{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "usage: ipykernel_launcher.py [-h] [-c CONFIG_FILE]\n",
      "ipykernel_launcher.py: error: unrecognized arguments: -f /home/francisco.jimenez/.local/share/jupyter/runtime/kernel-976255c1-9f4c-471c-966e-ca0fc33729f6.json\n"
     ]
    }
   ],
   "source": [
    "#Import relevant modules, import data and all that\n",
    "import numpy as np\n",
    "from scipy import interpolate\n",
    "import corner\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "from matplotlib import rc\n",
    "from configparser import ConfigParser\n",
    "import codecs\n",
    "#plt.rcParams['font.family'] = 'DejaVu Sans'\n",
    "#rc('text', usetex=True)\n",
    "plt.rcParams.update({'font.size': 16.5})\n",
    "\n",
    "import ptemcee\n",
    "#from pycbc.pool import choose_pool\n",
    "from multiprocessing import Pool\n",
    "import h5py\n",
    "import inspect\n",
    "import pandas as pd\n",
    "import json\n",
    "import qnm\n",
    "import random\n",
    "import dynesty\n",
    "from dynesty import plotting as dyplot\n",
    "import os\n",
    "import csv\n",
    "import argparse\n",
    "import scipy.optimize as optimization\n",
    "from scipy.optimize import minimize\n",
    "from scipy.interpolate import interp1d\n",
    "from pycbc.conversions import get_lm_f0tau_allmodes\n",
    "from scipy.optimize import fsolve\n",
    "from scipy.optimize import least_squares\n",
    "\n",
    "\n",
    "\n",
    "try:\n",
    "    parser = argparse.ArgumentParser(description=\"Simple argument parser\")\n",
    "    parser.add_argument(\"-c\", action=\"store\", dest=\"config_file\")\n",
    "    result = parser.parse_args()\n",
    "    config_file=result.config_file\n",
    "    parser = ConfigParser()\n",
    "    parser.read(config_file)\n",
    "    parser.sections()\n",
    "except SystemExit: \n",
    "    parser = ConfigParser()\n",
    "    parser.read('config_fixed_n1_m_af.ini')\n",
    "    parser.sections()\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "# path\n",
    "rootpath=parser.get('nr-paths','rootpath')\n",
    "\n",
    "simulation_path_1 = parser.get('nr-paths','simulation_path_1')\n",
    "simulation_path_2 = parser.get('nr-paths','simulation_path_2')\n",
    "metadata_file = parser.get('nr-paths','metadata_json')\n",
    "simulation_number = parser.get('nr-paths','simulation_number')\n",
    "simulation_number = np.int(simulation_number)\n",
    "\n",
    "output_folder = parser.get('output-folder','output-folder')\n",
    "overwrite = parser.get('setup','overwrite')\n",
    "downfactor = np.int(parser.get('setup','plot_down_factor'))\n",
    "sampler = parser.get('setup','sampler')\n",
    "nr_code = parser.get('setup','nr_code')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "if parser.has_option('setup','nb_cores'):\n",
    "    nbcores = np.int(parser.get('setup','nb_cores'))\n",
    "else:\n",
    "    nbcores = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(output_folder):\n",
    "    os.mkdir(output_folder)\n",
    "    print(\"Directory \" , output_folder ,  \" Created \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [],
   "source": [
    "# time config\n",
    "tshift=parser.get('time-setup','tshift')\n",
    "tshift = np.float(tshift)\n",
    "\n",
    "tend=parser.get('time-setup','tend')\n",
    "tend = np.float(tend)\n",
    "\n",
    "t_align=parser.get('time-setup','t_align')\n",
    "t_align = np.float(t_align)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [],
   "source": [
    "# n-tones & nlive\n",
    "\n",
    "nmax=parser.get('n-tones','nmax')\n",
    "nmax = np.int(nmax)\n",
    "\n",
    "npoints=parser.get('n-live-points','npoints')\n",
    "npoints = np.int(npoints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model: w-tau-fixed-m-af\n",
      "nmax: 1\n",
      "tshift: 0.0\n",
      "error: False\n",
      "error value: False\n"
     ]
    }
   ],
   "source": [
    "# model\n",
    "model=parser.get('rd-model','model')\n",
    "error_str = eval(parser.get('rd-model','error_str'))\n",
    "if error_str:\n",
    "    error_val=np.float(parser.get('rd-model','error_val'))\n",
    "    if error_val==0:\n",
    "        error_type=''\n",
    "    else:\n",
    "        error_type=error_val\n",
    "else:\n",
    "    error_type='False'\n",
    "    error_val =0\n",
    "\n",
    "if model == 'w-q':\n",
    "    tau_var_str='q'\n",
    "else:\n",
    "    tau_var_str='tau'\n",
    "    \n",
    "\n",
    "print('model:',model)\n",
    "print('nmax:',nmax)\n",
    "print('tshift:',tshift)\n",
    "print('error:', error_str)\n",
    "print('error value:',error_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Directory  /work/francisco.jimenez/sio/git/rdstackingproject/results_new/0305/w-tau-fixed-m-af-nmax1_False  Created \n"
     ]
    }
   ],
   "source": [
    "if error_str:\n",
    "    output_folder_1=output_folder+'/'+model+'-nmax'+str(nmax)+'_'+str(error_str)+'_'+str(error_type)\n",
    "else:\n",
    "    output_folder_1=output_folder+'/'+model+'-nmax'+str(nmax)+'_'+str(error_str)\n",
    "\n",
    "if not os.path.exists(output_folder_1):\n",
    "    os.mkdir(output_folder_1)\n",
    "    print(\"Directory \" , output_folder_1 ,  \" Created \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [],
   "source": [
    "corner_plot=output_folder_1+'/Dynesty_'+str(simulation_number)+'_'+model+'_nmax='+str(nmax)+'_tshift='+str(tshift)+'_'+str(npoints)+'corner_plot.png'\n",
    "corner_plot_extra=output_folder_1+'/Dynesty_'+str(simulation_number)+'_'+model+'_nmax='+str(nmax)+'_tshift='+str(tshift)+'_'+str(npoints)+'corner_plot_extra.png'\n",
    "diagnosis_plot=output_folder_1+'/Dynesty_diagnosis'+str(simulation_number)+'_'+model+'_nmax='+str(nmax)+'_tshift='+str(tshift)+'_'+str(npoints)+'.png'\n",
    "fit_plot=output_folder_1+'/Fit_results_'+str(simulation_number)+'tshift_'+str(tshift)+'_'+model+'_nmax_'+str(nmax)+'.png'\n",
    "samples_file=output_folder_1+'/posterior_samples-'+str(simulation_number)+'tshift_'+str(tshift)+'_'+model+'_nmax_'+str(nmax)+'.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [],
   "source": [
    "sumary_data = output_folder_1+'/summary'+str(simulation_number)+'_'+model+'_nmax_'+str(nmax)+'.csv'\n",
    "best_data=output_folder_1+'/best_values_'+str(simulation_number)+'_'+model+'_nmax_'+str(nmax)+'.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [],
   "source": [
    "vary_fund = True\n",
    "\n",
    "#sampler parameters\n",
    "dim = nmax+1\n",
    "ndim = 4*dim\n",
    "numbins = 32 #corner plot parameter - how many bins you want\n",
    "datacolor = '#105670' #'#4fa3a7'\n",
    "pkcolor = '#f2c977' #'#ffb45f'\n",
    "mediancolor = '#f7695c' #'#9b2814'\n",
    "\n",
    "#Import data and necessary functions\n",
    "#TimeOfMaximum\n",
    "def FindTmaximum(y):\n",
    "    #Determines the maximum absolute value of the complex waveform\n",
    "    absval = np.sqrt(y[:,1]*y[:,1]+y[:,2]*y[:,2])\n",
    "    vmax=np.max(absval)\n",
    "    index = np.argmax(absval == vmax)\n",
    "    timemax=y[index,0]\n",
    "    return timemax\n",
    "\n",
    "\n",
    "def EasyMatchT(t,h1,h2,tmin,tmax):\n",
    "    #Computes the match for complex waveforms\n",
    "    pos = np.argmax(t >= (tmin));\n",
    "    \n",
    "    h1red=h1[pos:];\n",
    "    h2red=h2[pos:];\n",
    "    \n",
    "    norm1=np.sum(np.abs(h1red)**2)\n",
    "    norm2=np.sum(np.abs(h2red)**2)\n",
    "\n",
    "    myTable=h1red*np.conjugate(h2red)\n",
    "    res=((np.sum(myTable)/np.sqrt(norm1*norm2))).real\n",
    "    \n",
    "    return res\n",
    "\n",
    "def EasySNRT(t,h1,h2,tmin,tmax):\n",
    "    #Computes the match for complex waveforms\n",
    "    pos = np.argmax(t >= (tmin));\n",
    "    \n",
    "    h1red=h1[pos:];\n",
    "    h2red=h2[pos:];\n",
    "\n",
    "    myTable=h1red*np.conjugate(h2red)\n",
    "    res=2*np.sqrt((np.sum(myTable)).real)\n",
    "    \n",
    "    return res\n",
    "\n",
    "def wRD_to_f_Phys(f,M):\n",
    "    c=2.99792458*10**8;G=6.67259*10**(-11);MS=1.9885*10**30;\n",
    "    return (c**3/(M*MS*G*2*np.pi))*f\n",
    "\n",
    "def tauRD_to_t_Phys(tau,M):\n",
    "    c=2.99792458*10**8;G=6.67259*10**(-11);MS=1.9885*10**30;\n",
    "    return ((M*MS*G)/c**3)*tau\n",
    "\n",
    "\n",
    "def twopoint_autocovariance(t,n):\n",
    "    #Computes the match for complex waveforms\n",
    "    dt=t[1]-t[0]\n",
    "    res = np.zeros(len(n))\n",
    "    taus = np.zeros(len(n))\n",
    "    for tau in range(0,int(len(n)/2)):\n",
    "        ntau=np.roll(n, tau)\n",
    "        taus[tau] = t[tau]\n",
    "        res[tau]=np.sum(n*ntau).real\n",
    "    return (taus[:int(len(n)/2)],res[:int(len(n)/2)])\n",
    "\n",
    "def QNM_spectrum(mf,af,l,m):\n",
    "    \n",
    "    omegas_new = [qnm.modes_cache(s=-2,l=l,m=m,n=i)(a=af)[0] for i in range (0,dim)]\n",
    "    w_m_a = (np.real(omegas_new))/mf\n",
    "    tau_m_a=-1/(np.imag(omegas_new))*mf\n",
    "    \n",
    "    return (w_m_a, tau_m_a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [],
   "source": [
    "gw = {}\n",
    "gw[simulation_number] = h5py.File(simulation_path_1, 'r')\n",
    "if nr_code=='SXS':\n",
    "    gw_sxs_bbh_0305 = gw[simulation_number][\"Extrapolated_N3.dir\"][\"Y_l2_m2.dat\"]\n",
    "    times = gw_sxs_bbh_0305[:,0]\n",
    "\n",
    "    gw5 = {}\n",
    "    gw5[simulation_number] = h5py.File(simulation_path_2, 'r')\n",
    "    gw5_sxs_bbh_0305 = gw5[simulation_number][\"Extrapolated_N3.dir\"][\"Y_l2_m2.dat\"]\n",
    "# Remember to download metadata.json from the simulation with number: 0305. Download Lev6/metadata.json\n",
    "# This postprocesses the metadata file to find the final mass and final spin\n",
    "    \n",
    "elif nr_code=='Maya':\n",
    "    gw_sxs_bbh_0305_amp = np.asarray(gw[simulation_number]['amp_l2_m2/Y'])[6:]\n",
    "    gw_sxs_bbh_0305_amp_err = np.asarray(gw[simulation_number]['amp_l2_m2/errors'])\n",
    "    times = np.asarray(gw[simulation_number]['amp_l2_m2/X'])[6:]\n",
    "    gw_sxs_bbh_0305_amp_int = interp1d(times, -gw_sxs_bbh_0305_amp, kind='cubic')\n",
    "    gw_sxs_bbh_0305_amp_errs_int = interp1d(times, gw_sxs_bbh_0305_amp_err, kind='cubic')\n",
    "\n",
    "    \n",
    "    gw_sxs_bbh_0305_pha = np.asarray(gw[simulation_number]['phase_l2_m2/Y'])[6:]\n",
    "    gw_sxs_bbh_0305_pha_err = np.asarray(gw[simulation_number]['phase_l2_m2/errors'])\n",
    "    times = np.asarray(gw[simulation_number]['phase_l2_m2/X'])[6:]\n",
    "    gw_sxs_bbh_0305_pha_int = interp1d(times, -gw_sxs_bbh_0305_pha, kind='cubic')\n",
    "    gw_sxs_bbh_0305_pha_errs_int = interp1d(times, gw_sxs_bbh_0305_pha_err, kind='cubic')\n",
    "\n",
    "    amps=gw_sxs_bbh_0305_amp_int(times) \n",
    "    amps_err=gw_sxs_bbh_0305_amp_errs_int(times) \n",
    "\n",
    "    phs=gw_sxs_bbh_0305_pha_int(times)\n",
    "    phs_err=-gw_sxs_bbh_0305_pha_errs_int(times)\n",
    "    \n",
    "    gw_sxs_bbh_0305 = np.asarray([times,amps*np.cos(phs),amps*np.sin(phs)]).T\n",
    "    gw5_sxs_bbh_0305 = np.asarray([times,(amps+amps_err)*np.cos(phs+phs_err),amps*np.sin(phs+phs_err)]).T\n",
    "\n",
    "elif nr_code=='LaZeV':\n",
    "    gw_sxs_bbh_0305_amp = np.asarray(gw[simulation_number]['amp_l2_m2/Y'])[6:]\n",
    "    gw_sxs_bbh_0305_amp_err = np.asarray(gw[simulation_number]['amp_l2_m2/errors'])\n",
    "    times_1 = np.asarray(gw[simulation_number]['amp_l2_m2/X'])[6:]\n",
    "    gw_sxs_bbh_0305_amp_int = interp1d(times_1, -gw_sxs_bbh_0305_amp, kind='cubic')\n",
    "    gw_sxs_bbh_0305_amp_errs_int = interp1d(times_1, gw_sxs_bbh_0305_amp_err, kind='cubic')\n",
    "    \n",
    "    gw_sxs_bbh_0305_pha = np.asarray(gw[simulation_number]['phase_l2_m2/Y'])[6:]\n",
    "    gw_sxs_bbh_0305_pha_err = np.asarray(gw[simulation_number]['phase_l2_m2/errors'])\n",
    "    times = np.asarray(gw[simulation_number]['phase_l2_m2/X'])[6:]\n",
    "    gw_sxs_bbh_0305_pha_int = interp1d(times, -gw_sxs_bbh_0305_pha, kind='cubic')\n",
    "    gw_sxs_bbh_0305_pha_errs_int = interp1d(times, gw_sxs_bbh_0305_pha_err, kind='cubic')\n",
    "    \n",
    "    amps=gw_sxs_bbh_0305_amp_int(times_1) \n",
    "    amps_err=gw_sxs_bbh_0305_amp_errs_int(times_1) \n",
    "\n",
    "    phs=gw_sxs_bbh_0305_pha_int(times_1)\n",
    "    phs_err=-gw_sxs_bbh_0305_pha_errs_int(times_1)\n",
    "    \n",
    "    gw_sxs_bbh_0305 = np.asarray([times_1,amps*np.cos(phs),amps*np.sin(phs)]).T\n",
    "    gw5_sxs_bbh_0305 = np.asarray([times_1,(amps+amps_err)*np.cos(phs+phs_err),amps*np.sin(phs+phs_err)]).T\n",
    "    times=times_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [],
   "source": [
    "if nr_code=='SXS':\n",
    "    metadata = {}\n",
    "    with open(metadata_file) as file:\n",
    "        metadata[simulation_number] = json.load(file)\n",
    "\n",
    "    af = metadata[simulation_number]['remnant_dimensionless_spin'][-1]\n",
    "    mf = metadata[simulation_number]['remnant_mass']\n",
    "\n",
    "elif nr_code=='Maya':\n",
    "    af = 0.6861\n",
    "    mf = 0.9515\n",
    "\n",
    "elif nr_code=='LaZeV':\n",
    "    af = 0.692\n",
    "    mf = 0.952\n",
    "    \n",
    "#times --> x axis of your data\n",
    "times = gw_sxs_bbh_0305[:,0]\n",
    "tmax=FindTmaximum(gw_sxs_bbh_0305[round(len(gw_sxs_bbh_0305)/2):])\n",
    "times = times - tmax\n",
    "\n",
    "\n",
    "#times 6--> x axis of your data\n",
    "times5 = gw5_sxs_bbh_0305[:,0]\n",
    "tmax5=FindTmaximum(gw5_sxs_bbh_0305[round(len(gw_sxs_bbh_0305)/2):])\n",
    "times5 = times5 - tmax5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "w , tau = QNM_spectrum(mf,af,2,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading priors\n",
    "w_mins=np.empty(nmax+1)\n",
    "w_maxs=np.empty(nmax+1)\n",
    "tau_mins=np.empty(nmax+1)\n",
    "tau_maxs=np.empty(nmax+1)\n",
    "a_mins=np.empty(nmax+1)\n",
    "a_maxs=np.empty(nmax+1)\n",
    "ph_mins=np.empty(nmax+1)\n",
    "ph_maxs=np.empty(nmax+1)\n",
    "\n",
    "for i in range(nmax+1): \n",
    "    wp_min=parser.get('prior-w'+str(i),'w'+str(i)+'_min')\n",
    "    w_mins[i] = np.float(wp_min)\n",
    "    \n",
    "    wp_max=parser.get('prior-w'+str(i),'w'+str(i)+'_max')\n",
    "    w_maxs[i] = np.float(wp_max)\n",
    "    \n",
    "    taup_min=parser.get('prior-'+tau_var_str+str(i),tau_var_str+str(i)+'_min')\n",
    "    tau_mins[i] = np.float(taup_min)\n",
    "    \n",
    "    taup_max=parser.get('prior-'+tau_var_str+str(i),tau_var_str+str(i)+'_max')\n",
    "    tau_maxs[i] = np.float(taup_max)\n",
    "    \n",
    "    amp0_min=parser.get('prior-amp'+str(i),'amp'+str(i)+'_min')\n",
    "    a_mins[i] = np.float(amp0_min)\n",
    "    \n",
    "    amp1_max=parser.get('prior-amp'+str(i),'amp'+str(i)+'_max')\n",
    "    a_maxs[i] = np.float(amp1_max)\n",
    "    \n",
    "    phase_min=parser.get('prior-phase'+str(i),'phase'+str(i)+'_min')\n",
    "    ph_mins[i] = np.float(phase_min)*2*np.pi\n",
    "    \n",
    "    phase_max=parser.get('prior-phase'+str(i),'phase'+str(i)+'_max')\n",
    "    ph_maxs[i] = np.float(phase_max)*2*np.pi\n",
    "    \n",
    "priors_min = np.concatenate((w_mins,tau_mins,a_mins,ph_mins))\n",
    "priors_max = np.concatenate((w_maxs,tau_maxs,a_maxs,ph_maxs))\n",
    "prior_dim = len(priors_min)\n",
    "priors=np.column_stack((priors_min,priors_max))\n",
    "\n",
    "if model == 'w-tau-fixed':\n",
    "    priors_min = np.concatenate((a_mins,ph_mins))\n",
    "    priors_max = np.concatenate((a_maxs,ph_maxs))\n",
    "    prior_dim = len(priors_min)\n",
    "    priors=np.column_stack((priors_min,priors_max))\n",
    "\n",
    "elif model ==  'w-tau-fixed-m-af':\n",
    "    mass_min=[np.float(parser.get('prior-mass','mass_min'))]\n",
    "    mass_max=[np.float(parser.get('prior-mass','mass_max'))]\n",
    "    spin_min=[np.float(parser.get('prior-spin','spin_min'))]\n",
    "    spin_max=[np.float(parser.get('prior-spin','spin_max'))]\n",
    "    priors_min = np.concatenate((a_mins,ph_mins,mass_min,spin_min))\n",
    "    priors_max = np.concatenate((a_maxs,ph_maxs,mass_max,spin_max))\n",
    "    prior_dim = len(priors_min)\n",
    "    priors=np.column_stack((priors_min,priors_max))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Select the data from 0 onwards\n",
    "position = np.argmax(times >= (t_align))\n",
    "position5 = np.argmax(times5 >= (t_align))\n",
    "gw_sxs_bbh_0305rd=gw_sxs_bbh_0305[position+1:]\n",
    "gw_sxs_bbh_0305rd5=gw5_sxs_bbh_0305[position5+1:]\n",
    "timesrd=gw_sxs_bbh_0305[position:-1][:,0][:]-tmax\n",
    "timesrd5=gw5_sxs_bbh_0305[position5:-1][:,0][:]-tmax5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7efb6b503fd0>"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Test plot real part (data was picked in the last cell). Aligning in time\n",
    "plt.figure(figsize = (12, 8))\n",
    "plt.plot(timesrd, gw_sxs_bbh_0305rd[:,1], \"r\", alpha=0.3, lw=3, label=r'$Lev6$: real')\n",
    "plt.plot(timesrd, np.sqrt(gw_sxs_bbh_0305rd[:,1]**2+gw_sxs_bbh_0305rd[:,2]**2), \"r\", alpha=0.3, lw=3, label=r'$Lev5\\,amp$')\n",
    "plt.plot(timesrd5, gw_sxs_bbh_0305rd5[:,1], \"b\", alpha=0.3, lw=3, label=r'$Lev5: real$')\n",
    "plt.plot(timesrd5, np.sqrt(gw_sxs_bbh_0305rd5[:,1]**2+gw_sxs_bbh_0305rd5[:,2]**2), \"b\", alpha=0.3, lw=3, label=r'$Lev5\\,amp$')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "gwnew_re = interpolate.interp1d(timesrd, gw_sxs_bbh_0305rd[:,1], kind = 'cubic')\n",
    "gwnew_im = interpolate.interp1d(timesrd, gw_sxs_bbh_0305rd[:,2], kind = 'cubic')\n",
    "\n",
    "gwnew_re5 = interpolate.interp1d(timesrd5, gw_sxs_bbh_0305rd5[:,1], kind = 'cubic')\n",
    "gwnew_im5 = interpolate.interp1d(timesrd5, gw_sxs_bbh_0305rd5[:,2], kind = 'cubic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [],
   "source": [
    "if timesrd5[-1]>= timesrd[-1]: \n",
    "    timesrd_final = timesrd\n",
    "else:\n",
    "    timesrd_final = timesrd5\n",
    "\n",
    "gwdatanew_re = gwnew_re(timesrd_final)\n",
    "gwdatanew_im = gwnew_im(timesrd_final)\n",
    "gwdatanew_re5 = gwnew_re5(timesrd_final)\n",
    "gwdatanew_im5 = gwnew_im5(timesrd_final)\n",
    "\n",
    "gwdatanew = gwdatanew_re - 1j*gwdatanew_im\n",
    "gwdatanew5 = gwdatanew_re5- 1j*gwdatanew_im5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "#taus, corr= twopoint_autocovariance(timesrd,gwdatanew-gwdatanew5)\n",
    "#plt.figure(figsize = (12, 8))\n",
    "#plt.plot(taus, corr,'ro')\n",
    "#plt.show()\n",
    "#vmax=np.max(corr)\n",
    "#index = np.argmax(corr == vmax)\n",
    "#taus[index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error estimate: 0.20053883528563624\n",
      "mismatch: 0.02010791222885977\n",
      "snr: 229.43188441714122\n"
     ]
    }
   ],
   "source": [
    "mismatch=1-EasyMatchT(timesrd_final,gwdatanew,gwdatanew5,0,0+90)\n",
    "error=np.sqrt(2*mismatch)\n",
    "print('error estimate:',error)\n",
    "print('mismatch:', mismatch)\n",
    "print('snr:', EasySNRT(timesrd_final,gwdatanew,gwdatanew,0,0+90)/error**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 307,
   "metadata": {},
   "outputs": [],
   "source": [
    "if error_str and error_val==0:\n",
    "    error = np.sqrt(gwdatanew*gwdatanew-2*gwdatanew*gwdatanew5+gwdatanew5*gwdatanew5)\n",
    "    error_est=np.sqrt(error.imag**2+error.real**2)\n",
    "    plt.figure(figsize = (12, 8))\n",
    "    plt.plot(timesrd_final, gwdatanew.real, \"r\", alpha=0.3, lw=2, label='Lev6')\n",
    "    plt.plot(timesrd_final, gwdatanew5.real, \"b\", alpha=0.3, lw=2, label='Lev5')\n",
    "    plt.plot(timesrd_final, error_est, \"b\", alpha=0.3, lw=2, label='error')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 308,
   "metadata": {},
   "outputs": [],
   "source": [
    "if parser.has_option('rd-model','phase_alignment'):\n",
    "    phase_alignment=eval(parser.get('rd-model','phase_alignment'))    \n",
    "else:\n",
    "    phase_alignment=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 309,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Phase alignement\n",
    "if phase_alignment:\n",
    "    phas = np.angle(gwdatanew)\n",
    "    phas = np.unwrap(phas)\n",
    "    phas5 = np.angle(gwdatanew5)\n",
    "    phas5 = np.unwrap(phas5)\n",
    "    position = np.argmax(timesrd_final >= (t_align))\n",
    "    dphase = phas5[position]-phas[position]\n",
    "    gwdatanew = (gwdatanew_re - 1j*gwdatanew_im)*np.exp(1j*dphase)\n",
    "    gw_sxs_bbh_0305rd6=gw6_sxs_bbh_0305[position6:-1]\n",
    "    timesrd=gw_sxs_bbh_0305[position:-1][:,0][:920]\n",
    "    mismatch=1-EasyMatchT(timesrd_final,gwdatanew,gwdatanew5,0,+90)\n",
    "    error=np.sqrt(2*mismatch)\n",
    "    print('error estimate:',error)\n",
    "    print('mismatch:', mismatch)\n",
    "    print('snr:', EasySNRT(timesrd_final,gwdatanew,gwdatanew5,0,0+90)/error)\n",
    "    if error_str:\n",
    "        error = np.sqrt(gwdatanew*gwdatanew-2*gwdatanew*gwdatanew5+gwdatanew5*gwdatanew5)\n",
    "        error_est=np.sqrt(error.imag**2+error.real**2)\n",
    "    else :\n",
    "        error = 1 \n",
    "\n",
    "    EasySNRT(timesrd_final,gwdatanew,gwdatanew5/error,0,0+90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Test the new interpolated data\n",
    "if error_str and error_val==0:\n",
    "    plt.figure(figsize = (12, 8))\n",
    "    plt.plot(timesrd_final, gwdatanew.real, \"r\", alpha=0.3, lw=2, label='Lev6')\n",
    "    plt.plot(timesrd_final, gwdatanew5.real, \"b\", alpha=0.3, lw=2, label='Lev5')\n",
    "    plt.plot(timesrd_final, error.real, \"b\", alpha=0.3, lw=2, label='error')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Test the error data\n",
    "if error_str and error_val==0:\n",
    "    plt.figure(figsize = (12, 8))\n",
    "    plt.plot(timesrd_final, np.sqrt(error.imag**2+error.real**2), \"r\", alpha=0.3, lw=2, label='all error')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Test the error data\n",
    "if error_str and error_val==0:\n",
    "    plt.figure(figsize = (12, 8))\n",
    "    plt.xlim(1,40)\n",
    "    plt.ylim(-300,300)\n",
    "    plt.plot(timesrd_final,gwdatanew.real/np.sqrt(error.imag**2+error.real**2), \"r\", alpha=0.3, lw=2, label='all error')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Take the piece of waveform you want\n",
    "tshift=0\n",
    "position_in = np.argmax(timesrd_final >= tshift)\n",
    "position_end = np.argmax(timesrd_final >= tend)\n",
    "timesrd_final_tsh = timesrd_final[position_in:position_end]\n",
    "gwdatanew_re_tsh = gwdatanew_re[position_in:position_end]\n",
    "gwdatanew_im_tsh = gwdatanew_im[position_in:position_end]\n",
    "if error_str and error_val==0:\n",
    "    error_tsh=error[position_in:position_end]\n",
    "elif error_str and error_val!=0:\n",
    "    gwdatanew_re_tsh+=random.uniform(0, error_val)\n",
    "    gwdatanew_im_tsh+=random.uniform(0, error_val)\n",
    "    error_tsh=error_val\n",
    "else:\n",
    "    error_tsh=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Fitting\n",
    "#RD model for nmax tones. Amplitudes are in (xn*Exp[i yn]) version. Used here.\n",
    "def model_dv_q(theta):\n",
    "    #x0, y0= theta\n",
    "    #Your nmax might not align with the dim of theta. Better check it here.\n",
    "    assert int(len(theta)/4) == dim, 'Please recheck your n and parameters'\n",
    "    \n",
    "    wvars = theta[ : (dim)]\n",
    "    qvars = theta[(dim) : 2*(dim)]\n",
    "    xvars = theta[2*(dim) : 3*(dim)]\n",
    "    yvars = theta[3*(dim) : ]\n",
    "    \n",
    "    ansatz = 0\n",
    "    for i in range (0,dim):\n",
    "        ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh*np.pi*wvars[i]/qvars[i])*(np.cos(wvars[i]*timesrd_final_tsh)-1j*np.sin(wvars[i]*timesrd_final_tsh))\n",
