpuS8oaAYIiAIuCALiyDbA+f0xzjBnZthngJn5vF8vX3L2c/DrzDnP+X6fB+vWrcPB\ngwdx8OBBfPPNN5gwYQIyMjIwd+5cc56rTRPHT5EkVd18OxhsyvKitRHkAt4d8r52Or0wrcab/X2/\nrqg10v507xfQzi8MxwKAYif1Q63+l9EhjyL8eG5TjeejXy5tZvSj2D31ABSuCuyeegCb792BV/u+\nbrCd7htufRVV0so9xhJqNraHSE25KFIKkyXTpkiqCqiTj/q6GHbnH/Pj3ci4cR6xfj3hpfM2thKV\nzV+1qAkUrgrsnPgbnOBssEy3J4wpqP9NjJd3/i5pbZ3b1zbs6atjH+LZ//SW9IjS7Z6qVClx4upx\nyTaNeQOlz9fVD53aBkvm6ffSGBo4XDteGQAUru1w6IF4gx4stRkTOt5oMCmj8DxSC1LQzq09AMBf\n6AA3uVtjL0fL19XPaLvXZyyg2hj9/AdIfke6aktWazJKpdmS6gV2H47HZ0r/jUWZTP3AZiYHLkur\n1Xk7+5iv7K5SiWEzXkDQ7eGbkdeB0jO1V5QiMimlEp6j74JDlvp7XpaVBa/Rw5gPogXU9MJMt/fy\nidVA/OrqYTW519T3UpqXhaHujcuTZuzlg0ZAmwDsmrIXm+/dgaC2nbTzHeCAr6fsgLzvILMG0CK9\noiTfcbW9DCWyZPUOiPTr1w/vvfcelEolFi1ahFmzZmHWrFlYvHgxioqK8M4772DgwIHmPFfbplAg\n69hxPDnRFYFPA9faqGebqrxofcT69ayzKoRSpcTiwh+MRtqHdbwbR6cnINonBr9NVeeVODL9FHyc\nfSRfRkNmqoMo//erYWUUDf3yrYMCBkvesg/sMAiPdpujPd/gtiF4pe/reLP/20YDJRq6XRf1ewY0\n5S22ZjjE5yO/lszv7y/9PxPQJlD75dOUyhuCXMCUiGkG80WIGLt5BHKLr6GwrLqUqyne0DennOIc\njPvxHpSh1GDZlB33mqSsqkakVxT8anjIvj/qwTq3r2nYk+ZG69dVN+A2vD9yc88jpzgHg9ffoe6S\nu2EQhm0YiLePvinZrrDUcPhOQ6XkJ+FCUYZkngOkFXMEuYAP7qpOlJ1TfBX5pdcb1AtI4arAh8M+\nNpj/f4dewaStY7Ulai8WXTDJm6eEayeRW1J3rx1jPVcaQ5AL+GnybklwUUNVpTJvyV2lEp4jh5g1\nqd7BLm7IbFs9bVdRAVm2+Xps6Pe4uqfTGLP1OJMlnIR77g3ttMoeiOtj+JlJZC6ylCTIsrIk8xyy\nMs2aD4Kq6QYzAOMvzHR7L3e+Dm0S5qg8IOfE7xDkArZM/BnLh36ELRN/btTn1dDA4ZJghz7NPe2L\nca9q51WiEmmF5ks4rZFbfE1SSr62l6FElqzeAREAGDVqFPbs2YO1a9diyZIlePvtt/H1119j3759\nGDdunLnOkW5Lkl3HR92LtcEQwHTlReujtjwRGin5SbhkV2g00v54z6e0w1k0QwOC3UOweuSXANTr\nnfVVl+XVROA/OfiOwTEAw4ooxiqk6J7v7n8cwNO9nsNjsU8YPPjrdofU7bp4OjdB0jPg/aErm5y7\nQb/srO7wB6VKiXGbRyDrZibau7aXDKVojJqqzeSWXMObhxZKKmS8EPeKSRJNNpffL+6SVErRVSVW\nmbS3iyAXsH3SrwZDdHxdfOHrWndvhJqGPekPE9v36wqM3nSX9uYj/Uaa0YBgQk58A6/AUKRXFDq4\nSYOKIqQ9azRvgTRVghoboLusvGQw71YLvmFysHPAmNDxda9YT6kFKZJqPM1FlnASslR1V2ZzJNVL\nyU9CzrXzUFRXXsYFHzluhJqvh8gDUdKk2Psv7W22t5HyKqDd9ab3viKqr4rIKFSEq1/aiLdz9Jkz\nHwRJCXJB+3LujX6Lja6j23v5nKc6cAqoe2rLOoVDqVJi0pYxeGbPE5i0ZUyjPq8EuYA9/ziEcSGG\nOYw0vaFzinPw5G5pL/wX9pq/t4Z+dUJ7O3vz93wkagE1BkRefvllJCYmGsx3dHRE7969MWHCBEyc\nOBF9+vSBo6OjWU+S1PTzeAS2CTJZedH6qitPhCZfgn6kvbauhLF+PbX11fUfEq/s32L0A18ohyRp\na03jNo3mZNAZ9qKfWfznv9Zrj3c2T5rY9ZKRB7uG0h/uoNt1f0/mbu1b+yvFV3DsypEmHSvYPQRL\nBv7X6LKfMqRVaEI9Qpt0rOam37NGlzl6uwS7h+DI9FNo61hd7jq3JLdeb0pq6iWgP0wswVuFLGX1\n28L2bv5G8+F09u7SwLM3JMgFvDXwbcm8KlRhZ7o6IKhUKXH3xkGYtHUsbpQW4vOR39QYBK1LfQYw\nyexkCPeMbPC+9cX69UR7V/9a1/lnl1kmDf7VNIRJZi83yTUZpVSizQtPaycrQsNM/hAV0CYQ49Mc\n4KTzD/hOHxWSy8zXQ6S0Uvq7zLx50WxvIyvCI7UPoQBQERzCB1FqXoKAgl17UfDzbuSdSlInVDVj\nPggypLlHnBHzTzjbG95HanovD5kJOFWqA6eA+ueprncY5Nho7OeVIBfQW6cSoIYm+frvF3ehSm/o\n7uVbl8ye00N/OE+VaN68TkQtpcaAyI8//ojMTDb61kTTNa+9m/qG38HecGx+S1KqlLhvq2FPoVf7\nvo7fptZcclWQC/jpvj/g4+yDs75Ask7v8/e3lOC3v6pziShVSiRk/IlhDz2Po58BZ1YB/kqHBj14\nqJM5qr9k9AMwvhevaUvhKsulgRgnByOJRxpIP3Dz2oEF2gDMkUvSKjf6040R6W2YvdyY0grDoSet\nWX5pzW/kn+r5vFl6u/i6+sHTqbrseKhHWL17TOj2QtLQH7O8Ped3SQDEWeaMbRN3YWb0o5J9qaqa\nXs1LqVLi9YOvGszXDO/RTeSaV5qHOb/+s9FJdzsIHepcp0KsMMnwEkEu4Nep+9BBqLl8qp2daZPx\n1hSMrahS4XRugkmPpSFLSYIsPU07ffPd903+EJV9MxPbwipRdvtrpswBOHlHJ/Pl9IBh0L8h/8ca\nSpaaAruK6l5mN//9Dh9EqfkJAip6xQEKhfpvtsEWIcgFLL7TeI/kMicZSuRAUFH1vFwfN7TtPgAB\nbQIlycGb0ntiUsQUg3n/Ob4YOcU58HNVwN7II9uze540ay+RoYHDtc8cGs1VzIGoOTVoyAy1vNSC\nFG25VE21htZCnYQ0y2B+r3Z15xxQuCqwZ9phuLj7YO6Y6vmR14HPN87X1mO/e+MgvLZmLNzOXwQA\nBN8ADqypxJWc+j9MKVwVODnjLJYP/QiLHt1ukO8k/uoJZNw4jw9PLZNsF+Pdtd7HqEmsX0/Jl8uV\nW5e1/4Z3dOgvWVd/urHH83as+8tLvzdMaxfpFYWgNp2MLnNyME+PtYRrJ3Hx5gXt9FsDltSrx0QP\nt0ic+lxmUHUJkPakunLrMuZ0e1y7LOOGOvHoXr2krEMDhzX5WvZk7ka23v9VBzggzCMcAJB8XZrs\nt0KsaPQwpLySvHqtZ6pEpwpXBfbffwxL71xmdPkDXWaY5Dga4Z6RNVY8yioyz0sF3a72FeERqIht\nfMnsmkR6RUHergN6zgK+jgFmjgOeG/yWWatIabqwb753BzbfuwO/Tak5kG5yLg2vDkFE1mNixH3w\ncPKQzJvXfT7eGbxc0qMzwx3I2rYVEAQcu3JE+5KiqXmjFK4K/DRRWimtsKwAo38Yhuk7p8DbSCDi\nQlGGWZ8DBLmAp3o+J5l36PIBsx2PqKUwIEImE+kVBScHadUPFweXemfdVrgqcKerQnMAACAASURB\nVOyh06iK7WUQpPjo5Pvat9ZnfYGLOon+gm8A0XXnUTQ41vSoGciTlRrkO+nvP9Bo9ZAN59Y37CBG\nCHIBr90hTZIZf1VdUSTGp5tkvv50Y8lldQcIaso30loJcgEbxm8xuqxLM+XVqW95Pff0TIRfU7+J\nNlZ1Sbf3SMDtoWMaBaUFkiAMUHvvmPqK16tcA6iTtE3cMgYZN87jlQPPS5bZw77Rw5DCPMPrtd75\nwvRG7d8YQS5gauf74e3sY7CsoMw0gReN7JuZBvlXNEwRvDJKp6u9ubrYC3IBH8a8jpNrgBl/Aeu3\nAKMffMnsFTA0CQQHdhhk1mBIRWxPVISqe6NUhIaZJahERJZDkAvYdd9eyOzUQ+nk9nI81uNJTIyY\nDG+fIMTNBu6a64rs339Hx7A+yCnOwexdMyX7aGoVuN7t+2DP1ENoK1MPz23n2l6bVyy31DTJwBtq\nTOh4ba9qub2jRSXgJ6ovWW0LT5w4gcpK4+UmazJhwoQmnZAxr732Gi5evIhvvvkGAHDp0iUsXLgQ\nJ0+eRPv27bFgwQIMHjxYu/6RI0ewePFiZGZmolu3bvj3v/+NoKAgk59XS4j164lg9xBk3DiPYPeQ\nRpX4MidXOxdJ5Y+ne73QoJtaQS4gplN/xM2OR3SuOhhyywmI8e2GK8rL2vXKdUYLXWonwDG6cb+H\nrKJM7Vt6jXm/z8YX96zF+yel+Tdmdvlno46hTzeRKgAsPvomvk3+Bg9Hz4JbGbTXvSdzN4K7GuaQ\naIiEaydxtfhKreu0kbWtV3LQ1sbYWwovJ2+z5dWJ9euJUI8wpBemIdSj/uX1KiKjcD3QD96Z1yRV\nl4DqHDZReergXxymAjojs7JvZkFmJ0OFqA6oBLuHmGQIwcyYR7Aq8UOD+ZdvXcJnpz81mP+vbo83\nehhSP/8BaO/mr+3ZVhNHEwxJ0yXIBWwavw1DNzS9p1VtIr2i0FEINCjRDaiDV8bywJiEpqu9Gd15\n9iacqnMvQ8i6AlVKktmP2ywEAQW//QlZSpI6dwiHKhDZvGD3EJyamYTfL+7C8KCR2u+9vdMOIyU/\nCZFeUdp72p3p2yTJ6YH6vyipjavcFUUV6gpYV4uvoFPbYFwoykB7V39cKZZ+j3rfrnCmVCnNFkBW\nuCrw63178UniSszt3vh7AaLWrNaAyIYNG7Bhw4Z67UgURdjZ2Zk8IHL48GFs3LgRffr00R5n3rx5\nCA0NxaZNm/DHH39g/vz52LFjBzp27IgrV67gsccew7x58zB06FCsXLkS8+bNw/bt22Fvbx0dYuzt\n7CV/txYJ106ioKJAMs/dyb2GtWvWTmhvEKS4WJihLcnY+xIQrnOY66+/gfaNvJkdEzoeC/ZLuwMW\nqW5ge/pWg3Xt7E2Te0A/NwmgHh5xM/+y5OH4+PC2RrY2vZsVRUjJT0IvhWU95AwPGgl7OEgSjb07\nZLnZbgoEuYDfpvxpcFNU94YCdn/zXyz7ZoY2wOfu6I4b5TcMcthE50rbvY+LrzYYAgD/HviOSa4v\n2D0E87s/iw8T3zNYVqYyLOXd1bfxvZUEuYBfp+zD6B+GScr36Qb/bjkZHz/dVPpJOjsIASYPIgty\nAW8M+Dce3SUditPGsa1Z8200i5HjIS54SZtrw+oSjzZDUImILIumB7EuTfJVXb6uvpJphavCJN8v\n+pVdhnS4C9179UB//4EY/cNwXC+tHobq4CDDpK1jEe4R0ejE53XJKc7B3RsHo0JU4YdzG3Bq5t8M\nipDVqTUgMnXqVMTGGi8Z2RyKi4uxcOFC9OxZ/QFz5MgRZGRkYN26dRAEAWFhYTh06BA2bdqEZ555\nBhs2bEDnzp0xe/ZsAMDbb7+NAQMG4MiRI+jf37xvCptDSn6SNtmhph54a3mQLSiVBkPs0bjylpMi\npuD1Q69I5v18cSe+GLkWqxI/hItetdWObYNqKMBaN4WrAq/2fR2Lj0qHsVzXG5agcG1nsoebkopi\no/NdUtMlD8eZmblAE9OWxPr1RFCbTgbDLnSZqtdBc1O4KnB4ejzGbL4beSW5CHYPwdDA4WY9prGb\novqICxuO3OgQ3Lrds2v92M2YsGU0zvpeRpJPdRDsrPT+CheMlN01BaVKiXXJXxld9nXy/wzm5ZU0\nrauuwlWBfdOO4JuzX+L1Q68Y9IzZ+cW/zXKDFekVhXCPCKQWnkNHoSN+uu8Ps9ww5hYb/n6+HLmu\n+fJfmItCgbxTSXDauQ2VHQNR0W8Ae1IQEQHwdPaSTL839COTfOb3atcb0CnyuSvzJ3yZ9DnCPSIw\nt/vjkvvVa8U5AKor3JjjeWBn+jZUiOo8KRWiCjvTt+GRrrNNfhyillRrQKR3794YN86wakhzWb58\nOfr06QNfX1+cPKlOGpSYmIguXbpA0Lkp69WrF06cOKFdHhdX/YHg4uKC6OhonDp1yioCIuqM1o5Q\nVZXDwU7WqrI9Z9+UJml8tveLjXrIUbgqsHLYGjy+u/oDN6f4KnacV5cELdFvtU1Mhjct6kHJF4xb\nGVDw5064+VaXDX606xyTPdzM6jYHa858bDC/KKSj5OG4LKJ+uRdqI8gF7Jl2CIcvH8THpz7Egcv7\nDdZ5OHqWxT64BbuH4NiDiQ3vtdHMBLmA3VMPSM7z4AMnsPDPBYib/bWkp4SuNYnSdlLaxPHJGin5\nSbheJg366ffY0FXfPCC1EeQCHop+GCtOvoeQ7DxJ8C+nwDwJLQW5gF1T9pq9fYwJHY9X9r8g6T6d\nqbxolmM1O4UCZY/w5peISJd+NTNNUvKmGho4HKGydvC+cBVXO3oj85Z62HNq4Tl08YnRDqN1gAMC\n3YOQceM8wj0izPZiS78njP40kTVoXWMudJw6dQq//PILXnrpJcn83Nxc+PlJ8x14e3vj6tWrtS7P\nyckx7wk3k+ybmVBVlQMAKsUKTNo61mwlt64qr2Jd0tfIKa7+3SlVSsTnHDd6TP2HjfZu7Rt97PaC\ndFt72GtzHpzoAKTcjgOZIhmewlWBp3qoh824lQEnVgP7PyvHidXVFUFCPUKbdAxdvq5+8HL0Mpj/\nQepqbYLXSc92RNdOpsmFIcgF9PMfgKTrSUaX+7gYJp60JJpeG601GKKhf56CXMCCfgsllWb0y/MW\nqgol+0i6/rdJzkW/vKmmx4axSjiejl4my8siyAV8MOxjScb+VD8ZOt3R8J5kDTmmuduHm9zNoDRh\nf/+BZjseERG1rD16FeD0pxvreu4FbH//Ko5+Bvyy4jo8VJokr44I8whHx7bq0r6B7kFYP3Yzlg/9\nCJsn7DTbd5yzXl6U0orSGtYksly19hBpKeXl5Xj11VfxyiuvwN1dmoOipKQEcrlcMs/R0REqlUq7\n3NHR0WB5eXl5ncf19HSFTOZQ53otaaB7H3Rs2xFZRereGJeU2bhQloyh/kNNepyryqsIej8I5ZXl\nkNvLsWXaFvRs3xOjN9yF5LxkdPbpjOOzj0NwrP4AvliSJtnHxZI0+Pq2adTx73YfjE77OuFC4QUA\nkLx5veUE9PoXsDp4Ph64fzF8TdCFO9BX/TDT+zLQ+faL887X1dP7goFgRUCjr0Xf+ey/kV9uvNKF\n5uF4btcxCPZvfEDJ2DGvl9VQ/tRRZbJrswbN+bvwRRtcee4Kxq4di+TMeGmC1dmGPTWUYqFJzs8X\nbZAw7xS2JG3BQ1seqjWXyQsDnzdpWxzvfg/ePBKBuNnncFexH9YsOARFO9MFHFvC+ey/cemWNFmy\n6FxqUf+vLOlciUyBbZ6aooO3n8G0KdrUN2vfx7M638cRORU4FgCoqspxpugEMm4Ppc24cR6Tt49F\ndlE2IrwjEP+veMk9uTGNOT+PQlfJ9Pw/HsOk2HFoJ7Rr8L6IWqsaAyITJ05EYGBgc56L1sqVKxEU\nFIRRo0YZLHNycoJSr+xfeXk5nJ2dtcv1gx/l5eXw8JDWFjemoMB4bofW5o1+iyUJ/K5cv45c4aZJ\nj/HVmW8hLy5HbC5w1leFMd+OQQe3AO1Nf3JeMg6cOyYZrxjZRlrutLtnb+TmNv687g64B2sKPzG6\n7JYTUNq1N3JLRKCk6dfe06Of+gf96pmiOgFmJ6fOTboWXX72gQhuG4KMoprzQ6hKRZMdT3NMTS4F\nXTJ7OQYpRpj0WJbM17dNs/8uHOCG6Z0fxvr4+FoTrAJAnE9/k57fSP978Xzvl/Fx2RKjuUzs7Rww\nLnCKyX8nv0yqHsZi7yBYfPtzq/SGzE6uHWcd7B4CP/tAi7mulmj3RC2JbZ6a6vy1LINpU7QpZadQ\no9/H4R4R6Nq2t+S7JrtIfU9+7vo5/Pb3PgzsMKjG/Ta2zZfdkt4YV4qVWH34CzwW+4T0vFVKJFxT\npzeI9evZ6nvtMiBKumoMiCxZsqQ5z0Ni+/btyM3NRY8ePQAAKpUKlZWV6NGjB+bMmYPk5GTJ+nl5\nefD1VX9iKBQK5ObmGiwPDzfN2L7WQD+RkynKfOkrun7Z4G31JWRrxy7K7R0R0KY6YKZUKfHvw29o\np+1hjz7t+zXpHDp7R9e6XP/30BQJueoP8YvugMoekFcBZfZAki/wr27zTPrBLsgFLBv6ISZtHVvj\nOleLay9R2phjanIpeDl745eMnwCoE9gyW3jLK68q1w4jqSnBqiBvY5akse3d1FWd4mYb5hB5d9By\ns7SPxianba2yb2Zqb1ABYNmQD1v9zSCZkFLJ8r1ENiagjV4OERPk2gKAST0fQdzsJZLv415+ffDl\n6HUG3zXNIdavJzwcPVFYXl04obxSWo1OqVJi6Pf9cbHoAgDA29kHe6cd5v0lWYxWmUPkm2++wY4d\nO7BlyxZs2bIFU6ZMQUxMDLZs2YLu3bsjOTkZxcXVvTni4+O11XC6d++uTcAKqIfQ/P333y1aLcfU\nwj0jIbNTx7JkdjKEe0aadP9n8/7C778uM3hbDUBbAlRVVY5snRKaW879IKmPXoUqyfLGyC+tYYgH\nAE8nL5OWz+zvPxBuZcCer9TBEABwqlJfe6zCtGU6AfUXjH4OB93cEaNDTJ/MWPMQGuwegsdin8Bj\nsU/wy6qVGBM6HqVOMm0OGWPDZSaFTTHLQ7amatUtJ/XNV3RudTv0cK67Zx1VV7MB1G/xTF3al1ox\npRKeI4fAc9QweI4cAijNk9OLiFoPpUqJ1w++qp2W2cnQzdc0zxkKVwW6dRqgzS0GAPHXjmHCllHw\ncvaGfQ2PbgWlBWbJKSjIBSzs95Zknr/QQTJ9+PJBbTCk03Xg6Z15eHhlX7PlOCQytVYZEOnQoQOC\ngoK0f9q2bQtnZ2cEBQWhT58+8Pf3x4IFC5CamorVq1cjMTERU6ZMAQBMnjwZiYmJ+Pjjj5GWloZX\nX30V/v7+6Nevab0VWpPUghRtYKJCrEBqQYrJ9r0tdQuGbugvSXpo7G11qHuYJKP1pnPfS5a7OLg0\nOeO1/ugVXdFeMSZ9OMwvvY7oXKBTkXS+n6uvyRJK6hLkAn6b+ice6DzDIKFl+8q2GBVSc+8Rsj4K\nVwUSHk7CwuHLcMe4Zw2CIQBwo6zAcKYJzIx5BIA0seqZVYDfTSC9MN0sx7Q2mh5YP0/ejV1T9rJ3\niA2RpSRBlqoeiihLPQdZivHk1URkPfZk7ka2snrITIVY0eSXgLo6tjFMWZBemIZDlw9IcurpenTX\nQxi5cYhZghCaYg4aN8ulQ2/SClIBqIMh6SuA1/YDx97NR0r8DpOfC5E5tMqASG0cHBywatUq5Ofn\nY9KkSdi6dSs++ugjBASou64FBARgxYoV2Lp1KyZPnoy8vDysWrUK9vYWd6nN7teMXzDrN3VuEk0X\n+preVut/IPdu11cyPdMEpVyjfWJqXOZWR+Kohor0isKt0E5I1qlifM4LePDBVWZ7uBHkAl6+YyFi\n9BJafhr0DB+obJDCVYFHus7G072fRztXwySmT/d+wSzHDXYPwdHpCfiXbKC2HQbfAI58Bgh156Km\n2yyl2hGZVkVkFCrC1b2DKsIj1MNmiMiqxV89Lpn2cPI0adnbkcGGORS9nL0xPGgkFC41JzNNLTyH\nlHzTB2X76g2B1592tFcXs5h/tPrB0h5Au6++M/m5EJlDq6wyo++ZZ56RTAcFBWHt2rU1rj948GAM\nHjzY3KfVYvRrn3s6NT2XhlKlxMyf75fM01Q8MSbjxnmk5Cdp8wDc02kUPjy1TLt8fOi9TT6nfv4D\n4GLvgpKqEoNlC/q+1uT96xLkArbPOIT9fXZgwfoXUVhWiMLoMPxootK3NVG4KvDRE4dwbuudiMit\nRJqfHF0HPWjWY1LrJsgFHJoej5/P78DmlI2QOciwoO/CWgOETRXsHoKAvqOR4X4AwTduz7sBTK0y\n3zGJrIIgoGDXXuYQIbIhY0PGY1Xih9rpz0d8bdJg+NDA4Wgra4uiiupuy6Iowk3uhvFhE7HmzMdG\nt+vYJtCkgRkNTZ49ja1pmxHk3kl7zUcuHwQAXHGTbpfhXArp4Bqi1ondJiyQfq3zKdvvbXIXue+T\nvkUlKmtdRzfPhR3sJElVf734i2Rd/enGEOQCfrh3u8H8taM2mOXhUJALGNV1Gpa/8TcWvLAbPz74\nZ7O87Q3yj4HjwWQcXvcRZAf+hpsH83rYOkEuYErkNHw3/gd8M+Z7swZDNHqGDMEds4CM25XOizoF\noG138wYEiayCIKCiVxyDIUQ2IqVQWtwhU3nRpPsX5AIe6DJTMq+gLB8p+Ul4IOqhGrf7etR6k9+3\nKlVKtHVsC6D6OWDN4f9KhufEKnoBAL7qCZTZqbcrswOCHl9k0nMhMhcGRCxQG0dpqai8klxtqavG\n+uKvzwwSe+rSz3PhWibidG6CdvmIoHsk698fZZpeDr3b98GeqYcwOngcpneegaPTEzAi+J66N2yC\nluj67uahQNjdMxgMoRZz9MphXGsDdJ2nHir32Ufz+IBHRESkZ3jQSMjt5QAAub0cw4NGmvwYlbdz\nBWrY29kjoE0gSisNe01rvH34LZPmEFGqlBi5cQge3WWY7+5yjnp4Tk5xDhYd/j8AwLU2QOCzwIeP\n9sTZg7+jY1gfk50LkTkxIGKB8koMq68UlOY3en8nrhzDpZxkyQedblBk5bDVmFAeblB1ZvYvM/HK\nvhfw0M5pGL9VHaSwgz1+mvg7gt1DGn0++qJ9YvDlqHVYftdHJt0vEVXzdVVnTtYMlWunsJ5S5URE\nRKbk5axOOufv1gFucrc61m64Wd3mSKarRHX1xkivKHg5ehvd5resX3DX9wNMFhRJyU9CaqE6aXS0\nXr67bnkOCGgTiM3nNkryCl5rA3R84i0GQ8iiMCBigYzVOs++md2ofSlVSkzdPsHgg65XvjMAdTWZ\nUSFjET3oAUnVmQvuQMzFYnx38lPsuvgTKqrUkWwRVQZdCYmodVOqlHj7SHVZvcA2QWaprkRERGTJ\nii+dxxcvxMEl6yr6ZAN5eRea3EvbmGD3EOyZekibJzDcIwKRXlEQ5AJ+nrK7xvK7F4oyTJZYVbek\n/Hk/Z8lzwGmfSvyZtRdlldJu5V5O3iw9TxbHIpKqklQ//wHwdfFFbkmudl5Am46N2teezN+hrFBq\ny+xG5an/XvbYH6j0toeffSAEuYBx3R9En9lvokuuOhiy96vqdYfMBDrdUJfmveUE9PcfaKpLJaJm\nkJKfhPQbadrpSrH2fEJEREQ2JycHHeN6Y1lFBd6F+q1ykg9w5p58mCN7aLRPDOJn/IWU/CRtMARQ\nB0sOTz+JMZvvRp7Os4CGs4OLSY6vKSmfkp+ExYfeQNzs/YjOrb7ff37PU/jo7k8l27w7ZDmrrZHF\nYQ8RCyTIBbzRf7HeXLHB+8m4cR6P7jIss7vkP/chyD8GfQP6aj/UFK4KbH/oEI4FqIMfur1Jjnwm\nHWpzSdm43ipE1DIivaLQUagOql5SZpuldB8RWTClErL444DSdDkKiCyJ085tsK9Q94jWPEBF5QF+\nFw2DEqZSU167YPcQHHswEVMj7jfYZtyPI00ybEapUuLw5YNIvJaArn6x2iG1t5zUy0uqipFZJE0o\nG+Ie1uTjEjU3BkQslH4ekfTC9AZtr1QpMWLDEMk8zQddlavxsZDRPjHoq+in7U0CqCtSaMp0anKL\nNCWfCRE1P0Eu4Kf7/kDH25WjNF1ziVoFMz2IK1VKxOccN2kSQqulVMJz5BB4jhoGz5FDGBQhm1Ts\n1dZg3jlfB3S6Y3wLnI36u/ve8EkG85Wqm1if9G2T9n3iyjF0+SwE03dOwYL9z2F14iqj631+WtpD\nZGva5iYdl6glMCBiofTziHz512cNuqlLuHYSN1SFRpfdFTSsxu3+0fkBSW+SO2ZBMqbwrG/DgzNE\n1PIUrgrsm3YEP0/ejV1T9rLLqyWytjf4SiVkB/6E592DTP4grqmeMOqHYZLykWScLCUJslR1ckVZ\n6jnIUtiDjGxPeqm0B/TTI4B33p3aohUCu/nGGp3/yoHnkXHjfJ3b6waGlSolDlz6E9+c/RKjfxyO\nUrFUu14lKvF875fh7xog2T77VpZkWr/qJJElYA4RCxXmIQ2IXL51CSn5SeiliKvX9gezDxid7+3k\njaGBw2vcbkLEZCw78Q4uIRvHbn8mxs2GZExheWV5/S6CiFoVTddcskC33+DLUs+hIjwCBbv2WnbZ\n5JwceI0eBoesTO0szYN4Ra+mt1Hd6gmpheca9P1piyoio1ARHqFtXxWR7EFGtqfS2UkyndAOGBnQ\ncglElSolfr+4y2C+W5n6vnziN4Ox65ETyL6ZiYHuhlVflCol7t4wCFevpaFXrhNO+1Wh0FFV4/Ha\nOLbBfwa/hwd/nlrjOimFyejdnhVmyLIwIGKhDl2WBjT8XBX17uKuVCnxfvy7BvNd7d2w9/4jtb4Z\nFuQC9j9wDAnXTuKK8jIOZR/AupSvtcERQP2BSUREzcfYG3xTBA5ahFIJz9F3wSFL+ubRlA/imuoJ\nqYXnOESsPgQBBbv2qttVZJRlB9uIGslnwGikeL+CyOtAijdwogMQUY9eGOag6eWWWngOcntHqKrU\nLyPdytQ5/dSFD25gnONApFfkoGPbjlh653vo5huL07kJOHr5CP64+CuuXku7vX4ZknzULzlvOVUH\nVTQvOwFgUsQUowEYDQc7BwwPGtkcl09kUgyIWKjhQSO1H4AOdjJsn7ir3l3cD18+iEoYVpFYcffH\nULjW3e1PkAsY2GEQACAlP0WyzA52mBQxpV7nQUREpmFNb/BlKUmQ6QRDKjsEoGjFJ6iI7WmyB3Hd\n6gm61RuoFoJguUE2IhPIrLqO+/4lDRTc4d+vRc5Ft5ebqqocs7s+hjVnPkZ0rrTwgfeFHKQHAFlF\nWZi+c4pBoKOP3vqaZdVBFXWQ5KG4J6FwVdQa8Lir4931eo4gam2YQ8RCKVwVODnjLJ7v/TLGhoxH\nsaq43tsevXzEyP7a1TpUpianck5Ipvv43cEPQyKi5nb7DX7Bz7stfriMJrgDABUdOyL/lz2oGDjI\n5NdUU/UGIiJjIr2i0M4vTFtppWObwEbdO5vqXMI91J+T4R4RmN/rWXg6eUkKH2hy+2n43QTOrJJW\nhtRdP9kbcCkHel+SBklicoHHe84HoH7+WDZ4hdFzuswqk2Sh7ERRbHi9ViuVm3uzpU+hQc7m/YWh\nG/prp/dMPYRon5g6t7t/+2TszvpNO+3k4IwTD50xCGT4+rap83eyP2sfJm8fp53+Ydx23NlxcH0v\ngahVqU+bJ7I2rbLdK5UcnkFm0yrbPFkEpUqJhGsnAQCxfj1bNKCqVCklvdwybpxH33WxBr1A3MqA\nOy8C/9sKtL9VvX3fWerqkm5lQO/LwKc7gMjr6sCIHdQ/p/ja4eZvBxHkHyM57oBve+PKrcuS83l7\n4LuY1W1OM1190/j6cng/VWMPEQv2SeLKWqeNUaqUOH75qGTeP6NnN7pXh6uja63TREREDSYIqIiM\nUlczsZaqOURk8TTDxgd2GNTivcv0e7kFu4dgz9RDuOUEbS8WtzLgxGrg52+lwZAM9+reI7ecgBK5\nOgACAJ2vA3PGAiMea4vKvackwRDNcQ8+cAIrh62Gm70bAKC9mz+mRU03+zUTmQMDIhZsbvfHa502\nZk/mbhRVFknm3dlxUKPPQb/LXrMkprO20pJERCR1u2qOqcvtEhFZs2ifGPwwbnv1dK46wKHrshtw\nx6zqZKl2sMOz079Gqp86teQ5Xwc8MmMNPn0tGb6+IUaPI8gFTImchjOPpuLnybtx8IETLR4gImos\nBkQsWJB7J3QQ1OVdOggBCHLvVOc2O9K3SabdZAL6+Q9o9DloEtP9PHk3dk3Za/4PQ94kExFZPWNV\nc4iIqG53dhyMtaM2AFD3Akn2rl52sS3QYy5w7faIkad6PIfTD5/DXdETID+QhMPrPoLjwWSM6vqP\net3TMxcTWQNWmbFghy8fxKXbCYwuKbNx+PJB3G0k+7NmjGFAm0D8lCYNiJjiQ0zzYdgcrKq0JBER\nGVWvqjnMM0JEZNSI4HuwZ+oh3PvjPej9ryL0vgxABCKHPYRpHn4oqSjGrG5zEOxe3QPEzUOBsLtn\ntNxJE7UQBkQsWFZRpmT6bN5fBgER3Trl3k7eKEOZZHmf9neY/TxNyZpKSxK1JvrJ2Yha1O2qOTUG\nPG73FtR8F1h6ZR0iIlOL9olBwsPJOHz5IAqrrmGQYgQrQRIZwYCIBevbXlr7/J1j/8b9UQ9KPux0\n65RfL9MbRAhgSuQ/zHuSplbXTTIRNZhu4DTcI6J5hr8R1UUQauwByN6CZJF0ezUBvJchsxPkAu4O\nGsnKSkS1YA4RC5aQe1IyXSlWYqdejhBnB5da95FfahgkafU0N8m8gSAyCd3AaWrhOW1JQWoAJntu\nVpreggDYW5Asg24OtLsHqf8wHxoRUYtjQMSCDTeSL0RuL5dMf3b6kxq393NVNE9VGCJq1SK9ohDq\nHqadfm7vfChVvEGvNyZ7bn63ewsW/Lybw2XIIkh6NaWnQZaepv6ZSYOJnfb0awAAHYlJREFUiFoU\nAyIWTOGqwMPRj0rmpRemaX/OKc7BuuSva9z++7E/slu8EUqVEvE5x/lASDZDkAt4a+AS7XTGjfPs\nJdIArIjSQthbkCyIpFdTaBgqQsO0P6OkhIFUIqIWwoCIhXss9knJ9MyYR7Q//35xV63b6g+5oepc\nCqN+GIaRG4cwKEI2w0VW+/A6qhmHbxBRnXR7Nf32p/rP5h0AAM9JY9m7jIiohTAgYuFc5W5wgAMA\nwAEOcJW7aZf19x9Y43Z2sDc65MbW6edSSMnnm16yDbF+PbXDZkLdwxDr17OFz8iCcPgGEdWHbq8m\nQQBcXDh0hoiohTEgYuE2n9uISlQCACpRic3nNmqXXVJm17jdfwe/z9JbRkR6RSHcQ/2mN9wjwrQ5\nVph0kVoxQS7gt6l/4ufJu/Hb1D85nK6hOHyDiBqIvcuIiFoey+5auLLKMsn09ZLqqjEFpQVGtwkQ\nOmJixH1mPS+z0i1bZ+KHD0EuYNeUvUjJT0KkV5TpHgpvJ12UpZ5DRXgE3yJTqyTIBfRSsHQpEVGz\nEARk79yJK8d3oX3cSLjxvoCIqNmxh4iFi/aJkUyvTHgfOcU5AIDc4muSZWOCx2PdmI348/6jlvv2\ntxmqOWgeCk35O2LSRSIiItKlVCkx4qcx6J/6BEb8NIZ5y4iIWkCrDYhkZmZi7ty5iIuLw6BBg7B0\n6VKUlal7Q1y6dAmPPPIIYmNjMWrUKOzbt0+y7ZEjRzBu3Dh0794dDz30EC5evNgSl9As+vkPgIeT\np3a6UqweNtPNp7tk3cdj5+PuoJGWGwyB5QYW2C2WiIiIdDFvGRFRy2uVAZHy8nLMnTsXjo6OWL9+\nPf773//i999/x/LlyyGKIubNmwcPDw9s2rQJEydOxPz585GVlQUAuHLlCh577DGMHz8eP/zwA3x8\nfDBv3jxUVVW18FWZhyAXMC92vtFlv178pdZpS2SxgQUmXSQiIiIdZs1bRkRE9dIqc4icPn0amZmZ\n2LhxI9zc3BAaGoqnnnoKS5cuxeDBg5GRkYF169ZBEASEhYXh0KFD2LRpE5555hls2LABnTt3xuzZ\nswEAb7/9NgYMGIAjR46gf//+LXxl5nFv2ES8ffRN7fQ9waMBADHe3STrjQi6p1nPyyxuBxbMlUPE\nrDRJF4mIiMjmmS1vGRER1Vur7CESEhKC1atXw82tuoSsnZ0dioqKkJiYiC5dukDQeRDu1asXEhIS\nAACJiYmIi6t+6HRxcUF0dDROnTrVfBfQzNIKUw2mz+b9hVm/zZDMTylMbs7TMh9WcyAyD1ZCIiJq\nVubIW0ZERPXXKgMiXl5ekt4cVVVVWLt2Lfr374/c3Fz4+flJ1vf29sbVq1cBoMblOTk55j/xFpJV\nlCmZ3ntxNyZuHS2ZZ29nj+FBI5vztIjIkjRDwmKiVoPBPyIiIkIrHTKjb8mSJUhKSsKmTZvwxRdf\nQC6XS5Y7OjpCpVIBAEpKSuDo6GiwvLy8vM7jeHq6QiZzMN2JN5PB4f2B/dXTa/76xGCd7yd9j5ig\nsAbv29e3TVNOjcji2GybP/83oJOw2PdaJhDct4VPipqLTbV7pRIYdBeQnAx07gwcP84ehzbIpto8\nEdjmiWrSqgMioihi8eLF+O677/DBBx8gPDwcTk5OUOq90SkvL4ezszMAwMnJySD4UV5eDg8PjzqP\nV1BQbLqTb0bfxH9X5zpbzm7HYEXDeoj4+rZBbu7Nxp6W5VIqLTNHCTWZzbZ5APALhGd4BGSp51AR\nHoECv0DAVn8XNsbW2r0s/jg8k28PIU1ORsGBY8zvZGNsrc0Tsc1LMThEulrlkBlAPUzmlVdewfr1\n67F8+XIMHz4cAKBQKJCbmytZNy8vD76+vvVabo16tetd5zp5xbl1rkNQDxu4e5B62MDdg9idmmwH\nKyGRjbDYamVERERkcq02ILJ06VJs374dK1aswIgRI7Tzu3fvjuTkZBQXV/fmiI+PR2xsrHb5yZMn\ntctKSkrw999/a5dbo6GBw+FmX52A1q0M6JOt/ltjfPikFjgzyyNLOAlZepr65/Q0yBJO1rEFkRVh\nwmKyBQz+ERER0W2tMiCSkJCAr776CvPnz0dMTAxyc3O1f/r06QN/f38sWLAAqampWL16NRITEzFl\nyhQAwOTJk5GYmIiPP/4YaWlpePXVV+Hv749+/fq18FWZjyAX0F3RA4A6CBK/Gjj6mfpvtzLA18UP\no0LGtPBZEhER1Y9SpUR8znEoVWbqpcfgHxEREaGVBkR27doFAFi2bBkGDhwo+SOKIlatWoX8/HxM\nmjQJW7duxUcffYSAgAAAQEBAAFasWIGtW7di8uTJyMvLw6pVq2Bv3yov1WSe6/0SAKD3JSDyunpe\n5HX19I5Jv7KcWz1VxPZERag6+WxFaBgqYnu28BkREdkWpUqJkRuHYNQPwzBy4xDzBUWIiIjI5rXK\npKovvfQSXnrppRqXBwUFYe3atTUuHzx4MAYPHmyOU2u1XB1d1T/Y6S2wAy4psxHsHtLs52SRBAEF\nv/3JpKpERC0kJT8JqYXqikepheeQkp+EXgozJD1lAm0iIiKbZ93dJmxIpFcUfJ19ccIfSPZWz0v2\nBk74t+x5WSR2pSZbpFRCFn+ciYSpxUV6RaG7Sxj6ZAPdXcIQ6WWGpKdKJTxHDlEn0B45hO2eiIjI\nRrXKHiLUcIJcwB/TDmHo9/3R+1+5iM4FzvoCfn4hiPXjsA8iqsXth0NtyV0mmqQWJJQBx9YAjmlA\neRhwYwoAuWmPIUtJgixV3QtFlnpO3VOEpXeJiIhsDgMiVkThqsCxBxORcO0kSipK4CJzQaxfT+YP\nIaJa8eGQWhNZShIc09TVvhzT0szSHjWldzVBQJbeJSIisk0MiFgZQS5gYIdBLX0aRGRB+HBIrUmz\ntMfbpXeZQ4SIiMi2MSBCRGTr+HBIrUlztUdNvigiIiKyWUyqSqSPySXJFjGZMLUmbI9ERETUDBgQ\nIdLFygNERERkLnzpQkTUqjAgQqTDWHJJIiIioibjSxciolaHAREiHRUBgRDljgAAUe6IioDAFj4j\nIiIisgZ86UImxd5GRCbBgAiRDll2JuxU5QAAO1U5ZNmZLXxGREREZA00FZQAsKIXNQ17GxGZDAMi\nRDp4s0JERERmcbuCUsHPu1Gway+TBlOjsbcRkemw7C6RLpYfJSIiInNhuWcyAc0LPFnqOb7AI2oi\nBkSI9PFmhYiIiIhaK77AIzIZDpkhy8MkUkRERERkyzQv8BgMIWoSBkTIsjCJFBEREREREZkAAyJk\nUZhEioiIiIiIiEyBARGyKKwCQ0RkA5RKqI7+iYSMP6FUsScgERERmQeTqpJlEQQUbN4Jp993oWz4\nSI6bJCKyNkol3EcMgmNaGm74ABNfCMOPD/4JQc7PeyIiIjIt9hAhy6JUwnPSGLR95gl4ThrDHCJE\nRFZGlpIEx7Q0AEBUHuCUmoaUfA6PJCIiItNjQIQsCnOIEBFZt4rIKJSHhQEAknyAsvAwRHpxeCQR\nERGZHofMkEWpiIxCRWgYZOlpqAgNYw4RIiJrIwi48eufUJ09iWw/4MeAnhwuQ0RERGbBgAhZnspK\n6d9ERGRdBAHyvoMQ29LnQURERFaNQ2bIosgOH4TsQob65wsZkB0+2MJnREREZqFUQhZ/nLmiiIiI\nyGwYECGL4pCVWes0ERFZAaUSniOHwHPUMHiOHMKgCBEREZkFAyJkUcrGjIcoU4/0EmUylI0Z38Jn\nREREpiY7fJAJtImIiMjsGBAhy+LmhsqOgQCASl+/Fj4ZIiIyuZwceMy4XzspymSoCAhswRMiIiIi\na8WACFkUWUoSZBnn1T9fuQyv0cPYlZqIyIo4/b4LdpUV2mm7igrIUlNa8IyIiIjIWjEgQhalIiAQ\nokN1cSSHrEx2pSYisiJlw0dCdHBo6dMgIiIiG2C1AZHy8nIsXLgQcXFxGDBgANasWdPSp0QmIMvO\nlLw5rOwYiIrIqBY8IyIiMimFAnmH4rXDIitCw1AR27OFT4qIiIiskazuVSzTf/7zHyQkJOCLL77A\n1atX8eKLL8Lf3x9jxoxp6VOjJqiIjEJFeARkqedQ0bEjCn7aDQhCS58WERGZUnAI8o8mQJaSpA56\n83OeiIiIzMAqAyLFxcXYsGEDPvnkE8TExCAmJgazZs3C2rVrGRCxdIKAgl17eZNMRGTtBAEVveJa\n+iyIiIjIilllQCQ5ORnl5eXo1auXdl6vXr2watUqVFZWwoFjky0bb5KJyFZs2wKP5+bD7kah8eX2\n9hA9PFH4n+UAUPO6dnaAgwNQJUKUy2FXVqqerqwEAHg6OACVVagS3GB/qxgQqwBBQPHQ4XCQyWF/\n9RLsqkTcfH0RAKDNs/Mhy85ElUwGwA52DvYoGTsBZf+4H64/bkKlnwJlXt7wWLEcha+9CYyf0PBr\nP3EMbV55CXbXcwFXVxS9/S5w5+Dq5Wf/gvDJSijnPg5ExzR8//rbb9sCj+efgl3xLVS6ucGhpAQo\nLa1eXy5HhbsnZIX5QIV66Kbo5AS7sjLA0RGivQPsSksAmUy7vKVVKdrhxrIPgRH3SBfs34e2Tz8O\nhyuXgaoqdRv65yy0Xb8ODlcu324jZdXr29mhsmMgit5+F7KyUjjGn0DxzEeA4JDqdXTbqkyGsoGD\nUPzOe9J19M9h/mNwuJStnSU6O6uPK4om/C0Y51nbQnt7iO4eUD70Tzj4+6NszHhAoahervn9Xb6k\n/j/k6AhRJlcP6bWzR6WLMxxu3lS3A0dHqAIC4VBwHfZFNwGZA6qcnWEnihDt7WEniqiSyeBQXAxU\nVGqPX+Xmiiq5I2Q5V9XzzNWu7OwAe3vtZ4HFcXVFwaKlwEMPm/9YSqXtvpCz5Wsnq2cnis3wrdPM\ndu3ahf/7v//D0aNHtfPS09MxevRo7N+/H35+xsu15ubebK5TtAi+vm34OyGbwjZPrcq2LfCZNQN2\n9VhV80Ven3Wboq7jiDrLND+LAPI++7phQZETx+AzerjkOCKAvB+2q4MiZ/+Cz9D+1fvfc6hhQRH9\n7V//N3zefM3sv7+WIALIW7uhOiiyfx98Jo8zuFbdf7va9qX775t3NEEd8KihrUrW0VXDObRWolyO\nvJN/q4MiFnbutkAEkLfsQ/MGRZRKeI4coh6yHR6Bgl17LSow0KT7Gwu/dmN8fdu09ClQK2KVPURK\nSkrg6OgomaeZLi8vr3E7T09XyGTsPaKLHxhka9jmqdVY8ma9V22uh7O6jmNn5Gc7AL5L3gQefaj+\nB/roPaP79l22BJg0FvjyU+n8Lz8Fvvyy/vvX337Z0vpva2HsAPi+swiYPkU9Y9mSGterz74k+926\nAVi8uMa2KllHVw3n0FrZqVTwPboPePRRizt3W2AHwHfpIuDZJ813kPN/A6nnAACy1HPwvZYJBPc1\n3/HMoNH3N1Zw7US1scqAiJOTk0HgQzPt4uJS43YFBcVmPS9Lw7flZGvY5qlVefl16+kh8vLrQEP+\nbz3xLHx++smwh8hzL6v38/Ac+Hz1VfX+H57TsP3rb//cAuvuIfLSwurfz3Mvw+eQiXqI3DtVvd8a\n2qpkHV01nENrJcrlyOs7WH0dFnbutkAEkLdgYcM+AxrKLxCemqT+4REo8As07/FMrEn3NxZ+7cbw\n5RfpssohMydPnsT06dORmJio7Rly5MgRzJ49G6dOnYJMZjwOxAchKT4ckq1hm6dWpxlyiMgAVDCH\nCHOI2FAOERmAWv+FmEPEcjCHSL00+f7Ggq/dGAZESJdVBkRKSkrQt29frFmzBn37qrt0rVy5Evv3\n78f69etr3I4PQlJ8OCRbwzZPtojtnmwN2zzZGrZ5KQZESJd9S5+AObi4uGDChAl48803cfr0aeze\nvRv/+9//MGPGjJY+NSIiIiIiIiJqBawyhwgAvPzyy3jjjTcwc+ZMuLm54fHHH8fo0aNb+rSIiIiI\niIiIqBWwyiEzjcWuZFLsXke2hm2ebBHbPdkatnmyNWzzUhwyQ7qscsgMEREREREREVFtGBAhIiIi\nIiIiIpvDgAgRERERERER2RwGRIiIiIiIiIjI5jAgQkREREREREQ2hwERIiIiIiIiIrI5DIgQERER\nERERkc1hQISIiIiIiIiIbI6dKIpiS58EEREREREREVFzYg8RIiIiIiIiIrI5DIgQERERERERkc1h\nQISIiIiIiIiIbA4DIkRERERERERkcxgQISIiIiIiIiKbw4AIEREREREREdkcBkRamczMTMydOxdx\ncXEYNGgQli5dirKyMgDApUuX8MgjjyA2NhajRo3Cvn37jO5j27ZtuP/++yXzlEolXn75ZfTt2xd9\n+vTBwoULcevWrVrPpSnHM6a8vBwLFy5EXFwcBgwYgDVr1kiWHz58GJMnT0aPHj0wcuRIbNy4sc59\nknWw5XaflJSEBx54AD169MCECROwf//+OvdJls+a27xGeXk5xo4di0OHDknm5+TkYN68eYiNjcWQ\nIUOwbt26eu+TLJs1t/varg0A9uzZg3HjxqFbt2649957azweWRdrbvPp6el4+OGH0aNHDwwdOhSf\nffZZo45H1OJEajXKysrEUaNGiU8++aSYlpYmHj16VBw2bJi4ZMkSsaqqShw/frz4zDPPiKmpqeKn\nn34qduvWTczMzJTs4/Dhw2L37t3FadOmSeY/99xz4uTJk8WzZ8+Kp0+fFseNGye++uqrNZ5LU49n\nzKJFi8SxY8eKZ86cEX/77TexR48e4o4dO0RRFMWMjAyxa9eu4scffyxeuHBB3Lp1qxgTEyPu3r27\nvr8+slC23O6vX78uxsXFiS+++KKYlpYmbtq0Sezevbt4+vTp+v76yAJZe5sXRVEsLS0VH3/8cTEi\nIkI8ePCgdn5lZaU4ceJE8ZFHHhHT0tLE7du3i9HR0eKBAwfqtV+yXNbc7mu7NlEUxdTUVDEmJkb8\n5ptvxMzMTPGzzz4To6OjDY5H1sWa23x5ebk4dOhQccGCBeKFCxfEP/74Q+zRo4e4devWBh2PqDVg\nQKQVOX78uBgdHS0qlUrtvG3bton9+/cXDx06JHbt2lW8efOmdtnMmTPF9957Tzu9YsUKMSYmRhw7\ndqzkg6yqqkp85ZVXxMTERO28r776ShwxYkSN59KU4xlz69YtsWvXrpIb45UrV2q3W7lypTh16lTJ\nNq+99pr49NNP17pfsny23O4///xzcciQIWJ5ebl2+cKFC8Vnnnmm1v2SZbPmNi+K6oe/8ePHi+PG\njTMIiOzdu1fs0aOHWFBQoJ23cOFCccWKFXXulyybNbf72q5NFEXxzz//FJcuXSrZJi4uTty2bVut\n+yXLZs1tPisrS3zqqafEkpIS7bzHH39cfO211+p9PKLWgkNmWpGQkBCsXr0abm5u2nl2dnYoKipC\nYmIiunTpAkEQtMt69eqFhIQE7fTBgwfx+eefY8SIEZL92tnZYfHixejWrRsAIDs7Gzt27MAdd9xR\n47k05XjGJCcno7y8HL169ZLs78yZM6isrMSoUaOwcOFCg/MuKiqqc99k2Wy53WdlZSE6OhpyuVy7\nvHPnzpLjkfWx5jYPAMeOHUPfvn3x/fffGyw7cuQI+vbtCw8PD+28t956C0888US99k2Wy5rbfW3X\nBgB33nknXnrpJQCASqXCxo0bUV5ejtjY2Dr3TZbLmtt8QEAA3n//fTg7O0MURcTHx+P48ePo169f\nvY9H1FrIWvoEqJqXlxf69++vna6qqsLatWvRv39/5Obmws/PT7K+t7c3rl69qp3+7rvvAABHjx6t\n8RjPPfccduzYgQ4dOtR6A2qq4+nuz93dHU5OTtp5Pj4+UKlUuH79OoKDgyXr5+XlYefOnZg3b16d\n+ybLZsvt3tvbG2fOnJFsc/nyZRQUFNS5b7Jc1tzmAeCBBx6ocVlmZib8/f2xfPlybNmyBYIg4OGH\nH8aUKVPqtW+yXNbc7mu7Nl3p6ekYN24cKisr8dxzz6Fjx4517psslzW3eV2DBg3CtWvXMHToUIwc\nObLexyNqLdhDpBVbsmQJkpKS8Pzzz6OkpETyFhkAHB0doVKpGrTPuXPnYv369WjXrh1mz56Nqqoq\no+uZ6ni6+3N0dDTYH6BOvKeruLgYTzzxBPz8/Gq9sSbrZEvt/p577sHff/+NtWvXQqVSISEhAT/8\n8EOjj0eWyZrafF1u3bqFrVu3Ijc3FytXrsTMmTPx1ltv4ffffzfL8aj1suZ2r3ttunx9fbFp0yYs\nXLgQH374IXbt2mWS45FlsNY2v2rVKqxatQpnz57FkiVLzH48IlNjD5FWSBRFLF68GN999x0++OAD\nhIeHw8nJCUqlUrJeeXk5nJ2dG7Tv8PBwAMDy5csxePBgHD9+HKdOncKnn36qXWfNmjVNOt6JEycw\ne/Zs7fScOXMQFBRkEPjQTLu4uGjn3bx5E3PmzEF2dja+/fZbyTKybrbY7gMCArBkyRIsWrQIixcv\nRmBgIGbMmIEvv/yyQddHlska2/zcuXNr3cbBwQFt27bFokWL4ODggJiYGCQnJ+O7777D8OHDG3KJ\nZKGsud0buzZdbdu2RZcuXdClSxecO3cOa9eu1b5RJ+tlzW0eALp27QoAKC0txUsvvYQXX3zRZNdH\n1BwYEGllqqqq8Oqrr2L79u1Yvny59gZRoVAgOTlZsm5eXh58fX3r3GdpaSn27t2LQYMGwdXVVbu/\ntm3boqCgANOmTcOoUaO06ysUCpw4caLRx4uJicGWLVu00+7u7jh//jyKiopQXl6ufUOem5sLR0dH\nuLu7AwDy8/Px6KOPIi8vD19//TUCAwPrPBZZB1tu9/feey/GjRunPc63336LDh061Hk8smzW2ubr\n4ufnh6qqKjg4OGjnBQcH4/Dhw3VuS5bPmtt9TdcGqPNJFRcXo2fPntp5YWFhOHnyZJ3HI8tmrW0+\nJycHf/31F4YNG6adHxoaCpVKBaVS2aTrI2puHDLTyixduhTbt2/HihUrJEmNunfvrv1C1YiPj693\nQq7nn38eBw4c0E5nZWXhxo0bCA0NhYeHB4KCgrR/nJ2dm3Q8Z2dnyf48PDwQFRUFuVyOU6dOSfYX\nHR0NmUyG8vJyzJ07FwUFBVi3bh1CQkLqdV1kHWy13R89ehTz58+Hvb09/Pz8YGdnhz/++AN9+/at\n1/WR5bLWNl+XHj164Ny5c5Ju02lpaQwC2ghrbvc1XRsA/Pzzz3jjjTck886ePct7HRtgrW0+PT0d\nTz75JK5fv65d7+zZs/Dy8oKXl1eTr4+oOTEg0ookJCTgq6++wvz58xETE4Pc3Fztnz59+sDf3x8L\nFixAamoqVq9ejcTExHolonN2dsbkyZPxn//8B/Hx8Thz5gyeffZZDB8+3KA7p0ZTjmeMi4sLJkyY\ngDfffBOnT5/G7t278b///Q8zZswAAHz55ZfasYcuLi7a6y4sLGzU8chy2HK7Dw4Oxv79+/HVV18h\nKysLH3zwARITEzFz5sxGHY8sgzW3+bqMHj0aMpkMr732GjIyMrB161Zs3ryZ+aJsgDW3+9quDQDu\nu+8+ZGZmYvny5bhw4QK+/vpr7Ny5E3PmzGnU8cgyWHObj4uLQ2hoKBYsWID09HTs2bMHy5Yt0w6l\nae7vFqImacGSv6Rn6dKlYkREhNE/KpVKvHDhgjh9+nQxJiZGHD16tLh//36j+/nwww8N6oeXlJSI\nixYtEvv37y/27NlTXLBggaQ2uDFNOZ4xxcXF4osvvijGxsaKAwYMED///HPtsokTJxq97vrslyyb\nLbd7URTFffv2iaNHjxa7d+8uTps2TTx9+nSd+yTLZu1tXldERIR48OBBybz09HRx5syZYkxMjDh0\n6FBxw4YNDdonWSZrbvd1XZsoiuLx48fFSZMmiV27dhVHjx4t7t69u9Z9kuWz5jYviqJ4+fJlcc6c\nOWKPHj3EgQMHip988olYVVXV4OMRtTQ7URTFlg7KEBERERERERE1Jw6ZISIiIiIiIiKbw4AIERER\nEREREdkcBkSIiIiIiIiIyOYwIEJERERERERENocBESIiIiIiIiKyOQyIEBEREREREZHNYUCEiIiI\niIiIiGwOAyJEREREREREZHMYECEiIiIiIiIim/P/RF7Br0SCxakAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = dataset.plot_analysed('CODtot_line2')\n", + "ax.legend(bbox_to_anchor=(1.15,1.0),fontsize=18)\n", + "ax.set_ylabel('Total COD [mg/L]',fontsize=18);ax.set_xlabel('')\n", + "ax.tick_params(labelsize=14)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['TSS_line3', 'NO3_line3', 'CODtot_line3', 'CODsol_line3',\n", + " 'TSS_line2', 'NO3_line2', 'CODtot_line2', 'CODsol_line2',\n", + " 'TSS_line1', 'NO3_line1', 'CODtot_line1', 'CODsol_line1', 'Cond_ns',\n", + " 'Turb_ns', 'Temp_ns', 'Ammonium_ns', 'Cond_es', 'Turb_es',\n", + " 'Temp_es', 'NH4_infl', 'NH3_line3', 'Turb_rz', 'Cond_rz', 'Temp_rz',\n", + " 'PO4_mixinggutter', 'TSS_efflPST', 'NO3_efflPST', 'CODtot_efflPST',\n", + " 'CODsol_efflPST', 'TSS_efflRBT', 'NO3_efflRBT', 'CODtot_efflRBT',\n", + " 'CODsol_efflRBT', 'Cond_line1', 'Turb_line1', 'Cond_line2',\n", + " 'Turb_line2', 'Cond_line3', 'Turb_line3', 'NH4_efflPST',\n", + " 'PO4_efflPST', 'PO4_sandtrap', 'NH4_splittingworks',\n", + " 'PO4_splittingworks', 'Flow_line1', 'Flow_line2', 'Flow_line3',\n", + " 'Flow_total'], dtype=object)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.columns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of a package-specific filtering, data points can also be filtered and replaced by other filtering algorithms, such as the Savitsky-Golay filter as illustrated below. The disadvantage of this is that no tags are added to the ``meta_valid`` DataFrame and that original data are replaced (when the ``inplace`` option is set to ``True``)." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:54:59.895406", + "start_time": "2017-05-09T11:54:59.892052+02:00" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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7HyQ/P59vvlnK9evXaNasOVZWVowZM5b333+X+vW96NSpC7t2befs2TPY2Oi/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\nMnjwYHbt2sWSJUsICwsDlHd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1/Tl4bb/O/W3LmWZe08lAWQghTCDCp73WD9HU3BRSciRH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\nfiH7OtAjCNG+Hewn+gBg8P9b2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GMNqUhXq8lYLvOg71uDsI88uyab1WOQSvAylmZ6kZhX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\n5rjy4otaYJeUdObfZdnZ4OIC7u7lr2/a1JviYgNdu5b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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.savgol('TSS_line3',plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check the reliability of the filling algorithms" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In order to be able to make a choice and apply the best method to fill gaps in the data, the ``wwdata`` package provides the option to check for the reliability of each filling algorithm. This is represented in the below figure.\n", + "\n", + "![validation](./figs/packagestructure_reliability.png)\n", + "\n", + "In wording, the workflow of the ``check_filling_error`` is as follows:\n", + "* Randomly (!) create large or small artificial gaps in the data within the given ``test_data_range``. \n", + "* Fill the created gaps with a chosen filling function (see [further in this notebook](#Fill-data) for illustrations of those).\n", + "* Compare the original data points with the filled data points and calculate the deviation between them.\n", + "* Iterate for a given number of times, to average out the random creation of the gaps.\n", + "\n", + "Before applying this, it is wise to check the total number of points within ``test_data_range`` and then determine the number of gaps to create. Take into account that the length of the gaps is sampled from a uniform distribution between 0 and the maximum length of a gap given as an argument. \n", + "For example: creating two large gaps of 50 datapoints in a dataset containing 100 datapoints would mean a theoretical average of 50% data recovery (2*(50/2) = 50 data points are left out of the 100; the 2 gaps can however still overlap)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4895" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(dataset.data['2013/1/1':'2013/1/17'])" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Average deviation of imputed points from the original ones is 39.46857910106997%. This value is also saved in self.filling_error.\n" + ] + } + ], + "source": [ + "dataset.check_filling_error(100,'CODtot_line2','fill_missing_standard',[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", + " nr_small_gaps=70,max_size_small_gaps=12,\n", + " nr_large_gaps=3,max_size_large_gaps=800,\n", + " to_fill='CODtot_line2',arange=[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", + " only_checked=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Average deviation of imputed points from the original ones is 54.261283673154466%. This value is also saved in self.filling_error.\n" + ] + } + ], + "source": [ + "dataset.check_filling_error(100,'CODtot_line2','fill_missing_daybefore',[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", + " nr_small_gaps=70,max_size_small_gaps=12,\n", + " nr_large_gaps=3,max_size_large_gaps=800,\n", + " to_fill='CODtot_line2',arange=[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", + " range_to_replace=[0,10],only_checked=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Fill data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Filling data can be done using a range of functions implemented in the package. Again, a new pandas dataframe is created (``dataset.meta_filled``, see also below figure), starting from the ``dataset.meta_valid`` dataframe, and updated with tags indicating what filling method was used to obtain a certain point.\n", + "\n", + "![validation](./figs/packagestructure_filling.png)\n", + "\n", + "Using the ``only_checked`` argument, implemented in most filling functions, the user can always choose whether only data points tagged as ``filtered`` will be filled, or all data points within a certain range.\n", + "\n", + "When using the plotting argument to plot the analysed data, the user will see a plot based on the latest function that was used; if this was a filter function, the data will be plotted based on the ``dataset.meta_valid`` dataframe, if it was a filling function, the tags in ``dataset.meta_filled`` will be used." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Interpolation\n", + "Fill missing data points by interpolation, if number of consecutive missing points is lower than a specified number." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:01.060520", + "start_time": "2017-05-09T11:54:59.898063+02:00" + }, + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:324: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n", + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:367: UserWarning: Data points obtained during a rain event will be replaced. Make sure you are confident in this replacement method for the filling of gaps in the data during rain events.\n", + " 'filling of gaps in the data during rain events.')\n" + ] + }, + { + "data": { + "image/png": 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d++67j2+++YaWLVua2rt06cJLL73EoEGDrltDUlJ6+d5UNdawobPeD7E66vdi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HAAAg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\nu9DfRrwGBJ4CfC5wK3wuAIGncG/vUV17YIQQQkgbK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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_interpolation('CODtot_line2',12,[dt.datetime(2013,1,1),dt.datetime(2013,1,31)],\n", + " plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Average daily profile\n", + "Fill missing datapoints by using an average daily profile. The ``fill_missing_standard`` function requires the running of the ``calc_daily_profile`` function, also developed for this package, first. This creates a dataframe (``dataset.daily_profile``) containing the average daily profile calculated within a defined time period (e.g. selecting only non-peak days for example)." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:01.103135", + "start_time": "2017-05-09T11:55:01.063627+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_HydroData.py:1593: UserWarning: Data points obtained during a rain event will be used for the calculation of an average day. This might lead to a not-representative average day and/or high standard deviations.\n", + " 'representative average day and/or high standard deviations.')\n" + ] + } + ], + "source": [ + "dataset.calc_daily_profile('CODtot_line2',[dt.datetime(2013,1,1),dt.datetime(2013,1,8)],\n", + " quantile=0.9,clear=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:01.844129", + "start_time": "2017-05-09T11:55:01.105608+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:675: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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Bl156ib59+142hrS0nBt7UzcxLy93PQ+xOxr3Ym805sUeadyLvdGYt+bl5W7r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vTs2RNpaS0LVBMcoyO/eFzhPqlftVMqlIITsgjvKFGybL7+8wte29tDl/MmojRF4//6v2TUdTBz\nmvv63A8tfndCLnNCOjfdgrpj35w9kCzobyz1Ajj9/V6Y0+LP5tb8+3Gzo/wSMAm8mSGDDOvGsw6u\n6VvGY815Y4mTXEI5bA1e5r2fF+Cr1dQa7iOD7ldzFlCpJtehfvSYC8fqeXfY+7ysPyFReT1iGlDs\nyNmGJolZ9lrzpH9Gl9k2ncNcC8w8eKuHIx4P4MVDyzDkf/1woexPvHv6LcsdNA/6G2q52V/P7ePr\nmdn7TDDVUsucewl9QvvhbwNe5x0nhVQ0C3pTkgKSEe3dWXBfdaMxUB3hzdXCNN8WEyH3xOvX/8/O\nszTi6tWBaGiw7v4qVNp148Y/7OhHx9H1qtPUCh6VU3kFg77rg6X7nkHvb7paDHxd6CRB+HPAvElA\n5FIgSy7spnes+AinNMjHzQdHZp02aPHN7T6Pc7z5dkfHYGzR/D6q/+YEpjCnwMBYHu3ZtTfeefU8\nNs0imqGuRp55FvIcNrAqLy1F0OihRNvLSQaEDeJoXglh+t6mKZq3cHep/KJT1xDu1gWyz84ag1MA\nLyP5lf6v4cDM41DIFAJnaML4zaN578nSvBDegl+Mb2yrBabFXrAmEAiEtsBq0Esmk+Hjjz9GeHg4\nPv74YwwZMgTz58/HG2+8gQ8++ADvvPMOFi1ahGHDhuHrr79GTEwM1qxZA6nU6mkJDsKoGYzeMBRj\nfxzpMgFqV+Jq90mhCZlYWTapZu6BwZ4hFrOi9DpFAHhOc5qbiVY1lADhCfJj3Z8QnIR0C+qO3xee\nxbghSnZgZdbf/jM3rN4n1nR6bEHIQUgLLY4WH+YENPRomtQOfwfxylBBLSd9wGl83CTIJWygxTSL\nw1GSApIR48Mv1Q6nI3iBIyFReT00RWPd+A14tvfzWDd+g1OTSW83HyDsNBB4iW0IvASEnYa/WwAe\nSp5l0znMnSmFgrf66353+PuctiKmEJO3juMd6yFtNnEwC/Kaao5du53Lu78ceSboS3z1AYseIT15\nx+igw8nrxzhtYgzcaYrGm0PfFdzXI8h4Hf5mLovm22Kid0+MiclAbOx+6HQ1aGgwd1AOsOlcJSVv\n2N2/Wl0s0GppDEDB25tdFFOVZ6Gs3sRcwCRDFYAhk1CtU1s0AUkKSIZvZCK+7A34Rlq+f8yNMNyk\nbpzMr2BFiCGYGe3dWRRX0/ZEjG8s1o3dwHk/XEIyLsBEWNvTk2iGthESDXuvE20vx6EpGnunH7Lq\nvGqu1dmvU3/OdkpIL4f7Z9QM0j99AdrSZkmH5uBUkEcQgj3Z50m0T2c83mMhlAol/jX4HcHzlNWV\n8t6T4++NAxXSvIDZvOBnzYlSbFyxYE0gEAitTYtPzbCwMPz000+YPXs2mpqacPjwYXz77bdYu3Yt\nvvzyS+zbtw8ymQwLFizATz/9hIAA2wbXBPvJvHmWE6BwRBy5LWkL98mkgGRDOVo4HYEI7yiDALc9\nTj3dg3pwtjdM3GL1+mN8Y5vLDy/yspNassb2kPNdIK2JbisVSszu+gi7YVbueF6yDsO/H2Bxgm/6\n+4nzi7c7EGmpfDIluDcnoKHHmWy7AWGDEODjwVs53XrlJ8P/B3my5Qrh3hFWBeZtgaZovDdiJa99\no+oHNDVxFbRNS9vMKaktwaDv+uL9s8sx6Lu+DjtEMWoG/zz6KvuzP9GnWZi6D+Beg1WjP7b572lA\n2CDDBL+TIhT9Qi3ruCX4J0EuoThtlQ18c5N6XT2CPIIgKb3Hosacl5zm3V9iPBNMHSBNOVh4gLMt\n1sDdUnnupC1jDN+tra6UYiGT0VAo2EzP7OyBALjZgJ07b0BiYjaUyvcQFPRvSKVdBc9TX2/f76Sq\n6heo1dznWXDwu0hMVCE0dBUiIjbA3X0waHoygoNfQ2LiRVAUG6zkZM1ZCZYC/ECtHlvvn/Fxkzhl\nsGX1ZZzvX1WehbzqawCAvOprd+Sk7v6YMXjzwccM74cuyEI3sMLa1cH+0KS49h4lGNGk9IYm0nhP\n698mRNvLOZQKJQ7NPIn0hOmC+5P8unC2Q+kwq9v2oCrPQpHnL5zx19tTHsfJOb/jxMOZ2DUlg6PL\nODlxCnzcfAXPZZ45rvTzwtnDXnh27SbDgl9rzgFcvWBNIBAIrYFNSwU0TePVV1/F0aNH8eWXX+Jv\nf/sbli5ditdeew2ff/45jhw5gmXLlsHd3YJtCkEUzAMMLek1tUdoip34qsqzRM9Uy626ijePv44L\nZX9ySkA1WnYVtYgpxITNo9H7m67NZTPdbA5AmFvYnzDLIhGiW1B3nJh3GO5PDOFkJzGN1ktUzSfV\nSkWnFkW3B4QNgo/cR9DZLr86z/rgqMnsXzsorS0VbD9x/RhoisbmB3fAz92Y5eJMth1N0fjxgZ95\n7R+fX42S2hKM2TgCN2qvAwDybl8TZUCY4J/EukaasPz0W3j58F85baalbebsyNkGTZMaAJvp5qhD\nlKo8Czfrmu9XEyH3EIXSblF2fTbujdrreHDLWIv3YmF1vuHa9QS4CS9slNWX4bHhA/gac83UaBiU\n1t7kfc7Z7BJ9ZuX0xJmcdvPyEbEG7ikhvREooMmiadJwMpLeHf4+Nj+wvUVXSjFhmAw0NXH/Jt3d\nh8PLqx8oSomgoAVQKhcjOfk4OnXiu82q1VdbLHHU09BwFYWF5pNLNwQGzgZFKREQ8Ah8fccgPn4n\noqO/RkjIMkPAC2C/t0UpzfqHZhmqpsFSAIj3s6zXY8v9o1QocXT2GYQ0Zweaf/9ilcG3d+b3m41l\nH2+GxyP9sT6gL2jUoMBXivJf98FhAUSCY5gYREkAaEOUqNi8g3wPTkJTNF7o97Lgvu1XuRmjrMmM\nUSPSWpZYSyQFJEPp780ZfyWEhIGmaMFnFE3R2DPNZGHGJNN1/cVveedX+nnh8bEpkLkbxfaX7V/c\nKhUfbbFgTSAQCGJjV36sp6cnBgwYgNmzZ2PhwoWYOXMmBg0aBIqiWv4wwWmuVuZY3e4IXCj7Ez0/\n7oOxH7yEYd+MEu2FfaHsT/Rfn4L3zy7HiA0D2RLQjUNZcfPmFXyADYaodewkXq1rxN683RbOaIRR\nM1h1jlvmFawItnA0lxjfWDzZ/1FOdtK3F7+0WmJlPvD6fsLmFgcZNEVjz4yDbMq7gLOdpcGRs+WN\n4+Mm8YJCAODt5g0AOFiwD5UNRuc6Zx2HhHS2btWXYW/ebhTVcI0G6jTCmlz2UFidjyaBaKBpmxRS\nq6WU5lkqH59f7dB97yETzjB6a8i7dg1CVeVZHLFca9bnpoGicK9wrB+/ETOSLWuHbcr/wjjonzuc\nDV6YZO0IaeOJAU3RiPfnZhWuv/Q1J6gt1sCdpmj8x6zsU8/qcx+gpLYEozcORfrWCfjrgWcd6sNR\namtPCbUKHhsY+BA6d94LIJBz7JUrvQxi89aoqFjHa3Nz6wqZzPbfK1uSTAG+1wBZ82RO1sBum2Be\nluQIMb6xOD77nOD3/3tppmhmE+2dp++dh9CUMgxdWIPxzwSh+uhZKMKJ43ZrIldlQV7EfV/JbpZA\nnq1qoyu6s4jxjcWJ2ZlIixrLaTeXqWDlL9jxoLZJi/StExwek9aoa1BWW8oZf609v6rF61w3dgMv\n03Xl8Y8EBe2zK1TQQmPYzq262mpZqaT0mUAgdHRsDnpdvXoVFRXCtusrV67E6dOnRbsogjBuMner\n2+2d3KqrGPHtaFSv2Qt8dgIF723Cp6e+dUqYv6S2BF/88Ske+GkMb19O5RWeKLxS0cmwskdJ3TAq\numXThcybZ1Fax89QsRUvN+4gQa+DZanEyjyr7GDhfpv6ifGNxbHZZ+ElMOm0NDhyNvtFqVBi1ciP\nee3VjdUAgJ052zntzjoOJQUkI1TBLUGQQYaBYYN57Y66RJr3J1Q6Z8r2yb8a9KWEGBA2CKFexmsr\nrilyaKC68ux/Bdv9PewrKRcS3bcmxP+PQW8g1CsMRTVFWLznSRwv4psX6LndWAV/2o3N8Pp6P69c\nLdKFGTTmJcC3G2/j/o3DOM8WsQbuI6JGGrKGTClg8rEjZ5vB/S+nUrwSFK2WQW3tKWi1lp+VND2a\n1+blNcTi8W5u0QDMxd+bUF6+rsW+vLyGCfQv7J5oCaVCiXNzL2II/SigbX6fad2Bqs6c4waGDbbr\nvJYQ+v5Lakswd6dRD681BaLbApqikTHjMDbNysCql35HcDAJeLU2mqRkaBLY967pkor3008AJY6V\nvxO4xPjGYm3a54j26QyA1dMy12FNCkhGuFe4YbuIKXToec2oGQz/7l5oGzw4uoTPpf61hU8CpfU3\nBTNdbVkgCqcj7uhnFYFAIIhJi0GvxsZGLF26FBMmTMCBAwd4+0tLS7FmzRrMmTMHTz/9NBjiPOMy\n0hOnGYS6pZBiaMTwtr0gG9E7Tr5x7J+8l/tb2390WJi/pLYEvb/pihcPLcNttXB5Wb2mzqDlIoMM\n2yb/gsMzT+HZ3s/j8MyTVoMVeoQyhiyV9QlhSY8rzldYQ6tB22B12xoxvrGYlfwwrz3IM9ji4Ogf\ng97A20Pew+YHdzgUDPATEOkeEcVOfoW0eKwFWFqCpmj8e8jbnDYttLhSmQ25zOgWKJfIRXHvoyka\nrw+24lQIQCLlZ7qZn+PXaQcMAZ+WgouWHFqzKy7zjlUqOtmtFyWUNSPUphd+n71jGq7XsGLltxpv\n4VzZGYvnDqcjMCJ6lMVyNdUtfrBPLEfaAWGDeFbw12uKWzSOcASaovHzZH6WqEwiszkL1B60WgZX\nrw5Hbu5IXL063GIwqqaG/44OCnrS4nlNnRRNKS//r+h9WUKpUOL1yQ9bLIsFgPJ6YVdGZ2EY4PNd\nmdDUG51rF/Z4+o7PZiBZG20MTaNi937cXrGKkyctv16MgHEjiYOjSNAUjX0zjvL0tEz3v3zva5y2\n3ErbyrtNUZVn4VZ1PSdbK8ajB/qE9mvxs6Oi0wS1X7df3cp7J6aE9EaMLxukDvUKwy9T95G/YQKB\nQLARq0EvrVaL+fPnY9euXejUqRP8/fmTW09PTzz//POIiopCRkYGnnzySZ7IM0EclAol9kw7CJlE\nBh10uH/TcIdFsVsLRs1g9EbWcXLb1Z94Quv6yU1O1RXsurrdypn4bL680ZCabom3Tv4LWmgBGIMj\ns3ZMxftnl2PWjqk2TbTrNfWcbZlEZpcz4ICwQQh0D+K168zEpvXE+cVxtq2J2Asxvyd/4vlc6gu8\nwZHeDXT2jml48dAyTPopzaHAg1BGVRHDlm4EePIDXM6WKnkI9He48CAKTDLINE0aZFeIUyrSUsaY\npbJDU7woL3xw3xpsfmC71dI6aw6tT/Z4hnOsr7sf9k4/ZPegd1R0GiRmj/6UYH7gTMh9EwDPZY9z\nnqBerDivhb/zXXk7OD+TmFboNEWjV3Aqr/3/Diw1nNcREwtLCAVitE1aXpszOjF6Ghqy0NjIfheN\njZfR0CCcKejvzw14d+68l6OjZQ7rpMiXJ9Dpqjl9CQUm7e3LGvWyUkFnVsDy4oCzMAyQlqbA+4um\nAp+eBhq8QEkpp11fCQSboGk0PJAOTRw3k1hWkA/5MfED9XcrLQV4y+rKONvPH1hi9/shwCOQt9Az\n0nOpTZ9VKpTYN+dXQS1WoYxwqUTK+ZdAIBAItmH1qfn999/j5MmTmDRpEn799VcMGyZUzkBj/vz5\n2Lp1K0aOHIkzZ85g06ZNLrvgu53M0rOGiZWtmlRtSebNs4ZSHzR4sQODucMFJzdPZzwhqGNgCXsy\noPSsPbcKOSXXgcJ+yCm53mKgjVEzeGE/d/Dyf31fsSlDTA9N0ZgQ/0DzRRsDBkIlh4yawZvHXzds\nR/t0tlukPMY3FvO7cwNfbx17nRdQMNXzAtgSSEdS+1NCenPK90wRCtiJVapkyjcX+KUAYmh6AazY\nrTV78I2q761+Xh/YSd86AUsyFqFGXWPxWEsOrSW1JViybxHn2C/HrLPrPtSjVCjxj4H/5vZbyv/e\nBUs7W3DZSw7qhkW9nhE0VGB/jhuce0xsK/ROdCdeWxFTCFV5VnNmaDe7TSwskbdnmtsAACAASURB\nVBSQjJBmK3o9vm6+OH/zPKdtm4m7qCNotQx0ujq4ubHfhZtbItzdhYNAcnkIZDI2o1Ami4KHh7BL\nox6KUiIx8SL8/ccK7ndzS4RGFiUYmLS3L2skBSRD6UdztQibn5WaBr6brRioVFJkZzc7OpZ1QdcL\n3RArUzrt+kog2AxNo2LPQVSs3wit0vjs8nvkISDX/owjgv3E+3NNMprQhBcPLMOevN0oqS2xKQt5\nX34Gb6FnRB/+u8gS3YK64/NJH/G0WM0X1FTlWYbxdBFTiHE/jmwVIXsCgUC4E7Aa9Pr5558RFhaG\nN954A3K53Nqh8PDwwDvvvAN/f39s2bJF1IskGBkVnWaiSUXZpEnVluRW5rL/YzpZ/no/K1RsJnIN\nACtPC+sWCRHnZ11rSYjDuac5k/andy61GmhTlWehrIG7EnioiF/W0xJJ/l14AQNKHcDLYDAPRK0Y\nscqh9HXzgrtq7W18n7We0xbhHWU1mGMrNEVjy4M7DaW3lJQylBaa61kBzpcqCWVe1WhqEOQR1OJx\njlBYnW8xKw9oORPPNLBTwBRg5IbBhoCLeQaNeaBOv7358kZDxiLAlqvaW9ZoinlptFCmF03ReK7P\nC9xGs9Vsr4p7Dd+7XCrH3O6PG0SEF6TOgU/MJc4g3vRnAsS3Ql+c+hyvTQYZAjwCsTdvN0es3NkF\nA5qi8cNE7ruuqrEKX/zBdUW8WeN4cE2rZXDlymDk5U2ARsMgMnIjYmP3WxSLZ5gMaLX5zZ/NR11d\ny0FsilKiSxd+0NjHZx5iY/cjuzJfMDBZU3PE7r4sQVM0/j7wX8YGk2dl3vINOHbtvOUPO0hSkg4J\nCezfVJw0Cye2XcBPKwpx6spe0fsiECxC09CMTkPNUqP+k0SrRcDENFLm2ArwnGEbvLDj0A3M3vwo\nUr5OxtgfR2LkhsFWg0uRPlGchZ6QJRMxoHNPu65jRNRInh7rVxc+52wnBSQjko40bBdU57eakD2B\nQCB0dKzOeLOzszF48GCb3RlpmsagQYOgUhEHGlei10QKo8NbfVXaHv2d09dPYtkBC5b0nx0XzBb5\nXrUeF8r+tOla/AW0pFpEQGvo74dewuGig4I/U1JAMk8naHL8VLu7LawuAIr6cPpWl8Tj3A2uPpK5\n3pWjpVFCJY7/Pv4a52fMrlBxgjmhXmEOB1LK629B08S6Cql1aoNYvb16VraQEtKbF+CSQIL3R6xB\nkCerpxTnG+9UUMiUlsTshTTNzD9vOlC9WVuCcT+OREltCS+DxjxQZylw90SPp5zS8jDP7Dpx/Zjg\ncRfK/uA2mK1mvz55Ns7NzcKKEatw7pEsQ+ZZjG8s3hj6H+yZflDQ3VMPTdFYN34Dnu39PNaN3+C0\nPomC8uIFcrXQYvKW8RgYNhiUlNVustXEoiWE3EQZTTVnW+hv0VZqao5Ao2GD8jrdDVy/btkNUq0u\nQWHhXE6bTmdbtqO7eyf4+MzktDHMjwDY4Ljp7y3COwpaLYOioqc4x2s05Tb1ZQm9+QUA3nP6ymU3\n4Q85AU0DuzeX4lf/UcjU9QWNGiSXAdWZwn8LBIIraRg/CU0mupSymyWQq0hAw9Xsy88wbpgtTGrr\nWXON3KqrWPrbMxYXSHsEp7CLP+41kEWcwc8P/Wj3u6xGXYMaM/3EOrXx+c2oGajKs7DpgZ8N46lI\nOtIpN2wCgUC4m2hR08vb29uuEyqVSmg0mpYPJNgNo2YwZuNwlNTeAADk3b4mmjOYrf2PXjcOYz94\nCaPXjbMa+MqtuopxP5k45ZhOln1zgaoY9v9NRK4BdoI6YsNAm8ocLQmVDw617FYmpDW0O38X0rdO\nwOiNfDH9GnUNqhqqDNuhXmGYnDilxWszZ1rMfGDHR8aGQBUQfAGzd07n9MkZgAls20qwIgQhntzS\nt1pNLWdV0Dyr6N+D33Y46GAtY0epUOLAQ8exa0qGVT0rW6EpGhsnbeO0NaEJD++ajrK6UoTTEdgy\neZdoAq9CYremtJRRRlM0Nj3wM2QSmaGtoDofn//+MS+DJiWktyHAZhq4S0+cBnlzhqdcSmGmgFmB\nPZhndq3JXCn498wrRTUrW+wU4A2lQonZyY8IllrG+MZi1Uhu5lO9yX1XUluCwf/rh/fPLsfg//Vz\nuuRwb95uway84poinL5xEl+NXY+3h7yHs49ccKg01JykgGT4ufGDnm8OfhczkmZj3/SjBuFhR6ir\n4y4AaDRFFvW8Kis3AmY/u1Rqe7ajm1tnzrZOV4W6urPIrlBxMuQKq/NRU3MEOh3XzEOjsd3cQ4jx\ncZMMpiPmz+n4xEanzm0Jv8KLGF2RARpsNmKuL+CdMsAlfREIVlEqUXb0NLQh7HNJk5AITRJx5nM1\nHLMdCwYsALA1ZzP6r0/BoYIDvMXf7AqVYdFPC61B09QehDKPd+b+jNyqqxzty1nbp+LFfq8i2DME\nBUwB0reMb5USR7EMZwgEAqGtsBr0Cg0NRX5+vrVDeOTn50OpdH4yQeCjKs9CUU0Rp00s3SJbyCy8\njJx3vwM+O4Gcd79DZqGAyHUzPLtl08ny/HuFnbpM9K7eO/lOi9fze2kmr21xr2V4rMcCyx+yoDUE\nADmVV3ip4nvzdkMLYxB3Se9lDgVTKgpCgVtdjA0TFgLuNajX1nH6NHc7FHI/tAVVeRZu1vEDCE06\nyyYTQgLxtkJTNHZP228xsCW2W5hQho2eIqZQNBF7PaW1NwXbo7yjbcooK6+/xRE5l0vkeP/sckMG\njT5QSFM09kw/iF1TMrBn+kHD78uL8kI4zVqrh4uQ4Wme6ZVfnYcNl/7HG9D+lC2gz+heY9Aesa2E\nlHvP/XX/s4bgltglh2z2lnBm2dMZT2D2jmn4+PfVomXI0hSNh7rwA5CrMz/AD6r1eOLXR52aJEil\n7rw2rbYWtbWneK6KOh1X41AqDYSnp+3ZjkLHVjGZWHPySXg0jxTi/FhR+YaGbPMrha+vcwLwSoUS\nR2efgUKm4DynJQv6o0e4/aXstqBJSkZ9TGcAwDUfYNACKbpGk6AXoQ1gGMjLb6E84zAqdmWgYvd+\nNh2R4FJ6BKcYNywYsAAwjE+nbHoIQ78eibEfvISR68aAUTMWZQnsIcmvC6+NUVdj0Hd9cKz4iGGB\nLKfqCp7OeAKldeyYRAwtzJYQ03CGQCAQ2gqrQa++ffvi4MGDKC21bQW3tLQU+/fvR1KScAYOwTmS\nApKhNMveqW/FoFddcSxnFayu2HIGQ7BCyXd5a54sd40O4QeezNLKN/y5zWq2F6Nm8Ny+v3DapJBi\nQc8nMSJqlEVhddPrMNcaAvjCoeYDkR5B9uk0GAgxG0yFnTbsMi1p7BGcAhnYEgcZ5NwBmR0IiWwD\nwORtEwy/V/N7x9l7SezAljWSApIR7uW8K56tjIgaKdhezBRZFabXY35fGUtBG/H2kPc4gUKh32Pm\nzbPIu30NgDgZnqOi0yCXcMvWXzy0jJfteF/0KPOPGrJxbC0hNS9XLm8ox/0bh4FRM6JrFCoVSuyc\nvMfqMblVV7EvXzzdJm0TN7NZIVMYVvqdnZD4+U3jteXnT0Ru7khcvTqcE/jy9ORqy4WGrrCo/SWE\nl9cgANzy6opbr+KVxEJ81BvwkALvDnsfNEVDJuOWFwcHv+Owc6MpCsrLaFDS/Jxucq82lEu7gsZm\nd95GOXCb0gkuphAILqWkBAHD7oX/2JHwH3cfNBFRJODVSnAWyPTB9rnDgXEmxjGm49NPTqNw+Rbg\nsxPI/Q+rN2irLIE1tl/dJtiuadLgSkW2IZPenEjvKJe425pibjjTmhUmBAKBIBZWg14PPfQQGhsb\nsXjxYjAtCGoyDIO//OUvUKvVeOihh0S9SAILTdGY0+0xTtvVypxW698z7ConcOMZJhyUYtQMlh/6\n0KLL2/Jh7yMuJBSIOAm5R/MERyCtfNj/BlgMfGXePGso89TzadpXUCqUoCkaR2adxiv9LZekWeK7\ni99wtn/N+8Xqtq2kRCQi7q+zgPn94fdMGifgdrT4sOH/C6vzDZllWmgcnuwJiWwDQIO2HgPXp6Kk\ntgSltdxgtvl2e4amaPwybR+CmzW8zHFUC80SlsT3NU2aFrOTGDWDGT8/aHH/yrP/xYZL/7Mobs+o\nGRwt4lrYO5vhqVQocWTWKfi5c0vzzLMdx8ZO4PwuOylCcXT2GV4mmjWmJfHfB9drivHtha8AsNqE\n+n/FyMDqEtQV3nIfq8e8cHCZaKvV83ss5GybusrG+MY6NSGhKCUUitGC+xobL3NKHb28BkEuZxci\n5PJYeHvzA5bWkMloeHn157Tpc+aivYDByghDkFOr5Zp7SCRqu/qyBJtZq+W0dfaJcdmkTp55Fj4F\n7HsksRzoUwQU3HZdgI1A4MEw8B93H2QF7H0nLyhAwLiRRMS+LdmxFvhmv3Hsajo+vdUFKG8OQN1K\nwonTaouyBPaQ2qmPxX0R3hHYPW0/1o/faDCOAdj38c4pGS5faEwKSDboiAHAXw88S7K9CARCh8Nq\n0Ktr16548sknce7cOYwZMwZr167F77//jurqauh0OlRUVOD8+fNYvXo17r//fmRmZiI9PR0DBw5s\nreu/C+GW7jRoXaN1IoRp4Cbur7OQEiG88nSs+AhqbkTxglhJfl2wb/pR9AntZyjhOjc3C6tHfsJN\nKw+8BDR6or5OioHfpQrq/JhP+kO9QjEiyjjJoykaj/dYaFgdi/GJxT8HvonP077B20Pe4190c1ba\n5ou/cF7mD8Sncw4z37YVmqKx5+Gd2LXkLfw0/QfOPlPdpKSAZIMrpb6UyFEslQBqocWOnG28rLX+\noR2rrKdWXYPSOuFA3S+5O0XtKykgGf7ufO0mmUTWYnYSW2oqXB4JsHpTLx5aht7fdEVu1VWM3jgU\nY38cidEbh6KktgQjfxiM5aff4nymvjk7xRnK62+hsqGC02a+akxTND4cadSiu1F7HeX1t+zK6LN0\nH7529GWM2ThC1Aw2gH3+VGtuWz2mrK5UtJKQGN9YrB75qWHbNGjTKMLz2dOzh2A7RUXB3d34Xclk\nNOLjDyMmJgPx8YftyvIy9iWcyXrjVhCyLnY1ZDVSFDeobL7tKKOi0yAxG5aMi5noukldBVd8P6ie\n1RYjEFoLuSoL8oICTpusIJ+I2LcSpgErAMK6XqbjU3Cf6Reu57AO1pN3YcWIVQ7riY6IGoVon84W\n99MUjQCPAEOWOABodK2jn1xaexMFJguwQlIgBAKB0N6xGvQCgMWLF2Px4sWorKzEypUrMWPGDPTr\n1w/dunXDwIED8dBDD+HDDz9EdXU1FixYgH/9618tnZLgBN5u3la3XYlp4GbPwzstvtgvlP0pqI3w\n90H/Qreg7oZzpSr7QqlQItYvjptWDolhlU1b74EdOcJp36b8e/A7gjpSep2pjBmHsSjlGUyMexDT\nu8xEJG2ilWWSun5r5U6OVtnVKm4mXbGZppo96H/migbuRMtc9FStVXP+dZSkgGSEKoTLPG/VlWHO\nzhmcNnOdp/YOTzfOhdAUjc0P7OC1r7xvbYuC6BHeUZBUhwFnHwOq+SWnetQ6NdZkfoicyisA2IHl\njpxtyL3Nz3a0pDFmD0IlosXV3HJNfQBYH4h1xH3TmrtUUY39gr8tYUumTqhXqKjZQ34efoLtRUyh\n05MDheJewXa1Oh86Hbe0ViajoVD0dSjgBQABAfME25UBZdD+sBpDXlwBRs3wBPLtEcy3hlKhxLdj\nvzc2NHghnnnYZUkvMjPphpX3vCaKwQGBYCuapGRoEtjFuSY5m8VDROxbD1MdzX8MeENY10s/Pp00\nDwDXSbaTnx8YNYP0LeOxdN8zDgvL0xSNfTOOYmLsZN6+wmr2PWnu7l1WX4oxm0a4POvKfKwllUiJ\naySBQOhwtBj0kkgkeOqpp7B9+3Y88cQTSE5ORkBAAORyOYKCgtCrVy8sWbIEO3fuxLJlyyCVtnhK\nghOkJ04zaODIJDKMiRnXqv3bottU08jwBOOjg4MxIGyQ4PEG5z/3GoCqA241a8KVJQPFfQw/L+c6\nGoF+hYBXcyWRv0eAzddLUzSe7rXEeJDZyl5FPhsoYtQMXti/lHO+KxXmAs72Y030dF9+BvKr8wCw\n4uKOujcCaF59FM54evf0W7jVYCzZsyVjqb1hbdDlir+LbkHd8d9hH3LaQmkr2nHN/J57HU3vXwW2\nfQG8n88PfJlo30mauJmckT5R6KQI5Z3TksaYPdAUjdcHv8lp02cBAuz9P+KHgUjfOgGN2kZsfmC7\nQ+6bLZXo6jXC5BLKoiOrPYyPm8RxyhTi4eRHRc0eMtfDkza/Wikp5fTkQEhrSw/r2CgeFKVESMhy\nXrtEAqSnf4jK71dh1/Fr0GorOft1OvG0JUvrmwO6zYsRz83pi7Q0hUsCXw0jRhpsFpoAUPfzJ5wE\ngkuhaVTs3o+KXRkoO5dFROzbAP048ZHuj8HdQytsduReA3TbwFYi6PG/gsUTh/A0rxxd6KApGn06\n9RVoZxe3TaUw9BQxhS7X2DIvvdQ16Vyqs0ggEAiuwOYIVefOnbF06VJs3rwZR44cwR9//IFDhw7h\nu+++w6JFixAZGenK6yQ0o1QocXjmKQR5BkPbpMWs7VPbVW09o2bw9Z+fsxvNQsSze07BvhlHLU4y\n9RlZ68dvZFfVTAcVP3+CvZePco6vqSzBsNnPIuMzL3y2ph98GB+7J8vj4yYZnPPMV/ayZOxEUlWe\nhbIGrnZNvH+CXf3Yy3Ez7SbzbXuxpEVljjflI5qjXWthbdDliGV4SzBqBqszPzBsd/aJsUm7o+DM\nPYC22YVP6w5kjzfuNDNwGBWazhF27xGcgvdGrOSd09bv1RqMmsFrR17htesdQ/fl7zWUHhZU56Oi\nvtyhQFFSQDIC3IWD0oCxHFDTpBZlIK1UKHF01hmEWMnYoUXOkDXXw9NBB4DN3nPWSVQmo+HtPUxw\nn1Zb7dS5hdBohL+DmhovABLs+jYKN268ZPYZ8fQAWXMDN85iRHa2DCqV+Atq8qJCg2CApHmbQGh1\naBqa1L6AUsn+SwJebQJN0Xhz6H8smx251wCPDgN82YVJf4Uvgj1DEOEdxXlvO7PQkZ7INy+5dOsC\nGDWDEIXSsKBiynP7/uLSeYCQOZR51hmBQCC0d0haVgekiClEWbOWUU7VlXblpHKs+Agq1dwsgN42\n6P/QFI3R0WnYN2cPcL9JdlV5InYdvY5DBQcAsBP1pWuGQXatEn1xCjOrTqDx0+P4veiKXdepVChx\n9pELeHvIe/CiJZyVvfx61m2u6Da3lDHYM8RitppYdAnsytm+N9w5fTy2hC28xeMqGys6nEbD3O7C\npViuQlWehZwq432m1tlWfjo+TQY51azzJGsAEkzKJM2yDH86mmU4rz5gEu/HDbSKJey9Lz8DhYyZ\nlgxkiPdLQEltCdacW8XZ91ueY46HNEXj8XsWtnicTCIXrWQixjcWx2efw1M9FwvuFzsTsH/oAL5b\nrYgEBj4l+jkt4ecnbESj0bCLBJ2TD0OnM10MkMHXVzwdLMOzecrjiIlj9XMSErRIStKJ1geBQCAI\nMTlxKvzcueXqT/VczJY+AkBVZ6AqGgBQURSMzEwpTl4/zntvO4pSoeRllKcoU5G2cThm75iGQIFg\n07XbuS6dB9AUjSW9l3HahLLOCAQCoT1Dgl4EUREq/8uptL0ksFtQd8zuydWaQhPw6pEXAbBBtT2e\nxdjp0w2XwE7866uScSLT/owHpUKJefcswPN9XuSs7G28/D1Kakvw9qk3OMcHeASIUhJlXgp1ovgY\nGDWDktoS/PXXvxkmzuF0BEec3xFoisa68S2XQIUolC63vRabGN9YfDb6G157oEeQQ+5JLZEUkIxI\n2pjRaqtek1IJ7DmSB0x6HHg2CvA20eMyyzI80PAhx51p2f7FvBLXJ3s+I8p9KJRFqIUWD24Zh15f\nJ+PMzZNmeyW8420lRWnh+zAJFGmbHHcrFYKmaCzq9RdIBK5bjEw5U07k/SHoVhvuFeH0vajVMigu\nFg56VVZ+Bq1WvBV+rZZBYeGjgvsmTvwcHopy9L7PE25urAaRTBaC+PgzoChxdbCUCiXmpc5Exp4G\n7NpVg927a12S/KJJ6Q1NHKtXp4mLhyZF/OcGgUDoONAUjd1T9xvew5SUwqJef8Ej3R9DBB0JBF+A\nJMg4pn3ueQrzt3Gfz866Kz+YOAWdfWIAAD4U60SsL58srW8bl23T6ghK6tbh5DAIBAKhwwS9Xn31\nVcyZM8ewXVRUhHnz5iElJQVjx47FgQMHOMcfP34cEydORM+ePTFnzhzk5eW19iW7jJSQ3ojxZa3p\nY3xjXTLBdxS99oAp9mbk3DfAFwhsXikLVAHhp3Gp/CJKaktwruQMACBBdgFdwAYLJIFZuObxs8PX\nbC4K3oQmfP3nF7hSyV2t+2uflx3ug9ufmXjyuf9iwPre+PrsBug+PWaYOM9NWOJ0cINRM5i1fUqL\nx82/50mX2167gj35u3ltmyZtc8nPQlM0dk79zWDdbY+oe73nNaD3F9yAF8AGW+cOZwVy5w5Hme4a\nx50pt+oqghXBnI+IoecFAPeGC2ctXq8p5lyDnoEWjreFAWGDoFR04jaalXZ6N4WJHnhVKpR4bxi3\nPDTUS/x+IuvH8h2/wD6rnb0XGxqy0Nh4WXCfVluK27f5Bguu6EupLMSAN4ZieNe+iI3dj5iYDCQk\nZMLdPVa0/s2haSA1Vee6ai+aRsWeg6yO0p6DpKyMQCAgxjcW5+ZmYcWIVTj7yEUoFUrQFI2DM09g\n16xtWLfWWK5/7aobmkq57xNPuXPGHjRF48sx6wEAt9W38XTGAkMQTMicKNCdzf5yZYmjUqHEr1P3\nY0bSbPw6dT8x/CAQCB2ODhH0OnbsGDZuNGarNDU14amnnoKfnx82bdqEyZMnY/HixShotn2+fv06\nFi1ahEmTJuHHH39EUFAQnnrqKeh0d055hFQi5fzbXrh06wJne3rCTEOAzlZGxN8L+qkRbLnhE6mA\new2a0IQdOdtQVluGPkVAr4oanEJfHEd/DLq/L5YOWOTwNQsF5U7dOMFrC1BY1iWyB6GgRUntDazd\n8xtn4ixpnjg7g6o8C9drr7d4nN5Vs6PxZM+neW31WvFEtc1RKpQ48NBx7JqSYZeou1CZqafUkw38\nfL2fFbn/ej+vNI5dbeZmKomlV9Y96B7Bdn834fvcFtF+S9AUjb3TDyGcNnGLNCvtXBi62iXBys5+\nMZzt5cM/EL2fAT394Bd+g93QO34BSA50/m/Y3T3ZkFklkfAnGpWVm53uQ6gvqZRroNAEYO2Dn4Km\naKddItsLDAOcUfmgMonoKBEIBCNKhRKzkx/hBHf0gvcDUt0QF8dKFigjqwzPe/3nxFiI3qj6nrM9\nPPw+rBixClsm70SgRxBnn0wmR/rWCUjbONxlga+S2hKM3jgMP6jWY/TGYSipLXFJPwQCgeAq2lfE\nRIDa2lr87W9/Q+/expfI8ePHkZubi9dffx3x8fF44okn0KtXL2zatAkAsGHDBnTp0gULFixAfHw8\n3nzzTVy/fh3Hjx9vqx9DVFTlWcipZLWFciqvtCstphi/eM52/zD7NaloisbPM3/kCYlSUgoZBb/C\nszkJhUYN+uMkVg39p1NBmxjfWAwLv4/TptXyM12cTVnXY6m0qsbvOKfULTah3um+kgKSEeNjPego\nk8jQIzjF6b7agm5B3bFz8l54u7ElAPZkXzmKLQ6mQp/5Zdp+Q9Anzjce+2ceg9/tIYIZQno0TRpc\nunWR0ybWffhLrrCzp1A5IC2nnR7IKxVKHJp5Ev8c2OwYaVbaOW2IcBDOWVJCeiPOl30uxfnGu0SX\nj6aBp9as4zl+jY+d6PS5ZTLaJLPqMADufafTMWCYg6KUOZr2FR9/EDKZ0WlUAqDh9vei9dXWMAyQ\nlqbA2LFeLnOHJBAIdzYyKdcp+L8jVomyqGLumLg7fyeW7nsGD++Yzlvsu9kcgHLGObIlduRsg6aJ\n1S3TNKkNLs8EAoHQUWj3Qa8VK1agX79+6Nevn6Ht/Pnz6Nq1K2iTldnU1FRkZmYa9vfta7T99fT0\nRLdu3XDu3LnWu3AXEuEdBbmEdYqRS5xzihETRs3g3ZNvctrUukaHztUtqDuW9OIKZ/6WtxcF1fmo\nk3OPjVJ2cagPU9LMhK3Pl/HvFWdT1vUkBSQjyD2I1+7moeYI6vv7uDndF03RyJhxGOvHb8SjyY8L\nHqNt0nZo++k+of1wfu4lu7OvWht90GfXlAzsmX4QMb6xWD1rCSfwg+ALPEH0T86vbdXrLG/kB2WX\n9X1JlN8rTdFGdyr3Gs79Xq5zTQk6TdHYM/2g4ffuqvtjZs8HIY04zQnUZ5aKIy6sz6yiKCVCQv7B\n2Vdffwh5eRNw6VIcamrMddic6ysm5lcAxgdueflK5OVNwJUr93b4wJdKJUV2NjthdZU7JIFAuPNQ\nqaTIyWGfHcV5NGexytx4xlFGRI2CUh4PFPZDgCQa12vYjP3sysvoGtTdoDkmg8xQTeHKRT9zmQXz\nbQKBQGjvtOtR3rlz5/DLL7/ghRde4LSXlpYiJCSE0xYYGIgbN25Y3V9Scmek42ZXqDgrLs44xbRE\nSW0J1md9Y0hlZtQMzpScEkyh3pe/FxWN5YZtKaQYH+e4q1e/sHs52zuusStLp8MBVbOBjVjiw1IJ\nN7ulWs0VxhdTHJ2maLwzfAWvvbGpkSOo7+8uTjml3hlzdOwYwf0dUcTeHEeyr9oC8+sc0LknopdN\nN2YIATxB9CozN1SxSE+cBplE1vKBcDx4LQQnwNp8v8cpQ116D7bG/eFFefFs3QeGDRa9H6nUkqFA\nHa5dG4W6uj9F68vdPRaJiVnw9X2E067R5KO62jE3T3tgGODMGalLsrCSknRISGBLlIg7JIFAsJWk\nJJ2hvDEo4hanvNHceMZR8krLUPL+NuCzEyj/cBfkatZRkpK6Id4vAZE+iLYz9QAAIABJREFU7GJ3\nlG80vp+wGStGrMLmB3e47B3nYbboW69xvhKBQCAQWhN5y4e0DY2NjXjllVfw8ssvw9fXl7Ovrq4O\nFEVx2tzc3KBWqw373dzcePsbG1ueuPn7KyCX2zYRbCvcK7iTHneFBMHBfAF5Z7nB3EDqt93QqG2E\nXCrHmQVnMOOnGbhUdgldgrrg1IJToN2ML9jzp09zPv9YymPoHh1vflqb6a5NFGyvcQdSnwA+iVmM\nWTPfQLAIWixz+83CS4eeRxOa2Ayb0m7sQKY5a6OzXzRiwkJbOIvtxDDhLR6zp3g7hicPEK3PUIZv\ndQ0ALwz6P1F/tjsBV/w9CfYDb/z53DEsP7Ic/zx4ks3wMi93jOBm74QGBopyfcHwhuoZFfp/1h+3\n6qy7GQb6+oj2Oxns2w9dgrrgUtklRPpE4qMJH2Fo9FDOs6QjcrXwIopquHprTR71ot9LPj6zcOPG\nMov7q6tXIypqnd3ntXyd3rh1ix910umOITh4jsDx4sAwwNChwKVLQJcuwKlT4spuBQcDZ88CFy4A\n3brJQNOt8zdPaF+01rOecOfg6QnImqcJchl3GhUeGCLKPbV23R6g7Dl2oywZmpJEIOIk1LpG/HH7\nNHKrrgIAcm+WYMKqV1Gq2IfEsJU488SZFt+ljlyfX6WCs734t0VIT5mITnQnC58gEAiE9kW7DXqt\nXr0a0dHRGDt2LG+fu7s7GLOl38bGRnh4eBj2mwe4Ghsb4efn12K/FRW1Tlx161B5u5a3XVpabeFo\nx1l+/CM05qUAwRegca/B4C+GoFp9GwBwqewSDl8+iVSlsYy0pz9Xg2CgcphT1/Xx8c8t7qtxB+rv\n6YPSuiagzvmfXQYvvNTv73jz0HI2w6YsmS03a9bnWdrrBVF/x53duyDEU4mbdZazDwcH3yd6n9He\nnZFXfc3QJpdSuD98kkvun45KcLB3q/8+5iYtxH8O/wd1ep0r/f0XzDWGUCo6obN7F9Guzwch+PT+\nr5G+dYLFY6QSGe4PE/ce2Tn5N6jKs5AUkAyaolFX1YQ6dOx70EsbCLmEMmThxvjGIkQa5YJ7yQvB\nwe+itPSvgnul0v5299nSPa/T8YP0anWIS/9OzpyR4tIltsT30iXg8OEapKaKn40VGwvU1bH/Ee4u\n2uJZT+j4nDkjxeXL7LPpRp4vZ3Hq6s0CUe6p6M71gmOBBL9E3OPTh33X1LsBn55CafMxlxf0xZ6L\nBzA4fKjF8zp6zzfUNHG2tU1afHLsSyxKeYbTzqgZZN5ky/rFcC92NSToTSDcPbTboNfPP/+M0tJS\n9OrVCwCgVquh1WrRq1cvLFy4EJcuXeIcX1ZWhuBgtsZcqVSitLSUtz8hQZxa+7bGXFtKLK0pU07n\nXcR782YAZf8wBH+qcRsyiQzaJi0oqRtPSyzWl5vV1T2oh1PXkNqpL3De8n7zdGtnKa0t4TnK6Qcz\ngQrhLClHoSkaT/dagteOvmxsNMswU1VeQp/QfpZP4kCf+x46imPFR3Ch7E+4y9yRnjiNWE+3A/Ra\nV+svfcMGWs0yDfW8OeQ/og8iU0J6w5fyRZW6SnD/u0NXiH6P6MsN7yQKq/MNAS8AeG/4SpcN+AMD\nZ6O09HVAIFDo5iZ+1iZFmZ9TgoCAh0XvxxR9+WF2tqxjlB8yDOSqLGiSkokTJIFwB6Mvb8zJkSE4\nshKlJotT8f7izDMe6T0d7y5I4YwFUkP64atx643vmtJeVo1wxCQlpDf83PxR2VhhaGvUNnCOYdQM\nRvwwEHm3rwFgZUH2P3SMjDEJBEK7oN1qen377bfYvn07tmzZgi1btmDatGno3r07tmzZgp49e+LS\npUuorTVmPJ05cwYpKawDXc+ePXH2rFFAuK6uDhcvXjTs7+gk+CcZRCzlEjkS/JNEPX9JbQkW/7BG\n8GWqbWJ1DNS6Ro42D6Nm8MAWblbeRtUPTl3HiKiR8JZZXoWpF8nFTk+XwG48RzkEX0CwZ4hL9IbS\nE6dBqv8TbPDiaDlJG30wKjpN9D71+l7Ppi7DopRnyGCkHbE4tbmUwUTXzZx6TQOvzVloisbkhGnG\nBjMh/Rg/6+6fBJakgGQk+LEl2Ql+iaJpAFpCLhcOxEul4i+C+PlNA6CXFJAiNvYIKMq1zw6aBnbv\nrsWuXTXYvbu2fceRGAb+acPhP3Yk/NOGg1hBEgh3B6W1xmz9KO9o0dyBlQolBnRO4YwFztw8iQe3\njEWARyA7dhQYr1bUVwhq7joLTdH424DXOW1hNDcD+FjxEUPACwBu1ZdhxA8DXXI9BAKBYC/tNugV\nHh6O6Ohow38+Pj7w8PBAdHQ0+vXrh7CwMLz44ovIzs7GJ598gvPnz2PaNHbiNmXKFJw/fx5r167F\nlStX8MorryAsLAwDBoinj9SWsEL2GgCApkkjqpD9hbI/0fOrJFyhfuS7ypkQ4xvLCQQdKz6C243c\nTJHLFdxsPHuhKRpj4yyXXeVU5jh1fnPUukajo9zc4cC4RZBAiu3pv7okY0OpUOLY7LNwgzsvw2xm\n4FskIHWXEeMbixOzM/Fs7+cxIFR44Hyh7A+X9L2oV3OJglnwVdLgLXpQ/U6Fpmjsnra/VVxEGxqy\noNFcE9hDwd1d/O9LKvWCXB4JAJDLO8PNrbPofQhB00Bqqq59B7wAyFVZkGdfZv8/+zLkqqw2viIC\ngeAqTN0bcSvJsCg8I2mWqM/9SAFn9pzKKzhafBg66HgOyHCvweO75yBt43CXBJrMDW2qG7mZxlcq\nso0b+X2AddtQpoo2lDsSCARCW9Jug17WkMlkWLNmDcrLy5Geno6tW7di1apViIiIAABERETgww8/\nxNatWzFlyhSUlZVhzZo1kEo75I/bIhX15S0fZAMltSUYsWGgxZepKbVqrq5Ywe18mLM0VVhzxh46\neVku1XGXuTt9flPGx02CDM0DmR1rgW/2o9N3BQiWuS7TJcY3Fodmn+Ct2N3XhwjL343E+Mbi5Xv/\njjeHvCu4f273eS7r98TsTHRRT+cEX5tKk7luiwSrtJaLKEVFARAyXFFDrRb/+2KDbKxwskZzFQ0N\nJKhjiiYpGZoENstPk5DIljgSCIQ7kogIHSiqWeNK1gD4XgMAVNZXWP6QA6TF8DWNAzwCMSo6DcEe\nIQKfYMmuvAxVufjP6P6hAziZ4P1DuYkEbtJmA7H8PsAXJ4ErE4EvTuLIcfEz1AkEAsFe2q2mlzlL\nly7lbEdHR2PdOssOVcOGDcOwYcNcfVltQkpIb0R6R6GgeTK68Nd56Dd3gNOZQZ+e/4jboC+zEqCk\n9gYyb541CGb2COrJ2b9qxCfoFtTdqesBgEDPIMF2CSRIT5wmuM9RlAoljs4+g7T3X0Rl88T/ep4v\nVCrXCCjrifGNxYl5RzDOYyxuFSgRHV+LEfG/uqw/QvunW1B37Jt+FCvOvItgjxBIpVLM77EQMb6u\nDcCmD+mKN78yiucGRt10SWkvwTnq6jIBaE1a5AA0cHNLhLu7+N+Xu3sy3NwS0dh42WV9dGhoGhW7\n9xNNLwLhLqCwUAq1utlFXesOVHUGvG9icsJUUfsZETUKPnIf3NbcNrQ1NTXBi/LCwPDB2Hpxt6Dx\nUqR3lEve2yfy/jD255uL77p8g5dGdTYs8hwvPsIeePDvAPQu8xJs/DQRL0wR/XIIBALBLu7M1Ke7\ngLpGY6aVpkmDHTnbnDpfbtVVrDz+EUfLh4eZ1k+diabWr3m/cA69UnXZqevRw9G9MuG36UdcUv4X\n4xuLQ0u+RGQMm9nWWgLKMb6xODX/GHYteQv75rimnJLQsegW1B2fpX2Nt4a9izeGvOPSgJee0QmD\nOBme3z7wGbkX2yGNjdxsrqCgVxATk4HY2P2QycT/vmQyGrGx+13aR4eHpqFJ7UsCXgTCHY5eyB4A\nEHjJIP+hqnRO0sMcmqIxq+tcTltFQzlU5VlY2OMpvvFSMeug/s3Y70V/bzNqBtVFkcb+qmLw6eJH\nMHrdOEMpZYoyld039HUAerfHJvz9RYp3PgKBQGhtSNCrA6Iqz0JZQxmnrampycLRtrH2xFccLR/T\nwNeYqHE8rR80eHFSuWcmc528zLcdRalQ4vyjKrzc/zXM7jIXr/R/DX88mi1KFpnFPv28sHObDitW\n1GHz5tYTUG6t0igCwRInrh/jCOn/XmbFPpXQZvj6ToJRWJ5CQMDDUCj6ujQYJZPRLu/DHIYBzpyR\nEl14AoHQTmEzmigp5RLzIXPDJl83XyQFJEMilbDBtkCTQNv2j4EGL7x57HVRNb0YNYO0jcPxRs40\nwDfXuKMqBjnZblCVZ6GktgT/OvZ3tj3qNDCvH4J7nsZnGy5j0vAw0a6FQCAQHKXDlDcSjCQFJMNb\n7o1qjVFE8q0Tr2NGsmMimiW1Jdhw6DzfrbG5tHHOPY/BtywNP5juvzAdT2MpLper0ATgVl0ZpJBC\nBx2kkEFBWcgWcwClQolnU5eJdr6WYBggPV2B7GwZEhK07d85jEAQiWBFMGc70ocvpEtoeyhKicTE\ni6iu3g1v7zSXOym2BQwDpKWR5zCBQGhf8ITsL0xHp3tPwEvEca+eIZHD8NXFzwzbbw5ZDpqikRSQ\njABvD5SPfxL4Zr/xWkq7YY/7L7jvh0H4bcYRURZRVeVZyK68DLgDmH8v8NlxoCoGCMqCNESFCO8o\nbL68kdUD1hN1Gh//pQSDw4kRDoFAaB+QTK8OCE3ReDLlGU7bbfVthxxSGDWDcZvuQ23ASUG3xhjf\nWAwIG4Tnxo837pc1ANu+AD45jQ9+PI2Vxz/C+ktfG154OmixN2+34z9gG6NSSZGdzQ5osrNlUKnI\nnwnhzodRM3jzuNGSXEz7dYL4UJQSAQGP3JEBL4A8hwkEQvskKUmHmFjWQV0/Hi747yYcuyZ+ZvSI\nqJHo7BMDAOjsE4OxseMBsPOAXdMyIAk/Kzh2v3Y7VzQx+6SAZCT4sUYdnj7VwFP3GCQQdG5VOFiw\nHw1arlh9gHsgUkJ6i9I/gUAgiAEZRXZQpibNEOU8mTfPooAp4Lk1hgb44rdHfkPG9MOgKRoxwSHY\nues2MGkeK9wJALe6sCtMZuWQADAwbLAo19cWmOo1xMW1jqYXgdDWqMqzkFN1xbCtbdJaOZpAcC1J\nSTokJLD3YGtpKxIIBIItNOqagzz68XBZMq5cdhO9H5qi8duMI9g1JYOXuRXjG4vj8w4hcPE4Qad1\nD5mnaNewe9p+7JqSgdROfTgSCADw/L4liPOL53zm3eEriFQHgUBoV5CgVwflSmU2Z1upUNq9qlJS\nW4KFv84zNpi8yJb0XoYRMSM4L60+0V3x3qIhxlUlPfpySBOKmEK7roVAILQtSQHJCKeSDGYVRUyh\nS2zPCQRboGlg9+5a7NpVQ0obCQRCu0GlkqLomlkpY1AW4hMbXdKfNb3XGN9YnHr8KKbfF8cJeAHA\npJ/SRNH2YtQMjhUfwfmbmbgnJIW3v05Xi/zbeZy2WN943nEEAoHQlpCgVwel4DbXvUujsy8rg1Ez\nGLNxOErrbvL2SSDB+LhJgp+TKmrZ1aS5w4FAFdtoklKtp85MfLMjYarXkJNDymoIdwkNNNy++N1g\nVhHnmeIS23MCwVZoGkhN1YEGA/mZUxBb0Z5RMzhTckpU0WcCgXBnExFXDWlws0N54CXgkeHwf2YM\nBnTu2SbXQ1M0HkhI57VXq6vx0+UfnTr36esn0fWzWMzeMQ0vHlqGT86vETzu898/5mxvvbLZqX4J\nBAJBbMhsvoMyPm4SpCZf3636Mrs0vVTlWSiqKRLc92D8VCgVwjoxo6LT2NWkmAPAE6lsSvXc4Wym\nl0mJo6dcnLTqtoCU1RDuRlQqKXJzmsszypLxbtc9pDyB0PaUlCBg2L3wHzsS/mnDRQt86R3Jxv44\nEmkbh5PAF4FAsInsmjPQze/Njn+f6APEHsC4LsPb9H3ZI5ifgQUAyw78BblVV1v8vOkCAKNmcLjo\nIL698BXG/TQK9U31huO00OL5Pi8hTBHB+XxhTQFn+/7oMQ78FAQCgeA6SNCrg6JUKLF82Aector6\nCps/36Rrsrjvxf6vWO133/SjkEDKBr+CLwBf7zdkh6DBq8MLWNI0sHlzLVasqMPmzaSshnB3YK5l\nl9LNvY2viHDXwzDwH3cfZAVsZrM8+zLkKnFKbg2OZACyKy+TUl4CgWA7ZrpW3YLuabNLYdSMsHlU\ngxdQ2A+jvx2PktoSNqjVyA/uM2oGI38YjLHfTUL3f8xG0upuSN86AcsOLDacw3RR29vNG/8Z9l+r\n16SqvOT0z0UgEAhiIm/rCyA4TqOOqx9QWssvVRSCUTOYtWOq4L7VIz9BjG+s1c93C+qO3x9VYUfO\nNhRfisDKsuYSqGZtrzn3DunQGSIlJcC4cV4oKJAiIUFL9GQIdw06HfdfAqEtkauyIC8wZhBoI6Og\nSRKn5FbvSJZdeRkJfomklJdAINhEOB3BayusLhA40vXoM1azKy+DkrpBrZ8XNHixC9FlybgdlIXR\nbuNwQ5ONSJ9IvD3kv+gRnILfSzNxovg49lzbhdzSEuDTU6gtS2YlSxb0Zc/TfA5Dm3sN0hOnWXVo\nl0lkbFUIgUAgtCNI0KsDMz5uEl49/CI0TWrIJZRFHS5zVOVZqGys5LUHeQZjbOwEm86hVCgx754F\nyO10EyuDsowvxeALaMIQu36O9gTDAOPGKVBQwCZBZmezml6pqSQKQLizycyUIjeX1bLLzZUhM1OK\nwYPJfU9oOyojuuJi5FT0LNgFj8gAVOzMgFgrEHpHMlV5FpICkjv0Qg2BQGg9jhYf5rXN7T5P4EjX\nY5qxqtY1YsE9i/DpH2tZyRGTBekb1/yBCKDgdgFm75jGP1FpP87xuDAd8LvKbSvthifH9YdSobQa\n1LovcrRFiRQCgUBoK0h5YwdGqVDihwmb0VfZHz9M2GzzSybAI5DX5iHzwL4ZR+0e+B8t+4Vd/TGx\nS67T1Np1jvaESiVFQYHMsB0ZqSOaXgQCgdDKMAyQlh6MwQUb0TuyBAU7TwJKcSdS1lzRCAQCQYhR\n0WmgpKz+pQRS7Jy8t8UKCVehz1gFgAS/RCxOfQ7+7gGs9IjeaV1vNmVaqmhetmh6vKwB2PYFsOMj\nM8Oqi3i692IA7PzjvWEfCl5TMXFvJxAI7RCS6dWBuVD2J6b8PBEAMOXnidg3/Si6BXVv8XO/5O7k\ntT3Ta6lDKzMDwwYbtQ2amd9jod3naS9EROhAUU1QqyWQyZqwaVMNKW0k3BWkpLCaXjk5MlbTK4UE\newlth0olRXY2uwCRXeAFVSGQqiT3JIFAaFuUCiXOPnIBe/N2Y1R0WptmNQllrP4y9Tf0X5/CLkSX\ndjO6q+tLFb3zAIkEuB3FKVvEgr5shte2L9jjb3Vhj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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_standard('CODtot_line2',[dt.datetime(2013,1,14),dt.datetime(2013,1,17)],\n", + " only_checked=True,clear=False,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model output\n", + "Fill gaps using a model output. This assumes that the user has good reason to trust that the model predictions are sound and can indeed be used to replace missing data where needed." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:02.248297", + "start_time": "2017-05-09T11:55:01.847864+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2717: DtypeWarning: Columns (0,1,2,3,4,5,6,7) have mixed types. Specify dtype option on import or set low_memory=False.\n", + " interactivity=interactivity, compiler=compiler, result=result)\n" + ] + }, + { + "data": { + "text/plain": [ + "Index(['.sewer_1.COD', '.sewer_1.CODs', '.sewer_1.NH4', '.sewer_1.PO4',\n", + " '.sewer_1.Q_DWF_UB', '.sewer_1.Q_in', '.sewer_1.TSS'],\n", + " dtype='object')" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_output_ontv_1 = pd.read_csv('./data/model_output.txt',\n", + " sep='\\t')\n", + "units_model = model_output_ontv_1.ix[0]\n", + "model_output_ontv_1 = model_output_ontv_1.drop(0,inplace=False).reset_index(drop=True)\n", + "model_output_ontv_1 = model_output_ontv_1.astype(float)\n", + "model_output_ontv_1.set_index('#.t',drop=True,inplace=True)\n", + "model_output_ontv_1.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:03.902986", + "start_time": "2017-05-09T11:55:02.251053+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:811: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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xMf32PlQ5Vru2q96HVDjq91LRqM9LRaR+LxWN+ry12rVdbR2ClFMxMTEMGzaM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\nW4fZs2cjPDwcubm5+j+9e/eGj48P5s+fD5VKhVWrViEtLQ3jxo0DACQmJ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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_model('CODtot_line2',model_output_ontv_1['.sewer_1.COD'],\n", + " [dt.datetime(2013,1,18),dt.datetime(2013,1,22)],\n", + " only_checked=True,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ratio or correlation\n", + "Constant ratios or correlations between data can be used to filled missing points. The user can calculate and compare ratios and correlations (currently only linear) between selected measurements, and fill data using these.\n", + "\n", + "*nb: in the examples below, data filling based on ratios or correlation is obviously not a very good choice. Both methods are included here for completeness of method showcasing.*" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:03.917107", + "start_time": "2017-05-09T11:55:03.905461+02:00" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(2.450642327196896, 0.672153214085126)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.calc_ratio('CODtot_line2','CODsol_line2',\n", + " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To find the 'best' ratio (i.e. the one with the lowest relative standard deviation ($\\sigma/\\mu$)), the ratio obtained in different periods can be compared and the best one used during possible further replacements." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:03.978297", + "start_time": "2017-05-09T11:55:03.919697+02:00" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best ratio (2.53282188261064 ± 0.16586491872475553) was found in the range: [Timestamp('2013-01-19 00:05:00') Timestamp('2013-01-21 00:05:00')]\n" + ] + } + ], + "source": [ + "avg,std = dataset.compare_ratio('CODtot_line2','CODsol_line2',2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Use the average obtained from the ``compare_ratio`` function to fill in missing values. (*in this case, as mentioned before, this does clearly not work, since zero-values are replaced with zero-values. This only showcases the function and its arguments*)." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:04.632959", + "start_time": "2017-05-09T11:55:03.980745+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:454: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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UXaxmTVe9D6lwNO+lotGcl4pI814qGs15SzVrulo7BLlLJSYmMmzYML7//nsM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\nAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_ratio('CODtot_line2',\n", + " 'CODsol_line2',avg,\n", + " [dt.datetime(2013,1,22),dt.datetime(2013,1,23)],\n", + " only_checked=True,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of a ratio, a correlation can be sought. In case of a zero intercept, this of course gives a result in the same range if the same data is used. To have a good impression on how useful the calculated correlation is, a prediction interval is plotted as well when ``plot`` is set to ``True``." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "slope: 0.405512924986 intercept: 0 R2: 0.973774656376\n" + ] + }, + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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pyGQyLl36By+vWTRvbkrnzl24dOkfrWCkUinR0Xmy3427eTOPhIR4LCzuP+1N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obE5mFXN4J6A6r9DAbTQrTaN+jU7Rz2SinbEf0z0eoVKspNRA1Od63Mmjh276VApFcI7Gxm7dq9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\n7rv06NGD1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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.get_correlation('CODtot_line2',\n", + " 'CODsol_line2',\n", + " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", + " zero_intercept=True,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After the previously made assessment, use the correlation function to fill gaps in the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:06.016129", + "start_time": "2017-05-09T11:55:05.261370+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:561: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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YPHiwrUP5xwwbNox69eoxceJEW4dyy9h8aWpxnD9/nuHDh+Pu7s7TTz8N5B39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IpEFVu7zUFJDc6r+lODY1Yw4rm0BXB39MAI/ziLvvPPWT+hts180CvcPQK7HjyA1Lw9eP3kEv3A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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_correlation('CODtot_line2',\n", + " 'CODsol_line2',\n", + " [dt.datetime(2013,1,23),dt.datetime(2013,1,25)],\n", + " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", + " only_checked=True,clear=False,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data from previous day\n", + "Under the assumption that \"The best prediction for tomorrows weather is todays weather\", one can also replace missing data by making use of (one of) the previous days." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:06.731819", + "start_time": "2017-05-09T11:55:06.018568+02:00" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/chaimdemulder/Documents/Work/github/wwdata/wwdata/Class_OnlineSensorBased.py:955: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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1VqlUqRIAr7zyCt7e3gXK69ate9V3TSYTQUFBPPXUUwXKqlatisViASAlJcWqLD/5J1Jc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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_daybefore('CODtot_line2',\n", + " [dt.datetime(2013,1,25),dt.datetime(2013,1,27)],\n", + " range_to_replace=[0,10],plot=True,\n", + " only_checked=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:07.431337", + "start_time": "2017-05-09T11:55:06.734413+02:00" + } + }, + "outputs": [ + { + "data": { + "image/png": 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2Y7id75mXl3dH3/9Bc98kygpPogBYsWLFLZ/39vYudm1voUGDBhVZUywiIiIi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qXIk+VhhP8o8rq4JgLcGgAAn6/Gxy9Pph3LHC6zzwKlNSS9V1hdgOEHWr7+owUk8mR5+Pnvn/BX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\npBR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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = dataset.plot_analysed('CODtot_line2')\n", + "ax.legend(bbox_to_anchor=(1.3,1.0),fontsize=18)\n", + "ax.set_ylabel('Total COD [mg/L]',fontsize=18);ax.set_xlabel('')\n", + "ax.tick_params(labelsize=14)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Calculations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Calculate the daily average of a certain data series" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:07.830400", + "start_time": "2017-05-09T11:55:07.433945+02:00" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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KwocOHdL999+v4uJiDRo0SD179lRISIhOnz6trVu36sMPP9TYsWP17rvvKjw8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\nD3dGzQAAuDVGrIDGMySxk82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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.calc_daily_average('CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,2,1)],plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Calculate the proportional concentration of different flows coming together." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:07.842239", + "start_time": "2017-05-09T11:55:07.833046+02:00" + } + }, + "outputs": [], + "source": [ + "dataset.calc_total_proportional('Flow_total',\n", + " ['Flow_line1','Flow_line2','Flow_line3'],\n", + " ['TSS_line1','TSS_line2','TSS_line3'],\n", + " 'TSS_prop')" + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.5" + }, + "latex_envs": { + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1.0, + "eqLabelWithNumbers": true, + "eqNumInitial": 0.0 + }, + "nav_menu": {}, + "toc": { + "colors": { + "hover_highlight": "#DAA520", + "navigate_num": "#000000", + "navigate_text": "#333333", + "running_highlight": "#FF0000", + "selected_highlight": "#FFD700", + "sidebar_border": "#EEEEEE", + "wrapper_background": "#FFFFFF" + }, + "moveMenuLeft": true, + "nav_menu": { + "height": "282px", + "width": "252px" + }, + "navigate_menu": true, + "number_sections": true, + "sideBar": true, + "threshold": "3", + "toc_cell": false, + "toc_section_display": "block", + "toc_window_display": true, + "widenNotebook": false + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/Showcase_OnlineSensorBased.ipynb b/Showcase_OnlineSensorBased.ipynb index e8168f15e..3cacb7368 100644 --- a/Showcase_OnlineSensorBased.ipynb +++ b/Showcase_OnlineSensorBased.ipynb @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.404080", @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -67,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -76,7 +76,7 @@ "'0.2.0'" ] }, - "execution_count": 5, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -94,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.587365", @@ -120,7 +120,7 @@ " dtype='object')" ] }, - "execution_count": 6, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -139,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.669059", @@ -164,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.780731", @@ -185,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.788079", @@ -206,7 +206,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.793662", @@ -227,7 +227,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:55.812335", @@ -248,7 +248,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:56.047638", @@ -262,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:56.758532", @@ -316,7 +316,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:57.347519", @@ -349,7 +349,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:57.358210", @@ -379,7 +379,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:57.391744", @@ -409,7 +409,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:58.312987", @@ -439,7 +439,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:58.360928", @@ -462,7 +462,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:59.889452", @@ -497,7 +497,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -517,7 +517,7 @@ " 'Flow_line2', 'Flow_line3', 'Flow_total'], dtype=object)" ] }, - "execution_count": 20, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -535,7 +535,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:54:59.895406", @@ -546,10 +546,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 21, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, @@ -595,7 +595,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -604,7 +604,7 @@ "4895" ] }, - "execution_count": 22, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -615,17 +615,9 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Average deviation of imputed points from the original ones is 38.45350418438349%. This value is also saved in self.filling_error.\n" - ] - } - ], + "outputs": [], "source": [ "dataset.check_filling_error(100,'CODtot_line2','fill_missing_standard',[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", " nr_small_gaps=70,max_size_small_gaps=12,\n", @@ -636,17 +628,9 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Average deviation of imputed points from the original ones is 55.3020444019021%. This value is also saved in self.filling_error.\n" - ] - } - ], + "outputs": [], "source": [ "dataset.check_filling_error(100,'CODtot_line2','fill_missing_daybefore',[dt.datetime(2013,1,1,0,5),dt.datetime(2013,1,17)],\n", " nr_small_gaps=70,max_size_small_gaps=12,\n", @@ -685,7 +669,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:55:01.060520", @@ -706,7 +690,7 @@ }, { "data": { - "image/png": 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\n", 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x2rcaNbS1PO0obwMAAACAuqpCyTZjzF2SHlK4IcKrknIU7kAKACgpNUty+qWglZyFCrbPVFZ2A5JtAAAAAFCHVbSy7QZJGyT1s9Zuq4R4AKBO6Numr9Tuf6Xr0qRloyVJMY4YeVO91RsYAAAAAKBSVTTZ1k7S8yTaAODYcg/kymEcCknSf6+Tgm45vh8njXWGP0kBAAAAAHVSRbuRbtFxNlUAgPrEm+qVy+GSsr0H120rLHQoK6u6IwMAAAAAVKaKJtv+KWmYMSa2MoIBgLrC086j60+9/tC6baZQTldAXm91RwYANYcvx6epi6fKl+Or7lAAAACipqJVavdLGijpdWPMbdbatZUQEwDUCYet25bt1R3X/EYez6jqDgtAVfP5pKwsyeuVPDRIKeLL8SltXpr8Qb/cTrcyR2fSQAYAANQJFU22rZAUI6mtpAuNMbsl7SplnLXWdjzR4ACgNju4blu7L+VI+VrNOv1JEsk2oF7x+aS0NMnvl9xuKTOThFtEVnaW/EG/gjYof9CvrOwskm0AAKBOqOg0UoekgKT1kcduSaaUR0WvCwB1jjfVq1hnrJzGqVhnLJ1IgfooKyucaAsGw88s3HiQN9Urt9Mtp3HK7XTzGQkAAOqMClW2WWtTKykOAKhzPO08yhydqazsLHlTvVRsAPWR1xuuaCuqbGPhxoP4jAQAAHUVnUUBoAos37qcL5RAfeTxSLNmSW+8IaWnM4W0BE87D5+JAACgziHZBgCVxJfjk/cVr/xBvyTJyCjOFcci4EB94vNJt98ermxbvFjq3ZuEGwAAQB13zGSbMWZ05Me3rLV7i22XyVo774QiA4Babt6yeQcTbZJkZVUQLGARcKA+KW3NNpJtAAAAdVpZlW0vS7KSvpS0t9j2sZjIGJJtAFAkZ6CU7ZXp8BmLgAP1CWu2AQAA1DtlJduuVzhxtimyPbZywwGAumN0n9F64bsXVLiuv/RKphR0y+GWdL1Lalfd0QGoEh6PlJkZrmjzeqlqAwAAqAeOmWyz1r5cYvuVSo0GAOoQTzuPFo1ZpNvv3aJvQrGy1qlQgFlkQL3j8fCXHgAAoB5xVHcAAFCXedp5NOv3oxQX65TTySwyACjJ55OmTg0/AwAA1AV0IwWASsYsstpj7rdz9cbKN5TeI13j+o+r7nCAOs/nk9LSDi1pl5nJZyQAAKj9yupGuuY4r2uttR2P81wAqBN8OT5lZWfJm+qVx+M5+AXysP10Ja0x5n47Vzdm3ChJ+mjNR5JEwg2oZDRrBQAAdVFZlW0Old19tDTmOM4BgDrDl+NT2rw0+YN+uZ1uZY7OlKed56j7Uf3eWPnGEdsk24DK5fVKLpcUCoWfmWYPAADqgrIaJKRWURwAUKdkZWfJH/QruP405Wefo3ktVstzk+fQfhuUP+hXVnYWybYaIr1H+sGKtqJtAJXP2sOfAQAAarsqaZBgjDnFGDP6BM53GmMeMcasNcbkR57/ZIxxFRtjjDEPGmM2GmPyjDFZxpieJa7T3BjzqjFmd+TxqjGm2Ym8NgAojTfVK+eGM6VXMmU/eUgvTbhGPl94v9vpltM45Xa65U31VneoiBjXf5zmDJ+jc08+V3OGz6GqDagC05/dLH+hlbXhqaRZWdUdEQAAwImrqm6kl0h66QTOv1vSeEm3Seom6f9FticXG3OXpDsl3SrpNElbJX1sjGlcbMxrkvpJukDS+ZGfXz2BuACgVJ52Hl3f7BWZUJxkXfL7pXlvrwt3Jz1/ltI6pGnW+bOoaqthxvUfpw+v/ZBEG1AZSrQdnfv2cr3992aRBUusHM4Q00gBAECdUFu6kQ6StMBauyCynW2MeVfSb6RwVZuk2yVNs9a+Edl3ncIJt6slzTHGdFc4wXamtfaLyJgbJS02xnS11q6q0lcEoM4bPaq9XpodVEFBoayjUH/Zea02/yNB7//8vgKhgBavX6zerXqTcKtBaF4BVJJS2o6+8X6BFOqu8FK/QfW9YJk8nn7VHSkAAMAJq6rKthP1maQhxphukmSM6SHpHEn/jhzvIClJ0sHFdqy1eZL+o3CiTpI8kvZJ+qLYdT+XtL/YGACInpN86jPpTplzHpCuS1MgebHeXvW2CoIFh63ZhpqhqHnFfZ/ep7R5afLl+Ko7JKDuKKXtaPoFCZLLL5lCKaZAvxsTU91RAgAAREVtqWz7s6TGklYaY4IKx/2otfbZyPGkyPOWEudtkZRcbMw2aw8tv2uttcaYrcXOB4CoKErcFDgLZM8Kycgc1trZyLBmWw1D8wqgEnm9ktst6y9QwOXQj90TNG5Ub+mfy/XG+7lKvyCyDQAAUAfUlmTbFZJGKzwldIWkUyU9aYxZa619odi4kn2sTIl9pfW5KjkmvNOYcZLGSVJKSsrxRw6gXipK3IQUkiR1a9lNa3auUSAUkNPh1PWnXq/RfUaTzKlBEhokyGEcsrIkQlE6ny9coeX1Sh7+7laIx6Plr83Sv54dr0/aB7V0xe3K7N9b40Z5NG5UdQcHAAAQXbUl2faYpMettf+IbC83xrRXuEHCC5I2R/YnScopdl4rHap22yyplTHGFFW3RdZ6S9SRFXGy1s6VNFeSBgwYQDN64ATVt7WwvKleOR1OBYNBSdKanWs0+4LZyj2QW2/eg9rEl+PTbe/fpsJQoZzGSfMKHKmUNcdIuFVMRkKuppxpFbQhOYtNo69P/20AAAD1Q21JtjWQFCyxL6hDa86tVTiZNkzSN5JkjImTdJakSZExPkmNFF67rWjdNo+khjp8HTcAUTb327m65d+3KGiDinXGKnN0Zp3/UuVp59H1p16vOd/OkZWVP+jXd5u+03PDn6vu0FCKecvmqSBYIEkK2qC+2/RdNUeEGqeUNcdItlWMN9Urt9Mtf9Avt9OthAYJ4en2gQI5HA49c+EzdAIGAAB1Qm1pkLBA0j3GmIuMManGmEskTZD0lhRee03SrMiYS40xvSS9rHBDhNciY36Q9IHCnUkHGmM8kuZIyqATKVB5fDk+jf/3eBWGChWyIRUEC+pNU4DRfUYrxhle8NvK6qX/vsSi+7XE5n2byx6E+iWy5piczvCz11vdEdU6nl+lH/ZcpxcTb1Dm6EzlHshVQaBAIYUUCAV0y79v4TMSAADUCbUl2XarpNclPSvpB0kzJD0v6Y/FxkyX9ISkZyQtkdRG0rnW2r3FxlwjaZnCXUs/jPx8bWUHD9RnWdlZCoVCB7eNTL1ZC6uous3ISJICoYCysrPk80lTp4ZnpaFmGN1ntJzGeXD7/Z/f50s/DufxhKeOPvIIU0iPR2QabvsZz2v0na/I82u40s3hOPS/okEbrDf/GAMAAOq2qppGaiKP4xJJmN0eeRxtjJX0YORxtDE7JP3P8cYBoOK8qV65nC75g35JUnipxPqjb+BmOT5rqWD7TLlSlyohd7jSrmbZp5rIFuuVQzdSlMrj4S9sGY66Pmcp03A9kyfrmQuf0c3/+6pCa8+Sq+MX9eYfYwAAQN1Woco2Y8yLxpgRZYwZbox5sfg+a+2D1traUkUHIIo87Ty6sPOFB7cDoYDmLZtXjRFVHZ9Puu2qHgpmPiC9slDB9afrO1+TI5Z9qvQ4cnyaungqlVrHMP2L6QrZQxWYVla7CnZVY0RA7ePL8SltXpru+/Q+pc1LO/wz5yjTcHv7x8m8min7ycMKvfKR9CvJTAAAUPtVNAE2RtKpZYzpI+m644oGQN1UT/v5hgs5jGRdUjBGwTVnSamLqnTZp2N++YWk8Hv0zo/vHLH/v5v+Ww3RALVXVnaW/EG/gjZ4sDr0oKNMw53+t68V8Dsk61LAb3TPX96vnuABAACiqDKqzWJ1ZOdQAPWUL8en91a/d3A7xhGj0X1GV2NEVSeh+3I5XAHJFErOQsV0/Fyjh3eu0mWfjvnlF5LCnUhtKRnh9B7p1RANKqJWVG3Wo0Uai7qNOo1Tbqf7yCmhHo80efJhH3wbW7wmOf0HPycXO/5Us3+fAAAA5XA8a7YdtUbFGBMr6WxJtHEDICmcyCgMFR7cvqjzRfViHSxfjk+3r0iTHd1PzmyvLj6vie66Ymr4tberumWfir78+oP+0r/8olQt4ltoXP9x1R0GjqGoarMgUCCHw6FnLnym5v3OIk0B6vQijT5fuIzX65XH41Hm6MzS12w7crg8Hul3I3vo641pUrZXSs2SOelr1ksEAAC1XpnJNmPMmhK77jDGjC1lqFNSosKVbf8bhdgA1AErt608bHtH3o5qiqRqZWVnqSBYoNBJn8vRzqekbuOUlR0u+q3KL5GedmV/+a3vRvcZrf/99vD/bLVu2LqaokF5ZWVnqSBQoJBCCoVCuuXft6h3q9416894KU0B6lSyrbRk4knHHj7knKD8fiO32+rTT5wa5xmnX678RY9/MV2yUqwrln8UAAAAtV55KtscOlTNZnX0zqKFkpZLypT0p6hEB6DWyw/kH3O7rkpokHBwwf2QDemF715QyIbkdrqVOTqzZiUEaqijdjWMMk87j67pfY3+tvxvB/e1a9JOUxdPJUFZESVLliqZN9Urh8OhUCj89ywQCtS8iqiipgBFyajKXqSxqpVIJq57e56GNH7pYCXtp9d9etjvY97b61RQkCxZpwoKCjXv7V/l8bTXqK6jtCd/j6Rw8rtG/Q4BAACOQ5nJNmttatHPxpiQpJnW2ocrMygAdYe3g1dfb/z64Pbv+v2uGqOpOt9t+u7gz0ZGgVBAVvbgumlV9WWyaKpd0Zff2pLoq+q4eyb2PGz7ozUfaeHahYp1xtaa96xa+XwKnjNExu+Xdbvl/OTTSk+4edp5NMEzQdM/ny4p3EE2oUFCpd7zuFwX6Rk1enTdqmqTjkgmzk/crIL9BZKkgmCB5i2bd9jfncTQfLnMLQrISs5CKXWRfDmdw9OBs/vJse4c9b25kTztqun1AAAARElFGyQMkfRKZQQCoO7x5fj01FdPSTkemcWTdU3zp2vemkqVwJfj0wvfvXBw22Ecx140vBLV1gYJxePOD+Rr3rJ5lXo/b6pXLsfh//4UsiEVBApqzXtWnda9PU82v0COkJXNL9C6tyv391WkWWwzOUz4f2UcxqHcA7lVct9yKZpi+fzz0it19H+dSnQYXdst6ehjfT498PT9+iSUpgfN/epz4XkaPbxzeDpwdj+FXv5IgYX365Yru9WHXhIAAKCOq1CDBGvtouLbxpgmkppK2m2t3RPNwADUfkVfovTKR7JBt177T6HOTlmucaN6V2tclT09sWRTCGutZl8wW7kHcg8m2qpqiqI31Sunw6lQMCSnw1lr1kIqijsYDMrK6vmlz1f69LLhnYdrwU8LFLSHGmqHFKqZ1VI1zIZfV2qDBipLXnmVJf26Uu2r4L7eVK9inbE1swFIXV+vrYjHc/B1rXn1wcMOLd209NBGVpYchYU6S19qoP1SgQNOSeEp98r2SkG3ZF0KFAY17+118niq4k8QAABA5ahoZZuMMU5jzD3GmJ8l7ZSULWmnMebnyP7j6XAKoA7ypnql7MEHv0TZgEs3PTNfvpzqK1somp5436f3KW1eWpXEElryOz1201Al/DBZy7cu1+CXB+veT++tsvubyDKbptTlNmsmTzuPeiT2OLgdtMGD0wWjrejPxIKfFsiYw98jh6quWmrut3N13qvnae63c6vkftG0dVmyhipT9+sRDVWm9q7sVCX39bTzaNb5s5TWIU2zzp9Vs6b7Fk2xdDrr5nptpfg85/PDtr/e+PWhzzivVwGXU4VGKnRKn6ZazVs2T7d/cLts+08lR0BSUNYU6sVd11XrfycAAABOVIUSY8YYt6QPJA1WuFlCjqRNktpISpX0qKTzjTHnWmv90Q0VQE1SnuowTzuPuvb/i37I8kvB8Bo9ofaZyspuWG1fikubVhntWPq26XtoY8n/J2XM0c+SbvzGylz8rWz/cNVbQbCg0tdvy8rOOrheXI1cQP4ofDk+Ldu87LB9G/durJR7Ff8zcbAdUISVrZJqqbnfztWNGTdKCq8XJ6nWTLn25fg0Z1+q/HIrKJf8slra5DKdV0X3vv2D2+UP+rV4/eKa0420qFnErFlSbm6VNY2oFpHXurx7gvYX7j/i8D2Z92jRmEWSx6Mf//G0/vXseH3SPqSlqbHqLckf9MsqdNg5temzCgAAoDQVrUKbIMkrKUPSndba1UUHjDEdJc2QdHFk3LQoxQighqnI4vX9Ti/QD9elhacJpWZJ7b5UQoOxVRpvcd5Ur9xOd6VOO8s9kCsjIysr/ZAe2WskWdmVl0j9w5VLTlP50zqr4vVWhqzsrPD7V0yzuGaVcq/i71HxKaRSONm2fOvySv/S/8bKN47Yri3JtnnL5ikx8b9yr/PLLyu3CtW13XJJF1T6vUtNnv+qKu2KegSfL3zvwkIpJqbuTh+VDq1L5/erq1MaeK30ZYnmBr/s+OXgz71HjdO+/r0Vn52lxyKfRa8se0X52efIhlySnFIoJMe6c2rNZxWA/5+9M49vot7X//NN0gUULKtswYICglZAEDqswVYQxXNR7j3nKFpEpAiictRTFq/KOSrSHu8RN5YoAlVc7v2hPYqirKEIUzhUwGpZhUIQUCggCF2SzPf3x2Qms2ZPafH75sUrnSWZSTIzmXnm+TwfBoPBYBgRaRnpfQC+BzBaKbQBAKX0RwD3APgBwNj4rB6DwaiPuCpcqPHVwEd9sjvLCN7N4+MfPgbsJcDguYC9BATkkoaYc3YO63LW4YVhL2BdzjoAYn5aPEuWWjRuERCKuksiinrYZrHhzTveTLiIU6/L7IJwtuasbtzBMwcTsixpm7ir612G0+dsmpOQ5Srp1bZX0OH6TPmpcuzvWYIvrFmYjefwhTULB3rVTQmgJJRKzUdGVbYQxZ9nnxUfL0XSfmGhmNFGqfhYWDfNIi4Jilw6i9eHnF3AjE1ApjswS/sm7c2ff5TDiN0/4vqaHCQlWWCxUiQlA29N+a8Gc6xiMBgMBoPBMCJSZ9t1AN6glApGEymlAiFkFYDHYl4zBoNRb2nRuAUE/2FAoOYB8q4KFwRBfbi41O4qZQgXHkMAACAASURBVPkrADiWOeDxeZBkTYJrXKBsKZYmCjuO7wgM9H0HhFhER1v3FUjqtwwTej+S8LB/CanMrsZbg/UV6wE0jPJE1yGXblz/Dv0TtjzOzpmWqZ6rTnz/n7SUgGuPgKiG6zunLpxCuR2Y9WAJHBUlmJUO9Lr+kTpZtiSUSvtqxvuuxDYlkMpDL+ey0EhwOMRMOkGAAIrxOwCbANRagaxxosttX+U+eXalK9r60yDQpevgqW0LoA0sVh/+cO8p5E1pA467tE10GAwGg8FgMGIlUrGtFsCVIea5AoAnxDwMBqMBU3mxEhZYIEAIGiDvSHfAZrWh1idGOFqIBa+PfP2SORZ4N49hy4bJJZUjrxspr1utrxaFuwrB2bmIymSNlvH2t2+rxt334AU0Sf4XABtyem5E2S9lmO2ajTE9xiRc+HJVuFDjrYEAAYIgYOqXU+tPrlUQ2jVppxvXJLlJQpeZmpRqOP5szVnwbj6hn5lSsKagDaoDassrWgKnRGGlxC6Khf/smVNny+fsXOC7cUBsRlBbG1VTgqAiu6JkEsnJwLp1xoJbTg6wZAlQUyMKUb176+e5jBCoAEIprBRIgr9g3gc4KsTtQbn/SB2qhUODIfx6DahHakhCIPgIVv48H3kdRgKo38cnBiNWEt0VncFgMBiXnkjLSL8D8J+EkFZGEwkhLQH8J4BdRtMZDMblgSPdgRRbCiywwGKxmAoDnJ1DZodM1bhwSkh5Nx/30k5AzJaq8dWAgqLGV4OSoyWq6Sd+OwHAOAcqXFwVLl3u1/7K/VgwagEWjFqAsl/KMGnlJKw+uBqTVk5KeOdJR7pD1WHTR30RvZ9LRd7APFg0P1GLdyxOWIdC3s2j2lNtOI2CxrUTqtH2verAKtU8C7YviNvyEk3z1Oaq4cEdB9fNxSPPAy+/jLIiJyavnIzJKyeD7wBRBHvhBXMxzOzlQnUqVpRMyq45IzgOeP11Ma+NUmDatEtTzloHnJhfAOLxgiBwQkkBUAK40gPzFe4SS2lbVI6CsGw1sP4F0B0PwmqVn+FvoLO+QRyfGIxYuBRd0RkMBoNR90Qqtr0JoBWAbYSQCYSQzoSQRoSQToSQ8QC2+qe/Ge8VZTAYlwYjYUDKAbNarBCogGlfTTM8WXSWOlF8uFgeDlZyqlxeok5CJTFNHr6gHm5zZRsA+hyoSMpeHekOEBDVOKVjyigIvy6pi6YM8YCzc/jD9X9QjfMIHvmiPZ5I29z2Y9tN59lbuTduyxq6dChmrZ+FoUuHytv3sXPqEtadJ3YmXIiNG+rNHc0bNzeeL574XWb02f/Gtf81CTuLFmJh6UIMWzZMFNxmzoy4zDOkyO5wAJJwTUhw11xlJSAI4v9gwlwDR1t6LW0K+5rrGyUAQOXuDFiERgC1gdAktBnyBXqNKoH1lrdhGZ+NlPRvG8TxCYAs9taZkFrXy2MkDFeFC9XeavioD9XeaiYwMxgMxmVKRGIbpfR/IXYZvQaAE8B+AL8BOADgHQCdAPzDPx+DwWjgOEudGLxkMGatn4VB7w7C3R/fLYsDlRcrIVABAhVM3V9GQpIqz8yAWFxloThddTro9KapTeXSjnm3z5ObKETi0uHsHHq26akap3T+aIPvx/QYg0RSuKtQ5bTzCb4gc9cfeDePL/Z9oRv/9rdvx90FIG1zAgSdUCqx59SeuCy3YEsBPIKYtOARPCjYIjrmJtw8QTfv4m8Xx7y8uqDNFW2CDicEv8uM+AQk+UsWARgeM8J1yjrSHbBZbCAgsFlsetGnrAzwesW/vV5x2PTFHGKpqdUaVTlrQ+H8DV0AyO1f5MfrKwNNEiywIMdfVuxwAElJAmDxglpq8FOnOdjZdwAyJixA334ePNb/MbgqXPrvqr4JTTwP35DBoLNmwTdkcOLXi+eBYcOAZ54RH+vL58CIirM1Z+UmShTUsCEQg8FgMBo+kWa2gVI6ixDyGYAJAHoDuArArwB2AHiXUsrOABiMywDezWPKF1NkoUaAgKI9Rfhi3xfY+OBG2f0l5ZoZuRHG9BiD1QdXq8Yt2bkkaHOAcF43Wo6cOxJ0uuuQC29sfSOqrDYJ3s3ju5+/U48kgWnzSubJo63EiozWdRsETkHhqnDJ2XT1NTOmcFehLEop8VGfnK0XLySRRfAJ4iMVdKXAFDQuy915YqdqWHK0GW0HP53/KaZl1RW92/YOOpwQ/GKWr6YaHguVSxYtxKI6ZmhzGjeM2xD0O1ReAOtYsUI/nGuSuchxYhnrZd5MgZ46CR/Ek0mKgLPNSgOZbQIElP1SJn7uHXjQnJnAjxyQ7hI7VSOwX2w7tg0EBKm21MDxN9ysvDrk4KzJ6OT1ieWzXh8OzpqMzht2hnxe1BQWihmAgPhYWHjJPwNG9Ow8vjPoMIPBYDAuDyItIwUAUEpLKKUTKaV9KaVd/I8TmdDGYFw+GGWPAYFSPqkLYDD3V26fXCwatQgdmnQIPN/nwWzXbFOXiVSimtUpC/NunyeLQvHIcDPL5JJo17RdzK46V4VL7tQqITl9XBUueHwewJ0JbJoB35F+CS8fyemZAyuxysOSY6chZ8YUHymO+/oKVJAFlvl3zkeKNUU3T/mp8piW4Sx1ouJshWqco5MDAAzLY89WNwy3g9atenbDqsS7kPxi1tGnJ2Hk+CSU2EXxev6d81XHIm1OY7AyZFeFC17BCwoKr+DV75u9egUfNlrHKMpZGxItRo4Bj0zMwQyUQMzn9CewqTLbJJemq8IFT7tiYPBcWWiT8R8Xqbs/anw1gc8/3Ky8OoTu2QMA4JGJlzED279rGt0L1TfHHqNO0DraE+1wZzAYDMalISJnGyHkOQAuSmlxkHkGAxhGKf17rCvHYDDMSbQryZHugJVYDQW3SMhonYFRXUdh8Y7F8AgeCBCw9tBabDqyyVCk4908pn01DbW+Wmw6sgkA5OFo3WYSzRo10+W0AWKZ58N9HsbobqPx9YGvVa66SD9nbSadlVgDJVTpDlh/GgTvsq8AXzJgrUWLUT9G9V4igRAi13dJgpJRuW59crc1TTW/eC0/WY6swqyYtgUlShedR/Bgx/EdGNllJIr2FKnmCyXWhsKorPq1ktcwuttoXZ4gADROahzT8i4FmW5g2nufA77PI3IhRXU84zhcw3EYW9obqeUrDLv7aj/X8pPmgunZmrOyUG6YL5mWJma1USo+pqWJIsll7l4LBg8OU0gOfDQJVgiYjymYiHewq2tTlNjPyfOl2sTcSmX5nAp3JrBsnXxcJA+OCDgUpZLcKDvMJoIDraz4+UQmsrEOtUiG9UwtzhaVIXd0CKeycnsBxJJQ6X1t2GC+DeXkAO++K877O+hwy2AwGAzG5UCkzrbZABwh5hkC4PloVobBYITHpXYl9W7bO6x1kOZxljpVJYECFVDtrTZ0mWhFoBXlK+KW4TYtc5rh+NPVp+XyTqVbD0DEn3PlxUo594uAYOLNE1XiQddzE8ULSmoDfEnYwUfpiAgTV4VLldPmFbwo3FUYUxOIRMO7efyT/2fQeeKd56dl5HUjdeOMctUiQZvXByDg4DGIijt18VTM+3aiOvsqyemZgxRrCggIsg9bkeTxiS6k6mqx3M3IueN0AiNGAE5nTMcz3s3jsVWPYc3BNXhs1WO650pNTyS+OfKN6bHqlS2vqMbpOic7HEBqqih2pKYCLVqI5Y3PPis+/g7dSa85T8NHUwBY4YMNUzAfxSQTaybeqpqvR6seAIKUy1U4VMfFu1L+J3DclEpyo+gwmyheG5KM9cSBWiTDBxtqkYTXPgpRCiiVw0rbS0GBWBJKaaA01AyOA95443fR4fb3gDaPs6HkczIYDAYjMqIqIw2BDYAQci4GgxE1iWwioFyGmattwfYFYa2DMnheCwXFkp1LdBe+WhFoTI8xcROFMlpnwGJy2Kv11crlsTMHzwRn56L6nFs0bqHKfZLyq5ylTgxdOhTlVy4ArLUA8QBWD5C+Mer3Ew6OdAcsRP+ewykDvlRoBUIjtNlcsaB10TVNbRqykUc0pKWkGY7/4eQP+GzPZ7rxUr5etDhLnRj47kDMWj8Lg5cMTpjgxtk5bBi3AS/d+hImXfdnEDktnwLvvKMXo5xOYNIk0NWrQSdNwo/5M6I+nhXuKkStrxYUVN6HlWi/WwGCochfsLkgUP7tL2c8e6C7foHjxgETJ4qiT2VloLyxqkoUT35nqD1qBD5Y8ffbJuK7zleoppyvPQ/AWHAGIOa3+Y+LSckEeWP7qafXs5LcC31uwkd3ukAsgWM5TXcFf5KyHLa6GtgbYYfj30mH298D7Zq0Uw1Lzk8Gg8FgXF5E3CAhDPoAOJWA12UwGH60ge6JcCXpSqjcmaL7IN2FXdiKyX0nh2xkIAlnVd4qw2V4fB5d+aIkAilLyjJaZ8SlZNZV4TIuYfKzYnegzK9329448usR2Cw2QEDYQt+qA6t0wxmtMwLNJuw8MC4LqHDA1nkzckblR/1+woGzc3hqwFP4x+Z/AACSrElyWStn5+qVyCbhSHeAEAJKzb8rj+AJhK7HiOuQSzd8c9ubdfOtKF+hK1OMBLPtZ3nZctPnfPXjVzjy65GgTUWM4N08Jq2cJA/7qA9TvpyCHZPiLyICim3pkRvUE6TunTU1ojjAccC8eXKYPgXQ++Ni2J5IiWg/kwiVo/f53s91405cOKErWz12XmxUoSxn/J9NAkZf79d3tCH9OTmi040oLIlFRcD06UB+Yvfp+sS03OaY9HUtICQDACw2L16c/RBy/v2yar6tR7cCMBacCQiovQQYl430sw+iV+ZZoMNgAPXv2CQxN3suBhwZAFydJf8u3pU9JPiTHA7RFenziUL0gQOiU83rFR9zckI/v56V0zKiI29gHj7f97l8Q5M/yoN38/Xy95jBYDAY0RNSbCOErNeMepAQ4jCY1QrADuAaAB/GvmoMBiMYPuoDBY05U80MlbNHk6dDx2Wh8mKlThTTIjU7eGHjCzh6/qh+ISQgQCgvfo1eJx4noY50B6wWK7yC13D6yYsnsbB0oWYVCf7j+v9A3oC8sNZh76m9uuHCXYXq78leAthLYDUI4Y83vJvHG1vfACBmt03LnFbvT+jLfinTNZkwIlbxS0LrKki1pSKnZw7e/vZt1fd2KUKsiw8Xo/hwMZbsXBKyk6YSI3dY2YmyOK+dCO/mZbfYK56LuMJoJkEQyy4BoKoKPDKxEQ4MhQttvCUY32s8Ol7VMSJB3VnqRPFhdYSs5KCSIAb1uT/8/AOGLh0KH/UhxZqCdTnrMOHmCdh2bJuqnFHw+mR9EC6XKBgKQkA4nDkTuPlmYNu2wIu/8gowenS9cWAlmtzRGcCKMixe6kG7Ju2QN6UNOA7of7w/Dpw5IM/Xv0N/AAY3cfyM7jYaX1i+QIWdR5s9wJcPWXHlo/ORMTr2/TsRcHYOva7uhZ0okRs9fFpeifzsIEIrxwEPPQQsWiSKbYIguiQ7dgwv8+930uH29wBn53BXt7vkXFBl4ykGg8FgXD6E42xzKP6mANL9/7UIACoBfAzgLzGuF4PBCELhrkJZMJIyuBJ6kqbK06FAhQOvb31dLrc0Q2p2UOOtMZye3Slb7jaaVZiFWl+t7GiioPKFcLzeG2fn8HDvh3WCWjAoKD7b+xnyBuSFNX+KLSXosBKPoHf2xRtXhUt2FlJK8Sr/KkZ3G12vT+qNGgkYYVqSFiE9WvVA8ZFi1TBn5zD/zvl4ZOUjshvyxzOxNbOIqCRU4SSFvUTOdgv3e1OKGg9vB8bsBj7pHn9hnnfzcCxzoNZXCwAg3a14a79hBB2wQxTw329yC3KxFLVIRjJq8exVWfj2+LdYMGpBRMs22k4+LPsQj97yqPw5jeo2Sud+239mv/y39LnKIr9UzuijsNgEOBz+Tr4tWojiCKAWDidMUIttgiBmb/2OhJDc0RnIHa0e1yS5iWrY/asbQCDTUukwpqA4dv4YPIIHmW5g3TIg2ecD3TQV2JBRbz/LA6cPqIb3n9kPZ6nT+AYAz4vbxYkToivN6w04JCN5fxxXbz8PRoSYG7cZDAaDcZkQMrONUmqR/kM8f56tHKf4b6OUXk0pvY9SejLxq85gMBJJTs8cWIn/QlORpyPmjLlw4sIJjHhvRNDXCJbZZjSfj/rgFbzwUR8EKqDKWxX3PDqt8yUcBCqEvR5Hfj2iGj5bfVbObdNiJdaENyY4W3NWNewVvAltLBAPwnWQ7Tu1Ly7L034/0vDysuUqUaBgcwGmr50e9XIc6Q4kWZJCzyg5Sde/ID66M+Xnh4sU7v/wdsC5EhjxI7BoJcS8tDjiqnDB4ws0P1l4s4BVT48Ghg8HhgTK6iiAH/ydQPOb9FYFyy9o5cC2Y9vgLI1g3XgeL2xtjDlrgFXvie8TUGey8W5eVyKsRdoH5X3CXgLc/gTQeR2ajf57QNeorAQs/lMmi0UcBoCMDHUpKUONP/+ueHMtnKVOcR+w6vcBSax1VADJPsBGAavXV69zyWwW/f1qw6B7nhedaAsXiqXGHg9w1131ptkDI4Cz1IkR742I7FgUBbybx+f71CXuwTpwMxgMBqNhEmmDhPEA/pWIFWEwGOFjJg7EE8nZc81V14gXoOOygFufEx/9ZTNrD64NemKqbHYgC3cKWl3RSjWfquTLf5FWtObnuL0n3s3jw++jq3L/4eQPIedxljpxuuq0alwjWyNUXqzUNWawEAvevOPNhDvMtN3/CCH1qvOoEbl9ctGhSYeQ8+2tjDBg3ATl92OBRRaqfjytd7LFKriRcIQZTWdGVDgAAEV7i8JejuRsm+CvBpeXuji+Xe+UDUEAUYBo9ngeMHs2AFFkk6ae3F6MCTN6oFeqCzZSCws8ECw+uNERcGfiv9f/NyavnBy6kYM/P63vW0WYsVkUEp0rA4IbEOiE/O9j/zZ9GZvFJu+DsijtzgS+eg04mI0zRc+B5/1lsmlH4EtOEjO3UlICeVlGYlDv+B+PGxo5PXN0ovGcD8Qy6MwOmap5CYgstrnSgVor4CGA10rqdS5Zbl+9g00bfA9A3EY8AUEaggB88YX4N88bd+vVEu58jKjg3Tzu/uhuTFo5CasPrsaklZMSKrgZNaAy7dTLYDAYjAZLRGIbpXQZpXRXolaGwWCEh7ZTYiI6J0oloEfPHRWFMnsJMHiuLLQBoosk2ImpsuPlwI4DddO/OfINXt4kBmmvy1mHwR0HixMUF2nbXp6DttPuicuJb8GWgrCywIxYXrYc939yf9B5jFwN0zKnwZHuQIotJSAmujMhFOfhx+9aR7Uu4cK7eTROaqwa9/SAp+t1CSkATF87XZXxJ3Wi1dKtZbe4LE/6fqzEihRbiixGjr1prOH8BZsLotoeXRUu07xAFQZO0kiXu+P4Djy8HUg/ExhHAKCdgRgQA0qhkoBgQu8J4I5CbCZQXBxYLoChh4FF+btRuH411tMsTMQ74rTSicCydTi591osLF2IoUuHBhfcXC6gulo+gZFef8xu8bFpalO4Klyo8dWYNkTp0bIHih8slkv+ZAecKrPNhsKiw8gqzMJDJ99GVg7F4acmqh1JUui9BCEB19vlSJiiD2fnkHbibpVoXHVA7DBa7akWZ/LfUOl47k/o2qIrAKDEDmSNA567FcjKAfjQmvslIz87H2MzAscIAoKRXUbqZ3Q4xAYISnw+saw0K0vfrVeL1Jwj1HyMqODdPIYuHaq7mRFunEE0SE2ulFyKTFAGg8FgJJaIxDZCyB8IIR8TQg4RQn4jhJwnhBwkhHxICLkzUSvpX3ZbQsgyQshJQkg1IaScEDJUMZ0QQmYTQo4RQqoIIS5CyA2a12hGCHmPEPKr//97hBB9aywGo55T8lOJarj8ZPCOfNHgqnChxlsjl3SGwrB8BuJFlyPdgc1HNuumHfn1CJ7d8CyyCrPE4XP+EsxdOYA3Rb5IO/F9N0xaOQl3f3x3aNeLCc5SpxxGHBH+C0K4M7G8bHlQV5PW1dDr6l7I7ZMri46tGrdSCYmvTLo9YddNvJvHkKVDVBcQSZYkjO422nT+lze9HPXnG08+Kf9ENdzmyjbo0aqHbr6LtRfjsjylKKzMCMzPztc5EiXMtvdgtGjcwnxfUmxnZk5SAHh+w/NhLavz/62DcyVwtf8jEgDAZgPyNNmDMTpmlEKl1FhCbiYAgEcmRmMFMsHjbTwMSZYagBJ0xBFAsOkcfFJYuCktWgCUqjqaAsCK7uKj65Ar+GcNoGvLrqph2ZGqEDotNh+QvlEucf+mvQ8fjOqoLv3jOODJJwPDlAby3C43IhR9ut58TCUap/c8DACYcPMEcTtf4gLWvQT3a++ha9U43fN91FfvS96HXKMslaaY+uVU42PoQw8BvRQZk4IAlJcD1dWi8FZba14y63KJ00PNxwgbZ6kT/d/uj7s/vhsz1s2AR/Do5kmk+MXZObx1x1vo3rI7erTqgUWjFsWl2Q+DwWAw6hdhiW2EkCsIIV8A+BTAf0HsONoYwBUQmyX8CcBnhJDPCCGN4r2SfkFsM8Tz6jsBdAfwGIBfFLPlAXjKP/4W/7Q1hBBlSu8HAG4GMBLA7f6/34v3+jIYiYR389j579TAhTmAw78ejvtyWjRuIWetUVD0vLpn0Pm1HR2V6LpxKvBRH2q8NZjtmo2j546K72nHeIiHJwpYfLKzp2hPEYYsHRKVIBSNOGKUnVWwucB0+VpXw+RbJquGf7n4i9o547Ml7LqpYHOBzkXlETx4+LOHdesvldxJwuelFtzu6XGPanjsTWMx/475uvlWH1wdF8ejshOu1vU36JpBhs/597F/R/w5GZUTA9BtZ2knRxo6SQHgxIUTYb3nwdvF8mvJ9XW0dYroNFMKRXFwzBgKlQ4HIAjYgkwMhQv/wt3Yhv6YBCfexsPycx1wIRl6Bx8AlBwt0S9Mwu8cUwptPgDfXy3+nWpLlYP4zSjaUwTHMof8HUpNRJRC5/yP9yJnVBcM+smKWZsIBv1kkrGYlmac53a5EaHo81Pa/1OJxnsbLwUglon3+vEDQEgGYIHgs+Jj5zUAgEw3cP+7D6N03SqMffdhjKqs38KlVvyWmt7ISPuY0wl89536yZs3i+IsIArhZiWzDofYTMFqFR/rcWltQ8BZ6sSklZOw7dg2FO0p0nU0ljAbHw+kyoF9lftw6MwhZLTOSNiyGAwGg3HpCNfZtgiiQHUKwIsAsiEKXj38f8+B2In0TgDht/kLnzwAxymlOZTSbZTSQ5TSdZTS3YDoagMwDcBcSukKSun3AMYBaALgPv883SEKbLmU0i2UUh7AJACjCCHxqUVi/K6pq2Ddgo836QQg9zl33AUSbWlqp7ROQS9eo0Eq8ZLKUb2CVxSjBBvES2kB6L1EJTh4BS/GFeldEKE4U30m9ExaTLKzzFw3ygt8AiJnfwGKTpRK54zVm7Drpp0/G+e/lJ8q15XpKRtU1PpqL7mbJD87H3kD83Bds+uQNzAP+dn54OycykUiEWupD+/mMWzZMDyz/hkMWzZMtx/NzZpr+DwKisJdhRHt90oXmKqESLOdtTt1LxaNWgQbMW4YHo5wfPHG6/3rKXLA0VMfxm4knsQjG4rjgKQkuOCAF0kQ92Vxv3gZM+X14lCC2wYaO/h2/rzT/JjmcAA2m+xsk/47KsTJzRs112XJGVHrq5X35RtaKYzw9hIMH/ctckdngDsKrF1G8fcNFGuXUbFE1mh9UlL0eW6XGxGKPq2uaKUSjX+t+VXeT85WdFLNe3jPVbASKzqvfRhTqRNrMAJTqRNfvRxG2fUl5Gz1Wd04lSAruTwFIdDNVsKnuAE1frx5swSOE0uXX3iBNVWIA+H+Zny297OErYPyN7fKW4VpX02L+hyuPrnSGQwGg6EmpNhGCOkFUbD6DsCNlNLnKKXrKaV7KaV7/H//N4AbAXwP4H5CyE1xXs/RALb6S1h/IYTsJIRMJYGk6U4A2gBYLT2BUloFoBjAAP8oDsBvALYoXnczgAuKeRiMqJDulNZFsO6xsq46AUigQkwna0ZoS1NPV53GXwf+1XT+TUc2mb7vnJ45puV4OpR5VbYaoKde2Np/en/oXCcFzlIn9p/eH3QeAgILsaCRrZEs9JhlZ5347YThaygv8CmoHFIPQN3t0O/2uPeVxQm5buLdPCrOVphO17ovpPwYAgKbxVYvGijkZ+dj/+P7kZ+dL49T5iPFi8JdhXK2V42vRiekcnZObBJiwIrdKyLa7zk7h3m3z0NWpyy8dcdbWDRqEdJS0nTbWde+x5HbJxdPDnjS8HXKfi4L+b7S/LFYRDMMICCotWgREE8IAd57Dxg6NCKnm6krctgwOODyzxUQvS5AzBD8+Qrg0T9Y8fltxg4+QHRnGsJxwFtvgVitcgMGj1UM1weAlftXYtWBVSHXHRCdgrybx/qK9arx0j5wuKgQpNYDqwCg1oPDRQZC++9FDInwfWa2F53XmW5gxibxURI6qom6kQxsF9E5rTN2nJFK98Qt95NDN8f1LcSb61tdrxru0ryL2h3rcITXrfZ8iC7ZHAfMnHn5blt1SLjloZ2bdU7YOjjSHbBaAlmP245tM7zZE4r65kpnMBgMhppwrn7vg3gum0MpPWk2E6X0FwA5EM+Q7ovP6sl0BjAFwEEAIwC8BmAugEf909v4H7VtC39WTGsD4CSlVD7r9//9i2IeGUJILiFkOyFk+8mTpm+bwQCgv1OayGDdCXdfaygAbTu2DYOXDI6b0FftrdYN52fn60J9JYLl1XB2Lvw8kiB5VUqKDxeH9X55N4/JKycHnQcQ88xeHPYi1uWsQ352PgrvLoTtmu2G6/LZvs8M32flxUpYiL+rJbGonG2qsji/2+NkM+PXiZUZ62aEnEcrqAlUAAWNuoFEXaD8PCXWH1qf8AsMnbjqz1c7ufda1eg5m+YEfR3ezePxVY9jzcE1eHzV48honSEGITyoCAAAIABJREFUw6u2+Wzk/UlsFJKfnY/mqc11r1Plq8KI90YEXVZbTX6gPKwsHZ02DXjsMaBrV8DrBXbvFrsmRpANZeqK/PprDBjeFPeR5f45xZ/e8VgCAHh2GPD/Bunfm5Jj54+ZT8zNBTZtAnnkEXydlY5hD4rh+oDofg23s9/pi6d1jSuSLEny/vHF6RJYqLj2Vgr8IBgL7UwM0ZPTMwcDj1qwYSnw4jpgw1JgsrcXnKVOnLhByr4UtwvbwPk4efEkqjNWqMYPH1NT16sdEfPvmC932rbAgqxOCsGD58UmCFTjsLRYAmXHEh9+yBof1BG5fXLRr12/kPNNuWVKwtaBs3N4qNdDqnE1vhrzGwwm1DdXOoPBYDDUhCO29QfwLaX0u1Az+juVlgLIDDVvhFj86zCTUrqDUroEwOsIiG3yKmiGiWacUU2Jdh5xRkqdlNK+lNK+rVq1imHVGb8HtHdKx/QYI4s8k1dOjq8YYOdNxSgf9ZkHNEdIlxZdVMOOTg4AwK3pt5o+xyeYB1rn9MyRhSgJU7ebSV6VjF/s8B25JeT7dVW45Ow5JdIFkkSyLRkzB8+UXQmcnUPxg8Xo0OOovgsrFQxLSR3pDqRY/V0trSkqQSvFlqKbf83BNarcqHjAu/mwsmbKfgm4owq2FMgB0SHD6esIo9IYI8edl3ox4N0BaPRSI4x4b0TE5TQ5PXOQbE0GAUGyNVkM+NfQ8aqOgQGDHD+Jw78eDir+GrnoJtw8QZzo3+bz/jxY5Yx5Oftlw9dafXB10PfZ9tE8CMlJEAggJCeh7aP+xgjK0tGaGuDVV0WRTUuY2VBBXZFff43lwgMY+8hPsF/hRh7mIh+z4APQsgoY33t88NfuFGL5HAcsWIDn/9RaFtoktDcLzCg+Uoz3vlNHt/7xhj+Cs3NwljrR5htRtJO8Sf2+0ziyfk9EmPHH2TksOjMIKT7ACiDFB2Su3yfejOr7DjAqF2i/Fbj+Uzz5H8OR1igNh257B50G5qJT86/Rfejj+NuCoUGXcanh7Bw2jd+E0d1GQ4CAhaULMXjJYJQVOcXPaNEifflodjZw773qcZSyxgd1BO/mse3YtpDzGd3cidfyX970Mnq37Y0ki7pLbdHeoqBNmLS0aNwCFmKBhViQbE2uF650BoPBYAQIR2zrAuDbCF6z1P+ceHIcgLbd4m4A0hWQdKtZ61BrjYDb7QSA1orSUynrrRX0jjgGIyJy++Ri0ahFGN55OBaNWgQAGPTuICwsXYiFpQujKg8wY0X5iqBiVDw6uPFuHh99/5FqXFqK2Lg3WGmFAAEFWwoMTxY5O4d7b1RfYDw98GlTwc30zrNG7PAc7hNUHDI7+XxqwFOqYaO72Jydg/tJt+Hzl+xcovtOzbpaAkCKVS+2UVBVblSs8G4es12zw5p3Xsk8+Tmf7VFn05iVyUbK9LXT0eX1LhFdPEjrZFQaw9k5tLlSZ0QGIIorqw+uxqz1syIqp+HsHFzjXHjp1pfgGufSNUgAgGWjlwW2U5McPwnpcw0X7bFDWTYrTW97ZVvD5wZ1QXAcrK6NsLw0B1bXxoDjSpm7ZbGoc6MkRo8WywSBsPLbvIIXFFTXkEPi/QUdcGTNT8hv9AIEqwXeZAv6jxWz+Fo0Mg/Al445oZAFSwUnLoS/De8+pRYb91eKJeeLv12MdprqvpZnwxPxLkui6IpZoxE9j50/hl5t/V05r/4e+PkmYO8f8D+P3IE/Nn0VAHDotndw6PGROJC1qMGUxSm7PvuoD65ls8XPSOtqs1qB2bOBG26Ajsu1i209I+j5kaIr9NkafR5frCgzQqd+ORU+QX/8/cfmf4S13UtNFqTj7mP9HzP8/WIwGAzGpSMcse0qAJHUUZ4CEN4ZcvhsBqBtYtAVgNSC8RBEMe02aSIhJBXAYAQy2ngAV0LMbpPgIHZUVea4MRhhoXXeZLTOQOOkxnh+w/OYtHKSyk1V4xO7bSb6wsECi85RFQ1G3UOV+WPBOFt9FgWb9YIb7+bxye5P5Gy0vIGi08bIdQYAqUmp2PLQFozuNlo9wUDsWFi6MKLPtklSE8MQfjN6temlG2dWslH2SxlcFS6VcwwA7rsp3tX1aiSBau3BtWHNv+fUHnR6rRNmrJth+h3EwvS101GwuQAHzhww3B6CEaw05m+Ov4V8fpW3CjPWhi6lDRfOzuGbh75Br6t7meb4Seyt3Gu6Leb0zJGdDEmWJNlFl9snF18/8LVpqfVsx2zD8esOrQux4galjcrcrbfeErsgKrFagTy/Cy4MF9OMdTPkY4WP+sxLmP3LtbzwIlJd32D0eHF/G9xxsOnqh3uxm9snN2S3ZCCIgK/hTNUZvLzpZaQmpWJxb3GcLJlM0At7vxui6Ip5VaY4D1UMn6s+Jw4ojuU+D8G5Pb0x+vrA8V514ygejTsSxJQv9TdqPr36jPgZKctFrVZg/nxxX5A+SwlKgalT6+X7a7CYbDOm50eaG3n/+PibuJ+zKd3NHsFj+NtLQcO6YeqqcKHGWyPHP7zKv9pgxGkGg8H4vRCO2NYIQG0Er+kBkBrd6pjyKoBMQsgzhJDrCCH/BeBxAG8BcvbaPAAzCCH3EEJuBLAUYkOED/zz7AbwFYBFhJBMQggHscvqSkrp3jivL+MyR+m8cSxz4O6P7sagdwehaG+RqaNi9cHVMTvceDeP1QdXm05vnNQYI64LnuUUDuUny1V3eIFASUVOzxxdCaYRS3YsUQ1LAgoFBQFBWkoa3tj6hunzd53YBc7O4dM/fyoLcwBMxQ4zccXopHVyPzHDzSiE34j5d8zXjaOgupP2YI0y8rPzMTZjrKqjKwFBijXFsHQxUqTPN1zhjIKioqwNit8fIH7Hiu/bzD0WCUt3LA06HAxHugPJ1mRYiVVXGpPbJzesrrjFR4rDEvhCdSOV4Owc5t85H8S+NWimoECFoBdKhBAQEJBwQtP95PbJRfeW3XXjf6v9LezXUCGJcLm5wEPq3CAIguhYCtPFtPvk7qDDhstViH95A/NMv89Pyj8J+3gZapsY3nk4tk7cimRrctD5AODAmQN4dsOz2OLegnf6ArmjgK+vBYpnjRU/s8uBaMSrKBpBXHtYFNaIZhiAwbF8I0ZeN1KeLFBBvMkTYflqXVP+i7bwAjjT63rxM3rxRbGUdM4cYNOmwPbDcfp9z+MRM94YscPzwJAhoLNmwTd4EIqWTA8dMaC5kUcPDYl7pIK28ZQZ4dwwdaQ7VL8jwWI8GAwGg3FpCLM94KWFUvpviB1J/wix4+lLAJ4FoLwCLgDwT4gC3HYAbQEMp5Qqi0DGAtgFsWvp1/6/H0j0+jMuP7TOm6K9RaLIoRGotBh1O4yEgi0FQZfxm+c3FO0piqhTpxGHv2+nyaXi5JM/ZUZNsAvckxdP6vK2lALK2ZqzqPJWmT6/WaNm8t/52flyea5ZA4XN7s2Gr6N1x1hg0bvlQsDZOTS2NdaN17rXXtv6mmp48beLVcPv3/M+Nj+0GXNunYO8gXm4rfNteH3k63Ep/ZA+X6PvJC01TeyuqkR5F3/pBvG///vu7Y09GNpL1SWF2ry+YAQrxwWAW9rdEtbrOLeHbhYSqhupEleFS+w2G6SMm4CYXii5KlzwCT5Q0IgvjMofLVd9t3PWAHtepzg6+f6wX8OQnBy1w0ZyLCldTFYrcOSIocihFQGNRMFgcHYOmx/aLLoGNRw4cyDskuCgzRQQcAdOy5wW8rUoKHzUJ5dnvdMXGPkA8BHXJORzGwQ8j28GPY05s87hm0FPhxavlMJcFI0giOYxp2eOWFavOZY37fKD2GTGf2pqgb/JTBTlq3WJ0c2n+XfOV4vaRp9ZTo64bzHiz4wZoF4vCACLT0Da3wowa/0sDF061PwYb3AjL16RCoB4Y0dbsm6G9tzCDEXPNwgQwq5AYDAYDEbdEO7Vz4OEkPXh/AcwLhErSin9glLak1KaSintSil9XdtZlFI6m1La1j/PUErp95rXOE0pvZ9S2tT//35KafxDGeoYoyBxRmIxFDaCBKcrieXkbe+O5vplGIhvsYbck8PDVHd421beqxI8JMdZ80YG3QQV66NcB62A4jrkCroOMwfNVA3n9skNiGQGYoeP+gzD6bVdCQUEdx6ZMbX/VN24yV8Eml/wbh57Tu5RTW+n6QgJiJ+DI92BN7a+gXWH1mHaV9Pisu9Kn++1za7VTfvyvi+R3TlbPVJbjutLkv/ewTeNaV14N4/TVeog+SuTr4zpNZVsnbgVVoS+SD1bczZkt9qSn9SCWfkpc+eBI90RkWho9HzTZgJh8NeBfwUgCm0zNgNdTgPtFy4HpkeWiaeC40Tx4pFHxP8bNojjJBfTxIkAIcDbbxu6iuZmz1WJI3Oz50a+CnYOOx7ZYSjUVXmrwjqWXZVyVdDpUr6d5DANhtTkJBwHb0Nk9YSFGC6swXN4AcOFNVg9YaH5zDwP35DBokNoyODIXWU5OUBKirgNpaQAOTng7Bw2jNuAlo1bqo7ln+/9XGwyY/M3mbH5IxGiKF+tS25prxb/e13dK7wbKBwnlpVareLnk5wsfl6M2PnxR9VgZ//PkUfwqDuDK7GXwPLgcNWNvHi4vAHR9T506VCcvBheKo/2Rp0RhbsKdU72VQdWRbV+DAaDwUgM4V41pANwhPk/PT6rxggHsyBxRmKRhI1JfSYFRoYITpdnO1sR9XK7/TZJvYxdOWp30sr5suj2zrfvRL09dLzpoOoOb5fePxnOp8tb0giOH35VoZrM2Tm542dqkr7avF+7fnJQvFF+Vd7AvKBlYEYnqK2uUHcTthJrVJl2RiKWQAX5It6o62nXll0NX0vKWvFRH2q8NXEr/eDsnK6BRb92/cDZOTRN1Qho2rv4Vo+qnCsWjN5PJCJzOKWdTw18Sv9EA+F5zqY5pjcjeDePnSfUYuyRs0dM14uzc3h6wNNB1z1U3g71p1dRGDXHDk5+dj6uSrkKY/2mB1nq/+CDiF9Lhb+rJxYs0Oe7dewIeL1BXUU2q19AtNp00yJBu69KLN6xOOSxTOmENULpfHv/nvfR5grzi+gnMp/AC8Ne0DVR6d22d9BlNBQ2HrKjFsnwwYZqpOD9A+YN5A/OmgyL1yc6hLw+HJw1ObKFcZwo4L70UkDIhbgv2Szq7eVM9RljV2sU5at1ydib1OLt5Fsi+Ixyc8Xy0pdeEvetevbeGix+QVY6yrrSA5N2/bzL9Gmkg/pGXjz2ed7NY8oXU8SO3yGqHyRqhUjSewIcOxfc4ctgMBiMuiUcsW1YFP9vTcTKMvQECxJnJBadgBEiOF1i5887cfUrV0fcoREAuvY5plqGhVgV4lsKsD1Xdrx5qRcD3h2A+z+JosysI68q72nezTjWUJWlBugEx1/39DK9SD5Xc043Li01LWhQvNQ5cs6tcwzDzo1OUKXOghJdW3SNqmzT7E5z0d4iOEudhq4nratOokXjFhDc/YBNMyC4+8W19EObCSM5zHTroizhenCY+P/W50DG3YacUbE1lDZ6P795fgvpMpMIp7RT16nSxFl6+NfDeGb9M4Y3I4xet1FSo6Drlp+dj0a24POYfZ+xlJFKVHmqcFCrK3U27xAcMw5HIOTdYtG5iuLxniR6tOxhOD4cp662I2mmG5ixSXw0mp7Ty9xBtPP4TswcPFO1jREQObeyoVPdg4cVXoiSrwUfeMfj/tffMpz3qm1qYcKyb7/hfEExKT1tntrccFh5UybUa9QHKi9Wysd+C7FEvp1IDRNcrnqXR9dgueEGCBBvSAgAdrcOTAp2o4NY1DEMq/bH7hSTG06FWf0ABL/pI2EkBBp1ZmYwGAzGpSOk2EYp3RjN/7pYeUbwIPHfM3VVWvtJ+SeBAZMsMSN+ufBLxB0aeTeP/3H/J3D7E0DndcDt09C0X5EovkHqHGrVueqWly1H/7f7R7Scbw5/oyrvMXOBcHYuZPMCo4tv3s1j36l9uvFjeowJuX7ShdjWiVvRoUkH1bRdJ3bpvnNtKWe3FtrGxuHRrqm+JFRiRfkKQ9eT2fvZsS1VddK9Y1t8esrwbh4/nVe7ECWnm+G6KMtx/X9f3/tMzBlyO47vMBwfTmlMuDjSHWrRK4izlIKi2lsdlhB0c9ubQ87zWP/Hgk5/ZOUjhsJii8YtYCEWWIgl6uM1IQQzswEPES8iPQTA3MhLN8OmrEwMbgfExzJ1llCspbFKcnrmmOZAmjWekcjtkys7peasAb5ZDLy0DtiwFMi52EUn4BsdfySkfeWHkz/I4yho2N1R6zs/P9MWva5eAuKXI3yw4sPP9I6YTUPT0fyietzJDsEdhJHwROYTQYcbCo50h1x6HFU3cG0DCKez3nZebTA4HKhNEo+PNTa1s01JijVFNayNO9hxwvi3LBJkV7fyN8qbDLieNxXcTlefDnlzSplvCIg3KzJaZ8S8vgwGg8GIHw2iQQLDnFBB4r9HtJ1CJ6+cnDDRrX8HjYilyRLTnshp0XbsDEbhrkL4jtwCfPUacDAb+Goe+rXvJwp7fZ2AtcbUVbft2LawmyYY5YDoShAVSM0L+rXrhybX/qATHN/77j2V8Cl9Pxe96qu4Ls30F8SRQkHlsk6JvIF5SLIkAQCSLEl6N16Y5A0I/TzpswhWCgsAJ364XiUMnfjh+qjWSUvhrkLTu/a5fXKxaNQitLmiDVKt5uLevsp9CdtfUm3hiYo5PXPkTMRka7Jht1bp2Cfn+IVwllJQnePM6HW1Tkgj8rPzkTcwD+2btEevNvpgfwqKR1Y+ovoceTePaV9Nk0P3H+v/WFTH6zZXtkGJHRj6EPBMFvDnx9sk1u2zeHHwYcRWGquEs3MYfM1g44lhvPQNrW7Aw9vFPDsLxP8pPuChMn15q1lDhX7t+iG3Ty54N48PytTluaFyJhsKN7S6AdtGFYLaAr8ZQvp69c0fnsfA4sMARHcQ9f9fPqJ93NZDOiaFOl7Wd2I+D1M2gKipAaZOrbedVxsMHIevF+XhuVuBrHFAid14ts7NOqvOD7Tb4OFfD4ftyDZDzn1LdwEWL8Sbo1bxPC6Iw+0vX/0l6G+xI92BJGuSPLz71G4WJ8NgMBj1jIjFNkLIUELILELIm4SQN/x/D03EyjHCw7Dk4neMtrR2Ueki3QlIvJxvN7S6QTeue8vumHPrHGx5aAvG9xof9Pk13prIFqhx7+wrbYdFk8dj+ONFaP/YA2pXnSYbpPhwsWn+lRIjB4lZOaREbp9cbJ24Fa8Mf0UnOO4+tVtVxid9P1qeHhg8C8uIHq30ZWef7ftM9R45O4e/dPhfXPfDYvylw/9GvZ9wdg6tGhtnSq09tBa8mwfv5lF5sRKzHbODXji2uWGPShhqc8Me03nDhXfzWFi0S5cH06ttQAzK7ZOL408fR9V/V5mGxPuoTydYGi3LaP9xljox4r0RaJraVL6AUXL8/PGw9j2pXPilW1+Ca5zL9DuTGnUkW5PDcpZqS4I4O4ch1wxRjQvmYFSSn52Po08exR97/NFwOgXFjLUz5GFXhQtV3ipQUAhUwKv8q1Edf2YNngVAvHicOxi4/YG/RfwaEdGuXdDhM68X4LOltZiwPfYyUkBfWigRTlD5gjsXYILfiKL0x90o6Pdbs3Kr0uOl4N28oXBt1PCkIeJIdxjuLwWbC0RhgeeB2bMBqD/HnW2AlCGOuK5Lbp/coNEBDYWYzsOUDSAsFlF0q6edVxsSo8fnY35WU1OhDQD2ntqLN+94E3NunYOND240zGaN1ZGtL/f071Uh8n0vei+GPGfz+Dzy35E4uBkMBoNRN4SdZuwX1BYAkGqwpHMw6p++B8AUVkLKiAZJhHGkO2IWDaXS2mpvNaj/n5Rnx9k52VlV66tFsjU5JkegUVnRAzc9gJmDA500l+xcghqfgajmzsS5CgdGYDa+njk75LKapjYNuHd8FLB6cKbNp8jts0p0Yjh4DHh3gPzaWLZOFOastfLFlJR/Fez9GpWMhlPeCYgXTo9++ajs3pFQfgeOdAesFit8Pp88PeY8JHemeMKa7oJgL1G9x+lLilCQOxzwJaPg01pc26wMuaOjK7UY33u8sRBFRVfZsl3LwtqueverFr8T/zr37hdclA0F7+Yx4uXZwLK1uu98X6Vxudz797yP9k3bY/l3yyFQAcd/Oy5PkwRLo/U323+cpU5MWik2DFl9cLWqvEVi/5n9GLJ0CHyCD8nWZGwYtyEuNwnaNWknNh6RymFN2PmzXjSemzUXQ5cOhUfwiM7HMByMSoKVjH1z5Bv5c9QeK7yCVz4mRYIkSqwoX4ExPcYkXqTIywNWrhSbJNhs4rCE04mRrxQBAIb/CCRZCRzjHTEtzkxUO197PuRzOTuHyhuHAD8Vq8a36KQX5XP75GJF+QqsPrhaNd5HRcHQqKGHWcOThoZU/l+wuUC3v/x79iRM+JLAKlDZ0QaIXpypdwJ3abMSGbEjNYBwuYCzZ4FXXxXH18POqw0NgQrBp0NA5cVK+Zxttmu2bh6jZk6RsPy75eIfFQ5AsEH0OVAAvqD5vgBQ46tBweYCfPrnT3XTjKoQjBzcDAaDwbh0hOVsI4SMAbAGwPUAjgP4EEA+gAL/38cBdAewhhByT2JWlXG5Eu+OqspOoVKOijIfKZ6dIN8pfUc3Tnnxzdk5bBi3QS9gKYJyVz+Xh+lLikIu63+//1+dG6Fn30ApJmfnsGjUInHAKL/K73RbV3zR8PUlcnrmyK4kAoK8gXkRXdAbuf0AyN8BZ+dwR5c7VNOizXpqdUUrw9Bh6UKZd/P4x/J/qz6LxZ/+GPFyJPKz89HY1lg3XirlqPZWw0d9Ie8uV16shKXjNmDwXFg6botJaOTdPBzLHDi/72bF+0yW75YH604mubNW/HGFKitLoAIKthi725T7T7W3Wg6u1979V10EKFyWXsErNz5QOr+07ymSY8LMQTNVw0auOgCG3x1n57DxwY2ysyFS8Yuzc4FSVg3KzqTaEkQCEnW+WZ26gTgOKC4G5swRH5UlqytWgCBw5+2lMzfHLJ6alawvL1sOZ6lTdk+alXa1eH4uqNUqlz3WWoCyEcYdBWc7ZuvGSd2KjUS/UA7fhkR+dr5aEHdnwr5yBnJWZsIiiBIbAXCmUxs4+xIMfZhgZ6dGLBc2UXAc0KKFKLR5PAClwC23XOq1avA0SWkSdLr2OGzUEdnMbRsuB88cFP9QRR3UiPEfIfJ9gUATJi0nfjth2N20Lhu51FU+MoPBYDRUQjrbCCHtACwD4AXwGIB3KKU+zTwWABMAzANQSAgpoZSy/tN1RDxdYZcCo46qsb4Pzs6Bs3PI6Zmj+2xaNG4hCwEChKjvAvJuHqerT6vGpVhTdOvO2Tl88qdPAq4zQCOGUSz59BDyQ5ib5IwhhXtnbtYW1TzSxfck9xKVAw6NTslOt/0ba+EcENzdRQgBAUGSNclUSDBjyi1TZIeTksEdB8vOwpX7Vqqm/YX7S1Tf+ckLJ3WfJSocOF0lfi6uChdo+nrA+oz8WbTLMA9GD4f0tHSUn1J3/Bx53Ug0TW2qyq4KFqYuBWpL7rBYLmDlstxGpwBqBUDFx0anAITfnUxbMmcm0in3HwoK57dO9G7b2zQDy8xlCQDFR4rhLHXqRKNIjwlat9ePZ340dCAadW+Lx/FzZJeRKNqrF8yVF3Jad8RNbW5qOMdrjjPOhRszBlgtOsMIgGZjY++EpxIlFY5V2EswZ9McHP5VzBGTHGk6wZHj8P4bE3Hx3YVixlgvC+5sUQmjo52RoDz/zvny9+IsdapE43Advg2FtNQ08TfMv48e9SZjBGqxDlngUAIKoHnPTNz0eh5GVbjwSgM9x2gQ8Dzw6KOigxQQxbbiYmDYMGDDhnrZhbUh0L99f8Njs4S2g/jJCyf1Mxn3bAmbHq164Oj5o4GbpYpjmsQjfR5B09SmphEOk7+YjIzWGer97ygHLJuq+m1NSd9RZ4J4PKtEGAwG43IlHGfbNACNAYyllC7SCm0AQCkVKKVvAxjrn7dhtpRqgEiulmfWPwPHMkeDvLuUyI6qRjkqlRcr5RMsC7FEfRfQyLn0nz3+03Q9ZNcZoAtz93VcF3RZvJtHraDOOWtsa2x4YpPbJxdbnv8nhjz790AeT1VLlbvrtY/MHRquChd8gg8U0WUwmX2e/FFe9fpK0qIsTRrTY4xhML4k4jjSHbBds112A1ofHIG8P5kEsIeJUce8z/d9jpV71QJisDB1zs7hsf6PoVNap6iD8iVksbiqJcRiLyI+VrWUw95D4apw6bpAmol02u9XoAKmfjlVVYaqIkiXUEAUyLREc0xQur3MtqcPyj7QZTfGw1Vrts03Sgp0S+3RUl3KmNneOBS7QZGRIeZMAeJjRuyd8ORcNAPH6uFfD6ucHGZZSl1G5eDJ0Y3w2F1WfJtu3h1y76m9quFrrrpGtb/YrOL9yGgcvg2Bl7NfFv/w76MUNtQiCS44AjO1acNyYesClwsQDEoeWW5bTCgbJBkhlY1LGArqMfR9cZY6xRsD0nELUGXaWogFi0YtwoJRC5CfnY+rUq4yfB2BCrpzsTYn/6T6bSUVw/D6yNfrbD81uinGYDAYDDXhiG23A9hKKdUHBmiglBYB2ApgZKwrxgiPwl2FqPXVyplYoYLN6yN13VHVke5QlUlKYkWo8iQtWudS95bd8f4975vOn9snF1se2oK2V7bVlYN62hebPg+AXKqnpG+7vqbzc3YOG5+bCzI4X1yWRpAqv3K+6ft0pDtgs9hAQKIq7zRzCl7wXBDF4XSH7m5ytO7C3D656Nm3yjAYf0X5CpT9UiZmtthLYBlSgPmPPBDz9pXbJxfpaemqcT7qC5SK+NGKo0qcpU4UbC7AgTMHAqHkUTL/3/PFP9JdgM3/Hdtq0apHObZO3BrWazjSHapOocM7DzcVFoy+K4/ggU9/HwYAYOm0KWiXUKOLm1iPCY4QM2pgAAAgAElEQVR0BxrZGunGU1CVmyleFwuOdAesxKobf8FzQe4CHE6H1QYBzwMvvyw+FhaKQe6A+FioP05Fitwt2KwUXiHApR4fZvga4W4/3Vp2Uw0rnY+uCpecPUkIifqGQH0mt0+u2CjF//tggQfJ8MABFygAgQDIaaDbaUPD4RCbI2ix2VhuWwwoYwLMGhz9cPIH+e/cPrm6pjnhNGcxY0X5CvVxq3A9Hmm9DItGLcKcW+fgm/HfqH5r773x3sCTNSWi2nPOnNHXwJokyL+tNN2FFeUr6uymeyJvlDMYDMblQjhi2zUAtoScK8AWAOlRrQ0jYrSdI/+191917m5TXnvVN6avnY4ur3fB9LXT5WyJsl/K5IsoH/Xh8VWPY/ra6Zi0chJWH1yNSSsnhSV+aJ1LTZKDZ4MA4onfij/6nTyKrp3na89j+trpEWVfzM2eG3IeubOWQee5eSXzTJ+nLIeMFDOXj/LOrDa0OJaMkQV3LtB1QJWY8sUUeVkCFbDj+I6ol6Ok41UddeOqfdWq4WCdZrWOnGDfRShkd47qO87Gv/5qnIdmhOS0k1h9cLXpPqB0hgKiYK0VT5UkKZyFRvk0xYeNheZY3DSS2DKk4xDdNOU2EK+LBc7O4a5udxlO8wgeuQz2jZFv4LbOt+GNkW80TJcQzwNZWcCzz4qPJ/RNBGKFs3Po0KSDoWNVK8A1/8U8Ijac7SdvQMD1om2O0aJxC9Wx43INHX//nvcxZFAyMC4L7fs+hy8tWeiHEngJUDEnj5Uv1iXU4PeWxFjDyJCPBeN7G2d1bKxQ93XTduo2ih+ICOVxy2tD+fZWyO2Ta3h8yumZI7rMDZy92vgNjgOeWvil4reVx5qDa+KSfRwOdX2jnMFgMBoi4YhtSQDMLRp6PAD0t/gZCUEbvK91biQa7bVXNILb/Z/cjwF/exKz/nYOg/7+17idJNz/yf0q99CAdwfgmfXPYPLKySoXTq2vFp+Uf6J6rlFpmxatcymYk0kJZ+d0J3MA8MrmV0zL2bSh4WMzxoZ1YlN4d2GgPFAjSO0+tdtQUIm1jNSR7jDsRAmIF7Az1s7QiXjB8s1Cwdk59Lq6l278wTMHdW4row6D0aAtCTSiW4tuptPaNW2nGt5buTeq7d5Z6lSLfP7vuEvPUxGf+GrD3832ASlvzkqssFlsuKXdLUHfa42vJrDtAbow5+VlyxNyYcDZOdx+3e268Ud+PSIvL54XC3kD8nSluBJna86Cd/N4fNXjWHNwDR5f9XiDLPmHyyWWtfl8cFY/gBHbX4TT+ogoCCQnx80Fdd9N9wXE4z7vAL2WiRM0AlybG/bEtByz5hg8D6xwdpW305i7Jddz5mbNRXL6t3CPmotnxm/FB3/ugT2fLMK1M/Iv9ar9fnC5jMU2jycujlGG2BTEqKy0c7POqmHtTblob9LxblH80h63fmz6rulzODuHhaMWGjp7K85U6OZPu253oIIBkJsP1VVJJysxZzAYjOCEI7YdBwyzhc24AUD8b3czDDEqRQrWfTDeKK69oooWmb52OpZ/+aN8B09YuhrD5zwfU3cj3s3j7o/uxvKy5bppFFTXKt1CLLinh9ohEU4Q9onzJ4IOB8PIBSdAMC1n097R3HEivJM/zs5h80ObRaeIAfHKy9Iu8w/d/mA4rfJiJfac0l8gB8s3C4f0Zum6cZ2bddaV9sVSDqIkp2dOUDcXIIbmm5E3IE/3/GhOjme7ZhuOP1sduXipfY7Za3B2DvNun4c+bfvAJ/iw7dg27D61O/QCDO7USxiVSccDI+GXgqrK7eN1scDZOfx14F8Np7kOuVC4qxA1vhr5YihR7zmhOBxAcjKcJBeT6EKsPtoDk3zz4fyPleLBP04uqPzs/EAp185xQOlEcZsBVPmLOaO6xLws7fcv3UBa885geTsN1fCkocPZObjGuTDn1jl45fnNeODDH5Ax+vLKp6v3OBxASopYSqosJ6UUePvt+lk60ADJz87Hxgc3yucGVmLVVQlob8qVn1Q3RAqXgs0F4o1FTWXB2Ds7B31ebp9ctLlxr87ZW+PTu+Ud6Q5YLerzHKmjMoPBYDAuPeGIbcUAbiOEXB9qRkJIdwAj/M9h1AGcnQtk3PgJt/tgPPBfe8FqFR/DjRaRSjrf2PqG7g7eb/v7YNb6WVE1fODdPAYvGRy0+5SWP9/4Z/mO53XNrgs7CPuC54JquNpbbTJneBD/P6tFf6J0ofZC0OFgcHYOU26ZYjitV1u9Iywe4f1GopZ0AnhVqj4AuNYXiXnWAANDwLpD65DVKUs1TusQjBbOzqHdle2CzhPMCcPZOSy4cwGSLEmwEAtSrOYh7hLSPqPcJ36t/tVw3u4tuwd9LSMOnD6gGjYT0Hg3j2lfTcO2Y9vCLjNu36R90EYJRo5Do/cbKZyd07kWgMSV2+dn54vvVUOqLTVurspLCscB69ZhXssX/SMIAIJ5e++Ie7nh3Ky5IBXD9NuM3yU58T9uTIibQrqBRAWrajvVOj8vN5hD5RLj37fw4otArub8I055iAwRzs5h0/hNmHPrHGwavynkNl98pBjT106PeDlyh25FV2WLfRvys0M7Rpt33auLXxCooPvd4uwc3rrjLZV4+OYdb7L9mMFgMOoJ4Yhtb0IsJV1JCDGtnfILbZ9DLCF9Kz6rxwgHOZfrEiCdH77wgvgYzvUW7+YxbNkwzFo/C1XeKuNsHogCzJQvjEUiMwo2F5gGtZvx0fcfYfra6XiVfxUHzx7EG1vfCHkhzrt5nK89rxp309U3hb1MI0ci9f8zKkXr3aZ30OFQONIdhq97rvqcblw8wvvl3BEF1F8i0yy1mW7+cEtwI8FHfdj20zbVOG3H0Fg4U30m6PRQTpiM1hmY0HsCcm/ODVnCaNZ1eFDHQbp5CUhYeX5atA03pIYWWqSmApFwofaC6X5uRLy6hALArzV6QZKCys6ySBujhOKWdrfoRxKxY62SmHOALhUchyohWTGC4uz52G40GC7GziHt+l36bcadCWyaid7eyH4bwkW6gUQsPtV2Go7bmcGICY4DZs4Uy7GtmjSWlSsBZ3yOUYzg4rLRzcJozoXSUtN0ju62Z81zJpU80f8JXfQHBcWMtfos1ozWGbBZbBGtG4PBYDDqhpBiG6W0FMA/AHQG8C0h5ANCyARCyHBCyG3+vz8EsMM/zz8ppdsTu9oMJdpSwHDyxuKJdH4YrrFBKqeSMQjvl9j5806MeG9E2Osi30mMAB/1oeCjYng2PgXhSD9UeatClvT98f/+qBsXicDB2TnxRAzQdZzy+Dy65WtLEoOVKJotr2ebnrrxRuUR2vB+7XC4yzMqqXNVuAydly0btYx4GUrMykMvei+qhz0XDeeLFN7No8pTFXSeYE4YSUxyljrxzo53UPZLWdDXKthcoOo6LAlFjZMbq+Zre2VbbH5oc1R3tbXOOmVDi2DzAdBtw1rSUtMwfGhT0/284tcK1fzx6hIKAN1bmbv8nKXOiBujhMJoW9xfuV93E2DVgVUxL+uS4HQirfJH1ajj3t0JcQpm9PlNvc0A/gvXv+Pxe3skpLKO44B5H5Qhvc/zeKBXFjJRErQ7L4MRdzgOmD9fLbgdPQpMmsQEtzrALCZi6pdTcf8n94ftuC4/Wa5zdN+V/EpY65DbJ1dXtQKILjvt75SrwgWPzwNAPJ+d+uXUhpkJymAwGJch4TjbQCmdDmC2f/4/A3ACWAXgK//ff4LoaHsBgP7XgZFQtHfc6/sd+JKfFN0IpYt0wDRAPVhnRC2OTo7IV8ggS0rZCt4IrahHQCIWONLT0k1zrLSChrIkMdqw7lMXTunGFR8p1p2UpSalBh0Ol9HdRqsy05KsSXCkO5DbJzeQx+SnR6vQDQeCYeQUBIDGNrUY1auNvmw2GlwVLpAQXeKC7YeuChdqvDUQIMAreDH5i8nyNq4tn+TdvM4VJaENbk62JkddPmLUbdGsA6NKODLYhrUZgTMHz8TXD3yNsXdciyZZb+k6kv507ifVcLy6hAJiOaIR5afKdUJyPG5UGDnWjv92XDeuLrM148qKFUjW9kyyJiaQe272XLW7Q3HhWlNLI84IDZfU4/NR/u1LWLK9BBuWAuc2hv8bxGDEhdxcYNMmoL2mLH1x5De/GJHB2Tnce+O96pHuTHg2PoXlX/6IWetnYejSoSEFrc7NOqsc3cTmQ87oa8JeD1V2pYLXSl5TDTvSHbAocv58NPLGVgwGg8FIDGGJbQBAKf07gC4QBbUNAPYA2AvA5R/XlVL6PKVG7ZQYiUYKAQ8V2p4IIslW4t08dp7wO360F+nbHzYNUP/LV38Ja13SUtIifwMGWVIfff8R7v74btP31LZJW9VwuybB87uMyGyfqVl2MlDh0DVwAKAS/6IN677vpvsMx4cKam+e2jziZQHqwH8CgvG9xstC0NysuUixpoCAIMWaYiqWhQtn5wwFu7ZN2sr7RpIlyfBOcTRIYpAZzVObB3XCaE+OBSpg6pdT4Sx16sonXRUuKA+rVmKVP68rkq5Qva52OBIqL1bqSn+NRF3dSbzB/tO3XV8sGrUIwzsPx6JRi+TP4v173se5mefQpbk62L59U/UFZdkvZchonYG7ut0Vc5dQwPi4WHy4GKXHS1Xj4nGjIlwhvC6zNePKmDHogn3+Af922XyfqTAbC5ydQ+srWgdGaEqRw80IjZQ+68qR4hPvIKb4gJxdde8YZzDAccAtmrL0dpGfazAiZ3/l/sCAwQ0lj+DBuE/HocvrXUzz3MbeNFZVufHXRV/FJdpSmRcsnSM8yT0JK7GCgMBmsbEGCQwGg1FPiEiZoZQe9gtq2ZTSGyilPSilWf5xhxK1kgxzeDePR798VBZopIv2urKQR5qtlPOpQlTRXqTvHmMaoH7RexH93+4fcn3MLvi0HQlVGGRJ+agPRXuKTO9ejr1pbNDhcMjpmQM0qgSoFQAVHxuJ7jOlAMa7eXz4/Yeq50YT1p2fnY9rrgp+V5V38/jm8DeqcdF28FS6k1JtqSpBjbNz2DBuA1669SVsGLchLmG+T/R/Qjdu96ndECDEPTRY6sj5/9m78/i2yjPv/59Lsp2FJEBCIAEcDGUNBAJOIQdKInDK3v5SmF83qENgMEuZgW4B2jKlhRKSbmHaAnHLFMIyTzsN7Qw8ZSkGkZAoUAJk0oYdHNyGhKxAyGJbup8/jmRrsy3bkm3J3/frpZd8jo7OuWUf29J1rvu6OpLtanT687/ufT1lXWuslR8t+xG7o7tTpk+GqkIMKRtCgABlgTLuOPeOttdx3hHnpezjmqmZ34NcZavrly3DMyPQm+X3Z9yIcdRV1/H4Vx7PGnQ8euzRKcsbtm9o+z1LTO18ft3z/PHVP3Y5xbYr4cYwMZcZwAY/A2DyfpO71RilKx3VRxw9dDRH7XMUE8dOTAlAFqONJAJg/uvcc8t+Pcq2zcXFky9uX0j64Dp5zjfy3ZOhze4szW4Gesa4lKg5c6C83P+6vNxfloJLqUvaQXOfN7a+0Vbb9ronr8u48NyWeR7Pzv1w7OPdHseulsy/Reu3r6d+ZX3K+++fLP8JMRfrsO5voeSjkZGISCnrMthmZkPM7HkzazCz8k62q4hvs6Kz7SS/wo1horHUWkCtsdY+SyFPTIeLuii7WzufShRpivDm1qSOh+kf0o9anL2Aenyq6fPPBbr8h54+rS7hUwdlFpJv00nNuJZYS9bMr9/97Xcpyz0JfnmVHjMP+mcgiv+hNQo7M2uXZQsW9PSD39mHZtZ6S64dtWjVopTMugCBHmedeZUeDbUN3HzazVmzk/Ld/a6uuq7DwGDURTs8N3qqs+BCLhl06VmYDsdbW98i5mIELNA2fTLxfbzl9FtYcvGStiBNpCnSNp3EsF4Hi7xKLyND86FXHsqsD/NOOPWJab8/wQl/6fY589729zj1N6cSaYrkvQZlR8GvhJc3vMybW99kwYoFefnA4FV6WbvBbt21ldc3v847W99h0r6Ten2c/rL1gbu5gMTPxM9su+W933Pe5vxntoF/kSDl9zr+wfXKz+VnSng25RdfSnMAYkBzAB6YHCjqn5kUqUjEb4/7i1/ArbfCM8/kveuvZLfh4w3tC50194m/P/3pbyN86qv38u3ZJzDtX+4j0hTJ6EDdk47UbbV9k+yO7ubyRy5n/vL5bbVNoy7a1h08W93fQshnIyMRkVKVS2bbhUA18BPnXEtHGznnmvEbKZwYf470gVBVKGOKlMMVZEpPNmOGj2nPqiPW6XGvb7g+tZB6epBryq8zg15p6fuzfn5Xp+PJVvB/zilzuK3mts6v9qV1fUpW/2J9ypuI6568jsZtjSnb9DT4Ne7oV6Es/iaurLntTdyooaPatkn/nl446cK8ZsWs/WBtWxOK9O/fsfsd26tgWL4Dal2ZemD2Av2F0Nm5/sfX/tjl87NNBU68Wd5/xP4sOGtB2/ct2/cxudGIw2XtLNtd6VONd7buzGgckHXKdPz3JzjhLymZdx3JFhSNuiiLVi3Kew3Kjpp1pEtuPNFb2TIMHc6/KBEtTH2zvhI5cX+O4a+U0Qw4AkSpiBmTXilMZhtAzcE1GesKlUkHsOUvSwjEZ8g68zspF/PPTIpQJAKnnQbf+Q5cfTW8+25/j2hQScko6+iCbNL709b/+DOxh++Et86g9b9/yfx/35rxf64nswSyvadNWPfhuuzlLKyDRkZ51p2L7SIig1Uuwbbzgbedc3/qakPn3GPAG8D/39uBSW68So9J+2VecS/kB5H04ySCfQELdHrc5ctdZk22+Id0q3yO8kB5ZtArLX3/jRf377Q76aYdqU0Axu0xjnkz5uFVeiy7ZBnTJkxjaLB7Bf/TuzI+tOahlMf3Gb5Pj4NftecdRsUl52S8iUvOlNu8Y3N7TT4CGVPwunW8DjKOnnj7Ca578jp2pU2f6qwu2UA05+Q5KU0Zkr343ot5PVZn53r6OZJNRoZYkr9/9HeueOSKlFowydM1Ik2RjG6WPblqnm7mETMpC5RlrE/OLptzSur32DBmHjGTK6qvYOnspTn9LtQeV5t1anfDOw289N5LbY8FLZiXjKKZR8zMabs1mzr+YNMdddV1nHHIGVkfi7nOL0rkRSQCc+dSiHade//rHL521OlECQIBYgS5ml8Q2dZx19feSqmfFNeTupU5iUQ4ed6DlDn/DVJ5FKY39s2HV5E2ixbB7t3gHLS0wMKFUFNTkN9pyZTtfXWG5PenscSEHv+i7suPVlN7XC0VwQoMoyJY0aNZAoeMPqTDx0IHh2iobWDahNSyFTMOntEnFzi7c7FdRGSwyiXYdjx+E4RcLQEKN79DMqTUlojrq396oaoQQ4JDCFqQIcEhHX4gqV9ZT+vbp2Ste3HgyANZdskynrn4GW49/VYWnrew/c1DIn2fVjAHwza1BYayqShLDQ4dPubwtq+9So9nZj/DU7OeYljZMAIECFqQyeMmc+L+J3Z61TH5g91JB6bWjjvzEx0H/7riVXqEvzuXaRcuT8mqmzy+/VcoVBWiPFiOYW0dPXtzvLHDx2Z97MfLfpwxZeGwMYdl3XagWv3+6tROmUmeX/d8XjsKZssqTTh/4vldPr+rphoOx/xl86lfWU/9ynqm3zOd7z79XUL3hph+z3TWfrA2Zft3tvW+bGa4MUwsllnfLDm7zKv0uOyEy9oyRQMW4MQDTuTO8+7M+Q2+V+nxqQmZU7vf2PIGd628q+0NfCLbrbdy3Ue2+jg9dVPopg6zafM9pTlFJOJ/KL/xxoJ9OH/pU89iFsOfRmpECRB+uQfNaXK0/6jM35WeTN3PSThMMOow/FcXAGaM+WSfZeeKZOUcNDdTsBa8kuK2GUmzITroGk9VGAKtJP4OJtuF/57xksmXcHn15YRnhXv0N6SjbtoAH+76EK/S46xDz0pZ3/BOQ59M6Xxg9QOdLouISG7Btn2ADV1u1W4DoMsbfejw0YdnrOurzLau6nIlLF6zOGvdi2kTptH09Sa8Sq9tqlxddR1nHXqW/0ancgWcdQ0EYuAC8Njt0DSV37z0m4xjRJoirN6QWkw9W4fK5BpYS2cv5aXLX+K5y57LnKqUNOU1OQspuRNUtuXuytZJM31KYGusFYejNdbaq2MBHDU2ewZKjBhL1i5JWZcto2Qg66q+Vz47CnqVHt88+ZtZH8slk+rswzLr52Uz99m5fPVPX6Ul1kLMxWiJttASy5zRv+6jdTntrzOhqhBmnRdXTryJTzS/SNSW6653Pxx406JCB4fytq9Fqxa1TQvuU+GwnxETjfr3ef5wHm4MEz3wWQ46+auU0UKAVobQTOVpBco0I63WZPzv8titny3MwUIhAmYpH59P31a4QKJIVrW1UJF08TAQ8JcL1YJXUiRmQ1TtWdVhgwQqV8Dxv8Gv7pj6f3PouHeoWVTDr178FfeuurdX45h5ZPb3E+s/9rPZ0xsZ5esiVVf+d/3/drosIiK5Bdt2AiO6sc8RQP7SA6RL6dO6ygO9y37qrpzrcmWpe3HbjOxX7UJVIYaWxad77tzHD7QlvdH5uDkzwBVuDHPiu1GuXwpTm/wpaB2l7Wcb88aPN7ZvkHYl8/nngm1BhvSMinxkWHRWSPf6huvbsrWiLurXvuuFzq6U7oqm/uq2/QyKRHJGYDb57ig4b8a8jGYIAQvkVLsk1+ymbTu3pWSbGeZPuU6TrZByd3mVHqdMOCVj/d0v3g34gbbT7j2Nu1bexe7obk6ZcEqnQfbOOJdbIOr48cd3e9/pao+r7TALMVl604q8SK5TGZeP19ShMWMgcb7EYv5yPnc/fAwxF+OdT/+aI86bzqmfuJFDPzODplNeyetxkm3esdm/+JL0d/l3c+oKN6PO2nMSDeACdSKVPuZ5fqD81lv9KaS33AINDWqQ0Ie8So8HL3iQwMFLO26QcNwiKNsNJC6E+v/XJhy5qa2zeG/rdM45OXvDpS07tgBk3feStUsKnt2217DU/5dDy4vr/aKISF/IJdjWBHyyG/ucAgy8lIUS5lV63HHuHVlrIA0EkaYIf377z/5CUk22OafM6fBDeiL77IrqK7JOJd3RuiNlSmCkKcIHTz/GD++ZyoiG67n1nqncvtcXuxUESAnEZFzJnM78ZfMB2LwzNWtwWPmwnI+Rqy07t7R9/crG1A+x6cvd5VV6GTU+OvLh7t4X3e9LnQVLxu0xLq+NJRJmHjEz/8HupADNB7s/IBho338wEOQX5/wi47XuPXTv3h0T//fo2bXPZqxPTONLbsoA/hv61e+vztg+FwfteVBO2+VjyqVX6XHnuXd2WM8vIZ8XKWqPq4UmL+v0o/R6e3m1ebOfBQP+/eb8Zjkn15D825QVPPOV21hdHSlo6YLEVPrkv8vR1rLCzKhbtKg9WAkwbRrU5f/vhkiXPA9uuME//264QYG2fuBVetx5RW2HHevbLiJ/4knaMtwsymgOb+si39s6nV6lx7SDMt+zbdyxkUhTJOvFtzWb1nDavacVNOD2+aM/n7K8accmdSQVEUmTS3QmDEw1syldbWhm1cDJwNO9HJd000vvvdRW56gl1tInKeS5CjeGM6ZTjSgfwbwZ8zp9nlfpced5d7Lwytn+VFJzEAvCoz+HpqltXRIjTRGm3zOddQ83c260ge9xM+dGG/josSHdGmdddR0Lz1vIGYecwQGT3sy4krnuo3Vc9NBFfNT8UcrzKkdVdus42aTXi1v67tK2Ny1H7ZM67TN9uSeyTa/NJr3hxEAXqgp1WCerUFl6i1YtSqkTd/ahZ+cU5K09rjZ78Cctq9I1ncTx49ozoVpjrbz03ksZ52E+pkBe33B929+RZInahw+//nDGYz2dmjt62OictuusG1t31FXXsXT2Uk7c/8Ssj59xyBn5r8vVwfSjdR/2fspvh0IhGDIEgkH/Ps/TzkJVIYaU+X9bpzbRlklcyDp0XqVHeFaYmWftTbA8RiDoGFJhfTOjbmJufytFpDTVVdf570PTOta31b+tXAGh7/vvFYkSLCM1+43e/328rea2jPc2Y/cYS82iGt79IHt+Q3O0uaAdQtMv+EVjUXUkFRFJk0uw7Rf4edH/ZWYdfso3syOB/wKiwB35GZ6UgmzZIsnZMV2pq65j5p4/8D+wEoToEFjlTw9dvGYx85fNpyXWQpgQzVQQpYxmynngg0O7Pda66joe/8rjjD3izYwrmYeNOYxH38jMSHl769vdPk662uNqU95IORz//D//TKQpwtTKqSmZTlMrp3ayp9zkOo3ty8d+udfH6ktepceXJ2Uf8+RxfdO3pbNGG8m8So+a8u9mTDHMFqBJDqw5HGs2rWm7ap6QjymQb215K+v6Hy//Mdc9eR3/+OgfGY/1dGpuh9+ntGmX+azt5lV6LDhrQdaA7CF7d9z1rSfCjWGoejrr9KN8TPntkOf5081uvrkg084SWceX7DyKhnvh5qeg4V44+NXed8Pt6rh/+OYcloYruOVmK9yMutpaP0hp5t/Xdr+DoIiUlrrquoySEbecfgsLz1uYuqEZZYGyjDpqK/6xgt7wKj3uOu+u9sNgjB42muZoc9YLZP5QrKAlZUJVoZSO9T2t3yoiUsq6DLY5514DfgAcBLxkZveb2SVmdoaZfdrMZpvZ/cBLQBXw/fhzCsbMvm1mzsx+kbTOzOwmM1tnZjvNLGxmR6c9b28zu8/MPojf7jOzkqh8XHtcbVsqeXmgvEctxgvlj6/9MWNd1Z5V3drHuJHjO3zsuX88B8DkIWEqaCZICxW0MHTfJ7p1jGSbdmxKmfIK8Oy7z7LfiP0yts2l82RXvEqP/fZI3feaTWuYfs90Fj3yRkqm08NP9j7bLJerrMOCw7rMPhyIUmrvJUl/o5wvtcfVMiQ4BMMYEhyS8+9eJAJPfu/67B3O0gI0r2xKnTq88eONKdmi+arTeOGxF2ZdH3Mx7vHaMxEAACAASURBVHn5noz1IytG9nhqbtbMvixd34aV5XeadmcB2XwKVYUITvhL1ulH+QjQdyox/axA0868So9/c9OpiEKZg/IofGFjbkHmXh+7sC/N3/HTT8MPf+jfa+qeiODXaE3Mflh43kLqquuoq65j+SXLOSM4lwBDwAVobYV1/5vayf0fH2ZeqOoNh+Ph1x6mLFBG0IJZa5KOqhiV12OmS2QcT5swjQNHHsg1U69R12YRkTQ5Fflyzv0A+C5+reAvA78CHgUeA34dXxcAvuOcu6UwQ/WZ2VTgMiC97c0c4BvAv+DXmHsf+LOZjUza5kHgBOBs4Kz41/cVcrx9KWABDMupEHhfevB/H8xYd+/nutedqbYWKGsGohDc7RelBV5c/yKtsVamNsHvIyt4khpu5t94ghq+ucfWHo85W0bX2g/W8t7291LW5TIdNlfZ6qO1xFpY/9cjUjKdbG0oL8fryicP7E6pxoEjW6bVtIOmFexNoFfp8fSsp/nh6T/k6VlP53yccBhi0fLsHc5m1UD1r2Fy9t+T5KvJAOcedm5eXt+8GfM6zJDbvnt7xrpPjP5Ej4+VqDWZUm8mS1bftVOv7fExOnL02JTrMJ02U+kpr9LjM4d/JiNoD/kJ0Pe3g2bWYkOGEA0YgSFDOGjmwLnA01sRPOZyAxH0wVFE2iVmPyRfZPIqPW66OMSQCiMY9JvG7j8ptZP7ASMP6PWxE42KEqIuytmHnk3NwTV86ZgvZWy/bfc2ahbVFLSO2ur3V7Pk3SX8/aO/M3/Z/JRayiIikmOwDcA5dytwOHAzfk22V4HX4l//ADjcOTe3EINMMLM9gQeAS4GtSesNuBa4zTm32Dn3V2AWMBI/EEh8CuxZQJ1zbrlzLgJcDpxnZkcUctx9IdwYpiXagsPREm0ZUHUT0uu1HTjywG4HBjwP5tQ/CjXfhYtPa/vgunnHZo4fdzyhRgjE4GRWcD23cQor+MK0q3o85nkz5jG8bHjG+m27tqUsHzqm+1NVO9ISa8n+QFqm0zVf6P10yA7rhSWZemDvp6v2h8R0j8RUwfJAeacdWPMh5468SUIhKC8DiEIgSvDgZ5lzypz2Ricvz4KVl6VmvcVt2L4hb2NPt+fQPbOu39G6I2Pd7tbcp4NnU1ddxzMXP9NeRy3tXB87cU1BmlqEqkIMKxtGgABlgTLuOPeOggRjs02V3WvIXkWZMZrB8wg+9TTBW35I8KnSyQCLRKCmBm680b8vWMdTESkZngcLFvh/MxYsgJppqe8f8/F+av+R+6csG8ajbz5KwzsN/PZvv836nELXbUsPAKYvi4gMdt1KgXLOrXXOfc85N8M5d7RzbmL865ucc2sLNcgk9cDvnXNPpa0/GBgHtM0bdM7tBJbgN2wA8IDtwPKk5y0DPk7apmiNGT6mrW5DjN51PsqnSFOEdR+lFgNPf8OQq3mzZ3LcPz2akiHicLy++XXCVRAL+MUFDb9WRW+78F190tVdbjP1gPwFpE6rOi37A4lMp9P/jWk3/oC6mZN6fSyv0mPp7KXMPGJmh11sX37v5V4fp7/MmzGPZZcs49bTb+WZi58ZsFMbAhbELEAwHvCZN2Mez17yLBVNZ2YtrJ+w/uPU+ljJ3Wt7a4/yPXLe9ogxvb9OkaijBqSc68yq4YIzeva3IpdjNtQ2cMvpt7Dk4iUFCegBWbPlEs0mSkLB53T2vXAYmpshGvXvC9LxVERKSiQC117rl8m89lp4e3VqWZBRQ3s/pXPOKXP8TPB4XdN9Nn+G5mgzURclFotlXEANWKDgddSGlg/tdFlEZLAbWPMNO2FmlwGHAjdmeTiRPpCe7rEh6bFxwEbnXFuaVfzr95O2KVrpNbgK2RmufmU9Z953Zlu6eKQpwtylc7OmqmfrRNqb4uDegZkf6ho/aGRFJXz1HGgJQNSAoUN73YWvo+y2ZLk2GsjFTaGbOn4wPhWt8pi/5+14XqXHnFPmdFhcd/L4vmkoUCg9yTbrS+EwtLaCcwaxMja/4gdRvUqPa784ObVu27BNmY0Ukryx5Y2s63vimqnX5LxtvurgeZUeM4+Y6S/Ez/XAhOcLWnuyr86P9GB2PrrGSuGEQv40sMR0sD7peCoiRS05SL+72fFEQ3PK4/m4eOlVepxW9u22uqYb7/xPXNNJAJQHy/nGyd8gaEEMI2hBpoyfwoKzFhT0f9zooaM7XRYRGezK+nsAuYhP87wVONU519zJpi5t2dLWpT+ebZvEMeuAOoAJEyZ0a7z9Yf329Z0u50v9ynouf+RyAJ54+wmWrF3CQ688RHO0mYpgBQ21DSn/2LNl2PWmOHhnVwd/PQX+uh9c13IiM69YkJdsixFDRvjT55qm+tlFVeGUzLrNO3qXPZcs3BjGsIzgZLI/v/3nvB0vccyO5KO7pXQs8aG+uTnzQ/282TOBPzL/gef8QNtjt/uZbsHmlEL7CTtbduZtXHXVdSxes5gn3u68wUjVXlV5fRM/55Q5/OnNP9EcbSZowYJN7exLWS826PeqVyIR/4NtKFSYhLpEM9dCHkNESkvy/3O/sdHTKY/n6+Lls0vKkrLeHTSGsMrnmD15NnsN2YuYi+FwRF2U59c9z4vrXwQoWPZ24weNKcvpXVhFRAa7Ysls84B9gL+aWauZtQLTgaviXyciHukZavvSnu22Htg3Xt8NaKv1NpbMjDicc/XOuSnOuSljx47