PNC_04Evaluation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from notebook.services.config import ConfigManager\n",
    "cfgm = ConfigManager()\n",
    "cfgm.update('livereveal', {\n",
    "              'theme': 'simple',\n",
    "              'transition': 'convex',\n",
    "              'start_slideshow_at': 'selected'\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".answers { \n",
       "    visibility: hidden;\n",
       "}\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import HTML\n",
    "HTML(\"\"\"<style>\n",
    ".answers { \n",
    "    visibility: hidden;\n",
    "}\n",
    "</style>\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Python Analysis Evaluation\n",
    "Presented by: Barron H. Henderson, Byeong-Uk Kim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "/Users/barronh/Development/RAQMSandPython/working\n"
     ]
    }
   ],
   "source": [
    "# Prepare my slides\n",
    "%pylab inline\n",
    "%cd working"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Process AQS for evaluation\n",
    "\n",
    "1. Download annual zip file(s)\n",
    "2. Unzip\n",
    "3. Use sed, grep, or awk to get spatial/temporal subset\n",
    "4. Reshape data\n",
    "    1. Missing data should be masked\n",
    "    2. Dimensions (time, point)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# CHECK POINT \n",
    "\n",
    "1. What do you think the dimensions should be for AQS observations?\n",
    "    - \n",
    "\n",
    "2. What meta-data should be present?\n",
    "    - \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Getting AQS Observations\n",
    "\n",
    "1. Get AQS observations\n",
    "    1. Raw outputs from AQS website\n",
    "    2. Representational State Transfer - good for small amounts of data\n",
    "2. REST format was having problems due to its transition."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Raw outputs\n",
    "\n",
    "1. Download directly or download inline\n",
    "2. A csv file has been prepared with data just for the 2006-07-31 to 2006-08-10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from urllib.request import urlretrieve, url2pathname\n",
    "import os\n",
    "ftproot = 'ftp://data.as.essie.ufl.edu/pub/exch/CMAQandPython/'\n",
    "urlpath = ftproot + 'aqs/hourly_44201_200608.csv'\n",
    "aqspath = os.path.join('aqs', os.path.basename(urlpath))\n",
    "if not os.path.exists(aqspath):\n",
    "    urlretrieve(urlpath, filename = aqspath)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# How big is your download?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "253.5M cmaq/CCTM_D502a_Linux2_x86_64intel.ACONC.GA12C_20060801.nc4\n",
      " 52.1M aqs/hourly_44201_200608.csv\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "aconcpath = 'cmaq/CCTM_D502a_Linux2_x86_64intel.ACONC.GA12C_20060801.nc4'\n",
    "aqspath = 'aqs/hourly_44201_200608.csv'\n",
    "for path in [aconcpath, aqspath]:\n",
    "    print('%5.1fM' % (os.path.getsize(path)/1024.**2), path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# ANSWERS HIDDEN\n",
    "\n",
    "<div class=\"answers\">\n",
    "253.5M cmaq/CCTM_D502a_Linux2_x86_64intel.ACONC.GA12C_20060801.nc4\n",
    " 52.1M aqs/hourly_44201_200608.csv\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Use aqsraw to read the data\n",
    "\n",
    "1. Read the whole file without options\n",
    "2. add the `--help-format` to see aqsraw option"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "**PNC:/Users/barronh/Development/pseudonetcdf/src/PseudoNetCDF/pncparse.py:419:DtypeWarning:\n",
      "  Columns (17,23) have mixed types. Specify dtype option on import or set low_memory=False.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "PseudoNetCDF.epafiles._aqsraw.aqsraw unknown {\n",
       "dimensions:\n",
       "        time = UNLIMITED // (226 currently) \n",
       "        LAY = 1 ;\n",
       "        points = 1184 ;\n",
       "\n",
       "variables:\n",
       "        float latitude(points);\n",
       "                latitude:units = \"degrees_north\" ;\n",
       "                latitude:standard_name = \"latitude\" ;\n",
       "        float longitude(points);\n",
       "                longitude:units = \"degrees_east\" ;\n",
       "                longitude:standard_name = \"longitude\" ;\n",
       "        float Ozone(time, LAY, points);\n",
       "                Ozone:fill_value = -999.0 ;\n",
       "                Ozone:units = \"Parts per million\" ;\n",
       "                Ozone:standard_name = \"Ozone\" ;\n",
       "        double time(time);\n",
       "                time:units = \"hours since 1900-01-01\" ;\n",
       "                time:standard_name = \"time\" ;\n",
       "\n",
       "\n",
       "// global properties:\n",
       "                :SITENAMES = 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;\n",
       "                :lonlatcoords = 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0,32.525000/-116.976667,32.498333/-117.054722,32.343333/-117.116667,32.500000/-115.388056,32.615278/-115.446944,32.629167/-115.504167,32.633611/-116.618333,32.575000/-115.448611,32.570278/-106.459700,31.735500/-106.395300,31.712200\" ;\n",
       "                :history = \"aqs/hourly_44201_200608.csv;--format=aqsraw aqs/hourly_44201_200608.csv;\" ;\n",
       "}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from PseudoNetCDF import PNC\n",
    "aqsargs = PNC('--format=aqsraw', aqspath)\n",
    "aqsargs.ifiles[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# How can we subset the observations to the modeling domain?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "All formats require a \"path\". Some formats also \n",
      "take extra arguments. All arguments other than \n",
      "the input path must be specified using keyword\n",
      "arguments.\n",
      "\n",
      "Example:\n",
      "pncdump -f aqsraw path\n",
      "\n",
      "Extended example with keywords:\n",
      "pncdump -f aqsraw,timeresolution=hourly,bdate=None,edate=None,rdate=1900-01-01 00:00:00,wktpolygon=None,sampleval=None,verbose=0 path\n",
      "\n",
      "* Any keyword with a non \"<VAL>\" default can be omitted.\n",
      "\n",
      "Hit Y/y to see detailed help\n",
      "y\n",
      "Help on class aqsraw in module PseudoNetCDF.epafiles._aqsraw:\n",
      "\n",
      "class aqsraw(PseudoNetCDF.core._files.PseudoNetCDFFile)\n",
      " |  PseudoNetCDFFile provides an interface and standard set of\n",
      " |  methods that a file should present to act like a netCDF file\n",
      " |  using the Scientific.IO.NetCDF.NetCDFFile interface.\n",
      " |  \n",
      " |  Method resolution order:\n",
      " |      aqsraw\n",
      " |      PseudoNetCDF.core._files.PseudoNetCDFFile\n",
      " |      PseudoNetCDF.core._files.pnc\n",
      " |      builtins.object\n",
      " |  \n",
      " |  Methods defined here:\n",
      " |  \n",
      " |  __init__(self, yearpath, timeresolution='hourly', bdate=None, edate=None, rdate=datetime.datetime(1900, 1, 1, 0, 0), wktpolygon=None, sampleval=None, verbose=0)\n",
      " |      yearpath - path to csv file from AQS\n",
      " |      timeresolution - choices = ['daily', 'hourly'] default = 'hourly', Defaults to hourly'\n",
      " |      bdate - Limit output so that the date starts at YYYY-MM-DD\n",
      " |      edate - Limit output so that the date end YYYY-MM-DD (inclusive)\n",
      " |      rdate - datetime(1900, 1, 1), dest = 'rdate', type = getrdate, help = 'Reference date YYYYMMDD HH:MM:SS')\n",
      " |      wktpolygon - WKT Polygon (default: None) equivalent to \"POLYGON ((-180 -90, 180 -90, 180 90, -180 90, -180 -90))\"\n",
      " |      sampleval - Defaults to \"Sample Measurement\" for hourly and \"Arithmetic Mean\" for daily\n",
      " |      verbose - level of verbosity\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Methods inherited from PseudoNetCDF.core._files.PseudoNetCDFFile:\n",
      " |  \n",
      " |  __add__(self, lhs)\n",
      " |  \n",
      " |  __and__(self, lhs)\n",
      " |  \n",
      " |  __delattr__(self, k)\n",
      " |      Implement delattr(self, name).\n",
      " |  \n",
      " |  __div__(self, lhs)\n",
      " |  \n",
      " |  __eq__(self, lhs)\n",
      " |      Return self==value.\n",
      " |  \n",
      " |  __floordiv__(self, lhs)\n",
      " |  \n",
      " |  __ge__(self, lhs)\n",
      " |      Return self>=value.\n",
      " |  \n",
      " |  __gt__(self, lhs)\n",
      " |      Return self>value.\n",
      " |  \n",
      " |  __le__(self, lhs)\n",
      " |      Return self<=value.\n",
      " |  \n",
      " |  __lt__(self, lhs)\n",
      " |      Return self<value.\n",
      " |  \n",
      " |  __mod__(self, lhs)\n",
      " |  \n",
      " |  __mul__(self, lhs)\n",
      " |  \n",
      " |  __ne__(self, lhs)\n",
      " |      Return self!=value.\n",
      " |  \n",
      " |  __or__(self, lhs)\n",
      " |  \n",
      " |  __pow__(self, lhs)\n",
      " |  \n",
      " |  __repr__(self)\n",
      " |      Return repr(self).\n",
      " |  \n",
      " |  __setattr__(self, k, v)\n",
      " |      Implement setattr(self, name, value).\n",
      " |  \n",
      " |  __sub__(self, lhs)\n",
      " |  \n",
      " |  __xor__(self, lhs)\n",
      " |  \n",
      " |  close(self)\n",
      " |      Does nothing.  Implemented for continuity with Scientific.IO.NetCDF\n",
      " |  \n",
      " |  createDimension(self, name, length)\n",
      " |      name - string name for dimension\n",
      " |      length - maximum length of dimension\n",
      " |  \n",
      " |  createVariable(self, name, type, dimensions, **properties)\n",
      " |      name - string\n",
      " |      type - numpy dtype code (e.g., 'f', 'i', 'd')\n",
      " |      dimensions - tuple of dimension keys that can be\n",
      " |                   found in objects' dimensions dictionary\n",
      " |  \n",
      " |  flush = close(self)\n",
      " |      Does nothing.  Implemented for continuity with Scientific.IO.NetCDF\n",
      " |  \n",
      " |  ncattrs(self)\n",
      " |  \n",
      " |  setncattr(self, k, v)\n",
      " |  \n",
      " |  sync = close(self)\n",
      " |      Does nothing.  Implemented for continuity with Scientific.IO.NetCDF\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Class methods inherited from PseudoNetCDF.core._files.PseudoNetCDFFile:\n",
      " |  \n",
      " |  isMine(*args, **kwds) from PseudoNetCDF.core._files.PseudoNetCDFType\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Static methods inherited from PseudoNetCDF.core._files.PseudoNetCDFFile:\n",
