GISS_SCM_PPE_distill00.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bdcbf3e9",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "2253dd3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors\n",
    "from matplotlib import dates\n",
    "from netCDF4 import num2date,date2num,Dataset\n",
    "import matplotlib._pylab_helpers\n",
    "#from joblib import Parallel, delayed\n",
    "import scipy.interpolate as interpolate\n",
    "from scipy.stats.mstats import scoreatpercentile\n",
    "import scipy.stats as stats\n",
    "from scipy.stats import pearsonr\n",
    "import pandas as pd\n",
    "import os,subprocess,time,copy\n",
    "import scipy\n",
    "import datetime\n",
    "import matplotlib.gridspec as gridspec\n",
    "#import pyart.graph.cm as pcm\n",
    "#import cPickle as pickle\n",
    "#import pickle\n",
    "#import pprint\n",
    "#import triangle\n",
    "import corner\n",
    "#import f90nml\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "id": "e80eb037",
   "metadata": {},
   "outputs": [],
   "source": [
    "from marcus_py_tools import make_edge_vec, xy_from_latlon, latlon_from_xy, walklevel, find_stuff_at_level,haversine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "f25d2210",
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "490be184",
   "metadata": {},
   "outputs": [],
   "source": [
    "def walklevel(some_dir, level=1):\n",
    "    some_dir = some_dir.rstrip(os.path.sep)\n",
    "    assert os.path.isdir(some_dir)\n",
    "    num_sep = some_dir.count(os.path.sep)\n",
    "    for root, dirs, files in os.walk(some_dir):\n",
    "      yield root, dirs, files\n",
    "      num_sep_this = root.count(os.path.sep)\n",
    "      if num_sep + level <= num_sep_this:\n",
    "        del dirs[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1f70f6f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "matplotlib.rcParams.update({'font.size': 14})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "160ebd5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "850 SCM_DYCOMS_gse850F110\n"
     ]
    }
   ],
   "source": [
    "#..Get a list of files to read from\n",
    "case = 'dycoms'\n",
    "#case = 'bomex'\n",
    "#case = 'rico'\n",
    "#case = 'sct'\n",
    "case_upper = case.upper()\n",
    "\n",
    "#main_dir = '/home/marcus/marcus_data/E3SM_BOSS_PPE_data/GISS_SCM_PPE/dycoms/'\n",
    "main_dir = '/data/gelsaess/giss-e3scm-ppe-elsaesser/'+case+'/'\n",
    "#main_dir = '/Users/marcus/Research/Elsaesser_NASA/SCM_PPE/'+case+'/'\n",
    "subdir_list = []\n",
    "num_subdir  = 0\n",
    "for root,dirs,files in walklevel(main_dir,level=0):\n",
    "    for dirr in dirs:\n",
    "        #if dirr.startswith('SCM_'+case_upper+'_jingbo'):\n",
    "        if dirr.startswith('SCM_'+case_upper+'_gse'):\n",
    "            subdir_list.append(dirr)\n",
    "            num_subdir += 1\n",
    "subdir_list = sorted(subdir_list)\n",
    "subdir_list = subdir_list[1:]\n",
    "num_subdir -= 1\n",
    "print(num_subdir,subdir_list[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "29ef08a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Pick one. First see if we can read parameters\n",
    "par_dict = {}\n",
    "pars = []\n",
    "parnames = list()\n",
    "with open(main_dir+subdir_list[420]+'/I') as myfile:\n",
    "    for myline in myfile:\n",
    "        if (myline[0]==' '):\n",
    "            pass\n",
    "        else:\n",
    "            r = re.findall(r'([a-zA-Z]*)=(\\S+)',myline)\n",
    "            for name,val in r:\n",
    "                if val:\n",
    "                    pars = np.r_[pars,float(val)]\n",
    "                parnames = parnames + [name]\n",
    "            idict={name:float(val) for name,val in r}\n",
    "            par_dict.update(idict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "203f0de1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'debdecaytime': 2150.66, 'mc': 42.159, 'xs': 110.259, 'qc': 0.000122477, 'multiplier': 0.639139, 'mstcnv': 10.6449, '': 3.31033, 'urelscale': 65.1935, 'dpscale': 64.3072, 'scale': 0.000714371, 'fevapfac': 0.0327813, 'fac': 1.00092, 'max': 113.406, 'detbyent': 0.357525, 'dd': 5.68312e-05, 'overshoot': 0.270718, 'aspcp': 0.139813, 'fddrt': 0.60429, 'tfmc': 255.196, 'env': 5.26882, 'homf': 237.609, 'rhcsl': 0.833764, 'rhctl': 0.932526, 'homfree': 239960.0, 'dcs': 0.000351213, 'rh': 0.970603, 'pow': 0.212904, 'time': 3553.15, 'cn': 0.838203, 'iifn': 8.71985, 'difn': 8.76673, 'ifluffy': 0.19737, 'sfluffy': 0.612629, 'multi': 0.854739, 'mults': 1.25661, 'entrain': 15.1426}\n",
      "(45,)\n",
      "45\n"
     ]
    }
   ],
   "source": [
    "print(par_dict)\n",
    "print(pars.shape)\n",
    "print(len(parnames))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9364c966",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['debdecaytime', 'mc', 'xs', 'qc', 'multiplier', 'mstcnv', 'mstcnv', '', '', 'urelscale', 'dpscale', '', '', '', '', 'scale', 'fevapfac', 'fac', 'max', 'fac', 'max', 'detbyent', 'dd', 'overshoot', 'aspcp', 'fac', 'fddrt', 'tfmc', 'env', 'homf', 'rhcsl', 'rhctl', 'homfree', 'dcs', 'rh', 'pow', 'time', 'cn', 'iifn', 'difn', 'ifluffy', 'sfluffy', 'multi', 'mults', 'entrain']\n"
     ]
    }
   ],
   "source": [
    "print(parnames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1773df9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#.. Now let's make a plot or two\n",
    "idx = 500\n",
    "#nc = Dataset(main_dir+subdir_list[idx]+'/allsteps.cijh1SCM_'+case_upper+'_jingbo'+str(idx+1).zfill(3)+'F110.nc','r')\n",
    "nc = Dataset(main_dir+subdir_list[idx]+'/allsteps.cijh1SCM_'+case_upper+'_gse'+str(idx+1).zfill(3)+'F110.nc','r')\n",
    "time = nc.variables['time'][:]\n",
    "prec = nc.variables['prec'][:,0,0]\n",
    "lwp  = nc.variables['lwp'][:,0,0]\n",
    "nc.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c6935889",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb38acf0dc0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(time,lwp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d2ffc01a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(48,) [ 0.25  0.75  1.25  1.75  2.25  2.75  3.25  3.75  4.25  4.75  5.25  5.75\n",
      "  6.25  6.75  7.25  7.75  8.25  8.75  9.25  9.75 10.25 10.75 11.25 11.75\n",
      " 12.25 12.75 13.25 13.75 14.25 14.75 15.25 15.75 16.25 16.75 17.25 17.75\n",
      " 18.25 18.75 19.25 19.75 20.25 20.75 21.25 21.75 22.25 22.75 23.25 23.75]\n"
     ]
    }
   ],
   "source": [
    "print(time.shape,time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "0adf6fbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Roll through all PPE files, scrape out what's requested\n",
    "def scrape_singletime_PPE(main_dir,case_upper,subdir_list,varn='prec',ftype='c',tidx=12):\n",
    "    varz = []\n",
    "    for i in range(num_subdir):\n",
    "        flnm=main_dir+subdir_list[i]+'/allsteps.'+ftype+'ijh1SCM_'+case_upper+'_gse'+str(i+1).zfill(3)+'F110.nc'\n",
    "        nc = Dataset(flnm,'r')\n",
    "        var = nc.variables[varn][tidx,0,0]\n",
    "        nc.close()\n",
    "        varz = np.r_[varz,var]\n",
    "    return varz\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "0493c0e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Get inversion height (from theta gradient below 6km) -- maybe not needed since there's a PBL variable\n",
    "def find_nearest(array, value):\n",
    "    array = np.asarray(array)\n",
    "    idx = (np.abs(array - value)).argmin()\n",
    "    return array[idx]\n",
    "\n",
    "def get_inv_height(main_dir,case_upper,subdir_list,maxheight=6000,tidx=12):\n",
    "    varz = []\n",
    "    for i in range(num_subdir):\n",
    "        #..look for max of delta(theta) below maxheight, output the av of the height of the two cells\n",
    "        nc = Dataset(main_dir+subdir_list[i]+'/allsteps.aijlh1SCM_'+case_uppper+'_gse'+str(i+1).zfill(3)+'F110.nc',\n",
    "                     'r')\n",
    "        var = nc.variables['th'][tidx,:,0,0]\n",
    "        zax   = nc.variables['z'][tidx,:,0,0]\n",
    "        nc.close()\n",
    "        idx_zmax = np.abs(zax-6000.).argmin()\n",
    "        dvar = var[1:idx_zmax] - var[:idx_zmax-1]\n",
    "        varz = np.r_[varz,zax[dvar.argmax()]]\n",
    "    return varz\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "3a6f0809",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..List of 1D variables and the file type for each\n",
    "#..        precip  pbl height  stratiform opt   conv opt\n",
    "# od_vars = ['prec', 'pblht',   'tau_ss',       'tau_mc', 'olr' ]\n",
    "# ft_vars = ['c',     'a',      'c',             'c',      'r']\n",
    "\n",
    "od_vars = ['prec', 'pblht',   'tau_ss',     'olr' ]\n",
    "ft_vars = ['c',     'a',      'c',            'r']\n",
    "\n",
    "#..Maybe some 2D variables we'd like to look at later?\n",
    "#..        strat_cloud  strat_prec\n",
    "td_vars = ['qpl',       'qcl']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ed1a2b1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "e2fb3b64",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Surface precip sucks because it's almost always zero. Let's get precip (well, qpl) at cloud base\n",
    "#..Define as: qcl > 1e-4, delta(qcl) > 0.\n",
    "def get_prec_cloudbase(main_dir,case_upper,subdir_list,maxheight=6000.,tidx=12,qcl_thr=5.e-5,dqcl_thr=1.e-5,logy=True):\n",
    "    varz = []\n",
    "    zz   = []\n",
    "    for i in range(num_subdir):\n",
    "        #..look for max of delta(theta) below maxheight, output the av of the height of the two cells\n",
    "        nc = Dataset(main_dir+subdir_list[i]+'/allsteps.cijlh1SCM_'+case_upper+'_gse'+str(i+1).zfill(3)+'F110.nc',\n",
    "                     'r')\n",
    "        qcl   = nc.variables['qcl'][tidx,:,0,0]\n",
    "        qpl   = nc.variables['qpl'][tidx,:,0,0]\n",
    "        nc.close()\n",
    "        nc = Dataset(main_dir+subdir_list[i]+'/allsteps.aijlh1SCM_'+case_upper+'_gse'+str(i+1).zfill(3)+'F110.nc',\n",
    "                     'r')\n",
    "        zax   = nc.variables['z'][tidx,:,0,0]\n",
    "        nc.close()\n",
    "        idx_zmax = np.abs(zax-maxheight).argmin()\n",
    "        condition = True\n",
    "        j = 0\n",
    "        if logy:\n",
    "            while condition:\n",
    "                if (qcl[j]>qcl_thr) and (qcl[j+1]-qcl[j]>dqcl_thr):\n",
    "                    if (qpl[j]>0.):\n",
    "                        varz = np.r_[varz,np.log10(qpl[j])]\n",
    "                    else:\n",
    "                        varz = np.r_[varz,-15.]\n",
    "                    zz   = np.r_[zz,zax[j]]\n",
    "                    condition = False\n",
    "                if j==idx_zmax:\n",
    "                    varz = np.r_[varz,-15.]\n",
    "                    zz   = np.r_[zz,0.]\n",
    "                    condition = False\n",
    "                j += 1     \n",
    "        else:\n",
    "            while condition:\n",
    "                if (qcl[j]>qcl_thr) and (qcl[j+1]-qcl[j]>dqcl_thr):\n",
    "                    varz = np.r_[varz,qpl[j]]\n",
    "                    zz   = np.r_[zz,zax[j]]\n",
    "                    condition = False\n",
    "                if j==idx_zmax:\n",
    "                    varz = np.r_[varz,0.]\n",
    "                    zz   = np.r_[zz,0.]\n",
    "                    condition = False\n",
    "                j += 1  \n",
    "    return varz,zz\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "979d456f",
   "metadata": {},
   "outputs": [],
   "source": [
    "prec_clb,zz = get_prec_cloudbase(main_dir,case_upper,subdir_list,qcl_thr=5.e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "b639204a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 22.,   0.,   8.,  47.,   0.,  18., 204.,   0., 528.,  23.]),\n",
       " array([  0.        ,  57.99935303, 115.99870605, 173.99805908,\n",
       "        231.99741211, 289.99676514, 347.99611816, 405.99547119,\n",
