PyGSLIB_declus_python_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "\n",
    "# Declustering in Python with PyGSLIB / GeostatPy for Engineers and Geoscientists \n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "#### Contacts: [Twitter/@GeostatsGuy](https://twitter.com/geostatsguy) | [GitHub/GeostatsGuy](https://github.com/GeostatsGuy) | [www.michaelpyrcz.com](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446)\n",
    "\n",
    "This is a tutorial for / demonstration of **spatial declustering in Python** with the PyGSLIB package (by Adrian Martinez Vargas) that wraps some of the FORTRAN algorithms from GSLIB, Geostatistical Library (Deutsch and Journel, 1997).  The GeostatPy (by Michael Pyrcz) is an informal collection of Python programs that write parameter files, data files, run GSLIB executables and then read results back. There has been some reimplimentation of visualization with MatPlotLib methods. \n",
    "\n",
    "Cell-based declustering is available in the declus algorithm from GSLIB. The methods is written about in the GSLIB book (Deutsch and Journel, 1998) and other textbooks such as Pyrcz and Deutsch (2014).  The method provides declustering weights that acocunt for spatial clustering of the data samples.  It is not sensitive to data boundaries, but relies on a cell size assumption. The common method is to attempt a range of cell sizes and retain that one that minimizes the declustered mean if locations with high values have been over sampled (and visa versa).\n",
    "\n",
    "We will demonstration calculation of declustering weights on regular and irregular spaced data.  \n",
    "\n",
    "This exercise demonstrates the cell-based declustering approach in Python with wrappers and reimplimentation of GSLIB methods.  The steps include:\n",
    "\n",
    "1. generate a 2D sequential Guassian simulation using a wrapper of GSLIB's sgsim method\n",
    "2. extract regular and irregular sample sets from the exhaustive realization\n",
    "4. run cell-based declustering\n",
    "5. visualize the declustering weights at the data locations\n",
    "6. visualize the declustered mean vs. cell size used to determine the optimal cell size\n",
    "\n",
    "To accomplish this I have provided wrappers or reimplementation in Python for the following GSLIB methods:\n",
    "\n",
    "1. sgsim - sequantial Gaussian simulation limited to 2D and unconditional\n",
    "2. hist - histograms plots reimplemented with GSLIB parameters using python methods\n",
    "3. locmap - location maps reimplemented with GSLIB parameters using python methods\n",
    "4. pixelplt - pixel plots reimplemented with GSLIB parameters using python methods\n",
    "5. locpix - my modification of GSLIB to superimpose a location map on a pixel plot reimplemented with GSLIB parameters using Python methods\n",
    "6. affine - affine correction adjust the mean and standard deviation of a feature reimplemented with GSLIB parameters using Python methods\n",
    "7. nscore - normal score transform (data transformation to Gaussian with a mean of zero and a standard deviation of one)\n",
    "\n",
    "These methods are all in the functions declared upfront. To run this demo all one has to do is download and place in your working directory the following executables from the GSLIB/bin directory:\n",
    "\n",
    "1. sgsim.exe\n",
    "2. declus.exe\n",
    "3. nscore.exe\n",
    "\n",
    "The GSLIB source and executables are available at http://www.statios.com/Quick/gslib.html.  For the reference on using GSLIB check out the User Guide, GSLIB: Geostatistical Software Library and User's Guide by Clayton V. Deutsch and Andre G. Journel.\n",
    "\n",
    "I did this to try out the PyGSLIB package in Python.  I created GeostatPy functions to allow people to use these GSLIB functions that are extremely robust in Python. Also this should be a bridge to allow so many familar with GSLIB to work in Python as a kept the parameterization and displays consistent with GSLIB.  The wrappers are simple functions declared below that write the parameter files, run the GSLIB executable in the working directory and load and visualize the output in Python. This will be included on GitHub for anyone to try it out https://github.com/GeostatsGuy/.  \n",
    "\n",
    "I used this tutorial in my Introduction to Geostatistics undergraduate class (PGE337 at UT Austin) as part of a first introduction to geostatistics and Python for the engineering undergraduate students. It is assumed that students have no previous Python, geostatistics nor machine learning experience; therefore, all steps of the code and workflow are explored and described. This tutorial is augmented with course notes in my class.  The Python code and markdown was developed and tested in Jupyter. \n",
    "\n",
    "#### Load the required libraries\n",
    "\n",
    "The following code loads the required libraries.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(null);\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.16.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.16.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.16.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.16.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<script type=\"text/Javascript\">\n",
       "var x = document.getElementById(\"ipython_notebook\")\n",
       "x.innerHTML = '<img  title=\"Opengeostat\" alt=\"Opengeostat\" src=\"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEASABIAAD/4REwRXhpZgAATU0AKgAAAAgABwEaAAUAAAABAAAAYgEbAAUAAAABAAAAagEoAAMAAAABAAIAAAE7AAIAAAAFAAAAcodpAAQAAAABAAAIjpydAAEAAAAKAAAAeOocAAcAAAgMAAAAggAAAAAAAABIAAAAAQAAAEgAAAABdGVtcAAAdABlAG0AcAAAABzqAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAiQAAAHAAAABDAyMTCQAwACAAAAFAAACPSQBAACAAAAFAAACQiSkQACAAAAAzcxAACSkgACAAAAAzcxAACgAAAHAAAABDAxMDCgAQADAAAAAf//AADqHAAHAAAIDAAACRwAAAAAMjAxNTowMzozMSAxMDowOToxNwAyMDE1OjAzOjMxIDEwOjA5OjE3ABzqAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA/+EFdGh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8APD94cGFja2V0IGJlZ2luPSfvu78nIGlkPSdXNU0wTXBDZWhpSHpyZVN6TlRjemtjOWQnPz4KPHg6eG1wbWV0YSB4bWxuczp4PSdhZG9iZTpuczptZXRhLyc+CjxyZGY6UkRGIHhtbG5zOnJkZj0naHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyc+CgogPHJkZjpEZXNjcmlwdGlvbiB4bWxuczpkYz0naHR0cDovL3B1cmwub3JnL2RjL2VsZW1lbnRzLzEuMS8nPgogIDxkYzpjcmVhdG9yPgogICA8cmRmOlNlcT4KICAgIDxyZGY6bGk+dGVtcDwvcmRmOmxpPgogICA8L3JkZjpTZXE+CiAgPC9kYzpjcmVhdG9yPgogPC9yZGY6RGVzY3JpcHRpb24+CgogPHJkZjpEZXNjcmlwdGlvbiB4bWxuczp4bXA9J2h0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8nPgogIDx4bXA6Q3JlYXRlRGF0ZT4yMDE1LTAzLTMxVDEwOjA5OjE3LjcwODwveG1wOkNyZWF0ZURhdGU+CiA8L3JkZjpEZXNjcmlwdGlvbj4KCiA8cmRmOkRlc2NyaXB0aW9uIHhtbG5zOmV4aWY9J2h0dHA6Ly9ucy5hZG9iZS5jb20vZXhpZi8xLjAvJz4KICA8ZXhpZjpYUmVzb2x1dGlvbj43MjwvZXhpZjpYUmVzb2x1dGlvbj4KICA8ZXhpZjpZUmVzb2x1dGlvbj43MjwvZXhpZjpZUmVzb2x1dGlvbj4KICA8ZXhpZjpSZXNvbHV0aW9uVW5pdD5JbmNoPC9leGlmOlJlc29sdXRpb25Vbml0PgogIDxleGlmOkFydGlzdD50ZW1wPC9leGlmOkFydGlzdD4KICA8ZXhpZjpYUEF1dGhvcj50ZW1wPC9leGlmOlhQQXV0aG9yPgogIDxleGlmOlBhZGRpbmc+MjA2MCBieXRlcyB1bmRlZmluZWQgZGF0YTwvZXhpZjpQYWRkaW5nPgogIDxleGlmOkV4aWZWZXJzaW9uPkV4aWYgVmVyc2lvbiAyLjE8L2V4aWY6RXhpZlZlcnNpb24+CiAgPGV4aWY6RGF0ZVRpbWVPcmlnaW5hbD4yMDE1OjAzOjMxIDEwOjA5OjE3PC9leGlmOkRhdGVUaW1lT3JpZ2luYWw+CiAgPGV4aWY6RGF0ZVRpbWVEaWdpdGl6ZWQ+MjAxNTowMzozMSAxMDowOToxNzwvZXhpZjpEYXRlVGltZURpZ2l0aXplZD4KICA8ZXhpZjpTdWJTZWNUaW1lT3JpZ2luYWw+NzE8L2V4aWY6U3ViU2VjVGltZU9yaWdpbmFsPgogIDxleGlmOlN1YlNlY1RpbWVEaWdpdGl6ZWQ+NzE8L2V4aWY6U3ViU2VjVGltZURpZ2l0aXplZD4KICA8ZXhpZjpGbGFzaFBpeFZlcnNpb24+Rmxhc2hQaXggVmVyc2lvbiAxLjA8L2V4aWY6Rmxhc2hQaXhWZXJzaW9uPgogIDxleGlmOkNvbG9yU3BhY2U+SW50ZXJuYWwgZXJyb3IgKHVua25vd24gdmFsdWUgNjU1MzUpPC9leGlmOkNvbG9yU3BhY2U+CiAgPGV4aWY6UGFkZGluZz4yMDYwIGJ5dGVzIHVuZGVmaW5lZCBkYXRhPC9leGlmOlBhZGRpbmc+CiA8L3JkZjpEZXNjcmlwdGlvbj4KCjwvcmRmOlJERj4KPC94OnhtcG1ldGE+Cjw/eHBhY2tldCBlbmQ9J3InPz4K/9sAQwABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB/9sAQwEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB/8IAEQgAlgFWAwERAAIRAQMRAf/EAB4AAQACAQUBAQAAAAAAAAAAAAAICQcCAwQFBgEK/8QAHAEBAAICAwEAAAAAAAAAAAAAAAYHAwUBAgQI/9oADAMBAAIQAxAAAAG/wAA2yKhD4xgcw2DL5MYkofQAAAAAAAAAAAAAAACHhW6S5JrGVDUaDD5CUjcWcklQAAAAAAAAAAAAAACpY3S1E8XuNDhmURDxG20vGyYe0wej3uo3uZYtMO41m4qjMslkQAAAAAAAAAAAAABU8ZYJ15/NEWxatxhIYx3ODP2WPJyuvb7zxxu/TrsuLLUYl0nYBZdcfTL6MsNAAAAAAAAAAAAAIqELC17N54HW1SvSe7X+g83p7vB6O0xZeb07/XHDyY+pz4Ok9Hl9Vqt1MqrrgqE6ZbJjNoAAAAAAAAAAAAKGS7oiJZ1R4mkkUzTG5VmONynn9MvK6dt7jn6bPbrwu+Pg5MXWZMeRNFI9Os3FU5c8AAAAAAAAAAAAR8ILFjG101edy0T6rye2TsGsCSsJsLWfQD4aDSbJsmwVMloJ74AAAAAAAAAAAFX5Jc8pYVZR0m9fer8ntk1B7AkrCbB1moA0Gg0G0bRsERzgE4QACs46g8WW6lIhnk8yWwFUh6YzedIYHPFFmJmwAFLBbWQftylMb76N7nbpJCFT6XdcWp9NR9PhpPhHacV3nCIzft/L7eOYtIhFlwAOIUnF3hVOTaKty8YpEJ7ldxJwwiZ6JMHXmEixIAFIpcQVqXj8+xym1f6MmKbtX27PGpLq3DUfT4aTbIHXBRfgttqLIaK+itzjnxhDssfABpPzxH6GijAuNPz5H6Pj8+xcSQPLhjzRWoSxOrI+lmoAKciy4rlvb53jRPK67XH2nBV1vz3qK7NZqANBoIDXFRUTLFrCwWlL+krA7G8AYXJvAAEOyAxNQnSfnEJFk2yapWmYHJzm+ZhOIY3JUAAroOwONZ1TV43NRPZ9O85Ktt6ftQXdrPoBpNJX1clExIsar8oR2UWt/O/09HUygZ1BiHdaLz/q8md45Jt/jsAKZi5kAAAAAAGOSl4uC92vpL+oPknRm806aruCwOn7v1GoHw+GkrxuehohWPVvD7Lu/lX7Ei3hzzhOeVL3RRnrfF78ga3adtg9M5a9sf4D6DS41OQPjj65qquGlLVaeusaXGpzsdutZFs09Z9UlxijEs/I7WhUlct0UVknT7jJmk33I4b/ABzucc/T4bXPGNN3oPEbTVOve6X5a+vOJ5Pdnc8Z7tdXPalR2jU9dfVZcPN6ZMP7yP1tWrUXF79LNamuKKUzg2Gt3pMb7fR3I0T9BVL3TRmQ9XuJaQucU1Xv89WgVBdfN6dsCSON9Zm8ko4fOKq7mo22yk75l5CZ3jApPLwnFb110PCWzqn5vTnmcc8njnc686jSbfPHH7cbBlTQyO3L5p+qsr8duQY92eojtK4fIuJzKAVm1V4Paab2Ph2O907cPJiydpt9GSXwi5ug/o6FlgVscRRmsEklE5jO2trTpzvj52uOof6Kw1v43FOaQOIk6r68P50+nqlbvoG3OjvoECIJAcuEIi2LWNdlv0n5TYavkcc7nHOo0nv9Tuu88ntxPvo9OarrbsmqG6+eDRzxDCwaylNC59u9O1b9uUrlPS7/ADjGpVnuMyzhZMVU12UFa3SV/QSsuqZBxaX5a0UhgtZVVSRiM1gxZFV2u0lf9UF3/P8AarSd+1MXl89230X9DVZ3RQ1p1LX1u8dgIxleJZWZb7447y6F4ckUY8z7PD6/wbHNcalOfYrMa07ko+Mc1gd0vzx9L5B1m3AHSejyxrl8Ix3tdPJyHTnJGo3cK7DrLrcuCYUDsbpvR5oiTmvMs6WQSrhM+g5Y9W7/AE7TXryzozzCEcDJi9P5PbhjfxrIOr3EroTP4YWBWmTNPvJBxeXgDzZAE8aSKMwnfm0dIcMhZbVMSdjUrlZCp4AAAAAAAAAAAAAAAAOKYpPHGo9Ue4PVnjvdrvZ+HYgAAAAAAAAAAAAAf//EAC4QAAAGAgIABQMEAgMAAAAAAAIDBAUGBwABCBEQEhMXIBUWQBQkMDMhUCIlNf/aAAgBAQABBQL4iEEAZJdMAjYnXkyr3v3juJ4F9/350G6bbZhNPJffcatuCSj/AEdg3LHYRglFsXUpjHHBkSFs0GiEe1rWtawQQi09V9C5Bkm44oTQJZHadPqoLacbnQfz7Tu9QpPrihNCxKmToyHOUNDXtTPXA3Zkhfj9/V3nCZE/EbSzpWDbc/tbpjg3oXRLP6SWsZlU3OF33+bedonDOqCoiIumWLErenepiudBFl6wBeBLz0s9LBF4IG9YzTBSj2ScUoKuCpi15dL2eN+K/Lt6e/YsXoOvf1pqtWnQJXt9VP6soGFgwAMCXmi89PBF4MGGAxhkBzIeUcUoKuCEnRF6r+YJ5tGvypUrU3BbKBEmbEU4ftuK8oORpiLehhhCbWahyfWaiZGs+1iM+1ic3FCN5uHp94KEJt4KBJd4ytG2VO/syORM9TvCyDWD+Tack1FYJxtjYQlSV0+jspXe8JyA/wBv8G83m8vpmG3SCLPIZDHfyOTbpspnqZq+kV9Zq7swnCsgX9v8O83l1NgHGC0C6frYV8bEs98WSPVHzFUW3TmZVZJCjCzi2OyZCxSA2prIkQIPPZHC5aqVJ0SYMhnNxvThTkxjyeoLJPmSe/XNa2RxoeLDtBHJIpOqtBX0tDNIv8OTCkZssQEgTIbAUerKCd4J5QJsrJ404KfPvPNvO87zvPNvPPvJTLzI4+N7mjdUm83vJmn0qifHvfpD+B5uiCeOBn1yc5yfLKJSVYsNX13SQylFvZyUABtmtyuJiap6qsx3iLF79SzKURSL3N5Om+jFqfCXqtbq8uqx40n7OhHw5G62Gwi9/wDCxXEtFLznFUqwG8pzf7rw7zvO/G1Rf9zC5WKPuGjP8ebvJD/4NGE7LcfhvWhaqt4KqW3ADAYDkjL00pkkPZPtqLVvOG6DWolXolyO1njVo3DbEdVSCteLc0bgocTPLQtW8rxbDEaX33Vt576qjiuLYoJ8OTSLyPrGvA5MdwJ/RloN4AWU1v8Ad53nfh3nfhbAunoQsrORbdGnJUf6UbplJssr42XS0ZsgWuMtgkgrahozX6nKoi7LMbOcOLcnJPq2k2GthZP+NzFJl2uOlnqQ1fTzNWO7grM+z2KERsUQic+i45pEKjro+s458OSzd6kKod7+sVzdDSI9rALAiyl9/u+87zvw7zvwtwXT4IeQV4E0SjeWQu2Qy1yh0ii/g7z6GMRqK069cBlmFnF/CmIBMmC1v5pcwFSmMceH89hljw2EPbUtRqWpcEeUqLtZnfj3nfhb4un0Q89YRYkxv6hNJyDZA/JU5aRNlr2a/O77FuODWUndeOsIVk1TApdAnX49/Jhm8rVXh4d68DN70XREzlElf/C/YouiE2hcpRTOOW3CxLiQjxjkzxHh6s2a5qzJpnuXM89yplnuVMs9yplnuVM8eX90fj9jwANm4QbtEwRZo1o/JE4CaWGj42QbIBjAWH6i34UoTqMsCZpoLG4/B55cJcjgc4p8EAlxU3jFy2q4x1SioCXvpKsdkUa7MD2ikbM4OkuuedKaDlDDk/iElmMZbog9LbBrqr5dEpHY7dashfjONzwMiq5lKIxN7SryTzFdXULfZi5VdAZHCh5MYo3TSOwSSO9OTMkwlSTY9ZmtwwjwJmaMzQ88+efPPmx5sea35hMyDaxT+mEtOKKASXksTbVxupygpDJTHyJTHzeNbOWVxwK2S/8AJEZpmMNmTBnZJLYc2kjDx/aHtnZWMr63fuX23lrIBQphm4C/w2Z1jMIpezE8D1vW9Rwjq/8AJdPI7CyS72XrtEOKmQXId/Tx2I9KS+Ns1clsFsrOx3KBrE5xCoiY1C2vQ3mNPUeP0DeaDvPLnl3nlxiiT9JDZrEPtBUlK7MrBg2udCCAkB8N60LR5KmIPza+NbqW6uLe3o6FI9J8vdkMXNVayJK9xc00ogtGuRuJD4VuDW0jWJHBPd0hRHNtasZschra7tjyRd0fjxaCsNqdwRu9Nuuvzg0J+TInC5d7TIk6haje7hM12XSQym+W6GDY/GwqxaJ0Q0Pc3qNyi86jssAcmJUlOdTw9w2so4Pfsi8Yjo9OHbXV8QbNgKAWG6daHIWdAoXLIwwkxxn+C9vSORDpWIT9gpg5SdGIYyxMClMnWp3SmCPXIpxwVDYGNFHGuTRNolaUymHMkyNVOzMqgWtC0vpvZKhspwAlJRRZBc0rNHKFcLrc6NOkxrpslhiWoXQ7YKqb0siyS1EQ5uEGg4oj8XVnbHxJIKRUJhJJlYUOG2W42KNETiLqM1Jo+LBSdj1hkrT7wCx2c8tJvPKe63gf26R/ojiCVJSuBRNWIVYsmArlIDZEIaysTsTUmzWtB0awtyh6/N//xABaEQACAQIDBAUDChALBQkAAAABAgMEEQAFEgYTITEHFCJBUTJhcRUgIzNCUmKBk6EQFhcwQERQVFV0dZGUs9HTJCU0NVNzgrGytNJDYGNywWRlg5Kio6Tw8f/aAAgBAwEBPwH/AHczHaPK8uLJJNv51uNxTWkcEdztcRx2PMO4I8CeGKnbatkv1Slgp17jKWnf5t2vzMPTiTaDO5zdswmXzRbuAD0bpEP5yceq+b/hKt/SZP8AViHaLO4D2a+SQe9mWOcH43Uv/wCVwcU221ShtWUcUq97U7GJx59DmRW9GpfSMZfnuW5lZaecLMfteb2Kb0BSbOR37tnHn+4dXV09DA9TVSrDDGO0zfMqgcXdvcooLMeQxnG1dZmLNDRl6Oj5cDaomHjI49rB/o4z46mfuVe7CpgJjd+bBjwU82CpUggm44gjgQRxBHfwPIjvxk+1tRSFafMtVTTcAJ+dRCPhf0yen2UdxfguIZoqiJJoJFlikGpHQ3Vh6f7xzB4Hj9wKqqhoqeWqqHEcMKF3Y/Mo8WY2VV5sxAHE4znOanOqreSXjp4yRTUwbsxr75u5pmFtb/2V7Iwq4VcKmNONGCuCuGXDLjIs+myacI2qShlb2eHnoJ4GaHwce6XlIBY9rSRDNHURRzQuJIpUDxuvJlYXBH7DxHI8fs/bDOjXVnqdA38FontIQeE1SODk/Bh4xr8LW3etoxjZ/Jo83epSSZ4dwkTgooa5csLG/hpwNjKYfbs3yaftwNkaf78l+TT9uPpTp/vub5NMfSpT/fUvyaftx9KlP99S/Jp+3B2Sp/vuX5NP24Ox1Oftyb5NP24OxVMft6b5KP8Abg7C0x+35/ko/wDVjJsqOUU70wq5amEvriWVFXck+WEIJ7DntaeQbUR5TfZ2f5j6l5VVVSm0unc0/K+/m7CEX5lLmS3ghwtybkkk8STxJJ4m5PMk+PE4jGNifbsw/qqf/HL9yOkCrJfL6AHgokq5BfgWb2GK/oAmt/zYTuwnd/8Ae7GxXt1f/Vwf4pfuRttNvNoZk+96ali+No9+f1wwhw+Z0cAsZdZHuYhrPovwUfGwx0d5kK+qzZViMaxQUpBZrltUkw4gCw5eLen6xtRtXJs5nlEu6aammoVeeJXAuOsTLdVbgJFC9lri/ktwxl9fS5pSQ11FKJqedbqw5g+6jkXmkiHsuh4qfiP2ftzWpS7TZkD25D1MhRwsOoUoBY93IjvJtietqKi4dyEP+zXsp8Y91/avgHHRR/Ks6/FqL9bP9Y6Uf55oPyYv+aqMbF7TtkNcIKl/4rrXVakNyp5DZUq097p4CfuaLj5UaYBDAMCCCAQQbgg8QQRwII4gjgR9ndKNOYtpUntZarL6V7+LQtLAfjConzfQBx0T/wArzr8Wov1tR9Y6Uj/HNB+TF/zVT9Do5z45jlbZbUPeqyvSkZJ4y0Te0nxvAQYW+Bue8m32b0r5Y02XUGaxrc0M7U9QRzEFXbdufgpPGqemcYB+h0S/yvO/xai/Wz/WOlP+esv/ACWP81UYJxsXmrZVtJl8l7Q1UnUKkdxiqiEB9Mc26lv8C3In11dtPs/lsjRVub0MMyEh4d+ryoRzV449bo3mYA4p9s9lqlgkeeUAY8t7LuPnnEY+fCOsiq6Mro6hkdCGVlYXVlYXDKRxBHAjiPsbNcuhzbLqzLp+EdXA8Oq192xF45QO8xSBZBxHFeeK2jqMuq6mhql0VFLM8Mo7tSG2pfFHFmQ96kHvwDjok/led/itF+tqPrHSqf46oPyWvx/wqpwThXaNlkU2aNg6kdzIdQP5ximl39NTz900EMw9EsayD/F6zbfbHM6/NPpY2aaVfZhSVFRT3E1VVMdLU8LjtRQQtdZpVtvGWTjuFvJkvRJQpEk2fVc9TVMAzU9IwigiPejSsryT298u5F721CxxW9E+zdRGRSSV1DLbsyLKs8d/hxSrqcDnZZY+PfbhjYnZrPtmazMKWsrVq8neFGo2WViu/wB53U7ktTvu9W903ja8dpHK2T63lu0meTdJM+USZhK2WrX5lAKQrHuhFBBO0SjsahpKKdWrUbcSbn1rkhGI5hSR6bY6Ndos5znMs2hzOvlq4ooN5EsgjtG2/VLroRbDSxFuXLhw9b0k7Kmsi9X6CLVU00YXMY08qamjHZqQvupKZezJbtNBY8dzxxlGfZpkTzPldT1ZqhUSY7qGXWsZYoLTI4Fix8m1+/A6QdrPwoP0Oj/cY+qBtb+FB+h0f7jH1QNrPwmP0Sj/AHGPqg7WfhMfolH+4x9UHav8Jj9Eo/3OPqg7WfhIfolH+4x9UHaz8Jj9Eo/3GM2zrMs7njqMzqOsTRRbhH3UUVo9bPp0xIintOxuRfjzxfCRmW/hjLF05blq8iuX0SkeBFLEP+n0c2qzQ5ZmFYvl09JPLGDyMixtuwfMZNIPmx0aZTHJmuYZrON5LSRJHCzcbTVhk3039Zu4yl/CZ+83wzKoLMQqjiWYgADxJPAY63S/fNP8tH/qwksUt93JHJbnodXt6dJONqtooNmcomzGUbyW4go4P6eqkDGNTaxEahWklNx2EIXtlQco2d2n2/j9Wc5zqWjy+V5OqRorMH0vpbq9IrwwxQAq0e8Z9bOlysnFjnOze0uwKLnWTZ1NVUMToKpSDHo1PpTrFK0ksU9OxZY76iwkIfQnZZdls+j2kyWlzNVEcrgxVUSm4iqorCVV4k6GussYYlhHImrjfHSFtzV5RPFkWSfznMqPUVAQSPTrL7TBAhDA1EvlMzA7uMpoBeTVFSdF+eZnH1zPc/mhrJVD7v2StlRiL2qJpJoxr99uzIB75jiql2v6NK+mElZ1/K6hiUQySSUVQqEGWIpINdJUhSp1oLkadLyorKMrzGmzfL6TMqRtVPVwrKl+a8w8bW4a4pA0b2uNaGxI44nr896Q9p6zJaPMGy7J6NpiyxkqOqU86wtUSRqymqqJZGTRGz6I9YAKLvHaToyznK9NXs/tJN1yMht3KJKMSW4sBLHNOCX5aJEEZFw72ONp8izjPsmoaSlzIZfXQyQTVUoaVY5WWneOVLwdq29fWvZ08OQ4Yo8izOfa+TII8xEeZJV1kBzDVNYyU8cryPrA33sioy8RftceGNk9js/yPNOu5jngrqfq8sXV1kqn1O+nSWEwCgLbVcXOoLw7xtdS7cZrmaZbkMoy/KeqxvNmAlEGqZnfWjSpqquyFA3UKWZW9kuGGH6JK1ojL9M0jVui9mp5N1vvxjrJlCfC3BYeHdjYnaLO8n2lbZLPah6iMySUke9k3ppqlF1QmGZu21PUKAixHheRJFEZ3gfbTZbOc/npZ8szn1PipqeWOWBnqEV2L694u5vcsvYa4HBE4t7nY/Z/Nc/rK2DLMzXL5aeHXLIXnTervVXTeEEntEN2sbGbM5xs81e2aZsMyFUIBCivUOIt1vdbHf2sW1gdkchxPAes58DxB5g9+NuNgpKJ5s4ySEyULFpayhiUl6I82lp0Fy1IeJaMcafuG59rvf6Fzi+LjFxi4xfFzgC5tjKqFqqpp6ZR2p5ooR6ZHC/Ne/8A+YVQiqg5IqqPQosP7vo59CajJsyiXiWpJTbx0DWfmXGwKrC2aQ8mbq0o849lQn0A6fz4zvKo87yqtyqWWSBKyMRmaKxeMrIkisAeB7SC44XFxcYk6HaJEd/Vyu7Ks1txF3An3+Oh3WM2zhSzaTl8Rtc2uKkAHn3cbeFz446ZpHIyGmv7GfVCdh4ugpUU/Erv+fGWbcbRUGXUFFT7FVrwUtHTwRSLHW2lSOJFE3Zo9J33tpYE6i+rU17nOdsNpc5yuuyuTYuviStgeAyiGucx3tZwpoxcqQCOI49+OiehzSgyrM4swpaqkiauR6WOqieFiTCBO6RyBW0kiMa9NmIsCdJAyweqfSxNJU2fc5zmegEDllsdRHSfHH1eJgeepAfodKtKlRsnNK1tVJW0U8Ztxu8vVio9Kzn02GOiqR22TSNrkQV9ZEl+5SUlt6NUjfnxm+z+0uxO0FRtBkEUlXQTyTSndxtOqwTsZJqKvpozvN1G1mSdLJZIpNccqlVyHpUynMGSnzaFspqGson1b6gdibcZbCSn4/0qGJR5U4wCCAQQQRcEcQQeRB8MZOh+q3Ut/wB7Zx+bq9UPobQbVZPs1GrZjO2+lUtBR06iWqmANtSoWVUS4I3kzxxkgqGLC2F6VKmpu1BsjmdXDcgSrK7Xt47ihnQHzCVvTiCvmzbpHy3MpqKXLZajNsuL0c2reRaEhi7WuOFu2F18Yl4MOfMye1yf8jf3HHQ+unOs6H/YVP56sfs9ftP0b0Oas9blDR5bXNdpIdJFFUseNyqAmmkJ5tErRt7qLVd8ZnkWa5NKYcyo5qY6tKyEaoJbcjFOt4pAeY0tfuYBrgaDjRjRjRjRjKNms4zyRUy+jkkjvZ6p/YqSId5knbs8PeJrlPuUONqdmfpaqKGkNT1maehFTUOF0xrKZ5Y9EI8ooqxjtOdTG50oOyKeK746P8o6xmPXpFvFl6618DVSgrF6d2uuS3cwQ+sIBBB4gixHmOJY59nM2E6IWiuwsOAnpXIuoPLUthcHyZEB8m16LNKDMED01RGxI4xMwWZD714idQI8eKnmrEWOK+spKOmleqqqemTdv2p5UjHknlqIvfwHE46Jo9Ga5qfHL4v8yMdK+VyVWX5dmCIWWhnlhnsD2I6wRhXa3JN7CiEn3UijvxsVnVPmuRUEYlTrtFSw0lXBqG8DU6LCJtHPROqrIGA0hmZL3U4d0iUvI6xoouzuwVVHiWNgPjxTVVNWRCelniqYWLKJYXWSMlGKOA6kqdLAqbHmMZqrbLdITZm8bGmkrWzC45vTZgrLWMnvmjklqNK34lAtxe+Kepp6uGOopZo54JVDRyxMHRgfOPnB4g8CAcdKGc0z0MOR08qy1MlSlRVrGwbcxQBt3HLpvaSSVldUPaAiuV7S32Jyt8m2aoYKhd1O6yVlQjc42qGMgR/B0i3auPcuGXuxRZhQ5lCJ6Cqgqoj7uFw9j4MPKRvguAfNjpRynJ0o6aujhggzWWsCEwhY3qoGjkaZ5kW28KOI/ZmGoFtJY6rY2GadtlMn6wXZxA6oXJLbhJ5Up+J46RAEEf8AwwtuFsUZWj6UJ5agiJWzeuXU50gGqilEJN+596lu46h441LqC6hqIJC3GogWuQOZAuL+FxjNooKzpLKZzY0Qr6aIrM1od0tIjU0bX4bmScprB7Da3DcGbBMNNDcmKCnhT4MUMUSDh4IiIo8yqB4YlqqfM+kilr6N97TPnFAsctrB9wsMLOt+aM0ZMbe6SzW44cXRh4qw+bHRe6Um0OZU8x3clTRyJEG4apKepRnjHw9BZwvvY3PdjUpYqGGpQCVuNQB5EjmAbG3jb18sMU8bRTxRzROLPHKiyRsPBkcFSPSMV/R7s1WktHTSUDnjeilKJ8jKJYlHmRVHhio6KUuTSZyyjuSpow/D+sinj4/+EP8Apj6ldffjmtFbxEE1/wA2of4sU3RTALGsziV/FaWkWH/3JZp/1eMv2C2aoCrmi67KvEPXOZ1v47myQH+1E2ERI1CIqoiiyqgCqoHcFFgB5hjpQTVnNB+TFH/yqnGXUU1VUxU0EZkmnkWONB3sxt8QHNmPBRcmwGMjyqPJsugoksXUa55APbah7bxvHSOCJfiI1Uetq6OnrYjDUxiROYvwZD75GHFW845jgbjhiu2FSZtVHXmL4E8W8t6JI3jP/oJ8+F6M3mkDVmbDQD5MFMWc+YSSy6V+Sf0YyPZrLNn1k6ikhlmCrNUTPrlkVCSq8AqIoJJsiLc+VewtPBDUwy088aywzI0csbi6OjizKw8CMVvRpDvjNlGZS0XG4imRpNHmjqIpI5VA7g6yN4vfEfRvVzsPVPPpZYx7iNZpmPokqZ2VPkmxlGVU2S0EOX0mvcw6yGkbVIzSOXdmICi5YngAABwAxnmz+XbQU6w1yHXFcwVEVlngLW1aGIYFXsNcbhkawNtSqQ3RpWxMy0edqsLH3UU8L2+EsM5SQ+fsg+A5YyTo/wAtyyeOsrJnzKqjYSR64xFTRyDiHEOqRpGVuIMsjLezaAQLEBgVPEEEH0HgcVXRtu5jNk2bzUVybRyCS637lqaeSJ9I5ANG5tzc4oujZDOKjOszlr7EEwxiRd5b3MtRNJJMyHkVQRm3JxhESJEjjVUjjVURFAVURAFVVA4BVAAAHADG02w9Nn1R1+Gp6lXFUSVjFvYZxGAqF1DxusiqAgkVj2FUFDa+Nmtipckr/VGqzLrcqwSQRRJG6ook03ZnkldmsFsECqBzucbSbGUO0Diq3rUdeqBOsIgkSVV8gTxErq08ldXRwvAllCgQdHVdIVhzLP55aFLWpod+1wO5RUTNFD8UUluQHfhdgaKDOcvzOiqeq09B1ZhR9X3jSyU5vrapM6nVMeMhaJiD5PCwXGddHcFdWS12XVvUZJ5DLLBJEZIhI51O8Lo6PFqbtFLOLk6SgsuNltljs71uSWuatqKwRBzuzGiLEXIA1SSu7HXxYlfAL3n670jxNJnFAqqWZqBEVQCxZmqpwqqBxJJIAA4kmwxsZsoMmi6/WopzKdOyp49Shb/Zr/x5BbfsPJ9qU21l/uTJldJLmMeaSpvKmCAU8GqxSEa5HaRFt7a2806zfSo7Gklifs3/xABbEQACAQIDBAQFCRMJBQkAAAABAgMEEQAFEgYTITEHIkFRFDJhcYEVFiAjQlJikZIQJDAzNUBEUFNUVXJ1k5Shs7TTJTRDc3SCstHwF4OxwcInYGNkZaLS4fH/2gAIAQIBAT8B/wC7lDkWY14V0i3ULWO+n9rQg9qixdxbkUUjy4p9kaRB881M0x7ogsSfrEjH4x6MR5JlEQstDC3llLzE/nGYD0AY9TMr/B9H+ZT/ACxLkeUTDrUUaH30LvER6EbR8aHFRsjTtxpKqSNuxZwJE9LIEYefS3mOK3J8woLtPATEP6eL2yH0sOKf7xUPk+0dNTT1cyQU0bSyvyVf1sxNgqj3TMQo7TjK9m6ShCy1WirqufWHtER7kRvHI+6OPxVXtZ8M+NWNWNQwG8uAwa4NiCLMpsQQeYI5EEcD5MZrszDUhp8v0wT8zDygk/F+5N5vaz3LxbEsUkMjxSo0ciHS6MLMpHeP9X5j7QU9PLVzx08Cl5ZW0oo/WT3KouzNyVQSeAxlWUwZRT6Es9Q9vCJ7dZ296vasSnxV7fGbrHDNhmwXwX4414D4D4VsI2M4yaLNYtSWjrI1O6l5B+3dS96n3J5oTflcGSOSGR4pUKSRsUdG5qy8CP8A75HmOH1/srlIo6Tw+ZfnmrW8d/6KmPFR+NNYSN8HQvfdzjPM1fLFpykSy75pAdTEadAU9nfqwdqqg/YkPy3wdp5z9jRfLfHrkn+94vlvj1xzfe0Xynx645/veL5b49cs/wB7RfLfA2onH2LF8t8DayoH2JD+cf8AywNsKkfYcH5yTGa5l6qTJUGmjp5QmiQxsx3tvEL390o6urmVsD4o+vskoPVLMqamYXi1b2fn9Ji6zg25a+Ed+9xhrDgAAoFgByAAsAB2AcgMOcbXfS6H+sn/AMMf2o2HperXVpHEmOmQ+Qe2ygecmK/4uH/zw+NrfpdF/WT/AOGP7UbIRbvIon+71FRL6Ffcj9icPhcuq5uIj0KfdSdT9R63xLjbvLzRU+Ws0gdpJqgEKtgNKRHgSbm9+4fQNntm0z3KKtt4sNRFWMsMhUmx3ETWYg3MZvxW3whxxW0VTl9TLSVcZinhNmU8iPcuh5PG44o44EfX+xtG9Ts9l5uFjHhQLc7kV1SeA7efmH6sRUkEHipdh7trF/Qfc/3bYOOkv+bZT/aKr9lF9A6O/qVW/lA/u9PjazZ1c5ojNAv8o0is0DKOM8YuXpW4cdXjQnsk4cpGwQQSCCCDYg8CCOYI7CO0dn190cT7zZ9ob8aavqFt3LKsUw/Wz29OCMEY6TP5tlP9oq/2UP0Do5+pVb+UD+7QfM28yUUGYrmEC2psy1M4A4R1a8ZR5pgRKPh73sAv9e9GWYLFX1uWSGwrIVqIL8jNS31r52hcv5ofmEY6Th865Qf/ADFX+yh+gdHH1Krfygf3anwBja3LRmWQVyW9tp4/DKc9okpgXI/3kW8j/vA9g9lRbOZ7mKLJR5VWzRNYrKIWSJgeRWWTQjDyqxGKjZDaamUtLktbpAuTFHv/ANUBkP6sMrIzI6lHQlWVgVZWU2ZWU8QQeBB4g/W2W18uWV9JXw8ZKWZJdN7a1B68ZPYJELIfI2KSqhr6WnrKdtUFTEk0Z7dLi9m7nU3Vh2MGGCMdJ/8ANco/tNX+yh+gdG31Jrvyi37tT4AwYxIrIwurgow7wwsR6QcVEe5qJ4TzimliPnjkZP8Al7DYzZLLaLLvXHtEsJG6NTBBU2aClpgCVqJ4zdZJpRZ4oiG0KU6hmbTHnHSpWvK0eSUkNPTqSFqKtN7PIBwDLEGWGEfAbfG1uK8Rij6UdooJAapKKui90jQ7h7fAkgZQp8rRSD4PaNsto8k2kpKCqpaRqXN1mdazVGuowboWvUoAKhd5bdFwsiWe6KCNX0PMdnsmh6PIM1joYkzA0WXTGqBk3hknngWQm76euHYWtYX4AcPYrxZQeRYX+PHSLkGT5Rl2VS5bQxUsktQ8cjRmQmRBAGGrW7XIbjfn5fY9H20opZPUOuktT1EmqgkflDUOetTlvcx1DdZL9VZrjhvcEYzXJMuzlIUzKn8IWBneIb2WPSzgBj7U6E3CjnwGPWLsx+Dj+l1f8fHrG2Z/Bx/S6v8Aj49Y2zP4PP6VV/xsesbZn8Hn9Kq/42PWNsz+Dz+l1f8AGx6xtmfwef0qr/j49Y2zP4PP6VV/xsZZlFBlEUkGXQbiKSTeuu8lkvJpVL3lZz4qqLA27bc8AYeQJbGYENmFew5NXVZHpqJD83LKYVuY0NK3i1FVBE5HMRtIokI8oTURjpEzWRMsocsgOiKqlZ5lXtipBHuovxNbh7dpiTlYjABYhVBYnkALk+YDHg1R97zfmn/+OHjkjtvEdL8talb+a4GNmshm2izWHL423cVjNVz/AHGmQjWw75GLLHEOIMjrqsgYjM9oNm9hX9ScoyeKrr40TwmRmVSmtdS+EVbRzTzSkEPulCxor8GTxMZVtFs9tyxyfN8nipq2RHNMwKyayq6n8GqhFFNBOqhnCG6MqkF2voO0uSPs/nFTlrMZI00y00rCxlppetEx4AahxjkI4bxHtYcMbCbGUuawyZ1nIvl0LOsEBYxrOYheaadwVIp4vFsrDePr1FUjtJUdJWSZc/gmTZCk1JExQSBoaCJlBtqhhSmmOk+5Mm7YjmgxTx7KdIlFUFKMUWZQAB3EccdZTlwd3LvIrJV05YMLSXtxusLOrHMsvqMrr6rL6pdM9LK0T28VrcUde9JEKyIeZRhcA8MU9FkmwWzlLnFXQLmGa1YgUNIFLeE1ELzCCF3SRaWCKNHDyrHvJNPHWWRFi6SMozLVS59s9D4JJw1xmOr0X4AmKWGJgV8bewyCRSAUTVxxs3neVZHm1bVVWXeqFFLFPDTRMkMjxBqhJIn01F1vuk0Mb6hq588VeeZdBstHncmX7zL3pqSVaDdwG0c8kSRpu29o9rLhrchp6vG2NqdrsjzrLPAqDJBRT+ERS+EGGkjsiBwygwDWS2oC3i2uTxAxsrU7G5Zl0mY53F6oZp4S6Q0JhM4WJVQo6xSaaU6izXknckEe1qCpunSpRLKIxs4qUYbT1aqLeCPvEAo1iv8A+HvQvZr7cbY5Dk+bbPDarJadIJFjiqZNzGIRUU0jiOUSwr1FqKd21PIACRHIrF+oRsftNlGRwVUGY5OMwlqKiKSKfd00jIoTRuz4QLqFbrrpY3LtcC122rz7LcjpKOfMcu9UI6iZo4o93TybthFr1WqOqOrw6vH0Y2v2jyrPhQjLcqGXGmM5lfd00bS70RaV+dxxC6CeseBPAc/YcuXDGxu2yVaxZTnEuirULHS1srAJVAdVYp3NtNSOAV24T+6O9+mFcEYti3kxbFsWxbFsHgL4zOsFNBUTseEMUkp80aFv+VsMxdmY82JY+cm5+bksogzbL5DwC1UQv3am0f8AVjbZjMMtm7AKiMnsB9rYfHx+LGT5nJk+Z0mZxRpM9JJvFikuEe6MhBI4jgxsRyNjxwnS1mDOi+pFJ1mC38Im7Tb3uOlhg+W5SeFxWzWNhexpwTx7jYX8w7sdEqIrZ3UW9sAoYQfgMal2HpKJ8QxmWx+QV2YVtZU7Y0iz1NXUTSoz0V43klZmi41gI3ZO7C2XSF06VtbGU7LbO5TmVFmUe19FI1HOkwjMtEgfTzQsKskBgSDwOOk+uy6vzLLZKKpp6qRKF46iSnkSVVXfu8KM8ZZLjVK2nVcBrkDUL5g3qf0YQxUxKb3KMu1kHj/KEkE1VxFuD+ESoR2o2n5nRnVPT7UQxr4tVR1kMnHhaOI1Sm3bZ6cAd1zjpLRRtPI685qKkkfysFaO/wAmNcZXn2z+2GQwZFnsqUlZCkMY3kiwlpoE3cNZRzyDd711JV4X63Wkj0vGwJzvo2zOgV58smXNIFBYwhdzWoo48IrlJ+H3J94T4sOORseBHMHmMZs//ZdTJ/6ZlP7em+ZkezWa7QSMtBCu6jOmarnbdU0RPHSz2ZmexB3cSSSWIJUA3w/RtT09krdqcupprXMTRxrbzb+tgcg9hMS4lo4sr2Ar8uhrYswjgyzMAtVEE3cmt5pOrokmXqFtHCQ8V7Dwwnjp+Mv/ABGOlV9WU5N/bJP3Yez2c6QKzLFSkzRXr6JbKk2q9ZTqOwMxtUIPeyMrr7mXT1cZdnWW5vFvcvq4qgWu0YOmaPySwtaRCDwN1t71iLHGv041DGsf6tjWP9f/ALjUMZptDlWTRs9dVIkgF1pk9sqZPIkKm/H3z6Ix2uMbNbQ+uGCsqhTimihrDTwKTqkaMQxSa5SOqHLOeqnBRYXYgsZ5LJjbnNNxQCjRrS1zaW7xTxkNJ8ttEflUv2+wBIII5g3HnGI3hz/LDCzAS8CTzMNSgNmt717kXHONiPGvary6soXK1EDqAeEgBaJx75JANJB9BHJgDcYo6Wpqp40pqeadta8IY3kPP4INvTjpOk15blg7q2X9hjo0zJKaurqFm0tWQxyw3IGuSlLkove27ld7D3KMezG12UzZbnNa5jfwSsqJaqllsd2VncymLVy1wsxjIJ1EKHtZhhEeRgiKzuxsqopZmPkAuT6MT089LIYamGSCUBWMcyNG4DqGUlWAI1KQRw5HGWuNpNhRlyOvhEdIKEX5JPQsrUqv3B444AW42DFrG2J4JqWV4KiJ4ZoyVeORSrqR3g/qPI8xwx0c5VUJWy5zNG0cEcDwUrSLp3sk1g7x3tdI4gyM46pMlr8GttdmSZttBWTwNvIUMdLA45SLAojLL3q8mtkPahU9uKuhrKCXc1tNNTS+9lQrcd6k8GHwlJHlx0cZpmjVc9E8s02WR0pcLIWdKaZXjWJYna+71qXG6XqkLqt1ScbYiEbS5ruAqqZ0ZggAXfPDG1RwHujMXL/DLX44qtVX0cwxQDeMuWUbWTrE+DTRmUWHG6bp792k92NLWLWOkWBNuAJ5AnkCbG3fbGWSz0vR6Gyq61Zo6iTVCLy7xqt1qJFtx3qQBtBHWXQuniowBLUS2G8mmmfs1SSyyOfSzuzHykk9+Iqeoy7YCpoqpd3OmV1rPHe5TfNLKFbucK4Dj3LXXnheDKe5h/xx0iq9VkeX1EQ1x09UjSEcdKT05VZDb3GtVQn3zoO3GlrBrHSSQGsbEi1wDyJFxfuuPZxySQuskMkkUim6yRO0bqR2q6kMD5jii262hpAFeojrUHC1ZGHe39bGYpT53Zj34g6THsBVZQrHtemqyg/Nywyftcf7SqK31MrL92/gA+PT/wBOKjpLnNxSZVHH8KpqWm/9kcUH+M4rttdoa0FfDPBI24FKJNwbHs3t2nH92QYZmclnZnduLMxLMx7yxuSfKTjo3a2U1v5Rb92gxmFXFS08k87hIoUMkjnsVefnJ5KO1iAOJxnGZSZtXzVb3Ck6IEP9HAt92vcDzZ7cC7MfY01VPSSCWnkMbjn2qw96yngw8h84seOKPbJogBVUQk+FDLo+ON0k/wAY82D0hLEhWkyw6zyaaoAQdxMcUepvzqefGc7QZjnjR+GOgihLGKCJNEaF7Bm4lnZiABd2a3Za5vDNLTyxzwu0U0TrJHIhsyOpurA94OKTpBl3QhzTL4qzgAZI2WPVb7pBJHJGxPepjHcuH2/poVPqdkkUTn3btFEo88dPCC/51cZnmVRm1bLXVWjey6ARGulFVFCKqgkngoHEkk8ycZPnlfkk7TUbjTIAJoJLtDMFvp1qCCGW50upVhci9mYFekKklVWq8nLTKOayQyrfvUywhkHk61u84zjbjMcxielpo1oKaQFH0OZKh0IsUMulAisOYjjVrdXWRe4NiCOYNx5xim6QN5EIs2yuGrsAN5GUs1u1qedJE1Hjcq6juUYq9v3WEwZRl0VACOErFDoJ7Y6eKNIlYdhYyDvTDu0jtI7F3dmd3Y3ZmY3ZmJ4kkm5J5nGz22FTksHgUsHhdGGZ41Em6lhLnU4Rirq0Za76Co67MQ4uQdoNrY84ovAKfLxSxGZJnkaRWdjHqsAiRoq8WuWLMTy4cSdn9rK3I0NPu1q6IuX3DMY3jZvGMMtn06ubKyOpPEBSSxm28pIw0uX5JBFWPzqJRCpBPMsYIlll9Mkfl7sNttVzZVXZfVweEzVu/BqzPoEaTgDQtOISNMQFkAkUcePG5bGUbeTUdJHRV9J4YkMYijmWUJJu14KkqujpLZbLruhsBq1tdsbR7RjPfBo46NaOCl3hQbwSO7SaASdMcaIAE4KAeNyWPIfRdgJBHlNcWIVVrXdmJCqFFNCWYk2AAAJJJ4DG1u0xzaXwKjdhl8DcW5eFyr/SEfcUP0lTz+msL6Qn2pTMaqOgky6N9FNNMZ5gvBpToRAjt9zXRfSLamPW1WUD69//xABeEAACAgECAwQDBwsMDwYHAAABAgMEBRESABMhBhQiMRVBURAjMkJhcYEgJDAzNDVDUmJykQclQHOCk6GipLTS1BZEUFNUY3R1kpSxsrPR4TdVVqOltWZ2hMXV1vD/2gAIAQEABj8C+pZ3ZURFLO7EKqqo1ZmY9AoHUk9AOOQ2V9MXBrrUwSLkCmmoPOtB46EJDdDE9vvHXcsLKCQ6YPstBGPwVjL3pJSflenTjh/Qt76eN+NrRRIfgriOzUlmPT8+56TZvnDj5uNeRmdP/k6t/wDiONcpUqTp8YZjs9PU+hXpPjND+cH+bhFzvZfRfKSziL+/r7Vp24l0HyG6x+XgRVMzHQukhfR+YHo6yS2u0QtK3dbROnlUszlNQJAjED+4c2Pr6ZztEq9MZWlCwU5CAU9KXAHWt0O/u8aTWyu0tDEkiS8NGnePQyS+OGAti+zVQ+oTOWJvzRjxBJXyFuLXekcatxHN2oydjK2tdWp476yxyD1RmVla7Y9plVqWuu3kDbvYeh+zuKpuP7Y7qk9w/nXrPOuOPkacgerjQAAewdB7mjKGHsYAj+HgtlOzeLmmbztw1xTu+WnW5T5Flh+S8rJ7V4M3ZTLS1ptSe4Zj3+s49SxXIIhYgI9XOitB/ItHpu4jx2RjsSYvVuRQym69iJ0B8XovIRsWr/jmCvYURGQSWKW6TxCCrIcdmhHvmwt107x4QOY9KUaR34EPm8QWZF0eevBuX+4E3ZTsBOzF2FS72gp++zTyu4RqWB2b9d32hsigaSRnYY3Y6xXWgznbxWZ5GFmHs9vOpJPMEmanR9zM7eN8fG35N2V989QRVakENWtAojhr140hhiQeSRxRhURfkUAcNHJP3iyuoNarpLIGHQrI2oiiIPwhJIGH4pPTj6zqV66+2XfYf+Awp/FPG58nYHyQ8uBQPZpAkf6W1PtPH30v/wCtS/0uNVyMzj1pOsc6n6ZUZx+4dD8vGl2lFMvrauWhf59rmRG+bVNfaOAtewFmP9rT+9T6+wKTtkP7U0g+XiWjkqde9TnGkta1Ck8L/OkgI1HxW+Ep6qQeP7Iewj3JoK0neGxkcsrZXHMh3rPjJ09/txRHpy9e/wAQ2srW9ZGirdm+10yRZQhIcbmW8EOUOgVK934kOQf4k3hhusdukVjYtj9mzdgOy85aST617RXKu55WebwegarJ+EfcBkjFubVhjtRJ3yIQdoe0ECTdo7EayVq0qapgo3GoUK2v65sCOfNoDV+54NDzpZpLVyZYIIx4nb1+xEUatJI3xI0Bdj0UHhoKRkoUeo8LaWpx7ZZF+1qR+BibTz3vJ02/VajoQdQR0II8iD6iPPX1cLXyhe1V8hP8K1D+cfw6fne+j1M/ROEngkWWKQbkkQ6qw9oP8B9YPQ9Rxa7V9ma2zIIHsZjGQjQX1Hjlv04x8G8nikswroLigyxL30MLadlO0FgvmqsRONvTMN2VqQqCYZmY7nyNZNWLaFrVZDM5M0UzP+y3lpyIM7l2ehhkbazRvs1tZHlE+NMfEysCQ0fe5accoKS7Se3ucR5wk8gwS2dz94uK7C3mJTINZzDNuhqybiO9izM2ssMTCa5akEcECb5GP6AoHxndiEjXzd2CjqeObLrHVjLCpVDeCJPx39TTuPtkn7hPAB9i2tulx8rfXEHmUPlz4fZIPjL5SqND4grLHPA4kilRZI5F8mVhqCPX9B6g9CAeKnbPs4DSp2byTnuuqHE5tHNhZIlHSOtcZTLEo96SYT1yiQvBG1PLppHcX60ytYdO75GFE54TqfeJQy2K7an3mVA+2VZEX9lJjMfL+tkVr0PRsAapDice7yZPJgfGE7Las19dnOVqcLFSRpUx1KIQ06NaGpVhHlHBBGscS/LoijU+s9ePRddvrPHyESaH7fcHhkY/k1/FCg/H5rdQU04tLJO8Hd0iYFEV93MLjruI0028fd8/7zH/AEuPu2b96T/nx91y/vaf8+PuqT97T/nx91Sfvaf8+PuuX97T/nx92zfvSf0uPu+f95j/AKXH3xsfvMf9Lh6ouS2oTJzIllRV5Bb7YEKk+Bzo23yV9zDq7cZDC313VchXeBiPhxP8KGxEfVNWmVJ4joRvjG4Muqm52UybBa+UtPhranULHlasjjHWo9fi2GLVtPwiW4pNx5Shv2T2gyauUtvU9HY7YRzO/wCSIp13TqPufmtbk08Sw15XAJXTjN9qpxq7MuEodPgoojt5GbU+ZkZqUMe3Tby7IbdzF2XLinSbYIKvlr3mf3uMjXzMfim09kR9nGpJJPUknUknqSSepJPUk9SfP3Ml+1Vv9+b7Jie09ImvLkIlRp4vDImSw5i7vZ3j8KKzVVjbz0pj1Lxhc0u3XI4+tYlC/BSyYwLUY+SOwssf7n9k9mcKD93ZK3kZB+Tjq6wJr+6yP8HHZiApslt0BlZumhL5V2vx7/y0rTwRH9r4xeNB6KJb0q+os3vEBP5qixp+efdyP7VW/wB6b7Jcm2bpsTcp5GFh5r753Kx+4Na5KWX1skbeaDiXHsffMLmLlXbr4u72lhyMUmnqRpbVmJflgf6r+wbsM0i2u8DH2btUp3uzkG1EtOnI3hqQ0+os3NyyiVZtGrQ1TLYNq72tq+kX8bRyHJXNznqebkXlSXeD0LCtN1HRiOvEfZ/thPPfxOsTSc+Z7+2hKxjXI4q3JrZMUex9acnT3qSHkQzaNxHNC6yRSoskUiEMkkbqGR0YdGVlIZSOhB147RrVfI5vI5Se1jMXUs2rl6FL0mVXlTLSMrmedYlkgqwxBSXlVPtW6N/Smd7S1kyUy8wU7dq5P3fd15G6snc6gX+9Uo5YFPlwnYrtfPPNSa4mNcXJ+e+Mnn2ilaq2pSWfHTb4dYjIIkrTd5hCNG0M1m7blSCrUgmtWZ5GCRw14I2lmlkY9FSONWdmPQKCTxex/Z64+E7OU+shEstWNK0jOtY5F657zdt21Rm7kp7quw7ggTnM+V7Odr5b9+pG83d4K9vDW5RGNxStKmUvJO8nUCtPyY3+CZH3beLeJzBU53FRrNz1jEXpCiWERneNAEjs15isdkKsaMJoHRdTKEwjUrtukZs6I5TUsz1mlQY684SRoHjLoHUPsYld6q2m5VIqYbs/ZlxGDxGOo0cnl57U8Ul+7HUiSx3q9FzLdmSZw7ipB05Do+QYmVCa3aGtnDLW7wkElvGzWV5Uj6mNL9SwOVNWmKlRzOfCZNquqM0etHMlVjt6yU8jEnwI79bQS8vXXSOZGjtRLqSkU6Ix3K31PZ6h8Sv2eayv59/I2YX/AIMfHxSqxjbHWqVq8aj4qQQJEi/QqgcTx/4LUowfS8Pe/wDZaHuaNNzG/EhHMP6R4B9LjjMKkBjWKCmQWfcW3SWB1AGi/B/Gb3PM/UefuUlMLT1pqCPPErgajvNhdUVhoJV2+F9w6eE6jiG9RmE1eddVbyZT8aORfiSofC6Hqp+g+72jgPXdhsg30xV3mX+NGOO1db8f0TOP3HpCNv8AeX6madgSsMUkrAeZEalyB8ug4y+YulZrseFtXt7dSLmTu1u8Tpr1Virzx7h15c7r5Mfc7I39FE3espTLfGaNoqs6gnz2o0bkD1GQ+3jshZmO5zhasWv5NbdVj/8ALhXjJB0SRoE7SSxFwGMcgucvmJr8F+XI6bhodrsvkT7mHyMJEct7ARNJt6E2MdetKs7evc0MsEWv4tZNPLjM2FJDW62Igcjodtu9REwPyPGXRh6wxHr4uVMX2BynaQWsnJYmylHv2zUVq0SU2NfFXU1rhTLoZtR3n4A11b/sj7Q/+rf/AK9xZyU3Z7NYfG262cmlFuhdr1q8NqYT1qhsWK8CSmOTlRpoFaQx8zYADp2bPt7Saf8ApORPHZNo0RObjmlfYoXdJJZnLyNp5u7dWY9SfPjtUzfg69Fx8jLlaGh4yvXUL2mtafTjMVr9TiWPwT2Wxv8AFzGb3cIfyV/2cZlSC8rejWVB06ehsaAXb1eRA8z0+njSSTRD+CTwx6ewjzb92W9zO/5Nj/8Ai2vsFD/Na/zu3wILL/rTedUshj0rSnRUup10XZ0Wx6ng6nxRR6Ag7lIBBB1BB6gg+sEdQR0PuZzX/ufJ/wAyn47RN6u6UR9POn/6/UlWAKkEEEagg+YI9YPrHF/BdoXapjy17svPbsHlpXXvUEuJyU5f+1Z1gg3TEhI4LvemblxseFkjZZI5FV0dGDI6MNVZWGoZWB1Vh0I6jjs92O7NMMvZxUk6WO4MLAmzOVkr14MXCY9UkswLCol2sRHLb5DlZYplXs/gTsMmKxNGnO0Z1R7UUCd6kQkA7ZLPNdeg6N5cXcvmhL6LmvZzGWp4VMjUkuX20utCoMk0UDRqZ44QZ+SXaGOaVVhkiyFK3Wt0J4ufDcrzRzVZYfPmpOjGNk6HVg2g0OvlxQwvZ+ZbtRHxvZajPAS9eYpans5S8hUsrQxSWrO+xH729Sgk3wBu47S4bGxma8uNSzRgX4dibFTQX0rRD1z2lqmvACQpmlQO6rqwzHYy9agrZF8j6XxUc8gjfIJYrQVrcFfeRzJ6ppxSmBffTHOzqpWKUpxaxtPJ4+1kKKo92lXtwTWqiyMyI1mCN2khDMjqOYq9VI47L6f+KP8A7NlOOxZP/dI/nNjjtiR/gdL/AN2x/GZJ/wDFVr/2rEfU9lsiNdbWIv0SfV9Y24p0+n9cX4w2Rj+DkMTjro9eneqcM+n7kvt+jiOxp0uYqm+v4zwPPWPzkRxxD5tPdz3+TY//AItv7Bj/APNS/wA8t+4+LsNrbxGxI2J1M2PfpAfbursDXb1cvu51JZtOMyx82oTQ/wCsDkD/AInHaGzt8Lz0K6v6t0UdiWRPnC2IWPyMv1QvzyS4btBFByI8zSijl50aa8iPJVHMa3ooCTs0mrWVQmJbSx6BWo1+3lBcaSRyVsZ2CF016M+Nj31dxHUoZX2npzW03cQ5iezN2h7RRKeVkbUK1alN3VkkfH45ZJ+S7IxTm2bNyZRryZIt7D3O0uAz1UWqFut2n10OyevMmSQw2qsw8UFmBusbjoRujlWSGSSN7FXA9tqxwczlkgyAyNSfYSdsdqvS59K3JGOneNK4lOrCtB8HhskbT5vtHNAa75SaBa0FWGQgyw42mHmNdZdqrLLLYsWJFXarxRO8J4s5vs1km7MZazM1meua/e8PYsOWeSRYUlgsY+WaQ7mkryy14zuK0CW4Slf/AFTj6M6I0PpPtPkIY4vLwYyeerVfaPgxc6JT5b18+L1qrkb2XyuTrwVrt20sVeHlwu0pWpTi3clJJW3Nz7NuXwIOd8LdjcXWzEWGnxmWXJrLPRe9FYXudum9ciO1VeBvroTLMOePejCYffhNDg+zT3BkHxFJar3FgNVZ23vIzrAZrBjXV9ADM50GpPXQZvsxHdXHSZavFEl165tpA0NqC0pauJ6xkVzByzpMhUPvG7bsa3hbOWhy81zLTZNp4Kb04ohJVqVVgCyWbLSkd15hlJi+2csRe98yT6ilnFTc2Dy0PMfTpHXyammN59SyX/R8I185JUXzI4xcTOXsYae7iZ9TqdI5zbrfQtS3BGo8gqADpxjM1Euvo6y9S1p5ite28qQ/kR2Ylj/OtA+7n/8AJsd/xbf2DHf5pT+eW/cxsm7SC5KMdaB8jDcKxq3ycqxyZ9f8WVPhdvchpp9sv249f8nqe/yfpm7sv5pf16cVX27GvzT339p5rCKJj89eCH6NPdevle0uJq2I2KSVu9LNZidehSWvX5s0bg9Crop+TgR1+1mJDnoBZmakP9K4kCfxuI5oZElilRZIpY2DxyRuAySRupKujqQyspIYEEHT6nM5fM9n72PxZi7Qql6cRCvK1q+jV+U6yNzeanjXZuG3qdB9nzvZ6XZplsZapo0g1WKd4z3af19YLIimUjqrIGXqBxmOxuRLQDKiVVqygqYM9hmlWaIKescslUW4rC+bvTrqesQ4v4qz0ivVpIN+3dynI1inC9NWglCSqNRqU8x58WsdcTl2qU8leZeu3fG2m5CQC0bjxxtoN0bK2nX3O0H+S47/AItv7Bjf80J/PbnuCRTo0ZDqR5hkO4H9I4rWB5T14Zx800ayD+BuIKEBOyN46MbaaqJHf65m0/FjPQ/jCHUdCOK9SEaQ1oYq8QPmI4UEaa/LtUa+5/YJ2Ge2ulkY63bx5Md3KZJmCPRpz6o9erWk1imsK8PPlWU80UY+ZYjn7XZK1cuMoZ8fipFrUoSdd0clp4ntWiOnji7kobd0lGjcMMZYy+Hs6e9yraF+Dd/jq9xWkkX8mK1WP5fGax2RyMV/svLUjkxZhnblC8bTNIVoSnfRlaIu9rl7oJmkibnSyK2z7Hb7PT5q3LhVzefprjSIu7LWp17vd0CiMEcswRtv13kglmO5tfc09xyPMIxHzgHTjtHVzuYtZKvBj4rEEdjlbYZTdMZMeyNdgKNt2jw9B08I92h2+wgarXy1uvc71BoopdpaG2XVgvl36OBbg1BWxMl/m+fvmPz1IoO8x7LtZT1o5GIAW6bg+IctzuiJ+215IZ1LJKrH+yjGQ7rdSLbloY/hWKcQ8FwL8aWmg2S7fG9UKevduvFiTD3O6NaWNJzyK829Yi7Rj64ilC6F3+Dprr18hx9+v5BjP6nx9+v5Bjf6nx9+f5Djf6px9+f5Djf6nx9+f5Djf6px9+f5Djf6nx9+f5Djf6pxHZy1rvU8UPIjflQQ7Yg7ybdsEcSnxux1IJ66a6ae4fZxjT+G9F4+KNT/AHzucI1I9iaFj82nr4kyUo1Kbo4Cf74/26X5SFOwHy8b+sDTjMZKMAy08dbngB8msJC3IU6ddrTbAdOuh4y2ftqZrGNrRxVHk66Wck03eLOvrmEELxAnXw2pfWVILyMqIo1Z3IVVHtLHoB8/H3fT/wBag/p8HkTwzbfhcqVJNuvlrsJ01+Xi1mpkE9kstTGVDrpayEyuYUkIIKwRqjz2G1B5MTLHrM8at/ZN2m7UT47ETSzChHy5JlkEb8t/R2Ljnq06lZXVoO9OzTyvCd6T/beF7Udmu1Fi/i4ZoUvBY5K3KEsnLiXI4ySzbp36jOyRc8ESRyzArBBp3jihnVjWCxJvrZCsh1WvkKxC2ETUlhE+qWIA5LiCaLcSeph7J9lW2ZuxHHJevqizSUlsnSrTpxMrq16yDzGkdDyImhESvNPvreku03bHuWSsqszwzQ3M/aDONSly3Jk6ISZOgIia2g9T+HQ0hJkjk8HcZmjhNiexhr6xkd4r8ix75jLyq6MZIFjZtVYSWo0kQY7OY5i1PJVksRbxo8ZOqywSj1S15lkglAJXmRttLLoTkOy+NzD4Xs7j2uScuMyiBcfRtR1DeuV4ZoHyd2xNNCYass6wxF/ezCsc1gpkuxnbef0pANyxTJPiWkYDUhLda3ZjZZCAhq2q/IkUkTTFNVOIxuPza4fK1rNS3kJ1mtwRWWSjNDYj30fHt7zKJUUqY/DroCF4m7IwZdYc1HkcnTbMGe4FaelHZeebnp9ee/iF13Hxtv8AH0J49L5ntWMpSFC1WNKO3k5+ZLM0PLZ0uaRBY9hfcPGGCgdC3EOC7J2ThezZoRS2svHbWjzLEkkoliltQF8mOWqIBBSjUMrazMyuNDOe3SSZIrv5cmKtcgzEdUa+cu8+3d/bPcSxHXu2vB/U67VXJ7lZ7FjGwi1O1psffhjaWqatqXWZqF1IxFFATy1M9eSNIPfg+Ou4PtN6IrUaM8E9N7GQro0rS83vCdy1WRpU0ik5iqVEEW0uHITJ0sHmlw09Kok9iZrF2DnxtY5Qj3UvG2j+PR/D6/PjMNnu0PppcgtNa0S2L9hIGrmwZJD374DOJUUctfEAdx6L7mQ7PZIEQ3I/ebChTLTtxHfVuQ7h8OGUAkeUsRkgf3uVwb/ZrtNHJHi57KVstHtkKRHqtPP0Omsldo23SbFbvNMldDZrRBI54JI569iJJYZYmWWGaGVQ6SRupKSRyIwZWBKsp1HTifPdnK5kxzl5r2MgVmkx7HxPPUjGu+iTuZ4U60vwamr9zfYQOKtVfhWZ4YB88rhNfo14jiUbY41CL7I4l0Bb5zoPnO1dfXwkUY0RBtA//vWfMn1nr7mZgUalqMzae3lDmkfoQ8Z2v5M/cZwPWVXvCN9AJX/S4yfZ+xPLWhycCwvPCFaSPZLHMpCt4WG6IBlPRkLLqNeJJB2lvnZG76ejqnXapOn23jtEBqFfD1SV8lLLd8JI8iVDMAfMan2njsnTBIh/Xi0w9XMTuEUbfuVkk/0uMRiqH6meRenj8bSqVpUgy2k8UFeNFsapjCrGxpz2cFt7OX3Nu3HKYKf9TbKwR5Oq9Zplq5eRod2hWQI2NAYowDAajqPPjPw5Shex9ebKQT1Ir1eWqzzd0WG3KkM6pJtKRU0MmzYxj2qxKMFsWb6rLyO1Od5YZen6xR3q2NOh+PCKNWQHzEse7z9yadtOZjsri7MR0Gus9j0c6g+fwLpc6efLGvlxHDJrpVy2Rhi19UbGKxoPk3zP+ni12t7JQS38XYktS7oYJLSpUuS8+1i8tUhPP5Ebqjx2U0iPKr2BJDYjMccVTP1XwNqTYqWw/esTKx0HinCrNT1Plz43rqvV7Y8uAQQQRqCOoIPkQfWDxcl/+JO0p/TBkvcjbL2JGszqXrY2nGJ79hAdu9Yi8ccUW4FedZlhiZlZFdnBXgyYn9T7MZCtuZVnjszyA7Tpo3dMTaiVx5OizybT03HjDZu1i58NPb7RYJpMdY5hmr8oU4PGZa9Z/fFjEo1hTo48x4jL+1v/ALp47TH24mH+f/ULZqcur2mxsbejbbeFLcPVmxl1tCeRIxL15fhVLB3g8mWzHK/Y/tjDbixUFgwfXCFrnZ2zu98QqNxmxzFt8kcbS8n7oo8yORklhtVZorFedFlgngdZIpY26q8ciEqyn1FTxJkMC0WIyTatLWKkYy45+NsjBNKXz1eBHif40AfWXg18xj7FM7yqSsu6tPp8avZTWGZWHUbX3afDVWBUev6lY8VQlliLbZLkmsNGAfGaW042eH+9x8ydvKOJ26cY2i1s3LFnGrctSBdkKTNZsQ8quD4zGiwr45PE7bm2xghBwbzpuhxqbl/FNuYFYdfby05k3yOsRPTodB8I/Cb2/wDQer3Sp6hgQR7Qeh4W1GhaEbgADotqjIRuj3fjpovRvgzxK3VdrMr07cTsw6wMypZjPrWSAneCPaNUb4SMykMZ5L92rTj5MniszxQg+AjQcxhqfkGp4zh088RAP5YOMPlkQumMs2K1nQE8uLICHZI+nknOrJFuPTfNGvm3GLg58ZyWLpV8ffr7hzg1ONa6WTH0bl2o0SYOBsDu8QOsZ4aWaRIokGrySuqIo9rOxCgfOeBaoWoLlZmdFnrSpNEzRuUkAkQlSUdSrdehHD5p4ZDTlyjZjp8KWpmFkGReLyDNFPYu8tNQC8SxllB3cRW6ViK1WmUPFPA4kjdT7CPX7QeqnoQDxW7M1Z0ntyXI7mQSJw/doaobkwz7ddss07rKsZ8aivuZQGQnGVbacizKs2RtRN0aF7bGVY5B8WSOvyllX4kiuvXTXjvWLvVr8H49aVZNp/FkUeKNvyZArfJxTykNarVztjIbGMCpFLerPFPJZlsRIBz2jlEP1yw3gybGc8wDjs93pnd1rSxxGQsW7rFanjqDVuuxKyxJD6hCsYXw6cWLFsiBW7RZVd0nhAN+OyK2pPkJe8RbT6xIp9fAQuodgWVNw3MF03EL5kLqNSPLUa+fDJ2i2tjPSlKFlsttg5CY6FqcMhOgFeW0Y+YpIjfmuH8LtrqTBUqVYh57IK9eCJdAPixxRRoNB5KqjToOKOVx786pL2ixCxTbdBL3XutZpE184neJmib48e1tBrw49qMP0g8ZanPpFLdxsscO7w75qlyN3gGvnIY2kkC/iQSn1cNGHUyKFZkDDeqtrtLL5gNtbaT56HTy+o7x4aGfgh2U8oiD3wLqY6uRUDdYqbidp+3VtzNA2jSRSnEZGq02OaQynG2XJo2kLANaxN5VfkNIF6sgdA/3XTaVdoAx9sQ3tu58Xc2QXlHrKR7illF+NJWeUJ05mzUavBZhhsQyDbJDPGk0TqfNXjkDI4PrDAjgvDUmxch1OuNnMcfX2V5xPAg9ixJGo8gOCcf2iZV9UV7HCRvps17cQ0+Tuh+fj79YrT28q4T+jlj/AG8a5HtDNMP73Rx6VtD+32LNveP/AKePhXOO9JSqdQ+Uk70mo9tbSOo3zSQPwEjRI0UaKiKqIoHkFVdFUD1ADQcYzQg7cMgOhB0Pfrp0PsOnEFOpE01mzMkMMS+bO50HU9Ao82Y6KigsxABPFbHR7WlUc23Mv4e3IBzX8gdo0EcWo15UcYPUfUmvchWWPzHqeNvx43HiRvlB6jo2qkjgvj8nyv8AFW4N/wCieFkIHyGBj+VwGyOcjWIHqlSq0srj5JrEqLEflME3zcTejI5WsWVRbFuzJzJ5UjJKJ4QkUaAknSONdx+GW2rpNUtwpYrWY3hnhkG5JI3G1kYewj/p14Njs/mJKHUkV7UbS7NT+BuwSRTRqvqEkU7np76NOoOa7TvLED1jhSxaldfYs92cLD/q8wPycQYmhzTXgMjBpmDyu80jSyO5VUXUsx6KqgDQAcJXycTCSAs1W5BtW1WL6b+W7KwMcm1eZE6tG5VG270RldaHaGHu7E/bILNaTafiukEs0chA821QOevLTyEN/Iztmb0LiWPfEK9KOVTuSQV98zyvGfJppmQt4+Sp02lT1DAgj5D0PBsdnM9NQ1PSGwJA8euv2u9Ukik2r5BHgdj65uBa7SZmXJ6EE14RKObofKe9YkkndG8ikccLj1TeyOGFFiihRIoo0UKkccahURFHRVRQFVR0AGg4OUq2/R2TZI0nZoefWtiJdkZlUPHJHMqBI+erOOVGqmFtAR6YvZYXbCVpq0NeGKRY0E2zc7zyyF38K6LEIYwp8RZugAuidsdlFjWLvSRCeKdE+ALVffEZCg1VJI5onA0DGRUVBHXzPaieXGRfBp1mty6geSxJbl7tU/OWvP08IUa7hiszjbopU8Y1KT0b3LnSTy02LGRrxuJo1htrSlqshB3BTtZBFxPk8NkFx0tmZp56k8JevzpDukkrzRMskAZtWMRjmXcx5bRIAnF6afI+kLeQECybYTDDEkHMIUF5ZZJmLSHWRuUNNFEQ6s31D0ctRr36r+cU6btp0I5kT9JIZVBOyaFklTzRweO+dlL3N2EOlC9IIrSEeurfULGzDptFgQEAamyzaArUzMVixBuCRx5yCR/gjqtXJKVkl1X4pnsxqBrGi+LcFyOLu03OnvlV4rkOvrJDGtMg+RUm+fjw5LZ8kta1F/vQafw8dMpWP0t/Q46XOZ+1wTt/Dywv8PGlarK/5U5SMf6Ccwkful40iVxH5aQLsj+XdKT1+Yvp+Txi4WHMmmxkW2OIF2LyXrSJGug1d2bRQFB1Y7V3celspGpzVqPRIz4vRtd/wQP+FSjTvLj4A+t0YrzWl/uE0FiGKeGTo8U0ayxOAddGjcFW6gHqPMa8b2xEMD+2m8tT+JXdI/4nGsFzJw/IZK0qfxqof+Px987JH7TDr+ny/i8DfPdm+RpIUU/vcCt/H497pxk+2XdMf/NLDgBQAB0AHQAewDiHO2Iudeq1FqVOZoY6wEs0rTRpp9vbnFeYxOxAOWEJct+zf//EACkQAQEAAgIBAwQCAgMBAAAAAAERACExQVEQYXEggZGhQPCx0TBQwfH/2gAIAQEAAT8h+l+xMzjCG1YAqgYp0d4QY1QIRgrPj7PAgBb6Z+G+ah1700sPBKvgEbjFrGYhoEi08FN5wGDdHyA/3uU4pIDN+GLzp5VREpsdicJ/0W+5zbQjFDbYD1NQeFHUjjko4o4ZeMkqjEQoAKsd0t6m3ongBTQDWDhLgAPgIeiJ15QvkCZt6BQ69D7SMEKYS1UgrtMn5MKZbxI70ZnKAvFHCXVAzFXMDoBuT/P3Soj0CdnDpNx0Pp5KtvzN1iXwdyknEh1aKyriqGi0ToOaJmEpodPX5NA+ETtcb1dngQK0sEc5XeGKydyIWnSAvbkg3Szg7CpLJ1NeLQ30nvNC7/GHI8u+PrzvAGgC42oFIwlBiLmJYCnLYBUjpjeo/ncVGodKglULz4qga+cEslPGMdTkq2klVRQMSmxosvCIm6nf35gNmMCACAQAgfYn2/xnsf38Z7OHs/WOnB+M9nFRkJpQUCKAARRpEzU0X5ZR19iBqKAb/n3+h2IgwSAhhtqXxobB2+WAbxvyigob/mChI/F5Sg0ARbOp3ELXnQh42DKHYeoh3grtRCTyHEy/nQilgBJ5hrqE8GexnHr0PZx9uc2sndZzaylwaGyiFQLN0ieEYb4tOVgGnYFwhBUV8xIxGnLjkaSepiHgttWh/l6BY8vcm2zLXlijPdKRFS6oDkstrjzZhsV8Ab9la3C8WsCKtkN80CKTmtzsT5wd6ejSoWYV9MZTrTFZ0YOdDM190fxrDlvicWrDhlFRYIyiGu5OpA1zDKDaEefyvQPqAd6aracMqoHHqNhhKyanm4u58PYX0r0ndiLKKmpnlOV1JQqVcHHxgnpYfQ+jnb1Buh6uuJzDM9AxSkUsBJ3Bg8fyURWwNM8fMlO8dOQyFv3JwhfZNBiLe9GxkeSvZq7zp9s/v9Yv7/8AbWDcPocXFxxejhEDkLBZWkgKLjEZknX+XMFTEPqNkdmvFMYBYeaRXoiBCbLAiDRIww/gpNnktBoNhqx/uiUqYJCDHBz8u363QTfY0LxoJVZSjtQO7VXhcy/mfRp2NpmOwjQseSioAx3Ha/xh4bXVxnrPYcB/WAEOs5T6jBY2hj3V/jSTHR+LiwJ0bYkCo8bzQMd8nAAGufYMxGE2UXbo68JLKcB+mUZp85Ez9D4fOGhLhAzjwe+MgrbnsF/Hk/PEzgfa/Abfwf4y0EztTeLH9p1gVFTcKGgVDY86rXufGf8A0HLz7svzPvngX5cn2Pyf6mdPChbCEDkKNdQoy0B1QXqnvYovQDMAol358iD3Mv2tJ8kfff8Ab6fy8BJLAoe+adloEZ90sCjYHNZSOBz91w5JnK/KtdnT5ZV757wVwaZlofeLYicFUL74uGifSG2WIJ6Jp1E2KaWmBYP1t0dFQCSmfSkI6LX6akdVQM52rK/3vbCFsEE3ksNx1S5BQ06ciDw9XwubFDb3Kf8Ax9NA1oOpMPn/ANyxOLHwmfrK0W1A4AQqIC7wEVVdxts6Cj1UZw5XMRwfR8vQuLkPn8t9MGXdEcIxoJZiwsJg9B0QEEESmTw58Yh6iLfCWRJu/wC9P0fSOgp4dEKAUQiacsqB50Owb5IVAKYmIn8VMqhEcBL4OUpB8Z4Ear0bAiYBylIUcegRiz5kvgRx5bRvwjCtKJAQqCztzslOnUpW8padPWlkf2I80OiaIjFo6emLiwlf/ajbmjmCYuuKz92JuC2wfmBP8WL7WH2+kivwlJs+Stmgl3FFGSpB6zlSnzhdTcz5m9k96B8Zw+hfFB9S+hwuTfpmw+YOg2uC2IIFcrhtoA90A+7E7uMFkSbG58Jeld/USnjwJu67ctPZxNzV0GQIF6MDImuDIG1edpKMQG+F8zf427FWP1VYMVpQzviM1LZ+kFtVwfQ2T1a8NbO99Dab6hIsi8v1nE+hx7hWuTKawDBigupR90wHsPnu3THPxi3kJHAK/BYfKQ3yE8BxmZqpxE8LI+kVZBE1Gh5isBpmTS1tzBN7OrJUACstQNbU9n/dCN4f8+lXf6QPQvocX0QfuZC5B8fg9yIcmqis6ua+IcHftM02FXRsk+UJFvT1V4GpgxChDLzhij0SeDvXVw6B2etmAGKZD9ItN9gfqSVMK2z/AJ5GjSu9hINdr4zJ4/fGoKuICcKvELEnaU8JZo3xOcLKoMFEO1QaZab9IuPovvl9/wB58vQvrKClTroIE9ICPnD3j31bfuOV/k2z0cqOcay7FxNgoGIARQhWs9HnYwhCsM9GGyrtNi+opuGAE5j0z9jJ5n6tZqEbc0QxTgXJkemfG3RgjsaeT1QcoXyz6BHhH4b6UtlWwvqJC3anq2bFeCl/HpqXdZdlp3vrBVq0qyZRJhnLQ9IPZDdKEVsVN6ZQaCwSHcWY5ipResMw7qpxhMCgY4sbCfenQXnUvkpBXKw+SxHlZ/fZPfZXysj1LOvwrUiH4tP0AZaZ0fvggNNmQ/FCOhjWMVvdWqDTugipeWei8A8+o6CH6ESusq4Mie3cpVDUyKHVES8qgu1Aemm5JiubPZYzSxnGNBcYCAI7522DpqKq61vZF0eJ68SAHAI5jIcVrR33whiFW/KDgq7hGgCOMqnn2gyENnLWJDB3wHNWS5AgF+D1quzDIJKi4i1pZQfwBDGGePJrUJTJhEZBhMSoxpsXSIzRycF7G4lc8FDqnDwiKbQDB6u6vxuQJCoSYMjMeUvYu6hUU2rZFJiYDtbTjIWi2xcCya7NeSneRD1GQxAA+wFw8QuoxwaIgU3Rd6EuWhvLIGsugMBMkyPkK7aNlMjidwrPIJwRUVmm68m3t6YjIa3GkRE8jT/We56HuYem493D/rnuy4dOwZZ9nNr7Y78AZoUCSWghwAME1L9kcr5S9oVt9Pd2GABjtTAbeCrmkfRKpg5avwm8l1I0Ci76q4obA8mIcESnaMmRka1hAoIBCBiFLKg7KThxZ96XHenC5HBk/cqzrBFJ1YTu+S1mmOuX75lNBRjTxa8QySBmuHYDqehPW4RibECJ00DwbJf+XBo/XawZyM7y1j4AYMy8JRd7Ca9W02wCZywAoGgbE0mzFiO6pr7D38+iJ2hYVJCWXBkKfbhAVX4wDdSqBWYUAqb1RNq9AcyBwP8APx7fRxySq4fsygpHJUJF5ueKrBAwY8b1X4//AMoe+nGTu4wDSHaZbtmDgUhc133nBTDT+w57r94L3/LnvYr3fu5D3kgjpDXtrd+HvVUnEBO6HdhBfu6P7/vGCnX+xP4dTcWGfR2y2ug78T5eX1M0UbYCD7IxxEfXC/1LOgjIxAP6PnztuJAhh0QbBGoi2mUCooAucdOinC4sdAmugPXYLERH6DJNZNmhvCTFH6KP5BF5AwhEJC23gwqh4xEaKa3w0wWCEAl/gwCK0BZNYITAebCZMzQ2yoaxUovuWk3dp2iq7BsLsPflO8bTsfQRiPW+CDlzmK7YxIOqDB0YqTG5ynZhDQxZy9BLLN4yJvCK75GoqWY6gGnhRaCqKOxOoa4IGNVuWN2mQjKCBMYvkL5EYsgdzwbJH8K6DVWBMyqTG8AAdzU9XsvpZrawk2+ctoelV3Pb8N7rACwpf2bli22eGglC2QNEoqGkxTOpQVdB/SvRMXLrnZ7New3nzKRKtwh9o/E3inOXEAdytmyDscfM234Zp0CIY7AhBNlwDhj40FAoBAQJl6wf1EjsDGMR4cj1UScBhtFwWMoMgToOq9XRI0+lcy2tgQjANRFiYpzrjkXwsHCbl87D3+NrxjaNNQ7OCGDgGbY74OAmYiOvq+Vp0nKAOcAnenQAE62tLYBa9yONlYzky6cc4RTbjAQdosBj/AEFidx16IMdrx43M1EkAmEC5CBkTuwNwS+J5wLvurCh9xTBCaIvJQpKGVVuFd3E4Ewb9ZvLZgKtRmjsKwAwAZwJVTP7emiPZ51EIy+yZRJTMt2nSUbRJrD5SiuBEFoEOVveMhCD1URHTHGwj0EcSWOSm6ZuLG5raIaRKhOIKY+mUvHGpKDZgNdCceqLrrUSPp2AzCiesfqSmBY623gtYB4GeboEJpThQkmbcXyl+L+cIp3sr+Nv1lWy8WPj9oTyhvEXphavInzi+2KiSqXfpeRwlPKGuE4BEYBbDnD0Ip6zJiNVxB8Xqx/0bKUwOgEXggcA5BiJUVSde7f7owzy+hZ4IgHu3yucWXqXP3OFsmc+wCAn5e+QUF3/AKTfYMOI4GAaAQAOA0ZYbi8ugX17L+dP/wD/2gAMAwEAAgADAAAAEAAABBJJAAAAAAAAAAAAAAAABIIAAJAAAAAAAAAAAAAAABIETXPJAAAAAAAAAAAAAABJM9mwFhAAAAAAAAAAAAABIjEqFIR5AAAAAAAAAAAAAAGhxLZ7lAAAAAAAAAAAAAJNVhAABAAIAAAAAAAAAAABJmKAAJBAJAAAJBJBJAJAAJL6hIAAGAIABIJAJBIBIAAJitJIAPJAAABIBBJAAJAABM/QBBI1AIAABIBAIBJAAAAFoAIIM4JAEcAAAAAAAAAJLm5AIA2SICyBIBQARQOJgBPDrADe0wHbo1SfWidaeuAJytAmnOUA5l53eHylxc1gBABe89aCAIxLEflDzW5DewBJNlP1PgAKWsHQ4BqCWQ8AAIIIIOAAAAAAAAAAAAAAAAAABIBgAAAAAAAAAAAAAB//xAArEQEBAAEDAwIGAgMBAQAAAAABESEAMUFRYfBxkRAgQIGhsdHhMFDB8WD/2gAIAQMBAT8Q/wDnFy0BLSNmBJGQJosEFjHgczeYkSWatOznsQWJMpaqtqX9fePthf28aDOCUdCKIyuLAsZnRzCUTMUKEyRriDhMkbErKqjKxQLhn/R1tQU5YwywTBAjrIMcHcQfEUMWUaGu2A3eLnO7tvb+9e5jEMT2nbKfeaXk77Z42YddyzfQNjLH3M/uzatzpC4PT+4PsZ11ofN7nbJ3TnRBCi6tEhAyUCCwgj2Oj9IqWkSjwqKA5KjWeQcjRIBACH17SjGNjAaXwtz2hUiSBS7YhrAwFwBxnbNCBnvvTBjJqgQ5HGQy9ec92986EnqdFu8/XR900ccHW5sznhx3g8UmjYRneHXidvMXsvJnH6I7dcb3XHJ2f2effUxTbNxt37S9vtzvbGfznJ27eu0mkpGoVYBqRgnJVGmkamqcrAlHICUAIfXJcqqobgIqmzXZNCu+FmN85kJ23w9ugBNAJuFkMpOvHO0+z5xn27aE2vl5376CJTN8XXsc8N3fS3H6eDzvpVxr559xs863Ly/f3efsHtjaX1xvT1zy6t4KJvemN073H3tUyYBW5GFqYbbfWyRc0RQj8i4c5ENUkGutKjFQqpTKraGHapnnr6dJ+rozqZP9QubCyCgo5TgvOF1sSdMkz0/P4PTWZ9z4O+Og+mpiecv+h0/1A32Fi2fYA2MevXVIuAzeAHl7Bu93WTJOMyYoKrwyYzo4cNXQhDCoNXImfnYOzVBfMxDIoLErQhwHxYa+OWIin1xbNbpTOGFABlIEddSFFhcANjqqc420R6P/AHfs9b6ot15zx/f2/wADh8rbG0/fG+5w6X7apd+ZBi45cWBknPDxcUggoEUR+u4UjEMrY2n3giRyNLqWOPPG/iad4U3vSwTbHD2nL85E4vNiA271p7d9Od86ZdnTFpmy37Beo/rgIQUYCxzBOGYuYO+OQ646z+ft8HQ5Pa/v2+/+D3n6fUNpffz/AM3zJDhqQbu0kcmxt+ZMkQlV0QkbfYl0vIYGK0Nq5QKLcXQX2YnGVTF1AiI/TIOL03WSkdRESLdTIltt9qCAuE/gahjfLtO0nX09udeN3/8Ab8f4IHt3c1x9vGbK7fe7228/3W6Qk5qIIncQETOgCaudUz7g+Q82X88j5bJZAx1oxXTUqusBMwBVIo1JSEEmhC8FdISySBGo6YRKaH4ahlYdXQjkadT4qG6Hqz5BHZHMw3JuY5+GEdgyHBQ+AiSA/CgxSuxSv2+HQEEuCTHOZjRUElQSKhkC3FkH5XjgT2cMiRuhygaceds/fjP9nsWneqhs0MMoCL5no/w7ryn9eebo527yf+O+3PTGtjJ18H6314h538cb0zdUfGdvzNKyFO9fXw99AuLFDj5KRNrAAQevB5t99PAGBztMZu9JkfvtTSOChG6WPcUN6fEuR3cCpo5AMiUqTWRSrU6o75XXfiABnKIdugAcqh8G1wZNZhZsFjLLHpoP6MFKo0BlQaOmSygBC3WGIdcNfLwVXIlNMS2Q13H48GIkMBAiSlGYspCAh01EZBqNaU5CYay+XOUXGhVtCkkEzS6Uss4so1MD2IZCODy2RaC2BhvUvTVAB0UgLwuOAj++KaIoQUzeDEV4IzOrUA0MSl073/rDmHpRFELoQ60zG18p5MM9pVLs392ISswSqPAMOY2mpzDSQk0CmOkBAxLgLxWUNSWKJCwo0pAMHcNKLDiSSABD302n5EAgAQAgSIjREURERjjTJRCdxwkzl1W1ghERKTPTkomT9lHXn89Omguj69evn7zovc9c+0vf23uu5+H+Ndw99dz96T068+2136cfnS3b00xDlMHr69/zphcBCqbYS7h6FDSZmAtoZdoPiEUQ6EYI1UAjVkzrAmCXIhVyqC5jLlNEhbBJJCB3a6DQLMnximm9BSXKHV01ITpkxBQoS4Inu0TkLwCDZC971nTRJ2S6AiKKNJ6MwLaHJ5OMMJqwQmGmmQkG0tCwoIDArIrtaw4APhHk+A5/GINIOVthGVpitdO+Dt3KzqPpgxaBxJAdLmeq1nZCX3b5LAEEzEABQKKERFEaY1R14fV1Gwczr6fB/wAYiUcJ8tnY1lMci8Rkud4GzWl71mzEE/OeAITRmHXTJkpNd6B5eBvPT51MjdFVYMKoaCQnZUeMlodAQChtLuB6s3cemPyTVYOXGLw8evcbwcavlpx/b/GdtTRu3FZ7ebGm9kOu/nT+9NXBJcBFj34UsTZZYjF6mXehHcGpCUwJuW12ykznsdjJM2qJCAcIoFC2xh+JJCSCiCIjuIomi8YDKccWtQO60tRMsec9UZSCGjSM4VOUQrtYKJgF06RIJ9yh0e8dMWZGVLUACoUqRQ4UgPyTbbBCxD3rAubqiOqDSGq3rgoV0iHGnb3cpuKgixC+IE0QiEIiMSyK4Qga7W6wxxt7EwXRc5TIeRvTOtIlOMKz2ddg5D8jQt2AUIwazAiCGlw7ItyrjduVNZMhUJ8YGXqAmwVBIuIFQy0QQIqJTSxXmVb+GgRySIQLKpLBWWAMSCDWfwVChGFRgUITpAsoh3UH70ERUBGjUrGCo2I0MZITVZbuIQKRY/O2DDfeFDXRDS3/AFVBVZQExYIDfT6NFtNyJyEAQEVmhjA6ji72FnHu50kAlylnAKJN1Ddg30jhpBDsjDcgQxNAbUVKgKMYAAMBo2IKE33pwZw/njWI9gaQBXFCxCpCVrxNAEagkAgRij8qc87iDCEYxUyCqmGZM3ZvAM7WaVJdCBEUkXIPDs4nlo/wvLATNjcBWqBF9dsYYUJwm4iCXFFDIqphvxCMoMve7oaxTFAg48EmqR2ErZuqgeAA0YWj4iBDcKIeNDfmylR3CM2qXM9DwOjJBgjYaaU0M2MnZBB9RTThsyO1SbyJkZlVtaQAIcFg4DsDRl0vkTQJOAAAGqdAiFhYShqqAsxKBTZmgXm0AC5klNFYsqzA1KlUCmGwhDAYeCGlkABpNvFUpEh/Cm23PEoL6w80hkmQ61RyJjAAZ/zBOvlldSPGQArHAUYQQKo0EZKC/wD1X08qZDzQCoQAfXE//8QAKxEBAQABAwMDAwQDAQEAAAAAAREhADFBUWFxgZHwEKGxIEDB0TBQ4fFg/9oACAECAQE/EP8A5zCDQyKpcbJHpSN0GSeXYLZSGN6ts4bDQ3bVVvE2AGYBTXBuXefzfOkQisdE3hcthLub6BeShzmA1eawzQ0bQTLisEYSoFChkh/o1ynDGCgirxEuQ0ZYIss2Rk3iq4vF0ouUzvnoZ3UNvxsa6DI4dz05X/smnPfL1Z4mevELjoa3u3GcS74yPTrk41sNTvZ9r7jttnS3C4w4vYfO+/bbRg0gIBEqkQRFREcjBlY7YsAR3ZyYOcRMdFvIT3EoEREX9+U9/MLVUYaWQQjoTKWpAFXRZISUZkQgUxN+707qs9jRO7v0wYE4z654d1dEW57cDt7/APc6QyQWzl9Ptkxgm2kdXplm2/tj5uCsedieNsD5DTdcePydMSm0Zc6sBeme/wDTx7eIx5smYXjfNZJzc6ekSSAFrBVjfZqvXN92AMVRRjsFCIoX98AiOABlEZREGQ4k1KC75x42883s9Lpe2aLi0c1oN2mG3UT1fHxjr+fGtyPxg8Y6/wBcaUb/ADDy/OMa+JfxoD+INAZy/Y6ba599vdzt042NQpj4wp6qfeccOj5tI+Dbg+c50AlAsl4RN/DCuJ/vQUKMKJDmQgKJAjHWIQQQAAwAiAgQMGpezPTf1uPTW4d3e6SPRi+r/qADFymTMHTzAHXS3xlO6T176x46gHSEX8ret08PQD8HoX0x/qFQAlSVplvUPfDMlsm4h1VAAObt541BXyJAMzJRjktl0g1WO/QOoKw2M/4CpEnwytDNkYoI5GsYVZgkDZVwiH74nhH8kIsUIVxYMo6REjbdU3QlXh3WaFE+fPuaEL/ApWF7OoccrBy6FqhHGS1EzhlIiAKBEBQiCJ++DPL8lwh3i7CYVuDm5z7ZffVs8/n7+077rgl+YOXGTx8ev+A34vw2N/TQAff549ffOiUWbEfCwNPCoyn98VyHFmpzjHxlRuIkw+H1Px0658EKzD9rx4/81ADhKZu56/4M8efX+BqO+/Tjvx/VN90L7riChGI0rkc73UNz+k86w05GLiOIZulyYAsDLcFCsU06CP4ghByMARBE/bW7DBGdMa5RiKJht+uwIMQpmjeOjqG5h6m/X2/p5NCed+Hjrz6/4CsB6nB8vOh3c/14T5jRJFwMLONkQNwjpQkHOig93+jp2KwosLK489KpvsTynMFA3RjTQfM++6cY5FLkzQJfxx2Y0ogA1/8AUi7F/RE3J9GnnNXhhGzeGJH0jLGdePf6EGUEdRAntoVjnQCkAAnNaq39B8ri7LVLQKhFshxvo/zPx6nU0sQYqa5lTjYYBXTwjvj2Ts26ZvGkt/Q/6vX+9V4e1/n+e23wPjx542mPoQ6nxP6fzvgHd76fbz/nrdO0bZTMmuyATAqRN87Y/jD/AO9ucgY07w8O/q+bTTiVGNkOTyN+rxJKTIgCbkEoXGgUOdAFY3F9BXoQ9EgWU7AFV4AV+irlCuDpd0lLLKabkQAGdOiMpEDQcgyF7xKUP8oxQvncrbAmKq9LWumoQpgoMIjiwFlim3o2fLApxrsxIZVS0iiQLcoDlhPEjcixOtQMw5dCG8KegRoIYHEuvdihSJOgqD7tQYBAFEIiAaqk0MkJ0gWAhKiyrqzhsmhioQNA8p8ebrhDRZAGl4iPl4qrIU0zTKmILKGxH1DiNDsdcDJdp1olyCyQPMjqRQlFnQq7KBOUiipRQy7Fe4qKAIO562CVT9RUKUIiKImREiI5EaOTR2xgBhTAKhPZeqDJY8mR+YvDbNdHE4539Km3Hd0ovIYvz/zSOYfHx65/Gk3dnptn2fN+91PV+39aDzX540DgribYnpXzdV0/55lnrrKSAHOWbJ25UyTwLHq+7bDz16HQjg19wJxU71b9VDoHUIPYEK7BlxqdFzkoT2BSM5R9IMpuwhyZTGU4RNKkaQpCqSUGhtdTOi8AEAFEUUFRMNMDYKFBGy79HsLJQQ5hSAoxBBAAnQYhKRJpAxLh20BfSaLJCIUYZpHUSIFEFFdRRCpX6JQzSiqIwkRMGHLS7BSMZTcqmVzA8sYpgz2YKdL1nUalqEbif0WMhnSKAoQEQYiORHCOzjQoGwJi4dzjZ8+X6FqHRjgBugAEq0XjcpKBHIxuDDI6KwU5XcUrW5haHWoDDUwdsX5+/wCsYmFARIIaSZAgCMknMmZ374Zoqao4nouTflIJN2+s0tmZkIbfec4w+mtjbvs/Hz212T30G2AdsR32td//ADY1iwZVcwzNHHMlc1IMqwDllQNdwDLHnibzfr7dXbUhoEbgJsmQZAjCn1RJAIbiUTuJdTrtwgB6bBQS0A0ebg4ciQSILVDhf9+UQquMAqwBldd2n42vBhxtfOidhTIFQqkWWJLA4sGd1u5JZFSaG8EBsHT2C76Pn8w4zKhCgmHRLd8yV4WeJV7q9rJ6SIMZTBQiKHSI3yV05QmEEtPQtmVSmHYOVCUFGmREUd9LO3V8LWGTMJAc6qECXQhHZwN0AMP71pq8CJYBcCgjNxxY0IR1DTdkDgAtpLHQ4leAJAKyFWDaQgswECri5FcuWrVTu0Vl8xbyxZQmmLbJfAF/GmsUGuPQhQKEYTBBhqILpkgwCuRKfrPI6IsgKoRBxvoRaghAAFhg1MtTDR4IOYWJF45tXD205w8QViYpS5c9neAqMuMWm84bsSj1xoFxEAtB3QGOWb3hKgKeGVVZ3QvLpS8PuRcW7cz1019sFKXAKiBFI0BM6uq2iIqRqIQxJ+jH0iJRqIt6DGIAEiZvmXGxFcqgV7JLikW2YBEbQSdS6WjB0OIUIjQEOqQnIgyJZAD0dkRTTwQMcOFymlHvUwWhzEdaOayqdHMoywEiQOgwleqF1JGXuSgIst7WEIIMFkiBkEy83LoXfQiRSsJSCn6EZQSdEEfRDVDFihgOU4HlgrppQhAAm0NK+lTSSrhN9iTkFRVVuoouy5eG5jkEagwJX0RvYQbzCtCqUkcAGAUAdHScCSbkIFQq8VNUmSdxOJw0Ez+AlH0FNGVMSLpAEqKI62MkDCEgX1RH+Zfe0MVmAzACqBTIAUluYFmJobUD/wBVs+ey5dRZEkELH74f/8QAKhABAQACAQIFBAIDAQEAAAAAAREAITFBUWFxgZHwECCh0bHBQOHxUDD/2gAIAQEAAT8Q+196klwxVzqwRp6kp0RdiFBkNkijcKABL5AU3YwgsRNQSgSdK0EjgTLSiYFqoQm1QhmuYpr4Ds6ArFqTytOe5qKl1RAwEsZs+q/S5s04AgAQFBRE0ibE0mz/AMJpjXcKDykE+Fy4gNCFkmD6ZH5LGa4GIMvH/KdCRJaaRAAMYPA/EnIwYeh9BwYgoJEUBFGmxmWoqR7C+TRNhkWnNgpIDLeH8sWbRYsBbpscEdi1iSn5RBnq/wDAJMSGlK20mmY37r1WAGuDrCZnyqYnf7QnqhmwBrKhDHoMUJzDZIfRC3QN87spABKpB9GVKh06gIRqZsKPWdI8Wc+Hg6y+GDZnO1cgAklorqhToQcSkaBscEQGhSLG4FRgLQhJZiUauprLQFBwEFcKcQD1LLS78xEroB2pv+dRpIPFjOVMZB4yz510OK6F4mRvlhaRVgJWuQMTeENIAvIAIRJiEJIGAOAAAHADnu3w6cdrZJz0Hsq8aRhqdbv14N+rrib3/ta/x2u7J26qUdDT+wfm4INPXYb53ePGduWawyVKjz6IjlIDKQJHQWQadGY3uZXVSAkOjIIX+V007igFCJBPHucv1NMaxf5gFVrYddWq+jQgr9ECpkfTpLSwZJd5ShCJFS0qKlNH9NNga1ziZgTsaoGuUJJwQ6anfcysewC7XjaduxqnOsHQ23aeA7YBdnaAF5w2U7ca/E/fO3kwPw9vU1fFVmPLw7zuGuOYzk9smdCPOuu9bf8Ahe2bA4LTnk5IcvXp1l3gzg7R551s0dd8nMHRZ0IKEXg5gMsHUbQhEYlQhx9MeWyuVAGdmCvYlUq2Y1pTrl/ln1Mn4ngAhwZXp2/BQygothsa7aDjg7SUAhCihlPOPLtPDy7Q3phFIkCIACylXElihsHBvHPo9MNJI3Zfgj53bnHv4v7H488k74TfvZC4XuZRmiROX2148e2W7ReG5/h4f3vAaA9BJ2e6apwzfbLoAiMXTzt5878tM0yvgIIeaznhB1L7HDWIlD7NdRg6II4kbM5X+VMUjvkvK5JzjMmi2F+l6GgVwcIjzKsWa8Ky1bK41sS5nobQqIiN3ThLx1DwdA1m/wA4SDr+P9nhoPoqD7+f2OHi6/f04nn+8Xs1/X+86PX+sEJ2ffn/AL5ZJw85wz2ZB8EY3ENTh6psSoN/yWNgS2IgWjr8qWkANBoqoq2BovBgFoMOLI8sRYRBmGeInoRJycQLbO2OOnonnUO+en47YxBu306++t8XEc9QZzfL5/f2c/T95HRt6454r34+fvOJ5/PnjgzW04enz9axK78/XeJ9EcBrDHGrLAxLK9g2GKhegUBX7UWH2HDjCr8qGRZGsW6gw6jApq0teZqi8l+r8ViWZM8xKBUPkS/kSUkozgAQ6UbeVVhI/QgAlnSbFTr91GDjoTNHp4iTkk/E9BLC/NZ0G2NqQTtA2pSNF9Jya9dlZu80yiZDwbqrIo7oxGOYMu/21hYOViswTStcUbo5nYZkOW77WOY+ber1GdyaOjNSOqm0xOuqG1wWkAVpGxzVhSp1ADsQA0pNgXQAKrAEvDl+hQRkbXdyfaC7TNZzuhfBQNQYMONL8AXfdqdtOz1wTkH0v511zuq+r/v+s8/u/wB4jwvFV96Yj7t1fzvzdZ6w3i96Pe3Bs/tHXbdtxFQwXyCsAX2+kTExEDmAdfnzv4MjNXXj8h55x61WPAC3LuEmzA4QN6kC6NFHbuh9hfmipcrpELygzup8uoaTVAX0AQ5D0vJFcVKw53RpCteCdgs8xytmEir9TroDfThDukAS7rLxYkgdGhBiCLrHuEZFxdgzGZkPK6lNx6xDPOp5x8sIwIBCf2OAcVYtsuRReNSePnphbCLml8cB23THBusK+d2KsEYrFxUSNJqSFWDHDrXl+1D1HEFsSLQpdRYI4aWpAeUfMKMWAh9PzFoXpZ8WIoFMxBoES1uwAJ8vDp88nV9MDtwr4Me+uf64md3Z0fnP84vXZ3+c/N4Dunnx+vfK7PxiO6/x+f1i9WHz3+az0z8vh/rIWw67wP59jo6rrVJxB5AIpkeVQ34JXXVYeJOZM7A63r3NxOdm5yFKAQ7ZTSOHTZwzthTYpyCj/PW6zc+1BKjER+oklIIpiDjhKzQqhJNnGPA9J220O5SjJFCsUUP085agmyenqhmXnQ60cQEx01bNvr/6Cya9omzE4B19EFgknOP901q8FxLhMdgjfqn6iSvRrh36Tpg5tLHRfitExFNHQI8hN6x7q5PVD/gxvo4t6Xpo8L1ySgO7dG5VXav2xgRCUcgrQwDbOMsPbhLhyVEc+1wJRZIFA0CkbKwBPCW6G9N6Zz1vfqds4fz182Py985OIedN3+t9d3p2fUfn8YA7j7/PbBPEfnXL7H5/eKOoT39t52Kvd+XO617fOMp3KssAh+U9J4mc6vf5o0XrP9EnISBJoamYbjcWik4mm9zx7f1vDebDyaniVjkA0wTBTuTkbze7M/dcZlBaVgI9BeYXTcn8AFm+k5ClLMO+64N9+iODHm+7apHLnkQO52D0M9FG+ZeOiqHp30XUFl4dGWraHQo+mCbElaCN3piYvzHXicwnjNFTtg9wlCMbwhHI2ImyIiOsv+hWUeq9cmUqAwHg9odGyPzkQlP7ecu2Cy6Gzg3iO+DMTpbWbcIl7KgzJx7dG2HAGLG3QldF58On/Ru8rGfjW/Lf/dGdzDrd/Ge3r44d2vEzxB6+M+d8jqf3+sns/j949h7/AK/3ncQnbn9485x3f58PXALeW264fNntl74OV553yzXte5MiNUBABS8sLFg9jdBr1+axybuhDq2Hn7VtjOpiXoB4OhFs8IgfTVKdevZKhuAUpfprJIAUEggu+hiUKgdQDXGoKfZO/HZnIjfw0P8A7gDbkJmUk1ZQwStYhTHJseICUMzoTB9ioPTAN5SZP3JU3ibdoPA2+/hOs26d7OsUPE2r/b8k7KOuHpx6647YDsnl8M3/ANk/nPl/1jHU+Tf7xHQ985a+h+v3kjUqBZ0/fV9+XZy7p4JOvt+u0uMD6wAvbDZsFOCUBQvLqctUNU2xeVm1AUtyK7KPUYcQ2ElpQCWsWfQySKJCMejPI4435VDbenOZNAeOS06R8DZsQhky0itdZ8KlIf6FAoAVVADuroPPAQCbEETuJR9PrL36EqexUrs0d/sHU0UUAJyKLE6nP0mIOESllT/rauoFGVUGdxNTxD6L6goENQhEERCPCJrKY9DBF+S9R+soMoqTzg0t86sxzFdk7LNmOsFCjoygO0Qz8njShelt3NdP1zzzxeCxH0eYK3QYxzQJzP1Tae22VpjuV3+84vj0njjuX+XbfGW9A6ic+Tr9PjjnvgOL8J+189XCWHnrcePt2B1jjhRG/QuyMx3Y1oYyW68Lrfsd+25ABGa+R34Hh143MPiELCKKLQCm5ZW3EgHKAT1RJ/Qe38pSF6QTI1ATH7AZR0oIAu8EKmhONO8bFHKfTQczpKFQMTDmnMVMWvVO6JO+LGxoFYffxYViauh5kFyvDkBjyWN9KwUXQ9K3mQqrj0umjbv2DxKaVWHg8FfwglcugpQyIuf+t+0wwARswUzFBCj/AJ14Ggc1lwiiJwVWRxAwVMWtVnIFluxHM7WHLRMF4GCnJxTiekLGkZzeHQvMI4Dsdoot4q7zRzInMCK3xerurlXcInF9uyY4lEDGd03FvDD56egeWCztl1bNRQVKvGVK/Ohbat5cS1HfTplbeGsaQ1UkMmwC7UVbl4nhJPck0ncbI3EoBKIjQiI7HkZM4IB83T7913vtzMJmw5aLxePfby9CGgeZeEqsLy7vzUxOVD1Q302tt7b451lTn1up7dOu9dcXue+jvqk8+MHt93j1Sc65fEmCsbpP9OLO/poSqa1IY2FFWTnjjOXmAAHQbR1to5LRdW1+cUF0OIWAGp9BTYsCuoXbg/RPhudhkN2glQgClQ9KbB9BLBAUZqKmJOuEy9gDMexXMDogpSFBvOItj9pAGmQdFm2Iax0SwC4RoXCNMCNVWwl86Ik07snOZ+5QODlHt8gtxr+DDaDAQEdSUKKQcj6VxByZAF/WxAME48LRYBAE404oqYHVfYotxeYuePJCvjqTGQ9lUfYGZxhWIsoERHGdLgzTDXamu29zj6QLUadXPNG6ao4Kyu4pBp1ljTXfBm3iXlORNHuHuOIgAxSK7twPC7W9fs3ynDXiRN+g7ISzN8VFe0meB4OBtbnZgh3RNgHHS4ZYZIsy5k1sE/MIPIhMyz/kOFP5Dfszy30SjwV3jQ8Dt685Hz5qe3PXpweOaEpvVd++R8p3QntKd99sGANMAOSlnRkSZur3NeB0AOYXrkQICK631LGzQtOGGNviCh/6IEXB+MHkkAgFqaKIjyqV+p92rFcJ0rA6RRx+WbNXCQi4rHBBYF/TMHQKDEg7jOZoizzkzANMq/z7AdG7FPXWCTqqN2BaoiVnFVzY9u1ASTsvMAZYcYoY6uJYWWyWqUSPOFOskeriCzrNzF9aiGjwELB2sXjuiziq4DLAZejUzUEKuZHOLG4HYSkDQWLmMyTs/FxcxzroCeQD8o6hpmRTv2iV7rmvaEvW+Em+L1FpQoxSOr6L4eVUUfGqhjNzKBHz9GEjAc7bCuZocAJtOjlCvVQxk7KAC5LtwIxxVNIhEKkgqSPs1uPSh9KaOm8zPM6geUJKt0xOCWAUQqzloNKMKQA7sw4tSJKBTBz6JjFfgw9QeGB04oLevAkCaromZ6SIMCVEwFRGot2ACIl+GwvwKEiG80Df8FYM4B1iwFYyCAbAFJCAB2nzxSm3uvmEKYggSqIVmJI9BY2qoJX88a+n2xfItVqYVxSBzQREYdwEax6hSkETADAQO0TvtAcaxkXwQjgKVddWVxrGVf8A1NyIrhIIbyBoprOoOLRyJXSCBNSGNECRfe7CoGqw9RapAry+jfGRp5mifkwWqQ47xDgZeGonEEw0mFxvrJQdGIxREY6coIjXNL83BX3PRV/JU7RQyLPxA3U6QsWK0QgLod85gON34bkPeS7AQ0QjvLQ1+zf1z6RLNHiBvx+VjgUAGYzhtYjgFFf/AA0aS5TFJOS3OqhyvuznfNzQIjKI7LXkesJVTHN1mRmqvNpiDvkQ10emTLhztKlJLAClU5zD01MLssFR7ykXSKBcig1/nvQ5dMCgBqx9mUrA2ycAcNI6a+qOt+E9abmY0NBdBSbbgS7Ujl715kpOaNB+j7Fo+lH/AOGlw1Js01H1yUDjlUiWcpMuwE6GPWFVmugatF2DFshJSOcV3x79SseBVeb3Vk4O5zpY40lQgInCE5KTXAKtJdBEcAAAABm/YYH04R5R/wA6vV//2Q==\" />'\n",
       "</script>\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os                                                 # to set current working directory \n",
    "import numpy as np                                        # arrays and matrix math\n",
    "import pandas as pd                                       # DataFrames\n",
    "import matplotlib.pyplot as plt                           # plotting\n",
    "import pygslib as gslib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you get a package import error, you may have to first install some of these packages. This can usually be accomplished by opening up a command window on Windows and then typing 'python -m pip install [package-name]'. More assistance is available with the respective package docs.  \n",
    "\n",
    "#### Declare functions\n",
    "\n",
    "Here are the wrappers and reimplementations of GSLIB method along with 4 utilities to move between GSLIB's Geo-EAS data sets and DataFrames, and grids and 2D Numpy arrays respectively and 2 utilities to resample from regular datasets.  Available GSLIB functions include:\n",
    "\n",
    "1. hist\n",
    "2. pixelplt\n",
    "3. locmap\n",
    "4. locpix\n",
    "5. vargplt\n",
    "6. affine\n",
    "7. nscore\n",
    "8. declus\n",
    "9. gam\n",
    "10. gamv\n",
    "11. vmodel\n",
    "12. sgsim\n",
    "\n",
    "For now we embed the functions in the workflow below. In the future this will be turned into a proper Python package.  Warning, there has been no attempt to make these functions robust in the precense of bad inputs.  If you get a crazy error check the inputs.  Are the arrays empty and are they the same size when they should be?  Are the arrays the correct dimension?  Is the parameter order mixed up?  Make sure the inputs are consistent with the descriptions in this document."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# utility to convert GSLIB Geo-EAS files to a pandas DataFrame for use with Python methods\n",
    "def GSLIB2Dataframe(data_file):\n",
    "    import os\n",
    "    import numpy as np  \n",
    "    import pandas as pd\n",
    "\n",
    "    colArray = []\n",
    "    with open(data_file) as myfile:   # read first two lines\n",
    "        head = [next(myfile) for x in range(2)]\n",
    "        line2 = head[1].split()\n",
    "        ncol = int(line2[0])\n",
    "        for icol in range(0, ncol):\n",
    "            head = [next(myfile) for x in range(1)]\n",
    "            colArray.append(head[0].split()[0])\n",
    "        data = np.loadtxt(myfile, skiprows = 0)\n",
    "        df = pd.DataFrame(data)\n",
    "        df.columns = colArray\n",
    "        return df\n",
    "\n",
    "# utility to convert pandas DataFrame to a GSLIB Geo-EAS file for use with GSLIB methods\n",
    "def Dataframe2GSLIB(data_file,df):\n",
    "    colArray = []\n",
    "    colArray = df.columns\n",
    "    ncol = len(df.columns) \n",
    "    nrow = len(df.index)\n",
    "    file_out = open(data_file, \"w\")\n",
    "    file_out.write(data_file + '\\n')  \n",
    "    file_out.write(str(ncol) + '\\n') \n",
    "    for icol in range(0, ncol): \n",
    "        file_out.write(df.columns[icol]  + '\\n')  \n",
    "    \n",
    "    for irow in range(0, nrow):\n",
    "        for icol in range(0, ncol):\n",
    "            file_out.write(str(df.iloc[irow,icol])+ ' ')  \n",
    "        file_out.write('\\n')\n",
    "\n",
    "    file_out.close()       \n",
    "\n",
    "# utility to convert GSLIB Geo-EAS files to a numpy ndarray for use with Python methods\n",
    "def GSLIB2ndarray(data_file,kcol,nx,ny):\n",
    "    import os\n",
    "    import numpy as np  \n",
    "\n",
    "    colArray = []\n",
    "    if ny > 1:\n",
    "        array = np.ndarray(shape=(ny,nx),dtype=float,order='F')\n",
    "    else:\n",
    "        array = np.zeros(nx)\n",
    "        \n",
    "    with open(data_file) as myfile:   # read first two lines\n",
    "        head = [next(myfile) for x in range(2)]\n",
    "        line2 = head[1].split()\n",
    "        ncol = int(line2[0])          # get the number of columns\n",
    "        for icol in range(0, ncol):   # read over the column names\n",
    "            head = [next(myfile) for x in range(1)]\n",
    "            if icol == kcol:\n",
    "                col_name = head[0].split()[0]\n",
    "        for iy in range(0,ny):\n",
    "            for ix in range(0,nx):\n",
    "                head = [next(myfile) for x in range(1)]\n",
    "                array[ny-1-iy][ix] = head[0].split()[kcol]\n",
    "    return array,col_name\n",
    "\n",
    "# utility to convert numpy ndarray to a GSLIB Geo-EAS file for use with GSLIB methods   \n",
    "def ndarray2GSLIB(array,data_file,col_name):\n",
    "    file_out = open(data_file, \"w\")\n",
    "    file_out.write(data_file + '\\n')  \n",
    "    file_out.write('1 \\n')  \n",
    "    file_out.write(col_name  + '\\n') \n",
    "    if array.ndim == 2:\n",
    "        ny = (array.shape[0])\n",
    "        nx = (array.shape[1])\n",
    "        ncol = 1\n",
    "        for iy in range(0, ny):\n",
    "            for ix in range(0, nx):\n",
    "                file_out.write(str(array[ny-1-iy,ix])+ '\\n')        \n",
    "    elif array.ndim == 1:\n",
    "        nx = len(array)        \n",
    "        for ix in range(0, nx):\n",
    "            file_out.write(str(array[ix])+ '\\n')             \n",
    "    else:       \n",
    "        Print(\"Error: must use a 2D array\")            \n",
    "        file_out.close()\n",
    "        return            \n",
    "    file_out.close()\n",
    "    \n",
    "# histogram, reimplemented in Python of GSLIB hist with MatPlotLib methods\n",
    "def hist(array,xmin,xmax,log,cumul,bins,weights,xlabel,title):\n",
    "    plt.figure(figsize=(8,6))\n",
    "    cs = plt.hist(array, alpha = 0.2, color = 'red', edgecolor = 'black', bins=bins, range = [xmin,xmax], weights = weights, log = log, cumulative = cumul)\n",
    "    plt.title(title)\n",
    "    plt.xlabel(xlabel); plt.ylabel('Frequency')    \n",
    "    plt.show()\n",
    "    return\n",
    "   \n",
    "# pixel plot, reimplemention in Python of GSLIB pixelplt with MatPlotLib methods\n",
    "def pixelplt(array,xmin,xmax,ymin,ymax,step,vmin,vmax,title,xlabel,ylabel,vlabel,cmap):\n",
    "    xx, yy = np.meshgrid(np.arange(xmin, xmax, step),np.arange(ymax, ymin, -1*step))\n",
    "    plt.figure(figsize=(8,6))\n",
    "    im = plt.contourf(xx,yy,array,cmap=cmap,vmin=vmin,vmax=vmax,levels=np.linspace(vmin,vmax,100))\n",
    "    plt.title(title)\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(ylabel)\n",
    "    cbar = plt.colorbar(im,orientation = 'vertical',ticks=np.linspace(vmin,vmax,10))\n",
    "    cbar.set_label(vlabel, rotation=270, labelpad=20)\n",
    "    plt.show()\n",
    "    return im\n",
    "\n",
    "# location map, reimplemention in Python of GSLIB locmap with MatPlotLib methods\n",
    "def locmap(df,xcol,ycol,vcol,xmin,xmax,ymin,ymax,vmin,vmax,title,xlabel,ylabel,vlabel,cmap):\n",
    "    ixy = 0 \n",
    "    plt.figure(figsize=(8,6))    \n",
    "    im = plt.scatter(df[xcol],df[ycol],s=None, c=df[vcol], marker=None, cmap=cmap, norm=None, vmin=vmin, vmax=vmax, alpha=0.8, linewidths=0.8, verts=None, edgecolors=\"black\")\n",
    "    plt.title(title)\n",
    "    plt.xlim(xmin,xmax)\n",
    "    plt.ylim(ymin,ymax)    \n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(ylabel)\n",
    "    cbar = plt.colorbar(im, orientation = 'vertical',ticks=np.linspace(vmin,vmax,10))\n",
    "    cbar.set_label(vlabel, rotation=270, labelpad=20)\n",
    "    plt.show()\n",
    "    return im\n",
    "\n",
    "def vargplt(lag,gamma,npair,vtype,name,xmin,xmax,ymin,ymax,sill,title,cmap):\n",
    "    plt.figure(figsize=(8,6))\n",
    "    marker = [\"o\",\"v\",\"s\",\"h\",\"^\",\">\",\"<\"]\n",
    "    if vtype==0:\n",
    "        im = plt.scatter(lag,gamma,s=None, c=npair, marker=None, label = name,cmap=cmap, norm=None, alpha=0.8, linewidths=0.8, verts=None, edgecolors=\"black\")\n",
    "    else:\n",
    "        plt.plot(lag,gamma,'C3',lw=3,c='black')\n",
    "    ixy = 0 \n",
    "    plt.title(title)\n",
    "    plt.xlim(xmin,xmax)\n",
    "    plt.ylim(ymin,ymax)    \n",
    "    plt.xlabel('Lag Distance (m)')\n",
    "    plt.ylabel('Variogram')\n",
    "    plt.arrow(0,sill,xmax,0,width=0.002,color='red',head_length=0.0,head_width=0.0)\n",
    "    plt.legend(loc = 'lower right')\n",
    "    cbar = plt.colorbar(im, orientation = 'vertical')\n",
    "    cbar.set_label('Number of Pairs', rotation=270, labelpad=20)\n",
    "    plt.show()\n",
    "    return im\n",
    "\n",
    "def vargplts(lag,gamma,npair,vtype,name,xmin,xmax,ymin,ymax,sill,title,cmap):\n",
    "    plt.figure(figsize=(8,6))\n",
    "    marker = [\"o\",\"v\",\"s\",\"h\",\"^\",\">\",\"<\"]\n",
    "    nvar = lags.shape[0]\n",
    "    for ivar in range(0, nvar):\n",
    "        if vtype[ivar]==0:\n",
    "            im = plt.scatter(lag[ivar],gamma[ivar],s=None,label = name[ivar],c=npair[ivar], marker=marker[ivar], cmap=cmap, norm=None, alpha=0.8, linewidths=0.8, verts=None, edgecolors=\"black\")\n",
    "        else:\n",
    "            plt.plot(lag[ivar],gamma[ivar], 'C3', lw=3,c='black')\n",
    "    ixy = 0 \n",
    "    plt.title(title)\n",
    "    plt.xlim(xmin,xmax)\n",
    "    plt.ylim(ymin,ymax)    \n",
    "    plt.xlabel('Lag Distance (m)')\n",
    "    plt.ylabel('Variogram')\n",
    "    plt.arrow(0,sill,xmax,0,width=0.002,color='red',head_length=0.0,head_width=0.0)\n",
    "    plt.legend(loc = 'lower right')\n",
    "    cbar = plt.colorbar(im, orientation = 'vertical')\n",
    "    cbar.set_label('Number of Pairs', rotation=270, labelpad=20)\n",
    "    plt.show()\n",
    "    return im\n",
    "\n",
    "# pixelplt with location map superimposed, reimplementation in Python of a MOD from GSLIB with MatPlotLib methods\n",
    "def locpix(array,xmin,xmax,ymin,ymax,step,vmin,vmax,df,xcol,ycol,vcol,title,xlabel,ylabel,vlabel,cmap):\n",
    "    xx, yy = np.meshgrid(np.arange(xmin, xmax, step),np.arange(ymax, ymin, -1*step)) \n",
    "    plt.figure(figsize=(8,6))\n",
    "    cs = plt.contourf(xx, yy, array, cmap=cmap,vmin=vmin, vmax=vmax, levels=np.linspace(vmin,vmax,100))\n",
    "    im = plt.scatter(df[xcol],df[ycol],s=None, c=df[vcol], marker=None, cmap=cmap, norm=None, vmin=vmin, vmax=vmax, alpha=0.8, linewidths=0.8, verts=None, edgecolors=\"black\")\n",
    "    plt.xlim(xmin,xmax-step)\n",
    "    plt.ylim(ymin+step,ymax) \n",