    "    # -1j to agree with SXS convention\n",
    "    return ansatz\n",
    "\n",
    "def model_dv_tau(theta):\n",
    "    #x0, y0= theta\n",
    "    #Your nmax might not align with the dim of theta. Better check it here.\n",
    "    assert int(len(theta)/4) == dim, 'Please recheck your n and parameters'\n",
    "    \n",
    "    wvars = theta[ : (dim)]\n",
    "    tvars = theta[(dim) : 2*(dim)]\n",
    "    xvars = theta[2*(dim) : 3*(dim)]\n",
    "    yvars = theta[3*(dim) : ]\n",
    "    \n",
    "    ansatz = 0\n",
    "    for i in range (0,dim):\n",
    "        ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tvars[i]) * (np.cos(wvars[i]*timesrd_final_tsh)-1j*np.sin(wvars[i]*timesrd_final_tsh))\n",
    "    # -1j to agree with SXS convention\n",
    "    return ansatz\n",
    "\n",
    "def model_dv(theta):\n",
    "    #x0, y0= theta\n",
    "    #Your nmax might not align with the dim of theta. Better check it here.\n",
    "    xvars = theta[ : (dim)]\n",
    "    yvars = theta[(dim) : 2*(dim)]\n",
    "    \n",
    "    ansatz = 0\n",
    "    for i in range (0,dim):\n",
    "        ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tau[i]) * (np.cos(w[i]*timesrd_final_tsh)-1j*np.sin(w[i]*timesrd_final_tsh))\n",
    "    # -1j to agree with SXS convention\n",
    "    return ansatz\n",
    "\n",
    "def model_dv_ma(theta):\n",
    "    #x0, y0= theta\n",
    "    #Your nmax might not align with the dim of theta. Better check it here.\n",
    "    xvars = theta[ : (dim)]\n",
    "    yvars = theta[(dim) : 2*(dim)]\n",
    "    mass_vars = np.float(theta[-2])\n",
    "    spin_vars = np.float(theta[-1])\n",
    "    \n",
    "    w_m_a , tau_m_a = QNM_spectrum(mass_vars,spin_vars,2,2)\n",
    "    \n",
    "    ansatz = 0\n",
    "    for i in range (0,dim):\n",
    "        ansatz += (xvars[i]*np.exp(1j*yvars[i]))*np.exp(-timesrd_final_tsh/tau_m_a[i]) * (np.cos(w_m_a[i]*timesrd_final_tsh)-1j*np.sin(w_m_a[i]*timesrd_final_tsh))\n",
    "    # -1j to agree with SXS convention\n",
    "    return ansatz\n",
    "\n",
    "# Logprior distribution. It defines the allowed range my variables can vary over. \n",
    "#It works for the (xn*Exp[iyn]) version. \n",
    "\n",
    "def prior_transform(cube):\n",
    "    for i in range(prior_dim):\n",
    "        cube[i] =  priors_min[i]+ cube[i]*(priors_max[i]-priors_min[i])\n",
    "    return cube\n",
    "\n",
    "# LogLikelihood function. It is just a Gaussian loglikelihood based on computing the residuals^2\n",
    "def log_likelihood(theta):\n",
    "    modelev = dict[model](theta)\n",
    "    result = -np.sum(((gwdatanew_re_tsh - modelev.real)**2+(gwdatanew_im_tsh - modelev.imag)**2)/(2*(error_tsh.real**2+error_tsh.imag**2)))\n",
    "    if np.isnan(result):\n",
    "        return -np.inf\n",
    "    return result\n",
    "\n",
    "\n",
    "# Logposterior distribution for the residuals case.\n",
    "# The evidence is just a normalization factor\n",
    "def log_probability(theta):\n",
    "    lp = log_prior(theta)\n",
    "    if not np.isfinite(lp):\n",
    "        return -np.inf\n",
    "    return lp + log_likelihood(theta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict = {'w-tau': model_dv_tau , 'w-q': model_dv_q, 'w-tau-fixed': model_dv,'w-tau-fixed-m-af': model_dv_ma}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [],
   "source": [
    "#nmax=2\n",
    "#dim = nmax+1\n",
    "#ndim = 4*dim\n",
    "\n",
    "# loading priors\n",
    "#w_mins=np.empty(nmax+1)\n",
    "#w_maxs=np.empty(nmax+1)\n",
    "#tau_mins=np.empty(nmax+1)\n",
    "#tau_maxs=np.empty(nmax+1)\n",
    "#a_mins=np.empty(nmax+1)\n",
    "#a_maxs=np.empty(nmax+1)\n",
    "#ph_mins=np.empty(nmax+1)\n",
    "#ph_maxs=np.empty(nmax+1)\n",
    "\n",
    "\n",
    "#for i in range(nmax+1): \n",
    "#    wp_min=parser.get('prior-w'+str(i),'w'+str(i)+'_min')\n",
    "#    w_mins[i] = np.float(wp_min)\n",
    "    \n",
    "#    wp_max=parser.get('prior-w'+str(i),'w'+str(i)+'_max')\n",
    "#    w_maxs[i] = np.float(wp_max)\n",
    "    \n",
    "#    taup_min=parser.get('prior-'+tau_var_str+str(i),tau_var_str+str(i)+'_min')\n",
    "#    tau_mins[i] = np.float(taup_min)\n",
    "    \n",
    "#    taup_max=parser.get('prior-'+tau_var_str+str(i),tau_var_str+str(i)+'_max')\n",
    "#    tau_maxs[i] = np.float(taup_max)\n",
    "    \n",
    "#    amp0_min=parser.get('prior-amp'+str(i),'amp'+str(i)+'_min')\n",
    "#    a_mins[i] = np.float(amp0_min)\n",
    "    \n",
    "#    amp1_max=parser.get('prior-amp'+str(i),'amp'+str(i)+'_max')\n",
    "#    a_maxs[i] = np.float(amp1_max)\n",
    "    \n",
    "#    phase_min=parser.get('prior-phase'+str(i),'phase'+str(i)+'_min')\n",
    "#    ph_mins[i] = np.float(phase_min)*2*np.pi\n",
    "    \n",
    "#    phase_max=parser.get('prior-phase'+str(i),'phase'+str(i)+'_max')\n",
    "#    ph_maxs[i] = np.float(phase_max)*2*np.pi\n",
    "    \n",
    "#priors_min = np.concatenate((w_mins,tau_mins,a_mins,ph_mins))\n",
    "#priors_max = np.concatenate((w_maxs,tau_maxs,a_maxs,ph_maxs))\n",
    "#prior_dim = len(priors_min)\n",
    "\n",
    "#nll = lambda *args: -log_likelihood(*args)\n",
    "#initial = [w[0],w[1],w[2],tau[0],tau[1],tau[2],a_maxs[0]/2,a_maxs[1]/2,a_maxs[2]/2,1,1,1]\n",
    "#bic2=np.ones(len(range(20)))\n",
    "\n",
    "#for tshift in range(20):\n",
    "#    position_in = np.argmax(timesrd_final >= tshift)\n",
    "#    position_end = np.argmax(timesrd_final >= tend)\n",
    "#    timesrd_final_tsh = timesrd_final[position_in:position_end]\n",
    "#    gwdatanew_re_tsh = gwdatanew_re[position_in:position_end]\n",
    "#    gwdatanew_im_tsh = gwdatanew_im[position_in:position_end]\n",
    "#    error_tsh=error[position_in:position_end]\n",
    "\n",
    "#    soln = minimize(nll, initial)\n",
    "#    vars_ml=soln.x\n",
    "#    initial = vars_ml\n",
    "#    bic2[tshift]=2*log_likelihood(vars_ml)+len(timesrd_final_tsh)*np.log(len(timesrd_final_tsh))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plt.figure(figsize = (12, 8))\n",
    "#plt.plot(np.abs(bic4), \"r\", alpha=0.3, lw=3, label=r'$bic: 4$')\n",
    "#plt.plot(np.abs(bic3), \"b\", alpha=0.3, lw=3, label=r'$bic: 3$')\n",
    "#plt.plot(np.abs(bic2), \"cyan\", alpha=0.3, lw=3, label=r'$bic: 2$')\n",
    "#plt.yscale('log')\n",
    "#plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "metadata": {},
   "outputs": [],
   "source": [
    "nll = lambda *args: -log_likelihood(*args)\n",
    "if model == 'w-tau-fixed-m-af':\n",
    "    initial = np.concatenate((np.ones(2*dim),[0.8,0.9]))\n",
    "    soln = minimize(nll, initial,bounds=priors)\n",
    "    vars_ml=soln.x\n",
    "elif model == 'w-tau-fixed':\n",
    "    initial = np.ones(2*dim)\n",
    "    soln = minimize(nll, initial,bounds=priors)\n",
    "    vars_ml=soln.x\n",
    "else:\n",
    "    initial = np.ones(ndim)\n",
    "    soln = minimize(nll, initial,bounds=priors)\n",
    "    vars_ml=soln.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 323,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "28308it [54:09,  8.71it/s, +2000 | bound: 106 | nc: 1 | ncall: 600714 | eff(%):  5.045 | loglstar:   -inf < -0.147 <    inf | logz: -9.689 +/-  0.083 | dlogz:  0.000 >  0.010]\n"
     ]
    }
   ],
   "source": [
    "mypool = Pool(nbcores)\n",
    "mypool.size = nbcores\n",
    "\n",
    "f2=dynesty.NestedSampler(log_likelihood, prior_transform, prior_dim, nlive=npoints,sample=sampler,pool=mypool)\n",
    "if parser.has_option('setup','dlogz'):\n",
    "    dlogz=np.float(parser.get('setup','dlogz'))    \n",
    "    f2.run_nested(dlogz=dlogz)\n",
    "else:\n",
    "    f2.run_nested()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {},
   "outputs": [],
   "source": [
    "wstr = r'$\\omega_'\n",
    "\n",
    "if model == 'w-tau':\n",
    "    taustr = r'$\\tau_'\n",
    "elif model == 'w-q':\n",
    "    taustr = r'$q_'\n",
    "elif model == 'w-tau-fixed':\n",
    "    taustr = r'$dumb_var}'  \n",
    "elif model == 'w-tau-fixed-m-af':\n",
    "    taustr = r'$\\tau_'\n",
    "    \n",
    "ampstr = r'$A_'\n",
    "phasestr =  r'$\\phi_'\n",
    "\n",
    "w_lab = [None] * dim\n",
    "tau_lab = [None] * dim\n",
    "amp_lab =  [None] * dim\n",
    "pha_lab =  [None] * dim\n",
    "mass_lab =  ['mass']\n",
    "spin_lab  =  ['spin'] \n",
    "\n",
    "for i in range(dim):\n",
    "    w_lab[i] = wstr+str(i)+'$'\n",
    "    tau_lab[i] = taustr+str(i)+'$'\n",
    "    amp_lab[i] = ampstr+str(i)+'$'\n",
    "    pha_lab[i] = phasestr+str(i)+'$'\n",
    "\n",
    "\n",
    "labels = np.concatenate((w_lab,tau_lab,amp_lab,pha_lab))\n",
    "\n",
    "if model=='w-tau-fixed':\n",
    "    labels = np.concatenate((amp_lab,pha_lab))\n",
    "    \n",
    "if model=='w-tau-fixed-m-af':\n",
    "    pha_lab[i] = phasestr+str(i)+'$'\n",
    "\n",
    "    labels = np.concatenate((amp_lab,pha_lab,mass_lab,spin_lab))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [],
   "source": [
    "if model=='w-tau-fixed':\n",
    "    rg = (nmax+1)\n",
    "elif  model=='w-tau-fixed':\n",
    "    rg = (nmax+1)+2\n",
    "else:\n",
    "    rg = (nmax+1)*2\n",
    "\n",
    "samps=f2.results.samples\n",
    "samps_tr=np.transpose(samps)\n",
    "half_points=int(round((len(samps_tr[0])/1.25)))\n",
    "\n",
    "if model=='w-tau-fixed-a-mf':\n",
    "    npamps = np.empty((nmax+1))\n",
    "    for i in range(0,(nmax+1)):\n",
    "        amps_aux = samps_tr[i+rg][half_points:-1]\n",
    "        npamps[i] = np.quantile(amps_aux, 0.5)\n",
    "else :\n",
    "    npamps = np.empty((nmax+1)*2)\n",
    "    for i in range(0,(nmax+1)*2):\n",
    "        amps_aux = samps_tr[i][half_points:-1]\n",
    "        npamps[i] = np.quantile(amps_aux, 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summary\n",
      "=======\n",
      "nlive: 2000\n",
      "niter: 28308\n",
      "ncall: 600714\n",
      "eff(%):  5.045\n",
      "logz: -9.689 +/-  0.083\n"
     ]
    }
   ],
   "source": [
    "res = f2.results\n",
    "res.samples_u.shape\n",
    "res.summary()\n",
    "samps=f2.results.samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [],
   "source": [
    "evidence = res.logz[-1]\n",
    "evidence_error = res.logzerr[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary_titles=['n','id','t_shift','dlogz','dlogz_err']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 341,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not eval(overwrite):\n",
    "    if os.path.exists(sumary_data):\n",
    "        outvalues = np.array([[nmax, simulation_number, tshift, evidence,evidence_error]])\n",
    "    else:\n",
    "        outvalues = np.array([summary_titles,[nmax, simulation_number, tshift, evidence,evidence_error]])\n",
    "\n",
    "    with open(sumary_data, 'a') as file:\n",
    "        writer = csv.writer(file)\n",
    "        if (outvalues.shape)[0]>1 :\n",
    "            writer.writerows(outvalues)\n",
    "        else:\n",
    "            writer.writerow(outvalues[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "metadata": {},
   "outputs": [],
   "source": [
    "samps=f2.results.samples\n",
    "samps_tr=np.transpose(samps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 343,
   "metadata": {},
   "outputs": [],
   "source": [
    "sigma_vars_m = np.empty(prior_dim)\n",
    "sigma_vars_p = np.empty(prior_dim)\n",
    "sigma_vars = np.empty(prior_dim)\n",
    "for i in range(prior_dim): \n",
    "    amps_aux = samps_tr[i][half_points:]\n",
    "    sigma_vars_m[i] = np.quantile(amps_aux, 0.1)\n",
    "    sigma_vars[i] = np.quantile(amps_aux, 0.5)\n",
    "    sigma_vars_p[i] = np.quantile(amps_aux, 0.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "metadata": {},
   "outputs": [],
   "source": [
    "sigma_vars_all = [sigma_vars,sigma_vars_m,sigma_vars_p]\n",