      " |  \n",
      " |  __new__(mcl, *args, **kwds)\n",
      " |      Create and return a new object.  See help(type) for accurate signature.\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data and other attributes inherited from PseudoNetCDF.core._files.PseudoNetCDFFile:\n",
      " |  \n",
      " |  __hash__ = None\n",
      " |  \n",
      " |  ----------------------------------------------------------------------\n",
      " |  Data descriptors inherited from PseudoNetCDF.core._files.pnc:\n",
      " |  \n",
      " |  __dict__\n",
      " |      dictionary for instance variables (if defined)\n",
      " |  \n",
      " |  __weakref__\n",
      " |      list of weak references to the object (if defined)\n",
      "\n",
      "\n",
      "*ifile or pnc are required\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Namespace(attribute=[], convolve=[], coordkeys=['time', 'time_bounds', 'TFLAG', 'ETFLAG', 'latitude', 'latitude_bounds', 'longitude', 'longitude_bounds', 'lat', 'lat_bnds', 'lon', 'lon_bnds', 'etam_pressure', 'etai_pressure', 'layer_bounds', 'layer47', 'layer'], expressions=[], expressionscripts=[], extract=[], extractfile=[], extractmethod='nn', format='netcdf', fromconv=None, help=True, helpformat=['aqsraw'], ifiles=[], inherit=False, inputargs=('--help-format=aqsraw',), mangle=False, masks=[], merge=False, mesh=[], operators=[], pnc=[], reduce=[], removesingleton=[], rename=[], separator=False, slice=[], stack=None, toconv='cf', variables=None, verbose=0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PNC('--help-format=aqsraw')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# wktpolygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x119fed128>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CAgCAySAUoBFCAQC6So8AwHAJCwAAxotQgEYIBQDoIj0CAO0RFgAAdJNQgEYIBQDoGj0C\nAN0kLAAAaJdQgEYIBQDoEj0CAONHWAAAMBpCARohFACgS/QIAEwOYQEAQLOEAjRCKABAV+gRAJgO\nwgIAgO0RCtAIoQAAXaBHAABhAQDA8QkFaIRQAIC26REA4HiEBQAAPUIBGiEUAKBtegQA2A5hAQAw\nbYQCNEIoAECb9AgA0DRhAQAwqYQCNEIoAEBb9AgAMErCAgBg3AkFaIRQAIA26BEAoCuEBQDAuBAK\n0AihAABt0CMAQNcJCwCArhEK0AihAACjpkcAgHEmLAAA2iIUoBFCAQBGSY8AAJNKWAAADJtQgEYI\nBQAYFT0CAEwjYQEA0BShAI0QCgAwKnoEAGCFsAAAGJRQgEYIBQAYBT0CALA1wgIAYDNCARohFABg\n2PQIAMDOCQsAAKEAjRAKADBMegQAYLiEBQAwPYQCNEIoAMAw6REAgHYICwBg8ggFaIRQAIBh0SMA\nAN0jLACA8SUUoBFCAQCGQY8AAIwXYQEAdJ9QgEYIBQBomh4BAJgcwgIA6A6hAI0QCgDQND0CADD5\nhAUAMHpCARohFACgSXoEAGC6CQsAYHiEAjRCKABAU/QIAACbERYAwM4JBWiEUACAJugRAAC2Q1gA\nAFsnFKARQgEAmqBHAABokrAAAO5PKEAjhAIA7JQeAQBgVIQFAEwzoQCNEAoAsBN6BACALhAWADAN\nhAI0QigAwHbpEQAAuk5YAMAkEQrQCKEAANulRwAAGFfCAgDGkVCARggFANgOPQIAwCQSFgDQZUIB\nGiEUAGBQegQAgGkjLACgC4QCNEIoAMAg9AgAAKwQFgAwSkIBGiEUAGAQegQAAE5MWADAMAgFaIRQ\nAICt0iMAALAzwgIAdkIoQCOEAgBshR4BAIDhERYAsBVCARohFADgRPQIAAC0Q1gAwGpCARohFADg\nRPQIAAB0i7AAYDoJBWiEUACA49EjAAAwPoQFAJNNKEAjhAIAbEaPAADAZBAWAEwGoQCNEAoAsBE9\nAgAAk09YADBehAI0QigAwEb0CAAATC9hAUA3CQVohFAAgPX0CAAAsBFhAUC7hAI0QigAwGp6BAAA\nGJSwAGA0hAI0QigAwDI9AgAANElYANAsoQCNEAoAsEyPAAAAoyAsANgeoQCNEAoAkOgRAACgfcIC\ngOMTCtAIoQAAegQAAOgyYQFAj1CARggFAKabHgEAAMaVsACYNkIBGiEUAJhuegQAAJg0wgJgUgkF\naIRQAGB66REAAGCaCAuAcScUoBFCAYDppEcAAAB6hAXAuBAK0AihAMD00SMAAAAnJiwAukYoQCOE\nAgDTR48AAABsn7AAaItQgEYIBQCmix4BAAAYDmEBMGxCARohFACYHnoEAABg9IQFQFOEAjRCKAAw\nHfQIAABAtwgLgEEJBWiEUABgOugRAACA8SAsADYjFKARQgGAyadHAAAAxp+wABAK0AihAMBk0yMA\nAACTTVgA00MoQCOEAgCTS48AAABML2EBTB6hAI0QCgBMLj0CAADAesICGF9CARohFACYTHoEAACA\nQQgLoPuEAjRCKAAwefQIAAAATREWQHcIBWiEUABgsugRAAAARkFYAKMnFKARQgGAyaJHAAAAaJOw\nAIZHKEAjhAIAk0OPAAAA0FXCAtg5oQCNEAoATAY9AgAAwDgSFsDWCQVohFAAYPzpEQAAACaNsADu\nTyhAI4QCAONPjwAAADAthAVMM6EAjRAKAIw3PQIAAADCAqaDUIBGCAUAxpceAQAAgOMTFjBJhAI0\nQigAMJ70CAAAAGyfsIBxJBSgEUIBgPGkRwAAAKB5wgK6TChAI4QCAONHjwAAAMBoCQvoAqEAjRAK\nAIwXPQIAAADdISxglIQCNEIoADA+9AgAAACMB2EBwyAUoBFCAYDxoUcAAABgvAkL2AmhAI0QCgCM\nBz0CAAAAk0tYwFYIBWiEUACg+/QIAAAATCdhAasJBWiEUACg2/QIAAAAsJ6wYDoJBWiEUACg2/QI\nAAAAsFXCgskmFGhBKeXkJD+c5AeTnJdkNsnJSf4pyaEkv5Pkt2ut9w4w57uTPHObSzq/1voX27x2\n+fWFAgAdpUcAAACAJggLJoNQYMRKKecn+a9JzjnBqYeT/ESt9YYtzvvpJF+3emiLS6pJvlUoADCZ\n9AgAAAAwbMKC8SIUGKFSyjOTvDO9uwKOe2r/8ViSn621/qcTzPvgJP+S3hv8g6pJniIUAJg8egQA\nAABok7Cgm4QCI1JKeXySm5I8ML03/WuS65P8anpbBh1Nsi/JxUl+Jr3goCS5N8kzaq3vP87c35bk\nT/uHNcnTaq0fGMoPsvkahAIAHaNHAAAAgC4SFrRLKDAipZQbkpyflUDglbXWqzY59/uSLCQ5qX/+\nLUkevVnHQCnl8iTLb/vUJA+ptd620bnDIhQA6BY9AgAAAIwbYcFwHTlyJNdcc03e97735frrr1//\nbaFAo4vo9Qj8eVa29/mjWut3n+CaX03yc/3DmuTf1Frftcm5b03yk/3DW2qte3e+6sEIBQC6Q48A\nAAAAk0RYsDO33nprXv7yl+faa6/NPffcs9lpExMKnNL2Avp+rP+4fJfAL2/hmrenFwosBwnflWTD\nUCDJN/Ufa5K/2uYaAZgAR48mF164NhBIkquvFggAAAAwnvbsSc47r/e1WpNhwX33JTff3Pt697tX\nxsc5LKi15q1vfWte/OIX5/bbb++PfnOS702y4SY2E6ErdwrcmORJ/cMvpre9z3EXVkrZleRLOcHd\nBaWUk5PckV5XQZL8Yq31FY0sfADuFADoBj0CAAAATDt3FiTHjh3L8573vLztbW/rjzwlyeuTnJfk\nSBKdAkNXSnl0km9Mckat9W1bOP//SPKFnDgUeFySj/cPa5IfqbX+TjOr3jqhAED79AgAAADA5qYl\nLKi15rLLLusHAicleXWSFyY5uX/GUiY5FOjK9kGptd6c5OYBLvnmdcebXftN647/5wCvAcCEOHw4\nufjitWO7dyfXXScQAAAAgGR6tiF661vfuioQuDbJDzf7Ah3XmTsFBlVK+YMky3cG1CT/V631vRuc\n9ytJXtI/vL3WekYp5QlJfjzJ05Kck+TU9OKfv0vye0n+c631Cw2v150CAC05ejS54ILkppvWjr/5\nzclll7WzJgAAABh343hnwa233prHP/7x/Q6B1yZ58QZnTfadAmMXCvS7BA4kee6q4Q/UWr99k/P/\nR5L/M73g4DNJPpbkB07wMrcleWWt9cAJztsyoQBAe/QIAAAAwOh0OSx4znOek3e84x1JnprkT7Oy\nZdBqQoFWlVJOSq8k+Jwk35Pk+UnOzkqXwOEk37rZX0gp5R+TLL/zvvzWz1Z+6JLkHUkuPlHp8VYI\nBQDaoUcAAAAAuqHtsOCOO47ka77ma3L06NEkH07yLZvMIhRoVSnlfUm+Y9XQ6gVfn+T5tdb/vcm1\nD0vyuVXXlP7z30/ypiQfSe+N+jOTXJDk8v5jWXXN62utL8kOCQUARu/w4eSJT0xuu21lbPfu5MYb\nkyc8ob11AQAAACtGFRY85CG/liNH/m2Sc5PclJXPkK832aFAZ4qGj+Nr1x0v/03dluSj6bVBbOYb\n1113V5JLaq3XrjvvH5O8M8k7SykvSvKaVde8qJTye7XW929j7QC05OjR5MIL1wYCSXL11QIBAAAA\n6JJRFRwfOfLB/tG/yeaBwOQbhzsFvpTe9kH3+1b/8ctJfqnW+qoNrn1Kkp9O8qgke5O8sNb621t4\nzdek1zCx/IdzQ631X21j+avnvN+dAocPH972nQKnnXbaTpYDMPH0CAAAAMBk2npYcOe648cluTXJ\n7yXZsKK2bym9t5PXmJg7BTodCpRSTknytPTKgT+f5KuSnJ/kBUmesfrUJL9ea/25hl73Qen91/GQ\nrGwltLfWuu0bVjYKBXaiy39vAG3TIwAAAADTZ31Y8NrXNvqpQKFA20opL0jy6+m9Yb/8xv331Fr/\nsKH5fyPJT/UPa5JLa62/uYP5hAIAI6BHAAAAAEiS0uxWARMTCoxDp8CGaq1vLKWcleQlWdnm56VJ\nGgkFktyYXiiwPPf97hfZqZ1sHwTA/ekRAAAAAJbdcccdX3l+7NixnHHGGf2jTyX56uNcueH2QRNj\nbEOBvquS/EyS3endLfBtpZQH1Vq/1MDc/7Tu+MwG5lzjtNNO0w0A0KArrkhuumnt2EUXJZde2s56\nAAAAgPasf+/17LPPzmc+85kkt6RXQ7uZu4a4qvad1PYCdqLWekeSD2WldPjkJI9uaPr195bc09C8\nAAzBwsL9i4Xn5pKDBxULAwAAAMm5557bf3bTcc+bdJ0KBUopJ5VSdg142fpP9D9o1XwPKqV8XSnl\nvFLK+QPOO7vu+MiA1wMwIocPJxdfvHZs9+7kuusUCwMAAAA9F1xwQf/ZtVnZNX76tB4KlFK+vpTy\nvlLKp5LcneQVA07xkHXHi/15T01yZ5LDST6c3t/0IJ68vMT+40cGvB6AEdAjAAAAAGzFs5/97Oza\ntSu9t3r/ou3ltKb1UCDJ55N8R5Kz09v+5/u3emEp5ZQk52cl1rkjyWeTpNZ6V3qNEcvfe2Qp5TED\nzPsDq679cpIbtrouAEZHjwAAAACwFWeeeWYuvPDC/tGLkhxrczmtaT0UqLX+c1Y+hV+SPK6U8vQt\nXv7cJMuV0TXJ79da7131/ev7cy6/uf+CLc77vCRfs2re36q1fnGL1wIwInoEAAAAgEFcddVV2bNn\nT5I/T/JrbS+nFa2HAn0Hs/LmfUnyhlLKcXeBLqU8KcmvrLqmJnnNutPemuS+5UuSPLeUckGOo5Ty\nLUlevWreL/ePAegQPQIAAADAoM4666y87nWv6x9dkeSdbS6nFV0JBd6e5C+z8ub+viTvL6XMrz+x\nX0Z8WZI/SXLqqmt+vda6Zt//Wusnkrx51TmnJPm9UsqPbrSIUsrFSd6bZPeqa36x1vrJJn5IAJqh\nRwAAAADYrksvvTSXXHJJep8nvzDJ6zJNWwmVWrvRslxKOTvJn6W3bc/ypg81yQfSCwzuTvLIJN+Z\n5BFZe4fA7yb5obrBD1NKeVCSP0qve2D13Qh/l16w8PkkD0vyXUnOWjfvf661XtLQzzeTfgnyssXF\nxczMzDQxPcBUeeEL779t0EUXJddcY9sgAAAA4MSOHTuWxz72ebn55rf1R56S5PVJzktyJMns+ktm\na61LI1zi0HQmFEiSUsqjkvx2kidmJRjYTO1/vTrJv6u13rfZiaWUByf5L0meuTx0gnnvS3Kg1vrz\nW1z6CQkFAJqxsJDs3792bG4uOXTItkEAAADA1nzoQ8lTnlKTvC290uHb+9/55iTfm+Sq9ZcIBYal\nlHJKkp9K8sIkezc57WiS9yT5D7XW/znA3D+c3kZR525yypfT2z7olbXWv9zyorf22kIBgB06fDh5\n4hPXbhu0e3dy4422DQIAAAC25tix5MlPTj760eWRW3PKKS/PySdfm3vuuWezy4QCo1BK2ZfkSend\nq/HA9Lb6OZzkhlrr3TuY9+Hp3Q/y8CSnp3c/yOeSfLDW+sWdrnuT1xQKAOzA0aPJBRckN920dvzN\nb04uu6ydNQEAAADj5zd+I3nBC9aOve51yU/8xJFcc801+eM//uO85z3vWX+ZUIDBCAUAdkaPAAAA\nALBTi4vJvn3Jv/zLytj8fO+ugQc8oHe8tLSU2dnJ7RQ4qe0FAMCJLCzcPxCYm0sOHhQIAAAAAFv3\nspetDQSS5I1vXAkEpoFQAIBOO3w4ufjitWO7dyfXXadYGAAAANi6D30o+c3fXDt20UXJt397O+tp\ni1AAgM46ejS58MK1xcJJcvXVioUBAACArTt27P49Anv2JK95TTvraZNQAIDOuuKK+xcLX3RRcuml\n7awHAAAAGE9velOvN2C1V74yecQjWllOqxQNj4iiYYDBLCwk+/evHZubSw4dsm0QAAAAsHVbKRde\nTdEwAIyYHgEAAACgKcqF1xIKANApegQAAACApigXvj+hAACdokcAAAAAaIJy4Y0JBQDojIWF5MCB\ntWNzc8nBg0kp7awJAAAAGE/KhTcmFACgE/QIAAAAAE1ZXEyuvHLt2Px8cvnl7aynS4QCALROjwAA\nAADQJOXKhiVZAAAgAElEQVTCmxMKANA6PQIAAABAU5QLH59QAIBW6REAAAAAmqJc+MSEAgC0Ro8A\nAAAA0CTlwicmFACgFXoEAAAAgCYpF94aoQAArdAjAAAAADRJufDWCAUAGDk9AgAAAECTlAtvnVAA\ngJHSIwAAAAA0SbnwYIQCAIyMHgEAAACgacqFByMUAGBk9AgAAAAATVIuPDihAAAjoUcAAAAAaJpy\n4cEJBQAYOj0CAAAAQNOUC2+PUACAodIjAAAAADRNufD2CQUAGCo9AgAAAEDTlAtvX6m1tr2GqVBK\nmUmyuHpscXExMzMzLa0IYPgWFpL9+9eOzc0lhw7ZNggAAADYnsXFZN++tV0C8/O9kKCJLoGlpaXM\nzs6uH56ttS7tfPb2uVMAgKHQIwAAAAAMg3LhnREKANA4PQIAAADAMCgX3jmhAACN0yMAAAAANE25\ncDOEAgA0amEhOXBg7djcXHLwYFJKO2sCAAAAxp9y4WYIBQBojB4BAAAAYBgWF5Mrr1w7Nj+fXH55\nO+sZZ0IBABqhRwAAAAAYFuXCzREKANAIPQIAAADAMCgXbpZQAIAd0yMAAAAADINy4eYJBQDYET0C\nAAAAwLAoF26eUACAbdMjAAAAAAyLcuHhEAoAsG16BAAAAIBhUS48HEIBALZFjwAAAAAwLMqFh0co\nAMDA9AgAAAAAw6JceLiEAgAMRI8AAAAAMEzKhYdLKADAQPQIAAAAAMOiXHj4hAIAbJkeAQAAAGCY\nlAsPn1AAgC3RIwAAAAAMk3Lh0RAKAHBCegQAAACAYVIuPDpCAQBOSI8AAAAAMEzKhUen1FrbXsNU\nKKXMJFlcPba4uJiZmZmWVgSwNQsLyf79a8fm5pJDh2wbBAAAAOzc4mKyb9/aLoH5+V5I0EaXwNLS\nUmZnZ9cPz9Zal0a/mua5UwCATekRAAAAAIZNufBoCQUA2JAeAQAAAGDYlAuPnlAAgA3pEQAAAACG\nSblwO4QCANzPwkJy4MDasbm55ODBpJR21gQAAABMFuXC7RAKALCGHgEAAABg2BYXkyuvXDs2P59c\nfnk765kmQgEAvkKPAAAAADAKyoXbIxQA4Cv0CAAAAADDply4XUIBAJLoEQAAAACGT7lw+4QCAOgR\nAAAAAEZCuXD7hAIAU06PAAAAADAKyoW7QSgAMOX0CAAAAACjoFy4G4QCAFNMjwAAAAAwCsqFu0Mo\nADCl9AgAAAAAo6BcuFuEAgBTSI8AAAAAMCrKhbtFKAAwhfQIAAAAAKOgXLh7hAIAU0aPAAAAADAq\nyoW7RygAMEX0CAAAAACjoly4m4QCAFNCjwAAAAAwKsqFu0soADAl9AgAAAAAo6JcuLtKrbXtNUyF\nUspMksXVY4uLi5mZmWlpRcA0WVhI9u9fOzY3lxw6ZNsgAAAAoFmLi8m+fWu7BObneyHBOHQJLC0t\nZXZ2dv3wbK11qY31NM2dAgATTo8AAAAAMErKhbtNKAAwwfQIAAAAAKOkXLj7hAIAE0yPAAAAADAq\nyoXHg1AAYEItLCQHDqwdm5tLDh5MSmlnTQAAAMDkUi48HoQCABNIjwAAAAAwSouLyZVXrh2bn08u\nv7yd9bA5oQDAhNEjAAAAAIyacuHxIRQAmDB6BAAAAIBRUi48XoQCABNEjwAAAAAwSsqFx49QAGBC\n6BEAAAAARk258PgRCgBMAD0CAAAAwKgpFx5PQgGACaBHAAAAABg15cLjSSgAMOb0CAAAAACjplx4\nfAkFAMaYHgEAAABg1JQLjzehAMCY0iMAAAAAtEG58HgTCgCMKT0CAAAAwKgpFx5/QgGAMaRHAAAA\nAGiDcuHxJxQAGDN6BAAAAIA2KBeeDEIBgDGiRwAAAABog3LhySEUABgjegQAAACANigXnhyl1tr2\nGqZCKWUmyeLqscXFxczMzLS0ImDcLCwk+/evHZubSw4dsm0QAAAAMDyLi8m+fWu7BObneyHBJHYJ\nLC0tZXZ2dv3wbK11qY31NM2dAgBjQI8AAAAA0BblwpNFKADQcXoEAAAAgLYoF548QgGAjtMjAAAA\nALRBufBkEgoAdNjCQnLgwNqxubnk4MGklHbWBAAAAEwH5cKTSSgA0FF6BAAAAIC2LC4mV165dmx+\nPrn88nbWQ3OEAgAdpEcAAAAAaJNy4cklFADoID0CAAAAQFuUC082oQBAx+gRAAAAANqiXHjyCQUA\nOkSPAAAAANAm5cKTTygA0BF6BAAAAIA2KReeDkIBgI7QIwAAAAC0SbnwdBAKAHSAHgEAAACgTcqF\np4dQAKBlegQAAACANikXni5CAYAW6REAAAAA2qZceLoIBQBapEcAAAAAaJNy4ekjFABoiR4BAAAA\noG3KhaePUACgBXoEAAAAgLYpF55OQgGAEdMjAAAAALRNufD0EgoAjJgeAQAAAKBtyoWnV6m1tr2G\nqVBKmUmyuHpscXExMzMzLa0IaMPCQrJ//9qxubnk0CHbBgEAAACjsbiY7Nu3tktgfr4XEugSSJaW\nljI7O7t+eLbWutTGeprmTgGAEdEjAAAAAHSBcuHpJhQAGAE9AgAAAEAXKBdGKAAwAnoEAAAAgLYp\nFyYRCgAM3cJCcuDA2rG5ueTgwaSUdtYEAAAATB/lwiRCAYCh0iMAAAAAdMHiYnLllWvH5ueTyy9v\nZz20RygAMCR6BAAAAICuUC7MMqEAwJDoEQAAAAC6QLkwqwkFAIZAjwAAAADQBcqFWU8oANAwPQIA\nAABAVygXZj2hAECD9AgAAAAAXaFcmI0IBQAapEcAAAAA6ArlwmxEKADQED0CAAAAQFcoF2YzQgGA\nBugRAAAAALpCuTDHIxQA2CE9AgAAAECXKBfmeIQCADukRwAAAADoCuXCnIhQAGAH9AgAAAAAXaJc\nmBMRCgBskx4BAAAAoEuUC7MVQgGAbdAjAAAAAHSJcmG2qpOhQCnl5FLKhaWU3yqlfLqUckcp5Uul\nlM+UUt5ZSrmolHLKNud+RCnlFaWUD5ZSlkop95RS/qGU8uH++N6mfx5g8ugRAAAAALpEuTBbVWqt\nba9hjVLK+Un+a5JzTnDq4SQ/UWu9YYC5fz7JVUl2Hee0Y/1zfrHWet9W597Ca88kWVw9tri4mJmZ\nmaZeAhiRhYVk//61Y3NzyaFDtg0CAAAARm9xMdm3b22XwPx8LyTQJTC4paWlzM7Orh+erbUutbGe\npnXqToFSyjOT/FmSRyWpx/lKkr1J3l9K+ektzv2GJK9O8sD+0GbznpTklUmu3dlPA0wiPQIAAABA\n1ygXZhCdCQVKKY9P7434k5OU/vD1Sb4zyRlJHpTkm5IcSHJvem/in5zkQCnlaSeY+6eTPL9/TUny\nxSRXpHc3wu70QoiXJrmt//2aZH8p5RWN/YDA2NMjAAAAAHSNcmEG1Zntg0opNyQ5Pytvyr+y1nrV\nJud+X5KF9EKNkuSWJI+utd67wbmzSf4+yWn9c48keWqt9eYNzj0nyQeSfHX/3KNJHltrPdzAz2f7\nIBhzL3xhcuDA2rGLLkquuSYpZeNrAAAAAIbl2LHkyU9e2yWwZ0/yt3+rS2AnbB80Av0egW/tH9Yk\nf7RZIJAktdbrk7whK3cUnJXkBzY5/Yokp2clbPjJjQKB/ryfSvKDWdlO6AHpbSUETLmFhfsHAnNz\nycGDAgEAAACgHcqF2Y5OhAJJfqz/uPzW2i9v4Zq39x+Xb3X4rvUnlFIekOQ5q875636gsKla641J\n3tlfS0nyI6WU07ewHmBC6REAAAAAumZxMbnyyrVj8/PJ5Ze3sx7GR1dCgfOy8un8LyZ5/xau+bt1\nx4/a4JynJnlo/3lN8ltbXM9/W/V8V5JnbvE6YMLoEQAAAAC6SLkw23VK2wtIklrrt5RSHp3kG5Oc\nUbdWdPCgLZzz9P7j8tZBf7LFJf1pVu4uSJJ/nbVBATAlrrgiuemmtWMXXZRcemk76wEAAABQLsxO\ndCIUSJL+Pv8b7vW/iW9ed7zRtas/x1uT/NUW13JbKeWWJF+XXqDwpAHWBUwIPQIAAABA1xw7lrzg\nBWvH9uxJXvOadtbD+OnK9kHb8ZL+4/Jbc7+7wTmPycon/j9Xa717gPk/vWruvaV4CxCmiR4BAAAA\noIuUC7NTYxcKlFJ2lVIOJvnuVcMfrLW+d4PTH95/rEk+N+BL/eOq56ckediA1wNjSo8AAAAA0EXK\nhWlCZ7YP2kwp5aQkD0xyTpLvSfL8JGdn5Q6Aw0l+eIPrdiXZs+q8Lwz40v+87vghSf6/AecAxpAe\nAQAAAKCLlAvThM6HAknem+Q7Vh3XrLzRf32S59dalza47vR1x7cP+Lp3rDu2YQhMAT0CAAAAQBcp\nF6Yp47B90NeuOy79ry8m+Wg2/xl2rTv+8oCvu/58eRtMOD0CAAAAQBcpF6ZJ43CnwNdm5c6A1c5I\n8u+T/N+llF+qtb5q3fdPXnd834Cvu/78xgOUO++8M6eeeuq2rj3ttNMaXg1MNz0CAAAAQFcpF96e\nO++8c6TXjYtOhwKllFOSfH+SjyX5fJKvSnJ+khckeUb/tFOSvLKU8tBa68+tuvzeddOtDwlOZP2f\nzT0DXn9Ce/fu3fa1tW6UkwDbpUcAAAAA6CLlwtt3+unrd5gn6fj2QbXWe2utf1RrXay1Hqu1Hqm1\nXl9r/Z4kP5veNkLLfqaU8oxVx3etm273gC+//vzGQwGgG/QIAAAAAF2lXJimdfpOgeOptb6xlHJW\nkpdkZXuhlyb5w/73byulHMtK8PHgAV9i/fmf3+5aN3P48OHMzMw0PS0wAD0CAAAAQFcpF96ZO+64\nY1vXLS0t7WiXl64b21Cg76okP5Pep/pLkm8rpTyo1vql/vcXkzys/71B333/6nXHiztZ6EZOO+00\n3QDQIj0CAAAAQFcpF9657b73etdd6zehmSyd3j7oRGqtdyT5UFa2ETo5yaNXnXJ41fceOeD0q89f\nrLXeva1FAp2lRwAAAADoKuXCDEunQoFSykmllF0DXvZP644ftOr5x1c9/6pSypbuFiillPTChdr/\n+vjxrwDGjR4BAAAAoKuUCzNMrYcCpZSvL6W8r5TyqSR3J3nFgFM8ZN3x6m1+blz3vSdvcc75JKur\nqT884JqADtMjAAAAAHSZcmGGqfVQIL0C3+9IcnZ62/98/1YvLKWckuT8rBQN35Hks6tOeW//cfn7\n37vFqZfXsPx54T/c6pqAbtMjAAAAAHSZcmGGrfVQoNb6z0k+0j8sSR5XSnn6Fi9/bpIzlqdK8vu1\n1ntXzf0PSf68P29JclEp5auON2Ep5YFJLstKkHBrrfUDW1wP0HF6BAAAAICuUi7MKLQeCvQdTO9N\n+9p/fEMp5bibeJRSnpTkV1ZdU5Ns9Otxdf+xJnlwkrefYC0H0rtrYXnOq497NjA29AgAAAAAXaZc\nmFHoSijw9iR/mZU34vcleX8pZX79if0y4suS/EmSU1dd8+u11o+sPz/JdUluyspWQM8spVxXSjlj\n9UmllF2llN9I8rys3CXw90nesNMfDmifHgEAAACgy5QLMyqntL2AJKm13ldK+ZEkf5bka9J7A/+J\nST5WSvlAeoHB3UkemeQ7kzwia+8Q+N0kL9pk7lpKeXaSG5Kc2R/+oSTfXUp5T5Jbkjw8yfcleeiq\neb+U5Fm11i83/gMDI6VHAAAAAOg65cKMSidCgSSptX6mlPK0JL+dXiCw3APwr/pfG7kvyauT/Lta\na93knNRaby6lfGeS/57kYf15T0/yo5tccluS/bXWj27yfWCM6BEAAAAAuky5MKPUle2DkiS11k8n\nOT/JzyX5dHqf2t/o654k70rypFrr/1NrvW8Lc/91kscmeWOSL24y79Ek/2+Sb6i1/kmjPxzQCj0C\nAAAAQJcpF2bUOnOnwLJa673p7eP/hlLKviRPSjKb5IFJPp/kcJIbaq13b2PuLyb52VLKi5N8e5K9\n6W0ZdFeST/Xn/ZfjTAGMET0CAAAAQNcpF2bUOhcKrFZr/V9J/tcQ5v1ykj9qel6gO/QIAAAAAF2n\nXJg2dGr7IICm6BEAAAAAuk65MG0QCgATR48AAAAA0HXKhWmLUACYKHoEAAAAgK5TLkybhALAxNAj\nAAAAAIwD5cK0SSgATAw9AgAAAEDXKRembUIBYCLoEQAAAADGgXJh2iYUAMaeHgEAAABgHCgXpguE\nAsBY0yMAAAAAjAPlwnSFUAAYa3oEAAAAgHGgXJiuKLXWttcwFUopM0kWV48tLi5mZmampRXB+FtY\nSPbvXzs2N5ccOmTbIAAAAKA7FheTffvWdgnMz/dCAl0C3bO0tJTZ2dn1w7O11qU21tM0dwoAY0mP\nAAAAADAulAvTJUIBYOzoEQAAAADGhXJhukYoAIwdPQIAAADAOFAuTBcJBYCxsrCQHDiwdmxuLjl4\nMCmlnTUBAAAAbES5MF0kFADGhh4BAAAAYFwsLiZXXrl2bH4+ufzydtYDy4QCwFjQIwAAAACME+XC\ndJVQABgLegQAAACAcaFcmC4TCgCdp0cAAAAAGBfKhek6oQDQaXoEAAAAgHGiXJiuEwoAnaVHAAAA\nABgnyoUZB0IBoLP0CAAAAADjRLkw40AoAHSSHgEAAABgnCgXZlwIBYDO0SMAwP/P3r0H6Z7X9YF/\nfzmDMzBnMALdQoSRQTmt2wmX7A5aMBvj4iwuxBCOyLggWjgYXKiz4ZJEUkciEJKqhTjuAbEOskSz\nYSwujk3F9UaKy+5CEDlrIsW6UCgDQ0rJ0yMyMMPVw3f/eLqn++nTp7uf7l8/v9vrVdV1+vn27/Lt\ngb9+7/783gAA0CfKhekToQDQKXoEAAAAgL5RLkyfCAWATtEjAAAAAPSJcmH6RigAdIYeAQAAAKBv\nlAvTN0IBoBP0CAAAAAB9o1yYPhIKAK3TIwAAAAD0jXJh+kooALROjwAAAADQN8qF6atSa217D6NQ\nSllKMtm+NplMsrS01NKOoBvW1pLTp2fXTp1KLlzw2iAAAACgmyaTZGVltktgdXUaEugS6L/19fUs\nLy/vXF6uta63sZ+mmRQAWqNHAAAAAOgj5cL0mVAAaIUeAQAAAKCPlAvTd0IBoBV6BAAAAIC+US7M\nEAgFgIVbW0vOnZtdO3UqOX8+KaWdPQEAAADsR7kwQyAUABZKjwAAAADQR5NJcvbs7NrqanLmTDv7\ngcMSCgALo0cAAAAA6CvlwgyFUABYGD0CAAAAQB8pF2ZIhALAQugRAAAAAPpIuTBDIxQAjp0eAQAA\nAKCvlAszNEIB4FjpEQAAAAD6SrkwQyQUAI6VHgEAAACgr5QLM0RCAeDY6BEAAAAA+kq5MEMlFACO\nhR4BAAAAoK+UCzNkQgGgcXoEAAAAgD5TLsyQCQWAxukRAAAAAPpKuTBDJxQAGqVHAAAAAOgz5cIM\nnVAAaIweAQAAAKDPlAszBkIBoBF6BAAAAIA+Uy7MWAgFgEboEQAAAAD6TLkwY1FqrW3vYRRKKUtJ\nJtvXJpNJlpaWWtoRNGdtLTl9enbt1KnkwgWvDQIAAAC6bzJJVlZmuwRWV6chgS6B8VlfX8/y8vLO\n5eVa63ob+2maSQHgSPQIAAAAAH2nXJgxEQoAh6ZHAAAAAOg75cKMjVAAODQ9AgAAAECfKRdmjIQC\nwKGsrSXnzs2unTqVnD+flNLOngAAAADmoVyYMRIKAHPTIwAAAAD03WSSnD07u7a6mpw5085+YFGE\nAsBc9AgAAAAAQ6BcmLESCgBz0SMAAAAA9J1yYcZMKAAcmB4BAAAAoO+UCzN2QgHgQPQIAAAAAEOg\nXJixEwoA+9IjAAAAAAyBcmEQCgAHoEcAAAAAGALlwiAUAPahRwAAAAAYAuXCMCUUAC5LjwAAAAAw\nBMqFYYtQANiVHgEAAABgKJQLwxahALArPQIAAADAECgXhllCAeASegQAAACAoVAuDLOEAsAMPQIA\nAADAUCgXhksJBYB76REAAAAAhkK5MOxOKADcS48AAAAAMBTKhWF3pdba9h5GoZSylGSyfW0ymWRp\naamlHcGstbXk9OnZtVOnkgsXvDYIAAAA6JfJJFlZme0SWF2dhgS6BNjP+vp6lpeXdy4v11rX29hP\n00wKAHoEAAAAgEFRLgyXJxSAkdMjAAAAAAyJcmHYm1AARk6PAAAAADAUyoVhf0IBGLG1teTcudm1\nU6eS8+eTUtrZEwAAAMBhKReG/QkFYKT0CAAAAABDMpkkZ8/Orq2uJmfOtLMf6CqhAIyQHgEAAABg\naJQLw8EIBWCE9AgAAAAAQ6JcGA5OKAAjo0cAAAAAGBLlwjAfoQCMiB4BAAAAYGiUC8N8hAIwEnoE\nAAAAgKFRLgzzEwrASOgRAAAAAIZGuTDMTygAI6BHAAAAABga5cJwOEIBGDg9AgAAAMDQKBeGwxMK\nwIDpEQAAAACGSLkwHJ5QAAZMjwAAAAAwNMqF4WiEAjBQegQAAACAIVIuDEcjFIAB0iMAAAAADJFy\nYTg6oQAMjB4BAAAAYIiUC0MzhAIwMHoEAAAAgCFSLgzNKLXWtvcwCqWUpSST7WuTySRLS0st7Ygh\nWltLTp+eXTt1KrlwwWuDAAAAgP6aTJKVldkugdXVaUigS4Cmra+vZ3l5eefycq11vY39NM2kAAyE\nHgEAAABgqJQLQ3OEAjAAegQAAACAoVIuDM0SCsAA6BEAAAAAhki5MDRPKAA9t7aWnDs3u3bqVHL+\nfFJKO3sCAAAAaIJyYWieUAB6TI8AAAAAMFSTSXL27Oza6mpy5kw7+4GhEApAT+kRAAAAAIZMuTAc\nD6EA9JQeAQAAAGColAvD8REKQA/pEQAAAACGSrkwHC+hAPSMHgEAAABgyJQLw/ESCkCP6BEAAAAA\nhky5MBw/oQD0iB4BAAAAYMiUC8PxEwpAT+gRAAAAAIZMuTAshlAAekCPAAAAADBkyoVhcYQC0HF6\nBAAAAIChUy4MiyMUgI7TIwAAAAAMmXJhWCyhAHSYHgEAAABg6JQLw2IJBaCj9AgAAAAAQ6dcGBZP\nKAAdpEcAAAAAGDrlwtAOoQB0kB4BAAAAYOiUC0M7Sq217T2MQillKclk+9pkMsnS0lJLO6Kr1taS\n06dn106dSi5c8NogAAAAYBgmk2RlZbZLYHV1GhLoEqBt6+vrWV5e3rm8XGtdb2M/TTMpAB2iRwAA\nAAAYA+XC0B6hAHSEHgEAAABgDJQLQ7uEAtARegQAAACAoVMuDO0TCkAHrK0l587Nrp06lZw/n5TS\nzp4AAAAAmqZcGNonFICW6REAAAAAxmAySc6enV1bXU3OnGlnPzBWQgFokR4BAAAAYCyUC0M3CAWg\nRXoEAAAAgDFQLgzdIRSAlugRAAAAAMZAuTB0i1AAWqBHAAAAABgL5cLQLUIBWDA9AgAAAMBYKBeG\n7hEKwILpEQAAAADGQrkwdI9QABZIjwAAAAAwFsqFoZuEArAgegQAAACAsVAuDN3VuVCgTP3dUsob\nSyl/VEpZL6V8rZTyF6WU/6+U8iullGeWUg6891LKO0sp3zjk1+OP8/dlHPQIAAAAAGOiXBi664q2\nN7BdKeWGJG9O8qhdfvwtG18rSX4iySdLKc+vtb77AJd+dJK6/VYH3FLd/xDYnx4BAAAAYCyUC0O3\ndWZSoJTy3CTvTfKdmT6M3+/rkUl+t5Ty0/tc9wFJHrFj+SDX3/yCI9EjAAAAAIyJcmHotk6EAqWU\n70/yxkz3s/mY9D1Jnp7kIUm+Kcm3Jvn7G+vJ9IH9iSSvL6U8eY/LP2bzNhv//p1a64kDfl1Ra/2D\n5n5TxkaPAAAAADAmyoWh+1oPBUopJ5L8YqYP+EumD/v/aa31xlrrv6u1rtdaL9Za76y1/mat9cYk\nP7ft2Psk+aVSyuWyxsfu+PyR4/lNYJYeAQAAAGBMlAtDP7QeCiR5SpLv3vi+Jrm11vqavU6otb46\nyVszDQZKpq8H+pHLHP6Ybd/fUWu96zLHQaP0CAAAAABjolwY+qELocAzNv7dfL3PPz/gea/e+Hfz\nvf9Pvcxxj9123B/NtzU4HD0CAAAAwJgoF4b+6EIo8D3bvv9UrfUTBzmp1vrHSb6w8bEkObXzmI1X\nE61mKzgQCnDs9AgAAAAAY6NcGPqjC6HA55L8eZKLSW6f89yvbPv+r+3y85UkV2ZrCkEowLHSIwAA\nAACMjXJh6Jcr2t5ArfUJyb1/1X/gv6MupXxLkqXNyyRZ3+WwnSXD/+kwe4SD0iMAAAAAjIlyYeif\nLkwKJElqrRdrrZ/f/8h7/XC2JgCS5GO7HLO9ZPjuWusnSymPLqW8tpTy4VLK50opXymlfKaU8u5S\nyktKKQ881C/A6OkRAAAAAMZGuTD0T6m17n9Ux5RS7pvko0m+M9NgoCb54VrrO3cc93tJbtz4+aeS\nfCTJ0/a5/F1JXlFrPbfPcfPueSnJZPvaZDLJ0tLSZc6gT26/PXnc42ZfG3TVVcmHPuS1QQAAAMAw\nTSbJyspsl8Dq6jQk0CVAn62vr2d5eXnn8nKtdbe31fRO668POqRXJHlUtgqE70jyW7sc95htx1y3\n8bVfCvKAJL9QSnlckufWPqYmLJQeAQAAAGCMlAtDP3Xm9UEHVUp5epKXZfpwf3NK4GdrrV/fcdxD\nkuyMc2qS3850WuDhmZYQf1uSm5K8f/PUjeOek+Q1x/NbMCR6BAAAAICxUS4M/dWr1weVUp6U5Dcz\nfZi/+fB+rdb6jF2OfXKS38lWePClJDfXWt+2x/VfkmSzBmXz+k+qtb6vgb17fdAAra0lp0/Prp06\nlVy4MC3VAQAAABiaixeT66+f7RK45prkYx/TJcAweH1QR5RSfiDJOzMNBDZ9IslzL3PKF5PcmuSR\nmb426EW11rfvdY9a6y2llIcmeWm2XjP0qiR/+whbv6x77rkn97///Q917tVXX93wbpjX7bcnz93x\n/76rrkre8Q6BAAAAADBcyoXpi3vuuWeh5/VFLyYFSinPSPKWJJtvJCtJ/izJDbXWTzV8r/tl2lHw\nwEQEg2wAACAASURBVGxNC1xXa73jiNe9ZFLgKPrwv9uQfe1ryQ03XPraoF/+5eSnfqqdPQEAAAAc\nN+XC9EkppcnLDWZSoPOdAqWUf5jkrbk0EPj+pgOBJKm1fjnJOzbus+lJTd+HftMjAAAAAIyRcmHo\nv86+PqiUcp8kr0vygmz1AiTJ7UlurLV+8hhv/6EkP52tVwhddxw3uf3223UK9NDaWnLu3Ozaysp0\ndK7Z8BEAAACgO5QL0zd33333oc5bX1/PddcdyyPhTuhkKFBKuSbJ25M8OVuBQE3y0SQ/WGv982Pe\nwn/Z8fnBx3GTq6++WjdAz1yuR+Dtb09OnmxnTwAAAADH7eLF5IUvnF275prkta9tZz9wEId99vql\nL32p4Z10S+dCgY2i399N8jczGwi8L8nTa61fWMQ2dnz+6gLuScd97WvJTTcld901u/761yePfnQ7\newIAAABYBOXCMBydCgVKKY9I8t4k12Y2EPi1JD9Za/36HNe6X5LlJN+a5D611t+fYyvLOz7fOce5\nDNRuPQLPfnZy883t7AcAAABgESaT5OzZ2bXV1eTMmXb2AxxNZ0KBUsrDM50GePjmUqaBwL+stb58\nzmvdP8n2F0Z9Jsm3z3GJ63fs4Q/nuT/Dc7kegfPn9QgAAAAAw6ZcGIblPm1vIElKKVdn+sqg7YHA\nxSQvmDcQSJJa65eS/Gm2ioIfVkr5rgPu5YokT9t27teTfGDePTAcegQAAACAsVIuDMPTiVAgyRuS\nfPfG9yXJXyV5Tq31jUe45v+Rrb/0T5IX7nHsds9P8m0b39ckb11QjwEdpEcAAAAAGCvlwjBMrYcC\npZSnJfnxzHYIvKjW+tYjXvp/S/KNzdsk+QellBv22cv3JHnNtr18feMzI6VHAAAAABgr5cIwTK2H\nAklekdlA4Ddqrb901IvWWv/fJL+87bpXJPmtUsr/uNvxpZTnJvn3Sa7ads6ra61/fNS90E96BAAA\nAICxUi4Mw9Vq0XAp5cYkj8n0Afzma35+uJTyjcufdVm11npix9pLN67/vZk+6D+Z5NZSys8leW+S\nv0jykCQ/kOTazIYTv1prffUh9sEA6BEAAAAAxky5MAxXq6FAkqdu/Hssf3dda/1yKeV/SPJvkvy9\nbT86tfG1m4tJztVa/9Fx7Inu0yMAAAAAjJlyYRi2tl8f9B3ZmhJo4usStdYv1FqfnuSmJP/PHud+\nLclvJ/legcC46REAAAAAxkq5MAxfq5MCtdYfWuC9fj3Jr5dSHprkCUkemunrhO5M8mdJ3l9r/cKi\n9kM36REAAAAAxky5MAxfqXXXP7CnYaWUpSST7WuTySRLS0st7Yidbr89edzjZl8bdNVVyYc+5LVB\nAAAAwPBNJtM/jtzeJbC6Og0JdAkwJuvr61leXt65vFxrXW9jP01r+/VB0Al6BAAAAICxUy4M4yAU\ngOgRAAAAAMZNuTCMh1CA0dMjAAAAAIyZcmEYF6EAo3b77clznzu7dtVVydvfnpw82c6eAAAAABZJ\nuTCMi1CA0dIjAAAAAIzdZJKcPTu7trqanDnTzn6A4ycUYLT0CAAAAABjp1wYxkcowCjpEQAAAADG\nTrkwjJNQgNHRIwAAAACMnXJhGC+hAKOiRwAAAABAuTCMmVCAUdEjAAAAAIydcmEYN6EAo6FHAAAA\nAEC5MIydUIBR0CMAAAAAoFwYEAowAnoEAAAAAJQLA1NCAQZPjwAAAACAcmFgqtRa297DKJRSlpJM\ntq9NJpMsLS21tKNxWFtLTp+eXVtZSS5c8NogAAAAYDwmk+kzke1dAqur05BAlwDMWl9fz/Ly8s7l\n5Vrrehv7aZpJAQZLjwAAAADAlHJhYJNQgEHSIwAAAAAwpVwY2E4owCDpEQAAAABQLgxcSijA4Kyt\nJefOza6trCTnzyeltLMnAAAAgDYoFwZ2EgowKHoEAAAAAKYmk+Ts2dm11dXkzJl29gN0g1CAwdAj\nAAAAALBFuTCwG6EAg6FHAAAAAGBKuTBwOUIBBkGPAAAAAMCUcmFgL0IBek+PAAAAAMAW5cLAXoQC\n9JoeAQAAAIAtyoWB/QgF6DU9AgAAAABblAsD+xEK0Ft6BAAAAAC2KBcGDkIoQC/pEQAAAADYolwY\nOCihAL2jRwAAAABglnJh4KCEAvSOHgEAAACALcqFgXkIBegVPQIAAAAAs5QLA/MQCtAbegQAAAAA\nZikXBuYlFKAX9AgAAAAAzFIuDByGUIBe0CMAAAAAMEu5MHAYpdba9h5GoZSylGSyfW0ymWRpaaml\nHfXH2lpy+vTs2spKcuGC1wYBAAAA4zSZTJ+PbO8SWF2dhgS6BOBo1tfXs7y8vHN5uda63sZ+mmZS\ngE7TIwAAAABwKeXCwGEJBegsPQIAAAAAl1IuDByFUIDO0iMAAAAAMEu5MHBUQgE6aW0tOXdudm1l\nJTl/PimlnT0BAAAAtE25MHBUQgE6R48AAAAAwKUmk+Ts2dm11dXkzJl29gP0k1CATtEjAAAAALA7\n5cJAE4QCdIoeAQAAAIBLKRcGmiIUoDP0CAAAAABcSrkw0CShAJ2gRwAAAABgd8qFgSYJBWidHgEA\nAACA3SkXBpomFKB1egQAAAAAdqdcGGiaUIBW6REAAAAA2J1yYeA4CAVojR4BAAAAgN0pFwaOi1CA\nVugRAAAAALg85cLAcREK0Ao9AgAAAAC7Uy4MHCehAAunRwAAAADg8pQLA8dJKMBC6REAAAAAuDzl\nwsBxEwqwMHoEAAAAAC5PuTCwCEIBFkaPAAAAAMDlKRcGFqHUWtvewyiUUpaSTLavTSaTLC0ttbSj\nxVpbS06fnl1bWUkuXPDaIAAAAIDJZPqsZHuXwOrqNCTQJQCLtb6+nuXl5Z3Ly7XW9Tb20zSTAhw7\nPQIAAAAAe1MuDCyKUIBjpUcAAAAAYG/KhYFFEgpwrPQIAAAAAFyecmFg0YQCHJu1teTcudm1lZXk\n/PmklHb2BAAAANAlyoWBRRMKcCz0CAAAAADsbTJJzp6dXVtdTc6caWc/wDgIBWicHgEAAACA/SkX\nBtogFKBxegQAAAAA9qZcGGiLUIBG6REAAAAA2JtyYaBNQgEao0cAAAAAYH/KhYE2CQVohB4BAAAA\ngP0pFwbaJhSgEXoEAAAAAPanXBhom1CAI9MjAAAAALA/5cJAFwgFOBI9AgAAAAD7261c+ORJ5cLA\n4gkFODQ9AgAAAAAHs1u58CtfqVwYWDyhAIemRwAAAABgf8qFgS4RCnAoegQAAAAADka5MNAlQgHm\npkcAAAAA4GCUCwNdIxRgLnoEAAAAAA5GuTDQRUIB5qJHAAAAAOBglAsDXVRqrW3vYRRKKUtJJtvX\nJpNJlpaWWtrR/NbWktOnZ9dWVpILF7w2CAAAAGC7yWT63GR7l8Dq6jQk0CUA3ba+vp7l5eWdy8u1\n1vU29tM0kwIciB4BAAAAgINTLgx0lVCAfekRAAAAADg45cJAlwkF2JceAQAAAICDUS4MdJ1QgD2t\nrSXnzs2urawk588npbSzJwAAAICuUi4MdJ1QgMvSIwAAAABwcJNJcvbs7NrqanLmTDv7AdiNUIBd\n6REAAAAAmI9yYaAPhALsSo8AAAAAwMEpFwb6QijAJfQIAAAAAByccmGgT4QCzNAjAAAAADAf5cJA\nnwgFuJceAQAAAID5KBcG+kYowL30CAAAAADMR7kw0DdCAZLoEQAAAACYl3JhoI+EAugRAAAAAJiT\ncmGgr4QCI6dHAAAAAGB+yoWBvhIKjJweAQAAAID5KBcG+kwoMGJ6BAAAAADmp1wY6DOhwEjpEQAA\nAACYn3JhoO+EAiOkRwAAAABgfsqFgSEQCoyQHgEAAACA+SkXBoag1Frb3sMolFKWkky2r00mkywt\nLS10H2tryenTs2srK8mFC14bBAAAAHA5k8n0Gcr2LoHV1WlIoEsAhmV9fT3Ly8s7l5drrett7Kdp\nJgVGRI8AAAAAwOEoFwaGQigwEnoEAAAAAA5HuTAwJEKBkdAjAAAAADA/5cLA0AgFRmBtLTl3bnZt\nZSU5fz4ppZ09AQAAAPSBcmFgaIQCA6dHAAAAAOBwJpPk7NnZtdXV5MyZdvYD0AShwIDpEQAAAAA4\nPOXCwBAJBQZMjwAAAADA4SgXBoZKKDBQegQAAAAADke5MDBkQoEB0iMAAAAAcHjKhYEhEwoMjB4B\nAAAAgMNTLgwMnVBgYPQIAAAAAByecmFg6IQCA6JHAAAAAODwlAsDYyAUGAg9AgAAAACHp1wYGAuh\nwADoEQAAAAA4GuXCwFgIBQZAjwAAAADA4SkXBsZEKNBzegQAAAAAjka5MDAmQoEe0yMAAAAAcDTK\nhYGxEQr0lB4BAAAAgKNRLgyMkVCgp/QIAAAAAByNcmFgjEqtte09jEIpZSnJZPvaZDLJ0tLS3Nda\nW0tOn55dW1lJLlzw2iAAAACAg5hMps9TtncJrK5OQwJdAjBu6+vrWV5e3rm8XGtdb2M/TTMp0DN6\nBAAAAACOTrkwMFZCgR7RIwAAAABwdMqFgTETCvSIHgEAAACAo1EuDIydUKAn1taSc+dm11ZWkvPn\nk1La2RMAAABA3ygXBsZOKNADegQAAAAAjm4ySc6enV1bXU3OnGlnPwBtEAp0nB4BAAAAgGYoFwYQ\nCnSeHgEAAACAo1MuDDAlFOgwPQIAAAAAR6dcGGDLFW1vYKdSSkny1CQ/lOR7k/z1JN+c5ItJJkl+\nP8nvJPn1Wus35rz2X0/yU0luTLKS5AFJ1pP8541r/u+11tub+U2ORo8AAAAAQDOUCwNsKbXWtvdw\nr1LKDUnenORRBzj8k0meX2t99wGv/Y+S/PMkV+5x2MWNY149b+BwgPsvZRpq3GsymWRpaemSY7/2\nteSGGy59bdCb3pQ873lN7goAAABg2CaT6ZsXtncJrK5OQwJdAsBu1tfXs7y8vHN5uda63sZ+mtaZ\n1weVUp6b5L1JvjNJPcDXI5P8binlpw9w7V9M8pok37SxtNv1kul/j1ckeVsTv9Nh6REAAAAAaIZy\nYYBZnQgFSinfn+SNme5n823570ny9CQPyfRh/rcm+fsb68n0Qf6JJK8vpTx5j2v/T0lesHF8SfKF\nJP8kyXckuSrTcOFnkty18fOa5HQp5eea+w0PTo8AAAAAQDOUCwNcqvXXB5VSTiT5SJLvytZD+X9a\na33NHuf8bJJXZesv/D+V5LtqrV/fcdxykj9JcvXGte9M8sRa6yd2ueZ3JPm/Mw0fSpKvJfnupjoG\ndnt90MMf/vA8/vGPzw033JAf+7Efyxe/+OA87nHJXXdtHXPVVcmHPpQ8+tFN7AIAAABgHC5eTK6/\nfrZL4OTJ5OMf1yUA7M3rg47fU5J898b3NcmtewUCSVJrfXWSt2b68L4keUSSH9nl0H+S5GS2woaf\n3C0Q2Ljmn2Y6mbD5OqH7ZvoqoWPzmc98Jrfddlte/OIX52EPe1iuv/4nctddd8wc8/rXCwQAAAAA\n5qVcGGB3XZgU+DdJnrPxsWb6F/+7Prjfcd5/leSj2ZoWeGut9dnbfn7fJH+W5IGZhgIfqbU+9gDX\nfWuSZ258/EqmCdDdB/x19rruJZMCyW8k+USmFQZ/uLF2TZKfT/K8PPvZJf/233ptEAAAAMA8lAsD\nR2FS4Ph9z7bvP3WQQCBJaq1/nGk/QDJ96H9qxyFPTPKgzcMznSw4iF/b9v2VSf7eAc87hBsyHWa4\nkOT3kzwhyReT/IN88zf/VN7whosCAQAAAIA5KRcGuLwuhAKfS/LnSS4mmff9/V/Z9v1f2/Gz/27j\n383H6u894DX/z2y9QiiZvt7omJVMs5H/K8m/SnKf3HXXm/PSlz4/bU9yAAAAAPSJcmGAvbUeCtRa\nn1Br/bYkVyV5xkHPK6V8S5Klzcsk2Tm6sf1N/DXJHx1wP3cl+fTmbZL8Nwfd09GdSPLSTIca7pM3\nv/nNefOb37y42wMAAAD02MWLyQtfOLt28mTy2te2sx+ALmo9FNhUa71Ya/38/kfe64ezNQWQJB/b\n8fPvytZf+/9ZrfUrObhPbrv2daUs+iU+P5Lkf0mSvOQlL8kdd9yx9+EAAAAAKBcGOIDOhALz2CgR\n/seZPvTffGD/73Yc9tCNf2umhcPz+Oy2769I8pB593h0L07yhHzxi1/My1/+8sXfHgAAAKBHJpPk\n7NnZtdXV5MyZdvYD0FW9DAWSvCLJo7Z9viPJb21+KKVcmeSabT//3JzX/8sdnx845/kNOJHkliTJ\n2972ttx5552L3wIAAABATygXBjiY3oUCpZSnJ3lZtqYEapKfrbV+fdthJ3ec9sU5b3P3js/X7HrU\nsXt8kr+Vr371q3nLW97SzhYAAAAAOk65MMDB9SoUKKU8Kcmtmx8zDQTWaq237jj0yh2fv5757Dy+\npUy5JLkpSfKBD3ygnS0AAAAAdJhyYYD5XNH2Bg6qlPIDSd6Z2Qf+n0jy3F0OP7Hj8zfmvN3O448p\nPLknyf33OWY1SfLhD38499xzz72rV1999fFsCQAAAKBHlAsDl7P9eeoizuuLXoQCpZRnJHlLtv5i\nv2RaHvyDtdbdXg30Vzs+7wwJ9rPzv8tX5zz/gK478JGf/vSnc/Lk1luRaq3HsSEAAACA3lAuDOxl\n+/NUtnT+9UGllH+Y5K25NBD4/lrrpy5z2pd2fL5qztvuPP6YQgEAAAAADku5MMD8OjspUEq5T5LX\nJXlBtkqFk+T2JDfWWj95uXNrrXeVUi5mK/R4wJy333n8X8x5/gHdnmRpn2P+S5LvSJLcddddOXFi\n3qEHAAAAgOFRLgzs5+677z7Ueevr67nuuoO/5aVvOhkKlFKuSfL2JE/OViBQk3w001cG/fkBLjNJ\n8pCNc/d78r7Tt+5yrWNw9cbXXj6VJFlevi4nTjwgqgQAAACAsVMuDBzEYXtZv/SlnS+iGZbOvT6o\nlPLQJO/PpYHA+5L8twcMBJLpn+FvThc8bM5tbD9+Umv9ypznN+jCdBOT/zpLS8kznpG8/e3JwLsu\nAAAAAC5LuTDA4XUqFCilPCLJf0jyNzIbCPxaphMCX5jjch/d9v23lFIONC1QSilJHrVx383phJbU\nTOsUkuSJ+fKXk9tuS266KQICAAAAYJSUCwMcTWdCgVLKwzOdBrh2cynTp+L/stb6nFrr1+e85Id2\nfL7+gOetJtleS/37c963QX+Q5D8muTLJj838REAAAAAAjJFyYYCj6UQoUEq5OsnvJnn45lKSi0le\nUGt9+SEv++83/q0b/z71gOf90LY9JMm7Dnn/I7qY5MVJkoc+9KacOPHgyx4pIAAAAADGQLkwwNGV\nWuv+Rx33Jkr51SQ/nq1XBv1Vkh+vtb51r/MOcN33J3nCxse7kjyy1vqXexz/TUk+luTbN/bx6Vpr\nIzXTG68v2lFYPMnlO5D/VZJ/nGuuuSYf/ehHc//7X5t3vnP6sP8975kW6uznfvdLnvKU5JnPTJ76\n1CgpBgAAAHrr4sXk+utnuwROnkw+/nFdAkCz1tfXs7y8vHN5uda63sZ+mtb6pEAp5WmZDQRqkhcd\nNRDY8LqNf2uSByT51/scfy7JI7bt43V7Hn1s3pHkZ5Ikt9xyS6699to8+MHJ856XvOtdyWc/m7zp\nTcmNNyYnTlz+KiYIAAAAgKFQLgzQjNYnBUop/zHJo7P1IP43aq0/0tC1S6adANdn6zVCv5HkebXW\nu7Ydd2WSX0jy09kKJz6R5G8cosvgcns5wKTAxY1t/EySb+Tmm2/Om970pkx/jd3deWdMEAAAAACD\nNpkkKyuzXQKrq9OQQJcA0LShTwq0GgqUUm5M8nvZemCfbL3Lf1611nrJ382XUh6V5ANJtr+U/+4k\nv5nk00kemuTvJnlQtgKBLye5oda6I38+vL1DgZppqfBLkvyHJMnNN9+cN77xjTmx1yjADgICAAAA\nYIh+8icv7RJ43/t0CQDHQyhwnDcv5X9N8j83dLldQ4GN+/zNTIuMH5K9Q4ea5AtJTtda39vQvjb3\nsEsocFuSP0nytiR/mCS55pprcsstt+Tmm2/ec0JgPwICAAAAYAg++MHkCU+YXXvWs5Jbb21nP8Dw\nCQWO8+al/GaSpzR0uVprvWKPez0gyasz7S+4ZpdDvp7k15O8rNb6nxva0/b77xIKbLnyyivzoz/6\no3nVq16Va6+9ttF7CwgAAACAPlIuDLRBKDAwpZT7Jvm+JNdl+sqgLyX50yQfqLV+fq9zj3jfS0KB\na6+9No9//OPzxCc+Mc95znPyoAc96Lhufy8BAQAAANAXv/RLyQtfOLv28z+fvOQl7ewHGAehAI3Y\nLRSYTCZZWlq6zBnHT0AAAAAAdJVyYaAtQgEa0cVQYDsBAQAAANAlyoWBtggFaETXQ4HtBAQAAABA\nm5QLA20SCtCIPoUC2wkIAAAAgEVSLgy0beihwH3a3gDd9uAHJ897XvKudyWf/WzypjclN96YnDhx\n+XO+/OXkttuSm25KlpaSZzxjGircc8/i9g0AAAD00xvfOBsIJMkrXykQAGiKSYEF6eukwOWYIAAA\nAACaplwY6IKhTwoIBRZkaKHAdgICAAAAoAnKhYEuEArQiCGHAtsJCAAAAIDDUC4MdIVQgEaMJRTY\nTkAAAAAAHIRyYaBLhh4KKBrm2CgpBgAAAA5CuTDA4pgUWJAxTgpcjgkCAAAAYJNyYaBrhj4pIBRY\nEKHA7gQEAAAAMG7KhYGuEQrQCKHA/gQEAAAAMC7KhYEuEgrQCKHAfAQEAAAAMGzKhYGuGnoooGiY\nTlJSDAAAAMOmXBigHSYFFsSkQDNMEAAAAED/KRcGumzokwJCgQURCjRPQAAAAAD9pFwY6DKhAI0Q\nChwvAQEAAAD0g3JhoOuEAjRCKLA4AgIAAADoJuXCQB8MPRRQNMzgKCkGAACAblIuDNA+kwILYlKg\nfSYIAAAAoD3KhYG+GPqkgFBgQYQC3SIgAAAAgMVSLgz0hVCARggFuktAAAAAAMdLuTDQJ0IBGiEU\n6AcBAQAAADRLuTDQN0MPBRQNwzZKigEAAKBZyoUBusWkwIKYFOg3EwQAAAAwP+XCQB8NfVJAKLAg\nQoHhEBAAAADAwSgXBvpIKEAjhALDJCAAAACA3SkXBvpKKEAjhALDJyAAAACAKeXCQJ8NPRRQNAwN\nUVIMAAAAU8qFAbrLpMCCmBQYLxMEAAAAjIlyYaDvhj4pIBRYEKEAiYAAAACA4VMuDPSdUIBGCAXY\nSUAAAADA0CgXBoZAKEAjhALsRUAAAABA3ykXBoZi6KGAomHoACXFAAAA9J1yYYB+MCmwICYFOAwT\nBAAAAPSBcmFgSIY+KSAUWBChAEclIAAAAKCrlAsDQyIUoBFCAZokIAAAAKArlAsDQyMUoBFCAY6L\ngAAAAIC2KBcGhmjooYCiYeg5JcUAAAC0RbkwQP+YFFgQkwIsmgkCAAAAjpNyYWCohj4pIBRYEKEA\nbRIQAAAA0DTlwsBQCQVohFCArhAQAAAAcFTKhYEhEwrQCKEAXSQgAAAAYF7KhYGhG3oooGgYRkxJ\nMQAAAPNSLgzQbyYFFsSkAH1iggAAAIDdKBcGxmDokwJCgQURCtBXAgIAAAA2KRcGxkAoQCOEAgyB\ngAAAAGC8lAsDYyEUoBFCAYZGQAAAADAeyoWBMRl6KKBoGDgUJcUAAADjoVwYYDhMCiyISQHGwgQB\nAADAsCgXBsZm6JMCQoEFEQowRgICAACA/lMuDIyNUIBGCAUYOwEBAABA/ygXBsZIKEAjhAKwRUAA\nAADQfcqFgbEaeiigaBhYOCXFAAAA3adcGGCYTAosiEkB2J8JAgAAgG5QLgyM2dAnBYQCCyIUgPkI\nCAAAANqjXBgYM6EAjRAKwOEJCAAAABZHuTAwdkIBGiEUgGYICAAAAI6PcmGA4YcCioaBXlFSDAAA\ncHyUCwMMn0mBBTEpAMfLBAEAAMDRKBcGmBr6pIBQYEGEArA4AgIAAID5KRcGmBIK0AihALRDQAAA\nALA/5cIAW4QCNEIoAO0TEAAAAFxKuTDArKGHAoqGgdFQUgwAAHAp5cIA42JSYEFMCkB3mSAAAADG\nSrkwwKWGPikgFFgQoQD0g4AAAAAYE+XCAJcSCtAIoQD0j4AAAAAYMuXCALsTCtAIoQD0m4AAAAAY\nEuXCAJc39FBA0TDAASgpBgAAhkS5MMB4mRRYEJMCMEwmCAAAgL5RLgywt6FPCggFFkQoAMMnIAAA\nAPpAuTDA3oQCNEIoAOMiIAAAALpIuTDA/oQCNEIoAOMlIAAAALpAuTDAwQw9FFA0DHDMlBQDAABd\noFwYgMSkwMKYFAB2MkEAAAAsinJhgIMb+qSAUGBBhALAXgQEAADAcVIuDHBwQgEaIRQADkpAAAAA\nNEm5MMB8hAI0QigAHIaAAAAAOArlwgDzG3oooGgYoMOUFAMAAEehXBiAnUwKLIhJAaBJJggAAID9\nKBcGOJyhTwoIBRZEKAAcFwEBAACwG+XCAIcjFKARQgFgEQQEAABAolwY4CiEAjRCKAAsmoAAAADG\nSbkwwNEMPRRQNAwwUEqKAQBgnJQLA7AXkwILYlIA6AoTBAAAMFzKhQGObuiTAkKBBREKAF0kIAAA\ngGFRLgxwdEIBGiEUALpOQAAAAP2mXBigGUIBGiEUAPpEQAAAAP2iXBigOUMPBRQNA3AJJcUAANAv\nyoUBOCiTAgtiUgAYAhMEAADQPcqFAZo19EkBocCCCAWAoREQAABANygXBmiWUIBGCAWAIRMQAABA\nO5QLAzRPKEAjhALAWAgIAABgMZQLAxyPoYcCioYBaJSSYgAAWAzlwgAchkmBBTEpAIydCQIAAGiO\ncmGA4zP0SQGhwIIIBQC2CAgAAOBolAsDHB+hAI0QCgDsTkAAAADzUS4McLyEAjRCKACwPwEBAADs\nTbkwwPEbeiigaBiAzlBSDAAAe1MuDMBRmRRYEJMCAIdnggAAAJQLAyzK0CcFhAILIhQAaIaAFK3X\nxgAAIABJREFUAACAsVIuDLAYQgEaIRQAaJ6AAACAsVAuDLA4QgEaIRQAOF4CAgAAhkq5MMBiDT0U\nUDQMwCAoKQYAYKiUCwPQJJMCC2JSAKAdJggAAOgz5cIAizf0SQGhwIIIBQDaJyAAAKBvlAsDLJ5Q\ngEYIBQC6RUAAAEDXKRcGaIdQgEYIBQC6S0AAAEDXKBcGaM/QQwFFwwCMnpJiAAC6RrkwAMfFpMCC\nmBQA6B8TBAAAtEG5MEC7hj4pIBRYEKEAQL8JCAAAWBTlwgDtEgrQCKEAwHAICAAAOC7KhQHaJxSg\nEUIBgGESEAAA0BTlwgDdMPRQQNEwAByBkmIAAJqiXBiARTApsCAmBQDGxQQBAADzUC4M0B1DnxQQ\nCiyIUABgvAQEAADsR7kwQHcIBWiEUACAREAAAMCllAsDdItQgEYIBQDYSUAAAIByYYDuGXoooGgY\nAFqipBgAAOXCACyaSYEFMSkAwEGZIAAAGAflwgDdNPRJAaHAgggFADgMAQEAwHApFwboJqEAjRAK\nAHBUAgIAgOFQLgzQXUIBGiEUAKBJAgIAgP5SLgzQbUMPBXpVNFxK+c5SyldLKd8opfyzOc9958Z5\nh/l6/HH9TgBwGEqKAQD6S7kwAG3qTShQSrlPkn+d5L5JDjPe8OiN8za/DsooBQCdJiAAAOiPySQ5\ne3Z2bXU1OXOmnf0AMD69CQWSvCHJDYc5sZTygCSP2LFc5/gCgF4QEAAAdNvLXpZ8/vOza294Q3Lf\n+7azHwDGpxehQCnlliTPz+Ef0D9m81Ib//6dWuuJA35dUWv9gyP/EgCwYAICAIBu+eAHk1/5ldm1\nZz0r+b7va2c/AIxTp0OBUso1pZTbkrwoR/uL/cfu+PyRI1wLAHpHQAAA0K6LF5MXvnB27eTJ5LWv\nbWc/AIxXZ0OBUspjk/xhkqdnGgiUvc/Y02O2fX9HrfWuo+wNAPpMQAAAsHjKhQHois6FAqWUB5VS\nfjHJHyR55LYfTXL4YGBzUqAm+aMjbA8ABkVAAABw/JQLA9AlnQoFSik/kORPkrwgyYlMQ4Ca5N1J\