    "    plt.title(title)\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(ylabel)\n",
    "    cbar = plt.colorbar(orientation = 'vertical',ticks=np.linspace(vmin,vmax,10))\n",
    "    cbar.set_label(vlabel, rotation=270, labelpad=20)\n",
    "    plt.show()\n",
    "    return cs\n",
    "\n",
    "# affine distribution correction reimplemented in Python with numpy methods \n",
    "def affine(array,tmean,tstdev):    \n",
    "    if array.ndim != 2:\n",
    "        Print(\"Error: must use a 2D array\")\n",
    "        return\n",
    "    nx = array.shape[0]\n",
    "    ny = array.shape[1]\n",
    "    mean = np.average(array)\n",
    "    stdev = np.std(array)\n",
    "    for iy in range(0,ny):\n",
    "        for ix in range(0,nx):\n",
    "             array[ix,iy]= (tstdev/stdev)*(array[ix,iy] - mean) + tmean  \n",
    "    return(array)            \n",
    "\n",
    "# normal score transform, wrapper for nscore from GSLIB (.exe must be in working directory)(not used in this demo)   \n",
    "def nscore(x):\n",
    "    import os\n",
    "    import numpy as np\n",
    "    file = 'nscore_out.dat'\n",
    "    ndarray2GSLIB(x,\"nscore.dat\",\"value\")\n",
    "    \n",
    "    file = open(\"nscore.par\", \"w\")\n",
    "    file.write(\"                  Parameters for NSCORE                                    \\n\")\n",
    "    file.write(\"                  *********************                                    \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"nscore.dat           -file with data                                       \\n\")\n",
    "    file.write(\"1   0                    -  columns for variable and weight                \\n\")\n",
    "    file.write(\"-1.0e21   1.0e21         -  trimming limits                                \\n\")\n",
    "    file.write(\"0                        -1=transform according to specified ref. dist.    \\n\")\n",
    "    file.write(\"../histsmth/histsmth.out -  file with reference dist.                      \\n\")\n",
    "    file.write(\"1   2                    -  columns for variable and weight                \\n\")\n",
    "    file.write(\"nscore.out               -file for output                                  \\n\")\n",
    "    file.write(\"nscore.trn               -file for output transformation table             \\n\")\n",
    "    file.close()\n",
    "\n",
    "    os.system('nscore.exe nscore.par')\n",
    "    file_in = 'nscore.out'\n",
    "    y,name = GSLIB2ndarray('nscore.out',1,nx,ny)\n",
    "    return(y)\n",
    "\n",
    "# cell-based declustering, 2D wrapper for declus from GSLIB (.exe must be in working directory)\n",
    "def declus(df,xcol,ycol,vcol,cmin,cmax,cnum,bmin):\n",
    "    import os\n",
    "    import numpy as np\n",
    "    nrow = len(df)\n",
    "    weights = []\n",
    "    file = 'declus_out.dat'\n",
    "    file_out = open(file, \"w\")\n",
    "    file_out.write('declus_out.dat' + '\\n')  \n",
    "    file_out.write('3' + '\\n')  \n",
    "    file_out.write('x' + '\\n') \n",
    "    file_out.write('y' + '\\n')\n",
    "    file_out.write('value' + '\\n')  \n",
    "    for irow in range(0, nrow):\n",
    "        file_out.write(str(df.iloc[irow][xcol])+' '+str(df.iloc[irow][ycol])+' '+str(df.iloc[irow][vcol])+' \\n')        \n",
    "    file_out.close()\n",
    "    \n",
    "    file = open(\"declus.par\", \"w\")\n",
    "    file.write(\"                  Parameters for DECLUS                                    \\n\")\n",
    "    file.write(\"                  *********************                                    \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"declus_out.dat           -file with data                                   \\n\")\n",
    "    file.write(\"1   2   0   3               -  columns for X, Y, Z, and variable           \\n\")\n",
    "    file.write(\"-1.0e21     1.0e21          -  trimming limits                             \\n\")\n",
    "    file.write(\"declus.sum                  -file for summary output                       \\n\") \n",
    "    file.write(\"declus.out                  -file for output with data & weights           \\n\")\n",
    "    file.write(\"1.0   1.0                   -Y and Z cell anisotropy (Ysize=size*Yanis)    \\n\") \n",
    "    file.write(str(bmin) + \"                -0=look for minimum declustered mean (1=max)   \\n\") \n",
    "    file.write(str(cnum) + \" \" + str(cmin) + \" \" + str(cmax) + \" -number of cell sizes, min size, max size      \\n\")\n",
    "    file.write(\"5                           -number of origin offsets                      \\n\")\n",
    "    file.close()\n",
    "    \n",
    "    os.system('declus.exe declus.par')\n",
    "    df = GSLIB2Dataframe(\"declus.out\")\n",
    "    for irow in range(0, nrow):\n",
    "        weights.append(df.iloc[irow,3])    \n",
    "\n",
    "    return(weights)\n",
    " \n",
    "# regular grid variogram, 2D wrapper for gam from GSLIB (.exe must be in working directory)\n",
    "def gam_2d(array,nx,ny,hsiz,nlag,xlag,ylag,bstand):\n",
    "    import os\n",
    "    import numpy as np\n",
    "    \n",
    "    lag = []; gamma = []; npair = []\n",
    "    \n",
    "    ndarray2GSLIB(array,\"gam_out.dat\",\"gam.dat\")\n",
    "    \n",
    "    file = open(\"gam.par\", \"w\")\n",
    "    file.write(\"                  Parameters for GAM                                       \\n\")\n",
    "    file.write(\"                  ******************                                       \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"gam_out.dat           -file with data                                      \\n\")\n",
    "    file.write(\"1   1   0             -   number of variables, column numbers              \\n\")\n",
    "    file.write(\"-1.0e21     1.0e21    -   trimming limits                                  \\n\")\n",
    "    file.write(\"gam.out               -file for variogram output                           \\n\")\n",
    "    file.write(\"1                     -grid or realization number                          \\n\")\n",
    "    file.write(str(nx) + \" 0.0 \" + str(hsiz) + \"  -nx, xmn, xsiz                           \\n\")\n",
    "    file.write(str(ny) + \" 0.0 \" + str(hsiz) + \"  -ny, ymn, ysiz                           \\n\")\n",
    "    file.write(\" 1   0.5   1.0        -nz, zmn, zsiz                                       \\n\")\n",
    "    file.write(\"1 \" + str(nlag) + \"   -number of directions, number of lags                \\n\")\n",
    "    file.write(str(xlag) + \" \" + str(ylag) + \" 0 -ixd(1),iyd(1),izd(1)                     \\n\")\n",
    "    file.write(\"1                     -standardize sill? (0=no, 1=yes)                     \\n\")\n",
    "    file.write(\"1                     -number of variograms                                \\n\")\n",
    "    file.write(\"1   1   1             -tail variable, head variable, variogram type        \\n\") \n",
    "    file.close()\n",
    "    \n",
    "    os.system('gam.exe gam.par')\n",
    "    reading = True\n",
    "    with open(\"gam.out\") as myfile:   \n",
    "        head = [next(myfile) for x in range(1)] # skip the first line\n",
    "        iline = 0\n",
    "        while reading:\n",
    "            try:\n",
    "                head = [next(myfile) for x in range(1)]\n",
    "                lag.append(float(head[0].split()[1]))\n",
    "                gamma.append(float(head[0].split()[2]))\n",
    "                npair.append(float(head[0].split()[3]))\n",
    "                iline = iline + 1\n",
    "            except StopIteration:\n",
    "                reading = False   \n",
    "    \n",
    "    return(lag,gamma,npair)    \n",
    "\n",
    "# regular grid variogram, 2D wrapper for gam from GSLIB (.exe must be in working directory)\n",
    "def gamv_2d(df,xcol,ycol,vcol,nlag,lagdist,azi,atol,bstand):\n",
    "    import os\n",
    "    import numpy as np\n",
    "    \n",
    "    lag = []; gamma = []; npair = []\n",
    "    \n",
    "    df_ext = pd.DataFrame({'X':df[xcol],'Y':df[ycol],'Z':rand_sample[vcol]})\n",
    "    Dataframe2GSLIB(\"gamv_out.dat\",df_ext)\n",
    "    \n",
    "    file = open(\"gamv.par\", \"w\")\n",
    "    \n",
    "    file.write(\"                  Parameters for GAMV                                      \\n\")\n",
    "    file.write(\"                  *******************                                      \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"gamv_out.dat                    -file with data                            \\n\") \n",
    "    file.write(\"1   2   0                         -   columns for X, Y, Z coordinates      \\n\")\n",
    "    file.write(\"1   3   0                         -   number of variables,col numbers      \\n\")\n",
    "    file.write(\"-1.0e21     1.0e21                -   trimming limits                      \\n\")\n",
    "    file.write(\"gamv.out                          -file for variogram output               \\n\")\n",
    "    file.write(str(nlag) + \"                      -number of lags                          \\n\")\n",
    "    file.write(str(lagdist) + \"                       -lag separation distance                 \\n\")\n",
    "    file.write(str(lagdist*0.5) + \"                   -lag tolerance                           \\n\")\n",
    "    file.write(\"1                                 -number of directions                    \\n\")\n",
    "    file.write(str(azi) + \" \" + str(atol) + \" 99999.9 0.0  90.0  50.0  -azm,atol,bandh,dip,dtol,bandv \\n\")\n",
    "    file.write(str(bstand) + \"                    -standardize sills? (0=no, 1=yes)        \\n\")\n",
    "    file.write(\"1                                 -number of variograms                    \\n\")\n",
    "    file.write(\"1   1   1                         -tail var., head var., variogram type    \\n\")\n",
    "    file.close()\n",
    "    \n",
    "    os.system('gamv.exe gamv.par')\n",
    "    reading = True\n",
    "    with open(\"gamv.out\") as myfile:   \n",
    "        head = [next(myfile) for x in range(1)] # skip the first line\n",
    "        iline = 0\n",
    "        while reading:\n",
    "            try:\n",
    "                head = [next(myfile) for x in range(1)]\n",
    "                lag.append(float(head[0].split()[1]))\n",
    "                gamma.append(float(head[0].split()[2]))\n",
    "                npair.append(float(head[0].split()[3]))\n",
    "                iline = iline + 1\n",
    "            except StopIteration:\n",
    "                reading = False   \n",
    "    \n",
    "    return(lag,gamma,npair)    \n",
    "\n",
    "# irregular spaced data, 2D wrapper for varmap from GSLIB (.exe must be in working directory)\n",
    "def varmapv_2d(df,xcol,ycol,vcol,nx,ny,lagdist,minpairs,vmax,bstand,title,vlabel):\n",
    "    import os\n",
    "    import numpy as np\n",
    "    \n",
    "    lag = []; gamma = []; npair = []\n",
    "    \n",
    "    df_ext = pd.DataFrame({'X':df[xcol],'Y':df[ycol],'Z':rand_sample[vcol]})\n",
    "    Dataframe2GSLIB(\"varmap_out.dat\",df_ext)\n",
    "    \n",
    "    file = open(\"varmap.par\", \"w\")\n",
    "    \n",
    "    file.write(\"              Parameters for VARMAP                                        \\n\")\n",
    "    file.write(\"              *********************                                        \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"varmap_out.dat          -file with data                                    \\n\")\n",
    "    file.write(\"1   3                        -   number of variables: column numbers       \\n\")\n",
    "    file.write(\"-1.0e21     1.0e21           -   trimming limits                           \\n\")\n",
    "    file.write(\"0                            -1=regular grid, 0=scattered values           \\n\")\n",
    "    file.write(\" 50   50    1                -if =1: nx,     ny,   nz                      \\n\")\n",
    "    file.write(\"1.0  1.0  1.0                -       xsiz, ysiz, zsiz                      \\n\") \n",
    "    file.write(\"1   2   0                    -if =0: columns for x,y, z coordinates        \\n\") \n",
    "    file.write(\"varmap.out                   -file for variogram output                    \\n\")\n",
    "    file.write(str(nx) + \" \" + str(ny) + \" 0 \" + \"-nxlag, nylag, nzlag                     \\n\")\n",
    "    file.write(str(lagdist) + \" \" + str(lagdist) + \" 1.0              -dxlag, dylag, dzlag \\n\")\n",
    "    file.write(str(minpairs) + \"             -minimum number of pairs                      \\n\")\n",
    "    file.write(str(bstand) + \"               -standardize sill? (0=no, 1=yes)              \\n\")\n",