    "sigma_vars_all=np.stack([sigma_vars,sigma_vars_m,sigma_vars_p], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 345,
   "metadata": {},
   "outputs": [],
   "source": [
    "key =['max val','lower bound','higher bound']\n",
    "dfslist = [pd.DataFrame(np.concatenate(([tshift],sigma_vars_all[i])).reshape((-1,prior_dim+1)), columns=np.concatenate((['tshift'],labels)), index = [key[i]]) for i in range(3)]\n",
    "df2 = pd.concat(dfslist)\n",
    "if not eval(overwrite):\n",
    "    if os.path.exists(best_data):\n",
    "        df2.to_csv(best_data, mode='a', header=False,index = True)\n",
    "    else:\n",
    "        df2.to_csv(best_data,index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {},
   "outputs": [],
   "source": [
    "if model == 'w-q':\n",
    "    tau_val = np.pi*w*tau\n",
    "    truths = np.concatenate((w,tau_val,npamps))\n",
    "elif model == 'w-tau':\n",
    "    tau_val = tau\n",
    "    truths = np.concatenate((w,tau_val,npamps))\n",
    "elif model == 'w-tau-fixed':\n",
    "    truths = npamps\n",
    "elif model == 'w-tau-fixed-m-af':\n",
    "    truths = np.concatenate((npamps,[mf],[af]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000.8x1000.8 with 36 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fg, ax = dyplot.cornerplot(res, color='blue', \n",
    "                           show_titles=True,\n",
    "                           labels=labels,\n",
    "                           quantiles=(0.05,0.5,0.95),\n",
    "                           truths =truths,\n",
    "                           truth_color='red',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 698.4x698.4 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "afdist=samps_tr[-1][::downfactor]\n",
    "mdist=samps_tr[-2][::downfactor]\n",
    "\n",
    "w_dist=[None] * len(afdist)\n",
    "tau_dist=[None] * len(afdist)\n",
    "\n",
    "for i in range(len(afdist)):\n",
    "    w_dist[i],tau_dist[i] = QNM_spectrum(mdist[i],afdist[i],2,2)\n",
    "\n",
    "for i in range(dim):\n",
    "    w_lab[i] = wstr+str(i)+'$'\n",
    "    tau_lab[i] = taustr+str(i)+'$'\n",
    "\n",
    "labels = np.concatenate((w_lab,tau_lab))\n",
    "truths = np.concatenate((w,tau))\n",
    "\n",
    "w_tau_dist=np.column_stack((w_dist,tau_dist))\n",
    "figure = corner.corner(w_tau_dist, labels=labels,\n",
    "                       quantiles=[0.05, 0.5, 0.95],\n",
    "                       show_titles=True, title_kwargs={\"fontsize\": 16},\n",
    "                       truths=truths,\n",
    "                       truth_color ='r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not eval(overwrite):\n",
    "    fg.savefig(corner_plot, format = 'png', bbox_inches = 'tight')\n",
    "    if model == 'w-tau-fixed-m-af':\n",
    "        figure.savefig(corner_plot_extra, format = 'png', bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jIt7Q0/tLkiRJqs5ZZ5Wtrxx5JAwdunrbwoVw4419956SNND0KKiJiEOBq4DNgdOBkyvb6ZW2qyPikJ4WKUmSJKn+Ro6EQw9t3z5lCqQzV0pSr+jqZMJtfRd4BDgoM+e3PhARpwO3At8BOvjrXJIkSVKzOf54uOqq1dueeALuuQf23LMeFUlS/9LToU97A+e0DWkAKm2/ACb18D0kSZIkNYiJE2Gnndq3X3BBzUuRpH6pp0HNEmDkWo5vUDlHkiRJUj/xtre1b5s+HWbNqnkpktTv9DSouRb4XETs2/ZAREwCPgtc08P3kCRJktRADjgANtmkfbu9aiSp53oa1HwRWAbcHhE3RcQvKttNwFRgaeUcSZIkSf3EoEHw1re2b7/uOnj55ZqXI0n9So+Cmsx8DNgd+A9gHPDByjYO+Hdgj8x8vKdFSpIkSerclCllq4Wjj4b11lu9bdkyuPTS2ry/JPVX3Q5qImJwRGwKvJKZp2Xmjpk5orLtmJn/LzOf78VaJUmSJDWI4cPhuOPat19yCSxdWvt6JKm/6HJQExGDIuL7wMvAM8ArEXFhRIzt7eIkSZIkNa43vQkGD1697ZVX2i/fLUmqXnd61HyUMu/MPOBPwL3ACcD/9GJdkiRJkrro1FPLVitjx8Ihh7Rv/9OfYPny2tUhSf1Jd4KavwOmATtk5nsycxJwBnBsRHQw97skSZKkWnj00bLV0jve0b5t7ly4/vra1iFJ/UV3gpptgf/NzMWt2n4GROWYJEmSpAFiwgTYf//27eedBytX1rwcSWp63QlqRgEvtmlreT28Z+VIkiRJajbveU/7ttmz4ZZbal+LJDW77q76lF1slyRJktRPbb897Lln+/Y//hHSfyFIUpd0N6g5OyLmtWzAzEr7ha3bK1vb3jeSJEmS+pn3vrd92xNPwB131LwUSWpqQ7pxjas7SZIkSVrNLrvATjvBgw+u3v6738F++0FEfeqSpGbT5aAmM0/ui0IkSZIk9cwxx9TvvSNKr5pvfWv19kcfhdtug9e/vi5lSVLT6U6PGkmSJEkN6JRT6vv+e+8N220Hjzyyevuvfw0HHACDujvxgiQNIP5VKUmSJKlXRMCHP9y+fdYsuPHG2tcjSc3IoEaSJEnqJ2bOLFs97bkn7Lpr+/bf/haWL695OZLUdAxqJEmSpH7itNPKVk8R8MEPtm+fMweuvbb29UhSszGokSRJktSrdt0V9tqrffvvfgdLl9a+HklqJgY1kiRJknpdR3PVvPACTJlS+1okqZn0SlATEW+MiO9FxM8jYsdK28iIOCIixvTGe0iSJElqHtttB/vv3779j3+E+fNrX48kNYseBTURsV5EXAVcBnwB+CiwWeXwEuC3wOd6VKEkSZKkpnTiie2X5F60CH7/+/rUI0nNoKc9av4VOBh4H7AlEC0HMnMpcB7w5h6+hyRJkqQmtMUWcMwx7dsvuwyeeab29UhSM+hpUPMu4D8z8zygo2nB/gZs3cP3kCRJktSkPvABGD589bYVK+CXv6xPPZLU6Hoa1IwBHunk/sN6+B6SJEmSqnDGGWVrJBtuCO9+d/v2qVPh/vtrXo4kNbyeBjWPAXus5fiRwIM9fA9JkiRJVZg4sWyN5q1vhbFj27f/7Geld40kaZWeBjX/DXwsIt7Wqi0jYp2I+AZlfpqze/geaxUR20XEHyLi6YhYGBF/jYh/iohhbc4bFhGnR8TsiHgtIm6PiCM7uF9V50mSJEmqzrBhHS/X/cQTcOmlNS9HkhpaT4OaHwO/B/4MPFRp+1/gFeBbwDmZ2WdBTURsDtwB7A+cCZwGTKdMcvyLNqefWzn+a8pKVCuByyLiwG6eJ0mSJDWUM88sWyM6/PCyZHdbv/41vPxyzcuRpIYVmdnzm0S8AXgnsB0l/HkUOD8zr+/xzdf+vl8Cvg/smpkPtGo/H3grsG5mLouI/YCpwGmZOblyznDgfmB2Zh5SaavqvLWZNGlSTps2rff+kJIkSVKVTjih7KdMqW8da/Lww/CP/wht/wly5JFw6ql1KUmS6iYipmfmpLbtPe1RA0Bm3pSZp2bmmzLzuMw8pa9DmooNKvvn2rQ/CywDWka8vqvy+v962WTmYuAc4OCIGN/F8yRJkiR10fbbw9FHt2+/5hr4619rX48kNaIeBTURcWVEfDQiRvdWQV10Q2V/TkTsERFbRMQHgZOA0zNzZeX4XsBDmflqm+vvAALYs4vnSZIkSeqGE0+E9ddv3/6TnzixsCRBz3vUvI7S++TZiLgkIj4SERt0dlFvycwrga8DRwMzgKcoc8ucnpnfbnXqeGBOB7doadusi+etJiI+GRHTImLa3Llzu/RnkCRJkgaSDTaAj3ykffsTT8AFF9S6GklqPD0KajJzZ2B34AfANpSJeJ+LiAsj4v0RsV7PS+zU48D1wCcp8+T8N/DtiPi7VueMAJZ0cO3iVse7ct5qMvPszJyUmZPGjRvXteolSZKkAeaYYzpeRvy3v4XZs2tfjyQ1kh7PUZOZ92fm1zNzJ8rQoR8DOwC/AZ6vTOzbJyLifcDPgI9n5s8z88+Z+THgf4AftRqS9RowrINbDG91vCvnSZIkSeqmQYPg05+GiNXbly6F//zP9pMNS9JA0iuTCbfIzHsy82uZuSPwd8By4O29+R5tfBqYnpltc/eLgPWAPSqv51CGNbXV0ja7i+dJkiRJDWfbbcvWDLbbDt7ylvbt998PV1xR+3okqVH0alATEXtHxPcj4lHgJ8AQ4E+9+R5tbAIM7qB9ncp+SGU/A9gxItpOW7Z/ZX9PF8+TJEmSGs7kyWVrFh/6EGyySfv2X/4SXnyx9vVIUiPocVBTWW3pXyLiYeBO4LOUQOMDwLjMfE9P32MtHgYmRUTb7w3eT1ma+97K6/Mp4c3HW9U9DDgZuKVVj5xqz5MkSZLUQ8OHwymntG9ftAjOPNMhUJIGpiGdn7JmEfE3YCKwDLgC+BZwUQfLW/eVHwLHAbdExJnAPODNlbafZubzAJk5NSLOA34QEeOBR4ETga0oS3nTlfMkSZIk9Y4994SjjoKrr169fdq0MgTq2GPrUpYk1U1Pe9Q8QultsnFmvjUzf1vDkIbMvBF4PXAX8BlgMrAt8GWgbTb/EeDfK/v/oPScOT4zb+nmeZIkSVJDOeGEsjWbj30MNtywffsvfgFz5tS8HEmqq0j7E/aqSZMm5bRp0+pdhiRJkgaglpBmypT61tEdU6fCd7/bvn2HHeD002FwRzNTSlITi4jpmTmpbXuXetRExJYRsWXb151tvfEHkCRJktR/7b8/vPGN7dv/9jc477za1yNJ9dLVOWqeADIiRmTm0pbXVVxn/i1JkiRprT7xCbj3Xnj22dXbf/c72Guv0rtGkvq7rgY1H6UEM8vavJYkSZKkHhk+HP7f/4MvfWn1FZ9WrizDn/7932HkyPrVJ0m10KWgJjPPXdvrtiJiMDCsy1VJkiRJGpB22gne/W744x9Xb587FyZPhq99DSLqUpok1URPV33qzD8Br/Txe0iSJEnqR97/fth++/btd9wBF1xQ83Ikqab6OqgBMO+WJEmSauAznylbsxsypAx/Wm+99sf+53/goYdqX5Mk1UotghpJkiRJNXDssWXrDzbeGE47rX37ihXw/e/DSy/VviZJqgWDGkmSJEkNaf/94W1va9/+4ovwr/8Ky5fXvCRJ6nMGNZIkSVI/cfnlZetPTjyx42W5H3wQfvrT1VeHkqT+oKvLcxMRu3fh9E27en9JkiRJ3XPWWWXfX4Y/war5ak47DebPX/3YFVfANtvA8cfXpzZJ6gtdDmqAGUC1uXV04VxJkiRJamfcOPjyl+GrXy1z1LR29tmwxRaw2271qU2Selt3gpqTe70KSZIkSVqLXXaBT30K/uu/Vm9fsQL+5V/ghz8sgY0kNbsuBzWZ+T99UYgkSZIkrc1xx8Fjj7Wfh2fhQvjWt0pYM2ZMXUqTpF7jZMKSJEmSmsanPgU779y+/fnn4Z//GRYvrn1NktSbDGokSZIkNY0hQ8pcNZtt1v7Yo4/C6ae7bLek5mZQI0mSJKmpbLBBGeo0alT7Y9OmweTJsHJlrauSpN5hUCNJkiT1E1OmlG0gGD8evv51GDq0/bEbbiiTDqfrz0pqQgY1kiRJkprSDjvAF78IEe2PXXEFnHOOYY2k5mNQI0mSJKlp7b8/fOYzHR+78EL47W9rW48k9ZRBjSRJktRPnHpq2QaaY46Bj32s42O//z38+tf2rJHUPIbUuwBJkiRJvePRR+tdQf287W3w2msd96D5wx9g2TI46aSOh0lJUiOxR40kSZKkfuF974O3v73jY3/+M/z85/askdT4DGokSZIk9QsRcPLJcMIJHR+fMgXOPNOluyU1NoMaSZIkSf1GBHziE2vuWXPllfC978GSJbWtS5KqZVAjSZIkqV9p6Vnznvd0fHzqVPja12DBgtrWJUnVMKiRJEmS1O9EwIc/DB/8YMfHH3oIvvhFeP752tYlSZ0xqJEkSZL6iWOOKZtWed/7ylCojlZ7evpp+PznS2gjSY0i0mnPe9WkSZNy2rRp9S5DkiRJUis33ww//jEsX97+2JAhcMopcOSRta9L0sAVEdMzc1LbdnvUSJIkSer3Dj4Yvv1tWHfd9seWL4fJk+EXv4AVK2pemiStxqBGkiRJ6idmziybOrb77nD66bDRRh0fv/BC+Na3YP78mpYlSasxqJEkSZL6idNOK5vWbMIE+Ld/g+237/j4jBnw2c/CAw/UsipJWsWgRpIkSdKAMmYM/Ou/wuGHd3x83jz4ylfgvPPAKT0l1ZpBjSRJkqQBZ+jQ0vvoox/teEWolSvhV78qQ6Hmzat5eZIGMIMaSZIkSQNSBLz97SWMGTmy43PuuqusCHXzzTUtTdIAZlAjSZIkaUDbe2/4j/+AnXbq+PiCBWUS4h/9CF59tba1SRp4DGokSZIkDXhjx8L3vgfveteaz7nhhtK75o47aleXpIHHoEaSJEmSgCFD4MQT4ZvfhFGjOj7nxRfhO98pkxG/+GJt65M0MEQ6jXmvmjRpUk6bNq3eZUiSJGkAmjmz7CdOrG8d/cH8+XDWWXDbbWs+Z8QI+MhH4PjjYZBfgUvqooiYnpmT2rUb1PQugxpJkiSpf8iE66+Hn/4UFi1a83nbbQef+MSa57iRpI6sKagx95UkSZKkDkTA4YeXnjV77bXm8x55BL74xTLh8PPP164+Sf2TQY0kSZLUT5x5ZtnUu8aOhW9/G/7xH9c8dw2UJbz/7u/gV7+ChQtrV5+k/sWgRpIkSeonrriibOp9EXDoofCTn8Axx6z5vGXL4LzzylCo88+HxYtrV6Ok/sGgRpIkSZKqNHJkWaL7+9+Hrbde83kLFsD//A98/ONw0UWwdGntapTU3AxqJEmSJKmLdtkFJk+Gz34WNtxwzefNnw8//3npYXPBBfDaazUqUFLTMqiRJEmSpG4YNAiOPhp+9jN417tgnXXWfO68eXDOOXDyyfDrX5cAR5I6YlAjSZIkST2w7rpw4ollGe+jjy7z2azJwoXwhz/ARz9a5ruZNat2dUpqDgY1kiRJktQLNt64DIX6yU/gkEPWHtgsXQqXXgqf/jR89atw662wYkXtapXUuIbUuwBJkiRJvWPbbetdgQA23xy+8AV497vhd7+D226DzDWff++9ZdtoIzj2WDjySBg3rnb1SmoskWv7G0NdNmnSpJw2bVq9y5AkSZLUIJ55Bv70J7juOli+vPPzI2CPPUpgc+CBMGxY39coqfYiYnpmTmrXblDTuwxqJEmSJHVk3jy48EK47LLqV38aMQLe8AY49FDYddcygbGk/sGgpkYMaiRJkiStzaJFcO21cMkl8PTT1V83ahQcdFDZDG2k5mdQUyMGNZIkSaqXE04o+ylT6luHqpNZ5qa55BK4/fa1z2PT1qhR8PrXw/77w267wdChfVenpL6xpqDGyYQlSZIkqQ5a5qLZYw944QW45pqyzZnT+bXz55chVJddVkKaPfeEffeFSZNg7Ng+L11SHzKokSRJkqQ6GzsW3vteeM974MEH4eqr4aabYPHizq9duhTuuKNsABMmlOBm993LEKkRI/qyckm9zaBGkiRJkhpEBOy8c9k++UmYOhVuvhmmT4dly6q7xxNPlO2CC8o8NttvX3rt7L477LCDq0hJjc6gRpIkSZIa0PDhZbWnQw8tExDfeWfXQ5uVK+Ghh8r2hz/A4MGwzTaw446w005lc6iU1FgMaiRJkiSpwa277uqhzfTpJbiZNg0WLKj+PitWwCOPlK1l0umNNirBzcSJsO22Zdtgg775c0jqnEGNJEmSJDWRddeFN7yhbCtXwsMPl9Dmzjvh8ce7fr8XX4Rbbilbi7FjV4U2225b5r0ZN64MzZLUt1yeu5e5PLckSZLq5fLLy/7YY+tbh+pn3ryy5Pc995Rt7tzeu/fw4bDFFrDllqtvBjhS96xpeW6Dml5mUCNJkiSpEWTCc8+VwObee+Gvfy3LgPe24cNh/Pj222ablWFVhjhSx9YU1Dj0SZIkSZL6oQjYdNOyHXNMaXvhhVWTCz/4IDz6aJm3picWLy5DrjoadrXOOuX9N9mk9Lxpu40ZA0P8V6m0Gv8vIUmSJPUTDn1SZ8aOhYMPLhvA0qVlYuFHH121zZpV5r7pDcuWlfvNmtXx8YgS1owbV2obPRo23LC0jR69ahs1qiw1Lg0EBjWSJElSP3HWWWVvUKNqDR0Ku+xSthZLl8ITT5TQ5rHHyvbUU6XnTG/LLJMZv/ji2s+LKAFOS5CzwQYwcmTZt/65ddvQob1fr1QLBjWSJEmSpP8zdChsv33ZWmSWYVNPPVW2WbNW/fzaa31fUya89FLZqjVsWAlu1l+/rJS13nrV70eMKHPvOCxL9eBj14GIGAb8M/BhYDRwD/DVzLymroVJkiRJUh1ErJpXZp99VrVnwssvw5w5ZZs9e9XPc+bAwoV1K5klS8rWkwmUBw8ugc2wYWXfdmvd3vrnoUPL/Dwt+9Y/r+nY4MFOvKzCoKZj5wLvBCYDM4GTgMsi4tDMvK1+ZUmSJElS44hYNY/MzjuvfiwTXn21BDZz53a8zZ9fn7qrtWJFCZtqEThFtA91WrbBg0vvniFDVv3cum1N7W3bBg8uc/203ff055Ytomytf269ddTetq1lLqLW7QONQU0bEbEf8D7gtMycXGn7FXA/cDpwSP2qkyRJkqTmEFGGHo0cufowqtaWLi09XubOhXnzSu+cefNWDXNq2V59taal10Vm+e+xdGl9eyI1orWFON0NhlruW+2+dWC0ptfVnNP69ZoY1LT3LmAZ8IuWhsxcHBHnAP8SEeMzc07dqpMkSZKkfmLoUNhss7KtzdKlJcR56SV45ZVV24IFq+9bt/d02XE1jsyy9dZqZI3OoKa9vYCHMrNtZnsHEMCegEGNJEmSJNXI0KGw8cZlq0YmLFpUAptFi0oPlZZ965/XtF+8uGwDJRhQYzGoaW888EwH7S3hTLusNyI+CXyy8nJJRNzfR7Wp/xsL9GC6Mw1gPjvqLp8d9YTPT4NqgjkdfHbUXT476olGe3626qjRoKa9EcCSDtoXtzq+msw8GzgbICKmZeakvitP/ZnPj7rLZ0fd5bOjnvD5UXf57Ki7fHbUE83y/AyqdwEN6DVgWAftw1sdlyRJkiRJ6nUGNe3NoQx/aqulbXYNa5EkSZIkSQOIQU17M4AdI2L9Nu37V/b3dHL92b1ekQYSnx91l8+OustnRz3h86Pu8tlRd/nsqCea4vmJzKx3DQ0lIvYHbgdOy8zJlbZhwP3Ac5l5cB3LkyRJkiRJ/ZiTCbeRmVMj4jzgBxExHngUOJEyG/NJ9axNkiRJkiT1b/ao6UBEDAe+A3wIGA3cC3wlM6+ua2GSJEmSJKlfM6iRJEmSJElqEE4m3AsiYlhEnB4RsyPitYi4PSKOrHddanwRMSki/hIRT1aenWcj4vKIeH29a1NziIh9I+KSiHgpIl6NiHsi4qR616XGFhEHRMQ1lWdmfkRcEBHb1rsuNZaIGB8R34+I6yJiQURkRBzW5pyNIuILEXFTRMyNiJcj4raIeHd9qlYjqObZqZz3ROVY2+37ta9ajaILz8/wiPhKRDwYEYsiYlZE/DYitq991aq3ymfisyLirxGxMCKeiojfR8TENue9NyJ+HREPV56t6+tU8lo5R03vOBd4JzAZmEmZy+ayiDg0M2+rX1lqAttS/n/4c8rS8BsCHwRujIjjMvOqOtamBhcRxwEXAtcDXweWAdsDW9SxLDW4iNgXuAF4Avgm5UubTwM3RcRemflcHctTY9kB+BLls829QEdfIhwI/AtwKfBdYDnlM9EfI+IbmfmdGtWqxlLNs9NiOuUzdGv3901ZahLVPj//C7yNsorP3cDrgM8Ax0TETpn5fN+XqgbyJeAg4DzKc7MpcApwd0Tsl5kPVs77e2AfYBqwUT0KrYZDn3ooIvYDprL6KlHDKb9gZmfmIXUsT00oItYFHgOmZeab612PGlNEjAIeBn6fmZ+rdz1qHhFxGbAvsF1mvlRpG095ns7JzFPrWJ4aSESMBIZm5osR8TbgL8DhmXl9q3O2BlZm5pOt2gK4mhLibJSZr9W0cNVdNc9O5bwngBmZ+bZa16jGVeXfPZsAzwI/yswvtGp/MzAF+Ghm/rKmhauuKiMSpmXm0lZt2wH3UT4vn1Rp24Ly7/QVETEDeDkzD6t9xWvn0KeeexflW+xftDRk5mLgHODgyodfqWqZuQiYS+ldI63JByjPyDegfKip/ONI6sxBwJUtIQ1AZs6h9LJ5T92qUsPJzAWZ+WIn5zzeOqSptCVwATACmNBnBaphVfPstFaZRmDdvqxJzaPK52eDyr5tL9BnK3sD4gEmM29tHdJU2h4BHgB2atU2KzNX1Lq+rjKo6bm9gIcy89U27XcAAexZ84rUdCr/yB4bETtExPeAXYFr6l2XGtpRwEPA8RExC3gFmFcZ0z24vqWpwQ2j4w+wi4DxfsGgXrJpZf9CXatQM3gjsBBYGBGPRsQn612QmsLjwCzg8