N76spYnMfDKdk2Dyw+gF2te4i6qLsbt2dEbzJFozqTXHwrq4OPj8hwH635CfQBvGuqVk6JCbkMz0/VBXqsrlFtiL1vT1merF9yF93S+lY4kP9zTf79+mn7LzZMzn0s7+Hnft0OqUU4Nhxx+Z1bI9/5XHGj+i4AzDADZ+6Ia/HTHQ2u/X0W1k6e2nBPhz0pTHDxxSka+xg1Vf11EpwdqyIFFDi//lll0HlqemVbvJ3kSV4yNKMbuUVwQpqj6tl2+5t7f9v4lNNW9dO4eo/XV2wJgnrPkwtE/PGljeyHivSFOHKR67kykeuLGjDBhGRgaYoMtuAPwIvpK37DfAGfsbb6/jBtE8DfwEws6HAqcC34ttHgBH4gbtE3TYP2IPUOm5FKb0Qd7bC3L1V/8fVNP77rzMybBL/3LPVitu2O7WhwIn7n9ir4uAXTLyg04ybY/c7Nq/ZMFt2boHGf8q4kkjlirx3uPQqParHV/P8uuc73CYpVpy3Y4ZnhVm0ahFrNq5h446NHLHPEcw5eU7RZxUVA8/r/AP96GGj25sGRF3bm+t0hWgAsd+I/TK67yYctvdhBQmGeZVeSZ13m3dsJkCAGDEM49LjLy2p19fXstVTG9ABsUKn4YnIgHLvvbBr96chMK3tPXLQgnm7yLLHIf/LR7NqUmZaHLXPZL/8xGPxzt2JC8Tx9+ots2oIN4YL8r/nyH2O5P13309Zt2jVopRjRZoinPwf7aWx61fW8+wlz+p/oYgMCkURbHPObQNSojZm9jGwJd55FDNbAHzHzF7FD759F78hwoPxfbxiZo8BC+P13wxYCDzinHutz15MgaTXDstHMdZkkaYI1/16KUS/nhF0SghYICOT7dcrf52y/OaWN3s1jrrqOr722NeydkYE2LZzW9b1PXXSgSfxZpZgh2EFCXBcesKlqcG2tOmrM4+cmfdjllqAo5T458Pl/pv2LNOYAYYGhxbk51cRSMt4TDoXxx+UmQ0pmUJVIYaUDWmbZl/IGnSDQWdTrwecRBpeYrDZ0ldFpGQkLga4WBBcedt75C8e88W8/Y8ePXQ06ytXpLwPeHnDy0SaIu3NCRpDGReICzW987YZt6UE0gDWbFyTsjzrD7NSlmPEuOpPV/HS5YWrLS0iMlAUyzTSXMwHfgr8Ej8LbjxwhnPuo6RtLgRW4XctfTz+9Vf6eJwFsXnHZoz2rKefRX6Wt1Tt6568jpP/42S2jftDRvp6MsMyM9t2bet0uSeyTXtM2LwzfzXUAI4ee3R7h8TqX8PkewH41infKkiAo666joXnLWRocGjG9NXg3z/F/effn/djysCVOB9OPCnGmDN+lRFoA7qcetxTl55waftC2rn4+ssDo9vxQJfoenrzaTdn1LOU7utq6vWAoramIoNKKOQ3VsGiEIi2vUde1rQsb8foqIFRuDHMxH0m+gtVYQi0Au3j+M+//mdBpm96lV77ceN2te5KWU6v6wawav2qvI9FRGQgKtpgm3Mu5Jy7OmnZOeducs6Nd84Ndc5NT2S9JW2zxTl3kXNuVPx2UTxrruiFqkIEA+1tv1tiLZ0Wv89V/cp65i+b7y8kgk6n/1vWIu1RF+Xax65N+YdeHixP2aY3nUgTqvaq6vCxaCza6/0nS6mj9vIsWHkZtuhpZu7R86mwXamrruP2s29PuzpZzhEfFX8NK+m+uuo6nrvsOR7+0sNZH//cUZ8r2HEXnreQEeUjMs7F2NunFuSYpWigd8UtNkVTT01tTUUGHTPApZb72N6cv1q7ddV1DAkOyVi/bfe2TjOnnXN5+UyQTfrMmsPGHJayXGaZk6gcjvqV9QUZj4jIQFK0wTZJ5VV6fOHoL6Ssy0fa+O3P3Z66onIFnHpb1gwb8K9oJf6hX/fkdeyO7k55fO6Mub0e09QDp3b4WL4DD16lx53n3ok1ntYWbLDYkIInKdRV13HhZw9MySS85ov56WYlxcmr9Fh+yXIm7zeZoAWpCFZw4aQLC5rtWFddR+WHn4cPJvhXyuPn4sWfO7hgxxQpCUWVhicivRUOQ2srQABiwbZmRieMOyGvx8mW3fa7v/4Or9KjPBCfvhorA4Ip4yhUc56NH29MWX7u78+1XXSPNEXYGc3eLX3xmsUFGY+IyEBSFDXbJDdvbH4jZfnB1Q/y1U9+tccZFZGmCGteHAWN12etFZWNw7VNJX1ozUMpj+0zfJ+8FFWvPa6WhSsXpnT5A7/5QiECD3XVdXD1aq5+1hFtdQypsD5JUrj/X7/KtAmrWfzoZi44ewx1MycV/qAyoHmVHi9d0Xd1TiIReP1nd0BL0A+2Vf+ao2peYN7su/tsDCJFq6sOKCJSMhLJrDt3t0IgezOjfJg3Yx4/Wf4Toq59JseGjzcAsP/I/Vmbpc6ww7H6/dV5z7CONEX8aaNJNV3f4jlqFtXQUNvAolWLOnzuBRMvyOtYREQGIgXbSkhztDll2eEyugJ1x/W/+e+UjkbZpo4C/j/ZVfH09eMW8dJ7fjDg/Innt09BBS45/pIejSOdV+mx7JJlXPV/r+KVTa+w97C9+X7o+wXpjphQN3MSk57u+8ZydTMnUZf/nggiOQmHIdoS9KePxhzs+S4jP/HXLp8nIiIymHgeLFgAc+vfonH8j9veLxciqDS8fDgfNbeXpC4L+B/nygPl7SVf0poqfe2xr+X1fXKkKULNohp2vjMZ7nkaouUQbMFdfBq7K58n3Bgm8vfUOnFBC1I9vppLT7i0oO/ZRUQGCgXbSsjWXVsz1q3fvr5H+6pfWc+SJZbR0Sg52HbhpAt54E9vxf/JxmtIvDSbepvBA6szu6F+Yu9P9Ggs2fR1hg8oSUEGn1AIAuWtxFrar5DvP3L//h6WiIjIgBKJwL9eE2X37k9A8HbY72/M+eKpBQkqHT/+eJasXZKyDEkXudM6lgLsaN3BdU9ex7wZ+ak5HG4M+xf5V30l/hnAIBqAVbXEKlcwZvgY3v3g3ZTnjBoyiucuey4vxxcRKQaq2VZC9qjYIy/7iTRF+OqfvupfEcvSfTRgARaet5D7z7+ffTd+3r+ahfm3aDmxd07lo+aPUq66geoziBSdAyMEZp3R1hQlOOEvzDllTn+PSkREZEAJh2H3bvwL1K0V0Did1ze9XpBj3VZzW1s2W1mgjNtqbgP8KaZnHHKGP+Nk6fX+fZI7n78zb2MIVYWoCFZ0+Pijbz6a0cwhW3MHEZFSpmBbCTnv8PMy1o0bMa7b+wk3hmmNtWbtPjrzyJk8O/vZtit1F8882A/E4fxboNUvpt6U2cRg8vjiLvAficDcuf69yGAQbgwTO2BZp01RREREBrsxYwAXwH8/HIRdo3h9c2GCbV6lx5KLl3Dr6bey5OIlKeVibjr0ccrufwaeutkvBZP0fvyjlo+47snr8jaGhtoGpn1mLQR3A1H//ji/TtsTbz7B4fscnvKcqZUdNzgTESlFmkZaQj7c9WHGuvSW3LlI6WKalIo+snwkf/jCH1K2nTd7Jg+/dimvNEyB7fvBG+fAysvg5VkZNd6yja9YRCJQUwPNzX4BXDWXk8EgVBUiEAgQi8UAvw5kuDGc9yLLIrmKRPq+dqaISFdeemstcAD+RysHkW9QEWoq2PG8Si/r/+JwGFxrhR/zy1ICZv6y+cw8Ymav/4/Xr6zn7hfvZv8j9scursE1TkupEbejdQdL1y5Nec7hYw7PsicRkdKlYFuJSzQryFWkKcIDqx/I+tjo4aOzrl9z293Y981PWX/tsx3WeFuzaU23xjKQhMN+oC0a9e/DYX3Qk9LnVXr88pxfcvWfribqogwJDiFUFervYckglXHRY8FqvM2P5D3yFmmKEG4ME6oKKbAsIjlZP/a3ELjWbyaEgQuw4a9H9fk4El1Rdzc7Ypa9K2pvL5pVLahi7Qdr/YV1QCVQuTxjO4dLWX75vZd7fEwRkWKkaaQlpPa4WgxLWdfdBglX/emqDh/79qnf7vCxURWjUmu8BaIZ00k3fryxW2MZSMaMgUDAv1VU+G9mRAaDSc11nPvaWqas/AsLjn5OwYdiVCJz4FMueuyKEr7qd3DjjX4ELk+vLdFh78anb6RmUQ2RpuL+nolI39gy5v/COV+FQAtYKwSbaZ3wZJ+Pw/P82Re33GyceMO3s5aA+PHyH3e5n0hThLlL57b9DYw0RbjykSvZ90f7tgfakowZOqbLfRaiM6uIyECmzLYS4lV6HLvfsazasKpt3ZZdW3J+/nVPXsfL67NfdTpqn6M67aj0ozN+xOWPXO5PHV1VCy/NzphOOnb42NxfzAASicC11/of8AIBv7W7stpkMIhE/MByc/N4YDyrHodJT+v8LyolNAc+FIKKsijN0RgVroVQ9Ekgv+nGiQ57URelOdqsadMikpNNOzbBlCWw31/9mR1VYY7/5Kh+GYvnAQdGCIdfgbfTHmyaypbGEFXvf4nLZx6bNYM3cdFhZ+tOaJqKNZ6Oq3qq09qtt8641f8c0IGuPkeIiJQiBdtKTHqnn10tu3J6XqQpwo+W/SjrY2OHj2XNVzufApr4B3r3i3fz1oYdbI6VZUwnnTh2Yk5jGWgS2RSxGJjB5s39PSKRvhEOQ0tL+7KmUBehEpoD73nQMPsBwgtfI+SewmOF/0c5j+nGiQ57zdFmKoIVmjYtIjmpKIt35kyqdQxn9MtYEsGy3a27Ux9omuo3TYhWsPaZZr79wQwqqm7inEPPYdyIcRw//nju/MudrNqwyp8CGt/eRSsg+B3/4jm0BRMTr7MiWEFddR1ff/zrfNzycdYxnTD+hMK9YBGRAUrBthJz6QmX8vy651OWcxFuDGfUVkj47y/+d077qKuuo666jsgxcPLjO6DV+Z1K4/Uiao+rzWk/A02i/kUiMURTSGWwCIWgvNw/9wHKynT+F50S+wPm1R6Gd+8V/usJVsAll0Btbd4CiIkOe6rZJiLdURGoyFjXX9MmExm6MWIECDC8fDjbW7b7QbJoRdLF8Ok04/hj+Mh48Oyu1B2lb7+q1p+xEq3wy8bEZ65MPcAvGTPzyJkd1n1+9I1HC/qaRUQGIgXbSkxddR1L1i7hD6/8gVFDc09f7+jqfU86FnkeBGedSfSdT7Vd+QpasGg/tCTqX6gDngw2ngc//zlcdVV7ZqcUmVL7A9YHr6ejLn8iIh1Jv9h94aQL+23aZHqG7k/O/Ik/xTNRWzkavxg+bFNbphuBVjj+N3DcovbMvOTtA1F47/i0YF2IQOXz3DbjNgDuP/9+Fq9ZzK5o5qyaD3d/2HffABGRAULBthJTv7K+7arSju072uon9PQf/pxT5vToedUnNvP8gbe1L4+v7tF+BorE57lwOHVZpNQlpk07589ELOJZiIOX55XWD63UXo+IFL3E++zFaxZzwcQL+rU+WbYM3cVrFvMET/jZaIlpoCmZa0F44Qq/5vLFp7VPh02uxfyPKUAw3gCiheGH/YUnL3k25eLE7WffnrV228F7HdxXL19EZMBQsK3ELF6zOOu6rv7pz18+P2PdYXsf1uOr+zOPnJlyhW/mkTN7tJ+BooRqjIt0S4nNQpRSEImUTqaeiJSMRDmVgSA9Q/fxrzzO+B+PZ31KTTn8jLZoML5gEB3iB9cS21Su8INysTL8j42tcMiTEPoBT377JxmfExKv/3tPf4/1H6+P79W493P3FuaFiogMYIH+HoDkV7b6ELnUjGh4uyFjXW/+MYaqQgwrG0bQggwrG9Y3RaYjEZg717/Ps2w1xkUGg8SsvZtvVpBZBoDElY8bb/TvC/D3XkSkFL33zfcYFhzWvqJyhT91FAd0XCdizyNf9qeTWguUNTNtVpjl38sMtCXUVdfx3jffY/kly7n19FtZdskyTc0XkUFJmW0lpq66jre2vsX8ZX6mWtCCTNp3UqfPqV9Zz0fNH6WsGxYc1qt/jH1eZLrAqWfK7pHBTLP2ZMAooe6qIiJ9rWFWAyf/x8ntK45b5E8RjQ7xlwPN/jpg4tiJXHPSNdRV11E/YzWLH93MBWePoW7mbVn2nEn1L0VksFOwrQS9vvn1tq+jLsr85fP5wxf+kLFdpClCuDFM/Yv1GY/tOWzPXo+jT//JFvgDWKnVGBcRKUaRMecRtp2EAk/hVbyY/cqHppmKiGTlVXosv2Q5s/4wize2vuFnt118GqyqpTxQQWDy/Rx5/E7uPHd5ynv4upmTqCvuijAiIn1OwbYStO7DdZ0ugx9oC90boiXagsNlPJ5o4100+iD1TNk9MhglgvJ9kqEq0olIBGqunURz7BgqgjfSsOBVPG9Slo1UYFNEpCNepcfr//o69SvrufvFu9n/yHHM+d7k+P/4S/t7eCIiJUPBtkFq0apFNEebO3z87MPO7sPR5IFSz0TyLtIUoWZRDc3RZiqCFTTUNijgJv2mLYE5ZjRbOeHNk8g4GzXNVIpVIiNzzBi/DbTey0iBDaSGDiIipUjBthL0yqZXUpZXbViVsc2Tbz/Z6T4279ic1zH1CaWeieRVuDFMc7SZqIuyq3UXi1YtUrBN+k1OCcwqsCnFKJGRuXs3xGIQCMCQIcrMFBERKWLqRlqC9ttjv5Tl3dHd1K9sr8tWv7KeN7e+2eHzgxbsm+6hIjKghapCBANBAByOu1+6m0iTuj9K/8ipM67a50oxSmRkxmL+ciym1uciIiJFTsG2EjTjkBkZ6xavWQz408KueOSKDp9bHihn6eylyl5JE2mKcOWdi7jyurVEFGuQQcKr9DjnsHPalltiLSxatagfRySDnefBDTd0EUPLaSORASSRkRmIvy0PBCAYhHffRW86REREipOCbSWo9rhaghZMWXfBxAsAf1pYtoYICVEXVaAtTaQpQuiWG7jrX/+Ju350AKedHtV7Xxk0xu0xrr+HICJS2hIZmbfcAgsXQl0dmMGvfuVPL9WbDhERkaKjYFsJ8io9vnHyN7I+FqoKEejkx75H+R6FGlbRCjeGaXnrFIhWgCvTzA4ZVGqPq6UiWIFhVAQrqD2utr+HJCJSehIZmXV1MGECtLamNvoQERGRoqJgW4l6+LWHU5YXrFgA+IG4zx7x2Q6f9+MzflzQcRWjUFWI8k8sg2AzWItqbsug4lV6hGeF+eHpPyQ8K6zMVxGRQktMKw0G1ehDRESkSKkbaYna2bozZXnrrq1tX2/ZtSXrc8445IzibQEeifhXfkOhvNfp8So9wt+dy6LJv4fG6dTOPEilgGRQ8So9BdlERPqK57H6wQVsfnQxY86+gEl60yEiIlJ0FGwrURP2nEDjtsa25Q3bNxBpiuBVeuxq2ZWybXmgnK95X2PejHl9PMo8iUT8mibNzf4V4AJ0oPMqPbwr9WZXRERECivSFKHmb9fSfEAzFX9bSkP1JF3wEBERKTKaRlqiRg8dnbLscG1dBPcaulfKY6dVnVa8gTbwM9qamwte2yQSgblzVadYRKQ/6W+xlLpwY5jmaDNRF6U52ky4MdzfQxIREZFuKopgm5ndYGZ/MbMPzWyjmT1sZsekbWNmdpOZrTOznWYWNrOj07bZ28zuM7MP4rf7zCw18lQixo3ouIPgyxteTll+e+vbhR5OYfVBbZNE8tyNN6oxmIhIf9HfYhkMQlUhKoIVBC1IRbCCUFWov4ckIiIi3VQUwTYgBNwBnAycDrQCT5pZcvrWHOAbwL8AnwTeB/5sZiOTtnkQOAE4Gzgr/vV9hR58fzh+/PEpy4ZRe1wt9Svref/j91MeO3/i+X05tPzzPH/q6M03F2QKKfRZ8pyIiHRCf4tlMPAqPRpqG7j5tJtpqG3QFFIREZEiVBQ125xzZyYvm9lXgA+AU4CHzcyAa4HbnHOL49vMwg+4fRlYaGZH4QfYPuWcWx7f5nJgqZkd4Zx7rc9eUB/YvGNzyrLDsfr91Xwv/L2U9SMrRhb3FNIEzytIkC0hFIKyMojF/Hs1BhMR6XuJROZEiU79LZZSpcY0IiIixa1YMtvSjcQfe6LF5sHAOOCJxAbOuZ3AEvxsOAAP2A4sT9rPMuDjpG1KRqgqRMBSf7w/eOYHrN++PmXdkLIhfTmsohaNgnP+vYiI9L0+SGQWEREREem1Yg223Q68DCSqtSQKlG1I225D0mPjgI3OOZd4MP71+0nbtDGzOjN7wcxe2LhxYz7H3ie8So8p46ekrPvHR//I2O6EcSf01ZCK2qJF0Nrqf93a6i+LiEjf8zy44QYF2kRERERk4Cq6YJuZ/RT4FHCBcy49x8ilb562Lv3xfPgZigAAFslJREFUbNv4GzpX75yb4pybMnbs2N4Mud+8vvn1Lrf5+0d/74ORiIiIiIiIiIgMDkUVbDOznwFfAk53ziW30EzMjUzPUNuX9my39cC+8fpuif0ZMJbMjLiS0BprTV3RNBWWXu/fx33c/HEfj6o41dbCkCFg5t/X1vb3iERERERERERkICqaYJuZ3Y7f7OB059yraQ+/gx9M+3TS9kOBU2mv0RYBRuDXbkvwgD1IreNWMk7YP2mKaNNUuLcBnrrZv48H3NK7lkp2ngdPPw0//KF/r+lLIiIiIiIiIpJNUQTbzOyXwGz8rLatZjYufhsBbbXXFgDXm9n5ZnYMcA9+Q4QH49u8AjyG35l0qpl5wELgkVLrRJpwW81t7QuNIYhWgCvz7xv9BgpzTp7Tb+MrNqoTJCLS/yJNEeYunUukKdL1xiIiIiIi/aCsvweQo6vi9w1p678P3BT/ej4wDPglsDfwHHCGc+6jpO0vBP6d9q6l/wNcXYDxDghepcewsmHsbN0JwzaBCwLOvx+2iTvPvVNt5UVEpGhEmiLULKqhOdpMRbCChtoG/R8TERERkQGnKIJtzjnLYRuHH3i7qZNttgAX5W1gRaAsEP8R79wHiOL/yFupaD6Auuq6fhyZiIhI94QbwzRHm4m6KM3RZsKNYQXbRERERGTAKYpppNJznz3is/4XVWEoawZrgbJmJn7y/X4dl4iISHeFqkJUBCsIWpCKYAWhqlB/D0lEREREJENRZLZJz91//v28sfkNnmcFzKqBxhB28BLuuPzH/T00ERGRbvEqPRpqGwg3hglVhZTVJiIiIiIDkvmzL6UzU6ZMcS+88EJ/D6NX6lfWc/eLd7P/qP2Zc/IcfUARERERERGJM7OVzrkp/T0OESkNCrbloBSCbSIiIiIiIpKdgm0ikk+q2SYiIiJFIxKBuXP9exERERGRgUg120RERKQoRCJQUwPNzVBRAQ0N4KkqgoiIiIgMMMpsExERkaIQDvuBtmjUvw+H+3tEInmktE0REZGSocw2ERERKQqhkJ/RlshsC4X6e0QieaK0TRERkZKiYJuIiIgUBc/zYxDhsB9oUyxCSka2tE2d4CIiIkVLwTYREREpGp6nGISUIKVtioiIlBQF20RERKRoRCLKbJMSpLRNERGRkqJgm4iIiBQFlbWSkqa0TRERkZKhbqQiIiJSFNSNVERERESKgYJtUjoiEZg7178XEZGSEwpBMAhm/r3KWomIiIjIQKRppFIaNLdIRGRQMEu9FxEREREZaJTZJqVBc4tEREpeOAwtLeCcf68/9SIiIiIyECnYJqUhFPIz2oJB/15zi0RESs6YMRCLOcARiznGjOnvEYmIiIiIZFKwTUqD58GCBf5U0gULNIVURKQEvfTWWrAYYGBRf1lEREREZIBRsE1KQyQC117r12q79lo1SRARKUVVz0BwN1gLBJv9ZRERERGRAUbBNikNqtkmIlLyas87jIpLzsFOv4mKS86h9rzD+ntIIiIiIiIZ1I1USkMo5Ndri8X8e9VsExEpOV6lR/i7cwk3hglVzcWrVMkAERERERl4FGyT0hGL+S3qYrH+HomIiBSIV+kpyCYiIiIiA5qmkUppmD8fWlv9r1tb/WURERERERERkT6mYJuUhnXrOl8WEREREREREekDCrZJabj00s6XRURERERERET6gIJtUhomTfIbI4B/P2lS/45HRERERERERAYlBdukNCxaBNGo/3U06i+LiIiIiIiIiPQxBdukNKxf3/myiIiIiIiIiEgfULBNSsO4cZ0vi4iIiIiIiIj0gUEZbDOzq8zsHTPbZWYrzezU/h6T9FJtLVRUgJl/X1vb3yMSERERERERkUGorL8H0NfM7AvA7cBVwLPx+0fNbKJz7t1+HZz0nOdBOOzfQiF/WURERERERESkjw3GzLavA/c4537lnHvFOfcvwHvAlf08Luktz4MbblCgTURK30kn+Zm8Xd3GjMl92+7cAgF/v3vs4X89cSJcd53/dfq2w4fDRRfB8cfDnnv6YwoG/a/r67v/2uvr2zOZzfxxJLvoIv8YF13Us+9tfb3/eo4+2v/6zDPz//0bCLfhwyESSX3t2V5reXn2n2vybdQomD4dKiv98yD955G+fVVV59//srL+//50dRs/PvP8LZaxD6Zb+t8HERGRPmLOuf4eQ58xswpgB/Al59x/Ja3/JXCMc256tudNmTLFvfDCC300ShERkU6cdBI8/3x/jyJ/Fi6Eurrctq2vh8svz1x/4onw3HN+YOeBB9rXX3gh3H9/7mPpaP+lbPly/yLVmWfCE0/kZ59z5sC8eZk/j2QHHQSNjanrivH7nzh/i3Hsg0Xi74NIF8xspXNuSn+PQ0RKw2DLbNsHCAIb0tZvAFIq6ptZnZm9YGYvbNy4sa/GJyIi0rkXX+zvEeTX4sW93zbxPXn00dT16cv5HEupCIf9+6VL87fPhx7y7zv7/r+bpXJHMX7/E2MuxrEPFqX2N1NERIrCYAu2JaSn81n6OudcvXNuinNuytixY/tuZCIiIp054YT+HkF+XXBB77dNfE/OPjt1ffpyPsdSKkIh//7UPPaKOv98/76z7/+ECZnrivH7nxhzMY59sCi1v5kiIlIUBluwbRMQJS2LDdiXzGw3ERGRgee55/xpUbkYPTr3bbvDzN/v8OH+10cd5U8dNMvcdtgwfzrn5Ml+ba/Ro/0aYKNGdW8KKfjbLlzo1xFLSJ4idv/9/rFGj+7+FNLk/R91lF+3beFCOOOM7u2jWAwb1j6FFODxx7O/1kQNss6MHAnTpsGBB7ZPIYX2n0e6bFNIof37Hwx266X0i3HjUs/fYhr7YKIppCIi0k8GVc02ADN7DljlnKtLWvc6sNg5d0O256hmm4iIiIiISOlSzTYRyaey/h5AP/gpcJ+ZPQ8sA64A9gfu6tdRiYiIiIiIiIhI0Rt0wTbn3G/NbAzwXWA88FfgHOfc2v4dmYiIiIiIiIiIFLtBF2wDcM7dAdzR3+MQEREREREREZHSMtgaJIiIiIiIiIiIiBSMgm0iIiIiIiIiIiJ5omCbiIiIiIiIiIhInijYJiIiIiIiIiIikicKtomIiIiIiIiIiOSJgm0iIiIiIiIiIiJ5omCbiIiIiIiIiIhInijYJiIiIiIiIiIikifmnOvvMQx4ZrYRWNvf4xgg9gE29fcgRPqYznsZjHTey2Cjc14GI5337Q5yzo3t70GISGlQsE26xcxecM5N6e9xiPQlnfcyGOm8l8FG57wMRjrvRUQKQ9NIRURERERERERE8kTBNhERERERERERkTxRsE26q76/ByDSD3Tey2Ck814GG53zMhjpvBcRKQDVbBMREREREREREckTZbaJiIiIiIiIiIjkiYJtIiIiIiIiIiIieaJg2wBkZjeY2V/M7EMz22hmD5vZMWnbmJndZGbrzGynmYXN7Oi0bb5jZsvM7GMzy5gvbGZjzezx+D52m1mTmf3SzPbMYYzTzWylme0ys7fN7Iq0x6eZ2f+Y2T/MzJnZxTm+9iFm9nMz2xQf9/+Y2YFJjx9nZv8ZH+tOM3vNzL5lZjqXi5zO+47P+/g2NWa23Mw+MrP3zGyemZXlsn8ZuAb5eV9nZk+b2bb486o62O5MM4uY2Y74tg257F8GpsF6zpvZ6Pjf+Vfjr6nJzO40szFJ2wTi+303fuz3zOx+Mzugq/3LwDZYz/v4835lZm/FX9NGM/tvMzsqbZu9zew+M/sgfrvPzPbKZf8iIgOVAhQDUwi4AzgZOB1oBZ40s9FJ28wBvgH8C/BJ4H3gz2Y2MmmbIcBDwIIOjhMD/gB8BjgcuBioAX7V2eDM7GDgT8By4HhgLvBzM7sgabMRwF+Ba4Cdne0vzQLgAuBLwKnAKOARMwvGH68GNgJfAY4Gvgf8G3B9N44hA1MInfdZz3szOzZ+7Cfix/4i8Fngtm4cQwamEIP3vB+Of07f1MnxZwL/B7gvfnwP+I9uHEMGnhCD85zfHzgg/tomARcB04D/TNvuKeDzwBH4/xcOib8OKW4hBud5D/BCfBxHAWcChv/ay5O2eRA4ATgbOCv+9X3dOIaIyMDjnNNtgN/w/7lFgc/Elw14D/hO0jbDgI+Ay7M8/5/8H3VOx/pX4L0utpkHvJG27tdApIPttwMX53DsPYFm4MKkdZX4bxzO7OR584GV/f1z0i2/N5337ec9cCvwUtrzPoP/Zndkf/+sdMvfbbCc92nPmQI4oCptfRB4F7isv38uuhXuNhjP+aTnnhP/Wz+qk20+G//9GNrfPyvd8ncb5Of9sfFz+oj48lHx5VOStvlU8ja66aabbsV4U2ZbcRiJn4W4Nb58MDAOPyMAAOfcTmAJ/hWzHjGz/YHzgWe62NRLPnbc48CUtKtU3VUNlJP6upqAV+j8dY2i/XsjpUPnffvrGgLsSnveTmBo/PlSOgbLeZ+LavzA824ze9HM1pvZE2Z2fIGPK31rMJ/zo4DdwI5sD8azni4EnnPOpf8PkOI2KM97M9sDmI1/IaUx6djb8bPqEpYBH9OL1y4i0t8UbCsOtwMvA5H48rj4/Ya07TYkPZYz82ug7QD+gX8FbXYXTxnXwbHLgH26e/y0/UaBTVn2nfV1mdkJ+Knpd/biuDIw6bxvf12PAyeZ2VfMrCxev+ff4o+N78WxZeAZLOd9Lg6J39+Mn915LvB34Jn4B0gpDYPynI/Xo7oZ+JVzrjXtsXlm9jGwGZgAnJev48qAMajOezO7ysy24wfVzgZqnHO7k4690TnXVoMu/vX79OC1i4gMFAq2DXBm9lP8VOoLnHPRtIfTC6NalnW5+Bp+bYSZ+B9u2upAmNn2pNtdXRw72/qszOzbafue0Nnm2fZrZkcA/xdY4JxbnMtxpTjovG/btwNwzj0BfBP4BX6G2+v4tVXAD9RJCdB5nyHxHuWHzrnfO+dWAnXANvy6nVLkBus5H8/ueRg/EDInyy5+hF836wz8v/H3m5ll2U6K0CA97x/AP6en47+H+S8zG97JsRPH78lrFxEZENTJbgAzs5/hF0I/zTn3dtJD6+P344CmpPX7knlVqkvOufXxfb5qZpuBpWZ2S3wq2+SkTT9MOn76laZ98Yu9bs7xsHcBv0taXhffbxD/CtrGtH0vSX6ymR0JPA38H+ecmiOUEJ33KftuO++dcz+Nf2/G4087qcIvYPxOjseWAWwQnve5eC9+vyaxwjnXamZv4Gf7SBEbrOe8mY2g/WLJedmmhzrnNuFnO79uZq/gfx8+BSzN8fgyQA3W89459wHwAfCGma3Afx9zAX4ThPXAvmZmiey2eHB5LD147SIiA4WCbQOUmd2O/8845Jx7Ne3hd/D/MX0a+Et8+6H4XQy/1ctDJzIJhgA4597Msk0E/0pZsk8DLzjnWnI5iHNuC7AleZ2ZrQRa4vt6ML7uQPzCqcuTtpuI363rd865r+VyPCkOOu87Pu/jz3fE37ya2Zfw35C/mMuxZeAajOd9jlbi17M6AngWwMwCwCfwp1ZLkRqs57z5XSUfxc/YOcs5t727Y5biNVjP+ywsfkuc0xH8hhEe7e97PGAP0t4HiYgUEwXbBiAz+yX+FJmZwFYzS1xp2u6c2+6cc2a2APiOmb2Kn479Xfw6CA8m7WcCMBo/AwYzS1zJetM5t93MzgPG4H+g2Q4cjT91YUUH/4gT7gKujo9hIXAKft20LyUdewRwaHwxAEyIH3+Lc+7dbDt1zn1gZncDPzKz9/GvpP0U+F/gyfh+j8YPtD0N3Jr0vUlcxZMipfO+4/M+vu9vAY/hd647H7ge+HyWKShSRAbreR9/3jj8TIrD46smml/H6l3n3Bbn3IfxKU7fN7O/4xfTvhrYG7i/kzHLADZYz/l4oO0J/KYIM4E94tNJiT+v2cw8/Kl/z+JPl/4Efl23xvg6KVKD+Lw/FD+D7Un87P0D8d+/7AYeAXDOvWJmjwELzewy/EDcQuAR59xrnYxZRGRgy2drU93yc8OvT5DtdlPSNgbchD/NZhd+l6Fj0vZzTwf7CcUfn4F/NWkbfmfD1/Fbf++dwxin42fU7Ma/GndF2uOhDo59Txf7HQr8HD/gsAO/pkll0uM3dfT96e+fm269u+m87/i8j2/zVNKYVwBn9/fPTLfe3wb5ed/R3/OLk7YpB+bjZ3x8CISBE/r756Zbz2+D9Zzv5DnJY56MfzFxc9Kx7wQO7O+fm24673t43lfiZ3O+DzTjZ+Q/AByZtt1o/IsoH8Zv9wN79ffPTTfddNOtNzdzziEiIiIiIiIiIiK9p26kIiIiIiIiIiIieaJgm4iIiIiIiIiISJ4o2CYiIiIiIiIiIpInCraJiIiIiIiIiIjkiYJtIiIiIiIiIiIieaJgm4iIiIiIiIiISJ4o2CYiIlJEzKzKzJyZ3VPAY9wTP0ZVoY4hIiIiIlKqFGwTERERERERERHJk7L+HoCIiIh0yz+Ao4AP+nsgIiIiIiKSScE2ERGRIuKcawFe7e9xiIiIiIhIdppGKiIiUkSy1WxLrrFmZpeb2Woz22VmG8ys3sz27GBfM8xsqZl9bGZbzOyPZnZkF8c/ycx+b2brzazZzJrMbKGZ7Z+23fnxMa0ws/K0x44xsx1mts7M9u3Ft0NEREREZMBRsE1ERKR0zI/fVgG/xJ9yehnwh/QNzeyfgMeBKcB/AQuBMUAEODjbzs1sNrAMOBt4GlgAvAD8M/CCmU1IbOuceyg+hpOAHybtYzjwW2AIcJFz7v3evGARERERkYFG00hFRERKx1RgknPuXQAzKwOeAk4zsxOdc8/H14/AD67FgFOdcy8kdmBmPwOuTd+xmR0ef04jMN0594+kx04H/gzcDnwu6WnfAE4GvmlmTznnHsMPwE0EfuCceypfL1xEREREZKBQZpuIiEjp+EEi0AbgnGsFfhNfPDFpu/8PGA08mBxoi7uJ7M0XrgTKgWuSA23x4zwF/A/wGTMbmbR+N/AF4GNgkZl9E7gYWAL8oLsvTkRERESkGCizTUREpHSkB84AmuL3eyetOyF+/0z6xs65D8zsZWB62kNe/H66mX0yy3H2BYLA4cDKpP29YWaXAw8APwI2AV92zkW7eC0iIiIiIkVJwTYREZHSsS3Lutb4fTBpXaJhwoYO9rM+y7ox8ftvdTGGEVnW/Rn4EBgF/Fd6ZpyIiIiISCnRNFIREZHBJzFNdL8OHh/XyXP2dM5ZJ7eUbDkzM2ARfqBtE1BnZtPy8SJERERERAYiBdtEREQGnxfj9+lTRTGzPYHJWZ6zIn5/ajeP9S3gLPxppKcDLcCDZrZPN/cjIiIiIlIUFGwTEREZfP4b2Ap82cympD12E+3TTJP9Aj9Q9rN4Z9IUZlZhZqemrTsJuAV4E7jSObca+BpwAHBPPOtNRERERKSkqGabiIjIIOOc225mdcBvgaVm9lvgPeBTwDH43UKnpT3nVTO7BPgP4G9m9hjwOn6H0gn4GW8bgSMBzGwv4P8ADviic+6j+H7uMrMa4J+ArwM/KfDLFRERERHpU8psExERGYScc7/Hn965Evg8cAWwBb/r6DsdPOd+oBp/SuixwNXARcChwO+Bq5I2v/v/tWsHNQACMRQFWyeoQBEicIA6NJULF+4/gZAZAd32+rJVtVTVPjPnc1Jt9xtHd6+ZiwAA4Bt6Zt7eAQAAAAB+wc82AAAAAAgR2wAAAAAgRGwDAAAAgBCxDQAAAABCxDYAAAAACBHbAAAAACBEbAMAAACAELENAAAAAELENgAAAAAIEdsAAAAAIOQCZxlk9JlqZNIAAAAASUVORK5CYII=\n", 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" ] @@ -717,7 +701,7 @@ ], "source": [ "dataset.fill_missing_interpolation('CODtot_line2',12,[dt.datetime(2013,1,1),dt.datetime(2013,1,31)], method='polynomial',\n", - " order=2, plot=True)" + " order=3, plot=True)" ] }, { @@ -730,7 +714,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:55:01.103135", @@ -742,7 +726,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_HydroData.py:1599: UserWarning: Data points obtained during a rain event will be used for the calculation of an average day. This might lead to a not-representative average day and/or high standard deviations.\n", + "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_HydroData.py:1959: UserWarning: Data points obtained during a rain event will be used for the calculation of an average day. This might lead to a not-representative average day and/or high standard deviations.\n", " 'representative average day and/or high standard deviations.')\n" ] } @@ -754,7 +738,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:55:01.844129", @@ -772,7 +756,7 @@ }, { "data": { - "image/png": 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\n", 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l/Xy9Cm6hoaFVJ06cqACAsLCwypiYmGbd1xrn6+tbXfechQsX+g8cOLAkJSXlF+vYHXfcURwcHNxv2bJlPm+99dalmXIXLlxQJSUlHRsyZEiFdezLL790+vzzz13XrFmTMXfu3EIAmDRpUombm5tx9uzZQfv27dMNGTKk4o033nD/9ddftcnJycetOUyePPlir169QvPy8tTX8r1Q+9UuppESERERERERUTuWkuKMmhoFzGbAaFQgJaXd7fDZXEeOHNFmZ2dr77vvvsKamhpYX87OzuaIiIiy/fv3O9nG+/r6VtsW2gDg888/76JWq+W0adPO215j4sSJxQCwa9cuZwDYv3+/k4+Pz2XFPqVSiYkTJxZdj2eltsHONiIiIiIiIiJqXExMCVatMsNoVEClMiMm5obd3fPs2bMqAHjqqaf0Tz31lL7u8a5du1bbfvby8qqpG1NQUKCqqakRXbp0iajvHoWFhSoAyMvLU7u7uxvrHvf29r5ijDoOFtuIiIiIiIiIqHGxsWVISvq5LdZsszdPT08TACxevPjM2LFji+se12q1l+00KoS4YudRNzc3o1arlV999dXx+u4REBBQAwDe3t41J06ccKh7PC8vj/WYDoy/XCIiIiIiIiJqWmxs2Y1WZFOr1bKiouKyJbTCw8MrfX19q48dO6ZbtmxZ7tVc94477ihev369z/nz55UTJ05ssMtv8ODBpR9//LF7SkpKJ+tUUpPJhM8++8ztau5LNwYW24iIiIiIiIioQwoODq5MTk7usmXLlmJ3d3djQEBAjV6vr3nttdeyHnjggeA777xTTJ48ucjT09N49uxZ9b59+5wCAgKqX3jhhbzGrjtu3LiScePGFT344IPBjz32WN7gwYPLFAoFTp06pfnyyy+7rFy58tf+/ftXzZkzp3D16tU+U6ZMCX7mmWfOeHt7Gzds2OBZWlqqvF7fAV1/3CCBiIiIiIiIiDqk119/PdPR0dF8//339xg+fHifhIQETwC47777Ln755Zfp5eXliieeeEJ/9913hzz//PPd8vPz1UOHDi1tzrW3bt16esGCBTnbtm1znTp1ao9p06Z1T0xM9AoODq7y8/MzAoCDg4PcsWPHz3369ClftGhRwMyZM/WBgYFVTz/9dE5rPje1LSHlFVOPqY4BAwbIAwcOtHUaRERERERE1AqEEAellAPaOg97Onz4cEZ4ePi5ts6DqKM6fPiwR3h4uL6+Y+xsIyIiIiIiIiIishMW24iIiIiIiIiIiOyExTYiIiIiIiIiIiI7YbGNiIiIiIiIiIjITlhsIyIiIiIiIiIishMW24iIiIiIiIiIiOyExTYiIiIiIiIiIiI7YbGNiIiIiIiIiIjITlhsIyIiIiIiIiIishMW24iIiIiIiIiIiOyExTYiIiIiIiIiavdWr17tHhgYGKZWqyOdnZ1vAQA/P79+cXFxemtMQkKCuxAiKj09XWMdqxtzrQYNGtRr0KBBvZoTu2fPHkedThdx+vRp9bXmk56erpk3b57vsWPHNE1Ht62kpCRnIURUUlKSc0vPnTdvnu+2bduuOC8uLk7v5+fXzz4ZXikzM1Ot0+kivv76a8drvZbKHgkREREREREREbWWjIwM9fz58/UTJkwoTExMPKfT6cwA8OGHH550cXExt3V+DVmwYEG3yZMnFwYFBdVYx6425xMnTmhXrVrV9bbbbivp27dvtX0zbT9WrVrV1Wg0YsKECSW240uWLDl74cKFvNa6b2BgYM39999/buHChf7ff/99+rVci8U2IiIiIiIiImrXjh49qjWZTJg+fXrhmDFjSq3jt956a0Vb5tWYvXv3On733XfOa9euzbIdb085G41GSCmhVqubDm5joaGhVa19j7lz5xYMGDAg9Ouvv3YcMWJE+dVeh9NIiYiIiIiIiKjdiouL048bN64XAEycODFECBFlnYZ5tVMyjx8/rpkwYUKQq6truEajiezdu3ffjRs3utSNS0xMdA0KCgrVaDSRPXr0CK0vpiHr16/3CAkJqRgwYECl7XhDU19TUlI6TZgwIcjJySnCy8ur//Tp0/3Ly8sFUDstc/z48SEAcNddd4UIIaLqTtNcuXKlR69evfpqtdpIV1fX8HvvvTcwLy9PaXtvIUTU448/7vfnP//Zx8/Pr59Wq436z3/+o7NO+/znP//pEhcXp+/cufMtTk5OERMmTAjKzc297BpFRUWKadOmBXh5efXXaDSRer0+7MUXX/Qymxtv1vv00087Dx8+vIenp2d/nU4X0bNnz9Dnn3/e22g0XpYfAKxZs6ar9RnnzZvnC9Q/jTQzM1N911136a2/x5CQkL7r1q1zs41pzvdrFRUVVdmzZ8+KxMREz0YfpgnsbCMiIiIiIiKiJiUno1NKCpxjYlASG4uy63XfJUuWnI2MjCx/5pln/OPj47MGDhxY7uPjY2z6zPqdPHlSPWTIkD7u7u7Gl19+Odvb29v4wQcfuE2fPj1YqVSefOCBBy4CwNatW51nzpzZ3WAwXIyPj/81Pz9ftWjRIn+j0SiCgoKa7LJKTU3tEhMTc7G5eT388MNBd911V9HDDz988ttvv3V67bXXfF1dXU2rVq3KGTJkSFl8fHzW4sWLA1566aXswYMHlwFAREREBQDMnj3bLzEx0XvGjBn58fHxv2ZnZ6tffvllv1GjRukOHTp0XKX6rfyzefNmd39//6qXX34528nJyRwQEFBz/vx5FQD86U9/Chg6dGjxW2+9dSo9Pd1h2bJlfhMnTlR/9913PwOAyWTCqFGjeh47dsxx4cKFOeHh4RXbt2/v8sILL/gXFBSo165de6aR711rMBhK5syZk6/T6eR//vMfx1dffdW3oKBAtW7dujMAkJycfDw2NrZ3XFxc4axZswoAQK/X1ztltri4WDF8+PBeFy9eVP7lL385ExAQUP3uu++6z5kzJ6i8vFwxf/78c839fm3jBg8eXLpz584uzf291YfFNiIiIiIiIiJqVHIyOo0bh5CaGihWrYI5KQk/X6+CW2hoaNWJEycqACAsLKwyJibmmu775z//2VdKiT179hz38fExAUBcXFzxkCFD1EuXLvWzFtuWLFniFxQUVLlz586TSmVtc5fl/r2bKrZlZ2ercnJyNOHh4c2einj33XcXWQs/kyZNKjlw4ECnLVu2uK1atSrHzc3NHBYWVgkAoaGhFbbfQXp6umbDhg0+Tz31VM6rr7561jrep0+fyjFjxvT+17/+5fLggw9esL3X7t27f3ZycpLWz4cPHwYA9OzZs+Ljjz/OsAwXu7m5GWfPnh302WefOU+cOLHkww8/7HLo0CGn119/PeOJJ54otORdXF5erkhMTPT+y1/+kte1a9d6C6ELFy4ssP5sNpsxduzYkurqarF+/XqfNWvWnFEqlbA+l6+vb3VTv+e1a9e6Z2Zmardv3/7zuHHjSgDg3nvvLR4yZIh62bJlfk8++eQ52yJjY9+v7XUjIiLKN23a5JmRkaHW6/U1uAqcRkpEREREREREjUpJgXNNDRRmM2A0QpGSghbvMtlepKamdhkxYsRFd3d3U01NDayv2NjY4vT0dF1RUZHCaDTiyJEjjuPHjz9vLbQBwMiRI8t8fX2b3JwgKytLDQBeXl7N7sCbMGHCZQWxvn37Vpw9e7bJnUeTkpI6m81mzJgxo8j2eUaMGFHm5ORk2r17t5Nt/PDhw4ttC2224uLiimw/z5gx47xCocC3337rBAC7d+92VigUeOSRRy6Le/DBB4tqamrE119/3amhPDMzM9VTp04N9PX17afRaCI1Gk3UihUr/EpKSpRnzpxpcTPY3r17nb28vGqshTar+++/v/D8+fOqQ4cO6WzHm/v9enl51QC//Q6vBjvbiIiIiIiIiKhRMTEoWbUKZqMRCpUK5pgYlDR9VvtUVFSk2rJli7tGo3Gv73h+fr6qrKzMbDQahbe39xWdTR4eHk12O1VUVCgAQKvVNnvXUU9PT5PtZ61WK6urq0VD8bb5AkBYWFhYfceLioouq/34+Pg0mH/d6bkODg6yc+fOxjNnzqgB4Pz588rOnTsbdTrdZcU6Pz+/GgAoLCyst85kMplw55139sjPz1cvWrQoJzQ0tNLR0dH88ccfu6xZs6ar9ftqiQsXLqg8PT2veBZfX98aACgoKLhsrbnmfr+Ojo4SAMrLy6+6QY3FNiIiIiIiIiJqVGwsypKS8HNbrNlmby4uLqaBAweWLF68OLe+44GBgTVqtVqqVCqZl5d3RXfTuXPn1H5+fo12t1k72uoWulqDu7u7CQA+/fTTE+7u7ld00tXtrhNC1NvVBgC5ubmX5VtZWSmKi4tV1mKaq6urqbi4WFVZWSkcHBwuXcdajPPw8Ki3k+/YsWPao0ePOr7xxhunZ8+efakrbsuWLc3ecKIuFxcX46lTpxzqjufk5LS4q9DWuXPnlNdyPtBOppEKIW4TQmwTQpwRQkghxHSbY2ohxF+FEP8TQpQJIc4KId4XQgTUuYZWCLFGCHHOErdNCNGtTkyAEGK75fg5IUSCEKLJlkwiIiIiIiKim11sLMri45F7IxfaAGD48OEXf/rpJ8fIyMiK2267rbzuS6fTSZVKhX79+pVv377d1WT6rSFq165dnXJycpqsI4SEhFRrtVp56tQprb3ydnBwMANXdlzdeeedxQqFAhkZGZr6nqd3795NTnu1+uSTTy7byfPtt992NZvNuPXWW0sBwGAwlJjNZrz99tuutnHvvvuum1qtlgaDod7/bZSWlioAQK1WXyrQVVVVibr3s8Y0p9Nt2LBhJXl5eeqvvvrqsqmrmzdvdnNzczNGRERUNnRuY06fPq1Vq9Wyd+/eTW6C0ZD20tnmBOBHABstL1uOACIBvAzgvwC6AFgJ4EshRH8ppbXSuBrARABTABQCeA1AkhAiSkppEkIoAXxuOTYMgDuAdwAIAI+34rMRERERERERUTuxfPnynOjo6D6DBw/u/dhjj+V37969qqioSHXkyBHd6dOntR999FEGADz33HNn7r777pBRo0b1ePTRRwvy8/NVy5cv923ONFIHBwfZv3//sgMHDjS4hllLhYWFVSqVSvn22297eHh4GB0cHGS/fv0qQ0NDq2bNmpW7ePHigPT0dAeDwVCi0+nMmZmZmuTk5M6PPPLIufHjxzdr2u+JEyd099xzj37KlClFx48fd4iPj/cbOHBg6cSJE0sAYPLkyRdfeeWV0vnz5wcWFBSo+vXrV5mUlNRl8+bNHnPmzMltaHOEiIiISl9f3+qlS5f6qVQqqNVqmZCQ4F1fbHBwcGVycnKXLVu2FLu7uxsDAgJq6tuoYM6cOYUbNmzwnjJlSg/b3Uj37dvX+ZVXXsm03RyhJb7//vtO/fr1K7NOJ70a7aKzTUr5bynln6WUHwMw1zl2UUo5Skq5WUqZLqX8D4DHAPSxvCCE6ALg/wAskFLulFIeAvAggP4AYi2XGg0gFMCDUspDUsqdABYCeEQI0fl6PCcRERERERERta2ePXtWf/fdd8dCQ0PLly5d6jdp0qSQefPmBezdu9dpxIgRxda4SZMmlaxfv/70qVOnHKZNmxackJDgs3z58uymdiK1iouLK9q/f79zcXGxXWovPj4+pvj4+KyffvrJ8Y477ug9fPjwPt9++20nAFi7du2ZlStXZqSlpTnNmDGj+5QpU3qsXr3ax8XFxdS3b99md3j99a9/zZJSYvr06d2XLVvmN2LEiAufffbZL9bjSqUSO3fuPBEXF1e4Zs0an3vvvbdHSkpKlxdeeCE7ISHhTEPXdXBwkB999NFJT0/PmtmzZ+uffvrpgCFDhpQ8+eSTV0zlff311zMdHR3N999/f4/hw4f3SUhI8Kzvmp07dzbv3r07fdiwYcVLly71mzp1ao9jx47p3njjjdPz588/19xntlVaWirS0tI6190ooqWElFddqGsVQohSAHOllP9sJGYwgDQA/lLKX4UQIwGkAPCSUhbYxB0F8LGU8nkhxBIAcVLKUJvjngDyAYyUUn7d0P0GDBggDxw4cK2PRkRERERERO2QEOKglHJAW+dhT4cPH84IDw+/qoID2UdRUZEiICAgfMWKFZm265S1R0lJSc4Ikor+AAAgAElEQVTjx48P2bJly8+TJk26YTe/uFZ///vfXZ988kl9Zmbm/zw8PEyNxR4+fNgjPDxcX9+xdtHZ1hKWNdZWAtgupfzVMuwDwASg7h+SPMsxa0xenePnLOf5gIiIiIiIiIjITtzc3Mxz5sw5u3r1ah+zudmbklIbWrVqlc+sWbNymyq0NaW9rNnWLEIIFYB3AbgAmNCcUwDYtu411MZ3xbgQ4lEAjwJAQEDAFScQERERERERETXm2WefzTOZTCIrK0td37pj1H5kZWWpbr/99gvPP/983UatFrthim2WQtu/APQDYJBSFtoczgWgBOABoMBm3AvANzYxt9a5rIflvCu+SCllIoBEoHYaqR0egYiIiIiIiIhuIk5OTvLVV18929Z5NGXcuHElUsqDbZ1HWwoICDCuXLnSLr+rG2IaqRBCDWAzajc8GCGlrLuA3kEANQBG2ZzTDbUbKOyzDKUB6GMZtxoFoMpyPhERERERERER0TVpF51tQggnAD0sHxUAAoQQtwAoApAD4CMAAwGMByCFENY11i5KKSuklBeFEG8CeEUIkQ+gEMBrAP4HINkS+xWAowA2CiGeBuAO4BUAf5dSXtpthIiIiIiIiIiI6Gq1l862AQB+sLx0AF60/LwEQDcAEwH4orYD7azN6z6bazwF4FPUdsB9C6AUwHgppQkALO93Aii3HN9siZ/fuo9GREREREREREQ3i3bR2SalTEXtZgYNaeyY9RqVAB63vBqKyQIwrqX5ERERERERERERNUd76WwjIiIiIiIiIiK64bHYRkREREREREREZCcsthEREREREREREdkJi21ERERERERE1O6tXr3aPTAwMEytVkc6OzvfAgB+fn794uLi9NaYhIQEdyFEVHp6usY6VjfmWg0aNKjXoEGDejUnds+ePY46nS7i9OnTauvYvHnzfLdt2+Zsr3waYu/nttWS76Cu+n5H9vTiiy96hYSE9DWZTK1x+WZpFxskEBERERERERE1JCMjQz1//nz9hAkTChMTE8/pdDozAHz44YcnXVxczG2dX0MWLFjQbfLkyYVBQUE11rFVq1Z1NRqNmDBhQklr3ru9fzet5emnny5Ys2ZN17Vr17r/8Y9/LGyLHFhsIyIiIiIiIqJ27ejRo1qTyYTp06cXjhkzptQ6fuutt1a0ZV6N2bt3r+N3333nvHbt2qy2uH97/m5ak5OTk7znnnsK16xZ49NWxTZOIyUiIiIiIiKidisuLk4/bty4XgAwceLEECFElHV65NVOlTx+/LhmwoQJQa6uruEajSayd+/efTdu3OhSNy4xMdE1KCgoVKPRRPbo0SO0vpiGrF+/3iMkJKRiwIABldYxIUQUAKxZs6arECJKCBE1b9483+eee85bo9FE5uTkXNYUZTab0a1bt37jx48PAoD09HSNECJq+fLlnn/4wx+6ubm5het0uogRI0b0qDsts77v5vjx45pJkyYFeXh4hGs0mshu3br1mzFjhr/1+O7dux3Hjh3b3dvbu7+Dg0OkXq8Pmzt3rl9paalo7nPbOnbsmMZgMPTQ6XQRrq6u4TNmzPCvqqq64lqJiYmugwcPDnF1dQ13dHSM6NOnT981a9a428aEhIT0HTVqVHDdc5OSkpyFEFGffPJJZ+vY73//+6JffvnFYefOnZ2uJu9rxc42IiIiIiIiImrS+fPJnc6fT3F2dY0pcXWNLbte912yZMnZyMjI8meeecY/Pj4+a+DAgeU+Pj7Gq73eyZMn1UOGDOnj7u5ufPnll7O9vb2NH3zwgdv06dODlUrlyQceeOAiAGzdutV55syZ3Q0Gw8X4+Phf8/PzVYsWLfI3Go0iKCioqqn7pKamdomJibloO5acnHw8Nja2d1xcXOGsWbMKAECv11c7OTmZV6xY4bdu3Tr3l156Kc8av2XLls5nzpzR/O1vfztne53Vq1d37du3b/m6desy8vLyVC+99JLfmDFjQtLT049qtVpZXz7Hjx/XREdH99HpdOZFixad6dWrV1VmZqZm586dl4pUp0+f1vTv37/ioYceKuzcubPpyJEjuldffdU3IyNDm5SUdKol33NlZaUYM2ZMSFVVlWL58uVZ3t7exsTERM8vvvjCtW7sqVOntJMmTTofEhKSq1AoZGpqqvNTTz0VWFFRoVi4cGEBADz88MMFzzzzjH9GRoZar9dfmpa7YcMGDz8/v+q77rqr2DoWHR1d7uTkZPr888+7jBo16rr9b9WKxTYiIiIiIiIiatT588md/ve/cSFS1iiys1eZ+/dP+vl6FdxCQ0OrTpw4UQEAYWFhlTExMdd03z//+c++Ukrs2bPnuI+PjwkA4uLiiocMGaJeunSpn7XYtmTJEr+goKDKnTt3nlQqlbC5f++mim3Z2dmqnJwcTXh4eLntuDV3X1/f6rrPceeddxZt3LjRc8mSJXkKRe1ExA0bNnjq9frKcePGXba+W6dOnUy2efXp06dyzJgxvdetW+f+1FNPXVaYs1q8eLFvVVWV4ocffjhmW6x6/PHHL021nD59+gUAF4DarrrRo0eXdu7c2TR37tyg3NxcpfX7ao433njD/ddff9UmJycftz7r5MmTL/bq1Ss0Ly9PbRu7fPnyXOvPJpMJd955Z0lubq76zTff9LQW2x577LHCl156qdsbb7zh8corr5wFgLNnz6p27NjhOn/+/BzrdwYASqUSISEhFd9//32bdLZxGikRERERERERNer8+RRnKWsUgBlSGhXnz6e0+m6arSU1NbXLiBEjLrq7u5tqampgfcXGxhanp6frioqKFEajEUeOHHEcP378eWtBCwBGjhxZ5uvrW93UPbKystQA4OXl1ewOvLlz5+ZnZ2drrTuVZmZmqnft2tVl+vTpBXVj6+Y1evToMm9v75r9+/c3WFzas2dPl5EjR160LbTVVVRUpJg1a5afv79/mFarjdRoNFFz5swJklLi6NGjDs19FgDYv3+/k4+Pz2VFRaVSiYkTJxbVjT1y5Ih2/PjxQV5eXv01Gk2URqOJ2rx5s0dGRsale7q6uponTZpU+N5773lYdxpdt26du5QSs2bNuqLA6O7ubszPz2+VHU+bws42IiIiIiIiImqUq2tMSXb2KrOURoUQKrOra0yr7qTZmoqKilRbtmxx12g07vUdz8/PV5WVlZmNRqPw9va+ojDl4eHRYLHKqqKiQgEAWq222buBjhgxojw0NLT8b3/7m+ekSZNK1q5d66FSqTBz5swrFvlvKK+zZ882WFy6cOGCsqlC4ZQpU4L27dvnvHDhwpzIyMhyZ2dn8759+zotXrw4wPpMzZWXl6d2d3e/otjo7e192djFixcVY8eODXFwcDA///zzv4aEhFRptVq5du1az48++sjDNvaPf/xj/nvvvef54Ycfdrnvvvsubty40XP06NEX/P39r7iPg4ODubKy8qrWmrtWLLYRERERERERUaNcXWPL+vdP+rkt1myzNxcXF9PAgQNLFi9enFvf8cDAwBq1Wi1VKpWsO90RAM6dO6f28/NrtGhl7WgrKipqUd3lD3/4Q/78+fMDT58+rX7vvfc8br/99iJvb+8rpm42lFdoaGh53XErV1dX49mzZ684z6q8vFykpKS4zJs3L+fZZ5/Nt47/8MMPupY8g5W3t3fNiRMnruiGy8vLu+w72bVrl1NOTo7myy+/TLfdaXb16tVXFMoGDhxYGRUVVfr3v//dU6fTmbOysrRr1qzJrO/+Fy5cULm6ul712n7XgtNIiYiIiIiIiKhJrq6xZd27x+feyIU2ABg+fPjFn376yTEyMrLitttuK6/70ul0UqVSoV+/fuXbt293tU5ZBIBdu3Z1ysnJaXJqYkhISLVWq5WnTp3S1j2mVqtlQ11if/jDH4o6depkvvfee7ufPXtWM3v27CumkAJA3by++uqrTnl5eerBgwc3+LsZNmxY8a5du1wyMzPrLbhVVFQoTCYT1Gr1ZRssvPvuux71xTdl8ODBpbm5uZqUlJRLU1tNJhM+++wzN9u4srIyBYDL7ltQUKDcuXNnvTu/Pvroo/nffPNNl6VLl/oGBgZWTZgwod4uy+zsbE1wcHBlfcdaG4ttRERERERERHTTWL58eU5paaly8ODBvdesWeP++eefO23atMll4cKFXSdPnqy3xj333HNnTp8+7TBq1KgeH3zwQZeEhAT33//+992bM43UwcFB9u/fv+zAgQNXrKEWHBxcmZyc3GXLli2dv/nmG8eMjIxLxS8nJyc5efLkcwcOHHDq2bNnRUM7aZaVlSlt83rggQeCAwMDq2bPnn3FlFOr+Pj4HI1GYx4yZEjvlStXemzfvt153bp1bhMnTgwCAHd3d1N4eHjZ+vXrvdeuXeu+efPmLmPHju1eXxddc8yZM6ewW7duVVOmTAlOSEhw37x5c5dRo0b1KC0tVdrGjRw5stTJycn0xBNPBHzwwQdd/vGPf7jeeuutvRrqSnvooYcuuLi4GA8dOuRU33p2AHDu3DllZmamw7Bhw0rrO97aWGwjIiIiIiIioptGz549q7/77rtjoaGh5UuXLvWbNGlSyLx58wL27t3rNGLEiGJr3KRJk0rWr19/+tSpUw7Tpk0LTkhI8Fm+fHl2UzuRWsXFxRXt37/fubi4+LLay+uvv57p6Ohovv/++3sMHz68T0JCgqft8fvvv/88AMyYMaPeQhIAPPnkk2e7d+9eOWvWLP2iRYsCQkNDy7/88suftVqtbOicXr16Ve/du/d4ZGRk6UsvveQXFxfXc9myZX4eHh6XilqbN28+FRYWVr5o0aKAWbNm6b28vIwrVqzIbs7z1uXg4CB37Njxc58+fcoXLVoUMHPmTH1gYGDV008/nWMb5+vra3zvvfd+MZlMYvr06cEvvvii37Rp087dc889V2ykAABarVaOHj36gkajkTNnzqx359WPPvqoi1qtllOnTj1/NblfKyFlg78HshgwYIA8cOBAW6dBRERERERErUAIcVBKOaCt87Cnw4cPZ4SHh9dbiKDro6ioSBEQEBC+YsWKzNmzZ9dbOKrP448/7vfmm296/frrr4fd3Nwu22AhPT1d07t3734rV67MnDdv3k35+62pqYFer+83cODA0q1bt56uL+a2227r6ebmZmzouD0cPnzYIzw8XF/fMW6QQERERERERERkZ25ubuY5c+acXb16tc/MmTOLFIrGJxd+++23uqNHjzq8+eabXlOnTi2oW2i72RUVFSkOHjyo27Rpk3tubq5m4cKF9W5wsW/fPt13333nfPDgwaPXO0crFtuIiIiIiIiIiFrBs88+m2cymURWVpZar9c3utbbvffe26OwsFA9dOjQi6+88kpOY7E3o3379nUaP358iJubm3Hp0qVZQ4YMqagvLicnR52QkJARFhbWrOm+rYHTSJuB00iJiIiIiIg6Lk4jJaKWamwaKTdIICIiIiIiIiIishMW24iIiIiIiIiIiOzE7sU2IURnIUSAva9LRHQjS0sD4uNr34mIiIiIrgOz2WwWbZ0EUUdk+W+rwQ0smlVsE0IECyE+E0JcFEIUCiHeFUIENRD+FIBW21qViOhGk5YGxMQAzz5b+86CGxERERG1NiFEbkVFhUNb50HUEVVUVDgIIerdDRVoRrFNCOEFYC+A8QCcAbgCmArgByHEnfZKlIioo0pNBaqrAZOp9j01ta0zIiIiIqKOzmg0vpiRkaEpKyvTscONyD7MZrMoKyvTZWRkaIxG44sNxamaca3FALwBbACwBEA1gD8AeA7Ap0KI+6SUW+2RNBFRR2QwABpNbaFNo6n9TERERETUmiIjI3ccOnRo7i+//PK8lNIHXLOdyB7MQohco9H4YmRk5I6GgoSUstGrCCGOA6iQUkbUGR8IYDsAFwD3SCmTLOPPA3hOSqm81idoLwYMGCAPHDjQ1mkQ0Q0sLa22o81gAKKj2zobIiIiIrIlhDgopRzQ1nkQUcfQnMp2IIBddQellN8DuA1AIYCPhBC32zk3IqIbWlp2GuL3xCMtm4u0ERERERER3SyaM420AoCpvgNSyp+FEAYAuwF8IoSYYMfciIhuWGnZaYjZGINqUzWUZ4ZCbEyBsUYJjQZISWF3GxERERERUUfVnM62TADhDR2UUp4AEAOgBMBWALfaJzUiohtXakYqqk3VMEkTan65FdXVghskEBERERER3QSaU2zbC+A2IUSXhgKklD8BiAVQidrCW4sIIW4TQmwTQpwRQkghxPQ6x4UQ4gUhRI4QokIIkSqECK0T4yqE2CSEuGh5bRJCuNSJ6SeE2G25xhkhxHNCCO7KQkR2Z9AboFFqoBRKqIO/hUYjoVRygwQiIiIiIqKOrjnFts8BaAHMbixISnkEtQW3C1eRhxOAHwH8EbXTVutaCOBpAI8DGAggH8BOIYSzTcz7ACIB3A5grOXnTdaDQojOAHYCyLNc4wkACwDMu4p8iYgaFe0fjZRpKVg6YilSn4nH17uUWLqUU0iJiIiIiIg6uibXbJNSfimE0KGBddvqxP5XCBEMoMEuuAbO+zeAfwOAEOKftscsnWdPAlgupfzEMvYQagtuUwFsEEL0QW2BbaiUcp8l5jEAe4QQvaSU6QAeAOAI4CEpZQWAHy3nzRNCvCab2paViKiFov2jEe1fW1lL+7WNkyEiIiIiIqLrojmdbZBSVkkpjc2MvSClzLy2tC4TBMAHwFc296gA8A2AIZahaAClAPbZnPctgLI6MXss51rtAOALQG/HfImILknLTsOs9RsxYqQJzz4LxMQAadyclIiIiIiIqMNqVrGtPkKITkKICCHEMHsmVA8fy3tenfE8m2M+AApsu9MsP+fXianvGrb3uEQI8agQ4oAQ4kBBQcE1pE9ENyvrjqQbPklHVZXkBglERFcjLQ2Ij+f/U0FEREQ3jBYX24QQ3YQQnwA4D+AAgK9tjg0VQhwTQhjsl+Ildad5ijpj9U0DbSpGNDAOKWWilHKAlHKAp6dnS3MlIsLGwxtRaayE1O8ClNUQChM3SCAiaom0tNqWYLYGExER0Q2kRcU2IURXAN8BmAggCUAafitYwXLMC8B99koQQK7lvW73mRd+60zLBeBlu7Oo5WfPOjH1XQO4suONiOiapGWn4a3/vgUJCfjvh3rG7Xhs/q/cIIGIqCVSU2tbgtkaTERERDeQlna2PY/aAlWslPJu1O7ueYmUsgbAHgC32ic9AMBp1BbKRlkHhBAOAIbhtzXa0lC7o6ntP2GjAXSqEzPMcq7VKAA5ADLsmC8REVIzUmE01y51KSDwfxP6Yv1fA1loIyJqCYMB0GgApRJsDSYiIqIbRUuLbXcA2CalTG0kJgu1mw40mxDCSQhxixDiFktOAZbPAZa111YD+JMQ4m4hRBiAf6J2Q4T3AUBK+ROAL1G7M+lgIUQ0gA0Akiw7kcISWw7gn0KIMCHE3QD+BIA7kRKR3bk7usMszQAAmf075H45g7OfiIhaKjoaSEkBli4FW4OJiIjoRqFqYbw3gBNNxNSgtqOsJQbAZu03AC9aXu8AmA5gBQAdgDcAuKJ2uupoKWWJzTkPAEjAb7uWbgMw13pQSnlRCDHKco0DqF1zbiWA11qYKxFRkwrLC6GAAubsQcA7KfjM7IAdb/HfikRELRYdzT+cREREdENpabGtCIB/EzEh+G2dtWaxdMqJRo5LAC9YXg3FFAH4fRP3OQLgtpbkRkR0NQx6A7QqLSozRkKaNJBScWm5If6bkYiIiIiIqONq6TTSbwFMEELU3WgAACCE6AlgLC7vUiMiuulE+0cjZVoKHovrBa1WQKEAhADc3ds6MyIiIiIiImpNLS22vQLAAcBuIcTtABwBQAjRyfJ5OwAzaqdnEhHd1KL9o7F+1jQkvK6EUgmYzcCTT4JrtxEREREREXVgLZpGKqX8TgjxKIC/AUiyOVRseTcCeFhKedRO+RER3fAKC2sLbWYzOJWUiIiIiIiog2vpmm2QUr4thNgLYDaAwQDcAVwEsB/AWpvdP4mIbnpp2WnIcjkBlfoBAEpoNIDB0NZZERERERERUWtpcbENAKSUJwA8ZedciIg6lLTsNMRsjEG1qRrKaW/hEZd3MG1SILvaiIiIiIiIOrCWrtlGRETNtPHwRlScvgWmbxbAaDYiYNz7LLQRERERERF1cFfV2SaEUALoBcAVgLK+GCnlN9eQFxHRDS0tOw1//+xH4J1kwKSBWVmNC0O+Aoa1dWZERERERETUmlpcbBNCPIvaKaRdmgittwhHRHQz2Hh4I0ynhwImDSBVgEli5fsHMSnWG9H+bG8jIiIiIiLqqFpUbBNCLATwImo3RNgEIBu1O5ASEVFd+lRAWQ2YJKCsgSkwBakZjiy2ERERERERdWAt7Wx7BMAZAJFSyoJWyIeIqEOI6BoB+P8NeCgGODwNAKBWqGHQG9o2MSIiIiIiImpVLS22+QP4OwttRESNKywvhEIoYAaA/z4EmDRQ/PgoMENZ+5eUiIiIiIiIOqSW7kaah6vcVIGI6GZi0BugUqiADMOlddtqahRITW3rzIiIiIiIiKg1tbTY9iGAUUIIbWskQ0TUUUT7R+PhWx7+bd02UQOlygiDoa0zIyJqP9Ky0xC/Jx5p2WltnQoRERGR3bS0S+05AIMBfCyEeEJKeboVciIi6hAuW7ctw4CnHvgdoqMntXVaRHS9paUBqamAwQBEc4MUq7TsNMRsjEG1qRoapQYp01K4gQwRERF1CC0tth0FoAbgC+AOIcRFABfqiZNSyuBrTY6I6EZ2ad02//1QBPwHLj1eAsBiG9FNJS0NiIkBqqsBjQZISWHBzSI1IxXVpmqYpAnVpmqkZqSy2EZEREQdQkunkSoAGAFkWV4XAYh6Xi29LhFRh2PQG6BVaqEUSmiVWu5ESnQzSk2tLbSZTLXvXLjxEoPeAI1SA6VQQqPU8G8kERERdRgt6myTUupbKQ8iog4n2j8aKdNSkJqRCoPewI4NopuRwVDb0WbtbOPCjZfwbyQRERF1VNxZlIjoOjiSf4T/oCS6GUVHA6tXA598AsTFcQppHdH+0fybSERERB0Oi21ERK0kLTsNhncMqDZVAwAEBBxUDlwEnOhmkpYGPPlkbWfbnj1Av34suBERERF1cI0W24QQ0yw/bpFSlth8bpKUcuM1ZUZEdIPbeHjjpUIbAEhIVJmquAg40c2kvjXbWGwjIiIi6tCa6mz7JwAJYD+AEpvPjRGWGBbbiIissgcDGQaIoL1cBJzoZsI124iIiIhuOk0V2x5GbeHsrOXzjNZNh4io45gWPg1v/vAmajKjgHdSAJMGCg2Ah1WAf1tnR0TXRXQ0kJJS29FmMLCrjYiIiOgm0GixTUr5zzqf32nVbIiIOpBo/2jsnr4bTz6Th+/NWkiphNnIWWREN53oaP5HT0RERHQTUbR1AkREHVm0fzRWz5wEB60SSiVnkRER1ZWWBsTH174TERERdQTcjZSIqJVxFtmNI/FgIj459gni+sbh0ahH2zodog4vLQ2IifltSbuUFP6NJCIiohtfU7uRnrrK60opZfBVnktE1CGkZachNSMVBr0B0dHRl/4Bedk4dyVtNxIPJuKxpMcAAF+d+goAWHAjamXcrJWIiIg6oqY62xRoevfR+oirOIeIqMNIy05DzMYYVJuqoVFqkDItBdH+0Q2OU9v75NgnV3xmsY2odRkMgEoFmM2175xmT0RERB1BUxsk6K9THkREHUpqRiqqTdUwZQ1EZcZIbHQ7gehZ0b+NSxOqTdVIzUhlsa2diOsbd6mjzfqZiFqflJe/ExEREd3orssGCUKI/kKIaddwvlIIsVQIcVoIUWl5f0kIobKJEUKIF4QQOUKICiFEqhAitM51XIUQm4QQFy2vTUIIl2t5NiKi+hj0BijPDAXeSYHc9SLenvcA0tJqxzVKDZRCCY1SA4Pe0NapksWjUY9iw7gNGN19NDaM28CuNqLrYMW6XFTXSEhZO5U0NbWtMyIiIiK6dtdrN9K7ALx9DecvAjAHwBMAegP4o+XzYpuYhQCeBvA4gIEA8gHsFEI428S8DyASwO0Axlp+3nQNeRER1SvaPxoPu7wDYXYApArV1cDGrZm1u5OOXY2YoBisHruaXW3tzKNRj2LHgztYaCNqDXW2HU3cegRb/+ViWbBEQqE0cxopERERdQg3ym6kQwBsl1Jut3zOEEJsA/A7oLarDcCTAJZLKT+xjD2E2oLbVAAbhBB9UFtgGyql3GeJeQzAHiFELyll+nV9IiLq8KZNCsTbCSZUVdVAKmrwj/MPIvcDd3xx8gsYzUbsydqDfl79WHBrR7h5BVErqWfb0U++qALMfVC71K8JEbcfRnR0ZFtnSkRERHTNrldn27XaC2CEEKI3AAgh+gIYCeDfluNBAHwAXFpsR0pZAeAb1BbqACAaQCmAfTbX/RZAmU0MEZH9dEtD+IKnIUY+DzwUA6PfHmxN34oqU9Vla7ZR+2DdvOLZr59FzMYYpGWntXVKRB1HPduOxt3uDqiqAVEDqKvwf9PVbZ0lERERkV3cKJ1tfwXgDOCYEMKE2rxfllKusxz3sbzn1TkvD4CfTUyBlL8tvyullEKIfJvziYjswlq4qVJWQQ4zQ0BctrWzgOCabe0MN68gakUGA6DRQFZXwahS4Hgfdzw6qR/w4RF88kUh4m63fCYiIiLqAG6UYtt9AKahdkroUQC3AHhdCHFaSvmmTVzdfaxEnbH69rmqG1M7KMSjAB4FgICAgKvPnIhuStbCjRlmAEBvj944df7/2Xv3+Cjqe///+dnNBVARjSigkaD1hqWAKDIqsgiVotiDek57WtugokEsWnpDpLXl1AqS2lPUihIvQLy0nt8XpRYvRQMriAPUCEjlJpfAIqAQwRsk2d35/P6Yndmd3dlbshsS+Dx58Nj9zHx25zOzM5OZ17zfr6Sm4cIAACAASURBVPc2QkYIr8fLrf1upbxvuRJz2hAlnUrwCA8SqYRQhTu6bkZo+XygqWM3KzSNdS/M5P+b9RMW9wzz/ocTqRnQh4rRGhWjj/TgFAqFQqFQKHJLexHb/gg8JKX8W6S9TgjRE7NAwtPA3sj0bkAg5nOnEo122wucKoQQVnRbxOutK4kRcUgpq4AqgIsvvlgVo1coWsix5oXlK/Ph9XgJh8MAbDuwjUdGPkL9ofpjZhu0J/SAzt2v303QCOIVXlW8QpGIi+eYEtyyY2FJPdOukISlgTcmjf5Y+tugUCgUCoXi2KC9iG2dgHDctDBRz7ntmGLat4F/AQghOgCDgV9F+ujA8ZjebZZvmwYch9PHTaFQ5Jiq2iomvDaBsAxT7C2mprzmqL+p0ko1bu13K7NrZyORNIWbWL1nNY+PevxID03hQvXaahrDjQCEZZjVe1Yf4REp2hwunmNKbMsOX5mPIm8RTeEmirxFlHQqMdPtQ414PB4eu+YxVQlYoVAoFArFUUF7KZDwD2CyEOJaIUSZEOJ64OfAy2B6rwEzI31uEEJ8E5iLWRDhhUifDcAbmJVJBwkhNGA2sFBVIlUo8oce0PnJaz8haAQxpEFjuPGYKQpQ3recQq9p+C2RzFkzR5nutxP2frU3fSfFsUXEcwyv13z1+Y70iNod2i7Y8MUYnul6OzXlNdQfqqcx1IiBQcgIMeG1CeocqVAoFAqF4qigvYhtdwH/D5gFbAD+BDwJ/DqmTyXwv8BjwHtAd+BqKeWXMX1uAtZiVi39Z+T9j/M9eIXiWMZf58cwDLstEMeMF5YV3SYQAISMEP46P7oO06ebWWmKtkF533K8wmu3X9/yurrpVzjRNDN19P77VQppc4ik4fb805OU/2Ie2i4z0s3jiV6KhmX4mHkYo1AoFAqF4uimtdJIReR/s4gIZhMj/5P1kcDUyP9kfT4DftTccSgUiuzxlfko8BbQFG4CwLRKPHboH7oTzzunEO5ZQ0HZ+5TUj2LYD5XtU1tExtTKUdVIFa5omjpg05DUn9MlDVe7914eu+Yx7nziWYztgyk4+91j5mGMQqFQKBSKo5usItuEEM8IIb6bps8oIcQzsdOklFOllO0lik6hUOQQrVTjmnOusdshI0T12uojOKLWQ9fh7h/0JlzzO5j3FuGdA1mtd06wfcr7OAI605dNV5FaKah8txJDRiMwJZKDjQeP4IgUivaHHtAZVj2M+5bcx7DqYc5zTpI03D5NFYhna5CLf48xbxHsUmKmQqFQKBSK9k+2AtjNQL80ffoCY5o1GoVCcXRyjNbzNQM5BMgCCBcS3jYYyt5uVdunlDe/CsDcRn/f+PeE6Wv2rDkCo1Eo2i/+Oj9N4SbCMmxHh9okScOtfH4VoSYPyAJCTYLJT71+ZAavUCgUCoVCkUPyEW1WTGLlUIVCcYyiB3Re/ehVu13oKaS8b/kRHFHrUXLBOjwFIRBB8AYpPHs55aPOaVXbp5Q3vwrArEQqXRThG3vfeARGo8iGdhG1eQyZNFrVRr3CS5G3KDElVNPg3nsdJ77dJ78A3ib7PLnM84e2/XsqFAqFQqFQZEBzPNuSxqgIIYqBKwFVxk2hUACmkBE0gnb72nOuPSZ8sPSAzsQPhyHLL8Jb5+O6EZ2Z9P3p5rqXtp7tk3Xz2xRucr/5VbhycseTqRhQcaSHoUiBFbXZGGrE4/Hw2DWPtb3fLFIU4Kg2adR1M4zX50PTNGrKa9w92xK7o2kw9j96s2r3MKjzQZkfccYq5ZeoUCgUCoWi3ZNWbBNCbIub9DMhxC0uXb1AV8zItidyMDaFQnEUsH7fekf7s8OfHaGRtC7+Oj+N4UaMM5bjKdXpdn4F/joz6Lc1byK10vQ3v8c65X3LeaLW+WfrtONOO0KjUWSKv85PY6gRAwPDMJjw2gT6nNqnbe3jLkUBjiqxzU1MPCN196FXhWlqEhQVSZYs9lKhVbD1v7fy0LuVIKG4oFg9FFAoFAqFQtHuySSyzUM0mk2SvLJoEFgH1AB/yMnoFApFu6ch1JCyfbRS0qnENtw3pMHTq5/GkAZF3iJqymvaliDQRkla1TDHaKUaN/W5iefXPW9PK+1cyvRl05VA2YbxlfnweDwYhnmchYxQ24uIsooCWGJUvk0aW5s4MXHHgmqGnjDHjqRdMmaJ4/eoXrCDxsbTQXppbAxSvWAXmtaT0eeN5ouGLwBT/G5Tv6FCoVAoFApFM0grtkkpy6z3QggD+LOU8vf5HJRCoTh68PXysWr3Krs99qKxR3A0rcfqPavt9wJByAghkbZvWmvdTFqpdtbNb3sR+lp73Bd2vdDRXrRtEW9tf4tib3G72WZHmtYSRy20Uo2faz+ncnklYFaQLelUkvflZs2YSM2o8vKjK6oNEsTEF7vupfHrRgAaw41Ur6127AtdjRcpEBMIIcEbhLK30QPnmOnAdRfh2XEV/e88Hq30CK2PQqFQKBQKRY7I1rNtKFCXh3EoFIqjED2g8+jKRyGgIep8/PC7p7c9T6U8oAd0nl79tN32CA8FngJCRqjVfdPcCiS0B+EodtwNoYaEm/Zc4yvz2b+RhSENGkON7WabHUmOlKjbpbgLHuHBkAYe4aH+UH3el5kx8SmW5UdhYRirwmjEhG17fTXUJumr6/zuL7/l28bLLPb4ePmadygfVWmmA9ddhDF3EUa4iAlLJX2WHH26pEKhUCgUimOLrKqRSinfllLusNpCiM5CiFIhROfcD02hULR3rJso5r2FXPx7XvjlrVQtWHekh5X3CobxRSGklDwy8hHuH3o/NeU1AK1WQdFX5sPr8SIQeD3eduOFZI0bzIilJ99/Mu/ba9Q5o/AKr2OagdE2o6XaGNaxHl76KxrrLmq1qre+Mh/F3mK8wkuxt415fbn5tR2NxFQY3XbAafP7/p73ow2/H08wyGBWMEU+yHWHzOO5pFOJWRwhXASygFDQQ/WCHSgUCoVCoVC0Z7IS2wCEEF4hxGQhxBbgAGak2wEhxJbI9OZUOFUoFEchvjIf1A2xb6JkqIDxj73YKiJTMqwInPuW3Mew6mGtMhbjvbH8cfxwSjbcy7pP1zFk7hB+s+Q3rbZ8EbHZFK52m20TrVSjd9fedjssw3a6YK6x9ol/bP4HQji3kYfWi5aqqq1ixLMjqKqtapXl5ZKDWy7AmLsIFt+PMW8RJfWjWmW5WqnGzO/MZFivYcz8zsy2FYFopVh6vUenX5sLywPLHe1Vu1dFz3E+H6ECL0EBQS8sKZNUr61m4hsTkT2XgCcEhJEiyDMHxxzRvxMKhUKhUCgULSUrsU0IUQS8CTwAlAEBYFXktSwy/a1IP4VCcRSTSXSYVqpx3oC94G0CEQRvEKNnTatFvbjhllaZa/p37x9tvHcbLJzNln/1Ytw4yR3/U0vQCJopiuHGvG8Lf53f9ouzDOTbA3pAZ+3etY5pu7/cnZdlxe4TsWmkYEbVtUa0VFVtFeMWjmPRtkWMWziuXQluekDnTy+8Z4vqIlxM/YY+rbbsiW9MpGZ7DRPfmNh2BBpdNyPZZs6E++83Uy2P1rxIXYfp01m3oIqvg18nzJ5cM9l8o2ls/NtfuH94AVff7OH9smIAmsJNSAzHZ9rTuUqhUCgUCoXCjWyj0H4O+ICFwC+klB9ZM4QQZwN/Aq6L9HswR2NUKBRtjGz8mS4a2MiGMcPMNKEyP5SuoKTTLa063lh8ZT6KvEX22PMhpNQfqkcgkEjYcGNkqgAkcv31MMAUUrwi/2mdrbG++cBf5ze3XwxdOnTJy7Jit1FYhh3zJJJ1n67Le8TU/PXzE9rtxd+wem014Z5rwDsFwhLpCVJywVYg/4KbqyfhLmwPsSMicOm6uexgEAoLzbEczUJbxJfuPC8M+jGsiCtusPWzrfb7PqMr+GpAHzrW+flj5Fw0b+08GuquQhoFgBcMA8+Oq9rNuUqhUCgUCoXCjWzTSH8I/BsYHSu0AUgptwI3AB8CN+VmeAqFoi3ir/PTGG4kLMMpo7P0gM6LH74IpStg8INQugKBOKIm5lqpRk15TV7900o6lUSFogssEcXZLvAU8Jdr/pJ3EadNp9ml4GDjwYRp8X5QucLaJ6479zrX+dOWTcvLcmPp171fynZbZv3+9eYxPmYYXPVbGDOM1QWzWmXZllDqFV6KvEWMqi8xxZ/77jNf9SMQ6VZdbXq0SWm+Vle3/hhaixhfOk8oTPlamLwMBgWiXU4/4fTkn9+lMWLDVs5vLKew0IPHKyksgsfu/K92c65SKBQKhUKhcCPbyLZvAI9KKQ23mVJKQwjxOnBXi0emUCjaLCWdSjAipwFDJjeQ99f5MQzn6eJIR1fpAR1/nd8eg2+ej2A4SKG3EP+YaNXJ2H7Z3vSt3rM62rj4KYTwmBFtF8yncOA8xva/g/K+5a1yM2ml2TWGGllctxigXURM+bf7E6ZdesaleVueVqolTVP9ouGLvC3XoktxNGpPIBztts7+r/ebb0pXmP8BaB2x0BJKrWO1z3P+xKIEuYwqs9JDj1TUXFvD5zM96QwDA8ktq6HAgCYvDBtjRrltrt9sd4+NivZ+fAVybg3Bpu5ANzzeMN/9wX4m3dkNTWudNGSFQqFQKBSKfJGt2NYEHJ+mz3FAME0fhULRjqk/VI8HDwZGSgN5X5mPAm8BTeEmADzCwyMjHzliEQt6QGfovKF2SuXIb4y0x9YUbqJ6bTVaqZZVmqzbMp58/0nHtB/e/DUnFP0dKKC879us+3QdU/1TubH3jXkXvvx1fhpDjRgYGIbBhNcm0OfUPm0+aqTHCT0Spp1QdEJel9mhsIPr9IONB9EDel63WaxgLZHtqgLqKcedAvujbYGgvG95qy1fK9Wiv40PsxhBU1OzihKkFNljUiYpKkruw1ZeDnPmQGOjKUT175/Y5yjCkAZCSrwSCokkzIfBV2eKbbHHj1W11tg+GOPznsigVZBEYIQFCz+ZxaQzRgJt+/ykULSUljzQUygUCkX7INs00g+A/xRCdHWbKYQ4BfhPYK3bfIVCcXTgK/NRXFCMBw8ejyepMKCVagw6Y5BjWiYppJkUX2gO1WuraQw3IpE0hhtZsWuFY/7er/YCLSui4K/zJ/h+fVT/EY+PepzHRz3Ouk/XtaoRvq/M56iwGZbhdmE8PunySXji/kQ9vfrpvBng6wGdhmCD6zyJzGklVLf9+/Utrzv6PP7e4zlbXr45ucPJjvbgMwe3zs1jjDH/+IXjGb9wPPoZmCJYM4oSpK1UHJMyaUfNuaFp8Mgjpl+blDBx4pFJZ20F9s6qRARDCKIXlBKQAvxl0X7Va81U2pL6URjzzKq1cvXNeL32JyIFdBa3i/OTQtESjkRVdIVCoVC0PtmKbX8BugKrhBBjhRBnCSE6CiF6CSFuAVZG5v8l1wNVKBRHBjdhwPIB83q8GNJIWgWwqraKpTuW2u1UKaexy8vXRaglptntr53tbsd3AxJ9oLJJe/WV+RAIx7TYiCk3I/zWpDWKMuQCrVTju+d/1zEtaATtm/ZcYu1z7+1+L2mfTfWbcrasIXOHMGXxFIbMHWLv37u/cKawrtm7pv1UJHXu7pzc6WT3frkkEmUm7/sNZ//XONYseIInap9g6LyhpuB2771Zp3mmFdl9PrCEayFSR83V14NhmP9TCXPtnPjUa2tX2HxyYqEEgPoNffAYHc2qtbKQble+Sr9RK/Be8iSeW4ZTXPZ+uzg/AbbY22pCamsvT5E3/HV+GkINhGWYhlCDEpgVCoXiKCUrsU1K+X+YVUZ7AlXAR8BXwBbgKaAX8MdIP4VC0c6pqq1i8JzBTFk8hSueuYLrX7zeFgfqD9VjSANDGkmjv9yEJIefmQstiSpLx2eHP0s5v3OHznZqx8zvzLSLKGQTpaOVavTt1tcxLTbyJ974/sbeN5JPqtdWOyLtwkY4Re+2gx7QeXXzqwnTn3z/yZxHAVj7nIGRIJRabNy/MSfLrXy3kqBhOi0EjSCV75oRc2MvGpvQ9+n3n27x8lqDbsd1S9nOC5EoMxE2KIykLAKu54xMI2V9ZT4KPAUIBAWegkTRZ906CIXM96GQ2U76ZT4z1dTrbVY6a3vhywvPAezyL/br+fXRIgkePHZasc8HhYUGeEJITyMf95rGmosvo8/Yx7l4YJC7Lr0Lf50/8bdqa0KTrhO+cjByyhTCVw7O/7h0HYYOhV//2nxtK9tB0SwONh60iyhJpGtBIIVCoVC0f7L1bENKOUUI8QowFugPnAh8DqwGnpFSqisAheIoQA/o3PnqnbZQY2CwYOMCXt38Km/f/LYd/WX5mrlFI9zY+0YWbVvkmDZnzZyUxQEy+d7msvOLnSnn+7f7eXTlo83yarPQAzoffPKBc6KIzpu5YqY92Su89Dm1dY3AJRJ/nd/2pmurnjHVa6ttUSqWsAzb3nq5whJZjLBhvkojIRVYInOy3DV71zjaVkSb237w8Zcft2hZrUX/7v1TtvNCRMwKNzYQ9Eg7ZdEjPI5zRrxP45IxS1L+hrE3wAnMn5/YrkjiuahpZhrrUV5MQe7fRxjzYlISjWzzyqhnm4HBuk/Xmdv9DB1Zfi9s1aDMbxfUsI6LVbtXIRB0KOgQPf9m6pXXimybMp5eobCZPhsKs23KeM5asibt55pNdbXpAQjma3X1Ed8GiuazZs+alG2FQqFQHB1km0YKgJRyhZTydinlxVLKcyKvtyuhTaE4enDzHoNoKp9VBTBV9FfFgApmj5rNGSecEf18OMhU/9SkUSZWiuqwXsOY+Z2ZtiiUCw+3ZJ5cFj0692hxVJ2/zm9XarWwIn38dX6C4SAEBsGyyYR3Dsx7+kh533K8wmu3rYid9uwZs3Tn0pyP15CGLbDMunYWxd7ihD7r969v0TKqaquoO1jnmObr5QNwTY892NA+oh3io1XTRa/mhIiYteuX4xh5SyErSk3xeta1sxznonifxlRpyP46PyEjhEQSMkKJx2a/fqnbbmNsRjpre6Jk5I3oDGIak1mB6c8ZcWBzeLZZUZr+Oj/BHkth8IMxlWsjRM6LMnApjeHG6PbP1CuvFZEbNwKgM4jpTOa9Dzo374vaWsSeolWIj2jPd4S7QqFQKI4MWUW2CSF+C/illEtT9BkMDJVS/r6lg1MoFMnJd1SSr8yHV3hdBbds6HNqH0adO4qnVz9N0AhiYPDW9rdYtnOZq0inB3QmvjGRpnATy3YuA7DbzY02szip40kJPm1gpnneNuA2Rp83mn9u+acjqi7b7RzvSecV3mgKVZkP78dXEJr3BoSLwNtEyaitzVqXbBBC2PldlqDklq7blqLbOndIfvO6ft96hlUPa9G+EEtsFF3QCLJ6z2pGnjOSBRsXOPqlE2vT4ZZW/fCKhxl93ugEP0GAToWdWrS89kSzzmeaRk9N46ba/nRYP9+1um/8dl2/L7lgerDxoC2Uu/pLdulierVJab526WKKJEd59FoqdDTuFOWEZSFeDGZxJ7fzFGvP7cyK0i/sfh0KTN/K2PQ5B4FBMK/GPi+Km0dEIxStlNxmVpjNB1u6evlk7yCGU0MTRXgPNHFwwToqRqeJVI7dX8BMCbXWa8mS5PtQeTk884zZ9xiocKtQKBQKxdFAtpFtUwFfmj5XAr9rzmAUCkVmHOmopP7d+2c0BqtPVW2VIyXQkAYNoQbXKJN4EWj++vk583CbOGii6/TPGj6z0ztjo/WArLdz/aF62/dLILj9otsd4sG5X9xu3lDKAggXslpvZkREhvjr/A6ftpARonptdYuKQOQbPaDzv/r/puyTaz+/eEZ+Y2TCNDdftWyI9+sDohE8LlZx+w/tb/Gxna/KvrGU9y2n2FuMQFDsLbbF5UxpyflMD+jc9fpdvLntTe56/a6Ez1pFTyze2flO0nPVQ+8+5JiWUDnZ54MOHUyxo0MHKCkx0xvvu898PQajkx6u+oywLAa8hCngTmaxVAzizduvcvTr3bU3kCJdrs7nOC9eV/yn6HnTSsltRoXZfPHwlUUsFj6aKCJMAU0U8vDf0qQCWumw1v5SWWmmhEoZTQ1NhqbBo48eExVujwXi/Tjbiz+nQqFQKLKjWWmkaSgAjLS9FApFs8lnEYHYZSSLanv8vcczGkOs8Xw8EsmcNXMSbnzjRaAbe9+YM1Goz6l98CQ57TWFm+z02HsH34tWqjVrO5d0KnH4Pln+VVW1VQyZO4T1xz8O3iYQQfAGoeztZq9PJvjKfHhE4jpnkgZ8pIgXCN2I9+ZqCfFRdJ07dM5LKmSX4i6u0z/c9yGvbHwlYbrlr9dcqmqruPyZy5myeAqD5wzOm+CmlWosGbOEB656IK0nWiyWEFi9trrZ5zPrsxJpH8OxxP+2BoaryF+5vDKa/h1JZzy45YLEBY4ZA7ffboo+9fXR9MbDh03x5BjDGaMmCOPl99++nQ/OOs4x58umLwF3wRkw/dsi58XCIsGkmwY657exlNyvB3yLv13rR3ii53JZ5k/9odh02IYG2JRlheNjpMLtsUCPE3o42lbkp0KhUCiOLrIukJABA4D9efhehUIRId7QPR9RSQkpVIFBZvRBmZ+1rGT8xePTFjKwhLPDocOuywiGgwnpi5YIFJtS1ufUPjlJmfXX+d1TmCLM3xBN8+vfvT87P99JgacADDIW+l7f8npCu8+pfaLFJkp1GDMM6nwUnLWc8lEzmr0+maCVavzisl/wx+V/BKDQW2hHHmmlWpsS2Sx8ZT6EEEiZ/LcKGsGo6XoL8W/3J7Qv6n5RQr/56+cnpClmQ7L95/l1zyf9zBtb32Dn5ztTFhVxQw/ojFs4zm6HZZg7X7uT1ePy46eW7b5kRbM1hZvwerxZH2cW6Xz0/rHpHwnT9n69NyFtdfeXZqGK2HTGPy0zGH1+RN+JN+kvLzcj3URMSOKCBXDPPTAjv8d0W2JixcmM+2cTGEUAeApC/GHqrZT/a7qj38pdKwF3wVkgkKUrYMxwyg7eTL9BB+GMwUDbOzdZPDj8QS7beRmcNsz+u3jd8CtTf8jnM6Miw2EzOm3LFjNSLRQyX8vTRIS2wXRaRfOYdPkk/rH5H/YDTX2Xjh7Q2+TfY4VCoVA0n7RimxBicdykm4UQPpeuXqAU6An8teVDUygUqQjLMBLZYk+1ZDgie+L8dOSYYdQfqk8QxeKxih3c//b97PpyV+JCRFSAiL35dfueXFyE+sp8eD1eQkbIdf6+Q/t4ovaJuCEK/uP8/2DSZZMyGsOm/ZsS2tVrq52/U+kKKF2B18WEP9foAZ1HVz4KmN5tEwdNbPMX9Os+XZdQZMKNlopfFvFRBR0KOlDet5wn33/S8bsdCRPrpTuWsnTHUuasmZNV1JhbdNi6vetyPDoTPaDb0WKZioJ3zn6Wwyt+CmV+wqUruGPAHZx54plZCepVtVUs3eG0kLUiqCyES37uh598yJC5QwjLMMXeYmrKaxh70VhW7V7lSGc0QmH8/ojY5vebqX6GYb76/Wak1UUXwapV0S9/6CEYPbrNRGDlm4rRfWD+Op6eG6THCT2YdGc3NA0u3XMpWw5ssftdesalgMtDnAijzxvNq55XqSvV6bYRXrvVy/E/mUWf0S0/vvOBVqrR77R+rGGFXejh5fX1zBieQmjVNLj1Vpg92xTbDMOMkjzzzMw8/46RCrfHAlqpxnXnXWf7gsYWnlIoFArF0UMmkW2+mPcSKIv8j8cA6oEXgZ+1cFwKhSIF1WurbcHI8uDK60Waw09HQp2PR1Y+YqdbJsMqdtAYanSdP7zXcLvaqBXlYkU0SaR9I5yrddNKNW7rf1uCoJYKieSVTa8w6bJJGfUvLihO2Y4laCRG9uUaf53fjiyUUvJn/c+MPm90m76odysk4EbSlLQs6d21N0t3LnW0tVKNWdfO4o6Fd9jRkFsPtKyYRVYpoTGRpJSusL3dMv3d3ESNVFGdzUUP6Pjm+WgKNwFkJAr+6JHHWDPjIVu8Z8ww3u/xPo+PejyrZbvtJ39d91d+cslP7OWPOm9UQvTbRwc+st9b29UW+a10xrDEU2Dg80Uq+ZaUmOIImK8lke07dqxTbDMM03vrGBJCKkb3oWK0c9oJRSc42oHPA0DU0zJ2X5RIdn+5m6ARZFAAauZBUTiMXDYBlvRps9tyy2dbHO2PDnxEVW2V+wMAXTf3i717zai0UCgaIZnN+mlam90eiizJ/elYoVAoFG2MtJ5tUkqP9R/Twnlq7LSY/wVSytOklD+UUu7L/9AVCkU+Ke9bjldEbjRj/HRMnzE/e7/ey4hnR6T8jlSebW79wjJMyAgRlmEMaXA4dDjnfnTxkS+ZYEgj43Hs/Hyno32w4aDt2xaPV3jzXpjgYONBRztkhPJaWCAXZBpBtnn/5pwsL/73sdrPr3veIQpULq/knrfuafZyfGU+Cj2F6TtakaSL7zdfA4Psz2dKgrk/cNZJZ2X8+Uzx1/kJhqPFT9w816pqqxjx7AiqaqsAeP3Nww4zfOp8rNq9yp6fEbrO/Ss7Me1NeP1ZuO09c3KsJ5se0BNShOOxjkF7zKUr4Ds/hbNqOGn076O6Rn09eCKXTB6P2Qbo08eZSqpwEvG/W7q8iaraKvMY8CYeA5ZY66uDojAUSPCGwm3al6zAk/i82tXoXtfNSLQnnjBTjYNBuO66NlPsQREl/lyVL/SAzj82O1PcU1XgVigUCkX7JNsCCbcAf8/HQBQKReYkEwdyiRXZ0/PEnuYN6JhhcNVvzddI2sxb295KeWEaW+zAFu5i6HpcV0c/R8pX5CZtwZuf5Gyd9IDOX//dvCz3D/d9mLZPVW0Vnx3+zDGtY0FH6g/VJxRm8AgPf7nmL3mPMIuv/ieEaFOVR92oGFDBGSeckbbfpvosDcaTEPv7ePDYQtXWzxIj2VoquIlMhJm4yozU+QBYsGlBxsuJj2wTCKqvT1HtsJnEFgQBEjwkq2qrm7EZMwAAIABJREFUGLdwHIu2LWLcwnFc+uSlFJ39blS894Th8zMhMIjfLP4N4xeOT1/IIeKfdvFjC5i8HEZshaqFUcENop5w/9r9r6RfU+ApsI9BW5QODII3HoZtwzmw4LfoeiRNtstOwkWFpudWcXHUL8tNDOqf+/Nxe6O8b3mCaDztBTPicdAZgxx9BcIW2/xl0OSFoICQV7RpX7KKixMj2OKN7wFzHwlGBWkMA1591Xyv6zB9evrKopn2UzQLPaBz/d+ud5yr8im4uRWgSlqpV6FQKBTtlqzENinlPCnl2nwNRqFQZEZ8pcR8VE60UkB3fbHLFMpKV8DgB22hDcwoklQXprEVLy8/8/KE+e/sfIfpy0wj7ZryGgafOdicEXOTtmr6NLpPvCEnF76V71Zm5AXmxvPrnudHL/0oZR+3qIaJgybiK/NRXFAcFRMDgzCWTmLrB6c2ayyZogd0OhV2ckz75WW/bNMppAD3vHWPw+PPqkQbz3mnnJeT5Vm/j1d4KS4otsWim751k2v/yuWVzdof/XX+pH6BDlwiSbNdbvw54T/O+4+8/O6xQqVAMLb/WMdy4o+JVbtXsfekl03RfsBT5sTa22FeDfs2nc0TtU8wZO6Q1IKb3w8NDfYFjCVf3rjBfO3coTP+Oj+N4cakqbO9T+nN0puX2il/dgScw7OtgOoFOxhWPYxb9z3JsHLJjl/c7oxIskzvLYSIRr0djWQo+milGl32Xu8QjQ9vMSuMNgQbzE6RBypnfvF9zi05F4AVpTBsDPz2KhhWDnp6zf2IMWP4DG7qEz1HCAQjzxmZ2NHnMwsgxBIOm2mlw4bBffeZr8m2qVWcI10/RbPQAzpD5g5JeJiRqZ1Bc7CKXMVyJDxBFQqFQpFfshLbhBDfFUK8KITYLoT4SgjxpRBimxDir0KIa/M1yMiyuwsh5gkh9gkhGoQQ64UQQ2LmCyHEVCHEbiHEYSGEXwhxYdx3nCSEeFYI8Xnk/7NCiMTSWApFG2fFxysc7fX7Ulfkaw7+Oj+NoUY7pTMdrukzmDddvjIfy3cuT5i38/Od3LfkPoZVDzPbX0RSMNeWQ6jYvknb++/zGLdwHNe/eH36qJckVNVW2WbEWRG5ISQwiOfXPZ8yqik+qqHfaf2oGFBhi45dO3V1CIkPjftO3u6b9IDOlXOvdNxAFHoKGX3e6KT9py+b3uztm0teWv+So93t+G707to7od+hpkM5WV6sKBzrEThj+IyEiESLZPt7Kko6lSQ/lmL2s2SRpAC/W/K7jJYVf06Ij7jMFbFCpVVYIpamugHwt/nwpA7v3RadUboCTtwJRkFCBJ9lFp6UkhKQpowmiFofzb/AfPVv96fe1sC5p5zraNvbJ0bo9BSEoextO8X9ndPDvDDqTGfqn6bBz38ebUsZ9XM72shS9Dn3ot0O0bis7w4Axl401tzP5/ih5gECDz/LuYfHJHw+LMNtPuX9yp7RCqQSyYTXJrifQ2+9FfrFeEwaBqxfDw0NpvDW1JQ8ZdbvN+en66fImKraKi598lKuf/F6JtdMJmgEE/rkU/zSSjUeu+YxLjjlAnp37c3sUbNzUuxHoVAoFG2LjMQ2IcRxQohXgZeB/8KsONoJOA6zWML3gVeEEK8IITrmepARQWw55nX1tcAFwF3ApzHdJgG/iEy/JDLvTSFErEvvC8BFwEjgO5H3z+Z6vApFPtEDOmv+1SF6Yw7s+HxHzpdT0qnE9lqTSPqe1jdl//iKjrEkVOOMISzDNIYameqfyq4vdpnrtPoWzNOTNNPMIpE9CzYu4Mq5VzZLEGqOOOLmnVW5vDLp8uOjGsZfMt7R/vTQp87ImXBB3u6bKpdXJkRRBY0gt71yW8L4rZQ7S/g80oLbDb1vcLRv+tZNzLpmVkK/RdsW5STiMbYSbnz01xU9r3D9zL92/yvr7eSWTgwk7Gdd9o10jSQF2Pv13ozWuSHUkLKdK5IJlQBVC9ax5sE/w8br4eNLYWGVU3BLEsEHsGKXc70dRCLHYoW2MPDv08z3HQo62Eb8yViwcQG+eT77N7SKiMQKnbNe3ET5qHO44mMvU5YJrvg4icdily7ufm5HG1mKPh93+X8O0XhTp7mAmSbeb+sLYBQBHoywlxeregIwKAA/euY2amte56ZnbmNUfdsWLuPFb6vojY0lUFZVwQcfOD+8fLkpzgIUFCRPmfX5zGIKXq/52oZTa9sDVmr7qt2rWLBxQUJFY4tk03OBlTmwuX4z2w9sp8+pffK2LIVCoVAcOTKNbJuNKVDtB/4ADMcUvHpH3k/DrER6LZB5mb/MmQTskVKWSylXSSm3SylrpJQbwIxqAyYCD0op50sp/w2MAU4AfhjpcwGmwFYhpXxXSqkD44BRQojc5CIpjmlay1i38sVlCQJQ4ItAzgWS+DS0Xl16pbx5bQ5WipeVjhoyQqYYZRRg3kob0H+OQ3AIGSHGLEiMgkjHgYYD2Q8wiXdWsqib2Bt8gXCY1Ns3YLGRM95Q3u6b1nzi7v+yfv/6hDS92AIVbgb3rc2M4TOYdPkkvnHSN5h0+SRmDJ+BVqo5okgsWprqowd0hs4byq8X/5qh84YmHEcPDnvQ9XMSSfXa6qyO+9goMEcKUdx+1mP/D5g9ajYFwr1geCbCsa+XL2W7NZj/ej0YhZjHcuTc8c690Q4pIvjWfLIm+TnN54OCAjuyzfrvqzNnn9zx5AQvOTeawk32sXxh15hA+NIVXD3mfSpG90HbBW/Nk/x+ieSteRJtl8sX+Xymj1u8n9vRRpaiT9fjujpE488bP7ePk4N1vRx9d2w8Ea/wctZbtzFBVvEmI5ggq3hjegZp10eQgw0HE6Y5BFm/HxobzUg2Iy7SMhzzAOqWW5IXS9A0M3X5/vtVUYUckOnfjFc2vZK3McT+zT0cOszENyY2+xquLUWlKxQKhcJJWrFNCNEPU7D6APimlPK3UsrFUspNUsqNkfe/Ab4J/Bv4kRDiWzke52hgZSSF9VMhxBohxAQRdZruBXQDFlkfkFIeBpYCl0UmacBXwLsx37sc+Dqmj0LRLOJNwPMpuO1ed26CAGRIo0UXa264paH96vJfJe2/bOeypOtd3rc8aTpeArHRLgWN0DdR2Pros4/S+zrFUFVbxUeffZSyj0DgER46FnS0hZ5kkTd7v9rr+h2xN/gS6TCpd1Q7jAgMP3jo6bzcN+kBnbqDdUnnx0dfWP4xApFgcH+kmDF8Bh/d/REzhs+wp8X6I+WK6rXVtrdXY7gxQUjVSjWzSIgL8zfMz+q410o1Zn5nJsN6DeOxax5j9qjZdCnukrCfnXvxHioGVPDzy37u+j3rPlmXdr26FHdxCL9divPjmJAqKvLGkdb+HyN6NUU9BIu9xUkj+MCMznRF0+CxxxBeLzLy7UGvaa4PsPCjhby+5fWMxr/3673oAZ3FdYsd061jYMeCakRTEK8BNAXZscBFaD9WxJAs13PQ6Wbk9aAATF5mvlpCR4OIS2suOMRZXc5i9QErdc/cd1/aflFOVyHXnN/1fEf7nJPPcUbH+nyZVav9Mk2VbE2De+89evetViTT9NB8VG+28JX58HqiXo+rdq9yfdiTjrYWla5QKBQKJ5nc/f4Q81q2XEq5L1knKeWnQDnmFdIPczM8m7OAO4FtwAjgYeBB4CeR+d0ir/FlCz+JmdcN2CeltK/6I+8/jeljI4SoEEK8J4R4b9++pKutUACJT0rzaaw79vqzXQWgVbtXMXjO4JwJfW5paDOGz0gw9bVI5VejlWqZ+5GkiHaJZemOpRmtrx7QGb9wfMo+YPqZ/WHoH6gpr2HG8BlUX19NQc/3XMfyyuZXXNez/lA9HhGpaik8jsg2R1pcRGDYd5L797SUyTWT0/aJF9QMaSCRzS4g0RrEbk+LxdsX5/0GI0Fcjfir7dt0tmPytGXTUn6PHtC5+/W7eXPbm9z9+t30ObWPaQzv2OeHM+n7ZqGQGcNncHKHkxO+53D4MCOeHZFyWb4yHx0KOtheavkSUFNFRVaM7sPAkZbIHfnT23+OPb9zceeU3737y93JZ1ZUwLJliDvu4J/Dyhh6s2muD2b0a6aV/T479FlC4YpCT6G9vV79bAUeaY7eK+FDw11oV2JIIuV9y7l8l4clc+EPNbBkLowP9aOqtoq9F1rel+Z+UXD5LPYd2kdDn/mO6Vff2Njaw86KWdfMsitte/AwrFeM4KHrZhEEGRdh6fFE044t/vpXVfiglagYUMHAHgPT9rvzkjvzNgatVOPWfrc6pjWGG5M/YEhCW4tKVygUCoWTTMS2S4H3pZQfpOsYqVRaCwxK1zdLPJEx3CulXC2lnAM8QlRss4cQ1xZx09xySuL7mB2lrJJSXiylvLhr164tGLriWCD+SemNvW+0RZ7xC8fnVgwo1ZOKUWEZTm7QnCXnlJzjaFtpaFeVXZX0M2EjuaF1ed9yW4iySBrtliLaBbDFjvDOS9Kur7/Ob3vPxWLdIFkUFRRx7+B77agErVRj6c1LOaP3rsQqrNJwTSX1lfko9kaqWnqLHQJHcUFxQv83t73p8I3KBXpAz8hrZt2n0eioyncrbYPotOb0rYRbaoybYBSSIS575jI6PtCREc+OyDqdprxvOUXeIgSCIm9RgsE/wJknnhltuPj4Wez4fEdK8dctim7sRWPNmZF9ftJ/D3ZExkwfPt31uxZtW5RyPVN5qeWSdFGRK187j5vu+JiTTz/ABaP/Ad+eYs+7pf8tqb87XeqrpsHjj/O7759qC20WmXrULd25lGc/cFq3fu/C76GValTVVtHtHVO0s2KTBn6Qn0IT7YIsCyRopRqzD1xBcRi8QHEYBi3ebD6MuvgpGFUBp6+E81/m5/9xNV06dmH7t5+i1+UV9Dr5n1ww5G7+5/EhKZdxpNFKNZbdsozR543GwOCJ2icYPGcw6xZUmdto9uzE9NHhw+EHP3BOk1IVPmgl9IDOqt2r0vZze7iTq+VPXzad/t37U+hxVqldsGlByiJM8ZR0KsEjPHiEhyJvUZuISlcoFApFlEzEtnOA97P4ztrIZ3LJHiC+3OIGwLoDsh41x0eonUo02m0vcGpM6qnl9daVxIg4hSIrKgZUMHvUbK4+62pmj5oNwBXPXMETtU/wRO0TzUoPSMb89fNTilG5qOCmB3T+9u+/OaZZaWipUisMDCrfrXS9WNRKNX7wTecNxi8v/2VSwS3pk+c4sSO4Y0BKcSjZxecvLvuFo+32FFsr1Qj8POD6+Tlr5iT8pqkEjmJvotgmkQ7fqJaiB3Sm+qdm1Hfmipn2Z17Z6PSmSZYmmy33vHUP5zxyTlY3D9aY3FJjtFKNbscnBCIDpriyaNsipiyeklU6jVaq4R/j54GrHsA/xu8qSs0bPS+6nybx8bOwtmumxJ87YtNmrfndj+/u+tl0URBaqeYQkPNFyAghkQkFOSyee/wM6nedzPqXv5uwriUdkxvgZ5r6aguWMez9OvN9eMP+DY72R/VmNN7T7z9Nj7jsvlMO5qfQRLugGVUxG+NEz91f7qZf90hVztP+DZ98CzZ9lz/dcQ3f6/xnALZ/+ym23z2SLcNmt5u0uNiqz2EZxj9vqrmN4qPavF6YOhUuvJAEjtYqtm2MlNdHMVWhDzYm+vG1lFiP0AmvTSBsJBaO+uPyP2a031tFFqzz7l2X3pX3c71CoVAosiMTse1EIJs8yv1Ars1hlgPxRQzOBawSjNsxxbRvWzOFEB2AwUQ92nTgeEzvNgsNs6JqrI+bQpER8ZE3fU7tQ6fCTvxuye8Yt3CcI5qqMWxW28z3jYMHT0JEVXNwqx4a6z+WioMNB6lcnii46QGdlza8ZHujTbp8EoBr1BlAh8IOvHvru4w+b7RzhovY8UTtE1lt2xMKT3A14U9Gv279EqYlS9lY9+k6/HV+R+QYwA+/levseieWQPXWtrcy6r9x/0Z6PdyLyTWTk/4GLeGet+6hcnklWw5scd0fUpEqNeZ/fP+T9vOHQ4eZ/Fb6VNpM0Uo13rn1Hfqd1i9lBU2ATfWbku6L5X3L7UiGQk+hHUVXMaCCf/74n0lTraf6prpOr9le06z1ySWTaybb54qwDKdNYY5f18FnDk7aN9Ob3YoBFWmrJUMKAT+OA4cPMH3ZdDoUduDp/uY0WzIZmyjsHTM0oyrmiYPMPjKm/UXDF2Yj5lweDgq+2Nif0edHz/eOB0e6DtOnt8lUyztfS3xQ8/JpB8xtFJsu6vXCrFlmRKa1LS2khAkT2uT6tVuS7DNJr4/iHuT98cV3cn7NFhvdHDSCrn97JTKjB6b+Oj+NoUbb/uHP+p/bjTitUCgUxwqZiG0dgaYsvjMIdGjecJLyZ2CQEOLXQohvCCH+C7gbeAxs77WZwGQhxA1CiG8CczELIrwQ6bMBeAOYLYQYJITQMKusLpRSbsrxeBVHObGRN755Pq7/2/Vc8cwVLNi0IGlExaJti1oc4aYHdBZtW5R0fqfCToz4Rmovp0xYv2+94wkvRFMqyvuWJ6RgujFn9RxH2xJQJNI2bH905aNJP79271q0Uo2X//tlW5gDkoodycQVt4vW8QNNDzc3E343Zl0zK2GaRCZctKcqlDFj+Axu6nOTo6KrQFDsLXZNXcwWa/tmKpxJJHXrurH0ucvM3zjm904WPZYNc1fPTdlOha/MR5G3CK/wJqTGVAyoyKgq7tKdSzMS+NJVI7XQSjVmXTsLUboypaegIY2UN0pCCAQCkYlpeoSKARVccMoFCdO/avoq4+/IFxv2bUjZTsekyycl/T1fWv9SxufLdPvE1WddzcrbV1LkLUrZD2DLgS3ct+Q+3g28y1MXQ8Uo+OfZsHTKTaZX3NFAc8SrZhSCOHuHKayJuDbgci5/m5HfGGnPNqRhPuTJMn21tVn/aXziBRzod765jf7wBzOVdNo0WLYsuv9oGtzq9OwiGDQ93hQtR9fhyiuRU6YQHnwFC+bck95iIO5Bntx+Zc4tFeILTyUjkwemvjKf4+9IKhsPhUKhUBwZMiwPeGSRUv4LsyLp9zArnj4A3AfE3gFXAv+LKcC9B3QHrpZSxiaB3ASsxaxa+s/I+x/ne/yKo4/4yJsFmxaYIkecQBWPW7XDbKh8tzLlMr4KfsWCjQuyqtTpxo5/94jzpdLsi79Yj5pUN7j7Du1L8NuKFVAONh7kcOhw0s+f1PEk+/2M4TPs9NxkBRSWB5a7fk98dIwHT2K0XBq0Uo1OBZ0SpsdHrz288mFH++n3n3a0n7vhOZbfupxpV01j0uWT+PZZ3+aRkY/kJPXD2r5uv0mXDl3M6qqxxD7Fn7vE/B/5vfuHWm4MHZLOlMJ4v75UpPMbu6THJRl9T9V76YuFpKtGGou/zm9Wm02Rxi0QSW+U/HV+wkYYicz6xmj9T9Yn/LYSmdVx/vnnOjt2TOfzz3MnVsSLgFY702VppRrLb11uRg3GseXAloxTglMWUyAaHThx0MS03yWRhGXYTs966mIY+WP4m3ZC2s+2C3Sdd674JdOmfME7V/wyvXgVK8w1oxCEiHst71serUQbcy7vfM6HZpGZyKWph0iRmWakr7Ymbg+fZl07K7qtKirct1l5uRntpsg9kycjQyEE4AkbdPmfSqYsnsKQuUOSn+NdHuTlylIBzAc78SnryYi/tkhGTM03DIyMMxAUCoVC0TpkevdzsxBicSb/gTH5GKiU8lUpZV8pZQcp5blSykfiK4tKKadKKbtH+gyRUv477js+k1L+SErZOfL/R1LK3JsytDJuRuKK/OIqbKQwTo+lJRdvm1afnLgMF/GtpSb3YsdQxxPe7vU/cAgeVsTZyR0TKyXGjid2DPECin+7P+UY7r3iXke7YkBFVCRzETvCMuxqTh9fldAgdeRRMiZcOiFh2vhXo8Uv9IDOxn0bHfN7nNAj4TNaqSlcPrryUWq21zDxjYk5OXat7Xv2SWcnzHvth68x/Kzhzonx6bjhQvv9aj11lch06AGdzw47jeSPLzq+Rd8Zy8rbV+Il/U3qwcaDaavVrvjYKZit35888sBX5stKNHT7fKpiAun41eW/SpiW6XH++ec6a9cOY/v2+1izxsemTeNzIro9OPxBhzjy4PAHHctau3ZYRoLb6jtWu0bvHQ4dzmgdTyw+MeV8y9/OijBNhVXkJJMI3vbIorFPcLXxJr/lfq423mTR2CeSd9Z1wlcONiOErhycfVRZeTkUF4MQ5mt5OVqpxpIxSzil0ymOc/k/Nv3DLDJTECkyUxCxRGhG+mprcsnpTvG/32n9MnuAomlmWqnXa26foiJzeylaztatjuZZkT9HQSPorAweS+kKPDdf7XiQl4sobzCj3ofMHcK+Q5m58sQ/qHOjem11QiT761teb9b4FAqFQpEfMr1rKAN8Gf4vy83QFJmQzEhckV8sYWPcgHHRiWmM0+1uB+uavdzzvhrnXMbacmd00sJZtuj21PtPNXt/OPNb2xxPeM/p/7FrvwS/pTjB8a9v1Dlmxxq2dyhMzDYf2GOgbZ7u5l816fJJKdPA3C5Qux7nrCbsFd5medq5iViGNOybeLeqp+eecq7rd1leK2EZpjHUmLPUD61USyhgMbDHQLRSjc4d4gS0+Kf43qAjnasluK1PNiJzJqmdv7j8F4kfdBGepy2blvRhhB7QWbPXKcbuPLgz6bi0Uo1fXvbLlGNP57cjI+5VErfi2KmZMXxGgqhUsy0z37aDB/0YRhMQRsom9uyZnZEQlgkF3oiA6C1IWJZhNHHwoD+j74k/Vi2eXv102nNZbCSsG7GRb8/d8Bzdjkt+E/3TQT/l/qH3JxRR6d+9f8pltBfe3l5KE0WEKaCBYp7bkryA/LYp4/GEwmaEUCjMtinjs1uYpsGSJfDAA+arFq32XOApcHQ90HDAPaq1GemrrclN33KKt+MvyWIbVVSY6aUPPGBG7LWxdWu3RARZ6yzrL4vOWvvJ2qQfE2c4H+Tl4pjXAzp3vnqnWfE7TfaDRZORjXtPlN1fpI7wVSgUCkXrkonYNrQZ/6/Kx2AViaQyElfklwQBI41xusWaT9Zw2kOnZV2hEeDcAbsdy/AIb4z4VgzvVdgRbyEZ4rJnLuNHL/0o+5U7U3ek95x8nrutocNLDRIEx8839kt6k/xF4xcJ07p06JLSKN6qHDntqmmuZuduF6hWZUGLc0vObVbaZrInzQs2LaCqtso16ik+qs6ipFMJRmAgLJuMERiY09SPeE8YK8IsYSyxKVw3DzX/X/VbxJhvUz6qZQWl3dbnq+BXaaPMLDJJ7UyoVJkksnTH5zv49eJfuz6McPvejoUdU45txvAZdCxI3SfZ79mSNFKLw0Fn6vWOz3ck6emkSxcfHk8R0WQ+iWE02kLY7t1VrF07gt27M/uNLNzWKbosLx5PEV26+ByfSbas3qf0dl1GJpG68RVJBwVg8jLz1W1+eb/kEURr9qzh3sH3OvYxgbB9K9s7Db11vIQwJV8PL4Ru4UePPOba98RVTmHCs/kj134pSZJ6enKHk13brlV0m5G+2lrUH6q3z/0e4cl+P7EKJvj9bc6Prt1y4YUYmGc7A9hwanRWqgcdwuNM1X/9o5ZHitkFpzLMfoDUD30s3IRAt8rMCoVCoThypBXbpJRvN+d/awxekdpI/FimtVJrX1r/UrSRxEvMjU+//jTrCo16QOdPgf+E7/wUzqqB70yk88AFpviGVTnUmxBV9/y657n0yUuzWs47O95xpPckiwLRSrW0xQvcBAU9oLN5/+aE6Tf2vjHt+KwbsZW3r+SME85wzFu7d23Cbx6fynleSXxh48zo0TkxJdRi/vr5rlFPydZn9aoOjovu1atyU1NGD+h8/KUzCtGKdHMdS2w6buT9+f0PtNhDbvWe1a7TM0mNyRRfmc8peqWILJVIGkINGYlbF3W/KG2fuy69K+X8Oxbe4SoslnQqwSM8eISn2efr+MIKmRZaOPFEjb59a+jcOTYa1WD37tns3l3F5s3jOHBgEZs3j8tKcHNLjbWW1avX/XzjGzM5eNBvR9ClWlZ53/KkPpDJCs9YVAyosCOlpr0J7zwND9TAkrlQfuicBAHf7fxjYR0rH+770J4mkRlXR23rfPLr7vQ7bQ4iIkeE8fLXVxIjYpYNKePkQ85p+85IHUGYDT8d9NOU7faCr8xnpx43qxp4fAGIqqo2W3m13eDz0VQIQQGNBc7ItliKvcWOdrzdweq97n/LssGO6o79GxUqAv/vkgpunzV8lvbhVKy/IZgPK/qc2qfF41UoFApF7mgXBRIUyUlnJH4sEl8pdPzC8XkT3S49I07EivMSi7+Qiye+YmcqqtdWE955CbzxMGwbDm/MZODpA01h7+Iq8DYmjapbtXtVxkUT3HxAElIQY7CKFwzsMZATzv4wQXB89oNnHcKn9fscCjnv4s45KfGGOFsk0k7rtJh0+SQKPYUAFHoKE6PxMmTSZek/Z22LVKmwAHs/PN8hDO398PxmjSme6rXVSZ/aVwyoYPao2XQ7rhsdvMnFvc31m/N2vHQoyExULO9bbnsiFnmLXKu1Wuc+28cvTWSpRCZEnLl9b3wkpBszhs9g0uWTOP2E0+nXLdHYXyK5Y+Edju2oB3QmvjHRNt2/69K7mnW+jvcQysZT6MQTNRobnRETjY072Lz5Dse0urr7s0ovdUuNPfFEjVDoIJs3j2P79imsXj2YrVvvYds2pxfjrl0z7fdaqcbgnnGp6dGFpOXCrhdy23swebl5ceMBisNw67qChL7JCioM7DGQigEV6AGdF9a94JiXzmeyvXBh1wtZNaoaWRD9m2GULXY+/NF1Ll9qRk0KzM0vgedHnJ6zcVjnpHTny7ZOi6/DYgtANDbChAlttvJqu0HT+OfsSfz2Khg2BlaUunc766SzHNcH8fvgjs93ZByRnQz7HF3mB08I8+Go17yOSxHh9rM3fpbyb7GvzEeTxJi+AAAgAElEQVSht9Bub9i/QdnJKBQKRRsja7FNCDFECDFFCPEXIcSjkfdD8jE4RWa4plwcw8Sn1s6unZ1wAZKryLcLu16YMO2CUy5g2lXTePfWd7ml3y0pP98YasxugXHRO5trezB7/C1cffcCTr/rx86oujhvkKU7lib1v4rFLYIkWTqkRcWAClbevpKHrn4oQXDcsH+DI43P+n3i+eXlqb2w3OjdNTHt7JXNrzjWUSvV+NkZ/8c3Pnyan53xf80+TrRSja6d3D2l3tr+FnpARw/o1B+qZ6pvasobx24XbnQIQ90u3Ji0b6boAZ0nFqxN8IPp1z0qBlUMqGDPL/dw+DeHk5rEh2U4QbB0W5bb8VNVW8WIZ0fQuUNn+wYmlj1f7sno2LPShR+46gH8Y/xJfzOrUEeRtyijyNL4lCCtVOPKnlc6pqWKYIxlxvAZ7Pr5Lr7X+3uu8yWSyW9Nttv+Oj+HQ4eRSAxp8Gf9z806/0wZPCVlO5b4iqC7d1fR2FjnOtpYmpp2sWbN0IwEt2Spsbt3VxEIxO5HYQKBSkIhZ+GMQ4c2OKLb4lMLLTIRFR+/9nHGRgJRYuPjvmkkHrfJ0q1q99SiB3RX4dqt4El7xFfmcz1eKpdXmsKCrsPUqYBzO67pBsVX+nI6looBFSmtA9oLLboOiy0A4fGYolsbrbzanhh9ywxmDeucVGgD2LR/E3+55i9Mu2oab9/8tqs3a0sjshPTPSNHVRp/30OhQ2mv2YLhoP0+mwhuhUKhULQOiY97kxAR1B4HrBysqPGLOX8jcKdKIVU0B0uE8ZX5WiwaWqm1DaEGZOSf5WenlWp2ZFVTuIkib1GLIgLd0op+/K0fc+/gaPTGnDVzaAy7iGqBQXxR52MEU/nnvVPTLqtzh87R6J2wBG+QA91epmLA62Ykhk/nsmcus7+beTWmMOdtsm+mLP+rVOvrljKaSXonmDdOP3ntJ3b0jkXsb+Ar8+H1eAmHw/b8FvshBQaZF6xlfozSFY51vGfOAiorroZwEZUvN3H2SeuoGN28VItb+t/iLkRJM6ps3tp5Ge1X/Qc2mL9JZMz9B6YWZdOhB3RGTJ8K895K+M0317unyz13w3Oc3vl0nv/geQxpsOerPfY8S7B0G3+y46eqtopxC82CIYu2LXKkt1h8dOAjrpx7JWEjTJG3iCVjluTkIUGPE3qYhUesdNgkrPkkUTR+cNiDDJk7hKARNCMfM4hgjCVVytg7O9+xt2P8uSJkhOxzUjZYosT89fO5sfeNSUUKqyKoYTTh8RTRt28NW7fe69rXDSlNP7cTT0w9Put8a+0P1vbYvv13GS9rz56n6dHDXI9kotqXTV+m/R6tVKP+m1fCx0sd00t6JYryFQMqmL9+Pou2LXJMD0tTMHQr6JGs4El7w0r/r1xemXC8/GvqOMa+JvAa0o5oAzMWZ8K1cF28V6Ki5VgFIPx+OHgQ/vxnc3obrLza3jCkkXo+BvWH6u1rtqn+qQl93Io5ZcPzHzxvvqnzgVGAGecggXBKf1+AxnAjlcsrefm/X06Y55aF4BbBrVAoFIojR0aRbUKIG4E3gfOBPcBfgRlAZeT9HuAC4E0hxA35GariaCXXFVVjK4VaPiqxN4G5rAT5VO1TCdNib761Uo0lY5YkClgxRrmLfjuJe+YsSLus//v3/yVEI/S9OJqKqZVqzB4122y4+VdFIt1qlh5y/X6L8r7ldlSSQDDp8klZRR24RfsB9m+glWpcc841jnmW11O2dD2uq6vpsHWjrAd0/vj8vxzb4umXt2a9HIsZw2fQqaBTwnQrlaMh1EBYhtM+Xa4/VI/nzFUw+EE8Z65qkdCoB3R883x8ufmimPUssp+Wp6pOZkVnzf/efIdXliENKt91j26LPX4aQg22cX3803/HTUBMlGXICNmFD2Ijv+LXKZtzwr1XOEUkt6g6wPW300o13r75bTuyIVvxSyvVoqmsccRWJo1PQRSIZntsZhINFF8RdOfOSsLhz5L2d2P//vTnJbcUut27qwgGM68+29gY3UeTpaw/v+55qmqr7OjJZKldJb97EOn12mmPTR5YN8K9ouBU39SEaVa1YjfRL12Eb3tixvAZTkE8MIjShZMpXzgIj2FKbAI40KsbVRcLhtwmWNOro/KFzReaBiUlptAWDIKUcMklR3pU7Z4Tik9IOT/+POxWETlZtG2mbDuwzXzjsDpoNO0/0vj7QrQIUzx7v9rrWt20NQu5tJY/skKhULRX0ka2CSF6APOAEHAX8JSUMhzXxwOMBWYC1UKIFVJKVX+6lchlVNiRwK2iakvXQyvV0Eo1yvuWJ2ybkk4lthBgYDT7KaAe0PmswXnzWuwtThi7Vqrx0vdfikadQZwYJpnz8nZmpAlusj2GYqJ3Hhz2rqOPdfM9LjDHEQFHx/12pNtHbzdRdVnq6C4hBAJBobcwqZCQjDsvudOOcIpl8JmD7cjChZsXOub9TPtZs37zfV/vS9iW1Pn47LC5Xfx1fmTZYvD+2t4WPfokN0bPhLIuZazf76z4OfIbI+ncobPDuyqVmbplqB0fDdQc7LTcjvtBegFpvnbcD2RenSw+ZS6ZSBd7/EgkVe9X0b97/6QeWMmiLAGW7lxKVW1VgmiU7TkhPtpr64GtrhGIbtXbcnH+HHnOSBZsShSmYm/k4qMjvtXtW3k9X1sVQa3Itq++yt7o+8svV7FqVW8GDlyfsp91vrXYsye7tKtwOFqZ2CFKxkSsUrqCacum2dVXrYi0BMFR03ju0ds59MwTpsdYPw/XltTjdrZzE5RnXTvLXpeq2iqHaJxphG97oUuHLubfsMgxuitUxAiaqGEYGiuQwMl9B/GtRyYxqs7PQ+30GqNdoOvwk59AKBIVLiUsXQpDh8KSJW2yCmt74NLTL3U9N1vEVxDf9/W+xE6Z1aBJSu+uvdn15a7ow9KYc5rFHQPuoHOHzkktHMa/Op4+p/ZxHn+7NJg3wfG3tbhsdasJ4rnMElEoFIqjlUwi2yYCnYCbpJSz44U2ACmlIaV8Ergp0rd9lpRqh1hRLb9e/Gt883zt8ulSPiuquvmo1B+qty+wPMLT7KeAbpFL/9n7P5OOw446gwQz9/CZNSmXpQd0mgynz1mngk6uFzYVAyp493f/y5X3/T7qx3P4FEd018N/Sx6hkcyDKVOSbU99l+74/li6NDM16cbeN7oa41sijq/MR0HP9+xoQO/NI5j0/SQG7BniVjHvH5v/wcJNTgExlZm6Vqpx16V30atLr2Yb5VvYYvHhUzCTvYT5evgU2+w9Hf46f0IVyGQiXfzva0iDCa9NcKShOkhRJRRMgSye5pwTYqO9ku1PL6x7IcG7MRdRtcn2+Y6F0WqpvU9xpjIOOt3dFDtXxFYE7du3hlDoQLO+59ChDWzdmnnVZHBGqmVCScl19nvbF80lYnXH5zsckRzJvJTOGVXOz0d35K7rvLxflrw65Kb9mxztnif2dBwvBV7zeWRzInzbA9OHTzffRI5RSQFNFOLHF+3UrZvyhW0N/H4wXFIelW9bi4gtkOSGlTZu4SqoZ1CcJRlVtVXmgwHrvAUOT1uP8DB71GweH/U4M4bP4MTiE12/x5BGwrVYt33fd/xtFXVDeWTkI612nLo9FFMoFAqFk0zEtu8AK6WUiYYBcUgpFwArgZEtHZgiM6rXVtMUbrI9sdIZm7dFWruiqq/M50iTtMSKdOlJ8cRHLl1wygU8d8NzSftXDKjg3Vvfpfvx3RPSQYOnL036OcBO1Yvl4h4XJ+2vlWq8/dsHEYNnmMuKE6TWHz8r6Xr6ynwUeAoQiGaldyaLFPw6+LUpDpf5Ep4mNze6sGJABX0vPuxqjD9//XzWfbrO9GwpXYHnykpm3fHjFu9fFQMqKOtS5pgWluFoqkiEeHE0lqraKiqXV7LlwJaoKXkzmfWvWeabMj8URH7jgia69l7PyttXZvQdvjKfo1Lo1WddnVRYcPutgkaQcOJzGAA8vZalrBLqdnPT0nOCr8xHx4KOCdMl0hHNlKubBV+ZD6/wJkz/Ovi1XQU4kwqruebEEzV69ryX/fsXOKLHLE499Sa6d7+DkpLReL3uxT8APvnk+YyXuXXrPTQ17UqYftJJV9O9+x10734HnTpdEJnq5dRTb6J37+h5064WnCwVPkaA67BnqOsYMt1/zjvlPEc7NvLRX+e3vSeFEM1+INCWqRhQYRZKifx98BCkiCA+/EjAEEB5/vdTBaY3m8flkrygQPm2tYBYm4BkBY4+3Peh/b5iQEVC0ZxsKj7HM3/9fOd5q3oxd5w6j9mjZjPtqmm8c8s7jr+1P/jmD6IfjksRjb/mLB/dE2+hYf9tlWV+5q+f32oP3fP5oFyhUCiOFjIpkNATSDSmSs67wO3NG44iW+IrR/5909+TGpvnC103H7z6fG0v0+Get+7hpfUvcUPvGxh93mj8dX5KOpXYN1FhGebu1+92pJ0lTU+KIz5y6YSi1N4gYF74zf/efDOlNCYd9Msmc6xdirtknM724PAH0/Y5+6Sz2XJgi2v6wswVnyddx9h0yGxJFuVjPZn1lfkSTItb4jHy+LWPc9knl7n6ntz56p32sgxpsHpP9ql0bpx54pmmIX8MDeEGRztVpdn4iJyZK2Y2O2rGjs5x/MZv8/df/Snj77Ai7WKPAbf0TohGhlrbVSAQQiQ1oi7s+R6NSVJnwKyS67ac+NTEbLDElslvTWbpTqeQHbsPJDP3b87yrjvvOhZsTExXChrB/5+9e49vos73x//6JG3K/V4pSLCCiKIIWFQGFQJl8cbur+r57rqLFsFj8HZWd90t4q5HVxQo6+7icRWpuqv1spdzUM/RFVEqEYQBlNvigoJCocpFKPdb0ySf3x+TpJnMJE3aSdqkr6cPH+lMpplpSZPJe94XeKo9mHn1TDxz3TPhUtd0vkZ/880zhnU5Ofm6IBegDVXYsGG0YVuv91scPao2OiwBAL799jnDOputE4YNW5LQsSpOBf0698M3UcNgUOgxlIz3+C52i9hEnj9lo8vwj23/MB2O0bNDT91rR7Y2HX/tptdQc2wslqMYZ29yoXK9B5cHVsMngN2zyzCwtb2pZzNp8n4rmlnDSOHXgiN1R0wvSH9crZ/rNnnoZCzf1fC+YdZ+ICmRr1s+iS2f5WPB3eY5CaXDSrFw3ULImisM7Rfe3fYuyieUN/xcCvDg8+9h3utrwu+tH+4QWLF7RVouXIfeZzO5jQ0RUaolktmWCyB2ioZRPQDjJX5KiejG+9GZG6mmqkBxMfDII9qt2oQLare+eStG/+bnePg3x3DV47+07KrcrW/eqsseGv2n0fjVR7/C3e/ercvC8fq9eHPLm7rvNSttixaduRQvkymS4lS0bIIoT618KmY5W3TT8MlDJyd0YlN5Y2VDeaBzta58YevBraYZVc0tI3UVukwnUQLaB9iHlj5kCOLF62/WGMWpYHjv4Yb1Ow7vMGRbmU0YbIrokkAzg3sOjnlf3y59dctf1n7ZpOd9xboKfZAv+G88aNjBpE98o5u/x/obCPWbsws7cmw5uKzvZXF/1jp/XcNzDzA0c3598+spuRKvOBVce961hvW7j+4O78/KrNqy0WWGUtyQI3VHoNao+Onin+LDHR/ip4t/mtaSfynPGNbZbHmGdV27KhgxYhUAh+G+TZv0Q00qKoBrrtFuIwUCpw3fK0QipxoNfnLJTxqCx0UvAsNf0e6IytAtuOiLpB43WqzhGKoKLKo4P/w8bfa05FZubvFcOArXo2bSXPxq6hq8ccsQfPHmQgx8qLzxbyZreDzmwbb6eqDSmNlOySufUG5aVjqg+wDdcvRFuaZepFNrVHy440PD69bXXf4U83sUp4LnJz1vmtlbfbjasH2387Y2VDAA4eFD6SrpZIk5EVF8iZwB7wVMewvHchEAaz7RUqPMSpHiTR+0msejtRTx+5vWWmTG0hl4/b2vwyn2gZc/wMTZjzZrupFao+LGv96I1zcbS58kpGFUuk3YcNMQfYZEIo2w9x3fF3c5HrMsuAACMcvZogcKbNiX2Mmf4lSwctpK9Ovcz/R+q/plRe/zB4N/YHpf7alafHHQ+AE5Xn+zRBR2LzSsG9B9gKG0rznlIJFKh5UaSmGjXTcodjV92egyw/c35eT4Mc9jpuuPnEk+eBn9PbEeQ3EqmH/tfBT1KYI/4MfaPWux9eDWxndg0oMrxKxM2gpmgV8JqctusOrDguJU8Msrf2l6n2enB5WbKlHnrwt/GLLqZz56VMWuXXNw9Kj56+WePRUwazrUu/dPTLfv2lUxDY4FAkewZ08Fdu2ag8pKFdOnAx98AEyf3hBw047BWE4c2ZMtEeUTyhtKuTZOAdbdqT1nAF3/xdJJg5J6XDPR//6hC0gfvnh1+Hna2MCTTKc4FXimeDB7/Gw89ehK3PaXf2FoSXb1p2v1XC4gL08rJY0sJ5USeOGFpl3JJIPyCeX4+PaPw+cGdmE3VAlEX5TbciD+gJhY5q2cp11YjGobMvmGAXG/z13kRsHFXxraL9T5jdnyrkIX7Db9eU5oojIREbW8RIJtywF8TwhxQWMbCiEuBHBN8HsoDRSn0tDjJijR6YNWcLkAhwOw27XbRFuLhMaFP7PmGcMVvBPbi/DwRw83aeCDWqPi6j9fHXf6VLRbLr4lfMXzvO7nJdwI+2T9Sd3yGZ8xeyQZIvif3WY8UTrpPRl3OR7FqeCey+4xvW94H2NGmBXN+82CWqETwK7tjA2Avf5kkmdNmCQEVO2sQvG5xbp10RmCTaU4FfTt1DfuNvEyYRSnggU3LECuLRc2YUOePXYT95DQ30zk38TRM0dNt72w14Wm6+P56tBXuuVYATS1RsUD7z+AtXvWJlxmfHbns+MOSjDLODT7eZOlOBVD1gLQUG5vtfIJ5drPGqVdTjvLsiojHT2qYtOmYuzc+Qg2bSo2DbgdOGAMqOflDcLAgbGzloQw7zCxbdvd2LnzERQUFGPIkIZ9zZ+v3R454jF8j83W2VCumoi5xXMhqscZnzPBLMk7/7+LU5JNEbqAJAN23fM0OvMz2zBDpYUpClBVBTzxBOCOOv/w+5ndZiHFqWDF1BWYPX42Vkxd0ehzfvnu5ZixNLkhMUDEBPmIqco251pdKWgsPc7/0tCLNiADhvctxang2euf1QUP/3j9H/l3TETUSiQSbPsjtFLSd4UQMWungoG2d6CVkD5rzeFRIgZ2H9hi+w6dH86apd0m0t5FrVEx7pVxePijh3Had9p0miSgBWDu+Yd5kCiWeSvnxWzUHstfP/8rZiydgT+of8COIzvwzJpnGv0grtaoOO49rlt3Se9LEt6nWUaiDP5nVoo2omBE3OXGuApdpo977IyxaboVzftLh5Ua9ieDJTLd23U3bJ9oCW4y/NKPtd+u1a2LnhjaHIfPxJ/u2FgmzNCzhuKOEXfAfam70RLGWFOHr+p/lWFbAZFQP79o0QM3QgMtooWGCiTjpPdkzL9zM1ZNCQWAo3XGgKSEDGeWJTsYpTGX9b3MuFJoE2sjNbsPELTgViDgBeBHIOA1DXbl50dn6dowZMgrcR/37LNjve4GAPhht3sxfHhoXxJHjmsXGrp1cyG6i8R55z0Vd1+xKE4F3S7YZHzO1IwCVszECF9y7w2JCl1AEja/7nmaSLYzUbMoCjBzpjaUwh7VjeXdd40129Rk8YLLZhcLm3Iu1K1dN0NGd58jsftMRrr/ivsNrT8kJB5a+pBh26FnDUWOLZEW3ERElG6NBtuklOsA/BbAAADrhRBvCCHuEEJMFEJ8L/j1XwBsCG7zeynlZ6k9bIoUXQqYSL8xK4XODxPtoxwqpwqLSrGPbKC+cf9GXPPqNQkfS/hKYhL80o95f12O+o8fRGD35TjtO91oSd8P//uHhnXJBDgUp6KdiAGGiVP1/nrD/qNLEuOVKMba37CCYYb1ZuUR0c37o5cT3Z9ZSZ2n2mOaedmrfa+k9xEpVnnoKd8p/XL9KdPtkqXWqDhdb+xNFSleJkwomFSxrgIvbngRm7/bHPex5q2cp5s6HAoUdXB00G3Xp1MfrJy2sklXtaMz60IDLRrbDoDhORytW7tumDi2S8y/8+qj1brtrZoSCgAX5sfO8qtYV4Hp707HBzs+wPR3p1sScDN7Lm6v3W64CLD4q8XN2s/RoyrOnNkdzEKzw2ZzBINdeh07DkVDAEzg/PMXNDroYODAcnTvPjHGvXb4/Q5s3Dg2vGavb2tEQDR0WiHgdJahb9+mlyMOLTqhf84AwQ+uj+OnPx6Skso6RQHmv7EZhUWP4rbhxRiF1XGn8xJZTlGA557TB9y++UZfs00pE6tNxH3v3Ydb37w14YzrLQe2GDK6v+9I7OKDu8htqFoBtCy76PcpT7UH9f56ANr57H3v3ZfWnqBERBRbQl2LpZQzADwW3P4WABUAFgN4P/j1j6Cdzc8CYHx3oJSKvuLe2q/Ar/42Yhph6EM6ELOBemgyYiJc57qSPyCTXlKRo+DNRAf1BETSAY7CboUx+1hFBzQiSxKb2qz74MmDhnXLdy83nJS1y20XdzlRJYNLdD3Tcu25cBW64C5yN/RjChqS3/jAgXjMMgUBoEOOPhg1vMBYNtsUnmoPRCNT4uL9HXqqPajz1SGAAHwBH+7+x93h53h0+aRaoxqyokKiGzc77I4ml4+YTVuMNYFRFzgyeQ5H9wicefVMLLltCSZfPxCdi581TCT99ti3uuXm9g2MNLfYPAi+5eAWQyDZigsVZhlre0/sNaxrTm9NbWro1di793lIWY8+fe7EsGFVpkG0ffsq0dBHTeL48cT6PQ4btgQ2WyfD+q5dr8QLL1Rhy5aIfdm1htzavurD+/L5jJmzyZg7Ya4+uyPig2udVybdIzRR7fY+hy3rn8SfP1uNZS8Dxz5O/D2IyBJuN7BiBXB2VFn6S8lf/KLkKE4FP774x/qVNaNQ//GDeP29r/HwRw9j7MtjGw1oDeg+QJfRLXL8KC05J+Hj0PWujPD06qd1y65CF2wRff78MvnBVkRElBoJjwiTUj4OYBC0gNoyAF8A+BKAJ7jufCnlo1KajVOiVAs1AW+saXsqJNNbSa1RsXFfMOMn+kP6Z/8es4H6z97/WULH0i2vW/I/gEkvqb9+/lfc+LcbY/5MfTr30S337Ry/f5eZUWePitq3A6h2GQY4ANAF/5rarPsnl5g3RG+sUXuPdj2S3hegb/gvIDB1+NRwIGhu8Vzk2fMgIJBnz4sZLEuU4lRMA3Z9OvcJ/23k2nJNrxQ3RSgYFEuPdj3iZsJEnxwHZAD3vXcfKtZVGMonPdUeRL6s2oU9/PvqmNtR97jRy8moPVVrKP01C+oaTuJN/n5G9h2JhZMWYuKAiVg4aWH4d/HaTa/h2MxjGNRD39j+7C76D5Sbv9uMoWcNxfcHf7/ZU0IB89fF5buWY93edbp1VlyoSDQQ3pzeml9//RAaAmgBnDy5JWa22rFjq+Mux9O7962GdUeProDTGVoKPi97bEPPDj2btS8zilPBWR3PalgRVYqcaI/QZBVVbUGeX7uCmOcHSjelP2OcCIoCXBZVlt43+XMNSt722u0NCyYXlOoD9Zjy1hQM+q9BMfu5Tb5ksq5y45cL30+4AiSeyH7BoXOEnys/h13YISCQY8vhgAQiolYiqciMlHJXMKA2QUp5kZRyiJSyOLhuZ6oOkmJTa1Tc+9694QBN6EN7ulLIk+2tVPpWRFAl+kP61ptjNlA/5TuFK164otHjiZWJEz2RUMekl5Rf+vH2F2/HvHo5+ZLJcZcTUTqsFGhfC0g7AKndtteyzyIDYGqNir98/hfd9zalWXf5hHKc0zX+VVW1RsUnuz7RrWvqBM/I7KR2Oe10ATXFqWDZlGV4cvyTWDZlmSXNfO+/4n7Duq0HtyKAgOVNg0MTOWMxuxod/f0/V36uW+cL+PDblb9Fnb9OVz7pKnQhLycPNtiQY8vBczc8F/45Jg2epHuM+0cZfweJMuvrZ5bhaQj0mvz9FHQqgLvIjSW3LTENOl6Uf5Fuef+J/eG/s1Bp59o9a/H2F283WmLbGE+1BwFpDGADWgbA8N7DkxqM0phY/RF7tOuBC3tdiCH5Q3QByKY4efKfcZcjnTmzK+5yPAUFZkFwidwOoRLY4M95qjdqT9U2a1+x3D789oaFiA+uw8setOSDq5k6k2E3rT1jnLJUWRmQm6t9nZurLVPK6fqSxhjus/3w9nBv2xlLZxguPIczz4PZucfylyR9HGfqja9F+07sQ8W6Ct359+9W/Q4BGYjZ9zdVrBhkRESUzRoNtgkh8oQQa4UQVUKI3DjbOYLbrI63HVnLU+2BP6DvBeQL+NKWQh4qh/NLP+p8dXH3q9ao+OpwxMTD6A/pFy4yb6AeLDVdu8bW6Bt6dFldyFXnGBvJh8XpGVcfqDfN/Pr7v/6uW25K8EtxKig559+hZagI7fa0sXeZWbCgqR/8rjvP2OstsndU5aZKXWadDbYmZ50pTgVVpVWYNW6WaXaS1dPv3EXumIFBv/THfG40VbwMpkQy6KKzMCUkvj78NQIyAJuwhcsnQ7/HJ8Y/geW3Lw8HadQaNVxOIiCaHSxSnIohQ/PNrW8a+8Ps9Oi/Mervx97/06SfM3tP7MXVf74aao1qeQ/KWMGvkI37N+Krw19h/ur5lnxgUJyK6TTYw2cOY1vtNuw8vBNDzxrarH3YbPrSbr//JHbtmmM6jdRmy4u7HE/Xrgpyc41/U76zFgWnkWqZbTkX/28wk0L/e05mX7GUTyjX/10HP7jefaM1JeFmcm+/A16bNg7CawNeH25r9r8ZUdJUVRuP+8c/ArNnAx9/nHhzXGqW/Sf3NyzEG+4TPD/9/d9UXHXvK3h46qUY8x+vQq1RDROomzKROtzbN0Kdvw7T352OeavmhXub+qU/PB0+EK0AACAASURBVB3crO9vKlg5yIiIKFslktk2GUARgN9JKetjbSSl9EIbpHB58HsoDVyFLkOJlISMmeFltZ4dejZk1SEQd78PVT2kb6QeHeQa+aIx6BWVvj/lmefjHo9Zw/+yK8swt3hu/Kt9UVOfIlWsr9CdRMxYOgPVR6p12zQ1+FVw0RdATvAkLscbPonr0q5LeJvo3+nkoZMtbda96+iu8BCK6N/fJb0vaVYwzOqAWmNG9TNv0J8K8Z7rb3/5dqPfb1YKHDpZ7tupL+ZfOz/8ezP7PUYOGpGQppNlkxVdanzad9owOMC0ZDr492Pv/6ku8y4Ws6CoX/pRuanS8h6UsYZ1RIscPNFcZhmGElK7KOGPf1EiEXZ756g19di582Fs2lRsCLh16TIq7nKy+5IAJg3dgt/9bgKGDFkFCD9+PupBDOkC+P2HdNu2b39+UvuKpfjcYsO6pvStTNShT5fDFqyQlUKbpMweSJRWqgqMGwf86lfAffcBu3e39BG1KbqMslgXZCPOT31/+hCBdxYAX0+E73+fxbz/Omx4n2tKlYDZOW3InmN7zNtZiBiDjCyWzMV2IqK2KpFg200Adkgp32tsQynl+wC2A/h/zT0wSoziVDC0t/GKeyo/iETvJxTsswlb3P2uWiWNPdmCH9KFcw1ybbnGoFdU+v729X3jTic9eEo/BKCgYwHKJ5RDcSpYOW0lxvQfg3b25Br+R09lfHPLm7r7e3Xo1eTgV+mkQXBMu95wEheZKVd7qrahJx9shhK8pPYXI+Pogx0fYMbSGTgTVT4Vry9Za1Q2ukw3lCHS+r3rLd1XvOd69HPEjCFDLMI3x7/BXe/epesFE1muodaohmmWTblqHq1kcAlybDmG9ZHZZWVX6n/HAgIlg0twV9FdWDF1RUJ/C6XDSk1Lu6t2VmHD3g3h++zCbklGUcngkoS223Iw9gebZLiL3Jg4wHyaZ0DGvyiRiEDAfBJuIFCHI0c8unX9+5cBCP2b5gSXm74vAUAIwOE4g+HDlwPSjj/850BsMglUduzYvMEnIbr+SUFN6VuZEFXF6PI3kCO1E6RcPzC2Oj0fXonCKiuBujpASqC+Hli4ECguRkpG8JKB2Xm1QeT5aSBU0KNd1N24uAilw0rhsDsgIOCwO5pUJTCgx4CY97nOdaGqtApj+uvbVkw4d0JaLnAmc7GdiKitSiTYNgLaEIRELQeQuvoOMtD1lghK15ueq9CFPHse7MKOPHtezA8kFesq4NtxpWnfi36d+2HltJX4+PaPMXv8bCyctLDh5CGUvg8fICTQ/mA4MGTGkaMPDp3fsyGzQnEq+Hjqx/hoykdon9MeNthgF3YMLxiOy/teHveqY+QHuyv66XvHXTMwdvCvMYpTgefXczBm8ipdVt3wPg1/Qq5CF3LtuRAQ4Ymezdlffod80/ueWvmUoWRhUM9Bptu2Vpu/26yflBlh7Z61lk4UNMsqDblpyE2Nfn9jQzUkJOatnIeKdRWoWFeBsS+Pxa+X/RquV1wY+/JY7Dqq74e180jz22Z6qj0IBIz9zSKzyxSngjsvvTOcKWoTNlx+9uVYMGlBwif4ilPBVf2Npd3bD23H8+ueD5/Ah7LdmivRxzDrj9NUj7kei5lN29yS5t69zYedAAH4fPogVNeuCkaMWI5zz52NESOWxxykkMy+pASEkOjf/18ABPx+iQMHooO9IkbPt+T17WL8W2lK6X5CPB7Y/RICWhafDcCEnpelLTuXyJSUgNeLlI3gJZ25EyKqIWJMjUehB7D5oL1S6F/rz0B7HZ42fBqmF02HZ4qnSa8hsaZpA8CxM8egOBVce961uvVVO6vSUtL5+ubX4y4TEVFiwbZeAPY3ulWD/QB4eSONzu9hLNVJV2ZbY325QhZtWWTa92JM/zGo+XkNFKcSLpVzF7lx7XnXaic6ztXAtfcDtgAgbcD7TwM1o/DnDX827EOtUbF5v76ZutmEysgeWCumrsCG6Ruw5s41xlKliJLXyCykyElQZsvJMpukGV0S6Av4ICHhC/iatS8AuDDf2E8K0K5MLt+1XLfOLKOkNWusv5eVEwUVp4JfjP6F6X2JZFJdN8jYP8/MnE/m4N737kV9oB4BGUC9vx71AWNF/57jexJ6vHhchS4IEb+5cugkPjT8ItRbLlm7j7W+sijXuS7LHqtyU2W4LNhqAweWw27vanrfd9/9zbCua1cF55wzM+lAW2hfOTkNvSQltMw2ALjqqrcB4UPAfhqOzvrXrC5drm7S/szoek0GX5fzD//Aksc2cLlgE0L38Xn8kSZMuSZqjtJSwBFx8dBm05ZTNYKXdELVEIVdC2MOSIBzNTDiz9C6O+rfN9sV7ERxZTFeWP8CXtn0SrOOo+QC8/OJfSe1CxzRg4ysukjVmH/u+2fcZSIiSizYdhpApyQesxMA69IDqFHRZV25tuZlPyUr4b5cJn0v5k4wv2rnKnShXU6w3PN0Ly3QFnGic9JrDHB5qj24fLcfD60ARtVoJWix0vbNjvnAyQMNG0RdyVy7xh4OMkRnVFiRYRGvke5DVQ+Fs7X80q/1vmuGeFdKz/j1f7rhf4MMEZkRaMbqiYLlE8oNwxBswpZQ75JEs5uOnD6iyzYTEFrJdRSzRsrJUpwKrux/pWH9S+tfAqAF2sa9Mg7Pr3sedf46XNn/yrhB9nikTCwQNaLPiKQfO1rpsNKYWYiRoodWWCKyT2WQFT/TWWf92HR9Xd03zX7saPn5/xb+OvIjZYcOJzHktmkQU76HgGOH7nsaidkmpfZUrXbxJeJ1+e9l7tRV1ImGnEQBADdzEimlmaJoWWyzZ2slpE88AVRVcUBCGilOBW/c/AZs566IPSBhWCWQUwcgdCFUe1/rf8HB8GTx5vbpLBttXvp/6JTWI9PssZfvWp7y7LZu7fXvl+1yM+t8kYgoHRIJttUAuCyJxxwJoPWlLGQxxanguRueM+2B1BqoNSo+3PGhthDRk63syrKYH9JD2Wd3Fd1lWkp6yndKVxKo1qg4uux9PPnyKHSqegizXx6Fp7vdklQQQBeIMVzJHIt5K+cBAGpP67MG2+e2T3gfiTp0uqHR+NYDW3X3RS8nS3Eqhh4fsRyra37T/XSKFywp6Fhg6WCJkJLBJdYHuyMCNEfrjsJua3h8u82OP17/R8PP2r1d9+btE9rf0Se7PjGsD5XxRQ5lALQT+s3fbTZsn4hzup6T0HZWTJFVnAoW3LAgZj+/ECsvUpQOKwVqFNPyo+h+e00Ru0TTjz17rCuXjrWvUDDtR5Nehey3Cu2EPlBfX3/A8D1NFSqlj3xd9vtyUlNRV1kJRJZSjxkDuK1/3SBqlKIAM2dqz7+ZMxloawGKU8GCu0pjTqwPX0QeuBThDDfhRw+cH54i39w+nYpTwZhzjOdsB04dgFqjml5823JwC8a9Mi6lAbcfXvRD3fLBUwc5kZSIKEoi0RkPgFFCiJGNbSiEKAIwGsCyZh4XJWnD3g3hPkf1gfq0pJAnylPtMZRTdcrthPIJ5XG/T3EqWDBpARbePVUrJRUSCNiBxc8ANaPCUxLVGhVjXx6LPe94cYO/Co9iFm7wV+H4+3lJHae7yI2FkxZi4oCJOHvoV4YrmXuO78Gtb96K497juu9zdnEmtR8z0f3iVuxeET5pubCXvuwzerkpzMprzUQPnGjtXIWumH2yUpWlV7mpUtcn7rrzrksoyFs6rNQ8+BOVVSlrrsCIgoZMKF/Ahw17Nxieh1aUQD5U9VD4dSRSqPfhO9veMdzX1NLcHu17JLRdvGlsyXAXubFi6gpc3vdy0/snDphofV+uGOVHe441v+S3a1cFNpt50vk338xv9uPH21dkUqKzg3Z7wKt/vW3ffrBl+1ecCjxTPCi5tjvsuQHY7BJ5DpGeiroh1gx5IKLM5C5ya+ehURPrw/1vnasB12+0c0X4Yc+BPvsNzb9oNLd4ruHcJr9jPoori7H7qHl+g9fvTemE0OgLfv6AnxNJiYiiJBJs+yO0vOj/FkLE/JQvhLgAwH8D8AN4zprDo2xgli0SmR3TGHeRGyVdH9c+sMIO+POATVqmxaItizBv5TzUB+rhgQteOOBHDrzIxetHz0v6WN1Fbiy5bQnyB39luJI5qOcgLN5uzEjZcXiHySMlp3RYqe5ESkLi3//v36HWqBjlHKXLdBrlHBXnkRKTaBnbTy6J1Yi9dVKcCn4y1PyYhxekZ25LvEEbkRSnguLcXxtKDM0CNJGBNQmJLQe3hK+ah1hRAvn1oa9N1z+16inMWDoD3x7/1nBfU0tzY/6eosoureztpjgVzL92vmlAdkD32FPfmsJT7QEKl5mWH1lR8nv0qIpA4ITpfadOfYGjR63LMIjeV2SJ6JHgfJ4v6kegOVNPG6M4Fbz1izKs8DjwxCyRuoq60lIgL0/7IfPytGUiatPcRW5Dy4gnxj+BhZMW6jcUAjm2HEMftdXfrkZzKE4Fz096vmE3EOjRvge8fq/pBTLtUERKW8q4Cl26ifVN7d9KRJTNGg22SSm/BPA4gHMAbBBCvCaEmCaEmCiE+J4QYqoQ4jUAGwAUAvhN8HtSRgjxsBBCCiH+GLFOCCEeE0LsEUKcFkJ4hBAXRX1fdyHEq0KIo8H/XxVCZEXn49JhpeFU8lxbbpNGjKfK21++bVhX2LUwqcco6Nwn5n1rvl0DABie54EDXthRDwfq0e6sD5LaR6SDpw7qSl4B4JPdn6B3p96GbROZPNkYxamgd0f9Y285uAVjXx6Lyne36zKd3lna/GyzRK6ytre3bzT7sDXS9d6LEH2ibJXSYaXIs+dBQCDPnpfw356qAksffch8wllUgGbrQX3p8IGTB3TZolb1aZx8yWTT9QEZwMsbXzas7+zo3OTSXNPMPpOpb+1zrC3TjheQtZKr0AV7/09Ny4+sCNAfOeKJc69ETc28Zu8jkX2d8AF59jzcMLSsWVNPExWqrEtZRZ2iAMuWAU8+qd2ydI+IoPVoDVU/LJy0EO4iN9xFbqyatgoT7XNgQx4gbfD5gD3/1E9y//aY8UJVc0hIvPPlO8ix5cAu7KY9Sbs4uli6z2ihjOMx/cegX+d+uH/U/ZzaTEQUJaEmX1LKxwH8Glqv4J8AeAHAYgDvA3gxuM4G4FdSyidSc6gaIcQoAHcCiB57UwbgQQD/Aa3H3HcAPhRCdI7Y5g0AlwK4DsC1wa9fTeXxppNN2CAgEmoEnk5v/PMNw7pXbkxuOlNpKYAcLwA/YK/TmtICWL9vPXwBH0bVAP+jrsZSFGMW/hMfoBi/6Hi4ycdsltG16+gu7D2xV7cukXLYRJn1R6sP1GPf54N1mU5il8uS/TXmsn7JtGpsPcwyrcacMyZlJ4GKU8GyKcvw5PgnsWzKsoT34/EAAX+u+YSzKcVA0YvAcPO/k8iryQBww6AbLPn5yieUx8yQO1FnzKIa2GNgk/cV6jWp6zdjktX3wKgHmryPWC7K112HiTtMpakUp4Lvn/99Q9AesCZA362bCzZb7EBkXV3zS1Ub25cQwND8c8LP++ZMPW1NVCiYg5lQkdk/BxFZK1T9EHmRSXEqeOx2F/IcAna7NjS271D9JPezO5/d7H2HBhWF+KUf1513HYrPLcaPLzYOzDlSdwTFlcUp7aO2+bvNWL57Ob45/g3mrZyn66VMREQJBtsAQEo5G8D5AGZB68n2BYAvg18/DuB8KeWcVBxkiBCiK4DXAdwB4HDEegHgAQBzpZSLpJSfA5gCoDO0QCCCJbDXAnBLKVdJKVUA0wFMEkJY11ymhXiqPaj310NCot5f36r6JkT3a+vXuV/SgQFFAcoqFgPFvwZuHxf+4Fp7qhYjCkbAVQ3YAsBorMZDmIsrsRo/GnNPk4+5fEI5OuR0MKw/cuaIbvm8nsmXqsZSH6g3vyMq0+n+HzW/HDJmv7AIo/o1v1y1JYTKPUKlgrm23LgTWK2Q8ETeCC4XkJsDAH7A5of93E9QdmVZw6CTjVOAdXfqs96C9p/Yb9mxR+varqvp+lO+U4Z1db7Ey8HNuIvc+Pj2jxv6qEU91/OHbEnJUAtXoQvtc9rDBhtybDl47obnUhKMNSuV7ZbXzZIAfdeuCoYNq8K5586GEMZAmM3WzrJS0sh9deig72HWK+cUepyqtLRstSWpKlBcDDzyiHabsomnRJQ1FAWYP197zZg/Hygeoz9/tOJ8qm/nvrplAYHFXy1G1c4q/O1ffzP9nlT3bYsOAEYvExG1dUmlQEkpd0kpH5VSTpBSXiSlHBL8+jEp5a5UHWSECgD/I6X8KGr9uQAKAITrBqWUpwEshzawAQAUACcArIr4vpUATkZsk7F6dugZ7tsQQPMmH1lJrVGx57g+wyL6hCFR5VNLMOzfFusyRCQkttVug6cQCNi05oICWq8K1NbGeqiE3HfFfY1uM+ps6wJS4wrHmd8RynQa/58Y88jjcJcMbfa+FKeCFVNXoGRwScwpthv3bmz2flpK+YRyrJy2ErPHz8bHt3/caksbbMIOIWywBwM+5RPK8cm0T+Couca0sX7IvpP7dMuR02ubq2Nux4S3Hdyz+dcpQn3UAOie65hSjJsnNu21IpF9VpVW4YnxT2D57ctTEtADYJotFxo2YYVQJlmXLsYs1KNHl2PDhtH49NPhlgTCQvvq1+9+3Xqf7wD27n0eGzaMzoqAm8cDeL2A36/dpmTiKRFlFVUFHngAqKrSbnds1rcF6dKu+SWdZVeWaZngwb6mvWq/D6/fC7/0IxAIGC6g2oQt5X3U2uW2i7tMRNTWta56wziEEHcCOA/AIyZ3h9IHotM99kfcVwDggJQNc9SCX38XsU3Giu7B1dzJR/FUrKvANa9eE04XV2tUzFkxxzRV3WwSaXOagyv9jEGT6qPVWO0E7r0eqLcBfgGgXTs0d1RdrOy2SIkOGkjEY67HYt8ZLEVzXvyNZftTnArKriyL2Vx3eJ/0DBRIlaZkm6WTxwP4fICUAgjkoHarFkRVnAoeuGW4vm9b+4PGQQoRth/abrq+Ke4fdX/jGwVZ1QdPcSooGVyiLQSf67b+a1PaezJdz4/oYLYVU2OjDRgQO3Pz5MlN2LhxjGWBsL593Tj//IVwOPoZ7vvXv/6fJftoSS6XVgYWKgdLy8RTIspokUH6Oq/EB1Ve3f1WXLxUnArG5Twc7mt6YMFfIGuuAADk2nPx4OgHYRd2CAjYhR0j+4zE/Gvnp/Q9rke7HnGXiYjaupzGN2l5wTLP2QCullJ642wqo5ZF1Lro+822Ce3TDcANAP3790/qeFvCvhP74i5bpWJdBaa/Ox0A8MGOD7B813K8ufVNeP1eOOwOVJVW6d7YzTLsmtMcPN7VwRdHAp/3BmbUX46Su+Zb0ti6U14nrXyuZpSWXVTo0WXW1Z5qXvZcJE+1BwLCEJyM9OGODy3bX2ifsVgx3ZJiC32o93qNH+rLp5YAeBvzXl+jBdref1rLdLN7dY32Q07Xn7bsuNxFbizasggf7Ig/YKSwW6GlJ/FlV5bhva/eg9fvhV3YU1bamU6mFxtS8HfVtasCm609AgHz54GUPhw54rGsl1rfvm7U1i5Gba0++O/1WtcnLhZV1T7YulypmV2gKFp2Sir3QUTZJfL9XBtstEx3v1UXLz9ZnhOR9S6BaheEcw2mDp+KbnndEJABSEj4pR9r96zF+n3rASBl2dvVR6t1y9FTWImI2rpMyWxTAPQC8LkQwieE8AEYC+Ce4NehiEd0htpZaMh22wfgrGB/NwDhXm/5MGbEQUpZIaUcKaUcmZ+fb+1Pk8HmvOHRZdi8vvl1nPGdgV/6UeerMwRvzIJRzWkO3tjVwbX9bej9hDWBNiA4NdVkQmKIlen5rkJXo8MtzJrUN3ef0c32AeumW1JsoQ/1s2Zpt9FP2fKpJTjvB/8DnO4Vt6QUAC4puMTSY1ty2xL06RR7AjAAzLxqpqX7DE02mz1+NlZMXZGyDwfp1LNDz5RMjTXTqVP8gSbdulm734Z30kipvX6Xrn5qKZ94SkRZJfR+fuedgPPq6E431l1ksQ9YYZhW7rA7UDqsFEfqjjS83wRLTX27RuK+9+5L2ZCEPcf0F1i2H9puui+1RsXd796Nu9+9O6UDG4iIWpuMyGwD8DaAz6LW/RnAdmgZb9ugBdO+B+BTABBCtANwNYBfBrdXAXSCFrgL9W1TAHSEvo9bRopuxG3WmLu5Kt7ejOr/etGQYRN6czfrFXekTj9Q4PK+lzerOfjNQ26Om3FzSe9LLM2GOXT6EFD9b4YriXCutnzCpeJUUNSnCGv3rI25jTD/hNusfXqmeFC5qRJbDmzBgVMHMLjXYJSNLsv4rKJMoCjxP9D3aN+jYWiAX4ZPrqOlYgBE7069DdN3QwZ1H5SSYJjiVLLqeVd7qhY22BBAAAICd4y4I2U/38CBc7FhQ/raj+bmGt9junRJ7b+dWT+1Vh0QS3UaHhG1Kq+8Apyp+x5gGxM+R7YLu2UXWToO+CeOTynWVVpc2Gu41n7i/eDk7tAF4uC5ev2UYniqPSl577mg1wX4bvd3unWVmyp1+1JrVIz+U8N7U8W6Cnwy7ZOseq8nIoolI4JtUsojAHRRGyHESQCHgpNHIYSYD+BXQogvoAXffg1tIMIbwcfYKoR4H8DCYP83AWAhgHellF+m7YdJkejeYVY0Y42k1qiY8eIKwP9zQ9ApxCZshky2F9e9qFv+6tBXzToOd5EbP3v/Z6aTEQHgyOkjpuub6op+V+Ark2CHgEhJgOOOS+/QB9uiyldLLiixfJ/ZFuDIJtrzYbp20m5SxgwA7eztUvLv57BFZTxGPBf7nGPMhiQjV6ELeTl54TL7VPag69pVgdNZhpqaeab3W1lGCgAFBaXYu/cFAP7gGhsGDkzt1N94pdetTigNL3SwZumrRJQ1QhcDZMAOyNzwOfItF99i2Xt0j3Y9sM+5WncesHH/Rqg1asNwgmqX4QJxqso7506YqwukAcCWA1t0y1PemqJbDiCAe967Bxump663NBFRa5EpZaSJmAfg9wCehZYF1wfARCnl8YhtJgPYBG1q6ZLg17el+ThTovZULQQasp7+oP7BslTtGUtnYPSfRuNIwVuG9PVIAsKY2XbmSNzlpjArewypPW1dDzUAuCj/ooYJiUUvAsNfAQD88spfpiTA4S5yY+GkhWhnb2coX7V/cxVeu+k1y/dJrVfo+XD5FQH0nPiCIdAGoNHS46a649I7GhainovbNraOacetXWjq6axxswz9LFPB5zsW877cXOv/zUR4+p0d55+/wNJgnpnGSq9bFY41JWpTXC5tsAqEH7D5w+fIK2tWWraPWAOMPNUeDOk1RFso9AA2H4CG4/jL539JSfmm4lQa9ht0xndGtxzd1w0ANu3bZPmxEBG1RhkbbJNSuqSU90UsSynlY1LKPlLKdlLKsaGst4htDkkpb5VSdgn+f2sway7juQpdsNsaxn7XB+rjNr9PVMW6CsxbGcyUCAWdxv+naZN2v/Tjgfcf0L2h59pzdds0ZxJpSGG3wpj3+QP+mPc1ha6P2sYpwLo7ISqXoaRj00thG+MucuPp656OujqZi8HHM7+HFSXPXeTGmjvX4J0fv2N6/40X3piy/S6ctBCdcjsZnouBHVenZJ/ZKJ1TcevrYw3GsaG+3toLEUeOeCBlw+ut1Y8fS8b0U+NYU6I2RwgAUt/u44TXul677iI38ux5hvVH6o7EzZyWUlrymcBMdGXNoJ6DdMs5wlhEJSFRsa4iJcdDRNSaZGywjfQUp4IfXfQj3Tor0safXvO0foVzNXD1XNMMG0C7ohV6Q5+xdAbq/HW6++dMmNPsYxrVb1TM+6wOPChOBQtuWABRPS4cbBCBvJQnKbiL3Jj8g366TML7b7FmmhVlJsWpYNW0VRjeezjswg6H3YHJQyenNNvRXeSG89gPgaP9tSvlwefi7Teem7J9UtPV1x+KWmMDYIfNlmf5gIRu3Vyw2RzBx3dY/vgZL6PS8IiouTwewOcDABsQsIeHGV1acKml+zHLbvv753+H4lSQawuWrwZyANh1x5Gq4TwHTh7QLa/5Zk34ortao+K033xK9qIti1JyPERErUlG9GyjxGyv3a5bfmPzG7j3snubnFGh1qjYsr4LUP2Qaa8oMxIyXEr65pY3dff16tDLkqbqpcNKsXDdQt2UP0AbvpCKwIO7yA3ctxn3fSLh90nkOURakhRe++m9GNN/MxYtrsXN1/WEu2Ro6ndKrZriVLDhrvT1OVFVYNsfngPq7VqwrehFXFj8GcqnvpS2Y6DEBQL68p0OHQajd+/b0K2by/ISz65dFQwbVoUjRzwpefys0NgEFCLKGqFk1tN1PsBmPszICuUTyvG7Vb+DPyKzeP/J/QCAvp37YpdJn2EJic3fbbY8w1qtUbWy0Yierl9jDYori1FVWoXKTZUxv/fmITdbeixERK0Rg21ZxOv36pYlpGEqUDIe+vP/6iYamZWOAtDeZDcF09eHVWLDXi0YcNOQmxpKUAFMGzGtSccRTXEqWDltJe75xz3YenArurfvjt+4fpOS6Ygh7pKhGLos/YPl3CVD4bZ+JgJRQjwewF9v18pHAxLouhudB37e6PdRy+jT5w4cP94wYKVfvwfQt2/qXhe7dlUYZCMignZeOH8+MKfia1T3eSp8vpyKoFKH3A447m1oSZ1j0z7O5dpyG1q+RA1V+tn7P7P0PFmtUVFcWYzTO4cDLy8D/LmAvR7y9nGoc66Fp9oD9Rt9nzi7sKOoTxHuuPSOlJ6zExG1Fgy2ZZHDZw4b1u07EauHT3wV6yqwfLkwTDSKDLZNHjoZr7/3dfBNNthDYsNUVIgJeH2zcRrqwO4Dm3QsZtKd4QMwSYHaHpcLsOX6EKhvuELet3Pflj4siiEUWDtwYBHy829OaaCNiIgaqCrw0/v9qKsbCNifBnr/JaK3HwAAIABJREFUC2W3XJ2SoNKIPiOwfNdy3TIQcZE7amIpAJzyncKMpTNQPsGansOeao92kX/TbcHPAALw24BNpQg4V6Nnh57YfXS37nu65HXBmjvXWLJ/IqJMwJ5tWaSjo6Mlj6PWqLj3vXu1K2Im00dtwoaFkxbitZtew1kHfqhdzYLQ/vfnIrDzahz3HtdddQPYn4Eo4/RTYZsyMTwUxd7/U5RdWdbSR0Vx9O3rxrBhSxhoIyJKI48HqKuDdoHa5wCqx2LbwW0p2dfc4rnhbLYcWw7mFs8FoJWYThwwUas4WfGQdhthwdoFlh2Dq9AFh90R8/7FXy02DHMwG+5ARJTNGGzLIpPOn2RYV9CpIOnH8VR74Av4TKePllxQgk+mfhK+Und7yblaIA5S+9/m05qp1xiHGAzvk9kN/lUVmDNHuyVqCzzVHgTOXhl3KAoREVFb17MnAGmDdj5sB850wbba1ATbFKeC5bcvx+zxs7H89uW6djGPnbcEOa99DHw0S2sFE3E+frz+OGYsnWHZMVSVVmHM93cB9joAfu12mNan7YOvPsD5vc7Xfc8oZ+wBZ0RE2YhlpFnk2JljhnXRI7kToZtiGpGK3jm3M9760Vu6bcunluCdL+/A1qqRwInewPbrgXV3AhunGHq8mR1fplBVoLgY8Hq1BrgcLkdtgavQBZvNhkAgAEDrA+mp9ljeZJkoUaqa/t6ZRESN2fD1LgBnQ/toJQH1QThcNSnbn+JUTN+LPR5A+hxazM+kBcy8lfNQMrik2e/jFesq8NL6l9B3cF+I24shq8foesSd8p3Cil0rdN9zfs/zTR6JiCh7MdiW5ULDChKl1qh4ffPrpvf16NDDdP2WuS9B/EZoKetf/iBmj7ctB7ckdSyticejBdr8fu3W4+EHPcp+ilPBs9c/i/veuw9+6UeePQ+uQldLHxa1UYaLHvM3Q6l91/LIm1qjwlPtgavQxcAyESVkX/7fANsD2jAhCEDasP/zC9N+HKGpqHVeiYAwn4ra3ItmhfMLsevoLm1hDwAnAOcqw3YSUre8ce/GJu+TiCgTsYw0i5QOK4WA0K1LdkDCPe/dE/O+h69+OOZ9XRxd9D3ebH5DOemBkweSOpbWpGdPwGbT/nc4tJMZorZgqNeNG77chZHrPsX8i9Yw+EAtRnfR44wfnnv+DjzyiBaBs6i+PzRh75Flj6C4shhqDfsGEFHjDvX8B3D9vYCtHhA+wO6Fr//StB+HomjVF0/MErh85sOmLSCeWvVUo4+j1qiYs2JO+DVQrVFx97t346zfntUQaIvQs13PRh8zFZNZiYhaM2a2ZRHFqeCS3pdg0/5N4XWHzhxK+PtnLJ2BjfvMrzpd2OvCuBOVfjvxt5j+7nStdHRTKbBhqqGcNL9DfuI/TCuiqsADD2gf8Gw2bbQ7s9qoLVBVLbDs9fYB0AeblgBDl/H5Ty3D5QIcOX54/QE4ZD1c/qUArE03Dk3Y80s/vH4vy6aJKCEHTx0ERi4Hen+uVXYUejDisi4tciyKAqCfCo9nK7Aj6s6aUThU7ULhdz/G9JJLTDN4QxcdTvtOAzWjIKrHQxZ+FLd36+wJs7XPATE09jmCiCgbMdiWZaIn/ZypP5PQ96k1Kn678rem9+V3yMeWe+OXgIbeQF9a/xK+3n8KtYEcQznpkPwhCR1LaxPKpggEACGA2tqWPiKi9PB4gPr6hmWWUFNLUhSgaurr8Cz8Ei75ERSs1l6ULUw3Dk3Y8/q9cNgdLJsmooQ4coKTOSN6HQMTW+RYQsGyOl+d/o6aUdrQBL8Duz724uGjE+AofAzXn3c9CjoVYESfEVjw6QJs2r9JKwENbi/9DsD+K+3iORAOJoZ+TofdAXeRGz9f8nOcrD9pekyX9rk0dT8wEVErxWBblrnj0juwds9a3XIiPNUeQ2+FkP+95X8Tegx3kRvuIjfUi4HRS04BPqlNKg32iygdVprQ47Q2of4XoT5BLCGltsLlAnJztec+AOTk8PlPLUspHQTllbu0J6XdAUybBpSWWhYBDk3YY882IkqGw+YwrGupsslQhm4AAdhgQ4fcDjhRf0ILkvkdERfDx8ILibc9FwSDZ8/rHyh6+02lWsWK36G1jQlWrow6W2sZU3JBScy+z4u3L07pz0xE1Box2JZl3EVuLN+1HG9tfQtd2iWevh7r6n1TJhYpCmCfcg38O68KX/myC3vGfmgJ9b/gBDxqaxQFeOYZ4J57GjI7iVpUGl6QY035IyKKJfpi9+Shk1usbDI6Q/d31/xOK/EM9Vb2By+Gtz8YznSDzQeM+DMwrLIhMy9ye5sf2DsiKljngs25FnMnzAUAvHbTa1i0ZRHO+I1VNcfqjqXvF0BE1Eow2JZlKtZVhK8qnTpxKtw/oalv+GVXljXp+4ou92Jtv7kNy32KmvQ4rUXo85zHo18mynahsmkptb6FLCOlFqcofBISUasSOs9etGURbh5yc4v2JzPL0F20ZRE+wAdaNlqoDFSXuWYHPrtL67l8+7iGctjIXszfjgRgDw6AqEeHQZ9i6bRPdBcnnr7uadPebed2OzddPz4RUavBYFuWWbRlkem6xt70562aZ1g3qPugJl/dL7mgRHeFr+SCkiY9TmuhqtrAu1ApaVUVP+tR28Ayamp1VJWpxkTU6oTaqbQG0Rm6S25bgj5P9cE+XU85aBltfntwQQD+PC24FtrGuVoLygVyoH1s9AEDlgKux7H04d8ZPieEfv5Hlz2KfSf3BR9V4JUbX0nND0pE1IrZWvoAyFpm/SES6RlRtaPKsK45b4yuQhfa57SHXdjRPqd9eppMqyowZ452a7HQkAR/xOA7orYgVLU3axaDzNQKhK58PPKIdpuC13siomy09xd70d7evmGFc7VWOgoJIHafiK4XbNTKSUU9kOPFmCkerHrUGGgLcRe5sfcXe7Fq2irMHj8bK6etZGk+EbVJzGzLMu4iN74+/DXmrdQy1ezCjqFnDY37PRXrKnDce1y3rr29fbPeGNPeZDrFqWfM7qG2jFV71GqYXfngk5OIKCFVU6ow+k+jG1YMq9RKRP152rLNq60DMCR/CO6/4n64i9yomLAZixbX4ubresJdMtfkkY3Y/5KI2joG27LQttpt4a/90o95q+bhrR+9ZdhOrVHhqfagYn2F4b6u7bs2+zjS+iab4g9gHJJARNTy1J6T4BGn4bJ9BMWx3vzKB8tMiYhMKU4Fq6atwpS3pmD74e1adtvt44BNpci1OWAb/houGHEaC25YpTuHd5cMhTuzO8IQEaUdg21ZaM+xPXGXAS3Q5nrFhXp/PSSk4f7QGO+MkYbUM2b3UFsUCsqnJUOVKA5VBYofGApv4GI47I+gav4XUJShJhuxwSYRUSyKU8G2n25DxboKvLT+JfS9oABljw4Pvsff0dKHR0SUNRhsa6MqN1XC6/fGvP+6Qdel8WgswNQzIsupNSqKK4vh9XvhsDtQVVrFgBu1mHACc0DAK3LhqR0Kw7ORZaaUqUIZmT17amOgeS5DKdaaBjoQEWUjBtuy0NaDW3XLm/ZvMmyzdMfSuI9Re6rW0mNKC6aeEVnKU+2B1++FX/pxxncGlZsqGWyjFpNQAjMbbFImCmVk1tUBgQBgswF5eczMJCIiymCcRpqFenfsrVuu89ehYl1DX7aKdRX46vBXMb/fLuzpmR5KRK2aq9AFu80OAJCQeGnDS1BrOP2RWkZCk3E5PpcyUSgjMxDQlgMBjj4nIiLKcAy2ZaEJAyYY1i3asgiAVhZ217t3xfzeXFsuVkxdweyVKGqNirsXVOLuGbugMtZAbYTiVHD9oOvDy/WBelRuqmzBI6K2TlGAmTMbiaEltBFRKxLKyLQFT8ttNsBuB3bvBk86iIiIMhODbVmodFgp7MKuW3fzkJsBaGVhZgMRQvzSz0BbFLVGheuJmXj+p/+G5397NsaN9/Pcl9qMgo4FLX0IRETZLZSR+cQTwMKFgNsNCAG88IJWXsqTDiIioozDYFsWUpwKHhz9oOl9rkIXbHH+2TvmdkzVYWUsT7UH9V9fCfgdgMxhZQe1KaXDSuGwOyAg4LA7UDqstKUPiYgo+4QyMt1uoH9/wOfTD/ogIiKijMJgW5Z658t3dMvzV88HoAXifjD4BzG/76mJT6X0uDKRq9CF3IErAbsXEPXsuU1tiuJU4JniwZPjn4RnioeZr0REqRYqK7XbOeiDiIgoQ3EaaZY67TutWz585nD460NnDpl+z8QBEzN3BLiqald+XS7L+/QoTgWeX89B5fD/AarHorTkHLYCojZFcSoMshERpYuiYPMb81G7eBF6XnczhvKkg4iIKOMw2Jal+nftj+oj1eHl/Sf2Q61RoTgVnKk/o9s215aLnyk/Q/mE8jQfpUVUVetp4vVqV4BTMIFOcSpQ7ubJLhEREaWWWqOi+F8PwHu2F45/rUBV0VBe8CAiIsowLCPNUj3a9dAtS8jwFMFu7brp7htXOC5zA22AltHm9aa8t4mqAnPmsE8xEVFL4msxZTtPtQdevxd+6YfX74Wn2tPSh0RERERJyohgmxBiphDiUyHEMSHEASHEO0KIi6O2EUKIx4QQe4QQp4UQHiHERVHbdBdCvCqEOBr8/1UhhD7ylCUKOsWeILhx/0bd8o7DO1J9OKmVht4moeS5Rx7hYDAiopbC12JqC1yFLjjsDtiFHQ67A65CV0sfEhERESUpI4JtAFwAngMwGsB4AD4AS4UQkelbZQAeBPAfAC4D8B2AD4UQnSO2eQPApQCuA3Bt8OtXU33wLWFEnxG6ZQGB0mGlqFhXge9Ofqe776YhN6Xz0KynKFrp6KxZKSkhBdKWPEdERHHwtZjaAsWpoKq0CrPGzUJVaRVLSImIiDJQRvRsk1JeE7kshLgNwFEAVwJ4RwghADwAYK6UclFwmynQAm4/AbBQCHEhtADbVVLKVcFtpgNYIYQYLKX8Mm0/UBrUnqrVLUtIbP5uMx71PKpb39nRObNLSEMUJSVBthCXC8jJAQIB7ZaDwYiI0i+UyBxq0cnXYspWHExDRESU2TIlsy1aZ2jHHhqxeS6AAgAfhDaQUp4GsBxaNhwAKABOAFgV8TgrAZyM2CZruApdsAn9P+/jHz+OfSf26dbl5eSl87Aymt8PSKndEhFR+qUhkZmIiIiIqNkyNdj2NICNAELdWkINyvZHbbc/4r4CAAeklDJ0Z/Dr7yK2CRNCuIUQnwkhPjtw4ICVx54WilPByD4jdeu+Pf6tYbtLCy5N1yFltMpKwOfTvvb5tGUiIko/RQFmzmSgjYiIiIhar4wLtgkhfg/gKgA3Symjc4xk9OZR66LvN9tG21DKCinlSCnlyPz8/OYccovZVrut0W2+Of5NGo6EiIiIiIiIiKhtyKhgmxDiDwB+DGC8lDJyhGaoNjI6Q+0sNGS77QNwVrC/W+jxBIB8GDPisoIv4NOvqBkFrHhIuw066T2Z5qPKTKWlQF4eIIR2W1ra0kdERERERERERK1RxgTbhBBPQxt2MF5K+UXU3TuhBdO+F7F9OwBXo6FHmwqgE7TebSEKgI7Q93HLGpf2jSgRrRkFvFIFfDRLuw0G3KKnlpI5RQGWLQOefFK7ZfkSEREREREREZnJiGCbEOJZAFOhZbUdFkIUBP/vBIR7r80H8JAQ4iYhxMUAXoY2EOGN4DZbAbwPbTLpKCGEAmAhgHezbRJpyNziuQ0L1S7A7wBkjnZbrQ1QKBtd1mLHl2nYJ4iIqOWpNSrmrJgDtUZtfGMiIiIiohaQ09IHkKB7grdVUet/A+Cx4NfzALQH8CyA7gDWAJgopTwesf1kAP+Fhqml/wfgvhQcb6ugOBW0z2mP077TQPuDgLQDkNpt+4NYcMMCjpUnIqKModaoKK4shtfvhcPuQFVpFd/HiIiIiKjVyYhgm5RSJLCNhBZ4eyzONocA3GrZgWWAHFvwn/h0LwB+aP/kPji8Z8Nd5G7BIyMiIkqOp9oDr98Lv/TD6/fCU+1hsI2IiIiIWp2MKCOlpvvB4B9oXxR6gBwvIOqBHC+GXPZdix4XERFRslyFLjjsDtiFHQ67A65CV0sfEhERERGRQUZktlHTvXbTa9heux1rsRqYUgxUuyDOXY7npj/V0odGRESUFMWpoKq0Cp5qD1yFLma1EREREVGrJLTqS4pn5MiR8rPPPmvpw2iWinUVeGn9S+jbpS/KRpfxAwoREREREVGQEGKdlHJkSx8HEWUHBtsSkA3BNiIiIiIiIjLHYBsRWYk924iIiChjqCowZ452S0RERETUGrFnGxEREWUEVQWKiwGvF3A4gKoqQGFXBCIiIiJqZZjZRkRERBnB49ECbX6/duvxtPQREVmIaZtERERZg5ltRERElBFcLi2jLZTZ5nK19BERWYRpm0RERFmFwTYiIiLKCIqixSA8Hi3QxlgEZQ2ztE0+wYmIiDIWg21ERESUMRSFMQjKQkzbJCIiyioMthEREVHGUFVmtlEWYtomERFRVmGwjYiIiDIC21pRVmPaJhERUdbgNFIiIiLKCJxGSkRERESZgME2yh6qCsyZo90SEVHWcbkAux0QQrtlWysiIiIiao1YRkrZgbVFRERtghD6WyIiIiKi1oaZbZQdWFtERJT1PB6gvh6QUrvlSz0RERERtUYMtlF2cLm0jDa7XbtlbRERUdbp2RMIBCQAiUBAomfPlj4iIiIiIiIjBtsoOygKMH++Vko6fz5LSImIstCGr3cBIgBAAMKvLRMRERERtTIMtlF2UFXggQe0Xm0PPMAhCURE2ajwY8BeB4h6wO7VlomIiIiIWhkG2yg7sGcbEVHWK500CI5p10OMfwyOadejdNKglj4kIiIiIiIDTiOl7OByaf3aAgHtlj3biIiyjuJU4Pn1HHiqPXAVzoHiZMsAIiIiImp9GGyj7BEIaCPqAoGWPhIiIkoRxakwyEZERERErRrLSCk7zJsH+Hza1z6ftkxERERERERElGYMtlF22LMn/jIRERERERERURow2EbZ4Y474i8TEREREREREaUBg22UHYYO1QYjANrt0KEtezxERERERERE1CYx2EbZobIS8Pu1r/1+bZmIiIiIiIiIKM0YbKPssG9f/GUiIiIiIiIiojRgsI2yQ0FB/GUiIiIiIiIiojRok8E2IcQ9QoidQogzQoh1QoirW/qYqJlKSwGHAxBCuy0tbekjIiIiIiIiIqI2KKelDyDdhBA/AvA0gHsAfBK8XSyEGCKl3N2iB0dNpyiAx6P973Jpy0REREREREREadYWM9t+DuBlKeULUsqtUsr/ALAXwN0tfFzUXIoCzJzJQBsRUTarqGjIZBYCuOIK/f233gr07KndNvXxhwwBLrpI+/qaaxr2lU3/d+gAqKr+Zzf7WXNzAZst/mN16QKMHQs4ncCMGcZ/j+jtCwvj//5zclr+99PY/336aMeaicfelv6Pfn0gIiJKEyGlbOljSBshhAPAKQA/llL+d8T6ZwFcLKUca/Z9I0eOlJ999lmajpKIiIhMVVQA06cb119+ObBmjRbYef31hvWTJwOvvdb8x89mq1ZpF6muuQb44ANrHrOsDCgvN/57RDrnHKC6Wr8uE3//CxcCbndmHntbEXp9IGqEEGKdlHJkSx8HEWWHtpbZ1guAHcD+qPX7Aeg66gsh3EKIz4QQnx04cCBdx0dERESxLFpkvn79eu128WL9+ujlpj5+NvN4tNsVK6x7zDff1G7j/f53m3TuyMTff+iYM/HY24rQ6wMREVEatbVgW0h0Op+IXielrJBSjpRSjszPz0/fkREREZG5m282X3/ppdrtddfp10cvN/Xxs5nLpd1ebeGsqJtu0m7j/f779zeuy8Tff+iYM/HY24rQ6wMREVEatbVg20EAfkRlsQE4C8ZsNyIiImpN3G6tbC83t2FdZInYa69ppaM9eiRfQhr5+BdeqPVtW7gQmDjRuuNvTdq3byghBYAlS8x/1lAPsng6dwbGjAH69WsoIQUa/j2imZWQAg2/f7s9qR+lRRQUNJSQApl17G0JS0iJiKiFtKmebQAghFgDYJOU0h2xbhuARVLKmWbfw55tRERERERE2Ys924jISjktfQAt4PcAXhVCrAWwEsBdAPoCeL5Fj4qIiIiIiIiIiDJemwu2SSn/JoToCeDXAPoA+BzA9VLKXS17ZERERERERERElOnaXLANAKSUzwF4rqWPg4iIiIiIiIiIsktbG5BARERERERERESUMgy2ERERERERERERWYTBNiIiIiIiIiIiIosw2EZERERERERERGQRBtuIiIiIiIiIiIgswmAbERERERERERGRRRhsIyIiIiIiIiIisgiDbURERERERERERBYRUsqWPoZWTwhxAMCulj6OVqIXgIMtfRBEacbnPbVFfN5TW8PnPLVFfN43OEdKmd/SB0FE2YHBNkqKEOIzKeXIlj4OonTi857aIj7vqa3hc57aIj7viYhSg2WkREREREREREREFmGwjYiIiIiIiIiIyCIMtlGyKlr6AIhaAJ/31BbxeU9tDZ/z1BbxeU9ElALs2UZERERERERERGQRZrYRERERERERERFZhME2IiIiIiIiIiIiizDY1goJIWYKIT4VQhwTQhwQQrwjhLg4ahshhHhMCLFHCHFaCOERQlwUtc2vhBArhRAnhRCGemEhRL4QYknwMeqEEDVCiGeFEF0TOMaxQoh1QogzQogdQoi7ou4fI4T4PyHEt0IIKYS4PcGfPU8I8YwQ4mDwuP9PCNEv4v5hQoi/BI/1tBDiSyHEL4UQfC5nOD7vYz/vg9sUCyFWif+/vXsPtqss7zj+/XEplDvB0sglE5ThLoOA0CiXCFqgBUuBoaI4Ax0BdWgtFRymdmyKtwIjhFELiFpGLgWhWlvacmsooCZtCbW1LSnQwgQx4RZICJdw8e0f7zpksdnn5Jxk49n77O9n5p2Vvda73mets5+cvc+73vWu5NkkS5Kcn2SD8bSv/jXkeX96kjuSPNPsN3OUekckmZ/k+abuP46nffWnYc35JNOa3/OLmnN6JMmlSbZp1VmvaXdxE3tJkquTbL+m9tXfhjXvm/2uSPK/zTk9keT7SXbvqLN1kquSLG/KVUm2Gk/7ktSv7KDoT7OBPwfeDRwGvALcnmRaq86ngU8Bvwe8C3gcuC3J5q06GwHfBeaOEufnwPeAY4BdgFOAw4Erxjq4JDsBfw/8CHgn8CXgK0mOb1XbDPhP4JPAC2O112EucDxwEnAwsAVwU5L1m+37AU8AHwH2BP4E+Cxw7gRiqD/NxrzvmvdJ9m5i39rE/iDwAeDPJhBD/Wk2w5v3m1Bzes4Y8Y8FrgOuauLPAr41gRjqP7MZzpzfDti+Obd3ACcDhwB/2VFvHnAisCv1c+FtzXlosM1mOPMe4J7mOHYHjgBCPfcNW3WuBfYFjgKObP591QRiSFL/KaVY+rxQP9xeBY5pXgdYAnymVeeXgWeBM7rsf0J9q8cV6/eBJWuocz7wQMe6bwDzR6m/EjhlHLG3BF4CPtxatyP1i8MRY+x3AbBwst8nS2+Leb8674EvAv/Wsd8x1C+7m0/2e2XpXRmWvO/YZ3+gADM71q8PLAZOm+z3xfLmlWHM+da+v9H8rt9ijDofaP5/bDzZ75Wld2XI837vJqd3bV7v3rx+T6vOQe06FovFMojFkW2DYXPqKMSnm9c7AdOpIwIAKKW8ANxFvWK2VpJsBxwH3LmGqrPasRu3APt3XKWaqP2ADXn9eT0C3MfY57UFq382mjrM+9XntRHwYsd+LwAbN/tr6hiWvB+P/agdz6uS3JtkaZJbk7zzTY6rX6xhzvktgFXA8902NqOePgz8cyml8zNAg20o8z7JpsCp1AspD7dir6SOqhvxQ+A51uHcJWmy2dk2GC4BfgzMb15Pb5aPddR7rLVt3FLnQHseeJR6Be3UNewyfZTYGwBvmWj8jnZfBZ7s0nbX80qyL3Vo+qXrEFf9ybxffV63AAcm+UiSDZr5ez7bbHvrOsRW/xmWvB+PtzXLz1FHd/4m8FPgzuYPSE0NQ5nzzXxUnwOuKKW80rHt/CTPAU8BM4CjexVXfWOo8j7JJ5KspHaqHQUcXkpZ1Yr9RCnltTnomn8/zlqcuyT1Czvb+lySi6hDqY8vpbzasblzYtR0WTceZ1HnRjiW+sfNa/NAJFnZKpetIXa39V0l+aOOtmeMVb1bu0l2Bf4OmFtK+avxxNVgMO9fa7sAlFJuBc4Gvkod4XY/dW4VqB11mgLM+zcY+Y7yhVLKjaWUhcDpwDPUeTs14IY155vRPX9L7Qj5dJcmLqTOm/Xr1N/xVydJl3oaQEOa99dQc/pQ6neYG5JsMkbskfhrc+6S1Bd8kl0fS3IxdSL095ZS/q+1aWmznA480lq/LW+8KrVGpZSlTZuLkjwF3J3k882tbPu0qq5oxe+80rQtdbLXp8YZ9jLgO63XP2vaXZ96Be2Jjrbvau+cZDfgDuC6UooPR5hCzPvXtf1a3pdSLmp+Nm+l3nYykzqB8UPjjK0+NoR5Px5LmuV/j6wopbyS5AHqaB8NsGHN+SSbsfpiydHdbg8tpTxJHe18f5L7qD+Hg4C7xxlffWpY876UshxYDjyQZAH1e8zx1IcgLAW2TZKR0W1N5/KvsBbnLkn9ws62PpXkEuqH8exSyqKOzQ9RP5jeD/xrU39j6lMMz1nH0CMjCTYCKKU82KXOfOqVsrb3A/eUUl4eT5BSyjJgWXtdkoXAy01b1zbrdqBOnPqjVr09qE/r+k4p5azxxNNgMO9Hz/tm/0Lz5TXJSdQv5PeOJ7b61zDm/TgtpM5ntSvwA4Ak6wFvp95arQE1rDmf+lTJf6CO2DmylLJyoseswTWsed9FmjKS0/OpD4yYxervPbOATen4HiRJg8TOtj6U5GvUW2SOBZ5OMnKlaWUpZWUppSQs7ah4AAAGFklEQVSZC3wmySLqcOw/ps6DcG2rnRnANOoIGJKMXMl6sJSyMsnRwDbUP2hWAntSb11YMMoH8YjLgDObY7gceA913rSTWrE3A3ZuXq4HzGjiLyulLO7WaClleZJvAhcmeZx6Je0i4D+A25t296R2tN0BfLH1sxm5iqcBZd6PnvdN2+cAN1OfXHcccC5wYpdbUDRAhjXvm/2mU0dS7NKs2iN1HqvFpZRlpZQVzS1Of5rkp9TJtM8EtgauHuOY1ceGNeebjrZbqQ9FOBbYtLmdlGa/l5LMot769wPq7dJvp87r9nCzTgNqiPN+Z+oIttupo/d3oH5/WQXcBFBKuS/JzcDlSU6jdsRdDtxUSvmfMY5ZkvpbLx9taulNoc5P0K3MadUJMId6m82L1KcM7dXRzpWjtDO72f4+6tWkZ6hPNryf+ujvrcdxjIdSR9Ssol6N+1jH9tmjxL5yDe1uDHyF2uHwPHVOkx1b2+eM9vOZ7PfNsm7FvB8975s681rHvAA4arLfM8u6lyHP+9F+n5/SqrMhcAF1xMcK4J+AfSf7fbOsfRnWnB9jn/Yx70O9mPhUK/alwA6T/b5ZzPu1zPsdqaM5Hwdeoo7IvwbYraPeNOpFlBVNuRrYarLfN4vFYlmXklIKkiRJkiRJktadTyOVJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH7GyTJGmAJJmZpCS58k2McWUTY+abFUOSJEmaquxskyRJkiRJknpkg8k+AEmSNCGPArsDyyf7QCRJkiS9kZ1tkiQNkFLKy8CiyT4OSZIkSd15G6kkSQOk25xt7TnWkpyR5CdJXkzyWJKvJ9lylLbel+TuJM8lWZbkr5Pstob4Bya5McnSJC8leSTJ5Um266h3XHNMC5Js2LFtryTPJ/lZkm3X4cchSZIk9R072yRJmjouaMq/A1+j3nJ6GvC9zopJTgBuAfYHbgAuB7YB5gM7dWs8yanAD4GjgDuAucA9wEeBe5LMGKlbSvlucwwHAl9otbEJcD2wEXByKeXxdTlhSZIkqd94G6kkSVPHrwHvKKUsBkiyATAPeG+SA0op/9Ks34zaufZz4OBSyj0jDSS5GPiDzoaT7NLs8zBwaCnl0da2w4DbgEuA327t9ing3cDZSeaVUm6mdsDtAZxXSpnXqxOXJEmS+oUj2yRJmjrOG+loAyilvAL8RfPygFa93wKmAde2O9oac+j+8IWPAxsCn2x3tDVx5gF/AxyTZPPW+lXA7wDPAd9OcjZwCnAXcN5ET06SJEkaBI5skyRp6ujsOAN4pFlu3Vq3b7O8s7NyKWV5kh8Dh3ZsmtUsD03yri5xtgXWB3YBFrbaeyDJGcA1wIXAk8CHSimvruFcJEmSpIFkZ5skSVPHM13WvdIs12+tG3lgwmOjtLO0y7ptmuU5aziGzbqsuw1YAWwB3NA5Mk6SJEmaSryNVJKk4TNym+ivjrJ9+hj7bFlKyRjldaPlkgT4NrWj7Ung9CSH9OIkJEmSpH5kZ5skScPn3mbZeasoSbYE9umyz4JmefAEY50DHEm9jfQw4GXg2iRvmWA7kiRJ0kCws02SpOHzfeBp4ENJ9u/YNofVt5m2fZXaUXZx82TS10nyS0kO7lh3IPB54EHg46WUnwBnAdsDVzaj3iRJkqQpxTnbJEkaMqWUlUlOB64H7k5yPbAEOAjYi/q00EM69lmU5HeBbwH/leRm4H7qE0pnUEe8PQHsBpBkK+A6oAAfLKU827RzWZLDgROAPwS+/CafriRJkvQL5cg2SZKGUCnlRurtnQuBE4GPAcuoTx19aJR9rgb2o94SujdwJnAysDNwI/CJVvVvAjOBc0spC1/fEh9tYnwpyQG9OSNJkiSpP6SUMtnHIEmSJEmSJE0JjmyTJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH7GyTJEmSJEmSesTONkmSJEmSJKlH/h8kZQ9WZ5BfNgAAAABJRU5ErkJggg==\n", 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" ] @@ -796,7 +780,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:55:02.248297", @@ -828,7 +812,7 @@ " dtype='object')" ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -845,7 +829,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2017-05-09T09:55:03.902986", @@ -862,3290 +846,265 @@ "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", "will be corrected to return the positional minimum in the future.\n", "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", " return (np.abs(df[column]-value)).argmin()\n" ] }, { - "name": "stderr", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_model('CODtot_line2',model_output_ontv_1['.sewer_1.COD'],\n", + " [dt.datetime(2013,1,18),dt.datetime(2013,1,22)],\n", + " only_checked=True,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ratio or correlation\n", + "Constant ratios or correlations between data can be used to filled missing points. The user can calculate and compare ratios and correlations (currently only linear) between selected measurements, and fill data using these.\n", + "\n", + "*nb: in the examples below, data filling based on ratios or correlation is obviously not a very good choice. Both methods are included here for completeness of method showcasing.*" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:03.917107", + "start_time": "2017-05-09T11:55:03.905461+02:00" + }, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(2.4506423271968965, 0.6721532140851265)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.calc_ratio('CODtot_line2','CODsol_line2',\n", + " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To find the 'best' ratio (i.e. the one with the lowest relative standard deviation ($\\sigma/\\mu$)), the ratio obtained in different periods can be compared and the best one used during possible further replacements." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:03.978297", + "start_time": "2017-05-09T11:55:03.919697+02:00" + } + }, + "outputs": [ + { + "name": "stdout", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" + "Best ratio (2.5328218826106403 ± 0.16586491872475548) was found in the range: [Timestamp('2013-01-19 00:05:00') Timestamp('2013-01-21 00:05:00')]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" + "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_HydroData.py:1400: FutureWarning: pandas.tslib is deprecated and will be removed in a future version.\n", + "You can access Timestamp as pandas.Timestamp\n", + " if isinstance(self.data.index[0],pd.tslib.Timestamp):\n" ] - }, + } + ], + "source": [ + "avg,std = dataset.compare_ratio('CODtot_line2','CODsol_line2',2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Use the average obtained from the ``compare_ratio`` function to fill in missing values. (*in this case, as mentioned before, this does clearly not work, since zero-values are replaced with zero-values. This only showcases the function and its arguments*)." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:04.632959", + "start_time": "2017-05-09T11:55:03.980745+02:00" + } + }, + "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" + "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:462: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_ratio('CODtot_line2',\n", + " 'CODsol_line2',avg,\n", + " [dt.datetime(2013,1,22),dt.datetime(2013,1,23)],\n", + " only_checked=True,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of a ratio, a correlation can be sought. In case of a zero intercept, this of course gives a result in the same range if the same data is used. To have a good impression on how useful the calculated correlation is, a prediction interval is plotted as well when ``plot`` is set to ``True``." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "slope: 0.4055129249855649 intercept: 0 R2: 0.9737746563763395\n" ] }, + { + "data": { + "text/plain": [ + "(
,\n", + " )" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.get_correlation('CODtot_line2', 'CODsol_line2', [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", + " zero_intercept=True, plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After the previously made assessment, use the correlation function to fill gaps in the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:06.016129", + "start_time": "2017-05-09T11:55:05.261370+02:00" + }, + "scrolled": true + }, + "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" + "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:569: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n", - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:1410: FutureWarning: 'argmin' is deprecated, use 'idxmin' instead. The behavior of 'argmin'\n", - "will be corrected to return the positional minimum in the future.\n", - "Use 'series.values.argmin' to get the position of the minimum now.\n", - " return (np.abs(df[column]-value)).argmin()\n" + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.fill_missing_correlation('CODtot_line2',\n", + " 'CODsol_line2',\n", + " [dt.datetime(2013,1,23),dt.datetime(2013,1,25)],\n", + " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", + " only_checked=True,clear=False,plot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data from previous day\n", + "Under the assumption that \"The best prediction for tomorrows weather is todays weather\", one can also replace missing data by making use of (one of) the previous days." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:06.731819", + "start_time": "2017-05-09T11:55:06.018568+02:00" + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:961: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", + " 'ensures the proper working of the package algorithms.')\n" ] }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -4155,114 +1114,331 @@ } ], "source": [ - "dataset.fill_missing_model('CODtot_line2',model_output_ontv_1['.sewer_1.COD'],\n", - " [dt.datetime(2013,1,18),dt.datetime(2013,1,22)],\n", - " only_checked=True,plot=True)" + "dataset.fill_missing_daybefore('CODtot_line2',\n", + " [dt.datetime(2013,1,25),dt.datetime(2013,1,27)],\n", + " range_to_replace=[0,10],plot=True,\n", + " only_checked=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "ExecuteTime": { + "end_time": "2017-05-09T09:55:07.431337", + "start_time": "2017-05-09T11:55:06.734413+02:00" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = dataset.plot_analysed('CODtot_line2')\n", + "ax.legend(bbox_to_anchor=(1.3,1.0),fontsize=18)\n", + "ax.set_ylabel('Total COD [mg/L]',fontsize=18);ax.set_xlabel('')\n", + "ax.tick_params(labelsize=14)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Ratio or correlation\n", - "Constant ratios or correlations between data can be used to filled missing points. The user can calculate and compare ratios and correlations (currently only linear) between selected measurements, and fill data using these.\n", - "\n", - "*nb: in the examples below, data filling based on ratios or correlation is obviously not a very good choice. Both methods are included here for completeness of method showcasing.*" + "# Calculations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Calculate the daily average of a certain data series" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 35, "metadata": { "ExecuteTime": { - "end_time": "2017-05-09T09:55:03.917107", - "start_time": "2017-05-09T11:55:03.905461+02:00" + "end_time": "2017-05-09T09:55:07.830400", + "start_time": "2017-05-09T11:55:07.433945+02:00" }, - "scrolled": false + "scrolled": true }, "outputs": [ { "data": { + "image/png": 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LUke53ECSJGnqGg3KJwNfmGRa9SZg3pQrUse5bkKa+dycRJIkaeoaXaP8h8Adk7TZBuwztXIkSc3icgNJkqSpaXRE+V7gkEnaPB74xdTKkSRJkiSpsxoNytcDp0TEH413MiIeB5wIfH26hUmSJEmS1AmNTr1eCbwAuDYi/gHYG4p7KgPPBC4EtgMXNLNISVL3c3q3JEnqFQ0F5cy8ISJOBy4GvlQ5dX/5/HvgNZn5/SbVJ0mSJElSWzU6okxmfjwirgP+DngacCBwH/Bt4KLM3NjcEtXL1gwOMbhpmK2j21m0Yh3LFi9wV94pcCRPkiRJap6GgzJAZt4BnNnkWjTLrBkcYvnqDWwd3Q7A0PAIy1dvADAsS5LUAX6ALUmFRjfzkppm5dqNjGwb3enYyLZRVq51UoIkSe020QfYawaHOlyZJLXflEaUI2IOsADYH5gzXpvM/MY06tIssHl4pKHjUis5fV3SbLerD7AdVZY02zQclCPiHIpp1/tN0nTcAC2Nmdffx9A4oXhef18HqpEkaXbzA2xJ2qGhoBwRZwHvpNi861+Bn1LsdC01bNniBSxfvWGnT6/75s5h2eIFHaxKkqTZyQ+wJWmHRkeUXwcMAX+emXe3oB7NImPTuM668ha2jm5noL/PTUMkSeoQP8CWpB0aDcqHAB81JKtZliwc4LIbNwGuEZUkqZP8AFuSdmg0KP9yCq+RZiWDvySpWZauWg+0/v8tvf4Bdrt+jpJmvkZvD/UZ4LkRsWcripEkSZIkqdMaDcpvB34OXBkRh7egHkmSJEmSOqrRadTfB+YC84CTI+I+YHicdpmZR063OLXfmsEhBjcNs3V0O4tWrHNtkiRJkqRZp9ER5d0obge1qXzcB8Q4j0av+7CIGIiIByIiI+JRleMREW+NiJ9GxEhEfCMinjTO658YEV+LiAcjYnNEnBcR3tO5DmsGh1i+egNbR7cDMDQ8wvLVG1gzONThyiRJkiSpfRoaUc7M+S2qo2ol8ACwT83xs4FzgGXA7cCbgasj4k8z8xcAEbE/cDVwK/AC4EjgAorg/rY21D6jrVy7cadbQgCMbBtl5dqNPTOq7OYdkiRJkibTVTtYR8QzgBOB91IE5rHje1EE5fMz86Ly2HrgLuAN7AjBrwf6gFMz837gqxGxL3BuRLy/PKYJbB4eaei4pO7nh0OSJHUPlznOHFOeIt1s5fToDwPnAffUnH46sC/FrtsAZOZvgS8CJ1XanQSsrQnEl1OE52e1oOyeMq+/r6HjkiRJkurjMseZZZcjyhHxivKPn8vM31S+nlRmfqrBWl4P7AX8M/DSmnNHAaPAHTXHbwOW1rRbV1PHpoh4sDz3xQZrmlWWLV7A8tUbdpp+3Td3DssWL+hgVZIkSZptenHkdTYsc+wlk029/gSQwLeB31S+3pUo29QdlCPiQOBdwMsyc1tE1DbZH3ggM0drjm8B9o6IPTJza9luvF24t5TntAtj/4GedeUtbB3dzkB/X0/8oyRJM8XSVesBp8xLmt0mGnkFZvTvpS5znFkmC8qvoQi9Py+/fnWL6ngPcENm/scu2owX0GOccxO1GzfgR8TpwOkAhx566OSV9rglCwe47MZNgL+oSa3if1uSJE2sV0de5/X3MTROKHaZY3faZVDOzE/UfP3JZhcQEX9CEcifGRH95eG9y+f9ImKUYkT40RExp2ZUuR94MDO3lV9vKY/V2o/xR5rJzEuASwCOOeaYyUbLJUmSJLVQr468usxxZumGXa8fB8wF1o9z7mfAvwCXAnOAxwIbK+ePorhV1Jjby2MPi4hDKG41VW0nSZIkqQv16siryxxnlm7Y9fo64Nk1j/eV506muE3Ut4D7gReNvSgi9gaeD1xVudZVwOKIeHTl2FJgBLi2RfVLkiRJapJlixfQN3fOTsd6ZeR1ycIBFh7az1MPP4Drzz7ekNzFJtv1+sdTvG5m5pF1NrwHuKbmfeeXf/xmZj5QHlsBnBMRWyhGh99MEfQ/XHnpxcAbgdUR8T7gCOBc4APeQ1mSJEnqfo68zjxrBodYuXYjm4dHmNcjf1+TTb3ejcl3uR7PI7atboIVFPUsBw4EbgKem5m/HGuQmVsi4gTgIopbQQ0DF1KE5RnNnVAlSZI0W7R7g1l/x566sV3Kx9Ze98ou5ZNt5jW/TXXUvu8nKG5FVT2WFLtjv2eS194KHN+q2iRJkiRJhV7dpbwta5Qj4r9FxCva8V6SJEmSpPbo1V3K27WZ118DH2/Te0mSJEmS2mCi3chn+i7l3bDrtSRJkiSpyZauWv/wXket0qu7lHfDfZQlSZIkSTPQ2Drk2bbrtSRJkiRJE1qycGDGB+NaTr2WJEmSJKnCoCxJkiRJUoVBWZIkSZKkCoOyJEmSJEkVbualR7jijGM7XYIkSZIkdUy7RpSjfEiSJEmS1NUaCsoR8bGIOGWSNn8VER+rHsvMczPTad4a1xVnHOsotiRJkqSu0Wh4fRXwpEna/BnwyilVI0mSJElSh7VilHdPYLQF15UkSZIk1WHN4BCDm4a54c57WbRiHWsGhzpd0owylaCcE52IiD2BZwK/mHJFkiRJkqQpWzM4xPLVG9g6uh2AoeERlq/eYFhuwKS7XkfEj2sOnRkRrx6n6RzgYIoR5YubUJskSWqBsVGGraPbWbRiHcsWL2DJwoGWvZ/7UEhSe61cu5GRbTtP8h3ZNsrKtRtb+u99L6nn9lC7sWMUOZl4B+ttwAbga8C7m1KdJElqqolGGQB/eZKkHrF5eKSh43qkSYNyZs4f+3NEbAcuzMzzWlmUJElqDUcZJKn3zevvY2icUDyvv68D1cxMja5RfjbwyVYUIkmSWs9RBknqfcsWL6Bv7pydjvXNncOyxQs6VNHMU8/U64dl5rXVryNiX2A/4L7MvL+ZhUmSpOZzlEGSet/YDKGzrryFraPbGejva/l+FL2m4V2vI2JORJwdET8EtgB3AVsi4ofl8YbCtyRJap9eHmXwViiSZoIrzji2LZscLlk4wMJD+3nq4Qdw/dnHG5Ib1FCojYg9gK8Az6LY2OunwM+BPwbmA+8BToyIv8zMrc0tVZIkTVevjjK4SZkkqZkaHVF+M3Ac8GXgCZk5PzOPLTf8WgB8EXhG2U6SJHWhXhxl2NUmZZIkNarRoHwa8F/Aksy8o3oiM38EnAp8H3hpc8oTOJVMkqTJuEmZJKmZGg3KjwWuyszt450sj18FHDndwlSYaCqZYVmSpB0m2ozMTcokSVPRaFDeCjxqkjb7ANumVo5qOZVMkqTJ9fImZZKk9ms0KN8C/E1EHDzeyYg4CPgb4HvTLUwFp5JJkjS5JQsHOP/Uo9ljTvGrzUB/H+efenRPrL+WJLVfo0H5IuBg4MaIeG1EHBERfRFxeES8GrihPH9RswudrZxKJklSfXpxkzJJUmc0FJQz8zPACuAw4BLgDuAB4IfA/wUOB1aW7dQETiWTJEmSpPZq6D7KAJn51oj4AvBaYCGwH3AfMAh8LDPXN7fE2a1X73cpSZIkqbWuOOPYTpcwYzUclAEy89vAt5tciyawZOEAl924CbCzS5IkSVKrNTT1OiLeHhHPnKTNMyLi7dMrS5IkSZKkzmh0M69zgeMmafNM4B1TKUaSJEmSpE5rNCjXY3dgewuuK0mSJElSy7UiKD8ZuKcF15UkSZIkqeUm3cwrItbVHHpVRBw3TtM5wCEUt466bPqlSZIkSZLUfvXsen1c5c8JzC8ftbYDvwauAM6cZl2SJEmSJHXEpEE5Mx+enh0R24FzM/O8llYlSZIkSVKHNHof5VcDN7eiEEmSJEmSukFDQTkzP9mqQiRJkiRJ6gYN7XodEadExBURcWdEPBARv4mIH0fEZRHxvFYVKUmSJM0kS1etZ+mq9Z0uQ9IU1TWiHBH7AJ8BTgSi5vQ+FJt7/Y+I+DKwNDNHmlmkJEmSJEntUu+I8irgJIr7I78beA7wBOCJ5Z/fS7Hj9fOAi5tfpiRJkiRJ7VHPfZSfBJwG3AI8NzPvrmlyO7AuIj4EfBV4WURckJm3NL1aSZIkSZJarJ4R5dMo7p/8inFC8sMy81fAKyimZp/WnPIkSZIkSWqveoLyU4Hv1jNCnJnfA74DPG26hUmSJEmS1An1BOXHAd9t4JrfKV8jSZIkSdKMU09Q3g+YcMr1OO4B+qdWjiRJkiRJnVVPUO4DtjZwzW3AXlMrR5IkSZKkzqr39lCSJEmSJM0Kk94eqvSqiDiuzrbzp1aKJEmSJEmdV29Qnk9jATgbrkSSJEmSpC5QT1B+disLiIgXAS8HnkyxcdhG4J8y87Kadq8DzgIOAb4PnJWZX6tpMwBcBDwX+B1wednuwVZ+D5IkSZKk3jFpUM7Ma1tcw5uBO4EzKXbMPhm4NCIOyswPA0TEi4GLgXOB64BXA1+KiKdk5n+VbXYH1lJsPLaUYuftD5TPL2vx9yBJkiRJ6hH1Tr1upedn5j2Vr9dFxDyKAP3h8tg7gU9m5rsAIuJaYCFwNjtC8IuAJwCPzcw7y3bbgMsj4p2ZeUfrv5XWueKMYztdgiRJkiTNCg0H5Yh4FrAImEexFvnnwPVTHXmuCcljBoEXlO93BPB44E2V12yPiM9WjwEnAf85FpJLayhGmE8EZnRQliRJkiS1R91BuQzI/wdYMHaofM7y/O3A3zVpqvbTgVvLPx9VPt9e0+Y24ICIODgz7y7b3VptkJlbI+JHlWtIkiRJkrRLdQXliHghcFnZfjNwDfBTirD8GOA4imnPX42IF2fm6qkWFBEnUIwmv6Y8tH/5PFzTdEvl/N3lc22bsXb7j3NckiRJkqRHmDQol+uFPwn8Hvh74P9m5mhNm92A1wL/G/hURHw7Mzc3WkxEzAcuBT6fmZ+oOV17y6kY5/h4t6WKCY6PvefpwOkAhx56aP3FSpIkSZJ60m51tPkHYG/gpZm5qjYkQ7FmODM/Cry0bPum2jaTiYgDgKuATey8S/XYyHF/zUvGvh6utKttM9ZuvJFmADLzksw8JjOPOfjggxstW5IkSZLUY+oJyicCN2Tm5yZrmJlrgBsoNtaqW0TsDXwJ2AN4Xmb+tnJ6bG1y7Trjo4B7y/XJY+12ahMRewBH8Mj1zZIkSZIkjaueoHwY8K0GrvktYH69jcv7H38WeBxwUmb+qno+M38M/IDi9k9jr9mt/PqqStOrgKdExGGVY6cAewJfaaB+SZIkSdIsVs9mXnMpbrFUr23AnAbafwQ4mWK69gER8bTKucHMfAg4F/h0RNwFXA+8kiJYn1ZpeyXwj8DqiDgH2A+4ELh0pt9DWZIkSZLUPvUE5Z8DRzdwzT8BftFA+78snz84zrnDgbsy87KIeBTwFuAc4PvAX2Xmf401zMxtEXEicBHwGeAh4HJgWQO1SJIkdZU1g0MMbhpm6+h2Fq1Yx7LFC1iycKDTZUlST6snKH8DOC0ijsrMXa71jYgnAIuBf6u3gMycX2e7jwIfnaTNz4Al9b63JElSN1szOMTy1RvYOrodgKHhEZav3gBgWJakFqpnjfJFFNOvvxQRT5yoURmSv0gx7fqfm1OeJEnS7LVy7UZGtu18w5GRbaOsXLuxQxVJ0uww6YhyZn4nIlZSTGH+bkSsBr4G/JTi/sSHAs8B/ppi1+oLMvOm1pUsSZI0O2weHmnouCSpOeqZek1mviUifgu8DXgxsLSmSQCjwLsoNt6SJEnSNM3r72NonFA8r7+vA9VI0uxRz9RrADLzPIqdpt8FfJ3i3sQbgWvKY4/PzHdkZragTkmSpFln2eIF9M3d+WYifXPnsGzxgg5VJEmzQ10jymMy8yfAO1pUiyRJkirGNuw668pb2Dq6nYH+Pne9lqQ2mDQoR8SewDeB3wAnZua2CdrtAVwF7AM8Y6J2kiRJqt+ShQNcduMmAK4449gOVzNzeZstSY2oZ+r1S4EnU2zSNWH4zcytwErgL8rXSJIkSR030W221gwOdbgySd2qnqB8KvDjzPyPyRpm5leAO4AXTbcwSZJmk7HRrhvuvJdFK9b5C7zURN5mS1Kj6lmjvBCYNCRXfAM4eWrlSJI0+0w02gU4NVRqAm+zNTO51ECdVM+I8kHALxu45i+BA6dWjiRJs4+jXVJrTXR8VhvuAAATKElEQVQ7LW+zJWki9QTlEeBRDVzzUcDvplaOJEmzj6NdUmt5my1JjaonKP8UeEoD1zwG2DS1ciRJmn0c7ZJaa8nCAc4/9Wj2mFP86jvQ38f5px7t0gZJE6onKF8DPC0ijpmsYUQ8GXg68PVp1iVJ0qzhaJfUeksWDrDw0H6eevgBXH/28YZkSbtUT1C+CEjgsxHxhIkaRcRRwGeBUeAjzSlPkqTe52iXJEndZdJdrzNzY0ScB5wLDEbElcA64GcUAfoxwAnAC4E9gbdnpruPSJLUgCULB7jsxmLlkju9SpLUWfXcHorMPC8ifg+8AzgNeElNkwC2Af+Ymec3t0RJkiRJktqnrqAMkJnvjYh/A14DLAL+mCIgbwauAz6emT9pSZWSJEmSJLVJ3UEZoAzC72hRLZIkSZIkdVw9m3lJkiSpxtJV61m6an2ny5AktYBBWZIkSZKkCoOyJEmSJEkVBmVJkiRJkioMypIkSZIkVRiUJUmSJEmqMChLkiRJklRhUJYkSZIkqWL3ThcgSZKk7nHFGcd2ugRJ6jhHlCVJkiRJqjAoS5IkSZJUYVCWJEmSJKnCoCxJkqSOWbpqPUtXre90GZK0E4OyJEmSJEkVBmVJkiSpidYMDjG4aZgb7ryXRSvWsWZwqNMlSWqQQVmSJElqkjWDQyxfvYGto9sBGBoeYfnqDYZlaYYxKEuSJElNsnLtRka2je50bGTbKCvXbuxQRZKmwqAsSZIkNcnm4ZGGjkvqTgZlSZIkqUnm9fc1dFxSdzIoS5IkSU2ybPEC+ubO2elY39w5LFu8oEMVSZqK3TtdgCRJktQrliwcAOCsK29h6+h2Bvr7WLZ4wcPHJc0MBmVJkiSpiZYsHOCyGzcBcMUZx3a4GklT4dRrSZIkSZIqDMqSJEmSJFUYlCVJkiRJqjAoS5IkSZJUYVCWJEmSJKnCoCxJkiRJUoVBWZIkSZKkCoOyJEmSJEkVBmVJkiRJkioMypIkSZIkVRiUJUmSGrRmcIjBTcPccOe9LFqxjjWDQ50uSZLURAZlSZKkBqwZHGL56g1sHd0OwNDwCMtXbzAsS1IP6bmgHBFPjIivRcSDEbE5Is6LiDmdrkuSpG5yxRnHcsUZx3a6jBlp5dqNjGwb3enYyLZRVq7d2KGKZi5H5iV1q907XUAzRcT+wNXArcALgCOBCyg+EHhbB0uTJEk9YvPwSEPHNb6JRuYBliwc6GRpktRbQRl4PdAHnJqZ9wNfjYh9gXMj4v3lMUmS1KPaMUo+r7+PoXFC8bz+vpa/dy/Z1ci8QVlSp/Xa1OuTgLU1gfhyivD8rM6UJEmSesmyxQvom7vzqq6+uXNYtnhBhyqamRyZb441g0MsWrGOw8/+csunr7fzvaRO67WgfBRwe/VAZm4CHizPSZIkTcuShQOcf+rR7DGn+DVqoL+P80892lHQBk00Au/IfP3Gpq8PDY+QtHZjuXa+l9QNei0o7w8Mj3N8S3lOkiRp2pYsHGDhof089fADuP7s4w3JU+DI/PS1c2M5N7HTbNNra5QBcpxjMcFxIuJ04HSAQw89tIVlSZIkaczYhwtnXXkLW0e3M9Dfx7LFC/zQoQHtnL7uVHnNNr02orwF6B/n+H6MP9JMZl6Smcdk5jEHH3xwS4uTJEnSDo7MT087p687VV6zTa8F5dupWYscEYcA+1CzdlmSJEmaydo5fd2p8pptem3q9VXAsoh4dGb+pjy2FBgBru1cWZIkSVJzjY3Ar1y7kc3DI8xr4fT1dr6X1A16LShfDLwRWB0R7wOOAM4FPuA9lCVJktRrliwcaFtYbed7SZ3WU0E5M7dExAnARcAXKdYlX0gRliVJkiRJmlRPBWWAzLwVOL7TdUiSJEmSZqZe28xLkiRJkqRpMShLkiRJklRhUJYkSZIkqcKgLEmSJElShUFZkiRJkqQKg7IkSZIkSRUGZUmSJEmSKgzKkiRJkiRVGJQlSZIkSaowKEuSJEmSVGFQliRJkiSpwqAsSZIkSVKFQVmSJEmSpAqDsiRJkiRJFQZlSZIkSZIqdu90AZIkSZq9rjjj2E6XIEmP4IiyJEmSJEkVBmVJkiRJkiqcei1JktTlnJ4sSe3liLIkSZIkSRUGZUmSJEmSKgzKkiRJkiRVuEZZkiRpClw3LEm9yxFlSZIkSZIqDMqSJEmSJFUYlCVJkiRJqjAoS5IkSZJUYVCWJEmSJKnCXa8lSeoS7qIsSVJ3MChLkiRJTeYHX9LM5tRrSZIkSZIqDMqSJEmSJFUYlCVJkiRJqnCNsiRJkmYF1w1LqpcjypIkSZIkVRiUJUmSJEmqMChLkiRJklRhUJYkSZIkqcKgLEmSJElShUFZkiRJkqQKg7IkSZIkSRUGZUmSJEmSKgzKkiRJkiRVGJQlSZIkSaowKEuSJEmSVGFQliRJkiSpwqAsSZIkSVKFQVmSJEmSpIrIzE7X0DUi4m7gJ52uo0scBNzT6SKkNrPfa7axz2s2st9rtrHP7+ywzDx4skYGZY0rIm7KzGM6XYfUTvZ7zTb2ec1G9nvNNvb5qXHqtSRJkiRJFQZlSZIkSZIqDMqayCWdLkDqAPu9Zhv7vGYj+71mG/v8FLhGWZIkSZKkCkeUJUmSJEmqMCi3WUS8KCK+EBFDEfFARHwnIl4yTrvXRcQdEfG7ss0JNecPjogPRcSNEbE1Iu6a4P0ujojby/faEhHfiIjnNFBvU+rYxfUHIuJzZX33RMRFEbF35fy+EfHO8vr3RcQvyvaPb+R91Dn2+Udcf5d9vmyzZ0R8oOzvD0bENyPC3SpnEPv91F4bEYdFxGURcW/Z978XESfW+17qHPv8Tq99TkRcERE/Kfvxf0XEGyJiTk27d0bEhoi4PyJ+ExE3RcTSet9HnWe/3+m1z4qIr0fEryLioYj4cURcEBH7NlpHtzAot9+bgQeAM4FTgK8Dl0bE3481iIgXAxcDnwJOAr4PfCki/rRynQFgKfAL4OZdvF8fcBHw18DLKO6hdlVEPG2yQptcx3jX3x1YCxxWXuNNwIvYeR3FocDrynZ/A5wB/DFwQ0Qc0sj7qWPs8zuuX0+fB/gQ8FrgXOCFFD+/qyPisEbeTx1lv2/wteW/6euBfuDVFD+3fy2/N3U/+/wOpwP7AG8DTgYuBy4A3l/Tbl/gE+X7vBD4LnB5RPxNg++nzrHf73AAMAj8T2AxRZ9/JXDpFOroDpnpo40P4KBxjl0K3Fn5eiPwscrXuwEbgE9Xj1X+/E/AXXW+/xxgE/ChOtq2rI6y/UuAUeDwyrH/AWwHHld+vQ/QV/O6Ayj+UXpHp/8+fdT192yf39G+nj7/GOD3wGsqbfYEhoCLOv336aPuv2v7fYOvpQgT36y29zFzHvb5SX8W7wVGgD0nee31wBc6/ffpY1p/17Oy30/wnq8DEjigkTq65eGIcptl5j3jHB4E/gAgIo4AHg98pvKa7cBnKT51qR6byvuPAsPAHrtq1+o6SicB/5mZd1aOrQG2AieW1/9tZo7UfA/3Aj+h/Jmpu9nndzJpnweOpvgf39WV93yIIkA8bxrvrTay3+9Uy6SvjYj9gFOBj0zzvzF1iH1+p1om+lnsRTGKvCu/ZpLvQd3Dfj+pX5fPezRSR7cwKHeHpwO3ln8+qny+vabNbcABEXFwoxePwu4RcWBEnAk8DvjYJC9reh0TvMdO18/MrcCPKu//COV7P5YdPzPNPPb50jh9fq/yeWvNax8CDoua9cyaUWZrv6/HnwNzgYyI6yNiW0T8LCKWR0S0qQY1n31+h6cD92Tm3bUnyu+hPyJeCvwlxbRUzVyzut9HxJwo9lp5EsXyg9WZ+Yt219EMBuUOKxevvwD45/LQ/uXzcE3TLTXnG7EU2EaxjuFdwNLMvHGS17SijvHeo/b6Y++xq+tfQDH1+vIm1KA2s89P2ud/WD4/ZexkGRSeAgTF+k3NMLO839fjj8rnVRSzJ/6S4he/dwN/26Ya1ET2+R0i4onA69nxs6ieexrF97CFYr3ymzJzTbNrUHvY74FizfHvKEbWfwW8vEN1TNvunS5gNouI+RTrGD6fmZ+oOV17g+uY4Hg91lL8kn0Q8FKKjSJOzsxryjqq/SDLaRxNqyMidmPnD2VGs1yUMMF1YqLrR8TfUmxe8MLM/PV4bdS97PMTXufhPp+ZGyLieuCfImIzxdqjN1NMVYJijbNmEPt9XcZed1Vmnl3++esR8RhgOfCReutQ59nnd2qzP/DvwC0U65RrbSi/h36K5TUXRcT9mXlZvXWoO9jvH/ZCYD+KpWRvBz4bEX9V06aZP4+WcUS5QyLiAOAqil+CX1Y5NfaJSu2o0djX441G7VJmbsnMmzLzK5n5copdRc8r65hP8anU2ONHLajjYzXv8crKe4w3OtY/3vUj4hTgw8BbMvNzDby/uoB9/uH3qKfPvwp4ELiJ4tPY5wMfLK91bwN1qMPs93Ub69dfrzm+DnhMjHN7EXUn+/wOEbEX8HmKDRlPKZfa1H4Pvy2/h6sz80yKnd7f10AN6gL2+53q+35mfiszV1FsYnoy8OwW1NFyjih3QLnG8EsUC9ufl5m/rZwem7N/FMWGVVS+vne8tS1TMAi8uPzzZipTPCnWQTa7jnMptrIfM7aR0e3UrEWOiD2AI6hZnxMRT6eYan1xZq5s4L3VBezzjfX5zPwhsLDc9GIu8AOKD4m+m5nbGqhDHWS/f7jf1+O2CY6PjTK4wdcMYJ/f0eejuGfypcCfAE/PzF/Wec3vAq+OiLn+ez8z2O93+W/9d8vnIyg++GzHz6NpDMptVk6H+CzFwvtFmfmr6vnM/HFE/IDi3qpry9fsVn59VRPeP4BjKTt1+enmTbXtmllHZt4F3DXOqauA0yLisMwc+4/lFIpPXr9SqflPKP4B+grwxkbeW51nn99JXX2+WlNZx0EUt5H6x0bqUOfY7xuTmXdFxPeBEyjWKY85AfhRZj4wleuqfezzj/ARirsZPCczNzZw2UXAzwzJM4P9flKLyuex+lr682g2g3L7fYRiCsKbKHZ3q94gfDCL28CcC3w6Iu6iuJ/eKyn+AzyteqHYcUP6xwN7V76+NjPvjohnAP8LWE0xFeTA8lpPo5jKOZmm1LGL619J8Yv/6og4h2I9w4XApZl5R3ntP6AIEA8AHwL+InZsgHp/Zrrzdfezz+8waZ8vr/9GilsqDJXvv5xiHdu/1PE9qDvY7xt/7TnAv0fESuD/AcdRbALzijq+B3WefX7H694KnA6cD2yv+Vncmpn3R8RhwMcpRp1/DDwK+GuKkUE3sJs57Pc7XvevFDPgbqZYPvbnwFkUU8Ory2rqqqMrZBfczHk2PSg+gckJHvMr7V5HsfvtQxTTFk4Y51oTXee48vx8il/Mf1Ze52cUI7PHNlDvtOuY5PqPobiP7AMUweCfgb0r54/bxfWv6fTfpw/7fLP7fNnmLRSfvj4E/JRivdre9X4PPjr/sN9P7bUUa/tuo7g92g+B13f679JH3X3IPr/jddfU8T3sB3y6/Ln9DvgFxdTUkzv9d+nDfj/Ffv/3wHeA+yh+x9lA8QHoo6ZSRzc8oixWkiRJkiThrteSJEmSJO3EoCxJkiRJUoVBWZIkSZKkCoOyJEmSJEkVBmVJkiRJkioMypIkSZIkVRiUJUnqIRFxTUR470dJkqbBoCxJUheKiGzw8apO1yxJUq/YvdMFSJKkcb1znGP/AOwHfBAYrjl3c/n8CmDvFtYlSVLPi0xnZ0mSNBNExF3AYcDhmXlXZ6uRJKl3OfVakqQeMt4a5Yg4rpyefW5EHBMRX4mI+yJiS0T8e0QcUrY7IiIuj4i7I2IkIr4eEX82wfvsHRHLI+LmiPhtRDwQEesj4iXt+D4lSWolg7IkSbPHU4Bvln/+KHAjcCrwtYg4qvz6McCngC8DzwK+GhGPql4kIvqB64D3AqPAx4BPAgcDl0bEu1v/rUiS1DquUZYkafY4GXhZZv7b2IGI+BfgNcC3gAsy8z2Vc+cA5wGvpVgXPeZ/AwuBt2Tm+yvt9wLWAG+NiCsz82YkSZqBHFGWJGn2uK4akkufLJ/vA1bUnPtU+fyksQMRcSDwMuCmakgGyMzfAW8BAjitWUVLktRujihLkjR73DTOsc3l882ZOVpzbqh8fkzl2FOAOUBGxLnjXG9u+fyEqRYpSVKnGZQlSZo97hvn2O8nOpeZv48I2BF+AQ4sn59SPibyqF2ckySpqzn1WpIkNWIsUF+YmbGLx7M7WqUkSdNgUJYkSY24EdgOPKPThUiS1CoGZUmSVLfM/BXwb8AxEXFORDxiGVdEHBkRh7e/OkmSmsM1ypIkqVFvAB5Hceuol0fEdcAvgXkUm3g9BXgJcGfHKpQkaRoMypIkqSGZeX9EPAs4neI2UC8E9qIIy3cAZwJf7VyFkiRNT2Rmp2uQJEmSJKlruEZZkiRJkqQKg7IkSZIkSRUGZUmSJEmSKgzKkiRJkiRVGJQlSZIkSaowKEuSJEmSVGFQliRJkiSpwqAsSZIkSVKFQVmSJEmSpAqDsiRJkiRJFf8fMvG6GdcixxIAAAAASUVORK5CYII=\n", "text/plain": [ - "(2.4506423271968965, 0.6721532140851265)" + "