    "    file.write(\"1                            -number of variograms                         \\n\") \n",
    "    file.write(\"1   1   1                    -tail, head, variogram type                   \\n\")\n",
    "    file.close()\n",
    "    \n",
    "    os.system('varmap.exe varmap.par')\n",
    "    nnx = nx*2+1; nny = ny*2+1\n",
    "    varmap, name = GSLIB2ndarray(\"varmap.out\",0,nnx,nny)               \n",
    "          \n",
    "    xmax = ((float(nx)+0.5)*lagdist); xmin = -1*xmax; \n",
    "    ymax = ((float(ny)+0.5)*lagdist); ymin = -1*ymax; \n",
    "    pixelplt(varmap,xmin,xmax,ymin,ymax,lagdist,0,vmax,title,'X','Y',vlabel,cmap)\n",
    "    return(varmap)  \n",
    "\n",
    "# regular spaced data, 2D wrapper for varmap from GSLIB (.exe must be in working directory)\n",
    "def varmap_2d(array,nx,ny,hsiz,nlagx,nlagy,minpairs,vmax,bstand,title,vlabel):\n",
    "    import os\n",
    "    import numpy as np\n",
    "     \n",
    "    ndarray2GSLIB(array,\"varmap_out.dat\",\"gam.dat\")\n",
    "    \n",
    "    file = open(\"varmap.par\", \"w\")\n",
    "    \n",
    "    file.write(\"              Parameters for VARMAP                                        \\n\")\n",
    "    file.write(\"              *********************                                        \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"varmap_out.dat          -file with data                                    \\n\")\n",
    "    file.write(\"1   1                        -   number of variables: column numbers       \\n\")\n",
    "    file.write(\"-1.0e21     1.0e21           -   trimming limits                           \\n\")\n",
    "    file.write(\"1                            -1=regular grid, 0=scattered values           \\n\")\n",
    "    file.write(str(nx) + \" \" + str(ny) + \" 1  -if =1: nx,     ny,   nz                     \\n\")\n",
    "    file.write(str(hsiz) + \" \" + str(hsiz) + \" 1.0  - xsiz, ysiz, zsiz                     \\n\") \n",
    "    file.write(\"1   2   0                    -if =0: columns for x,y, z coordinates        \\n\") \n",
    "    file.write(\"varmap.out                   -file for variogram output                    \\n\")\n",
    "    file.write(str(nlagx) + \" \" + str(nlagy) + \" 0 \" + \"-nxlag, nylag, nzlag               \\n\")\n",
    "    file.write(str(hsiz) + \" \" + str(hsiz) + \" 1.0              -dxlag, dylag, dzlag       \\n\")\n",
    "    file.write(str(minpairs) + \"             -minimum number of pairs                      \\n\")\n",
    "    file.write(str(bstand) + \"               -standardize sill? (0=no, 1=yes)              \\n\")\n",
    "    file.write(\"1                            -number of variograms                         \\n\") \n",
    "    file.write(\"1   1   1                    -tail, head, variogram type                   \\n\")\n",
    "    file.close()\n",
    "    \n",
    "    os.system('varmap.exe varmap.par')\n",
    "    nnx = nlagx*2+1; nny = nlagy*2+1\n",
    "    varmap, name = GSLIB2ndarray(\"varmap.out\",0,nnx,nny)               \n",
    "          \n",
    "    xmax = ((float(nlagx)+0.5)*hsiz); xmin = -1*xmax; \n",
    "    ymax = ((float(nlagy)+0.5)*hsiz); ymin = -1*ymax; \n",
    "    pixelplt(varmap,xmin,xmax,ymin,ymax,hsiz,0,vmax,title,'X','Y',vlabel,cmap)\n",
    "    return(varmap)  \n",
    "\n",
    "# variogram model, 2D wrapper for vmodel from GSLIB (.exe must be in working directory)\n",
    "def vmodel_2d(nlag,step,azi,nug,nst,tstr1,c1,azi1,rmaj1,rmin1,tstr2=1,c2=0,azi2=0,rmaj2=0,rmin2=0):\n",
    "    import os\n",
    "    import numpy as np\n",
    "\n",
    "    lag = []; gamma = []\n",
    "    \n",
    "    file = open(\"vmodel.par\", \"w\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"                  Parameters for VMODEL                                    \\n\")\n",
    "    file.write(\"                  *********************                                    \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETERS:                                                       \\n\")\n",
    "    file.write(\"vmodel.var                   -file for variogram output                    \\n\")\n",
    "    file.write(\"1 \" + str(nlag) + \"          -number of directions and lags                \\n\")\n",
    "    file.write(str(azi) + \" 0.0 \" + str(step) + \" -azm, dip, lag distance                  \\n\")\n",
    "    file.write(str(nst) + \" \" + str(nug) + \" -nst, nugget effect                           \\n\")\n",
    "    file.write(str(tstr1) + \" \" + str(c1) + \" \" + str(azi1) + \" 0.0   0.0   0.0 -it,cc,ang1,ang2,ang3 \\n\")\n",
    "    file.write(str(rmaj1) + \" \" + str(rmin1) + \" 0.0 -a_hmax, a_hmin, a_vert               \\n\")\n",
    "    file.write(str(tstr2) + \" \" + str(c2) + \" \" + str(azi2) + \" 0.0   0.0   0.0 -it,cc,ang1,ang2,ang3 \\n\")\n",
    "    file.write(str(rmaj2) + \" \" + str(rmin2) + \" 0.0 -a_hmax, a_hmin, a_vert               \\n\")\n",
    "    file.close()\n",
    "    \n",
    "    os.system('vmodel.exe vmodel.par')\n",
    "    reading = True\n",
    "    with open(\"vmodel.var\") as myfile:   \n",
    "        head = [next(myfile) for x in range(1)] # skip the first line\n",
    "        iline = 0\n",
    "        while reading:\n",
    "            try:\n",
    "                head = [next(myfile) for x in range(1)]\n",
    "                lag.append(float(head[0].split()[1]))\n",
    "                gamma.append(float(head[0].split()[2]))\n",
    "                iline = iline + 1\n",
    "            except StopIteration:\n",
    "                reading = False   \n",
    "    \n",
    "    return(lag,gamma)               \n",
    "               \n",
    "# sequential Gaussian simulation, 2D unconditional wrapper for sgsim from GSLIB (.exe must be in working directory)\n",
    "def GSLIB_sgsim_2d_uncond(nreal,nx,ny,hsiz,seed,hrange1,hrange2,azi,output_file):\n",
    "    import os\n",
    "    import numpy as np \n",
    "    \n",
    "    hmn = hsiz * 0.5   \n",
    "    hctab = int(hrange1/hsiz)*2 + 1\n",
    "    \n",
    "    sim_array = np.random.rand(nx,ny)\n",
    "  \n",
    "    file = open(\"sgsim.par\", \"w\")\n",
    "    file.write(\"              Parameters for SGSIM                                         \\n\")\n",
    "    file.write(\"              ********************                                         \\n\")\n",
    "    file.write(\"                                                                           \\n\")\n",
    "    file.write(\"START OF PARAMETER:                                                        \\n\")\n",
    "    file.write(\"none                          -file with data                              \\n\")\n",
    "    file.write(\"1  2  0  3  5  0              -  columns for X,Y,Z,vr,wt,sec.var.          \\n\")\n",
    "    file.write(\"-1.0e21 1.0e21                -  trimming limits                           \\n\")\n",
    "    file.write(\"0                             -transform the data (0=no, 1=yes)            \\n\")\n",
    "    file.write(\"none.trn                      -  file for output trans table               \\n\")\n",
    "    file.write(\"1                             -  consider ref. dist (0=no, 1=yes)          \\n\")\n",
    "    file.write(\"none.dat                      -  file with ref. dist distribution          \\n\")\n",
    "    file.write(\"1  0                          -  columns for vr and wt                     \\n\")\n",
    "    file.write(\"-4.0    4.0                   -  zmin,zmax(tail extrapolation)             \\n\")\n",
    "    file.write(\"1      -4.0                   -  lower tail option, parameter              \\n\")\n",
    "    file.write(\"1       4.0                   -  upper tail option, parameter              \\n\")\n",
    "    file.write(\"0                             -debugging level: 0,1,2,3                    \\n\")\n",
    "    file.write(\"nonw.dbg                      -file for debugging output                   \\n\")\n",
    "    file.write(str(output_file) + \"           -file for simulation output                  \\n\")\n",
    "    file.write(str(nreal) + \"                 -number of realizations to generate          \\n\")\n",
    "    file.write(str(nx) + \" \" + str(hmn) + \" \" + str(hsiz) + \"                              \\n\")\n",
    "    file.write(str(ny) + \" \" + str(hmn) + \" \" + str(hsiz) + \"                              \\n\")\n",
    "    file.write(\"1 0.0 1.0                     - nz zmn zsiz                                \\n\")\n",
    "    file.write(str(seed) + \"                  -random number seed                          \\n\")\n",
    "    file.write(\"0     8                       -min and max original data for sim           \\n\")\n",
    "    file.write(\"12                            -number of simulated nodes to use            \\n\")\n",
    "    file.write(\"0                             -assign data to nodes (0=no, 1=yes)          \\n\")\n",
    "    file.write(\"1     3                       -multiple grid search (0=no, 1=yes),num      \\n\")\n",
    "    file.write(\"0                             -maximum data per octant (0=not used)        \\n\")\n",
    "    file.write(str(hrange1) + \" \" + str(hrange2) + \" 1.0 -maximum search  (hmax,hmin,vert) \\n\")\n",
    "    file.write(str(azi) + \"   0.0   0.0       -angles for search ellipsoid                 \\n\")\n",
    "    file.write(str(hctab) + \" \" + str(hctab) + \" 1 -size of covariance lookup table        \\n\")\n",
    "    file.write(\"0     0.60   1.0              -ktype: 0=SK,1=OK,2=LVM,3=EXDR,4=COLC        \\n\")\n",
    "    file.write(\"none.dat                      -  file with LVM, EXDR, or COLC variable     \\n\")\n",
    "    file.write(\"4                             -  column for secondary variable             \\n\")\n",
    "    file.write(\"1    0.0                      -nst, nugget effect                          \\n\")\n",
    "    file.write(\"1    1.0 \" + str(azi) + \" 0.0 0.0 -it,cc,ang1,ang2,ang3                    \\n\")\n",
    "    file.write(\" \" + str(hrange1) + \" \" + str(hrange2) + \" 1.0 -a_hmax, a_hmin, a_vert     \\n\")\n",
    "    file.close()\n",
    "\n",
    "    os.system('\"sgsim.exe sgsim.par\"')       \n",
    "    sim_array = GSLIB2ndarray(output_file,0,nx,ny)         \n",
    "    return(sim_array)\n",
    "\n",
    "# extract regular spaced samples from a model   \n",
    "def regular_sample(array,xmin,xmax,ymin,ymax,step,mx,my,name):\n",
    "    x = []; y = []; v = []; iix = 0; iiy = 0;\n",
    "    xx, yy = np.meshgrid(np.arange(xmin, xmax, step),np.arange(ymax, ymin, -1*step))\n",
    "    iiy = 0\n",
    "    for iy in range(0,ny):\n",
    "        if iiy >= my:\n",
    "            iix = 0\n",
    "            for ix in range(0,nx):\n",
    "                if iix >= mx:\n",
    "                    x.append(xx[ix,iy]);y.append(yy[ix,iy]); v.append(array[ix,iy])\n",
    "                    iix = 0; iiy = 0\n",
    "                iix = iix + 1\n",
    "        iiy = iiy + 1\n",
    "    df = pd.DataFrame(np.c_[x,y,v],columns=['X', 'Y', name])\n",
    "    return(df)\n",
    "\n",
    "# extract random set of samples from a model   \n",
    "def random_sample(array,xmin,xmax,ymin,ymax,step,nsamp,name):\n",
    "    import random as rand\n",
    "    x = []; y = []; v = []; iix = 0; iiy = 0;\n",
    "    xx, yy = np.meshgrid(np.arange(xmin, xmax, step),np.arange(ymax-1, ymin-1, -1*step))\n",
    "    nx = xx.shape[0]\n",
    "    ny = xx.shape[1]\n",
    "    sample_index = rand.sample(range((nx)*(ny)), nsamp)\n",
    "    for isamp in range(0,nsamp):\n",
    "        iy = int(sample_index[isamp]/ny)\n",
    "        ix = sample_index[isamp] - iy*nx\n",
    "        x.append(xx[ix,iy])\n",
    "        y.append(yy[ix,iy])\n",
    "        v.append(array[ix,iy])\n",
    "   \n",
    "    df = pd.DataFrame(np.c_[x,y,v],columns=['X', 'Y', name])\n",
    "    return(df)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set the working directory\n",
    "\n",
    "I always like to do this so I don't lose files and to simplify subsequent read and writes (avoid including the full address each time).  Also, in this case make sure to place the required (see above) GSLIB executables in this directory or a location identified in the environmental variable *Path*.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"c:/PGE337\")                                   # set the working directory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will have to update the part in quotes with your own working directory and the format is different on a Mac (e.g. \"~/PGE\"). \n",
    "\n",
    "##### Make a 2D spatial model\n",
    "\n",
    "The following are the basic parameters for the demonstration.  This includes the number of cells in the 2D regular grid, the cell size (step) and the x and y min and max along with the color scheme.\n",