xFxQkS8LiIOAP4deJAyNFwDXOVLzE1owt9FzlHTc+OBZzpon1PZb1bDWtS8fkkZ0w+wFPgp8L36laMmMJEyF825wA8oY7PfTBmfOxw4tV6FqeH9DTgwIgZl5kqAiBgK7F85vhmrfodJXRYRY4CPA9dn5tx616OGdi9wE2Xo5TjgE8DPImJMZjqhsNYoM5dHxLuA3wIXtTp0O3CIQy5V8UFgc+Cr9S6kqwxqem4EsKSD9sWtjkud+TbwM8okaB+mfOO9Dh0/WxLA+sBo4J8y8/RK258jYn3g0xHx3cxsum8PVBP/BfwE+HlE/JjSu/ZrlC8ewN9b6oGIGAT8BhgFfLbO5ajBZeZbWr+OiF8CNwNfj4ifZOb8+lSmJvES5YuqP1LmDJ0IfBk4PyKOyUw/Rw9gEbEjcBbl75T/rXM5XebQp557jfKP6raGtzourVVm3peZV1UmPTuGMhP5ufWtSg2u5e+W37Vp/w0l5NuvtuWoWWRmS4+9D1PGbd9HWYHuB5VT2g7llbriPym/x07OzPvqXYyaS2XeiMnAupTJqKUOVRZVuAm4OTO/kpkXZuaPKT3UDwU+UtcCVVcRsSlwCSXMe3dLD+JmYlDTc3NY9S1kay1ts2tYi/qBzFxGGVf7jojwm22tScvQlLaT6LW8Hl3DWtRkMvOrlDHbbwB2z8x9KZ8JEni0nrWpeUXENylLvX8xM9uGyFK1ZlX2Y+pahRrdOym/x1oPeyIzb6DM23dQPYpS/VVCvMsoPTuPycxnO7mkIRnU9NwMYMfKcIPWWsb631PbctRPjKBMRj2y3oWoYU2v7Ddv0/66yt55IbRWmflSZt7cqtfDUcAdmbmgnnWpOUXEZ4BvAWdk5o/qXI6a2zaVvb/HtDabVParLaBQmTx2ME7xMSBFxHDK8uzbA2/OzL/VuaRuM6jpufMpwww+3tIQEcOAk4FbMtMeNVqjiBjXQdsGwLuBWZn5fO2rUpM4r7L/WEtD5cPJxymrZ9xej6LUnCLivcC+lCEHUpdUnp//oAy9/Hydy1GTiIgxlTmNWrcNB74ALABuq0thahYPV/bva9P+FmA9ytw1GkAqq57+gTJs8t2Z2dSfhU0aeygzp0bEecAPKkuaPgqcCGwFnFTP2tQU/hARi4FbgWcpq/icTOkV0fYXj/R/MnN6RPwK+HJEbAzcBbyJMjfEFzPzlboWqIYVEUcAXwGuBF6kfKA5CfhNZv6+jqWpAUXE1yo/7lTZfzgiDgZezswzI2I/4FeUZ+ka4IMlM/4/V2Vm2yGaGgA6e3Yo/6D+akScDzwBbET5DL098PeZ6XxZA1gVz88Uyjxr346IrSmTCW8HnEJZkfeXNS5Z9fdjyt8rU4AxEfGhVsdezcwLACLiEOCQSvsmwKhWz9tFmXlvjepdq8jMetfQ9Crp/3eAD1HmhbgX+EpmXl3XwtTwIuKjlMnOdqY8Oy9TekL8qDLGVlqjypLKX6d8sN0UeIwy7OBndS1MDS0itqOsgrAXZXjlI8DPgTObcbI99a2IWNMHxSczc0JEnMTa/0F0eGZe3+uFqeFV8ezsQxkutxdlae4llC8dfpSZF9emSjWqzp6fyjmjKZ+D3kT5knwBcBXw5cx8shZ1qnFExPWUiaQ70vq5+RbwzTWcd3JmntvbtXWHQY0kSZIkSVKDcI4aSZIkSZKkBmFQI0mSJEmS1CAMaiRJkiRJkhqEQY0kSZIkSVKDMKiRJEmSJElqEAY1kiRJkiRJDcKgRpIkSZIkqUEY1EiSJPWSiPhWRGS965AkSc3LoEaSJKlBRMR3ImJFRGzTpj0i4oKIWBIRB9WrPkmS1PcMaiRJkhrHWcBy4LNt2r8OvBX4bGbeUvOqJElSzRjUSJIkNYjMfBb4PfDRiNgAICLeBHwL+Hlm/qyO5UmSpBowqJEkSepDLfPWRMTWEfGriJhf2X4ZEet2cMkZwEjgYxGxHfAb4HbglFrWLUmS6sOgRpIkqTb+BIwA/gn4I3AS8M22J2XmDOB6yvCnC4BFwDszc2ltypQkSfU0pN4FSJIkDRB3ZuanWl5ExEbAx4AvdXDuGcCFwFLg8MycU5sSJUlSvRnUSJIkdSAiBgFDqzk3MxdXcdpP27y+CXh7RGyQma+0ObZTZX9fZt5aTQ2SJKl/cOiTJElSxw4BXqtmi4ixVdzvqTavX6rsR7dujIjjgO8BjwD7RMR+3f0DSJKk5mOPGkmSpI49BJxc5bkLqjhnxRra4/9+KJMH/xa4lbIc92PAacD7q6xDkiQ1OYMaSZKkDlSWyj63Vu8XESMpkwcvBN6VmfMi4hfA5yLiC5n5dK1qkSRJ9ePQJ0mSpDqLiAB+BWxLWeHpucqh/6T0uPmHetUmSZJqy6BGkiSp/r4BvA34dGZObWnMzCeBPwOfiIj16lSbJEmqIYMaSZKk+noL8E3gJ5n53x0cP4My4fBJtSxKkiTVR2RmvWuQJEmSJEkS9qiRJEmSJElqGAY1kiRJkiRJDcKgRpIkSZIkqUEY1EiSJEmSJDUIgxpJkiRJkqQGYVAjSZIkSZLUIAxqJEmSJEmSGoRBjSRJkiRJUoMwqJEkSZIkSWoQBjWSJEmSJEkNwqBGkiRJkiSpQRjUSJIkSZIkNQiDGkmSJEmSpAZhUCNJkiRJktQgDGokSZIkSZIahEGNJEmSJElSgzCokSRJkiRJahAGNZIkSZIkSQ3CoEaSJEmSJKlBGNRIkiRJkiQ1CIMaSZIkSZKkBmFQI0mSJEmS1CAMaiRJkiRJkhqEQY0kSZIkSVKDMKiRJEmSJElqEAY1kiRJkiRJDcKgRpIkSZIkqUEY1EiSJEmSJDUIgxpJkiRJkqQGYVAjSZIkSZLUIAxqJEmSJEmSGoRBjSRJkiRJUoMwqJEkSZIkSWoQBjWSJEmSJEkNwqBGkiRJkiSpQRjUSJIkSZIkNQiDGkmSJEmSpAZhUCNJkiRJktQgDGokSZIkSZIaxJB6F9DfjB07NidMmFDvMiRJkjQAzZxZ9hMn1rcOSVLnpk+f/kJmjmvbblDTyyZMmMC0adPqXYYkSZIGoBNOKPspU+pbhySpcxHxZEftBjWSJElSP3HMMfWuQJLUUwY1kiRJUj9xyin1rkCS1FNOJixJkiRJktQgDGokSZKkfmLmzFUTCkuSmpNDnyRJkqR+4rTTyt7JhCWpsa1cueZjBjWSJEmSJElrkQlLlsCiRfDaa2veqj2+dOma38ugRpIkSZIkNa2VK2HZsjVvy5ev/vPSpV0PV5YsKWFNLRjUSJIkSZKkhrJiRZlz65574L774KWX1hzE1CpAqRWDGkmSJEmSVFeZMHt2CWZmzIB774WFC+tdVX0Y1EiSJEmSpJqbP39VMDNjBsydW++KGoNBjSRJkiRJ6nWZZQjTsmVlXpilS2HWrFXBzOOP17vCrhk6FEaMgHXXLfs1bdUcHzYMBg3q+H0MaiRJkqR+4owz6l2BpEa3cmUJTFrmd2n7c0fHliwpk+ouXrxqgt2WnxcvLlvLtW23WswfEwHrrFO2IUNW/by2tuHDuxa4DB8Ogwf3/Z8FDGokSZKkfmPixHpXIKkvZbYPTDoKUBYtKsOK5s+Hl19e9fPChaWHS7MYMQJ22w323BN23LEEJx0FL7UKUGrFoEaSJEmSpBrLLOHJ3LklQHn11bJfurT0elm5siwl/cIL8Nxz8OyzZb98eb0r7zuDB8MOO5RgZs89YbvtSigz0AzAP7IkSZLUP515Ztmfckp965AGshdfhAcegAcfLD+3hC6Zq+ZseeUVmDOn9IAZ6LbYooQye+0Fu+5aetEMdAY1kiRJUj9xxRVlb1Aj9Z1Fi+CJJ+Cxx0ovl5YhR3PnlvBl/vx6V9hYIsrEuUOHrpqMd+LEVb1mxoypd4WNx6BGkiRJkjTgZZbhR23ndXnppbKfNw+eeqqEMc1u6NAyt0vLvuXntbW3nlS37X748NXDmHXWKa/74/wxtWBQI0mSJEkakFasKD1jLr0Ubr219JZpdG2DkjX9vMEGMGrUqm3DDWH99Ut4ElHvP4XWxqBGkiRJktSUli6F2bPL0KM1LQ+9dGmZpHfBgjI3zIIFq36eP7++qyANHQqbblpClPXWK9uwYaUXyuDBMGhQCVc23RTGjy/79darX72qDYMaSZIkSVJTyCw9YC67rEzYO3t2mai3kQweDBMmlIlxt9++BC8RZRs0qOxbApqNNrJ3i9ozqJEkSZIkNYwVK1b1eHn55TJHzLx5ZeLeu+9ujDliNtsMttmmBDKjRpUwZtSo0j5unPOyqGcMaiRJkqR+Yttt612B1H1PPQV//GOZK2bZsvrVsemmq+Z02XDDVT+PGlVCmAkTXEJafcugRpIkSeonJk+udwVS5zJhyRJYvLjMLTNrFlx0EdxzT33q2WAD2GILeMMb4Mgjy2S8Uj0Z1EiSJEmS+sSCBXDTTfD44/Dii/DCC/Dkk707r8zYsWWul5bloFv2Q4eu+nnddWHkyLJtsMHqPxvMqNEY1EiSJEmSeiQTHn4YZsyA558voczcuaW3TGbvvlcE7LgjHHEEHHRQCVyk/sSgRpIkSeonTjih7KdMqW8d6t8yy8S+Ldv06fDXv5beM71p/PgyN8zo0TBmTNnGj4c99jCcUf9mUCNJkiRJ6tDixfD002X1pQULynLYN99c2vrC6NFw2GHwjneUkEYaiAxqJEmSJElAWRr78cfhkUfgqqvKz8uX9/77DB1aVk4aPrxs48fDoYfCgQe6tLVkUCNJkiRJA8jy5WX+mMWLyzZ3bplX5vnn4Y47yvwyvWmDDeD1r4eddoKNNy7LX48d27vvIfUnBjWSJEmS1E8tXVom9F2woOzvugvuv78ENH1hp51gn31gyy1LGDNuHIwaVSYAllQdgxpJkiRJ6mceeaRMKn3LLSWs6QvbbVd6yAwfDttuC4ccUkIZST1jUCNJkiRJTWjFihLI/PWvMGdOmei3ZRjTihW9+15bbVW2kSNLOHPAAbDZZr37HpIKgxpJkiSpn/jMZ+pdgWrhmWfg+uvhsstg/vy+eY9ddoHdd4cJE2D77Z1TRqolgxpJkiSpnzj22HpXoN62aBE89dSq7b774LHHen7foUPLSktDh5ZlsDfdtMwnM24c7LBD2UuqD4MaSZIkSWoAmfD002UI0+zZZeLfe+4p7T2x/vqwzTZlP3487LhjmfB3nXV6p25JvcugRpIkSeonLr+87O1Z0xxeew2mT4fHH4eHHoJ77+29ew8eXCb4PfZYOPTQ0nNGUnMwqJEkSZL6ibPOKnuDmsby6qvw5JPw7LNlst8nnigT/j75ZO+syLTPPrDbbmVy3/Hjy7Clddd1SWypWRnUSJIkSVIve+45mDEDbrutDGHq6fCltrbcEvbeGw4/vAxrktR/GNRIkiRJUg9lwsyZcMcd8Je/wJIlvXv/XXYp21ZbwXbblZ4zkvongxpJkiRJ6qKWYObBB+HRR+Huu+Gll3p+3wjYYAOYNKkMZXrd62CPPWC99Xp+b0nNwaBGkiRJktZi6VKYMweeeaasyvTkk/DXv8ILL/T83iNHwoEHwvbbl238eBg+vOf3ldS8+m1QExHDgH8GPgyMBu4BvpqZ11Rx7XbAd4GDKtc+CfwKOCMze7kToyRJkqRGsnIlPPIITJ0Kt99ewpmezjEzcmSZ8HfcONhkkzKEadNNy2sn/ZXUWr8NaoBzgXcCk4GZwEnAZRFxaGbetqaLImJz4A5gPnAmMA94A/CvwC6U4EeSJElSP5AJL75Yhi+1DGWaORMWLuz5vUeNgoMPLstj77ADDBrU83tK6v/6ZVATEfsB7wNOy8zJlbZfAfcDpwOHrOXyDwEbAgdn5gOVtrMjYgTwvoj4aGYu66vaJUmSpO6aMqXeFTS+FStWDV2aNq30nHnlld6595AhsPvusO++ZclsJ/yV1B39MqgB3gUsA37R0pCZiyPiHOBfImJ8Zs5Zw7UbVPbPtWl/tnLPFb1drCRJkqS+s3gx3Hdf2W64AebN6537RsDWW8NBB8HEibDzzs4vI6nn+mtQsxfwUGa+2qb9DiCAPYE1BTU3AF8BzomIb1CGPh1CGTp1emau7IuCJUmSJPWeBQvgzjvh5pvhrrtKT5qeGDsWNt+8bK97XZljZtttXY1JUu/rr0HNeOCZDtpbwpnN1nRhZl4ZEV+nhDVvaXXoG5n5nY6uiYhPAp8E2HLLLbtVsCRJktRTp55a9pMn17OK+siEJ54ow5keeABmzOhZOLPOOrDnnrDrrnDIISWokaRa6K9BzQigo9WZFrc6vjaPA9cDfwFeBN4EfDsi5mbmT9uenJlnA2cDTJo0qYfzwUuSJEnd8+ij9a6gtpYvL8OZbryx9Jrp7pCmddYpQ5i23XbVtvXWMHhw79YrSdXor0HNa8CwDtqHtzreoYh4H/AzYPvMnF1p/nNEDAJ+FBF/yMyXerVaSZIkSVV58UW4++4yGfAdd8D8+V2/RwTssQdsvz0ccEAJZYb0138ZSWo6/fWvozmU4U9ttbTN7uBYi08D01uFNC0uosxTswelt40kSZKkPpYJDz9c5pqZPh1mzerefcaMKeHMXnvBbrs5lElS4+qvQc0M4HMRsX6bCYX3r+zvWcu1mwBzO2hfp7Lvr//NJEmSpIawdCncc0/pMXPHHd0f0rThhmV+mQMOKCsyOZRJUjPor6HD+cA/Ah8HJgNExDDgZOCWlt4yEbEusCXwQma+ULn2YeDoiNg2M1uP8n0/ZWnue2vyJ5AkSZIGkOeeK/PMTJtWQpolHc04WYWddy6TAE+aVOaaGTSoV8uUpD7XMEFNRGwIjAWSEpx0Y7RpkZlTI+I84AcRMR54FDgR2IoyfKnFfsB1wLeBb1XafggcB9wSEWdSlud+c6Xtp5n5fHfrkiRJklRkwsyZcPvtMHUqPPlk9+7TsjrTXnvBYYfByJG9WaUk1V7dgpqIGAG8E3grcBBlyFHr488BtwIXAH/OzEVdfIuPAN+p7EdTesIcn5m3rO2izLwxIl5PCW4+A2xEWQXqy5QQR5IkSWpIxxxT7wrWbvHisnT2HXeUgKa7Q5q22aaEMzvvXJbPXm+9Xi1TkuoqMmu7mnREjAG+BPwdsC4lQJkOPAa8BAQlWNka2AfYnbJK00+B0zPzxZoW3EWTJk3KadOm1bsMSZIkqSFkliW0r7gCbrsNli3r+j2GDIHdd4f99y/zzYwZ0/t1SlKtRcT0zJzUtr0ePWqeAB4BvkjpKdPRxL3/JyLGUXrefJwS7mzQ1wVKkiRJ6r6VK8vy2dOmwZ13wlNPdf0eI0eWeWb2378Ma1p33d6vU5IaUT2Cmndk5tXVnlwJcn4K/DQijuq7siRJkqTmNnNm2U+cWJ/3f/BBuOkmuOWW7g1r2m472Htv2Gcf2H57V2mSNDDVPKjpSkjTm9dKkiRJ/d1pp5X9lCm1eb9M+NvfymTAV14Jr7zSteuHDIHddivDmfbbD8aO7Zs6JamZNMyqT5IkSZIaX0s4c911pefM/C6u1breeqXHzAEHlN4zTgQsSaureVATEf/djcsyMz/W68VIkiRJ6lQmPPxwCWZuuw2efbbr99hhB3jrW+HAA0tPGklSx+rxV+QRQNulptYFxlV+fqmyH13ZzwUW1qAuSZIkSa3Mmwc33ADXXANPPtn16/fdF17/+rKUtsOaJKk69ZijZkLr1xGxM3Al8D1gcma+UGkfC5wGfAR4U43LlCRJkgakl14qc87cdhvcfXfpTdMVm29e5p15//tdRluSuqMROh3+J3BZZn6tdWMlsPlqRGxcOccVnyRJkqQ+8NJLcOutcPPN8MADXQtnhg6F3Xcvy2jvvjuMHw8RfVerJPV3nQY1EXFId26cmTdWeeoBwPlrOX4X8P7u1CBJkiSpY8uXlwmBr7226+FMROk1c8QRZWjTiBF9V6ckDTTV9Ki5ntXnlAnazzHTkcFV1jAPOAb4yRqOHwe8XOW9JEmSpAHrjDM6P+e11+DSS+GSS2Du3K7df8cd4Y1vLEtpjxrVvRolSWtXTVBzeJvXw4AfUCYAPhv4W6V9R+ATlIl/v9iFGn4G/HNE/IkyxGlmpX074B8o89N8swv3kyRJkgakiRM7bl+5Eu6/H66/vgxveu216u85ZgwcdRQccghstVWvlClJWotOg5rMvKH164j4N2ApcEBmLm51aEpEnAXcABwLXFVNAZn53YgYBnwBeFubw8uB72fmd6u5lyRJkqQiEx5/vKzadMMN8OKL1V87fjwcdBAccABsv71zzkhSLXVnMuEPAt9tE9IAkJmLIuJ/ga8Cn6/2hpn59Yj4d+BoYMtK85PA1S2rQEmSJElauzPPLEtqb7013HILPPNM9deOHw8HH1y2rbc2nJGkeulOULMesOlajm9KGRbVJZVA5nfdqEeSJEka0ObNK71m/u3fYOHCModMtSZNgve+F3bYwXBGkhpBd4Kaq4FTI2JqZl7U+kBEvBX4HHBlV25YGfp0InAYMA74YmbeHRGjgbcDV2XmrG7UKkmSJPVLy5fDHXfAFVfA3XeXoU4LF1Z37brrlp4z73wnbLZZ39YpSeqa7gQ1nwGuBf4SEbNYNfnvRGAL4FHKJMBViYiNK/fbCZgDjAdGVw6/DHwN2Bn4x27UKkmSJPUrL7wAl10GV14JL79c/XWDBpXeM294Axx4IAwb1mclSpJ6oMtBTWY+ExF7AJ+iLJ3dMvf7Q8C/AT/PzC7MI88PgM2BA4HHgOdbvVdGxJ8py3cb1EiSJGlAeuWVMufMDTfAAw9Uf10E7LxzWbHpoINcUluSmkF3etRQmUj43ytbT70JmJyZd0TERh0cn0lZ9luSJEkaMJYsgdtvL0tq3303rFhR/bXbbQeHH17CmTFj+qxESVIf6FZQAxARg4F9WNWj5gngrszswq8QoExOPKeT44O6XKAkSZLUhGbNKkObrr22+jlnADbdtMw3s9FGZVJhSVJz6lZQExEfAH4EbAK0zA2fwHMR8fnM7MrqTQ8CBwFnr+H4CcA93alTkiRJagZLlpShTZdfDg8+WP11gweX+WaOOQb22ANOO63vapQk1UaXg5qIeCfwa0p48i3K3DQAOwJ/D/w6IpZk5p+rvOWZwM8j4m7gL63eZ0vgG8AbgPd2tU5JkiSp0T3zTAlnrrkGFiyo/rrNN4fDDoNjj4UNN1zVPnlyLxcoSaq5yMyuXRAxHVgMHJ6ZS9scWwe4ARiWmft04Z7fpKzuBDAYWF7ZJ/CNzPxel4qso0mTJuW0adPqXYYkSZIa2KOPwvnnw803V3/N2LFlxabDDoOtty4TBUuSmldETM/MSW3buzP0aWfgC21DGoDMXBYRvwV+2JUbZua3I+Jc4B2UZb4HUZb5/ktmPtqNGiVJkqSGsnQp3HYbXHwxPPRQ5+cDDB1awpmjjoJddjGckaSBoDtBzQLgdWs5vkXlnC7JzCeBM7pRjyRJktSw5s8vkwNffHH5uRoTJsDRR8MRR8D661f/XiecUPZTpnS5TElSg+hOUHMx8NmImJaZ57c+UJm/5h+AqicTjohrgeeBz2Xmcx0cPwr4SmYe0Y1aJUmSpJrLhMceK+HMDTfAsmWdXzN48Kp5Z3bYwd4zkjRQdSeo+RJwAPCHiHgGeLjSvh2lp81DwD914X6HUeaieUNEvDszb21zfBPg0G7UKUmSJNXUvHlw5ZUlnHn66equGT0ajj8ejjsORo3q2/okSY2vy0FNZs6NiL2BTwHHAVtVDj0I/Bg4OzMXd/G2X6bMT3NdRPxjZv5nV+uSJEmS6iETHngA/vIXmDYNVq6s7rqtty4BzRFHlLloJEmC7vWooRLE/Htl6w1PU5bhPhP494jYH/hEZr7WS/eXJEmSetVrr8G115b5YJ55prprBg2C17++9J7ZbTeHN0mS2utWUAMQEYOBfVjVo+YJ4K7MXNGd+2XmMuBTETGVEtjsFhHv6G59kiRJUl+YPRuuuQYuvRRefbW6a9ZfH445Bt70Jhg3rm/rkyQ1t24FNRHxAeBHlPljWr4HSOC5iPh8ZlY9mXBbmfnfEXEP8GdgGnBJd+8lSZIk9YaVK8uwpilTYMaM6q/beWc4/PAySfDw4X1VnSSpP+lyUFNZ2enXwD3AtyiTBwPsCPw98OuIWJKZf+5uUZk5vTIPzh+AD1BCIEmSJKmm5s4tw5uuvBKef766a8aOhaOOgje+sfa9Zz7zmdq+nySp90Vm1zKQiJgOLAYOz8ylbY6tA9wADMvMfaq836HAg5nZ7ldfRAyihD9jM/PbXSq0TiZNmpTTpk2rdxmSJEnqpszSa+ayy+D228vrauy+exnedNBBZaltSZLWJiKmZ+aktu3dGfq0M/CFtiENlHlmIuK3wA+rvVlm3rCWYyuBs7pRoyRJklS1THjyyRLMXH991yYHPuwweMc7YKutOj1dkqROdSeoWQC8bi3Ht6ic06GIOAQgM29s/bozLedLkiRJvWX5crj1VrjwQnj44eqvGz++rNx0+OGw4YZ9Vl6XXX552R97bH3rkCR1X3eCmouBz0bEtMw8v/WByvw1/wCsbTLh64GMiBGVXjnXs/Y5aKJy3A6kkiRJ6hWvvlpCjSlTYN686q6JgEmT4PjjYZ99GnNp7bMqfdENaiSpeXUnqPkScADwh4h4Bmj57mE7Sk+bh4B/Wsv1hwO0Gjp1eDdqkCRJkrpszhy46KIyOfDSdgP5O7bRRiX4OOII2Hjjvq1PkqQuBzWZObeyItOngOOAltG4DwI/Bs7OzMVruf6Gtb2WJEmSetusWSWgaRkaVI3ddoM3vxn22w+GdOfrTUmSuqFbv3IqQcy/VzZJkiSp4axcCdOmleFNM2ZUd80225TJgQ8+uPZLa0uSBN0ManoiIq7txmWZmUf2ejGSJEnqdxYuhKuvhosvhmef7fz8CHj96+GEE2DnnRtz7hlJ0sDRraAmIo4BPgZsA4ymTPjbWmbmtmu4fBBrnzy4w7fs4vmSJEkaYGbNKuHMtdfC4jUOxF9l8OAyMfAJJ5RVnCRJagRdDmoi4gvA94HngDuA+7pyfWYe1tX3lCRJkjrSneFNI0bAW98Kb3kLjBzZp+VJktRl3elR8zngOuC4zFzWy/VIkiRJnVqwAK65Bi65pLrhTQCbbVYmBz7ySFh33b6tr16mTKl3BZKknupOUDMaOK+3Q5qIWAfYERhFGR61msy8sTffT5IkSc3n2Wfhssvg0kurG94EsM8+ZXjT3ns7/4wkqfF1J6i5A9i+twqIiEHAvwKfBtb23cbg3npPSZIkNZcFC+APfyhz0KxY0fn5I0bAUUfBm94Em2/e9/VJktRbuhPUnAJcFhFTM/OPvVDDV4AvAD8Dbgb+F/gS8DIlvEngi73wPpIkSWoyL70EF14Il19eVnPqzOabl3CmPw9vWptTTy37yZPrWYUkqSc6DWoi4q41HPpdRPwUmAW0/V4jM3OfKms4CfhjZv59RGxUaZuemddGxP8AtwFHAFdXeT9JkiQ1ueeeK0tsX3QRLFrU+fkObyoefbTeFUiSeqqaHjWv0H457flAb/0aeB3wg8rPSyr74QCZuTQifg38P0rPG0mSJPVjf/tbGeJ0552dnztkCLzxjWX1Joc3SZL6i06Dmhosp/0isH7lvV6NiFeAbdqcM7qPa5AkSVId/e1v8LvfwfTpnZ87bBi8851w/PEwalTf1yZJUi11Z46a3nY3sG+r19cBp0bE3ZTVnz4L3FOPwiRJktR3MuGuu+D88+H++zs/f5114PDD4YMfhDFj+r4+SZLqoZo5ag6BVctjt7zuTBeW0z4bOCkihmXmEuCrwI2VLYCXgPdXeS9JkiQ1gUcegf/+7+oCmogyOfCHP2xAI0nq/6rpUXM9kBExIjOXtrxey/lROV7VctqZeRFwUavXf42IbYHDKJMU35qZ86q5lyRJkhrXypVlaNOFF8I9VfSXHjcOjjuuhDQGNJKkgaKaoOZwKBP7tn7dlzJzPnBhX7+PJEmS+l5mmRz4nHNg9uzOz9900zIHzdFHw+CqvvpTi2OOqXcFkqSeqmYy4RvW9rq3RMRgYDxl4uB2iypm5r198b6SJEnqG5kwbVqZJPiRRzo/f/PN4e1vh6OOMqDprlNOqXcFkqSeqvtkwhGxIfBD4IPAsI5OoQtDqSRJklRfmTB1Kvzxj9UHNB/6EBx0UJmPRpKkgayayYSv7cZ9MzOPrPLc/wHeDPwemArM78b7SZIkqc4WLYLrroOLL4ann+78/M03h3e8A444AobU/evD/mHmzLKfOLG+dUiSuq+aX4mDWPvkwR3pynchRwOTM/PzXXwPSZIkNYBZs2DKFLj2WliypPPzd965zEGz7772oOltp51W9lOm1LcOSVL3VTNHzWF9XMNc4PE+fg9JkiT1opUr4fbb4dJLq1vBCWDbbeEDHzCgkSRpbRqhk+mZwIcj4qeZubzexUiSJGnNli0rw5vOPx/mzKnumm23hQ9+ECZNMqCRJKkz3QpqImIccBpwGDAO+Ehm3hYRGwGfA36fmX+t5l6Z+cOIGALcHxG/AZ4GVnRw3q+6U6skSZJ6buFCuOwyuOgieOml6q7ZZRd497th770NaCRJqlaXg5qI2Ba4CRgF3ANsA4wAyMwXI+LtlPDm77twvw8A2wPfXsNpCRjUSJIk1dgLL8CFF8KVV5bJgjszYgQceigcdxxss03f1ydJUn/TnR41P6T0eNkZWAg83+b4RcA7u3C//wa2Br6Eqz5JkiQ1hFmzyvCmG26AFe36Ore3+ebw5jfDkUeWsEaSJHVPd4KaI4DvZeaTlaFObT0BvK4L95sEfDczf9iNWiRJktRLMmHqVLjqKrjzzvK6M3vuWXrPHHigw5skSeoN3QlqhgAL1nJ8I2BZF+73VBfPlyRJUi9aubL0nPnjH+Hppzs/PwIOOqgssT1xYt/Xp+qdcUa9K5Ak9VR3gpp7gDcCP2l7ICIGA+8F7ujC/f4Z+JeI+G1mzu5GPZIkSeqGFSvg2mvhz3+uLqAZOhSOOgre9jYYP77Py1M3GJxJUvPrTlDzr8CFETEZOK/SNjYiDgG+AuwGHN2F++0LvAI8EhFXALNov+pTZubnq71hRAyjBEAfBkZTwqWvZuY1XaiLiPgicDpwT2bu2ZVrJUmSGtXy5aUHze9/D88+2/n5I0fCCSeUOWhGjuz7+iRJGsgiqxl83PaiiJOAM4ANgKCsygRlSNQpmfnrLtxrZRWnZWYO7sI9f0eZ0HgyMBM4iTIXzqGZeVuV99gUeBgYBMysNqiZNGlSTps2rdpSJUmSauaVV8oS21deCc+3XQ6iA2PHloDm+ONh+PC+r089d+aZZX/KKfWtQ5LUuYiYnpmT2rV3J6ip3HA9Ss+Z7ShhxqPAlZn5SkQMzswq1gfofRGxH2X1qNMyc3KlbThwPzA7Mw+p8j7nAltS/mwbGtRIkqRmNW9emX/mqqtg6dLOz99ttzL/zF57waBBfV+fes8JJ5T9lCn1rUOS1Lk1BTVdHvoUEV/NzH/JzIXABR0cHw6cD7y5inuNAM4CLsnMP3W1ljV4F2Vy4l+0NGTm4og4hzIXzvjMnNNJXfsBH6L0wpncS3VJkiTV1KxZ8Je/lHloqllie/fd4f3vh1137fvaJElSx7ozR80/R8SSzPxR2wMRsT5wCbB3NTfKzNci4t3Ard2oY032Ah7KzFfbtN9BGaa1J7DGoCYiAvhP4H8yc0a4zqQkSWoyDz4If/gDTJ9e3fl77gkf+hDssEOfliVJkqrQnaDmM8BZEbE0M/+jpTEiNgIuByYCx3ThfrcA+9GqB0wPjQee6aC9JZzZrJPrPwLsDLyt2jeMiE8CnwTYcsstq71MkiSp12TC/feXIS+3VTEjXwTsvXfpQWNAI0lS4+hyUJOZP42IocC/RcSyzPxJRGwOXA2MAQ7PzBlduOUpwBUR8U3gZ5lZxdoDazUCWNJB++JWxzsUESOB7wPf72x4VGuZeTZwNpQ5aqovVZIkqWeWLoWbb4YLLoDHH+/8/OHD4bjjygpOG2/c5+VJkqQu6k6PGjLzPyphzX9GxFjg5Mq93pCZD3fxdncC6wDfAL4REUtYFaq0esvcqMr7vQYM66B9eKvja/I1YCnwb1W+lyRJUl288gpccglcfHH5uTPrrbdqBafRo/u+PkmS1D3dCmoAMvNHlbDmu5RlrA/NzFnduNWFrFreuzfMoQx/aqulbXZHF0XEeOBU4OvAJq3mphkODI2ICcD8zHypF2uVJEnqkuefL71nrriiuhWcNt0U3vIWOOooGLHGfsXqL7bdtt4VSJJ6qtOgJiL+3MkprwIvAP/eKtzIzHxnNQVk5knVnNcFM4DPRcT6bSYU3r+yv2cN120CDAVOr2xtPV5p/6deqlOSJKlqs2bB+efDDTdUt4LTRhvBu95VetC4xPbAMXlyvSuQJPVUNT1q9mbtPV5eBDavbC3qOU/L+cA/Ah+nsrR2RAyjDM+6JTNnV9rWBbYEXsjMFyhBzNs7uN93gfWA0yg9hyRJkmpm5kz4/e/hjjvKhMGd2WEHeOtb4cADYUi3+05LkqR66fTXd2ZO6OsiKitG/RPwJmCrSvOTwMXA6Zn5YrX3ysypEXEe8IPKcKZHgRMr9z2p1an7AdcB3wa+lZnzgQs6qO1UYHlmtjsmSZLUV/76Vzj33LLUdmcGD4ZDDimTBO+4Y1nRSZIkNae6f89SmfvlZsqy2bdXNoAdKD1j3h8RB2fmk1247UeA71T2o4F7geMz85beqluSJKkvzJoFv/413Hpr5+e2rOD0lrfA2LF9X5sa3wknlP2UKfWtQ5LUfdXMUbMlQGY+1fp1Z1rOr8IPKEOLDszMqW3eez/g8so5763yfmTmYuALlW1N51wPdPp9U2YeVu37SpIkdddjj8Fll8HVV8Py5Ws/d4MNSjhz/PEwcmRt6pMkSbVRTY+aJ4CMiBGZubTl9VrOj8rxwVXWcBQwuW1IA5CZd0TEfwCfrfJekiRJTeVvfys9aGbM6PzcjTaCt78djj0Whg3r89IkSVIdVBPUfJQSvCxr83pN1qGsnlStYcArazk+v3KOJElSv5AJt98O550HjzzS+flbbQVvfjMceSSss07f1ydJkuqnmsmEz13b67Yi4qvAPwP/VWUNM4CPRsQvMnNBm3uNpARDd1d5L0mSpIaVCXffXQKa++/v/PzRo+G97y3z0LjEtiRJA0PdJxMGvgFcBjwUEeewagnsHShLam8MHFun2iRJknps5Uq44YayzPbs2Z2fP3x4GeL0jneUnyVJ0sBR96AmM6+JiOOBHwJfa3N4BnBiZl5b88IkSZJ6aMECuOIKuPRSmDu38/PHjCnhzNFHw7rr9n19kiSp8dQ9qAHIzKuBvSJiU2CrSvOTmflsHcuSJEnqliefhAsvLL1oli7t/PxttimrOB16KAxpiE9nalaf+Uy9K5Ak9VRDfRSoBDOGM5IkqeksXw633gpXXgn33FPdNVtsASeeCPvtBxF9W58GhmOdMECSml5VQU1E7N6Fe27a1SIiYjBwDLANMJqyxHdrmZnf6ep9JUmS+tq8eXDJJWWI0/z51V2z/fbwznfCAQc4SbAkSVpdtT1qZrD2Jblbiy6cS0RMAv4EvI72AU2LBAxqJElSQ1i5Eu66Cy6/HO68s7zuTARMmlSW2d5rL3vQqG9cfnnZ27NGkppXtUHNyX1Yw38BI4C3ATdl5st9+F6SJEnd9sILcPXVpffMCy9Ud81665XJgY8/HsaP79v6pLPOKnuDGklqXlUFNZn5P31Yw+7AVzNzSh++hyRJUresWAHTp5eeCtOmQVbZb3izzcoEwUce6RLbkiSpeo0wmfDTrHnIkyRJUl0sWVKW1b7ooup7zwwZAvvvX4Y37bKLw5skSVLXNUJQ80Pg1Ij4aWa+Wu9iJEnSwPb883DxxXDttdVPDjx2bBne9MY3lp8lSZK6qxGCmmHAImBmRPwWmAWsaHNOZuZ/1rwySZI0IGTCQw/BhReWJbarGd4UAfvuW+YC2XtvGDy47+uUJEn9XyMENZNb/XzqGs5JwKBGkiT1qgULSs+Za6+Fxx6r7ppx40rPmaOOsveMJEnqfY0Q1Gxd7wIkSdLAsXJlmRz42mth6lRYtqy66/bbr6zctNdeMGhQ39YoSZIGrroHNZn5ZL1rkCRJ/d/SpWVZ7b/8BebOre6aiBLQfOADsM02fVuf1BumuI6qJDW9mgc1EXEP8H3gvMxcXuU1Q4D3Al/MzD36sj5JktS/zJ8PV10FF1xQ/eTAY8bAm95UJggePbpPy5MkSVpNPXrU/AE4EzgzIi4ArgbuAh7PzKUAETGMMiRqEnAU8BbKPDU/qkO9kiSpCT3zDPzud3DzzbCi7TIFa7DDDiWgecMbylLbkiRJtVbzjyCZ+b2IOBP4OHAicDIlhCEiFgNBWQmKys/3A98B/jszq/weTJIkDUSZMGMGXH453HZbdas3bbABHHlk6T2zxRZ9XqLUp049tewnT65nFZKknqjLd0WZ+Qrwb8C/RcQE4PXAjsBGlVNeBB4CbsvMx+tRoyRJah4rVsDVV8Of/wyzZ3d+fgRMmrRqaW17z6i/ePTRelcgSeqpun8sycwngCfqXIYkSWpCS5fCDTfAeefBnDmdnx8BhxwC73oXTJjQ5+VJkiR1Wd2DGkmSpK566aWygtPFF1c3QfDIkaX3zBvfCJtu2vf1SZIkdZdBjSRJahovvwy//jVccw0sr2LtyDFj4O1vLyHN8OF9Xp4kSVKPGdRIkqSG9/TTcOGFcO21ZbhTZ/bcE447Dvbbz/lnJElSc/GjiyRJalgPPliW2L777urO33tv+MAHyjLbkiRJzcigRpIkNZQVK+Dmm8sS2/ff3/n5gwbBwQfD294G223X5+VJDe2YY+pdgSSppwxqJElSQ5g/v4Qzl18OL7zQ+fnrrQdvelMZ4jR2bN/XJzWDU06pdwWSpJ4yqJEkSXX1xBNw0UVw/fWwbFnn56+3Xlm96Z3vhFGj+ro6SZKk2jKokSRJNbdgAUydCldeWeahqcb48aUHzRvfCCNG9G19UrOaObPsJ06sbx2SpO4zqJEkSTXzzDNw6aVw2WXV9Z4B2HxzeNe74PDDYfDgvq1PanannVb2U6bUtw5JUvcZ1EiSpD718stw441laNMjj1R3zaBBsM8+8I53wC67QERfVihJktQ4DGokSVKvW7IEbr8drruuLK29cmV11623Hhx7bBniNG5c39YoSZLUiAxqJElSr8iEBx4oS2tffz0sXFj9tVttVVZvOvJIGD68z0qUJElqeAY1kiSpRxYtKj1nLrkEZs2q/rphw+Coo+DQQ2HHHR3eJEmSBAY1kiSpGzLh4Yfh2mvLtnhx9dduu22ZGPiww1xeW5IkqS2DGkmSVLVFi8qwpssvh8cfr/66ceNKMHP44bDFFn1VnSRJUvMzqJEkSWu1dCnceWfZbrml+t4z66wDhxxShje5cpNUG2ecUe8KJEk9ZVAjSZLayYT77iu9Z265pfSkqdauu8Ib3wj77VdWcZJUOxMn1rsCSVJPGdRIkiSghDNPPgk33AA33gjPP1/9tUOHlp4zxx9fVnCSJElS9xjUSJI0wD3zTOk1c+ONJajpih12gGOOgde/3t4zUiM488yyP+WU+tYhSeo+gxpJkgagllWbzjsPpk7t2rUjRpRJgY87DiZM6JPyJHXTFVeUvUGNJDUvgxpJkgaQZ58tPWeuvbb0pKnW8OFw4IFl22uv8lqSJEm9z6BGkqR+bsWKMjHwxRd3rfdMBOyxBxx9dJkY2HBGkiSp7xnUSJLUD7UMbbrlljI58Lx51V+7005w6KFw0EGw4YZ9VqIkSZI6YFAjSVI/MmdOWVL7uuvKz9UaMwbe+tYSzmyySZ+VJ0mSpE4Y1EiS1OReegluu62EMw891LVrd9sNjjgCDjmkLLEtSZKk+jKokSSpCb3wAtx8M9x6awlnMqu/duzYMu/MkUfae0bqb7bdtt4VSJJ6yqBGkqQmsHw5/PWvMG0a3HknPP10164fPBgmTSrLau+/PwzxE4DUL02eXO8KJEk95cc0SZIa0NKlZTLgRx6B++8v26JFXbtHRBnadMghZVntDTbom1olSZLUewxqJElqAJnw5JOl18w998D06bBkSffutdVWpefMoYeWYU6SJElqHgY1kiTVycKFMGMG3HsvTJ0KL77Y/XttvnnpNXPIITBhQulNI2ngOeGEsp8ypb51SJK6z6BGkqQaeu65MgHwHXfAAw90bRLg1iJg663LfDNveAO87nWGM5IkSf2BQY0kSX1o4cIyv8zdd5feM8880/17jRgBe+8N++4L++wDG27YW1VKkiSpURjUSJLUixYvLvPMPPxwCWceeghWruzevdZfH/bcE7bfHnbeuSy762pNkiRJ/Zsf9yRJ6oFnny1DmB5+uIQyTzzR/WBm8GDYZZeyUtOuu8KOOxrMSJIkDTR+/JMkqUorVpSVmR56CP72t7KfPbtn99x44zKcaffdy3699XqnVkmSJDUngxpJktbguedKGPPYY6XHzCOPdH/J7BYRZQjTAQeUVZq22MJJgCVJkrSKQY0kScD8+fDoo2Xo0qOPlh4zzz3XO/feeGPYa68y38wee8DIkb1zX0lq6zOfqXcFkqSeMqiRJA0oS5fCrFllCNNTT8HTT5dg5oUXeu89xo0rc8xsv30JaDbbzF4zkmrj2GPrXYEkqacMaiRJ/VImzJsHM2eWIUstwcycOeVYb9p++zLHzA47lJ/HjOnd+0uSJGngMKiRJDW1FStg7twyqe+cOfDMMyWUeeIJeOWV3n+/9dcvgcyOO5b9xIkOZZLUOC6/vOztWSNJzcugRpLU8BYvLmHM88+XMGbOnFXBzHPPwfLlffO+EbDddrDTTrDNNiWYcRiTpEZ21lllb1AjSc3LoEaSVFeLF8PLL8NLL5V5Ylq2lmDm+edhwYK+r2PQoLIC08SJsNVWZWWm7baDESP6/r0lSZKkFv0yqImIYcA/Ax8GRgP3AF/NzGv68lpJGugyYdEiWLgQXn21bK+8UlZUar21BDMvvQSvvVb7OseNK2HMlluW7XWvgwkTYNiw2tciSZIktdYvgxrgXOCdwGRgJnAScFlEHJqZt/XhtZLUNDLL/C4rVpShQ8uWldBk8eJV22uvrdoWLVq1b7u1hDKLFtX7T7W6IUNKALPddqWHzIQJpdfMuuvWuzJJkiSpY/0uqImI/YD3Aadl5uRK26+A+4HTgUP64toWr74KN97Ysz9Di2pXJanmvN5e4aQ3axtI79nItdXjPRu5tnq95/Llq4KTtvu1HevOfsWK7v25G9EGG8D48WX+mJZt661L25B+95tOkiRJ/Vl//Pj6LmAZ8IuWhsxcHBHnAP8SEeMzc04fXAvAs8/CD3/Y4z+DJKmVQYNg7NgyZGnjjVeFMS3hzHrr1btCSZIkqXf0x6BmL+ChzHy1TfsdQAB7AmsKW3pyrSSpGwYPhg03hNGjYcyYVYHM2LEllBk3rrQPHlzvSiVJkqS+1x+DmvHAMx20twQsm/X2tRHxSeCTlZdLLr447q+iTqkjY4EX6l2EmpLPjrrLZ0c94fPToCLqXUGnfHbUXT476olGe3626qixPwY1I4AlHbQvbnW8V6/NzLOBswEiYlpmTqquVGl1Pj/qLp8ddZfPjnrC50fd5bOj7vLZUU80y/MzqN4F9IHXgI4WWB3e6nhfXCtJkiRJktQj/TGomUMZwtRWS9vsPrpWkiRJkiSpR/pjUDMD2DEi1m/Tvn9lf08fXdvi7CrOkdbE50fd5bOj7vLZUU/4/Ki7fHbUXT476ommeH4iM+tdQ6+KiP2B24HTMnNypW0YcD/wXGYeXGlbF9gSeCEzX+jKtZIkSZIkSX2h300mnJlTI+I84AcRMR54FDiRMpvySa1O3Q+4Dvg28K0uXitJkiRJktTr+l1QU/ER4DuV/WjgXuD4zLylj6+VJEmSJEnqtn439EmSJEmSJKlZ9cfJhGsuIoZFxOkRMTsiXouI2yPiyHrXpcYXEZMi4i8R8WTl2Xk2Ii6PiNfXuzY1h4jYNyIuiYiXIuLViLgnIk6qd11qbBFxQERcU3lm5kfEBRGxbb3rUmOJiPER8f2IuC4iFkRERsRhbc7ZKCK+EBE3RcTciHg5Im6LiHfXp2o1gmqencp5T1SOtd2+X/uq1Si68PwMj4ivRMSDEbEoImZFxG8jYvvaV616q3wmPisi/hoRCyPiqYj4fURMbHPeeyPi1xHxcOXZur5OJa9Vfx36VGvnAu8EJgMzKfPZXBYRh2bmbfUrS01gW8r/D39OWR5+Q+CDwI0RcVxmXlXH2tTgIuI44ELgeuDrwDJge2CLOpalBhcR+wI3AE8A36R8afNp4KaI2Cszn6tjeWosOwBfony2uRfo6EuEA4F/AS4Fvgssp3wm+mNEfCMzv1OjWtVYqnl2WkynfIZu7f6+KUtNotrn53+Bt1FW8bkbeB3wGeCYiNgpM5/v+1LVQL4EHAScR3luNgVOAe6OiP0y88HKeX8P7ANMAzaqR6HVcOhTD0XEfsBUVl8pajjlF8zszDykjuWpCVVWJHsMmJaZb653PWpMETEKeBj4fWZ+rt71qHlExGXAvsB2mflSpW085Xk6JzNPrWN5aiARMRIYmpkvRsTbgL8Ah2fm9a3O2RpYmZlPtmoL4GpKiLNRZr5W08JVd9U8O5XzngBmZObbal2jGleVf/dsAjwL/Cgzv9Cq/c3AFOCjmfnLmhauuqqMSJiWmUtbtW0H3Ef5vHxSpW0Lyr/TV0TEDODlzDys9hWvnUOfeu5dlG+xf9HSkJmLgXOAgysffqWqZeYiYC6ld420Jh+gPCPfgPKhpvKPI6kzBwFXtoQ0AJk5h9LL5j11q0oNJzMXZOaLnZzzeOuQptKWwAXACGBCnxWohlXNs9NaZRqBdfuyJjWPKp+fDSr7tr1An63sDYgHmMy8tXVIU2l7BHgA2KlV26zMXFHr+rrKoKbn9gIeysxX27TfAQSwZ80rUtOp/CN7bETsEBHfA3YFrql3XWpoRwEPAcdHxCzgFWBeZUz34PqWpgY3jI4/wC4CxvsFg3rJppX9C3WtQs3gjcBCYGFEPBoRn6x3QWoKjwOzgM9HxAkR8bqIOAD4d+BBytBwDXCVLzE3oQl/FzlHTc+NB57poH1OZb9ZDWtR8/olZUw/wFLgp8D36leOmsBEylw05wI/oIzNfjNlfO5w4NR6FaaG9zfgwIgYlJkrASJiKLB/5fhmrPodJnVZRIwBPg5cn5lz612PGtq9wE2UoZfjgE8AP4uIMZnphMJao8xcHhHvAn4LXNTq0O3AIQ65VMUHgc2Br9a7kK4yqOm5EcCSDtoXtzoudebbwM8ok6B9mPKN9zp0/GxJAOsDo4F/yszTK21/joj1gU9HxHczs+m+PVBN/BfwE+DnEfFjSu/ar1G+eAB/b6kHImIQ8BtgFPDZOpejBpeZb2n9OiJ+CdwMfD0ifpKZ8+tTmZrES5Qvqv5ImTN0IvBl4PyIOCYz/Rw9gEXEjsBZlL9T/rfO5XSZQ5967jXKP6rbGt7quLRWmXlfZl5VmfTsGMpM5OfWtyo1uJa/W37Xpv03lJBvv9qWo2aRmS099j5MGbd9H2UFuh9UTmk7lFfqiv+k/B47OTPvq3cxai6VeSMmA+tSJqOWOlRZVOEm4ObM/EpmXpiZP6b0UD8U+EhdC1RdRcSmwCWUMO/dLT2Im4lBTc/NYdW3kK21tM2uYS3qBzJzGWVc7Tsiwm+2tSYtQ1PaTqLX8np0DWtRk8nMr1LGbL8B2D0z96V8Jkjg0XrWpuYVEd+kLPX+xcxsGyJL1ZpV2Y+paxVqdO+k/B5rPeyJzLyBMm/fQfUoSvVXCfEuo/TsPCYzn+3kkoZkUNNzM4AdK8MNWmsZ639PbctRPzGCMhn1yHoXooY1vbLfvE376yp754XQWmXmS5l5c6teD0cBd2TmgnrWpeYUEZ8BvgWckZk/qnM5am7bVPb+HtPabFLZr7aAQmXy2ME4xceAFBHDKcuzbw+8OTP/VueSus2gpufOpwwz+HhLQ0QMA04GbslMe9RojSJiXAdtGwDvBmZl5vO1r0pN4rzK/mMtDZUPJx+nrJ5xez2KUnOKiPcC+1KGHEhdUnl+/oMy9PLzdS5HTSIixlTmNGrdNhz4ArAAuK0uhalZPFzZv69N+1uA9Shz12gAqax6+gfKsMl3Z2ZTfxY2aeyhzJwaEecBP6gsafoocCKwFXBSPWtTU/hDRCwGbgWepaziczKlV0TbXzzS/8nM6RHxK+DLEbExcBfwJsrcEF/MzFfqWqAaVkQcAXwFuBJ4kfKB5iTgN5n5+zqWpgYUEV+r/LhTZf/hiDgYeDkzz4yI/YBfUZ6la4APlsz4/1yVmW2HaGoA6OzZofyD+qsRcT7wBLAR5TP09sDfZ6bzZQ1gVTw/UyjzrH07IramTCa8HXAKZUXeX9a4ZNXfjyl/r0wBxkTEh1odezUzLwCIiEOAQyrtmwCjWj1vF2XmvTWqd60iM+tdQ9OrpP/fAT5EmRfiXuArmXl1XQtTw4uIj1ImO9uZ8uy8TOkJ8aPKGFtpjSpLKn+d8sF2U+AxyrCDn9W1MDW0iNiOsgrCXpThlY8APwfObMbJ9tS3ImJNHxSfzMwJEXESa/8H0eGZeX2vF6aGV8Wzsw9luNxelKW5l1C+dPhRZl5cmyrVqDp7firnjKZ8DnoT5UvyBcBVwJcz88la1KnGERHXUyaS7kjr5+ZbwDfXcN7JmXlub9fWHQY1kiRJkiRJDcI5aiRJkiRJkhqEQY0kSZIkSVKDMKiRJEmSJElqEAY1kiRJkiRJDcKgRpIkSZIkqUEY1EiSJEmSJDUIgxpJkiRJkqQGYVAjSZLUSyLiWxGR9a5DkiQ1L4MaSZKkBhER34mIFRGxTZv2iIgLImJJRBxUr/okSVLfM6iRJElqHGcBy4HPtmn/OvBW4LOZeUvNq5IkSTVjUCNJktQgMvNZ4PfARyNiA4CIeBPwLeDnmfmzOpYnSZJqwKBGkiSpD7XMWxMRW0fEryJifmX7ZUSs28ElZwAjgY9FxHbAb4DbgVNqWbckSaoPgxpJkqTa+BMwAvgn4I/AScA3256UmTOA6ynDny4AFgHvzMyltSlTkiTV05B6FyBJkjRA3JmZn2p5EREbAR8DvtTBuWcAFwJLgcMzc05tSpQkSfVmUCNJktSBiBgEDK3m3MxcXMVpP23z+ibg7RGxQWa+0ubYTpX9fZl5azU1SJKk/sGhT5IkSR07BHitmi0ixlZxv6favH6psh/dujEijgO+BzwC7BMR+3X3DyBJkpqPPWokSZI69hBwcpXnLqjinBVraI//+6FMHvxb4FbKctyPAacB76+yDkmS1OQMaiRJkjpQWSr73Fq9X0SMpEwevBB4V2bOi4hfAJ+LiC9k5tO1qkWSJNWPQ58kSZLqLCIC+BWwLWWFp+cqh/6T0uPmH+pVmyRJqi2DGkmSpPr7BvA24NOZObWlMTOfBP4MfCIi1qtTbZIkqYYMaiRJkurrLcA3gZ9k5n93cPwMyoTDJ9WyKEmSVB+RmfWuQZIkSZIkSdijRpIkSZIkqWEY1EiSJEmSJDUIgxpJkiRJkqQGYVAjSZIkSZLUIAxqJEmSJEmSGoRBjSRJkiRJUoMwqJEkSZIkSWoQBjWSJEmSJEkNwqBGkiRJkiSpQRjUSJIkSZIkNQiDGkmSJEmSpAZhUCNJkiRJktQgDGokSZIkSZIahEGNJEmSJElSgzCokSRJkiRJahAGNZIkSZIkSQ3CoEaSJEmSJKlBGNRIkiRJkiQ1CIMaSZIkSZKkBmFQI