" ] }, - "execution_count": 29, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "dataset.calc_ratio('CODtot_line2','CODsol_line2',\n", - " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)])" + "dataset.calc_daily_average('CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,2,1)],plot=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "To find the 'best' ratio (i.e. the one with the lowest relative standard deviation ($\\sigma/\\mu$)), the ratio obtained in different periods can be compared and the best one used during possible further replacements." + "Calculate the proportional concentration of different flows coming together." ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 36, "metadata": { "ExecuteTime": { - "end_time": "2017-05-09T09:55:03.978297", - "start_time": "2017-05-09T11:55:03.919697+02:00" + "end_time": "2017-05-09T09:55:07.842239", + "start_time": "2017-05-09T11:55:07.833046+02:00" } }, + "outputs": [], + "source": [ + "dataset.calc_total_proportional('Flow_total',\n", + " ['Flow_line1','Flow_line2','Flow_line3'],\n", + " ['TSS_line1','TSS_line2','TSS_line3'],\n", + " 'TSS_prop')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Data with drift\n", + "Finding and replacing a dataset with drift." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Best ratio (2.5328218826106403 ± 0.16586491872475548) was found in the range: [Timestamp('2013-01-19 00:05:00') Timestamp('2013-01-21 00:05:00')]\n" + "No drift detected.\n" + ] + } + ], + "source": [ + "dataset.detect_drift(data_name='CODtot_line2', arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=20, \n", + " plot=True, period=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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MevfunfuCeQgICHA/ztohqaivAyA4OLhI9yktha7xYIyZbIw5YYzZnK1tujFmfebXPmPM+sz2JsaYxGzH3s92zkXGmE3GmF3GmLeN9pESERGRMpaclkzzt5szetZod9vlzS7H39e/TO7/3IDnuLbttWVyLxERKVyfPn2YPXs2iYmJxMXFMW/ePPexuLg46tatS2pqKtOmTXO3V6tWjbi4uEL7ZdewYUOio6PZuXMnzZo147LLLmP8+PF5Fh7+eP2Svo6iKs59i6ooi0tOAQZlb7DW3mit7WKt7QLMAr7Mdnh31jFr7T3Z2icCdwEtM79yXFNERESktD3w7QPsObOHzzd/TlJaUpnfPy45jsTUxDK/r4iI5K1bt27ceOONdOnSheuuuy5HIeC5556jZ8+eDBw4kDZt2rjbR40axauvvkrXrl3ZvXt3vv3+qGfPnrRq1QpwTb04fPgwl112Wa5+Q4YMYfbs2TkWlyzJ6yiqmjVr0qtXLzp06ODxxSVNfsM0cnQypgnwtbW2wx/aDXAAGGCt3VlAv7rAImttm8zno4F+1tq7C7t3VFSUzVpoQ0RERKQkVh1eRY//9qBFjRbsfGBnmd8/4pUIRnUYxYTBE8r83iIi5dGaNWtyLIIo5deaNWtYtmwZAwcOpH379gAYY9ZYa6MKO7ekazz0Bo5ba7P/5G5qjFkHxAJPWmuXAfWBQ9n6HMpsy5Mx5i5coyNo1KhRCSOKiIiIwPgV41l7dC0nHjlBZHCkYzmK8qGPiIiINylp4WE08Fm250eBRtbaU8aYi4A5xpj2kOfeUfn+1LXWTgImgWvEQwkzioiISCWVkJpA8L/PL6hVo2oNR4sOWuJKREQqo2IXHowxfsAIwD0uxlqbDCRnPl5jjNkNtMI1wqFBttMbAEeKe28RERHxTmeTzhIaEOqxX9C3ntya43lqeqpHrlsSNv/PXkREKqWMjAx8fIqy/KA4JSMjo0Tnl+T/7hXANmutewqFMSbSGOOb+bgZrkUk91hrjwJxxpiLM9eFuA34qgT3FhERES+z58weqr9cnYmrJ3rsmlmFh6nXTqVuSF3ev+b9Qs4oXSbPQaAiIpVXUFAQx44dK/EvtlJ6MjIyOHbsGKmpxS/eFzriwRjzGdAPiDDGHALGWWs/BEaRc5oFQB/gWWNMGpAO3GOtPZ157F5cO2RUBb7N/BIREREBYF/MPgCWH1jOfd3v88g1Z2yZQVW/qoxsP5KbO93skWuWxKOXPkq7yHZOxxARKTeaN2/O77//zpEjRzQdrRxLTU3lwIEDAMUanVJo4cFaOzqf9rF5tM3Ctb1mXv1XAx3yOiYiIiJSK7gWACPajvDI9V5f+TpjOo/h6X5PU8W3ikeuWVKP9vLs9mQiIhWdv78/TZs2ZerUqRhjCAwMdDqS5CMlJQUfHx9q1ap1weeWdHFJEREREY9Iy0gDwM/HM29P/v7D3wGw48rPmgpH444S6BdIeNVwp6OIiJQboaGhjBgxguXLlxMfH+90HMlH9erV6dWrFzVr1rzgc1V4EBERkXIhNjkWgPk75zO8zXCPXfdM4ply84t+1/90ZXib4Y6vNSEiUt7UqVOH66+/3ukYUkq0dKiIiIiUCx1qdcjxvaRuaHcDAD5Gb3dEREScpJ/EIiIiUi74ujbGck+5KKn3rn6PHffvICwwzCPX8xRry8/UDxERkbKgwoOIiIiUC1tObgFg3bF1JbrOr4d+5eYvb6b///qTnJ7siWgeoxXbRUSkMtIaDyIiIlIunEk8A8DpxNOF9CzYl79/yaebPqWqX1UahDbwRDQREREpARUeREREpFxpFNqo2Oc+u+RZXlnxCgB1QupQPbC6p2J5xLi+42ge3tzpGCIiImVKhQcREREpFyyutQ/+3O3Pxb7G+6vP7xbRrW63EmfytHui7nE6goiISJnTGg8iIiJSLmQtKunnU/zPRVLSU9yPJw2ZVOJMnrb79G6OxR9zOoaIiEiZUuFBREREiu3Vn1/l2unXXvB57/z6DvVfr8/c7XPZeWon8Snx+Pv6A/Cvn/7FjTNvZFv0tgu+7qnEUwBsvnczNarWuODzS1ufKX146qennI4hIiJSpjTVQkRERIrtsQWPFblvbHIswVWCSc1I5cHvHgRg2OfD3Mf7Nu5LVb+qzN85H4AZW2Yw/6b5tI5oTURQBKEBoQVePyktyf24SfUmF/AqylbWlBIREZHKQoUHERERKTXpGenEJMVwwxc3sGjfohzH7o26l4mrJ7qfL9m/hCo+VXL0GfzpYPfj+MfjCfYPzvde/137X/fj7ae2l8s1HgzaTlNERCofFR5ERESk2DrV7sTG4xtztV82+TJ+PvhzgefeG3Uv/Zr0I6peFFtObGHo50NJzUjNt//w6cMZ03kMt3S6Jdexw7GHeeDbB9zPy9tuFtlZqxEPIiJSuajwICIiIrlsOr6JKz65gnF9x3Ff9/vy7bfhng3ux9uit/Hyzy/jg0+uosMjlzxC5zqd6dekHz/s/oGR7UcS4h9Cx9odAQgPDMdgCpyGsGDPAhbsWUCP+j1oVbMVAImpiaw/tp5LJ1/q7vfu4HdpWr1psV53aTNGIx5ERKTyMeW96h4VFWVXr17tdAwREZFKZe72ue71F2L/GUu1gGq5+sz+fTZv/foWzcKbMXPrTOJS4nIcv63zbXy84WMe6vkQbwx6o9B7nko4xYGzB6gfWp+aVWvy3qr3ePu3t9l1eleOfq1qtuLaNtfy8s8vExEUQXRCtPvYFc2u4MdbfyzOSy4Tn276lPrV6tO3SV+no4iIiJSYMWaNtTaq0H4qPIiIiFQc0QnRrD26lp71exIWGFZq9/ny9y+5bsZ1ABx8+CANQhvkOH4s/hh1X6ub57n/6PUPOtTqwKgOo0q0NWZ2Xf/TlfXH1hfaL6+sIiIiUjqKWngodDtNY8xkY8wJY8zmbG1PG2MOG2PWZ34NznbscWPMLmPMdmPMldnaB2W27TLG/LM4L0pERKSy+/XQr1w59Uo+Wv9Rqd4nNf38WgsxSTFsObGF1hNa89qK1zDPGG7/6vYc/R+++GE+GPIBC25dwEtXvMQtnW7xWNEBYN3d63JM68jL1vu2lvuiw8bjG9l7Zq/TMURERMpUUd4RTAEmAB//of0Na+347A3GmHbAKKA9UA9YYIxplXn4XWAgcAhYZYyZa63dWoLsIiIilc6OUzsAePj7h3no4odK5R4nz51k+pbp7uefbPiEV1a8AsAjPz4CQLuIdoQGhDJ56GQ+3vAxt3W+rcAdJzxh4Z6F+R6LDIqkbWTbUr2/Jwz5bAgDmg7go2GlWzgSEREpTwotPFhrlxpjmhTxesOAz621ycBeY8wuoEfmsV3W2j0AxpjPM/uq8CAiIlIEj/7wKFtObmHrydL/0Tlo2iDWHl3rfp5VdMi+g8ULl79AoF8gAPd2v7fUMwGM7TKWBXsX8MaVb9B6QmsAutfrTp/Gffhbz7+VSQYRERG5cCUZA3m/MeY2YDXwd2vtGaA+8Eu2Pocy2wAO/qG9ZwnuLSJ/MOCZASxiEWcfOUtocKjTcUTEw8avHF94Jw/YHr3dXXQY1noYN3e8mUX7FjFx9UTu734/LWq0oEWNFu6iQ1kKrxrONzd9A8CW+7ZQN6Qu4VXDyzxHSZX39bVEREQ8rbiFh4nAc4DN/P4acAeQ1x5RlrzXksj3p64x5i7gLoBGjRoVM6JI5bLy7EoIg5hzMSo8iHiZ3ad352ob3mZ4ia87ffN01hxdwysDX3G3tXm3jfvxk32eJKpeFDe0v4F3B79brraCbBfZzukIxWLyfKskIiLi3QpdXDIv1trj1tp0a20G8AHnp1McAhpm69oAOFJAe37Xn2StjbLWRkVGRhYnokil06dGHwBCg1R0EPE22ddbyDKgyYASX3fUrFG8uuJV9/PktGT34+9u/o6oeucXqS5PRQcRERGpWIpVeDDGZN8/61oga8eLucAoY0yAMaYp0BL4DVgFtDTGNDXG+ONagHJu8WOLSH58TLH+WotIOZaWkZar7cHvHvTY9bOG/u+Nce220K9JP65scWVBp0gxvX3V29wTdY/TMSQP7339HtFno52OISLilQqdamGM+QzoB0QYYw4B44B+xpguuKZL7APuBrDWbjHGzMC1aGQa8FdrbXrmde4Hvgd8gcnW2i0efzUildhPMT9BNTgTf0ZTLUS8zOHYw6Vy3drBtTl+7jhpGWlk2Awu+fASAP5+yd9L5X4CQ1sPdTqC5OHnLT/z1zV/5ZVFr7DvtX1OxxER8TpF2dVidB7NHxbQ/wXghTza5wPzLyidiBRZ96rdWclKqvpXdTqKiHjYudRzReq3P2Y/J86doHv97gX2i06IJvLVSEa2H8n4geOpNb4WMUkxAAxsNpCrW15d4sySt18O/UJoQGiFXaPCWx07c8z13R5zOImIiHfSmGwRL1E9sLrTEUSklEwdMZX9D+0vsM+WE1to8lYTevy3R452ay0JqQk52mZsmeH+vufMHnfRAWD8n8ZrPYdSdNOsm3hp+UtOx5A/aFqnKQCX173c4SQiIt5JhQcRL7E+ej0ASalJDicRkdJQO7g2AG0i2uRoT05LZuhnQ+kwsUOe5y3Ys4DGbzbmTOIZd1uP+q7ixJBWQ+jbpC/JTyYz/6b5bLp3E51qdyqlVyBZbP4be4lD/Hxcg4DDfMMcTiIi4p1UeBDxEscCXcND09PTHU4iIp4UnRDNsM+H8dPen/j+lu9Zdvsyrm93PQCJqYkEvhDIvB3z3P271OmS4/y0jDSiE6LZdGITACfOnWB79HZ2P7ib2TfOBsDf15+rWl5Fh1p5Fy/EczSapHyqGVKT8F/CaVutrdNRRES8UqFrPIhIxRCYFEhiYCJV/Ko4HUVEPGjZ/mXM3T6Xh3o+RP+m/QF4tt+zNA5rzB1z78jVv2udrjmeN6/RHIDfDv9G3yl93e2LxiyiWXizUkwu+cnaRUTKj4SUBM5cfIYNMRucjiIi4pVUeBDxEpeGX8pCu5CIsAino4iIBx2Ld41myj7Fom1kW15b+Vqe/ZPTk4lJinGv+/LCMtd6zx9v+DhHv7YR+mTXCQaNeCiPTsadBGBTzCaHk4iIeCdNtRDxEpozLOKdjsYfxcf4UCu4lrutoO01P930qbtYAZCe4Zp+lTXVAiAiKILaIbVLIa0UZtKQSdqutBw6fvo4APsTC17EVUREikeFBxEvsThuMQDHzxx3NoiIeNSx+GNEBkXi6+Prblu0b1GuftGPRvNMv2cAiE2OdbefTT7rfjys9TCS/pXEiUdOlGJiKciApgPoWrdr4R1FRES8iAoPIl6ifzXX3G8tXCbiXWoF16JXo1452jrW6pjj+VUtrqJmUE36N3H9OxCXHOc+FpscS6uarTj292O8fdXbBPgF6N8JB/209yfWHFnjdAzJh/5uiIiUDq3xIOIlQvxDINnpFCLiac8PeD5XW+c6nTn56ElS0lOo/3p9gqoEARAaEAr8YcRD0lla12ytqRXlxD1f30NUvSg+ve5Tp6NINrXDXX8/rm5wtcNJRES8k0Y8iHiJlcdXAtpOU6SyiAiKoF61egT4BrDz9E4g78LDs/2fpWn1po5kFKkofI1rKlOIb4jDSUREvJNGPIh4iZOBJ52OICKlYPSs0UQGRfL2VW/neTzmnzHunRIahTXi5KMnCQsIcx8f2nooV7fUp7jliRYDLn+aRDYh/Ldwmgxt4nQUERGvpBEPIl4iKMk11LpqQFWHk4iIJ209uZUDZw/kezzQL5AAvwAAfH18iQiKoIpvFQD2xezjcOzhHAtTirO0hkD5lGpTOdPjDGvPrHU6ioiIV1LhQcRLRIVFAVCnRh2Hk4iIJ6Wkp+Dv61/k/s8sfoY52+YAMG7xOLp/0L20ool4jcOnXVvUborZVEhPEREpDhUeRLyEhu6KOOepn57CPGOYuXWmx6+dkp7iHtFQFJ9s/IRpm6YBsOLgCjrX6ezxTFJ8n1z7CU/1ecrpGPIHR6KPAHA05ajDSUREvJMKDyJeYlniMgB2H9ntcBKRyuf5Za6dJ2744gaS0pI8eu2U9BT8fYo+4qFT7U7M3DoT84xh1+lddIjs4NE8UjI96vegXWQ7p2POr3ZaAAAgAElEQVSIiIiUKRUeRLzEkPAhAGRkZDicRKRyS0lP8ej1LmlwCe1rtS9y/1s63ZLj+dguYz2aR0pm3vZ5LNu/zOkYJZKRkcH83+Y7HcOjstbe8PHRW2MRkdJQ6K4WxpjJwDXACWtth8y2V4EhQAqwG7jdWhtjjGkC/A5szzz9F2vtPZnnXARMAaoC84G/WWs1NlzEQ7IWkxMRZyWlJbm3tfSEGTfMuKD+17a5lhnXz6Bx9cZsObHlgooWUvoeW/AYnWp3onfj3k5HKbZrX7mWuclzmRwzmdv/dLvTcTwiLNi1E8x1ja9zOImIiHcqSll3CjDoD20/Ah2stZ2AHcDj2Y7tttZ2yfy6J1v7ROAuoGXm1x+vKSIlsOTIEgAyrEY8iDjJ01MtLpQxhhva30CP+j24vat3/FLobSr65y7rTqwDYP3+9Q4n8RwffCAZQnxDnI4iIuKVCi08WGuXAqf/0PaDtTYt8+kvQIOCrmGMqQuEWmtXZo5y+BgYXrzIIpKXU4GnnI4gIkByWnKBx1PTU/ls02ekZ6Sz+/RuzDOGr3d87T6++shqfj/5O+AqJDZ5swkTfptQqpml7Bgq/naa3riYcacmnai+pTphNszpKCIiXskTE9nuAL7N9rypMWadMWaJMSZrHGF94FC2Pocy20TEQ0ISXZ/SVAuq5nASkcrnyuZXuh9/tf2rHMfGLRpHkzebcPLcSX4+8DMTfpvATV/eROf3O9Nrci8Aluxbwu7Tuxn4yUC6f9Cddu+148VlL7L6yGr2n91PYmpimb4eKV0V/Rf39298n4E+A7n7T3c7HcVjrLHEdIthQ8wGp6OIiHilQtd4KIgx5l9AGjAts+ko0MhaeypzTYc5xpj2kGd5P9+fusaYu3BNy6BRo0YliShSaXQK7cTPGT9Tr2Y9p6OIVDrf3PQNfs+5fqQ++uOjDG45mO92fceYzmN4dumzANQaXyvHOVtObnE/Hr9yPONXjs9x/ImfnoCfXI+DqgSVYnopS1mLGFZkV/e8mqt7Xu10DI/afdy1I9Sm2E0OJxER8U7FHvFgjBmDa9HJm7MWibTWJltrT2U+XoNr4clWuEY4ZJ+O0QA4kt+1rbWTrLVR1tqoyMjI4kYUEREptuiEaOJT4ovU93RijhmJfLPjG/7+w985k3SGYa2H5TiWtfDkHV3uAOAfvf5R6PWdXjdCPOeLG77g5StedjpGiUyYN4GaD9Vk+ablTkfxmEMnXANzo1OjHU4iIuKdijXiwRgzCPgH0Ndam5CtPRI4ba1NN8Y0w7WI5B5r7WljTJwx5mLgV+A24J2SxxeRLCtSVkBV2LJvC+2baBV7keI4cPYA7d9rz/LblzN+5Xg+3/w590Xdx/Fzx3myz5OsPrIaf19/moc3p2eDngAkpCZwyYeX8HTfp3l6ydPA+aH0Ld9p6b52vWr1+EvXv/Bknyfdu9C8eMWL1AquRRWfKjy/7Pl8c8WlxJXSK5ay1i6yndMRSuzlRS9zOvw0M3+dyWUdL3M6joiIVABF2U7zM6AfEGGMOQSMw7WLRQDwY+aQwaxtM/sAzxpj0oB04B5rbdbHQPdyfjvNb8m5LoSIlNDIyJFMj5/udAyRCudo3FHe+OUNnuj9BP6+/sSnxPPIj4+wYM8CAN7+7W0Apm/J+fdr1shZfLvzW6ZvmU5cShzhVcPZ/eBu6oTUIfjfwTn6fnvzt/Rv0p8Av4Ac7bWCXdMvBrUYxPPLnufqllfzzc5vAOjdqDfLDiwD4IneT3j+hYsjvtjyBWGBYfyp+Z+cjlJiFX13juyypsD4+vo6nERExDsVWniw1o7Oo/nDfPrOAmblc2w10OGC0onIBfOmN4IiZWHm1pm8uuJVXl3xKkNaDQFwFx0Kct2M63I8H9JqCE3DmzJjy4wc7ROumsCgFgXvIN2rUS8y/i8DYwy7T++meY3mgGthyjYRbfD39b+QlyTl2LNLn6VVzVZeUXjwJoFVAgG4udnNDicREfFOJVpcUkTKjx8O/gDhTqcQqXhu6ngTD373IADzdszLceyn235i0tpJRAZF8s5v77DqzlV0qdOFkV+MZPa22e5+L17+Ik3DmwIwsv1IRrYfecE5sj5xzSo6ADzT/5kLvo5IWfGGrUGz+Pn4QSyE1A1xOoqIiFdS4UHES8RUjXE6gkiFVDOoJqM6jOLzzZ8D8P0t37P6yGoe6PEA1QKq0b9pf6y13NH1DrrU6QLAlzd+ydg5Y9lxagdzR88lIijCyZcgFYxGppU/l7S9hND9oaQ3Snc6ioiIV1LhQcRLhCaGcjbwLDVCazgdRaTC+GrbVwyfPpyPh3/M/d3vJ6peFAF+AbmGwRtj3EWHLFOGTynDpOItvGGUwLQx0/h42cc8NOwhp6N4jK+fL7EdY9lydkvhnUVE5IKp8CDiJdpWa8svab9Qr2Y9p6OIVBibTmwC4LY5t2HH6VNokaLo07kPfTr3cTqGR23ctxGAzfGbHU4iIuKdfJwOICKekZqeCn6Qlp7mdBSRCiMuWdtUStmaN3oeEwZPcDpGibz4xYsE/r9AFqwpfBHWiuLwycMAxKRp2qKISGlQ4UHES6xLWwfA5n36tEakKJLSknhlxSsAXNLgEofTSGXRuHpj6lUrfyPTHv/f4zR/pDnTfppWaN93V75Lclgy89fPL4NkIiLiDVR4EPESo+qOAiAjI8PhJCIVw/6Y/e7H80bPK6CniOf8b/3/mLNtjtMxcnlp30vsqbaHW5bdwuhXRmP+YSrVCDqLa6qVn59mIYuIlAYVHkS8RNZWfCJSNJtPuEYHVfWrSs2gmg6nkcrijV/eYMr6KU7HKNChs4cgCFJSUwrs5027c/gY11viv7T6i8NJRES8kwoPIl5i3j7XJ7YZViMepGhS0lOYvnm6V/3ycCE2HN8AwPFHjjucRCqbrE/Xy5M6MXUACIkPITAwEMj/54k37MzxR/4+/hANwb7BTkcREfFKKjyIeIm4qlokTy7Ms0ueZdSsUXy942unozhiw/ENtIloQ7WAak5HkUqkvI5OS4hNACAoJYiV8SsBSE9Pz7NveSyclNSV3a+k2slqnDx10ukoIiJeSYUHES9RPbE6AHXC6zicRCqKw3GuVdyjE6IdTlL27p9/P3O3z6VZeDOno0glVB5HGWUV4Bqca8C5gHMApGfkXXj4+p6veb7N8zx+w+Nllq+0+fr6Etc2ju3x252OIiLilVR4EPESzYObQyo0iGzgdBSpIK5rex0AHWt3dDhJ2Tpw9gDvrnqXgc0GMmXYFKfjSCVTXqcpVAtxFR62h5z/xTu/qRZdWnXhXzf+i1phtcokW1lYud01ymPrua0OJxER8U4qPIh4iaS0JKhS+GJgIlmyFlOrbOuCTPhtAgAP9HiAyOBIh9NIZfP9Ld8zZfgUp2Pksi14GwDnws/RxXYBoEZojTz7PjntSXz+6cO8Fd6zG8zhE64RYHHpmrYoIlIaVHgQ8RLb0l1vGtftWudwEqkogqsEc3nTy6kV7D2fWhYmOiGaqRunElUviiGthzgdRyqhyOBIalTN+xf68iLABkDa+eLkH01ZMwVb1bLo90VlnKz0VLYCrIhIWVPhQcRL3NzoZkBvnqTojsQdYeHeha7RMpXEqsOrALi0waUOJ5HK6j+r/8O0jdOcjlGgX6v8Cn5wJvaM01HKTNa6GwFVAhxOIiLinVR4EPES5XXesJRfe2P2AnAo9pDDScrOVS2v4tubv+XlgS87HUUqqQ/WfsBnmz9zOkaR9HyuJyu3rnQ6Rpm6t+29TkcQEfFKRSo8GGMmG2NOGGM2Z2urYYz50RizM/N7eGa7Mca8bYzZZYzZaIzplu2cMZn9dxpjxnj+5YhUXl/s/QLQiAcpul2ndwGwP2a/w0nKRobN4FzKOTrX6UygX6DTcUTKjakLpxIcE5yrfWfITt7+5m0HEpW9AJ8AOAwhfiFORxER8UpFHfEwBRj0h7Z/AguttS2BhZnPAa4CWmZ+3QVMBFehAhgH9AR6AOOyihUiUnIJgQlOR5AKprKNkjkce5iQF0P4aN1HTkeRSs5SfrbT/NsHf+PW5bdyrvq5PI8HBuQu0hnj+rfDx8d7Bs4Ou2wY1ZKqse3gNqejiIh4Jb+idLLWLjXGNPlD8zCgX+bj/wGLgX9ktn9sXZPlfjHGVDfG1M3s+6O19jSAMeZHXMWMijHeUKScC08M53TgaRpGNnQ6ilQQ/r7+wPlfIrzdvph9ANSrVs/ZIFKplbe/b78d+K3Ad4OpNjVX26IHF7Fy20qG9PaeBVqNMcQ1iWNPwh6no4iIeKWSlKprW2uPAmR+z1oWvT5wMFu/Q5lt+bWLiAc0rtoYkqFRrUZOR5EK4uZOrgVJG4VVjj8zWWtaNA1v6nASkfKjSpUqBR4/FJN7DZgWjVtw65W3Uj2oemnFKnMLNy4EX9iWqBEPIiKloTTGyOVVyrcFtOe+gDF3GWNWG2NWnzx50qPhRLxVfFo8BEBCkqZcSNFkTbWoLOuC7Dq9C4OhcVhjp6NIJbZk7BJm3jDT6RhuVzW7Cp/9+b8drOKXuzDxt8l/wzxjmLm4/LyOkjp68igACRn6GSoiUhpKUng4njmFgszvJzLbDwHZx3o3AI4U0J6LtXaStTbKWhsVGRlZgogilcf+dNcCgat3rHY4iVQUcSlxXN70cjrV7uR0lDLx6+FfqRVciwA/bZcnzgmqEkTVKlWdjuH2+C2PM3n05JyN0ecfvjjqxVznzNo8C4CVu71nx4vKUoAVEXFKSQoPc4GsnSnGAF9la78tc3eLi4GzmVMxvgf+ZIwJz1xU8k+ZbSLiAbc1vw3QmycpugNnD7Bw70LSM9KdjlLqDsUeYvfp3Tzd72mno0gl99Yvb/Gf1f9xOobbwvULGbt0bM7GiPMPI0MqxwdAWQt+BlUJcjiJiIh3Kup2mp8BK4HWxphDxpg/Ay8BA40xO4GBmc8B5gN7gF3AB8B9AJmLSj4HrMr8ejZroUkRKbnKtkOBlNyhWNfc7e2ntjucpHTFJMXQ8I2G7D6zm9u73O50HKnkPtv8GbO3zXY6htuQz4YUuLjkh19/WHZhnJQ5+feBTg84m0NExEsVdVeL0fkcujyPvhb4az7XmQxMzuuYiJTM1F1TobpGPEjRHY1zzWnedXoXA5oOcDhN6flu13fux5pmIZJTanruXSuyW3NsTRklcVZwlWB89vtQvZ33LJgpIlKeeM8GzCKVXFJgktMRRMqlzSc2A7D3b3sdTiLiYvNeW9sR1hScZcnJJbnafPEFwK9KkT6/qhCu73c9gRmBLN261OkoIiJeyXt+YohUcjWTahIdGE2Lei2cjiIVRLWAagD4GO+tQe86vYv5O+czusNomlRv4nQcEYwpX9PirE/BhYdz4edytS1/dDlbD2zlsi6XlVYsRyTUT+BQSu7tQ0VEpOS8992mSCVTN6AuJsnQqFYjp6NIBZG13kF4YLjDSUpPy3dasu7YOsb1Hed0FJFyqbARD3lpWLchV/a8kuCA4FJI5Iy5v80Ff9iRvMPpKCIiXkmFBxEvEZsaiw20xMTHOB1FKgjXkjzeuS7IiXMn6DTx/DahLWu2dDCNyHkr/7yS728pP5t6dYztSMPjDQvvmM2d79+JecYw7YdppZSq7B0/fRyA5Ixkh5OIiHgnFR5EvMSJjBMArNq+yuEkUlG8+MGLsAf89jsz62579Haum3Ed51JcQ7nPJJ7hyZ+e5KN1H/HZps84HHu42NdevG8xm05sAmBY62FePZ1EpCQ2vLeBUd1H5XvcP8k/V9u3O74FYO3BtaWWq6xlFWJFRKR0aI0HES8xtvVYJh6f6HQMqUjCgGZQtWpVR27/8PcP8+2ubzmVcIrejXrz/LLncxzvWKsjG+/dmOe5R+KOsC16G30a98HPx/WjbMXBFbz161usOryKYH/XEPB7o+7VNAspV15e/jJVfKvw/y75f05HIcNmcDj2MAdPHsy3T5BfUBkmcl6Yf5jTEUREvJI+AhLxMt44bF5KR6q/axu9vcmu3R6staSkp3j8Phk2g9OJp93P0zLSeOqnp/h2l+tTUz8fv1xFB4CGYQ25/avb2XNmDwDzts/DPGP46zd/pf7r9bn848t57MfH+HTTpyzYs4Bek3sxY8sM9sbsde9k8eagN6kdUtvjr0mkuObumOv+s++0w9GHafRmIzL8M/h0wKd59onxqxzT97JGPPyt698cTiIi4p004kHES0zeMdn1CbZIER2LOQbA7yd+B2Dc4nE8t/Q5Ep5IoGqV4o+COBR7iCo+VagdUpuE1ASC/+0affDNTd+w49QOHv7+YQCub3c9vRr24v4e91PluSq5rjN/53wApm6ciq/xJTndNff6vdXvufu88csbBWbx9809TFxEXE7FngLAN8OX0b1Hc9MPNxXpnWF52g7UU6oHVsd/rz8R3SKcjiIi4pU04kHES6QEeP6TavFuJ0+eBCAmxvWJ5nNLnwPgms+uofnbzfM971zKOf618F8kpiaSmp7KNzu+wVpLcloyX+/4moZvNKTOa3V4funzhPw7xH1e47DG7qIDwNRrp/LQxQ/h5+PHxKsn8tLlL3FXt7sIC8hZQUvLSHMXHYoiPDCcIa2GsPC2hUU+R6QslZf1BE7HuUYihQSEuDIdLdp5/rgKek5N0yoNNw64EWMMM1bOcDqKiIhX0ogHES8RkRTBycCTtG/c3ukoUkG0bdyWHWd20LRp0xztP+39qcDz3vzlTf69/N/UqFqDA2cP8PZvbzNv9Dw2Hd/EEz894e731KKn+HDoh9z99d1s++s29sbs5ak+T1HNvxrXtbuOAL8Ad997ou5xP46qF8VdX9/lfv7jrT8y8JOBRX5dux7cRY2qNYrcX6QsGYzTEdzOxJ8BILRqKMYYQg+EEtswttDzVj25ioMnDtK+pXf9vEmuk8wpe8rpGCIiXkmFBxEvUcu/FtEJ0TSIbOB0FKkgLg+7nK/OfIW/nz/pGel59tlwbAP1Q+sTERTBQ989RIsaLWgY5tp6LzEtkU82fgLAkM+GuM+pHlgdPx8/moc3Z0znMdzR9Q4AmtdozhXNrig0150X3cmdF93J4djDxKfE0zqiNY3CGnHg7AF3n3mj5zG45WDWHFnjXkgyMiiSoCpB7uci5VFQlaAcRTcnxZxzjXYKDQwFoEq73FOe8hJRI4KIGhGMGDeCpNQk5v97fqllLCufL/8cAmFX3C6no4g4LiMjg7NnzxIeHu50FPEiKjyIeImY1BhsmCX6bDQRYZqjKoXbvXs3WIg+GU1ssutTzgahDTgUewiAfTH76PKfLlzb5lpe+9NrvPXrWwDUq1YPgDnb5nDw4YOEvBhCo7BGnEo4RafanVg0ZpFHfrGqH1rf/Tgr04SrJnBliytpUaMFAN3rdy/xfUTK0g+3/uB0BLcWkS3ofKwzPQf1BIq+dsNN79zEZ6c/gxQISQwp/IQKIPpMNACpGakOJxFx3lOfPsUPC39g1Ufaol08R4UHES9xNuMsAL9t/43BPQY7nEYqgjVn1kACtGvczj21IesXfIBmbzUD4M5ud/KfNf9xtx+JO0L7yPbUCamDxbL3b3sJDQglITWBOiF13NtbetKvf/mV5LRkejXq5fFri1RWfbv1Zf3E9e7nGeTeFck3zTdX25I9S6A6EAjxgfGlGbHMlJd1N0TKg/dXv09yWNHXVhIpChUeRLzE7e1u552j72g7TSmyhh0awjGoX78+G3ZtyHXcYqkVXIum4U0Z/KmrmDX12qnUDqmdY8pEiL/rE8/SXFchql5UqV1bpCw9u+RZDIan+j7ldBTOJJ7hWPwxmtdojr+vf56Fh/rUz+NM7xURoBGDUrmdTTjL6fDThXcUuUAqPIh4CWPKz4JlUkFk7jS5Nm4taRlpDGg6gKnXTmXX6V38Hv07pxJO8UDPB3j0h0cBeHXgq9zc6WYHA4tUfAv3LsTH+JSLwsM/PvoHH5z8gGXXL+Oy9pcRFBhELDkXlzzgd4Bdp3fRMLRhuVmbojRkFe0f7v5wIT1FvNvWfVudjiBeSoUHES8xcdtECEUjHqTIzpxyrWi/+Nhi9sbsZVSHUdStVpe61erSu3Fvd7+HL3mY/k37M7L9SKeiyh+cOHGCWrVqOR1DKrjYRFeRoXpwdQC2Pb6N6m9Wz9Wv5Tst+erKrxh68VBXgxfWuWuH1CZ4dzC1L6ntdBQRx2RkZPDgtAfdH0yIeJKP0wFEBIIeDsI8XrJ3cmn+aR5KI5XFsaPHADiQcAA/Hz+uanFVnv1a1WylokM5sHbtWpYsWcLKlSupXbs2M2bMcDqSFFN5WU/gXMo5AGqG1gQgLCwMkvLuGx9/fi2Hqraq+/HFXFx6AcvQqMtHkVIlhfd+fM/pKCKOGPXaKHyf82W1/2p3W2xC4dvrihRVsQsPxpjWxpj12b5ijTEPGWOeNsYcztY+ONs5jxtjdhljthtjrvTMSxCp+BKrJ0Jgya4RmRQJQFRLzYWXomlR37UzxM7knfSs35NLGl7icCIpyK233sqQIUNYunQpAIsXL3Y2kBSLKUfDBbIKDzWqZVufJZ+fRct2LnM/Xv/c+QUpe9funVf3CiktMo1YH/2iJZXT9PjpOZ4/1uIxqlWt5lAa8UbFLjxYa7dba7tYa7sAFwEJwOzMw29kHbPWzgcwxrQDRgHtgUHAe8aY3Esli0ix1KhSA59zPtSrWc/pKFJBzImb4368/I7lpbIbhXhO3bp16dixI4GBrt8MJ06c6HAiKY6IoAhqBtV0OgYACakJkAYBVQpfuyH7OkIhISGExYQB8MOm8rM9aEl8uOBDbFXL3vS9xTp/+pLpJKXkM1xEpAIa3nW41g8Tj/LUVIvLgd3W2v0F9BkGfG6tTbbW7gV2AT08dH+RSu906mkygjM4dPJQ4Z1FgDRc03NG1RvlcBIpjLWWhQsXsnXrVtLT0wFo166dw6mkOGaOnMmskbOcjgHAsFbDGJAwIEfbFT5X5Nk3+0iN4a8P52x11xbOm0I2lV7AMhQTGwNAekb6BZ87++fZjFo8ioEvDPR0LJEysWz9shzPBxwfwOjXRvPNim8cSiTeyFOFh1HAZ9me32+M2WiMmWyMCc9sqw8czNbnUGZbLsaYu4wxq40xq0+ePOmhiCLeLdWmArBqxyqHk0hF09/2dzqCFCJrPYeYmBhatmwJwLFjx5yMJF7g8dseZ+FrC3O0/X3Q3/PsGx4U7n686tD5nzMZQd6xoHFJ1t3YsM+1HfH22O2eiiNSpnp36c1jjR9zP79l+C3sb7SfX/f86mAq8TYlLjwYY/yBocAXmU0TgeZAF+Ao8FpW1zxOz/NfeWvtJGttlLU2KjIysqQRRSqF2zveDmhXCyncsfhjfLfrO7rX6A4/Q40aNQo/SRy1ceNG9+OhQ107C5w+rX3WK6InFj7BP378h9MxiD0Xy8DXB7Lv9L4c7Ys2Lcqzf3hIeJ7t3sJmviWtXzXPz8QK1Kd1HwBq+Ojf0oro9TmvE/ZYGAnJCU5HcdTLY1+maWxT+tg+NK7VGICjZ4+6jw96fhA3v6EttaX4PDHi4SpgrbX2OIC19ri1Nt1amwF8wPnpFIeAhtnOawAc8cD9RSq8OQPn8EHPD0p0DR+jTWqkcNZavtv1HVdNu4p/dfsX/IjmcFYAjRs3djqC1ztw4ACHDx8u9fv8cugXVh5aWer3KczIN0ayIG4BN7xxQ472jo075tn/sk6XFXi9bfu3UXNMTf499d8ey1iWskY8PHzxwxd87oCoAZh0Q8PaDQvvLOXOrI2ziA2OJfTxUNo+1tbpOI54duazhP4rlNn3z2bJ00toXrc5ACfiTjDtp2nExMfwffr3fBr7KSmpKQ6nLV8yMvSBX1F54jeV0WSbZmGMqZvt2LXA5szHc4FRxpgAY0xToCXwmwfuL1LhDbt0GH8Z9JcSXeON398Ays82bVL+WGtpNaEVt3/lGh1zYvsJAM6dO+dkLCmCu+66y+kIXq9x48Y0aNDA6RhlYs6cOXy/4nsAZtyXc1vWWy6/hRuCM4sR2XZprlOtjvtxrM2980NcUhynm51m26ltng9cBhpVb0TI9hAiAy98pO3mI5v5+uav+f7R70shmZS2xMREANLD0tmWUTH//JbUpr2biPOPw8+4FpluENEAMmBu8lxuWXYLHf95viD57y8qZnGxNPz6+6/4PuPLbW/e5nSUCqFEhQdjTBAwEPgyW/MrxphNxpiNQH/gYQBr7RZgBrAV+A74q7X2wlfwEfFCvo/5YsaV7FPnDD9VXKVgKekpHI8/DsCw1sNYt3odoGq9JyQllf5q9tmnW0jZsNZy9OjRwjte6HXznmlaZj7f9jn0BJKhad2muY53btQZAL/k8zvdHDtxfk2RtPjzFYnRYaMB2Ljf9efzh8MVc5eLUVeMIqVaCq9898oFn/uX9/7C1VOvzmcCsZR3O+N3nn9SDVZtr3xrZcUkuRZXbRjpGrXj6+tLYPz5vXUPRZ5fuDzAt/BdcCqLWb/MAh+YfWR24Z2lZIUHa22CtbamtfZstrZbrbUdrbWdrLVDrbVHsx17wVrb3Frb2lr7bUnuLeJNMoIzSjz+qFZSLQAua1/wcFipvAL8Aoj5ZwzLbl/G7Btn06JFCwBGjBjhcLKKr2fPnjz++OOldv1u3boxa9Ys6te/8Pnnkr9169blKLz9ccTDd999R7169fjiiy+YMWOGR0aUOT216V+f/IvpydNdT6rk3Wf9gfUApAWfLzBM/226+3HCpPNz4RPiXY8TklzfE1MTPRm3zFhrSQtL45zPhY8Ai06KBj+oeXdNzDOGtTvXlkJCKS0JgTnXdvhw4Yds3rs5n97e6WzSWUiD0OBQd9vjV+f9M+2JbU/Qe1zvsopWru0+uRuAH+/80eEkFYMmhYt4iVC/UHzjfalTo07hnaXSybAZTF43mWPxx3j/7M4AACAASURBVLis0WUYY9y/cDn9i5A32LhxIy+99FKpTHWKjY1l3bp1pKenM3z4cG688UaP3yMvR48exRjDvHnzyuR+AEeOHMEYwxdffFF45xJauXIl3bp1w9fXl/T0dGrUqMGwYcNy9MnaQWTkyJHceOONzJkz54Lv89hjj/HUU0+5nzcMbUjDUOfWAnh3zbvnn+TzLvDdP7/LRSkX4Rd3fsRD9u00rbWYRNfzr9K/4p2575RK1rL0zvx3yAjO4IA9cMHnnko7BUBMA9enxtN/nl5QdylHzsSdISMkA5N0/s/3f07+h44fd2TqwqnsP77fwXRlJy41DpOS873A/w34Pwb5DaJqTFUA6p89X/he7rOcbQe38dWKr8o0Z2lJS09j5PiRFzza5eBZ14aNr3z0CovWLGLQ84NYvGFxKST0Dio8iHiJ06mnSQ9JZ+/RvU5HkXJo1tZZ/Hnun5nw24T/z95Zx0WZvX34GrpLREVFwEQQdXGNtXXtXmtX13rtWLuwsVfswFpdsWNt1+7uRFFXFEVSmqGZed4/HplxBBRkKH9c+9mPM6ee8wwT59znvr+3oizVhfzSpUt5Na18g7e3N6tXr1bJFHHw4EEcHBxITk7O9DiLFi0iKUm9wlvnz58HoHbt2qxevZrdu3czcuRITE1N1Xqdz7l37x4Aa9euzdHrfMrLly8B2L9/f45fy8zMTPHYx8eHO3fu0LhxY2QyZRRouXLlMDQ0VDzX0dHJcDxBEHB1deXBgwcq5Tdv3uTatWuK51s6bmFn553quIVvwljDWPH4h8Qf0m1jZW7F3Xl3VUJCUg2UKbIUDKcbIugr6yJiI9DSEo0U+jr6OTHtHCdGGgN8W+hZrKaql4SBjkGm+snlcq56Xc3y9QpRH8b6xhyvd5wbv95ANl2GRKbcfPfa3wvbdbZoj8vANeg7wkpuRZGwImnKT0w9Qfif4XTU68i1SddYbr1cUeew2YGOZzoW+NCUgLAAio8vzr7YfQzeMjhLfR2MHDB8a8hB3YOMOzyOU7JTND5QmKI8IwoND4UU8p2gKdEE4PbLQs3WQtKy/NZyHCwdmNN4jqIsVVTSz0+02AuCoLLp+l8hLi6OypUr88cff/Dq1SsEQSA5OZlp06bx/PnzLIlvTp48We1inQEBYgIoFxcXRZm2tjZRUVGEhoaq9VqfkpIiutmnbihzA3t7ewCaN2+e49e6fv264vGaNWs4duwYXbp0wdbWVlHu5eWlYuCpUaNGhuPJ5XIWLlzIzJkzVcqvXLnChQtiisrExETF65pXvDcVY7U7G3Tm1KQviyFqamkqHqemavYP9SdBR1XTxMTAhBJmorZ4zwoFM93et3oryeVykvVVjZNh0rBM9e27si/199dnw4kN33TtQrJHaFQoR28dpVXTVtSqWgsNDQ38xvspGxQT/0kxSSEkQhRjthhtge0429yfbA5y7NYx7G3sCdkYkm69no4eBycdpEyxMowaOIo7v92hfoIy1KLm7prp9isotF3ZljAz8TMblBhEdGw0ZceX5ditY1/t6+nqie8yXwAeaD6AGEDjf1MnJDMUGh4KKeQ74f+q/R+gXBwWUkgqybJk7gXco3X51mhqKDcSY8aIaeN0dUWhqLlz56KlpZUrQon5hTNnzqicaNeqJS4+dXR0sLa2pkqVKpiYmBAZGZnpMRMTE9U6x4CAADQ1NSlaVKm2n3ryXrRoUX744QcmTZrExIkTkUgkVKmSfjrErGJkZATApEmTvtjuwoULrFu3Ti3XTDVy5MbmfNKkSQwbNowKFSrw6tUrRThEVJRCtort27crDD8AxsbGacZJRVNTE2NjY8qWLZthGz09PWwG2DDs32FquIOs8+z9M0ySTWih24J/JvyDpanlF9u3tWireLzsvZg5ySdQjGlOzXjRxKAJg1oPwlzfHOPXxpQxK9ipX+2N7LPUPik5ib66fTEMMoQUWFJ3CYPbZO7U1DvCG4A3YYWeinlB/+X9+eXsL3Re01lRVtKkJDETY1j1g2r4kNseN+IS4ogwj+CtyfcVftHueDu2RGwhOi5ttpr0qFGhBqPajMrhWeUe76OVwpmBpoGUnFqS18av+WVvWv2re/fu8fDhQ8XzYGkw5sbmiud72u8BGYzcPjJnJ11AKTQ8FFJIPuBK5yvsaZy9mNDCOP1CMuLS20skyhKpWVL1VEJfX9UlesaMGQAq4QbfO76+vhnWnT17FkdHRzQ1NTE3N/+i8cHSUrmBU7fhpk6dOkycOBFNTaXRKNUoULVqVR48eMCiRYtwd3cHxFP6zBITE0NQUFC6dT///DM9e/akXr16X3xPeHp6KoxY2eXFixdA7oT/REdHY2JiQvny5bl+/TrR0eKiOyYmhtevXwNKI8SmTZsAMDQ05M4d1ZOssLAwAgMD2bZtGzExMfj7+xMQEEBoaCjDhikNDKlZSWIMYngY9JDcRhovxXGTI9Ha0UxvN/3rHUg/+8bbEHHTZRYjhqroJOlgoG2AQxkHBASlYaKAkWq0H/vT2Cz109PV4+/pf1PHtg5owbhr42jq1jRTfX8s8SMATRyaZG2yhaiFa5FiCNThN6o6BUb6RoxoN0KlzCPYA5cZLnxvJCQlKHaDpoaZD9/r9FMn7GOURrq4uLgvtM6/pMhSCNUNhU9+tqXmUgCSTZKxHmNNUrIYPnnizglq7K9BPXdRxF0ul1N8UXFaLm7JgsoLONryKN0adENHqsMr6St+mv4TXr7i7/GqA6soOrooYzeN5fjt44z5Sz2/mQWNQsNDIYXkA+o51aNbg27ZGmPh04VAYWrEQtJyL+AeP1r/SNsKbVXKU92/P9cwePjwIXfv3s21+eUlenpiurDKlSszefJkunXrxs8//6yoP378uOKxubk5EomEAwcOpBlnx44disfq9nho06YN8+er5k13dnYG4NGjR9kau1u3bpQoUSJN+dWrVxk+fLjivvbu3ZvhGJ6enmoztqR6cnTs2FEt42VEYmIiycnJGBsbU7Vq1TRGpbJly5KYmMiHDx9wcHCgX79+WFmJmYMaNWrEhAkTuHXrFpGRkVhaWmJtbU3v3mIe93379lGyZEmKFi2qoo9RtaqYorKIZdo46tyg+BRReFiSIKGuY91M9Wlg2SBN2fsw8XRwdpPZOEmd+O/Nf+w6s4sUIQWpvZTXMa/VN+lcpELRCpg+NcVcy/zrjT/hQ/QHPC550Ltmb0VZpFHmPKQSksTPTUHVxSjIBEQHKNzryeDcxquPF496Kb9jnxs+xyxWNLjlhJBwXvD4tWgQLRpZ9CstVdHQ0MBnsQ9acaKXmqG7IU6TnDj/8Lza55iTnL53GkFfoL1eew7WO4hutGqq0ECzQNadWMe5R+dofbw16EJshVhSZCn0W9UPNEFIEJjcdTJta4lrrOXtlhNqFsoNrRtU8ayCxE3CyCcjCTUPZdn7ZbQ50Ybl/sv/J9frhYaHQgrJB0hmSZC4ZdNjofDTXEgGTKo3idsDb2OgrSp4lnpya2hoqCKIOGHCBNq3b5+rc8wrUjeL2traLFiwgD179nD69GlevHjB9evX+e+//9DV1aV27dqKPr///jtXrlxRGadpU+UJ54kT6s0WHRUVlUY3ok2bNl/sk1lBzEqVKim8J1J5+vQpf/zxBx4eHoqyoUOHcv/+fWbMmEFCQgJJSUkcPHhQ5ZRLHYuo1MW8uXnWNn9ZJdWDw9TUVGHEAVi/fr3isaenJydOnMDKygqJREJwcDDly5cnLi6OxYsXU7t27W+a51vftwQHBwNijHmKLOfDSgLCAog1E99DKfMyf73R/zeaaXbTFKeB0ngpZwPOoumriVNpJxZ1W4RPaR+uvb7Gifvi+/5m+E21zz83+PXnX4kvGs/M4zO/3vgTzj84z/CLwzn+QGmkTNbO3Ofv0WtxU3vw+sEsXbOQ7FNlmjIkbW7Nuem2cbR1xNnemen2Sg+h4sbFMZIa4f3OO8fnmBs8ffsUZDD8x+Hf1H9HD6XR/anBU3bf2Y3mBE2O3TrGmXtnKDamGO9Csp4pJrf49/6/APRp2oeOTTuSsCSB5z2fs8x2GTYBNgCMejCKnw99PJD4+NHeeWEnW4O3AjCo0SCVMYc0GpKpa2tN0cJ0vOn/lAGicKtSSCH5ATVESRRLEFWQmlVvlv3BCvlukMllGep+pGoG9OzZk6tXlcrqz549IzAw8Ls50cmIVNd6gPfvlTGeEomEChUqUKdOHaysrAgLC+PkyZMMHDgQLS0t4uPjadCgAadPnwbETf6nYStjxoxR62vXqlUrOnXqpFIWHx+fYfvGjRtnWiPBzMwMqVSq0t7JyUklhjUVFxcX5syZw5QpU7C3t+eXX35h6tSpivo3b96QmJjImTNnmDZtWqau/zmp93X7ds6J5J47dw5ra2sAKlasSMOGDRV1derUYfPmzVSrVo2jR48SFxen8rf9VGiySZMm2NnZoaenx9atW7l//z6HDh1i2TJRC2HGjBnpG4hS4PWH11j3tabo8qLUml4rh+5USeM5osr6hY4X0NDI2tKvdY3WIDoGYbzQmMvSywyuMZjG1RtjqCvqoySmJBIbJxo2klLUm9Ult0iWJZNsmky8ZsafrVS2Xd/GEM8heL/zJlwqGrEcSjgo6uUGciLjv+71MLTlUABMTTJ2cW81rxWrj67OsL6Qb8NSVwyPq5lck8ldJ3+x7exes9nTeA9FIotwbtg56mrVxXGLI3329smNqeYo3et351a7W4xoOeLrjdOhW9VuXOl8Bc0YTUZajWRjwEbkRnIevH9A82PNCTELwWGRA1vPblXzzNVDbZva/BD8A42rKjNRVCxXkdF9RvN2/Vt0YpSZjOyi7djcYDMA045PA12Y7zA/jceyRCLhaperzK00lwWVFwDgGOdI7ZTavB/xHj5qeAr6AtHG0bgfdWeIxxBGbhjJ2E1ZC/UqcAiCkK//d3FxEQop5HuHWQjMIltj2I+zFzTHaappRv87yGQyoerkqsIf6//I66nkCOvurBNKLS0lvAh9kaZuxowZgvgzIAiAAAhLlixRPD5y5Iggl8tze8q5xp07dxT3+uTJk0z3mzJliqKfkZGRsHbtWgEQmjdvrii/fPmyUKFCBeH9+/dCdHS08O7du2+ep4uLi9CmTRuVMrlcLvz666+K62lpaSkeL126VKXt0qVLBSsrKyE+Pl6l/MGDB4o+O3bsEARBEGbPnq0oAwQPDw8hODhYqFixoqChoaFS97X/W7duLSxatChL93r06FFFX3Uil8uF9u3bC1OnTlXMr3z58kJcXJwgCIIQGRkpXLx4UdFeJpMp2p0+fVpRHhUVJfz333/C/PnzhZSUlAyvFxkZqXj8+vVrARBGjRoluLm5CTRF8Z3PLATNqZrCvZf31Hq/nyKTybL1G3P7+W2V+TILYdrWaYIgCMKdF3cEZiH0WtZLWHFohcAsBJPRJuqcfq6xYP8CgVkIemP10q2XyWSCIAhC5YmVVV6L0RtHC8xC2HZ2m/Ds7TOh+ZzmArMQZhybISQkJ3zxmtvObhOYhTBl65R065NTktWyPigkLSXHlBR0xuh8U985u+Yo/i6SiRLhyevM/35876S+LkVGFUnzvXHV6+oX+w5eM1iwHWsrhEWF5dJsv87Z+2eFRf8of8fCosIEpiNoumoKJTqUEKKkUVke86/LfwmNNjRK8/oU5M86cFfIxL6+0OOhkEK+E8JSwpAZy74b97/cIiklCe9Eb/Y/35/XU1E7ckHO7MuzKWNahrLmaZX2U0+5//77b0XZuHHjFI+LFi1KmTJlWLp0qeq4cjmHDx8u8B4R9+/fB8DHxwcnJ6dM95s7dy6lSpUCQCqVMnSoeGrZqVMnhZhgkyZNePnyJdevX6dfv37Y2Nh88zyTkpIU2gepSCQSdu3apfgbfOqx8NNPP6mkRfXz8yMkJEQlO4O/vz/Vq1dXPH/y5AmCICgERmfOnIkgCAwdOhQrKyueP3+OTCZj165dij47duzgwoULdO3alYEDB6aZ9/HjxxWZNubOncu4ceNYuHAhRkZGyOVyHj9+rDIegIWFBfDl7BHfwv379zly5Ajz5s1TlG3fvl3hzWBqaqri+eDtrfwebdZM6UVmYmJCuXLlcHV1VRH7/JxPPSPs7Ox49OgRS5YsYcqUKSxsvhDvXt601GqJbpQuMm0ZLjtdkLhJ6LegH9JYaabSuGWW0KiPKVfV6M3r2tUVAEM90eMhISVBIXBsomuivgvlIqlhQxl9r2nO0UTiJuGZwTOV8uX+yyERutTvgoONA5PaTkI7RJvZd2ejP0ufIzePZHjNlVdXAhAdnzabwMVHFzEer97PQSFKpHIp+vJv09aY9qvSo0swEKiytQo+AT4EhAXQel5rhXZHdGw0i/5ZRKQ081mRcpsOKzrQzSN7GmOfUk9eD71wPcLiwyARrnZRelO23NYSiZsE29m2afrVnVGX9R/W42viS5FlRfjnyj9qm1NGyOVyph+aTnxyxl5OTas3ZULnCYrnFiYW9LXqi4aGBheWXsDEMOvfd/3r9+dM/zMIMwXOtDmTpj5VzPJ7pNDwUEgh3wnGGuIC5c7LwtzBWUFPRw9zwZxwIa1q/66Lu3jo8xDJFAnFxhQjLiEOwzGGOEx0SGek/Mcerz0ExATQy7mXShrNVFI3CqkZBFq0aMHatWtxdnZm6NCh1KlTBz8/P+bNm0doaChlypRh9+7d/PXXX3Ts2JFt27bl6v2ok7179zJt2jTMzc2xs7PLUl+JRIKfnx+TJ6u653bt2pXVq1eza9cuZs2aBUCDBg2oU6cOIBospk2bxrZt21ixYkWmdRgSExPTGB7SIzk5mYMHD1K7dm1u3lTG2fv7+wPwzz//IJFIqF69usJwAjBnzhzmzp3L0aNHAVizZo1i/p/z66+/IggCcrmcHj160KhRI/bu3cuGDRtYvnw5VatWxcTEBC0tLcaPH6/oN336dI4dO4arqyuxsbF4eXlRtWpVevToobLRS9XScHBQ32fs6tWr/P777yrPBUGgZs2Mc89XrlyZw4cPq02p3dnZGU1NTbS0tJg0cRKV7CtxYuoJEpYmUCJSKe65JWkLJnNNaHeyHZ5nPdVy7dQsE73Me31T//Ily0MsEAilo0ojmy7DQE/UiyliLApl7ovdx+mnYujRiBrf5rKd13zJkNpggVJk0+iDEXof9FTqWxi0QE9HLGtSrQk9K/YUx9QW6HCqg0oM90Ofh5y6e4qnvk8JjhK1PtKL8R68fTAJZuIG1jwuZzVPcppTd0+x+uhq6s2oh09A/sh6kqCRgKGG4dcbZsAQqyHgB3zUUnVc60izJc04kXKCrku60nBWQ0wXmzLp6SQs3dKmrb3se5lOezpx5+Udzj04983zyC5nfM9w6T/1ZRG64naFmKUx9KjUA99RvtR1rKsIN0gJFA3k7+LfqXze/rnyD9c1r6uM0/V8V4qNKcbIDTmXltInwIe5j+YycENaw/mX+HvE3yTMTqCifcVvvraWhijK+XONn9lcRwzf0IjWYHOdzehof/33vqCildcTKKSQQtRDvx/6McdnTl5PI18xY/sM5vjM4UnvJzjZKU+0F+xdQJ2KdWhUtRGrjqwi2CwY5LD38l5aurTEQM+Abku6cTD+IJJ4CehDiG4Ihn8aghk85zkzts+gTNEy9GzckyUHl+B22412xdqxf2L+8ZyYf1XMhNDELv1Ubf369WPevHncu3cPgLFjx9K8eXOGDBmiSB8I4oY5JCSEd+/e8dtvv7F8+XJAuQFfsGABixcvxsDAIN3r5Ee6d+8OwMqVK785FW2bNm1wdnamUaNGSCQSihQRN2G//vqrYszixYsr2k+frprC8Pnz56xdu5a9e/fSqlWrDE/50/N4+JQGDRpQvHhxtLS0KFZM1Hr5VL8i9WR+48aNAAr9hgoVKijSV4aEhNChQwdAFJz8Gum9ZqNGjWLUKDG3e2JiIjKZDE9PTz58+ADAy5cvKVWqFO/fv1dkeACoX78+VapUwdXVFRsbGzQ0NDKtUZEZtm/fzvPnz/n3339p06YNFy9epG7dL2d1kEgkuSawGrAsALlczspTKxlzewyCnrggr2jz7YvaVJKSk2i3vR3ogpWJ1TeNYWZkhrAo/U25lbkVPax6sDNkJ6eCTmEZZYld/awZ8vIbGnINJqycgPtId0WZd4g3iMkMSNZJJmFpAnEJcfiH+uMX6kcj50YqY3yuq6M/Xp+iFGVtt7W0P/XJ++qjY0zZkmXpuawnZYuWZY7PHDroduCl0UsAamvW5oLbBbXfZ27S8t+W4gNNGLd1HIcmH8rbCQFtDNpgW9z2m/uvHbqWtYhZa2zG2hCoEYiNhQ3Pkp9xLOmYinaXzEhGaFQolqZKA4TbVjfOC+c59PwQkgQJ70q9o7hFcbQ0c29rJo2XEq8fT1lZWo/I7KClqcWOMUrRycldJzM2eSy688WMEd7DvCnhWoKEhATG1hrL9vvb4aPGsV64HgkWosEtxCyEVYGrWMlKtc4vleveorHDxjjrHolZ1cr5Ev2a96Nf835qGy8/U+jxUEgh+QCvPl6cbns6W2OkyMWFekF3f1cna+6uAeDwbWWObrlczhTvKTQ+1Jh5e+Yx8sFHa7oGdL/QHdPFpmjP1eZgvKgyXlu7tsIa/SlzfOYw4OYALCdZMu35NJJNknkQ/OCrcwqJDeF1xNfTzW28t5HeB3t/tV1GxCbFUsmyErMazqJ8kfLptilXrhwAXl5ePHv2jEaNGinqevfuTXx8PPHx8fTs2RNHR0dF3ejRowHRHf/PP/9k7dq1XLp0CUEQiIiI+OY55xap6TAdHBz4448/vnmcevXq8dtvv1GiRAkVAwNAu3btMuyXmpZx3bp1dO3ale7duzNyZManOuPGjaNLly4Z1l+6dIk9e/YAYigAQExMjKI+1Qjx6d8X4MwZpYunlZUVPj4+7N69m8aNG5NddHV1MTAwICQkhKSkJEaOHMnNmzfx8/Nj+/bt2NnZceLECczNzalTpw7r1q2jX79+nDx5ErlcrhLqkB2mTJnC+vXrMTMzo0WLFnTv3p369eurZWx1oqGhwehWo1XK6uyqg/c7b/qt7IfWBC1SZCm8j36fwQjpM3nrZMJ0wzCIM2BOz5wxTBfREg1uLpYuRAvRHLxZMDM0yD/GoiRrJbPKd5WifP/V/YSahWIbbYtnXU/u/iGmGjbQM6B8qfI0qdYkzSZkVrdZlI4qTXFpcYqnFCfJNAl/U38Vo0OpZKXX0ZpLa9gZvVNxeHA48eNvVjycH3deJetQQeNzt/GHH9IK1+YF++fuZ8mIJWoZ693SdyQvTmZB6wXw2U9g1QTRyGq10IoJmycQlxDH3Zd3OS8o004KegKlPUpjPd5aGRqVg0jjpWhO0sR4kTHoQkennE1fDKCjrUMDoQE20TYEvQ4iWD+YKPMoZr6cyX+a/wFQSlqK+BXx/CT7SaVveHRaj1R1cN9XDLd0sXfJkfELSUuh4SGH8Anw4cazG3k9jUIKCOVLlqdp9aZfb/gFFnovVNNsvh9K6YkLu0ollSe4n55ETXv+ZeX9RU6LuDjjIv2a90OYKSj+n2CjjPeLNYtVxE6/1XxLY7fGdFzYEY9jHpy5d4bNFzajO0MX7wBvpElSii0uhpOHE5EJkTwOfswNP+X3REJKAhHx4qrlwPMDbHu8je2Pt3/TvUcnRrO3y16mNpiapk4QBLZs2aJS5uDgoHKqrq2tjZ6eHnp6ejx7poxptre3Vzx+8+YNFSpUAKB169bMnDkTCwsLKleuzNq1azl27Jji5PrZs2dfzMSQm2zdKqpr52SoyIEDBwgMDMTCwoKBAwdy8eJFoqOjuXz5Mv7+/oqNyj//iHGsr1+/JiEhId2xRowYkenT91SviU89HlINCVu2bEEQBK5cucL8+fPT6E7Y29vTvXv3b/YAyQhtbW1WrFhBrVpi9oaePXvy+vVrWrZsSXh4OO7u4sny+fPnFQaYfv360b9//wxfk8yyYIHo4uvu7o6mpia7d++mQYMGX+mVd2hHa6s8rzy7MlsitiAzktFweUNKLyvN8UfHM+idlohY8fvEtbor+rrfFs/+Nc4/FTdQk3+eTJJ9Eu8Ts2YcyS84Wztj8diCFOMUEk0TAdEFvO+2vgAMrj2Y3j/3VvGeywi7Ena8W/qOQPdAfFx94KRYbhBpQOAfgcimy3g35x3d33eHEHhtLBqj5zjOwSpMNEy20WlD8KRgyo4pS9lJ6j2Rzk22nN0iPvgPCIS3Jm/zcjoAPPN/hsclD8KkYWodt1q1asS6xxI2MYyYiTEkT0tmx2Dx5F/QE1jstxijqUbUWqTMZCOJUn7ffjD7QK05yroUWQpDPIZw6u4ptc7zwLUDyA2Ua6EJv0z4Qmv1cWnWJd4ueUvDhg051OyQIk1v05imfBj+AT93PwCuzb7GFPspin5LDisNRCERIQSEBaAOngc/B6Bu5S97wBWiPgoNDzmEwxIHftr309cbFlIIoDtfF805GQuVqYMFexfgccwjTfmA1QPSLf8eKGshLtaq2VcDoNTYUpQcX5J9TfaBuK7ENMKUxCmJXO96HWGmwOtBrxlgOYBXA18xofOEdGPtFvVbxNGWR7nQ8QImESZsqbeFzgadMUwy5CIXOZx4GLdzbjQ/1pz+l/uTpJmE01onjBeIm8Iptaew4/EOqq6ryk+bfyI8PhxBENCfp0+3f7qx5PoSTr4SV6peIV5ZumdBEBh6bCjWS63Z92yfIo7wU7y8vOjXT+nW9zUvhQoVKrBhwwZkMhk+Pj4IgoCXlxd79+6lW7duClf+OXPE0zpvb2+GDRtGu3bt2Lx5MxKJBEdHR4UIYypSqZQdO3bkupdO8eLF6dKlCy4uOXfKoaWlRfHixQkLC2PDhg00bNgQY2Nj6tevj5aWFjKZDEEQOHDgkkNjfwAAIABJREFUAN26dcPR0ZGGDRsyceJEOnTooPBgAHj79i2RkZkTJ0vP42HcuHFUrlwZXV3RzbVevXq4urqq8W6zz/z5YlhQaljGnj172Lx5M3fv3v3mMT+Nm69WrVr2JphLhM4O5d9W/yoLSisfXpeKbsHPnj1j/vz5mfrcxCSK74OudbuqdZ6f8q/rv/Qy7YVPiBi7/0z67Cs98ifdm3Yn3Fl5svrXyb/oer4rUmsphpGGX025mBEGBgYkX03m1cBXxC6LpbhFcTQ0NJBIJKx2Xw0fI2DmVprLtC7T8Fvix6ofVnFg/AGszK3ElHsG0YSGhqpNcyQ3OfvoLACPZj9iYu2JmISaYDjGMFfEAzNizdE1DL84nNve6k/ba6BtgIW+BUb6RmhpauFo68g0+0/EKE0Efij/A7WSa3Go2SHkS+Ucb3ycGqE1APA18KXGlBrojdVjzF9jWP9hPS3/bYnbPjek8VK1zDE0RvSq6JjUkcutL3+TQGJ26fBTB4QF4mHO2TVnsbRU1cGY10spBLzwykIk4yXYTbGj2MpilFxdkmHrhmVbhPF1xGuQQnGL4l9vXIhakOR3t+waNWoI2Vl45BUSN9GCKczM369vfiIoPIj4xHjsShTs+NBvQR3vlxJjShBkFkTYmDAsTCzS1BuMMcAYY4KXBav92vmVBXsXsOrGKm5MvkHpoqUVxp3y0vK8dH/Jf+//o6x1WbXF6q0/vp4hd4YAUCyymKgd8REzXzMibcXNY6U9lXCZ68KOJ+JJyKW+l9j+eDsb729MM2ZJ45K8H5v2BNHzoSd1bepSzqKcouxt5FtmXZrFlodbAFjXZh2DawxO07dPnz5s3bqVO3fuYGVlla2MCwBBQUH4+PhgYWGBk5OTyoZvwIAB/PXXX4Bo8ChVqhQmJiaEh4cze/ZsVq5cyd9//03fvn2zNYessGfPHqpXr67w1sgPuLq6snChqtdS6u+zjo4OY8eOTVOfHjKZDFdXV9q2bUuDBg2Ijo4mMDCQMmXKiMYt/Zw59VYHN2/eVAhxfkpQUJBCuyKzREZGcuXKFdq3b4+dnR0PHjxQyTSR31l+aDlXXl7hQPyBNHV1IupwI/IGD6Y+oFr5jA0qySnJ6MwTDacxE2Mw0jfKsfla97cm0DgQzEVjbuTy/Kvi/znrj6+nzY9tWHtqLfN95qfbJmFKArraujly/bfBbyldtHSGv0PN5jTjrPwsBEJDeUMubriYI/PIDpUnVsZb35ur3a5S11H19DgiIoLLty7ToaWoIVNxTEVemon6FRPKTmDR74vSjCeNlzJl2xSW9l+aI5oH3RZ3Y1/svjT6TznJ4euHGbhvIJMbTGZsp7Hptnnh94KA0ACaHElfl6l4ZHEClwVmey6unq4s9F3IzoY7+a3Rb9keL6d4E/gGl1UuROimfzhSLaEaDxZ8PcQ1PdzPuuN53ROdOB3uL7yfnWkWAkgkknuCINT4Wrtsr7YlEomvRCJ5IpFIHkokkrsfyywkEskZiUTy38d/zT+WSyQSyUqJRPJKIpE8lkgkP2T3+oV8P1j/aY39BvuvN8wDUmQpvAt5R4pMfYJn6kZXQxetaK10jQ4A8UbxhGuoL05ux/kd9F7eW20W+JxAX0efQLNA9l/fz57Le9CNEheO9qbi+6x8qfJqFQga3HowcyvN5UnvJ3jN8qJWci1KRpXkl+hfmF5tOuwEPGDkHyNZ1WwVbrXd+NXpV/yi/BRGh3uD7vFk6BN2d96NWyM3/GP8WXVLGW+cLEvmn2f/0PdwX1w2uPAo6BGBMYFc9L2I7QpbhdFhcbPF6Rod5s+frwg1qFq1araNDiB6ENStWxcHBwfFSf7r1685efIkS5cuZfDgwbx58wZ7e3tsbW3R0NDA0tKSlStFwajUdJ6+vr5ER0fnWEhGYmIiP/30E9ra2vnK6ACku7Hu0qULZmZmJCcnY2iYOfV1TU1NFi1apAgnOH36NJUqVeLx48f52ugA4OLikq42xueinJmhS5cuivAUNze3AmV0ABjdcTT7J+6nodCQAZYDVOpumN8AOwiP/fL3+cm7JxWPc9LoAIAJUMASL8jlcpznODPkzhAqzK+QxuhgK7UFxJC7nDI6AJQpVuaLv0OVi1cWH5SAZ4Y5400SEhWCxSQLdMeK91l7Wm3Kj09fG+hTTtw5QemxpfE29AYNqLejXpo25ubmCqMDwPQ6ys9zU6emSNwkSNwkzNujPOE2XmTMqsBVaM/VVtSvPro6O7eoQnic+NnJjrhkVunwUwdCloVkaHQAqFi6IvWd61NeqnztGwjK0LAgsyDGrx+fbhaUrCBLkIE/2Fhm//c/J7ErYUf4/HA0pel7BD/Ue8jWE1u/aew5/84hLCCs0OiQy6hrxd1YEIRqn1g6JgPnBEEoD5z7+BygFVD+4/+D4KMc7HfM4euHv96oEEDMhZxf8fL1oszaMnRclPMCPN9KmCyMFJMU7v+XwZeoFqSYpDWcmEeYYxSR9UXpxssb2Ra1jX6r+7HhxAYm/j0xy2PkNMkyMV1hcFQwPU71wFpijVcfL45MyjivenaZ2n0qTnZOWJpacnPuTd4vfc/+Jfvp37c/vIQB7QcwdOhQenbvycyWM7G7Z8eN96LOw4wGM/ihxA84WTnR3ak7I2qKaem8Qry4+f4miSmJrLi1gq77RLfp6MRoqq2vhvVSaxp7KgUBD3Y/yLifxqWZm5+fHy1biuric+fORVtbO00bdWFnZ0eLFi0wNjZm3bp12Nraoq+vr4jzB+jYUfw89enTBycnJ+zs7DA1NeWHH3LGJu3r68uNGzeIjY3NkfGzQ3obj/379xMVFQWQqXSaqSQkJPD+veglc/fuXbS1tVWySORXtLW1OXLkCJ6enlSuXFlRvnHjxiyF43h7e3P+vKg7YGFhQcWK2c8OkVdcnHWRjcM3YhqR1nDy2PcxP03/KcP0hD129wDgSIuc+75LpZie0nBW1Khojl8vuzz1fcrwDcN5In8CQLyZ0th5qdslzvU4h8+fPiROSWRC59yJf88Ip9LKE/kPRh9y5BqXHl0iwiCCJNMkgsKDuKV9i1fGr77YJyEpgdbHW/Pe9D3c+1ioC9uObaPU2FLUmlaLpOQkqsypwvITyxX9fu/2O4lTEnk79C2LFy1WlE97Po2KEyqSIkuhpH/JNNf74/63CwF/TmRiJCTlgkHuG9DS1OKl+0tOtjmJ/wh/Ls26xEhrpfjwkqAlLNi3IFvXWDR4EckeydSpnNbDLD/yesJrHvV6lG5dn9t9MB9rTqmxpbJkkJHqSDEzMVPXFAvJJDml8dABSE1A7Ql0/KR8qyByEzCTSCQl0hvgeyEqLiqvp1Bg0IjVUIj05TcWHhJdnP9N+pfGbo15F/KOuIT8FWtZTEtc+N33yZz1ds+lPSzYuwAdiQ4aaKAzTodui7sRlxBHiiyFp75Pv9g/KlF8b18OuMzg24Nxf+f+xfZ5wYIr4o/zoreLQA8almmIo61jnuRINjU1RRAERUrDVF2EBQsWYJAkpqFsUa6FSh8LfQtSpqfwIOgBdTbVof7f9Xn6If2/y5jaYxj0wyC8hnrRsVJaA9nbt2+xsbFh9OjRCILA1KlpRSdzgxMnTnDo0CG8vLw4ePAggiDQqlUrnj5V3tfz58+RSCQqKT3VgY+PuEErWzb/CbUNHDiQ1atXs27dOoXg5KeYmWV+gdS/f39Kly6NRCLhzJkzODs7K/QdCgK9e/fm9m3V2OvUmPjU1K9fonLlygpDxdmzZ3NUyyO3ONTvENZR1iplYx6N4YbWDeosr4NMLlOp23VnF1JzKSRBqx9b5fj8htQfong8rdGXRXvzmm6Lu+Hk6cS64HVp6nY22EkDhwY0KS9mqsiL34rPaViloXJtpAW+b33Vfo1UEVKAVwGv0InXwSDOgNiEWCQzJNRwrUFQeBAyuYzEFFEgqf+a/mKHZIjZGcP93vfRSdSh973e+Jv6c1v7Nn8e+hMvuRfXvK6pXE9HWwcbKxvO7DxD2Ziy2ETZgB+8NHqJ20433m94z6VOl2iMaoadaq7q0WqJTopGIzl/y9y1qNEC6yLiZ37FwBX4j/DnF/1fAJjmNY3flvxG+fHlv9n7QUtLS60enzmJjZUNzvbO/NvqX5ppNAOgRKRy+xhpGom/qT/tFmacTepT3oW8QzAQKG1c+uuNC1Er6njHCcBpiURyTyKRDPpYVkwQhECAj/+mJo8uCfh90vf9xzIVJBLJIIlEclcikdxNFZoqSKSqzzaiERbGFrjtdMvjGRUMjJKMMIsy46HPQ7Ur+H6N8Ohw3PerbpzvvLhDXEIcWuO12CNVCr1d5CJl1pbBcaojcrmc4euGqyjsftOPgOzrTb5G3xp9M6wbuUE1Vd+ui7sYdHAQU7ynEGwWTLR5NMkmyeyL3UeTuU3Qnq6Nk6cT5qPN2X91P0CakIroZFE1P1Tn66mfhq8bjsEYgzz3APqjlfpOTLKLh4eHIgWjLEl8A9ibKEONEhISuH//PtIYKT2r9ATgTsAdRShF0rQkPFp7YKZnxqW+l1jaYinr263H0cqR9BgzZgzAF9M25gYSiYQOHTqopOcsUaJEuqEPnp6eacqyQ342POjr6zN8+HAGDx5M586dGThwoEq9kVHmT+Y6dFC6Nd+/f58aNb4adpnvMDQ0TDelZo0aNTKldZFKQkKCwshXkGlUtRH+S/3Trftg+IFmk5qRlJyEXC5n+aHl9Dguejs01WmaIzHynzO4tTKs6/DzwySnJOfYtd4Gv6Xm1JrfnHZwX+w+leepm7kZejP4rXH+i3evULICH8Yq18IVJqk/TCwyVqnJERwZjCRJQpxBHKWmlgJNuKd3jxKrSqA1Rwu9eXoYjzFmZ/ROtKK1iJkag5GREdXtqnOw40FIAVKgkm4lZjybAUD5YhmHbbxa/Iq3S9+yv5+41pj7ei7NlzSngXMDTk87DfGgESduVwRD9XjGujV2Y3rZrIdw5SXWRazZP1F8jdCC3dLdvDJ+xexdszEZbZKldXO3Vd0oNb3U1xvmM1rXbM3p6acRZgq8X5JW++p48nH2XNqTTk9V1p0UjY5tnNuofY6FfBl1GB7qCoLwA2IYxXCJRPKlPFXp5ehK8y0iCMIGQRBqCIJQo2jR/O+y9zmdd3QG4L+o/2h3sh2z/puVoStkIUpalGqBta41DVc1pOW/LXP12uVmlGOi10TFF9amU5uoubsm5VzLITNWtQr86fgnAL4mvuy7sg+PYA9Kri7J0oNLef/hPboTdZG4SdCaoJVx2MNn+P3hx70e97IVt5d6YvFpukgQ9SlWvVNqBGhM1qDHpR5EmyvT7fkO8VU8vqV9Cz4ejkaaR9LlXBce+jzEeJExPZb2wGasDVoTtJDKREPEpymZGs5qyLkH55DGS5m9azYAree1xiPYg3izeBafUrpV5jSTtkwiwlx8TYwijdjdaDc/lM8/sjKlS5cmMDCQuLg4IiLFeZZwKMHUqVNJSUmhZcuWuLi4cOnSJUbVHsX/Vfs/THVNGVpjKHMbz0VbU5uhPw4lYlIEDcp8OT2gTCbj3LlzDBo0iC5duuTG7WWZq1ev4unpiUQiUWgRWFpa8vLlS7Vlvbh79y5FihTBysrq643zmFWrVnH16lXFc1tb20z3/eWXX2jcuDHNmoknQ23btlX39HKFSpUqceLEiTTlrq6u9OnTJ8N+JUsqzzM+Ddn4nrlgdEGRHWnMozGK8o4/5F544J624u/nwbCDHLmWc+EdwzYN447OHX5bmXUjQbnxSjFe/xH+JE9LZv/E/QgzBdwm5d9DIktTS/5pKnpCJTsk88LvhVrH/9TjodeaXop0opEm6YuESs2kkAw/6v+oEq7QumZrPoz/QNTkKHZ13aUo7/Bjh/SGUaFjnY6UiS4DwI9WPwJi2MGAmgM42O8gwkyBwRUGozlYk6DwoKzf5Cf81vo3Zg2ela0x8ooDP6sKzm67tY0Y8xjG7s5YO+JzLr2+RFB89l7DvEZDQ4P1NdenKf/90O94HPPI0CtZEARO3jgJcdC/ef+cnmYhn5Ftw4MgCAEf/w0BDgI1geDUEIqP/4Z8bP4eleRQlALUk4w1HxFrJsYP1y9ZX1HmG+ybR7MpOATFBPHM4JnKhjinCYkIwWmSEyaaYiqhXy/+ilwuZ8BNUcyruV1zQMyt/keJPxBmCkzsMpGGQkMA+h7qqxhr3ONxlPYoTYqxqKMgM5LhstOFAasHoDlRU7ERzwjbYrbZcntb9mpZuuU7L+wEbbCKFDdbgr64iasorYh2tDYeNTwoU6wMwkwxrdEU+ykUjSyKS6LSPfnADfGHblfMLvxM/ZAZyZAiRTNGPEmUxIs2xcuSy/x85GdsXG2Y+XImWhO0OJGi3Dhc1bjK2n9zR9pl12Plouevjn/RvWH3XLluVtHX1+fo8aPikyqi+KO2tjaXLl0C4OVLUf17U4dNRE6OxKONB1MbZC1M4sSJE0RHR1O/fv2vN84jihYtSu/evQkODlbM8+DBg1SsWJFFi9KqnmeVW7duceTIERo0aIBEkp4NPH+hq6tL3bp1sbe3p3///tStm/k841paWpw/f57169ezfPly2rQpuKc6LVu2JCAg7TJh69atBAcHM3PmTJ49UwruCYKgSDno7u5e4EQlv8bOhjvZ02gPtr62X21bNaEqI9qNyPlJfaRjNaWR45z3Oe68vEOJSSV4E/Lmi/2auDWhiVv6Kv7pkZoiuIptlSzP0cfYB+sYa4SZAtZFrHPFG0RddPypIx1NxNe40uZKah07Mk5pYIivpNS70JAq1yRzKsxRPLYMt0SYK3B97vU0Y1maWmJiaEK1stUQZgqEjQmjlkOtNO0+R0NDA98lvggzBZVUiht/2Uj7SqJQrMddD+TWctwPfntoZ4oshTYr2nDiSVqjZkGgU91OKl6yr4u8BuANb7AaY8WO8ztYfXQ1DWZmfCARqhWKjZC/hSUzw6BWoqO9RqIGpu/F7/oUsxSG3xtO8cnpp8gMiw+jsmNlNjbemC81Pr53smV4kEgkhhKJxDj1MdAc8AKOAKnHEX2AVP/qI0Dvj9ktagNRqSEZ3wsrDq8AxHR9kzpOUpR7v0/rMlqIKt7ROf8apchSaDirIWP+GkNoVCh15tXhqcFTNCVKV1zN6crN9OqBqxlRfAQvxr9g5aCVijZdXMRT41qmtVhfcz37muzjdNvTivoDPx+gaKTorbMpbBNyQzkzX87k3INz9Fjag0FrBvEppT1KU2RZkWznJE6PPtfEj+LQGkM52eYkt3+9TZHIIhz84yBJS5IY2maoSvt5veYRsiyEu/PvUldWF+Rw2zdtrus4szgu9r2ISYQJaxsojQklo0oqPA1kRjJmlpup0s/zhid6Y/WwH2dPUHgQ07dNx2qMFUsOLGHo2qHZVmtOZf1v66mWIC588qvRIZUWtqK2Q6NajdiwYYNK3fPnz7M9fnBwMJ07d6ZTp07ZHiunKVq0aJrN4po1azh8+DChoaG4u7tn+T3y+PFjateuTWRkpNrDN3IaHx8fRTrSrGJnZ8eoUaMKhKHlS5QoUQJBEHj37h2jRo1SlP/888/Mnj0bR0dHJBIJDx48IDg4mIgI8fundu3aeTXlHOO3Rr/RrWE31o5aSx+bPph8MEm3nUGkAfv/2J+rc2swRbnR2f9iP+7/uhNkEMTrgNeKch8fH85eOavS78LH/zJLRHwECLDw18yH3AB4nhE/+2HysCz1yy9oamjS3rF9mnLvd94s2LuACZu/XQRzYIOBjDYfzfaW21XKD3RSnq5P+20aSxyWgAzOjjz7+RAZklGmrW/h+kzR0LH0/VJuPBNFmeVyOUlJmV87bTy5keORx5m3b97XG+dTnBKd0I5WFYeON47ng9kHfr/yO3/c/4MrGleQuElw3++O+353Ws5tyfrj6+m4sCNyIzmWepZ5NHv18qzfM/zH+1OxmKqIcIx5TLrtWy5oye6g3QxoOSDd+kJyFkl2XFglEok9opcDgBawUxCEeRKJpAiwF7AB3gFdBUEIl4irn9VASyAO6CcIwt0vXaNGjRrC3btfbJKvSJGl4DjZkV2DduFs74z2XOUXw81uNzNl9f1fReKmujgWZqo3y8Xb4Lf8ffZv3F6J7pTGEcaKL6aOeh2Z/9t8Shctzf+t+T+OBBwhZE4IJobpL+pSZCkMXDOQP3v9iZW50m171o5Z1K9cn6bVmyKXyykytghRelEKL4P2uu05kqh0Qd1cZzO9mvZSvE+yk2vdeow1gQaBxExTHaPjwo4cTjzMvR73shVqEB4djk+gDz9W/JESY0pgpm2G9yJvEpISSJGlUGFKBYbXHs7U7lPp6t4VQ11DutfpTqsfW3Hx0UVqVqzJibsnmHxo8hfVsmeVn8XMHjMzrM8M155ew6W8C3o6etkaJ7eY4z6HGXEzaJTQiAsLLijSUY4YMYKTJ0+SkpLyXcSpZ5b4+HhOnz6tyHrh7OzM48ePFfU3b97k7NmzVKpUiY4dO371tVmzZg0jRozA0tKSgqgbVIiSbdu20bt37wzrtbW1SU4W9QW8vLxUtES+Rz7/3UzlF/Nf2D8ydw0PuuN0STJRbgB1o3RJ1kwmdn4smx5s4pXXK5b7idkNEqckIhfk1Jheg6cGorDs2fZnOe91Hrcebl/0RHCc6MgznvFm2JsvhiCFxoWiIdHg4YuH3P7vNkvvLOWD4Qe0orVIXpJzGhQ5za6Lu2hVoxVmRmbc/+8+Nf6qocgK9k/Tf+hcr3O2xt98ZjP9r/ennWE7jow/wtvgt4CY9jM/UG9GPa5pXqObYTeCo4K5pHWJ8lHleblU9A6Uy+Vf9B7t6t6Vf+L+4XrX6wUmq0NGPHn1BOcdzt/Ut768PpfdLqt5RnlHiiyFSGkkZeeVJdpQ9JxuRCMuzFQaNQVBQH+APnIzOUlL1H/Q97+MRCK590l2y4zbqSt2NqcoaIaHz7EZa4Ofqain2VBoyMVZF/N2QvmYnDY8aE7URG6oPCntadqTW+9v4S/zJ/zP8BzbpJ57cA4TAxMMdA2osrZK2rShMuDjviliXARmRt+W3sdmrA3BkmASlyRmb8I5jGSGBDShk34nTgaeVEljBvBj0o/0r9ufcGk4rt1cszz+hhMbGHx7MGVjyvJq8ZfTgeUXxi4ey7LYZYyuMpplvyhDZjZv3kz//v05d+4cTZpk3hX5U/z8/DA2Ns5SVoT8wrVr1/D39+fWrVssXbo03Tb79u1T6FZIpVJu3bpF06ZNFfU+Pj78/PPPREZG8v79ewwNDXNl7oXkDKdOnVKkhP0S3t7eVKqkXnf0/Mj+q/vpfrg7MiOl77WJ1ISnE59SqmjuiseZjzYn0vwzTYAUxGOpdKiWUI2Heg/FJ0nAxwQS635cpyJW+TmvXr2i/KLyFDMoRtDyjOPUK7lXwkLPghvhNxRlOpE6PBz9EIcyDpm4o/yJIAjExMTwLuwdVbaqhpu00GzByWknszReiiyFFu4tcCnnwqIui5DL5QxbN4y5PediaZr/TsXlcjllZpahrV1b1vkpM5OYRpsi1ZAiM5KxxmUNw9oOS7d/qbGlCNIIImlRUoHJ6vAlyowrwzuTd1nqYxhpyK1Rt3C0/f4Ms+FR4ZSZXAZpcVGH7NO9xNI9Sxn3fBykgDAnf+9/CxqZNTwU/E9cPufd0ncIMwU0YjXwiS4UmMwL5HI5tafVVhgdOul3QjZdxvbR23mx6AXSJdIcPRlvWr0pP1b8EUdbR671ucbyasuRTVcuEivEKxWqXwW8osXcFlx8dDHL1wkTwkgySeLGsxtsOLGBH1x/wHacLeM2jVPHbaiN2z1v86fjnxyYeICAOQG42rkSNT4K2XQZ0+yn4R/vz5A7Q5jiPSXT4pwgLp6iY6MZfFtcsA6qPegrPfIPrwXRFTlJU9UC36tXL44fP07jxo3T6/ZVBEGgbdu2ODk5IZVKv94hn1G3bl26devG4sUZi5J27dqVmTNFD5n9+/fTvHlzwsLCiIiIoFatWpQrVw5fX1/WrVtXaHT4DnB2dqZq1apfbZcVMc6CTOd6nXnr+pZWxVrRoXgH5jaey4Y+G3Ld6ACwo8cOAIqFFqOZqShsmpHRARCNDh+9oZuaNUXiKx4+vAx8+cXrlCtXjhKGJYjQiPhiu7cBb3nzWlVfYk2LNQXa6ADgccgD02WmaYwOAN6JWQ9Z7ezemfOJ53F/KuomaGhosG7YunxpdABxfn5z/Fh3RzUdapRJlMIAN/zecJynOGM2yoyADwGcunuKURtHcfTaUfx1/bFMsfwujA4ALxa8wG+YH/Xl9VnivASvPl5c6Pjl0CXpMul3aXQAsDC14K/OyvDEU3dPsffyXgBi9MQvHENp4Vogryj0eMglio8pTohuCPKF6olf/x6RuEkwjTBl0k+T0NTQZGKXidkeMyg8iBKrlLl+lzgvYWynzCv/5iRn7p3Buog1jraO/L78d3ZE7VCpP9TsEB1++roSdCqSaRLQBo8aHgy/MlwR3tHbrDeeowpOXLvC8yUBSiaW5N3id5laIGi4aiDoifdcOqo075Zm7QQgL1l5dSWjzo1iba21DGk5RKUuPj6eSZMmIZVKWbt2Lbq6YsqRQ4cO4eLiQunSGeeh9vDwYPjw4SxevJhx4/KXASqrODg4ZFrvonnz5jg7O6sYLGQy2Xez0CxE9G6pU6cONjY2HD9+XKVu69at9OrVK49mVgjA2TtnaXaoGbYJtoTLwulTuQ/HXhxjQpMJDLub9iR6mtM0OlfrTPXt1dFM0qSyrDLdq3dnave0QrrtV7Xngv8FpHpSznY4S9PqTdO0AZCMkqAn1SPBJgGA3ia98RxTcH4LM+LIzSN0OKW6NjAMNeTe6HtULFuRLvO68C76Hbf/TKvNBDDJcxIbX2wkcHYg/iH+lPUoC9pgEmFC1PKo3LgFtVBrWi1R8CVaAAAfcUlEQVRua4uaVWFmSt0OiwgLws3DFc9/TP6R8PBwfIopD/9+NfqVXeN28T2z9/JeEpISFDpfExwn4P7IHbTU71GcH6kxpQb3tO8pj9g/el9pJGjw8o+XlLXOf2m1CzKFoRb5jHYL2nEs6RjP/+85FUtX/HqH/0EkMyTUFmqzqtcqHr5+qBbhF7txdvia+AIwxGoIa4fmTkaFrJIiS8F4vDEJZgkq5Q9+f0C1stW+2DchSeyjv0BMQbjGZQ2HHx7mtOw0BpEGxC6LzZlJ5xBjN43F84kn3St1Z22w+Pd6O/QtNlYZKzB/briJnRSLgZ5Bjs9VXWy8tZFBJwcxUX8if078U6UuIiICCwtRnGvYsGG0atUKgHbt2gFi1ovy5dPmSI+Pj8fAQHwNvodY9+3bt7No0SKePHkCwJEjR9i0aROHDx/+Sk+YMWMGbm75N1VeId9OYGAgy5Ytw93dnXr16uHp6Ym9vX1eT+t/HkEQOHjyIOXLl6dKufSzT2y6v4kT905w8OVB9rTfQ+sfW2P4p+pJZNGQomjoaHBu1DkcbR2Ry+VoTtekeFxxgsyCqJNSh+tz0mZWgE+M2PFQTVKNe/PufTfGx3Ljy+Fj7IPDBwe8i4peDi01WrJvzD5KjSpFVKkoZlVMXy/p07BWBxxICEqgi0sXZvScUaBU/uVyOX4fxFDmDac3MLTlUHyDfannVA+dMTokmyl1PPST9InXEcM6n/R5QqXSlQpURhN14RPgQ2hU6P+E3lxcYhxDFg9hW8o2lfKz7TM2Vhby7RQaHvIZs3bMwu2VG5NtJ7Ogz4K8nk6+ZOjaodx5f4dncc+IN4tHNj17J5RyuRzdibqkGKdwtctV6jpmPh1dXpGUnMSdl3eo9089APqY92HLyC2Keo9jHgxoMQAdbR1FWZVJVfAy8FI8H1F8BHf87jCj/Qxa12yda3NXN596q5SOKk27Cu1Y0GsBJoYmJCUn8feZv3E97YqTqRPVS1VnZYCYdSRsTJhaVbRzg4m7JuL+0p2eQk+2z9qepn7AgAFs2rQp3b5ly5bl1au0WhZr165l2LBhrFixgpEjR6p9znlJaGgolpaW4ibkK8KST548oXLlyt/NhqOQ9PHy8sLOzq4wnKaAc8v7FrV31wYNKBZejGDzYPi4T24gNGBFrxVU316djnodORd4jniteJIXpy8U+ekG++3/vcWmdMFPH5iK5xlP+l7vy7Ym21h0bBFPDESDrKGfIbGllYcNn4vrvY18i+0KW5WxRpcczbIB6afjLqhceHWBJjuUukhtddpyOvQ0hjJDwpeHf6FnId8LcrkczTni+qCWpBa3hFsQB8Kf+XvfW1DJrOHhf8/cl0d0rduVY0+P0ap6q7yeSq6SIkuhs3tn5nSbg7O9syINXnqbAGcbZ9aFrFMITCWlJGVLe8F1qyspein0Ne9bIIwOADraOtR1rEunfztxMP4gx98cJyQihJj4GB6+fsjwe8M58lDMinHM9Rj3Xt5TMToA+Ib7ckv7Fnde3SnQhofiFsVJnpaM9lxt/Ez98Aj2wONPD3SkOox0Gsliv8VgDle4wpWAK7we9JoIaUSBMzoAePuKJ1beSenH5/711180a9aMJ0+eMG+eagqwN2/ekJycTGhoKH5+fhgZGSm8G44fP06LFi1ydvJ5gKWlGHssk8mwsrKiZ8+eyGQyVq5cmaatk5NTbk+vkDyg8O/8fVDLoRZP+j6hXMly6OnoER0bjeliMb3uy+iXVN9eHYCadjXp16wfpx6dQqevDiPqj2B8x/FYF7FmwOoBFDEqohizZFTJ78roANCnWR9qV6pNxdIVKW9Zntp7a1M2pixJJknEojQ8XOQi/73/j/KlRK+4X9b/AkDRiKJ8MP+AJF7CnJ5z8uQecpLG5RrTz6Ifulq6Ck/XuIS4/0kvh/9Verkrw+1uzriZhzMp5FMKP4G5hKOtI3fnF3zPjayw5MASJl+fTIpxCke2KVNIGkYaEjQ/SMWlTxov5dyzcyr9E5ISvsnwkJCUQN9VfWlXvR1/lfiLfs36fftN5BEHJh6gxtQa3DO7R7GVxQAoGlkUzOB8xHmSTZL5demvPAh+AMZQUVqRF0YvAJALonFHU6Pgp1/U0tRicZXFjH8yXizQhCTTJC74XAAd0I/UJ94sHvsYe+xK2GGHXd5O+Bspp1EOADN5xpknunfvTvfu3Tly5Igi3GDevHlMnToVHR2ddPs0aPD/7d15fFX1mcfxz3OzEiAERJBNtiqrCrJoLR1ZagvWYuloB1sQUVpwawVEUUehdamChVocq4wwZWqnCloVFbWCooyDS4qIIIsoRCIBwhK2iNl+88c5CZc1CUnuyT35vl+v88q5557zu0+Oj+Te5/6Wfwn1N/1JSUls37697PGVV15JYWEh/fv3Z8OGDWWFThGJH93bHy4ipddPp/juYtZnr2fdlnX85KWfkFyQzI0/vJH0+unkbMuhsH0hM7NnMvPRmTza61Hm7JoD/pD/5J3JzB45O6DfpGaVDtu9oMsFZWP2h9w/hC1FW4447+sCb4jBU0ueYsWhFTTOacz7k9+nRcsW7N6/O66GV1TG3JvnHvE4noZfStV9sucTqBd0FHK08L4jrYWytmfRekJrrp11bdChVJv8Q/mM/uNofvu33/LYy4/RfmJ7NuV4s0hPXTaVooZF3olRKzwerH+Q2a/NpuOtHVm9aTXX/+l6srZn8Vz+kWuOl85dUBklJSU0vb0pzxx4hhFLRjD6ktFx+8Er8/5MGuQdfkOQm5ELQGG61630ufznyCnO4bQ9p7H6wcO9Hoac4/WqMTv++u7xZuJPJtIsr9kRx1YWrIQCyJ+Zj5vi+Pzh+F4xpl7E++uYRFK5565atYpdu3aRnZ3NddddR7NmzY45JyEhgY8++qjOdTvv168fAwYMwMzo1KkTXbrE9+z1IuL1kOxyZheGfWcYe/59D/sf2k96/XQAxl46louKLyo796nlRw5V+2bWN3Hd86+yHv65N6HuyEYjGdnI+8b362+8wsPI//Uet2zUkvbt2pOanErL01oGE6hIjPQt7Bt0CBJFPR5i6ONNH/NVo6/4r93/xVzmln9BLVY6xv6JZU/wUepHULqqVTp0mN2BrvldmTNsDjv27mDcpd4s/eOfHM/nOz9n/m3zSZ+ajmvoOOe/zyF9Tzo//+7Pj32NooJjjpXnZzN/xsEMr5vhP37yj7gtOpT602V/4uo3ri5boeJoo84edcyEmaU9HcLQ46FU1kNZFBQWMH/ZfMYtHkdSSVKovs0uTi+GfOjSq2IflEsnmwTYvn07S5cupWvXruTn5zN16lTuuuuu4044KSISzzIaHNsr7N3fvgtAUUkRBQUFbNy6kTlL5tCnQ59Yhxe4bu26lfV+GPOoN0H3gfwDLF61mM45nVnXYh1Pj3s6yBBFYurMRuEaZhXvVHiIofM7nl+2v+qLVZzb4dwAozl167esp/Pczt6DqJEQyfuSySjJYEfGDj5N+5T+5/SnWePD38bOGjsL8IoWzQuasy1tG5EDERJJZMCfB0BDr42CdK/g0KRh5cfqv/DVC9AIFl26iEt6XXLqv2QtMWLQCEYMGsHSj5fy4EsPMubiMbRt1pZ9+fsYcN6AIworqXmpHMo4xIrNKwCIWHwXXaKlJqeSmpzKmMFjGLdkHIcaHcK+DkePDoCtxVsB2FN08nXpT6R///5l+3/+85+rISIRkfiSGEkkMTWRczucyyMdHgk6nMAlJ3pD8L738vcAuLjdxaydfPx5hETCprYvnlBXqfAQQ61Pb80fe/6RmW/P5Ly/nAcQF6tcrN+yntdWvMbq7NU8ue1J7ut+3xHPzzp/FlcPvJr0+umUlJRw4xM3knsg97jfTIA3gWLOzJyyx++ueZd+z3irOMwePJtNOzaRlpJG73t68/iIx1mwfAHPrn+Wi864iF8O/CUv/fMlBnUfxCU9L+GVD1/hqv5XlbX1wU0f8GXulwzpE65JPPuf15/+5/U/6TnNI83JIoturbpx8LqDR6x8ESZWYjTY04A/DPlD0KFUm0G9BvHUa09xfuPzyz9ZRESkHBP/dSIXb7mY4S8NB+CS9vH/ZYxIRTVPb87qotV0bNIx6FAkipbTDEDqhFS+aeRNetA8rznbZm4LOKITy9qeRbvH2wHQZE8Tdjf2liEa33o8nVp04t/+5d9OWGCojH0H97F87XJ+0Nubgd/uNEjxnmuQ14ADGQdOeO3jfR5n7KVjqxxDvCtdOmzmeTO55ce3BBxNzUmZmEJz15wvZ3wZdCjVZt6787hm8TXcdcZd3Df2vvIvEBERKcfVc67mL9l/AWDBwAVc8d0rAo5IRMKoostphqcvdhyZ1HNS2f72jO1cMb32/CHYuXcn9u+G/cbbxsweU/ZcadEBYMZ1Mxh76dhqKTqAN3N1adEB4IXLXijbPyv1LFrktTjmmrMOeGPYn3z3Sfrd0w/7jTHusXHVEk88y9ycyTm3n8Mb/3wj6FBqhDkjOymbSXMnlX9ynFizcQ0An+V+FnAkIiISBm9++GZZ0cHyTUUHqVOccxSVFGnIRS2jwkMA7h15L26Ko8P+DoC3OsG+g/sCjgp27NlBpymdiJ5Yf/2e9aTvSadXQS9ybs7hx6k/Zu+te2s8lssvupziu4u5re1tLL5jMVtnbiXr+iyWXL6EqWdN5e6Od7Nh+gYS9yfyydef8G6CN7lUi4xjCxR1TdaeLFanrWbdV+uCDqVGRFwEl+b4w6fhGWqxbqv33+qzfBUeRESk6l5e9XLZfo9IjwAjEYm9H933I5LuTeKG2TcEHYpE0RwPAZoyeAqj3h0FwIavNtD77HJ7qNSY7Nxs2jzWBhpDi7wWpERSSImksHr6ahITDqfJ87c/H7OYIpEID13zUNnjM5udyZnNzmRgj4Flx1KLU8uGYQxJHMKUn02JWXy1VYnzVnsIy3KaR7vp3Jt4eN3DQYdRrc5M8GZdblGswpmIiFRdYVFh2X5iRG/3pW7ZfGAzpMGu/buCDkWiqMdDgEYMHMGwesMAmPrc1MDi+N3833lFB9+yScvY9PtNrJu+7oiiQ2209s61LLp0EVekXcHCyQuDDqdWuKz7ZUC4ltOMNm30NNoUtcFceAorSeZ1M0pySeWcKSIiUr6ikqKy/ZsvujnASEREPCo8BCgSiTD3hrkAvFLwCk8seiKmr/965uucdetZ3Ln2TgCurH8lxXcX07Fl/MwA2/r01gzpM4QFkxbU+iJJrJT2eAjTcprRXs98nR1uR6gKD/Vb1geg7XltA45ERETCILrwMPKHIwOMRETEc8qfTMysjZm9ZWZrzWyNmf3aPz7VzL4ys5X+dmnUNXeY2UYzW29mPzhx63VHRoMMJrebDMC4D2M3MeKiDxYx+JXBbGy4EYBOBzox/9b5RCLh/LBaF6Ts9ZYBWZG1AorC2+Nh+FPDOdToEEZ4Cg8t0rwhFm0bqPAgIiJV161Ft7L9Dzd9GGAkIrHn8CaVDNN7xTCoyqfMImCic64LcCFwo5l19Z+b6Zzr4W+LAPznhgPdgMHAY2YWzk9GlfS7Ub8jY4+3OkTW9qxqaTNzQyazFs6i4fiGdJ7UmaLiw5Xv7rd354ev/rDscc9DPVk3PZwTEdYlpfME9GnfB3evY8zgMeVcEZ8SSCByMMLzV8VuvpGaNuyCYUz6ehI/+JbqsSIiUnXXDLmmbH/K/2j+K6lbzj7tbAC+1exbAUci0U65b7pzLgfI8ff3m9laoNVJLrkceNo59w2wycw2An2B5acaQ5hce861zMieQecHO/P1zK9PqY2de3cy9OGhXNXnKn710a+8gxmwnvWM/MNIPt7+MU3rNWVNmrd039CUoaQkpjB26Njq+jUkQJ8leysiRBeZwihiEVILUxnSZ0jQoVSbbdu2Mf2h6fS7qB/dunUr/wIREZGTyKiXwQfDP6Dv031JTkgOOhyRmHr+tvB8ORUm1dKv3szaAT2B9/1DN5nZKjOba2aN/WOtgC1Rl2Vz8kJFnTJ99HQa5DWgILHglJfWfPqdp1meuJzx74w/9rkDT7O2/lqWRZYBcFvb23hx8ovMv3U+g3oOqlLsUkv47yve/uxtOt7akXdWvRNsPDUkgQTyM/KZOGdi0KFUm/Xr1wOwbp16HomISPV49t1nAbigwwUBRyIiUg2FBzNrADwH3OKc2wf8CegI9MDrEfH70lOPc7k7QZu/NLNMM8vMzc2taohxIRKJsPf3eymeXkx6/fRTaqND8w4AFDcsLjv2i6a/oMvBLtjXh2//He3vOGKZSgmX7P3ZfNHwC7bs3FL+yXEowR+hNXv17IAjqT7btm0DICcnJ+BIREQkLKZtmQbA+R3ODzgSEZEqDLUAMLMkvKLDX51zfwdwzm2Pev4/gZf9h9lAm6jLWwNbj9euc242MBugd+/exy1OhFEkEqGgsIDmk5qT1ziP1aNW061dxbtdf77t87L94Q2G87eJfwOgpMRb5eD9de/TrW23Uy5sSHwJ60Shdw68kxv/eWOoVrW4/PLLmTBhAqNGjQo6FBERCZnTG50edAgiIlVa1cKAOcBa59yMqOMtok4bBqz29xcCw80sxczaA2cBH5zq64fVzn07yWucB8C8t+ZV6trpS6eX7T/wswfK9iORCJFIhG93/baKDiG2etRq3vvpewztOhQI76oWN1x2Axl7MkI1U3GHDh1wztGjR4+gQxERkZCwPIOt0Ll156BDERGpUo+H7wAjgU/MbKV/7E7gKjPrgTeMYjMwFsA5t8bM5gOf4q2IcaNzrviYVuu4lqe1pMmeJuxuvJszMs4o9/zd+3Zz4NABpj4zlS2NvK71ubfk0rRR05oOVWqZ0t4xzy73xnRGLJw9Hl798FXyGuWRsTcj6FBERERqrRRSyEjLIK1eWtChiIhUaVWL/+X48zYsOsk19wP3n+pr1hW5M3L59X/+mnvfvpfFny5m0V3eLZ04ZyIrv1rJknuWADDvjXlc83/XAJC4LxHSoVdBLxUd6qjMDZlc8cQVtKrfCiswkpPCOYv1hAUToL7WZhYRETmZQxmH2Ma2oMMQEQGqaVULqV6RSIRHfvEIBVbAq0WvMuyhYbye+TozsmfwpnuTNZvXMGvhLK5Zek3ZNZ0TOzOt+zQy788MLnAJ1I68HWSlZ9GrdS9KHixh6IVDgw6pRiSaVy998+Y3A45EREREREQqokqTS0rNiUQiLB23lL5P9eWFQy/wwt9fgBTvue7zuns7/hfav2r5KyYMnUDb5m2DCVZqhdI5HYpKigKOpGYlRBKwQ0aPjpoPQURE5EQ67O9AlmUFHYaICKAeD7Van059mPvduQB8J/E73sGjZsX45OpPeOQXj6joICQlJgHw1hdv0XJ8SzI3hLP3S1FJES7V8eRrTwYdioiISK21/5v9WIGGJYpI7aAeD7Xc6O+PZvT3RwOQnZtNelo6W3K3sG3PNh546QHOaFL+BJRSNyRGvP+dcwty2dV4F7v27Qo4oppxsOggAMvWL2PM4DEBRyMiIlI75TbNDToEEZEyKjzEkdantwagW/1udGvXjUE9BwUckdQm9VLqETkYIcG8IRdhXdXip+f8lGlZ02hUr1HQoYiIiNRaAxhAYUlh0GGIiAAaaiESGn069aF4WjHDzhoGQEJCQsAR1YyurboCkJGm5TRFRERO5M0pb7LsN8uCDkNEBFDhQSR0ip03EUhYezwsyFwAQKsmrQKOREREREREKkJDLURCYlPOJi6cdiGNEhuR6BKpl1wv6JBqROlQkh9d8KOAIxERERERkYpQ4UEkJPK/yWdHxg4GNBjAhokbgg6nxrw4+UUKCgtITkoOOhQREREREamAcPbFFqmDEhO8OmJRSVHAkdQ8FR1EREREROKHCg8iIZGc6H0YX/rVUprc0oS1X64NOCIRERERERENtRAJjdJVLHY13gXAwUMHgwxHREREREQEUI8HkdBITUo94nHp0AsREREREZEgqfAgEhLNGjeDwsOPEyMqPIiIiIiISPBUeBAJESu0w/tmJzlTREREREQkNlR4EAmJQwWHcGmu7HFaSlqA0YiIiIiIiHhiXngws8Fmtt7MNprZ5Fi/vkhYJScm03ZfW+7tdC9uiqN9i/ZBhyQiIiIiIhLbVS3MLAH4D+ASIBv40MwWOuc+jWUcImEUiUTY/PvNQYchIiIiIiJyhFj3eOgLbHTOfeGcKwCeBi6PcQwiIiIiIiIiEiOxLjy0ArZEPc72j4mIiIiIiIhICMW68HC8afbdMSeZ/dLMMs0sMzc3NwZhiYiIiIiIiEhNiHXhIRtoE/W4NbD16JOcc7Odc72dc71PP/30mAUnIiIiIiIiItUr1oWHD4GzzKy9mSUDw4GFMY5BRERERERERGIkpqtaOOeKzOwm4HUgAZjrnFsTyxhEREREREREJHZiWngAcM4tAhbF+nVFREREREREJPZiPdRCREREREREROoQFR5EREREREREpMaYc8esZlmrmFkukBV0HFJpTYGdQQchtYJyQUB5IIcpFwSUB3KYckFAeRDP2jrnyl2KstYXHiQ+mVmmc6530HFI8JQLAsoDOUy5IKA8kMOUCwLKg7pAQy1EREREREREpMao8CAiIiIiIiIiNUaFB6kps4MOQGoN5YKA8kAOUy4IKA/kMOWCgPIg9DTHg4iIiIiIiIjUGPV4EBEREREREZEao8JDHWFmbczsLTNba2ZrzOzX/vEmZvaGmX3m/2zsH+9sZsvN7BszuzWqnVQz+8DMPvbb+c1JXnOU3+5nZjYq6vj9ZrbFzA6UE3MvM/vEzDaa2R/NzPzj081snZmtMrPnzSyjqvenLglTLkQ9f6uZOTNreqr3pa4JWx6Y2c1mtt6PYVpV7k1dE6ZcMLMeZvaema00s0wz61vV+1NXxGkeHPc8M0sxs2f8/HjfzNqd2l2pm0KWCxPM7FPz3jMuMbO2p3pf6pow5UHU81eY935Rq2cEwTmnrQ5sQAvgfH+/IbAB6ApMAyb7xycDD/n7zYA+wP3ArVHtGNDA308C3gcuPM7rNQG+8H829vcb+89d6MdzoJyYPwC+7b/mq8AQ//j3gUR//6HSmLXVvVzwn2sDvA5kAU2Dvr/xsoUpD4ABwGIgpTTWoO9vPG0hy4V/RO1fCiwN+v7GyxaneXDc84AbgMf9/eHAM0Hf33jaQpYLA4A0f/965ULdzIOo3+Ed4D2gd9D3ty5u6vFQRzjncpxzK/z9/cBaoBVwOTDPP20e8GP/nB3OuQ+BwqPacc650ipikr8db6KQHwBvOOd2O+f2AG8Ag/023nPO5ZwsXjNrAaQ755Y771+L/46K7R/OuSL/1PeA1hW8DUK4csE3E7jtBK8tJxCyPLgeeNA5901prBW8DULocsEB6f5+I2BrBW6BEH95UM550TE/Cwwq7RUj5QtTLjjn3nLO5fsP9Z6xEsKUB7578Yomh8prR2qGCg91kN/lsCdexbF56f+g/s9mFbg+wcxWAjvw/oF4/zintQK2RD3O9o9VVCv/mvKuvxbv2y45BfGeC2Y2FPjKOfdxJdqTo8R7HgBnA9/1u1S/bWZ9KtGuRAlBLtwCTDezLcDDwB2VaFd8cZIHJ1PWtv9FxV7gtGpqu04JQS5Euw69Zzwl8Z4HZtYTaOOce7k62pNTo8JDHWNmDYDngFucc/tOpQ3nXLFzrgde1bivmXU/3ksd79JKvEy515vZXUAR8NdKtCu+eM8FM0sD7gLuqURbcpR4zwP/ZyJet8wLgUnAfH27WXkhyYXrgfHOuTbAeGBOJdoV4ioPTqYm264zQpIL3guYjQB6A9Ors926IN7zwMwieL1jJ1a1LakaFR7qEDNLwvuH46/Oub/7h7f73VZLu69WuIuycy4PWAoMNrMLzJvMa6X/LXQ23tj7Uq05SZfX0kqov/3Wvz66O9wR1/sTzlwG/NzvaiuVEJJc6Ai0Bz42s83+8RVmdkZF467rQpIH+M/93e/O+QFQAmii0UoIUS6MAkrjXwBocslKiLM8OJmyts0sEW/Yze6Kxi2hygXM7Ht4X1QMdf6QPKmYkORBQ6A7sNR/v3ghsNA0wWTMJQYdgMSG/+3fHGCtc25G1FML8d6oPej/fLGcdk4HCp1zeWZWD/ge3qQy7wM9os5rAjxg/ky3eBNCnrDLq3OuOPp6v439ZnYhXreuq4FZ/vHBwO3AxVHj9qSCwpILzrlPiOre5/8x6e2c23myuMUTljzwn3oBGIj3puJsIBlQHlRQyHJhK3Ax3hvbgcBnJ4tZDovHPDiJ0piXA1cAb+pLiooLUy6Y18X+CWCw0/w/lRKWPHDO7SXqywgzW4o3+WVmeddKNXO1YIZLbTW/Af3wuiutAlb626V4Yx6X4L05WwI08c8/A6/yuA/I8/fTgXOBj/x2VgP3nOQ1rwU2+tvoqOPT/PZK/J9TT3B9b/81PgceBcw/vhFvDFjp7/F40Pc3nrYw5cJR52xGq1rUyTzAKzQ85T+3AhgY9P2Npy1kudAP+CfwMV5RolfQ9zdetjjNg+OeB6Ti9XjZiLcCSoeg7288bSHLhcXA9qjfY2HQ9zdetjDlwVHnLEWrWgSylf6hFhERERERERGpdprjQURERERERERqjAoPIiIiIiIiIlJjVHgQERERERERkRqjwoOIiIiIiIiI1BgVHkRERERERESkxqjwICIiIiIiIiI1RoUHEREREREREakxKjyIiIiIiIiISI35fyAK68zIiTSqAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from scipy import signal\n", + "data = dataset.data['CODtot_line2'][:].copy()\n", + "detrended_values = signal.detrend(dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'])\n", + "line_segment = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] - detrended_values[:]\n", + "line = line_segment - line_segment[0]\n", + "line10=10*line\n", + "fig, ax = plt.subplots(figsize=(18,4))\n", + "\n", + "ax.plot(data['2013/1/1':'2013/1/14'],'k--', label='original data' )\n", + "\n", + "dataset.data['CODtot_line2']['2013/1/5':'2013/1/8']+= line10\n", + "\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/1':'2013/1/14'],'g--', label='data with drift')\n", + "ax.legend(loc='upper right', shadow=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Drift detected in period 5 to 6, slope: 55.642857142857146\n", + "Drift detected in period 6 to 7, slope: 56.714285714285715\n", + "Drift detected in period 7 to 8, slope: 48.5\n", + "Drift detected in period 8 to 9, slope: -112.21428571428571\n" ] }, { - "name": "stderr", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.detect_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=34, \n", + " plot=True, period=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_HydroData.py:1380: FutureWarning: pandas.tslib is deprecated and will be removed in a future version.\n", - "You can access Timestamp as pandas.Timestamp\n", - " if isinstance(self.data.index[0],pd.tslib.Timestamp):\n" + "Drift detected in period 5 to 6, slope: 55.642857142857146\n", + "Drift detected in period 6 to 7, slope: 56.714285714285715\n", + "Drift detected in period 7 to 8, slope: 48.5\n", + "Drift detected in period 8 to 9, slope: -112.21428571428571\n" ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "avg,std = dataset.compare_ratio('CODtot_line2','CODsol_line2',2)" + "dataset.remove_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=34, period=2, \n", + " plot=True)" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 41, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Use the average obtained from the ``compare_ratio`` function to fill in missing values. (*in this case, as mentioned before, this does clearly not work, since zero-values are replaced with zero-values. This only showcases the function and its arguments*)." + "fig, ax = plt.subplots(figsize=(18,4))\n", + "ax.plot(dataset.data['CODtot_line2'],'g--', label='data with drift')\n", + "ax.plot(data['2013/1/5':'2013/1/9'], label='original data')\n", + "ax.legend(loc='upper right', shadow=True)" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 42, "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:04.632959", - "start_time": "2017-05-09T11:55:03.980745+02:00" - } + "scrolled": true }, "outputs": [ { - "name": "stderr", + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.data['CODtot_line2']['2013/1/9':'2013/1/12']+= line10.values[::-1]\n", + "dataset.data['CODtot_line2']['2013/1/5':'2013/1/8']+= line10\n", + "\n", + "fig, ax = plt.subplots(figsize=(18,4))\n", + "ax.plot(dataset.data['CODtot_line2'],'g--', label='data with drift')\n", + "ax.plot(data['2013/1/5':'2013/1/12'], label='original data')\n", + "ax.legend(loc='upper right', shadow=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", "output_type": "stream", - "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:462: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", - " 'ensures the proper working of the package algorithms.')\n" + "text": [ + "Drift detected in period 5 to 6, slope: 51.6\n", + "Drift detected in period 6 to 7, slope: 52.53333333333333\n", + "Drift detected in period 7 to 8, slope: 44.86666666666667\n", + "Drift detected in period 9 to 10, slope: -48.266666666666666\n", + "Drift detected in period 10 to 11, slope: -41.06666666666667\n", + "Drift detected in period 11 to 12, slope: -34.6\n" ] }, { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -4272,99 +1448,63 @@ } ], "source": [ - "dataset.fill_missing_ratio('CODtot_line2',\n", - " 'CODsol_line2',avg,\n", - " [dt.datetime(2013,1,22),dt.datetime(2013,1,23)],\n", - " only_checked=True,plot=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Instead of a ratio, a correlation can be sought. In case of a zero intercept, this of course gives a result in the same range if the same data is used. To have a good impression on how useful the calculated correlation is, a prediction interval is plotted as well when ``plot`` is set to ``True``." + "dataset.detect_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,15)], max_slope=30, \n", + " plot=True, period=2)" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 44, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n", - "C:\\Users\\joras\\Anaconda3\\envs\\wwdata\\lib\\importlib\\_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n", - " return f(*args, **kwds)\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "slope: 0.4055129249855649 intercept: 0 R2: 0.9737746563763395\n" + "Drift detected in period 5 to 6, slope: 55.285714285714285\n", + "Drift detected in period 6 to 7, slope: 56.285714285714285\n", + "Drift detected in period 7 to 8, slope: 48.07142857142857\n", + "Drift detected in period 9 to 10, slope: -51.714285714285715\n", + "Drift detected in period 10 to 11, slope: -44.0\n", + "Drift detected in period 11 to 12, slope: -37.07142857142857\n" ] }, { "data": { + "image/png": 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\n", "text/plain": [ - "(