nfnDjsLleI1RKOZFkddt5QgEA2IWAAADgeCgXBqBLOhUKZPrw/puz9QD/niQvrrX+90n+8pDXXEly\nZbamDIQCALAPAQEAQDOUCwPQNV0LBTbVJL+WZLXW+rojXmtnyfB/OuL1AGBUBAQAAIejXBiALupa\nKPC1JG9J8rdqrc+ptd7RwDW3lwzfXWv9ZCnl0aWU15ZSPlxK+Vwp5SullM+UUt5dSnlJKeWBDdwX\nAAZHQAAAcHDKhQHoolLrXK/ob00p5duT3J6tVwu9stb6qgOc93tJbtw471NJPpLkafucdleSV9Ra\nzx16w5fuYynTsuR7TSaTLC0tNXULAGjNnXcm73zn9GH/e94z/au4/dzvfslTnpI885nJU5+aXH31\n8e8TAGBRJpNkZWW2S2B1dRoS6BIA6Lb19fUsLy/vXF6uta63sZ+mdW1S4Dg8JltBwnWZBgJ1n68H\nJPmFUsqvllLKJVcEAGaYIAAAmKVcGICuGnQoUEp5SJKdkU5N8tuZhgMPz7SE+NuS3JTk/Zunbhz3\nnCSvWchmAWAgBAQAwNgpFwagywb9+qBSypOT/M7GOSXJl5LcXGt92x7nvCTJZuXPZjjwpFrr+464\nf68PAmDUvGIIABiDixeT66+f7RI4eTL5+Md1CQD0xdBfH3RF2xs4Zl9McmuSR2b66qAX1VrfvtcJ\ntdZbSikPTfLSbAUQr0ryt5ve3D333JP73//+hzr3ak9FAOiZzQmC5z3v4AHB5gTBbbcJCACAflAu\nDNAd9xxy/Pyw5/XFoCcFjnCv+yW5I8kDszUtcF2t9Y4jXPOSSYGj6Mv/bgCwHxMEAMBQKBcG6JaG\n62IHMykw6E6Bw6q1fjnJOzINBDY9qaXtAMCg6SAAAIZCuTAAfWBS4PL3+4kkv7Ltfv+i1vrPjnC9\nSyYFbr/99kN3Cnh9EABDZ4IAAOiTD34wecITZtee9azk1lvb2Q8Ah38N0Pr6eq677rqdy4OZFBAK\nXP5+P5jkt7fd74211hcc4XqKhgHgkAQEAECXKRcGGJahFw17fdDl7Xzh1Fdb2QUA4BVDAECnKRcG\noE8GHQqUUu5XSvn2UsrjSynfO+fpO6OgO5vaFwBweAICAKBLJpPk7Nn/v717D5f2rOtD//2RhBAM\nZBNISDAIEdkkpKGUzamBFhFQCwIGUbYpoGCVFkqrliqtCuGwe2kQWizgprpBpWgouoVdsG4QoQIm\naIUqFptAwqFCs3NAEkkIObz3/mNmmHmH9a53Zs0zp2c+n+uaa9bMeu5n7iTrzm+t+c79/A5/7pxz\nkhe+cD3zAYCj6W0oUFV3TnJjBpccujTJ2+Y8xcNGpxref7SjqQEAHREQAADrprkwANumt6FAa+2m\nJFdk3BPgjKo6a5axVXVskqdOjL01yYc7nyQA0BkBAQCwapdckrz5zYc/d8EFyWMes575AMAsehsK\nDL0rg0/6j97cf8GM456X5BuHX7ckF7fWbuh4bgDAkggIAIBlu/325AVT7zKceGLyqletZz4AMKu+\nhwK/nOTQ8OtK8iNV9ej9BlTVI5JclEEYUBnsErhomZMEAJZHQAAALIPmwgBsq16HAq21/5bk32W8\nW+DYJO+uqu/f6/iqek6S9ya508SYV7bWPrGaGQMAyyQgAAC6oLkwANusWmtHP2oDVNV9MmgaPJrw\ny1prL59h3AlJfi/JIzN+o7+SXJ7k/UmuS3Jakscn+aaJ77ckv9Ja+6GO5n9Kkqsnn7v66qtzyimn\ndHF6AGAB116bvOMdgzf7f//3B5cDOJoTTkie+MTk+74vedKTkm/4huXPEwDYDM997tf3EvjAB/QS\nAOiLa665Jqeeeur006e21q5Zx3y6to2hQDJ4w36mUGA49q5JfjXJU0ZP7XN4y+CSQ69trb3ogNPd\naw5CAQDYAgICAGA/l1ySnHfe4c9dcEHy1reuZz4AdK/vocC2XT6oZbxTYPZBrd3QWjs/yTOS/MnE\neaZvtyT5nSSP7DIQAAC2h0sMAQBHorkwAH2wNTsFulRVpyc5L8npSU5Mcm2SLyT5UGvthiW9pp0C\nALDF7CAAAN7whq8PBV796uTHf3w98wFgOfq+U2AnQ4F1EAoAQH8ICABg91x9dfKAByRf+tL4uXPO\nST72seS449Y3LwC6JxSgE0IBAOgnAQEA7AbNhQF2h1CATggFAKD/BAQA0E+aCwPsFqEAnRAKAMBu\nERAAQD/cfnvysIcNLhM0cuKJyWWXJfe61/rmBcDy9D0UuMO6JwAA0Ef3uEfyD/5B8p73JFddlfzS\nLyVPeEJyzDFHHvOVryS/9VvJM56RnHJK8vSnD0KFG29c3bwBgMO98Y2HBwJJ8rKXCQQA2F52CqyI\nnQIAQGIHAQBsE82FAXZT33cKCAVWRCgAAEwTEADAZtNcGGA3CQXohFAAANiPgAAANovmwgC7SyhA\nJ4QCAMCsBAQAsF6aCwPstr6HAhoNAwBsGE2KAWC9NBcGoM/sFFgROwUAgEXZQQAAy6e5MAB93ykg\nFFgRoQAA0CUBAQAsh+bCAAgF6IRQAABYFgEBAHRDc2EAEqEAHREKAACrICAAgIPRXBiAkb6HAhoN\nAwD0iCbFAHAwmgsDsCvsFFgROwUAgHWygwAAjkxzYQAm9X2ngFBgRYQCAMCmEBAAwOE0FwZgklCA\nTggFAIBNJCAAYNdpLgzANKEAnRAKAACbTkAAwK7RXBiAvfQ9FNBoGACAJJoUA7B7NBcGYBfZKbAi\ndgoAANvKDgIA+khzYQCOpO87BYQCKyIUAAD6QEAAQF9oLgzAkQgF6IRQAADoGwEBANtKc2EA9iMU\noBNCAQCgzwQEAGwLzYUBOJq+hwIaDQMAsDBNigHYFpoLA7Dr7BRYETsFAIBdZAcBAJtEc2EAZtH3\nnQJCgRURCgAAu05AAMC6aS4MwCyEAnRCKAAAMCYgAGDVNBcGYFZCATohFAAA2JuAAIBl01wYgHn0\nPRTQaBgAgLXSpBiAZdNcGADG7BRYETsFAADmYwcBAF3QXBiAefV9p4BQYEWEAgAABycgAOCgNBcG\nYF5CATohFAAA6IaAAIBZaS4MwEEIBeiEUAAAoHsCAgCORHNhAA6q76GARsMAAGwtTYoBOBLNhQFg\nb3YKrIidAgAAq2MHAcBu01wYgEX0faeAUGBFhAIAAOshIADYPZoLA7AIoQCdEAoAAKyfgACg/zQX\nBmBRQgE6IRQAANgsAgKA/tFcGIAu9D0U0GgYAICdpEkxQP9oLgwAR2enwIrYKQAAsB3sIADYTpoL\nA9CVvu8UEAqsiFAAAGD7CAgAtofmwgB0RShAJ4QCAADbTUAAsLk0FwagS0IBOiEUAADoDwEBwObQ\nXBiArvU9FNBoGAAA5qRJMcDm0FwYAOZjp8CK2CkAANB/dhAArJbmwgAsQ993CggFVkQoAACwWwQE\nAMunuTAAyyAUoBNCAQCA3SUgAOie5sIALItQgE4IBQAASAQEAF3QXBiAZep7KKDRMAAArJAmxQCL\n01wYAA7OToEVsVMAAID92EEAMBvNhQFYtr7vFBAKrIhQAACAWQkIAI5Mc2EAlk0oQCeEAgAAHISA\nAGBMc2EAVkEoQCeEAgAALEpAAOwyzYUBWJW+hwIaDQMAwJbQpBjYZZoLA0A37BRYETsFAABYFjsI\ngL7TXBiAVer7TgGhwIoIBQAAWAUBAdBHmgsDsEpCATohFAAAYNUEBEAfaC4MwKoJBeiEUAAAgHUS\nEADbSHNhANah76GARsMAALADNCkGtpHmwgDQPTsFVsROAQAANpEdBMCm0lwYgHXp+04BocCKCAUA\nANh0AgJgk2guDMC6CAXohFAAAIBtIiAA1klzYQDWSShAJ4QCAABsKwEBsEqaCwOwbn0PBTQaBgAA\n9qVJMbBKmgsDwHLZKbAidgoAANA3dhAAXdNcGIBN0PedAkKBFREKAADQZwICoAuaCwOwCYQCdEIo\nAADArhAQAAehuTAAm0IoQCeEAgAA7CIBATALzYUB2CR9DwU0GgYAAJZGk2JgFpoLA8Dq2CmwInYK\nAADAmB0EwIjmwgBsmr7vFBAKrIhQAAAA9iYggN2muTAAm0YoQCeEAgAAcHQCAtgtmgsDsImEAnRC\nKAAAAPMREEC/aS4MwKbqeyig0TAAALCRNCmGftNcGADWw06BFbFTAAAAumEHAWw/zYUB2GR93ykg\nFFgRoQAAAHRPQADbSXNhADaZUIBOCAUAAGC5BASwHTQXBmDTCQXohFAAAABWR0AAm0lzYQC2Qd9D\nAY2GAQCA3tGkGDaT5sIAsH52CqyInQIAALB+dhDA+mguDMC26PtOAaHAiggFAABgswgIYLU0FwZg\nWwgF6IRQAAAANpeAAJZLc2EAtolQgE4IBQAAYDsICKBbmgsDsG36HgpoNAwAADBBk2LolubCALBZ\n7BRYETsFAABgu9lBAPPTXBiAbdT3nQJCgRURCgAAQH8ICGA2mgsDsI2EAnRCKAAAAP0kIIC9aS4M\nwLYSCtAJoQAAAPSfgAAGNBcGYJv1PRTQaBgAAKAjmhTDgObCALC57BRYETsFAABgd9lBwC7RXBiA\nbdf3nQJCgRURCgAAAImAgP7TXBiAbScUoBNCAQAAYJqAgL7RXBiAPhAK0AmhAAAAsB8BAdtOc2EA\n+qLvoYBGwwAAABtAk2K2nebCALAd7BRYETsFAACAg7CDgG2guTAAfdL3nQJCgRURCgAAAIsSELCp\nNBcGoE+EAnRCKAAAAHRJQMCm0FwYgL4RCtAJoQAAALAsAgLWRXNhAPqo76GARsMAAABbTpNi1kVz\nYQDYPnYKrIidAgAAwKrZQcAyaS4MQF/1faeAUGBFhAIAAMA6CQjomubCAPSVUIBOCAUAAIBNISBg\nUZoLA9BnQgE6IRQAAAA2kYCAeWkuDEDf9T0U0GgYAABgh2lSzLw0FwaA7WanwIrYKQAAAGwTOwjY\ni+bCAOyCvu8UEAqsiFAAAADYVgICRjQXBmAXCAXohFAAAADoAwHB7tJcGIBdIRS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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112dd3e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from shapely.wkt import loads\n",
    "geom = loads(\"POLYGON ((30 10, 40 35, 20 40, 10 20, 30 10))\")\n",
    "x, y = geom.exterior.xy\n",
    "plt.plot(x, y, ls = '-', marker = 'o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# CHECK  POINT\n",
    "\n",
    "What should the bounding box be as a WKT Polygon?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# ANSWERS Hidden\n",
    "\n",
    "<div class=\"answers\">\n",
    "\n",
    "\"POLYGON ((llcrnrlon llcrnrlat, lrcrnrlon lrcrnrlat, urcrnrlon urcrnrlat, ulcrnrlon ulcrnrlat, llcrnrlon llcrnrlat))\"\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Window observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "**PNC:/Users/barronh/Development/pseudonetcdf/src/PseudoNetCDF/pncparse.py:419:DtypeWarning:\n",
      "  Columns (17,23) have mixed types. Specify dtype option on import or set low_memory=False.\n"
     ]
    }
   ],
   "source": [
    "from PseudoNetCDF import PNC\n",
    "aqsncpath = 'aqs.nc'\n",
    "os.remove(aqsncpath)\n",
    "aqsargs = PNC('gen', '-O',\n",
    "   '--format=aqsraw,bdate=\"2006-08-01\",edate=\"2006-08-01\",wktpolygon=\"POLYGON ((-90 25, -75 25, -75 45, -90 45, -90 25))\"',\n",
    "   '--rename=v,Ozone,O3',\n",
    "   aqspath, aqsncpath);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "netCDF4._netCDF4.Dataset aqs.nc {\n",
      "dimensions:\n",
      "        time = UNLIMITED // (24 currently) \n",
      "        points = 518 ;\n",
      "        LAY = 1 ;\n",
      "\n",
      "variables:\n",
      "        double time(time);\n",
      "                time:units = \"hours since 1900-01-01\" ;\n",
      "                time:standard_name = \"time\" ;\n",
      "        float latitude(points);\n",
      "                latitude:units = \"degrees_north\" ;\n",
      "                latitude:standard_name = \"latitude\" ;\n",
      "        float longitude(points);\n",
      "                longitude:units = \"degrees_east\" ;\n",
      "                longitude:standard_name = \"longitude\" ;\n",
      "        float O3(time, LAY, points);\n",
      "                O3:_FillValue = -999.0 ;\n",
      "                O3:fill_value = -999.0 ;\n",
      "                O3:units = \"Parts per million\" ;\n",
      "                O3:standard_name = \"Ozone\" ;\n",
      "\n",
      "\n",
      "// global properties:\n",
      "                :SITENAMES = \"010030010;010270001;010331002;010510001;010550011;010690004;010730023;010731003;010731005;010731009;010731010;010732006;010735002;010735003;010736002;010790002;010890014;010970003;010972005;011011002;011030011;011130002;011170004;011190002;011210003;011250010;100010002;100031007;100031010;100031013;100051002;100051003;110010025;110010041;110010043;120013011;120030002;120050006;120090007;120094001;120110031;120112003;120118002;120210004;120230002;120310077;120310100;120330004;120330018;120330024;120550003;120570081;120570110;120571035;120571065;120573002;120574004;120590004;120690002;120712002;120713002;120730012;120730013;120813002;120814012;120814013;120830003;120830004;120860027;120860029;120950008;120952002;120972002;120990009;120990020;121010005;121012001;121030004;121030018;121035002;121056005;121056006;121111002;121130015;121151005;121151006;121152002;121171002;121272001;121275002;121290001;130210012;130210013;130510021;130550001;130590002;130670003;130730001;130770002;130850001;130890002;130893001;130970004;131130001;131210055;131270006;131350002;131510002;132130003;132150008;132151003;132230003;132450091;132470001;132611001;170190004;170230001;170310001;170310032;170310042;170310064;170310072;170310076;170311003;170311601;170314002;170314007;170314201;170317002;170436001;170491001;170650002;170971002;170971007;171110001;171132003;171150013;171170002;171191009;171430024;171431001;171570001;171670010;171971011;172010009;172012001;180030002;180030004;180110001;180150002;180190003;180350010;180390007;180431004;180550001;180571001;180590003;180630004;180710001;180810002;180890022;180890030;180892008;180910005;180910010;180950010;180970042;180970050;180970057;180970073;181090005;181230009;181270024;181270026;181290003;181410015;181450001;181630012;181630013;181670018;181670024;181730008;181730009;181730011;210130002;210150003;210190017;210290006;210430500;210470006;210590005;210610501;210670001;210670012;210890007;210910012;210930006;211010014;211110027;211110051;211111021;211130001;211170007;211390003;211451024;211830032;211850004;211930003;211950002;211990003;212130004;212218001;212270008;220870009;240030014;240051007;240053001;240090011;240130001;240150003;240170010;240210037;240230002;240251001;240259001;240290002;240313001;240330030;240338003;240430009;260050003;260190003;260210014;260270003;260370001;260490021;260492001;260630007;260650012;260770008;260810020;260810022;260910007;260990009;260991003;261010922;261050007;261130001;261210039;261250001;261390005;261470005;261610008;261630001;261630015;261630016;261630019;280330002;280470008;280590006;280750003;280810005;291570001;340070003;340110007;340150002;360130006;360130011;360150003;360290002;360450002;360530006;360551007;360631006;360650004;360671015;360750003;361010003;361173001;370030004;370110002;370210030;370270003;370330001;370370004;370510008;370511003;