       "        463.99482422, 521.99417725, 579.99353027]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IvfDCCwGnx3bu3KmWlhbl5OT4Q48kJSYmasGCBbpw4YIOHz4czJQBAAD8emVxc2Njow4fPiyHw6GxY8dKun70pqamRsnJyXK5XAH1Q4cO1ZQpU3Tp0iV/UJLkP5WVmpra7jN8werIkSO9MWUAAGCh7p8zauPq1avasmWLWltb9dFHH+n1119XdXW18vLyFB8fL+l68JHk//nL2ta1fR4WFqbIyMgu67vS1NSkpqYm/89dLaIGAAB26XHwabs2Z8iQIfrFL36hlStX+sfq6uokKeCUVVu+83W+Ot/zESNGdLu+I4WFhQFzAwAA8OnRqa7Y2FgZY9TS0qL3339fBQUFysnJ0axZs9TS0tLbcwxKdna26urq/I/q6up+nQ8AABg4enTEx2fw4MGKjY3VqlWrNHjwYGVlZam4uFg/+clP/Ed6OjtC4zsF1faIkG/1dnfrO+J0OuV0OoPeFwAAcPvrtSs3+xYk+xYo32hNTkdrgOLj41VfX6/a2tpu1QMAAASj14JPTU2NJPm/7h4fH6+oqChVVFS0u1BhY2OjysvLFRUVpdGjR/vHU1JSJEllZWXt3r+0tDSgBgAAIFhBBZ/Tp093eCrq008/1bPPPitJmj59uiTJ4XAoPT1d9fX1KigoCKgvLCzUlStXlJ6eLofD4R9fvHixQkJCtG7duoDPOXv2rPbs2aO4uDhNnTo1mCkDAAD4BbXGZ9euXdq+fbseeughxcTEyOVy6YMPPtBrr72m+vp6zZo1Sz/60Y/89VlZWTp48KCKiop06tQpTZgwQZWVlTp06JDGjx+vrKysgPdPSEjQmjVrtHr1ao0bN06zZ89WQ0OD9u/fr+bmZhUXFwd11WYAAIC2gkoRs2fPVl1dnY4dO6by8nJ99tlnuuuuu/Tggw9qwYIFeuKJJwKO4LhcLnk8HuXn5+vAgQPyeDyKjIxURkaG8vLy2l3YUJJycnIUGxurLVu2aOvWrQoNDdXkyZNVUFCgSZMmffU9BgAA1grqXl23Iu7VBQB24l5dt7YBca8uAACAWxnBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANQg+AADAGgQfAABgDYIPAACwBsEHAABYg+ADAACsQfABAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANQg+AADAGgQfAABgDYIPAACwBsEHAABYg+ADAACsQfABAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1ggq+Fy6dElbtmxRamqqRo4cqdDQUEVGRmrWrFk6fvx4h6/xer3KzMxUTEyMnE6nYmJilJmZKa/X2+nnlJSUKCkpSS6XSxEREZoxY4ZOnjwZ3J4BAAB8SVDB51/+5V+UkZGh//qv/9IjjzyilStX6sEHH9S///u/a/LkyfrlL38ZUN/Q0KCUlBRt3rxZY8aMUUZGhsaOHavNmzcrJSVFDQ0N7T5j/fr1mjdvni5fvqwVK1Zozpw5qqioUHJysjwez1faWQAAYDeHMcZ0t/jll1/W3Xffre9973sB42+++aYefvhhDRs2TDU1NXI6nZKkvLw8FRQUKCsrSxs3bvTX+8Zzc3OVn5/vH6+qqtLYsWM1atQonThxQm63W5J09uxZJSUl6Z577tG5c+cUEhLS7R30er1yu92qq6tTeHh4t18HALi1xa56rb+nELSLGx7t7ykMGH319zuo4NOVtLQ0lZWV6e2339bEiRNljNF9990nr9er2tpauVwuf21jY6OioqL0ta99TdXV1XI4HJKkZ599VoWFhdq9e7cWLFgQ8P4/+clPtG3bNpWWlio1NbXb8yL4ABho+IN8c9DnW1tf/f3utcXNQ4YMkST/0ZiqqirV1NQoOTk5IPRI0tChQzVlyhRdunRJ58+f94/7TmV1FGzS0tIkSUeOHOmtKQMAAMv0SvD58MMP9dvf/laRkZH61re+Jel68JGk+Pj4Dl/jG/fV+Z6HhYUpMjKyW/UdaWpqktfrDXgAAABIvRB8mpubNX/+fDU1NamoqEiDBw+WJNXV1UmSf53Ol/kOW/nqfM+Dqe9IYWGh3G63/xEdHR3cDgEAgNvWVwo+ra2tWrJkicrLy7Vs2TLNnz+/t+bVY9nZ2aqrq/M/qqur+3tKAABggOj+16O+xBijZcuWad++fXryySe1bdu2gO2+IzedHaHxnYJqe4THt4ipu/UdcTqd/m+VAQAAtNWjIz6tra1aunSpduzYoblz52rXrl0aNCjwrW60JqejNUDx8fGqr69XbW1tt+oBAACCEXTwaW1tVXp6unbu3KnHH39ce/fu9a/raSs+Pl5RUVGqqKhod6HCxsZGlZeXKyoqSqNHj/aPp6SkSJLKysravV9paWlADQAAQLCCCj6+Iz07d+7UD3/4Q+3bt6/D0CNJDodD6enpqq+vV0FBQcC2wsJCXblyRenp6f5r+EjS4sWLFRISonXr1gWc8jp79qz27NmjuLg4TZ06NZgpAwAA+AW1xqegoEC7du1SWFiYEhIStHbt2nY1M2fO1Pjx4yVJWVlZOnjwoIqKinTq1ClNmDBBlZWVOnTokMaPH6+srKyA1yYkJGjNmjVavXq1xo0bp9mzZ6uhoUH79+9Xc3OziouLg7pqMwAAQFtBpYiLFy9Kkurr67Vu3boOa2JjY/3Bx+VyyePxKD8/XwcOHJDH41FkZKQyMjKUl5fX7sKGkpSTk6PY2Fht2bJFW7duVWhoqCZPnqyCggJNmjQpuL0DAABoo9duWTFQccsKAAMNt1K4OejzrW3A37ICAABgoCP4AAAAaxB8AACANQg+AADAGgQfAABgDYIPAACwBsEHAABYg+ADAACsQfABAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANQg+AADAGgQfAABgDYIPAACwBsEHAABYg+ADAACsQfABAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANYIOPvv27dPy5cs1ceJEOZ1OORwO7dq1q9N6r9erzMxMxcTEyOl0KiYmRpmZmfJ6vZ2+pqSkRElJSXK5XIqIiNCMGTN08uTJYKcKAAAQIOjgs3r1av3rv/6rPvjgA91zzz1d1jY0NCglJUWbN2/WmDFjlJGRobFjx2rz5s1KSUlRQ0NDu9esX79e8+bN0+XLl7VixQrNmTNHFRUVSk5OlsfjCXa6AAAAfkEHn+3bt+vixYv6+OOPtWLFii5ri4qKdPr0aWVlZamsrEwbNmzQoUOHlJubq9OnT6uoqCigvqqqSnl5eUpISNAf/vAHbdq0Sc8//7x+97vfKSQkROnp6WppaQl2ygAAAJJ6EHz+8i//UjExMTesM8Zo+/btCgsLU25ubsC27OxsRURE6IUXXpAxxj++c+dOtbS0KCcnR2632z+emJioBQsW6MKFCzp8+HCwUwYAAJDUh4ubq6qqVFNTo+TkZLlcroBtQ4cO1ZQpU3Tp0iWdP3/eP+47lZWamtru/dLS0iRJR44c6aspAwCA21yfBh9Jio+P73C7b9xX53seFhamyMjIbtUDAAAEI6Sv3riurk6SAk5ZtRUeHh5Q53s+YsSIbtd3pKmpSU1NTf6fu/r2GAAAsMttdx2fwsJCud1u/yM6Orq/pwQAAAaIPgs+viM9nR2h8R2JaXtEyO12B1XfkezsbNXV1fkf1dXVQc8dAADcnvos+NxoTU5Ha4Di4+NVX1+v2trabtV3xOl0Kjw8POABAAAg9XHwiYqKUkVFRbsLFTY2Nqq8vFxRUVEaPXq0fzwlJUWSVFZW1u79SktLA2oAAACC1WfBx+FwKD09XfX19SooKAjYVlhYqCtXrig9PV0Oh8M/vnjxYoWEhGjdunUBp7zOnj2rPXv2KC4uTlOnTu2rKQMAgNtc0N/q2r59u9566y1J0n/+53/6x3zX4Jk5c6ZmzpwpScrKytLBgwdVVFSkU6dOacKECaqsrNShQ4c0fvx4ZWVlBbx3QkKC1qxZo9WrV2vcuHGaPXu2GhoatH//fjU3N6u4uFghIX32RTQAAHCbCzpFvPXWW9q9e3fAWEVFhSoqKiRJsbGx/uDjcrnk8XiUn5+vAwcOyOPxKDIyUhkZGcrLy2t3YUNJysnJUWxsrLZs2aKtW7cqNDRUkydPVkFBgSZNmtSDXQQAALjOYdreM+I25PV6/d8WY6EzgIEgdtVr/T2FoF3c8Gh/TyFo9PnW1ld/v2+76/gAAAB0huADAACsQfABAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANQg+AADAGgQfAABgDYIPAACwBsEHAABYg+ADAACsQfABAADWCOnvCQC3q9hVr/X3FIJ2ccOj/T0FAOhTHPEBAADWIPgAAABrEHwAAIA1CD4AAMAaBB8AAGANgg8AALAGwQcAAFiD4AMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWCOkvycAAACui131Wn9PIWgXNzza31MICsHnK+AXFACAWwunugAAgDU44gPglnYrHnkF0H844gMAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoDNvi8/fbbmjFjhiIiIuRyuZSUlKSSkpL+nhYAALiFDcivs3s8HqWlpSk0NFRPPPGE3G63Xn75Zc2bN08XL17Us88+299TxE3GV5YBAL1hwB3xaWlpUXp6uhwOh8rLy1VcXKznnntOlZWVSkxMVF5enqqqqvp7mgAA4BY04ILP4cOHdeHCBf3oRz/SX/zFX/jHhw0bpn/8x39US0uLdu7c2Y8zBAAAt6oBF3w8Ho8kKTU1td0239iRI0du5pQAAMBtYsCt8fGdxoqPj2+3LSIiQsOHD+/yVFdTU5Oampr8P9fV1UmSvF5vL89Uam36rNffs6/1RR9uhlux17eiW/H3g9+Nm4PfDXSmr343fO9rjOnV9x1wwccXVNxud4fbw8PD9d///d+dvr6wsFD5+fntxqOjo3tngrc495b+ngEGMn4/0Bl+N9CZvv7duHbtWqeZoCcGXPD5qrKzs5WZmen/ubW1VZ9++qm+/vWvy+Fw9NrneL1eRUdHq7q6WuHh4b32vrc7+tYz9K1n6Fvw6FnP0Lee6apvxhhdu3ZNUVFRvfqZAy74+FKd78jPl3m93i6Tn9PplNPpDBi78847e21+XxYeHs4veQ/Qt56hbz1D34JHz3qGvvVMZ33rzSM9PgNucbNvbU9H63iuXLmiTz75pMP1PwAAADcy4IJPSkqKJKmsrKzdNt+YrwYAACAYAy74PPzwwxo1apRKSkp0+vRp//i1a9f085//XCEhIVq0aFG/zc/H6XQqLy+v3Wk1dI2+9Qx96xn6Fjx61jP0rWf6o28O09vfE+sFb7zxhtLS0uR0OjV37lyFh4fr5Zdf1vvvv6+1a9cqJyenv6cIAABuQQMy+EjSiRMnlJeXp6NHj+r//u//lJiYqJ/+9KeaN29ef08NAADcogZs8AEAAOhtA26NDwAAQF8h+AAAAGsQfIL09ttva8aMGYqIiJDL5VJSUpJKSkr6e1o31b59+7R8+XJNnDhRTqdTDodDu3bt6rTe6/UqMzNTMTExcjqdiomJUWZmZpf3dykpKVFSUpJcLpciIiI0Y8YMnTx5sg/25ua4dOmStmzZotTUVI0cOVKhoaGKjIzUrFmzdPz48Q5fY3vfrl69qqeffloPPPCAIiMj5XQ6de+992rq1Kl66aWXOrx/j+0960xRUZEcDoccDoeOHTvWYQ29k2JjY/19+vJjxYoV7erpWaBXXnlFjzzyiL7+9a/rjjvu0De+8Q3NnTtX1dXVAXX93jeDbnvjjTdMaGioCQsLM+np6WblypXmG9/4hpFk1q1b19/Tu2liYmKMJDN8+HD/8507d3ZYW19fb8aPH28kmUceecQ888wzZtq0aUaSGT9+vKmvr2/3mnXr1hlJZuTIkSYzM9P8+Mc/NuHh4SY0NNS88cYbfbtzfeSZZ54xkkxcXJxZsmSJWbVqlZk1a5YZPHiwGTRokPm3f/u3gHr6ZkxVVZVxuVzm4YcfNsuXLzfZ2dlm6dKlZsSIEUaSWbZsWUA9PevYO++8Y5xOp3G5XEaSOXr0aLsaenddTEyMcbvdJi8vr93jP/7jPwJq6dkXWltbzY9//GP/v3F/+7d/a5555hkzf/58M3LkSPPmm2/6awdC3wg+3dTc3Gzi4uKM0+k0v//97/3jXq/XJCYmmpCQEPPHP/6xH2d48/zmN78xFy9eNMYYU1hY2GXwyc3NNZJMVlZWh+O5ubkB43/84x9NSEiISUhIMFevXvWPnzlzxnzta18zcXFxprm5uXd36CZ46aWXTHl5ebvx8vJyM2TIEHPXXXeZxsZG/zh9M6alpaXDOXu9XjN27FgjyZw5c8Y/Ts/aa2lpMZMmTTJJSUnmySef7DT40LvrYmJiTExMTLdq6dkX/vmf/9lIMk899ZRpaWlpt73tfg2EvhF8uqm0tNRIMosXL2637cUXXzSSTHZ2dj/MrH91FXxaW1tNVFSUCQsLa5fi//SnP5mIiAhz7733mtbWVv94dna2kWR2797d7v1WrFhhJJnS0tJe34/+lJqaaiSZt99+2xhD37ojIyPDSDKvvvqqMYaedWbdunUmNDTUnDlzxixcuLDD4EPvvtDd4EPPvvDZZ5+Zu+66y4waNeqGAWSg9I01Pt3k8XgkSampqe22+caOHDlyM6c04FVVVammpkbJyclyuVwB24YOHaopU6bo0qVLOn/+vH+8qz6npaVJuv36PGTIEElSSMj1ewbTt641Njbq8OHDcjgcGjt2rCR61pEzZ84oPz9fq1evVmJiYqd19C5QU1OTdu/erfXr12vr1q2qrKxsV0PPvvCb3/xGn376qWbOnKnPP/9cL7/8sjZs2KBt27YF7L80cPo24O7OPlD5bpra0Q1SIyIiNHz48A5vrGqzrnrWdryqqirgeVhYmCIjI7usv118+OGH+u1vf6vIyEh961vfkkTfvuzq1avasmWLWltb9dFHH+n1119XdXW18vLy2u0bPbuupaVFixYt0je/+U2tWrWqy1p6F6i2trbdbZGmTZumvXv3avjw4ZLoWVu+BcYhISH69re/rffee8+/bdCgQcrIyNBzzz0naeD0jSM+3VRXVydJcrvdHW4PDw/31+C67vSsbZ3veTD1t7Lm5mbNnz9fTU1NKioq0uDBgyXRty+7evWq8vPz9fOf/1zPP/+8amtr9Ytf/EJ5eXn+GnoWaP369aqsrNSOHTv8RxQ7Q+++sGTJEnk8Hn388cfyer06duyYpk+frl//+td67LHH/N8kpGdf+OijjyRJmzZtUnh4uE6cOKFr166pvLxcCQkJ2rRpk7Zu3Spp4PSN4AP0g9bWVi1ZskTl5eVatmyZ5s+f399TGrBiY2NljFFLS4vef/99FRQUKCcnR7NmzVJLS0t/T2/Aqays1Nq1a/Wzn/1M999/f39P55aSm5urlJQUDR8+XMOGDdN3vvMd/epXv9KDDz6oo0eP6vXXX+/vKQ44ra2tkqTQ0FC9+uqrmjRpksLCwvS9731PBw4c0KBBg7Rp06Z+nmUggk83+RJnZ8nS6/V2mkpt1Z2eta3zPQ+m/lZkjNGyZcu0b98+Pfnkk9q2bVvAdvrWscGDBys2NlarVq3S2rVr9corr6i4uFgSPWtr4cKFiouL05o1a7pVT++6NmjQIC1evFiSVFFRIYmeteWb88SJExUVFRWwLTExUaNGjdKFCxd09erVAdM3gk83dXUu8cqVK/rkk086PW9pqxudf+3ofG98fLzq6+tVW1vbrfpbTWtrq5YuXaodO3Zo7ty52rVrlwYNCvzPkL7dmG+ho2/hIz37QmVlpc6dO6ehQ4cGXIBv9+7dkqQHHnhADodDr776qiR61x2+tT2fffaZJHrW1pgxYyRJd955Z4fbfeN/+tOfBkzfCD7dlJKSIkkqKytrt8035qvBdfHx8YqKilJFRYUaGhoCtjU2Nqq8vFxRUVEaPXq0f7yrPpeWlgbU3GpaW1uVnp6unTt36vHHH9fevXv963raom83VlNTI+mLb8LRsy8sXbq0w4fvj8Njjz2mpUuXKjY2VhK96w7f1dXpWXsPPfSQJOndd99tt625uVnnz5+Xy+XS3XffPXD6FtSX3y3W3NxsRo0aZZxOpzl16pR/vO0FDN97773+m2A/6e0LGL733nu35UW+Pv/8c7No0SIjyfzwhz+84T7QN2NOnToVsC8+//u//+u/8uvevXv94/Ssa51dx8cYemeMMWfPnjVXrlxpN/7mm2+aoUOHGqfTaT744AP/OD37gu9aZMXFxQHjBQUFRpJ58skn/WMDoW8EnyAcPnzYDBkyxISFhZlly5YF3LJi7dq1/T29m6a4uNgsXLjQLFy40Nx///1GkklOTvaPvfLKK/7aL1+efNWqVWb69OldXp587dq1AZcnX758uQkPDzdDhgwxhw8fvol72nvy8vKMJBMWFmZycnI6vCR+20BN34z5h3/4B+NyucwPfvAD89RTT5msrCzz+OOPm7CwMCPJzJo1y3z++ef+enrWta6CD727/t/oHXfcYX7wgx+Yv/u7vzMrV640aWlpxuFwmMGDB7f7o07PvnD+/Hn/rWQeffRRs3LlSjN16lQjycTExJj/+Z//8dcOhL4RfIJ0/PhxM23aNON2u80dd9xhJk6caPbt29ff07qpfP+AdvbIy8sLqL969arJyMgw0dHRZsiQISY6OtpkZGR0+H/zPvv27TMTJ040d9xxh3G73WbatGnmxIkTfbxnfedGPevoqJntfXvzzTfNokWLzJ//+Z+b8PBwExISYkaMGGGmTZtmSkpKAq7u6mN7z7rSVfAxht55PB4zZ84cM3r0aDNs2DAzZMgQc99995knnnjCHD9+vMPX2N6ztj788EOzaNEiExkZ6e/FU089ZS5fvtyutr/75jCmg1scAwAA3IZY3AwAAKxB8AEAANYg+AAAAGsQfAAAgDUIPgAAwBoEHwAAYA2CDwAAsAbBBwAAWIPgAwAArEHwAQAA1iD4AAAAaxB8AACANQg+AADAGv8PZ/rUrUcsfzsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(zz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "96d9169c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([198.,   0.,   1.,   0.,   1.,   1.,   1.,   1.,   2.,   0.,   1.,\n",
       "          5.,  25., 121., 165., 189.,  15.,  11.,  52.,  61.]),\n",
       " array([-15.        , -14.47106354, -13.94212708, -13.41319063,\n",
       "        -12.88425417, -12.35531771, -11.82638125, -11.2974448 ,\n",
       "        -10.76850834, -10.23957188,  -9.71063542,  -9.18169897,\n",
       "         -8.65276251,  -8.12382605,  -7.59488959,  -7.06595314,\n",
       "         -6.53701668,  -6.00808022,  -5.47914376,  -4.9502073 ,\n",
       "         -4.42127085]),\n",
       " <BarContainer object of 20 artists>)"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Look at some of output\n",
    "#plt.hist(out_file[:,0])\n",
    "plt.hist(prec_clb,bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "447434f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(850, 4)\n"
     ]
    }
   ],
   "source": [
    "#..loop through files and dump requested outputs to some outputs file\n",
    "numout   = len(od_vars)\n",
    "out_file = np.zeros((num_subdir,numout))\n",
    "print(out_file.shape)\n",
    "for i in range(numout):\n",
    "    out_file[:,i] = scrape_singletime_PPE(main_dir,case_upper,subdir_list,varn=od_vars[i],ftype=ft_vars[i])\n",
    "    \n",
    "#..Replace precip with precip at cloud base\n",
    "out_file[:,0] = prec_clb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "bf32025d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Save the file\n",
    "#np.savetxt('giss_scm_ppe_dycomsonly_00.txt',out_file)  #..first try\n",
    "np.savetxt('giss_scm_ppe_dycomsonly_01.txt',out_file)  #..replace prec with prec@cloudbase"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "749b5db0",
   "metadata": {},
   "source": [
    "## Now get BOMEX... only LWP for now (hours 3-4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "id": "3b173c0d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "850 SCM_BOMEX_gse850F110\n"
     ]
    }
   ],
   "source": [
    "#..Get a list of files to read from\n",
    "#case = 'dycoms'\n",
    "case = 'bomex'\n",
    "#case = 'rico'\n",
    "#case = 'sct'\n",
    "case_upper = case.upper()\n",
    "\n",
    "#main_dir = '/home/marcus/marcus_data/E3SM_BOSS_PPE_data/GISS_SCM_PPE/dycoms/'\n",
    "main_dir = '/data/gelsaess/giss-e3scm-ppe-elsaesser/'+case+'/'\n",
    "#main_dir = '/Users/marcus/Research/Elsaesser_NASA/SCM_PPE/'+case+'/'\n",
    "subdir_list = []\n",
    "num_subdir  = 0\n",
    "for root,dirs,files in walklevel(main_dir,level=0):\n",
    "    for dirr in dirs:\n",
    "        #if dirr.startswith('SCM_'+case_upper+'_jingbo'):\n",
    "        if dirr.startswith('SCM_'+case_upper+'_gse'):\n",
    "            subdir_list.append(dirr)\n",
    "            num_subdir += 1\n",
    "subdir_list = sorted(subdir_list)\n",
    "subdir_list = subdir_list[1:]\n",
    "num_subdir -= 1\n",
    "print(num_subdir,subdir_list[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "15662bca",
   "metadata": {},
   "outputs": [],
   "source": [
    "od_vars = ['lwp',]\n",
    "ft_vars = ['c',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "id": "86792084",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "(850, 1)\n"
     ]
    }
   ],
   "source": [
    "#..loop through files and dump requested outputs to some outputs file\n",
    "numout   = len(od_vars)\n",
    "print(numout)\n",
    "out_bomex = np.zeros((num_subdir,numout))\n",
    "print(out_bomex.shape)\n",
    "for i in range(numout):\n",
    "    out_bomex[:,i] = scrape_singletime_PPE(main_dir,case_upper,subdir_list,varn=od_vars[i],ftype=ft_vars[i],tidx=6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4aef0446",
   "metadata": {},
   "source": [