,\n", - " )" + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dataset.remove_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=35, period=2, \n", + " plot=True, drift_type='B')" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" ] }, - "execution_count": 32, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -4372,40 +1512,68 @@ } ], "source": [ - "dataset.get_correlation('CODtot_line2',\n", - " 'CODsol_line2',\n", - " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", - " zero_intercept=True,plot=True)" + "fig, ax = plt.subplots(figsize=(18,4))\n", + "ax.plot(dataset.data['CODtot_line2'],'g--', label='data with drift')\n", + "ax.plot(data['2013/1/5':'2013/1/12'], label='original data')\n", + "ax.legend(loc='upper right', shadow=True)" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 46, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "After the previously made assessment, use the correlation function to fill gaps in the dataset." + "fig, ax = plt.subplots(figsize=(18,4))\n", + "\n", + "ax.plot(data['2013/1/1':'2013/1/14'],'k--', label='original data' )\n", + "\n", + "dataset.data['CODtot_line2'].update(data['2013/1/1':'2013/1/14'])\n", + "dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] += line10\n", + "\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/1':'2013/1/14'],'g--', label='data with drift')\n", + "ax.legend(loc='upper right', shadow=True)\n" ] }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:06.016129", - "start_time": "2017-05-09T11:55:05.261370+02:00" - } - }, + "execution_count": 47, + "metadata": {}, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:569: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", - " 'ensures the proper working of the package algorithms.')\n" + "Drift detected in period 4 to 7, slope: 90.5\n", + "Drift detected in period 5 to 8, slope: 103.42857142857143\n", + "Drift detected in period 7 to 10, slope: -98.71428571428571\n", + "Drift detected in period 8 to 11, slope: -99.28571428571429\n" ] }, { "data": { - "image/png": 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\n", 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LC9+5kBuevYHie4rxifWx9R8cPxiAb4d9S6hfKIv3LObZX56t9nxd3u3CLe1v4cXlL9YY518u+As9onuczUsVEZHzmF2SW8MwZgA3ABmmaXaqbHsWuA84VNltomma8yvPPQncA5QDD5umuaiy/VrgLcAdmG6a5sv2iE9ERMTZhL0eBtRuI6eztS51XbXkduX+ldw85+Ya+/934H+5rfg2gv4XhN/Pfhj+BkGDggAwDKNKYnu8G9vdCEDXiK58s+MbNqVvqnJ+V+aukya2AFOum1Lr19RQElISGPTpIL667Ssua36Zo8MREZFTsNfcn5nAtTW0v2ma5gWVf6yJbQdgGNCx8pp3DMNwNwzDHZgCDAQ6AMMr+4qIiJwTTNPkg/UfkF+S3yDP9XifxwFYmbKSPVl7KCgt4F+//IuRX4+k74y+Vfpf1eIqNjywgbwn8yh/t5zI0ZE02tSIuGfj6LOvDy3/3bLWz+3n6cfGBzdS9nQZaX9Po2BiwSn7j+wyks1jNlcpB+QsSstLOVxwmJLyEkeHIiIip2GXkVvTNH81DCOult0HA5+ZplkM/GkYxm7AOgdpt2maewEMw/issu82e8QoIiLiaGsOrOHeefeSmJWIj4cP9110HxbTUi/rTP888ievrnwVqBi5bf12a97o/waTfp4EwOvXvM7hgsM8d8VzzN85nz7b++CX4Yd/hD/GYAPDwyDy/kg8Aur+UcHdzZ2IgAgAogOjOZB7oMZ+U6+fSoBXQJ2fpz4ZhkoBiYi4ivreteGvhmH8YRjGDMMwGle2RQP7j+uTUtl2snYRqYHFtPDF1i+wmBZHhyIitRTdqOJtLSElgaKyIt5e8za/7fvN7s9TWFpIq8mtqrU/tvgx2+NHej3CC/1eIGt2FlG3RLHtlm2kvpsKgF87P2IeizmrxPZEv971K+/d8B7fD/8egKHthzL39rlsHrPZaRPb45lm/U8fFxGRs1OfG0pNBZ4HzMq//wPcDTVWQzepOdGu8Z3EMIz7gfsBYmNj7RGriMtZsmcJt315GwvuWMC1rWtaFSAizsY67faXfb/Y2rIKs87qnruzdhMZEIm/lz8A69PW021aN9v574d/T8ewjrz020sMaD2A/q364+nmyaFZh0h6Noni5GL8u/jT/tP2hN4SelaxnErLxi25v9v9QMOsM7YXo8aPLSIi4ozqLbk1TTPd+tgwjPeB7ysPU4CY47o2A1IrH5+s/cR7TwOmAXTv3t113iFF7MjbwxsAH4+aN3YREeez8eDGam1nM+3VYlpo83Ybrml5ja2Wbe8PetvOLx21lKtaXgXAe4Peo+xoGe4e7hhuBoW7C/Fu5k3bd9rS5Lommn57EmH+YdzZ9U4iAyMdHYqIiJxGvSW3hmFEmqaZVnl4E7Cl8vF3wCeGYbwBRAFtgDVUjOi2MQyjBXCAik2nRtRXfCKurrisGECbnIi4kKs+vKpa29mMDFo3prLWsv099Xfb74SZg2faEtuS9BJS/i+FA+8coP3s9jQd1JS4Z+MwPAwltafRJqQNs4bMcnQYwrGp4fo3KyInY69SQJ8ClwNNDcNIASYBlxuGcQEVU4uTgAcATNPcahjGHCo2iioDxpqmWV55n78Ci6goBTTDNM2t9ohP5FyUkJIAwIrkFfRv1d/B0YjI6ZRbymtsP5sP6v5e/vh5+nFp7KUAfL+rYpLUirtX0CemD0X7ikh+LZmDHxzEUmwh9JZQfFv6AuDmWd/bbojYl9u/3Lg09lJ+vetXR4ciIk7KXrslD6+h+YNT9H8BeKGG9vnAfHvEJHK+MGtemi4iTiY9P73G9rYhbasc55fkszd7L53DO5/yfmsOrOHGT2+koLQAdzd3jhQd4dlfniUyIJI+MX0wTZONV22kOLmY8FHhxD4ei1875yu14+wSUhK4fOblzBs+j2taXePocM57vyXbfwM2ETl31OeGUiJSj6zlNcL8wxwciYjUxv6j+6scXxp7KXHBccQ3jbe1Ld6zmAGzBwBQ9FSRbW19uaWcwrLCKrsK95ze0/a4W2Q3Jq+eTNsDbXlw54NY/mrBzduN+P/F4xPng0+M1ubXlWmaFJcXU27WPPIuIiLOQ3OSRFxUh9AOAFU+GIuI80rJSQGgiW8TAL4d9i2vXfMayUeTAXhkwSO2xBYgpzjH9njC0gkEvhRYZY39lOumADCw1UAe5VGuePoK3nv/Pbpt6kbe5jwAgi8NVmJ7lrS+03m0bNySkV1GOjoMEXFiGrkVcVH6wCXiWpoHN6eJbxMS7kkgNTeV7KJsWy3az2/5nMlrJlfpf7T4KKH+FaV5Zm+eDcCuzF2E+oUyZ+scUnNTOXDXAdJuS2PT6k14hnvS/JXmRD0YhUcjvb3bm+rcOt77g96nsU9jR4chIk5MI7ciLurP7D8ByMjPcHAkIlIb3aO6s2XMFtqEtKFfXD98PXxt527/8vZq/Y8WHbU9HtN9DADP//o8Ua9GMfl/k3l5xctENIvAO9qbNu+0oVdSL2Ifj1Via2eqc+s8HvrhIV5Z8YqjwxARJ6Z3QBEXZa25GBsU6+BIRKS2jq+VGuQTdMq+x09LvrPrnfx7yb8pmlnERys+onF+Y25/9Hbc3Nzo9FWneotXIDwgnIe6P6TftU5gZ+ZOisuLHR2GiDgxJbciLqqwtBCAgtICB0ciIrXRZWoX7ux6J+P7jAfA18MXTzdPSi2l1fpeEnsJ/eL6AVCWW8aRt44w/935eGR6sC16G0tHLmXVY6saNP7zVVxwHFOun+LoMKRS0pEkR4cgIk5M05JFXNT6tPVARZ1bEXFuhaWFbM7YXGVDKMMwqiW2C+9YyIS+E5h7+1zcjIq36KI/izjy7BE2Bm3k0dGPErUkihlvz6BjeMcGfQ3nK9M0KS0vxWJaHB2KiIichpJbERenOrcizu9wwWEAQv1Cq7TPvX0uk689tpHUgNYDeKLlE8wbOY+fhv0EQECXAP75z38y/5n53D/2foa0H9JwgQvrUtfh9W8vFiQucHQoIiJyGpqWLOKiYoJigGP1bkXEeVnXCfp4VC3LMzh+MAD94vqxf+N+dtyzg/SP0mlW3oz0gemYpklhWSFrvNZwb9N7GXPxmAaPXcSZnPgzJCJyPCW3Ii6qfdP2QEXdPxFxbtbpyF7uXjWeD1sYRtZdWWR4ZxD1QBRXe1/Nbf1vY5gxjJX7V1JqKaV/q/4NGbKcQLNkHC+mUQxXt7za0WGIiBNTcivi4lR7UcT5+Xr4MqjtINuMC9M0OfrbUdz83GjUvRGNr25M7IRYmo1rhleYF8WvF9t2S/499XcA+jXv57D4z2eqKe48Zg2ZRWNf1bkVkZNTciviohKzEoGq5UJE5OyYpsk/lvyDfs37MajdILvdt0XjFnw3/DtM0yTzh0z2vbiPnJU5NB3alE5fdcI72puWLx6bhRHkE8SR4iMADO88nDYhbfShXs57Dy98mLYhbfnqtq8cHYqIOCkltyIuKsw/DFCdWxF7MgyDd9e9i2madk1uAQ7PO8yf//yT/D/y8Y71ps1/2xBxd81r5psHNWdB4gKM5wzuv+h+3hv0nl1jkdqLCIjgib5P0KpxK0eHct7bkrGF9Lx0R4chIk5MuyWLuKj8knxAI7ci9pRdmE1+aT5vJLzBN9u/Oev7WYotWMos/LrvVyZMm0BBQQHxs+Lpubsn0WOjcfd1r/G6b4d9y8A2AwGYtn6aPtA7ULNGzXj56pdpH9re0aEIcKjgkKNDEBEnpuRWxEVtydgCwIr9qnMrYi9rDqyxPf5257d1vk9ZXhn739hPQssEMj7JIK8kj1kXzMJ7mTcRd0bg5nnqt19fT19eu+Y127G3h3edY5GzU2YpI6swq0qNYlfy8R8fs3D3QkeHISLSIJTcioiIVDo+gZm1adYZX1+aVUrSc0kkNE9gz9/34NfOD99WvpSUl1DmUYaPV+3LmMQGxVL+TDlpf08j2Cf4jGMR+9icvpmQV0Ncts7tyG9GMvDjgY4OQ0SkQWjNrYiLspYAigyIdHAkIueOMx2dKyorqlJ3c/P1m8lJyCHkxhCiHo+iSZ8mGIZB4eZCoGLX5DPhZriplrXIcUJ8Qxwdgog4MY3cirio+KbxALbSIiJy9k5MbvNK8myPswqzGPvDWPJK8kg+mozxnEGrx1qxcMRC3ljyBl2mdiH65Wi6buzK149+TdOlTXly2ZOs3L+SF5e/CECAV0CDvh6xH9W5dbyIgAhubn+zo8MQESemkVsRF1VmKavyt4icXF5JHmsPrOWKFlecst+Jye1f5v6FnZk7uSTmEvrE9OGdde+wJnUN2euz+efyf3L51sspdyvnM/fP2Nx6MxEZEYT5h5GRnwHAKyte4ZUVr9juF+QTZP8XJ/XK1evcmpPOnaT8k6Gf6GdIRE5Jya2Ii7LWuRWR0/vXL//itZWvsfLulfSO6W1rzy/Jx9/L33Z8edzlxDeNZ8fhHQB8tb2inuaWjC0UlRfhWerJ0NeG0juxN0XeRczpM4cve31JVmCW7R7WxLYmGrkVqbvxS8YTFRjFvOHzHB2KiDgpTUsWcVFNfJsAEB0Y7eBIRJzb3uy9/Jb8GwCj545mxFcjKC4rJvClQAJeCmDV/lUA7Dy8k8a+jdnwwAZ2/233sRuYEJcex8yNMyn1LKXAu4Cku5O4MvVKpv42lR3P7WDVPavIfTKXYZ2GnTSOuOC4+nyZUk8iAyL59xX/pn1T1ywFZDxnYDzn2qPPVuvT1rNs7zJHhyEiTkwjtyIuKrc4F4DMwkwHRyLiPCymhbE/jCU9P522IW3p3aw3Qz4fYjufmJVIYlYigV6BtvW0Ly1/iUMFh0hISQDg05s/ZVinYXw59EumvjCVO5bfQUxaDCMeGYFblBsHXzjI4wMex8vbC4BQ/1BC/UMBGN5pOIt2L6JPTB82HNzAA90eYPLqyWQWZjKh74QG/q8h9hAeEM5Tlz3l6DCkUmFZoaNDEBEnpuRWxEXtytwFwMr9K7m29bUOjkbEOeSX5PPu7+/WeO6jmz4itziXh+Y/xLT102zt83ZVneI46vNR9FvTj+hXovnnrn/i29aXvBfzuKXtLbw9+G3c3dxP+vw3truRrCeyKLeUk1mYSZh/GP/o8w/GLx7P0PZD7fMipUGVlJeQlptGqH8ofp5+jg5HREROQdOSRUTknBHoHcjDPR6u1v70ZU8zsstIxlw8ho9u+giAQ/84hDnJZO7tc239/nrxX9lz+x523r8TD38POszpQI9tPbjqiat456Z3TpnYHs/dzZ0w/zAAfD19mXL9FNvorriWHYd3EPdWHAt3L3R0KCIichoauRVxUdZSQFGBUQ6ORMR5ZBZkMr7PeCavmQzAhgc24OHmQYfQDrY+I7uM5I7Od9h2wR0YNpDpSdPpkNeB3pMqNptqsqEJ/p38XX6nXLEf0zx3dh12ZbFBsY4OQUScmJJbERfVNqQtUFH3T0QqNH2tKQDlz5TjZpx8cpJhGBSnFZPyZgqpU1NpldeKgBsCsBRbcPN2I6CzdjWWCgb6gsNZhPiGMKjtIEeHISJOTMmtiIsqKisCqtflFDlflZaX2h6fKrEFyFyQyZabtmCWmoTdHkbshFgCuiihlZMzcc2R23Opzu2Xt31JoFego8MQESem5FbERVnr3KpupkiF/NL8U5/fmk9ZThlBvYNo1KsRkfdG0mxcM/xaa5MgOTlnnZp+uOAw7oY7jX0bOzqUBjNh6QSCfYJZOFLrn0WkZkpuRVxUI+9GQEUNRhGB/234HwAdQztWac9ZncO+l/aR+W0mjfo24qLlF+HZ2JO2/23riDDFxUQGRPLWtW/RNbyro0Ox+WD9B9w7716gYhfwtQfW8tbAt2rsa61xey6M4K4+sNrRIYiIk1NyK+KicopzADiYd9DBkYg4h8cWPwbA81c8D8DRFUf585k/OfLjETyaeBD3bBzRf412ZIjigkL8Qni4Z/UduB3px6QfbY9nbpzJsj+XnTS5FRE5n6gUkIiL+jP7TwBWpaxycCTibEzT5H8b/kd+yamn6Z5LUnNTAbjvgvu4sdWNABTsKKBgRwGt/tOKXvt6ETcpDs8QT0eGKS6oqKyIrRlbOVp01NGh2MzZOsf2OLpRNHHBcY6F2Th3AAAgAElEQVQLRkTEiSi5FRE5x6zYv4K7v7ubp3962tGhNJjY12IZsHEAI8aPIPWdikQ3/M5weu3tRcxjMXgEaKKS1M3e7L10mtqJRXsWOToUmzJLGQCvXP0KS/cuJelIkmMDEhFxEnq3F3FRXcK7AKpzK9WF+4cD0C2ym4MjqX/lheXse28fsyfPJuJoBD6dffBt7QuAm6e+vxX7ccY6t4/3fZwnlj7h6DAa1Ilr6kVEjqfkVsRFtW7SGoCmfk0dHIk4G2sZHItpcXAk9W/b8G1kfptJdPdooidE02JoC6fd3VZckzPXuX3xtxcdHUKDCvQKpH+r/o4OQ0ScmL7WFnFRuSW5wLF6tyJW1imKv+z7xbGB1IOSjBL2PrWX4oPFAPj8zYfnH3qelA9SaHlzSyW2Um+cqc7t1S2vBuCpH5+iX/N+p+xrTjLPiZ2SAX4Y8QPDOg1zdBgi4sQ0civiohIzK+rcqhSQnMha7zUjP8PBkdhP0b4ikl9L5uAHB7EUW/Br70fI8BCu3nw1yWHJvBTykqNDlHOUM35hUm4ptz3uENqBbYe2OTCahjPxx4l4uXux7M5ljg5FRJyUklsRFxXgFQBAmH+YgyMRZ2P9wuPWDrc6OJKzZ1pMdt67k/SP0sGA8FHhxD4ei187P1buX0ny0WS6hHfhosiLHB2qnKMiAiKYceMMekT3cHQoNiM6j+CnpJ8AmLpu6in7nkt1bpcnL3d0CCLi5OwyLdkwjBmGYWQYhrHluLYmhmEsMQwjsfLvxpXthmEYkw3D2G0Yxh+GYVx03DWjK/snGoYx2h6xiZyrjhQdASD5aLKDIxFn4+7mDkCQT5CDI6m7gt0FABhuBpgQNTaKnnt6Ev9BPH7t/ADYeXgnAF/f9jUebvquVupHsE8wd114Fy0bt3R0KAAUlxVXG6k1MCgsLXRQRCIizsNea25nAtee0DYBWGaaZhtgWeUxwECgTeWf+4GpUJEMA5OAnkAPYJI1IRaR6g7kHgBg9YHVDo5EnE1uccV67E0HNzk4kjNjmibZP2az6ZpNrGm7hvxtFdOr4/8XT5v/a4NPjE+V/q2atOK+i+4jNijWEeHKeaKwtJCElAQOFxx2dChsO7QNnxd8eDPhzSrtJiahr4U6KCoREedhl+TWNM1fgawTmgcDsyofzwKGHNf+oVkhAQg2DCMSGAAsMU0zyzTNbGAJ1RNmETmBM5anEMey1sDcfni7gyOpHdNicvjbw6zvvZ5NV20ib3MeLV9piXeM9ymvu6z5ZUwbNA1Pd88GilTOR/tz9tP7g94s3rPY0aGwOuXkX2bml+azOX1zA0YjIuJ86nMeV7hpmmkApmmmGYZhXRgYDew/rl9KZdvJ2kWkBt2jugOqcyvVWWsg943p6+BIaqc0q5Rtw7fhFeFFm6ltiPhLBO4+7qe9LiM/g6Z+TW2lj0TOddYlB1ZuhluVkl/nw+75vZr1cnQIIuLEHPGJoKZtB81TtFe/gWHcbxjGOsMw1h06dMiuwYm4ihbBLQBo7KvZ+1KVs9e5LS8q58DUA2wdthXTNPFq6sWFv11Ij109iH4wulaJ7S9JvxD+ejh/m/+3BohYxDlmyXi7V53NcOLP+Ml+5v08/eotpobk4+HDZbGXOToMEXFi9ZncpldON6byb2tNihQg5rh+zYDUU7RXY5rmNNM0u5um2T00VGtM5PyUVVixEkCbiMiJNmdUTE1MOJDg4EiqKsspI/nVZFa3WE3iQ4kU7yum7EjFFOrAboG4edT+LenyWZcD0Dm8c32EKmJj1Pjdu2MMbDOQlXevPOn5mpJbc5JJ/sT8+gyrwfx4548Mjh/s6DBExInVZ3L7HWDd8Xg08O1x7XdW7prcCzhaOX15EdDfMIzGlRtJ9a9sE5EaJGZV1LltG9LWwZGIs8kryQOO7ajtDHLW5JDQPIG9T+zFv7M/XX/qyoUrL8Szcd3WyzZr1AyAO7veac8wRZyaaZr0mdGnStv43uNtj511toa9PPXjU0xYOuH0HUXkvGWXNbeGYXwKXA40NQwjhYpdj18G5hiGcQ+QDFgLLs4HrgN2AwXAXQCmaWYZhvE8sLay379M0zxxkyoRqeTr4QtAE98mDo5EnI21BvKY7mMcGkfR/iKKk4sJ6huEf2d/mg5pStTYKBp1b3TW936o+0M09Wt6zky3FOcVERDBnFvmOEWd23m75lVre33V6wAMajuIYJ/gaufPpTq31tq+IiInY5fk1jTN4Sc5dVUNfU1g7EnuMwOYYY+YRM511lG53Vm7aR/a3sHRiDOyJrkNrWBXAcmvJJP+UTo+LXzosaMH7r7uxP8v3i73f3v128Q3jeem9jfZ5X4ipxLoHcitHW89fccGMPuP2TW2uxluvHTVS+d8WSx/E0odHYSIODVtMSniotLz0wFYm7r2ND3lfFNSXgLAb/t+a9Dnzd+az9bbtrImfg0Zn2QQ9UAUXRd3xTDst2ZxyZ4lPLzwYacoyyLnh4LSApbsWUJqbo3bgDSok+2GbDEtdJraia7vdm3giBpWHo3YgL+jwxARJ6bkVsTFOcMOnuJcrCO21o2l6pNpmljKKtb5FewqIGtRFrETYum1rxdt3m6DT3Mfuz1X0pEk+s/uDxwrhSVS39Jy0+g/uz/L9i5zdCjkl556Y6g/j/zZQJE4TgdOv5u6iJy/6rPOrYjUI2sNU9W5lRNdHHUxcKzebX0wTZOs+Vnse3Efja9uTIvnWtB0cFN6J/fGI8j+by1bM7bSaWon2/HQ9kPt/hwip2LWXJ2wQRWUFjg6BBERp6aRWxEXZV1bFegd6OBIxNlY69zWx6i+pcxC+qfprLtgHZtv2ExxSjE+LSpGZw03g0Xpi3hiyRNAxfToxMxEbp5zM4cLDtf5OXOLc6sktqVPl6q+szQYe06rP1v5JfmE+4ef9Px9F91XY3t0YHR9hSQi4lQ0civioqxrbvNLzo36hWI/K/avAGDDwQ12v3fiXxNJey8Nv3g/4mfFEzY8DDfPimT6i61fcNuXtwEQ3zSeRxc9ytHiowB8vf1rpg+azh1d7sDH49hU5dziXHJLclm8ZzFlljKGxA+hqV9TADYe3MisjbP4Pe13W/8tY7bg4aa3Lml4zrAEZMMDFT/TjX0b23ZBPt6Q+CHV2s6FXZJFRGpLnxBEXNTurN0AXBR5kYMjEWdjrXNbWFYIVHwBkpiVyAURF5zxvcryykh7L42QwSH4tfYj6sEofK/0JWpoFPd8fw9XbbvKVmv27u/utl13/GOre+fdy73z7uXBbg/y1sC3yCzIJOqNqtPqX1/5Ol0jutI5rDNP//R0lXMfD/2YjmEdz/g1iJwNA+cZuT3djIUpa6dwXZvrGigaERHno+RWxEV5unkCEOQT5OBIxNlYzIoNnp657BkARn4zkrk75rJj7A58PX1rVS6kNLOUlLdTODD5AGXZZaTlprFl8BZ2Ht7Jq9tfhRegW2Q3Ptz0IaPnjgbg2tbXcij/EFOvn8pPST/xxNInarz3u7+/yydbPmFcz3HVzu3M3MnOzJ3M2Tqn2rkRnUfU+r+BiL2EB4Sz4I4FdA7r7NA4TNNk4rKJXNv6WkL9Q2vsMz9xfrW2c6nOrYjI6Si5FXFR1jq32w5to21IWwdHI87Emtx6uXsBcLSoYmpw/JSKOrOn+5C7d+JeUianYMm3EDI4BK+/ehG/Ih6+q9qvQ2gHjhYftc0iGN5puG0Ut3tUd9o3bc8PiT/gZrgxdd3UKtfmFOfwr1//VavX848+/2BYp2G16itib36eflzb+lpHh0FhWSEvr3iZxr6Nub/b/Wd+fWkhvp6+9RCZiIjzUHIr4qIyCzMB+D319xrXWcn5y7o28Ptd39MtqhvrUtedtO/C3Qt5dcWrzLh4BqmBqWw6uIm4pDiaXt+U9y9+n/fz38dvjZ+t/6c3f0qoXyhpeWnc2O5GCksLKSwrJDIgEk93T1s/wzAY1G4Q/eL64evhy4URF5JXksf93e7nQO4B2v23XZU4/D392TZ2G83/rzkAl8ddTsvglkQ3iuZfV9QuCRapDwWlBSzcvZCLIi8iLjjOYXFY91fw8/Qj2CeYmEYx7M/ZX+vr/V70Y8MDG+q0PEFExFUouRUROcdYpyz+kfEHJeUl5JbkVjmffDSZwZ8NZur1U0lOSOaS1y5h7/a9PPKXR9gSuwXaAgZQuVdZQWkBTXybcPcFd1cbQW3k3eiUsVjP39ft2C6ubUPa0r5pe7Yf3g5UrGlcfvdyYoNiuTT2Uu696F7bCLCIox3KP8TNc25mxo0zuOvCuxwWh7UMkL+nPwDPX/E8f/n2L2d0D+uMHxFxXnkleVz/yfU80vMRlb2rAyW3Ii7qyhZXMunnSUQGRjo6FHEyfWL64O/pT4vgFjWuwRv06SAsayzsnb6XtuvaEu0Vzee9P+dAkwMVHQy464K7yCvJIzowmgsjL7R7sjn1+qncO+9e1t63lmCfYFv7r3f9atfnEbEXR9e5zS+t+LbJ36siue3fqv8Z36N90/Z2jakhmabpRFt7idSfvdl7+XXfr+w8vFPJbR0ouRVxUda6hX6efqfpKecjN8MNi2nhy21fVju3I2UHcz6bQ4BPANOvnM7ci+eS75vPtBum0SO6Bx3DOtZ7uZ1+cf1I/FtivT6HiD04S51b68it9Xf+sj+XVetz74X3nvIe1nX4IuK8rD/rfWP7OjgS16TkVsRFWddaqc6tnGjeznnkluSy7dA2roi7AjeLG9O9phPycwgz755JemE6Lee2ZH3gej5e/DHzhs/jhrY3ODpsEafm6Dq33SK7UfhUoe2Lp4nLJlbrsy5tHT2n92T1vattbbv/tpvWb7cGKmpfX9niyoYJ2M6c5UsGkfpmTW4f7vGwgyNxTUpuRRxkQeICyixlDGo3qE7XW3eo7RfXz55hyTnAOn1x1d5VdPq5Ez8s+QGfZB982/rySd9P8In1AaAznRnde7QjQxVxes5S59YwDHw8fGzHNU2T3nhwY5Vj0zTZk73HdlxuKa+/AEXELmIaxTDxkok0D27u6FBckpujAxA5X/1n1X94ZcUrdb7e3XAHNC1ZqrOYFqIzo3n/P+9zwwc34BngSYc5HeixrYctsRWR2gnzD2P5XcsdPrthXeo6Hl7wMOl56QDMuaV6LWiAIO9jtc9NTAbMHmA7LrOU1W+Q9UiJuZzrHl/yOMZzBnd/dzff7PiGaz66xtEhuSSN3Io4SE3rpc7E0eKK2qUbD26kZeOW9ghJXFxpdikF2wowA03SgtP4o/kfrO+9nq/++5XqW4rUkbeHt1OsfduasZW317zNuF7jAOgd07vGftb3Bqg+lbrcdN0E0dEbeonUt9dWvgbA8uTleLl7EeAV4OCIXJNGbkVclLWkw4a0DQ6ORBytOK2YPY/vISE2gS1DtzAtYRoWdwsv3PwCX7z9hRJbkbNQUFrArI2z2JW5y6Fx2HZLriwFVBsnJoSuPHJ7NmueNx3cxNS1U+0YjUj9KikvIbswG4tpcXQoLkfJrYiIiypKLmLXmF0ktEhg/3/2EzIohM6LOrPlyBYAplw3xVY2RETqJrswm798+xd+SfrFoXFYNw88/mf6+SueP+U1JyaEXcK72D8wF3DBexfw0PyHHL4pmMipfDz04yrHJqZqU9eBklsRF3Vdm+sAiAiIcHAk0tBMS8UHtMK9haTNSCNidAQ9dvagwycduGLNFWQVZtEnpg8PXfyQgyMVEXtJzEok2Ce4ysht96ju1fodX8v2xJFb6xKWQ/mHOFp0FFdij2nJhWWFdohExP6SjyZXOX76sqcBOFxw2Na2PHm51p7XgpJbEQfpGt6VYJ/gOl8f7h8OVKwHk/PD0YSjbB68md3jKnbKDu4XTO/9vWn3Xjv8WvtRZilj26FtAHSPrP6hV0TqztFrPtPz0+kR3aNKSZwDOQeq9SspL7E9djPcmOgRxAizYouVrMIsAC6adhEjvh5RzxE7D+su07nFuQ6ORE6nuKyYlJwUnvv5OVJzUx0dToNZuX8ld3x9BzMHzyR5XDI3t7+ZcT3H2b7MWp68nEv/dynjFo5zcKTOTxtKiThIl/AuBHoH1vl6a3mHvJI8e4UkTsg0TbKXZpP8UjJHfjqCRxMPgvpW7IZqGAZeYV4A/LDrB1YfWE3+xHxyi3MJ8gk61W1FpJYcXV81syCTpXuXMvf2udXWzN7e6Xb+tuBvVUYk92TvwTRNDMPAw82DF0pNwI9PyOGHXT8wqusoAr0Cz2jtrjPwcveq87UFEwsc/v9Ramf84vH8d+1/Afh538/8NPonB0fUMKzTj/u36k9kYCQxQTG8MeANXl7+Mq+seIXRXSvK9v137X95+7q3HRmq01NyK+IgA1sPPKuNfqx1bh1dnkLqV9JzSex7bh9eUV60+k8rIu+PxCOg+q/u4V8NJ7ckl7YhbRnZZaQDIhWR+jB+yXhmbpzJd7u+Y8aNM6qcC/AK4PX+rzN2/tgq7eVmOR6GB3kleRy/36o1ObaYFtyM82fynhJb12FNbAH2ZO05Rc9zizW5PX5G3xNLn7DtoDx5zWRbe7mlHHc394YN0IWcP7/ZRJzMmwlvMu33aXW+3qDizfpsvs0W52MptZA2M428TRUj8uEjwmk7rS299vYi5rGYGhPbg3kHyS3JpV1IO3pG92zokEXOaaF+oWx6cBM3t7+5wZ/7cMFhZm6cCcAnmz+pcWq0r4cvTXybVGmzrstbtHtR1fbKUkA7M3fy+dbP6yHi+lNcVlyn60rLS/F63gvjOYNe03vx8vKX7RyZ2Et2YXaV44N5BzmQc6DO/+9dyZGiI3i6edqm0JeUl9gSW4AQ3xDbY4/nPcjIz2jwGF2FklsRB1mbupYFuxfU+XprLcPVKavtFZI4UHlBOSlvp7C69Wp23rWTgx8eBMCvrR9R90Xh5n3yX9fvrnsXgE9u/oQ2IW0aJF6R84WnuyddwrsQ4hdy+s52dvxmMgDe7tX3WLjrwrvIfDyzSps1iT1xp1VXLgVU15IoB3IPUGopBWD1gdU8uexJe4YldpSYlQjARzd9xPuD3qfUUkqzN5sx/KvhDo6s/h0tOkqwT7BtloGXuxf/HXhsFDuzMLPKF2zhr4fz277ftDStBkpuRVyU9RfaH+l/ODgSOVspk1NIiEtg98O78Y7xpvMPnWn1eqtaX3+k6AgtG7fkgogL6jFKkfNTfkk+U9ZMYUvGlgZ/7md/frbKcW2n11oTweyiqiNhPyW57vrFum7ote/IvirHNe0wLc5hQ9oGAHpG9+SGtjfYSld9s+Mb7vr2Ln5J+oWDeQcdGWK9+feV/2be8HlV2sb2GIs5yWTfuH28P+h9Prn5E1675tho7mUzL+Omz29q6FCdnpJbEREHKDlUYqu5WHKwhMDugVzw6wVctPwiQq4LOaM1Yv937f+xfez282oNnUhDyS3J5a8L/sry5OUN/tzWqcPmJBNzUu2TO+u05MyCqiO61k2kekb3ZECrAXaKsmHUtUbtiSVW1qWus+0afSrrUtdx33f31bgjtdjf5vTNPPjDg7Rs3JLWTVoTERDBz6N/tp2fuXEml8+6nFeWv+K4IOvJL0m/MG7ROC6OvrjG87FBsdx70b14uXsxvs94to/dzoS+EwBYundprf49n0/0SUjERQ1tPxSAMP8wB0ciZ6JoXxGJf0skITaBrPkVb0gt/t2CLvO7EHzpmZeGspa20NprkfpV1+SqrpKOJAEw9uKxp+5YqVtkN9vjUd+MAqpPa07LSwMqSgTVdZqvq8kszKzWVlpeetrrdmftZvqG6eSWqHxQfSspL6HLuxWjtBP6TrB9udvYtzF5T+Yx9fqptr7r0tYB8I/F/2Do50Or/Rt3RZfPupzZf8xma8bWWvWPbxrPR398ZDs+m/1bzkVKbkUc5JqW19DIu1Gdr7duLuDp7mmvkKQe5W/PZ/vo7axuvZrUd1MJGxGGX7wfAIZb3XbyLC4rptmbzXhkwSP2DFVEjmPdvK8h69yapkmLt1oAMLjd4FpdM2PwsZ2U5+2qmN54R5c7qvSx1sBdlbKKXZm77BFqg6nrzJSYRjEMbD3Qdvz5LZ8THhB+2utSclIAyCnOqdPzSu2N/eHYFziD2g2qcs7fy58h8UOIC46ja3hXlicvZ8LSCby+6nW+2fEN3+74tqHDtavjv2Rq2bhlra9bdc8qbu1wKwBPLnuSgtICisqK7B6fK1JyK+IgncI60Tmsc52v33ZoG1CxHkycm1lu8sfAPzj0xSGixkbRc29P4j+Ix7dV3UtBQcWmZDnFOVzZ4ko7RSoiJ2roMjKmafLe7++x4I4F3N7xdq5ueXWtrmsX0q7afY4fbe4W2c2W3EYGRNK/VX/7Bd0A6lo67+YONzP/jvk80O0BADzdPG0zXk7l97TfAUjMTKzT80rtTd8w3fa4pi/9IwIi+PORP3nq0qcAeGXFsanJ9867t/4DrEfWXY+fvuxp/L1qX3s6JiiGiZdOBKBLeBf8X/TH9wVfnljyBBn5GZimyUu/vcTOwzvrJW5npuRWxEHaNGnDo70erfP11jq3wzoNs1dIYiemaZL9Yzbbhm/DUmzBcDfo8GkHeu3rRZv/a4NPjI9dnufXfb8CcEnsJXa5n4hUZ53yP3b+WIznDEZ9M6pepyiv3L+SMT+MIdArkM9u+azWybW3hzdTrptiO278SmOu/PDYF1+h/qG25Na6m/K5asLSCUxfP71K24aDFZsVDZ0ztNq5UznZf3+LaWHJniUNPl39XNSmScUu/82DmuPn6XfSfrd2vJU7OlfMRmjftD3Ng5oD8J+V/3HZ6ckl5SXc2O7GWn+JdbwLIi4g6ZEkAryOVbN+deWrdJvWjZScFCb+OJH4KfHVSiyd65TcijjI5DWTmbNtTp2vt77hqjh97cxPnF9t10x7My0mh789zPre69l01Sayf8qmYGcBAEG9g/AKtd+62HJLOXN3zKVzWGeHlCgROV8E+wSz9aGttpk2s/+YXa81Ji/5X8WXVSeW8akNT7djy1Ss5eKsuoZ3pWt4V6BitOj99e+fRZQNr7azlJ7/5XleWfEK9827j3fXvct9391Hnw/68MWtX9hKqzy2+DGM54xTjuBayy5Zp6Wf6LUVr9F/dn8W7VlU43mpvUUjF7F45GK2jd122r6zh84m5dEUNjywgYUjF/J4n8cZv2Q8oa+Fcij/UANEa1+xQbF8O+xbLmt+WZ2ubx7cnBk3zmDLmC22wY6UnBRm/zHb1mfwZ4NJy02zS7yuQMmtiIPsOLyDOVvrntxa1wH9kvSLvUI6p83+YzbvrH2n3u5fkl7C2i5r2TJkC6UZpbSZ2oZeSb0I6BJw+ovr4Nud37I2dS0P93y4Xu4vIse0b9KeWX1n4VXqBSZE/CcC4zmDB+ZVTHXNKsyy2wZNPh4VMzvah7Y/42utU2mt7rrgLtvjl69+mWmDXHfjmVPV6N2QtgHjOYPbv7ydZ35+xtY+5ocxTN8wnebBzYkNimVsj7EEegXazm8/vP2k97T+bq1pJHHZ3mVnVadeqmrRuAXXtLrmlKO2x4tuFI23hzfxTeO5teOttva0vDQKSgsoKS9hztY5tlH10vJS22w3Z2OP3xvtmrajY1hHPr35U7Y+VLEp1cQfJ9p2m/4t+Tei3oiqcSO1nOIcnvnpmXNqva6HowMQkbopLC0Ejq29lVNblbIK91j3Km2FpYVszthMj+geAGQXZrM5YzOXxl7K5ozNtAtph7eH90nvWV5UTt6GPIJ6B+EZ5klA1wCaP9mc0NtDcfM49XeHqbmpRAVG1fn19G/Vn4V3LNR6W5EGUJxazNGuR1nEIvCEI55HyPfOZ9bls4jYGUF5Wjlvbn6Tnu174tHIA/cgdzyCPAi+Ihi/1n6UF5RTlFyER5AHHkEeuPm6nXTWzZsD3mRX5q4z2lzGakCrAbz3+3u0btKadiHteOf6d2DDV7bzTyx5osoURldyqg29Lpp2EYDtC+NXrn6F11e+zqGCipG8iZdMtPXNeTKHS2Zcwor9K0hISaBZo2ZEBUZhMS3kFOeQkZ9B25C2tlHwUsuxhMA0TQzD4OqPrq7S5mpM02TZn8tIz0sn1D/U4euvZ2yYQaewTrb34jNxYcSFjOk+hqnrplJmKcP/xWPrVv2G++FuuPPBhg/4avtX3HPhPUy/sfqU9HJLOWtT13Jx1MW4u7lXO1+fbvr8JnKKc/hptH1qUHcI7cCkfpMY0GoAvWN6Y04yCXwpkLySPK79+FpaBLegU1gnxvUaR1FZETd9fhM//vkjncI6cVvH2+wSg6MpuRVxcQ25g6cr+XLblzQPas7F0Rfz9uq3STqSRGOfxizcvZBLYi9hd9ZuJv08ie92fsejvR4lszCTDzd9WOUeE/pO4KWrX2J58nIGfzaYOzrfweSBkynLKSP13VT2v7EfS76FXvt74RnsSYePO9Qqtu2HttPhnQ58P/x7rm97/Rm/tvS8dJr4NmFAa9eqUyniqjwaedDmnTaUHS2j/Gg5UUej2LBrA9n+2aTnpxNXFIfHGg8OrjlIeU451l/L7We3x6+1H7nrctnYb6PtfoaHgXuQOx0+7kCTAU3IWZvDvhf2cdA4iIfFg792/ivJm5MJGxaGTzMfSjJKKNxbaEuOPdf9E7f102DIVIi7BPIyoFl3bmp/E5ZnLDUmzlPWTOHVla8yoNUABrQaUKdpz85ia8ZWOoZ1tB37ePhUGXl6rPdjPN73cdJy0ziQe4DO4VU3b3zxqhfpN7Mfjyx8hEcWPoKnm2eVJDbpkSRbaZrOYZ15bcVrJB1J4p111Wf/FJQW2Pvl1bvPtnzGiK9H2I7PpIayvZmmyZgfxjCu57g6Jbfubu5MuW4KL171Ikv2LKlybtCnVXdePrFWtcW00H1ad9t67BevfJHRF4w+qy+ez4RpmmzJ2HJWm4vW5NnLn25BtqEAACAASURBVK1ynDE+A78X/fjxzx/pFtmNDzZ8wCebP6FF4xb8+OePAA32mhuCklsRFzW883Ce+fkZQv1CHR2KQ2UXZjN0zlAe6fkIQ+KHABVvGLd+UTFV6fNbPufhhRXTyzYc3MDAjwdWu8ebCW9ycVT14ukfbPiAgW0G0m9mPwBm/TyLh359iMPvHqbsSBmNr2lMzJMx5HvnE0xFjdp5O+fRs1nPU9Yftp7bfnh7nZLbh+Y/xM9JP7Nv3D6XHYURcSUeQR5Ej4mu0tbGbMNjbz4GuZAUlsTwR4cD8McDf9DGpw0H9h/ACKtIMv3a+dH+4/aUHS2zJchlR8vwiq5Yh1+eW07R3iIykzOJKIogeV4ymBDUNwifZj5kzs9k513Hdj29fFLl9OK5Y2xtG37+2Zb8egRVjB7H/D0G6ypc/1X+dNjfgfTcdNo0b0MeebaRSFdw/Ajp9Z9cT9K4JAA+2vQR/8/eeYZHUXUB+J3d9EJ6gyQEQi8JvUrvRUAUpAmCgIIINqqIiogIKAoiTT5BBBRpgvTee4dQE0oSCOm9bvl+THaSTe/NeZ8nz87cuffO2c3uzJx72vzO87E1tcXT1hNvJ28MFOLjrYulCy6WLpnmal+1PZo5GhRzRQ+b9IqtuaE5Hj95SPt1l9fNtIj8Y48f+fDAhwAkqBKK5P2VJH4Rfnr7/lH+uFm5lYosofGhJKuTc7xn5oYgCFibWDOo/iC09bWceXaGvQ/3Mv/0fL1+98PuI3wlcO3da3g5eaGcq2+lnXV0FrOOzmLDaxsY4TVC71hCSgKGSkPpu1VYRu0cxUHfgwTFBjG97fQimTM7TA1Nmd1uNomqROzM7Ljy4gqXnl+SyoHtHrq7QiWmlJXbEmDcrnFUMq7E9z2+L21RZMoQwxsOZ8e9HQUeb2VsBZCtC82xx8eobFmZ2va1szxeUQhLCOP4k+N4OXoxoM4AwhPC2eqzVTr+5tY3AXAwc5Bc1HT82ONH6jnUY+nFpazuu5obL28QEhdCd8/uDNwykJsvb4qKrRYQwCHageernmPb35bL/S8TXTua40+Os3vhbmJnxjLt0DR+ufwLh946REB0APdC7/F63ddpXqU5KeoU1lxdQ99afXGr5IaLhQu3g2/n+/1uubOF7Xe3817T92TFVkamFBEEgXX919H9D32XTq9VXnr7B0ccpJtnN5yGZV9b1aazDc1vNqfFV6LlyneSL+6G7ihMReXLtrstDfc0lJRjgrKYRAOJTxLTlOdoFVUmpSnkHh96sJzlekPUo9QYVDLg6YKnhPwVIrlT6/5q/FQDQSEQdSaKRP9EDKzTjhlYG2BcOfuwjaImvVLxNOopscmxfHPyGxacWcDQBkPZ9PqmfM0nCAJfdfyKZReXsXfYXq4HXWek90iMlEa0X9eeCwEXSNGkSIrtqdGn2OazjWUXlzGw7kDGNhlLVFKUVHO+PHH86XGczJ3oWaMn62+s52H4w1JTbk88FfOG1LGvU2RztnVvSy27WpwLOMf/+v8PJ3MnlAolbda24cqLKzRf05wvO3ypN2ZCswmceHoCnxAf3trxFsZKYwbVH8SeB3sIjAnk3X/fpXfN3uwZtqfQ8mm0Gj1PsWENh+XQu2j4uvPX0vartV7lh3M/8G1XsVRQu6rtiv38JYms3JYAF59fpJp1tdIWQ6aMUde+Lk9dCp6998bLGwBSaYeM6EpApHc3uhd6j7rL63LjvRt4OXllOS4rktXJXAy8WCZX9nRZSy89vwSA90pvAqIDODjiIHOOz+F8wHm2Dd7GwLoDpTGJqkRC40NxreQKQDfPbgB6K/ynR58myieKte+tJTg2mGH7htFrYy+GfDiEMOswNE81kO7fZ/FtmqJZy64W3TaIc3535jvUc9Qc9D3Ixwc+5v29acXqLwReyNd7VWlUkrL+lvdb+RorIyNT9HTz7IZmjoZH4Y844HuAD/Z9kKnPyJ0jiUuOI2J6RI7xfLpyHTPazqC6nX68rXFlY31F8svM4xufbKy3nzEWtPGZxszZNYdbj25hlWxFD6cedLAQvVKMHI0wdjVGFaWSFGRtipaay8QSLc9XPuflHy/15jOwNeCVMPGecG/0PSKPR+opxybVTaj5ozg+eGswqjCV3nFDR0PMaphJsuZmQc64mPcs6hkLziwAoLVr6xzHZsecDnOY00FMQNW8Spr3zrFRx1Br1HRc35Gg2CAujbuEvZk9bdza8HXnryVZzI3MiUyMZMn5JUxrOw2FULR5WhNVicSnxGNrapvvsbde3iI2OZbWbvqfjUqj4nzAeUZ5j2Jpr6U4mjvS5fcuANx7/16OC+JH/I7g7eyNvZl9vuXJDl2G46aVmxbZnCCWvjo66qhe26G3DmG70BaVRoWblRvHRx2nuk11XCu5St+/8bvHs+bqGnxCfLD9zpaIxLQyOnsf7uXy88s0q9ysULLpEoICdK3etcQXqus71mdt/7UAhbKYl1WKPVuyIAhPBEG4JQjCdUEQLqe22QqCcEgQhIeprzap7YIgCEsFQXgkCMJNQRCaFLd8JcHNlzf55/4/pS1GmefrE19z8+XN0hajxNCiZUrLKQUer3Mnyeg6kxPbfMTEIn/e/jNf51p0ZhHtfmvHqaen8jWuJNA9wAmCQLI6mYDoAEC8sZ175xzaL7R6ii2I8Vk6xTYrYq7G4DPYh+sNr9P8cnPGdRyHl5MXPu/7YOZuxux2szON0SV/WdFnBe5W7no166bsm8Jfd/7i9XqvS22mBqZZZsyOTorGeJ6x9L8CMdOj8JXAgtMLeK3OaygERYEf5mRkZIoWQRCoaVeTSS0mZRm7GBQbRExyDHEpOZey6bmxJ0CBQhWykyu9wmjVxor6g+pzrOExdjbdye3XbiMoxOMuY1xouLshjU82pvmN5rR+0po2gW2ksZ5LPGl+pzmNzzam4b6G1PuznqT4Alg0tcCqnRUmVU1AgCT/JOLvpsWiBiwJ4MF7D7g79C63et/iWttr3B2alqn4aournLY5zTmPc1zyvsS19tfwmym6zi46s4il45ey88OdUv+WD1qy7I9l2JraIiAwts5YtJqiixs1UBhgbGDMuXfO8XjKY0mZUwgKPUVk8dnF2Hxnw8wjM9n7cG+RnV9Hr429sFtoR0JKAiqNisN+h/M0btf9XXit9GLttbWZjl17cY3Y5FjaV22PQlDoxWf22tiLRFUiex/uJSpRv5TU+YDzdN3QlRHbR7Dj7o4iS6SlUx5tTGyKZL6csDG14cmUJ/zW/zeGNxxOB48OuFm56f1OVr+6GtXnKvrW6ivJ9kGLtEWr5muaF/q96xayFnZdyM43d+bSWya/lJTltpNWq01fXXkGcESr1S4QBGFG6v50oBdQM/WvJbAi9bVCkKhKlFL8y+iTrE5mzvE5LDy7kJiZ2dedK2l0FzC1Vl1kcRY6VlxeQe8avXmj3htFOq+Oho4NsTHVv1kUNPnUi1ixPtq5gHNlzn1FrVVL279d+w0AO1O7AidoCFwZyMMJD1FaKXGf6Y7rFFeMHMW4OGsTaynO66tOX6HRargbchd7M3ucLJz0rA8HRhwgMjGSY4+PMf3wdHwjfNHM0TDKexTt3NsRnhDOuN3jaFkl7RJ3+fllmq8RrQfjdo/j9LPTRCdFS6v2nx/7HPUcdZFbB2RkZIqOoE+CaL6mOf7R/nrtiapEopOis1xYS1GncDHwIk1dmharh0wN2xrS9vJLy/m59895Gmdkb4SRffZ1ul0nZb9YCOB9yBtVpEov5lgwTlMoHIc5kuiXKB1XRam4/uQ6nl95AvDXX39hE20DX4j9F2xawLEbxwi5FYJCUHDK+hTqaDXKSkrJddrxTUeqzqoKwMPJD1FaKKVYZAMrA8wbmmPRwAKtRktSYJJ4zEIpKfx5Yc6xtLJDxWF9O/7kOABv//M29R3q88XxLzj81mGWX1pOeEI4x98+nmnMb9d+Y8yuMQC80/gdJu2dxOSWk6luU51d93cxoM4AkmcnS/cRM0Mzzow5Q99NfWnk3Ih2v7Xj8vPLgOj5pdVq2f9oP7039QbggO8BDvge4PaE23pJvQrKzFdmMrnl5BwrExQlVa2r8najt3Pso1QoaVq5KbNemcUP539gUbdFjGsyjv5/9udx5GOmH57Owm4LCyyDLplbTbuamBuZ59JbJr+Ulltyf6Bj6vZ64Diictsf+F0rahTnBUGwFgTBRavVVojKw9YLrEmcXXHqSBUlSaokQCzSfiPoBrXsamFqaFrKUsHJpyfpuL4jAA8/eKj3YFBYnsc859drv7Km35oCjdcVnz/w6ECWLqr2ZvZ6q5EvY19KK6NdqnXhwKMDdKneBbVGnetNRRff2616txz7RSRE0O63dkxtM5VRjUbl6/0UFN1356z/WcwNzXm36bss6rYoz+n8tVot4XvDMXQwpFKLSti/ao8qUkWVCVUwsMr5EqkQFHo39/Sft0JQYGtqS59afXjj7zek47qSC1UMq7B76G5mHZnFwrMLWdZrmZ5LY0RiBD9e+BGAvcP2svjcYgBik2OpZFwpT+9NRkam5HGycOL77t8zeKt+WQ2nxWLMbW272tyZeEfvGqXz7upSrUuxytbAsYHeflRiFFYmVsV6TgClmRKlmTLbGF23j9LiPbVaLXEpcTT5Ns15782P3sQkxYQERAX7+brnvNfwPUlB85jjgSpCpaccKy3Fz1eTrOHlppeoo9RoVWkLvG7T3bBYYIEqSsV59/Nio4CoIFsZ4D7TnSrvVSE5NJlHUx7pJeoysDLAuqM1lYwroU5QUyW8Cs1oJp03PwpyTvSr3Y9d93dx/IkYIwtwMfAi14KuYWqQ9TOSzouohm0NNt7ayPJLy1l+aTnrB6xn1M5R/NL7FyY0n6A3po1bG8Knh4sfwVdpsu+6v4sbQTf0agfr2HFvB0nqJJq4FM7JUhCEMps/4psu3/BNl28AaOjUkHFNxjHr6Cw6VO3AledXUGvVxCTF0KV6/n63UUmiVdzaxLrIZZYpGeVWCxwUBEELrNJqtasBJ53CqtVqXwiCoHP4rgKkX+oMSG0rt8pt+lT7SeokXsS8yDJz338d3U3exdKFRqsa8Wb9N/nzjfy5zhaUwOhAnC2cMylDxx4fk+JWAWouq4m7lTsr+qyga/Wu+Ib78izqGUGxQSWmyKVHF2urc09Oz7envuXYk2McHXlU6uv8vTO9avTi3DvnaL1WdGk1NzSXXOXebvQ209pMo65DXWkelUaFgcKASsaVaFmlJY1dGrPwzEL8o/xZ1ntZpvMaKAwIjQ/l12u/lpxyq06Stg/5HcJnog+Wxpa5jtOoNIT8HcKzBc+IuxmH4zBH6m2sh3EVY6rOqFpk8uXkraFUKFl4Vlz9Ta/Y7h66W6+EgZHSCM0cDRqtpsRr8MnIyOSfQfUHEVY9DLuFmZMN3Q+7T81lNfGbIrrd/nzxZ+n3/0XHL4pVLkdzR1b0WcGEPaJyM//UfL7r9l2xnGvH3R108+yWb8Xlb5+/pdwCAF5OXtx8eRNLa0uIE6/3w0bpJ+Bx+zj7ZEgKIwWvhL6CVqtFk6CRlF+DSuIjsMJYQa01taQM1ro/Y1dREVfHqIm+EC0ej1RJCnKtVbX4qNVH/G/D/1i1ehWXV4jWTgRQWiqp8786OLzuQOzNWPxm+ukrx9YGOA5yxNTTlOSQZOLvx+tnuk5VkGvZ1gJEhbWWnbg96+gsnC2c8XLyQqPVsP/RfhacXkAPzx4ceXyEjh4dCfw4EBcLFy4GXmT5JTGJ2IrLKwAx2/7vN3/n3Dvnsvy84mfFc8D3ANvubqP/n/0B0WU4bFoY0UnRWH8nKmSfH/uc7899T/CnwRgqDbOcKy8svbAUtUbNR60/KvAcJcX0V6YzwmsEPTf2xCfER2q/OPYiB30PMqvdrDxlH+/o0ZHk2cnlJlN5eaMklNu2Wq32eaoCe0gQhHs59M3qv5zJj1IQhPHAeAB3d/eikbKYGL97PAC3J9xm1tFZVP6hcqnWEyurmBma8eKTF0QkRFDvl3qZapEVF7de3sJrpReLui3i49YfE5ccx/2w+wzZOgTfCF+9vn+98Rdvbn2TeSfncSnwEl+e+FI61si5EaP/Gc3e4XtxtnAuEdl1ZHQ1TlGnMOuoWLB++PbhOJo74mkrunbte7SPp1FpWZCsTawl5Xbd9XWsu76OoE+CeGfXOzyNesrt4Nv4TPThw1YfMrXtVA48OsD0w2LK+q86fYWhwpAkdRKB0YE8DH/IHzf/QCEo8AnxKTE3/M7VOkur2y2rtJQeAHLi5eaXPJ79mES/RMzqmlFnfR0ch5ZOUoUzY84wcsdIfCN8cTR3pIlLE/rW6otmjoa7oXepZl1N8mJQCrJiKyNTXrA1tdUrN5Oex5GPAWi4oqGUNd3BzAEzQ7OCn1Cjhjwsfr3X7D3+ffAvex7uKVCiorzwOOIxA7cMZGWflbzb7N08jwuJC5EU2zWvrqGmbU06eHTAN9xXvI99WXArsyAIaRZklzQLstJMSeWx2df4NK1mSqtHrQD0FGSlhZJpFtOYUHMC/SL6YZ5oTge7DgxyG4QqSoVJdfH+p45XkxwkKrA6BVqbosWyqSWmnqZEHo/EZ7CP/kkFMQHY4nOLaXW/FW+ve5sIwwhmG88m1iSWOOM4trbeSpPIJoT6hOIW6sZfp/4izjiO4ORgHLzFEoEtXVui/ULLYb/D1LGvw3env+PnSz9zISD7ZIamhqYMqDOAAXUG8DDsIRcCLzCl5RQEQcDKxAoHMwdaubbiZdxLLgZepM7yOvhO9s12vtz4685fGCmNyoVyqxAUuFm50admHz3lduzusdx8eZNXa7+a52SdhVkQkMmZYldutVrt89TXYEEQdgAtgJc6d2NBEFyA4NTuAUD65TdX4HkWc64GVgM0a9asTGuKf/v8DYgZXQ0VhtS2q81hv8N0qdZFXrFJh1qjxsLIQnIxLU4uBl7k3wf/MqbxGKlI+457O1hwegFhCWGZ+n/T+RtmvjITQRBYeXklx54c00uZv7bfWhqtagSA1wovFndfzDn/c6zouwK/CD88rD2KJUZyTOMxzDk+J1MZAt1DE4ixsi9iX0iZlUFU0uOS46htX5vopGhG/zOae6H3eB4j/tT6bOrDlRdXpP71fqkHwOx2s5l3ap7UnpVFIj0D/xrI3uFFn2AjPTeCbnDq2SlMDEz4oMUHLO21NNu+qlgVCmMFCkMFSYFJGNoZ4rnYE/v+9kXmQlYQ2ri14fbE24QnhONg5iB9VwRBoJ5DvVKTS0ZGpvAIgkDS7CT6/9mf/Y/26x1z/cGVwJhAaf/qu1cLd7Kv7eEjH6iUs3eYRquRarOmv18UJUGxYq0id6v8GSDSyzO2yVhpW7dAW9qkV5B1VHKqRP1R9fnl8i+4NHahWj/96hhWraxodiUtu65Wq0WTqEEwEO871h2s8TropVf/WBWlwqSqCTVsa9DAuQFxQhw2sTa4hrlinmiOeZI5e5ru4cbLGwy5O4R3D+svIJwZf4bWga0xrmxMwE8BVFpTiWCrYMZZjWOU2SiUVkrUiWqUJkqizkWR4JugZzk2b2COoBQ4P/Z8ps/A/yN/DJWG3A25S4MVDfCL8CvwYrZGq+Gs/1lGeo/M99jSZMYrM1h0dhEAAoKUDHX5xeVYm1hja2pLfEo8fWr1oUWVFpnGLzqziIjECOZ3mZ/pmEzhKVblVhAEc0Ch1WpjUre7A3OBXcAoYEHqqy6V8C5gkiAIfyImkooqz/G214OuS9txKXFsuytmP+22oRt7hu2hd83epSVameNe6D0arGgg1lwbsL7QMRzZkaJOoe+mvoTEh/D1SbHmV8sqLalsWZmz/mcBeLfpu3St3pUrz68wqcUkqlRKqxPY2rU1x54cw9XSleBPg7ny4go1bdMyRjZybsSonaI7rpHSiKUXRWVr/YD1PI54zNgmY6X5Pm39qRRTWRB0K/zpF0m0Wi33Qu+x5tU1tHVrKymmYxuP5ceeP2ZKXGBtYs2RkUcAuBBwgVZrW2FvZs+CLguYcWQG7dzbceqZmCE5p2RUnTw60c69HXNPzpXaOnp0xGGRA6HxoRwYcQBrE2u6/t6VRd0WERwXzJRWUwoVOxqfEi8tKkRMj5DigjOSEpZCwLIAApcGUuOnGji/5Yzrh664feJWYgtMZoZmTGg2IdvjJgYmVLbM3nIgIyNTfjFSGtGnZp9Mym16xXZpz6U5ZnCX0Grh5l/ZHNNAXEiuyu0/9/7h6GMxZGXVlVVMaDaBw36HGd14dJFZcnXKbX4UHrVGTctfxQR7PhN9culdtljaaynjm45n8bnF7Hu4j141e5GiTmHd9XVEJkYyofkEyT1bEASUpmnKsZGjEbbdsv7c1Ro1Se2S+NLhS2KSxTwb45uMZ/XV1aCFpx8+JfyNcIb8NIR5zeYRExZDT8eeqKJUGNqJlkFDJ0PMapmhilKRHJyMOkpNUnQSitXiQmrQ+iBerNJ/1G6f1B5BmfX9UZejo75jfZ5//BwDhYH0fx61cxQhcSF5Xtg+8+wMANWtq+fSs2xhY2LDq7Ve5XbwbYwNjLkXKjqlrr66Wq/f3JNz+ajVR4xpPEaKd7/y/ArTDk+jtl1tWbktJorbcusE7Eh9gDQANmm12v2CIFwCtgiC8A7wDBiU2n8v0Bt4BMQDo4tZvmLF28mbuR3nMrbJ2EwX+PiU+GxG/TfRxU3uf7SffcP3Ffn82+9u50nkE049O0VIfIjUPrj+YDa/vpnfb/zO8IbD+eL4F8zrPA97M/sssxjPbDeTxi6Neb3u6wiCQM8aYumGlM9TUGlUGCuN2XFvB69veV1SbAFJ4f3yxJcs7bmUQ36H2P1gN1WtCh7bqavrmp79j/bT/8/+7Bu+j7oOdfPlAq9zXwJxNXVIgyFUta7K3BNzCY4LZl7neXzR4Qvuhd7j65NfM6/zPHzDfen/Z39+7fcr1W2qM+OVGcQmx2KkNGLF5RWExotJ0kfuGMnLOLFG4nt73gMgPCGcJT2XFPj977wnps8fXH9wlkkZkgKT8P/Bn+ernqOJ02DX3w7zBqJyrzAo2WzDR0ceLXF3dRkZmbLDpBaTmNRiEmHxYdgv0q8Rurz3ciY2n5i3iR4cgB05uPlqNblOkfFa9NaOt7gVfIu6DnXpXbM30w5Nk6xSwxoOY8NrGwiMDsT9R3caOjbk5oTcS/bprvcD/hpA1IyobPsdeHSARs6N2HFvh15sbvrcD+UBpUJJPYd6bL61GQ8rD6rZVOPjAx+z75H4PHM/7D6/9vs13/PGJMdgaWRJ9MxoTjw5QbI6mc7VOrOs9zIiEyNxNHfE3cqde6uzj/hzGuKE0xCnbI9XX1Adt4/d0jJZR6tRGOXtHuli6YJ/lD/jd4/H3sye32/8DkCtZbW48d4N7ofdp4Fjg2yrTVwMvAjAuKbj8nS+soIgCOwaukvc/irnRfIl55ew5PwSVvddzU8XfuJOyB2AMpE0taJSrMqtVqv1A7yzaA8DMqUWS82S/H5xylSSCILA5x0+B0SL2qetP2XXg108CHsgZbqVEUlUpWWR9lrhxbS20/JVvzU74lPiCYkL4fUtYn3RbtW70b92f77u9DWfH/ucjQM3ohAUUlr4AXUG5DifhZFFlkqvgcJAunj3q92P/rX7M67JODpV68TUg1P55fIvUt8vjn8h1U5Lv3KfX+6H3gfgLa+0TMm/XvsVY6VxoUtJKAQFVa1FxVtX4B7EGJGGTg3ZMkiszVrLrhbJnydLx00NTaULdkePjgBMbTOVic0n4rnUE026B6+lF5fiYulCcFwwi7otypcV1T/Kn+HbhwPwx2t/ZNnnVr9bxN6IxWmok5gVs0HpZWPcdncb14Ouc/Ctg6Umg4yMTOljZ2ZHd8/uHPQVrwWH3jqUvwzJsS9zPp4H5TZ9WM2FsRcYtk1MztRnU+b6uptubUIpKJnUYhIAt4JvIXwlcGzUMekanxU6y61ao862j1qjpufGnjhbOEv9QbRMlkcMlYY4WTjhE+pD3eX6yvnaa2sLptwmxUhKfwePDlK7EiWO5kWTJ8LQ2hBD64LHfwZEB7Dmqn7Vh4fhDzGbnxY/7jvZF3cr90xKrpmhGf1r9y/XnkvrB6zn5NOTNHVpysS94iJVVauqevlNAMb/q/+93jVkV4nJ+F+jtEoB/ecQBIFF3Rcxv8t8HoQ9yHccSkUnfaztreBbTD88vdDK7e3g2zRc0ZDF3RZLbRsHbsTBXEy0sHNI8RTONlAY6M39c++fmf7KdBzMHDjoe5BXa7/K8ovLmbx/Mu5W7tKq39AGQ/lj4B95js/N6CZ8xO8I2+9u5836b5aJtPqtXFvx9MOnuFZyRSEoCP40mErGlTBUGrLswjIm758sJacaVG8QLV1zL2mdqEqk8/rOmBuZU8e+DiMajpCSMsTeiCXgxwBq/FQDg0oG1PqlFoaOhphWK/3V0cVnFxe4xrCMjEzF4o26b0jKbdfqXfM3WJVLOUFt7teZ9O7PNWxrZEqemJENNzew4eYGvbZO6zuxbfA2BtYdmOWY1q6tUQpK4lLiiEiIyFRzHZDifqMS0yy7ueVOKOtEJ0Wz/e52vbZadrV4EPaAkLgQ6fkjK55EPmHX/V180OIDtvps5Yz/Gaa0nIK3cyYbUZmieZXmjG40mt+u/5ZtH8+lYsy0bjHnRewLpuyfwqq+qzKVJSpvjPQeyUjvkag1akwMTHjL+y1Jic/Oqru422K9RSaZokVWbksYQ6VhkRS9rmgk5nbDLgDjdotuLp8e+pSfe/1Mr5q9cryxFBeCIEiLGf3riGn1P2j5AcMaDtNzT9t8ezM1bGswt9PcLOdJz+Kzi1l1ZRUg1kcMTwhn6qGpAHzUquxkHEy/iGNnlpaA6oOWH+Dl5CXVEN7zcA/3Qu/lWj5o0ZlFnAsQyxe8+OQFzhbORJ6O5Nm3t3ZrzAAAIABJREFUzwjfG47SUonTKCdsOtpQqWXZqQUrK7YyMjI6xjYZW/D6lrkqt7lbbgE+b/85a6+tZd9D0W12pPdI2rq1ZaT3SI4/OU6Xal2YfXQ2xgbGUn4KgNGNRnM/7D5n/c/yycFPWHd9Hbsf7Gb74O28Vvc1qV+PGj04M+YMrda24tervzK17dRMMiSkiMrtwm4LpVJI33f/Pk/yl1XGNBqjF5IEYu3ij1t9jJHSKMex1X4SE1E9Cn/Esotiqb2r46/S2KVx8QhbRBgoDPhf///hYuFCPYd69KjRg08OfsLvN35nhNcI/riZ5l3VbUM3vbEHHh0gemZ0SYtcLCgVSkY31o+mDP40GL8IP1qtbSW1eTl5lTs37PKGoM3DKl9ZplmzZtrLly+Xthj54ojfETbe2sjafmvljMmpPAh7QO2fa0v7lS0rE/hxwV12AVr+2pKLgRdZ0mMJH7b6sLAiFgvHnxxn3O5xVDKuxNUXYqbMLW9sYVD9QdmOSVGnYDbfDJVGBcB7Td9j5ZWVAPwz5B/61e5X/IIXEQ/DHtJkdROGNxzOqiurODjiIO2qtssUo67Vall3fR1rr63ljP8Z2ldtz9FBR7nZ6yZRp6IwtDekypQqVHm/CoY2ZS+9vm71Vi4DJiMjUyj+mQTXNmR/fMwBcG+l36Yrn/Nl5tjXuOQ4vj75NVPbTNVbgEyPf5Q/YQlh3Hp5i7e83yIwOhDXJZmTX33S+hMWdxc9pZ5EPqGKZRWarWlGbHJslqVinkY+xeMnD2l/WptpudfczeG9lBUO+x2m24ZutHZtLS3Gxs2KY8bhGey8t5Mtg7ZQzboaThb6cbBm35hJ1myA7p7dOTDiQInKXlxkZ8E8OOIg3Ty7ZXmsInHI9xCPwh/xZoM3i6381n8BQRCuaLXaZrn2k5Xbkmfl5ZVM2DOBnW/ulCx5MuIq7s2XN2m1tlWhlNtEVSIjto9gcsvJ1LStiYtlzpkjywL3Q+/TYEUDSWHVKUET/p3Avw//5cjII9iZ2mFnZkf739pLGYwBxjUZx5qraxhUb5AUC1veCIgOwG1JmovO1DZTWdhtIYvOLOKg30GeRj7lYfhDFBoF75u9z8fvfoyHtQd3R93FsqklLu+4oDQvuzVgZeVWRkamSNg8FO7nkIl29D6o2ka/rRgUwmsvrrHj3g761OzDhpsbWH5pOa1cW1HdpjoHfQ8SGh/K5BaTGd14NEGxQfiG+zLCawRWJqIsl59fprJlZRquaEh4QjgASbOTcrVulgflNkmVxKorqxjhNUIqmXfy7ZO0X9der1/MzLR4Wov5FlLN+U4enYhNjuXC2AsVxgCiS1K2ceBG6jnUIyw+jKikqGzd2mVksiKvyq3sllwKvN3obaYemsrm25srtHKbkJLAissrmH9qPnZmdjwIe8CUllP4sWfm8jexybHEJsdK+wVddNFqtSw+u5htd7fxdqO3y4ViC1DbvjYpn6dIsahfHv+Ss/5nOeR3CIAfzv3A6Wen+bTNp5Ji28CxAbeDb0vldDpX61xq8heWjCUwFp1dRHRStOR6baAyoPfN3oy/NB7rUGuchzuDNdRdX74yasrIyMgUitQF0GzJo1tyYWns0lhyl23p2pIfevzAo/BH1P8lLeyqX+1+NHJuxIFHB5i0bxKT9k3C0siSM2PO0HxNc735fur5U+6KbTnB2MCYyS0nA/Dsw2eoNCpOPD2RqZ+5oZi9PyElQVJsL4y9QLPKzbgbcrfCKLYA33X9jvld5mebNVlGpiiRv2WlgImBCUMbDGXz7c1otdpyfwG7G3IXYwNjIhIiWHR2EZ+0/oSmlZviusRVWpENSwgD4KcLP9HAsQGB0YEYGxgz45UZgJiR8d1/36VXjV6s7LMyxyyM2aHRami9tjUXAy9ioDAol8rea3VfY/L+yXx14iu9dp2SN/qf0czvPJ/mVZqz/NJybgfflhYCBMr39+jWhFv4RfjR/09xwWfVlVWYJJvQ50ofJt6YiCJIgUUTC9yXumPsYlzK0uaPqlZV9TJdysjIyBQIdUrOx3d/CB+UvDebkdKIeg71WN13NRZGFlSzqUYrV9E9urtnd1wruRIQHUBMcoye5xHk0WJbTtElDcqY5LFFlRYIgsCBRwfouVEsKdjRoyPNKzdHEIQKl5tFEAQMBFnlkCkZ5G9aKVHfoT6xybG8vuV1vu3yLSqNqlxezL449gVzT+onQPrrzl9Maj6J8IRwjJXGBH0axOOIx3x35jtsTGzwi/Dj29PfArDu+jquvXsNvwg/APY92seQBkOobV8707ly49bLW1LNtKvjr2JmaJbLiLKHayVXZr4yU/p8MlLNuhoz280EkErhWJlYMbDuQKrblK8i6Blp4NiABo4NCJ0ayptb3+TI4yNYxVkx8dBEbNrZUHV9VWy62ZTLxaADIw6UiQzWMjIy5ZzcEkqFPSwZObIhq0Q5giDg/5E/yepkDvoexFhpTPyseCbsmYCpgSmGirKXJ6GocTB3IGl2EgYKAw77HWbphaX8eftPhm4bCkD/2v35Y+Af5fL+JiNT1pBjbkuJbT7beONv/Xqp5SUeL0WdwndnvqNFlRb0+KOH1F7FsgqBMYGM8BpB9+rdWXdjHQdHHESp0I+FDI4L5rW/XuOs/1k8bTx5HPlYr/4pwGftPmNe53n5kismKYb+f/Zn48CN5cYdOSe23NlCfYf6eNp6otKoSEhJwN7MXrr56eI4I6dHSnFM5Z2kF0kELAkg7FEYLb1b4m7lznc1vmNI3yGlLVqheGvHW0QkRPDvsH9LWxQZGZnyzMp2EHQz5z4Z41HLQZxqnqkA72XTrU3S4jSImarXD1hfihLJyJQP5JjbMs7AugNZ3ns57+99X2p7GfsyU/a8ssKeB3vwjfDF0siSMbvGAKAQFPSt1Zf4lHh2DdmFQlBwIfCC5FI8qP6gTIotgKO5I2fGnJH2jz4+yqubX6WpS1NikmO4HnSdb059Q7I6mcH1B9Put3YYKAyY1HwSCaoEHMwcmNJqCssuLOPTNp9iqDQkND6UqMQojow8UmFWPgfXH6y3n9HyN7j+YLbcKZ8JpDKS4JfAs4XPCFoXhDZFi/Uga6a1mMYg70E0q5zrdazMk74UgoyMjEyBSYkvbQlkCklGS/XUNpnLJMnIyBQcWbktJQRBYGLziXrK7elnp3m93uulKFVmll5Yys57Ozn25FimY2fGnJFianSkj5XNWM4lOzpX60z0jGjUWjV+EX7UXS4mCVp0dhGLzi6S+i04s0DaXnJ+CWEJYYTGh7Ko+yIm7JnAVp+tPPvw2X+mMLa3kzdb7mxh8dnFLL+0nJ97/8ywhsNKW6x8E7IjhDtv3EEwEHAe7Yz7VHdMPU1pRCOSVEmoNeosF0lksker1fK/M08Y3MwVS5OK7/InI/OfISUh9z4yZRpDpf41uZp1tVKSREamYqIobQH+6/zx2h9sfn0zAG/8/QYLTi/IZUTxc+rpKZqsaoLwlcCU/VM49uQY09tOl4538ujE9XevZ1JsC4NSocRIaUQd+zpov9ByZOQRXCxcODbqGLuG7GJBlwWs7LNS6j/zFTHu9GH4Q2y+s2Grz1a6e3b/zyi2INYGBvCL9CMiMYKU3BKNlCGizkcReSoSAOuO1rhNdaPV41bUXlkbU09TtFotkYmRWH9nzUcHPiplacsfpx6G8vW/Pny5y6e0RZGRkSlKkuOgTl8wsixtSWQKSPqMwaMbjcbcyLwUpZGRqXjIlttSZriXGHfx7elvufnyJjOPzJQyCJckupjXJeeW8OmhT/WO1XeozyetP2FB15JTvDtX68zzT55L+6/WfhWAd5u9S6IqERMDEw75HWL3g91SH90iwX+F9TfEGB3d/66su2NrtVoiDkfw7NtnRB6LxLqzNY2ONMLQxhDPBZ56fWOSY7D5zgYApSBbbfNLYooagKiE8rPgISMjkwdSEsDOE1qMh9/7lbY0MgXAMt3CRFWrqqUoiYxMxUS23JYRNry2oVTPfyPoBsq5SkmxdbZw5vw753n56UtuT7yNg7lDqcqXHp27c3Wb6lgaWfJGvTe4+/5dbE1tS1mykmVis4lAWq08hVB2f87hh8K52uIqN7vfJP5+PJ7fe9LgnwbZ9k+/si27JBeG8pGkTkZGJg9o1KBOAkNzMLfP//gXN4peppKknCdA1VHHvo60XR5DiWRkyjqy5baMUN+hPm3d2mJiYMIRvyN0qd6lRM6r0Wq4FHiJVmtFF+P+tfvzdqO3GVBnQImcvzDM6zyPH3v+WGHr4+WGTumTLLdlrM6tJkUDGlAYK0h6lkRKRAq1VtfCeaQzCuOcFfH0CTcqguW2WeVmOJiV3AJRWbfiy8jIFIDkOPHVyAwc6+V//Kr2MHIXVC+nNbcriHKbmFrOqbpNdWra1SxlaWRkKh5l19TzH0OpUHJ6zGlUGhVdN3QlND60SObd5rNNis3MiEqjwuNHD0mxBdjx5o5yodgC2Jra/mcVWxCzTAO4W7kzyntUmalzq45XE7AsgAs1LvB8peha7jTKiRb3WlB5XOVcFVuoeJbbXUN2sW7AutIWQ0ZGpjyjSyZlaAqCABbO+Z8jJqhoZZLJN9eCrgHiwrRfhF8pSyMjU/GQldsyhk5Z++n8T4WeS6PV8Mbfb1D759oIXwlsvpUWk3oj6AaGXxviH+0PwCvurxD8abBs8SlHPAp/BIhlBNYNWEdrt9alKk9KZApP5z/lvMd5Hk1+hLGbMeYNU12mDRQoDPJ+uREEQbLYps/AXV5xsXTB0dyxxM9bQQwdMjIyACmpllvDQiQgKtfJiyrGBS0yUUym+CTyCfse7itlaWRkKh6yclvGmNZ2GgDzTs3j1stbBZrjyvMr/Hj+R8myp2PY9mFsvLmRzus702hVIwDaurUlblYcp0afKlNxtTK5M7zh8Nw7lSB3h97l8WePsWxqSaOTjWhyugk2nW0KPN/cTnM5OvIo3T27F6GU/w3kJSoZmQpIcmqNW0PTgs9hZFY0spQGFWS1bmiDodJ2xrJAMjIyhUeOuS1jdK3elaMjj7Li8ooCX/SarWmW7bERO0ZI23Xt63J6zOkCnUOm9KllVwuAKfunsP7Gev564y8G1h1YavJ4fO2BxzcenDSIxaVaIR6+Upn5ykxC40NJSEnAtDAPczIyMjIVAZ1bcm7W19M/wisfZn2sDCceLFbCfMWEWg1K7x6pw9jAWNpu4Jh9YkUZGZmC8R+9ypVtOlXrxJZBW6hjX4fguOB81y+tYllFb7+7Z3diZsYQOT1SalvQZQEXxl4oEnllSgffCF8AHkc+RqVRlbI0UKlZJV5UFpi06Rofb7le6PkeRz7GcbEjP57/sQikk5GRkSnnSG7JOutrNpbMw1+kbWe0dmrURS5WyVEIy+2KNrB1dJmz/npYe5S2CDIyFQ7ZcltG0Wq1dN3QlaOPj/Jhyw9Z0nNJnse2qNKCHfd2APBkyhOqWqfVUdPM0aDRaipEkp7/OtWsqwFpJYBKM1vysXvBfLf/HveCYgA45xtW6Dm9VngBFSOhVGlRth7jZDISGJmAQgAXK9kzQSYPpE8oBVCjG1z/I+cxFUm5LYximpqhGFVi4dy6ixgLI4vSFkFGpsIhW27LKIIgEJea9v9vn7/zPC4qMYpEVSIWRhbsHbZXT7HVzSsrCxWDme1mYqQ0khIvlWadW2szQ0mxBVBptKSoNYWaU/d+KkIpoJJGzgtXdklRa5i98xbB0Ym0XXCU1t8ezX2QjAykKwWU6pb8al4ST2ZQCLXlWLktCpJicu9TAlS2rIyXk5es3MrIFAOycluG2Tp4KwCetp5o061YhsWHcTv4trSv1WpZdmEZ7/zzDtbfWfMs6hlz2s+hV81eJS6zTMmiEBSkaFKk7dKisbsNuya11Wur+dm+Qim4uszd8mKMTEXixP0Q/jj/jC923ZHatGXMVVKmjJKiSyiV6paszIPzXUWy3BaFL0pidOHnKALaurWlp2fPUr1vy8hUVGS35DKMayVXkmcnExQbRI8/ejCnwxzaurWl+x/dufriKuo54k2q3W/tOOt/Vho3sflEJjafWFpiy5Qg7au2p4lzE+rZ16OaTbVSlcXL1ZqTUztx+3kUEzdeBeCvS/6MaFU1l5FZo7vpyzf/giMrTWUPTer/JDI+LZfCyYehdKglZ6uXyQXJLTk/GY8zKreln5+hVEmKKm0JABjlPYqA6IDSFkNGpkIiK7dlHEOlIYmqRE48PUG739rpHbsYeJHWa8Xapp+1+4yFZxbiZOFUqhlzZUqWAyMOlLYIerjbmeFuZ8bxTzvScfFxZu+8zckHIbSoZkuvhi5Usc57rJOdqR2RiZFUt6lejBJXTGS35LLL2tOPATjnlxaXnpD8H1c4ZPJGUqrVMX05n7ZT4EwO7skZF7h0bsm3t4O5PVRrX7QyFicFXaxLb63+cwQ0HQUdZxSNTAVk8+3NnAs4x7vN3i1VOWRkKiKySaQcUNOuJifePpGpfcjWIdJ2h6odSP48Gf+P/HG2cC5J8WRKGY1WQ5IqCY22cDGuRYmHvTmTu9QE4KDPS+btucvM7bd4FhbPyQcheZpjToc5/Dv0X/rW6lucosrIlCgXHodn0SqvRsjkgXt7wMpNPyFSrgpfNm7JW0fD+leLVLzip4DKbUxQuu3ncPzbvI/VFM99deOtjfhF+BXL3DIy/3Vk5bac0Mq1FbEzY9kzbA/HRx1npPdITo0+xdp+axnSYAit3VqXtogypUCrX1vRZ1MfTL4x4aDvwdIWR4/+jSrr7Z98EEL7RccY+b+LaDS5P6T08OyBm5VbrmWOklUaJm68wsOXZSNRiIxMdmTnJi5b2guOVqvli39uc8M/MvfO5ZlnF+D5NTC21G+vnU1uDd13LWOMabmOuS0gUf4FG3f3X5hrAyH3i1YeGRmZYkVWbssR5kbm9K7Zmw4eHVg/YD1uVm6MaTyGza9vljPu/Ufxi/DjRcwLoOzFpno6WHDv6548/rY3a0c10ztWfdZeHgXH5jh+/qn5eK/0JjY55363AiPZeyuIadtuFlrmioYccVu2iE7MeqFG1m0LTmySivXnnjJo1bnSFqX4CPOFv0eJ250/1z9WtQ10mJ55jM6TJ9gnQ3s5Vm4L6pYclUVsa1weytX57BRfnxe+bntGPmjxAR+2/LDI55WRkZGVWxmZco1CUEiWzdKsc5sdJoZKBEGgcx1H5r/WkDebuUnHpm29kWPCo6UXlwJ5rwOY07sPjEyg4ZcH2Hrlv5HAoyx+F8oLao2WCX9c4cyj0CKf+3lkQpbtgmy6zTcqtQbfkFgSkkVlLVml7z46718fFu6/R1R8itQnP2y55M/j0LgikbXQHJoDqYuYuLfKfPzFjcxtOgttQoR+e8i9opWtRCmgchuXxW858mnhRCkkS3stZUnPJaUqg4xMRUVWbmVkyjFKhVJSbsua5TY9giAwrKU7373hxe5JrwBw9VkkO64F5jrWQJFz3rvs9OMZ226y5qQY0/QoOJaYRBXrzj7On+Ay/znuvohm3+0gvtp9J/fO+SQ75bY4eR6ZQHhccomd78+LzwiNTSrWc9wOjKLGZ/vo8v0Jvfra6fn19GN+Oe6L99yD9F12Kl/za7Vapm27yYDlZ4pC3MIR6Q/3/k3bz2qxr06fzG06C21ihuzAZ5cVnWzlhay8fxKyin3PgO7mIi8+yciUK8ru07CMjEyulJU6t/mhoauV5Kb88ZYbfPp3FlYH4KeeP/Flhy9znU+n2+qsX/7h8aw785g/L/nzzd67XHsWwc3UeLzbgdHEJf13MtP+lysBRcWnFKjOcmzq9+PBy1guPcnDA3A+uJ76PXSxMtFrVxdT0hqANguO0urbI8U2f3qehsUxY/st3k8tBVZcLDyQFgN5+WlEDj1FfENytsD+dPih9L8BSEq1AkclpGQ3pOTwv6C/b2CUuU+TkTAnw3dV55acWIFikQt6QUuOA4Whflt8Xn7b0t0l68MpCXB+RfmNY35+HW5ugYeHSlsSGZkiRS4FJCNTjulWvRuWRpaYG5lT1bpg9WRLgy51naTtrVcCeLuNBw2qWOn1mdxycp7mSp+cSq3R0m7hMb3jr/1yVm9/1o5b/DSkcX5FliknqNQaRv12kTOPwujT0IVaTpb0bOBMQoqapUce8svwJpgYKrMdn14hHrTyHE8WZGEVKyDXnkXiZmvK5nGtuPYskk/+vkGySkOyunhXITK67GYkIi4ZjVaLnYVxkZynuC236TOu33uRljDp93NPGNnaI19zqTValhx+wJLDD6T/dWKKvrJy7VkEXq7WKBWlYMHb9k7e+ikyfKd1Cld8OAjKNEtujW5FJ1uJk4/fyZPTYOkCdp6icmtkDgYmEJuaOTngMtTqASZW2c+Rm+X26Dw49zNYOkP91/IuW1ng7r/w1/C0/S/LRv1fGZmioHyYemRkZLJkhNcIfr32K1PbTC139WBXjmgqbQ9ccTaHnjmTkqoYCMDkP69J7YbKrB9I/rn+nIuPw9l+NYCo+JRMD7IVAc1/2GT7IiqRM4/EZDF7br1gyeEHvLHyLGPXX+LovWAO+bzMcXxBrL15JSg6kXoulXC1MeNV78psn9AGgB8PPSA0NomQmCQO3AnCY8Ye/rmeu8t+fth/+0W2xxp/fYim8w4X+hwZvSiKA12cvrWZIRbGBnpuyXP+EV3Js8rGnqTK+ncel0WN4cSUtO/AlacRvPbLWVae8C2U3IVmyk2YHZz3/gc/E1/jw8DcIa29DJWMKzaiX8C6PrCsiejWnRQtKrfvHISeC8Q+F1fBAvdcEkvlcB29u1tUbAHKideUHkEZEjD6XywdOWRkioFy+IuUkZHRsfDMQuJT4tnzcA8p6jLgQpcPejZw5t7XPQHR4jPqfwW7ueqU08tPI9hzM+0B/ofBjVg5ogmeDubc+aoHa0amZWwevOocH2+5gffcg3h9dZCNF57y5qpzRCeWr88wO3TP9rpHM7+QWH45/ijHBF4VhYyWe4CYRBWhsWLc6dYrAdwOzN5Kkawqvs/oZVQizpXSXJLtLEQXU7/QOJrNO0zzbw7z7oYrAEz583qhF17S/7/33w7KoWf5ISH1M3mvgydutmY8C4/XO67WaInJIit17dn7UWu0BEcn8ig4hocvY6g+cw9eX6aVUFt/9gmTNl3Vc+P+bMctgBy/M8VGcGryJ9vqYFMVDPJhWb/6u/iaEAFmduBQV9xXl1z8dZGT2/XL/6JYC/iHOmltPzaAG5vBqYH4GbaaAM5eaccPzi6Yu/NfI9K2DUyy71dW0WWArtZefF3brdhq+srIlDSycisjU4459UxMlPLWjre4GFj+Vl5NDJVSgqkTD0LyXavWPzyesb9f1msb0tyNJwv68Kp3ZXo2cOHIJx0xNzagWz0nHn/bm2OfdtTrn6zS8NmO21x4HE7nxSd4GZ3Ig3JeM1en1OheO39/goX775eNGMJS5sSDEPouO41vSCwvohJQZbDUFpflNi5JRUySCqd08bYWxjlHBsXmIT5cq9XSYdEx/rz4LFP76tSEaiBajUuK4nTejU1VXC2MDbAzzxx/+uaqc4SkukW/3cZD75jnrL20mH+Erj+cpNuSk2Q08H6x6w7/3tS3cOsswyW+LqRWwS8txe3+y/M2pk2GUA6tVkxGZWwJE89BtQ5QzhZB9cnhn7DnE1FB+3NY1sdbT0zbfi9dgrEbm+DxCdHCe3ENbBoCX1rBxsFwZ4fYR50MvsfE+NovrcS/9KSUfKK4QqHRiLHcTUbCyF1g5S62z7WBdX3F0lMyMuUYWbmVkSnHGCvTVvLLS0KpjDR0teLk1E4AdFtykpCYvMXrabVaPsmQjKpTbQe+HtAg2zGCIFDN3pwLs7rwbvvq/Da6OS2q2UrHQ2OTaDn/CN2XnMTneXS285R1svDKBOD7gw9YfuxRyQpTgqRXTLdNaM3nfeuxdGhafLW3m7W03eX7E7T+9ig1PtunZ5UrLuU2MnVhwdYsTSEzN8pFuc2mLm56klQanobFM2P7LaktRa1h/dknfLsvrezLeb9wjtx9yYbzT4lOTEGt0XLyQUiByuRkR0kogFefiQmkbM2NMEgXerBpnKgIXn4aISWp61rXiScL+tC1rmOhzxtfkuELWq1ocQTR4lq1Td7Gdf8avIak7X+fasH0Py/GjSqNyrflNj3nV+rvX/pVf//tvTBwjajAdZsL1TtmP9fv/cXPe++n8GCf2PbwQNrxnRNgwwDYPyPr8WVVud39IazqAEkZskW/vCUmGnNvLX4vBv2WduzJKdGdW04yJVOOkRNKyciUYyIS0zKFludame52ZtJ2828Os2xoY171rpzjmIM+L7n4WMx4ufP9tjhXMsHZKm/uYU6VTJjZW3TTa+xmzc5rgbzqXVkv7rD30lMsesOLQelq85YX0rujpo8/3HBerO34fqcaJS5TSTA+nRW/aVVbmlYVFy76eVdGrdGi0WqZvu0m26/qx7OOXneJS591BTIrt7tuPKdfLt/FvKBLtmRsmLYIpcglQVF6y+2x+8GsPuHHxrEt9cZlZd39Zs9d1p19kqn9nfXi5/P5zttZnu/K0wiq2Zuz+qQf1e3NGdw8f999VTG5NT4JjcPYUMHAX87yIkq0QNd2tmRGrzocvx9CXZdKtK5ux9AWbmy+6C9lPra3FBcS5vStT4pay4kHIQxt4cawFlU5/SiUQc1csbcw5mV0Ii3ni67IC1/3Qq3VMjPdYgGISawCIuJxtTGj2HlxPa2u7Xv5K2OETbrEgrrkSS0niK8GxuXbcpt+9WT/dGj1nritTvcbsPEA76Hg0Vbc9xqc9VwjtkP0c9g1KfOxmt3h4cHM7QBuLUWr55sbwbUZfF8bUuKz7lsU3NkBDw7CayvE9x8XChYOOY+Jfg4/1E3bX9MZJpyF6EAx9vjlnbT3AuLhlKTzAAAgAElEQVT7GHMArm+CaxvEuOytY2D6U1CUz0Vzmf82ZU65FQShJ/AToAR+1Wq1C0pZJBmZcoFQrM6Axc+CgQ0l69MHm69x/H4Ic/vXJyohBUOlAgdLY56FxdPlh+NYmRpKMZT/vN9WzyKXX6zNjHi7bTUANo5tSWhsEosO3CcgIoGpW29ib2lMp9qFt/yUJOkttz4vyq8FOr8cux+S7TGlQkCJwA+DG9GxtiOTN19j3oAGzN55m5CYJDxm7MHK1JBXatjrjZu72wdDhYCbrVmmjN75Qac0Gyr1Hxa93ay54Z91uZb0MeCTN10jJklFUHQila1NAfjh4H2WHk2zxIfFJqXWc34itVmZGrL1vdYMWnWOyPicFZvXMyR2m7btJs09bPh+UCNpAepeUDQ1HCwwUGZ+6FWnfvGKcp1t9Ulf5u+9l6ndw84cpULgyYI+aLVaBEHgsz712HzRX+pjn5r92d3OjPVjWpCkUmOkVCAIAg1d0/6XTpVMMmXF7lbPiTUn/fioWy0+33mbf648JubZTdA6gdIQrFyL7k1mZLXoycLra8Vz5YeELL5LvVIfo5SGYs1XdQUph6ZRg0YF81Kvz70XQ4txeRtbo4v4aucpxuoG34XGI6BaO7H96TlIioFNg8T9+gNFxbnTZ5ASJ2ZZViWDoRns+Vh0WR57CExtivQt8vfb4qt7KzEj9j/vw7sn4cIqsYbxkI36/VXJ+ootQOh9+Noubb9aB/HVIq1qAe6txL++P4rWW7sasmIrU24pU8qtIAhKYDnQDQgALgmCsEur1fqUrmQyMmWTn3r+xKKziwiIDsBAUaZ+zvlmSAt3/r4SwJXUupXbrgYQEBHPhVTr7Aeda7As9UFep9h+3b9+oRTbjLRNVWy61nWi/heiW9ro3y7xw2Bvfj72iGk9atOzgUuRna+40KbGpqk1WvouO53p+NVnEdRyssTC2IAklZrdN17wepMq5dr6n56JHT1zPN7Pu7JkjfV2tebVn8XPKCohhT23XqS2W3EjIIrQ2CQmpNZt3TGxDa/9cpZDH7WnppNlvmTSWW6NMiiFOya0wT8ing6Ljmcak94t2dbCiJgkFU/D4qlsbYpKrdFTbEGsG13XpZK0f/jjDtRwtADg6uxufLTlOubGBmy6IMbnfvFqPbZdDeB2YPYLIJeeRNB+0THqV67EnVRX/TFtq9HHy5kJf1zl93daUMdZPKdKp9wW0UJbkkqdSbHtUd+Jse2q65Xl0X1vLYwN+KRbLb4/9ID2tRz0XMABjA2yLwGVEXsLY8m7o0d9Z5rdmEPdHcfTOnT9Cl75MJ/vKK+krk65eOd/qG2GrPmdP0/bNjKHiMfwc1PKJxn83pPjYHmLtH3vIeSbqm2ydvuu2lp8neorJuRKf21Upi6MGBiBKjWMJuyhGJfbYGD+ZcgLJxaCe6ql1e84XN+Ydb8r69K2xx0Vrb4nMtiIHp8QX40tMo9XKKB6h8JKKyNTqpS1p+EWwCOtVusHIAjCn0B/QFZuZWSyYHLLyfSr3Y+d93bi7VyAB6EyxrYJbTh2P5jRv10CkBRbQFJsdSwe5M0bTYvHemJubMDO99syfM154pLVfLxFjOF774+rRVr3tLjQWW7jsklItPqEH/vvBPHryGZcfRbBL8d9qWRigCAIxCer6N+oSglKW3jUGi1TUstAVbYy4d0OOSu36WnoasXvY1owMkO27hUjmtJmwVG9Nl2yoVk7btGjvjM7rwfSqbYjEzvWwNQoZ8UpWWe5NdBXbhUKgap25tL+ldldeRQcy5urz+u5HJukKmbnfEMZuua83hw2ZoZUd7DgxIMQTqTWgH2jqauk2OrOo6vvPKlTDUwNldiYGzG6bTVCY5P4/uAD6rpYMuefO9RzqZTJ4n8nXQz6/8485n9nHgPQ88dTrBjehG71nCTLbVFx/VlmK+Sqt5pl0TOND7rU5IMuNYtUDgEtvZQX9BsPfwGxL0XrYdspYFWEvxnPLqIl0b4A76PFOKjVXUwSdHUdNEpXy9Qy1b0+4klRSFnyZAzqXpDObX7QejFxVlFjbp/zcUNT0RoOxRvPnBST9v4PzUlrX1xL/B4CONSBkHtgVxMmngelATh7QyUXuL0Nmo6GfdMhLh8lpWRkyiFlTbmtAvin2w8AWpaSLDIy5QIPaw8+bFVcFoSSp1NtR9aMbMa4DFmQdXzYtSajWntgk0Wm1KKkkZs1t7/qQbWZe/Xaj9x9SZe6TtmMKhvoYm5vBKQlSvp1ZDP+vfmcndefs/+OGIt37H6wpABHJaQwdatY+7B/oyokpqgxVCr0LGRllW1XAyTFc/nwJliZ5s+Vs11Ne95u40FQVCIdazvQtoY9la1NWT+mhV6JqrWnRYXu0pMILj0RPQxuB0az73YQ+6e0Y93ZJwxq5pbl+VN0MbdZuPMC/DSkEf878wQ7C2PJPpVeuTVKVYozWmt3TGxDY3cbklRqJm26xiGfl/RvVJnFg7Jf7NK5NeuwtzDm24ENARjZ2kNqfxGVwKYLz6SFpdl96rLlsj8PXuonqJmw8SquNqb0b1T42GQdV59F8FbqZ39iakc6LDrO6LYeOQ8qLgSBNknL2DKyLvWeb4XTS8T287+IrxdXgbEV9PkevAYV7lzB98D3CFRuUrDxCmWa9bb5WP1jjnUy9y/r+B6D7eOhxfjs03DXfw3qDyhRsSSMLNKU28u/QcPBxePOmxQFd7Znbo9NV7c7JNXLocFAUbEF8bXp2+IfQN1+cOtvcKpf9DLKyJQRyppym9WlK9NSsCAI44HxAO7u7sUtk4yMTAlTxzltBX5QU1cWDfImMUWNiWHe3QqLAkEQuPRZV/7f3p3HR1XdfRz//rKy76uA7KuiqKAgLoCKgLVardU+bu2joiJardZKtZZaEZVqrT4upatV69pasaIoCtYFQVBQkMUAUYIoO8gOyXn+uHeSSTKTSUgmc+/k83697it37jYn92SZ3z3n/M78/M36ZO02PTp7pW5/aYm6t26kFo1y1KReFcfD1ZIPVm0u9fqpy4/T0B6tdErfNmqQm6Xn56/R/kKn9/I2Kn+TlwwlEthKUsGWXTrhnlm6ZEhn3XFW/OzTQeCikv/kZGWo3yFNEpxRnplp4nfLf9gb3K2FhvZoqffyNlV4ft76Hepxq5dldem6b3XfD8oHlvFabiPOGtChuMU8MkVQ9Hyt8XqMH3WoN8YvNytTf7xkoLbs3KfG9WrmX3v7pvV148jeunZET23euU/tmtbT5Sd202uL12nZ198qK8P0xtL1WrRmqwq27NbDs7wpRPYcKNQLCwqq1dX9nEe88b/De7dW55YNtequMTU6lrcqzKQdaqD9jTtKp06UTr5Fev9BadakkoP2bvPGXkaCW+cObvBxZPqfegc/vjuuvmfV/DWT6Ys5XpZiSZp1Z8n2oT+R3vu91Lyr9L3HvLGiqXL2w9KT53rraz6QPnhYOv7a1JVHKv9QI1pmljTgh7VXFiAFghbcFkiKTs/YUdJXZQ9yzk2VNFWSBg4cWNuzzwFIsujWwsh6bQe2Ea0b52p0//Ya3b+9WjbM0Z2vLNWw386WJK24c3Rxi1qQPB015+mNp/XS8d29ZCJmpru+1193fa+//vD2ylJTxUQ74Z5ZkqS/z/lChUVO67/dq937CpWdafrDxQO1YcdetWqUU6UxjMny6uKvi7vDrrhzdI1eOzcrU09dPljbdu3XI2/n6eMvt2rcsO6a+t9VuvLk7mrTOFejf186m+1LC9fq6mHd1bF5fT95kXffIwmlyo65jaVedqZyMjNKBbfR42+nXnyMZi1fr6tPLp/1Ohk9GnKyMkplIh91ePvisefjR/TUEx98USoD8xebdumm5xfp7RUb9FDUVEwH46ReXmbYRJmla1V2Penkm6WjL5Xu61Wyfe92bw7UkZOk12+VLvynl5xn2C1e99WqGDW5ZssseYHNsAnS7LtV4ZyxQbD6Henx78Ted9odXmtt28OrnnCrpvU4VZq4rWTu29dvkwaP81rQa0LTTtK2NaW3dRvmjbuVpOs/9aZ4eu4S6cwHpQN7pEbhSoAI1LSgBbcfSuppZl0lrZV0gaQ4M3IDSFfR81cG6UPt+YM66c5Xlha/7nXbq8Xr/xp3vI4+tIYzZR6EK58o6c49qEtzjR/RI2br2diTumnNll168oMvNWfCCOVv3KX5+Zv14sdrtWrjzuLjnpr7Zanzor9nSbrjrMNKdWXdumufNu7YV2q8Z7Ks3bpb4/xkT6/+5MSkvU/TBtmaMLokA+mwqOzZqyeP0adrt2ny9GWas2qTDhQ5nXr/28X7rxvRQz8d2bs4oVTZbMnxNKqXpR17vezGu/YdKK6T+847UiMPa6eRh7Wr9vdVUy4e3FltG+dq7BMLSm1/edFXOnvAIVXqxu+c0/MLCopfH9qiFqbeqaRy4WDjttIpt0tv3lF6++u3el+f8lv09u30gsqGLVWhyDQ9x18ntelb8bEHq0U3BT6w3bAifmA7zh/7fEj1HprUuEumSX//rre+anZJNuZ9u6RtBd746YNpyS/cL7XrLzVuXzI90flPeUH9rk1SE38owGVxpi4C6qBANTk45w5IGi9phqSlkp5zzi1JbakA1LasqDFLmQHK4Nu4XrY+u+N0Lb1jVLl95zzyvoqKnP763mqt2rAjxtnJVbBll2YtX68ZS0rGYD19xeC43ULNTHee3V/5d5+h9k3ra0j3lrr2lJ5666Zhyr/7DL1z83CN7Jc4KLn9pSVa8pU3tveJOfkacMcbOvX+t7X3QGGNfF8ViSQcuvyErqW6stcmM9MRHZvp6bGD9Y8ryqeIePCtPN38wiK9tcxL4tIgQeKpiEa5WcUtt3P9buaPXXS0zk1SErXqOq1fW43oU77F6LLH5+vMh97Vum27K3Wdd/M26ma/i3yPNo0CMQ1Xhdmfh94gjZ1d8QU+/KM0pZs3TUtFXrzS+5qdxIC+bDblZNqw3Eu4VRVFhdLDg0pej7xTun2zNPZt6VdbgztuuNvJ0hB/ztyNn3tf82ZKd7X3vp8PHq36Nfds8+Yq7nKSdOHz0iUveUF0biNvzuImNTfGHUgnQWu5lXNuuqTpCQ8EkLaiW26DltCoQY73ZzNv0mideO8srdu2p3hft1+U/Ol6/qohGtSlRa2V68yH3tUWfx7TPu0a6+ej+sSci7SyOrVooKmXDNRXW3ersMhpxTffal7+Zu3Yc0BXD+uu0Q+8o6uHd9eUGct1xoPlpxu65qmP9asz+2lfYZH2FxYVTxdTk/I3ea2ZN5zWKxDTGB3fvZVGHdauOGFXxHPzS1oiG+RWLrht3ThXX/s/Wx99uUUZVtJFN4jMTH/50SBN/3Sd7n1tWfFYbkn6dO02DZn8llbdNabCnhirNuzQlBnLi19fOqRzoHpuuLLZeiUvedAhR0k3r5a+eE969qL4F9i/y5s+Jp7F//TfKIkPhsomEsqb6XWtrWnb13nT9Bw7VhozpfLnrZpVsn7bhpL7dciAmi1fMoy800sqtfULadp10kePl+x7935pyLiqXe8+P5CPTNnTbVhNlBJIe4ELbgEgO7rlNkAfbqNlZWbo/VtG6NO127Rp5z498MaKUtmJz3tsjh44f4BO6dtGjZOceGrN5l3Fga0kPXvlkCpnDI4nklm3U4sGpbqXfvrr0yVJDbIzNfHl8rO1zVz6jWYuLWlFfuiHR2loj1ZqUYNjQldv3Kk2jXPVMDc4/8quOKlrueA2WsOcypW1V9tGenreGnW55RVJUt/2TYofrATZmP7tdUrfNup922vl9j0594tSXdjLuuhPc/VV1MOi7wZlSqrK/Alq0ELqe6Y0foE35+nTMeZc3ZQn5b3pZa5tHNUrYvs66f6oFsnBVQyCqiK7vpdw6MM/ea/nTk1OcPutny5l0TNVC25n3eV97TW64gcBQWTm/RxEsmhH27lB2rPd604cb/z13D9Ib/5GGv9h6Z+HXuV7CgGIL1DdkgFAip1QKogiXVKH926jl8afoKkXH6NFt4/Uf649QZJ0/bMLdcOzi8qdt3tfoSZOW6JtUQHpwXLO6dqnvTleX7nuBK28a0yNBbaV8aOhXbV68hj99UeD9PoNJ2nZb0Zp7Enluz5e+/THOvo3b9ToXKj5G3eqS6uGiQ+sRcd0bqH8u8/QveceEXN//UomRhvTv32p1wM6Nat22WpLblam5kwYUW777S8t0Sn3zda23bF/7jfvKt1ttzZ/jiujUj+5rXpIvUdL//N8+X1/OkWafZeXhGp1VCKylW+WrN+wxAuQkqlR1HjtPf5cwp/PlA7sjX9O4QFpSk/pk+cq9x47NlS9XFu/lNb647bPfKDq5wfB/gq639/dSZpUwVj5V2+W9n1bOrC96l2pw0FOCwXUUQS3AAInOzqhVAC6m1bWyMPaqWmDbB3eoWnxnJ8zl36jVRt2qKjIadby9Soqcpq2aK3+9n6+HnhzRbXf87+fb9TCNVt1ZKdm6te+SUoeBpiZhvdpo15tG6tedqZ+Maav5v3ilJjHrv92T8ztVfXc/DWa/8UWdQtYcBvxg0GdlH/3GfrPtSeoeYOSIK2y3WyP795KvdqWJOWKNZ41yNo3rR8zwF25Yad+/XLsVBr7C0vCx7d/NixZRauyg/qN6jVS+mUFU0g9/h1p4dNey+ZL15Rsb1ILrdWNowKszaulL+d6ya+ipzZ65SZp9j0lr/dslXaul165sXLvEZl/NVZX7gjnpGculD6b5mUbfqB/yb5GwZ5LPK7zn0x8zMSm0u6tpbdtyS9/3I+me8mkAFRJ8Ps4AahzzEyZGabCIqdqDBtNqSnfP1Ij+rTRT55ZqBH3lWTPPbxDE114XGdJKh5TWR2zl69XblaGnrsyfvKoVGjTpJ4+mThSR0wsncVzyOS3ymVYPhiRpEOHdUjCfKA16PAOTfXPq4/XiPve1h8uPqbS52VmmF6/4WR9tXW3Zi1fr1P7hiu4lbwAd/mdo/TMvDX61bSSgPbFj9fqXx+tlSSNG9Zd/Ts01Wn92ha36g/s3FydWwbvoUVFcVpMmQk+Yv37qtKvz3/q4DLqVlV0cLtzvbTwKW998yov0Ny53kuCFdF7lPRnbxiC9m6XHjpG6j1GGvmb+O+xw0ugJlcU/5jC/dKy/3hLtJ8urZ37kAydh5Ss//hV6a/+9GSdh3pjsiPu6Szdskaq5+ci+L0/N3aTjtL2Aum4q6QuQ2unzECaIbgFEEjFwW1IP+TkZGXorAEd9LMXPimeBkaSFq/drgn/+lSStHlnguypCWzbtV8vL/pKg7q0CMScs2U1qZet164/URu/3aeL/jy3ePvtLy1Rl5YNdVKv1lqzeZfaN61XpeRX0z9dV7x+/sBOFRwZDN1aN1L+3Wcc1LmHNKtf/DAkjHKzMnXp8V100eDO6u4nXIsOEh+ZvbLcOdEJ5YKgWg+NrnpXmjdV+ujviY/tc3A/I1VWtlU0kvho6cveEm32Xd4SbVOe9P6D0ohfxh8Xu9MPbvfv9KZCyonxsOJAjC68134U/izAt62XMrK8uW4Hj5NyGkkNW5cObiXvvtRrIi38R8m2i16QWvWSLKRPdYEA4LcHQCBFgtogZUs9GP/92fDi9TkTRignq+TP7jfb98TOwFpJ7+Zt1MYd+zRuWPdqlTGZ+rRrohN6ttKVJ5ceh3vJX+apyy2v6MR7Z+mcR9/XuY++r/yNOyt1Pyb6rYBXD+te6n4iuKrSXX5g59rLMl41B/G72q6/NOqexMddMav2WiubdylZt2o8FHvyHCn/XW/Kn7J2lCSTKxW8RYs1PrVlcP+WVVpWrhfYStKoydKIW6WeMZJ2ff669PovpX9f7b0++zFvfuOMzPC2XAMBwKcCAIEU+Swc1pbbiHZN6xWvt29aXyvuHK2Ft5+m287oq/xNuzSjgsy6iXyydquyM03HdGleE0VNqgmj+2rBbaeqd9vy89F+UrBNC77YomG/na3nF5RMm7Nj7wF99tX24tdFRU73vrZM67/dqx5tGuma4T1qpeyoGbESjZXVo00jjR8RrHqt9l+gnAbeVEFn3CfVj/O72i52ArKkqBc1LVdkeprWfaVOg6Vz/iideKN0/WKp7eHlzz3z9162Z0nKf0f62xnelD8Tm0mzJkub/Jb4b7+WupwoteguTb9J+uL98tcqG9xe8Va1v7XAatFNunGFd19Pn+xte/k6rwU84ojzU1M2IM0Q3AIIJEuTlttYmjXI0RlHeNlw//zu6oO6xtqtu/XPBQU6smOzQHZJjqVlo1zNuOGkCrvo3vzCJ+p126t6L2+jLvvbhxrz4DsqLHJavHabuv1ienE31kuGdFajAE0BhMQmjO6jzyeN1rFd47fMThs/VPUqmVG6tlWjk4WXAXnQ5dLP870pgyLqt5Cuei/x+NyaNna2F8hGAqrT7pAumyEd8QPplNulZp2kq9+TJm6TfrpMum6hdMlLXmA7+l6pcdmuw056+27poaOlOY9Ia+Z6Ad0RP/B2/3W0Nw7XOWn9MmnOw9KKMtNFdaj8mPRQatzWu6+NyoyfP3as9Kut3pzJAKqNTwYAAikS0malYXArea24Pzz2UD0970st+3q7+rQraU0pKnIJg/orn5ivjTv26W8/PjbZRU2K7q0bauWGnTH37TtQpAv/VDJGNzJWM9rZRwVkDlRUmpkpO9P0x0sG6u5Xl2nl+h2al79ZkpcduV3TeoF8UFPjnUfG3OeNbbVM6ecH93Cr2g45ylskb4xoVm78Y5v401K16Op9zcqVrp3vTd3TqpdUdEBaM8/LAC1JMyZ4Xw8dIvUcKc32Wyp/2zP29Ru2lsbPr973EyYZZX7GB11BN2SgBhHcAgikyP/6IM9zW10XDOqkp+d9qVEPvKNurRvqnnOP0IzFX+tP767Wecd01D3nHhEzyJ352TdavHa7crIydHjAswXHc87RHTVlRslYvSM7NtWigm2VOnfOhBFqUi9Yc6Ci8prWz9bkc7wpTvYdKNK23fvVunEFwVVA1NgMzY3betMEVZRJuDZVFNjGk9PQGx8qecFa1xO9Vt4nvy/t3CD1+Y7XapuR6bVKPnS0l405lrGzpfrhmce52sqOc24W/KR4QJgQ3AIIpOJuyWn8RPvITiUf6FZt2KnzHptT/Pr5BQXq0qphuXGlzjnd8OxCSdI/Lj+udgqaBOOGddcFgzqpZaNcHSgsUmaG6UCRU89bX63wvLxJo6uUWRnBlpOVEfjA1qo/6ra82u6GXFsueqH8NjPpuo+9LskbV3hTADXvIq1bKDVuLzXtWOvFTKnohxpDxkvZ9VNXFiANpelfVwBht3tfoaT0brmVpBV3jtaQyW9qU4xpgabMWK7CIqcfD+2iFxYUaH9hke6avkySdPHgzhrYJahZZRMzM7Vs5AU1kWA1O9M0blh3HdGxmVZu2FHcsvvjoV301/fydemQzgS2QFiZSa17l7zuckLqypJKRQdK1nPLJ9gDUD0EtwACaV+h93S7T7v0/uefk5Whf18zVJ+t264rn1hQbv/9b6zQ/W+sKLf9ptN7l9uWDm4e1ad4/fITuyorI0OZGaZfnXlYCksFVDOhFBAR3XKbwcdwoKbxWwUg0No3Tf8uW51aNFCnFg30ycSRKti8W9mZpu179uvcR+eUO7Zv+yb6v/85Sk3rp/+Y0yAmF0Ldk8YjI5AKRYUl65k5qSsHkKYIbgEEWqN6defPVJN62ep3SEnQunryGL25dL1O7NVK76/cpE8Ltmn88B5pOT0SEHSOplvUBBcd3Kb/Q0qgttWdT40AQqlhbt1tvTMzndqvrSRpeO82Gt67TYIzANQ0HiUhaeiWDNQ4MnMACDS6pgIIAtptUSP6n1eyTsstUON4ZAQgkEYd1k4FW3eluhgA6jqablGToucVbnt46soBpCmCWwCB9NjFx6S6CABQjCG3qHFNOqS6BEDaoVsyAABAHEbTLZIlp2GqSwCkHYJbAACABByjblHTCG6BGkdwCwAAEAfz3CJpMkiYCNQ0glsAAIBEaLgFgMAjuAUAAIiDhlsACA+CWwAAgARouAWA4CO4BQAAiMMYdAsAocE8twAAAEBtGTKeZFJAkhDcAkCS/f6CAcrNoqMMEGaOfsmoKadPSnUJgLRFcAsASXbWgA6pLgKAg0SvZAAID5oSAAAAEnCklAKAwCO4BQAAiIOGWwAID4JbAACABBhzCwDBR3ALAAAQB2NuASA8CG4BAAASoOEWAIKP4BYAACAumm4BICwIbgEAABJwDLoFgMAjuAUAAIiDMbcAEB5JC27NbKKZrTWzhf4yJmrfBDPLM7PlZnZ61PZR/rY8M7slWWUDAACoCtptASD4spJ8/d85534bvcHM+km6QNJhkg6RNNPMevm7H5Z0mqQCSR+a2TTn3GdJLiMAAEBMNNwCQHgkO7iN5SxJzzjn9kpabWZ5ko719+U551ZJkpk94x9LcAsAAFKLplsACLxkj7kdb2afmNlfzKy5v62DpDVRxxT42+JtBwAASAlj0C0AhEa1glszm2lmi2MsZ0l6VFJ3SQMkrZN0X+S0GJdyFWyP9b5jzWy+mc3fsGFDdb4FAAAAAEAaqFa3ZOfcqZU5zsz+KOk//ssCSZ2idneU9JW/Hm972fedKmmqJA0cOJCOQgAAIKkc/ZIBIPCSmS25fdTL70la7K9Pk3SBmeWaWVdJPSXNk/ShpJ5m1tXMcuQlnZqWrPIBAAAkQqdkAAiPZCaUutfMBsjrWpwv6UpJcs4tMbPn5CWKOiDpGudcoSSZ2XhJMyRlSvqLc25JEssHAABQKY6GWwAIvKQFt865iyvYN0nSpBjbp0uanqwyAQAAVAX5pAAgPJKdLRkAACD0aLkFgOAjuAUAAIjDGHULAKFBcAsAAJAADbcAEHwEtwAAAHEw5hYAwoPgFgAAIAHHoFsACDyCWwAAAABA6O4aOpwAAAskSURBVBHcAgAAJEC7LQAEH8EtAABAHIy5BYDwILgFAABIgCG3ABB8BLcAAABxMM8tAIQHwS0AAAAAIPQIbgEAABKiXzIABB3BLQAAQBwklAKA8CC4BQAASICEUgAQfAS3AAAAcdByCwDhQXALAACQAA23ABB8BLcAAABxMBUQAIQHwS0AAEACjLkFgOAjuAUAAIiDMbcAEB4EtwAAAAk4Rt0CQOAR3AIAAMRBwy0AhAfBLQAAQAKMuQWA4CO4BQAAiIMxtwAQHgS3AAAACdBwCwDBR3ALAAAQF023ABAWBLcAAAAAgNAjuAUAAEjAkVEKAAKP4BYAACAOEkoBQHgQ3AIAAAAAQo/gFgAAIA4abgEgPAhuAQAAEmDILQAEH8EtAABAHMagWwAIDYJbAACABJxougWAoCO4BQAAiIN2WwAID4JbAACABBhzCwDBR3ALAAAQB0NuASA8CG4BAAASoOUWAIKvWsGtmZ1nZkvMrMjMBpbZN8HM8sxsuZmdHrV9lL8tz8xuidre1czmmtnnZvasmeVUp2wAAADVZYy6BYDQqG7L7WJJ50j6b/RGM+sn6QJJh0kaJekRM8s0s0xJD0saLamfpB/6x0rSPZJ+55zrKWmLpMuqWTYAAIAaQcMtAARftYJb59xS59zyGLvOkvSMc26vc261pDxJx/pLnnNulXNun6RnJJ1l3iRyIyS94J//uKSzq1M2AACA6mLMLQCER7LG3HaQtCbqdYG/Ld72lpK2OucOlNkOAAAAAEBCWYkOMLOZktrF2HWrc+6leKfF2OYUO5h2FRwfr0xjJY2VpEMPPTTeYQAAADXCkVEKAAIvYXDrnDv1IK5bIKlT1OuOkr7y12Nt3yipmZll+a230cfHKtNUSVMlaeDAgfy3AQAAAIA6LlndkqdJusDMcs2sq6SekuZJ+lBSTz8zco68pFPTnPc4dJak7/vnXyopXqswAABAreJJOgAEX3WnAvqemRVIGiLpFTObIUnOuSWSnpP0maTXJF3jnCv0W2XHS5ohaamk5/xjJennkn5qZnnyxuD+uTplAwAAqC4SSgFAeCTsllwR59yLkl6Ms2+SpEkxtk+XND3G9lXysikDAAAEC023ABB4yeqWDAAAEHpG0y0AhAbBLQAAQAKOplsACDyCWwAAgDhotwWA8CC4BQAASIBpbgEg+AhuAQAA4mDILQCEB8EtAABAAjTcAkDwEdwCAADEYYy6BYDQILgFAAAAAIQewS0AAEACJJQCgOAjuAUAAIiDhFIAEB4EtwAAAAk4UkoBQOAR3AIAAMRBwy0AhAfBLQAAQAKMuQWA4CO4BQAAiIemWwAIDYJbAACABGi4BYDgI7gFAACIw2i6BYDQILgFAABIhEG3ABB4BLcAAABxMM8tAIQHwS0AAEAc2ZkZOrFnK7VvWj/VRQEAJJCV6gIAAAAEVdP62XrisuNSXQwAQCXQcgsAAAAACD2CWwAAAABA6BHcAgAAAABCj+AWAAAAABB6BLcAAAAAgNAjuAUAAAAAhB7BLQAAAAAg9AhuAQAAAAChR3ALAAAAAAg9glsAAAAAQOgR3AIAAAAAQo/gFgAAAAAQegS3AAAAAIDQM+dcqstQLWa2QdIXqS4HYmolaWOqC4FaQ33XPdR53UOd1z3Ued1Dndc9Yajzzs651okOCn1wi+Ays/nOuYGpLgdqB/Vd91DndQ91XvdQ53UPdV73pFOd0y0ZAAAAABB6BLcAAAAAgNAjuEUyTU11AVCrqO+6hzqve6jzuoc6r3uo87onbeqcMbcAAAAAgNCj5RYAAAAAEHoEt3WEmXUys1lmttTMlpjZT/ztLczsDTP73P/a3N/ex8zmmNleM7sp6jr1zGyemS3yr/PrCt7zUv+6n5vZpVHbJ5nZGjPbkaDMx5jZp2aWZ2YPmpn526eY2TIz+8TMXjSzZtW9P+koneo8av9NZubMrNXB3pd0lm51bmbXmtlyvwz3VufepKt0qnMzG2BmH5jZQjObb2bHVvf+pKOQ1nnM48ws18ye9X8W5ppZl4O7K+ktzer8p2b2mXmf4d40s84He1/SWTrVedT+75v3GS65WZmdcyx1YJHUXtLR/npjSSsk9ZN0r6Rb/O23SLrHX28jaZCkSZJuirqOSWrkr2dLmitpcIz3ayFplf+1ub/e3N832C/PjgRlnidpiP+er0oa7W8fKSnLX78nUmaW9K1zf18nSTPkzWvdKtX3N4hLOtW5pOGSZkrKjZQ11fc3iEua1fnrUetjJM1O9f0N4hLSOo95nKRxkh7z1y+Q9Gyq728QlzSr8+GSGvjrV1Pn6V/nUd/DfyV9IGlgMu8dLbd1hHNunXPuI3/9W0lLJXWQdJakx/3DHpd0tn/Meufch5L2l7mOc85Fnshk+0usgdunS3rDObfZObdF0huSRvnX+MA5t66i8ppZe0lNnHNznPdb8feosr3unDvgH/qBpI6VvA11SjrVue93km6O895Q2tX51ZLuds7tjZS1krehTkmzOneSmvjrTSV9VYlbUOeErc4THBdd5hcknRJpyUeJdKpz59ws59wu/yWf4eJIpzr3/UZeYL4n0XWqi+C2DvK7/Rwl7+lN28gPov+1TSXOzzSzhZLWy/tFmBvjsA6S1kS9LvC3VVYH/5xE5/+vvCf/qEDY69zMvitprXNuURWuV6eFvc4l9ZJ0ot9V8W0zG1SF69ZJaVDn10uaYmZrJP1W0oQqXLdOCkmdV6T42v5D622SWtbQtdNSGtR5tMvEZ7iEwl7nZnaUpE7Ouf/UxPUSIbitY8yskaR/SrreObf9YK7hnCt0zg2Q97TtWDM7PNZbxTq1Cm+T8Hwzu1XSAUlPVeG6dU7Y69zMGki6VdLtVbhWnRb2Ove/ZsnrGjVY0s8kPUeLTnxpUudXS7rBOddJ0g2S/lyF69Y5IarziiTz2mknTercewOziyQNlDSlJq+bbsJe52aWIa/n3Y3VvVZlEdzWIWaWLe8X5Cnn3L/8zd/43cQi3cUq3fXPObdV0mxJo8zsOPOSgCz0W9kK5I2RjOioCrqYRZ4q+csd/vnRXVVKne8PdP+OpAv9rm2IIU3qvLukrpIWmVm+v/0jM2tX2XLXJWlS5/L3/cvvUjVPUpEkEonFkEZ1fqmkSPmfl0RCqThCVucVKb62mWXJ646+ubLlrkvSqM5lZqfKe2j9XecPPUF5aVLnjSUdLmm2/xlusKRplsykUi4Ag6ZZkr/IeyLzd0kPlNk+RaUHpt9bZv9ElR6Y3lpSM3+9vqR3JH0nxvu1kLRaXstLc3+9RZljEg1M/9D/JYgkHRnjbx8l6TNJrVN9X4O8pFOdlzkmXySUSvs6l3SVpDv89V7yuktZqu9x0JY0q/Olkob566dIWpDq+xvEJYx1Hu84SdeodEKp51J9f4O4pFmdHyVppaSeqb6vQV7Sqc7L7JutJCeUSnnlsdTOIukEed0LPpG00F/GyBvb8qakz/2vLfzj28l7irNd0lZ/vYmkIyR97F9nsaTbK3jP/5WU5y8/jtp+r3+9Iv/rxDjnD/TfY6Wk/5P/wda/3pqo7+OxVN/fIC7pVOdljskXwW3a17mkHElP+vs+kjQi1fc3iEua1fkJkhZIWiRvbNkxqb6/QVxCWucxj5NUT14rfZ68LNrdUn1/g7ikWZ3PlPRN1PcxLdX3N4hLOtV5mWNmK8nBbeQfCgAAAAAAocWYWwAAAABA6BHcAgAAAABCj+AWAAAAABB6BLcAAAAAgNAjuAUAAAAAhB7BLQAAAAAg9AhuAQAAAAChR3ALAAAAAAi9/wf1tm3gAZEuNQAAAABJRU5ErkJggg==\n", 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" ] @@ -4415,44 +1583,32 @@ } ], "source": [ - "dataset.fill_missing_correlation('CODtot_line2',\n", - " 'CODsol_line2',\n", - " [dt.datetime(2013,1,23),dt.datetime(2013,1,25)],\n", - " [dt.datetime(2013,1,1,0,5,0),dt.datetime(2013,1,31)],\n", - " only_checked=True,clear=False,plot=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data from previous day\n", - "Under the assumption that \"The best prediction for tomorrows weather is todays weather\", one can also replace missing data by making use of (one of) the previous days." + "dataset.detect_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=90, \n", + " plot=True, period=4)" ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 48, "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:06.731819", - "start_time": "2017-05-09T11:55:06.018568+02:00" - } + "scrolled": true }, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "C:\\Users\\joras\\OneDrive\\Skrivebord\\wwdata\\wwdata\\Class_OnlineSensorBased.py:961: UserWarning: When making use of filling functions, please make sure to start filling small gaps and progressively move to larger gaps. This ensures the proper working of the package algorithms.\n", - " 'ensures the proper working of the package algorithms.')\n" + "Drift detected in period 4 to 7, slope: 90.5\n", + "Drift detected in period 5 to 8, slope: 103.42857142857143\n", + "Drift detected in period 7 to 10, slope: -98.71428571428571\n", + "Drift detected in period 8 to 11, slope: -99.28571428571429\n" ] }, { "data": { - "image/png": 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\n", 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\n", 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" + "
" ] }, "metadata": {}, @@ -4460,27 +1616,30 @@ } ], "source": [ - "dataset.fill_missing_daybefore('CODtot_line2',\n", - " [dt.datetime(2013,1,25),dt.datetime(2013,1,27)],\n", - " range_to_replace=[0,10],plot=True,\n", - " only_checked=False)" + "dataset.remove_drift(data_name='CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,1,14)], max_slope=90, period=4, \n", + " plot=True, drift_type='A')" ] }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:07.431337", - "start_time": "2017-05-09T11:55:06.734413+02:00" - } - }, + "execution_count": 49, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ - "
" + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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QkxoDwP5r++kd2NvB0QghhBBCCGF/NWvWZNiwYezbtw+9Xi68lVc1a9akZ8+e+Pr6FnlfSUAI4QQS9YkAXIi74OBIhBBCCCGEKD2BgYEEBgY6OgxRSqQJpRBCCCFEGbuRnE7gxPUETlxPfKqBA5fiMJml8ZoQQojbmyQghHACAT4BAFTxKvo8KyGEEOXP+Zhk69eTVh3nwW/28uW/+Ve5yUpIQgghnJ0kIIRwAsE1ggFoEdDCwZEIIYSwi2y5hOgkbZ5z9qSEzV0k/yCEEMLJSQJCCCfg6uKKn4cfbi7StkUIIf6rJP8ghBDC2UkCQggncDnhMhXcKhDkH+ToUIQQQthZZmJBIf9172UKhhBCCGcnCQghnEC6OZ0buhuYLCZHhyKEEMIOsqcS8k872N5HCCGEcEaSgBDCCdxIvQHAjss7HByJEEIIe1OUwqUgpABCCCGEs5MEhBBOIMWQAsClhEsOjkQIIYS9hV6O174oIA+hSg2EEEIIJycJCCGEEEKI8qCA/IJUQAghhHB2koAQwgnU9qsNQDXvag6ORAghhD2km9JzbVt/PIp52y44IBohhBCibBQ6AaEoyo+KosQoinIi27YqiqJsUhTlfMb//hnbFUVRvlAU5YKiKMcURWmfbZ8nMsafVxTlCfs+HCFuT21qtAGgUZVGDo5ECCFESa0Ivcq7a07avO3zzefz3M9ikRIIIYQQzq0oFRCLgIG3bJsIbFFVtTGwJeN7gEFA44x/44D5oCUsgKlAF6AzMDUzaSGEyJubixu1fGvh5ebl6FCEEEKU0P9+P8rVeKPN24xmS577Wcj7NiGEEMIZFDoBoarqDiDuls3DgJ8yvv4JuD/b9p9VzT6gsqIotYABwCZVVeNUVY0HNpE7qSGEuMXJGydJ0CcQVCXI0aEIIYQoRS75rIghFRBCCCGcXUl7QNRQVTUKIOP/6hnb6wBXso27mrEtr+25KIoyTlGUEEVRQm7cuFHCMIVwbmaLmTRTGqp0IBNCiNtafityyioYQgghnF1pNaG09fap5rM990ZV/VZV1Y6qqnYMCAiwa3BCOJsbOi0J90/YPw6ORAghRGlS8quAkCS0EEIIJ1fSBER0xtQKMv6Pydh+Fbgj27i6QGQ+24UQ+dCb9ABcSbpSwEghhBDlmd5ozvd2l/wqICQBIYQQwsmVNAGxFshcyeIJYE227Y9nrIbRFUjMmKKxEbhHURT/jOaT92RsE0IIIYS47ekM+ScgFJvFoho3V3d7hyOEEEKUKbfCDlQUZSnQB6imKMpVtNUsZgHLFUV5GogARmUM3wAMBi4AOuBJAFVV4xRFmQ4czBj3vqqqtza2FELcon6l+gAEeMt0JCGEcGY6gynf2/PtASEFEEIIIZxcoRMQqqo+nMdN/WyMVYEX8jjOj8CPhb1fIQS0qt4KgMDKgY4NRAghRIkUNAVDZzBjNFtwd81dpGowGwCpghBCCOG8SqsJpRDCjlxdXAnyD6KiZ0VHhyKEEKIECpqCAWAwWWxuN5rzr54QQgghyjtJQAjhBA5eO0hYfBiNqjRydCiiHDBbVBLTjI4OQwhRDGmFSEDkNQ1DmlAKIYRwdpKAEEIIJzN93SmCp/1TqBMZIUT5oitgCgbk3etBluEUQgjh7CQBIYQTuJl2E4C1Z9c6OBJRHqw9qq1eXFAzOyFE+aMvROIwr0SDRbU9NUMIIYRwFpKAEMIJaI3HIColysGRCCGEKInMHhDdgvfmOcYiFRBCCCFuU5KAEEIIJyWnIkI4n+R0PQDLz87Lc0xevR58PfxKJSYhhBCirEgCQggnkNl8srpPdQdHIsqDPPrTCSGcQLxOB4AFPSYlxuaYvCogVEk7CiGEcHKSgBDCCbQMaAlAHb86Do5ECCFESSTptQoIlXSiPd62OSavqRadZ2xh0e5LpRabEEIIUdokASGEkwjyD8Lfy9/RYYhyRKaDC+F8ktPTUTGCYkFVDDbHpKSn5rn/bwevlFZopUqWEBW3q5k7Z/LShpccHYYQTkMSEEI4gb1X9xIWH0azas0cHYooB5SMORhSji2E80lJN2Ihswoir9Uu8v7b9vZwLZW4hBDFM+nfSXx18CtHhyGE05AEhBBOQK4cCVvkaSGE89EZTKikZ3xne1nNCm5eee7v4+lWClGVPnm9Ere7zBXLhBD5kwSEEE4gXh8PwPKTyx0ciShPZEk+IZxPRY9qNKpWj4b+DclrLZtus7ZyKjLJ5m2ebs750U1ercTtqpZvLap6VZWLRUIUknO+iwnhZA5FHWLI0iGcvnG6WPubLCYAbqTesGdYwsnl1SlfOE6CzkBMst7RYYhyTG804+3uRtjLYaiY8hy3eP/lPG6RdXCEKE8i/xdJ7IRYPN08HR2KEE5BEhBClIGY1BjWnVtHYnqio0MRtwXtBMQiGYhy48st5zkXnUzb9zfRecYWR4cjyrHIpJtcS7nETd1NVCUtz3HKbZZnkKvD4nZyPeU6yjSFyVsmExIZwtHrR0lKt121JITISRIQQpSB6ynXgeJXMLQIaAFADd8adotJOD/5PF8+pBnMzNl0jlEL9lq3SXJI5CUhTcf11MuYLCauvHYFb69km+OU26zSQRIQ4nZyPPo4AB/u+pBO33Wi7Tdt2XNlj4OjEsI5SAJCiDJwMuYkAGdizxRr/+bVmgNQw0cSECKL9IAoH9JNZgAS04zWbctDnHOpRFH60o0qKul4u3ujoBBtsH3SklcFRHjCxVKMrvSU5NXq+50X2RMWa7dYhCipOyrdkWtbfFq8AyIRwvlIAkKIMlDS5RKNFiNB/kFU96lup4iEM8s8MZEERPmw+vC1XNsSsiUjhMjOYAJVyUhAKApx7vNtjsur/iE8IbzUYitdxa/o+GD9aR75br8dYxGiZGwti34z7aYDIhHC+UgCQogy4OvhC1DsBkW7InYRFh9Gy+ot7RmWcHKSgCgf3vvzVK5tt1fxvLCXNIOZ5LQKqK43cXVxxUVxAcV2I0oljxKIqt7VAIhKTONSbGqpxVpeZFYYifJr9fGDfL59o6PDKFMPr3jY+vWah9YAcFOXlYDYFr6NiMSIMo9LCGcgCQghysDdDe8GsqZSFJXMnRW2SJuB8ut2ayBYVtIMZsy38RP7tWVHAPDx1qYTFKfPg5ebFwB3zvyXvrO32S220mZWi5dIiEs12DkSYW+vLo7hs79MdJn9NQcjLjg6nDKx9dJWHm39KMfGH2No06FUrlCZWF0sKYYUVFWl7099aT2/taPDFKJckgSEEGUg80qWRbUUa//Mzso/HfnJbjEJ55V5yiIVEEVjMhfv7684XCQDUSzN3/2bN38/6ugwSsU/J6/z90mtIfGp11YCaBUQQLTHpFzjzartyggfD59SirB0WSzF+/u7mSIJCGcRHRvItLXnHB1GmUjQJ1Dbrzata2hJhm/u+wZ/L3/8ZvoxZtUYQPvslrmM+n+NqqqMWD6CD3Z84OhQRDkkCQghykBcWhze7t7FXsUi88pRgj7BnmEJJ1fMz/P/SZtPRdNo8l9ciLG94kBx6Y1SHm4vmQmilbf01LieqEdncP4P8eN+CQXgrmbV8fF0A6BShUoA6F2P5Rp/OOoQkHtFFR9379IMs9yRCgjnkpDq7ugQSp3epCfdnE7lCpWt20a1GMX0HdMBWHx8sXX7gWsHyjy+8iBWF8vK0yup6VvT0aGIckgSEEKUAZ1Rh86ow93l9n9jFmVHKiAK76e94QBcitXZ9bjXE/UA+Hi45tie1/z9klJVlfgyPCGLTtKX+n0s2R/B68uPcCMl3ebtA+buoMdHW/kj9CqXbxat58GeC7E89v1+h0/r+GHXJevXe8KuMWmLVvHg4epBh1odbO5T1bsqACm3JF8uRDtng9Pivl7FJGc9LwInrif0cpy9QhJ2cCU+Mcf31xP1HLx0k9R0508a5iVRrz3mSp6VrNv+vvC3zbHdf+zOjB0zyiSu8uRKkrYS1GsbX+NEzAkHRyPKG0lACFEGYlJjALiadLVY+7er2Q6g2BUU4vaSatROwtJN/60rg2E3UliyP4LDEfHWvigms4WoxLQC9/Vw1d7unv05hGNX7VdJFHpZW3YtsFrZlMX/sOsS7aZv4kqcfRMptqwIvUqXD7dwKKL0lpY7ciWBSauOs/LQNRbtDrc5JjHNSFyqgTd+P8qI+baXrMzLC0sOsetCLAk6x/6tfLjhtPVrvdGdnRE7rd8PazoMgFj3OaS4bsq2l/YcT7plRZW4VOcsfSpuAiLsRs6Ew+bTMfYIR9hJdKJWBebrlYqqJGOyuDDqm320mfY3L61YwpoTIQ6O0P6MFiOdanfKsRRncM1gvN29aV1dm5LRqEoj621Ttk7hvW3vcfS6c04vM1vMvLjhRf48+2eh97mSqCUgUgwp/BP2DyOWj2BT2KYC9hL/FZKAEKIMZC6bdjzmeLH2b1K1CQBVvaraKyThxJLTtWkEyYYUB0dStu75bAeTVh3ngXl7aPD2Br7eeoGvt4Zx58x/uZaQfxLCwy3r7W714Ui7xXQiUrsStnRcV75/vCNuXtr8Z5dsBRCqqtqt/8TGjB4C+T1eVVXtcsV/30Wto/v5aPtOW8luzj9nrV9fic+qbojJqLy4tQFvbD79AHadjyVw4vocyZk0o3ac5HTHrRahM5hy/D58q27Gxz0rYdW9XncAUt22YlSynpvRKdqJduJ/fEnXsNicCbDC5jGWHogg/D+wSoij7bignWhuenUI4+7Kmh5ktij8ebASr/wazRc7/gFg/+XzbA/LvWqQs6lbsS4Hnj3A0KZDrdtq+9UmdVIqR8cf5Z/H/uHMC2eIfD3r73na9mm0/aatI8ItkaT0JHw+9OHrg1/z6sZXgZyrfeQlswICYPqO6aw8vZJ7fr1HmqoLQBIQQjgFnVFHkH8QdSrWcXQoohzIbELnqmjzyDeevM7xq4n57eL0tp2NyXVS/cnGs3y2WTvh330hNt/9PbMlIOw5OyI6SU/DAB8ORu6gfo0kLqnvAzDtz1Ncik0lPDaVn/aE02jyX6w5cq2AoxXMlPEzeOjbfXmOmfXXGYImbbDbtIPirNRQWDvPZ/3ejkdmXdl+6Dvt8aUVocfGnC1adcSa41nlvmkmLVETq0vgt0OH+HbP3hLFWxyRCVnTWLa+0QfFdzPe2fo43NXgLmr71QZAIWsqT2ySBwAJutsjAeHuWrwpiJG3JNsWbA8rcB+zReXtlccZuaDsf9//JbvOx/LF5qtUqBBHrUpevNZ7gM1xOy5oy1GOnn+OJ767ZHOMszBZTAR9EcS3od/avF1RFO4OuhtXF1dq+dXC8q6F489lXXzKnL7hLH45+gvpZm0a1MX4i6w7t45qn1Rj3sF5+e6noNCgcgNA6182qNEgQFue1FkYzAbpvVZKJAEhRBnIrFzwcPUo1v7bL28nLD6MNjXa2DMs4aQyO+dbMq6s/98voQz5apeDoypdYxcezPf2CX8cY8b6vK+sZa+AsOfp9PVEPTUrVmDg4oEsPLIQlayTpb6zt9Fn9jbe+1OL65XfjpT4/m5tSGhLZr+BdFPJGmSWxXWqelW8SXXdQbpylis3s6pELt7Qrlyn6HPPIz8dlZRrW4LOwPkb2pXyy4lZj19RfQFI1uuZuDyKD9eWff+Ad9doCZGvHmlHg2o+JKcn51rJol6lehlfuVm3xSZUA3I3YXRzdc6ERHEvfCamFX36jDGj4ijewVNvbmdJeiOP/bAfAK8K2t+kt4cn2yd0ZsOrwXRvnPUcDzlXizG/LnRInPa27MQyLsZf5P/W/V+hxiuKQtOqTWlcpTEAT619qjTDs7sLcTmXVR2ydAgAPx7+Mcf2Dec3oExTCI3Umu2+0PkFLr5ykcGNBwPw+6jf8Xb3Zs3ZNUQlR1n32xa+jbC4sHJVGRESGYIyTcHzA0/8P/L/z65kUpokASFEGbi3yb2AVrYnREmZLNoJiNliydHc7tXfDheqH8Lt6rudl3ju11D6f7qdX/ZdzvGBJvtVfPtWQKRT1dcNk8XEoahDQP4nPIWZihF6OY7WUzfmajZ5PjqZo9kqXQo6Vpqh/K/QcS0xFgvJmFyiuDU1FHo5nquJua8+Dfp8J+uPRdFq6kaWHYyg58f/0vb5YLCpAAAgAElEQVT9TaSkaifsl2LcCZy4nqZTsprCPfmDY666Lg+5wp4wrVx5cKtaGM1GKlWoRNOqTXOM23dVq/gwKzdyHSPzJDrRTVu6U1Wdc4lXg7l4yYDUW5pwVvYp+HltyPjbcM6flHOY+EfulVsA6lcJoEXNunw8oguP31mfmpUqALDzRHXrmLAbzjt98M9zWh+EXU8WPunv7urOukfWAbDy9EpCI0M5cv1IuTrpzsuuK7voXb83116/RpB/kHV7aFQoU/6dQufvOpNiSOHeJdrn3J+O/oTBbOCNf97g6PWjrH9kPepUFR8PH3RGHZ/v/5zan9ZGmaYQ8EkAfX/qS6MvG9H3p76YLeXjPSszWZTJGX5PzkYSEEKUgcyTH4tavHngmXP+F4QssFtMwnm5KlqZtre7b47y5NVHIvn477N57ea0sj/GI+/eTfise7k0czCv392EkR3q8vUj7a23/3XiOhdiUnhn9QlCLmfNHTdmO1k/fs1+JbDJeiNXkrWf+cawjahK/h9UUtML/oA1b2sYyemmHPHHJOm5+7MdOca9sOQQR68kcCpSu/oYcVNHfKrBWrlQlOkLtqSbtLJbg6V0riJbLComszsWRcfTHUdatxsUrcR+xPw9HL2iTdGI8XifgPpZr38vLDlESrqJt1Yc50pczqRbyAXPfO/37xPXy2R1j3PRyUzIOEnb+GovXFwU3F3dOTr+KJN7Tra5T4rrRnQuWdMGTGYLC7ZpP48Et59IdFsOuNrct7wryslF9g/8JrMrrp5Z88kNxoKnchgynvsWtXyc0NyOtl/I+p0MbJW7QXadyl68P6wVT9yZe+rorL9O59rmLNxd3bmj4h3W3i2FlVXlBGvOrqHdN+34+ejP9g7PrvQmPYejDtPtjm7U9qvN2Rdzfr6YsXMGByMPUmN2DUa3HA1oTSc/3v0xc/bOYe3ZtTnG/3x/zscbq8uagrf98nbcprvx2t+vcSzadnKrLKw5s4bx68ejm6TjtxG/8ceoPzgd67zP1/JKEhBClIEzsWfwdvcu9hQKNeOUItUgDbVEFlWFbedyXjFNtlGy7uxeWnrY+nXFCtrJh6IovNyvMbNHBXNvm1qseO5O3F1zXu8ctWAvV+N1JKYZrVdEAfZdjLNbY0WD2cKh64Vf5z05Pat8ftqfJxm7MOe+BpPFmkDI3sOh84dbch1r48lohn29m8Ff7GTQ5zvp9clW2k3fZN3vUmwqeqOZv45HsTzkSq79C3I9RWt4GZMSXeR9C3IlTkfDSRtQcKfjHYFU8s26IhrtOcX69bS1lwGo6+9J/8atSHOx3UU+wW0xCW5LC3Xf438NpcuHWwicuJ5XfjtcqGktxfF/v2ilyJMHN6dpTT9Wn1nNsN+G8euxX3Mt02qYkpHkUeCGx0fW7Y0m/0VkxlKvKGZUTJgtilNekVMLOaknNiWdBm9vYPIqbd68K14Mb521VKnOYGH5wSsk6/OeipJmzKgSyyMBYTBZmPXXGYevjuLMKnhpPW08KlxhxuDheY77v15NCKqjvZZ8+3g7Kvvq2XQqhi6zvyYy0fmWVH2x04t8MeiLIu9Xwa0ChikGDFMM+Hn4ATBxy0TWnFnDXT/dhTJNQZmmcO7mOXuHXGyphlQeavUQvev3BsDVxZV9T+/j2/u+Jf6trAT58ObDWThsIcfGH6Ntzba8s/Ud+gb2ZXKvnInWMcFjuPzqZRYPX8yn93wKwNwBc9n91G7rmLn75xK8IJghS4eQZkxj/9X9rD+3vgwerZYkvX/Z/fx24jc2nN/A6FajOXz9MO2/aV/wznkcb/PFzXaO8vbgVvAQIURJJaUnoTPqqOBWoVj7l2YTuNuFqqpMXn2CNnUq8VDnegXv4MT0Zh3gQYI+ics3cy7HuPl0NKqqkm6yUMHdlUMR8VT386Suv7ftgzmBiGyrGri42P5b6FC/Cptf783m0zE8fmd9Gk/+C4AeH221OX71kWssO3iFZf93Jx6uLpgtarGW0jSaVZLVeMh2UTbBbTGVTY/aHJ+SnpUgWmhj2ckmU/6yfv3lv+cZ2KomU1bnXD3nkW4V6HRHU15blnUybqsvwpgfciY35vxzlrua1WDqkBZUcHe1xuPrafujgFax5Yqri32uuCfqjMzfHsbZ60lsPZuVOKte0Uy4/nduul/lkeB7+PZkMpGeL1I7/SvrmM/vnc49jXrw0S4/PCyBeJt7kOC+GFXRsWDw9+hMnTCrZip7xDFh1Q5S3DbSrHpdBjXpzbItPQAY2cWdP/bnPGldcySS1nUqMbrTHXi4ueDpZr/qgksZKzA801NrxPbAsgcA7ef6WJvHcozN2aAxd6WczkX7Xapo8RvNTpiAKCDkuFQDeqOZbrP+BWDx/gj0RgtJehPXdRe55vkK3ube+JseZ8KKY8zbdoFtb/bN42ja7zGzWuxWa49GsmB7GOkmM1OHtCzuQ/pPM1tAcb/OuffG5zvOxcWFLS89bf3+r7NGVu2vQHRsIN1m7uXA5B5U96tU2uHaTZe6XYq9b+bf+Rvd3mDVmVXsvbqX+5fdn2NM06+acv1/16nqXRU3F9uvzTsv76SWX60cS32WhqreVfl1+K85tnWp28X6M1j70Fp8PXzpUa8H7q7utK7RmjYLtAttjwc/bu1XlV29SvV4pPUjALza9VVrMjbhrQQqf1TZOm7duXV4f5j1uUU3SUe8Pt7asLc0bL+83fp1u1rtAO3zd2Gql0MjQ/Fy96JFQAvrtjl75/DW5rdY9/A661Rs0N4DEvQJVPGqAsDvJ7X+GNnH3O4kASFEGYhL07L8526ey1GGV1iZL/Y1fHOXOQpNYpqRJfsjWAJ5JiBS0034eLphtqgkphmp4lO8pqCOZlJTcKEyR6/a7s7c79Pt+Hm6sebFHgyftwdXF4XQKf35Ze9lnu/bCNc8TuLLI5PZYr3SOXtUcL5j61f14eke2snerrf65ko+VPZ2x9/bg0uxqXy9VStr/2HXJZbs1zq0h88q2pu/2aItd6m65DypTXRfyjsDe/LlutzPQ1tNFZP1Rrw93HJ1+z8ZmcRvByL4dZ8WX8MAH1o1X8XMg19wvOtxPn0wmKUHIjgYrl2JeqFvEL8duMLNVNtXdaOT0ll6IIKlByK4t3Ut1h/XGoHNeKAVXRtWZd7WMGYOb21t2BmZHAXU42J8GFD8D92Zxv8ayt6LOZdvUzFSLwBUKpPi9g3fnlxP4sREKs2snGNcA/8auLq48sOwr/lkzyfse2Y2Senv4uHqQXWfrLnlZouZ6n6VuLfxAmvi5JVOaVRwd8Xf251LCZ/Rvn5FfCy9mLv5PAAfrD/NB+tP4+qisPz/ulKxgjuNa/iV+PFmUhSFsLislRu2h2+3OS7y9Ug+3PkhXx34KtdtNzzez/hKe/4kFKMxo6NZ8slAvLbsCKsO514lZsWhqwBsiPgYk0s0Kco/+JseByD8po4jVxJoe0flXPulmzJOGGxMiVp/LIo3fteSd+6uUghcXDqDK57uRX8ezhn2IKv2ZyVaO83YzkPd0+lQsytpRgNPdAvi7zNHOHPNhabVAxjYqmaOiiG90UCqIZ2qPvb7Gy2sRH0i/176l+71uud43SkqRVH4qP9HPLH6CS4laP1pzr14jiZfaUuuv7/9feaFzKNepXqEjgulmrfW3+aL/V/wyt+vWI9jmGJAUZQ8ExUllahPxM/Tz2YiAWBI0yG5tsW8EcPuK7sZ0iT3bbfK/nutVKES6VPScXdxZ/eV3fRc2DPH2MxkxNeDv+b5Ts8X5WEU2p9ntf4eka9HUsuvFqA1/S5M9dao30dR2682u57K6g1y/qb2HnP4+mFO3TjFG93eQFEUXtrwEvNC5hE3IQ5/L3+eXvs01byrSQJCCGFf0alaCfOR60fo37B/kffPbPxTydN5rhLY2/VEPUazhTuq2L6Sn32puk2norm7RQ2uJ+pJTDOy8vBVzken8O+ZGOr6e3E1XjvRe7RLPSYMbEYlL+2qREySnope7tarw+WVqmgl2Qu2aieQ43o1xGRW+XXfZQxmi3UFgdSMq+1mi8r0dadZcegqretWoneTAFQ172qC8iLNYKb5u1ojwVf7N2Zkh8I3ca3r782ycV0ZnW25ylnD29CveXXG/LCffRe1pODRK1lJnA7TN1lP3l/t35hX+zfJ9z4y+0qomOhcpzMHrmVVHFT388XdVcFoVjk/YxAnriXywLw9JKfnTkA89+shdt2yjOhT3Rvw4+5LTFyZVf3w69Nd+P6o1geimnc1WrWvyfD2dUlNNxERp6N5rYq8OaAZ49e9wB97PZjcZzyfb8nZwTxTZvIBYPKqrGUrVxy6ytF376GSt3u+J4zFcWvyIaLCCFQlnXEdLgLw0e6POPPCGSp6VmT/s/vo+l0f3NQAVCzUrngSgCfbPcmT7Z4EoKJnxVz34eriytCmQ3Nsq13Zy/r10eR5eCV05dfhz/BKv8Y8teigtRrDbFEZMV/rv1DUZNStMhuEPptR/ZC9k3yywfb0n1p+tbSllhVIdd2Jv0tXDEZ3gut5cjmjYMSiaNVAnWfknpJT3mU/2Zi86jgzHmht/f7W5MOAljXYeDJj6o/HRYyu58EMFiWBNK9f8UrTKkju/3o3Byb3IzXdTPjNVH7Ze5kAX0+6BGnvE9mvXO6/eBN/Hw9eWHLIus3Lw7kqSeJS0nnwu21ciTMwvKMXM4cV/fOEvRiNnvj76QoeeAsXFxdeGuDCgi1GjCZXFFxZttubZWjz/lcfDePw5cz38yusf7kHLWtnffbpPmcRNxPqMLyTG4906ETHwCr2eDiFciLmBMOXD+evR/9iYKOBJTpWz/o9ufjKRXZH7KZ5QHOqeFVh79N7Gbp0KPNCtCUul49cjqviiqqqWFRLjuQDgMcH2kWUR1o/wuLhi0sUjy1DfxuKi+LC1idsVxLaEuATwP3N7i94oA2ZK8X1qNeDhLcS6PtTXyyqhfub3c+07dMAWH1mNT8c/oGlI5bSpGr+79FFlZSeRB2/OtbkA2StOqaqaq6pc9lV8apCpQo5P6Nnjn9n6zsAbLm0hb8f+5sOtbUpZYnpifh7+dMioEWufW93koAQwgkk6BMI8g+igX8DR4fiMF1nah+4s58Y/LLvMlPXnODktIEs2hNu3f7szyH87+4mzNmUey5lZvIBtBLfxfsj+OGJjmw4fp0Vh67Sp2kAi57sXHoPxA5cTTnLLt8e1AxFUXiwU10e+34/sSnaSXT2D9qZVxIT04yM+yWU8NhUNr3eu+yCLobsJ8mt6xT9zblLw6r881ovAqv64OJi4c+zf+Lmcj9dG1a1JiBORmZNXcheOTB383m6N6rGWyuOMaBlTd4a2CzX8Q3ZEhC3Ns0ymA2sfK47287G4O7qgl8F7e3WVgXErcmHcx8MwsPNhce61mPwFzvRGy2se6kHtSt7Wa90+Vfwt4738XSjea2sk/Ft4Vu46XGW5/vO4rW7s1ZbiLip4921J9iWccLduk4lmw05g9//h2d7NsBg1KaMlXQKmKqq/HVCmwPetbGFfeczPtApWpPLzNc1dWrWyWD7Wu1RlTSMSgSbxmyymWwodjwZV7MURWHhk51JSTfRaurGHGM2n4qmT9MAdpy/QZ8m1YuUrLNYVBplTAHy9XQnzZjGwMUD6d+wPz3u6EGv+r3y3DdzubdYj4944s7/Ma33LPZc2cHajHMLs3Izz33LuwpuWYmgxfsjrAmIpFt6OYzr1ZBJg5tbv685uyYPNX0IXw9fzsSeYfuZSLyyjbeVjFkWkvGF6s7gz3fi5qpw7Gru5/q28M28Rotc28ur8ctWcyHaF3Bh6d50Zg5zXCwWszd+FYq36tL/+g7ifxmzZwbNX8Dpy3dYb8tKPmieXbyBeY90pYK7Bz8f2MfNBK2p5cqDJlYe3MtTA08yocfLxZ7iWhgW1UJ8WjxfHvgSgObVmhewR+Flb2bZtW5XTr1wioBPAnB3cae2X22aftWUG7rcq+Nkt+T4klJJQITFhRXropk9VKpQiUP/p32GUVUVV8WVRUcX8VLnl/h036esP7eeJnfaNwGhkjvJkLXsuSXPKV0AJ2+cJDE952vMh/0+5MGWD3L0+lHe2PQGG8M25jhmZi+f/df24+vha7fH4QwkAVHKVpxaQYuAFjQPsN+LlXA+dfy0N0x3l4K7d9uyNXwrYfFhtK3Z1p5hOTWT2cI7q7Urt5lXybOzlXyYMLCpdZWI6n6exCRrJ0BP/xRiHbPt7A2uJ+pJNZhoWM0HVYXzMSn4+7hT3a/0PuAUlvmWhnnrX+5hfcNsVrMiIVPuJj7VQN8526wnmtm98tsR69cvLDlEncpeJOgMJKYZmTu6HRZVxcPNpVyUJr+9Ujup/3hkG+5qVrxy1yYZpfRvb57MrN2z2PjYRl7o2x+DycK8bWH57jtqgXY1fP62MNsJiIwy77d6vE6/Vm/x5YEvuRh/kX1X99G4amNa161E67qVSDGksP+aVrmQ2QMiryaCT3YPtE6BaBjgy5npg9AZTHh7aG/Xmd24n1r7VJ4fOAcEDeB6ynU83XKuBlGvqjeLnuyMzmAiLCaV1nUrYTJbmLv5PKeiknBRYPPpGEBb0hRqZMTqzeWbqdSvWvQeGQCL9oQz7c9TAKyIeA7F0x0PFy22vK6subm4EfW/KCISI+hcx34JQVtXsHw93fj71Z4MnLvTuu2Zn7NeE3o1CeD41QRWPt+dBoXoExKbkm79emTHulxN0pJ/my9uZtOYTfnum/1D6Jy9c5h9z2z8vStyX5P7eLPbm+j0roxfaHvqVbln4ykfn2qg3XTtZ7LwyU70aRLApoubGL/ucyKTI1k5eiVJ6Un4efgxZ8AcUgwpjFo+mq3n3mR695XWqVT5OWWjP4pJicFNrY6r4mVjj/IrPC4eyHqOfL/nEM90K16DvJKISzWgqL50qFu1xMf66zmth0S8Lp1272sN+zzcVAwm7W818mZF7v/yVMbo3O/BM/9dzNTtb6GbpMPLXft9GswGXBQXu01N+Pnozzy55knr9/Ur17fLcW2p5l2NVaNXcUfFO/D38s+RfNg0ZhOnb5zmxc4vsuL0Ckb9Psp6m0W15DlVojjSjGlcS8659KajKIrCO73f4Z3e76CqKlO3TeX1f14nKiUKs8XM0KZD6R1Y8gsqKmqun+HQpkOpV6levtUPoK0Ykr3SDbTfZf+G/QlPCM+x/ePdH1vvL1OKwXmXpi0OSUCUIotqYeTvI3m317tM6zvN0eEIB7q/2f28/s/rVK6Qe65qSamqSr+f+/Fa19dyzMdLSk/icsJlWtdonc/eziku1cDD2UrrM339SHt2nr9Bg2o+rD4SyemoJGYNb83gNrXYfCqaocG1Gdm+LmZVpVYlL77dEcasv85waxP8zGqLW+2c0DfPKSBlITpJT9/Z26zff/JggxylqZn8fTxY+mxXBn2+k6d7NOD5PkH8HnqVdcciOXEt68P4+mNROfa7NZHz/rCWPH5noPV7vdFMuslinbJSmp5fHIrRrDIkuDYPdryj4B0KcPi6tpLGqtOr6NegHxMGNmPCwGYcDI+jTkaJfkq6iSY1/EhMM9Jj1r85pksM+2oX04a1IjIhjaAAX5rW9LNOwWhYpT5d69aja92uJKUncerGKbrW7cqR60cwmA3M3jObP06uox6/W/tZ6Aw5u/Nvfr0XR64kMqJ9HdJN6WwM22idSpCZfAiNDOXXY1pDsCXHl/B2j7dpVb2V9RhGsxFXF1d0Rh3e7nk/T7093GhdV3veuLm68MaArCqJZL2RbjNzPvY1B91Yc3Abm1/vRaPqRZ93fSgi64TZ5KKV2vdvNIgNj57Jd7+avjWp6VuzyPdXEFvJnybV/Xiye6DNxqA7MlaaeWrRQb56pJ3Nv7nskjKqXLo3qkqdyl6M+/MTAH4Y+kOBsb3a9VX+98//ckwd6Fi7I38+/Ge2UWXTEd7eUo05V3FK0hutyQeAs0lrOLIvhdf/ed26rebsmqSZ0qzJd18PX+5q0Ie/wzbwxclBvDVoCbo0f+J1BqYPa4WbqwtHryTwyabD7DqXc3rAwrEd+XnvZS6bv2TrtV+pl7aaNtU74EziknxIcznK+F5N+GmbFx+sjWJoKz3VK5Ztcjyz/9CQlsVb2csWf29PPn0kgOjkZJ7r3g+Au76cx8VruU/2PdxMvDmkAi9seA6jyyUGNhqIwWxg+o7pvNr1VXr82IPzcef5+9G/GdBoQIljuxR/yfr1j0N/LPHxCpJ9CkPsm7FsOL+B5gHN6Vi7o7UiYWSLkcS/FY//R1o1nOv7rrzY6UXGBI9hxs4ZPNr6UR5s+WCxY/gm9BuAcld5qygKL3V+iafWPsUne7TX1tp+te2SgLCollwVf8E1gwmumX//qbysP7ee0X+Mxt9L+x2NaD4CyLqQ4IyrGdmL4y9x3cYys1m3XoUS5dupG6fQm+y7Rnxm5rQwnXRt0Rm1D1Kf7f0s121ppjS2hm9l+PKcy2Ddu+Re2ixoU+T7fHvz2+yO2F3wQAeasf40ZzOWUZxyr1ZdtOjJTtzbphazRrTh/3oH8dcrPQmfdS8Pda5HxQruDG9fFzdXF6pXrECtStoJ57heQVyceS8f3N+K6cNaEvbhYAa0zLvR58SVx2j7/j90mrGZK3FFn/taEuuPRTFj/WnriavR9Qyj2uddOty8VkXCZ93LO/e1oKqvJ+N7B7HuJe1ncu6DQTzYseB+Cu+uOWldrvLvE1E0e+dvgqf9Y58HlA+90cyG41rJ/kt32afL92tdXwNgQegCaxktQKfAKtSu7EXtyl7WaolKXu4cnzaAFc914+V+jQE4ejWR+7/ezfOLDzFgrlbNkG7U/rb2X836e/Hz8MPLzYsxq8bQ7pt2dPm+C7+f+h0VPaBap2BkloN3blCFg5P706i6HyM71EVRFBYdWcSw34ZxMf6i9bgJ+gQ6ftcxx2NqPb81ree35qk1T7Hv6j48PvCg1pxafH/4e6JSovgm5BvMFjMnYk5gUS38dOQna0PcTFHJUdYPQaqq4lfBndB37qZToD+36v/pDnSGoi3zGp9qIN2oPWdVl1iGN9dep/JaHrG0VfGqYl0CLzsXF4WpQ1pycHJ/Avxsv2dfik3l3i92cTNbhYMti/ZoJytP92iAqqp8d+g7AMa0GVOoGLN3UbeoFnZF7LIuzbf0+FKCGjrPsm56o5kT1xKJTzWQrM/ZsLDNe1mvJdNHefHchnE5kg8AN9NuMrDRQEa1zLrSm7mSwNXkcF7Z3oM+rZO4Kzian44uRJmm0PZHf+5qd4loj0nEV/iYQ+/czfSRFblrWU0WRXRh6zUtiWdyiWTR7igCJ663rlhiTz/tCSc6qeifJZYdjOC5X0NJN+X8G7mRrMdkrEK3oMq8c8/9uLhrPTI6f7iFBpOXcTo6MtexEnQGFu7bT7tZX5OsL950CVsuxGqJxBoV7XsaMbxNZ2vyAeDfl57nq0fa4OHmQrv6Ffjn9XYZ72HDeKpTf0a37c6GRzbwx6g/qPxRZWbumkmN2TU4H6c1/xu4eCCTtkwqcVwGs/bc7RPYh5EtRpb4eEVR1bsqY4LH0LF2x1y3Va5QmeUjl1u//+rgV3T5vgtrz65l9B+jUaYprDu3rlj3m/k5OHuSu7x4ou0TLB2xlOPPaT2SCrvEb0GC/INyVRpfS7rG7ojdmC1Ff89ac3YNqcZUaxXcxB4Tc9yemZj4L7JLBYSiKOFAMmAGTKqqdlQUpQqwDAgEwoEHVVWNV7Qzsc+BwYAOGKuq6iFbx3V2SenalcbJ/05mUs+SvwCK0mcwG+jyfRdm9pvJi51ftNtx/730L15uXiXOxGe+CWaXZtQ+VNyaSd0VoXXiTTGkFHr+tMFsYNbuWczaPSvHfOzy5Gq8ztrPAOCZng15oltgiaYMPNY16wrLzOFtSEwL5bX+TfjrxPUcvSV2X8iaf93z463seLMv9aqWfkVEfKohRz+HFoEX2XXzE+B/xTqeh5sLH48M5p37WhB2IxWzxcLi/RHEpRp4a2AzBn2+k15NAtgbFsvdn+3Itf+8bRd44s5Aa5NCvwr2rYjITO58/lBba1IAtBUO/r30L7X9alO3Yl18PHwKXWLbsnrWUnvJ6babAN6qQ31/OtT3p2E1H15ddiTHbYETs65CH47eBzxs/b7tNzamSikqFlKJz1i9YE+Y1vfhuzEdqeSd8+eX2Qcg+4ly5lWuW52IOcGJmBOERoUCEJMaY71t/PrxjF+fc4k8dxd3BjQawM/3/8zmi5t58I8HmXPPHBL1iby/432Wj1zOqJaj+OqR9nT5MHclUIt3N/LxiDY82KlwVSnZr3Bfd/+Ap9rO5fWur1sfY1nb/8z+fG8P8PPk4OT+/LjrEu+vO2VzjHWFhTxkrlpiJoU5e38h+o1ojGbjLUtt5m3rE1sJ+CQAgBc3vMj8kPmA1iPj7M2z7Ly2ito4rvlgYVksKlNWn+CP0Kv5jps8uDlLzrxg/b5znc6sHr2avy/8zZCmQ6wrAGTK/ndhUS10+T73Ci2T/52M3vU6euBqyhkeX5+z78az7Z9ly0EXMt9SNxyP4oW+9lvS8EqcjqlrTzJ17UnCZ93Lp/+cpU3dyvRqEkDo5XjuDMo9dSFJr1VeZVbQJC86yC9Pd7FewNh/SUsevnfPI7i5uLF2/Aju+1J7n1fNvgz67DBwmLmPVuf+1p24mZpMh+mZr9+BtH7vXzo1jeL3J58p8ePbG3EMqIabW+mvxnJfmzvo37w2nm4uOcrgXV1c+eWBX6zfz+o3i4lbtBM8b3dv64Wbmbtm8lCrh2hTo/jVGgn6BAK8A4rUjLGsjGo5ileuvMLn+z+3efsza5/hymtXCv36k2lij4mMbTu2VKrQSspFceGhVg9ZL/Taq5Lg3d7v5tq25PgSJmyeQMrbKfh45D0Fr1X1VjSu0tjmba2rtw86fIYAACAASURBVOZ4zHHSTek5xmYuwxlcI7hUp/WUR/acgtFXVdXsnbQmAltUVZ2lKMrEjO/fAgYBjTP+dQHmY4/1vcqh7B9yIxIjirX84u0sLi2OYb8N440732BYMwd2UsrG3UVrGBaVHFXw4CJISk8izZSGl1vx5pvm1wQu84P8k22fzLH9wZYPcjjqcJGat916dTQ/R68kULNSBWqUcennD7uySiG3vtEHsO9SalV8PPht3J2A1sTwvaHaiWu6yUz3WVuJTUnn4c71WHoggl6fbGVcr4bWJpClZdOpaOvX97WpxfbEiSSboglPCCewcmCxj+tXwd26hF2H+lmdxDMbfX67I4wPN+Quk//477PWXhoAh9+5G387LmmaeTXy1p4DHb7twNHoo9bvX+78MnfecSdbL21l/n3z853/eiXxCtP6TGPqtqk0rmr7Q0JeejUJyPf2qj5Zc7Lzex6YlJtcvJGIzmDiUEQ8LWpVzJV82HF5BzsitJOGqJQoAnwCmLNnTo4x0W9EE5cWx/KTy+l+R3f6/9KfY9HH2DRmE3f/cjfDmg5jzdk1NmMwWoysO7eOe369hyuJVwCY8u8U0kxaIvPBPx7kWLVjVPWuyrjBx/h04018zX1zHGPCimME+HnSt4C+HJlTFwC8vG5QrwpOs8zYUz0a8FSPBvy67zJTVp/IcduhiHi+3XGR5/sE5Sh9j0nS50hUzT8yhVVnf6Nfg37WNeULI/tUvczkQ+Z7h4erByblerEeU1lKM5jpM3sr0Um5q0VueHxIgGESr/ZvzIj2ddGr19geW5W9T++lc53OKCgoimJd7eRWY4LH4OXuReMqjfH18KXFPK1iZEDQAO6seydbLm3B292b6ynazyl4gVY+vWzkMgYEDeDczXN0rN2RWns/ogJaJZihgKRSUSWnZ1Ub6I1mvvhXmxv+TI8GfL/rEute6kGrWxrrZq8IAdh14SbP/rKfA5fiSEpTrUsMB2b0IWlVpxL/TmjFrC0r+ftwNVws2mv4q4tjCLvrLFFpR4Gcr6EHz9YiJV2Pr2fJ3rfjMxr21vOvVsBI+yjMylRv9XiLB1s+SEhkCCNbjGRnxE56L9LK8oMXBLP/mf3F7ieTkJ5QKlNo7WXuwLk80/4Zlp9czvQd03PcFp0ajc+HPni7e3PupXOFWj70x8M/MnPXTPY8tae0QraLzM/G9qqAsCV7E8r85LdKRmZ8PRb2QJ2qkmZMIzo1GpPFhJuLGxfiLjgsKe8opTkFYxjwU8bXPwH3Z9v+s6rZB1RWFKWWrQM4u+xLbT299mkHRlI+pRpS2RWxi1+P/+roUKw+2v0RZtXMh7s+BCAkMsQu0zES9Vq5deY89KLK7Jpu643Dx8MHwxQD3w3VynzTjGm8vfltLsZfJMWQgvcMbx5d+SgrTq3g1A3bV/QyZSYgFg5bmO84ncHEsK93M+bHXfmOKw2Zc7SPv3dPoRrC2YunmyshU/oTPuteZg5vzUMZV4C/3XGRc9G5mwe1ePdv3v8z/593YdxMSWfCimP4erpxaeZgvnqkPTd1WiVG5hWe0jKuVxBhHw7m/WEtWfhkJ45OvYf+zXM/B9tN30T/T7fb7X7Db2oJiAbZEhBXk67mSD4AfHHgCx5e8TArTq9Ab9LnmLJwq5+O/sTUbVMBivw3XcXHg09GtuHOhrYbrnm7F26ancEljN0XEmnx7kZ2X7hJg+pYSzMz9V7Um+UntZLa4AXBRKdEs+eq9iFw7oC5WN61UN2nOs2qNePd3u/Sr2E/lo5YyoRuE+jfsD9pk9NYOXolE7pN4MwLZ3i+4/O80+sdZt89myk9pzDnHi2ZERIZYp1LnGZK483/Z+88w6I4uzB8z7L0piIqojQVRbFhwV6w9xJ7jz3GkkRNLIm9fTEajTH2WKLGrrE3LFix94YFFBVUbBSl7Xw/xp1lBREQWNC5r8vL3dmZ2TPL7sw75z3neaoMB6Bt8bYsu7AMx5mOjD44ijCTGbStlngG++tlp3kb++GS1AfPo+j2t86W9FHsjkQCXYZg0M5BfLXuK9ZcWZOi9Vt7OdLIU38GcODq8yw7HkjFKb5cfaRTPf91z02O35F+m9sHVWPzTek9UjvzmpTS+qsR0vuYGJkgCtHYW+vmj/45GZSq/Wc08RoRjzG7k0w+RAs3iTI6TpBZK8nm1igM9z/dWXV5FVYmVqgE1UeTuSZGJnQq2YkKjhXwsPfgyNdH+K3eb+zqvIuxtcays/NORlUfRW0XKXHWv1x/epbpSZvibbA1s6WCYwUEQcDCVPf9nXfoTqKWh08h6IWuHeLVG52rw+J3CfQzDx7w4HkUVx6+QhRFjgbo5u/CjP+gjLuU+N1/LYzXb6SbFyn5rsHSRPf5uOVyZmHb7wma3IVmpXRD6TkHbrPhhCUq4xBmttMvofcc6ytr0aSV12/jEInCzDj9Es/pgWtOV9qWaIsgCNRwrsH+rvsp5yDpfHgv9qbWsloM2jkIURRTdcPnlsNNz60iK+KZx5MJtSewr+s+XHO46llUxmpieRX9CrfZbina15lHZwiJCMHO4tNFRjMS7bkivSogRvmOounqpkm+x8cSEHde3NGz4k4Y15UnVxKte/zBce48l0R0VYLqo04nnxvpVQEhAnsFQRCBBaIoLgTyiqL4GEAUxceCIGhHrY7AgwTbBr9bpjflLAhCX6AvgJNT9qwc2H93P9Ym1oTHhOMX5Mee23vSRQzncyE6XhqcbLi2gVrLajGu1jhqudTK9DjWXV3HhmsbCI0MxS9IV25ec1lN/IL8mOIzhcoFK7Pu6jpaFG1BXbe6vI5+TeDLwBTPammTUecen8PH1SfVMWpnud+36YmOi8buVzti4mO4NuAaL9++pMrfVRJtv/ryalZfXq23bH/X/XgX8Ob0w9M8f/OciJgIarvWZlaDWVRzqsaAHQOYd2YedwbfwS2n/kVLa114KyT5Xuj0IuEADqBHFZd0L/tPLaOaeHDvWST+957TYJYfp0bVoeuSU7TycqRPdTeiYuL5+9g9xjT7NIs3yY0ARjX2SDQwT6umSGowUgl6QpQLu5bnQvBLWv+lPzNy+0n6KDiHv41lys4bmKhVetUBBX//cMl/2JswLKdIyYrL31wm6GUQjYs01vu8YuN136GkNAA+RtvyBWlV1pFJO67rteUACOgnIPqV6ycLeCUkysgPq3jd73/FtUn8dWsv4SPDefn2JUeCjiTaJt+MfLQoKlWINSrSKMmbsw6eHejg2QFAtqL7X73/ATC3ydxE67cv0Z6DgQfpXLIz/7T6h603t1LDuQZfl/kalxwuWEzRbyv67Wx/rI2bkyu2r97yYr/sZn3/ylRwycX7vP+bjTI6yRSfKYnWy2z+PP0nAJuub2Lo3qFUdKzIomaLEpX5a7EwUTOvSzm9lpuENPnjKKt7exMdr9FrNUg4u22k+vjsbUK0f+Nc5rl4/uY5v9T4RS6ftjWV9nvj7R/YMQCAX3fdoGul9C/f3XL+IXuvhfBX59QJNc47pJ9o+vWrUqz0D6JgLlPm3ZJE2CoXlPrZ99/V6VmUsC9BWqjmVI1qTtXk51YmVtRwroFvN1/JOu8Dn39eBz/uBZpipvEgJl7Db3tuMrpJ+lhy5jRzAKRWnOshTxK9Pm5LEON4P3EUS75Cs1jTaBp5LfNT4bdZWMbXJErlj6VGe/OrQm2UeOguCAJzOnkRq17J7nO6dq2aHmpaezlzLeQJi/10cXhN3kzAxLQLFEa81SCo0k9TIqOo41aH031Oo5ogzbceDjrMpdBLqAQVi84tImJURIqcIybXmZzRoaYbdd3qcneIlIxfcm4JvbfpWm7eF4JNisXnFjPvzDyaFGmSrq4aGYG52hzNGE26VaAGvQrixjP9qk/ZMvMjVRblHMol0vwzMUo6Qbe69Wo6beok79PLwStDqziyIun1zaoqiqIXUnvFt4IgfNjkmiRryRN96qIoLhRFsbwoiuXt7ZMvf82qjD4wmvCYcOLHxBMTH0PDVQ0NHVKWQtsLBdJFQTurmxGIoki8Jp6D9w5S7e9qtFzTkr/P/82d53dov6E966+t10s+9PXqK/s8H31wlJ7/9WTemXk0XNWQxecW4zzLGa+FXuwM2MmCM4lvNJKLIy08iXxCoZyFKJq7qN7yW2G3ZF2I4n8V10s+NHNvRj23epgYmVC1YFUqF6ist23df+rSa2svfFb40GZ9G3r814MGKxtQ1akq/934Ty793XJjC6N9R3P20Vnar/mW2r+vle0JAcZtvYrmfRuJdKZPApvMvjXc5LYIQ2JjZszafpXJ8e4mueIUX26GhjNt1w3aLzjxka1TzrHbz6jokotO3rpE7MwGM4HMSUC8j0ol4OWUk+2DqiV6rfiY3dwKTZm+wodYcUIalH+oJLqcQznccrrxV+O/kny95LySNP23KYN3DdZLOsRodL3Kow+MTlP1iNpIxbjmJbg3tTGnR+t68J3s9fc1v+l8wkfqPodupbsB8EZ1hm7VdUmVCKMDcswFfy9Ip02dAGlw8mb0G6bVmQZI/czRP0frzWh9Co42jnQp1QVBkErdWxRrQU7znHjYe2BubM6uzrsA/Zn4cPVWnhnPSLSvtvNPJDlzHBOv+/tpiMIxpxEjq49Ml/jTi0fhj9hyYwv20+35w/8P1l5ZS2x8bJIzo87JaL10WuzP10tPy89//UqqeHg6/ClPhiW++UwJb0a/4enwp5zre46+5XSJH20yOl7QXS+1jiX3nkUSF/+RWbqnESm+Dn239gI7L4fwJBVCipHRcfy2VxLM/L19aQKnNaFdhYJsHViN2R3KMq/pbFp7tOZh+EOE8QJ9t0vH9vCHh+nexiYIQrLJnxquZQg1HU6coLOejf3I55dS3sTq9tPj78sp2iba6Aq+3XdQqUAlXHM6sXdgF9rXOcaqXrUoXkwSEnyp/ifZfcxv14WAyY3oUTU/7gWeMa5hYwBalMmLm2MQB4ZXACA21pJR2zem5dAACH8roDZOX7HujEIQBA730FXovXj7gj9O/cGbuDd6ApWpaUHNLvQs25NdnXfJ7gsALda0YOWllfgHJ62H02dbHyDlormGRHsNSy+SaqNIaQuG/0N/Lofq/9an1JnCyV4nmdNojt7y9ys3Dgcd1rsH+RJIlwSEKIqP3v3/BNgMVARCta0V7/7XXoWDgYRTWQWAxNK92Zyzj87Kj0MjQjFWGeOaw5X+2/sns9WXxftl0Buub0j393j4+iEbr23EYooF6olqfFb4cOzBMf67+R+9tvai8JzCBH0XJAvBTPGZwuOhj1nQbAE9y/YEYGfATlmptlDOQmy7tU2uaJhzag79d/THfY47B+8dRBgv4B/sj0bU6A3yCueSxK1SOxOm5cC9A9x5cYey+fQrLrRKz862utmvX+v+ysz6M/mvw3/s7bqX6J+jOdrzKFs7bmVX5116PvTvX2BuPLtBhUUV9P4WQ/cOZcrRKZRfVJ4NN1ZxL1S/CmPZ8UCm7LzOufsv6LH0FHuvhjBs/UUa/O6XLomJV29iORUoDQx+bFiUkY2KffI+05OjPyWuaDkT9EJ+nFyZ+kf3HfCMyw9fUbOofhJWO8ttiASEFk9HW5Z0L0/z0vnlZVEx8dT/3Y/wt7GIophqx4TI6Dim75G0JZb2qCAvT5hI8PvajzuD7/BNhW+IHxPPvq77CBkaQtWCVfm5+s/yen+e/hOHGQ7cf3Wfc4/P6Z1vbobdxPeuL8P2DkuT97YgCNhbmzKqcTG2DqzCeJ9fEq1jZWJFXkvJUeXv5n9zru85EMCrUBRXxjfg6E+1QZA+nxdvdN+XnGY56ViyI2ZqM36q9hORoyIZ7D34gzMpGUHDwg0Rx4qJBBsj1Qf5qvpN7Kz0Y1l/JhiXETvostiff0/dJy5ew/0wXVLmgVk7KhWolCmxf4yidkVpV6IdtwbeYnq96fLyIbuH0GFjB0wmmVB5SeVE2+39vgZ/dkpZxVu7CgUZsX8Ea6+sxd4ybRMoZmozVIKKsg5lKWCjc6ypV6gebYq30UtAgNTyUvu3Q/y+/5a87NjtZ7KLjfZ5nRmH2XjuYapiefgy5TPdJ+/q4mpc0oFN1zchjBdovKox3+3+jv47+mNnbsf9V1J1QJwmjvP9zpPfOv+HdplheDl4AfDEZJy87OCNtCWM3ufGk3sfXeelpb44ubtTkJ7InZeDF7/W+5X6heqzo/tfbPveias/Jk4Cvo+xkYpxzcqyd2B3nHNJ37+S+Z04MGgAbnZ52DZYsuZefdSM+y+eERkdx5bzD1N8vX4TE09UhDMVnQqlaP2sgJeDF/UL1U+0/H/H/ofVFCtWXlqJ3a92+Cz34VG4/i3J5dDLWE2xklvjshOCINCwcEM2tNvA1DpTAdh6cytdN3el0pKkz8lPhj3hQLcDtPdsn5mhpol4TTx9t/VlZ8DOdNmfiJhIc61xkcZsbLcRS+PkW37jNHGJ2ihszWzxLuCdqOpy9IHR8vt9qXxyC4YgCJaAShTF8HeP6wMTgK1Ad2Dau/+1ilhbgYGCIKxBEp98pW3V+JzQzq71LNOTnQE7idXEcu/lPRacXcD8pvMNHF3W4P0BdXr3swe/DpbLto1VulnHNsXbcO3pNVkP4dzjc4T9mLj6oqJjRTa338zgXYPx6+EnDwx+O/4bOwJ20KJoC0ZVH8Xu27sJeB6AzwrpRjThSX1Oozm0L9Fetk9K603Eh05SO25JZcGXvrnEHP85qFVqhlcdnuS6uS1y07CwVIVz49sb+D/0p6l7U77z/o5c5rm4GXaTVZdXISDwW73fqLZUN8PdslhLttzYgpudPZvbFqbK3J8w1jihEi2x1FRj8dF7cm/roZu6E7DbqJ3sHFyd4vlTLoT5Po1nS2XpK3pW/KgYoCGwMlVTumAOLj54ybzOXpiZGLHa/z7+d8N4/TaOc0EvqFI4bUJdRwKeYmwkyOJjWg7ck2bO0ypqml7U8chLlUK5OXE3jKfhuoqmkgnE1AbWLkzBXOa0K1/wozMVe67qxPUSChx+v0ey0HS0dsTCWDcTrRJUso7B0Z6SHsm4WuMIfBnINzu+Yd/dfTjP0iXnnG2dCXolVVi0XNsSjajBWGXM1LpT5XXCo8N5Hf0aRxvHjx5/3xrJD8CP9TzGieATGKmMKJyrMFs7bKWCYwWsTNVYmuiSkY2LNObfK/8CcLrPab19WBhbGOzm3TOPJ+UcylG5QGW5dWHmGcl5pVf5Kew/I830a0Uaj95+xtHbz9h5+TFHEvS0I0Cnkp0yN/gPoP0OFrErwrAqw2hRtAV77+xl4C6d61FsfCzxmni9hLGp2ogmJR2YkftWspaNfsNr8+LNC/53TGqBae3RGgfr9JW5qutal81X9R1K/j4mnX+P3wnjyeu3GBup6LxYSiCdGOmDpamaNael7teLD17SrLQDpuqUJcQT/raTQxRFer2rVpvcypM9d3bw1Tpp5nXX7V3yeh08O7Do3CJ+rPIjP1T+gbxWH7Y+zkjae7aniF0Ryi0sx3PjReSK7UPQu8SZ362nsobJ7u+qUyxf6q5hD14+AVSIqpcIGkm8MFZ4QJjFSKzf9uaFegUX+vniPedbYlQ30QgRLKy76YP7EwSBknlLpu1A36NkficK5N1GcKgLo7ftRi0W4OD1SNadv8A/PRpjpEr+PH3tsaRH4uPumux6WQkrEyv2dNlDQFgA7n/qV5JFxkbSdbM0GXMw8CCOMx052esk3gW8efj6IaXmS+e5hOPI7Ej30t0Z6atfhXbu8Tk5EQew7MIyCucqTG3X2u9vniXRiBoWnVuEk60TjYs0TvX2MfExxGni5HFFUhUQhXMVlicRU8v6q+tpt6Gd3OLXo0wPAFmvKr20K7IjwqcevCAIbkhVDyAlNFaLojhZEAQ7YB3ghNQI11YUxefvbDj/BBoi2XB+LYrimSR2LVO+fHnxzJlkV8mSaL/I225uo/ma5vLyqFFRmBsb9sYhq1B6fmkuh15GRKSZezO2dtyaLvsduX8k159d51X0Kw4FHmJ+k/l0L9Md37u+cm+4KIoEPA/45LLmUb6jmHp0Kr/V+41/Lv2TSCivUM5C3HkhCc3Mbjibwd6DU/0ei84uou/2vvQu21sWm9x0fRMCUolp86LNP7KHj6MRNWy/tZ2m7k31Ss60j++9uIejjSMmRia8fPuSs4/O0nVzV1q7/I/tpxP3gCdk04AqOOWyILdVysT6tNwKDaf+OxvIrd85E6N5m6QXtqFpN/8EpwKfM79LORq+E6wLfxtLyXF7MTc24vrEtLVftVtwgjcx8Wx7r92h37Z+/HfzP0KGZR01/H3XQumzIvnz9O3JjVC/cywJi4jG1txYfh4ZHUeJsXsAWNytPHWL625KXGe7EvgyEL8eflR3rp6ieJIaaN749gZnH59l5aWVtPZoTZ9tfTjy9RGmHZ3GjoAdHOx+kNrLpYHXrYG3cMnhkqx1WWRMJEP3DqWjZ0dqutRMUVxaomKjZN2KZu7NWNd2HWFRYSlKfBiCMvPL6J/bRBXOb1N2vg4yb0r4yPBEGjaGQBgvDS4jR0XqJbN2395No1WN5OdfeXzF0hZLsTC2YGfATobuHcquzrsoaOPK+fsv+HXPTc4mqHQCsDFTc3Fsfe6+uEvhOdKANfaX2BRbxaaUR+GPePDqIe3/TPlsfbvyBVh3Rl9M9Pu67gyp+2FHGK3uxeRWnnT2TlpjYvj6i4S8fktAaAQhCVo1zv5cl9wzknZaEMeKvHjzQq4sNDTF/izGzbCbuERvoFPFQhirjPV0XrpWcmZiS88P7yAJuq3YhN81U7rWvcy0I3Oxix3EU5MJrGi9gC6buzDFZwojq49k2tFp1C9UH0drx0xNxMTFx+P+824+VPTQsmx+fmtTisKjd1PZI4R/u+uE1HutXovvJStOjqxNPtuMt6FOb/LPyM/jiNTPez74/oFeNVJ2JE4Tx8wTM/lp/0+A1GYXN0ZXqag9P94ceDPdWv4ykjhNHMYTjZlQawK/1Excifgxyi0sx7nH52Tb+Ul+k7j9/DbLWi6T1wl+HczVJ1ep6VJTrj5NCu1nl9DCvs/WPiw+v1h+frbvWbwcvOR1nw5/Sm6L3AjjBaxNrHk98nWqjyGrIQjCWVEUPzpQ/+QWDFEU74qiWPrdvxKiKE5+tzxMFMU6oigWeff/83fLRVEUvxVFsZAoiiU/lnzIzmizaM2KNuPekHv8VPUnzNXmvIp+9ZEtvxxO9jrJni7STUd6DE633NjClCNTmHZsGv/d/I+lLZbi282XfuX7YaY2o4l7E/nvIghCupxgJ9SegH9vf4ZWGcqF/hdY2HQhY2tKavudSnaSkw8A9dzqMffUXE4Gn9TTwPgYCSsg7r+6z6yTs+izrQ8zT85Ml+QDSLPJzYs21xMdSvjYNaerXMGRwywHddzq8GjoI5qVciDcaAePTAcwvUsMvaq5srxnRRZ1051/Wv91nPKT9hOfipaMS8Ev5eTDlm+r0nlzx0TqxO+z5soaLoZcTHadjCThzJG1mTHF8lnzJjY+xTOICdl4NphT957jk4TVoYio97f59div/HcjadvFzKJe8bwETmvCxbGJy1y1fDXvOCM3XSYqJo5yk/Yzcfs1RFFk3NarcvIB0Es+gFRmCchVAimhiF0RYn6OYWsH6SbZt5svRXMXpVPJTuzsvJOVlyT3nepLq7MjQLrR0iYfANz/dMdkkglbbmyRK07eJzwmnAVnF3zUXQakhPS2m9tkNWwjQfKw7+vVl7mN52KmNsuyyQeAn6r+pL9ASFn7z2PTH7jY/2KWSD4A/FbvN0D3ndJSw7kGfzT8Q36+8fpGbKbZoJ6opvma5gQ8D6DBygYce3AYbzc7Nn5ThXLO+jfQWwdWQxAE2e1oc/vN6Z58AMhvnR/vAhU+vmIC3k8+APy+/9YHZ+ASaiE8ScLNQsv6s8EcCXiml3wY0cRRL/mwtMVSrg64ysAKA7n/ndR6kVWSDwA7Okm//1gxnFUnHyYSmU0oLpoSLge/wu+alGzvXb4LO7v9TZ+64QQMuUTnUp3RjNHIeigjqo3Ay8Er06tA1EZGdKj4YYH3LecfUWi0VNZ+4no+YuLi+PXADo7cuY7vJStEITxbJh8ATvQ6we1Bt9nYTtLAWN5yOX49ku+/P9j9YLZPPgCoVWr6l9e1gseL8bKOmNatDUjUhpJV+VQbznOPz+k9/7nGz3rJB5DasBuuavhRjZDCuQrT0bNjkq9p7zVevn2pt662MqKoXVEaFWmU5LafK+l/ZVRIEpccLrQt3pZWxVrJfcFfOgfuHWDY3mEsbLYQ4JNntkVRpNXaVnrL8ljmkUW7Mgq1Sq3nLd2nnCTgM67WOADmN5nPqYenOP3otOxXDlI53PsnuqS4++Iu/bb30+1/Wx/23pFK3NsVT7uKdXrxJj6C5yaSYOXUYxMxVZsy4fwZAocEsv+HGtSdqbuw/7zlMhNbeMqz3kkhiiKuI3X9fBVdc1GmYA7sLexlBfikCI8Op+PGjrjmcJUVoDOb9ytXZ7YrQ+M/jlBh8n6O/FibgrmkAduBG6G457WmQM6kB3Cv38YydL2USBnkk7j0zy/Ij8cRj7kQcoEy+crIsxkxP8ckO2OfGdiaf/j9Lwa/4mLwK/49Jd2ELD8RxPIT+krwvzTVV6Hvv70/g70H45nHM9UuOcZGxjQr2kxvRkLLhyyvhngPIeB5gNxTqj2nzKg/g0aFG3Hj2Q2cbJ0ol7+cnER8X/k6KQRBoO36tgzxHsL/6v0PU7UpXUp1oUupLqk6JkPRsWRHHG0cqblMV+lx36wdsxrMZuZ/SbcYPDGZQIzqVqptKDOSDw1ULYwtGOQ9CBtTG3r81yPJde68uIPPCh8eD31MPqt8zOlYlirTDlAgp7meFkzb9W0BqbIloxi+dzhRKgssNBXpW8OFhX6B8ms1NlWnPgAAIABJREFU3O0Jfh5FlcJ2rDx5P9n9dF96Gi+nHLQtXxDHHLrKzLAInWjriTthfF8vZXH9UM+dbw5Ig+1aLrUYVW0Udd3qSi4Njed8ZGvDUChXIdZ8tYahq5JuA30TG8//dt/AztKE3tUT2xhGxcRRfMwenO0s+KZmIUZs0gnR5TS3oV6hetQrpPsA01tsM61MbOHJsaATBIUknfgUEsxRlpiwmtgYO/5CurbaWmecaHhG45xDquYplKuQ3rXhyNdHeBr5lN7beie62TSEQ1tGYWNqw4a2G2izvg0AppNMaebeDJWgokeZHkTGRFLdKWWVhoYmvW04kyKlIpRJtW9oeRMr6ejUWVEHcaxIeHQ4t5/fJjouGlO1KTfDbmaZ80JmoSQgMpFy+VNnZfW58zTyKedDzjP9+HRae7SmUM5PEzTac0c3g/pT1Z+YVnfap4aYLlibWlPHrQ4FbQvq9d8tv7icARUG6CUvkmLE/hHyY3tLe36t9yu5fs1F6bylGVhxYDJbZg5NijRhcMXB9CnXB/9gf9nyqcDvBbA0tmR8nePM8ZV6j/899YBboRFs/CaxVaiW8dv0Z5NX9fYG4GH4w0SzlhpRw8ZrG2lZrCVhb6QBUfsShhNOUr13AfFw0AkPVf/1IBYmRkTF6I5h3/c1KJI3sSXkxHefQffKzkkma7TCiVGxUfLsRbHcxTCZZMKGthv4qvhXibbJTN4/zlyWJjyPjElmC4kWZfLr6V0EvQyS7SzT02oL4OqAq4iiyMpLK/HM40kBmwJExUbJg9PLoZcZsHMAR+9L2hJD9w5l6N6h8vbiWJE3cdKgIrmyzITYWdjxJEoqm191aRX5rfNnm15bkKoENGM07Lu7j43XNrLw3EKG7O2DpXFtrOOaYipKLj25bV9y6e0oYlXJ3/waguH7JI2cD32Xupfpjo+rDz/s/YEN15IWRtb+5vLnMCdgciM9ybLQiFAA6rjWSbPocErYfWc3YSYPiNC4cy2iMlCfme1K09pLf5Z2RCMPRFFkwKpznA58TtVCuVnYrTy1fzvE/edR+N16it+tp8zaH4CLnQVTWpeknHNOnoRLFQ0eDjacCnzOlYev9KxFP8RXFawZIv1kWN16dbrrX2QU7T3bM9C6DOrXSdstzjskVTK62FkmqtDyvyfdrAaFRcnJh4pFotgdMhhL49RVT2QmRiqBfQN7ciLoFhbGJmy8eAmfIsVQG2k4H/yAOXt0N1yxMXZ62+4dmDU0XdITrZVrw8INZSviE71OfNCiNzvzVfGvuPzNZUrOk3RFtt3aBsDIaiOZUsfwdskpRUDA0tgyzRMvv9T4RU+g+tsd33LnxR12d9ktL0tpAuJp1FP23dmX5GsPXj/Qex4aGUpoZCjXn12nTL4yONk6ydURXwpKAiKTWXd1Hf7B/vxW/7cvLtv1Ptof/bqr62RrvU9hV4AkcnWg24EsOah3t3NHHCsSHReN2WTphmXOqTnMbTwXG9OkBa7OPDrD+mvraVS4Ebtu7yIiJoISf5VgecvlsrWfoTE2MmZ2o9kAuOV0Y8P1Dey+LZ28I2MjiTL5j7tTfmbmvlv8efA2Z4Ne4DJiB72rudK2fEGK5LFix+XHDPr3fKJ935zUEON3N+C3wnTq7tFx0fx1+i+mH5/O44jHmBqZ8k35bwCYdmwaapWaiT4TM/rQE6F6rwRCEATW9q1E+4UnAfRuygG6LjnFoeG1MDPW3ajsvvKY9WeDcbaz+KDdaMIL4rzTUvWJ1rv6RPAJgycg/EfVQaMBG3M1r9/EYWthTN2Zh7n95MOOE3/3KE+1wvoio1rxyYm1J2bI+VIQBLqWTtpqrGTekhz5+gjxmngKzylM4MtAvdedZznLSv7vK1x/iMK5CrP/7n6G7R3GjBMz6Fyyc5Y8VyWHIAjUL1Sfak7VWHhOql6LVB8kUn0QALWmAEHRIaCS+oqzomYLkEjpPCEFbQvy71f/MqfRHALCAvhp/0+cCNZZ6847PY8l55fwR6M/6ODZQV4uiiJ/+EttHD9W/THjggcGVRxEv+39eGN0ms23rxI2cabeeUSLlak0zPunl5TIDY0IxUgl4Pdjbb6ad1xPxyIwLIpOi/wp65SDeu9usg+HDSUPY2k65yjr+lWmouuH9X6G1Xdn751d1HSuSXWn6tkm+aClvLMDNy5LOvhPjadjHyslq6zNjAh/K527e684w8DahRnWQEq2RcfFM2KjftufhkhMc+7gfufrGZqESg9M1GpqFpKqzio46artarh5sOHUdh6/kL4/InEYGwmYGBlzfGRtcpinLOmaHTE3Nk/3hHdW5Pbz24mWaSt3swuCIBAxKvVOVlom1J6g9zwkMoTg1/pJw5QmICrkryBPSmhJ6GqTkM3tN+tVbHvk9uDF2xdJrvu5oiQgMpkzj84w8+RMepTpkW6KxlkNURTpsLED666uY1fnXbjkcOFZ1DM5u6wlOl7XV3r28dlEtpyp4cGrB6y8vJJJtSdl+QG9qdqUU71PcTPsJl03d8XK2ApzY3Nae7Tmn4v/MLbWWNmSTNtb7m7nzvmQ85SwL8GciDlyOVdWw8LYgl2dpUTQxmsbabO+DWMOjWFYlWF8V68QPaq6UH7SfgDZOaNXNVeWHNW3LGtRJj/T25TGRJ10q8avx35lzKEx8vOE3yWASUcm0bV0Vx6HP6ZU3lIZ32/8bpySlHi4t5sdS7+uwNdLTyd6LeT1W4r9spsqhew4fke/pHVqq5IfHAAta7mMOivqoBE1TDumX+njaK1fThv0MghbM1tymOVIxQF9GtZmutkIWwvp8ewOZfjr0B1qF83DsHftJY45zGWLv2qF7fX+3qIosvmGpG88xHtIZoWeCCOVEdcGXGPZhWUM2DlAXq5NPkDK9WsaFW7ESN+RzDghWel9rPopK5NQwDEhcSrd4O1i/4t45PbIrJBSRUINlaRQq9Tks8pHPqt8HO91HMsplrJTk/Y313FjR6Jio2TL5iG7hzDn1BwcrR2TtPxLTxL+zr/z/g5jI6larl+5frjmlKqIImMiUavUcovQsfvHqLa0GuvarKNtibas7yfZjapUkijzNyvPsftqCOfvv+T8/ZdoiOaN6gL2NvD0tSSK29rLERc7S3ZdCcHcWP8zrOFhROmF0mdxqMehDD3+jGBHpx1M9pvCmIO/AAIxcW15q7pENec2HL2pSx7/efC2nIDYdTmE0NdSRUyU6jgmYmFCTUbSudSyTD3npjdqIyP8hjXjnxNBdK7klGLHlM+Fzz35AOjZijYv2hwBIVPtnrMCKy+tJCo2ir7l+gJJt1GkNAHhe883UTXklDpT6FuuLwfuHWDQrkGJttG2jiSs4P5S+GQRSoXUMbTyUASED5Z2ZkciYyJ5FqWzXDsUeEg+sTVa1QiPuR5UX1qdduv19QreF2Gcfnw6qeV19GuqL63OuEPjeDz0MaNrjE7DEWQ+FRwr0MGzA9Ym1sw/O5/fT/5O9aXVWXhuIY4zHTGZaIIwXsDUyJTHQx8z78w8QiJCKJ2vNJA9Lo5fFf+Kla1WYmpkisUUCxqtakRuK1M8HPSrPd5PPkxsUYLZHcp+MPlwMeSiXvKhbXGp37pr6a6MrKZrcbn57Ca1ltci16/SjN20o9MQxgsEhAWky/ElhdEH/i61i+YhcFoT5nfxwjW3JaUK2JLHWqcb8H7ywcZMnax1p5EgDQbjNHGEROg7YYz0HcmKiyuY5DcJAJfZLlReUjlNx5OelMhvy9xOXrQpV4DbkxtxenRdjo3w4e6Uxlyb0CDJv/fNgTe58e0NrE1TVmGQUZgbm9O/fH9aFG2R5OsVHFMmCPh1ma/1nrcq1uoDa2YPFjZdyOJmiz/4egn7EgbXJHmfEvYlaO3ROtVOVC2LtUxyea+tkjuAwwwH5pySNA68C3h/WpApIKFgqYO1A+dDzvO/Y/+j7/a+8nKrqVayPXRsfCyXn0jtAVefXiUqNgpB0FVtCYLA/K7lWNNXsnzNZWnCc+P5IMQysHEYLcpISfFN5x4yc98trj9+zbn7upLh+2btKb3w09ooDY1KUDHm0C9SQlkQeWw2kBcmC9ly99ck1z95N4zv1l4AIF54xlPTKVg6TqNZ8Sqy5XV2xthIRc9qrl9c8uFLY1mLZfzX4T+2dNhi6FDSRJdNXVh/dX2atu26uauexppU/6Q/jqvrVpe9XfaSzyrfR/f3/kSqhbEFxe2LJ5qk+Hbnt/L7fakoCYhMJq9VXpxzOLPu2joevHrw8Q2yKNtvbUcYLyCMF7CaaoX9dHt6/tcT/2B/arnUokeZHpTPX54zfXQmJ+uvrWfVpVVYTLZAGC9wMPCg3j7TUgFRdkFZjt4/yt8X/s52/VNqlVpuG3ifWE0sIHlS57PKJ99waj+jj83eZRU6l+pMx5KSKvD+u/sJjQhl5+Bq9KrmmshrfJBPYe5NbUzXyi5J7uuHSj8AUGZBGQCqO1VneJXhLG+5nI3tNlI2X1km+UwicEgguzvvJuC5LtFw4sEJWX/D/U93jCca47XAK5GmxKfyscRQQ08HDg6rxdaB1fD7sTZ9qkszlSXy65IyfsNrc2lcg2T3s/Wm5OyQVOm/rZkt3bd055eDv8jH16pYK+6/us/ph6eJ08Rx78U9/IKSV/3OSNRGKuzfJWBUKgELE/1ivPDocGaemIlKUFE0d1FDhJgIQRDY0G4DwyoPw9lWZ0lYx7VOiisg8lrlRRwrcqbPGVa3Xk1B24IZFW6m0KdcH3p59ZKTgCZGJlz55goX+1/k+Y/Ps2T5eVqTt3Mbz2VCrQmJlncv3Z0pR6boJQJXt16d5vhSipOtzsHgr9N/ERkTCUjXiLor6mI2SZqJO/7gOPPPzGfmiZl8s0O63jhYOfDnqT8Z5Tsq0X4rudlxb2pjzv5cl0i11M8cEvGY2R3KMreTF8XyWWNjpsbLKQeWJtLf95XFBEQhUt5H2I/ZV6CwTXFJmO90H6libVLtSVQqAi/Uf/NCvVRez2XEDjq8a60DeGbVn9cjXlMyT0n+avJX5gatoJAGzNVSEjaXefI26lmdf6/8q28R/QkkVQGR3zo/9QrV+2DVX3Isv7AcYbwgn3sHVxwM6FxGMlI8M6ujtGAYAG0vsdMsaQCxreM2mronby+YVei8qTOrLyc9uFp6YSlLLyzlybAnLG2hu1BH/xzNqYenpBsiMV7ukdp8YzOBQwJxme0CpD4TeCHkAndfSIrMSancZwcm1J6Aj6sP/g/9GXtoLCXzlOT5m+d4OXhRJFcRenlJs2vahMPUo1OB5PuXsxo/V/+ZnQE7eRL5hNvPb2Nvac8vTYvzS9PiTN11nQWHpb9hJTe7D94czPGfI88uavH7WncD3dqjNSB9Ls45nHHO4YxnHk+O3j9Ki6It5JO9raktr6JfEaeJ43zIeQ4GHqSuW92MOOyPYmZsxOgmxRndROq/jYnT8OpNrHxjnhyPIqTj8VnhQy2XWkyqPYmwN2HkMMuh51Jw/MFxQPreaL870+pMY+yhsXxX6TtqONcAJEHYv8//zfCqw4mIicDUyDRFzg4ZxY1nNxi2bxiFcxWmcK7ELiCGQq1SM73+dKbXn068Jh71RLUsCJoayuUv91mJEq9ru+7jK2URrjy5wpUnV3gb9zbF4qEgWQ93KtmJMYfGUChnIdleefnF5XrrrflqTab8dnKZ56JN8TZsuLaB68+us+DsAioXqMzD1w+591K/qkw7+NVy/dl1ZvtLuj2T60xOlNAWBIEXb3T9yNeeSa2ATUo50KSUvq5D1b+rUlhtje+7t3w7+q1Bzx2fyvq2upnUwCGBONk6ERUbhe89SZhPLebBOr6J3jYPzDozs840rE2t2dDu86luVfi8KZa7GECWb1v+GAJCut3Iezt645rDVW/Zg1cP8H/oT/1C9T+o1/Yhjj04BugmD7XteloSJpIL2mTvCYnUkj2mUT8zfLv56vUGau3esipPI5/SYUMHhuwaIicf1rZZy9o2aznc4zCaMRp8u/kC8HuD37G31BeSMzEyoZpTNbZ13EbLYi0JGBRA86LNKW5fHCdbJ7Z33A5IVRWx8bHce3GPb3d8y+vo16y7uo5H4Y94FP6ILpu64B/sL+9XW3J1rOexzPgYMgRTtSkNCjdgTM0xiGNFLn1zieAfgtnacSszGsyguL10c6qdSbQwtqCDZwcK5co+pa6FchXiUv9LlM1Xlvuv7tNhg060zd5KN1B930FCiyiKDN49mFhNLFYmVhirjDnfL7Fg5fs42jiyqf0mupfpTvOizfHr4ceLn16gGaORy6kvhlxklO+oLKGpYaJWpSj5ALqseURMBIcCD1GlYBWaF21OpQKV2N5xO8d6HiPm5xhqLKuRaNsRviOIjo/mf8f+J1cxlfirBCN8R7Dp+iZK/FUCs8lm/Hb8N73tHoc/ZuDOgbRYk3QbQnqiFcfKSsmH9zFSGXGh3wU9tWyFrM+0OpJ+Q1oGrIVyFeJkr5MEDArgyNdHEr2+oOkC2ntmnguPtl+7SZEm/HvlX648ucK9l/fwdpRaQEZUHZHkdocCD8mPnWc5I4wXmHh4op71oLaio4BNAXKa5fzg53X8wXF87/nKNsmfUw+5cw5nBEGQJwIARPT7wIPMWqERXjGkkuF0ahQU0oJaJc1Bp3claGYjCEK6tTKMrD6S3xv+rrfs+IPjtF3floevHya7bQGbAonaLLVodd20k2HadbX3S862ztk+EZRalAoIA+Dj6sPCpgtpt0HSRDBkKfSH8L3ry9H7R7n/6j7+D/25+vSq/Nq4muNoV0Jfz8HH1eejVQjaMmUbUxs2t9/My7cvEQSBJu5N8MzjyZUnV2iyugn77kpln4IgMPf0XL19rLq8iqhRUZgbmzO6xmi+Kv4VXg5e6XHIWRptC0Zu89wsar7IwNGknrxWeTnX7xxV/67K8QfH8Q/2x7uAt+xwASRqydCitYma3XA2g70Hp+n9jY2Mqe6s87Xe3H4zsfGxmEySBstTj07l17q/MufUHP796l+qOlVN0/tkFgnFkE73OS1XjpgYmdDEXTc790uNX9gZsJM1bdaw49YOrj+7jl+QH8Xti1PHtY4sqvg06ikAHTZ0IF6UBiPD9w0nJj6Gey/uMch7ELNOzmLpBamy6XDgYcrnL8+buDc8iXwiJ8rSC20C4lOdcTIarSaLQvbhUweqWn2HUnlL6S3f3nF7pvf95zCVJjKauTdjR8AOPOw96OTZib7l+sr2bq45XbEysaKZezMarmpIvCaewz0O03JtS3bf3i0rvo85NIb2nu1Zcm4JddzqUDJPSe4MvoOduR2nHp4i72958e/tLwtcvs/TqKcEDgnMFvpEqcUtp5s8vik6ZiPRCe7XarhUZknzJQaKTEEh7Wiv25dCL+mNj7IbKkGVoa0MKRWhFMXE+hHauF69fQVA49WNEceKvHz7kgshF4iMicTSxJKgV0FyxeqXgpKAMBBVClZBQMC7gDcng08yeNdgZjecbdCL986AnTRZ3YR2JdrpqeNqccvpxoFuB3DO4ZzE1qlDJaj0+s4u9r+IgIBqgu6GNKFFUDWnahy9L5mL77u7j7mn5zKtzrQvIvkAMKvhLLpv6Z7t/aiXNF+Cx1wPKi2pRGuP1rQoqJtlN3qvHutt3FviNfFy8qu3V+90jcXYyJhhlYfx2wkphh/3S7Z5Lda04NmPz5Lb1GC8iX3DoF2DWH9Nqv5Z0XJFsjaHE2pPkG2m3p+hE0URG1Mbph2bRueSnfnl4C+sb7ueum51Kb+wPD/X+JmRviMJfh3M4vP6QoPPop5hNVWne/Doh0fparl3/dl1CtoUTLVQoILCx9BqwXzqtdbG1Ia+Xn1lK9KEib/MYkaDGQyvOhx7C3sOBx1mbM2xsmaK9tqoVXcHOPr1UTSiBiOVEbs670IURQ4FHsJnhQ/13Opx7vE5+Tw4qOIgeUwSGRvJ06inuP3hxqJmi7A1tWXSkUnExsfqxZMSkbbsTnSMrm3nlXodWztsxdbM1oARKSikDe2k4Kc40GUFHKwcUqzD9D4z688kThMnP++yqQshESHs77ZfXpbSBESsJpYN1zewpEXihGRkbKTe84iYCM6HnOfyk8tUKlCJMvnK8CTySZqOIbuiJCAMhKONI5qxGpZdWMbJ4JPMOTWHoZWHpsvNfWoIiwpjwdkF9C3XlyarpQHUlSdXaObejG23ttGrbC8m1p7I8ovL6V66e4b5emt/4Kd6nyLwZSBtirchPCacB68e8CzqGTVdpL7252+eY/erHQC1nGtR1qFshsST1ehWuhvdt3TnwesHWE+1ZnGzxZla6pteaHsOATZd38SL5x6A5NCgEXXTSieDT1J5SWVqONfg8jeXMVObpUkA6GNMrz+dUdVH0WFjB0rYl+D3k78zunrWdFKJ08RxIvgES85LFzdLY0u6lu6a5v0JgkDnUp3pXKozACOq6cq1bwy8AUCRXEX4/eTvrL26lupO1VnXdh0Wxhb8eepPvX1tubGFWi618LD/dMtFjajhYfjDz0ojQSHrkR46OnMazyFejKdyAcO4zJipzXDJ4QLA6q8+LnwpCIJcTad9Xtu1tjy7n3AAPOfUHL4u8zVlHcrSslhLvB298X/oT59tfdjecTuXQi/J617od4Hi9sWznONJRvNGdVZJPihkW7Q27+/bmGc3Ar8LTPO231f+Xu/5y7cvEwnapzQBUSF/BR5HPNZb9iEL+F2dd9FoVSP5ubOt80f3/7mhJCAMTEfPjnz9n9QzdO/lvUxPQHy/53v+ufQPxXIXo7h9ca49vcbWDlvl0mftLFHCm5OMpIJjBdnSzsbUhhJ5Sui9PvPETPnxj1V/zJSYsgLnH5/HwtiC8vnLs+ryKr2MbXYj6Lsgll1YxthDYzn18AS53yUg+u/oR+0ibsw4MUNe1y/ID888nhkaT07znOzpsgdRFKlcoDKvo1/zw54fuPviLouaLUqkaZIU2luZjLJU0ogaGq5sKAsgVchfgeUtl39kq0/Hu4A3a9qsYU2bNXrLteKVWgbsHEDZfGU52P3gJw3IEyYYAwZlnF2qgkJ6VBuaGJmwuPmHbUizG3ks8/D8x+csPrcYH1cfvXOv39d+9N7aG1MjU0rkKUGb4m24FHqJUnlLfbGtSD6uiTV2FBSyC1onutfRrw0cieH4w/8PImIiGFVdcgTSiJpE14aUJiB2BOxItGySzyQGVRzE9lvb5ZbXhGhbNP67+V+a4s/OKAkIA2OqNuXyN5cpOa8kKy6uoLpT9Uy1LtMKTc07M4+rA64Sr4nPktZpWnKa5aSOax02t9+cpeNMb5r924yo2Ch5QJhdbDiTwsnWiR+r/siMEzOIi9NVPVx+cpFzzzbrrXuu77lMi0sQBNqWaEvXzV1ZeWklIN1g5DLPRdl8ZSlgU4DGRRobpE3qQsgFfO/5Mq7mOOI0cWztuDXTY0hINadqRP8czZUnVyi3UKpUOB9ynlLzS7G85XJqudRK037/u6G7CGdlAUqF7EvpvKVxzuH8WYklpic5zXMyvOrwRMtNjExY0WqF/DyhW8SXSvuSbQ0dgoLCF0/b9W1pVLhRIoeJlDBkt9Saqk1AiCTWcajuXJ3jPY9TxK5IqvdvYmRCQdvE7aQdN3aU3+9LJfvexXxGeObxxN7CnqUXljJ079AMfz+NqKHYn8UQxgtyCda6NpLmQ1a/qf+h8g/s7boXa1NrQ4eSqWj/LlqV8uwu9GWmNuPlTy+xNk3YVqFhRNUR1HapzcX+F4n7Jc4gLTbja42XH9uZ27Hg7AL67+hP03+bsv/ufq49vcbcU3Mz1b9Ze14YUGEA/3XIGplyEyMTvBy8+Lv53/Ky+6/uU3t5bRxmODB873CcfnfiTewbzj46+1GnkXhNPLvvSI4SmZl4UviyyO7nToWsg6mRMoenkH3R6rClVT8hq7ArYBdXn1z9+IopQBTFRNeIXOa5qFywcpo+p/ln5iOMF+RK91HVpESHts0jM8eRWQ3l7JlFCB0Wivuf7sz2n83vDX5Pl0HS4cDD5LXKS6GcheTezNj4WErPL83NsJuAdOK5NfDWB/uUshqCIKRL7252Q1vxMPnIZL3n2RlBEGjl0YJdp6Xn+7ruoWZhd8MGhb7iuX+wP/PPzpdfa7O+jVyuOP34dG4OvJnhnvdH7x/lUOAhSuYpmaJ2kMymR5kePHj9gLGHxsrLQiJCZHFPtz/c5EqrmJ9jMDYyRhRFftjzA93LdKdMvjKERoSSb4YkYNeiaIsvRttFIfO5EHKBCyEXiI2P/eI0CxTSFwfrPIYOQUEhzVQpWIW5p+dS1K6ooUP5JNLThrOOax2iYqP0lgW/DmbfnX00cW9CHsvU/ebPPdafTEmo3WZraou7nW7MWzJPyTREnH3J/ncxnwmCIFDTWRJanHZ0Wpr28eLNC3zv+jLHfw7CeIFay2vhMdcDk0kmtFrbilZrW2EyyYQupboAUNSuKJN9JqeprEghc9EKh1mZWNHHq0+WtydMKZ55dKKFjjb5DRhJ0ngX8OZg94Nsab+FPl59GFp5KDPqSxoVQa+CcJnt8sEM9qpLq7jy5Monx7D43GIsjS3x7eb7yfvKCARBYEzNMQR/H8ziZouZ32S+3uva5AOAySQTll1YRkhECLP8Z1F2QVl+PvCz7EwAkuOLgkJGMan2JEOHoJCNUdtukx+75CxgwEgUFD4NtUqag87OmmIgCQqnVyXB8KrDGVtrrN6yK0+u0HNrT+6+uJvstrktcjOgfGKdB4AcZpJl8s1n0uSvnbkdnUt2lieV8lrmNZiYsaFQKiCyENPrTWfJ+SWMOjCK7yt/j5na7OMbJaDdhnbsv7s/yde23NgiP25for3c76SQPdC2YNhb2LOw2UIDR5N+eOb1AE4BEBP/Bsh6pYBaPYMWxVrIy36o/APD9g4jThNHg5UNMIvTibRqL4QEaAgYAAAcpklEQVRdNkuJPm01RVrpUqoLNZ1rZsnqh4Q42jjSy6sXACeCT7D8YtIimdpSRC3aqh6AxkUay6r+CgoZwZfcc6vw6USqjmBKMwByWyk6IgrZlzL5yuDt6E0Bm+ydSEvPCoikSKkI5du4t0TF6VdPaMeD2paLdhvaIZYQefH2BX73/Xj59iU5zHIQGhnKnjt7MiD6rItSAZGFyGmek/lN5qfZD/Zy6OVEy/Z31U9IVMhfASdbpzTHqGAY/mj4ByBlST8n4hLYP916fsOAkaSe3+r/xveVvmff3X2ceiglUXyW++Ay24VnUc/S7X3qutXl67Jff3zFLIQ2+aCdbV7RckVyqwOwtMVSRdhOIcP55eAvgKIFoZA2yjjoHD8eRwYZMBIFhU/D3c6dk71PZnsr2cK5CpPbIneatl3WYhlLmi+Rnzde1Zjay2vrrZPSBER+6/xsur4pRe+rETVceXKFCyEXAPBx9SFWE5ua0LM9SgVEFqNf+X70K9+P0b6j2Xt3L6f7nE7xtj3L9mTq0anMajCL8vnLUz5/eUzVprz46QXRcdFEx0cryYdsSoPCDbA2sSbgeQDCeIHN7TfTslhLQ4f1yRy5fwiQ9EeMs7gAalI453DG0tiSV/FrMI3xIFZ1l/uvIll9eTWA3oUtLewM2IlapaZ+ofrpEW6m4d/bn6jYKGo416BTyU645nSla+muXH1yFc95Omu/3Ba58czjyaHAQ7Qp3gYLY4tk9qqgkH58iVpCCp/O+FpjaXftNqAT8VNQUDAcZ/ueTfO23ct013seHR9NbLx+IiClCYiSeUrKbS1a8lnlS3Ldg90PUnt5bblCwt7CnmCT4FTFnt1REhBZkNj4WKYcnQJAdFx0ikTuRFGkulN1VtuuxsnWiapOVeXXtL1HCtmbyT6TidXEcjDw4GchQglgbKRLOqiNsl8CAiBkWAjWU625b96SKgWrsKfLHrbc2IKZ2owqBavIJXapJV4Tz4j9I8hpnjPbJSAqOlaUH7vmdJUfl8hTgmfDn3Eh5AK7bu9ier3phMeEExAWkO2VuBUUFD5/zNS6tgslAaGgkL0Ze3Asr6Nf83vD34GkXTBSmoDYeH1jomXjao1jaJWhrLu6jn7b+8nL30+Ar726Nk3xZ2eUBEQWxEhlhK2pLa+iX7H3zl6aFW0mvxYaEUpeK/0y/Mfhj8k/UxLw29B2A608WmVqvAqZwyDvQZx5dAb4fGbvTNS6pEN2rIAASRj02oBrvI5+jXcBbwBqu9Tm7uC7lJpfisK5CnOi14lU73fWyVlcfnKZxc0Wp3fIBsXOwo46bnWo41YHABtTG8rlL2fgqBS+FMo5lCOfVb4sbzmtkDUxzqaJcgWFz5UWa1rg4+LDkEpDUr3tBL8JALoEBGKi8XX5/OW5/M3lNOlTGamMyGGWAxMjfb2Y+ivry+/3pfJ5TKN+ZqgEFSHDJOX4E8EniNfEA7Do7CLyzciHX5AfAP2390cYL1BhUQV528ZFGmd+wAqZwu3nt3kc/hj4PGw44b0ERDYe2HnYe8jJB5AEGR2sHXgW9YyTwSd5E/smVft7GvmUYfuGYWFsIQs7KigoKCgYFhO1Mm+noJCVOHb/GLfCbqXLvpKqgLAyscIzj2eaqjRnnpiJMF6Qxbcn1JISHjHxMfL7fakoZ9IsipnajDmN5hCvicd5ljMPwx/Kr628tJKAsAAWnF0AQOl8pXkY/pAjXx/B3NjcUCErZDDV/q6Gg7UD8BklIIx0pyDXnAUNGMmnseLiCrpv6c6Bbgeo7aoTMNrTZQ8NVjZg2N5hzG0yF4CImAisTKySvNBp0f7eh1YemvHBKyh8QZx9LPULa0TNZ3MeVcg8cpnnNHQICgoKCUgPFwzteKxF0RaJXnsc/pj119bTomgLnHM4J7sfI0F/Iu3GM31x9SbuTeTHhXIWolTeUvLzGs410hJ6tkVJQGRhBlYcSJwmju/2fKe3fNG5RQS9ktSXvR292dFphyHCU8hkVIIKewt7fqj0w2djVehh7w5I3soFcqRNxTgrsOjcIgCiYvUtmGq7SMmIv878xeUnl3ka9ZRbYbfkXsJFzRbR26u33ja3n9/GxtSGyT6TGVltZCZEr6Dw5TC25ljGHx7/2bSxKWQuCTUgFBQUDI9KUH1yJYFG1GAkGPF95e8TvRb4MpAhu4dQ1K5osgkIKxMr+nr11VumjcvEyISY+BjOPjqLl4MXlsaWtCjaQrZXtzW1pUzeMp90DNkNJf2fxVGr1IQMDWHNV2uY23guDQs3xEgwYmS1kdRyqcXcxnMNHaJCJmGkMqKgTUFmNJiBh72HocNJF1xz6lxZ3sa9NWAk6cP7M6rGRsayE8aR+0e48eyGnpBRn219AHgW9Yxj94/x076fKDKnCIX+KMSo6qMUq0AFhQxC+W0ppAWNGGfoEBQUFBIgIHxUIPJjaCso4jRxctu7lpSKUEbERPA06mmSr2lbLvpulxIUkbGR7AjYwZPIJwC8in7F+mtflg25UgGRDchrlZf2nu0BGFBhgLy8lkstA0WkYAhUgooYTQzh0eGYG5snsvvJjsRqouXHj8If4ZbTzYDRfDpJCdv1LNsTUyNTumzukuQ2wnjlRkhBIbMYf3i8oUNQyMaISAmI58YLgSbJr6ygoJDhlMpbCidbp4+vmATbOm4DdK0TtZfXxsTIBN9uvvI6KU1AVC5Qma03t6bofc3UZtwMu8m5x+doWLgh7Uq04+j9o2k5hGxL9r+DUVD4QlAJKo7dP4bNNBv2dd1HXbe6hg7pk7n+9LL8+P3euezIh3rKO5fqTPOizTE3Nmf37d34BfnhbucuV0AkxLebLz6uPhkdqoKCgoJCKjE2UhNk3tTQYSgoKLxjb9e9ad62qbv+bzmpVo6UJiDccroRGhmqt+xDLRsHux+k8pLK8vuZqz+PScXU8GUdrYJCNmaKzxRuhd1i3OFxn414monaWH6cnW3x7MztAMht8WEdC2tTa0C64Gkvei2LtWRXwC5aFmtJaGQoN5/dVJIPCgoKClkU7U1C2+JtDRyJgoLCpzJo5yAiYiNY1GwRapU6SRvOlCYgVl1elWjZ6OqjGVFtBP9c/IeeW3vKy99/j+UXl6f1ELItSgJCQSGb0LFkRw4FHoLDiU9e2ZUcFsa8VV3nlXotRkLKSteyIvOazGN8rfGUzlc6VdvltshN19JdASlBUThX4YwIT0FB4R0VHSuS00xxMlBIG0YqI4K/D5bF4xQUFAxLk9VN8Hb0ZkzNMane9s/TfwIwt/FcKQGRhDtZcfviBA4JTNNvXhAE1II6kUtHpSWVAD7ZvSM7oyQgFBSyCVeeXCEgLAD4fGw4zdQmhJoOB7J3BYSDtYNskaqgoJB1+VyStwqGw9HG0dAhKCgovONS6CXyWub9pH1oWyGSqoAwVZt+1H7zQ0w8PJExh3SJkf/V/V+S7/sloiQgFBSyCSXnlZQffy4JCG05awfPDtia2ho4mrQz6+Qsvt/zPSd7ncS7gLehw1FQUPgA/g/9DR2CgoKCgkI6ISB8ciWBtr2iS8kumKpN9V57GvmUhWcX0sqjFcXtiye7H207rpYHrx/oPU/YYlu5QGW98WLLYi3TFHt25fO4i1FQ+ILwyO2RZsXfrIajjSOLmy1mss/kRCf97MSWG1sAeBP3xsCRKCgoJMfo6qM/mwSugoKCwpeOIAhpqiRIuI02gfFtxW/p7dVbb72nUU/5+eDPXHlyJdn9GQlG9CvXL9l1DgUeAqRJRB9XH1k3zNTIFPdc7qk9hGyNchVWUMhmjKo+Ks3lYFmNHGY5KGhbkKCXQYYORUFB4QtBacNQUFBQ+DxIawVEwm20yYjX0a+JiInQWy+lIpTxYjyBrwKTXWf4vuHyvtZeXUvw62AAouOj+fvC36mKP7ujJCAUFLIZMfExxMTHGDqMdCEmPoaGKxvy3Z7vDB2KgoLCF8DkI5OJF+MNHYaCgoKCQjpQqUAlitoVTfV2AgLHeh7Dv7e/7FJWZ0Ud2m9or7deShMQzdybsf3W9hS9t72FPbef3+bMozMA9PXq+1lY0acGRQNCQSGb4GzrTNCrIHpt7UUJ+xKfhdZAWFQYIiKXQi8ZOhQFBQUFBQUFBYVsxJo2a9K0nSAIVClYRW9ZUq0cKU1A5LXMi5WJld4yj9weSa67t+teyi4oK7+fIHy6jkV2Q6mAUFDIJixoukB+/Ln0MGtFKM3V5gaO5NMoYFMAABtTGwNHoqCgoKCgoKCgkBzxmni6be5G67WtiYqNApJ2wUhpAmLx+cU8Cn+kt+z7yt8jjhVZ1mKZ3nLte2iTDgvOLuBJ5JM0H0t2xGB3MYIgNBQE4aYgCLcFQRhhqDgUFLILDQo3oE3xNgCYGJkYOJr0IbdFbgZXHMyZvmcMHcon8WfjP7k96Dal85Y2dCgKCgrJUKVgFeq41jF0GAoKCgoK6UD9f+ozdM/QVG8Xp4njn0v/sPnGZl0CQhQRBP0EhLOtM2E/htG+RPukdiNvlxyRsZF665ZZUCbV8X5uGKQFQxAEI2AuUA8IBk4LgrBVFMVrhohHQSG7MKfRHJq7N8czj6ehQ0kXBEFgdqPZhg7jk8lhloMcZjkMHYaCgsJHUAQoFRQUFD4f7r28J7tJpIaELQ/a6oakKiCMVEbkMs+V4n0lZJTvKKYenSo/n91wtl4lRVrcOz4XDKUBURG4LYriXQBBENYALQAlAaGgkAz5rPLRtXRXQ4eh8B6/HPiFSUcmca7vOco6lDV0OAoKCv9v7/6DrKzOA45/HwkmaIoDBAyyKGg0UaoV3bLWpFQTK1YdjTVxbDqtKWlsJprQP5xgxk5im7GtjpGpJpNEp47BiTUdbUbS+NsxY6IiUCWLCAqokRXlhyw/BNwFPP3jvuBVdpddlsu7+57vZ+bM3j33fc/77HnY5c5zz3tuN55c+WTZIUiS9pMgWLBqATMemMHFJ1zM1KOmsmrzKq7/7fV7HPulE79ES1MLr7S/wo1P3bi7/5rHruHqz1zN15u/vsettBvf2cjMR2fywtoXmPzx917fnXvsuUz7xDTat7Xz3V9/F4CjRxzNqxteZdbTswD4xdJfvG+sea/PY9lby4DappWfnfhZZjwwA4DpJ0/nweUP8sCyBwC46vSrGH/Y+P5Oz4BVVgFiHLCy7vs24H076kXE5cDlAEceeeSBi0yS+ug3r/0GgA3vbCg5Ekk9mfnpmcyaO6vsMCRJ+8Hp40/nvhfvY3brbCaNmcTUo6bSvq2d2a2z9zi2pamFlqYW1m5dy13P37W7/54l9zB98nS+eupX9zjn4CEH88Tvn+C1ja+xaM2i3f3jDxvPtE9MY8v2LdzZeiejho3iprNvYt3Wdbuv3bGjA6itkj3r6LNYv209v1r2K0YNG8VXJn+FEcNGMLt1NqOGjeK8486jdXXr7nOnT55uAaIBuloD+b51KCmlW4FbAZqbm/NdoyJpwPvgPYOSBi5vw5Ckarjj83fs0TdpzCTaZ7Z3e86UcVN6fL7esKHDeOGK7hfoNw1v2mOs3o7d1bHf+vS3en3uYFbWJpRtQH1ZpwlY1c2xkjSg3XzOzZwx4QxOazqt7FAk9eD6J6+nY2dH2WFIkpStsgoQ84FjI2JiRBwMXArMKSkWSeqXEw8/kccve5xhQwf3x4lKkiRJjVTKLRgppR0RcSXwEDAEuD2ltLiMWCRJkiRJUuOVtQcEKaX7gfvLur4kScrL1KOmclCUtfhTkiSVVoCQJEk6kDp3dr7vc9glSdKBZQFCkiRl4dk3nqVzZ2fZYUiSlC3XIUqSpCx8Y8o3OGToIWWHIUlStixASJKkLHTu7HQFhCRJJfIWDEmSlIVb5t1SdgiSJGXNFRCSJEmSJKnhLEBIkiRJkqSG8xYMSZKUhTMnnMn2d7eXHYYkSdmyACFJkrLwdufbbOzYWHYYkiRlywKEJEnKwtJ1S9ncubnsMCRJypZ7QEiSpCxMnzyd4R8eXnYYkiRlywKEJEnKwsaOjWzq2FR2GJIkZcsChCRJysIdC+8oOwRJkrJmAUKSJEmSJDWcBQhJkpSFg8KXPZIklclPwZAkSVn43MTP+SkYkiSVyAKEJEnKwrqt61i1eVXZYUiSlC0LEJIkKQttm9pYu3Vt2WFIkpQtb4aUJElZuGTSJYwcNrLsMCRJypYFCEmSlIU3336T9dvWlx2GJEnZsgAhSZKycO+Se8sOQZKkrFmAkCRJkiRJDWcBQpIkZeHQoYeWHYIkSVnzUzAkSVIWph41lXVb15UdhiRJ2bIAIUmSsrBy00pWrF9RdhiSJGXLWzAkSVIW2re1s23HtrLDkCQpWxYgJElSFs4/7nzGHDqm7DAkScqWBQhJkpSFVza8wpota8oOQ5KkbFmAkCRJWXh4xcNlhyBJUtYsQEiSJEmSpIazACFJkrIw+pDRZYcgSVLW/BhOSZKUhZamFl7f9HrZYUiSlC0LEJIkKQvL1y9n6bqlZYchSVK2vAVDkiRloXNnZ9khSJKUNVdASJKkLJw54Uze2fFO2WFIkpQtV0BIkqQsLFm3hFWbV5UdhiRJ2epXASIiro2I1yNiYdHOrXvu2xGxPCJejIhpdf3nFH3LI+Lq/lxfkiSpt55a+VTZIUiSlLX9cQvGrJTSjfUdEXECcCkwCTgCeDQijiue/iHw50AbMD8i5qSUXtgPcUiSJEmSpAGqUbdgXAjcnVLqSCm9AiwHphRteUrp5ZRSJ3B3cawkSVJDHXnYkWWHIElS1vZHAeLKiGiNiNsjYkTRNw5YWXdMW9HXXf8eIuLyiFgQEQvWrl27H8KUJEk5O2XsKZw45sSyw5AkKVt7LUBExKMR8XwX7ULgR8AxwMnAG8D3d53WxVCph/49O1O6NaXUnFJqHj16dK9+GEmSpO4sWr2IRWsWlR2GJEnZ2useECmls3ozUETcBvxv8W0bML7u6SZg17bT3fVLkiQ1zNAhQ8sOQZKkrPX3UzDG1n17EfB88XgOcGlEfDgiJgLHAvOA+cCxETExIg6mtlHlnP7EIEmS1Bst41rcB0KSpBL191MwboiIk6ndRvEq8A8AKaXFEfHfwAvADuCKlNJOgIi4EngIGALcnlJa3M8YJEmS9uq5N5/jtY2vlR2GJEnZ6lcBIqX0Nz08dx1wXRf99wP39+e6kiRJfdW6urXsECRJylqjPoZTkiRJkiRpNwsQkiQpC8d/7PiyQ5AkKWv93QNCkiRpUJg0ZhIRXX0iuCRJOhAsQEiSpCzMbZtL26a2ssOQJClb3oIhSZKyMOIjI8oOQZKkrLkCQpIkZeGkw09iy/YtZYchSVK2XAEhSZKyMLdtLi+3v1x2GJIkZcsChCRJysKK9hVlhyBJUtYsQEiSJEmSpIazACFJkrLQfERz2SFIkpQ1N6GUJElZOGbEMWzq2FR2GJIkZcsVEJIkKQvPvfkcL731UtlhSJKULVdASJKkLPzk/J+wcuPKssOQJClbFiAkSVIWzphwRtkhSJKUNW/BkCRJkiRJDWcBQpIkSZIkNZwFCEmSJEmS1HAWICRJkiRJUsNZgJAkSZIkSQ1nAUKSJEmSJDWcBQhJkiRJktRwFiAkSZIkSVLDRUqp7Bj2KiLWAr8vO4598DFgXdlBqOHMc/WZ4zyY5zyY5zyY5zyY5zyY58HhqJTS6L0dNCgKEINVRCxIKTWXHYcayzxXnznOg3nOg3nOg3nOg3nOg3muFm/BkCRJkiRJDWcBQpIkSZIkNZwFiMa6tewAdECY5+ozx3kwz3kwz3kwz3kwz3kwzxXiHhCSJEmSJKnhXAEhSZIkSZIaLqsCRESMj4jHI2JJRCyOiBlF/8iIeCQilhVfRxT9n4qIpyOiIyKuqhvnIxExLyJ+V4zzzz1c87Ji3GURcVld/3URsTIi3t5LzKdGxKKIWB4RN0dEFP1fLK79bkS4K2ydiuX5exHRGhELI+LhiDiiv/NTBRXL8bUR8XqR44URcW5/56cqKpbnn9fl+NWIWNjf+amKiuX5j4rYFkXELyNieH/npyoGaZ67PC4ipkbEsxGxIyK+sK9zUkUVy/PXit/lhRHx24g4YV/npUoqluMvR8TaeO//57/f13lRH6SUsmnAWOCU4vEfAC8BJwA3AFcX/VcD1xePxwB/DFwHXFU3TgAfLR4PBZ4BTuvieiOBl4uvI4rHI4rnTivieXsvMc8D/qS45gPAXxT9xwOfBH4NNJc9twOpVSzPw+uO+Sbw47LndyC0iuX42vqYbNXM8weO+T7wnbLnd6C0KuUZmA/8WfF4OvC9sud3oLRBmucujwMmACcBs4EvlD23A6lVLM/1r8EuAB4se34HQqtYjr8M/KDsOc2tZbUCIqX0Rkrp2eLxZmAJMA64EPhpcdhPgc8Xx6xJKc0Htn9gnJRS2lVBG1q0rjbTmAY8klJan1JqBx4BzinGmJtSeqOneCNiLLU/fk+n2m/J7LrYlqSUXuzTBGSiYnneVHfood1cPztVyrG6V8U8F++UXwL8Vy+mIAsVy/MngSeKx48AF/diCrIw2PLc03EppVdTSq3Au3sbIzcVy7OvwbpQpRyrHFkVIOpFxARgMrVq2+G7/lEWX8f04vwhUVtCu4baL8UzXRw2DlhZ931b0ddb44pz9vX87FUhz7uWjQF/DXynD+NmoQo5Bq6M2q02t+9asqj3q0ieAf4UWJ1SWtaHcbNRgTw/T+2dUoAvAuP7MG42Bkme1U9VyHNEXBERK6i9u//N/TVuVVQhx8DFxWuweyLCv9kHQJYFiIj4KHAv8I8fqG72WkppZ0rpZKAJmBIRf9jVpbo6tQ+X6e/5WatKnlNK16SUxgM/A67sw7iVV5Ec/wg4BjgZeIPa8nzVqUied/krXP3QpYrkeTpwRUT8H7WlyZ19GDcLgyjP6oeq5Dml9MOU0jHATOCf9te4VVCRHP8SmJBSOgl4lPdWcKiBsitARMRQar8sP0sp/U/RvbpYUrlraeWa3o6XUtpAbR+GcyKipW4TkwuoVejqK2lNwKoeYhtSd/6/FOc39fZ8vaeieb4Ll/PuVpUcp5RWF/8BvwvcBkzpbcw5qEqei+M/BPwl8PPexpuLquQ5pbQ0pXR2SulUaoWmFb2NOQeDLM/aRxXN89146+RuVclxSumtlFJH8e1twKm9jVn77kNlB3AgRUQA/wksSSndVPfUHOAy4N+Lr/ftZZzRwPaU0oaIGAacRW2jlWeovYu567iRwL/Ge0uqzwa+3d24KaWd9ecXY2yOiNOoLW36W+CW3vysOatSniPi2Lql2hcAS3uKORcVy/HYuvsSL6K2hFtUK8+Fs4ClKaX65fvZq1KeI2JMSmlNRBxE7d3SH+/t58/FYMyz+q5Kef7Aa7DzAG+do3I5rn8NdgG1/SzUaGkA7IR5oBrwGWpLdlqBhUU7FxgFPEbtD8tjwMji+I9Tq7ptAjYUj4dT2/n4uWKc5+lhN3NqyzGXF+3v6vpvKMZ7t/h6bTfnNxfXWAH8AIii/6LivA5gNfBQ2fM7UFrF8nxv0d9KbZnYuLLndyC0iuX4TmBREcMcYGzZ8ztQWpXyXDx3B/C1sud1oLUq5RmYQW1H+JeovQiP/TFHVWiDNM9dHkdtR/82YAvwFrC47PkdKK1ief4PYHHxMzwOTCp7fgdCq1iO/63I8e+KHH+q7PnNoe36D1OSJEmSJKlhstsDQpIkSZIkHXgWICRJkiRJUsNZgJAkSZIkSQ1nAUKSJEmSJDWcBQhJkiRJktRwFiAkSZIkSVLDWYCQJEmSJEkNZwFCkiRJkiQ13P8DSTY+PqUKoRUAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -4488,42 +1647,65 @@ } ], "source": [ - "fig, ax = dataset.plot_analysed('CODtot_line2')\n", - "ax.legend(bbox_to_anchor=(1.3,1.0),fontsize=18)\n", - "ax.set_ylabel('Total COD [mg/L]',fontsize=18);ax.set_xlabel('')\n", - "ax.tick_params(labelsize=14)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Calculations" + "fig, ax = plt.subplots(figsize=(18,4))\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/1':'2013/1/15'],'g--', label='data with drift')\n", + "ax.plot(data['2013/1/4':'2013/1/12'], label='original data')\n", + "ax.legend(loc='upper right', shadow=True)" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 50, "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Calculate the daily average of a certain data series" + "dataset.data['CODtot_line2'].update(data['2013/1/1':'2013/1/14'])\n", + "fig, ax = plt.subplots(figsize=(18,4))\n", + "\n", + "detrended_values = signal.detrend(dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'])#, type='constant')\n", + "line_segment = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] - detrended_values[:]\n", + "line = line_segment - line_segment[0]\n", + "line10=10*line\n", + "dataset.data['CODtot_line2']['2013/1/5':'2013/1/8']+= line10\n", + "\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/1':'2013/1/15'],'g--', label='data with drift')\n", + "ax.plot(data['2013/1/4':'2013/1/12'], label='original data')\n", + "ax.legend(loc='upper right', shadow=True)\n", + "\n", + "asd = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8']-line10" ] }, { "cell_type": "code", - "execution_count": 36, - "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:07.830400", - "start_time": "2017-05-09T11:55:07.433945+02:00" - }, - "scrolled": false - }, + "execution_count": 51, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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" + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -4531,31 +1713,176 @@ } ], "source": [ - "dataset.calc_daily_average('CODtot_line2',arange=[dt.datetime(2013,1,1),dt.datetime(2013,2,1)],plot=True)" + "fig, ax = plt.subplots(figsize=(18,10))\n", + "ax.plot(asd, 'm--')\n", + "\n", + "\n", + "detrended_values = signal.detrend(dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'], type='constant')\n", + "df = pd.DataFrame(detrended_values, index = data.index[len(data[:'2013/1/4']):len(data[:'2013/1/8'])])\n", + "\n", + "line_segment = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] - detrended_values[:]\n", + "line = line_segment - line_segment[0]\n", + "line10=10*line\n", + "#ax.plot(line_segment)\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/4':'2013/1/9'],'g--', label='data with drift')\n", + "#ax.plot(df, label='detrended drift')\n", + "\n", + "detrended_values1 = signal.detrend(dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'])\n", + "df1 = pd.DataFrame(detrended_values1, index = data.index[len(data[:'2013/1/4']):len(data[:'2013/1/8'])])\n", + "line_segment1 = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] - detrended_values1[:]\n", + "ax.plot(line_segment1, 'c--')\n", + "\n", + "b = df.iloc[-1][0]\n", + "a = line_segment1[0]\n", + "slope = (b-a)/len(df)\n", + "f=[a]\n", + "s = df\n", + "s[:] = a\n", + "ax.plot(s)\n", + "for val in range(len(df)):\n", + " a+=slope\n", + " f.append(a)\n", + "\n", + "ds = pd.DataFrame(f, index = data.index[len(data[:'2013/1/4']):len(data[:'2013/1/8'])+1])\n", + "\n", + "ax.plot(ds, 'k--', label='Slope')\n", + "ax.plot((s+ds)/2, 'r*')\n", + "#ax.plot(df1, 'k--', label='detrended drift org')\n", + "\n", + "ax.plot(((s+ds)/2)+df1, 'k--')\n", + "#ax.plot(df1+ds, 'r--')\n", + "\n", + "ax.legend(loc='upper right', shadow=True)\n", + "\n" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 52, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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fMGvlLIa3HG5r69Koi+04OTOZLSe2FLsuMyeTJ5Y+wYrYFTWS0yo7T+0kKTPJ6hgiIiJ2ocKDiIiI1LiUrBQAZq+dbWubPWJ2kT6HEw8Xu65g3Yc5G+Y4MJ31luxfYnUEERERu1HhQURERGpcalZqkb8BLv/08iJ9StrBoqAtNjHWgelERETEnlR4EBERkRpXuOBQmhK30yxhpwsRERFxbio8iIiISI3LzMkst09JhYe6IjIo0uoIIiIidqPCg4iIiNS4m7reRHTTaAB6hfUqsU9JO1sEeAXQNLApl7W8zKH5rNYnvA/tQ9pbHUNERMQuVHgQERGRGjegxQBeHv4yAJtPbC52vmVQS67qcFWxdjfDjdYNWhPqF+rwjFa6ocsN3BZ1m9UxRERE7EKFBxEREalxe8/sxcPNg66NupY4pSLufBwHzx0s1p6WlcbgiME82OfBmohpmd+P/M70ZdOtjiEiImIX5RYeDMNobhjGMsMwdhuGsdMwjAfz24MNw/jFMIy9+X83yG83DMN40zCMfYZhbDMMI6rQvabk999rGMYUx70tERERcWb//O2f3PnjnWy7e5utLdg32HaclZtFqzdbFbsuLTuN51Y9xx9H/6iRnFaJORZDWnaa1TFERETsoiIjHrKBR03T7Aj0Be41DKMT8ASw1DTNtsDS/NcAo4G2+X/uAOZCXqECmAH0AXoDMwqKFSIiIlK3ZOVm4enuWaRtXPtx5V5XsJ3my2tedkguZ7Hs0DKrI4iIiNhNuYUH0zSPm6a5Kf84CdgNhAPjgY/yu30EFEzEHA98bOZZBwQZhhEGjAJ+MU3zrGma54BfgKIbdouIiEidkJWThadb0cLDvC3zyr2uYDvNY0nHHBFLREREHKBSazwYhhEJ9ATWA41N0zwOecUJoFF+t3DgSKHL4vLbSmsXERGROqakEQ8VUTDiQURERGqPChceDMMIAL4BHjJN83xZXUtoM8tov/g5dxiGEWMYRsypU6cqGk9ERERqkcIjHqb1m2ZxGufTNrit1RFERETsxqMinQzD8CSv6PCpaZrf5jfHG4YRZprm8fypFCfz2+OA5oUubwYcy28fclH78oufZZrmO8A7ANHR0fpaQ0RExAVNHzzdtpvFv0b+izkxc0jNSi33ulC/ULo17uby22l2a9wNL3cvq2OIiIjYRUV2tTCA94Hdpmm+WujU90DBzhRTgP8Wap+cv7tFXyAxfyrGYmCkYRgN8heVHJnfJiIiInXMkMghDGs5zPb64qJD/+b9MWcU//7BMAwigyJpEtDE4RmtNKX7FCZ3n2x1DBEREbuoyFSLAcAtwDDDMLbk/xkDvAiMMAxjLzAi/zXAQuAAsA94F7gHwDTNs8AsYEP+n5n5bSIiIlLHrD2ylm3x20o9v//s/hLPn884T8ugltwTfY8j41lubdxanvrtKatjiIiI2EW5Uy1M01xNyeszAFxWQn8TuLeUe30AfFCZgCIiIuJ6pnw3hV5Ne/H5pM8BaN2gNfvP7bedj0+Jp/vb3YuNekjJTOGN9W/QIbQDA1oMqNHMNWll7EqycrOsjiEiImIXldrVQkRERMQezqSdIcQ3xPa6cNGhLAXbaf7zt386JJez+P3I71ZHEBERsRsVHkRERFzY4n2LSctKszpGETm5OZxLO0ewb3Clry3YTvNsmmZrioiI1BYqPIiIiLio2IRYLv/0ciZ/N9n2gd0ZJGUmYWIS5BNU6WvN4jtxi4iIiJNT4UFERMRFuRl5P+bn75pPg5caWJzmgoIdLPw9/S1O4rw6hna0OoKIiIjdlLu4pIiIiNR+iRmJfLj5Q/7W829WRyHYN5jFNy8u8uG6kX8jTqacLPfaZvWacWmLS3F3c3dkRMu1C2mHl7uX1TFERETsQiMeREREXNzN3W4G4O/f/51xn4+zjTiwio+HDyNbj6R5/ea2touLDhM7Tiy2o0WBiKAIWtRv4dCMVrs96nau73K91TFERETsQoUHERERFzckYgh3RN0BwA9//cDCvQstzXM69TTzd80vUmx4YsATRfrsPrWb3w8X39nhTOoZvNy8iA6LpsnsJiw9sNThea2w/uh6nlz6pNUxRERE7EKFBxERERfVNLAp8dPiubHrjbx2+WtMHzQdgKeXPW1prp0nd3LN19ew8+ROW9u49uOK9Nl9ejcDPxyI8azBrlO7bO1JmUl8sOUD9pzeQ3xKPGnZzrVjh70s2rdIC2mKiIjLUOFBRETERbm7udPIvxG+nr74efrxzJBnABgcMZg1R9aQkJ5gSa6UrBQAfD19bW2e7p6l9l8Vu8p2XLA7x5yYOQDEJ8c7IqLlYo7FWB1BRETEblR4EBERcVEJ6Qk8/dvTbDq+CQDDMIh9KJZx7ccx4IMBNHipAfvP7q/xXDHHYnAz3GgX0s7WdijhUKn9+zTrYzu+eBSA1etViIiISPlUeBAREXFRiemJPLfqObae2Gpra1G/Ba0atLK9tmJ3iBnLZ5Br5hLsG2xrG9N2TKn93Y0LGQtGPBQoPGpCREREnJMKDyIiInVMh9AOtAluA8CdP95ZY8/dc3oPr6x5he6Nu9OzSc8i5/w8/YgKiyrxur1n99qO3Yyiv7oUvA9X06VRF6B4oUVERKQ2UuFBRETERZW1OOHyKcsJCwhjyf4l9Hi7R43sdDFj+Qym/TKN/0z8Dyv/trLY+es7520fGeoXWqQ9xDfEdtyyQcsi5wY0H+CApNaLqB9Br7BeGIZhdRQREZFqU+FBRETExZX04TW8XjjHk48DsDV+K2lZjt0dYnv8dr7a+RUAXed2JSUzpdScSRlJ3BN9D8unLAcgx8wp0q/w1AsrporUhPt638eEDhPINXOtjiIiIlJtKjyIiIjUUfW869mOH/z5QYc+6/V1rxd5XVIx5OtdXwOQkZPBtpPbmPDlBABOpZyy9TmedLzIqIfPtn/miLiW23B0A08te0pTLURExCWo8CAiIuKiWtRvQeqTqdzc7eYSz2+4fYPtOD4lnjfWvcHZtLMOyRLgFVDma4C3r3jbdrz68GrOpZ8DIDkz2dZ+PuM8+87uw8/TD4DMnExHxLXcN7u/AcqeLiMiIlJbqPAgIiLiotwMN3w9ffFw8yjxfLuQdpx49AQA2bnZPLT4IaZ+N5WYYzHEJ8fbLUdObg4L9iwo0ubrUXw3ip5hPXlu6HPF2n08fGzHBR/EC7bRzMnNKdbfFWyN31p+JxERkVpChQcREREXdSb1DA/9/BB/HP2j1D6NAxrTJ7yP7fUPf/3AJe9ewuB5g+2WIz4lniPnjwBw8MGDzL9mfqmLJpbUPqL1CNvxxVMPLl7/wdVoqoWIiLgCFR5ERERcVGJGIm+sf4M9p/eU2W/BdQu4seuNRdp6hvUspXflmKbJjd/k3XvG4BlEBkUyqdOkUvsb5BUeWgZdWMeh8GKSF089cNURDyIiIq5EhQcREZE6LiwwjE8nfspvk3+ztR08d5C+7/XFeNao8od70zSZs2EOK2JXAPBY/8fKvWb90fVA3iiJAhuOXViL4uJpI50adqpSNmfXvXF3vN29XXbXDhERqVtKnvQpIiIitV5lh+kPbTmUwRGDWRG7wlYAADiYcJA2wW0q/fx7F97LqsOrAPj5pp/x9/Iv95rXL3+dka1HciL5BLNWzgIurOcAeetSXJzZFTUOaIyvpy9uhr4jEhGR2k8/zURERFxcwfSFiph7xdxibYcTD1f6mWlZacyNmcuOkzswZ5iMajOqQtdFBkVyzyX3EBYQZmu7eMSFv+eFAkaumVvpbLXBY/0fY3Sb0ZpKIiIiLkGFBxERERfmZriVupBjSTo27EjsQ7FF2ubGzOWyjy+r1HP3n9tfqf4Xm797vu248JaZH235iNbBrW2vZ6+ZDeQVJ1bFrqrWM53JhqMbmLF8Btm52VZHERERqTYVHkRERFxU6+DW5EzP4eZuN1fquhb1WxR5vXjfYn47+FspvUvWpVEXAAa2GFip6woUfl7hUQ1x5+PYFr+NZ4c8C1wYDfHx1o8ZNG8QG49trNLznM1HWz8Cii+mKSIiUhtpjQcREREp1SN9HyHAK4CZK2eSa+ZWas2Bs4+fxcfDp9oZ6nnXsx2fzzgPwIzlM4AL22kGegcC4OXuVe3nOYM/z/xpdQQRERG70YgHERERFxWfHM+t/72VdXHrKn3toQcP8dd9fzF75GyWxy4Hik55KM+dP9xJ8MvBnEw5WelnA9zZ607b8fgO423HSZlJRfoVjIYoWEjT1RZjrOwCoSIiIs7ItX46i4iIiM35jPN8sOUD9p+t/HoLEUERNPJvhNtMN1bGrgQgIzujQtceSjjEO5veAaC+T/1KPxvA2927xPaCEQ8FCkY+LNm/BIBt8duq9DwRERFxHBUeREREpEQXL0p59093M2TeEOLOx5V5XUO/hrbjIJ+gKj179+ndtuMXVr1gO24a2LTE/uk56QBk5WZV6XnOJiosiiYBTfD2KLkAIyIiUpuo8CAiIuKiqrsw4cWjDj7f8TkrYldwy4JbyrzuwZ8fBODLq7+s8rM/HP8hb1/xNgD//O2ftvaXR7yMOePC+4oKiwKgdYO8nS4KrwdRmwX5BNEmuI3LTR0REZG6ST/NREREXFxlttMszMvdi0f6PsJtPW8r0r780PIypzQcSjjEgOYDuLbztVV6LkB4vXDGtR9ne13atpJZOXkjHPo16wdAY//GVX6mM5k+aDrDWw6v1LoaIiIizkqFBxERERflZrhR37s+nm6eVbreMAxeGfUKfZv1LXau+9vdOZt2tsTrkjKTCPAKqNIzCyv8bX/B+hJD5g3hpdUvEeoXClyYWlFQXCm89WZt9sfRP3hmxTO2woqIiEhtpsKDiIiIi2oT3IaEJxK4pvM11brP8eTjJbYfOHegWNtN397EH0f/YPvJ7dV6JhQtPKRn563hsC5uHWfSzvDm5W/SqkEr2wfzX/b/AkByZnK1n+sM5sTMAao/XUZERMQZeFgdQERERJzbtP7TeHrZ08Xaz6WdY82RNfRv3p+tJ7by0OKHWH5oOQBXtb+q2s/1cveyHQ/7eBh9wvuQkZOBn6cfN3S9gW6Nu9kKDZ0adgKgQ2iHaj/XGRxKOGR1BBEREbvRiAcREREXdfT8Ua79+lp+P/x7te7j4+HDPy/9Z7H2kf8Zya3f3wrA9pPbbUWHV0a+wpuj36zWMyFvK053wx3I2ybz3U3vAhdGWnRu1Jk+zfoAF6ZYVHU9C2dlmhrxICIitZ8KDyIiIi4qKTOJr3d9zZHzR6p9rxmDZ7DgugXF2vec3sOGoxtITE+0td0dfTfubu7VfibAzzf/XKzt+i7XA7Dp+Cbm75oPwKrDq/L+jl1ll+eKiIiI/ajwICIiIuXydPfkqg5XMaLViGLner/Xm/sW3Qfk7S7h6+lrt+cObzWcV0e+anudOz2XMW3HAPDRlo+47fu8HTdyzJy88y6yuGR002g6hnbE38vf6igiIiLVpsKDiIiIi3LEMP2FNy3kz/v+LPX8mlvX2P2ZD/Z9kKGRQ6nnXa/IVApPd0/brhZdG3UFwM/Tz+7Pt4K/pz9NApoUWWBTRESkttLikiIiIi7OwH7rHni4edCsXrMSz+29f6/dnlOYm+HG22PfJjYhtki7l7uXbVeLgS0GAhDoHeiQDDXthcteYNHeRaRnp+Pj4WN1HBERkWpRGV1ERMRFFRQJ7Dn1AUoeVdCjSQ9aN2ht1+cU1i6kHSNaF53m4emWN+LBNE1ycvOmWhT8Xdutj1vPc6ueIyM7w+ooIiIi1aYRDyIiIi6qbUhbjjxc/YUlS/Lule/StVFX3tv0Hu9tfo91t66r8R0lCkYCnEo9xbe7vwVwmTURXl7zMgAm2tVCRERqP414EBERkUq7Leo2+jTrw9yxcznx6Am8PbxrPMPk7pMZ1nIYjWc3JjIoEriw1kNtdyL5hNURRERE7EaFBxERERcVmxDL6E9HO3SLSQ83DxoHNHbY/csSXi+cjqEdCfYNdpndLC7miAVCRUREapoKDyIiIi4qOTOZn/f97NLfnr+14S3Opp1l4/GNAPz4148WJxIREZGLaY0HERERqfUOJx4GqPF1Jhyld3hv3A13gnyCrI4iIiJSbRrxICLF8Qv4AAAgAElEQVQi4qLqwsKELeq3AKBDaAcgb+qHK6jvXZ+G/g1dppAiIiJ1mwoPIiIiLs6VP7x+OP5D4MKikp5unlbGsZunBz1Ny6CWJGcmWx1FRESk2lR4EBERcVHe7t50DO1IoFeg1VEcJiwgDIB9Z/cBkGPmWBnHbrbGb+WN9W+Qnp1udRQREZFqc43xiCIiIlJM25C27Lp3l9UxHKpZvWYAvPnHmwC0DGppZRy7eXrZ04B2tRAREdegEQ8iIiJSawV6BzIoYhAR9SMA6BnW0+JE9pGQnmB1BBEREbtR4UFERMRF7T+7n0s/vJQVh1ZYHcWhVkxdwZTuUwDIzs22OI191YUFQkVExPWp8CAiIuKiUrJSWH14NWfSzlgdxaHSstL4ds+3AHyz6xuL09iXplqIiIgr0BoPIiIiUqttPL6RHSd3AK4zQqB3eG+CfYNpHNDY6igiIiLVphEPIiIiLqqufFve0K+h7fjOH++0MIn9NPRrSIhviNUxRERE7EKFBxERERdnYFgdwaEa+l8oPKRmpVqYxH6m9Z+Gt7s3iemJVkcRERGptnILD4ZhfGAYxknDMHYUanvGMIyjhmFsyf8zptC5fxiGsc8wjD8NwxhVqP3y/LZ9hmE8Yf+3IiIiIoX5efrRO7w3DXwbWB3FoYJ8goq8doXiw57Te/hgywekZadZHUVERKTaKrLGwzzg38DHF7W/Zprm7MINhmF0Aq4HOgNNgV8Nw2iXf/otYAQQB2wwDON70zRde3NxERERC7UNacv629ZbHcPh3Iyi36PsP7ufro27WpTGPh76+SGg7kyXERER11buiAfTNFcCZyt4v/HAF6ZpZpimeRDYB/TO/7PPNM0DpmlmAl/k9xURERGptlYNWtmO957da2ES+8jIybA6goiIiN1UZ42H+wzD2JY/FaNgDGc4cKRQn7j8ttLaxY5mrZjFjd/caHUMERFxEntO76HH2z1YdnCZ1VEcbly7cbbjHSd3kGvm8tYfb5GcmWxhqupzlV06RESkbqtq4WEu0BroARwHXslvL2n1KrOM9mIMw7jDMIwYwzBiTp06VcV4ddP05dP5fMfnVscQEREnkZaVxtb4rZzPOG91FIdbE7fGdvzcyudYc2QN9y26jxdWvWBhqupz9YVBRUSkbqhS4cE0zXjTNHNM08wF3iVvKgXkjWRoXqhrM+BYGe0l3fsd0zSjTdOMbtiwYUldpBTXdLqGjqEdrY4hIiJOoi59W/7Xmb9sx4HegXRr3C3v2CvQqkjV0rNJT65sdyVhgWFVuv7o+aMs2L3AzqlERESqpkqFB8MwCv8UnAAU7HjxPXC9YRjehmG0BNoCfwAbgLaGYbQ0DMOLvAUov696bClNXfolU0REKsYwXP9b8w23bwAgLCCMM4+fAaCedz2OJh21MlaVRQZFEh5Y9Vmpg+cNZuJXE8nOzbZjKhERkaqpyHaanwNrgfaGYcQZhnEr8LJhGNsNw9gGDAUeBjBNcyfwFbAL+Bm4N39kRDZwH7AY2A18ld9X7OjrXV+z5/Qeq2OIiIjUuIItNb09vMk1cwl6MYjzGec5lnSM7fHba910k1t73MPx86mcST1TpesLdvpIyUyxZywREZEqKXc7TdM0byih+f0y+j8PPF9C+0JgYaXSiYiISJUFegUyrOUwQv1CrY7icKF+obw68lWu7Xwt9y+83zYCcPOJzXR7O2/axRMDnmDRvkW8PfZt+jbra2Xcck2fn8KZpGtJG5tWpeun9Z/GnT/eSUpWCvV96ts5nYiISOVUZ1cLcTITO06kc8POVscQEREn0TakLUsnL6V/8/5WR6kRD/d7mPB64fx1Nm+9h2n9puHj4WM7/+LvL7I1fiv93+9PZk6mrX3ZwWXEJsTWeN6ynEnK+27INKs2hTLAKwCg1u/qISIirkGFBxdTF+bxioiIlOWB3g8AcFf0Xay/bT03db2Ju3rdZTtvYrL80HLb62EfD6PDWx1qOqZDvfz7y7QJbkPTwKZWRxERESl/qoXUHt/u/tbqCCIi4kS2x2/nqi+v4t0r32VYy2FWx6kxV7a/kpzpObZ1Dv4z8T9k5WSxInYFu0/vBmDUf0ax/e7tfLPrG/w9/Z3236eqi0YnpCcwKGKQbeSDiIiIlTTiQURExEVl5GRw4NwBUrNSrY5S4wqKDgU83T3Zde8uujTqYmv7bPtnfLnzS4J8gvBwc87vYi5+HxUVmxjL0oNLiTsfZ+dEIiIilafCgwu5vsv1tA1ua3UMERFxElVdH8CVvTbqNQB6NunJxuMb2X16N0eTjrIidgW5Zq7T/Zs1q9es0tekZeUtSHks6Rhrj6y1dyQREZFKU+HBhaRnp9fJb7VERKRsBlr/p8DwVsPJfCqT+3rfx5L9S2ztZ9PO4j7THd/nfau8haWzOJ583HackqXtNEVExHoqPLiQ7/Z8x9Gko1bHEBERcWqe7p5c2e7KIm0zh8wE8qanrItbV+49VhxawR0/3OHwERLxyfGVvsbAYEjkEAB2ndrF0gNL7ZxKRESkclR4EBERcVFBPkGMbz+exgGNrY7idBr6N8ScYdK3WV8gb0vqazpdA8DnOz4v9/oJX07g3U3vEp9S+cJAZaRlp1X6mpYNWrLwxoUAvLXhLYZ/Mpzs3Gx7RxMREakwFR5cyPj24+neuLvVMURExEm0DWnLd9d/R3TTaKujOK1FNy3iv9f/l86NOjP3irkAfLr903Kvu6zVZYQHhtMkoIlD81V1RIWPhw9uhpttCmZKpqZciIiIdVR4cCFV3XJLRESkrgryCWJc+3EAhPiFcGevO/Fy9yLXzC3zupTMFMICwxyeryo/22etmEWDlxqw+m+rbW2JGYn2jCUiIlIpKjy4kO///J6t8VutjiEiIk5i0/FNNPpXI3498KvVUWqN6KbRZOZkcuv3t5KcmVzqiIO/zvxFzLEYVhxa4dA8rd9sze+Hf6/UNUmZSWTmZNKveT9b26fbyh/FISIi4igqPLgQrVouIiKFZeVkcSr1FFk5WVZHqTUmdJgAwLwt8wj830AiXo8osd+0/tMA2Ba/zeGZvtvzXZHXuWYuGdkZpfZPzUrF19OX19a+Zmsb0XqEw/KJiIiUR4UHF3Jj1xtp1aCV1TFERMRJaApe5YX4hfDRVR/x+qjXAThy/giPLn60WL+/9/w7AOfSzzk8U0RQ0eLHI4sfwed5H55c+iSfbP2EQR8OYuHehWw9kTfqMTUrFT9PPx5Z8ggAj/d/XOt8iIiIpTysDiD2cy79HKdTT1sdQ0REnIxhaERcZUzuPhmAw4mHeXXdq7Rs0BLTNG3/jtm52Ww+vhk3w41jScfs8syHf36YzJxM3rrirWLnzqadLfL6jfVvAPC/q//X1rbqs1UAmDNMW+GhwMtrXuZ8xnnmjp1rl6wiIiKVpcKDC1m4d6HVEURERFzGK6Ne4ZVRr5Br5jL8k+GMbjOaaf2ncSL5BH3fz9uG83Di4Wo9Y1v8Nrq/fWFHqpIKDxuPbyzyuoFPg1JHWnyy9ROGRg6lQ2gHujbqytPLniY+JZ7jycerlVNERKQ6NNVCRETERYX6hXJzt5tpGtjU6ii1WkZ2Br8d/I3HfnmMw4mHbaMLA70CSctOq/J9+7/fv0jRAWDR3kX8deavIm2tG7QG4FTKKfq814dz6ee4Pep22/mvr/nadjz5u8n0adaHZ4Y8w6ROk9h17y66NOpCQnpClXOKiIhUl0Y8uJCx7cbabciniIjUfm2C2/DJhE+sjlHr+Xr6MjRyKMsOLeOLHV/QuWFnABbdtIgBLQZU6Z65Zi5r49YWax/z2RgAIvgRgM4NOxPdNJo31r1B3Pk4/jj6Bzd0uYEXh7/IrT1vpZ53PTo27EjmU5nc9O1NfL3ra3q/25vMpzNt9wzyCSI2IbbC2U6lnCIhPYG2IW2r9N5EREQupsKDC8nOzdbK5SIiIg6wdPJSgl4KYkXsChLTE4G8wk5VfbnjSwDqe9fn/t73czbtLFFhUdz2w21F+v3PgP/hpm9vKtL2z0v/SbBvMH2a9bG1ebp78sXVX/DtrG/p2rhrkf5BPkHEucVVONuo/4xi84nNmDO0OKmIiNiHplq4kJ/3/cz2k9utjiEiIk5iXdw6fJ/35dcDv1odpdYzDIO7et1F+5D2fLXrK4J9g2nk34i7f7wb41mDc2klr7mQmpXKjpM7SMpIIic3B9M0WR+3nhu/vRGAjyd8zKxhs3jrirfo2LAjAJM6TrJdP3359CL36x3em86NOpf4LDfDjezp2cTcHlOkvV1wO06nnsZ41mDGshnlvtfoptGEBYSV209ERKSiNOLBhQR4BZCcmWx1DBERcRK5Zi7p2enkmrlWR3EJL414CdM0ebDPgxxNOophGOw/tx+Alm+0JOGJ4usobDmxhQEfDGD+NfO5+uurGRI5hOWHlgMwsvVIxrUfZ+vbv3l/Ep9IpJ53PSI3/QTATzf+xMmUkzQJaMKZ1DP0Du9dbs6LdzF5YuAT7Dq9i8+2f8bMlTN5duizZV7v4eZBdm52uc8RERGpKBUeXMikjpNsv8yIiIiYpobK25thGEQERRARFAHA/172v/xy4BcSMxJJz07Hx8OnSP+483lTHGIT89ZYKPxzeljksGL3r+ddr8jrTg070alhp2pldndzp1No3j3ahbQrt//cGG27KSIi9qXCgws5mnTU9ouNiIhIAQOj/E61yPdbj9GhSSDtGgdaHYVeTXux6KZF/LzvZ3Jyc4qd33FyBwBJGUn4evjadsGYN34eN3e7ucZyFhRELt4xQ0REpCZojQcXojm8IiJSFzzw+WZGvrbS6hg2l7e5nFlDZzFj+QxG/WdUkWkKbkber1pJmUmkZafRIbQDr458lcndJ+Pu5l5jGVOzUm3HT/32FBnZGTX2bBERERUeREREXFSTgCbcHX03zeo1szqKyzMMg1fWvsKS/Uu484c7OXr+KB9u/tA22uSVta8AsOf0Hh7u93CxdRgc7c7oO4luGg3A86ueL3OE5NDIoQxsMbCmoomISB2gwoMLubzN5VzS9BKrY4iIiJNoHdyaOVfMse2WII4T4BXA8inLAfhgywdEvxvN37//O6uPrC7S77/X/9eCdNDIvxEbbt/AkpuXAPDokkdL7ZualUp6drrWCBEREbtR4cGFJGcmk5BefEVtERGpm0zTtG3hKI43OHIwq/+2mgkdJrBsyjKg+DTIwrtYWKF5/eYA/PjXj/z0108Yzxr86/d/sebIGtv/TtYfXU/MsRjthiIiInajwoMLWX14NXvP7rU6hoiIOInfj/yOxywPlh5canWUOmNAiwF8e923dAjtQOeGnQGYPmg6MbfHsPOenRangw6hHfj36H8DMPbzsQA8/uvjDPhgAF7PeXEq5RQvDHsBQFtqioiI3ajw4EKaBDSxOoKIiDgRjXSw1ryr5nFP9D083O9hejXtVe1tMe3l3t73cvzR47bXBes5ZOdm88HmD2wjHVR4EBERe9F2mi5kTJsxLN6/2OoYIiLiZFxtO83aIrpptG1BR2fTJKAJ5oy8wlR2bjaL9i7iYMJB2gS34YrPrrC1i4iI2IMKDy5k37l9HE06anUMERFxEiYa8SDl83Dz4Mr2VwIQ9GKQrb2swsP/rf8/vt71NSv/5jzbmoqIiPPSVAsXsjJWP/xFRKS4mt66UWqnUymnCPELAWBk65FsPrGZMZ+OISM7g5zcnCJ9957dy/aT262IKSIitZAKDyIiIi6qWb1mPN7/cVrUb2F1FKkFGvo3ZP8D+8l+Optg32BGfDKCRfsW0erNVnjM8uCxJY+Rnp0OgLe7NxnZGRYnFhGR2kJTLVzIiFYjSMpMsjqGiIg4iVYNWvHSiJesjiG1jLubO+2C29leH0s6BsDstbOZvXZ2kb6maWpEjYiIlEsjHlzImbQzHD2vNR5ERCRPdm42CekJZOVkWR1FaplnhjzDwhsXkvFUBqv/tprru1xfYj8tQCkiIhWhwoML2XR8E0fOH7E6hoiIOInfD/9Og5casPrwaqujSC1jGAaj247Gy92LAS0G8M7Yd/jrvr+K9SuYeiEiIlIWTbVwIa0btGb/uf1WxxAREREXE+gdSKB3IOYMk7SsNB5Y9ABj2o7B19PX6mgiIlILqPDgQoa1HEZKVorVMURExEloO01xBF9PX94d967VMUREpBbRVAsXsi1+GyeST1gdQ0REnIwW/xN7O3DuAO9teo+E9ASro4iISC2gwoMLWX90vdURREREpA44nHiY23+4nbVH1lodRUREagEVHlyIgb7REhGRCyKDIpk5ZCaRQZFWRynT2v1nyMjOsTqGVELXRl0BeG3da/x28DeL04iIiLPTGg8uZGjLoWRkZ1gdQ0REnERkUCRPD37a6hhl2n38PDe8uw6Af9/Ykw5N6pGZnUunpvUsTiZlCfYNBuCXA7/wy4Ff2HPvHtqHtrc4lYiIOCsVHlzIsaRjnEo5ZXUMERFxEunZ6ZxKOUUj/0Z4e3hbHadE51IybccLNh1l6Z7NABx68QqrIkkFXLxuyJm0MxYlERGR2kBTLVzIntN79INfRERs1hxZQ4vXW9SaNYC0Bmbt5e3unIUtERFxDio8uJDujbtbHUFERMShTFNbhDqL2Idi6RPehyGRQ+jVtJfVcURExIlpqoUL6desH8eSjlkdQ0REnIQ+pIsjtajfgnW3rbM6hoiI1AIa8eBC1h1dx6lUrfEgIiJFudKuR6qlOJ9xn4/DeNbgwLkDVkcREREnpcKDC9lyYovVEURERKqh/AKJ6g7OZ9G+RQAqPIiISKlUeHAhWthJREQKaxvSltdGvUarBq2sjmI3mj7ifBr6NQQgLCDM4iQiIuKsVHhwIX2b9WVQxCCrY4iIiJNoUb8FD/V9iPB64VZHsZu6VnaoDYWWt8a8BcDADweSkJ5gcRoREXFGKjy4kIMJB4k5FmN1DBERcRLJmcnsOrWL1KxUq6OUqvDH6i1HzpXf3/k/h9c5EzpOACAhPYFnlj9jbRgREXFKKjy4kMOJh536l0sREalZa4+spfOczmw+vtnqKBVyOjmz3D5mHRvzUFsKLa+MfAWAc+nlF49ERKTu0XaaLqR/8/6sObLG6hgiIiIOU1s+iNc1j/R7hKSMJDo27Gh1FBERcUIa8eBCoppEEewbbHUMERFxErV5dMC9n27iTHKG1TEsV5v+C84YMoNrO19rdQwREXFCKjy4kKUHl3I27azVMURExMkYRvnbVDqbn7YfZ9fx81bHsFxtWFyyQGZOJqdTT9te7z61m692fmVhIhERcRblFh4Mw/jAMIyThmHsKNQWbBjGL4Zh7M3/u0F+u2EYxpuGYewzDGObYRhRha6Zkt9/r2EYUxzzduq23ad3Wx1BRESkwto/tYib3ltf6nm3EgomtehzeJ3zyOJHaDK7Cevi1hH0YhCd5nTiuvnXEfBCAPHJ8VbHExERC1VkxMM84PKL2p4Alpqm2RZYmv8aYDTQNv/PHcBcyCtUADOAPkBvYEZBsULsJ9Ar0OoIIiLiRDo17MR7V75H6watrY5Soozs3DLP55ZQZajN00eqoja92wY+Dcgxc+j3fj8SMxKp510PgJSsFBbvX2xxOhERsVK5hQfTNFcCF4/fHw98lH/8EXBVofaPzTzrgCDDMMKAUcAvpmmeNU3zHPALxYsZUk3dm3RnaORQq2OIiIiTaFavGbdG3UrjgMZWR6mS3BI+dWvEg/Ma225skdfnMy5MlTl47mC17j13w1wmfjmxVk09ERGRC6q6xkNj0zSPA+T/3Si/PRw4UqhfXH5bae1iR3tO72HZoWVWxxARESeRkJ7A+rj1JGUkWR2lSkr6kFnXPnbWps/ZfZr14c5ed5Z4rlfTXtW69z0L72HBngV8ufPLat1HRESsYe/FJUtavcoso734DQzjDsMwYgzDiDl16pRdw7m6wgs6iYiIrItbR9/3+7Lz1E6roxSTnVP2NAso+UO3vvF2bq+MfIWrOlxVpO3UY6eKjYaoqoJtw5fsX0J6drpd7ikiIo5X1cJDfP4UCvL/PpnfHgc0L9SvGXCsjPZiTNN8xzTNaNM0oxs2bFjFeHXTqNajrI4gIiJSISmZOeX2KXmNh7qltq1p4e/lz6AWg3jq0qdsxYZlB5dxKOGQXUbePNrvUfac3sOo/4zipdUvVft+IiJSMzyqeN33wBTgxfy//1uo/T7DML4gbyHJRNM0jxuGsRh4odCCkiOBf1Q9tpSkQ2gH1sattTqGiIg4CWceHfDnifI/hJa0xoM4v4f7PQxAzLEYfvzrR66dfy0A0/pNw8vdi+eGPVflLV7redcjOTMZyFs8FSA9Ox0fDx87JBcREUepyHaanwNrgfaGYcQZhnEreQWHEYZh7AVG5L8GWAgcAPYB7wL3AJimeRaYBWzI/zMzv03s6Ps/vy+ykJOIiAiAUeKMR2udOF/+MPkS13ioY8WI2vx+uzTqYjsODwxn9trZvLD6BXad2lWp++TkXhgds3j/YlKzUgHw8/Rjy4kt+D7vy3/3/Le0y0VExAmUO+LBNM0bSjl1WQl9TeDeUu7zAfBBpdJJpRxMqN6K0SIiIjUlLTO73D4ljnioxR/E6xofDx/eH/c+yZnJrItbx+c7Pgegef3m5VxZVEGhAeCX/b/QsGveVNyxn49ldJvRACw9uJTxHcbbKbmIiNibvReXFAsF+wY75bdaIiJijR5NevDl1V/SJriN1VGKSa3AGg8l72qhykNt8veef+eBPg/QIbSDrW3f2X2Vuoeb4cZj/R/Lu/bcPoZ/Mtx2btG+RQDc2PVGO6QVERFHqeoaD+KE2oe0x9/L3+oYIiLiJMICw7i287VWxyhRWlb5hYek9OKjImrz1IO6rHDhodc7eVtrJv8juUK/t/h7+fPyiJdZfXg1K2NXltgnwCuAXDMXN0PfqYmIOCP9v7ML2Ra/jV8P/Gp1DBERcRKnU0+z9MBSEtMTrY5STFoFRjw8/s22Ym11re7gKoWWoZFDeWbwM0Xabv3+1mL9TNPkm13fFNkqMzs3m8T0RG7udnORviG+IbbjmStm4j7Tnc3HNxe758/7fubN9W+Sa5a9heuZ1DMMnjeYxfsWV+QtiYhIJajw4EJSslKsjiAiIk5kfdx6hn8ynL/O/GV1lGIqUngoiTPv1CGla+jfkBlDZhRp8/X0LdZvRewKrv76ap767Skg77/32M/GEvRSEJFBkeROzyU8MByAxIxEkv6RtzvK17u+BiDqnagi98vMyWT0p6N58OcHiXg9gglfTuB06ukSM4b+K5SVsSu5/NPL2RZfvOglIiJVp8KDC5nUcZLVEURERCokM6fsb59LU9fKDq62psW6W9fx800/4+/pX2TEAuSNbJjw5QQAXln7Cm+se4NbFtzC4v15IxD8PP0wDIOzaXkbox1+6DABXgHFnmE8a/DGujfYcHQDk7668LtRi/ot+G7Pd3yy9ZNi1xw4d6DI65RMfZkjImJPWuPBhUTUj8DfU2s8iGNk5mSSa+Zqr3SRWsSZP7Rm5ThvNnGcPs36AODu5k52btE1PIZ9NIyE9ATb64cWP1TkfI8mPQD4874/OZF8grDAMAA83DwYGjmU/0z8D41nNwbgo60fcSL5BD/+9SOr/7aa+j716dywM/VfrM/mE8WnY6w9shaAzyZ+xjub3uHSDy8l+clk/cwTEbETjXhwIZ/v+FzTLcRh2v1fO3yfLz4sVkScn2E4345H2VUd8VDH6hWu+n493DyKFB7WHFnDqsOrABjVepSt/YHeD7D1rq1suXMLQT5BQN52nJeEX2Lrk/V0FktuWUIj/0ZM6T4FgGNJx3jx9xfpFdaLAS0G0KVRFwzDwN3NnU+2fcKZ1DOkZaXZpu6si1uHn6cf13S+hruj7ybHzOH2H253+L+DiEhdocKDCzmefNzqCOLCYhNjrY4gIi4kO9ckPKjyxUxnHsXhCK76budeMZfJ3ScDcCTxCAM+GGA798yQZ2xTKB7q+xDdGneje5PuFbrvEwOfoHm95kzsOBGAey+5t8j5QRGDALj0w0vxe8GPt2PeBuC3Q78xsMVAPNw8GBwxGIAFuxc49Zoi2+O3O3U+EZHCVHhwIY39G1Pfu77VMURExEn0Du/NwhsX0ja4rdVRisnKycXbw43pYztV7kJ9znIJ13a+loT0BIxnDVq83sLWfuqxU/Rt1pc99+7h11t+pWWDlpW6b4fQDhx++DAvj3iZd69811bcKPDZxM/45ZZf2H16NwAP/PwAObk5PND7AR7s8yAAjQMa8/qo10nJSmFt3NpqvlPH+OHPH+j2dje+2PGF1VFERCpEhQcXEhEUQd9mfa2OIS5qTNsx9ArrZXUMEamERv6NGN12NPV9nK8onZ1j4uFu8PeBlftgWdfqDq76jfa3u7/l7p/utr2+q9ddrPn7GkL9QgEIrxfOZa0uq/L9A7wCuC3qNtzd3Iu0+3v5MzRyKJM6TqJvs75k52azNX4rd0bfyZi2Y2z9+jXvB8CADwYQm+B8I/6a1WsGQEZOhsVJREQqRotLupCYYzHl7lEtUlV3RN1BYkai1TFEpBKOJx1n/dH1DIkcYpsf7yyyc3PxcKv89x8u+jm8zim82wTA3LFza+zZ7m7uzL92PgDjvxhPr3d6MXPITB4f8DjeHt5A3mihApFvRJIzPQc3w3m+r2sckLeIZka2Cg8iUjs4z/+DSrWp6CCO9PmOz3lh1QtWxxCRSthwbAMTvpxQbKtAZ5CVY+LpnrfopZdHxX8d0RoPYk/3974fgOnLp7P04NIi5449cgwAgwtbeDqLbfHbALjrp7voOrerxWlERMqnwoMLmdpjqtURxIWtObKGP8/8aXUMEXER2bm5eLjn/Rry/26p+DQujXhwPf8e/W/Lnj281XAGthgIQOeGnYucCwsMI3d6Ll9d8xV7z+xlZd5tmJgAACAASURBVOxKKyKW6J2N79iOd5zcwa8HfrUwjYhI+VR4cCEN/Rpqv2lxmCPnj1gdQUQqyZnXB8jKMfFwyxvxMLR9oyrdI/KJn9h6JMGesZyOE/8ntIvBEYOZ1GlS+R0daOXUlZycdpKIoIhi5wzDoFdYL/p/0J/B8wbz4KIHLUhY3F9n/iryesn+JRYlERGpGBUeXMh7m94jPTvd6hgiIuJkDAyrIxSTnZOLp3sV1ni46PWiHSfsE0hqVMF2mb/c8gtNAppYmsUwDBr6Nyz1fMsGLZkxeAYAb/7xZk3FKlWumUtsYiwt6l/YDWTnqZ0WJhIRKZ8KDy7kXPo5qyOIiIhUSHZu3q4WlXXxKA4fTxf/VcZFRzwMjRwKQEpWisVJKuZ/BvwPlzS9hM8nfU5sQiw7T+Z90E9MT+Rc2jliE2KJOx/n8BymaRJzLIbkzGSeHfIsu+7ZxeVtLudkykmHP7s2Ss1KZefJnaRk1o7/nYm4Mhf/aV23hAeGF6l+/3/2zjusiawL4+8k9C5FUUSUZkMFUcTee2ftn3Vdy9rLWtaOa+9t7d21994VEUGRKiKigNKk9xIgJPn+GDNhSKhJSMD5PY+PmXbnhiQzc889530ZGGQJm2CXvRMDA4NS0alBJ7hPdoeNkY2iuyJGQSEfapXJeCg2ENdUZa5N1ZG7X+4CAKz2WSE9T/nLZTRVNeE9zRt73+1Fw70NYXfIDgBgsNUAhtsM0XBvQ1jsES/VkDU7PHeg3fF2AEib66YmTWGiZYJPSZ9AuBK4GHRR7n2oTnhFe8HukB18fvgouisMDL88jJ1mDcJUx5SyV2JgkDWdGnT65dTkGRiqO0ZaRuhs0VnR3ZBIJocLfU1VqdvRqOGBh5p+3U3lpCqVTWVZfE//Tr2+EXKDtk3e7mJu392w9NlSAEDgzEDU1ia1Uerr1UcuNxcAsPXNVoxtMVau/ahOXPtE2qYyWcEMDIqn+lzpGcrEN84XD74+UHQ3GGooi9ovwhT7KYruBgMDQwWIyojCucBzSmcFCADp5Qw8pOcW0JaLZzzU+FKLXwAVVvWZB/P+wxvHBx/Hxh4bse3NNtTTrUdZcgJA7e21cSbgjFzOfTrgNPU6OTeZer2qyyo4mDoAACLSIlB3Z12mtOAnfvF+AFAtsmoYGGo6zN2agYGhXNwNvYsVz1couhsMDAwVwPeHLybemojoDOVypckv5CG3gFeuwIP9+qfwixLNVhbPAGCzavajTE13tQAAVZb0mS9Vhbm+Oaa2noolHZaAzWJjgPUA7O67GxnLM6Cvro+k3CRMvj1ZLufWU9ejXs9/JHLX0FLVgtdULxzofwBZBVmIz46H6ytXprwAoNze0jhMxgMDg6Kp2XfrakBsZixc3VzxNeWr1G3Nc5ongx4xMEjmScQTxGXHKbobDAwMNYCcfB4AQEejfDPdwT8yqde/wkD8V8Bjigcs9ElNBDar+pXLsAgWBlgPwKy2s8BmsaGnrkdzxpBHxkHRWfsRTUfQtqmrqON/Lf9HLW/33I7NHptl3ofqhjColVWQpeCeMDAwMIEHBROTGYN1r9bha6r0gQdtNe1qNWvAUL2IyohSdBcYGBgqiLLqA+RxycBDefUZlM8MtOpQzk9Qejo26IiNPTZikO2gaqXxIITNYmNll5VwqOtArRPOrgPAxFsTxRxYpEWo47C3316s7bZWbLuBhgF8p/tSy10adJHp+asL+YX52Oi+EXmFeSjkFwIAhjQeouBeMTAwVL8rfQ0jPC0cAPA+9r3Ube15uwdcPlfqdhgYGGo+XU51wfgb4xGVEYVlT5fhS8oXRXeJQY4QhHIN3YWBh6KOFEcnOJa4f9HuFx/K8Wt4CoSsB6/KQkRaBPgCPi64XFB0V2RGHW2RwLd/nL/MZ9lNtEwwuvlozGtXcoZr67qtcWroKQCAGlutxn5/SmPfu31Y9XIVNDdq4lXkKwxrMgz2pvaK7hYDwy9P9VHzqaEI0+bis+OlbotTyJG6DQYGhl8DTiEHqZxUBCUEYZvnNtga2cLWyFbR3WL4Rcjjkur/RYUh+aWMj4giOQ/FB1L80g5kUFo8oz0x8dZEfJr1CU1Nmiq6OzLh5NCTCE4MhkNdB6TkptA0GWTBoUGHyrXfhJYT8Dn5M2Y9mIVhTYahrm5dLHmyBLrquljTdY1M+6SMGGgY0JZdu7kiODEYzWs3V1CPGBgYACbjQeEQMkwgtdC3QIvaLWTWHgNDUaqT6jhD2WioaCCvMA8RaREAgD/u/qHgHjHIgx6NesB/hj9sDG0U3RUaHAmlFmoq5bsfimc8yKpXykll314el4fo1FyZ9kWWsAnys5eXEKMiaKDfAP1t+sNUxxT6Gvr47cpvCnGUYbPYaF+/PQAgOCkYALDDawfWuomXZ9RE3kS/oS1PvjUZy58vV1BvGBgYhDCBhxpELc1aaFSrkaK7wVBDsTe1R3/r/oruBoOM8IjywMvvL5lMqRqOgYYB7E3toamqqeiu0MiXEHjo3rh2ifvTSi2KjcR5v2AqeXmYc8Efnbe9VNqMEKGugzpbXcE9kQ8z7s3AjZAbmPNgjsza7HCiA474HCnXvtaG1gCA3ud646T/SZn1oTpwJpBuZxqZEYmsfEZckoFB0TCBBwXT3pyMSHdt2FXqtgLiA3An9I7U7TAwSGJd13X4relviu4Ggww44XeCeu323U1xHWGQO+Gp4Tj4/iBSclMU3RUaWfmk4FtRjQeCIGBmIDlAQs+F+LVKLSobV3kWkgBAlF2ibAidLNRVambg4faY2wCAwIRAmbTH4XLgFeNV7gyKomUFU+9MxcRWE9FAv4FM+qLsXB91nbbcyKARMvMzS9ibgYGhqmACDwpGS1ULlrUsZV4HyMAga158e4EFjxcouhsMMmDvu73U64dhDxXYEwZ54x/vj9kPZiudFe7H2AywWQRs6uhU+FixjIcaHniQlpyCQkV3QSLCjIeiThA1CRWWCha3X4zw1HAU8Aqkbi8oMQgAYKhpSK37kV56xtqj/z2iXtsa2mJ///1S96M64NLUBT0b9QSLYCFzeSZsjWzFhD7zC/PBF/AV1EMGhl8TJvCgYFgEC8ObDEdjo8ZSt7Wi0wqZakYwMBTl6qeryC7IVnQ3GGQA8zkyKBIeX4D9L8LA4wugpUbXjilJgb88rhZvI1LQcPl9xKQpr65BZZDWEjU3XzkzHjqadwQAOJg6lLFn9aVTg07QU9fDj6wfUrflF+cHQJTJ8PprEjpseYFHH+OQXyj5M+5r3RdnhpFlB2PsxmD32934+9nfUvdFmfme/h0N9zTE+Jbj4TXVC7rqutBT1xPLeNDYqIFJtyYpqJcMDL8mTOBBwURlRGGn107EZMZI3RaLYCmdZRpDzSE6M1rRXWCQEQ//x2Q5KJJPSZ+qbKZNGa30fL6TqeJqKuKPIP9ztpB4TGlBdWHGw+X35DXK+1vVi/kpM8qa8aCvoY+1Xdeit2VvRXdFbvS37o9pradBV01X6raELmit67YGAATFZgAAZv7nh8arHpWY+TOx1UQI1gpgZWiFQn4hnkY8lbovykx6XjoiMyKhp64HJzMnAMB0x+k4PfQ0tU8hn/xN/PfhP6W8RjIw1FSYwIOCicqIAgC8/P5S6rY2vN7ApI0xMDCUiSQR2pr88K9M+MX5ofnB5tjhuaNKz6ss2XAxabk4+eYbAODEpDZi22d1s8Li3hJsXYt0Pykrn7apxldaSPn+cguUM+MhKScJtbVrw8ZIuRxXZIm6ijpmtZ2F26G3EZMZgzMBZ2C0zYga+FYEB1MH/NnmT2iqSNZBCUssO5OtRe0W8I3zRWR6ZIXPX10QikgWDfa0rtsaPS17YsLNCTj0/hDSOGnUtrS8NLE2GETw+Dz0ONMDG903KrorDDUAJvCgYHK5ZEpoYk6ignvCwMCgaO59uYe1L+Vvd+bq5opJregppv7x/nI/LwOo7LbXUa8V3BPFMP9SAB4Hk6KH9WtpiW0nCIKayaWtL/K6+ACLz8xYlkpOvnJmPAQmBGL2g9kISQpRdFfkSkhyCKbemQrz3eaYfHsyUjmplZpl72vdFwcHHqQyW4sHEwOiyx5ACwWi7Q7ZwfeHb4X7UB0QlhLqqosCD3FZcVDfoI7/PvyHWQ9mYbPHZmpbUk5SlfexOhGbFQu3725oWaelorvCUANgAg81CKtaVujUoJOiu8FQQ1FhqUBHreJCcAzl50bIDZwKOCXXc2QXZGOTxybkcHMAgHqYSM5NZlJOq4Da2qRlZHELwTROGta+XCtzy7f+Nv0RNjdMKWaV+XwBfCNFg6OijhZFiUoV12goWkaYlcelbROmmNfU729l3lXRv0VCZl65ZsOrms/JnwGQAdeaTNt6bcXWqbJVK9xOLjeXlikRXUzLJCA6vcw2ejTqAYC8D7Q73q7CfagOCEUki2Y8+MbRgyy73+6mXjf5t0mNvXbIgvjseAggqFSWDgNDcZjAg5Igi4uelqoWTLRMZNAbBgZxbAxt0M+6n6K7UaPRVNGksqDkRVwW6W5ga0imsy/vuJzaVlUPFnmFeQp70MspyEF+YX7ZO8oQjygPBCWQivTtzNphoM1AjGg2grbPx8SPWO++Hpteb5LqXGtfrgXhSlB/Xx01HVgZWkGNrSZVu7LgjNd32rKmmuTAg00d8Xr4onO72cXEEv2imFTp4qTnioIzy64HodeuVwrsjWSEv8Oa6mohRF9DH5yVdPcJjQ0aFc44GH1tNJyOOVHLn37QxRK/JefAMywZuaVoehAEgSODjgAAeALlLMGRljradTCsyTAYaRlR6wbaDBTb78QQka20+gZ1mQd9awrx2fEAAJcrLjjgfUDBvWGo7jCBBwUjHMi1qy995DkoMQg3P9+Uuh0GBkns6bcHPRr2UHQ3ajQHfQ4ihZOCrPwsuQ3MPyR8AABqBjwkWZTmXBWBhzROGjQ3amLrm61yP5ckdDbroPXR1lV6zs6nOqPl4ZYYemkoCILAvXH3MMZuDH0fi87QV9dHcFKwVOda774eAMDlkwPPkKQQbPXYiuTcZKnalQXFrf+0Sgg8bHFpgfvzSs7eK1464BZKpkrXVHHlylwKErPEg2vKZjs622k2xtqNxeIOixXdFbmjoaKBtV3X4vKIywCAfF4+2hxrg8sfL1NaX2WRkZcBfQ19ajkug4PezepgSKt6aG9phLcRqRh3/B1W3AhC8A/xciUh0x2nY1yLcQCAx2GPa9xMdteGXXFz9E2Y6phS6wiCwO0xt+H9hzeGNh4KQOSqApDXy0EXB+Frytcq76+yIww8AIB3rDfaHW8ndYCc4deFCTwoGHW2OlrVaUXzZWZgUEY8oz0x68EsJiWxDHIKcrDTcye4PC7CUsMw6uqoCttX6m0Rt/6SFW+i3wAga32PDjqKuU5zqW1V8QAqnGWThb1cZfmU9KnKzlXAK6Be3wm9g5shN9H8YHOJTkZ66nq4++UuCFcCs+/PLrPtc4HnkJEneYAhnE3+kPABy58vV4o65mOvv9GWVdmSH0G01VXQvJ4+bV3RmEJ2CZoFzLVJRGJWntg6ZXO3MNAwwIXfLvwyzz/ruq3DqOajaOvGXB8Diz0WCIwPLPP4jPwM6KuTv4vs/EIkZuWjhZk+9o11gKWJNrXfrYAfGLjPA2OPvsXl95KDGsLBd7/z/XA1+Gpl35JSUpLI+pDGQ9DWrC3ODDuD66Ouo7FxYxzoL5rBd490h+0BW7z49qKqulqlPIt4Bu9Y7wofx+VxUUujFow0jXDuwzl4x3pj5YuVcughw68AE3hQMCmcFLQzaycT0Za1XeUvSsfw63LM7xgA6T3layICgQBLnixB+xPtMfb6WPz19C/cCb2DrR5bcfXTVZz/cL7Cbcor/ZgAAQdTB+iq62Ka4zSYaJugVZ1WAESz5PJET10PAJkOqyiEFmtVQVH3ChbBQnx2PD4lfcK46+No+/3r/S/NsrZ4TXJxPiR8wMRbEzHt7jTa+sMDD0NfXb9KPsuKUMgTDQbm97TBvbmV1yPKyiuEdgnZEgA9SFETqMw1NzFTPOMhMVM8GFESB158xbhjbyt8Xoay2dlnp9i6M4FnUMgvhKuba4nBxFROKmpp1gJAWtIKBEDL+mQgor2Vkdj+XhEpWHY9iFp2/5IEz3Ay82lU81EoXF2IxkaNMe7GOFz/dF3q96UsjLo6Ct1Odytxu76GPlyaugAgs274a/g473IeC9otAAD0PNuzKrpZZWTlZ+HFtxcYfHEwJaoZmxlLlV2WxWyn2UhdloqGBg2pdX2s+sijqwy/AEzgQcFEpkfiqN9RpOSmyKxNZtaHQR4IZ6iF36+YzBg8CX+iyC4pBSFJIWCtZ2GH1w68jXkLjygPAMC0u9Nwwp+sIfWL86twu/JyutnZdyf8ZtD7I8x62O21GzkFOXKtdRW2HZmhGDs3M10ztKjdosrOF5URBR01Hazushp8AZ/6Hb2Oek277qdyUmnHlVU2IPw7Fg1WAMCMNjOQvjwdhpqGyOXm4ojvEVm8DalJzRFlfizsbQs7M/1S9hanqGZBJoeLFvVFx9vUpove1rRbYGXeT1I2GXhgFfkaLS8yCC2LHU++wDNcds8lDCIWtV8E3hoezg0/R60LTQnF9U/Xse7VOix9ulTsGB6fh7isOJjpmuFLQhYmn3oPAHC2JAMOA+zqwkCrdMHKiSe9Me7YO2qZzWJjgTM52B5xdQT2vduHza83l3R4teCIzxFcD7leoew9giAwrsU4pOeXLc5ZHXka8RQ9z/ZEXmEebn2+hdeRr1F/d33U21WvQu1Y1rKErpouHv3vEdZ3W4+5D+Yy4w2GCsMEHhSMsHbqduhtqdtyfeUqdRsMDGUhTGNse6wt+v7X95e/8TQ72Iy2nJaXBlWWKtLy0qiZyt+a/YaA+IASU0AB8YChUJm7KpjaeioAYMPrDTDdaQq9LXqYdX8WGh9ojFaHW+FdzLsyWig/Qk2JY37HSpzZE7Li+QpscN8gs3MDQFuztjDWMpZpm6WRXZCN2tq10dS4KQAgLC2M2nb1kyjFOZebC1WWKlUDXtwqrySGNxlOWz7ud5yyZF3xfAVefn9JtqfgNIDwJNJFZcMwu0odv/6eqDwmM48LPQ3RIKtQybQLlIHc/EIQBGCsI3JPMdRWvMAoAwmLYGF8y/EQrBXAa6oXull0w/LnpNCvJHcyLp8L126u6GPVB/MuiqyPNX46w7BYBHxW9sK3zQNwa3ZH2rF3An+goFDyvWeG4wwMbTwUDqYOmP9oPla8WCGrt6gQhK5Qtka2FTpOIBDgdMBpalnouFLdEQgEuB5Cz2bpcroL9VrSM8m2N9uoCRQAmH1/Nja4b8CVkVeQ+Xcm+lr3hVeMFw68P6DQkklZcNL/JM4GnsXbGCa7q6pgAg8KRpgOqwzCXwwM5YEv4IPH51FBs3xe1ToEVAeKlkkk/pUIfXV9OBxxwE5P8RRbITwBj3ZcUW0AWTLiyggc9T0qtt65vjMAkQf6IZ9D+JLyBR8SPuB7+vcKnSM9L73EgFRR145nEc9KbWezx2asfrm6Qucui5jMGEpgsyrILsiGjpoOmpk0Q+cGnZGeJ5pV+/P+n+DyyHtAZn4mdNV1sdOL/I54xXhJ/BumcdJQyC/Ek/AnMNczxyDbQcjl5oLL42LP2z2Ydnca1ruvR3BisNLUzucX8jD2Z9r+gBZ1pW4vk8OFnqYo8FB8UFXzSi0qDofLg4YKmyYyWUevZrtHVFec6zuDzWJT19nGxo3F9tFQ0cDKLitRyGmMz/GSg9IqbBYIgkBdffJzrl9LEwAw76I/+u5xl3gMQRC4NeYWfKb7YEmHJQCAoIQgJOcm42PiR2nfWpWzscdG9LXqi919d5e9cxEIgsC9sffQvWF3AMA6t3Vy6F3Vk5ybjAtBF0rcbr3PGtc/Xac0gW59voVlz5ah86nO1D4Pwx6KBWIaGTQCAEy8NRFnAs5Q6w/7HEb/8/1l+RbkxpmAM5h6Zyom3ZqE9ifa45jvMUV36ZeACTwoCbKYNbY1ssVg28Ey6A0DgzgqLBVY1rKEKlsVGfmimerlz5ajzdE2CuyZYhF6tF8ZcQWnhp5C+rJ0/O7wOwBgcfvF0FTVhPMJclD/IOwBxl0fh/8+/IdD7w/R2lFhqeDGqBvUsjwCDwKBALc+3xILJATEB5Ra7lURccy4rDjU2lpLbJYFAEKTQ3HY5zC1XFoGiLyISIugqXTLmxxuDnTUdNDKtBUuj7iMoIQg9GgkcocJTQkFQOr9GGkaoa9VXwDAVIepaHygMTyiPDD51mQExgcipyAHhtsMofqPKta7r0d0ZjTU2erQ3qQNtQ1qWPh4IdWu3SE7rHUjMx9C54TC2tC6yt5zceZeIGdozQw0KzTr/nvHRrRl4X0yM68Q+pqquDW7IxoZa6OQzy+2n5QdrgHkcflidqUZHOXS/WAQUTQI+4/7P+DyuHgU9oialPrn1T948PUBdj75UmZbdfQ0ELqhH/aMtqfWfUvOoV57holPdLEIFqV70PJwS5hsN0GLQy1gvtscwYnSOe1UFQW8AmioaODibxdp7h/lZaDtQKzvTroCXQ6+XCPsNb+mki4dF1wuIPGvRITPC6e29WzUE9/Sv2HE1RHQ2EgGq0ZfGw2ADOAAZObHt/RvyCuk68MItZpefHuBybcng3Al0OtsL/x5/088CnsEHp9X5bbVFaW2dm3a8vR70xGeGl7C3gyyggk8KBgVlgoA2aTBsgk21FXUFZ5Sy1AzMdM1Q6cGncAiWLQb8t53e8sUwqvJCAME5vrmmGw/Gfoa+tjVdxe8//DGjj47oKMmqj93++6Gix8vYsLNCZj1YBZt9h8AtNVEyuTyuGkX8ArAE/BofQLIDAXhA4okKlIKlsIhAxiSgqmORx1plr+jro2CX5wf8gvzqywIkcpJhX+8f9k7ygg7Ezu0MyPtkmfen4nYrFi4dnOFazeyNO6wz2HkcnPRwbwDRjQbgfXd10OwVgCPKA98Tf2Kzqc640zgGdgfsUeTf5uItW+9v/SAAiFQw9uIFCRnKcbRwDMsGU8+JQAAXi/tXqFj1wxuhvk9bajl/EI+svMLkZ1fCD0NVdibG6CDlREKeTU70lCZiQkOlwdNVXrgITOPCTwoK1dHXqW0Z+59uQe1DWrof74/Wh1uhcScRKxxW4MX316Aw+VRx0zu0LDE9tRV2GhZ30DittOe3yWud67vDHtTe9q6mMwYiRlyykhkeiQ6neqEe1/uVboN4TMOAFz7dA2EK4HBFwdTThepnFRsf7O9zDJBZSEslSztc6znCBNtE1jWssSSDkvgNskNA2wG0PZd/mw5JXwqdD1Z/IS0ui0aLAeAbg274fDAw7R1z789p16r/KMCjY0aIFwJpOSm4HnEc/D4PCgLb2PeIjwtHIK1AgjWCiidq+ryXa/OMIEHBSP8cdvVrlzda1FCkkNw7dM1hcwiMtR8zg0/hzZ124DL48JIS6SgraeuV6VifcpGYAJpg2ama0atYxEstDVrSy37TfeD5++eYsce9ztOvc7Mz6Q5HXQ53UXmWQ/C0i5VFl2ETFdNt9Tjis8eZeVnwT1ScuquMDuiaBBFIBBgyu0pyOHmiO0fmR4JjY0a+PPenwBIr/rR10aX2H51IrsgGzPbzMSuvrsAkHaaAJCUk4Q1XddgV59d+Pf9v9j+Zju+pHzBpp4ib3RJriZCC86vc7/iD4c/ytUHlkAPa66nwnnzc2x//BkX3kWBU1B1D4DjjpP6IEcmOILFqnhQfLyzBfU6KSsfdmsfAxANolXZLHB5NbvUojyk5xbgnNd38H/qXXC4PKirsjCjqyW1D5PxoLxoq2njw58fcHsMPcj7I+sH6uwgHYAc6zpSZRQAsHYwXV+oOGoqLJp7jNtf3dCyvj6efEooUfPBf4Y/0pel0zQS9vbfW+H3owjiskmXhrq60pVzpSwlg+e/3yEzF+99uYeeZ3uCL+Cj6b9NsfTZUky/N126zlYRkemkiLOFvug6uq33NnRt2BWL2i/C5RGXsafvHgDA1jdbAQAeUzxwO/Q2noQ/gbGWMZZ1XIZZbWfR2iUIAjPazMDtMbdxbLCoREFo91oU4+3G6HWuFybemijz91cZLn28hPYn2mPuw7lw++4GAFSmCzNxK3+YwIOCUWOroVODTjDVMZVZm7+62B+DfPCO9ca8R/OQV5iHU/6ncKD/AdTWro3M/Ex8TPwIDpej6C5WOTdCyNKI1nVbw1zfvMT9HOo6oL15e9TXq49hTYZRN+r5j+bjfex7xGTGICYzBrFZsbTjZF0SINQTUGXTAw/FUw6Lk1NADxhMuzsNXU93FROWSspJoiy69nvvF63PTaIJd1noW2BTj01IW5aGLW+2AACiMqPQ62wvnAk8gyvBV9D1dFdq/4D4gHK+Q+XBM9oT7U+0R5N/m1AK64cGkuU1wgDMGLsxAIB1r9bh3/f/0jJgzg4/i5HNRuLU0FM473IenJUcuE1yw4uJL2BtaI1jQ44hakEUALLcR7BWgLC5YbjgQtbz2pvaY0/fPeARohKaf1+GY8XNIDRd8wgZufIfhKYVcbLo27xy97iisYrO215SrzVUyccXFRZR48Uly3NL3/v8K1bfDsbcS2Q2T/7PjIc/OlmiX3NTdLI2hn9UOpZf/4Do1NwyWisfmx+EoEuRz4RBeoY0HgK/6X5Y2mEp/h3wL21bX+u+MNBUg4GWKnxW9SrXIMnOTB8h6/vh6cIuaGisjU7WpLCu7aqHOOYeIfEYfQ19hM4JxZ9t/sTmntXH5UJ475H2edpAwwAeUzzgM80H2qqiAPpR36OU29SV4Ct4HvG8pCaUhsiMSJjqmEJdRV3i9lHNR2G+83w8/N9DbOu1DSOajUB2QTZWvliJvv/1hYmWCVV2IYkhjYfgj9Z/IH9VPk4PPY2I+RHgr+EjbnGcSUSYtQAAIABJREFUmGX2haAL2P9uPxY8WoBhl4bhTdQbmb7X8jL2+ljqtXesNwDyM+9j1QeWtSxLOqxcxGXFYafnTmYcVgoqiu7Ar87n5M8w1zOnUnGlYX239VjjtkYGvWIAyFndibcmYnH7xRJVpn81dr0lZ20LeAWY92geAEBThRSvEkCA6fem0+zB8grzEJcVh0a1Gok3VkOYfpec9SivOGzQn0HQVtWGCksFDfQboO9/feF03Im2z6Yemyhl8cScRIy8OhKz2szCJPtJUvdXAAGamTSDiZYJbb25vjmODT6GNE4alj4Tt3IrnqnwJYWsM47OiEY9XZElV+0dogDGo7BHyMrPgo6aDsx3i4Iyf7b5E3v67YEaWw0/sn5QN/7A+EDEZcfBM1o8M8ThiAM29diEH1k/wBfwMcVhCpqbNEd8dnylvl+jmo+q8DHlgS/gw+mYE0Y2G0kp1APAucBzmOIwBTPbzMQMxxnUgKH4A/L4G+NxYzQZzGpZpyWujLxC2961YVfasrm+OdKWpVG/QytDK1gZWmFsC9GD1ZY3W8Ap8IMmvzXt2Cs+0ZjWRbqHrLKITZc+GMkuIUtiTneyBEOFzarxpRZlcfx1BE69+Q4AuP8hDiNaJyImjYPaehow0VXH4QmOlBPCpffRuPQ+Gt+3DCxX23y+oMRMlSMlDFwZpMOhrgMc6jrA9wdZwrixx0b83elvEASBdM4XWBpr09xKykJTjQ2bOmRW24JetjjoRtaxb3wQAnNDLfSzkzxQPzjwIJ5FPAPhSsBM1wzh88JLHMAqA5+TP4MAAXO9kicBykvHBqQzyPVR19HvfD8AZObDZPvJaKDXAOvd16PXuV6IXRRLuwdKgsfnISA+AI71HKXuV0XZ028PVnQu26mkn3U/9LMm36dGfVFWzcRWE8FmsUs6jEKNrUZ7RjHVMcXXuV/R6VQndLXoSk1ECJ8dATJbNGJeRJVnGZjpmiE2KxZDGg/B0o6i553H4x+Xuw3hpEvxz37k1ZF4E/0G/W36o5lJ6RlJsZmxuPn5JuY4zalA76s/TMaDgonMiMTFjxdlap0nqJQGNkNxPKI8cOvzLezw3KHorigFwgttUaFBTqFoYOH7wxf/vPoH8x6SN5YD3gdguc8SXB4XfAGfmm2vSQjf/6hm5RvIGmgYQJWtCoIg0MeqD+UkUZT6evWhq6YLLVUt2NW2Q1RGFNwi3WTSX0NNQwTPCsb/Wv5PbNsfrf/Ako5LaDW+eup66Nmop5i4pIEGWTtcNENDUoR/p9dOhKeFUyUje/ruwcGBB6HGJgUG6+nWg0tTF4xuPpoqLejRqAcc6zqigX4DuE8WlVuseLECB94fwEGfg2h7rC20NmnBcp8lrRxl7oO5OOF3AgCQkJ1AlSYU76PQ2lLW3Ay5Cd84X1rQAQD1QAfQUzkJgqClNAtriyuCgYZBqYOB11Ne49zUdvi2eQDmFdFL2PggBA2X30fD5feRnC0fEbD8QrKko0+zOmXsWTKSHkq9V/SkhBNV2QS4/F+vvDA6NZf6/LY8pCvOTzn9Hp/js9DeUlQSN71YkCmPW75yG0nZJHy+AAdelKwJwyAbHOs5InZRLJZ2XEr9DjI4XBhoVd4WVU2FBe0ioqMz//NFZAoZWE7Kykd8Bl1EsKM5OQCPzYqFV4xXpc9bFfjF+6GZSbNKCUuWRE/LnihcXYiO5h1x/+t9HBl0BK7dXal7yLyH80rVLkjOTUbbY23R5lgbdD7Vmcp+qyp01HQqPItvoGGAlZ1XggCBxkbiDivlRVddF4EzA7Gv/z4I1grwftp72vbv6d/BWs+C+gZ1SkOjKtBV18XwJsNxc/TNsncuAbNdZjDbZSa2vlvDbgDIv3vxUtkVz1dg8q3J1PKQS0Mw9+FcRGVEVbof1REm8KBghNZq5wLPlbFn2TDZDrJFeAGRVGsthC/g42rwVWpQfTbwLJWKV1NJz0vH0UFH0cigEQbaiGbNRjYbiTVua6jItjqbHAyl5aVh0q1JUNtQczzkBQIB4rPjweFysNB5Ibb13lapdv4b/p/YuoG2A+E3ww/xi+OhoaKBxkaNEZYahrisOGzx2IKA+AC5WW0CoJxxclfkIuGvBKzrtg5bem6h7XN7zG24T3ZHH6s+CIgPwLOIZ5R+BABKf+Br6leEJpOuDV5TvTDfeb7Y+a6Puo5LIy7h6YSn2NZrG+6NuwevqV74OvcrVXpQWuqs+gZ1PIt4ht1eu3Hg/QH8cZc8t+lOU3Q62Uns9zi8yXAxhW5ZIBAIMOLqCGpZQ0UDuStyIVgrKLXmOHBmIPb03YP9/fdTWhCyxNrQGn2s+oAgCCzqbStxpvuoewScNj7Ds58ikLIiO598IJ/R1arSbairiD+m1C5iC6nGZkEgAB59jP+lQu4jDosyg0oqNRnTVjTza2emj4W9REGuQfs9ynUenoS2P/7IwI4i7go1Ma24kKccwax6uvUoEXIASM/lwkBTtZQjymZxH/pgsut2N0w/64O2G5/BeTNZPuAbmYp+e9zhtMEd7Q3I+nfPaE/cCLmBQn4hMvMz8dvZtbgX8gofEj4oxXdgXdd1ODjwoEzbVGGpgM1i48CAA1jVeRWljzSk8RAAgM8PH6j8o4KtHlupoLeQkKQQmGw3ocSMPaI8sOTJEnxLE3eJkAexmbGY93BepVxJNvTYAO5qrkwzXNrUo7ufWdUi7wsFvAL0PNsT4anhVSJAKRAIoMpWFQv0OxxxwEb3kstKykN9vfoAyAxO9Q3qePj1IbVtl9cunAkUWY8Kg3rCjMVfBabUQsEIhSDT8tJk1qYy3ACUGYFAgLcxb+Fc37nUFC9NVU20rtsal4MvY5DtIIxvOR75hfnI5+XjTMAZZORnwMnMCaOujYKhpiFWd1mNhY8XwsHUAX4z/GhtcbgciW4C1RH7I/Z4PvE5wueFg8vngsPlQF9DH+c/nKf2SeWkUuKCaZy0amPHVV6uh1zHyKsjAQAdzDtUOlXQXN8cbeq1QWZ+Jjb22AgWwYKhpiEMNQ2x5uUa/OP+D7XvjZAb+Pv53/j7+d8ASCuscS3GYfaD2UhdmgpN1bJvXpHpkRh3Yxxcu7mil2UvifuMtRsLx7qOUFdRB4tgSSwz0lXXRWeLzuBwOXA44kCtn99uPua1mwfLWpYY1XwUamvXxvsf5CxHWemvVoZWWNKR9JEXalD0seqD7/O/w8LAAtc+XYOWqhZ01XRxPug8jvgeoY7tfa43rS3Clfw8IjMiUWdHHeSvyocaWw0EQaCQX4jH4Y+xpRc9mCItybnJ2NprK1I5qbj75S5sDG3K9ZloqGhIDMjIk2+bB+BrYjb67CYzSo7+TJlfc/sjekmRnVAcoW2frkblHzU0VNl4+3dPGOuo4VlIIj79oKvJG/y055z5ny8Gtyo95bm60nnbSxyb2Aa9i3w2CZn0LJUNw+wwzqkBzntHITEzD83r6aFWMetSXpHMkLDEbKTnFkCFzcLH2AwQANbd/QTbOjpY3Fs0MCWtSskZct/INJjqa+BVaBKt3UK+AKrsmiHKdsUnGq53gpFTwMOyfk3wZ7fKB83kQQaHCz0pAw+/d2qE3xzrIywxC08+JeDIqwjKeQYAxh17C89wkTZMYXJbDGk+BCtfrBQ1IlCBRd4tvP+UCJbGK2wemomxDootSXWo61D2TpXE3tSelg24occG9LLsRd173CLd8DjsMUY0GwF9DX3cDb2L4CTx55497/ZgzztSzFGwVr7P6p+TP2O/934MbzIczdG8wseXp8Siogh1iYy0jHDt0zVMujUJQxsPxe3Q27Deb42VnVdiQ48NMj9vUdrVb0cFPYryLe0bknKTJBwhjhpbTeJYS1iGKszgmHJ7CuL/IrW6pjpMxeXgy9S+DQ0aUm39SjCBhxpEY6PGsDe1FxOOY6BzNvAsJt+ejCsjrmBk85G0bYX8QrAJNgiCwLQ70+AXRwYQJtycgAE2AzDowiBaumHkAlIxOJWTioWPFwIA/OP9QbgS8JnmA8d6jkjOTYbDEQfEZMbI/UYjL4o7pfQ82xPc1VyosdWoi2Z9vfpwru+MEU1HQJ2tjql3pgIA1rqthX+8v5iuQHXmY+JH6nXLOi0r3Y4aW00s/VBILY1atOU5D+l1gM+/Pafsqz4kfICTmRPWua3DaLvRJdYWZhVkwTPaE2mckgOdTU2aoqmJqBQhJCkEkRmRtHKBQ+8P4bDvYezoTS9DUmGpUGmdva3IB7ILQRfQzKRZpQS/CIKAhQGpxj2imSiboLNFZ/zu8DuSc5Mx8AI5g+8/wx8vvr3AiGYjYLHHgtbO/nf7sbjDYvD4PPjH+8slY6TTqU5Izk1G8pJkbH2zVandhQiCgG0dXWz9rQWWXQ+i1ifJsOQiLDGL0gAoqsRfGUx/Ht/PzlSsHt1ER/TQxilQjGVoVXDubSQt8NC0rh5C4jJhbqiJ6FQORrc1B4tFYIKzRYlt6GrQnw3s1z8V2yckLhO3A0SisZ/js3A38Adqaalh73PJ5RX5hXyosmtGAu3Sax+o16c9vylV4KGQx0dWXiEMtKR/xtPXVIWjhSFaN6gFK2MdHH0dgbBEsqSuaNABIB1SFjgtoVx5ujfsAfdv5Cw+C1pAniMe+augtXkoGhtXPjVfGrILsnEl+AoG2AyQqVh7SaiwVNDLshdUWCoo5Beir1VfPAp7BIOtBnj0v0cYcmkIta+BhgHcJrnB/oh9KS3KnujMaABAA/0GVXre0igqwj2x1UT8r8X/wGaxsfTpUmz33C5W1ikPzgw7I3E9QRDlvm93MO8gcV+hs4pwW0JOArUcnxNP08uKSCPvj0WzRX8FasadohojTLFhE9JHFhlth/IRkhwCQORvTK1PCoHqP6pgrWfBL84Px/2P07ZfDb5KBR2E/scWeyxwYogovW5EsxH43Z60YGpzrA14fB6GXhpK1Zork49xRXgU9oi2fHfsXVr6J0AK33lN9cLiDosx+OJgar0wApyUm4TOpzrDZLuJmBgjl8dFSi79YUdZSeWkwvWVKwDg+cTntBp9WTLHaQ6WdhAXepTE0mdL8d+H/7DefT02uJc8W1CSq0VpHPM7RmV3CLn48SI+JHzAyYCTtOCDpODShh4bEDgzUOazJ05mThhgMwBxi+PgMcUD9qb2WNR+ERroN8CB/gfQvWF3zG9HZhL89fQvjL0+Fn3+64OYzBiZlkNxuBy0OtwKX1K+oH399iAIAqeGnpKqfrSqGN2W/kDK5QnQcPl9+EWlwXbVQ2x5+BkCgaBSaee9d4v0OYoPeGWJpYkoiywrr+YGHorqO154F4WQuEzM62GN10t74PuWgeUa+E9ob4FTU9pi58hW5T7vyMNeOOsVWWLQAUCJ1ozVnYTMfKV6b5k/v9/6UmY8FIUgCIxqa45ni7riw7o+1Hq1Yt+nKUczMK/Zc7iPD0Nc2BLUz6OXB7/6koJBZ+aJOSDJm5jMGMy6PwsWeyww9c5UhCSFVOn5H4x7gM09N2NiK5FVZFGB5gktJ8Dzd0+0Mm0Fx7oiccmhjYfKvW/RGWTgQZj+r4wInwu29d6GglUF2NBjA/a+3YulT5dWefY2i2CV+5wL2i3Akg5LxNY7m5G6XS5NXWjrUzmpuBFyg1ZiIwxKVEXZjTLBBB4UjHDGXTirJw1fUr7gcvDlKhevqW7YGJICaybaokESj89Ds4OiWWLHo+QN4saoG3jzO2n5U1S99uJvFzHXaS6VUv5swjPMaTsHV0depSzyAMBkuwlNpd8jygMJ2Qk0G6HPyZ8pW0ZlJK8wj2brePG3ixhkO6jE/ZNykvDyO2mxtq7rOjyb+Iz6m3hEeSA5Nxkm201AuBLodbYXCFcCahvUYLzdGDw+D+l56WI2jcqEzw8fAOSDQ49GPeR2HlW2Krb23grBWgHC54XjxcQXiFoQhYS/EsBdzQVnJQc3R99Ez0Y94R7pTnlk5/NKnrUWRtaFdarlQUdNBzkFObQbslAM99LHS2hv3h6pS1OxpMMSierMqmxVsSCVLDHVMaUUyIXMdpqNF5NeYE+/PTg66Chcu7ni0sdLNAGrp+FP8TVFeoE8/3h/fEggZ0n/7kSWwUy2n4wmxk2kbrsq6GxjLLbO5aAnCgr5OPwqHI3+fgDrlQ/BrWDwoV0jQ7Kt1uICXLLE9qdaPwDk1OCMB9bPci7PsGSsuElmqXSyqVgWmYYqG90b10bv5nXEBq8h6/vh+5aB2DS8RYnHj2tHBqrUVFj4urE/NruQ+wpFRKs7MWkim1FnS/L7u/bOx5J2r3LeRpDBeWkziEpCT0OV0gEJ+acfIjYNwLsVPantt305mHDsMzjFhEm7N1NBFvsRwrKeQmezDla/WE3bnpKbIreAxOmA0zjkcwipnFQAQBeLLnI5T0n0tuqN5Z2Ww1DTEHkr8xAwIwBnhp1Bb8veeD/tPc4OP0tlED743wOs7LwSdXXqIjM/ExFpEXIdXEdlRKG2dm2ldiIpiipbFZtfb8aCxwuw3XM7vGO95fL36X2uNxY9XiS2nkD5Mx62vtmKve/2iq0XPmO1qEO/jgrfh566HrWum0U3AEypBUMVo8JSQX/r/lStjywo6Yfj+8MX0+5Og/sUdzGtAQ6XQ9V013Sc6zvDwdSBUutN5aRSTgxF2dRjE4Y3HQ6ArMXjC/jY2GMjujXsBj11Pezrvw/7+u8DQCof97Qkb9C9LHvh+qjrcKzriIZ7GwIADg08hPNB52GsZQzTnWQa4M3RNzH88nDqfMcHH8fU1lPl9r4ry7yH83DM7xgA4NJvlzDabnSp+6urqGOqw1RMsZ9CDQgv/nYRPRv1hNt3NwggwIWgCwBAlQoI2ftuL7a+2QoAODvsLBY/WYw3v7+RqUq1tAjFEk8NPVVl57SsZSmmTK3CUsGwJsPQum5rzHkwB3e/3AVAakHwBXxk5GUglZMKgiCoYyuT8aCjpgMBBOAUcqClqgWAtJoVYqRphFqatSotsClvpjlOw563e8TW9/mPnN3L/jub0iOpDEWz1Yo/bFQHjk1sg7DE7DLFBsOTsmFlolPulHptNRU0r6eHXaPkn148qGVd3PsQh+wanfFA4FtyDsYdf0etc/oZ3KkoehqqCFxLfv8jkrLRyFib0qkZ3dYcDY218P5bGnY/+0I77p+hdmjXyBDdGteGKptFCX/mcZUnK0AaPsaS+iG3Z3eEhiobffe446J3NDYOa1GipWhVInScaNfIqIw9K8/8XjaY30vkflNHTwNL+zXGtkehtP201NiY4GyBv/o2xtfUzzj97QCMtYyRnJuMDa83oHnt5hjdfDRaHm6Jj4kf0duyN55MeCLz/uqri54NhjcZLhddgvKirqKOVqZkNpGk91pbuzY29NiAja83Ii47Dlb7rNDOrB08p3riW9o3aKhooJ5uPZnZS2YVZMFCX/pJzapkk8cm6rXzCWd4TPEQm1iQlm9p31Bbu7bY+v42/ct9Dy/J4eV0wGkApLhkUYQZ6Zt6iN6fsOTzV9Plq/mjTCXHI8oDbBZbJlHajT1KV2P96+lf8I/3h3esN219fmE+tDZpYdnTZVL3oTpgY2SDV5NfURez0wGncT6IFEb0ne6LuMVxOO9yHn93/pt2HItgYUXnFehg3qHU9gmCgEtTF1gYWOCCywUcHngYM9vMxOspr7H77W5qv6JBBwC48ukKANKSr6gSrqJ5F/sOeup6mGI/hXL6KA09dT0cH3Jc7GbxR+s/8J/Lfzjvch7nhp9DP+t+ODroKG2fxU8WIzEnEYk5ieh3vh+Ck4Jx0v8kbZ+QpBCY7jBFZHqk1O+tovD4PMxtNxepS1NRS7NW2QdUAQ30G+D6qOs4PfQ0ld43+OJgGG4zhPV+azgedaTqJrXVtNHOrJ2YfkRpaKuSg3JhG1weF+Fp4XAyc8Kb398orKa3IixwXoCnE57i+ODjYtuGXpIu5TUzP5N6raumW8qeyomGKht2ZvrYPboVShtbTTrpDZuV5bsu8fkCvAlPhrZa1cxtzOhC1uHHZ9bclNXAmHR03+FGLb9e2l0m7Vqa6NAGOmwWgQ5WxpjSqSF2jWqFiE0DELimD96v7AU2i8BQezMqW8LCiLw2vAlLxuFX4dXiAfr991Sk5kjWePn0IxNsFoHGprpobKqLuT2sAQCWKx7A42syUsrQQPmWnIPo1NxS95EGYSmRNGKtlWFWN2vsG0sKN7a3NIL/6t74tL4f/h7QFKpsFuWcc3P0TSzvSFoJj70+Fmvd1lJ6SE8jnoJwJfA9/btM+ybMvtNT18NC54UybVteXB91nXr9LvYdNDdqwnq/Nervrg/WepZYKWpliM6Ixrx28+A22U3qtqqSyAWRCJkdgifjycCNPErIBRCAgPjN7tzwc5jZZqZMziGcXCtOUQt6YcaE0L3rV4EJPCiYyPRI3PtyT6Y1PiXd/IU/tOLbhQ/OwnqjihKaHIq7oXep2VRl50LQBeht0UNkeiQEAgGuBF+htlkbWsNUxxTjWoyTybnGthiLGW1mUMuBCWQU9PPsz2KD+CfhT0C4EnC54oIBFwbg9ufbMumDNHhFe+FDwgdMaDkBJ4eeRB0d2Sjej285Hg//9xDTHKehcHUhClcXYpHzIuzssxOhc0QzK3W062DRk0XwjPaEQCBAYHwgTvifQEJOgpjYYlUw7sY4OB1zUpqggxBVtiom2U/CqaGnMKHlBFqda3peOmUJa29qj7d/vEVbs7blbluYHSVMlQ1NCYW1oTVmt51dZhBOmehl2UtiNtjzb8+pUonKkJFPzpKedzkvs5kqRTDcoT7CNw2AU0PJs+jFXRRK47B7OPK4fITEZ5a9swywMCYzcYQz75IeKqsD9z/EYeXNILyNSEEGh34/TcoS/f072xjD3FBLrn3R01CFS+v6YLEI6GupwkRXPF27iSkZaFt16yO2PPyM4B/y/bzbbXqG/ntfV/r4l58TMfKwF3rteiWxdMg/Oh02tXWgoUrOmjc0EmVCjT/xDr12vZLYblYeFxvufUL3HW7ovO2l3AIw2flcaKqyoaIAIc8hrerhycIuODLRUcwtRY2thsfjH6NTg07Y3GszXk0m/05CV6Ybo0SlpC6X6bXv0pKVnwVVlirSl6Wjs0VnmbYtL1yautAsFIuLHZtsN5F6TNDsYDN0PNmRJoRdHWig3wBNjJtQ91J5/JYEAoHc7tXCsUPxLErh+1jyVKQLUZ2fF6RBqqsXQRDfCYIIIggigCAIn5/rDAmCeEoQxNef/9f6uZ4gCGIfQRBhBEF8IAiitSzeQHVHeMHZ/26/1G3RrI4kMNWBTOMvbvEmjBj3bNRT7JjycO3TNQy5NKTaiFsKI+6Pwx/jsM9hvIslU1cd6zrS6q/kgfcf3uCv4aOxcWM8n/gcj/73CAudF1LuGIBooDfs8jCZRL4rg0AgwKz7s9DhJDmwlGUpUHHYLDbYLDZ29t2JRe0XwdbIFol/JeLTrE9wn0IK1O3w3IHlz5bD/og9dnrtBAC8iXpDS/mvCiLTI5Wq7KM4eup6WNJhCb6lf6Ot/+vJXyBcCTgdc6pwm32s+sBtkhulFG5X2w5f536liWlVF0r67FofaU2V0FSEkKQQMpgz9W2ViIXJG4IgcGSCI9YObob1QyXbr/H4ZV/nvX6q4udXUQq+noYqtNREKdbV5V5UnNkX/HD+XRTGHH2L0UfEU3k1VFmY2N4CZ3+v+O9YHmir02fei9f+y5qEzHyExGUiJC4TGRwubFY+gPsX0v7u9dekEr+bAoEACy8HYMpp0kEoNacAF95Fie33OT4LreobUMvDHMworRIASMvlouHy+2i4/D4Ss0QDwxbrnuC4h+ia2+jvB1h2rfLBzJLIyius8myHotjW0YVeOYRiu1h0gd90kaX40CZDsa8fWZbqH++PHZ47aJli0mCmZ4bujbpXu0Fc6JxQBMwIQB1tyZM5kjQIyktOQQ6yC7JhqmOKNvXaVLodRUJNlFZhxoP9YXup/u4AqOek4mXrxcvbAWCILel8YqhZuZK56ooswqbdBQKBvUAgEH67lwN4LhAIbAA8/7kMAP0B2Pz8Nx3AIRmcu9oj/FFVhYXM0CZD8Xn2Z7SuS4/5CG8AaXklW+yVhtD3NighqIw9lQMOl0x1Ss9Lp3QZprWeBp/pPnI/N0EQ1A2SRbDQ17ovdvXdhQb6DZC2LA0eUzyQuTwTp4eehp66Hvzj/HEz5GaVp7B+TPyIQz6H0NCgIZqZNKOCVlWFibYJmpo0ha2RLRa0W4AuFl2wzXOb2D7OJ5zxr/e/SMopn/eytERlRKGBnvJYU0lC0g1OmNL3/sd7tDzUknJZKQ91deuia8OuYgHL6sio5qMQODNQzC2EJ+DhTKBki63ScDjigBn3ZqBd/XZS6UQoE7W01TClYyNMbN9Q4vaCQj4+xmZIVPsXCATwi0rD669kwHR8KdaOskaZ3AcqSmRKDhouv09b9zmeDKoeHu+IHk1qw1RPA5//6Y/1Q+2UdpCVnV81GhvXfWPw6UcmuDwBDrwMw8vPiZhwwhvHXkdI3P+vqx9w0z8WANDCjAw+rr0TjA8x6Vh27QNmnvNFdGou0nMLYFjEnpXNInB5Rnt83zIQ9+d1orW55lYw3L8kIa+EYMtln2hZvFUaWfmF0FFg4KEiONR1QNqyNHBXc8EiWLRA9ZKnS9DyUOVtqIsyx2kOHo9/LJO2qhJzfXO0Mm1VYnnIIZ9DyCnIwZwHc/As4lmF2hbaaO7ovaPa6rbJM+OhV6NecDB1EFufnJuMjLyMcrVhomVCaV4VRTgOKp7Foq2mjYXOC2nPZ3V16wJAtRH/lBXy+EYOBSB8gjsDYFiR9WcFJG8BGBAEUVcO56+WyOJBwtrQGuNajCvxSxwQH4Dn355TaddChIGHhY8rVx8nnHW+HXob72Le4YTfiVIvFrncXISnhlfqXLLkpP9JHPA+APdjw62zAAAgAElEQVTJ7tjbT1ydtqox0DBAxwYdQRAEJtlPwuGBh7HixQq4XHEpUcjmXcw7+P7wlXlf1ritAQB4TPFA8KxghZYW7O63GwucF2Brr60473IeYXPDIFgrQODMQPD4PMx5OAcz78+ER5SHXB1d8gvzEZcdp1Se2JKwMLDAIudFCJ0TKlFAKSgxqMIPIy+/vYTLZRe8+v4Kgy8OxsrnpWdXKTMt67TE1t5bkbYsDTv77KTWb/bYjC0eW8qlau323Q2EK4F8Xj5efHsBr2jJv8/qTldbEzHdh4H7X2PQfg/YrnpIcwEAgAdB8XA5SLr4dLYxxsqBTauqq2heT5StJsy4qA5kcLjout2txO19m9fBsYlt8Ga5/Bx0ZEVCRtVobOQUFFKTNvlcHmLTycmEyBTxWmkuj4/rfqJA67U/21Ovhxx4g8s+0XgUHI/RR7zA5QlQS0vyjH7zevp4vECkxfUoOB4TT3rj1JvvAID5PW0wpq057ZhVt4LAL0eGUHkhMx7kZ00raww0DChHI30NfQT9KZqcWtdtXbkdBGoyyzotQ/i8cOzpKy6A/Pud3/Hv+3/R+1zvCmWIxGaSQTYzPfk6CskTC30LLOmwRC5WoMeGHMPC9uLjHRbBKneGReu6rdGitrgQZWIuadVdtJQGAAr5hQhLDaNNMgtdtRiNh4ohAPCEIAhfgiCm/1xXRyAQxAHAz/+FT75mAIqGgGN+rvulESryFlVGryylDfb5Aj6WPVuG2Q9mUynFAoEALQ61gF9ckZS4S0NBuBIYe30seHweup/pDlc311LPm80lf0gB8QG49uka5j6cW2ogZe6Dueh8SnG1eMILy9fUr9jvvR853BylnM0d22IsJdRUUnDB+YQz2hyTbSrdx8SPuPX5FlgEi2YhqmiWdlyKcS3GwcqQFJLTUNGgUtRuhNxA51Odse/dPrmdX5gloOyBBxbBws6+O8mSlZxEiftIitSXRv/z/XHz8010O9MN977cowkkVVcMNAzQyKARbd3fz/9GSm7Zg9bLHy/TloXaLTWNM787wXdVb9q6iCSRLV6nrS9p6e0pOSIdgm0jWoJdhU4AawaLSkOu+JQ/o0fRtN1An83saiuyyNw7xh4EQYDNIqr0b1kRig7Ul98Iwo90+V8bBALyHwAExmRg1S2yjp3PF+CKTzSiU3PxMjQRPL4AtwNIa+ZNw1vg+5aBUFdhY0YXS7E2f/wMmhhqlzz72NhUl3IDEbL10We0MjfAwt622PIbfRb/v7dRCIxJr/T7LE52Hhe66tUj40ESdrXtULi6EDkrcrD77W5MvjWZ2iZ0YqooE25OwMSb1a/sryiWtSwx33k+QmaHIHhWMBa3XwwANP2x9a/Wl7u9err1MNNxJuXcVh2xMrTCtt7bqOe9qoAgym+nOd1xOtZ0XSO23r4O6eI0qvko2vqE7ATKeUyI0HqzqkuGFY20gYeOAoGgNcgyitkEQZRmzSDprik2UiYIYjpBED4EQfgkJVVN+rQiEQqRGGuJe6lXlPC0cFwIuoD8QnERsKCEIHhGkzNRfnF+yMzPxOwHs/Ex8SMWPl6Izg3IQMCd0DsAgEsfL0HlHxW4fXfDQZ+DmHp7KvgCPgp4BUjJTUFwYjCiMsgaSeHN4lXkK/jG+YJTyCnxh8Tj81BXty7isuNkVuNXUYqLOtrVtlNIP8qDS1MX2BrZYt6jeUjPS0dSThKGXhpK/e1tDG0wxm6MTM951Pco1NnqiJgXobQpvULmOs2lLS9+shiEK0ETV5QVFz9exIhmI+BYz1HmbcuLpCVJ+DTrE5zM6DXhxaPxZdHHiv6w3bKObNJkFY3QLrcoLQ61wJ/3/iz1uOLXjKr2jq9K1FVLf0zwi0pDdn4hQuIy8c+9T9R6o1IGcPLAWIcueFcVpRcvPidg3LG3lZ7VFggEKPgpctjBygjbfmuJoxMdscWlBb5u7I+h9so/N/N8cTdcmSHKIlgqB20DSfAlTLRc9onG0msf0HnbS0w59R5WKx7gr6uBUGUTGNVGNHO6rF8TfHTti/+1a4CTk9tgcoeG1LZ6Bhpi7RZFX1MVe0bbw9FClAVoUUTos44e+b2f2okMao479g6FEoQsK4OiNR5kAZvFhoaKBj4kfMC5D+dAuBJY8XwFdnntgsFWA/zI+lGh9r6kfCkxwF7daGLcpMTS1p1eO/Hqu2Rx06LcDb2LDa834ODAg1Qqf3WkkF+IjLwMuWSxtjnaBvMfzhdbX5GMh42vN+Lg+4Ni64XZCyW5fRXN4BCOuxRpAasIpAo8CASCHz//TwRwE4ATgARhCcXP/4VXhBgARfPQ6gMQu8IIBIKjAoGgjUAgaGNiYlJ8c7WgPDNmQgiCwKjmo9DMpJnMzi8pYmdrZEu9PhN4Bvpb9HHIRySzIQx8rOu6Di5NXWgp2ok5iTgZcBJ3Qu/AfLc5jLcbw+6QHSz2kPW7u/vuxpoua5CZn4mX318CAA54H6D8bCPSIhCWGkYFMza+Jm0/v6TQPcKrgmufruFN1Bt0seiC7b23I35xvFxSuWQFQRCY4Ui6YgQnBuN/N/6HO6F3YLHHAjkFOUjlpFbIGrE8zG83HzdH34SFgfL7P49tMRZHBh0RWx+dGS3T9LU0ThpWv1wN/zj/ajXoNtYyRlOTpnj3xzts772dWq/GVivlKHFuj7mNm6NvUsvjW46XWR8VzYkhJ2jLCTkJOOx7GGOulRzQa2/enrYsy+u3sqGuUvpD0cjDXrBb+xj9974Gl0c+tI1wrA81laqtLTbSoQc60nMlWybKkvkXA+AZnoJvKTll7yyBRn8/AAA0MNTChWnOGNXWHOoqbIxxagBVBTgXVAZDbTU4NTKkBsQ/MuST8VDUhSIkLhMTTniXsjcdp0aGNCcIFouAjroKNg5vgR5N6mDVwKZoXk8PBAHYmZUtHjzMwQxXZ7TH2sHN8EenRljSVzTI2D+2Neb3tMGqn2VGHC4Pi67IJiMqncOlrEyrMyyChTltRa5Umz024+Zn8v6yw3NHudsp5BciPDVcJhN3ykRTk6Zw7Saeafww7GGZz81DLg3BhaALlNtSdcUz2hMGWw3gHuku87YTcxKRWSA+8Tms8TA4mzmXqw2/OD/c/3pfbP3VT1cBAN6x9OuTMKCxposoS0JYdlEdbIhlSaXvbARBaBMEoSt8DaAPgI8A7gCY9HO3SQCEnoB3AEz86W7hDCBDWJJRk/jX+18YbzfGiucrEJcVh5shN0uN2N0MuYnEnESxGcXKsKXnFgCSVWDV2GrwnU6m6z8OFwnxBMwIQKcGnXB08FFwVnKwtttaXB91HfGL4/FP93+wvpsovWvyrclikWXClUCzg83g0pRukbTixQpMuT0FR32PwmqfFWz222DOA7r94ewHs3E3lJ56JG/cI91xPug8Xk1+hb86/CUze0h5MtdpLqa1noZcbi76Wfej1j8Ke4QUTgoO+RySaRDHytAK/W36y6w9eTPGbgx+a/obbRZ66KWh0N6kjTRO5QRTiyN0QhEGgaojQtcat0luFc5kIQgCw5oMg+90X9wbe4+q260J/O7wu0RxssvBlyEQCJCSm0IJ0gqprV0blrUsYVnLEnkrq6auXVGwWQRuzOpAmzEui22/VX1wTluNHiD5kZEHLo+PPc++ICO3bKvnqz7R+BhbsYd1/Z9lBrFp0g22p3RsKNXxysCUn1kDEUk5ePQxXubtF3XMCIwp+XMa2EJ8lrdHk9Lv8ypsFu7P64xvmweWy7UBIIMXUzo2wqpBzWjWpk6NDLGwty0IgsDt2R0BAC9DpZ+R5/L4SMrKR2290jMyqguxWbG0ZWFG7u63u/Eu5h3ex76XmL1blB9ZP5DCSamRGWft65PB7R29RYGYrW+2ovGBxqWWlljWIsuIhGXc1R252GmW4Gqxu99u/Nm29GzH8lK8HFP4PoRi/ACwz5ssDRaWXPwqSBNSrwPAgyCIQADeAO4LBIJHALYA6E0QxFcAvX8uA8ADABEAwgAcAzBLinMrLUJf+80em1FvVz24XHHB9jfbEZclOcYSnRkNt+9uMkknKmkwce/LPaj8o4Ktb7bSom11tOuglWkrvJ7yGsZaxjTRSYIgsKrLKqzuuhref3jjxcQX6G1F1vp2segippz//sd7pC0TH+TNuCcaqKVwUmhKst6x3hhyaQj4Aj7ufbkHo21GeBT2CO9j3+O433Fw/9/efcc3VfV/AP+cdO/SlkInZRQoUKBl7ymyBVGmgLgewYmKAxQfBRRB8VFxgv5EwQnIFBkqosjeq1D2Hh3Qve/vj5ubJk3apk3aNDef9+uVF+m5N+eehNP03u8953sKrf/LuPnsZpMJ92oyFycXjGkxBv2W9sPzm55H5vRMNApohN/P/a7bR0lSY6kPd32I7458Z5W6qouvmy+Wj1yOg/85qCtT1sBecWKFVY6hLE+prIJij+JC4iC9LqFHVI9K1xEfEo9BjQdZsVU1Q7+G/ZA9IxvPdZSX0nJ1ckXH8I74v4P/h6D5QfB8yxM/HftJF+B76++3cDb1LNyc3BwiI3V8ZC30a1bXrH3vbxMOjQ3yEZT8+3f6ZgY2HruO/21JxLubipdKzckvxOK/zxoNf5+2/DAGf/RPhY6p5LdIz6n43+/zSfIoiZbhftW6+kdVmXpX8ajK5fusn2MjJ6/0pTrn3luc5G3h2DjMGS4HoWfd0xyDWoZgVImkj9WlVYQ/nuzVCOk5BVhzSB7ge/V2Nn49UvF7bpuP3wBQPJXD3unfRCmp45cd0X5xeyzav8hoW2FRcT9IyU4BIK8woDZ3NbwLfz34F57t+CyyphuO3ixrFby03DRMbju5xk+TLU+VLqcpmQ48WMNjbeR0hyVHlSrvY8Yf9puY21oqHXiQJOmsJEmttI/mkiTN0ZYnS5LUR5KkaO2/KdpySZKkJyRJaihJUqwkSVW/dqENxIXE4bdxvxmUTf9jOkIXhEK8IXDxzkVsv7hdF8lVomDK9ANLvLTlJYM6FVPWyzGeW5m38N+e/8WpJ0+h4LUCXH3evLl07cLaoVf9Xvj5/p9x7flr+HPin0h/JR0nnyw+mRvceDD83f2R+JR8AfxB/w90n8ObPd/EB/0/wJ8T/8Qvo37BvL7zsOPhHRjTYgwA4L1/38OQ74cgJTsFA5YNQPvF7fHo2kcx9IehWLh7oWUfip5nf3sWCUkJGNJ4iNXqrC76CQ09XTyxYuQKvN3nbWwevxmAvFKBNfx5/k/M2jbLKnVVNyeNE97u87ZB2aNrH4X3W95GSxtV1KqEVQCAKP8oi+qhmsvd2R3v3f0eXuj0AvIK85CSnYJLd4rzIY9aPgq9l/TGhsQNumlqtspTYwt9m9XBeDMukF8f2rzcfarDrHXHdasc5BYUX6x8svUMZq8/gcX/nNOVVfauWoEu8FDxIHnPd7cCAIJ93O1mWkVZhBBY95S85KSrc/FJ/W9Hr2HIR/+gw1tbkJxR9h3ssigjHu5qVgf1AotHGHw9qR1Gt4/EvBEtsfHZ7hBCYGz7SPwypTPGd4rCx2Pj4W3DhIy9Y+QbHU9/fwAA8NT3BzBl2X7cTKvYSKnEG/LF5uCWNSfhsyUejX8UBa8VoHBmodGIWcVTG57S5Wx6ecvLmPvPXDjPckbAOwEInBeIuM/j0CWiS7UmIKxO3et1h5PGCR4uHljQb4GuPMTbdO6GwzcOIykrye5urplSlctpSpBMBmZaf9YaE1dNNPEK8wV6BAIwDoTXcq8Ff3d/g7KhjYcCKP3/U63UM162Brm70d2Y0W0G5vw9B73r90ZyVrIu67mSF6FbZDc0DmyMfy7Kd1jKG1JWWclZyUjKSoKLxgVfD/saQghEB0ZXur663sV3vRoHNsbaMWtRz6+errxRQCNIr+tlOX8xGa5OrgYjJKZ1mQYAiA2OxfdHv8eLW16Ei8YF+UX56BjeETsv7wQgTyX47fRveLK94RSNyvr+6PcAYLCetL0oObRdyTPQp34fNAlsghl/zMDLXV+2+Dgnbp1A8+CaceFQGS93fRkvdH4BLrNcEFc3DgeuH0BmfiZe2fIKGgU0QrBXMC7cuYDmtZsjpnaMWStU/HvpX1zPuI4JrSZYPZ8G1TwX7lwAIOeg+e9f/zXYdl+z+/DAL8X5LUoOF1a7GYNiEF/PH8t2XsTeC8Yj3Pw8XIymPNjKnex8fLdLTsLrpBF4d+NJnLqRjk3aO8dzNySgc8NA5BYU4dkfikdL7T6XggMXU/Fgl6hy81uYO+JBkiT8czoJXRsF4ee9l3EnuzhQMbS1Oi4kATk/QqcGgbh+J0f3nh9fWrxq1p8nb+G+NpXLqZSlHfFwb1wYBsSGYNTnO7DrXAp6NpEvskbqjWoQQiAusmZ8V8dH1sK4DpFYtusi5m5IwD7t7037t37HismdERfhj7zCIri7OEGSJKw6eAUDY0OM+t6Ja2mIDPBURY4HQP4/UlZze6PnG1h5YiXCfMJMfqc2+8Qwh05qTvF3z+NtH7ervEuVNbXTVHSN7Ir2i9vjk72f4IMBHxicFxYUFaDVZ60AAHc3vNtWzbQaa414SEhKwPLjy/Fq91d1ZcObDkerOq2M9s0tzNWNli1Pw1oNDaZNKHZd2QUARqPYfdx88Hibx/HejuIlvJVV2Rxh1KQ+Bh6qyOzeszG792zdz2ELwgyy9f598W/8ffFvqx4zyj8K3SK7wcvVS1cW6BmItFfSkF+YXyVLRg5uPLjM7covlilerl5wc3JDbmEurj1/DTczbyKmdgxWHF+B93e+j+2XtgOQR2rU9rJ8KN3eR/ciMz/TLpImlqQRpu+ICSHQNrQtTiafxPaL29Elskulj5GclYzTKaeNlgGyN84aZxydfBRR/lH4z7r/YNmRZViwU75b0CigEU6nnAYAPN7mcXw6uDjB6vnb5+Hh7GGQ9+Ns6ll0+Ur+TPNfy7f74YtUPhen0k/s155aqxveCwCvdH2lOppUY7i7OGF4XDgGxYbiyJXbGPHpDoPt26b1qlG/I1e0Szt+v/uSye1DF27HsNahuv0AYOTn8ntqFuqLbtFl/93J166ckZxZ9oiqn/ZewksrjuCl/k3xzm8JBtuGtFTX3a4Ab1ecuJqG/RdvGyWA3Hs+pdKBhwMX5WUp3bWBrW8ebq9LZlrT3dWsDpbtuojP/jpjUD7i0391z5c/3gnpuQWY+uMhJFxLxysDYwz23X8xFZ0bBlZLe6tbi+AW2P7Qdni7eiM2OBb3/nQvViWsQr+G/bDpzKYyXxvmU/NXfrEW/UDD9N+nY95d83Q/6+dfK5n82B5F+kXijZ5voGEty0az9P2mL66kX8HznZ7XXQMtHGh6JLWA+ctpNqvdDJfSjP+uKOcHJW9S5Rbk4sD1Awb5HE4my6PGM/Iy4Ovma9Zx1cD+x/fZiUOPH8KeR/fg4rMX8cnAT4wu7jRCg4t3LqKwqNCiYeHKSd/NzJvYeHojJEmCs8a5SoIO1nB48mH8+9C/CPQMRExt+Q/tiGYj8M9D/yDhiQTc3+x+BL8bjBc3v6hbQrKicgty0ePrHjiTegZNg5pas/nVprTAAwDMv2s+vhn2jcV/bP6z7j+QIGFEzAiL6qkJmgc3h5erF5beuxRDmwzVlStBBwBoVbcVlh5eqotM1/+gPkLeK74IWHliJRp+WPxHT00JFal0j8Q9Uuq2s6lndc/j6sbhrT5vVUeTahxXZw3a1CsOKof6uWNk23D4etj2d+T1IRVfXWTVQdNTDsvLU5BfWIT0XPm741o5KzlcSpG3J940XGZ6/2t31ahAjTXU8nTB2aRMLNt5wWjbygOVGyF0KSUL03+RpxN6usiBBzdnJ5tOoaiIuMhaiAgo+xzsvs926EbonNXm/0jNzENRkYR9F1JwMz0XseH+ZVVh1zpHdEbLOi0hhMAvo36B9LpkMumvvkYBjdAx3LxVCNRAOUcGgPn/yqtUKTkvSssjZ68i/CIws8dMi6fRPN3haQDmjZzQCI3ZUzseaPmALqG/PuUaY2zsWIPyK+lXDBL7A9AFG5Kyksw6plow8FBNgjyD0Da0LSL8IjC53WT8eN+PkF6XdHkSFu5ZiHr/qwfnWc5wm13xYTdZ+Vk4f/s8vjn0DbLyszBq+Sj0X9Yfmjc1mLd9XvkV2EjjwMalXjA3CWqCvg36ApC/ZHdc2oHrGeZnyy4sKkTU/6LgPscd2y5sw9GbR63SZlvwd/dHi+AWGNV8lNG2EJ8QjI0diznb5lQ6aCVJEjxcPDC712y0qms8BM2epeemmyyfvH4yxv8yHsHzg5GZJ5/oSZAgSRJyCnLw6NpHdfsqSQdJ/XrV7wXpdQkpL6boMoSbsnLUympsVc00pJU8TeCBTvUw775WNr+IVtrj6qxBw9ryyL/2UXKAZER8OPw8XDAoNgRB3qUvJ9u2nnynavXBq8jJLz2h4W29lTJOXjf9HaNQcm3qT8lYMbkzArwqtqytPfB0lYMBpoIMeQVFuJSShT3nU4y26bt2JxuTl+5DckYujl9Nw5RlxdM1moXa351BPw8XbJvWq9z9lASSGTkFyCsoQtyszWgw/VfdyKKYuj5V2s6aaPP4zWgU0MigzNNFzvHh6uRaY2+qVQV3Z3csHrJY9/OCHQvgPMsZm89sRqhPKJ7v9DymdZ5mwxZaT15hHi6nXTZ76kNplCkb+iMZGnzQAE9veNpoX43QmD3i4c2/3sQX+78wKlfON0sLmMQGFyfCVRYjcLTlNO0jXKxijQMbY26fuTh/+zw+2/eZrjyvMM8oK2ppbmTcQIfFHXQ/FxQVGFyg22MyRcWARsXLOo5eMRoAsO3BbehWr1u5r31/5/u6+dqAHKG0V16uXjgyufQEkodvHMbMrTMxc+tMHJl8BDFBMTiRdAKL9i1CkVSEjwZ+VGb9+UX5+Hb4t9Zudo3w5/k/y9yempOKgHnFd2/rf1Af2QXZuiFzo5qPwrv9zF9bnNShlkctnHn6DILnB+PB1g/q7jDN7TMXgxoPYqJRAB+NicOkLlFoXUPuxNbydEX/5nXxSLf6+Gr7OZy5lYmHukbh43HxCPJ21QVGUjPzcPDSbVxKzcLM1cd0r/9kXDz6xASjyatyYuSmr8n/jm4XgRf7NzUIFNzOkoO8sWF+OHLlDo5euYMWYaaXsFOOq5/bIS6iZnxm1tarSTC+2Ha21O3d5snfx9tf7o0wf9MXjZ3e/gOAHEBarR2R4u/pgjnDYuFj5nKXNY0QAismd0ZhkYQbaTlYsPkUxrSPQGZuISb3bKjrawCw42wyGr+6weD1AV6u6NBAnVMtytK3QV8kPpWI/MJ8TP99Ot7d8S7CfMIwusVou58WWhmT4ibhwp0LmLVtFp7f9DwAoN/SfgCAjFcyDKZa27MD1w6g45cdsX7segyMHljpet76Rx6VqH9xn5mfafIm3cjmIxHkGWRWvcduHcOxW8eMytcnrgcA/H3BcCq9cvwXOr+gK0vOSpa3VcHKHTUZAw81wEtdX4IkScgvyseak2twK+sWDt84jNjgWLOSjvx47EeDC+zdV3YjISkBz3R4Bl0iuhgMz7I3EX4RKJxZiO+OfIfxv4wHAIxdORaXppqes6tv2ubiyO/aMWuNMsrak4KiAhy5cQThvuEm813ov7fYT2ONtpcVeLicdhkR70fg5S4v4+2+b5e6n72a0GoCCosKEVc3Dp/t+ww/jPgBf1/8G1M3TtXto/9HSP93Kco/CtO7Tbf5nVyynZvT5Lmzd3Lu4ETSCbzU9SUbt6hmia8hSfwAOYnkZ+PbAACCvN0Q5O2GXk2DjRL11fJyRa+mclLCoa1CkZKZhx1nkzGgRV0IIdAy3A+HL9/R7f/Dnkv4Yc8lvDa4GUa2DYePuwuSMuTvjPGd6uHF5Yex6dj1UgMPGu33x+5zcjAzJsTXJkuOVodODQPRLToIfyeWPXz4hZ8O4dMH4uHvWfoNltV602C+f7QjYkLsb7SDvjb1in9XlNE5iqGtQnVLbpqy85U+cFJpnzGHi5ML5vebjxndZ6BIKiozf5iaaYQGzWubTgD+yZ5PdMnbSXY7R84Noz9dubTlNPUTUFrq5+M/G/ysBBfOpBTneflw94dWO5494VSLGkIIgcVDF+OJdk8AANotagf3Oe4G+1xNv4rsfMO5pHmFeXjmt2cMyvIL5bsqg6IH4f7m91dhq6uHRmgwLnYc9j66F4/FP4Y/J/6JwzcOY+PpjQYXjJl5mZAkCVfTr2LWX7PwardX0SK4BS5NvVRuEsyaLi03DfFfxCP4XdPLJNWvVR9Lhi1Bs9qm5zjP+H1GqcO5ntsoTyPoXb+3dRpbwywZtgRL712K5zs/j8SnEtEmtA2e7fisQe6H0px75pxDZMym8n0+5HNsm7TN1s0gM0UFeeHNe1qUuzKFv6crGtT2xrgO9XQBxhWTOyPM3wNB3oaB/1nrjiP2v5uQkpmnS0jZLioA0cHe+PCP03hx+SGTxyh5vbhycudKviv7cE9rOeHffW3C8UDH4pWDBusl0txxNhmt39yMpBJLbF69bZwvY0rPhnYfdCjPgpHFUxxD/NzRv3ldTB/YFPUCPfF/k9rB1Zmn64B8k8VRgw4KJ03xd9qH/YsvXsfEjrFFc6qEtZbT7NugLzqFdzIaCWLqZlKRVKTLmVFZUzvKN7RK5mVT3seb2940eg2nWpBNTesyDZfTLmPxAXke17X0awjxkf9Yhy0Iw90N78bCgQsR5hMGDxcP/Hj0R6M6lDlKarpLK4RAm9A2+Dz0czy38Tm8v/N93bbRLUZjybAl8H7bG0MaD8HaU2sBAP0b9S9zeoI9KSu5pGJCqwmY0GoCUrJTEDjPcEjmW/+8hYTkBCy/f7muX1xOu4wXNr2gi8ze1fAu6ze8Bls9ejUkScLTG57G0iNLdZFxTxdPZOVn2bh1RGQrLk4a/POSPCdf+b5cdeAKnv1RXnYzfm5rbYgAACAASURBVNZmAICzRiDU3x0xIb5IvJmBn/ZexuxhsbqLxJz8QiRcTzca3eBRQ5YcrSr3tQnHiPgwCCFwKSULS3deRM8mtREVaDwMfMrS/fjp8eI8T53nytMsRrYNx097L8NZI/CfHpYlmLMHzk4abJ7aHUt3XsDrQ5rr+sxj3dX/3qli9Kf5tQ9rDyfhhM8Gf4Zw38qtGFMTWWs5TUmSjK6FSquz3aJ2CPEOwbqx6yp9PCVhZMlgQh3vOgarqgHyNPiPdn9klyvtWYKBhxrG08UTHwz4QBd4WLR/EXILcjGj+wwAwMYzGxH9UTRe6vIS5vadi/ub34991/ahVZ1WeGjNQwZ1mXOxao/0gw4A8MPRHzCp9SQA0AUdAOjK1KAi/5cBHgF4rftrmLVtlkH5yhMrMXXjVHyw6wOj1zzV/imL22iPhBD4aOBH+GjgR0jKSsK19GsI8w3DhsQNaBHcwtbNIyIbKXmyOiwuDK0i/NHr3a26srhIf7g5O2H28Ba4kZaDXedS0PjVDWgXJQ+p33M+1ajeLc91r9J21xTK5xcR4InzcwcBML1SSEpW8ajFgsLixG6x4f6YOaQ5UjPz4Odhn3kdKiq6jg/euId/d6hsbUPb6p63C2uHDeM2qG7EqrVGPPx+7ncA8lRJP3d5KtzEVhPRJqSN0b4aoTE70NE2tK3BtAnFXxf+AmAc3PB188W42HF44683dMEQH1cfOGuczc7npxYMPNRAni6ekF6XM+t7zJGTLy05tMRgn3e2v4N3tr+DaZ2n4Y2ebyAjL0O3TRlSZGoOkxpsnbgVPZf0NChbc3KN7vnsXrPRrV43dK+nnhO8igaR3uz1JsbGjsW3h77FjO4z4PWW3CdKBh2GNx2OIY2HYHSL0VZrq70K8gzSJRYa13KcjVtDRDVN/SAvzBvREsevpaFZiC8GaqcO+Lq74NuHO+gSApoKOADAubcHqmokYkV1bmicHLFJHXmlhvzCIkTPkD8/dxcNRrWNgKuzxm6WzCSqTnW968JJOEEjNKocrRrhG4EF/RagebDpfBYVVSgVT6EoLVm4gDB7VQtl2cyS7uTKuYFCfQxzuGTlZ2HbBcOpmieSTqCgqADJWckI9HScxLHqvCWuEidundA9v5Juev3r+f/Ox5X0KwYXpr5uvugQ1kE35EdtekT1wOrRqzG86XB8M+wbAMCXB75E0cwiJDyRgBndZ6gq6ABUbvRK06CmmNNnDjxdPPHHhD+wfux6RAdEY9GQRegULg9tfbL9k5gUN8mhlqQiIqqske0i8N+hzTGyXYTBRbGrswYnZ/fHx2PjdTkdWoT5IlYv4aQjBx0AINTfA2uf7Iq598bi/x5sBwDwdHXC66uP6oIOALD6ia7MaUBUik1nNiE5KxkrRq6wdVOqTB3vOpjaaWqZS1qbQ8mBoR9QKJKKTI6k0AiN2SMsetbridd7vG5UXt+/PgBgfMvxBuUXbl/QrbCmjIZQ9r2ZedOsY6oFQ8k1WC0Pw2zhPaN64k7OHZy7fQ6LhizC/T/fj/fvfh/NajdDQVHx+uDRAdHY+cjO6m5utRraZKguOeD52+fRJKgJhBBoEtTExi2rGq5OrugU3glxdeMq9fpe9eX5ysqyRP0b9ce+q/tUNzyPiMhW3JydMKhlCAa1HIT8wiK4OGmQW1CI1Mx8BHk71nDa0sSG+yE2XA7G1PJ0wc8lpl90b1wbTer62KJpRHYjvyjf4LxfbXIKcnAu9RzCfcPh41b57wNTUzaC5gXhgZYP4MMBhqtKaITG7BEP72x/B21C2xglrldyhYX5hhmUK8GGHvV66Mrah7U3812oCwMPNViUfxQyp2di/an1yMrPwsTWE1EkFSE1OxWBnoGQXi/+RXLWFP9X6g8pcgRHbx3FzK0z8dSGp7Bm9Bp0CO9g6yZZnbPGGf8+/K/V6gv3DVdVIiIioprExUm+Y+/m7IS6fupOJllZThoBFyeB/EL5XGbWPc0xvlOUbRtFVMM5Cfn7ZNrmaVY9L6xJEpISEPd5HFaOXInhMcMrXc+Lm18EYJhzobQ8DuNix8HFybx8MokpiUhMScT3I743KP/jnJwcd8vZLSZfN6XdFN0I5stpl8tsj1pxLFsN5+niifub34+JrScCkCNypuYC5RTkoK53XQDAjks7EPtpLPZf21+tbbUVJehyM/OmaoMukiRh4+mNOJl00tZNISIispiTRsBLb7rK2A6Old2dqDKU5TTNvTtvj6yVoy67QF6eVz+BoyRJJut/ov0TeKzNY1Y57soTKw1+VkZcHLh2QPd84Z6FBtscBQMPKpFXmIfrGdcBAOl56Th68yiy843Xw1Yj/dEeal3JQ4KE/sv6o+nHphPaEBER2ZMbabm4nZWv+9lJ49g5MIjMoYx4cIScMZaOBugS0QW96/eGv7u/QZ2mPrvMvEyDRP2VMbPHTN0x9Ck/z90+F/lF+UavcyTqvEpzQPoX3EoUVK0X4SUpX8Iln6uJWlcoISIiIiLzKPkDIv0ibdySqmOt5TQlSEbXQqWNeBj03SAM+m6QRcdzd3bXHUNfpF8kOoQZTgMfHC3nh2gc2NiiY9obx7gydQD6F9zKL5kjREMBxxjx4Cj/l0RE5Hh+e7abrZtAZBei/KMAAM2Cmtm2IVVICQxYOuLh30v/YsvZLboR4QDwdIendQnX9VVkVYu+Dfrqll/XtyFxg4m95dUGlYT4yjHcnN3g6eJpdl4JtWBySZXQv+D2cZUzwDrKXfJH4h9BHa86OHv7rEOthUtERKQG+kuTElHpJEnClLZTVL0qQphvGBYNWYT4kHir1FdYVJz/bXbv2Sb3EUKYnTejcUBjZOZlGpVn5MtTNZSlMhVpuWlYn7geQHEw5fit48jKz8L1jOu6HH2OQJ23hx2QkmwGAAI9A9G3QV/4ufuV8Qr1aB/WHrN6z8Kye5fpIsFERERkH5w1PB0lMsehG4fwyd5PVJ0rIMAjAI/EP4IGtRpYVM8Xg78AYDhyIi03DTkFOUb7aoTG7BEWDQMaYlrnaUblYT5hcHNy0y0IoDiXeg7/XpJXIFFGPLQNbQsAuJFxw6xjqgW/6VVCf6pF48DG2Dx+M5oGOUYiwjMpZ7D1/FZbN6PKDWg0AK92e9XWzSAiIrIqZyfHGKFJZCllNHNuQa6NW1J1svOzsfvKbiRnJVtUj6lcESHvheC1P14z2lcjNGaPePhg1wdYfXK1UXlyVjJyC3ONpmEoAY17Y+7VTa2IqxtnsM1RMPCgEvo5APSHFDmCz/Z+hl5LesFzjidOJZ+ydXOqzK/jfsWs3rNs3QwiIiKrcuaKFkRmycrPAgC8v/N9G7ek6py/fR4dFnfA5rObLarnsbXy8pj6F/el5XGY0HICHol7xKx6L965iCWHlhiV77yyE4BxrgflmONbjtflpTuTeqbM9qgVAw8qUsu9FgBg05lNiPpfFI7dPGbjFlUP5Zc4uyBb1Xktlh1ephuqRUREpBZcSpOIFNZKqK4EHDycPQzKTNU/ruU4PBz/sFWOu+rkKpPt+PvC37qbwx/v+dhgm6Ng4EFFUnNSAQAZeRm4cOeCqud/6XOEVS0A4IFfHkCXr7rYuhlERERWxRwPROZxpFXOLB0NEB8Sj0HRg1Dbq7ZBuamblMlZyRbnW5h/1/wyty/YuQDZBdkWHcPe8ZtehQolOZqm5rv/+vQDD/pJNomIiKjmY44HIvP4u/sDAFoEt7BxS6qOtZbTlCTJ6IZkacGMiasmYuB3Ay06XmnHiA6IxsDogQbbBjYaCBeNC1rVaWWVY9oLBh5USLkQd5SoqH6wQc0jHoiIiNTIyUHOV4gspQQe2oS0sXFLqo6ppJCVceD6Aaw9tRbnUs/pyl7r/hruaniX0b4aoTH7eCObj0Rtz9pG5SuOrwBgHDDxcfNB76jeBts0QgNvV2+Hu2HKhZNVSPlScpSL8FHNRyErPwtJWUnwcfWxdXOIiIioHO+MiMVLK44AADTM8UBkFm9Xb7zW/TW0CVVv4CHEOwQ/jPgBHcI7WKU+ZSQ4AMzoPsPkPhVZ1aJhrYYmp2XkFMrLdMYExRiUJ2cl44djPwAoDqYcTzqO1JxUXLxzEZF+kWYdVw0c48rUwYT6hGJ40+HwdfO1dVOqRXRgNN7q8xa+GPIFannUsnVziIiIqBwa7V3NOr5uNm4Jkf3wdfPFm73eRNvQtrZuSpXxcfPBqBajEOUfZVE93w7/FoDhyIkraVeQlptmtK8QwuzAg6uTK6a0m2JUHuQRBB9XHzzY+kGD8jOpZ7D36l6Dsn4N+gEArmdcN+uYasHAgwrV86uHlaNWOkwE7VzqOfxy4hfkFOSoelmaB1o+gPfvVu/ySURE5DiUlSz8PVxt3BIiqkmy87Px+9nfcS39mkX1mMoVEfVBFN755x2jfTVCY3ZOic/3fY4tZ7cYld/KuoX0vHSj0dfKtclj8Y/B08UTABBbJ9a8N6EyDDyoSKBHIAA4zGoWinWn1uHen+6FxxwPJGcn27o5Vebb4d/i2Y7P2roZREREFlMCD24uPBUlomLXMq6h77d9senMJovqeeCXBwAYjngo7Qblg60exLTO08yq93rGdSzav8io/OD1gwCANSfXGJQrAY1hTYfBxckFAHD4xuEy26NW/LZXkQV3LwAA/HzsZwTNC8LplNM2blH1MFjVQjhWkhYiIiJ7pCSQc3XiqSgRFbPWqhYKP3c/3XMJksnk+0OaDMGEVhMsOo6bszxtbO2ptQblSnBhw+kNyCvMAyCPmlDa40j4ba8iSjLJrPwsJGcnmz1Xyd5xOU0iIiL7oqxk4erMU1EiKmatVfligmJwf7P7Ude7rmH9MK7/avpVnEk5Y9Hx5t81H0DpwYSPdn+E9Nx0gzKOeCC7pQQelOytpn6x1Eg/8OAoK3kQERHZM2WggxsDD0RkgqUX5UVSkVEQo7Q6n9/0PAYsG2DR8Uq77oqtE6sbTaEEJe5ueDfqeNVBp4hOFh3T3vDbXkUi/SJxb8y9usQl1ooY1nScakFERGRfirTn/xzxQET6rDXV4mTySfx07CccvXlUV/Zev/cwINo4wFCR5JL/afMfBHsFG5UvObTE5P7ert5oF9rOoMzRRjoonMvfhexF18iu6BrZFd8c+gaA49z979ewH97o+QZuZt40CEIQERFRzZRXIE8HdXPmDQMiKhbsFYz1Y9cjNtiylR+8Xb2RkZdhcJE/tdNUk/sKmL+cZj2/emhZp6VRuZLcP65uHFYlrNKV6yejVNpy7NYx3Mi8gdMpp9EooJF5b0gFHOPK1ME0qNUAE1pNMFrORa3qeNfBzB4zsXDgQl22WCIiIqq5igMPPBUlomIeLh4YGD0QEX4RFtXz9T1fAygeOSFJEhKSEpCUlWS0rxDC7FEINzJvYFLrSUbl/m7+CPIMwoOtHzQoT0xOLF7FQtuWMS3GAJCDEo6E3/Yqsv7UegTOC4S/uz+WDFuC2l61bd2kanE57TLmb5/vMKt4EBER2bvcAjkfFadaEJG+7PxsrEpYhfO3z1tUjzLlXAkoSJAQ83EMPt79sdG+GqExe8TDN4e+wY5LO4zKb2bdRFJWElydXA3KlWDD9K7T4e/uDwBoEtTEoG2Ogt/2KpJflI+U7BQUFBXYuinVav+1/Xhxy4vo/GVnWzeFiIiIzJCrHfHAwAMR6UvJTsHwH4dj05lNFtUz4qcRAIxzRZjKgfdQ64cwt+9cs+pNzUnFwj0LjcoTkhIAACtPrDQoV4ILfRr00QUldl3eZbJtasdvexVRcjp8uf9LuM12w6U7l2zcouqhJJRU1s8lIiKimi2vkDkeiMhYyZEKlqrtWbvc+npE9cDoFqMtOo6fmx8A4NfEX01u/+nYT8jOzwYALD6wuNw2qREDDyqiBB7yCvOQV5jncKtauDkx8EBERGQPWobJQ447NAiwcUuIqCYpbVnKioryj8L4luMR5hsGoHh0gan6z98+j4PXD1p0vHf6vmNwHIXy8+f7PkdqTiqA4msXJ41jBV4ZeFARJfBQKMnzJq31i1vT6QIPHPFARERkF7pGB+HAa3ehVxPjZemIiCydhpBfmI+MvAwUFsnXRcroAlM3Zudsm4OBywZadLzSbvi2D2uP5zo+Z9CGrpFdEeEbga6RXS06pr1h4EFFwn3DMbHVRAR4yHcPHGU5TSXwUDKZCxEREdVctbz4d5uIDFlrqsWV9Cv4JeEX7L+2H4A8uuCLwV9gUPQgo301QmN2oOOp9k/pkkTq+3iPnLSyZLs9XTzRNKipvE1vhQ1HGZmuzzGuTB1Eyzot8fWwr1Hfvz6A0iNvahMfEo8n2j2Bmd1n2ropRERERERUSQEeAfjrwb9wT9N7LKon1CcUQPHFvkZo8GibRxEXEme0b0VWtYgOiEaXiC5G5crrO4V3Mii/eOciFuxcYFB2IukELt65iKM3j5p1TLVg4EGFWgS3wBPtnoCni6etm1ItfNx8sHDgQgyPGW7rphARERERUSW5Ormie73uusBBZS0asghA8QiEIqkIe67swbX0a0b7CiHMDjzsu7YPo5qPMir3cvFCqE8oHo5/2KD8VPIp3YoXSluebPckAOBGxg0z3406MPCgIlvPb4XbbDdIkLBw4EL4uvnauklERERERERmySnIwdLDS3Ey6aRF9Si57pQRD3mFeWi/uD2WHFpitK9GaMye2rH8+HKTiShvZt7E1fSrKCgqMChX6l3QbwGCveScNlH+UWa/DzVh4EFl8grzkF+Yj7zCPIdbooWIiIiIiOxXRl4Gxv8yHpvObLKonoHfyckileuhsq6LJrWehC+GfGFWvZn5mUZTJwDg3O1zAICfj/1sUK4EPtqHtdclwv/j3B8G2xwFAw8qoiSTHL1iNNxmuyElO8XGLSIiIiIiIjJPyZEKlgr3DTeoz9Sqf21C2+DemHstOk4drzoAgI1nNhqUKwGPLw98ifTcdADA14e+NtjmKBh4UBEl8JCUlQTAcZJLEhERERGR/bPWqhZ1vOrgsfjHEOEXYVCfqeujxORE/HX+L4uO93aft+XjlBIw+b+D/6e7RlNW4lNGQDgKBh5UpOTymaYiekRERERERDWRta5fcgpycD3zOnILcsut/9O9n2Lw94MtOp4S0CiZpLJHVA/M6T3HoKxNSBs0CmiE7vW6W3RMe8PAg4qEeIcY/FwyEEFERERERFTTWTrV4k7uHaw5uQa7r+wGII8u+H7E9xjc2DjAUJHkki90egEezh5G5XP/mWtyf3dnd4T5hAEwfE+OeIOYV6YqUr9WfXw66FPdz5xqQURERERE9sLXzRf7H9uPsbFjLaqnaVBTAMUX+84aZ4xuMRoxtWOM9hUwfznNZrWbYUD0AKNy5YZv76jeBuWJyYl4c9ubclu0wY2EpAQkpiRi39V9Zr4bdWDgQUUkSdJ14PiQeLg5Oda8ISIiIiIisl9OGifEhcTplp6srI8Hfgyg+GK/oKgAf5z7AxfvXDTaVyM0Zo+wWHVyFYY2HmpU7u7sjvr+9fFI/CMG5aeST+Fs6lmDspk9ZgKQl+B0JAw8qMjB6wex+MBiAPL6sI6WsISIiIiIiOxXXmEePt3zKQ5eP2hRPSVXx8jMy0Sfb/pg+fHlxvsK80c8/Jr4K04mnzQqv5l5E+dun0N6XrrJ1y0ZtkSX6FKZHs/lNMluZeVn6Z5n5GU43BItRERERERkv3ILcjHl1ynYcnaLRfX0/kae8qBcD5W1nOaDrR/EqlGrzKq3oKgAb//ztlH5lfQrAIBlh5cZlCvHjQmK0a1mse7UOoO2OQoGHlQkwCNA93zTmU3IKcixYWuIiIiIiIjMZ63lNBUNAxqarF9f06CmJvM2VER9//oAgM1nN+vKJEnSvY//7fofUrNTAQBLjyyVt3PEQ9USQvQXQpwUQpwWQrxc3cdXs5jaMbjxwg10iegCQE6iQkREREREZA9KTpGoLF83XzzT4RlE+kXK9ZURyEhISsDqhNUWHW9279kADJfT1A9yfHfkO11OB3dndwCAl4uXRce0N9UaeBBCOAH4GMAAAM0AjBFCNKvONqhdsFcw1o1dh3PPnIOLk4utm0NERERERGQWa63Kl5WfhcSURGTmZQIoe6rFd0e+w7Afh1l0PKVeJfCg/DwgegA+H/y5wb7NazdHs9rN0Kt+L4uOaW+qe8RDewCnJUk6K0lSHoAfANxTzW1QPX93f0T5R9m6GURERERERBVm6VSLgqIC/Jr4K7Zf2g4A8Hb1xrox6zC0ifGKFMpSmOYcc3rX6XASTkblr/75KoDiwIMECYVFhXDWOMPXzVdXpvxrKgCidtU9Fj8MwCW9ny8D6FDNbSAiIiIiIqIaxt3ZHYlPJSLQIxDPbXwOOy7vMNhez68efrjvBwDA4+sex6Ebhwy2xwTF4Kt7vkLH8I7YeXknnvntGfi7+8Pd2R1/TvzT5DGVwEOnLzthQqsJmNJuCtJy03D30ruN9q3lXgujW4wGALy0+SVsu7gNAHD81nF4uXhhctvJ2LNmDwCgy1ddcCntkm6KxeqE1WjatSn83fxx7NYxeL3lhZZ1Wurq/vqer9EkqEmFPzN7Ud2BB1OhHYPQkhDiMQCPAUBkZGR1tImIiIiIiIhsTCM0aBTQCADg6eKpGy2g8Hb11j33cvEqdfvGBzbi4TUPIy03DQDg5uRW6jEHNBqAnZd3olAqNNivZN0AML7leIyJHWPUvo7hHdGvQT9MipuE5SeWQ5IkFEqF8HP3Q3puOrxdvVHLoxYA4J273sFXB79C18iuRu9dzUR1LuMhhOgE4L+SJN2t/fkVAJAkyXhNEgBt27aV9u7dW23tIyIiIiIiIiLzCCH2SZLUtrz9qjussgdAtBCivhDCFcBoAGuquQ1EREREREREVE2qdaqFJEkFQognAWwE4ATgK0mSjlVnG4iIiIiIiIio+lR3jgdIkvQrgF+r+7hEREREREREVP3UncGCiIiIiIiIiGyKgQciIiIiIiIiqjIMPBARERERERFRlWHggYiIiIiIiIiqDAMPRERERERERFRlGHggIiIiIiIioirDwAMRERERERERVRkGHoiIiIiIiIioyjDwQERERERERERVhoEHIiIiIiIiIqoyQpIkW7ehVEKIWwAu2LodZDVBAJJs3QiyK+wzVBHsL1RR7DNUEewvVFHsM1QR9tpf6kmSVLu8nWp04IHURQixV5KktrZuB9kP9hmqCPYXqij2GaoI9heqKPYZqgi19xdOtSAiIiIiIiKiKsPAAxERERERERFVGQYeqDp9YesGkN1hn6GKYH+himKfoYpgf6GKYp+hilB1f2GOByIiIiIiIiKqMhzxQERERERERERVhoEHByaEiBBC/CmEOCGEOCaEeEZbHiCE2CyESNT+W0tb3lQIsUMIkSuEeEGvHnchxG4hxCFtPW+UccyJ2noThRAT9crnCCEuCSEyymlzGyHEESHEaSHEh0IIUWL7C0IISQgRVNnPhUqntj4jhHhKCHFS24Z5lnw2ZExN/UUI0VoIsVMIcVAIsVcI0d7Sz4eM2WmfMbmfEMJNCPGjti/tEkJEVe5TodKorL88J4Q4LoQ4LIT4XQhRr7KfC5VOTX1Gb/t9Qj73Ve1qCLaitv4ihBip/Z45JoT4rjKfiUUkSeLDQR8AQgDEa5/7ADgFoBmAeQBe1pa/DOAd7fNgAO0AzAHwgl49AoC39rkLgF0AOpo4XgCAs9p/a2mf19Ju66htT0Y5bd4NoJP2mBsADNDbFgFgI4ALAIJs/fmq8aGmPgOgF4AtANyUttr681XbQ2X9ZZPe84EAttr681Xjw077jMn9AEwB8Jn2+WgAP9r681XbQ2X9pRcAT+3zyewv7DPl9Rm997ANwE4AbW39+artoab+AiAawAG9+qr9vJcjHhyYJEnXJEnar32eDuAEgDAA9wBYot1tCYBh2n1uSpK0B0B+iXokSZKUqJqL9mEqecjdADZLkpQiSVIqgM0A+mvr2ClJ0rWy2iuECAHgK0nSDkn+jflGaZvW+wBeLOXYZAUq6zOTAcyVJClXaauZHwOZSWX9RQLgq33uB+CqGR8BVZC99Zly9tNv83IAfYQwHKVHllFTf5Ek6U9JkrK0P+4EEF5eXVRxauozWrMgXwTnlFcPVZzK+sujAD7W1muT814GHggAoB0CGgc5AldH6bDaf4PNeL2TEOIggJuQf2F2mdgtDMAlvZ8va8vMFaZ9jdHrhRBDAVyRJOlQBeojC9h7nwHQGEA37RDov4QQ7SpQL1WQCvrLswDmCyEuAXgXwCsVqJcqwU76TFl0dUuSVADgDoBAK9VNJaigv+h7GPKIK6pC9t5nhBBxACIkSVpnjfqobPbeXyCf9zYWQmwX8tTR/laq12wMPBCEEN4AVgB4VpKktMrUIUlSoSRJrSFH6NsLIVqYOpSpl1bgMCZfL4TwBDADwMwK1EUWsPc+o/3XGfIwto4ApgH4iXcjq4ZK+stkAFMlSYoAMBXAlxWolyrIjvpMWaqybtKjkv4iH0CIBwC0BTDfmvWSIXvvM0IIDeSRvs9bWheVz977i5Yz5OkWPQGMAbBYCOFvpbrNwsCDgxNCuED+RVomSdJKbfEN7ZBjZeix2UNxJEm6DWArgP5CiA5CTsR2UDsi4TLkPAyKcJQxXFmJDGofb2pfrz/0UHl9QwD1ARwSQpzXlu8XQtQ1t91kPpX0GWi3rdQOf9sNoAgAk5JamYr6y0QASvt/BsDkklXEzvpMWXR1CyGcIU/RSTG33WQeFfUXCCH6Qr6RMlTSTgMk61NJn/EB0ALAVu25b0cAawQTTFqdSvoLtHWvliQpX5KkcwBOQg5EVBvn6jwY1Szau7tfAjghSdICvU1rIJ9kz9X+u7qcemoDyJck6bYQwgNAX8hJVnYBaK23XwCAt4Q28yuAfihjuLIkSYX6r9fWkS6E6Ah5aAY7PgAAAbhJREFUmNMEAB9JknQEekOctF/AbSVJSiqr3VRxaukz2k2rAPSG/Ee7MQBXAOwzVqSy/nIVQA/IJwu9ASSW1WaqHHvsM2VQ2rwDwH0A/pAkiSMerEhN/UXIw+Y/B9DfFnOvHYVa+owkSXegd7NECLEVcjLDveW9lsynlv6itQrySIevhbz6X2PIySurj1QDMobyYZsHgK6Qh+8cBnBQ+xgIeQ7q75BPrH8HEKDdvy7kaFkagNva574AWkLOknoYwFEAM8s45kMATmsfk/TK52nrK9L++99SXt9We4wzABYCECb2OQ+uasE+U06fgRxoWKrdth9Ab1t/vmp7qKy/dAWwD8AhyEGJNrb+fNX4sNM+Y3I/AO6QR8echrxaSgNbf75qe6isv2wBcEPvfayx9eerxoea+kyJfbaCq1qwv5SxH+RpHAsAHAdwBMDo6v48lRMqIiIiIiIiIiKrY44HIiIiIiIiIqoyDDwQERERERERUZVh4IGIiIiIiIiIqgwDD0RERERERERUZRh4ICIiIiIiIqIqw8ADEREREREREVUZBh6IiIiIiIiIqMow8EBEREREREREVeb/Ac0kkK9XC851AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Calculate the proportional concentration of different flows coming together." + "dataset.data['CODtot_line2'].update(data['2013/1/1':'2013/1/14'])\n", + "detrended_values = signal.detrend(dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'])\n", + "line_segment = dataset.data['CODtot_line2']['2013/1/5':'2013/1/8'] - detrended_values[:]\n", + "line = line_segment - line_segment[0]\n", + "line10=10*line\n", + "\n", + "\n", + "dataset.data['CODtot_line2']['2013/1/9':'2013/1/12']+= line10.values[::-1]\n", + "fig, ax = plt.subplots(figsize=(18,6))\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/3':'2013/1/15'], 'g--', label='data with drift')\n", + "asd = dataset.data['CODtot_line2']['2013/1/9':'2013/1/12'] - line10.values[::-1]\n", + "ax.plot(asd, label='original data')\n", + "ax.legend(loc='upper right')" ] }, { "cell_type": "code", - "execution_count": 38, - "metadata": { - "ExecuteTime": { - "end_time": "2017-05-09T09:55:07.842239", - "start_time": "2017-05-09T11:55:07.833046+02:00" + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "749.1368773481072 513.0807872140786\n", + "-0.20490980046356652\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "dataset.calc_total_proportional('Flow_total',\n", - " ['Flow_line1','Flow_line2','Flow_line3'],\n", - " ['TSS_line1','TSS_line2','TSS_line3'],\n", - " 'TSS_prop')" + "fig, ax = plt.subplots(figsize=(18,10))\n", + "ax.plot(asd, 'm--')\n", + "\n", + "\n", + "detrended_values = signal.detrend(dataset.data['CODtot_line2']['2013/1/9':'2013/1/12'], type='constant')\n", + "df = pd.DataFrame(detrended_values, index = data.index[len(data[:'2013/1/8']):len(data[:'2013/1/12'])])\n", + "\n", + "line_segment = dataset.data['CODtot_line2']['2013/1/9':'2013/1/12'] - detrended_values[:]\n", + "line = line_segment - line_segment[0]\n", + "line10=10*line\n", + "#ax.plot(line_segment)\n", + "ax.plot(dataset.data['CODtot_line2']['2013/1/7':'2013/1/15'],'g--', label='data with drift')\n", + "#ax.plot(df, label='detrended drift')\n", + "\n", + "detrended_values1 = signal.detrend(dataset.data['CODtot_line2']['2013/1/9':'2013/1/12'])\n", + "df1 = pd.DataFrame(detrended_values1, index = data.index[len(data[:'2013/1/8']):len(data[:'2013/1/12'])])\n", + "line_segment1 = dataset.data['CODtot_line2']['2013/1/9':'2013/1/12'] - detrended_values1[:]\n", + "ax.plot(line_segment1, 'c--', label='slope')\n", + "#ax.plot(df1)\n", + "\n", + "b = df.iloc[0][0]\n", + "\n", + "a = line_segment1[-1]\n", + "print(b,a)\n", + "slope = (a-b)/len(df)\n", + "print(slope)\n", + "f=[a]\n", + "s = df\n", + "s[:] = b\n", + "ax.plot(s, label='Slope1')\n", + "for val in range(len(df)-1):\n", + " a+=slope\n", + " f.append(a)\n", + "\n", + "\n", + "#print(f)\n", + "ds = pd.DataFrame(f, index = data.index[len(data[:'2013/1/8']):len(data[:'2013/1/12'])])\n", + "\n", + "\n", + "\n", + "ax.plot(ds, 'C1', label='Slope2')\n", + "ax.plot((s+ds)/2, 'r*')\n", + "#print(df1)#(s+ds)/2, ((s+ds)/2)+df1)\n", + "#ax.plot(df1, 'k--', label='detrended drift org')\n", + "\n", + "ax.plot(df1+((s+ds)/2), 'b--', label='fixed drift')\n", + "\n", + "#ax.plot(df1+ds, 'r--')\n", + "\n", + "ax.legend(loc='upper right', shadow=True)" ] } ], diff --git a/wwdata/Class_HydroData.py b/wwdata/Class_HydroData.py index 859583eec..67849e3e8 100644 --- a/wwdata/Class_HydroData.py +++ b/wwdata/Class_HydroData.py @@ -1755,7 +1755,7 @@ def drift_analysis(self, data_name, arange1, arange2=None, plot=False): """ pass - def remove_drift(self, data_name, arange, max_slope, period=None, plot=False): + def remove_drift(self, data_name, arange, max_slope, period=None, plot=False, drift_type=None): """ This function calculates the slope of the data in a certain given period by fitting a line through it and removes the drift. @@ -1829,8 +1829,34 @@ def remove_drift(self, data_name, arange, max_slope, period=None, plot=False): series[value[0]:value[1]] = series[value[0]:value[1]]-line_segment1+ds elif value[2] == 'm': + if drift_type == 'A' or drift_type is None: + series[value[0]:value[1]] = series[value[0]:value[1]] - (line_segment1 - line_segment1[-1]) + #if value[1].day - value[0].day == 1: + elif drift_type == 'B': + + #else: + detrend = signal.detrend(series[value[0]:value[1]], type='constant') + df2 = pd.DataFrame(detrend, index=series.index[len(series[:value[0]])-1:len(series[:value[1]])]) + + b = df2.iloc[1][0] + a = line_segment1[-1] + slope = (a-b) / len(df2) + f = [a] + s = df2 + s[:] = b + for val in range(len(df2) - 1): + a += slope + f.append(a) + + ds = pd.DataFrame(f, index=series.index[len(series[:value[0]])-1:len(series[:value[1]])]) + ds = ds[:] + s[:] + ds = ds / 2 + ds = ds.squeeze() # from dataframe to series + #ax.plot(series[value[0]:value[1]]-(line_segment-ds), 'm-', label='without drift') + series[value[0]:value[1]] = series[value[0]:value[1]] - line_segment1 + ds + # ax.plot(series[value[0]:value[1]]-(line_segment-line_segment[-1]), 'm-', label='without drift') - series[value[0]:value[1]] = series[value[0]:value[1]] - (line_segment1 - line_segment1[-1]) + #series[value[0]:value[1]] = series[value[0]:value[1]] - (line_segment1 - line_segment1[-1]) """ detrend = signal.detrend(series[value[0]:value[1]]) diff --git a/wwdata/Class_OnlineSensorBased.py b/wwdata/Class_OnlineSensorBased.py index dbe8dbae3..d1e3fea6f 100644 --- a/wwdata/Class_OnlineSensorBased.py +++ b/wwdata/Class_OnlineSensorBased.py @@ -1375,8 +1375,8 @@ def check_filling_error(self,nr_iterations,data_name,filling_function, # turn warnings on again wn.filterwarnings("always") raise ValueError("Checking of the filling function could not "+\ - "be executed. Check docstring of the filling "+\ - "function to provide appropriate arguments.") + "be executed. Check docstring of the filling "+\ + "function to provide appropriate arguments.") filling_errors = filling_errors.append(pd.Series([iter_error]))