    "\n",
    "Then we make a single realization of a Gausian distributed feature over the specified 2D grid and then apply affine correction to ensure we have a reasonable mean and spread for our feature's distribution, assumed to be Porosity (e.g. no negative values) while retaining the Gaussian distribution.  Any transform could be applied at this point.  We are keeping this workflow simple. *This is our truth model that we will sample*.\n",
    "\n",
    "The parameters of *GSLIB_sgsim_2d_uncond* are (nreal,nx,ny,hsiz,seed,hrange1,hrange2,azi,output_file).  nreal is the number of realizations, nx and ny are the number of cells in x and y, hsiz is the cell siz, seed is the random number seed, hrange and hrange2 are the variogram ranges in major and minor directions respectively, azi is the azimuth of the primary direction of continuity (0 is aligned with Y axis) and output_file is a GEO_DAS file with the simulated realization.  The ouput is the 2D numpy array of the simulation along with the name of the property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx = 100; ny = 100; cell_size = 10                               # grid number of cells and cell size\n",
    "xmin = 0.0; ymin = 0.0;                                          # grid origin\n",
    "xmax = xmin + nx * cell_size; ymax = ymin + ny * cell_size       # calculate the extent of model\n",
    "seed = 74074                                                     # random number seed  for stochastic simulation    \n",
    "range_max = 500; range_min = 200; azimuth = 90                   # Porosity variogram ranges and azimuth\n",
    "mean = 10.0; stdev = 2.0                                         # Porosity mean and standard deviation\n",
    "#cmap = plt.cm.RdYlBu\n",
    "vmin = 4; vmax = 16; cmap = plt.cm.plasma                        # color min and max and using the plasma color map\n",
    "\n",
    "# calculate a stochastic realization with standard normal distribution\n",
    "sim,value = GSLIB_sgsim_2d_uncond(1,nx,ny,cell_size,seed,range_max,range_min,azimuth,\"simulation\")\n",
    "sim = affine(sim,mean,stdev)                                     # correct the distribution to a target mean and standard deviation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's check the simulated truth model with histogram and pixel plot.  We will make sure that the distribution is now Gaussian and the values have the correct spatial features. The hist function parameters are (array,xmin,xmax,log,cumul,bins,weights,xlabel,title).  Array is a 1D or 2D array, xmin and ymin are the min and max values in the plot, log is 1 for log axis and cumul is 1 for cumulative distribution, bins is the number of equal sized bins, weights is an optional array of the same size as the data array with weights and the remainder are labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exhastive Mean =  10.0 , Exhaustive Variance =  4.0\n"
     ]
    }
   ],
   "source": [
    "hist(sim.flatten(),vmin,vmax,log=False,cumul=False,bins=20,weights=None,xlabel=\"Porosity (%)\",title=\"Porosity Dataset\")\n",
    "ex_mean = np.average(sim)\n",
    "ex_var = np.var(sim)\n",
    "print('Exhastive Mean = ',round(ex_mean,2),', Exhaustive Variance = ',round(ex_var,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at our 2D model with pixel plots.  The parameters below for the pixelplt function are(array,xmin,xmax,ymin,ymax,step,vmin,vmax,title,xlabel,ylabel,vlabel,cmap).  Array is a 2D numpy array with the realization (the output from the *GSLIB_sgsim_2d_uncond*), the xmin, xmax, ymin, ymax are the extents of the model and step is the cell size, vmin, vmax are the min and max of the feature, title, xlabel, ylabel and vlabel are the plot labels and cmap is the color map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1bbd6157ef0>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pixelplt(sim,xmin,xmax,ymin,ymax,cell_size,vmin,vmax,\"Porosity Realization\",\"X(m)\",\"Y(m)\",\"Porosity (%)\",cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like 090 (x axis) is the direction of major continuity and 000 (y axis) is the direction of minor continuity.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "#### Regularly and Irregularly Sampled Data\n",
    "\n",
    "We have a function that extract random samples from a 2D ndarray with the parameters (array,xmin,xmax,ymin,ymax,step,nsamp,name), where array is the 2D numpy array followed by the extents and cell size and nsamp is the number of random samples and name is the name to given to the values sampled in the output DataFrame.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "rand_sample = random_sample(sim,xmin,xmax,ymin,ymax,cell_size,100,\"Porosity\")\n",
    "rand_sample['Z'] = np.zeros(100)\n",
    "rand_sample_mean = rand_sample[['Porosity']].mean(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize out new data set with and without the simulation shown. We can visualize the truth model and the samples with locpix. The parameters of locpix are (array,xmin,xmax,ymin,ymax,step,vmin,vmax,df,xcol,ycol,vcol,title,xlabel,ylabel,vlabel,cmap). These are the same as pixelplt with the addition of the locmap parameters described below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1bbd97725f8>"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locpix(sim,0,1000,ymin,ymax,cell_size,vmin,vmax,rand_sample,'X','Y','Porosity','Porosity Realization and Random Samples','X(m)','Y(m)','Porosity (%)',cmap)\n",
    "locmap(rand_sample,'X','Y','Porosity',xmin,xmax,ymin,ymax,vmin,vmax,'Random Porosity Samples','X(m)','Y(m)','Porosity (%)',cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also have a function to extract regularly sampled values from a 2D array and write them to a DataFrame.  Note, while regular and random sampling should provide representative samples of the truth model, it was convenient to use these functions, given the small number of random samples and the extra space around the outer samples in the regular pattern, it was anticipated that there would be some mismatch between true and sample mean and interesting location maps of declustering weights to demonstrate the declusteirng method.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1bbd7a910f0>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg_sample = regular_sample(sim,xmin,xmax,ymin,ymax,cell_size,10,10,'Porosity')\n",
    "reg_sample_mean = reg_sample[['Porosity']].mean(axis=0)\n",
    "n = len(reg_sample)\n",
    "reg_sample['Z'] = np.zeros(n)\n",
    "locpix(sim,0,1000,ymin,ymax,cell_size,vmin,vmax,reg_sample,'X','Y','Porosity','Porosity Realization and Regular Samples','X(m)','Y(m)','Porosity (%)',cmap)\n",
    "locmap(reg_sample,'X','Y','Porosity',xmin,xmax,ymin,ymax,vmin,vmax,'Regular Porosity Samples','X(m)','Y(m)','Porosity (%)',cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Declustering with PyGSLIB\n",
    "\n",
    "First we need to define a library with all of the parameters.  These are the same paramters used by the GSLIB algorithm declus.  We start with the regular sample case and then proceed to the random sample case. The parameters, their settings and explanations are below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "reg_parameters = {\n",
    "       # database\n",
    "        'x'      :  reg_sample.X,     # data x coordinates, array('f') with bounds (na), na is number of data points\n",
    "        'y'      :  reg_sample.Y,     # data y coordinates, array('f') with bounds (na)\n",
    "        'z'      :  reg_sample.Z,     # data z coordinates, array('f') with bounds (na)\n",
    "        'vr'     :  reg_sample.Porosity,    # variable, array('f') with bounds (na)\n",
    "       # cell size\n",
    "        'anisy'  :  1.,           # Y cell anisotropy (Ysize=size*Yanis), 'f'\n",
    "        'anisz'  :  1.,           # Z cell anisotropy (Zsize=size*Zanis), 'f'\n",
    "        'minmax' :  0,            # 0=look for minimum declustered mean (1=max), 'i'\n",
    "        'ncell'  :  100,          # number of cell sizes, 'i'\n",
    "        'cmin'   :  5,            # minimum cell sizes, 'i'\n",
    "        'cmax'   :  5000,         # maximum cell sizes, 'i'. Will be update to cmin if ncell == 1\n",
    "        'noff'   :  8,            # number of origin offsets, 'i'. This is to avoid local minima/maxima\n",
    "        'maxcel' :  100000}       # maximum number of cells, 'i'. This is to avoid large calculations, if MAXCEL<1 this check will be "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try running theses parameters and checking the resulting declustered mean vs. the sample mean and the true mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The true mean is 10.0, sample mean is 10.13, and declustered mean is 9.93\n"
     ]
    }
   ],
   "source": [
    "declus_reg = gslib.gslib.declus(reg_parameters)\n",
    "print('The true mean is ' + str(round(ex_mean,2)) + ', sample mean is ' + str(round(reg_sample_mean[0],2)) + ', and declustered mean is ' + str(round(declus_reg[1],2)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is also useful to visualize the resulting declustering weights at the data locations.  See the lower weights for the data at the edges as they appear to be less spatially clustered."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1bbd7b2de10>"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg_sample['wt'] = declus_reg[0]\n",
    "locmap(reg_sample,'X','Y','wt',xmin,xmax,ymin,ymax,0.8,1.1,'Porosity Weights','X(m)','Y(m)','Declustering Weights',cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is useful to also visualize the plot of the cell size vs. the declustered mean to assess the cell size selection process.  We can note that a cell size of about 800 m minimized the declustering mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "declus_mean_reg = declus_reg[11]\n",
    "cell_size_reg = declus_reg[8]\n",
    "plt.scatter(cell_size_reg,declus_mean_reg)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try with randomly sampled data.  As stated previously, the randomly sampled data should be representative, but may diverge from the true mean due to limited sampling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "rand_parameters = {\n",
    "       # database\n",
    "        'x'      :  rand_sample.X,     # data x coordinates, array('f') with bounds (na), na is number of data points\n",
    "        'y'      :  rand_sample.Y,     # data y coordinates, array('f') with bounds (na)\n",
    "        'z'      :  rand_sample.Z,     # data z coordinates, array('f') with bounds (na)\n",
    "        'vr'     :  rand_sample.Porosity,    # variable, array('f') with bounds (na)\n",
    "       # cell size\n",
    "        'anisy'  :  1.,           # Y cell anisotropy (Ysize=size*Yanis), 'f'\n",
    "        'anisz'  :  1.,           # Z cell anisotropy (Zsize=size*Zanis), 'f'\n",
    "        'minmax' :  1,            # 0=look for minimum declustered mean (1=max), 'i'\n",
    "        'ncell'  :  100,          # number of cell sizes, 'i'\n",
    "        'cmin'   :  5,            # minimum cell sizes, 'i'\n",
    "        'cmax'   :  5000,         # maximum cell sizes, 'i'. Will be update to cmin if ncell == 1\n",
    "        'noff'   :  8,            # number of origin offsets, 'i'. This is to avoid local minima/maxima\n",
    "        'maxcel' :  100000}       # maximum number of cells, 'i'. This is to avoid large calculations, if MAXCEL<1 this check will be "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The true mean is 10.0, sample mean is 10.08, and declustered mean is 9.83\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1bbd980d518>"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "declus_rand = gslib.gslib.declus(rand_parameters)\n",
    "rand_sample['wt'] = declus_rand[0]\n",
    "print('The true mean is ' + str(round(ex_mean,2)) + ', sample mean is ' + str(round(rand_sample_mean[0],2)) + ', and declustered mean is ' + str(round(declus_rand[1],2)))\n",
    "locmap(rand_sample,'X','Y','wt',xmin,xmax,ymin,ymax,0.8,1.1,'Porosity Weights','X(m)','Y(m)','Declustering Weights',cmap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "declus_mean = declus_rand[11]\n",
    "cell_size = declus_rand[8]\n",
    "plt.scatter(cell_size,declus_mean)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comments\n",
    "\n",
    "We cannot guarantee that declustering will always improve the estimate of the global mean, debias the sample set, but on average it should improve the representativity and reduce bias.  \n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "On twitter I'm the @GeostatsGuy.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}