0mSJEmS1CAMaiRJkiRJkhqEQY0kSZIkSVKDMKiRJEmSJElqEAY1kiRJkiRJDcKgRpIkSZIkqUEY1EiSJEmSJDUIgxpJkiRJkqQGYVAjSZIkSZLUIAxqJEmSJEmSGoRBjSRJkiRJUoMwqJEkSZIkSWoQBjWSJEmSJEkNwqBGkiRJkiSpQRjUSJIkSZIkNQiDGkmSJEmSpAZhUCNJkiRJktQgDGokSZIkSZIahEGNJEmSJElSgzCokSRJkiRJahBD6l1AfzN27NicMGFCvcuQJEnSADRzZtlPnFjfOiRJnZs+ffoLmTmubbtBTS+bMGEC06ZNq3cZkiRJGoBOOKHsp0ypbx2SpM5FxJMdtRvUSJIkSf3EMcfUuwJJUk8Z1EiSJEn9xCmn1LsCSVJPOZmwJEmSJElSgzCokSRJkvqJmTNXTSgsSWpODn2SJEmS+onTTit7JxOWpOZlUCNJUjctXQpPPglPPAHPPw8vvwyvvgorV0IErLcebLABbLIJbL45bL01rL9+vauWJElSIzOokSSpC555Bm6+GWbMgIceguXLu3b9llvCHnvA/vvDLrvAEH8TS5IkqRU/HkqS1ImlS+H66+Gyy3o+98NTT5VtyhQYORIOPxze+EbYaqteKVWSJElNzqBGkqQ1WLoULr4Y/vKXMqypty1YABddVLZJk+C974Udd+z995EkSVLzMKiRJKmNTLjpJjj3XJg7tzbvOW1a2XbfHU48EbbfvjbvK0mSpMZiUCNJUisvvABnnVVCk2qMGQPbbluGLo0ZUyYPHjy4TCj86qswbx7Mng2PPVbmt+nMvffC5z8PRx9dAptRo3r255EkSVJzMaiRJKni1lvhP/4DFi5c+3nbbAOHHQb77ltWc4qo7v7z58Pdd8Ptt8Odd5ahVWty1VWlno98BI47rvr3kDSwnXFGvSuQJPVUZGa9a+hXJk2alNOq/RpWktQQli8vw5wuvHDN50TAG94Ab387TJzY8/dcuBCuuw4uuACee27t5+6xB3zuczBuXM/fV5IkSY0hIqZn5qR27QY1vcugRpKay6JF8K//WpbbXpN994WTT4Yttuj991+xAm68Ef7wh7UPjRoxAj71KTjiCHvXSJIk9QcGNTViUCNJzePFF+Fb34Innuj4+OjR8OlPwwEH9H0tK1bApZfCb36z9qFXhx9eaho+vO9rktR8zjyz7E85pb51SJI6t6agZlA9ipEkqd6efx7+6Z/WHNIccAD813/VJqSBMgHxCSfAz35WJhJek+uug//3/+Cpp2pTl6TmcsUVZZMkNS+DGknSgPPcc/DlL8Ozz7Y/FgEf/Sh85Suw/vq1r23UKPjsZ+Gf/xnGju34nFmzSlhz7bW1rU2SJEl9z6BGkjSgzJsHX/ta6VHT1vDh8PWvlwmD6z0PzF57lSEMRxzR8fElS8rqLmefXSZDliRJUv9gUCNJGjBefRW++c2Oe9KMHFkmFd5339rXtSbrrQennQanngpDh3Z8zpQp5c+0YEFNS5MkSVIfMaiRJA0Iy5fDv/xLx3PSjBpVQpreWHa7Lxx5ZOk9s6ZVp+69twyFevLJ2tYlSZKk3mdQI0kaEM4+G+6/v317S0+arbaqfU1dseWW8G//VlZ96sizz8I//iNMnVrbuiRJktS7DGokSf3epZfCZZe1bx8+vCzPvaaeKo1m+PAyFOrjH+94Dp3Fi+G734Xzz4fM2tcnqf623fb/s3fn8XGW5f7Hv1eSZu++l1IKbdl3CogiIoqoiKKA+jtuIEf0CCocxQ3BBUXFBTzqcV/Rc1AQhSqLoKLsUPZ9aWnpvqVp0+yZ3L8/rnnOTGZJJpNktnzer9fzmuR+nnnmSpq2yTf3fd1+AADKV02xCwAAYCw99phveZ2qqkq66CJp770LX9NImElveYvPAPr6173vTqpf/cpn2HzoQ1IN/9MD48qVVxa7AgDASDGjBgBQsbZt8zCjvz/93DnnSIceWvCSRs2hh/pSqGyzgW65Rbr0Uqmjo6BlAQAAYIQIagAAFam/X/rWt6SdO9PPvf710hvfWPiaRtvcudI3vykddVTm8w89JH3qU9LWrYWtCwAAAPkjqAEAVKRrrpEefzx9/MADpQ9+MHOPl3LU2OhLuE49NfP5Vaukj39cWrmykFUBKJZTTvEDAFC+CGoAABXnqaek//mf9PGpU6VPf7ry+rZUVUlnn+09aTIFUC0t0mc+k3nXKwAAAJQWghoAQEVpb5e+8Y30vjRmPrNk8uTi1FUIJ58sXXyxVFeXfq6jQ/r856X77y98XQAAAMgdQQ0AoKL87GeZe7KccYZ0yCGFr6fQjjzSGyhPm5Z+rqdH+spXpH/8o/B1AQAAIDcENQCAivHgg9Ktt6aP77uv9P/+X+HrKZZFi7zJcKYdofr7fbeoG24ofF0AAAAYGkENAKAitLdL3/te+nh9vXThhZXXl2YoM2dKX/uatGRJ5vM/+Yn0299KIRS2LgAAAAyOoAYAUBGyLXk6+2xp1qzC11MKJk3ypU7ZlnxdfbX0m98Q1gAAAJQSghoAQNl75JHMS54OPVQ66aRCV1NaGhq8ifDLX575/O9/T1gDVJJzz/UDAFC+CGoAAGWtp0f6wQ/SxxsapI98JPN21ePNhAnSpz4lve51mc8T1gCV4/Wv9wMAUL4IagAAZe2666T169PH3//+8bvkKZOqKum886S3vCXz+d//XrrqKsIaAACAYiOoAQCUrQ0bPGBIdcABLHnKxMx79mQLa665xg8A5evmm/0AAJSvcbYHBgCgUoTgS556eweOV1dLH/4wS56yicIaM+lPf0o/f9VVUnOz9MY3Frw0AKPg+9/3R5Y/AUD5YkYNAKAs3XWX9PDD6eOnniotWFDwcsqKmS8NO/XUzOd/+EPpX/8qaEkAAACII6gBAJSdjg7pJz9JH585U3rnOwtfTzmKwppTTkk/F4L07W9LDzxQ+LoAAADGO4IaAEDZufpqqaUlffyDH5Tq6wtfT7kykz7wAemEE9LPxWLS174mPf104esCAAAYzwhqAABlZf16admy9PGjj/YDw2MmffSjmT93PT3SpZdm3lULAAAAY4OgBgBQVn7+c6mvb+BYba10zjnFqacSVFdLn/ykdPDB6efa2qQvfEHasaPgZQEAAIxLBDUAgLLxyCPSffelj59+ujRrVsHLqSi1tdLnPictWZJ+bsMGn1nT01P4ugAAAMYbghoAQFmIxaSf/jR9fMYM6W1vK3w9laihQbrkEmn27PRzzz4rfetbUn9/4esCkLtlyzIvDwUAlI+KDmrMrM7Mvm5m682s08zuNbPXDPGcI83s+2b2lJm1m9lLZna1mS0uVN0AgHS33CKtXp0+/r73SXV1ha+nUk2Z4kudmpvTz919t/SrXxW6IgAAgPGlooMaSb+UdIGk30j6mKR+STeZ2TGDPOdTkt4m6bb4c34s6XhJD5vZfmNZLAAgs/Z26Te/SR/fZx/pVa8qfD2Vbv586aKLpJqa9HPXXSf9/e+FrwkAAGC8qNigxsyOkvROSZ8MIXwyhPBjSSdIeknS1wd56rcl7RFC+GgI4achhC9LeqWkCfIQBwBQYL/7nTe1TfWBD/iuRRh9Bx4oXXBB5nPf/a4vhQJQes4/3w8AQPmq2KBG0umSeiX9X0eDEEKXpJ9JOtbM5mZ6Ugjh7hBCT8rY85KelMSMGgAosM2bM/dbOP54n1GDsXPccdJ73pM+3tcnffnL0tatha8JwOBWrPADAFC+KjmoOUzSMyGEXSnj90sySYfmeiMzM0mzJfEtKQAU2G9+k3k77ve9rzj1jDdnnOGBTarWVg9rursLXhIAAEBFq+SgZq6kDRnGo7F5w7jXuyTtJun3Iy0KAJC7F1+Ubr89ffzUU323J4w9M+ljH8u8bfeKFdJ3viOFUPi6AAAAKlUlBzUNkjL9nq8r6fyQzGxfSd+XdKekq7Jcc46ZLTez5Vu2bMmnVgBABr/6VXoIMHEi23EXWm2tNxeeNi393B13SNdcU/iaAAAAKlUlBzWdkjJt2FqfdH5QZjZH0l8kbZd0RgihP9N1IYQfhxCWhhCWzpw5M996AQBJHntMevDB9PF3vlNqaip8PePd9Oke1kyYkH7uN7/J/GcFAACA4avkoGaDfPlTqmhs/WBPNrPJkm6SNFnSSSGEjaNbHgAgmxCkX/4yfXzWLOkNbyh4OYjbe29fBpUqBOkb35A2ZFpwDAAAgGGp5KDmEUn7mllzyvjR8cdHsz3RzOolLZO0t6Q3hRDYhBQACuiuu6Tnn08ff+97M8/oQOG86lXeYDhVe7t02WVSV1f6OQCFc9JJfgAAylclBzXXSpog6d+jATOrk3SWpLtCCOvjY41mtq+ZzYi/Xy3pd5KOkS93urfglQPAONbXJ/361+nje+2VefchFN673y0dfnj6+KpV0ne/S3NhoJjOO88PAED5KnhQY2YdZvaOpPfrzew/zWz+aL5OCOE+SddIutzMvm5m50j6u6Q9JH0q6dKjJD0tKfov7VuS3ixf9jTNzN6ddJw6mjUCANLdckvmJTRnneU7EKH4qqqkT3xCmj07/dy//iXdcEPhawIAAKgUxZhRUy+pOun9JknfkC8zGm3vlfSd+ON/yWfYvDGEcNcgzzk0/niKfJen5OPKMagRABDX1SX97/+mjx96qB8oHRMnenPh2tr0cz//ufTEE4WvCYD0wgt+AADKV95BjZm9zswuM7OfxLewlplNNLMTzCzDBp6D3y7fOgYTQugKIVwYQpgbQqgPIRwVQrgt5ZrbQwgWQvhC/P3j4+9nOhaORZ0AAPfnP0s7dqSPn3lmwUtBDvbcM/MSi/5+6Wtfk7ZuLXxNwHh3wQV+AADK17CDGjNrMrNb5UuDLpT0fknz4qe7Jf2PpAx7QgAAkF17u/SHP6SPH3ectGhR4etBbl79aumUU9LHd+yQvvpVqbe38DUBAACUs3xm1HxV0rGS3ilpgZJmw4QQeuR9Yd6Ux31pPQgA49j110u7dg0cq6qS/u3filMPcvf+90sHHJA+/txz0o9+VPh6AAAAyllNHs85XdJ3QwjXmNn0DOeflfSuIe5xvpmdHn87Wt3+JTPbkuHaEEI4LY86AQBloq1N+tOf0sdf8xppt90KXg6GqaZG+tSnpPPPl1paBp675RZp772l172uKKUBAACUnXyCmmmSnh/kfJWkukHOvyRpZvyIrJY0P36kYqYNAFS4666TOjsHjtXUSO98Z3HqwfBNnSp99rPSpz/tW6wn+8EPvJ/NkiXFqQ0AAKCc5LP0aaWkQwY5/xr5dtcZhRAWhhD2HMaxVx41AgDKxPbtmbdzft3rpFmzCl8P8rfPPtIHP5g+3tcnXXZZ5kbRAAAAGCifoObnks42s1OTxoKZTTCzS+T9aX48GsUBACrfNddIPT0Dx2prpXe8ozj1YGROOkk68cT08a1bpcsvl2KxwtcEAABQTvJZ+vQtSQdIuk7StvjYVZKmy5c8/TSEkFNQY2aTJL1C0iJJEyW1SXpB0l0hhLY8agMAlJGtW6WbbkofP/lkadq0wteDkTOTPvQhadUq6fmUhdKPPSZddRXbrQNj6Yoril0BAGCkhh3UhBCCpLPM7OeSTpO0RD4zZ4Wka0MItw91DzOrlnSZpHMlNShp5yh5T5oOM/uupItDCPzuDQAq1NVXp/czqa+XTqOFfFmrrfVeNeef742ik/3hD96r5hWvKEppQMVbvLjYFQAARiqfGTWSpBDCHZLuyPPpv5P0NklPSvrf+OMuSc2SDpJv/f0pSXtK+n/51ggAKF0bNki33po+/uY3S5MnF74ejK5Zs6RPflK65BIppGwLcOWV0oIF0u67F6U0AACAkjbsHjVmtp+ZvXuQ8+8ys30HOf96eUjzHUkHhxAuCyFcH0L4W/zxy/Kw5nuS3m5mbOgJABXof/9X6u8fONbUJL31rcWpB6Pv0EOl9743fbyrS/rKV6SOjoKXBFS8733PDwBA+cqnmfDX5TNesnmHpK8Ncv49kp4LIVwQX0aVJj5+vrxfTYZv8QAA5WztWun229PH3/Y2qbm54OVgDJ12mvTyl6ePr1vnvTQyfycAIF+33OIHAKB85RPUHC3pH4Oc/0f8mmyOlDciHlQ8rPmDpKOGVR0AoORdfXX6D+iTJkmnnFKcejB2zKSPfUyaPz/93L33StdeW/iaAAAASlk+Qc0kSV2DnO+VNGWQ83MkrczxtVbGrwcAVIi1a6V//St9/PTTpYaGwteDsdfYKF10kTeKTnXVVdLDDxe+JgAAgFKVT1DzgqQTBzn/OkmrBjnfLCnXVemdkppyvBYAUAZ+97v02TSTJ0tveENx6kFhzJ8vXXBB+ngI0je+IW3eXPiaAAAASlE+Qc0vJL3ZzC43s4nRoJlNMrNvSDpZ0s+HuAcr0gFgHFq3TvrnP9PHTzst82wLVJaXv9xnTqVqa5Muu0zq6Sl8TQAAAKUmn6DmCkm/kfQJSdvMbKWZrZS0VdLHJV0t6ZtD3OPHZtYy1CHph3nUBwAoUcymwbvf7btBpVqxQvrv/6a5MAAAQM1wnxBv8vteM/uVfJvtPeOn/iLpjyGEvw9xi18N9zUBAOVv3brsOz0xm2b8qK6WLrxQOv98acuWgef+9jdpn30I7oCRWLSo2BUAAEbKsuyQjTwtXbo0LF++vNhlAEDJ+fa3pX+k7Bk4aZL0s58R1IxHzz8vfepTUm/vwPGaGulrX/PABgAAoJKZ2YMhhKWp4/ksfRoVZlZtZnPMjG/PAaDCZZtNQ2+a8WvJEuk//iN9vK/P+9W0tha8JAAAgJIw7KDG3AfN7H4z22pmsQxH3yDPrzKzr0lqlbRO0k4zu97MZuT/YQAAStnvf5/ee2TSJOmNbyxOPSgNJ54ovf716eMtLR7WpM62AQAAGA+G3aNG0uWS/lPSI/KmwtuH+fz3S/qkpDWSbpK0l6RT5L1rTs6jHgBACVu/Pn3Jk0RvGrhzzpFefFF69tmB408/Lf3gB9JHPiKZFac2oBydcoo/LltW3DoAAPnLJ6h5n6TrQghn5PmaH5K0XNJxIYQuSTKzb0k638xmhxA25XlfAEAJyjab5mSieUiaMEH69Ke9ufCOHQPP3XqrtOeeiR88AQAAxoN8etQ0SLp1BK+5SNJVUUgT9yNJFj8HAKgQGzZknk3z1rcymwYJM2Z4WFNdnX7uJz+RHnmk4CUBAAAUTT5BzT8kpXUlHobJkraljEXv8207AFSQ3/1O6u8fODZxovSmNxWnHpSuAw/M3Fw4BN8Fav36wtcEAABQDPkENR+WdKyZfdLMpuT5utn2BGevcACoENlm09CbBtmcdFLmEK+9Xbr0Un8EAACodPkENY9LWiDpq5K2mdkOM2tJOVJnzKT6cfL1kl6Ij1+fx70AACUo22waetNgMGefLR18cPr42rXSN76R/jUFAABQafJpJny9Rjbz5VcjeC4AoAwMNpumoaHw9aB81NR4v5qPf9y/jpI9+KD0y19K739/UUoDAAAoiGEHNSGEM0fygiGEs0byfABA6bvmGmbTIH8TJ0oXX+xhTWfnwHN//KO0cKF0wglFKQ0oeeeeW+wKAAAjlc/SJwAAstqyJftOT8ymQa5231268ELJLP3cd78rPflk4WsCysHrX+8HAKB85bP0SZJkZvMlHSbfxSkt8Akh/HoEdQEAytR110l9fQPHmpuZTYPhO/JI6b3vlX6Vsmi6r0/6ylekb31Lmju3OLUBAACMlWEHNWZWL+8zc5o8oAmSot93JfeuIagBgHFm+3bpr39NH3/zm6XGxsLXg/J32mnS6tXS7bcPHG9rk774RW8wPHFiUUoDStLNN/sjs2oAoHzls/TpMklvk3SRpOPlIc37JL1O0k2SHpV0yCjVBwAoI3/6k9TTM3Csvj7zlstALsykj3xE2nff9HPr1klf/Wr6DC5gPPv+9/0AAJSvfIKa0yX9IoTwdUnRCvF1IYTbQghvktQqiTZmADDOtLVJN96YPv6mNzHjASNTWyt97nPSrFnp5x5/3H8oDSPZjxIAAKCE5BPUzJJ0f/ztaC+GpqTzf5DPuBmSmS0ws6ytJc2swcwW5FEjAKDAbrhB6uoaOFZbK73lLcWpB5Vl8mTpC1+QmprSz912m/SHPxS8JAAAgDGRT1CzSdJ0SQohdEjaLmmfpPOTJNXneK8XJb11kPNvjl8DAChhHR3SsmXp4yedJE2ZUvByUKF231369KelqgzfvfzqV9JddxW+JgAAgNGWT1Bzn6Rjk95fJulCM3uXmb1H0gWS7s3xXhk23RxggqT+4ZcIACikG2+U2tsHjtXUSG/LaX4lkLtDD5U+/OHM5779bem55wpaDgAAwKjLJ6j5L0krzawu/v7F8r40V8l3g9oh6aPZnmxmk+JLnqIlTdOj91OOgyW9U9KGPGoEABRId7c3EU71mtdIM2YUvByMAyedJL01w3zcnh7p0kulzZsLXxMAAMBoGXZQE0K4M4TwsRBCd/z9NZL2k3SYpIMl7RdCeHaQW1wgX870onw77yuT3k8+Hpb0Rkn0rQeAEnbLLdKOHQPHqqqk008vTj0YH848U3rZy9LHW1ulL30pfYYXAABAuagZ7hPM7L2S/hVCWBWNhRD65dtyy8z2MLNXhRB+neUWN8tn4Jikb0v6jaQHU64JktolPRhCeGS4NQIACqO3N3MT11e9Spozp/D1YPyoqpI+/nHvWbNixcBzq1dLl18uXXKJVF1dnPqAYsnULwwAUF6GHdRI+oWk90haleX8y+LXZAxqQgj3yfvcyMwmS/pDCOGJPOoAABTZ3/4mtbQMHDOTzjijOPVgfKmv9zDmP/9T2rZt4LmHHpJ+8APp3HP9axIAAKBc5NOjZqhvd5ok9eVyoxDCFwlpAKA89fVJ11yTPn7MMb47D1AI06Z5WFOfYb/JW26Rrr228DUBAACMRE4zauKNfQ9NGnqlmWV67hRJH5I0WI+a1HtPlfT/JO0laarSg6AQQjg71/sBAArjX//K3LT1He8ofC0Y3/baS/rkJ72RcAgDz/3619LMmdLxxxelNKDgzj/fH6+8sphVAABGItelT2+V9Pn420HSB+NHJi3ypVFDMrOTJF0rn4WzU9L2DJeFDGMAgCLq7888m+bII/2HZqDQjjxS+uAHpR/+MP3cd77jM28OPrjwdQGFltqzCQBQfnINan4o6U/y2S4PSbpI0o0p10QNgFeFEGI53vdbkjZKelsI4fEcnwMAKLK775bWrk0ff/vbC18LEDn5ZGnTJumPfxw43tcnXXaZNxhesKA4tQEAAOQqp6AmhLBJ0iYzq5Z0lqQbQwhbRuH1F0u6kJAGAMpHCNLvf58+fvDB0r77Fr4eINlZZ0lbtkh33jlwvL1d+sIXpG9+02fXAAAAlKrhNhOukvRTSe8epdd/QVLzKN0LAFAAy5dLL76YPk5vGpQCM+mCC6T99ks/t2WL9MUvSl1dha8LAAAgV8MKakIIvZLWDPd5g7hE0ofNjInIAFAGQpB+97v08X33lQ46qPD1AJnU1koXXyzttlv6uZUrpa99TYrlukgbAACgwHLtUZPse5LOMbOfhRBah/NEM/t2huEtkp4xs5vlIVDqt04hhPDxPOoEAIyyxx6Tns2wr9/b3+4zGYBSMXGiL3X6xCekHTsGnnvwQekHP5DOPZevWwAAUHryCWpikvokrTCz30taJakz5ZoQQvhuhueeP8h9T80yHiQR1ABACcg0m2avvaSlSwtfCzCUOXOkSy6RPvMZqadn4LlbbpFmz5bOOKM4tQFj5aSTil0BAGCk8glqrkh6O9sW3UFSWlATQhitJVMAgAJ7+mnp8Qyt39/xDmYloHTtvbf0yU9KX/mKL91L9utfSzNnSscfX5TSgDFx3nnFrgAAMFL5BDV7jnoVAICSl2k2ze67S8ccU/hagOE4+mjpgx+UfvjD9HPf+Y7vAnXwwYWvCwAAIJNhBzUhhNVjUQgAoHStWOF9PVKdcQazaVAeTj5Z2rRJ+uMfB4739UmXXSZdfrm0gK0NUAFeeMEfFy8ubh0AgPzlM6NGkmRm0yS9VtIe8aHVkm4LIbQM4x798mVSg+mStFbSPyR9I4SwIo9yAQAj8Pvfp4/NmSMdd1zhawHyddZZvkX3nXcOHG9vlz7/eekb35BmzChObcBoueACf1y2rLh1AADyl1fPGDP7jDw8uVrS1+PH1ZLWxs/l6kuSHpM3KP6zpCvjx1/iY49I+m9JT0k6S9JDZnZoPjUDAPLz0kvS3Xenj59+ulRdXfh6gHyZ+Q+x++2Xfm7rVm883NZW+LoAAACSDTuoMbMPSfqKfIbL6yUtjB+vl/R3SV82s2xNhlOtlzRD0r4hhLeEED4eP94saX9JsyU9FUJ4q6QDJfVK+vJwawYA5C/TbJrp06UTTih8LcBI1dZKF18s7bZb+rk1a6QvfUnq7i58XQAAAJF8ZtR8RNLNIYSTQwh/DSG8FD/+GkJ4k6RbJH00x3tdKOn7IYSVqSdCCC9I+r6kz8Tff17SjyS9Io+aAQB5WL9e+te/0sdPO02aMKHw9QCjYeJE6YtflKZOTT/3zDPS178uxWKFrwsAAEDKL6hZJF+mlM2f49fkYr6kvkHO90naPen9FyXV5XhvAMAIXXtt+pbGkydLr3tdceoBRsvs2dIXviA1Nqafe+AB6XvfS//aBwAAKIR8gpqtkg4Y5PwB8Wty8aSkD5rZzNQTZjZL0gfj10T2krQxx3sDAEZg82bp739PH3/b26Q6InNUgL32kj73Oakmw9YKt90mXXVV4WsCAADIJ6i5Rh6ufMLMGqJBM2sws49LOkdSho4GGX1CPqvmBTP7uZldFD9+Ien5+LlPxO9fJ+l9km7Po2YAwDD94Q/pyz8mTpTe8Ibi1AOMhYMOkj7xiczbzF9zjXTDDYWvCQAAjG8Whjmv18yaJC2TdLykHvnuT5KHKrXyJsOnhBA6crzfYZK+KOk1kqLgp0vSbZK+EEJ4KOna6hBCSa8aX7p0aVi+fHmxywCAEWlpkf7936Xe3oHj73qX9M53FqcmYCzdeKP0gx9kPnfhhWxFj/Lxwgv+uHhxcesAAAzNzB4MISxNHc8w2XdwIYR2SSeY2VskvVHSgvip2yTdKGlZGEb6E0J4WNKbzaxK0qz48OYQQn+Ga0s6pAGASvHHP6aHNI2N0imnFKceYKy98Y3S9u3S1Venn/v2t6WGBunIIwtfFzBcBDQAUP6GHdREQgjXS7p+tAqJBzP0nwGAItuxQ7rppvTxN71JamoqfD1Aofzbv0mtrdLNNw8cj8Wkr37Vmw8ffHAxKgMAAONJ3kGNmTVKOlbSwvjQKkl3DrbkycwukRQkfSWE0B9/fyghhHBpvnUCAIbnhhuk7u6BY3V10pvfXJx6gEIxkz70IQ9r7r134LneXunSS/3Yd9+ilAfk5Hvf88fzzituHQCA/A27R40kmdknJF0sqVlScvu9XZIuDSF8I8vz+uVBTUMIoSf+/lBCCKE6jxrrJH1J0nskTZX0qKSLQgh/G+J5cyV9TNLRkpbKP8ZXhxBuz+V16VEDoJzt2iW9//1SZ+fA8VNPlc4+uyglAQXX0yN98YvSY4+ln2tqki67zHeMAkpRtER12bLi1gEAGFq2HjXD3vXJzC6UdLmk+yWdIemQ+HFGfOxr8WvShBCqQgjVIYSepPeHOoYd0sT9UtIFkn4jD176Jd1kZscM8bx9JH1K3hw5w7doAFC5/vzn9JBmwgTprW8tTj1AMdTW+rbd++yTfq69XbrkEmnt2vRzAAAAoyGf7bk/IummEMKJIYTrQgiPx48/SDpR0l8lfXRUqxwmMztK0jslfTKE8MkQwo8lnSDpJUlfH+LpD0qaEUJYIinjzCAAqESdndL1GTqPnXiiNG1a4esBiqmhwXvS7Lln+