370590002;370630013;370650099;370670022;370670028;370670030;370671008;370690001;370750001;370770001;370810013;370870004;370870035;370870036;370990005;371010002;371070004;371090004;371170001;371190041;371191005;371191009;371290002;371450003;371470099;371570099;371590021;371590022;371730002;371790003;371830014;371830016;371990004;390030002;390071001;390170004;390171004;390230001;390230003;390250022;390271002;390350034;390350064;390355002;390410002;390490028;390490029;390490037;390490081;390550004;390570006;390610006;390610010;390610040;390810017;390830002;390850003;390853002;390870006;390870011;390890005;390930018;390950024;390950027;390950034;390950081;390970007;390990013;391030003;391090005;391130033;391331001;391351001;391510016;391510021;391530020;391550009;391550011;391650007;391670004;391730003;420010002;420030008;420030010;420030067;420031005;420050001;420070002;420070005;420070014;420110010;420130801;420210011;420270100;420290100;420334000;420430401;420431100;420450002;420490003;420550001;420590002;420630004;420690101;420692006;420710007;420730015;420770004;420791100;420791101;420810100;420850100;420890002;420910013;420950025;420958000;420990301;421010004;421010014;421010024;421010136;421174000;421250005;421250200;421255001;421290006;421290008;421330008;450010001;450030003;450070003;450110001;450150002;450190046;450210002;450230002;450250001;450290002;450310003;450370001;450730001;450770002;450790007;450790021;450791001;450830009;450870001;450890001;450910006;470010101;470090101;470090102;470370011;470370026;470630003;470651011;470654003;470750003;470890002;470930021;470931020;470990002;471050109;471210104;471490101;471550101;471550102;471571004;471632002;471632003;471650007;471650101;471870106;471890103;510130020;510330001;510360002;510410004;510590005;510590018;510590030;510591005;510595001;510610002;510690010;510850003;510870014;511071005;511130003;511390004;511530009;511611004;511630003;511790001;511970002;515100009;516500004;518000004;518000005;540030003;540110006;540250003;540291004;540390010;540610003;540690010;541071002;550090026;550210015;550250041;550270007;550390006;550550002;550590019;550610002;550710007;550730012;550790010;550790026;550790041;550790085;550870009;550890008;550890009;551010017;551050024;551110007;551170006;551270005;551310009;551330027\" ;\n",
      "                :lonlatcoords = \"-87.881412,30.498001/-85.802182,33.281261/-87.650562,34.758781/-86.136587,32.498567/-86.053867,33.904039/-85.423117,31.190657/-86.815000,33.553056/-86.915000,33.485556/-87.003611,33.331111/-87.305556,33.459722/-86.549167,33.545278/-86.816667,33.386389/-86.669167,33.704722/-86.942500,33.801667/-86.773889,33.578333/-87.339730,34.342904/-86.586370,34.687670/-88.087526,30.769941/-88.141140,30.474674/-86.256367,32.407120/-86.976939,34.518735/-85.083841,32.467971/-86.825092,33.317316/-88.201865,32.364010/-86.122667,33.498328/-87.459731,33.089600/-75.556800,38.986672/-75.732000,39.551300/-75.563889,39.817222/-75.496389,39.773889/-75.610600,38.653900/-75.163230,38.779100/-77.121900,38.583226/-76.958072,38.895572/-77.013178,38.921847/-82.296111,29.544722/-82.441111,30.201111/-85.731517,30.130433/-80.628611,28.053611/-80.615556,28.310556/-80.295000,26.272000/-80.096470,26.292025/-80.111000,26.087000/-81.711000,26.270000/-82.619167,30.178056/-81.587339,30.477725/-81.454000,30.261000/-87.203550,30.525367/-87.270967,30.368050/-87.276000,30.399000/-81.340556,27.188889/-82.465146,27.740033/-82.162117,27.780508/-82.454722,27.928056/-82.538611,27.892222/-82.230400,27.965650/-82.125833,27.992500/-85.603889,30.848611/-81.723333,28.525000/-81.980000,26.547861/-81.939444,26.448889/-84.346389,30.439722/-84.199444,30.484444/-82.546111,27.632778/-82.618889,27.480556/-82.522222,27.449444/-82.100833,29.170278/-82.173333,29.192500/-80.161806,25.733378/-80.326811,25.586384/-81.381389,28.454167/-81.362500,28.596389/-81.636667,28.347222/-80.233889,26.730833/-80.060867,26.591230/-82.305833,28.331944/-82.758056,28.195000/-82.731944,27.946389/-82.739875,27.785866/-82.700833,28.090000/-82.000278,27.939444/-81.972222,28.028889/-80.408330,27.448889/-87.008033,30.394133/-82.570556,27.306944/-82.480000,27.350278/-82.362583,27.089194/-81.310556,28.746111/-80.993889,29.108889/-81.052500,29.206667/-84.161111,30.092500/-83.543521,32.805408/-83.788749,32.827967/-81.048769,32.069230/-85.408003,34.474293/-83.344495,33.918067/-84.607407,34.015482/-82.131189,33.582144/-84.745988,33.404040/-84.059766,34.376317/-84.290480,33.687970/-84.213398,33.845741/-84.779192,33.743656/-84.418998,33.455739/-84.357056,33.720192/-81.495881,31.169735/-84.069010,33.961270/-84.161708,33.433575/-84.626422,34.785197/-84.944795,32.521302/-84.880303,32.508712/-85.045340,33.928500/-82.022217,33.433349/-84.065294,33.591077/-84.081059,31.954298/-88.229531,40.123796/-87.668297,39.210857/-87.732457,41.670992/-87.545350,41.755832/-87.635556,41.878980/-87.601646,41.790787/-87.607683,41.895812/-87.713488,41.751400/-87.792002,41.984332/-87.990570,41.668120/-87.752470,41.855243/-87.863225,42.060285/-87.799227,42.139996/-87.675254,42.062053/-88.072827,41.813049/-88.548934,39.067159/-88.624943,38.082155/-87.841406,42.386706/-87.810047,42.467573/-88.242207,42.221442/-88.996896,40.518735/-88.925594,39.866834/-89.809739,39.396075/-89.959963,38.726573/-89.606943,40.687420/-89.585869,40.745504/-89.788459,38.176278/-89.604839,39.844122/-88.190967,41.221537/-89.077005,42.287190/-89.037775,42.334982/-85.016821,41.221418/-85.101816,41.094965/-86.395172,39.997484/-86.553035,40.540455/-85.690278,38.376944/-85.245367,40.300015/-85.830550,41.718050/-85.834167,38.308056/-86.990120,38.985578/-86.000503,40.056090/-85.840471,39.935041/-86.397124,39.759003/-86.080489,38.920844/-86.152363,39.417243/-87.304729,41.606680/-87.494734,41.681400/-87.493623,41.639460/-86.907743,41.717022/-86.684615,41.629098/-85.656937,40.002547/-86.248784,39.646254/-86.021317,39.858922/-86.186314,39.749019/-86.060850,39.789486/-86.477893,39.575634/-86.603594,38.113159/-87.199248,41.617558/-87.038546,41.510293/-87.718429,38.005289/-86.214683,41.696692/-85.870648,39.613423/-87.569458,38.021727/-87.536957,38.113947/-87.401398,39.486150/-87.313056,39.560556/-87.278337,38.052003/-87.341396,38.194501/-87.321939,37.954511/-83.736940,36.608430/-84.852637,38.918330/-82.640410,38.459340/-85.711920,37.986290/-82.988100,38.238870/-87.323337,36.911710/-87.075307,37.780776/-86.142953,37.131790/-84.468333,38.125833/-84.497610,38.065030/-82.731163,38.548136/-86.897190,37.938290/-85.852629,37.705612/-87.463750,37.871200/-85.576480,38.137840/-85.898040,38.060910/-85.710250,38.263550/-84.588250,37.891470/-84.525000,39.072500/-88.394024,37.155392/-88.572510,37.058220/-86.956097,37.319725/-85.444280,38.400200/-83.209320,37.283290/-82.535320,37.482600/-84.611520,37.097980/-86.566284,36.708607/-87.851944,36.783889/-86.250628,37.035438/-89.955703,29.936909/-76.653056,38.902500/-76.631673,39.462029/-76.474444,39.310833/-76.617194,38.536722/-77.042252,39.444294/-75.860051,39.701444/-76.811864,38.508547/-77.375190,39.422760/-79.012000,39.705950/-76.296946,39.410191/-76.203889,39.563333/-75.797317,39.305021/-77.106876,39.114313/-76.878333,39.055277/-76.744170,38.811940/-77.720244,39.564178/-86.148577,42.767786/-86.109408,44.616943/-86.309694,42.197790/-86.001629,41.895570/-84.393795,42.798339/-83.670159,43.047224/-83.461541,43.168336/-82.642900,43.836388/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8.504420,38.663730/-77.634620,38.852870/-79.884520,37.283420/-79.512570,37.626680/-77.370400,38.481230/-81.254230,36.891170/-77.044350,38.810403/-76.398633,37.000983/-76.438080,36.901180/-76.730780,36.665250/-77.964125,39.448006/-82.425900,38.424133/-80.632633,37.908533/-80.580717,40.421539/-81.628317,38.345600/-79.920867,39.649367/-80.700972,40.114876/-81.552367,39.323533/-87.907990,44.530980/-89.108900,43.315600/-89.357298,43.100838/-88.527778,43.435000/-88.422045,43.687402/-88.818640,43.002000/-87.809300,42.504722/-87.505240,44.443120/-87.616100,44.138619/-89.771830,44.707350/-87.933333,43.016667/-87.913504,43.060975/-87.884000,43.075000/-87.900000,43.181000/-88.395178,44.307380/-87.920000,43.343000/-87.810000,43.498060/-87.798634,42.713897/-89.062810,42.509080/-89.679700,43.435100/-87.716000,43.679000/-88.499046,42.580009/-88.220278,43.327222/-88.215070,43.020075\" ;\n",
      "                :history = \"aqs/hourly_44201_200608.csv;gen -O --format=aqsraw,bdate=\"2006-08-01\",edate=\"2006-08-01\",wktpolygon=\"POLYGON ((-90 25, -75 25, -75 45, -90 45, -90 25))\" --rename=v,Ozone,O3 aqs/hourly_44201_200608.csv aqs.nc;\" ;\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "from PseudoNetCDF import PNC\n",
    "PNC(\"dump\", \"--header\", \"aqs.nc\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Extract CMAQ at AQS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "if os.path.exists(\"cmaq_aqs_extract.nc\"):\n",
    "    os.remove(\"cmaq_aqs_extract.nc\")\n",
    "    \n",
    "PNC(\"gen\", \"-O\", \"--extract-file=aqs.nc\",\n",
    "    \"--variables=O3\", \"--slice=LAY,0\",\n",
    "    \"--from-conv=ioapi\", aconcpath,\n",
    "    \"cmaq_aqs_extract.nc\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PseudoNetCDF.core._files.PseudoNetCDFFile unknown {\n",
       "dimensions:\n",
       "        points = 518 ;\n",
       "        nv = 4 ;\n",
       "        ROW = 122 ;\n",
       "        TSTEP = UNLIMITED // (24 currently) \n",
       "        tnv = 2 ;\n",
       "        LAY = 1 ;\n",
       "        COL = 127 ;\n",
       "        VAR = 7 ;\n",
       "        DATE-TIME = 2 ;\n",
       "\n",
       "variables:\n",
       "        double latitude_bounds(points, nv);\n",
       "                latitude_bounds:coordinates = \"latitude longitude nv\" ;\n",
       "                latitude_bounds:grid_mapping = \"LambertConformalProjection\" ;\n",
       "                latitude_bounds:units = \"degrees_north\" ;\n",
       "                latitude_bounds:standard_name = \"latitude_bounds\" ;\n",
       "        double y(ROW);\n",
       "                y:coordinates = \"ROW\" ;\n",
       "                y:units = \"km\" ;\n",
       "                y:long_name = \"synthesized coordinate from YORIG YCELL global attributes\" ;\n",
       "        integer LambertConformalProjection();\n",
       "                LambertConformalProjection:standard_parallel = array([ 33.,  45.], dtype=float32) ;\n",
       "                LambertConformalProjection:grid_mapping_name = \"lambert_conformal_conic\" ;\n",
       "                LambertConformalProjection:semi_major_axis = 6370000.0 ;\n",