    "## Now get RICO... LWP, cloud fraction, RWP (hours 20-24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "53469b62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "850 SCM_RICO_gse850F110\n"
     ]
    }
   ],
   "source": [
    "#..Get a list of files to read from\n",
    "#case = 'dycoms'\n",
    "#case = 'bomex'\n",
    "case = 'rico'\n",
    "#case = 'sct'\n",
    "case_upper = case.upper()\n",
    "\n",
    "#main_dir = '/home/marcus/marcus_data/E3SM_BOSS_PPE_data/GISS_SCM_PPE/dycoms/'\n",
    "main_dir = '/data/gelsaess/giss-e3scm-ppe-elsaesser/'+case+'/'\n",
    "#main_dir = '/Users/marcus/Research/Elsaesser_NASA/SCM_PPE/'+case+'/'\n",
    "subdir_list = []\n",
    "num_subdir  = 0\n",
    "for root,dirs,files in walklevel(main_dir,level=0):\n",
    "    for dirr in dirs:\n",
    "        #if dirr.startswith('SCM_'+case_upper+'_jingbo'):\n",
    "        if dirr.startswith('SCM_'+case_upper+'_gse'):\n",
    "            subdir_list.append(dirr)\n",
    "            num_subdir += 1\n",
    "subdir_list = sorted(subdir_list)\n",
    "subdir_list = subdir_list[1:]\n",
    "num_subdir -= 1\n",
    "print(num_subdir,subdir_list[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "f7fcebb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "od_vars = ['lwp', 'cldtot_2d', 'prec']\n",
    "ft_vars = ['c',   'c',         'c']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "eb9fe023",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(850, 3)\n"
     ]
    }
   ],
   "source": [
    "#..loop through files and dump requested outputs to some outputs file\n",
    "numout   = len(od_vars)\n",
    "out_rico = np.zeros((num_subdir,numout))\n",
    "print(out_rico.shape)\n",
    "for i in range(numout):\n",
    "    out_rico[:,i] = scrape_singletime_PPE(main_dir,case_upper,subdir_list,varn=od_vars[i],ftype=ft_vars[i],tidx=40)\n",
    "    \n",
    "#..Just for rico it would be nice to append RWP, but no dice. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8cd1dce",
   "metadata": {},
   "source": [
    "## Now get TWP-ICE... peak IWP. Or just skip it for now..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53c575ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#..Get a list of files to read from\n",
    "#case = 'dycoms'\n",
    "#case = 'bomex'\n",
    "#case = 'rico'\n",
    "#case = 'sct'\n",
    "case = 'twpice15mins'\n",
    "case_upper = case.upper()\n",
    "\n",
    "#main_dir = '/home/marcus/marcus_data/E3SM_BOSS_PPE_data/GISS_SCM_PPE/dycoms/'\n",
    "main_dir = '/data/gelsaess/giss-e3scm-ppe-elsaesser/'+case+'/'\n",
    "#main_dir = '/Users/marcus/Research/Elsaesser_NASA/SCM_PPE/'+case+'/'\n",
    "subdir_list = []\n",
    "num_subdir  = 0\n",
    "for root,dirs,files in walklevel(main_dir,level=0):\n",
    "    for dirr in dirs:\n",
    "        #if dirr.startswith('SCM_'+case_upper+'_jingbo'):\n",
    "        if dirr.startswith('SCM_'+case_upper+'_gse'):\n",
    "            subdir_list.append(dirr)\n",
    "            num_subdir += 1\n",
    "subdir_list = sorted(subdir_list)\n",
    "subdir_list = subdir_list[1:]\n",
    "num_subdir -= 1\n",
    "print(num_subdir,subdir_list[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc71ac77",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "753e85f1",
   "metadata": {},
   "source": [
    "## Aggregate all the output files into one, save that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "5f3aa91d",
   "metadata": {},
   "outputs": [],
   "source": [
    "out_all  = np.hstack((out_file,out_bomex,out_rico))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "7b4af2cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(850, 8)\n"
     ]
    }
   ],
   "source": [
    "print(out_all.shape)\n",
    "np.savetxt('giss_scm_ppe_dycomsbomexrico_01.txt',out_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f833d512",
   "metadata": {},
   "source": [
    "## Below here is just some plots/tests of output fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "0fabb05f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_23970/3331346384.py:20: RuntimeWarning: divide by zero encountered in log10\n",
      "  pco = ax2.pcolormesh(T1.T,P1.T,np.log10(qpl))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7fb371daf4c0>"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1400x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Look at some of the fields\n",
    "\n",
    "#..Hard to find a case where precip reaches surface\n",
    "idx = 27\n",
    "nc = Dataset(main_dir+subdir_list[idx]+'/allsteps.cijlh1SCM_'+case_upper+'_gse'+str(idx+1).zfill(3)+'F110.nc','r')\n",
    "time1 = nc.variables['time'][:]\n",
    "p1    = nc.variables['p'][:]\n",
    "qcl   = nc.variables['qcl'][:,:,0,0]\n",
    "qpl   = nc.variables['qpl'][:,:,0,0]\n",
    "nc.close()\n",
    "T1,P1 = np.meshgrid(time1,zax[0,:])\n",
    "\n",
    "fig=plt.figure(figsize=(14,8))\n",
    "ax1 = fig.add_subplot(121)\n",
    "pco = ax1.pcolormesh(T1.T,P1.T,qcl)\n",
    "ax1.set_ylim(0,5000)\n",
    "plt.colorbar(pco)\n",
    "\n",
    "ax2 = fig.add_subplot(122)\n",
    "pco = ax2.pcolormesh(T1.T,P1.T,np.log10(qpl))\n",
    "ax2.set_ylim(0,5000)\n",
    "plt.colorbar(pco)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "5021c14c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(48, 110) (48, 110)\n",
      "(110, 48)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb376510ee0>]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Let's try to get boundary layer depth\n",
    "nc = Dataset(main_dir+subdir_list[200]+'/allsteps.aijlh1SCM_'+case_upper+'_gse'+str(200+1).zfill(3)+'F110.nc','r')\n",
    "theta = nc.variables['th'][:,:,0,0]\n",
    "time  = nc.variables['t'][:,:,0,0]\n",
    "zax   = nc.variables['z'][:,:,0,0]\n",
    "p_3d  = nc.variables['p_3d'][:,:,0,0]\n",
    "time1 = nc.variables['time'][:]\n",
    "p1    = nc.variables['p'][:]\n",
    "nc.close()\n",
    "print(time.shape,zax.shape)\n",
    "\n",
    "fig = plt.figure(figsize=(10,7))\n",
    "ax = fig.add_subplot(111)\n",
    "#T1,P1 = np.meshgrid(time1,p1)\n",
    "T1,P1 = np.meshgrid(time1,zax[0,:])\n",
    "print(T1.shape)\n",
    "#ax.pcolormesh(T1.T,P1.T,theta[:,:])\n",
    "pco = ax.pcolormesh(T1[1:,:].T,P1[1:,:].T,theta[:,1:]-theta[:,:-1],vmin=0,vmax=10)\n",
    "#ax.set_yscale('log')\n",
    "ax.set_ylim(0,10000)\n",
    "plt.colorbar(pco)\n",
    "\n",
    "#..Plot the PBL height variable on here\n",
    "nc = Dataset(main_dir+subdir_list[200]+'/allsteps.aijh1SCM_'+case_upper+'_gse'+str(200+1).zfill(3)+'F110.nc','r')\n",
    "pblh = nc.variables['pblht'][:,0,0]\n",
    "nc.close()\n",
    "ax.plot(time1[1:],pblh[1:],'w-')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a3ff3ae",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "8e02bda4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fb371481870>"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Xv/hFXNflgx/84IK3pyMdGo1Go9FoOvK9732Pm2++mXe84x1s2rQJ13X59a9/zT333INhGHz1q19lw4YNC96eFh0ajUaj0awAjkV65YILLuA3v/kNv/zlL3nggQcol8usXr2a3/u93+OKK67g7LPPXtT2tOjQaDQajWYFEEKjAuVw118s5513Huedd95h71NFezo0Go1Go9EcFXSkQ6PRaDSaFcDSm4Md+ziDFh0ajUaj0awAmluZH+76x5pjfwQajUaj0WheFehIh0aj0Wg0K4AQQchSjKSHv+5yoUWHRqPRaDQrgBMhvaJFh0aj0Wg0K4Cl9+k49qLj2B+BRqPRaDSaVwU60qHRaDQazQoglIJwKc3BlrDucqFFh0aj0Wg0K4BwiemV46FPx7E/Ao1Go9FoNK8KdKRDo9FoNJoVwOGOp29e/1ijRYdGo9FoNCuAAEGwhF4bS1l3uTj2skej0Wg0Gs2rAh3p0Gg0Go1mBaDTKxqNRqPRaI4KAUtLkQTLdyiHzaJlz+23387HP/5xzjzzTFzXRQjBN7/5zbblPM/jBz/4AR/5yEc47bTTSCaTpNNp3vzmN/N3f/d3BMHsL/873/kOZ599Nslkkp6eHt773vfyxBNPzLr8jh07uPTSSxkYGCAej3PGGWfwt3/7t4RhuNiXp9FoNBqN5gix6EjHNddcw+7du+nv72fNmjXs3r2743K7du3ikksuIZ1Oc+GFF/K+972PbDbLj3/8Yz71qU/x05/+lH/6p39CiFbV9vnPf56rr76aDRs28IlPfIJ8Ps93v/tdzj33XO6++27OP//8luWfe+45zjnnHIrFIpdeeilr167lrrvu4tOf/jRPP/00X//61xf7EjUajUajOe44EdIriz6C2267jVdeeYXR0VE+8YlPzLpcOp3m7/7u7xgeHuZHP/oRN910E1/96ld58cUXOfPMM/nxj3/M97///ZZ1duzYwbXXXsu2bdt4+umn+cIXvsDXvvY1HnnkESzL4vLLL8f3/ZZ1PvnJT5LNZvnRj37E7bffzk033cQvfvEL3vGOd3Drrbdy3333LfYlajQajUZz3FEf+LaU27Fm0Ufwzne+k40bN8673Nq1a/nkJz9JIpFoeTyZTPKZz3wGgAceeKDluW984xv4vs/VV19NJpNpPL59+3Yuu+wydu3axb333tt4/MUXX+TBBx/kggsu4L3vfW/jcdu2ueGGGwC49dZbF/sSNRqNRqM57pC10faHe5Ov1pJZ27YBsKzW7M79998PwLvf/e62dS666CKgVajMtfzZZ59Nd3d3m7DRaDQajUZzbDgm1Sv/8A//ALSLhR07dpBKpRgcHGxbZ+vWrY1lmpdvfq4ZIQRbtmzhiSeeoFgstkVc6lQqFSqVSuN+Lpdb5KvRaDQajebIs9QUyYpMryyVr3/969x1111ceOGFLSkRgGw225JWaaarq6uxTPPywKLWUbnxxhvJZDKN2/r16xf+YjQajUajOUrUp8wu5XasOaqi4yc/+Ql//Md/zMaNG7n99tuP5q5n5aqrriKbzTZue/fuPdaHpNFoNBrNCclRS6/cfffdfOhDH2L16tXce++9rFmzpm2ZTCYza1SinvZojmrUf59vnXrEoxOu6+K67sJehEaj0Wg0x4hgiaPtl7LucnFUjuCnP/0pF198Mf39/dx3332cdNJJHZfbunUr+Xye4eHhtuc6+Tc6+TzqSCnZuXMnQ0NDJJPJ5XgZGo1Go9EcM3R6ZQHUBUdPTw/33XcfW7ZsmXXZ8847D4B77rmn7bm77767ZRmg0Sis0/KPP/44U1NTLctrNBqNRqM5dhxR0aEKjk5VJs189KMfxbIsbrjhhpaUybPPPsu3v/1tTj75ZC688MLG49u2bePtb3879913H3feeWfjcc/zuOaaawD42Mc+tsyvSqPRaDSao0+IseTbsWbRno7bbruNhx56CIBnnnmm8Vi9Z8bFF1/MxRdfzPPPP8/FF19MpVLh/PPP54477mjb1qZNm/jIRz7SuL9t2zauu+46rrnmGs444wwuueQSCoUCd9xxB57nceutt7b19vjKV77COeecwwc+8AEuvfRShoaG+OlPf8rTTz/N5ZdfzgUXXLDYl6jRaDQazXFHIAXBElIkS1l3uVi06HjooYf41re+1fLYww8/zMMPPwxEQuLiiy9meHi40f/iu9/9bsdtnXfeeS2iA+Dqq69m06ZN3HLLLXzlK1/BcRzOOeccrr/+es4666y2bZx++uk8/vjjXH311dx1113k83m2bNnCl770JT71qU8t9uVpNBqNRqM5QggppTzWB3E8kcvlyGQynM/7sYR9rA9Ho9FoNMcxvvS4n38im83OWSm5FOrnpY8/+CHc1OGflyp5j6+9/QdH9Fjn45h0JNVoNBqNRrM45BKnzMrjoCOpFh0ajUaj0awAAgTBEoa2LWXd5eLYyx6NRqPRaDSvCnSkQ6PRaDSaFUAoWVKDr/A4cHBq0aHRaDQazQogXKKnYynrLhfH/gg0Go1Go9G8KtCRDo1Go9FoVgAhgnAJZtClrLtcaNGh0Wg0Gs0K4EToSKrTKxqNRqPRaI4KOtKh0Wg0Gs0K4EQwkmrRodFoNBrNCiBELK1k9jjwdBx72aPRaDQajeZVgY50aDQajUazApBLrF6Rx0GkQ4sOjUaj0WhWAKFcYnrlOKhe0aJDo9FoNJoVwIlgJD32R6DRaDQajeZVgY50aDQajUazAtDpFY1Go9FoNEeFE6ENuk6vaDQajUajOSpo0aHRaDQazQqgnl5Zym2p3HzzzQghEELw2GOPLXp9nV7RaDQajWYFcKw9Hb/5zW/47Gc/SzKZpFAoHNY2dKRDo9FoNBrNnARBwIc//GFe97rX8YEPfOCwt6NFh0aj0Wg0K4BjmV656aabeOqpp/iHf/gHTNM87O3o9IpGo9FoNCuAY5Ve+fWvf83nPvc5rrnmGrZv337Y+wctOjQajUajeVWRy+Va7ruui+u6HZf1fZ+PfOQjnHbaafz5n//5kvet0ysajUaj0awAJDO9Og7nJmvbWb9+PZlMpnG78cYbZ93n5z//+UZaxbbtJb8GHenQaDSaVyNiAdecMjz+9znfNpf7NRxDliu9snfvXrq6uhqPzxbleOqpp/iLv/gL/uzP/ow3vvGNh73fZrTo0Gg0Go1mBbBcoqOrq6tFdMzGhz/8YU4++WSuu+66w96nihYdGo1Go9Fo2njqqacAiMViHZ9/61vfCsAPf/hDLr744gVtU4sOjUaj0WhWAEe7euU//+f/3PHxBx98kB07dvC+972PgYEBNm3atOBtatGh0Wg0Gs0K4GiLjttuu63j4x/5yEfYsWMHV111FW95y1sWtU1dvaLRaDQajeaooCMdGo1Go9GsAKQUyCVEOpay7nKhRYdGo9GsRBZSftqyeOsJR1gL6LmglJvKIJhncTnn8+oxdHwNyolx3m0qLbnV+/O9hvm232kbx4p6v42lrL8cfPOb3+Sb3/zmYa2r0ysajUaj0WiOCosWHbfffjsf//jHOfPMM3FdFyHEnIonl8vxmc98ho0bN+K6Lhs3buQzn/lMWxvWZr7zne9w9tlnk0wm6enp4b3vfS9PPPHErMvv2LGDSy+9lIGBAeLxOGeccQZ/+7d/SxgeH+pUo9FoNJqlciwHvi0Xi06vXHPNNezevZv+/n7WrFnD7t27Z122UChw3nnn8eSTT/Kud72L3//93+epp57ib/7mb7jvvvt46KGHSCaTLet8/vOf5+qrr2bDhg184hOfIJ/P893vfpdzzz2Xu+++m/PPP79l+eeee45zzjmHYrHIpZdeytq1a7nrrrv49Kc/zdNPP83Xv/71xb5EjUaj0WiOO04ET8eiIx233XYbr7zyCqOjo3ziE5+Yc9mbb76ZJ598kiuvvJJ77rmHv/zLv+Suu+7is5/9LE8++SQ333xzy/I7duzg2muvZdu2bTz99NN84Qtf4Gtf+xqPPPIIlmVx+eWX4/t+yzqf/OQnyWaz/OhHP+L222/npptu4he/+AXveMc7uPXWW7nvvvsW+xI1Go1Go9EcARYd6XjnO9+5oOWklNx2222kUik++9nPtjx31VVX8eUvf5m///u/57rrrkOISH194xvfwPd9rr76ajKZTGP57du3c9lll/HVr36Ve++9l3e/+90AvPjiizz44INccMEFvPe9720sb9s2N9xwAz/72c+49dZbueCCCxb7MjUajebIoRgo28yPnR5TTZjz7kMxjpom0jTAsaPnbCv6KQBJ9D0sASmh6iGCEKlc5Ik2E2aoPK+ktFUDpvqaRIfXpG5D2ed8ZlQRcyMvqmFEx6OaX73W19T2fIfjluFc1+cGLMCLuhwcq9H2y8kRq17ZsWMHBw4c4KKLLmpLocRiMd7+9rfzT//0T+zcuZOtW7cCcP/99wM0REUzF110EV/96ld54IEHGs/PtfzZZ59Nd3c3DzzwwDK+Ko1Go1lhxF1IxpHJBMScWRdTz5vS86FYhlIlEjy2DbY5I1rCsHaTkVAIayf4oOnxMIh+ytrWhUFN4YBhgGVGP4WAQhHK1SW/XOnYsLoXbAtZ8aLt5ktQqS5T7cax40RIrxxR0QE0BIVK/fEdO3a0/J5KpRgcHJxz+YXsQwjBli1beOKJJygWiyQSiY7HUalUqFQqjftzGVw1Go3muKV2dY/jQMKFRBxiLpjKVXrVi0QBRGKgrjbqUQfDAMeKIiGZVHQ7GvR3Q6kMI5NQKB3eNpIxGBqYiQq5NrgZ6M2A5yMPjrVHOlYQcomRjhNadGSzWYCWNEkz9Ql39eXqv69atWpRyy90H7OJjhtvvJHPfe5zs74OjUajOeoIAYlYdKtHGGwLLKuWDqmLhaaoQadUBYAfQLEExQqUyjMpELv16180pSmkEBBzkI4VCZcwjMRKpRr9lDLaJ0QneMOYOQaz9rshascmZo6t+Rgb0ZEwWiaVhHgMNq6JIiyHxqMoy0JxbVg3GG2rWIaxqSiyU4v0YFuwdhXsObi47WqWlVd9c7CrrrqKz3zmM437uVyO9evXH8Mj0mg0r0ocG7pSkEpEV+zGYbZR8vwoYlCqRLdKlLLo5BuZDSFltO50ofWJeTwdbX6MxXg6zEno7YLudCS2Ng3BeBaGx2bSM7NhmbBhTSR4ShUYHo9SKfkSZPNIQ8CagWi7G9fAnuFImKww6pabpax/rDlioqMefWiOTDRTT2M0Rykymcyil1/IPuoRj064rovrurM+r9FoNG3M0w20rfun2jXTibwV0jIjkdGViq7UmwkCqHgIv+aTkESRAQkt5oR61CMIQMooEGIIgqRNsCpFkLAJXRPpWoSOhTQFZtHDLPqYxSpmwccsecpGa8dZ9dqPqfl5RWTIaqsnQ+3+2W6OVd7HqTxyIgcDPVFap78bkUrAgZHOfo+YEy3XlYoiGRUPMZFDODPvpQyM6D0Zm4SB3ijysWENHBxFzCI8ZJu3dO5OrEeLEIE4DjqSLoUjJjo6eTCa6eTH2Lp1K48++ijDw8Ntvo7Zlp9tH1JKdu7cydDQUJuRVaPRaI4JhgFxF5mupRISsZnnpIRyLTpRrjZOL9IQBAmbIO0SJmxC20RaBtIUSKsprSIjw2boWIRJe/Z0CxAmbFrkhJQY5QCz4GHnKtjjJczKMTrRBkEU3cgXYHV/JCw2r61FbTyoVqM0UzoRRYfq+D7sP9QQdCpCghyZgL5MJPSGBpAHR2Eqf5RemAaOsOgYGhri4YcfplAotJz4y+UyDz74IENDQ2zZsqXx+Hnnncejjz7KPffcw2WXXdayvbvvvruxTJ16o7B77rmHP//zP29Z/vHHH2dqaor3vOc9y/3SNBqNZm5MI/JiOHZ0ZR2PgetEN5VahYgslZExiyDtEgx2E2TiBEmHMG7NKSBmQ1QDzHwFs+BhVHwMTyKqAULKhogJEjZB0kZaBmHcIoxbeP1x2JzBmqrgHsjhjBYRC5lPstzkS1DaH0UnMqkZj0szYRiZTqeLUZVKKCMj7SwIiMykg32QTsKqXsgWlpazOIro6pU5EEJw+eWXc/3113P99ddz0003NZ678cYbmZyc5NOf/nSjRwfARz/6Uf76r/+aG264gfe///2N9Mmzzz7Lt7/9bU4++WQuvPDCxvLbtm3j7W9/O/fddx933nlno1eH53lcc801AHzsYx87Ui9Ro9FoIqNlOoFIJaOrcttCzOHHkJUqUgYEpiS0BcGAQ9DdRZDqUGlSQ3gBZtHDKHoYlQDhhzO32glT1vIuwg+wpquRwGjeSFNqw54sg1WsrQfSNgiSDn7KweuN4Wdc/J4Yfk+Moh9iFKoYXoio+hhegJmr4IwUEEc6GBKEsH8k8nY4ViTi6rdyBQ5NLLp/iQDkofHo72ZbUeRjbOqIHP5yE0qBWOF9OoSUi5N4t912Gw899BAAzzzzDL/85S8599xzGxGLiy++mIsvvhiI2qC/7W1va7RBf9Ob3sRTTz3FXXfdxetf//qObdBvuOEGrrnmGjZs2MAll1xCoVDgjjvuoFQqcffdd7c1+qq3QS+VSlx66aUMDQ3x05/+lKeffprLL7+cW2+9dVFvSC6XI5PJcD7vxxILmMKo0WhWNmpzqQ4nsRYvgmlGV8npRFSWas1i0AwCpBcQmpIgYeEno6hCkHTAmkWUBCFm0ccq+piVALMUYJZ8hC+RtoGfMJCGQEggiLwcZjnECEGopaDqV7saLVEFTtPzgWNQ6YtR7XUIY7NcmwYhzmgR9+A09lStGqSieDqU5mKdGpapzOcLUV+XsJQqnJSSTlfNrzWfikzGYVVPJGxe2ttqglXXmWO6ri897gv+X7LZ7Jz+waVQPy+95nv/DTNx+B7EoFjh15f+1RE91vlYdKTjoYce4lvf+lbLYw8//DAPP/wwAJs2bWqIjmQyyf3338/nPvc5vv/973P//fczODjIFVdcwbXXXtvRa3H11VezadMmbrnlFr7yla/gOA7nnHMO119/PWeddVbb8qeffjqPP/44V199NXfddRf5fJ4tW7bwpS99iU996lOLfXkajUYzg2lEqZFkIvoZd9tKTWUYEoY+viMIbYG0DULXQrpOJDDsDqJESoySHxk681WsikRUfUIDwoSBnzDx+mz8uIWfSuClLfyE0fmqPpQ4kz6x0SrumIc7VsUqLs0yaFZDEgeLxHdnCZI2oWsQWgbSgNAx8XrjhHGL6mCK6mCK5LOjuCOF+Td8PFEoQSUZpby6u2B86lgf0bxIubRM0PGQRVp0pONER0c6NJpXGWqkoysZVUOkk4gOHgyJJDAlvgN+wiLojiPd2a/fpB9iVCvIMEASAiHSNgkdg9A18JMWQcoidOYvkRW+RAQSBEgRmUwx2+WFUQ1xJj2cSR9nwiN+qIJVUr7q54h0NFCrV2qRCwn4aYfKmhTV1UmEF9D98F5EeeVEOgBkVzJKr+TycGB09nWOk0jH6d+9csmRjuf+w80rK9Kh0Wg0K4p55pyImBNFMVKJKGWiPC99PxIYcYsg7eBnWr0XEghNiTR8JBIpZFRZYkLoGnhpC8zOzQnbDtWTWKUQsxxiVqPUiVWUWMUQqwJGRTYiGEJGLo4gLqh0m1RTgkqvSbUrEjTl1S7l1TMnKGs6ID7i0bWzjF0M2wSA7CA62mRQbRkB2GWJ9eIEXk8M6Zj4fQnsYXWuibJNNVLTKXKj/n0UkdHWG2SWY2ygiBKahVB9W9bhmXU1i0eLDo1G8+rBsiJxEXejSoh4rMWTURcQgRHiuwZBl0uQ6Wo5IUkgNAKk9AliUO2xCeMmMEfVhB9iZ33s6QCjEmKEAsOTGNUQqxRieCL62XQ+lEpaRnbwgQjAKkmskk+qXItCCPDSBl7aoJoxKffZVHtM/LTJdNqkNGgzdG8OYxlMoILIlFpdncTrcrGHl77No0rdxzGbL+c4Q1evaDQazfGKY0f5+mQCUSu3FHZrylQa4MUMfFdEqZKk3S5CbAiFT2iGBHGB12WDadH89Sl8iTNSwZmqYlRCTE9ieCFGOUCEAWHCws8YhK7ArEgM38CeltjZEOHRfjW+BIQEJxfiTvmwF6BEYAvKAxYTZyTxkyZTp8TofW55OnLWxZDhzROBOB6pn4NXiMvgRKhe0aJDo9GsLJrTJa4TCYq4G4kM245KKy2rpRxfAqFjEDgGoQWBLQgSFmFipomWFBA4EFoSSUDogJcykY4BtIoVoxJi5zyE9JFOiNdnMH2WSVjrbix8CSFIi/lLOkOJ4RHdqmBNg52T2HmBnQM7B1ahPdJh+K0neUNJDxjeTCjDABKjITxbYvTMJNObY/TsaPVrdEqvtI2uV1MdUkZCjch82tbm3GhNtwi1k2unlMY875cwDGTcjRqtlSrt25gnTdKSXrOsqDV4GLaUOcu2jrPHR0fSE8FIqkWHRqM5vjENcN1GfwYRc6MeCzEX0eytEE3CwjEIbYPAEkjHIHTN1hRJTWAEMaIIhgtBon4yErS4GcIAs+xhBD7SlgRJqKy3KKYMZvsKldbMvoQnsXMSa1piViVBTOAnDPw0hG40EC10IazZL6q99WOYQfgyiozkILULEgcO74rVj0evyywvT1TC63ajktogxMp786+wDMi4C+tWz9yvelGL9OkiotKhVfpc1AWIf3yIilcDWnRoNJrjB8eBZBxRL0+Nua1zNKBWtmkQOiaBaxA4gsA1kbV+EvVlpAVh7SbNmtnTlASOqEUv6phRYy1LIgIfEYZghISOJEgL/C6Dmnuh7XDtyZD4sCQ2ArERiZWv7dsEDBABmEVqfTkEdTEROrWfVpS+CdxaGscFLwl+F3jp6OYnIxFT7YFqDxTWw+DPBO54a1TBmqdrqB+HqW1RR8+u3V5b5KRjpCNQrvjDVpFX3BhVQMQOFREh7dUpasRAjWIsxLzZIhYFrO5rfb7eLCydQB4YbYlwzbfPhm+mujLG3UeRjqV4OpbxYA4TLTo0Gs3RQxi1KEWtc6dtRX0vbBtiDqIW7pamIHCjCEXgGoS2ILSiCEa9ciRKmdRSIk7tpF07icsOZaQgInFhgrRCRBgAATIm8TIC6TSv03qytPISZ1ziTkicCYmVN3Cy9eyBIHSik5e063sCwuiXIBkJkWbU8th6eoUiOJPRY9Kop30kfiISItMnh1T7JeNvkgw+0Co6Ql+p+mgSIYEDo2+MIW2BMxWQGA4a26/T8T3zVNEwc7+8KkaYsBBeSOxgaWa0fcvyh9G+XREqLefJ/u7o8+L50Yh6IaIGbT3pyL8z0IPMFlvjRHMJm3rPlaq3IqpXtJFUo9FoVEyz4augJiqE4zSaa9Vz51IQCQlb1HpWmPg1oSFtY8bEac8ICmnWfhrRY/WTWkNM2DLyZNgSCBEyjB6vtRyXrvqlOxN9IJA4kyFOVmJPRr+74yHuWIgwbDAkpEJEV0jYLxCbQkiGiEQIaYmIh8i8ifdYCjm2fD1+hBTYBbDKAjsnGH6Xj9cbvU7Dn/8kEtgw+oYYfsLALIb0P1mOOpouAT9mUl4dRU0Su6cxgiN/CS1T8WgGi5RwaLwmqiQUy8hyFdavAsdGdiUgV5y3OZoUYkZ0dJpgqzkiaNGh0WgWjiDyV9g1UeHYUbSiMRPDafVZEKUGfLcpHeJGfgtZjw6IWorBafrpROKiTVRYUYpEWtHvmCHSDCM/xCzRjdafQCCxCpFHwj0UEBsD91CA64eI3gDWCOgJERsDRFcI6UhokAwXdDFsnlHE/02CykMZZL6W8lGu+ENLiTJ02K5UPJnSABkSeRpN8JICqzizommqkQuDwIax1zn4SQOzHDLwZAUjFG3b7nSM0TbUdImI0irrkyAE9mRUsXM4EQ2gfbQ90Mm0KR07Gs4GMJlDlCqtxxWGyOFxWDMAro3sTkK22GZ8rb2I6KfrRL9XPcQczb+OJ2oya0nrH2u06NBoNJ0xzNpkzzgi7s54LJSqEGlG7b9De8bAGVqi4bvAEFF777qoaIpeSGvmxCaFjESFrfw0JdKVc4S/ZyIVbs4nXvVxfR+7GvXBEKGBUQWzGhk5kSYIiYhLGAwQbwwQq/3o/jzIAGTRJCyatZ8GsmwSVg3CioGzoYRzUgl7exFjfYXp/3cQWbDa0ivqybxj1Ft5TBqR8RUzeuNFUIv21AhtRSBUBeOvtfGTBkZF0v9UFbPaWVwAHYWDNNp9H6XVLkHcRPghyT35Vg/FEUhRSNOAoYFIoBRL0fC3ZuoNy6p+NMhtdR/YFrInBZP5dl9JfbuxWl+V4vKUDh8NdHpFo9GcGNRz48k4IhGPBIbrNK5sQ8cgcM1adYggtEQ0Dr0mKiLxUUt9WJ3ERc1PYdAuKuyasLBnFxZCSGzh41YD3MDHkQG2DLCMEMsJMWIS0RUiTj78azkZgsyahDkruk2byGkTWTDxK3YkNEqRIdSPq5GL6GdhdxfWcxUyvzWKlfFJvmeMqZ+saRMVqgjp/KKVdYSguDa6IreyAmkYLdtRhUxplYmXNhC+pO9ZD6vMnKKgo6dDESJBwqTSH5XZxIfLGP4RuHY2WkUtvb1R75SqByOTc6ZNRLkKuQIynQDTQKbjiKKSOjGi1B3xmugolJb3+DVzokWHRnOiMMsVHUJEX9qmGf20LHCsqFGWbYFba6JlGEhb4LsmgWsSxIyGmVMK0RATYfNPa0ZoNPpdUBMTTnQL7drvVpQiaUdiGhLLDLCDALfq4wYBruVjxwPMTICRXPjJTRYFMmdCWYBUruwlNBqJe4Jw3MafdAjHbMJJG4J2QQEQOCISAbVu5n6ss+gA8IsxgvsHGfh3+7BXVxBrK/jjMeVv0vYWzEtoS8pDkehwR82WfQKETe+tBKY3RA8kDwZzRzjq63SqXlE+UqW+WJRWyXk4+aBtnWW/jk7GIRWPfBwjky3m2NkQQQjTRWQmGaVa/ACh9DTBtaPISRBGvT5WCidAfkWLDo1mpWNZDT8Fjo1watUg9b4WSovneuTCr/ezaHgtzFqqpLUqJGjyV7R4K5r9FbVoBUaniIXEMsNIVJgBru/jBj6u5WPFA6xkiJi9g/jMVipAzoCcgZye+SmLJjJvQNZEThpI5WwcuEqVh5KGWMigtcUSFGwqw3Fia0vYvVU8VXQsEmlI8qd6SBuMosAZm/uYK72CIB61Wk8cXJ6eHL5r4KcskJLY6MJP1NIQUcVS44HamU8QpfDqeD4EM9NxZdxFdqeiOxM5hDp8bg5EEEbm0rgb9fXIlxrmWWka0aA3gFJl+YXSkWSJ6ZXOebyjixYdGs3xiiASD/WIhGNHVSBqZUjb4C5a/RVOrUmWJRoGzkb3TWfGwNlIhQjAjK6sZVOUon7rHK2IClJtK8C2fOKmR1xWiTk+djJgIQObZUFAviYopg3kmIEcNQmyLnLShHLtRCvmEA0OhEqaIHRbT9BBm+hove93GOLZtoyiIdo9GzNG0NCK3uMW1NYRc+gCKSSFbR5+WiJ8SO6yor+lsk7DG2NAcVX0e3J/iEBEx2fMfZnbMeXTiF5BpTf6IzpTHqY3y7baynAN5Kqe9k6ls+EHkVgwROQnAsjmo9tCqUVDRL6MtC2wTGTChUIl+j3dFUU5/ABRrMxiZp0b2RRxOZqD2nVHUo1Gs3RsC+KRj0LEZjpvdhQUAEa91LSpf4VVe8ytVYXUvRi2kgpRxEVLCqTur7A7CQuJbQbYdoBt+rh+gBMGWCJ6zIyHGEk5q2VAhkCulvbIGsgpA0ZNwqyFnDBhygRfEMTav5KChBn15aoJF/ViTY1cqGkE9YSvLq+KkKCj6FCOSbnfVg3ih7h9kUGxPO22ra+GuTuWsMpIcBRP8gi6JAQQ32Uj/OjvLdSJ77VjKPZHAtMsS+LjslHVI5Xy2rbKjo7plegxL1HrkRJI3PFqI60yW0av/hJlbyYSHH5Q6/opaVFcjeKiWvmqZUbplDrTRRjPzh2NmOVMKgByxchQapnIdGxGYFR9RDbfmNSrOXpo0aHRHGkMAY47E61wnchDUfNSNPpWUKsEaYpQhJYgNKPHZU1oNJpjiVZPhSos6q2423pYOJLQDaOKkKaTRnOkwrV8YqFHzPCx3QAzESIWcLEqq8CEiRwxkQcswjELeciCCRNCEbUjbyK0awdQu6itt+luWSYlSabLJLtKJNNlEl0l4qkKk4e6ePn5ITzZGkZpFyXqfVV0KM93SPWo21CFiSo6Ur0FDFviFS3KJadtAK0a2egY6ZCS0iaPIF0THC/bmOUZ86i6z9AUBBZUemrHsD8E0aRvVGOq8sBsFTRSQDUTnSpiE9UoYDJPcEBC1FfDtaO5JuNZhB+0C4SmQXdSEPXZsMxIcJfKiEJ5SaJABCEUK1GkwzCi/RcriHxpZaVVaujqFY1GE12dOU5NVDgIt+avcGvRilpouSEqammOxk8nilgEjgmW0VIJUm+I1agMaaoQaa42qJebYtJojiUdiTRDpCPbwt6GCEm4VZJmlYSo4sb8SFjMdeXqA1MmcsqIIhY5A5k3I19F1kBOmsiKRXR2k/Suz7L2TfvZ8B+GiXeVKWZjFHIJCtk4ftUk1V0k2Vsi1VMklqhSLjgUizGK+RjVsk0qU6Srp0AyPXtJY6no8C//fA4H9g/MPKiKDtVwqYoM9fmFiA410tH8vglJ5uQpALLDaQJXtEUl2kSHGrUQkso6jzAZCY7YXhujYrQcqzqaPjSgPAAIgVmUODnZ8l6o55u200+nXiFCUMlEXh/hhThT8/sqJCATsejzLyViIhcJjnkQEqh4iGWuJhF+CIUK0jYRVR+xgkpk25Biab4MLTo0mhWCYdTKSF1ErBapqKVCWqdTElV8OOZME6wmgVEvL0VE1QaN8lKljfecTbHMmsCoP2bKWRpjRZiGxDUrJIMqcdMjlvSwMp0bXckqMGbAiIGctJCjJoyZyLHIuBnaM18ZTrJKek2R9Koi7poqTsLDTga4ySqrt42T6ms9eSQyFfpReiw0kcyUSWY6nxAC3yCfj1OYjlHIxymXHTZsHibTXeT9H3yI733nQsbHM7Nu+2jSOzSFk/DxqwbZ/V2LXl8aNcGRqAmOPTZmaX7fgZcCPyEio+fE0itJJFBNm/jJSDS72WD+Lp8QRRXiTiQ4JqcRlaMzCG4uRBBGUQ/NMUeLDo0GZnLK9ZtlRYPGYi7EY42hY/UOm4FrErpNjbCaTZp0aN9dT33UDYad2nfXjZt1w2bHSpA6EkNILCPENENMI8QKAhw/wJU+jhFguSFmMsRIdQ5QyzGBfNmCV0zksEk46UTVIbVTS5C0iKWrdA9Nkzl9mvRAgUR/mWR3ia6BAm5y7pOJVzXZ9+Jqdj+3hslDXSTSZeJ9UZrEdnzy2Ti56STT2QTlokssXsXprZBIlnFdj3w+TnYqyWQlSbnsoJ5GrccCPvT+B1g7NM62M3bz/z12Ru1v2XocoZqGUKIWcp5ICLRHQ4KY6oeIfsQSFfrXTwEw9nIfoTDAajdpqlGKxrEYkspaDxmLBIe7z8aoGlE/M+Wc2TR7DWlEs1kAnKlo+/OWyAJBTBDYBoYvETLahwACK0p11aNpdj6IGqvNM0Ze1pvIAaJQbuscygJKXjWzo42kGs1KwhBRC+94rDYe3amVlloIq/VfoWXoWKzWt6I2zbSeAqm36m7pW2HPRCqiyaXNUYqZSAWmRBrR/U6mTdOQ2JaPY9WMmzUhYVsBphViOBKxiP9eOSaQBy04YCL3m8hXLEIvOjmYTkDXYJ7kGwoke0qkBwpk1kzTvXaaeGrumRT5bJzceJLidJQSqXg21YrNxEgXe3etxmv+islCMKKcpJpfwzT4HYZ9Bi6N/hi1twcAH5OxXBdrh8YxYwF+vH3dtn3QLiDavBFO+zdzewqmfRnLClh30ghCQG48wVQ2AbXl1Bkp6jW3QfS5qA56UTosAHe/jeEZM8enaoi6twPwE4ARmUedaRpejBZqAiE0wY8ZBK5oiN+GBgolIpzxA4lA4kwHmOVwfh+HISDRJDgWEuFQS3CWg+PhzHqk0H06NJrjEMOcadldFxedRqTbgsAxCG2z4asITdFIidRTIW19K2r3EUrfiuZohR1GUYqOV5s1UWFGIsIxa30r8LGdACsZYCygbwWA9ICCgKKBLBpQFMicAeMmsta3gnETKkbDtOmmKqx+wwSrtk8yuHWMnqHp2bcfQm4yycRoF9nxFLnpJPlcnNxUkuxkCt9XemI0l5a6C/BTKCf8oINwCNQWF7UvzsGeSbZv3Q3A88NrZ9ZVvljbJry2RTpaV4iGxc29DZzWk6Vl+WxYO4btBFQqFgf39SObDKuhUp5iKAoicEO8fi8SoD7Yh2xEYLRXxSjHJCGaO2NEAsGdiH6fpRgGL2kQNJl1RRC1iq+3sseolddKiVGVxKb8lsqajg3EIPqc1wzOolCOOoPCiS0ANIeFFh2alUfd7WhbkaBw3daKEMdulJpKAUHMjG51YWFHXTYbKQ4x07ZbKp02m8WFtEA6IaFbM2nWhUXbF3EkKBw7wBY+jh9EbbuNAMsNsFIhhruAOR9ZEVWCTBowaRDmbGS21sOiaEDRBA/ql8Bqk6v6CcJJV1n9xjEGTx9nzdbRjiKjXHCYmkgxPZVgOptgcrSLkVw3k+PpFmHRcsJ2AKWKYz5RMV9qo1O0IlDeKyFhIJ3ld895CMsMeXF4kJdy/VBPeYRqrwhFVLRFOtTnO/xt1MeaREcqXmbtwCSWGeIHBntG+vAN0dIXQxUZ9T4PEkmYCpDJaHuiKrDGbYQU7UJHOYTQqBuKo+fccYGQTREO0bpqNWUQxqKNGtUQqxRiVGdqWALHiNKAhsDwJUYYbWQu76GEyE9kdBAch8vxkIKRx6f/Q1evaDRHA8uMxqI3Ihe1FElT6WjdtNm4WSLyXLhRz4rQnKWFt03LFakUM70qpC0JHYm0OlWASBwrwLF9HMPHDT1cw8dxA6xEuKDUh5wWMClgPKr8YMJAThgwZiCzNtRC8rGuCqtfM87qMybpP3kKO+ZjOgGmHWLaIaFv4JUsqmWL8rSLDAWW60cCxwlI9JTa+h9N7O/iwCsDHHy5n0Ov9FHKx9pae3uJ5e/UuRRs0+fkVYc4dXA/pw3tx7YCDmUz/PCJN3MEGnAvAMmqnhwD3VHjqlLFZu9IL56/sK9VaUqCjA+1yIqRNzCnLMQCX4ust5+XYHhgzpLNkEQRKGlFJlM7H2JWZVtLcQEIH4zFxOANMVOKGsilCw7N/BwHmmwpaNGhOX4QQCwWCYp4k7iwrc4j0mttvOvmTWk0GTbrVSFua88KmCkvbRYX0gxrZabtX/iGCHFtn5jpkQorxBwPp2vuLpvSJ6oCmaylO/JG9HMy6rIpJ2dEBYB0DRI9ZdKrC3SdVSA9VCDZW6JrdYGetbOnPwAMM4qgxKmQGSx0XGbqUIr9L63iwK4BDrzcT6Xo4jeLiiT4butr95Pt21EjF22mzbaeGMp9Ncqg6JqgadJrzK6yJjPJmr5J1nePcVLfCLY5cwW6e6KP7/7qHEqW1RKJaG+aJee8r3pqpN1+lSuUdeKJMoPdORJudKafyCcYmUojhcCwA0K19bwapXAkYcaPfBIhGFMWRsWMyqNry7Q1EJVNPyWNb+/G61X7cNR6dIR2u+BYFsJwRogH4YLmokglgiAWMvlO8X1I5b5Qu522vdnzHNeR8JVoZkWLDs3RR4goFVKrDhGx+tj0WDQG3a3NBXFrKZGawMA0ZlIhTa27G7NB1L4V9UhFPRXSKDXtfCUpBMTtKnGqxEMP1/ZxEj5mepbqjyowYkSRigkzilKMmshRg7Dotjj5pD3z5RrrKrPqnDH6NmbJDE2T7i+QGihidTjZ1Rnfl2HfrlUcfGmA4rRL4Jv4vkngG5hWiBPzsFI+iWQFhMSrWvieiV+1yGfjFPPxGb+FIBIZymAzteGVl6CNNo/BPKKjzaSpig4lbdHTN8Xr1+zh9NX76Uu0C6iJUoLnx4Z4fmwNe7J9UXWFoZyUFNNmm6hQBISw1JNY+99b1BSAbfoMZPJ0J6Ny4CAUHMqlyVdiGPaMyy9QttmiroREpoJIcPgCkbcwPNGmMtTqExE2Nh+97TISHKLW5LNT5Dy0FiE4FhMskhLhBdE/TRAe25TIq0g06PSKRjMXhojSIs3VIm5k6GzuZxGNTZ8ZnR410GoycCoj0utIo6mFd719txHWBpC1H44QEscMsMwAJ/RxfZ8YPrYdpUSMrtmbY8lpgRw2Ya+J3GsRjLkwZoIUCCMkva5E15o8yVPLxM6uEOutEu8qY1ohUkJYc/2l+op0r+48RyIMBNOTCaZG00yNp5meTJKfinNobx/lotuW/mhQjW5hcY6/RaK9E6eviAq14VUnU6cqItpGtisiYj6RIQ1IOSXOXPcypw/uZ3Uq1/L8eCnJwWKGA4VudmYHGCmlkUHtj+SGHQ9CHdGu/k1VUSHM1pOWYUoMEZKOlTEMiRASw5DYRkA6Xm5c3E9XHCaLCfzQxFS2IVQPSP2kLCTYtbpUX0DBjARDp8+dOs+ltrqQ0e9GbTMzrcSVXZqikTo0fA4vwtHRBx0JDlH7vXlI23HBfObVlWxu1dUrGg1RxKJm5BSuW2uc5SBcp+auN/BjM5NM6xEMaSqiovZ7fUy6REZO/Ka5IGFdWMySCoEoHeJYAfGwSjLwiDkedjrATM9/RSSnBfKAhRwxYcREHrIIphwoNjn+zZC+U3IMXTjKqpMn6N84iR2bv+NiYx8hjB/KcGhfLxOHMmTHU0zlUkxnE8ja2aflZF2LTATu3F/t6gm+zXioiAp1aFmoRDr8ePs31HyRjnlNmU3PGyLkLRt2cf6G54lZUa1sEAp25QZ4cnwdL+f6KQcOljPz3tqxgDBQw+3KQDdFZQhDFRlKJUmTYLDMgN5kkUy81LnwCCh5FrlKDC80MUyJY/ptV5Blpfwoel+iUmkhgEBA0ZwxPHcQHS3HLUGEoiE4pAkEit5q/j2UjaiT8GXHviAd573Mh5QIP2jMLGmIj6b9LnZ7R5xlMIXK48HcCtScN0tc/9iiRYdmcSRikEw0GTpdME2kIQidmbbeDXHhRpGLwInC94E7U35a72XRGI1uNXktah6L2VIhIDCNgGS1TErWhEUiEhZijinisgJkDciKaOjYeK3z5rgRRS5yIpr90IwjcJJVejfk2PyW/Wx44zBOorWhhFe2mBpJkR9PUMzFKBZjkTmzaiJEJKSEkFRKNsOvRCfTZsJZX+eJycbMGL+z7UlWpyK/yr7pbh4/cBI7iu3vzZFHEnc8uuMl0rFKoxip4ptUfWvGSiEFRc+m5Nk49sJFJhCd4Y1IcEgJomAu2DBKCGaFVsExlxVCSswKUeojlBgdep8cLqLm3YhKzk2M6jJuXPOqQIsOzezY1kx6JBmHVALMKAXix0yCeK0U1TUILWNmXojS1yKsRy7MaNBYS8mpxRxfoCKaEVKtEverxPBw7AArFmJ0SYyu2a8+ZEFErbz3R9EKeSCKXFAQhG5r7iVs8lu4g1X6Nk/Qv3mKnnU50v1FUgNFnFjrl2u54LDvxVUc3NnPyO4+xqYyLZed6ij0lqFiFsi2UlMlRdDhPVEjE239KBStpF7Jts0PUdInbdNY1a6bdIhcqItYIZu6x3BNjwPTPUyHMwcdM6ts6x/mNX37OaX3EABFz+Zf957Ok6PrkQhiySqu3VqG4diKwPNbX2gQqm9W69eaUDwfRpM/oytWpitWwWqKdpQ8i2w5Ttmvz5EBs2kbthXimK2iQ00wGE2eDhkSVXgIoogF1HppNJlfO4RVpABCsMpEJbTUG8/VV2pbJdp3tdbxVEpMryn7Mt/F+mzNPerbLfuNVuLSMhc2El6NEKj3O/QhUc2mmiZ0ekVzwuA6kIgj4rEomhF3EZYVTa6Mm/jxGZERWgahE50EG9GL5nkhRpOJs+63cMKOPgtDhLiGR7zi4foeDhLLDDDdEKs7RMwlLEIiYXHARO63YDiaERKWXPCavB9W7ctRSOJDFeJrpkn1Fkn0lIh3VYhlKiTSFdL9BdJ9sxsjCtkYe14YZMevNnBguL8lpB4kFJGhiI623hDzNazq8H0+W5OsxjaUfbS1ze4wKTXuVDhp1SF6EgUyXXm64wUSTpWpUoLRSorRUprxYopDxTTVwO5osgQQSE7pPch5619kKJVtPJ6rxthf6MY2AjanxzBrJ3wp4RdjG3jg0NYohVJLT8Xd9rpP12oVHVXFP6GKEDXVYbScbSUJp0p3vES8ScyEEoqeQ77iENTOhHaTcLCV/IRjtd5XhY8wZNSyOhCRB0X1Xah/3w6KQIQCswgCgTRkFA1r7r3RoVrF8GSjdNbwDjOF0gFR8TELUTmsNEQkkqRsb616PKAaS1eyh0NFiw7NisSxIRFDJJORwEjEEIZBaAr8usCoNdSK0iUz4qKeJsGoRS5itchF88yQjl0UJa7pka5WSFLFjfuYXQFGav7DlVkRDR4bjUSFzNpR6emICdXIjNpM4JrggOX4DG4dY/C0MdZsHaV7MI+pVhV0YHI0xcj+XsYOdEd+i3yKXDZJ0HRyC5TKD9UvMV+TrLaqjsMQHaqoaPNbzCE6TCPgLae+yG+d/Dwxuz1EPtiV5dTmbUuYKCcZLnUxXOyiGloIJAaROfe1ffvoi0WCrRqYTFYTDMSm6XLKdDnDje2MllO8mFvFs1NrmKimsMwQ15zZf8Jp7/MQt1qFSMlvfbNM5cyqCoAoSiFJ2B5pt9KIUkgJlcCi4ltUAhMQGAaYas0tYCuRDcdsfc8C5arfMEKCqjljehVRiKOeupFqpYrSYM6o0BAcoSnxE7P34agjPIlZm5cX2FGEZE4WeAIyKj5mvhoFapo6jy4LC/FKqKJhqSLiRBYlKwAtOk5khDEjMBL1CEYs8mBYAq9JXLQIDCc6wdVFRtQauV5+WhMZbohsS73XZ4YExCpV4p6HawTYToDd7yM6lGACyJyIJplOGchiNCqdaQM5ahFM2VBROm3Wv/Ss6Ba6gr51U3QNFEh2l0j0l0n1FhjaMortKGHwQJCfjpOfSpDPJSjmYxRKLoV8NL10dLibiqf4LWwBNtGthlpeOt949Pn6U8wXCYHWHhbRRpV11PSK2q+idvwn9Q/z3u1P0peMqmhGCmn2Z3uY8uNMlhMUfZfeWIHVXVl63QL9sTxpu0JfvEBfvMD23oPtB0ckBn41sZ6fj2+kFDjYhs/a5BSD8RwC2JXvZ7qe0xFRVMNUlFPaqbRtN6GIDkMRGZayDb9JdBiEJJwqCctribKUfJuSbxNKI+oe2yRGRYfwgLoPNb3iN508q56JXzFrBleJ5QRR9VIT7XNR6k+AWQKrZlwObEmQiJ6XqjZs2oaTlVEahmhYW+ACc7d3aUN92cILsKarGNXotQauGVUndxxAWD/+ZagcWaoZdbF9OlYSerS95rhBKOWp8aixFlaTByNmzAgMS4lgqALDbRIYTmeBEberdPllknYVOx5gpsK5G2ZVQO6zkHvtqEJk1CTIOy2iQo1ahJZoHfYFjTLAZHeRU978ClvP3k1qlpHouckEe19ezb5XVnFofy/5XBy/bR9NdwyQiteh09TRNv/DPJGO+ao+AnWAWIfvhiCmlGUGaqmonPV5Q4RsWT3MWeteYlt/5KeYrrr86yvbeXok8lMY7sxZbVehn2RlRgDEzSqrYtMMxnP0u3kMESKlIJQCieBguYvnsmuQtamq9ejEuJ9mfDo9sx3Fr6GmLVJWe6Qj0eGxZlQRUvZtTBEQs3xc02+cI0MZPedLA4mo+TjCtmPohCoynA7rSAlT0wlGp9JRikdI3LiHaYVUyko1i/L3rffdsAoCsxw9Gbgyim7NdZ6Qktg4uLWMVlBriBe96AVECMKoGgVEJLbqPpJ8FbNSiwgBYcwiSNgY09WW7QgdJTiq6CmzmmOD6ygDzWJRDwwh2kyefiyKagSKwAid2hefSau5cxbvhWUGpKplUrJCLOHh9AeIWYoM5DQwbsDoTGWIPFjrcWErH7nYQkO1knhXhd6hLD3rc6zZMsa6bYcaPRiqZYuxA90UsnGmCwny2QSjB3oYOdBDaB57dX80MUWAa/nEHJ+Y7bFt4CBvXPcKmXjU0CqU8G97T+a+/adSCeZQiU2UAofdhT72lXtaHle/xNRUx9FHkrCqxCyvITb80KDsW1TDKIViGstvRPB8g+HxDMVyFAIzzAA37s3a90VFVCPBYQRRRVeQlG3m4jZCSWIY7OjPiu/MzAqalyDELPqRObT+mBIZkUQXAUHcBmsZUyqaVzVHRXRIKfnhD3/Il7/8ZZ5//nmy2Szr16/n/PPP57//9//OSSed1LJ8Lpfjuuuu4wc/+AHDw8MMDg7yoQ99iOuuu46urq6O+/jOd77DLbfcwrPPPovjOLz1rW/l+uuv58wzzzwaL/HIYduRqTOZiKpH6v4LS8ykRpTGWi3pkXobcFVguJLQCTt8AiSWGZKqlKOW366P3R1gZDpUMkwDL1nIHVYkKiYEsuBEPQhqBPGmHSQhtFX/ReuXWajc71mfZftbd7Hh1IMkUu2h930vDfDsr07ipReHCINo2y0mznh7lGG+1Mh8XTajfcy9jHrfcHyGuieJWR7jhRST5WRLyL2tKqTTeSMWYIoQXxrRArX32TZ8NnWPccrAQU7tO9gxRQFQ8Bx+dWgDTxzcxEQ5heEGiKYreMttvXqPO+0mAtXboPonLOV5NS2hmkLVKEXKbo9YpczWSEeohAnq90MZCYx6NMULjUhoyFoT3NqxqaLDWoAIUSMbzetM5ePsGe0lCA2ECFnTmyPnuy3nfrWCpp7LEB7YUyZmuT5HSOKlJaHL3KWuoSQ5DFYp+t8urgK7uDCxYRU8jMpMfw1pRAZVCY1W5qFr4afsmQZkh3mJPF8lylGpVFluT8ixRBtJF8af/dmf8cUvfpE1a9Zw8cUX09XVxVNPPcWtt97KHXfcwSOPPMJrXvMaAAqFAueddx5PPvkk73rXu/j93/99nnrqKf7mb/6G++67j4ceeohksnUoxOc//3muvvpqNmzYwCc+8Qny+Tzf/e53Offcc7n77rs5//zzj8bLXBpWbWJqc3ok5s6UqLpGu//CpqXvRaNrZ60vhHTDyIdR+9lJYLiWR6pSIRlG5k6rJ8RIdhAYITBsIPdayD0W8iULDhlIu/Xs2iIy6CAqlEmo6vP1BlhdPXnOvuBZtr5278y6IUxNpBkbyTA+kmHXC+uYmkhHIqNJBKiCoE10qM+rqRA19G2HbBo8xIbVo0zk0uwd7We8nKJZGaiTULEkG/tGOanvEBt6x1jbPdlyogpCwWQpSb4Sw7U8YraHa3k4pk8oDQJpEIaCEIElQiwzwK6tH4SCUmBT8hwqocXqRK7xXDPVwKQSWIyVUvzi0CaemxwkqL0Zwg5bmm4BuIqhNGG3pzXaKkmC1jdXTUPM54VQn+/q4H6MKw5KT/FHeNKg4lv4tUiGlDRSKLYRtgmb+Twhneh03EEo2DPay0guSh8l3CobV40Tc3zyE60fsk7BBytnYGWNqDoFSRCX+EnZVNnSKQcDhJL0nhnBURiCICaw5+pICwg/xM5WZoSFZRC6VlTdJQRBp6hj9RiUpyxVFKxkUTEfR9nTMTU1xWc/+1l+/vOf8/LLLzM5OUl/fz+nnHIKn/rUp/jgBz/YaHC3UI646BgeHuaWW25h06ZNPPXUUy2RiltuuYUrrriCL37xi/zDP/wDADfffDNPPvkkV155JTfddFNj2WuvvZbrr7+em2++mc997nONx3fs2MG1117Ltm3bePzxx8lkMgD8yZ/8CWeffTaXX345zz//PJZ1HGWSLBPSKUQqCYlaB8+auGj0vag12AocA+mIxuj1utBoVJDUp6I6TUbPWQSGY/ikyhWSVIglfOxVnVMkMiASGPtq3ouDVtTvQj07xyJzWSxdwU1WMe0QkYwmn0L0vx9YJmEo8D2TatmmFDhUK5EyiiUq9K6dpqc/RzJVJggMPGnixjzedPbzmDWPwgvPr+fXz5zEwYN9BL7ZarKMzx91mC/S0bm1t2Rt3ziv2biH09bvIxlrjR4Uqw4HpnoYznYzMp1huNjFeCHFUGaS16zZx+mD+0i7retMV10KVZfeeAHHDOhP5ulPdmqJHtRunTENScqokmoSBVOVOLumB3ghu5oDxW4qgYnvtX4IDCfEYkY02IrIiCl+i2QH0RFTRYfR+uapUQP1hB4z5zaFpswORlIl0lEJLaSEgu8wVY1TDBzqZ+S4WY1MrE37nVd0LCjS0VReG8L4dIp9492UPQeQDHbnWNs31ehiaqhdUJv3KcGeNLDytchcLMRPyDYzcXu9a1Smmt4DTr4mONZEgmNeQomViwSHNAR+2mnvD9/pXK2+Ner9xUYR1MqRBVTCqAPeFtLrY85jUu63bR+Oow6kx5axsTH+4R/+gbe85S1cfPHF9Pb2MjIywo9//GMuueQSPvaxj/H1r399Uds84mfiV155hTAMOffcc9tSI7/zO7/DFVdcwcjICBClYW677TZSqRSf/exnW5a96qqr+PKXv8zf//3fc9111zXU1Te+8Q183+fqq69uCA6A7du3c9lll/HVr36Ve++9l3e/+91H+JXOgWPXREYCEnGIOYSOEVWPtJSnRqmRsF6a2pSjlUSlqFH/i2aDp2y7jBJIYkYUwUgYVdykj9XXeSqqLAP7ouZZ4aiDHLaQhyzwREvTrCg10/rfneor8MYP/IaTXr9/UW9HtWoSBiax+PxjsL/9j+9idLw7ulOrVmnrcaHODFGFlDrJVI10NKU2VnVl2b5uD9vX7qMnOTNwrFBxeWlsFZl4kaHMJAmnypZVh9iy6tCsx170bF6YGOSVbD97Cj1MlJPUui6Qdsv0xfIk7CoV36YqDMqBHbXWFlEpqilCDBGlDLzQxHQDAmngGD5x08MRPjHTZ6KSYKySmjnRGbUTqZISUE+2MadVQKjpFLVqJHqs9W/WJjoUkaHuM64IiDbR0SHSkTBm1ikFFtlKjIlqAq/pLB0zPbrsEnHL52Ap07J+m+hAFR1KhVOH0iFLhFR8k4NTGYanuvCCaN+O6XPq0DDx2Nxpo5koBYi9May8iUTi94QEXSGUFtZoK7UXnOma4BhsL91uoX5ylZLYoRJGIJECvC4XTAPDVye+zn8Iy84ynNzbps4eDcHQnBY6is3M6rN3lrL+Yti8eTNTU1NtF+3T09O85S1v4dZbb+VP//RP2b59+4K3ecRFx9atW3Ech4cffpjp6WnS6Rkn+5133gnAhRdeCERRiwMHDnDRRRe1pVBisRhvf/vb+ad/+id27tzJ1q1bAbj//vsBOoqKiy66iK9+9as88MADR150WCYk42DbCMuKunlaFiRiyJhNELdmzJ2Jug+j1dwprVrkwlH6X5idIhczxKsV0l6ZhOPhdvmYfSGiw/KyDByMunTyskF4wIVDRiPkFsYWZioEyRkXvcjrfvvFRlSjUrSjqaa+GUUjZO1qz4iGZVl2gBurYtkhjjP3lXwzv/2OxxkZ7WEym6JcdqhWbcq+TaViky/EmS7E6dzSVDKb7d+xPDb0j9HflSNmV3Fdj7hdZVUmy6qumYFjFd/i+QNreebgel4aW9WYi2KIkNW9k6zNTLIqlWV1OsdAOkfc8ij7Fs+PreGZsXXsmhponMCaJ5lKBLlqnFx1pkzGdNT61vZjj9VO+NXQIu/HCAL1dZ+YV2deaDDpJdhX6mGsOpPWMkVAn1NsST0tF0EoyBVjFCouxYpDsWpT8Wb+P1zLY6gny5ruLLYZUl6IIdcHsTuOKEaCw+sPCDukMjsfEFGEoyY4pjfQMvxwVqTEHS1jlQIk4NcEh2aFcpQ9HabZOYyUTqe56KKLeO6559i5c+fxJTr6+vq44YYb+G//7b9x2mmn8b73vY90Os0zzzzD//2//5c/+qM/4tOf/jQQiQ6gIShU6o/v2LGj5fdUKsXg4OCcy89GpVKh0lQamMvlZl22gW3VBpy5iLgLqQQiHpsZbuY2pUjiZq1cdR6B4UTmTmnLlnOlIUJMQ2IYIWYYYld8kl6VuOFhJ0PM3rBj/wtZAPaZyL31yagG4XSs5WQmHROaGk75idaPgzoPJHQNhJCc//s/5+TX7wNg385VPHrXGUwciq4u28alK505X3f2i5x33lNzvr2HxroZmejm1JP2sKo/y6r+7KzLhqFguhQnV0gghCTuVIm5VeJOlbJnM5brYiyfZjKfImZ7bBwYYahnsi383XgPQoMdo4P8+uB6XhwZxAut6O9hQf0/NkCwv9LN/pFuGKmt6Aak7EqtJNOMLiksELV4tKmOrVcuOWxllkeno4spkQhfER2m8poqSqBCNXmq/gy1CVenUtWk1Zr+sBUXriXmjq4k5ulwlRRlsn6cKS9B1ouT9eMUlXxYl1ViMJaj1ylgCJj0Wy9QOpWzthyjGgFipn/HVDHOSC7N2HSqY8QjEy+yrneS/nS+ZSCcuk2114fwgJcSiKqBNCTeQNCxzXwnhAeZF8Eu1gTHevDSAkvxcLRdxUqJO1bGLvhIIEg7YBozZa4dlm/bt/JYW4nsfFGFw4k6LPeo+hOpb8dx0qejXC5z7733IoTg9NNPX9S6R81IOjQ0xMc//nG+8pWvNB4/55xz+I//8T9i18yI2Wx0cmlOkzRTT8/Ul6v/vmrVqgUvr3LjjTe2eERaSCcjY6djg2MjHRuZdJGORWhH5an1AWehE6VHpCFaGmsFsdrkVFu2lKWGtmxpNhUhcWyfLsqkRIVYl4eZmv8fRFaBPWZk8NxtRUJj0kA6islTFRWKqdOPK6ZPVXQ4gpO37+Pk1+8jDAQP/ssb+PWzm4GZXhpqfrmeyjDNgPPOfYrXn7ELgBd2rWN6OoEV83Fsn1AKDo318MrYACNT3QDc+9Rr2TQ0Qk86T3eyQMyp4joeru0Rc6qk4yVMU5JJFskk2110CbfKhoExNgyMtT03XkyyP9tLsepQDqPoSa4SZ9fEqpmrVhuieHjb6jNj1WsYdkgRGywwCNomm6qiQj0puUqqIwzbd6r2uPCV1IZalaHuQy1njbWJDMXTYbX7K1TPRUURGfNFHOJGq5AxRUg5sBivJpn2XF7MDhB0iFwlzTIbYhOckjxEXmmkUlSMSbOJisZ95X2QIeyd6GH/VIZqU7fTmO2RSZRIuRV64kXSsTK22fn1+eo+mu4HBQt2JhC+gbRD2FwirCxsqJ1ZhMwOMKuC0ITpjeAnFhjhGK9g56MjqwzEMIPDOOEsQJgs6fkT2fR5HKNeXLuui+u6sywdGUpvueUWwjBkZGSEO++8k71793LttdfOGiSYjaMiOv7iL/6C66+/nuuuu47LLruMnp4ennzyST7zmc9wwQUX8L3vfY8PfvCDR+NQ2rjqqqv4zGc+07ify+VYv349ANXXbSTojhO4Bn7cIIgJpCmQRmQ+lEbTrXa/3v9CurUIRiz62Wx2EiLEMUMsKyDuV0n4VWJugJXxMTpFLQKgLKAioCyQhwwYNgknbOSoFQ0yCxQPRqfyVMWd3i46FJGhiI7Ahi1vjKpJDuzv45nfnNSWU1ZbdQc2rB8c5aK3PUFvd2SafOyZU3jgF68FROemWrXPfp4YzwxvgOHWZWYuQCWpWJmurgJd8SJhaFDyHIqhTdmzSThV+pPT9Kdy9CYK+KHBK5MDvJzvI1uZeaObUx+YwAJapRuKiLDdVtGgfr27SpRCNXyrgqJ9iFm7sVP1U7T5CBRUUaKKDDWy0cnUmbFKLfeLikFmvmNImzOejYJvs7vYy0glTfM75hoeA840/XaePjvPOneypYJlr2KQdZXaUmeesap1k2nZs3hlvI/9k90EtQ+VbfqsSk+zpjtHJl5q/J3Ubaplu+rrbvQImbIpvphBhAJiAWJzCWwJnauaW48zC107wQgFfkwyvV4QujP7bY9s1H9KkvvK2NPRe1btjxEkbcwp5X1pi2J0OIjl6DC6VBa5D7UMV8wXOVlJwmeZ0iv1c1yda6+9luuuu27W1aamplouzm3b5q/+6q/4r//1vy76EI646Lj33nv5n//zf3LFFVfwP/7H/2g8fu655/Iv//IvnHTSSVxxxRV88IMfbEQ4ZotM1NVZcyQkk8ksanmV2RSeME0mz0hS7TMjIVGfKyLCqGulYGZqpKTm6haE8bBFZAgkCbdKyqmQNstR5061vLIJ6QG7LMI9DvJlC7nPgkr7fBFoMnbWLvxCSxUVrV+Mflv5qvK8IhjUplqhDfsP9bF5y0H6V2dZdfI4+8b6Z92GEJI3v/55fuuMX2MYMF2M8ZOfn8lLB9c00jpt/S2Uzpyd2oE3n9FzMsZU0YFiU9MqO9pGthrjYLULmR1qXd0OEU0eCkMVGQu4IFRFhlpuqkYZ4vM8r5aneuqwFmipVoH5Rcd899siG+b8oiNhzG3+tTvMLYHoe70amlSCyDA7XMkwXOmi/mb3O9OsdnNsT+ynxyq2iLKk0XocMdF63DFD6XI6RwlsKGGiEGf/VDfDua6GTycTK7FlYJTBdA6vQzmEqX7Tz/MZEUiqIzFKL6ejL4uUDxtL81da1IgfgvRLAgFU05A7WWB4olUYzCISknvLJA5F71ml18VP2rXvqXlExkJOZoutTjmcE/q8Qkfdx+IiOCt6iu0yiY69e/e2FHbMFeUA2LRpE1JKgiBg7969fPe73+Xqq6/mkUce4Xvf+96iqkOPuOj4yU9+AsAFF1zQ9tzAwACvfe1refTRRxkbG5vXg9HJ87F161YeffTRRhOx+ZZfDIWtPkFPgGlEvgrTCAlDI2r9HIra1U77B16IkG6zSLddJN7rz141MiWizp37BfKQHY1fHzbAF4TxhZo6jy6/+OUpnLJtLwMDWX73Q/fxi6dO4edPnkKp3PqhTSVK/M5vPc6mocj08PSujfzfX7yBcqdOW5pjipTRd1Gx1iI8kAIDMGRX1CPEiFqFO8InaUCHKez4oaAYuJQDi7zvUgmt2rZMfBlV38gO/yur3SwnJ0bJ1JqC9c7XbOIwmS67HJjKcDCboRrMfO31JvNs7R9lIJWfETpLOCdJCVOjKaaf6yEsRp91u7+MN+h19ju3bQCSewWp/dHBlPuilAoGMM/ANwJJeneR2Hi0YKXXjUpjNRqFrq6uWRttzoVpmmzatIk///M/xzRNrrzySm699VY++clPLngbR1x0VKvRldHo6GjH5+uPu67L1q1bGRoa4uGHH6ZQKLRUsJTLZR588EGGhobYsmVL4/HzzjuPRx99lHvuuYfLLrusZdt33313Y5nFIhybDWtHSaya3ZQmQ/BzBtWsRTVnUi2bpJMV4ps9RFPaWeZA7rThBQu524Rxg1DaNAsWWU+N1CIAqv8isNu/sdTunerFcXukY570iRLpaCtNtSDA4I5/voAL3/YrXnPKbs56wwu87jU7GR7rJVtIkC0n8AKLt5z2PHHHo+qb/PRXb+TpPRvBFFGJb8sxKvtoM1zSjvKYdJRwqqV6G1qXVytFLNXEuYArp7ZGWh26dzYTV6IUam8INepQ7RTpUDwWZUXNGvM0uWpvihXUhEa0L7UCI+93uvqRuIbf8CyECKQUVNuaTLRTL+VOmFXSVpktiZGG2KijRjUAkqL1vVMjG65yv+7p8EPBwWyGvRO9TJVm0mmO6bO2e5INPZN0x1vTRdD5fVR9Iuo/myFCsmNJ9rwwSH6q9r1lhsTWFnGHimSLykAfFSkggMxLEBuPPn+FNVAcomUY3GxY0wE9zxWwyiESmN6UwArNuSMjauQj6GAkVU2X8/XpmIe28tZFNpY6LFZS+mQ+jnL1yly8+93v5sorr+T+++8/vkTHueeey9/+7d/yxS9+kQ996EMtqY5vfetb7Ny5kze96U2NUtrLL7+c66+/nuuvv76lOdiNN97I5OQkn/70p1s+qB/96Ef567/+a2644Qbe//73N7b/7LPP8u1vf5uTTz65UZK7GIx4gpP9EeIJnwkvydR0gqAcjUwnJhFG1FvH7g6xu6sklfXluIF8zEE+Y8NBAz/ddEZ32/0W6pwFP1F/Pir9VAUCzHTvbOxTFQlKUEFdXm3/3dY0a5ZJqCVsfvLY2Ty/bx3nvuFZ1vROsWFNu6jcP9nDD58+m/FCupYCku0jvW3lviogOooOJW2gCBU1XaJWqqhNsWxrbtHRSYSoIkMVFSpqakQVHW2CokMJptqtUx1UphomVeqiIwgF5cAm58WanguJGx6u6WOLgBBBTHhUQ5OqtCgHNuXQRiKozBKtihtVeuwiGbtI2qxgGwFmbaCaY/jEDK/NE6JWiKipk+ix1r+XKkymRataliG8OLKK3RN9tS6lkeAZ7MqyvmeSdV3ZWauXomNqFx2qCTdsEiZBIHj510MM745SjYYRYg+WiK0tYNgL+JaXEBuD1J7IMCqFJLcZqj2i8XwnREgtnVKl+/kSRhhdSExvTuB12Vijahm2bF+/+X6n6pX5ljkejaGLrajptPzxmoI5TqpXAA4cOACw6MabR1x0/O7v/i5f+9rXuP/++9m6dSvve9/76Onp4amnnuJf//VfcV2XW265pbH8lVdeyT//8z9z880386tf/Yo3velNPPXUU9x11128/vWv58orr2zZ/rZt27juuuu45pprOOOMM7jkkksoFArccccdeJ7HrbfeetjdSLeYo6zORObHsFswtSfFvscHeOFfN+L5NiRDxFAA63yMNVUYDGGvSfiQDS85S/4Dv+ndz/Kat+3i2YdP5uf3bl/QFfjRZNe+IV4cXcNgzyS9XXkyiQLpriLpWIm9E/08tmsrgR4UdVwQeSoMvNDCC2uzW2rD0TJ2GcsI6bMLLetscMfbthETHsXQRsrIb1CWNgKImVVcI2gbVR90NOUcGUIJT42s5969pzZSKAmnwsaeCTb0TBCric25BMdimc7GefoXJ5OfjiIpqzeMs27rIV4q9S1ofXsK0jtM7OnofztwJNmTwcuAMU86RQSSvicLxEej11VNW0xvTsxETTWaJfLkk0+yefPmNl/kxMREw6P5nve8Z1HbPOKiwzRNfvrTn/K///f/5h//8R+54447qFarrF69mj/4gz/gqquuasxdAUgmk9x///187nOf4/vf/z73338/g4ODXHHFFVx77bVtTcMArr76ajZt2sQtt9zCV77yFRzH4ZxzzuH666/nrLPOOrwDT8U58G+9+GWL3tNL0YTTk6bpPWmaNW+d4Kdffht+1Yr6NIyAM9V69RWmlfkQaaV8VUmNSMW0afZXeeM7XgDgDRe+wP6JPl7e2WqIVNMnqiZpi3TMN5NESa+0DT7rYIILXdhf6mF/KTJyBvGmL3SXqESwZZ/K1ZYalbDVSEeHE4RyXGp6xFIiF2r/CkeJdKhzNVRxp1YqACSVoWpqJMNXqk+6nNYohdq5Uy1PbQvnd1om7DxePZQi6lwqTEIpqIQWRd9GNpkKYqbHUDzbGIIG7d1AEx1SHX1Wa9v26aA1bWArUQlPSbuoUYq25ztEOhLKexFT0i0mAS9lB/jZntM4VIzy1F2xEq9dc4DBdK4tWmYchmlDXcf3LPa+soodz69Dhga267HldXvpHqi9P0rWpi2zEUB6p0Fyf/Q3CQ1JcQiKawCjFsxTvastqRJJ79NF4qM+0oCpbXGCeDRpur6emhpp+1dSr/AXUr2y6D4di68cmbft+WI5HqMxh8nR7kj6zW9+k9tuu40LLriAjRs3kkwm2b17Nz/5yU/I5/N86EMf4g/+4A8Wtc2jUjLrui5XXnllW5RiNjKZDF/84hf54he/uOB9/OEf/iF/+Id/eLiH2JEXfjDECz8Yorx1FcmeEmtOGePMDzzLwMYpLvzPj/OvX33rEYs+VEoO2ckkmZ4ClbLFwf0Lu3LSnBjUvxdDIsNyKAWT1Th+aBBKgxCBF0ZDzQJp4IdGzbhZj2K0Y4iQuOkRtzxsI2wRHCuNUMLL0wM8MbqJx0c3k6+limJmlVNWj3By/2hHw+uS9hkKRkcy7Ns7wMGDvY2pxgODk2x8zQFsd2Hvp6hA71MmzlQ03qC0RlIcbC8fn4ueZ8skDnlIAaNvSlLptYl3ts1pTiSOsqfjkksuIZvN8thjj/Hggw9SLBbp7e3lbW97G5dddhn/4T/8h+Nv4NtKRaYSSDMyOZQGbErYjO3q4tAd3bzvww+y9rQRut80yYFXao3J1CFCSuSi0j23h0ONIvhxwb/e9ya2n/4Kjz62nWkrBmnmXGe+kezzRTrULz1VT7WNX6e9xDVMKE2wlHXaGlYpkQ1zniZa0H5KVSMXqkdDzcer5alqZ041StGpZ4Ya2UjZyhV8YLYIhopvNio4DBFiColJiBBRZKLo2QS1CEUgRUtUok622qGJyywYhJi1braO4ZO2y8QMv+WqX23UlTbmN3WmhTIbxVTvtv49q7L1b6GaQqtKO3w1qhGtM/N7wXe4b/+p/N/9pzFWmfmHiJlV3jCwl/PXPc/L/uq2bcx1jGozsmYjabViMTaSYWK0i9FD3VSrM/9UyVSJTVuGWbthlOm2MOEs+540SP5bDKMkCE1J9rSQSr/EKJpzRzagYeJMv1yh+4XobzN5eoJqj127Ap4ncjFPd9FOM0vajaRqueoiS2SXIcqgDmNr+45YwZGM4423ve1tvO1tb1vWbWrRMQthwiG0ItFR7p35UtpT6mfvgQFO2jRMcn2Bci0Xa1Za30rVzF/tUk5kqhdPOcf4MXhpcjUvPRx9gcr2rFKbEbStqmO+ke5KqkOtLGnbX4f0iowpJ/i4MvjKnNvUaSrPqwKik4hWqzBU0eCarffna4oVU5b3FR+COr4dwKkl3OtF0xYBAoknTcqBRSWwW0pEm3s/BNKYt/pxBoklIjNm0qzgGj6WiASFRGCKEFtERk3LCHBqpk1DQNZvFSlqmiih9OFQe3B0rCRRlgkVQaamV8rKZGJ1H3abkbT9M+gKk5Fykjv2vo4f7NtOoeZ4jptV3tS3m619h9jWPYxV+2ztC9QBbnM38lJPnPnpGIcO9DAy3ENuKhrSV8dxPNauG2P1ugm6uguNz6dqiG0zI4cCe59J8lcuIhT4ccnU9hA/CUjROezdoXN+fNij78kod5Pb7FIadKi3Rmk3fSr31eoU5X6n6hV1mXmrV9pSNnN/p3Sa8LrsomGxwqkTx6uxdAWiRcdhUCxFVzWJePtETM2JQb13RSc/B0BRKSftVF4qkNhGgGWEpK0yTs1oGUgDU4T4tfSIKUKSZgXLCBqCohLajWmz9RPbGmeqZftqFUmwkK5mK4SxSpJnptbw9NQQz2bX8mK+v2FKHUpM8jvrnubcVTtxzID9fs88W5ufYtHlpZcG2X+gn3y+VayluwqsHpxk1eopenunMQxJpU3xz43zskXy6egzUl3tM7lFtI+yn4f4sMfAzwsIYHqDw/TmhUVXNCcOgiV6OpbtSA4fLToOg0w6cvlP5xce7tYc30g545+IxADM9S9q19tiS4EkunqWUmAaQVR2aoRYImwIhm671VmopjbUqEO40NaVJwBeaPBCdpBd06s4mO/l+dzqWmv0Vt7QvZ/LNv6KgcyBZfNreJ7J8y+s58Udawnr5bUipG8gx6o1kwysniIW99parS8G+Vy8ITjKmz1Kr60is4sQDFLS/UKVvl+VEUBxlcX46+PYhePhFKI5qhxHJbOHixYdsxDErWhEPVDpbn5G0tsftVcfDrqo1C6y7Lzq0Wi9X021br+t1UGH9Mpcz0f7UB6Yx4MRqj0x1G06athRuWu2S2xDSa/E4kplgZJOMZRUh1o54ljzezra0itKeqSeLqlHaev7kERhb9vwIzNmzW9R9k3CDm+wUesxIUTkC2lO9fS5rVUcag+NkpI/6zJbRcd8qY1O7cTTRus2HCWVoTboCpUR5p6Sb1P3mVaPUbT3Hkmq1SlCbUGupNuUD1FzdcpEJcE/7T+Dew5sJ+u1CniDkC2pcV7XfZCzew7xhu6DrIlFYv8FT0nRKTF/tWxX/ecxRYiU8Mru1Tz165Mo17rp9vdnOWnzQRL9pZYBfZ2mzaqPqRGxUNaqSH4dRzwd5UZLWz1Kp3pAh3RKhwF/IhQIXzLwRIn07uh9m97gMHFGHIFoT6eoL1tNn7RVsyjfBx09HfPMMVHWUVuMz1uJYi7gJLjY1IayzxXd9vwERIuORTLYN0kyVqHqmYxMZuZfQbNoBBJThBhG9DM64UuEcgKb7euq9XtNUAlaP+ad5ppES0YVHYaI0iJ1A2p1kaF0zQxSRubPqWqCvB/D902m/RhPTa7j/xvZ2uiG2u0U2J45wJndhzi96xCnpkcb3puEWL73v1h02bNnFS+/Mki+EJX7JpMlXvvalxlaM44QkPPn6R66EMoCnk4gdkTbKp5apbxtcdESazpgzUMFnFyIFDC5Pc70ZmeWjnmaVwVHuXrlSKC/TWfBj5lQ6xpazcz8pU7ash+AnWODlLoM6n/F6tTcPTM8pc29avJUL6aCmPLp6NDQaL5ImRrpULt9qmdtobYgVw+hQ6TDjrV+kaZiaqQjnOV+tC1bBBgiimiYIhIZS/9O7bwBgcQQIU7NO2EZAbYISVhVHHNGZBSVKEUn0aFGNjJW68wQk9ZQVfN01eh+a1TBVSIG6tU7QJeyjbLSp6OqfqgUVA9Is1E0lIJixWaklGaikqISWFgypBJYVEOLhBW1Lh9y8nTZZVzTj8bSS4EhJAXfYaKaJFtNMFFJMlJJM1JOM1zqoqi2um3itK4DvH/9U5zT/xKWETLUEp0xau9N63GbyohWtTpJJQwFBw708dLLgxwa6aH++bAtn9NP282Gkw5hmrIR7erkjVEjYeoydfOxn7eY+lUvPNuDqI2SD9+Qp7jWbI1mKJENNUoRH/YZfLCI6Un8mGDkzUn8lNWyXFukQwmOGfMYR/EX0JK8bRtq5GKJPTU6mUbn28ZiB74t0twa7eI4ODt3QouOExtRy9M37iN57bo9ADx/aGi21TSzIrFEgGsGc4qL+neCpKXXUQM12K2mV1wzCmHX16zn4+v7SynTVNX1Xy1kKzF+PryZFydXMVVJdEwjLBcpq0zaLtNtl0jbFVbHcrx3zbNsTI8dsX2Wyza7Xh5i50tDlEozwmegf4qTNh9k/dpRLCtcliGEYcVg4rEBcs91Qxh1a5W9HvK1RVjrQa5D+VknpCTzQpX+X5YREsq9JofemiSIG1jtY2I0mhWHFh1z8KZ/9yw9a6a5e3Q7B6Z62Tp4kJ5kkWLV4TfD64714R01DBHOWsWxEAQS1/SJWX6bH6Nu4Iw6aRqYRthi4uw8T0St01ePt3UZHY1uZbSY4pfDG3hxYlWL0LBEwEB8mv5YnrhVpcss45oethFQ8h2mvRgV3yHnxfCkSSANqrWmZCmrSo9ToN8t0OsU6HPzDMZz9Ll5VsWmG8IubagltcsvdHLTcZ57fiN79sy8PtetsnnTMJs3DZNJL+8k29yeFPvu3oyfj8RLbKhI8RQPBr1FlQsIXzLweImul2v+jY02Y29MtPX80bx6OdodSY8EWnTMgkiHnHruKzgxn8s5xJMHN9ATj4xsvxzZQDUd0ly07idbm2Co36V+cm5Tp4qMKWaoTvMi1O8itS5fSa+og9A6N+qSxGyfmO0RszzijodthjPttcPIgOkFJlXfBCOqPvBr8zwysfrlWNSlwhRhVOY1y/em3dKnI2gbhKa2C4f2KaCO0lAqrkQy4mZr6iKlmDhV86Ol3FdNodAhXaI01lL/s9SW4hmz9cTnqAbMDt8OCaEctxKhKYStaYzmFuNTlTjPjq/hhYnV7Mv3Nh7f3DXKmwdfZk0qy/bkvpaqkD6j/eS8WjH+ZpU/j60ctyoqlJ54BMqH1hadDL3qNjobA4cnu7nvmdfy1CubGz1S+nqznHzyQdatHcXskB6EdhOo38Hz4yl/Hz80CaoGBx9ew/jT0aA3q6tK7/kjxNaW2DXVBxiN/0kZtL3wFpyJgMFHijjZyL8x/voY+Q0uQgrq3l01faJ4etvSKW3G0XlNoR3MrErPE3zlvvr8vAPh1L/d/FVai051LLI3yHGbSumETq+cuPiexQ+/fCFvuPB5trxxD69fE6VVQgk/H958jI9uuZHEHY/uVIlUrNxostRMvYLDrJ3gY0oTLymjTp71plWRf6L1+RAxb/5ds3DqJk0/NBECimE0fK3guUxWEgyXupmqxHkl18+BQndjPYHk1L6D/NbQDtamso3Hl7tt+NEgV47zxMsn88zuTTy/fyb6uHbNGNtPe4X+3um2qp2lICUURxIMPz/A5PM9+IVIkKZOn6L7nLGFTZVV6NrhsfrhMkZA5N94a4LSaguzvAL/IBrNPGjRMQe58RQP/P/O5BGxgd977b8Rtz1+eWATU5WV35/DMgISsQoJ1yMdK2M3RUGCUFDybIoVh7JnU/YshJA4VtCoKHGsAMf0iTlRJ0xDNEctoi/eRoOtRt/Omec081MNTKarMaaqcbKVOL5nMFFJMlFJMl5OMV5JLaKyRrI+PckpvcOc0nOILrdMbL4xpscpparNfTtfw2OvbOW54XWNFIpA8pqNu1m7ZZTenvw8W1k4MoTpQ0kmX+pm4sVeylMzJmE7XWX9O/fiDy6+LFP4ktWPlMnsiAR8cbXFyFvjBDE9JVYzCzrSceISOAJRiwXvq/by9V//Ftt6RvjFyAacVHv/Ak9Jr6ipjyChhPTUShHVl6AMj2pr3bwARCOcLHEtn2S8QsyKUieO0n48DAVF36ZYdSj7FiDwg+jLz6odqzCjpImPie+bFH2HLqNMcyqlJ1ZCyigyYnUwi6rTU9XXpaZT7A6zOFSfh9q4SU2vJNT7C+iJMR/qNtT79XkeFd8kW0kw5cWZKCco+dHnJG5UI0EWGlRCCy8wqQQWpcAhW40zVU1Q6ZDW6YTBjA9GIoibVXpjBbqcMhm3yJpkjlN7DrYIy06v22b+z5yp/EHVZdTTpZpusZUPuoe6/uwn3MlSjNt//Vr+zzPbyVdnylrX9Eywff0eXr/5ZQYyOX5V3FgTuhHtPTRaIx9qd9FKaBF6gsLuFNMvpynsThOUZpYRVkhq0zTprTlSm6YxLEleuRCp/+809um33nfGQ4buL+FO1cphT48xdaoLYuHpFCVriKohhaekU/y5K0+E3yG90rbOPOmUxVazdHp+kX012maxtC1wHJxplwnt6XgVMVFJ8dhw1OHLWcTkjKOLxDYDHDvAtXxcx8exfGKWh6F8l0sZXUmXPJuyF4kNy1r81VpE1EHDlya2cbjbWHl4QWSiDKVABDGCUDBWSnOgkGFPvpdDhS6K3uzlogvBMXy63SLdTpHVsciY2efm6Y/l6Y4V6XULjfdc9XRMh639JpajSuNoE4SCJ0dXc9euLXz/N6dR8qPXMJSZ4KJTn+LsjTvJxRYxnnUO/IrJ1EsZhl8YoLAnhWwSCqbjk944TfeWKbo256iah//V2fW8z+qfeRh+NNjx4NvjeOnleQ0azfGOFh0rFollhsTsyOwZczxitoc1i1kuCAUV36LsW1HKxLeQR7BE8kQhCAXjhSSjhRQTxSTFmkir+BbeAlMbCatCb6xAT6xI0q4gmDGWmiLENX3ipodreMRMj4xTwrEDMk4J15yZDNtrtKYMvBOwVbqUcGC6i6cOreHhPRt5ZN9Gpsoz4un0/lHee8ajvHnjjka325w3sKR9+hWDfY+s49DTA8imCIXdVSV1Uo7U5mn61k0hmt/uxQfHEJ5k1QMe3c9GKxfXmBz8rThBwsBavmyQ5kRGt0E/cZGWaIyfdxJK9UO8ffrmVEKpw1fjWMrId3WEu4rjelhGiGWEGEaIUW+eZYRRFMPy21qMw0wEoxqY+KERVZkEJl5g4tRTOga4ToD6zammMjyz9aSmNvqC9jHxGae1mUCgfMjVygO1EkUN13dKfcy3jJpOSSmVJmoqpLmdeMm3GJnuYzif4WA+w6FCV8dqhvZjiv5GPW6B9alJehJFBpNZBhJ5HDOgW6lWGbSmWu6r7cLLHaaBtVW4KA3EykoTLXXia6CkRuZrH64e05EglPDMwQ08sfckdo6v5qWx1UxXlcZqToVz1u3lQ6c9z7nr9vKcH72X9QZdalM0tePsbEZSKWHsxV5evPekhiE01lsidlKB5EnTOP2VhuAr47T8u5SV1FdZ7Xrrt+7TKArW/XOF+KEoFTbxOpeJ17hgCEQAnUa7qOmS9vtKaspX7ivpFTxlxIBaxdF+CB2qVcI570u1mkWhLRWyEN286HTLPE3P5q2oOY7Rng5NK5JZu2EKSdypYllR50vTDqITlRGJCUNIDCPENKIUiWXO/49QFxj1CEaldqsfQyeR8GpGSij7NsXApuC5FDyX6apL0XOYrsYYK6UYK7UPGnNNj1WpaVYlp0m7ZeK2x4b4OCm70pjNooqK8SDVth3NDLsne7ln53bu2Xkao/nWcQK2EbCld4w3r9vL29a/wlmD40pp9dIpTsbYde8mJl6Ohie53WXWXbCPro3TZL1laIPehFGQrP9hmdhYiB+Dg78do5xeWtpN8+pEezpexdiGT3esXLvqlgy+PocQ4HsG1Ypdu1lYdkA8WSEWry66SVUoIQiNRm+Mep+MutCo+FajH8GJiJSQq7hMFJJky/GZ7rC1H6EUhKFA1t4bo9ZG3TF9LCPEC81GKqTk2ZR8Z0HvV8YtsiaVZU06y5pUFttuN8T22svbYOp4RUooVKMTpGmEVAmjeTgdomyhhHzVJV+NcWg6w96pXnZn+9if7WWikKLk21R9O/IR+TMehqRT5pxNL7J99X7esmqSk3omWkSGLZbHiyIlTO3JsO8Xa5h4qRsQCDNk9ZmHWH3WIQxr+b+RzZxk1f8jscclfhz2vj9Otd/AyM6/rkZzIqJFxyyEZtRcS5iSuNsaju9yS8Qtr2NfA8sOsewKiVR7CsYPDKq+GaUcRHTSrJ8wG7daoy3b9msnyGgnUklTmJacd9y2emJwrfmWV8LrarOhTg2rrNaYb1Id0a74RtTqlea+HUEoGC8mGS8kmCimGC8kqQbL/xGNW1VSdoWkXaHLKZFxSmTcEt1ukXWpSSpGq6kvH7SPIVdTOmr5qRO2vtdqKkOtFFHp1Im1rZpknnNkp/ktKp5vcnCyh1whwbOVDUwUUkwVk0wWUuRKCSaLSfwO3hVTBNhmgG362GZANbAoVt0Ft1I3RcBZ61/mvC3PcvaGXY3pwquNaF/eHK9NrUZRDbJqOiVfjjH+m14OPbmK0vhMFCOzeYoNb9+H1yWoYDfSJ0W/3dQZKo3Yin7rPkvK/SAwsCYlq74bYk+BlxLs/Z04XsYAD4yqUgXUXhCH8q/UVq2iZBExKkpaoa16RfnMqWmI9kPoUI0yTzplsamLDs/P16xr3hTNfA3KVlIzMBWdXjlxEW5A90WHkL5gFJvmf0nbCDFEPVwfRRv2vrwKKcG2A1zHw4l5OLZPEBgUSy5Vm0bXTqBldHYnLLWk9gQiDAXTFZdC1aVYdchXXLLlOJOleJu51RQBfckCfYlCo1upUTuZ1lNTZm0ibCgFgTSwZIgXGthGSNyO2nMn7SoJu0rcqtJtt/pODOXkXAlO/EqCsWyap3eexJMvbaZUXXyoP5AmgW+2RCzquKZHXzLPusw4a7snWNc9wUAyR9z26HGqxCyP7liRhONROIJfgqUpl/2/GmT416sIKtFXnWEH9G8fZ/XrR4j3RGd1z28XlUsiDz33BXT9QmJ44HXDnvfG8dPauK1ZIktMr2jRcRxjJH3sgQrCknRVQnKV6IvJMoKG4bIamI3pk37NOBYEJuWyA3ml/0R3e+Tj1YSUkC3H2D/Vzd6pHrxZIhiu5dGbKNCbKNCfLLAqOd0WsVGv4NUIgNqiXG1B/mpluhRj1/41PPPyJvaMrGo8noqV6OuaZjA1SU8iT08yT0+iwFByit5Enu5EEZCE0qCbqAW4HxhUA4tJ36IamLimT8qtkHFL2E2t0tVprMkjnA0MAsHYjh4OPr2aiZe7qYt8N1Nm9etH6d8+huUeIUE/DfaDFvajFqIWqqmsgUOXmPhVLTg0GtCiY1aCCZfcw31kzhujy61QDUzKvkVPrIQQUSrAP8FLTqUEzzPx/VqERtRbUBFV1BiSqmNim0FHv0oYCiZKCcYLSfZPZZiuzIS2LSMg5VZIu+Xazwq9iQIx22vZVifvgGZ+pIR8KcZINsNLhwZ5Yd9a9k/0N54XImTb2gOcuWUnW4YOYhiS9fZ4yzbSbTH/kJSSgksrf56jUfHSiamJFL95chO/eXIzxfzM56x38yT9rxsjsyl3xAb/yazAucfGetxEeNFOKoMw+TaD0hYRdcqbODL71rzK0OmVExdpQPmVFNZAleTpOfriRSqBhWsFgMQyJOnmpGpMbR/YeldNp8Td1gSt6pdIOq1f+J2mvPrB3PVm6jZjiv9C9YkYIqRYdiiWHSoVm4o3UwkzG+MTaeo9QxzLZ9RNEbM98hWX8UKSoCm/boiQdZkpNveOsTqdwxDtUQs1H7+QVt2q/6Gt06ZyX02nqPNg2iMp7VfGanmpuk31mALUtFHr8kFbWqm9Y+xIrouD2R5G812M57sYyXcxno+qbRzLBzOqfJouxTmU7aZYaU8bDPZOsG3dAV578it0J6IBhn5tMJl6DJ3Kdsuyotxv/Xs5yvtQVV+34mXxlH16HXwonpL3L0iHqmfy0itr+c2LG3jyhS3kJmaqhayEx8Dp4wy8ZoxYT4VSaFOW9qxfuHm/Nb2U99pTRlFqdIaib8OkwLzPxvi5jV3r5umtkxQvDDnUl4jERu3fWFRa11f1nOrfWMgyZln53CqeDqOqeLhU/4V6v5Mq8+fZxjx+iTZ/xmEMfJuXeXwjagntikaLjhOf/BM9OKfksc2QWM2IOdfU1JWGlFCq2BRLLsWyQ6h8uRpGiGP7UaCjvg4QBrWJs4ERtUYPTPzApFhp/QJ3TJ/+ZJ7BdJYN3ZNtg+Je7dQH5ZU9By+wKHkOY/k0h6a7mcinGZ3u4lC2m5FcpqOhcy4Ekp5UnqHecU5Zu5+hNeMde8ysJKbycX58/9k8/G+vpVKdEQdChAxtHuOUN7xCbq2FMUuTvKUiA5DP2ViPxBAvmIiacPc2Sornh3hbZPSPMnGCfEFoNMuMFh3zIQXT1RgZt4RpSKqBgWvObQI9npESqp5JueJQKjuUq3ZLxMM0ApKJCnHXQ5gS05wpF+00i2NVLF/L75t4vkXGLFLyHOJ2lYFUnpRTOWEE2mKQEnLFBFP5JPlinFLJIVdMkC/FKJRjeFWL6VKcYtVdcNmzbfqs7ppiVTpLfypHTzJPX2oaU4RUAovJagovsIg7FVZ3T9GdzjeqQqC9LfpKYiKX5AcPvok7H3sdFS+qFMl05Tlt624SmwsMbRrFiUWC9teFdXNtavGEIPeahM/ayJ+7kJ2ZEBNu8Qne6ZFda88XFNRolozu0/EqQSLIVWO4pk/Zt4nVwtIrgbovo1q1yPpxylW7LZphGiGJeIV0okzMnfFUVBZQrioE2FYYDRNzPU5OjbU83yktdKIQhIJCOUahFGO40kO2lGBkqpsDkz3sn+ij0iFMPxcCiWN59KWm6U1N05+epi81zerMFIOZSTamxzGaPC5qakJtSLacI92PBX5g8IsXNvGzX57Gv/3mZDw/+jxuWHuId13wc7af8gpCwDPl9cu/87xAPGtF0YwdFkGp6XOcCgnO9AnO9mCg9veorLy5NhrNsUCLjtlomsbu1NIqAQa2FRAz21MEQh2WppxrHSWtoPbMUKMIccV/oeaUO60DkcioVK3Ik1GxqFTttitpIUISsSpx1yMRq+LY0XwPSzEJBso+O/XpUPtuqP6JENU3ouShVW9Dh9e53KgejrmQEnL5BFPZJNlcklw+Qb4Qp1hwmS4m2nwxzRhGSCZZIJ0okUkWSceLpOJlErEKJ6cOkYqVSTplHCvAMANMYyaq1EkwBEK0tJX3FM9FWar9KpTn5xn4VpSKSOqQCi+K1s9lUdlmWXlv20Sn8udt9o1ICcWsw659gzz70gYeffoUcoWZ8QLbNuznQxc+QmxzFiEgL2MgYTps9a7klZLnouLZUI8pVy8ZLgO/tpFPuFi7BCKcWU7GJcGWEP+1AcH2gIq0AAdq2apiuXWfsqqMEKgofXZUf0aHrJdVVpdRKuIUD4dZUdqcq56OquKPUv0YosP/3rxt0FWPx9ImxHbaxnx9O9pQlzfVNugL2P5Kao2+wtCiYwUThpGZtFq1qHr1n+3mT8MIiTkeqXiFRKxKzImiGZ2EzKsZPzAYncqwc2yQ0ckMo5NdTGS7GlfYnTBESCJWpjtRJB0v0ZfOMdQ7QayrSl9XDrPmLVDF2Ca7NSKklpa+GpASDh7q5dkXN/HiS+vYs38V+ULriPhMqsDbXvcbfuuNz7JpzQhCwAtez/IeiA/ibhcedBC+aOgif0jinRribZWYG71Wz+PxOmhac2KjjaSa5UbKqFKhWLapehaebzban4dhrRV6EJWxztb90TBCYq5H3I2mz1pWVNIat0+sb8rovTLwAkHgmxhmzfRqzjxfqdpMl2JMFxIUyjFKFQe/alIsu5SqLhUvigZVPJtCxSXsMNzNECGZrgKZrgJd6SKpZIlN3aN0pwokY2WEgD5lTOio3z7D5dVGEAhGJ7oZHulluhCPunRKSRAajE5keOaFzYxPtc5dMY2A9YNjnLx2mLO27+CMLa80hNsROcb9JuJbScTB6O8uVwWUXwvVM0LCmQpjzJWdqdKcIGhPh2ZBSBlVe/i+SVgL2QaV6FusMT8kFAShIAiMRY2cFyLEsQMc28dxoptVM392aqW9kggCwcGRXvYd6Gd0NIMfRO9fWKuaCWqVMyqW6ePYPlXfwp8jStGJuFOhvyfHQE+W/p4s/d05REK2eCkA1thTS3lpxz2eZzJRSDOdj5MvxCmVYpTKDqJiUKq4mGZAzPHADnEcj2rVJl+IUyjGyBfijE1kODTWM+/7b1k+2zbv47Rtu9m8fpjXDe3Hmadb73IgQ6jeF6fyLymEL5CpEHlJGV7jU66sXMOt5lXAyv5a16JjuWlJk8qZn9PZ1rDx3IWLEtsKcKwA2/YjH4SI/BDCiHpiWGaAFKLtZLiS8TyT8ak02akk42MZDh3qXrBoECJsiDU/sPCbTLCJWJmuZJFkvEzcrdIdL5BwK8TdKjHbw7U9XKdKwq3SlSgyGSRbtp0NWv92JwqBb3DglX5G9vVSzMW5P2+SyyWZnk5QqSxPK3jb9lg9MEl3Vx7LDHDMAMMIScbLbN+6m02bD+I4M94DxziygkN6UH0iRvXeBOHB6DMiT/eQl5bbO51pNJplR4uO2ZAgawrCVr4IHdPHDwwOTGaoeBZeYEZio/GdJTqoURmNta8ZTp1a2a0QEtMIscwQw4x+WlZAt9sqS6odwv5VpTmYapBTTZuW2nDqGNWySgnlssPUVJJsNslUNsXkVIp8vv3kHotVWDs0zprBCdxYFcOQGCLqhmrW3ivTDDCMmsfFt3DD6Mrbtn2S8TIpu/W9VNukNzfFqki7zYDZydSpPqaaNNX7gZi78VZVuR+qjkvAUAxvqkl3Opj7Cr0YuviewfBL/ex9fpD9Owfw56i6MK2AVKpEMlkiFq8Si1XJxAvE3Go07bhiU6i6VCs2tuOTTJRJJUukUiUymTyrV02S7CpiNL2UhGjteFWUNsVg5hicDoPwVL/LlCIKJ73W+3mv1Via81zIC3jUgYccmI4OSLoS+b4y2ddZIGKRkRTIl9sFl221/r0j79QMlZLyPhZbl7dKQrnPnPejx9TmX8r9sjKwraq8d948jb1U1EZgHdZRB7zN23jrSBgyF9tgTDXMrmS0p+PERQpJ/pQAEUJGtjYDCyX8Zv8gudJsX/K1v2ytA7IwJN3dhZZtpJ3WE2GnypATCSlhcjLN/v197D/QT6HQ+b2LxSpkugtkugusXj3J6r6pBff5MAxwHJ8uqwR0+BZ/lZLPxtmzc5BdL67l0Ct9BP7Ml3QsVWbNyWMke4qs7x4j3VUk1VUkmSrTFSu2vfd9Zqt3pRC2Voao1UjHsmxXlgTe0y48EYcXLailNmUmRP5WFd5ShThQ1l+DmpWB9nScwPhpSWV1CAKy+Tjd6egkJiXsGh4gV4ojhGRtzxQx2+Ol8ZrrrPYlrX5Zr8QGWTIEv2jjFy1C34BQIP3IfwKAgNCOgVGbxWKGGAkT0wwJAqNWthvdRse6KZWaT1CSrnSRnp48PZk83d3RLbTU8t6j93pXCmEoKBZjZKcT5PNxDEPiOB5ZM4Hl+OSzCcYOdjN6sIfRA91MjXe1rJ/MFFl3yiGGTh2hb+2MqNvotFbUrMT33suZVH8ew3/awf+NC17Ti1jvw9uryNf5y9J9W6PRLJ6jKjp++MMf8nd/93f88pe/pFgsMjg4yFve8hZuvvlm1q+fafCTy+W47rrr+MEPfvD/b+/so6Sozvz/vVXVb9M90zMML8MgLzLMEJYfSHwhUVYJKpA150ROfEkIoChgMCY5C+uOEgwDsyBhNkSz7lk9EYUkrLpnXUP8beJKPDgiHJS4PyCiogOKIMjrMNPT711V9/dHM83UrZqpfpue6eH5nNMMVXXr1q1b1V1P3ft8nwenTp1CVVUV7rjjDqxevRplZWWWdb/wwgt48skn8cEHH8DpdOL6669HY2Mjrr322qza6ghI8H4qI1Sj4XybDw5Fg9cTR3uHB+cDyXwjE6pPocIXBgB8dmFwzxUWAbrKELngQfSCG7GAE7GgK/V22B0hGFUaJ1DVbVlFUTG8qhVXXHEOVcNaoSi66c04fBmklc+EcNiFL09U4ssTlTh9YhC+PFWJjo6SjJyNAY5hV7Ri2LjzqB53Bv4hwWTSwgEg0+UciHzhQttfS9G+vwzBwyVAl2lGaagK/asq8NUEMPTivTaAA9YRAxyaXkkPzjmWLl2KX//616ipqcH3vvc9lJaW4uTJk3jrrbfw+eefp4yOUCiE6dOnY//+/Zg5cybmzp2LAwcO4IknnsCbb76JXbt2wes1zuE+/vjjWLlyJUaNGoWlS5ciGAzipZdewrRp0/D666/jG9/4RsZtZhzwHJegeTii1TpOny9DpT+E8+3JqI9jh55Dpe9SZFIm9Tx3aUoqJpQ3+V8I29MNDpYJOmdQIzIi5z2Invcg2uY2/SAzWYfiS4ApOiSZg8k62EUJI+cMJXICuChd1TUGD0tA02TIkg6nK3FRUZNAWVkYQ4a2peSPHAwJLpv8UGJCfpF0ztFchzC/LnSdQzfOS4vJ2MK60fCxCqolBuISpxnCwrKYNK417MP5c34E2kug6xJimhOaxhCPOXDhfClaz5Wh7Vwpwt1MQwEcJd4oSrxRAAzxmIJo3Ak1psDljWNQVTsqqgIYNDyAyuo2uEoSaL/o8xG4GA5dTPDWLht9asLM7AMg+prYBRwT+zYqCQnjbPYHgIQwLPFl3I+zf63A6f8dhLMHKhA9b+xrPkIDJqrgExPQR+joiLsBuFI+G5pgSAejxv2jYbPhGxcUNZoQ/EsXpmgcYSEYmI0PhyNsEXgvIvxGJIxlJCEYmBQTJPEJYdkuWZt1quie9xGW7QJ5idvtfjfTwVSn6PMh/HZmHGysH0HTK2ny1FNP4de//jUeeugh/OpXv4IsiN7VLg5MTU1N2L9/P+rr67Fhw4bU+oaGBjQ2NqKpqQlr1qxJrW9paUFDQwPq6uqwd+9e+P1J3f9PfvITTJ06FYsXL8ahQ4egKJmfKgODr0UGuzKKSMyJc23Jt/oqfzuqy9szrq8/wDkQDzoRPFuCjjM+JELGH1jFnYC7MgpXWQx6iQ7JrfWYe2WYxzjHX+M722ttLxY4ByIdLrSf8SESdCEecSARVRCPOBBu9yBwzotIR/qyzPLKAIZWX8DIEWdQVX0e5RUdKCmJgQuRFr+IV+b7VPoVnAOf/mU4dr10FTqOXXrxYA4drvFReP5PBCVXhXHc6e+hFoIg+pJeNzoikQjWrFmDsWPH4sknnzQZHABSBgHnHJs2bYLP58OqVasMZVasWIGnnnoKzz33HFavXg128Um4efNmqKqKlStXpgwOAJg4cSLuuecePPPMM9ixYwdmzZqVVfsZZxg+uA3HTw9CQlXgccVRM+xs0cx3cw6oIQdiAScCAQci7W6o0a5vlxwufwzuygi8g8NQStTUuYUyzB1yucE5EAm6EDjvw7FWJ9rOl6L1TBlaT/sRjbhs9/eVhuEvD0JRtKRfjKxDcWgoH9SB8soOlA/uQEVlB5yupFHuFUYJBsL0SLqc+bQcO7dMxokPhwAAFI+KEX97FkOmtOL0KB8kZxeDONhNJQRR7ND0ij1//vOf0draioULF0LTNLz66qv45JNPUF5ejltvvRXjxo1LlW1pacHJkycxe/Zs0xSK2+3GTTfdhD/84Q84fPgwamtrAQDNzc0AYGlUzJ49G8888wzeeuutrI0OAJBljiuGXUAo7ILPG4XUz3/rdY0hdsGN6DkPoufd0FWjocckHSWDInBVRuGujEB2Jocjc52uGWhwnhxGD3e4EQ85EAs6EWn1INzqwYE2BwLnvVDj3UwPMI7SQSF4yyNwehJweeJwehLw+GIoGxzEpOFH4fZcGv6OCnlPNPI7AACcOFSJd/8wAZ++NxzgDLJTw5hvnsSV3zoJpy9pjJ0Nem1qIYgBAhkd9rz33nvJAykKrrrqKnz88cepbZIkYdmyZfjFL34BIGl0AEgZFCKd61taWgz/9/l8qKoyOzB2LdMdsVgMsdilN8hAIGBZTpF1+Ev7pwxTi0uIdzgRC7iSf9tchnlMJutwlsbhrQjDUx6F2x+DJHNE08giO1BREzLiUQcScRmxhANqXEE07ET7uVKcOVOOjnNehC6UQEv0LHNgTIevIoKKygDKKzswaGgAg4YGoJdzyI5Lc8uiT4fbObBC0ucTNS7h6P4q/OXV8ThxaEhq/fi/PYYb5h3E6TKaPiGIYqXXnzpnzpwBAGzcuBFXX3019u7diwkTJmDfvn144IEHsHHjRtTU1ODBBx9Ee3vST6LrNElXOpUrneU6/z906NC0y4usX7/e4CPSiaTCENQo3/Q0qqDFJQTavYgEXEiEHckQ6ZwBnIFzgGtJp01NlaEnJOgWD0bZrcJdGYGrMgKnPw7GAPfFzLY6kjlc7BK+qULwMatYImLQsohmfPMXz1N0+nQIjmQRQb3SmV8mHlKQCDmgRhQkwsm/WkyGlpCgxhRoCQmSQ4fiVuHzReHwJKCrEuIhJ7SQjGjQhXjYkfpoifRvfcmpwVGSgKMkAXd5DO6KKIYPbYWvMgxvRQSSzFEiGYNetapeWMS5urRdNqahT8ehMiY4r4qOoK1qz2/8bQmjo6g4PeOWjIaQmKQOMDvMinE4xHxA4jFKJWNgto6QG+HTbnQcL0HbkVIEP/Xiwuc+cC1Zj6TouOJvT2Pct75A6YgIWuHDiagx4dvpqFFB1SbEzxEdRcVMxvGwGNjLfG8khOBgLGGsQ44al5WQcJ+HjfU5QlxYNjtUmoJ/aWJwMGMwL1NWWSFDLLcK/tV1f4s5YzEYmMkZVXTKzDVDbJb7XC6QI2ka6Be9n51OJ7Zt24bq6moAwI033oiXX34ZkydPxsaNG/Hggw/2dlMsWbFiBZYvX55aDgQCBvluvuAc0KMyuJr8YneGmdZVCWok+RBVI8kHqxbL9LJwKCUqFF8CDl8czvIYlBK16EOkJ0IKWj8ZhPMfVSJ8Nv1Q5KfTLcg4FKcKxaFDdqhwuFWUVobhGBSHtzKMksoIXN44opLZIKhyFacjcW+jqwzhMy6Ev/QgdNqN0Bk3IqfdUMMymMzhcGhgMocWlxA85UmOylng9scwdvpJ1H3zOHh5Yc+BIPotNL1iT+eoxbXXXpsyODqZOHEixo4di8OHD6OtrS1VtruRic6pj64jIX6/P6PyIi6XCy6XvdNfVsQYWEgGC8sIRtzgXUYkwj3sBnA4vQm4S2Nw+ZJTIZ1z/Iwlp0skRYfKpKSk1aNCUrjpDa6Y4ByItrsQOF2K6AU3gsd96DhWeknCyzgcHhVKSSL516NCdmmQnRokpw7JqUNPSFAjCliUIR52QFJ0uHxxlPiicPticHoTcJYk4PeG4CpJQHGplvEq2lXBwOn5BXFAoicY4hEFalhBIqggcsaF8BkX1LMOhM+6wCRAcWuQ3Dpkt4ZYmwOhLz0In3GnRinSxemPwzc8Av+VQVTXnUdlTTu8Q6KXHJr1Xvp+EkSxQUaHPePHjwcAlJeXW27vXB+JRGx9MKx8Pmpra7Fnz55UEDG78r2OBrCAAqlNAYtcMjI4ADAO5tTBGE9lgGUyh3LxIap4ElBKVDh9cZR5hNwrmnkKpZh9MuIhBcGTpQh96UXgpA+hMyUmh1cA8A0PYvCE86iouwCHx3q+QjQayhTjEL44bSBOhVyOcA4kziqIfuZG/KQTaquCc+1DETvvQLzNCT2evQEruzR4h0dQUhWFe0gMJcOicPhUcJ3BpavgGgOTOXxVESjDEnCUXLqu5XLP5jhBEMVNrz+1ZsyYAQD46KOPTNsSiQQOHz4Mr9eLIUOGoKqqCtXV1di9ezdCoZBBwRKNRrFz505UV1cbFC/Tp0/Hnj17sH37dtxzzz2G+l9//fVUmWzgDLBTJXIORIMusDYFLCSBBRSwi2/nHBzcq4OXaCgdEobsS6Az75ff3T+dUjOFa4Aek1MWdPyibwK7GEhMcehgEke0zYXAiVIEvkh+Yu1uU11M1uGqiME9KAp3ZRTltW0oq6SHUL6In3Ig+P98CH/sQfSoC3rYPha4UqJCKdHgHhyDZ2gM5cODKBmSNOrUqIxYxAEtIsNRmoCvOoKSqhhcg+KpUQo7nw4xyBpBEN1DPh1pUFNTg1mzZmH79u3YtGkTFi9enNr285//HG1tbZg/f34qVsfixYvR2NiIxsZGQ3Cw9evX48KFC/jxj39scHi677778Itf/ALr1q3D7bffnppK+eCDD/Db3/4WNTU1uPnmmzNvuM4RqgLAAE9MhuS4dLVULiHc7sbJliEItXmgq7IhZiJ36tD9GnS/eqmHfVoyOuNFPytbJ07R2c0iy6w4naKKobGFG0wSHNHiNiMlcVUGghJYm5w0qCISEJLAwhIQk4AYw+mE0Yn3LEb3WGfXxrkHR+EdHkLJ8DC8VSE4/XGEu0hHVQAB1WyciJjOWyDChAywsnFZdG4Nasbh/I6EuQ2KkHnYJRnnYOzaXSIbR7LCmv0UgjhiIzqSno0bnVM1VUL8Cycif/UgvM+LxAkh7orCIY1QIV+hQhqkwT8sBKVChVKhQvLqcHkuGcmdeLu02wEVOtfR2ZsRKIhAAbpkfU0I96hPOG/ROfaCbHaGDWrGvvw8NMiw/GXQmBqhXYjiGhczwGrCm0TI+D1QQub7icvGdUwVIo4aTwsOQQTnCIqOo0IE4rB5FE+Ki46kwnLMJqus6Dgq7G8KNmSVjVVw6jRlle2NLLI5Yhv1tB+2OW1oeiU9/u3f/g033HADlixZgm3btuErX/kK9u3bhx07dmD06NH453/+51TZ+vp6vPrqq2hqasK+fftwzTXX4MCBA3jttdcwZcoU1NfXG+quq6vD6tWr8dhjj2Hy5Mm48847EQqF8OKLLyKRSODZZ5/NKhoplwHdAXCF4fz7Q1A56WzK8Gg9WYZjB4eDX/xBlWQdqouDe3Rwnwbu0WE7RNIP4QmAn3aCn3YC5xUo5x0mL/1u9uwSapwjmQnOHE7dMzQC74gQvCOCKBkehuzSU9NMKWyyb1/OcB2InHYhfsGBeLsDsXYnEgEFYIDs1tEhOyE5ORJnFcSOuBE76gLvOk0icSh1cTgmxSBfmQAbroF1+WqUuo1RtYolAB5BEMVDQYyOmpoavPfee1i1ahX+53/+B9u3b0dVVRUeeughrFq1yiB59Xq9aG5uxpo1a/Dyyy+jubkZVVVVWLZsGRoaGkxBwwBg5cqVGDNmDJ588kk8/fTTcDqduOGGG9DY2IjrrrsuqzZLKlD6BUfHFYAadOL8X4egYkIrgl/4EDmVfKMsG9KB4bVn4fHF8Jfjwht+P7Ao04EHJfDjLvAvXEljo4uxwABwiYOXa4BXA7w6uFcHSnRwtw64dJT7w0k/lYvPtiu8bcl6OcA1BkXn0FUJskuDpHDoRWiM9SVqSEb7QR/a/1qK9oOlSLRnNh3BPDrctVGUXB1CYgKH5L10Y4ojPARB9G9oeiUDRo4cic2bN6dV1u/345e//CV++ctfpl3/vHnzMG/evGybZ4kcTxoewVodasiJs+9dclQdNvYchtcWTzj0rvCoBPWoB+phL3BGGHL3amDVMbDBKmJ+Dvi11CiGVZwOyW09VMkYwBQOmemQXUU8nNmL6BoQv+CEGpERCruhRyUkAgoiJ92InHAhctKN2BmnMWuqU4d7cAwOvwpHmQpHWXLKRYvKCEVc0KMSZL8K99gYHGPjcFRdmiJpT6Sf74UgiH4ITa8MfOQ4UDnlDFoPDoYWcUB2q7hy8gmUDioOB0fOAYQl8HMOxFpLoJ91Qjvl6vIg48CwBKQrYmAjYoD/UoI3JMjJL1u4DmhtMvSYBDCASRyQAfW8gugnbrR+OhiBFh+0qL0zp6c6Cv/kDgyZcgH+uiAkJfnLIfp0nIwZpeFioC6CIIi+hoyONFA8GgZ/9QzibS64KmIoLe3fBgfnAFoV6J95oB91A6Hkg62ru4RUGQfGxMCujIKV0EhEtnANiJ92InTci8hxN2KnncnPGSd4Gv4wTNGheJLxLiS3DsWrwTM8Bs+IKDzVUXiuiMJRlrxyoiMpQRCXGTTSMXCRYxzyRS/ouJZ01pMqVCQgI66bu40LjpNc8JBXhYBJCUGNwoX59bAwlSGWB4C4ejE7rw6gQ4Z+QQE7rwDHXWDBLjFCWHKahA1OgFUmgGEJwK8hpioAZKCb/CLRuPE8raaSwopxeiYgDOErQs4ROz+CsGocXVFEz3OLOsRlVegrp6AsEZUnIqGYC7xdgh6QAJUhHHMkVUcJBrRJ4K0S2tsHQTsnQz3lSK63QuJgbp68PjoAzsBKdMhjE6j4SgdK6iJwVsfBJCBiCoPOEYGMCLzARWWEmL9F5HTUqOIQFVAdcaNCRvSvERVSVn0v9qXY12KdYhtKlLiwXbhWsjkSWzBhbLeoVjnfbvTzUoPGvmTCaJIkXC8lLCyHTE0AF7I8ihHiZSH0i1PIdGtSq4SMFcgR83lLCUGtogrLYtjzuNEoNYU9F5UnAuI5AjCHPbdSuGSCKUx6GqNxva02KSI1SxpRHGz3z4QTJ07gP//zP/GnP/0Jhw4dwqlTpzBo0CBMmzYN9fX1+NrXvpZxG8jo6GfwBAM/ryB+3g3tjBN6e+cluhSZs/PO48l/gA4Z0Bi6fn25zIERcfDRMWB4HFAAWS6eL5cdnCOpqY0x8JgExAE4kXRyVYwGEk8k/Vj0KAOPStDiCniUQQ/KySmQdhlaQEr+bVWgtckGPworuiokmUuHMiIBxxVxOIYnIA9VkRgkQRqkgV183omGUYXbOrEgQRBEf+Gpp57Chg0bUFNTg5kzZ2Lo0KFoaWnBtm3bsG3bNrz44ou4++67M6qTjI5CEmFgUQngAHcryQdnVAa/oIC3OsAvKEAg+cDLOGamzMHLVaBcAx+WAEbEgAHiksGjDPqHDuinZPDTMvgpGfysbI63cJF2iYOV8NS+ULN4N5A5mF8Hc3DoEgMkDigA8+tAhQ7v0CjkSg1yVQLyYA0OxfhGqKsUupsgiDxT4OmVqVOnYufOnbjxxhsN699++23ccsstePDBB3H77bdnlEqEjI5ehCUAR6sE53kJrrZSSB2XhnlVlHa/Y4kGZVgM0pA4pEEJMIknA2Bxdumm4UCiM2y4Twd8WnLkYwDBT0tI7PZA2+sCYj2cm4MnPwmW/OgMPGguz1w6mJuDuXVILj051VGuQS7XIJVpkMt0yJUq4mUyWOklGXAw4TTVVeLq3349BEEMPAotmf3Od75juf7GG2/EjBkzsH37drz//vu49tpr066TjI7eQANKDsvwfiaDdfH14IwDbg6OiynfGQCHDlahglWowMW/rESHWzHOz+oWPh1MFS5fkc+e8CgDPyaDf6GAf+gA//jSUA0bqkGqSYAN04ChevKvVwecAO8yl8LjgDehgoekZK4bD4ezJAHm4ikjws6nQ6VRCoIg+iP9yJHU4Uj+PmcafJOMjm6Q4xzSRaepoCAdjYoPeyRT1IMDrtMSSj+RIUeTD0K1hCM+SAcfEYc6WENnlO8yjzEHxSX5Y9KxU/QBsMogKyaB02yye8qCI1ks3vPlTwgOplaOpB2S8QHtEB7oDlmYdug8rxiAEzLYcQnsuAz2hQx2zth+zji0CToSN6jQx+kX3VokcC4jNXcUN/dNzB0DukTOVpgTXeerJMHcF6Oiion0whYjHXZOl+I9IjoKi6Hb00neZ4reKtAaNWbHFZ2XQzHjeYhtCrmN262Opwh+QWLfazb3rVsxOjeK97l4bQAgkjD2TUeH0VlZv2BstxIxHrPzu5g6hiACUsI9LwOAqD4WfXpNjqQdxgLOoHFZCRv7wcqRFKLjqPD9ZWLYc9HpUwxhLmxnknBSYph0wOw4agqL3vNyQRAdQYV7Ki1n1cuMzgzsnWSabf3YsWN44403UFVVhUmTJmV0bDI6eiBRwsBlBlyQgYru3465yuA6JaHkmARnW/IG11wcHXUaYkOTIxqu0gEU35tzKO2A8yyHtxVQzgIsDjAVcMCd1ObKAHdzMI+eNABUAB0McocEBBnQxlKJ8bqi+zn0ah3aCB3q1TpQWeTDNwRBEPkkD3bdyJEjDcsNDQ1YvXp1WvsmEgksWLAAsVgMTU1NkGX7WENdIaOjGzgDdIUBEoOyvQz6/4lA/0o0+TDlAI9J0C44EG3xIf6pF+UXYzJwiSN0pYbQqGQwqIGAFOVwn+Bwn+Rwf8HhOs0hpeQbouGQ/knzMh18lAY+Ugeu0MBH6Ii6BZluTi0nCIIYOOTLp+P48eMoK7skPU93lEPXddx///3YuXMnlixZggULFmTcBjI6uoFxwNWhI1EiQXcwyH8tgXTEBcjA+XA5oArDym6OyHAdkSs06B6YEp4VDZzDcRZwfgE4jqtwn+RwnrcoJgHxwYBWxaEOBfQSADLgLYkl7Q4VQJRBjnOwKANXOODj4D6Al+pAOQf8Ft8ei1FmgiAIIn+UlZUZjI504JxjyZIl2Lp1K+bPn49nnnkmq2OT0dEDjAOOkI7QNyOQ95WAhQQfB48G58gw3HVBfBKrLNrXchbh8HwKuA9zeI4AssWcdrwCiI1giF4hITacIT4YgMzgcRsnsz0lQtAjWTOMBop+BARBEESa9JEjqa7rWLx4MTZv3oy5c+diy5YtkESfoDQho8MGBoBfGYdanQA7rQBOjiFDApC8GpjS5Qp+3mdNzAqpDSg9yOE5xOE6bhyy0x1AfAQQGS4hWs0QrWbQS1hRJrcjCIIYKPRFltmuBsd3v/td/O53v8vYj6MrZHR0gxTXIV30Fo/ELiolhgEAQ8zLACjGqQAxUJWQd0MVlCJh2ehxrwvTMaLywEq9IqpVxDpSowo6h6MVUM7qcJ7h8HzK4ToNdDV7Y5UM4bESwmMlREYwQGbQ4l3qjwJWQzniMUXEoFl2Ix3phF4Xz1v8HoXjQhhs4ZsmS7zH7an4JxeJJcxfk7BTPIZxu1iHSChuvP6iEskK276LGdukCW0Qk8uJofujTmObmGT+hWLCbaiL972wi3gMSRHCYAvnZJXJWBdVVB3G69HpvN2JEjHuLwnKEllQr8hCeUfE3Aax68VmSgnjCpNaJSioVQT1CotZ5NXRhPtUDGOeEPYRw57bhDDnohrG4ssmlsmYIgoxTpjRdR2LFi3Cli1bcNddd2Hr1q05GRwAGR0Dk4t+GSWf6Cg5wuE8zSGGpuAMiI5gCNZKCI2ToZbTMAZBEES/psDTK42NjdiyZQt8Ph/q6uqwdu1aU5k5c+ZgypQpaddJRkd/RgekIJI3is6Tfxmgu5GK9wEA0Dgc5wHlFIfrS46SwxyONqEqJxAfAsSHMsSqGcLjGBJOuvwEQRDFQqGnV44ePQoACAaDWLdunWWZMWPGkNFRtGgcztOA6xjgOQ44jwFSxHoEgsuA5tHAXYDSZs56qStAZAxDuFZCZBSDWo5U8rEUlCmdIAiC6IYtW7Zgy5Ytea2TjI5CoXO4v+RQOjigAU6Zg6mAHASUc4DjLIfS2jXSYdLY4IwDEgDGkgMdPGlgMA1QggAuptDWnUB8aHIkIzKaITKWQXeIfiB9EC2QIAiCyA/9KAx6tpDR0YvIER3eY1ry84UKOWa/j+4GYiOBxBiO+GggMRyADGhdHPJYgkMKA+iQIEUBtTz50cVYzf3gBiMIgiDyBBkdAxc5pkG+6P0dF1QBobhF9LauSg+No/J/Exh0IIauKTk0FxCrlMBlAE4OLgO6B4hXMsQGyYhXMqg+AIxdUg50Z6i4AF02qktEpYDdDcbVnnXWLC5KFcxlVKFMh6DakRyZea9rcWEOyOocRJWOsBxziF75ggpAVGWI3SYoMnjC7K0dUwSlBxOVAT33bUTYX7e5FhePYlwU+yYm1KEay8tR43bzlJzwcyBbKElscpCI18Y0hyzubzqCGVkQZSgh417ONmG78J0R1SuSamyUEu15GUhDvSLWKapVIsa5TClqbBSLWUTFE5UjYh4UVVCG2ahVxLwp4rUwlbdaZ8pz0gvqlF5WvPRJfpg80ReS2XxDRkdPqBoYB6SYBN2VnrrDc0rDsJ0xuC4kvzjRCgmhkQqCdQzRYRIgJetRSoQssjbJ2giCIAii2CGjozs4h5TQwHSOMf8GhGolBCbJiIy0Nj6UoI7KfXGUf5h8Y1HdDGenutFxpZL0xyil+N4EQRBEDtD0ysCGKxKQ0CGpHKUf6Sj9SIfqA9QpEuKTdWjVgPIZg+sdCeUfhlNDV23jFZy72pP26AhBEARB2ME4B7OaBstg/76GjI7uYAzcoYA7OE7O4Sg7qMF3SIcSBJRdMty7ZOhuDil6ybAIV8s4d7UDkREKWIwMDoIgCILoChkddrBkMK2z1RLO3szh/UxH5ZE4HB8xSFEG7uCIf1XHydE+xAcNkFz2BEEQRP+DplcGLlJMhaQl/TC06CW1SmAkoE7SwP6Ow/klEK9i4G4FieMOsC5e83LUONKhSsauFj08TEoS0c3YYuCEiXkvxGUbJ3BZFdUQgvJACB5mOh4ALigcdJeQM8aZ2V3O4jbqBwAsYZPvwyg2MlVil+jWrEywOm9hWVDESHY5SQSliF15q3aJZSSh7yThJpOjQn2i2EE8J9n+vMV7TFSziG3OJsmwWKcjJCx3CMoRk3pFvDZCLp6o8QBiHpV0kFRjHXLU2PlSVMy1IlychIXPl0kpIqpRhO2CKsOUN0WsT5AicZMUyapOO0lc3+daEdvIpL5vU74g9cplDHcxxMb0dSsIgiAIonggo4MgCIIgigGaXiEIgiAIohAMhOkVikhFEARBEERBoJEOgiAIgigGaHpl4CLFNEjqRY/ykNewLep0msqLahUlLCpJjMu6JnS9hTLEDpNSQFy2UUSI6gbTdkG9YioPgEvGY2hCQDQunKaYk05EzJMhKiys2iUOGeriXc2ENtkpm4V+tDxvk3pFUN3YXBtdEcoL52klJBCvj0llI/aLUIedekUc99Qt+snUd2IbLK5XJlipW8TzVMLGFc4OQTkiqlUENQoT1A1SzNhoMY+KdUNt6hRyrbCYcHFEtUpC2J7GMSHmWrHLvWKqT1S3ZP4bVMx5TIqRgTC9QkYHQRAEQRQDA2Ckg3w6CIIgCIIoCDTSQRAEQRBFQn+YIsmFgo90NDU1gTEGxhjeeecdyzKBQADLly/H6NGj4XK5MHr0aCxfvhyBQKDbel944QVMnToVXq8XFRUVuO222/Dee+/11mkQBEEQRGHhPPdPH1NQo+Ojjz7CqlWr4PV6uy0TCoUwffp0PPHEExg/fjyWLVuGv/mbv8ETTzyB6dOnIxQKmfZ5/PHHMW/ePJw+fRpLly7F3Xffjd27d2PatGlobm7uxTMiCIIgCCJdCja9omka7r33Xlx11VWoq6vD1q1bLcs1NTVh//79qK+vx4YNG1LrGxoa0NjYiKamJqxZsya1vqWlBQ0NDairq8PevXvh9/sBAD/5yU8wdepULF68GIcOHYKiZHaqLJYAk5M2mbPNaJvFJbN6xRk0en47gsbtkpAPQo8a67RSaWSKSQEh1mmjXjGrX4zLsoWDvejwrgtdIypJTOoVuzZZ9IupHWJ+D1FZIop4bBQYItaqnZ6XTalzTOoVm2Nkk3tFUF2Yrp+o6hCOKZ6DqLABzH1np9IxVyB2jKAsSkNA4QgbD6KEjCcqx43bmZAXxdTmuCZszyJXh5DPhcVtcquIahXV4iazPaZdbpae86YwKY3O7u1cKv0gV0sxMRDUKwUb6diwYQMOHDiA559/HrJsrVnknGPTpk3w+XxYtWqVYduKFStQUVGB5557DrzLl2vz5s1QVRUrV65MGRwAMHHiRNxzzz04cuQIduzY0TsnRRAEQRCFgufh08cUxOg4ePAg1qxZg8ceewwTJ07stlxLSwtOnjyJadOmmaZg3G43brrpJpw4cQKHDx9Ore+cPpk1a5apvtmzZwMA3nrrrTycBUEQBEEQudDr0yuqqmLhwoWYMGECHn300R7LtrS0AABqa2stt3eub2lpMfzf5/Ohqqqqx/LdEYvFEItdmvvoyVmVIAiCIPoKpqcxhWmzf1/T6yMdjz/+eGpaxeFw9Fi2vb0dAAzTJF0pKyszlOv8fyblRdavXw+/35/6jBw5ssc2EgRBEESfQNMrPXPgwAGsXbsWDz/8MK6++urePFTWrFixAu3t7anP8ePH+7pJBEEQBDEg6dXplXvvvRc1NTVYvXp1WuU7Ryy6G5nonProOrLh9/szKi/icrngcrnSah9BEARB9BUDQb3Sq0bHgQMHACSdQK24/vrrAQC///3vMWfOHFsfDCufj9raWuzZswenTp0y+XXY+Yj0SDwBSMmBIPd5caNZfeMUXEFEyazu6Hk5L3NtmSZ0E2V+mrhdrM/+jtUcQmI74Tw561mmJ5uSc5nLmNohLorjd8IxxURmdl9EplkUsKvTJCU11iHKUU2J0iyC+NhLZns+piiZFWWeItxhvla6LCa2E66XTRttsbg9RBmtEhESvEWFhG2iBFbtWVrKEkLnZyOZFXcRJbJxG4lsFsfkQoI3LtZhI0c1SWjTeSIVocR1QCWlyzXAVz8IDtarRseiRYss1+/cuRMtLS349re/jSFDhmDMmDEAksZBdXU1du/ejVAoZFCwRKNR7Ny5E9XV1Rg3blxq/fTp07Fnzx5s374d99xzj+E4r7/+eqoMQRAEQRQzNNJhw6ZNmyzXL1y4EC0tLVixYgW+/vWvp9YzxrB48WI0NjaisbHREBxs/fr1uHDhAn784x+DdXnLvO+++/CLX/wC69atw+23356aSvnggw/w29/+FjU1Nbj55pt76QwJgiAIgkiXfpfwrb6+Hq+++iqampqwb98+XHPNNThw4ABee+01TJkyBfX19YbydXV1WL16NR577DFMnjwZd955J0KhEF588UUkEgk8++yzGUcjJQiCIIh+B6W2zz9erxfNzc1YtmwZDh06hI0bN+LgwYNYtmwZmpubLfO2rFy5Elu3bsXQoUPx9NNP46WXXsINN9yA3bt3Y8aMGX1wFgRBEASRXzqnV3L59DWM837gWdKPCAQC8Pv9uHX0j6BISVXLiTkjDGWileb93OeMy+RImoQcSTuXyZE0LQaIIykTHUdjceOymHslG0dSwVmVx4VjCM6qdg6VzCo9heA4anZeFb98/cDRlGX4Lp1jm1WeQDP+gPb29lRsqHzT+Vz6+rf+CYrDWpiRDmoiinf++LNebasdNO/QHYku6pVWIXGSxS+jq91YxtkhPGREo0NMpiV8d9NyJBeqEPeREjY/MqLRIXz3TEZJGkaHLhod4nnaGB1mg8J8TNN5iUWEB6Mp4VuGv0kmgyCNOu0TvgkPb7Gv03lYiw98mzokMRGazUNIV8wdxUWjQ3yAC20QjUzTMcV+tLo/hGZIMSHBW8T4cLU1IsQ2i0ZJNmoH8T4VjQqt5zaJD/Osjmn3/ig+XMWHs8XDd0ApPwYCpF4hCIIgCKIQDAT1Sr/z6SAIgiAIYmBCIx0EQRAEUQwMAPUKGR0EQRAEUQTQ9ApBEARBEESa0EhHdyTUS+qVC4JMjJmlZa6A0fNbCQn7iIoKG/WKiJWFalJhiMIAtWc1g0nuaKeGsJBYmlQcsrFR4nmK5UVExYwVLCGoMEQnfvEYzKbvbRRzTLMokGGdYt+K5U19m8UbidhOk2xXFaSkNn3NHBYSSkm84D3fQyb1io33vLV6RZAXxwS1StxGvSJeP7ENorrFSrEhnreIqD5RxTYIvwdi+TTuMRM27bZVnpjUKhbXeyDSH2S92aLz7NRVXffvY8joIAiCIIhigHw6CIIgCIIoBAw5+nTkrSXZQz4dBEEQBEEUBBrpIAiCIIhigCKSEgRBEARRCAaCZJaMju7Q9JSXs6NDSJxkMTGmhAX1SljYR1Sv2HnDi1hZqDZ1mHJKiNvFzSY1i6CGsFSvCG0Qz1POcAYvDe9q8bxERYSpTWKKCcm4wm5/y360qVNE7EuxX+zyoFhil0NEbIMpx0jP5SWr+mQ7FYfQJjEnjV1uFqtuFMsI6hRRvWJWjtioFVQxM6IFdt9X8frZqVPE5XQSvon3WJ7fWgdMnhW7HDNEn0JGB0EQBEEUA6ReIQiCIAiiEDDObWPd2O3f19C4E0EQBEEQBYFGOgiCIAiiGNBhG0HZdv8+howOgiAIgigCBsL0Chkd3cA1FVxPzj7J4YRhm9OivBQ1eqtLsYRQQMhJYpdXQcDqZhEVMaZ9bNQMJvWDKf+HTY4KAMykFBHOU2yjWN50DOEAFhOApvMSz0PcIcO+N6VusVIWiLlXxPM05V4R1CuKcGJi+Wx+HETFhJ0Kx07VoVi0IUP1inj9TPeYjdLIqowpt0pCVK8Iy3aqjHSUI5m+IYrXW7w24jHTud5inaY6el4W1SksHQWdTR1FnceESIutW7fi7bffxv/+7//i/fffRzwex+bNm7Fw4cKs6iOjgyAIgiCKgT5Qrzz22GP4/PPPMXjwYAwfPhyff/55Dg0gR1KCIAiCKA46I5Lm8smQTZs24ejRozh79iyWLl2a8ynQSAdBEARBFAF9EZH01ltvzf6AFtBIB0EQBEEQBYFGOgiCIAiiGMhTwrdAIGBY7XK54HK5cmlZ2pDR0R26nkpOIkUEJYqVmMEuH4ToxW+nXhG3WylHbPJ9mPaxcTQ3KSbEZSu1g0l90LOaxTS2ZqPasFKaWKpJDHUK7Rbzv4hqCLvcK9nkxRAw1aH3rF5JB9P1slOj2CkmRHWD1Y+b2G4RsQ0297Hpe2D1vRDvKTG3iqhWyTSvSTrXN1NMKo+el01KFAtM3/d+IH8kCgu79FjKen8AGDlypGF9Q0MDVq9enX3FGUBGB0EQBEFcRhw/fhxlZWWp5UKNcgBkdBAEQRBEcZCn6ZWysjKD0VFIyOggCIIgiGJgAGSZJfUKQRAEQRAFgUY6uoFrGjhLOqxJglOoZDG8ZQrNLDq7peMw12ODLExUOydO0aHObljOxrHQMuQxEx1FBSdMO2dXmzZYOtxm6kgqOD+a6rQLo57GcGamTr1MlzM+hi3iPWdywMwwPLgVds7GdnWK95B4/1ghOgLbOY6K2zO9762w+76KjqE2Yc/NIcztv992zqamEOU2mMOiU0jz/g7lXiEIgiAIojDkyacjEzZt2oRdu3YBAN5///3UuubmZgDAnDlzMGfOnLTrI6ODIAiCIAhLdu3ahd/85jeGdbt378bu3bsBAGPGjCGjgyAIgiAGHBxZxfQx7J8hW7ZswZYtW3I4qBEyOgiCIAiiCBgIPh29rl45ceIEnnzyScyaNQujRo2C0+lEVVUV7rjjDrz77ruW+wQCASxfvhyjR4+Gy+XC6NGjsXz5clPo1q688MILmDp1KrxeLyoqKnDbbbfhvffe663TIgiCIIjCwpFjltm+PoECjHQ89dRT2LBhA2pqajBz5kwMHToULS0t2LZtG7Zt24YXX3wRd999d6p8KBTC9OnTsX//fsycORNz587FgQMH8MQTT+DNN9/Erl274PV6Dcd4/PHHsXLlSowaNQpLly5FMBjESy+9hGnTpuH111/HN77xjcwbzrsIohNGb3hmFW5a9CwXPehN6pVMVR1pKEfs9hGtXBsVh20oZ8Ack1dUTOSq0pFkcxldM68zbBfbnaNtnc7bgVU7u5Jpm7NBvOdyVTOJ9QH2fSkeQ2yD6TxtygPm+1hU6dgpQWzOU1SaMMvvVYbXJ8M2pFWHSD7uGYIoML1udEydOhU7d+7EjTfeaFj/9ttv45ZbbsGDDz6I22+/PRWGtampCfv370d9fT02bNiQKt/Q0IDGxkY0NTVhzZo1qfUtLS1oaGhAXV0d9u7dC7/fDwD4yU9+gqlTp2Lx4sU4dOgQFIVmkgiCIIgipg/UK/mm16dXvvOd75gMDgC48cYbMWPGDLS2tqZkOJxzbNq0CT6fD6tWrTKUX7FiBSoqKvDcc8+Bd+m4zZs3Q1VVrFy5MmVwAMDEiRNxzz334MiRI9ixY0cvnR1BEARBFAg9D58+pk8jkjocDgBIjUK0tLTg5MmTmDZtmmkKxe1246abbsKJEydw+PDh1PpOrfCsWbNM9c+ePRsA8NZbb/VG8wmCIAiCyIA+m3M4duwY3njjDVRVVWHSpEkAkkYHANTW1lru07m+paXF8H+fz4eqqqoey3dHLBZDLBZLLffkrEoQBEEQfcVAUK/0idGRSCSwYMECxGIxNDU1QZaTTnjt7e0AYJgm6UpnVrzOcp3/Hzp0aNrlRdavX2/wEbHEyqFOJB2nSwM2YdJF0nHitNsnU0dSk2OpxfHE8N96vh1JLc7bLgy6XZ125223v1UdtuG/xe15CEkuYnKoFNuo97ycDXb3jF0bTNfC4n4x9bVQhxhyXHBm5VZO2Ib6hBDm4ncTsHZw7bHODMOeW13/TI8pkGlY9AGL3fUvJsinI3N0Xcf999+PnTt3YsmSJViwYEGhm2BgxYoVaG9vT32OHz/ep+0hCIIgiIFKQUc6OOdYsmQJtm7divnz5+OZZ54xbO8c4ehuZKJz6qPrSIjf78+ovIjL5UopZwiCIAii30IjHemj6zoWLVqE559/HnPnzsWWLVsgCUPzdj4YVj4ftbW1CAaDOHXqVFrlCYIgCKIoySkwWI4GS54oiNGh6zoWL16MzZs347vf/S5+97vfpfw4ulJbW4vq6mrs3r0boVDIsC0ajWLnzp2orq7GuHHjUuunT58OANi+fbupvtdff91QhiAIgiCIvqPXjY7OEY7NmzfjrrvuwtatWy0NDgBgjGHx4sUIBoNobGw0bFu/fj0uXLiAxYsXg3VxLLvvvvugKArWrVtnmGb54IMP8Nvf/hY1NTW4+eabs2g4v/RRNfuPJnxUteePrhs/4v7idqs6xH3s6rBrY6b1WdWZzj49ffJxzEz7IdM2ZXNepjqFT671pXNevXHe4ltUrsfIQ19ybvwYvstWn3TeDu3qED+Z/L50V9623XrPnzzAdW74EH2MnodPH9PrPh2NjY3YsmULfD4f6urqsHbtWlOZOXPmYMqUKQCA+vp6vPrqq2hqasK+fftwzTXX4MCBA3jttdcwZcoU1NfXG/atq6vD6tWr8dhjj2Hy5Mm48847EQqF8OKLLyKRSODZZ5+laKQEQRBE0UOS2TQ4evQoACAYDGLdunWWZcaMGZMyOrxeL5qbm7FmzRq8/PLLaG5uRlVVFZYtW4aGhgZT0DAAWLlyJcaMGYMnn3wSTz/9NJxOJ2644QY0Njbiuuuu661TIwiCIIjCMQAcSRnn/aAV/YhAIAC/34+bXXdDYU4AgFRZYb9jOjEtuiLGtxARYxOIsQjSqUMk07gM6SStMiWyE5ZzbaPVVJxVX/REpm0Qseo3sc5M46yI++fjayj2i3gMcbvdMa36rZup0bTbkM33wu67ICSAM8XlyDiGigWZxpsR2igmlTMlxssG4TzFY2Q6HcIs4oLY1jGQYmBkicoTaMYf0N7enooNlW86n0u31i6DImevtlS1GN5oeaJX22oHzTsQBEEQRDGgc4Dl8ILSD/xyyOjoDs6R8rrJ9A0xnTJ22+2iMKbbjlzKi1jesOIbfIbRPk3VpeOEJ/RFppFVs4n+KiLeE7nWmc4olN2IjXgMu/vW7gfI6sfNbpQp0zakM6Injq4IfWU7spFp31v1c67RfG1/DyyuP+vT1FhEf2QATK/QXU0QBEEQREGgkQ6CIAiCKApyDfDV9yMdZHQQBEEQRDEwAKZXyOhIB9M8dT48tjP0hcjGnyJDp6FMs3FaHZPp4oxdrm20aJNpHzsVhlg8wy9ePjKA2vk6pIPdPuJ9KbTRpKCwgVkVlzP0KxER+zKdCV6x3WIddj4c6fhs9FTeap9C/HiL30fy8SAGAGR0EARBEEQxoHPkNEVC6hWCIAiCINIi1xD3/SCuCo3XEQRBEARREGikIx2E+dtM58YB2PsAmMI+GO1BW38LizpMmObTM/SvsJrHFprFJZt2Zth1Zh+RNPvCpo5MsDqeqU67Q2Tjy5AhYjttz9vmeltdS8Zt7mO7OjNtI2DqK9P1yDQasLg9m9gwNnCxvMnvJIs3zlzfUslHpPghR1KCIAiCIAoC+XQQBEEQBFEQBsBIB42vEQRBEARREGikoxu4zsE7c09kmsvBCi2z/B88U+eHdDDNfdtsF0knfkGenaMtfUQyjT9i52dih8XxxDrtfBOy8mXIFKGdpvPO+D62uEcz9Nmw2z+da5NzXxUkpkbh3yAzzSJb6PqIXoAjx5GOvLUka8joIAiCIIhigKZXCIIgCIIg0oNGOtLAnDq7F9KQi9ilzs4H+Ui3nmmI6UzPy6oJmaYZz3XKJx9S4SymFXIm1xTvFlOAmZ6nrVQ8nSF9IbO9OQx6FhLYrsXTuM+Z3X1tqjTTNpjLs0xD7ReCfhBc6rJG15HTD1qG0u/egIwOgiAIgigGaHqFIAiCIAgiPWikIx2yUa/kOoxlUoX0/bCY5XmLQ/B20y2ZDvGnM6xtV6fddEym9VmVsbs8pjptosFmM7SecfZcm0Zb1pdhu+y+O3bXAplHoDXtL5xnxlMlBNFfGAAjHWR0EARBEEQxMAAikpLJTxAEQRBEQaCRjiyw8nY3Ddlmqk4RSccjP42h6YzalA12w+W9MS2UaZ2ZXpt0jmdXp+31tZtm6oVrldV0ilhHFkkBcy5vo07qBbWK3T7i9922TmGKKJ1AXGKZfqlmIQoK53pO0425TlXmAzI6CIIgCKIY4Dy3FxLy6SAIgiAIIi14jj4dZHT0Y3iXICxpXKiMPeRznX5Jp448k9W0Uq5KkXxMz9jVkY1SKFOVjlheFiJeZaHqyLhNItn0vdjuTMlGnZRprp1M75l89H0/IOPcKeJQOyMXP6L3IaODIAiCIIoBXQdYDi9i5NNRpKTh1JlzbIBeGMXI2Rkuizr7xHk1Y6fOLBwsc30bzjS2SDbkGB7cknzHWclq5KOXfziz+H6b6AVHYMoCSwyE6RUaTyMIgiAIoiDQSAdBEARBFAFc18FzmF4hyWyxkM5wrs2Qvt1wrN30SzZTH3b0Rp19Qj8YMuyXYeoznAIyTZXl6jQKZN4v6cREEbCPkdEP7g+CyAc0vUIQBEEQBJEeNNLRTyiKUYdecKDNdQQoLfrCmdWufKYy3l6gT+65ASJPJYg+QecAK+6RDjI6ssHKi5xCFFvSFw+2fGcVTSs+Sb7JR7/l+gPTD36gsqI/KKYIojfgHPYpre3271sGzPTKX/7yF9x2222oqKiA1+vF1KlT8cILL/R1swiCIAiiqMnn83VAjHQ0Nzdj9uzZcDqd+N73vge/349XXnkF8+bNw9GjR/HTn/609xshjn7YmXP5SNaWax35eFvrg+HyfI9k5IUimDbIy6hTpk6bmU479UUkXtN3t/9dO0v6gRKBKCxc5+A5TK/wLL47+X6+Mp5NK/oRqqriK1/5Cr744gvs2bMHX/3qVwEAHR0duP766/Hxxx/jww8/RG1tbVr1BQIB+P1+zJC/A4U5AACSx2MowxOqfUWZ/nDlGi68v5Dnh62VQZHpw7NfTq/0hlFic4/kpd/64j61MY5N55VxFuEsjA47g12sM4sss7ZkWqedkZJOGHQydEyoPIFm/AHt7e0oKyvrlWNYPZeyQeUJvKm9knZb8/18BQbA9MqOHTtw5MgRfP/73091CACUlpbiZz/7GVRVxebNm/uwhQRBEASRO1znOX8yoTeer0U/vdLc3AwAmDVrlmlb57q33nqrkE3KjiIYnk+LXM/D7i22n9DrYe6zuP79ctqpGEnHUTzD0ZSsRiEoARvRx/TG87XojY6WlhYAsBzeqaiowODBg1NlrIjFYojFYqnl9vZ2AMlhqE4kbgySxPUETJiGW3PNzZHb7r1CVqqdXIfj82B8ablXYQfjmUmD7Q2CzH0bxGiDYptsoxEK9TFmFRwst+uZnWFkN72S4wVOx4DI9Ptsc23M5a2222UJFqZXbPP52BnwNL2SDSqSz4NCeCqoPJbTNehsayAQMKx3uVxwuVym8rk+X60oeqOj00jw+/2W28vKyvDFF190u//69euxZs0a0/q39f97aSGYWxsJgiD6Pf3xRaeI6Ojo6PY5lCtOpxNVVVXYdepPOdfl8/kwcuRIw7qGhgasXr3aVDbX56sVRW905MqKFSuwfPny1LKu62htbUVlZSVYsU5xFAGBQAAjR47E8ePHe835irgE9Xdhof4uLH3Z35xzdHR0oLq6uteO4Xa78dlnnyEej+dcF+fc9GyzGuXoLYre6Oi0wDotMpFOr9/usBpWKi8vz1v7iJ4pKyujH+UCQv1dWKi/C0tf9XdvjXB0xe12w+129/pxupLr89WKovdU6pxrsppXunDhAs6dO5eRnIcgCIIgiN55vha90TF9+nQAwPbt203bOtd1liEIgiAIIj164/la9EbHLbfcgrFjx+KFF17A/v37U+s7OjrwT//0T1AUBQsXLuyz9hHWuFwuNDQ0FHQu8XKG+ruwUH8XFurv3qE3nq9FH5EUAN58803Mnj0bLpcLc+fORVlZGV555RV89tlnWLt2LVauXNnXTSQIgiCIoiPfz9cBYXQAwN69e9HQ0IA9e/YgHo9j4sSJ+Pu//3vMmzevr5tGEARBEEVLPp+vA8boIAiCIAiif1P0Ph0EQRAEQRQHZHQQBEEQBFEQyOggcOLECTz55JOYNWsWRo0alQq5e8cdd+Ddd9+13CcQCGD58uUYPXo0XC4XRo8ejeXLl5ti+nflhRdewNSpU+H1elFRUYHbbrsN7733XrflW1pacPfdd2PIkCHweDyYPHky/vVf/xV6N0ngYrEYGhsbUVdXB7fbjeHDh2Px4sU4depUZh3SBzQ1NYExBsYY3nnnHcsy1Oe58/vf/x4zZ85EZWUlPB4PrrzySsydOxfHjx83lKO+zg3OOV555RXMmDEDw4cPR0lJCcaPH48f/OAH+PTTT03lqb8vIzhx2fPII49wALympobff//9/NFHH+V33HEHl2WZS5LE/+M//sNQPhgM8ilTpnAAfObMmfyRRx7h3/zmNzkAPmXKFB4MBk3HWLduHQfAR40axZcvX84feOABXlZWxp1OJ3/zzTdN5T/44APu9/u5w+Hg8+bN4/X19XzSpEkcAF+yZImpvKZpfPbs2RwA/9rXvsYfeeQRfuedd3JJkvioUaP4l19+mbf+yjcffvghd7lc3Ov1cgB8z549pjLU57mh6zp/4IEHUvf5D3/4Q/7II4/wBQsW8FGjRvG33347VZb6OneWL1/OAfDhw4fzpUuX8vr6ej579mzOGOOlpaX8/fffT5Wl/r68IKOD4P/1X//Fd+7caVq/c+dO7nA4+KBBg3g0Gk2tX7VqFQfA6+vrDeU7169atcqw/pNPPuGKovC6ujre1taWWn/w4EFeUlLCa2pqeCKRMOxz0003cQD8j3/8Y2pdPB7nt9xyCwfAd+zYYSj//PPPcwD8e9/7Htd13bT+nnvuyaBHCoeqqvy6667jU6dO5fPnz+/W6KA+z41f/epXHAB/6KGHuKqqpu1d+4L6Oje+/PJLLkkSHzNmDG9vbzdse+KJJzgAft9996XWUX9fXpDRQfTIrFmzOAD+l7/8hXOefGOsrq7mPp/P9AYSiUR4RUUFHzFihOGLumLFCg6A/+Y3vzHVv3TpUg6Av/7666l1H3/8MQfAZ8yYYSr/zjvvcAB87ty5hvXXX389B8CPHj1q2mfChAnc5XLxQCCQ2ckXgHXr1nGn08kPHjzI7733Xkujg/o8N8LhMB80aBAfO3as6WEkQn2dO3v27OEA+Lx580zbPvnkEw6Af+tb3+KcU39fjpBPB9EjDocDAKAoydyALS0tOHnyJKZNmwav12so63a7cdNNN+HEiRM4fPhwan1zczMAYNasWab6Z8+eDQB466230io/depUlJeXG8pHo1G8++67GD9+PEaPHm3aZ9asWYjFYt36SvQVBw8exJo1a/DYY49h4sSJ3ZajPs+NP//5z2htbcWcOXOgaRpeeeUV/PznP8czzzxj6DOA+jof1NbWwul0Yvfu3ejo6DBs+9OfkqnZb775ZgDU35cjZHQQ3XLs2DG88cYbqKqqwqRJkwBcSvzTXZIfqwRBLS0t8Pl8qKqqSrt8d8dgjGHcuHE4efIkwuEwAODIkSPQdT2jNvU1qqpi4cKFmDBhAh599NEey1Kf50anc6GiKLjqqqtwxx13YMWKFXjwwQcxfvx4PPzww6my1Ne5U1lZiXXr1uHo0aOYMGECfvjDH+KRRx7Bbbfdhn/8x3/EAw88gB//+McAqL8vR8joICxJJBJYsGABYrEYmpqaIMsygEspjrtLZ9yZVrprKuT29vaMy2dyjGza1Nc8/vjjOHDgAJ5//vnUaFJ3UJ/nxpkzZwAAGzduRFlZGfbu3YuOjg7s3LkTdXV12LhxI55++mkA1Nf54uGHH8a///u/o729HU8//TSamprw2muv4brrrsP8+fNT9zz19+UHGR2ECV3Xcf/992Pnzp1YsmQJFixY0NdNGlAcOHAAa9euxcMPP4yrr766r5sz4OmURDqdTmzbtg3XXXcdfD4fbrzxRrz88suQJAkbN27s41YOLNauXYuFCxdixYoVOH78OILBIHbt2gVVVTFjxgy88sorfd1Eoo8go4MwwDnHkiVLsHXrVsyfPx/PPPOMYXun9d+dld+pq+/6luD3+zMun84xOt84smlTX3LvvfeipqYGq1evTqs89XludLbh2muvRXV1tWHbxIkTMXbsWBw5cgRtbW3U13lgx44d+NnPfoYf/ehH+OlPf4orrrgCXq8X06ZNw3//93/D4/Fg2bJlAOjevhwho4NIoes6Fi1ahOeffx5z587Fli1bIEnGW8RuPtNq/rS2thbBYNAyqE535bs7Bucchw8fRnV1dcrxrKamBpIkZdSmvuTAgQM4dOgQ3G53KiAYYwy/+c1vAADXX389GGPYtm0bAOrzXBk/fjwAoLy83HJ75/pIJEJ9nQf++Mc/AgBmzJhh2jZkyBBMmjQJx44dw7lz56i/L0f6VDtD9Bs0TeP33XcfB8C/+93vWsYy4Dw9iVt1dbVB4vboo4/2usTt61//uq3ETYwZ0FcsWrTI8lNbW8sB8G9/+9t80aJFfN++fZxz6vNcOXz4MAfAx40bZ9oWj8d5eXk593q9PJFIUF/ngR/96EccAH/uuecst48bN44D4IFAgPr7MoSMDoJrmsYXLlzIAfC77rrLNpZBpsF8Pv7447wF87n11lsHbDCf7uJ0cE59niud8WaeffZZw/rGxkYOgM+fPz+1jvo6N1588UUOgE+cONHQH5xzvmXLFg6AX3PNNal11N+XF2R0ELyhoYED4D6fj69cuZI3NDSYPp1v3ZybwxY/+uij/O/+7u84eghbvHbtWo4uYYt/8IMf8LKyMu5wOExfeM4vhS12Op18/vz5vL6+nk+ePJkD4IsXLzaVV1XVFLb4rrvu4pIk8ZEjRxZF2OKejA7q89w4fPgwHzp0aCow1T/8wz/wm2++mQPgo0ePNrSV+jo3VFXl3/jGNzgAPmTIEL5o0SL+8MMP85kzZ3IA3OVy9Rh2nvp7YENGB5F62PX02bx5s2GftrY2vmzZMj5y5EjucDj4yJEj+bJly0xvNl3ZunUrv/baa7nH4+F+v59/85vf5Hv37u22/Mcff8zvvPNOXllZyV0uF584cSL/l3/5F65pmmX5aDTK16xZw8eNG8edTicfNmwYv//++/nJkyez6pdC05PRwTn1ea4cO3aML1y4kFdVVaX676GHHuKnT582laW+zo1oNMo3bNjAr776al5SUsIVReEjRozg3//+9w15Vzqh/r58YJxznq7/B0EQBEEQRLaQeoUgCIIgiIJARgdBEARBEAWBjA6CIAiCIAoCGR0EQRAEQRQEMjoIgiAIgigIZHQQBEEQBFEQyOggCIIgCKIgkNFBEARBEERBIKODIAiCIIiCQEYHQRAEQRAFgYwOgiAIgiAKAhkdBEEQBEEUBDI6CIIgCIIoCP8f7hZwt2f84aMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Look at output from DHARMA for DYCOMS precip at cloud base (because we need a q, not a rate)\n",
    "filenm = '/data/gelsaess/LES/LES_DYCOMS-II-RF02_intSfc_profiles.nc'\n",
    "nc = Dataset(filenm,'r')\n",
    "qr = nc.variables['qr'][:,:]\n",
    "ql = nc.variables['ql'][:,:]\n",
    "time = nc.variables['time'][:]\n",
    "zf   = nc.variables['zf'][:]\n",
    "nc.close()\n",
    "\n",
    "clp = plt.pcolormesh(time,zf,qr.T)\n",
    "plt.colorbar(clp)\n",
    "plt.contour(time,zf,ql.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "7b4375e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fb37137d4e0>"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Look at output from DHARMA for DYCOMS precip at cloud base (because we need a q, not a rate)\n",
    "filenm = '/data/gelsaess/LES/LES_DYCOMS-II-RF02_profiles.nc'\n",
    "nc = Dataset(filenm,'r')\n",
    "qr = nc.variables['qr'][:,:]\n",
    "ql = nc.variables['ql'][:,:]\n",
    "time = nc.variables['time'][:]\n",
    "zf   = nc.variables['zf'][:]\n",
    "nc.close()\n",
    "\n",
    "clp = plt.pcolormesh(time,zf,qr.T)\n",
    "plt.colorbar(clp)\n",
    "plt.contour(time,zf,ql.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "3daf34b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fb37026dd80>"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#..Look at output from DHARMA for DYCOMS precip at cloud base (because we need a q, not a rate)\n",
    "filenm = '/data/gelsaess/LES/LES_DYCOMS-II-RF02_profiles.nc'\n",
    "nc = Dataset(filenm,'r')\n",
    "thetal = nc.variables['thetal'][:,:]\n",
    "ql = nc.variables['ql'][:,:]\n",
    "time = nc.variables['time'][:]\n",
    "zf   = nc.variables['zf'][:]\n",
    "nc.close()\n",
    "\n",
    "clp = plt.pcolormesh(time,zf,thetal.T)\n",
    "plt.colorbar(clp)\n",
    "plt.contour(time,zf,ql.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b895cf12",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:pymc3]",
   "language": "python",
   "name": "conda-env-pymc3-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}