       "                LambertConformalProjection:coordinates = \"\" ;\n",
       "                LambertConformalProjection:latitude_of_projection_origin = 40.0 ;\n",
       "                LambertConformalProjection:longitude_of_central_meridian = -97.0 ;\n",
       "                LambertConformalProjection:semi_minor_axis = 6370000.0 ;\n",
       "        double time_bounds(TSTEP, tnv);\n",
       "                time_bounds:coordinates = \"TSTEP tnv\" ;\n",
       "                time_bounds:units = \"seconds since 1970-01-01 00:00:00\" ;\n",
       "                time_bounds:long_name = \"synthesized time coordinate from SDATE, STIME, STEP global attributes\" ;\n",
       "        double level(LAY);\n",
       "                level:positive = \"down\" ;\n",
       "                level:coordinates = \"LAY\" ;\n",
       "                level:units = \"sigma\" ;\n",
       "                level:standard_name = \"level\" ;\n",
       "        double x(COL);\n",
       "                x:coordinates = \"COL\" ;\n",
       "                x:units = \"km\" ;\n",
       "                x:long_name = \"synthesized coordinate from XORIG XCELL global attributes\" ;\n",
       "        float O3(TSTEP, LAY, points);\n",
       "                O3:long_name = \"O3              \" ;\n",
       "                O3:coordinates = \"time level latitude longitude\" ;\n",
       "                O3:grid_mapping = \"LambertConformalProjection\" ;\n",
       "                O3:units = \"ppmV            \" ;\n",
       "                O3:var_desc = \"Variable O3                                                                     \" ;\n",
       "        double time(TSTEP);\n",
       "                time:bounds = \"time_bounds\" ;\n",
       "                time:coordinates = \"TSTEP\" ;\n",
       "                time:units = \"seconds since 1970-01-01 00:00:00\" ;\n",
       "                time:long_name = \"synthesized time coordinate from SDATE, STIME, STEP global attributes\" ;\n",
       "        double longitude(points);\n",
       "                longitude:bounds = \"longitude_bounds\" ;\n",
       "                longitude:coordinates = \"latitude longitude\" ;\n",
       "                longitude:units = \"degrees_east\" ;\n",
       "                longitude:standard_name = \"longitude\" ;\n",
       "        double latitude(points);\n",
       "                latitude:bounds = \"latitude_bounds\" ;\n",
       "                latitude:coordinates = \"latitude longitude\" ;\n",
       "                latitude:units = \"degrees_north\" ;\n",
       "                latitude:standard_name = \"latitude\" ;\n",
       "        double longitude_bounds(points, nv);\n",
       "                longitude_bounds:coordinates = \"latitude longitude nv\" ;\n",
       "                longitude_bounds:grid_mapping = \"LambertConformalProjection\" ;\n",
       "                longitude_bounds:units = \"degrees_east\" ;\n",
       "                longitude_bounds:standard_name = \"longitude_bounds\" ;\n",
       "        integer TFLAG(TSTEP, VAR, DATE-TIME);\n",
       "                TFLAG:long_name = \"TFLAG           \" ;\n",
       "                TFLAG:coordinates = \"TSTEP VAR DATE-TIME\" ;\n",
       "                TFLAG:units = \"<YYYYDDD,HHMMSS>\" ;\n",
       "                TFLAG:var_desc = \"Timestep-valid flags:  (1) YYYYDDD or (2) HHMMSS                                \" ;\n",
       "        double layer(LAY);\n",
       "                layer:coordinates = \"LAY\" ;\n",
       "                layer:units = \"model layers\" ;\n",
       "                layer:standard_name = \"layer\" ;\n",
       "\n",
       "\n",
       "// global properties:\n",
       "                :IOAPI_VERSION = \"$Id: @(#) ioapi library version 3.1 OpenMP enabled $                            \" ;\n",
       "                :EXEC_ID = \"CCTM_D502a_Linux2_x86_64intel                                                   \" ;\n",
       "                :FTYPE = 1 ;\n",
       "                :CDATE = 2016225 ;\n",
       "                :CTIME = 202104 ;\n",
       "                :WDATE = 2016225 ;\n",
       "                :WTIME = 202104 ;\n",
       "                :SDATE = 2006213 ;\n",
       "                :STIME = 0 ;\n",
       "                :TSTEP = 10000 ;\n",
       "                :NTHIK = 1 ;\n",
       "                :NCOLS = 127 ;\n",
       "                :NROWS = 122 ;\n",
       "                :NLAYS = 35 ;\n",
       "                :NVARS = 7 ;\n",
       "                :GDTYP = 2 ;\n",
       "                :P_ALP = 33.0 ;\n",
       "                :P_BET = 45.0 ;\n",
       "                :P_GAM = -97.0 ;\n",
       "                :XCENT = -97.0 ;\n",
       "                :YCENT = 40.0 ;\n",
       "                :XORIG = 504000.0 ;\n",
       "                :YORIG = -1488000.0 ;\n",
       "                :XCELL = 12000.0 ;\n",
       "                :YCELL = 12000.0 ;\n",
       "                :VGTYP = 7 ;\n",
       "                :VGTOP = 5000.0 ;\n",
       "                :VGLVLS = array([ 1.        ,  0.9975    ,  0.995     ,  0.99000001,  0.98500001,\n",
       "        0.98000002,  0.97000003,  0.95999998,  0.94999999,  0.94      ,\n",
       "        0.93000001,  0.92000002,  0.91000003,  0.89999998,  0.88      ,\n",
       "        0.86000001,  0.83999997,  0.81999999,  0.80000001,  0.76999998,\n",
       "        0.74000001,  0.69999999,  0.64999998,  0.60000002,  0.55000001,\n",
       "        0.5       ,  0.44999999,  0.40000001,  0.34999999,  0.30000001,\n",
       "        0.25      ,  0.2       ,  0.15000001,  0.1       ,  0.05      ,  0.        ], dtype=float32) ;\n",
       "                :GDNAM = \"CMAQ-BENCHMARK  \" ;\n",
       "                :UPNAM = \"WR_ACONC        \" ;\n",
       "                :VAR-LIST = \"O3              NO              CO              NO2             ASO4I           ASO4J           NH3             \" ;\n",
       "                :FILEDESC = \"Concentration file output                                                       Averaged over the synchronization time steps                                    Timestamp represents beginning computed date/time                               Layer mapping (CGRID to AGRID):                                                 Layer  1 to  1                                                                  Layer  2 to  2                                                                  Layer  3 to  3                                                                  Layer  4 to  4                                                                  Layer  5 to  5                                                                  Layer  6 to  6                                                                  Layer  7 to  7                                                                  Layer  8 to  8                                                                  Layer  9 to  9                                                                  Layer 10 to 10                                                                  Layer 11 to 11                                                                  Layer 12 to 12                                                                  Layer 13 to 13                                                                  Layer 14 to 14                                                                  Layer 15 to 15                                                                  Layer 16 to 16                                                                  Layer 17 to 17                                                                  Layer 18 to 18                                                                  Layer 19 to 19                                                                  Layer 20 to 20                                                                  Layer 21 to 21                                                                  Layer 22 to 22                                                                  Layer 23 to 23                                                                  Layer 24 to 24                                                                  Layer 25 to 25                                                                  Layer 26 to 26                                                                  Layer 27 to 27                                                                  Layer 28 to 28                                                                  Layer 29 to 29                                                                  Layer 30 to 30                                                                  Layer 31 to 31                                                                  Layer 32 to 32                                                                  Layer 33 to 33                                                                  Layer 34 to 34                                                                  Layer 35 to 35                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \" ;\n",
       "                :HISTORY = \"\" ;\n",
       "                :Conventions = \"CF-1.6\" ;\n",
       "                :history = \"gen -O --extract-file=aqs.nc --variables=O3 --slice=LAY,0 --from-conv=ioapi cmaq/CCTM_D502a_Linux2_x86_64intel.ACONC.GA12C_20060801.nc4 cmaq_aqs_extract.nc;slice_dim(f, LAY,0, fuzzydim = True); --slice=LAY,0 cmaq_aqs_extract.nc;slice_dim(f, LAY,0, fuzzydim = True); \" ;\n",
       "                :lonlatcoords = \"-87.8814,30.498/-85.8022,33.2813/-87.6506,34.7588/-86.1366,32.4986/-86.0539,33.904/-85.4231,31.1907/-86.815,33.5531/-86.915,33.4856/-87.0036,33.3311/-87.3056,33.4597/-86.5492,33.5453/-86.8167,33.3864/-86.6692,33.7047/-86.9425,33.8017/-86.7739,33.5783/-87.3397,34.3429/-86.5864,34.6877/-88.0875,30.7699/-88.1411,30.4747/-86.2564,32.4071/-86.9769,34.5187/-85.0838,32.468/-86.8251,33.3173/-88.2019,32.364/-86.1227,33.4983/-87.4597,33.0896/-75.5568,38.9867/-75.732,39.5513/-75.5639,39.8172/-75.4964,39.7739/-75.6106,38.6539/-75.1632,38.7791/-77.1219,38.5832/-76.9581,38.8956/-77.0132,38.9218/-82.2961,29.5447/-82.4411,30.2011/-85.7315,30.1304/-80.6286,28.0536/-80.6156,28.3106/-80.295,26.272/-80.0965,26.292/-80.111,26.087/-81.711,26.27/-82.6192,30.1781/-81.5873,30.4777/-81.454,30.261/-87.2036,30.5254/-87.271,30.368/-87.276,30.399/-81.3406,27.1889/-82.4651,27.74/-82.1621,27.7805/-82.4547,27.9281/-82.5386,27.8922/-82.2304,27.9657/-82.1258,27.9925/-85.6039,30.8486/-81.7233,28.525/-81.98,26.5479/-81.9394,26.4489/-84.3464,30.4397/-84.1994,30.4844/-82.5461,27.6328/-82.6189,27.4806/-82.5222,27.4494/-82.1008,29.1703/-82.1733,29.1925/-80.1618,25.7334/-80.3268,25.5864/-81.3814,28.4542/-81.3625,28.5964/-81.6367,28.3472/-80.2339,26.7308/-80.0609,26.5912/-82.3058,28.3319/-82.7581,28.195/-82.7319,27.9464/-82.7399,27.7859/-82.7008,28.09/-82.0003,27.9394/-81.9722,28.0289/-80.4083,27.4489/-87.008,30.3941/-82.5706,27.3069/-82.48,27.3503/-82.3626,27.0892/-81.3106,28.7461/-80.9939,29.1089/-81.0525,29.2067/-84.1611,30.0925/-83.5435,32.8054/-83.7887,32.828/-81.0488,32.0692/-85.408,34.4743/-83.3445,33.9181/-84.6074,34.0155/-82.1312,33.5821/-84.746,33.404/-84.0598,34.3763/-84.2905,33.688/-84.2134,33.8457/-84.7792,33.7437/-84.419,33.4557/-84.3571,33.7202/-81.4959,31.1697/-84.069,33.9613/-84.1617,33.4336/-84.6264,34.7852/-84.9448,32.5213/-84.8803,32.5087/-85.0453,33.9285/-82.0222,33.4333/-84.0653,33.5911/-84.0811,31.9543/-88.2295,40.1238/-87.6683,39.2109/-87.7325,41.671/-87.5453,41.7558/-87.6356,41.879/-87.6016,41.7908/-87.6077,41.8958/-87.7135,41.7514/-87.792,41.9843/-87.9906,41.6681/-87.7525,41.8552/-87.8632,42.0603/-87.7992,42.14/-87.6753,42.0621/-88.0728,41.813/-88.5489,39.0672/-88.6249,38.0822/-87.8414,42.3867/-87.81,42.4676/-88.2422,42.2214/-88.9969,40.5187/-88.9256,39.8668/-89.8097,39.3961/-89.96,38.7266/-89.6069,40.6874/-89.5859,40.7455/-89.7885,38.1763/-89.6048,39.8441/-88.191,41.2215/-89.077,42.2872/-89.0378,42.335/-85.0168,41.2214/-85.1018,41.095/-86.3952,39.9975/-86.553,40.5405/-85.6903,38.3769/-85.2454,40.3/-85.8306,41.718/-85.8342,38.3081/-86.9901,38.9856/-86.0005,40.0561/-85.8405,39.935/-86.3971,39.759/-86.0805,38.9208/-86.1524,39.4172/-87.3047,41.6067/-87.4947,41.6814/-87.4936,41.6395/-86.9077,41.717/-86.6846,41.6291/-85.6569,40.0025/-86.2488,39.6463/-86.0213,39.8589/-86.1863,39.749/-86.0609,39.7895/-86.4779,39.5756/-86.6036,38.1132/-87.1992,41.6176/-87.0385,41.5103/-87.7184,38.0053/-86.2147,41.6967/-85.8707,39.6134/-87.5695,38.0217/-87.537,38.1139/-87.4014,39.4861/-87.3131,39.5606/-87.2783,38.052/-87.3414,38.1945/-87.3219,37.9545/-83.7369,36.6084/-84.8526,38.9183/-82.6404,38.4593/-85.7119,37.9863/-82.9881,38.2389/-87.3233,36.9117/-87.0753,37.7808/-86.143,37.1318/-84.4683,38.1258/-84.4976,38.065/-82.7312,38.5481/-86.8972,37.9383/-85.8526,37.7056/-87.4638,37.8712/-85.5765,38.1378/-85.898,38.0609/-85.7103,38.2635/-84.5882,37.8915/-84.525,39.0725/-88.394,37.1554/-88.5725,37.0582/-86.9561,37.3197/-85.4443,38.4002/-83.2093,37.2833/-82.5353,37.4826/-84.6115,37.098/-86.5663,36.7086/-87.8519,36.7839/-86.2506,37.0354/-89.9557,29.9369/-76.6531,38.9025/-76.6317,39.462/-76.4744,39.3108/-76.6172,38.5367/-77.0423,39.4443/-75.8601,39.7014/-76.8119,38.5085/-77.3752,39.4228/-79.012,39.706/-76.2969,39.4102/-76.2039,39.5633/-75.7973,39.305/-77.1069,39.1143/-76.8783,39.0553/-76.7442,38.8119/-77.7202,39.5642/-86.1486,42.7678/-86.1094,44.6169/-86.3097,42.1978/-86.0016,41.8956/-84.3938,42.7983/-83.6702,43.0472/-83.4615,43.1683/-82.6429,43.8364/-84.5346,42.7386/-85.5419,42.2781/-85.6713,42.9842/-85.4166,43.1767/-83.9466,41.9956/-82.7935,42.7314/-83.006,42.5133/-86.2426,44.307/-86.2944,43.9533/-84.8919,44.3106/-86.3111,43.2781/-83.1832,42.4631/-85.8527,42.8945/-82.4562,42.9533/-83.5996,42.2406/-83.2082,42.2286/-83.1065,42.3028/-83.096,42.3578/-83.0001,42.4308/-89.9878,34.8217/-89.0498,30.3904/-88.5339,30.3783/-88.7315,32.3646/-88.7662,34.2649/-89.6986,37.7026/-75.0976,39.923/-75.0252,39.4223/-75.2121,39.8003/-79.3188,42.4996/-79.5896,42.2907/-76.8022,42.111/-78.7715,42.9933/-75.9732,44.0875/-75.7844,42.7305/-77.5482,43.1462/-78.4789,43.2239/-75.7198,43.3027/-76.0592,43.0523/-76.4632,43.2843/-77.2098,42.0914/-77.1714,43.2309/-81.1898,35.929/-81.9331,35.9723/-82.5999,35.5001/-81.5303,35.9358/-79.4674,36.307/-79.1597,35.7572/-78.728,35.1587/-78.9625,34.9689/-80.5591,35.8093/-78.9042,36.0356/-77.5828,35.9883/-80.2267,36.1106/-80.2158,36.2031/-80.342,36.026/-80.1439,36.0508/-78.4637,36.0962/-83.7956,35.2579/-78.7681,36.1411/-79.8011,36.1092/-82.9647,35.5053/-82.7925,35.3792/-83.0742,35.5871/-83.2361,35.5244/-78.4619,35.5908/-77.5688,35.2315/-81.2767,35.4386/-76.9062,35.8107/-80.7857,35.2401/-80.9195,35.1132/-80.695,35.3472/-77.8386,34.3642/-79.092,36.307/-77.5989,35.5833/-79.8592,36.3089/-80.395,35.5519/-80.6676,35.5345/-83.4421,35.4348/-80.5408,34.9739/-78.5742,35.8561/-78.7925,35.5969/-82.2649,35.7654/-84.053,40.7729/-80.5728,41.9597/-84.5444,39.3834/-84.3942,39.5284/-83.8046,40.001/-83.9977,39.8557/-84.1441,39.0828/-83.7885,39.43/-81.5753,41.5552/-81.8646,41.3619/-81.4588,41.5373/-83.064,40.3567/-82.9575,39.9138/-82.8156,40.0846/-82.9555,39.9652/-82.9598,40.0877/-81.2499,41.5151/-83.9427,39.6657/-84.3662,39.2787/-84.6909,39.2149/-84.504,39.1289/-80.6156,40.3664/-82.6917,40.31/-81.4225,41.673/-81.2425,41.7223/-82.6664,38.5208/-82.4589,38.629/-82.433,40.026/-82.0957,41.4209/-83.5462,41.6441/-83.7189,41.4942/-83.307,41.6752/-83.4752,41.7195/-83.4761,39.7882/-80.6589,41.0961/-81.9116,41.1009/-84.1138,40.085/-84.1821,39.7807/-81.3305,41.1825/-84.7205,39.8356/-81.3783,40.8281/-81.6008,40.7088/-81.5035,41.1065/-80.591,41.4542/-80.6626,41.2405/-84.2008,39.4269/-81.4604,39.4321/-83.6111,41.3777/-77.25,39.93/-79.9608,40.4654/-80.0162,40.4456/-80.1699,40.3756/-79.7294,40.6139/-79.5648,40.8142/-80.5039,40.5625/-80.3597,40.6847/-80.3164,40.7478/-75.9252,40.3927/-78.3708,40.5353/-78.915,40.3097/-77.877,40.8114/-75.7682,39.8345/-78.5262,41.1175/-76.847,40.247/-76.6814,40.2722/-75.3725,39.8356/-80.0386,42.1418/-77.4756,39.9611/-80.2657,39.8093/-78.92,40.5633/-75.5782,41.4791/-75.6231,41.4428/-76.2833,40.0467/-80.3464,40.9958/-75.4325,40.6119/-76.0033,41.2092/-75.8464,41.2656/-76.9238,41.2508/-80.4848,41.215/-75.3233,41.0831/-75.3092,40.1122/-75.3411,40.6281/-75.2372,40.6922/-77.1656,40.4569/-75.0978,40.0089/-75.2408,40.0496/-75.0116,40.0764/-75.2228,39.9275/-76.9392,41.6447/-79.9022,40.1467/-80.2614,40.1706/-80.4208,40.4453/-79.6928,40.4281/-79.5057,40.3047/-76.6994,39.9653/-82.3864,34.3253/-81.7887,33.3422/-82.4904,34.7769/-81.4655,33.3203/-79.9367,32.9873/-79.6572,32.941/-81.8166,35.1304/-81.2037,34.793/-80.1988,34.6154/-80.965,33.0079/-79.7449,34.2857/-81.8536,33.74/-83.2377,34.8053/-82.8387,34.6536/-80.9623,34.094/-80.7811,33.8147/-80.8683,34.1313/-82.0758,34.9887/-81.5604,34.5394/-79.5651,33.7238/-81.2284,34.9358/-84.2232,35.9652/-83.9416,35.6335/-83.7836,35.6031/-86.7447,36.205/-86.6233,36.1507/-83.1345,36.3078/-85.1816,35.2335/-85.1622,35.1026/-89.1711,35.4687/-83.6021,36.1056/-83.7648,36.0855/-83.8738,36.0192/-87.47,35.116/-84.3422,35.7209/-84.9461,35.2894/-86.5989,35.7329/-83.6097,35.6967/-83.4981,35.5628/-89.8345,35.3782/-82.4245,36.5415/-82.4857,36.5821/-86.6531,36.2976/-86.5641,36.454/-87.137,35.9512/-86.2863,36.0608/-77.0592,38.8577/-77.3774,38.2009/-77.2592,37.3444/-77.5936,37.3575/-77.4652,38.8941/-77.0774,38.7423/-77.1047,38.7733/-77.1634,38.8374/-77.1982,38.9326/-77.7677,38.4737/-78.0816,39.281/-77.2188,37.6061/-77.4003,37.5565/-77.4893,39.0247/-78.4347,38.5231/-78.5044,38.6637/-77.6346,38.8529/-79.8845,37.2834/-79.5126,37.6267/-77.3704,38.4812/-81.2542,36.8912/-77.0443,38.8104/-76.3986,37.001/-76.4381,36.9012/-76.7308,36.6652/-77.9641,39.448/-82.4259,38.4241/-80.6326,37.9085/-80.5807,40.4215/-81.6283,38.3456/-79.9209,39.6494/-80.701,40.1149/-81.5524,39.3235/-87.908,44.531/-89.1089,43.3156/-89.3573,43.1008/-88.5278,43.435/-88.422,43.6874/-88.8186,43.002/-87.8093,42.5047/-87.5052,44.4431/-87.6161,44.1386/-89.7718,44.7074/-87.9333,43.0167/-87.9135,43.061/-87.884,43.075/-87.9,43.181/-88.3952,44.3074/-87.92,43.343/-87.81,43.4981/-87.7986,42.7139/-89.0628,42.5091/-89.6797,43.4351/-87.716,43.679/-88.499,42.58/-88.2203,43.3272/-88.2151,43.0201\" ;\n",
       "}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmaqextract = PNC(\"--slice=LAY,0\", \"cmaq_aqs_extract.nc\").ifiles[0]\n",
    "cmaqextract"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Python Evaluation\n",
    "\n",
    "1. Read in files\n",
    "2. Get variables\n",
    "3. Calculate: Mean obs, mean pred, mean bias, root mean square error\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MO 0.0354791925669\n",
      "MP 0.0274811\n",
      "MB -0.00798024894065\n",
      "RMSE 0.0185395552126\n"
     ]
    }
   ],
   "source": [
    "aqsfile, cmaqfile = PNC(\"aqs.nc\", \"cmaq_aqs_extract.nc\").ifiles\n",
    "aqso3 = aqsfile.variables['O3'][:]\n",
    "cmaqo3 = cmaqfile.variables['O3'][:]\n",
    "\n",
    "bias = cmaqo3 - aqso3\n",
    "rmseO3 = (bias**2).mean()**.5\n",
    "print('MO', aqso3.mean())\n",
    "print('MP', cmaqo3.mean())\n",
    "print('MB', bias.mean())\n",
    "print('RMSE', rmseO3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# PNC Eval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# aqsnc_0 = ifile0 = aqs.nc\n",
      "# cmaq_a_0 = ifile1 = cmaq_aqs_extract.nc\n",
      "# ifile0=aqs.nc\n",
      "# ifile1=cmaq_aqs_extract.nc\n",
      "# Stats calculated as func(ifile0, ifile1)\n",
      "# Generally: func(obs, mod, ....)\n",
      "# Meta-data from aqs.nc\n",
      "# Date Range: 2006-08-01 00:00:00 to 2006-08-01 23:00:00\n",
      "# Longitude Range: -89.98783111572266 to -75.01155090332031\n",
      "# Latitude Range: 25.586383819580078 to 44.70735168457031\n",
      "# Meta-data from cmaq_aqs_extract.nc\n",
      "# Date Range: 2006-08-01 00:00:00 to 2006-08-01 23:00:00\n",
      "# Longitude Range: -90.02883287646353 to -75.33641820005224\n",
      "# Latitude Range: 25.628315232511536 to 39.52255381919687\n",
      "O3,N Observations (#),NO,11943.000000\n",
      "O3,N Predictions (#),NP,12432.000000\n",
      "O3,N Observations/Prediction Pairs (#),NOP,11943.000000\n",
      "O3,Mean Observations (obs unit),MO,0.035479\n",
      "O3,Mean Predictions (model unit),MP,0.027481\n",
      "O3,Mean Bias,MB,-0.007980\n",
      "O3,Root Mean Square Error (model unit),RMSE,0.018540\n",
      "O3,Index of Agreement, IOA,IOA,0.757777\n",
      "O3,Anomaly Correlation,AC,0.583813\n"
     ]
    }
   ],
   "source": [
    "from PseudoNetCDF import PNC\n",
    "PNC(\"eval\", \"--variables=O3\",\n",
    "    \"--funcs=NO,NP,NOP,MO,MP,MB,RMSE,IOA,AC\",\n",
    "    aqsncpath, 'cmaq_aqs_extract.nc');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "anaconda-cloud": {},
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   "display_name": "Python [conda env:atmsci]",
   "language": "python",
   "name": "conda-env-atmsci-py"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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