rkdOzzI2bSp4GUBAIBxIJ+gZpqkP2c6Ed/taZl8qVHOzOx1ZnaZmf3EzPaNj000sxPMLJ8fD06X1Cvpp0m1dUn6maRj48ubMgohtIUQtuXxmgBQ1m680Zc+Jauulk47rTj1AMXW3Ow9aXbbLf3ctm3SRRdJW7YUvi4AAFDZ8glq7pH3bsnmCEl353IjM2sys1sl3STpQknvlzQvfrpb0v/Ily0N12GSngkhpPzIofvlPXUOzeOeAFCxurt9S+5UJ5wgzZpV+HqAUjF5svTlL2f+e7Bpk/TZzxLWAACA0ZVPUPMhSceZ2eVmtjAaNLOFZvYNSa+MX5OLr8p3jnqnpAVKakwc72NzjaQ35VHjXEkbMoxHY/MynMubmZ1jZsvNbPkWvlsDUIZuusmXcyQzk04/vTj1AKVkxgwPazItAdy4kbAGAACMrnyCmuXyIOTjklaYWbeZdUtaIek/5SHIcjNrSTqyLSU6XdJ3QwjXSOrJcP5ZSRlWhw+pQT4jJ1VX0vlRE0L4cQhhaQhh6cyZM0fz1gAw5rq6pGuvTR8/7jhp3qjG2kD5mjvXw5qJE9PPEdaglCxa5AcAoHzV5PGc6+VbbI+GaZKeH+R8laS6PO7bmeV59UnnAQDy3jSZZtO84x3FqQcoVbvv7ltzf/azUlvbwHNRWHPZZRK/s0ExXXllsSsAAIzUsIOaEMKZo/j6K+Vbe2fzGklP53HfDfJZP6misfV53BMAKk5nZ+bZNK96lf9QCmCghQsHD2s+8xnpK1+RZs8uSnkAAKAC5LP0aTT9XNLZZnZq0lgwswlmdom8P82P87jvI5L2NbPmlPGj44+P5nFPAKg4f/5z+g+bZtI731mceoByEIU1kyaln9u0SfrUp6Q1awpeFgAAqBD5LH2SJJnZK+T9Y6YqqQlwJITwXznc5luSDpB0naSoj81VkqbLly79NISQT1BzraRPSPp3SVfG662TdJaku0II6+NjjfImxltDCFvzeB0AKFsdHZl3enr1qzNvRwwgYeFCnzlz0UXSzp0Dz23bJn3609KXvkSvEBTeKaf447Jlxa0DAJC/YQc1ZnaYpP+VtEQZApq4IGnIoCaEECSdZWY/lzcWXiyf5bNC0rUhhNuHW1/8vveZ2TWSLjezufH7vU/SHpLOTLr0KEn/kPRFSV+IBs3sc/E394s/vsfMjpXUGkL4Xj41AUCpWbYsfTZNVRWzaYBcDRbW7Nzpy6M+/3lp//2LUh4AAChT+cyo+ZmkWfItuO+TtGPwywcys6sl3SHpLkmPBndHfGw0vVfSpfHHqZIek/TGEMJdOTz30pT33x9/XC2JoAZA2Wtvzzyb5jWv8d1tAORm4ULpa1+TPvc5qaVl4LmODuniiz3IOfzwopQHAADKUD5BzX6SLg4h/CTP13yLpLfLZ93sMrN7Jd0pD2ruDyF05HnfAUIIXZIujB/ZrrldmZdtZZspBAAV4frrPaxJVl3NTk9APnbfXfr61z2s2bRp4LmeHunSS6ULLvAt7wEAAIaSTzPhZyVVj+A1J0k6Rh6g3CrpYPnSo79JajWz+83s22Z2mpmxZwIAjLJduzyoSXXiiexUA+RrzhwPazLtltbXJ33jG9If/iCFUPjaAABAecknqPmspPPMbHE+LxhC6A0h3BdC+HYI4fQQwlx5b5oz5btA1Uv6qKTfS1pvZs/l8zoAgMz+8AdfkpGspkZ6+9uLUw9QKaZP92VQi7N8h/TLX0o/+pHU31/QsgAAQJkZ9tKnEMKNZnahpCfM7C5JayXF0i8LZw/jnislrZR0VXwnptdL+rh85g37JQDAKNm2TbrhhvTx171Omjmz8PUAlWbSJOnLX/blTk8+mX7+L3+Rtm6VLrxQqqsrfH0AAKD05bPr0xvkM19qJR0naVeGy4KknIIaM5sn6RVJxyHypVUr5Vt13zPcGgEAmf3v/3rPjGS1tdIZZxSnHqASNTX51tzf/KZ0T4bvYu67zxsMX3yxNHly4etDZTv33GJXAAAYKQvDXCxtZk/Ll0y9W9LyMMwbmNkhkl6uRDCzh6ROScsl3S0PZu4OIWwdVmElYunSpWH58uXFLgMA0qxdK334w+k9Mk47TTrzzKKUBFS0/n7ppz+Vli3LfH7WLA9rFi4saFkAAKBEmNmDIYSlqeP57Pq0QNInQwgP5FnLw5J6Jd0g6VvyYObREEJfnvcDAOTg179OD2mamqTTTy9OPUClq6qSPvABD2R+9rP085s3+xKoj39cetnLCl8fAAAoTfk0E35I0m4jeM0XJU2QdLJ8m+4zJL3BzKaP4J4AgEE880zmJRhnnCE1Nxe+HmC8MJNOPVX61Ke8aXeqri7pK1+Rfv97doTC6Lj5Zj8AAOUrn6Dmo5LebWZvy+cFQwiLJM2VL516QNLxkq6VtNnMnjWzX5jZB8zsgHzuDwAYKATfbSbV9OnSKacUvBxgXDr2WG8yPHFi5vNXXeU9bbq7C1sXKs/3v+8HAKB85bP0KZq8e42ZtSr7rk9HZLtBCGGTpOvih8ysXtLR8p41L5f0NUlTzGyHpHtDCG/Mo04AgKTlyzPvPvOud3kjYQCFccAB0re+5TtCrVmTfv5f//JeUp/+tDR3buHrAwAApSGfGTU7Ja2Q9C9Jj0lqkbQj5dg5nBuGELpCCP8MIVwmn7HzcUn3Spoi6aQ8agQASOrry9wbY/fdpRNOKHw9wHg3d67PnDnqqMznV66ULrjAd4YCAADj07Bn1IQQjh+tFzezGkmHa+D23LPip/sk3S/prtF6PQAYb268UVq3Ln38fe+TqqsLXw8AqbHRt+e+6irp2mvTz7e3+zKp00+X3v1u/q4CADDe5BTUmNnBw71xCOGxLPc6WYntuY+UVC/J5DNx7pF0pzycuT+E0Dnc1wUAuJ07pf/5n/Tx/ffP/tt8AIVRVeWB6cKF0n/9l9TTk37NtddKzz7rO0NNnVrwEgEAQJHkOqPmEUm57kVg8Wuz/f5nWfxxtbxHzV3x44kQ2O8AAEbLb3/rv5lPZiadc44/Aii+V71Kmj9f+upXpU2b0s8//rj00Y9K//mf0mGHFb4+AABQeLkGNWeN4mu+Q9JdIYT1o3hPAECS1aulm25KH3/ta6VFiwpfD4DsFi2SrrxSuuIK6f7708+3tkqXXCK99a3Se9+beZtvAABQOYxJLKNr6dKlYfny5cUuA8A4FoL/UPfIIwPHGxqkH/2IJRRAqQrBlztddZW/ncmiRb4UarfdClsbAAAYfWb2YAhhaep4Prs+AQBK2P33p4c0kvT2txPSAKXMTDrjDG8kPHly5mtWrJDOP1+67bbsYQ4AAChvBDUAUEG6u6Uf/zh9fM4c6S1vKXw9AIbv4IO9wfChh2Y+39Ulfec70uWXS21tBS0NAAAUAEENAFSQq6+WNm9OH3//+6UJEwpfD4D8TJsmfelL0llnZd+e+847pQ9/WLrvvsLWhtJ2/vl+AADKF0ENAFSIl16S/vjH9PFDDpFe9rLC1wNgZMykt71N+sY3pLlzM1/T2upLpa64Qtq1q6DloUStWOEHAKB8EdQAQAUIQfr+96VYbOB4TY30H//BdtxAOVuyxJc6veY12a/5+9+lc8+VHnywcHUBAICxQVADABXgttukp55KHz/jDHaHASpBQ4MvZ7nwQqmpKfM1LS3SF77g/W3a2wtZHQAAGE0ENQBQ5nbskH7xi/TxefOk008vfD0Axs5xx0n//d/S0rSNPBNuvVX60IekO+5gZygAAMoRQQ0AlLmf/zzzzi8f/rBUW1v4egCMrWnTpEsukT72MamxMfM1ra2+K9SXvpS5wTgAAChdBDUAUMYeeMB7U6Q6/nhvIgygMplJr32t9L3vZd/GW5KWL/fQ9o9/TO9hBQAAShNBDQCUqfZ2/yEtVVOTdPbZha8HQOHNnOmzZs49V6qvz3xNd7fPvPvP/5Seeaaw9aHwTjrJDwBA+bLA4uVRtXTp0rB8+fJilwFgHLjySulvf0sf/8hHpNe9ruDlACiyrVulH/1Iuvfewa979aulM8/0JVQAAKB4zOzBEEJa5zlm1ABAGXrggcwhzeGHSyeeWPh6ABTfjBnSRRdJn/2sNH169uv+8Q/pgx+Urr1W6u0tXH0AACA3BDUAUGba2jIveWpo8Nk0ZoWvCUDpOOYY3xnqlFOy/3vQ1SX96le+ZOq++9gdqpK88IIfAIDyRVADAGUkBOm735VaWtLP/fu/+2/UAaCxUTrnHOmb35T22iv7dRs2SF/+snTxxdLzzxeuPoydCy7wAwBQvghqAKCM3HqrdM896eOHHcaSJwDp9t5buuIK3/lp4sTs1z36qDcbvvxyD28AAEDxENQAQJlYt0768Y/Tx5ubpY99jCVPADKrqpLe8AZvNHzKKf5+NnfcIf3Hf0g//KHU2lqwEgEAQBKCGgAoA729voShuzv93Ec+MnjjUACQfEbNOedI//Vf0sEHZ78uFpP+8hfpAx+QfvMb74sFAAAKh6AGAMrAT3+auTnkiSdKL3954esBUL722MP70nz2s9K8edmv6+qSfvc76eyzCWwAACgkghoAKHH//Kd0443p43Pn+m/HAWC4zHx3qO9/3/vXTJmS/drOzkRgc9VVBDYAAIw1ghoAKGFr1mTeirumRrrwQqm+vvA1AagcNTXev+YnP5He/W6poSH7tZ2d0u9/L73//b619/bthasTAIDxxEIIxa6hoixdujQsX7682GUAqAAdHdInPuFhTaoPfUg6+eTC1wSgsu3Y4WHMjTdKfX2DX1tTI51wgvTWt0rz5xemPgwtWia7eHFx6wAADM3MHgwhLE0bJ6gZXQQ1AEZDf7/3kHjggfRzxx3nAQ67PAEYK1u3StdcI/31r0MHNpJ09NHS294m7bcf/zYBAJArgpoCIagBMBp+9Svp2mvTx3fbTbriisGXJwDAaNm61f8tuuWW3AKbffaR3vQm6RWvkCZMGPv6AAAoZwQ1BUJQA2Ck/vEP6dvfTh+vr/ctuvfYo/A1ARjftm2T/vAH6eabpd7eoa+fPFk66STvfzNjxtjXh4Sor9l55xW3DgDA0AhqCoSgBsBIPPGEdPHFmX9zfdFF0steVviaACCyfbv05z9Lf/mL1N4+9PVm/u/WySdLBx/MsqhCOOUUf1y2rLh1AACGli2oqSlGMQCAdC++KF16aeaQ5j3vIaQBUHxTp/q/R6ef7v1rrr9e2rIl+/UhSPfc48ecOdJrXyu95jXMsgEAYDAENQBQAjZtkj7/ed/pKdVxx0lnnFH4mgAgm4YG6S1v8Zkyd90lXXedtHLl4M/ZuFH6zW+k3/5WOvRQ6cQTvQlxbW1BSgYAoGwQ1ABAkbW2ekizfXv6uX32kT72MZYLAChNNTXSq17lgfLTT/uSqLvvHrzxcAjSww/70dwsHXusP/+AA6SqqsLVDgBAqSKoAYAiam2VPvtZad269HPz53uAw2+bAZQ6M2n//f3Yvt13ibr5Zm9CPJhdu/y6m2+Wpk2TXvlKP/bem4AaADB+EdQAQJFEIc2aNennpk+XvvQlaeLEgpcFACMydar0znf6ks377vPQ5uGHfSbNYFpavOfN9ddLs2f7LJtjj5X23JPQBgAwvhDUAEARtLRIn/tc5pCmqUn64helmTMLXxcAjJbqaunlL/djyxbp73+XbrvNe9UMZdMm6Zpr/Jg505upv+xlPmOnhu9eB7VoUbErAACMFNtzjzK25wYwlLVrfUnT5s3p5xobfeenvfcufF0AMNZCkJ58Urr1VunOO6WenuE9v7lZOvJID20OP1yqrx+bOgEAKIRs23MT1IwyghoAg3nmGV/S1NaWfo6QBsB40tUl3X+/9M9/Sg89NHgD4kxqarwB8RFHeGizYAFLpAAA5YWgpkAIagBkc+ed0hVXZP4NMiENgPFs1y7pnnukf/1LevTRofvZZDJ9ugc2Rxzh2383NY16mQAAjCqCmgIhqAGQKhaTfv1r6brrMp+fPNmXQi1ZUti6AKAUtbZKd93lwc3jj0v9/cO/h5m0eLF04IHSwQd7b5vGxlEvtSSdcoo/LltW3DoAAEPLFtTQjg0AxtCOHdI3vyk98kjm83Pm+FKouXMLWhYAlKwpU6STT/ajrU1avly6915fHtXVlds9QpCef96PP/4xEdwcdFAiuGloGNMPAwCAvBHUAMAYeeAB6Tvf8bAmk0WLpC98wX8oAQCkmzhRevWr/ejp8WVR997r4U1LS+73SQ5urrtOqqqSFi6U9t03ccyZQ48bAEBpIKgBgFHW1SX94hfSjTdmv+YVr5DOP58dSwAgV7W1vuPTkUd68LJ6tfTggz7T5qmnhteMuL9fWrnSj+jf6smTpX328dBmn328Zxj/RgMAioGgBgBGSQj+m94f/1jaujXzNWbSe98rnXYav7kFgHyZ+YyYhQv939POTumxxzy0efhhacOG4d9zxw7fher++xOvMW+ez35cvNgf99rLtwgHAGAsEdQAwChYv1766U99uVM2EydKF14oHXZY4eoCgPGgoUE6+mg/JA/LH388cWzcOPx7hiCtW+fHv/6VGJ81y4ObvfbyLcEXLPA+Y1VVo/OxAABAUAMAI9DSIl19tXTLLYPvTHLEEdLHPiZNnVq42gBgvJoxI9HbRpK2bBkY3GzalP+9N2/24+67E2O1tdL8+YngZo89/HH2bGZPAgCGj6AGAPKwdav0pz9JN98sdXdnv662Vjr7bOkNb+CbdQAolpkzpRNO8EPykP2ZZxLHCy9Ivb3537+nJ9HzJlldnc+2mTcv/ZgyZWz+Xzj33NG/JwCgsCyEUOwaKsrSpUvD8uXLi10GgDHy4ovSDTdIt98+dOPKI46QPvQh30kEAFC6+vr83/couHn22ZHNuslFQ0MixJkzx2ffzJyZeKyrG9vXBwAUn5k9GEJYmjZOUDO6CGqAytPVJd11l3TTTf7N+1CmT5fOOUc65hhm0QBAudq1y2fIrFiReFy71nvXFMLkyd4PJ/mYOdP/j5k2zWfk0BcHAMpbtqCGpU8AkEFPj2/7escdvgPIYMubIo2NvvvIm9/Mlq4AUO6am6WDD/Yj0tXlM29WrJBeesm3CH/pJQ91RtuOHX48/3zm81VV3vds2jQ/pk/3Y8UKb17/pjf5+YkTCXQAoNwQ1ABA3LZtvrXrQw95SNPZmdvzamulN75Revvb/RtiAEBlqq+X9tvPj0gI0vbtHtgkhzcvvSR1dIxdLf39/v/Wtm0Dx6PtxW+5xR/N/P+myZOHPiZN8oCqhp8QAKCo+GcYwLgUgu8C8vTT3o/gscf8m+rhiH5j+aY3+Te3AIDxxywxq+XQQxPjUYCzfr20YYM/Jh89PYWpLwRp504/1qzJ7Tl1dR7Y5Ho0NnrPneiorh7bjwkAKl1FBjVmVifpS5LeI2mqpEclXRRC+NtYPhdAaert9b4Cq1cnjhde8G+g87HXXr6L0/HHs8QJAJBZcoBz4IEDz4XgO09FIc6mTf7Lg82b/e1t2wrXCyeT7m4/Umfr5Kq21gOb1AAn21hdXeajtnbg+wRAAMaLigxqJP1S0mmSrpT0gqQzJd1kZq8KIdwzhs8FUGAheG+AHTuk1lbfNjv6Rjd63LTJp4iPxMSJ0stfLr3uddKSJTQJBgDkzyzRU+agg9LP9/V5SLJ588Bj61YPeFpaxqYvzmjp6fFjx47RvW9NTXp4EwU6tbXShAmJo6Zm4PvZxjId0XU1NR4ORUdNjff7SR6vquJ7AgCjr+KCGjM7StI7JV0QQrgyPvZrSU9I+rqk48biuZEQsm/ZO9hvRkbyW5OhnjtW9y7V1833vmN571J93XzvO9J7x2L+96S314/o7eTHnh7vERMdHR0D3965M9FoMRbLv5bBNDb6zk2vfKV0yCGs2QcAFEZNjW/TPXt29mu6uxOhTUuLBzstLd5MuKfHt/3esUNqby9c3WOtr8+Psez9k4/kMCc12MllvKoqEfhUV/tjNJZ8brD3c7lmsOdEYVPUeNos/Si185Fsb+d6Pnl8qPPFfL3h1jacesaTwT4fg31+cv08jtbnuxJ/7DhdUq+kn0YDIYQuM/uZpK+Y2dwQwoYxeK4k/8/xrW8d8ccAoEj22ks6/HA/9tuPcAYAUJrq6qS5c/1I9sc/+uOPfuSPfX0Df7kx2NHW5jN1irnsqhzFYmP3SyMA41Ml/ghymKRnQgipE0Lvl2SSDpWULWwZyXMBlJmaGmnRIg9k9t1XOuAAacqUYlcFAMDoqalJ9MrJRQg+e3XXrtyP5BmwnZ0EPQAwUpUY1MyVtC7DeBSwzBvt55rZOZLOib/b/ec/2xM51AlkMkPS1mIXgbLE1w7yxdcORoKvnxJVBksc+NpBvvjawUiU2tfPHpkGKzGoaZDUnWG8K+n8qD43hPBjST+WJDNbHkJYmlupwEB8/SBffO0gX3ztYCT4+kG++NpBvvjawUiUy9dPVbELGAOdkuoyjNcnnR+L5wIAAAAAAIxIJQY1G+RLmFJFY+vH6LkAAAAAAAAjUolBzSOS9jWz5pTxo+OPj47RcyM/zuEaIBu+fpAvvnaQL752MBJ8/SBffO0gX3ztYCTK4uvHQoW1ZTezoyXdK+mCEMKV8bE6SU9I2hRCODY+1ihpgaStIYStw3kuAAAAAADAWKi4ZsIhhPvM7BpJl5vZXEkrJL1P3k35zKRLj5L0D0lflPSFYT4XAAAAAABg1FVcUBP3XkmXxh+nSnpM0htDCHeN8XMBAAAAAADyVnFLnwAAAAAAAMpVJTYTLjgzqzOzr5vZejPrNLN7zew1xa4Lpc/MlprZH81sdfxrZ6OZ3WxmLy92bSgPZnakmf3FzLab2S4ze9TMzix2XShtZvYyM/tb/Gtmh5n9ycwWFbsulBYzm2tmXzOzf5hZm5kFMzs+5ZrpZnahmd1hZlvMrNXM7jGzM4pTNUpBLl878etWxc+lHl8rfNUoFcP4+qk3s8+a2dNm1mFma8zsf8xs78JXjWKLf0/8fTN7yszazewlM7vazBanXPcOM/uNmT0X/9q6vUglD6pSlz4V2i8lnSbpSkkvyPvZ3GRmrwoh3FO8slAGFsn/Hv5Evj38FEnvkvQvM3tDCOHWItaGEmdmb5B0vaTbJV0sqVfS3pJ2L2JZKHFmdqSkf0paJenz8l/afFjSHWZ2WAhhUxHLQ2nZR9Kn5N/bPCYp0y8RjpH0FUk3SvqypD7590S/N7NLQgiXFqhWlJZcvnYiD8q/h072xNiUhTKR69fPVZJOle/i87Ck+ZLOlXSSme0XQtg89qWihHxK0iskXSP/upkj6TxJD5vZUSGEp+PX/YekIyQtlzS9GIXmgqVPI2RmR0m6TwN3iqqX/wezPoRwXBHLQxmK70i2UtLyEMKbil0PSpOZTZb0nKSrQwgfK3Y9KB9mdpOkIyUtCSFsj4/NlX89/SyEcH4Ry0MJMbOJkmpDCNvM7FRJf5T06hDC7UnX7CmpP4SwOmnMJN0mD3GmhxA6C1o4ii6Xr534daskPRJCOLXQNaJ05fhvz2xJGyV9M4RwYdL4myQtk/T+EMIvClo4iiq+ImF5CKEnaWyJpMfl3y+fGR/bXf5zeszMHpHUGkI4vvAVD46lTyN3uvy32D+NBkIIXZJ+JunY+De/QM5CCB2Stshn1wDZ/Jv8a+QSyb+pif9wBAzlFZL+GoU0khRC2CCfZfP2olWFkhNCaAshbBvimheTQ5r4WJD0J0kNkhaOWYEoWbl87SSLtxFoHMuaUD5y/PqZFH9MnQW6Mf5IQDzOhBDuTg5p4mPPS3pS0n5JY2tCCLFC1zdcBDUjd5ikZ0IIu1LG75dkkg4teEUoO/EfsmeY2T5mdpmkAyX9rdh1oaS9VtIzkt5oZmsk7ZTUEl/TXV3c0lDi6pT5G9gOSXP5BQNGyZz449aiVoFy8DpJ7ZLazWyFmZ1T7IJQFl6UtEbSx83sFDObb2Yvk/QdSU/Ll4ZjnIv/EnO2yvD/InrUjNxcSesyjG+IP84rYC0oX7+Qr+mXpB5JP5R0WfHKQRlYLO9F80tJl8vXZr9Jvj63XtL5xSoMJe9ZSceYWVUIoV+SzKxW0tHx8/OU+D8MGDYzmybp3yXdHkLYUux6UNIek3SHfOnlTEkfkPQjM5sWQqChMLIKIfSZ2emS/kfSDUmn7pV0HEsuEfcuSbtJuqjYhQwXQc3INUjqzjDelXQeGMoXJf1I3gTtPfLfeE9Q5q8tQJKaJU2V9OkQwtfjY9eZWbOkD5vZl0MIZffbAxTEf0v6gaSfmNm35LNrPyf/xYPE/1sYATOrkvRbSZMlfbTI5aDEhRDenPy+mf1C0p2SLjazH4QQdhSnMpSJ7fJfVP1e3jN0saTPSLrWzE4KIfB99DhmZvtK+r7835SrilzOsLH0aeQ65T9Up6pPOg8MKoTweAjh1njTs5Pknch/WdyqUOKif1v+N2X8t/KQ76jCloNyEUKIZuy9R75u+3H5DnSXxy9JXcoLDMd35f+PnRVCeLzYxaC8xPtGXCmpUd6MGsgovqnCHZLuDCF8NoRwfQjhW/IZ6q+S9N6iFoiiMrM5kv4iD/POiGYQlxOCmpHboMRvIZNFY+sLWAsqQAihV76u9m1mxm+2kU20NCW1iV70/tQC1oIyE0K4SL5m+5WSDg4hHCn/niBIWlHM2lC+zOzz8q3ePxlCSA2RgVytiT9OK2oVKHWnyf8fS172pBDCP+V9+15RjKJQfPEQ7yb5zM6TQggbh3hKSSKoGblHJO0bX26QLFrr/2hhy0GFaJA3o55Y7EJQsh6MP+6WMj4//khfCAwqhLA9hHBn0qyH10q6P4TQVsy6UJ7M7FxJX5B0RQjhm0UuB+Vtr/gj/49hMLPjjwM2UIg3j60WLT7GJTOrl2/PvrekN4UQni1ySXkjqBm5a+XLDP49GjCzOklnSborhMCMGmRlZjMzjE2SdIakNSGEzYWvCmXimvjj2dFA/JuTf5fvnnFvMYpCeTKzd0g6Ur7kABiW+NfPf8mXXn68yOWgTJjZtHhPo+SxekkXSmqTdE9RCkO5eC7++M6U8TdLapL3rsE4Et/19HfyZZNnhBDK+nthksYRCiHcZ2bXSLo8vqXpCknvk7SHpDOLWRvKwu/MrEvS3ZI2ynfxOUs+KyL1Px7g/4QQHjSzX0v6jJnNkvSQpJPlvSE+GULYWdQCUbLM7ARJn5X0V0nb5N/QnCnptyGEq4tYGkqQmX0u/uZ+8cf3mNmxklpDCN8zs6Mk/Vr+tfQ3Se/yzPj/3BpCSF2iiXFgqK8d+Q/UF5nZtZJWSZou/x56b0n/EUKgX9Y4lsPXzzJ5n7Uvmtme8mbCSySdJ9+R9xcFLhnF9y35vyvLJE0zs3cnndsVQviTJJnZcZKOi4/PljQ56evthhDCYwWqd1AWQih2DWUvnv5fKund8r4Qj0n6bAjhtqIWhpJnZu+XNzvbX/610yqfCfHN+BpbIKv4lsoXy7+xnSNppXzZwY+KWhhKmpktke+CcJh8eeXzkn4i6Xvl2GwPY8vMsn2juDqEsNDMztTgPxC9OoRw+6gXhpKXw9fOEfLlcofJt+bulv/S4ZshhD8XpkqUqqG+fuLXTJV/H3Sy/JfkbZJulfSZEMLqQtSJ0mFmt8sbSWeS/HXzBUmfz3LdWSGEX452bfkgqAEAAAAAACgR9KgBAAAAAAAoEQQ1AAAAAAAAJYKgBgAAAAAAoEQQ1AAAAAAAAJQIghoAAAAAAIASQVADAAAAAABQIghqAAAAAAAASgRBDQAAwCgxsy+YWSh2HQAAoHwR1AAAAJQIM7vUzGJmtlfKuJnZn8ys28xeUaz6AADA2COoAQAAKB3fl9Qn6aMp4xdLeoukj4YQ7ip4VQAAoGAIagAAAEpECGGjpKslvd/MJkmSmZ0s6QuSfhJC+FERywMAAAVAUAMAADCGor41Zranmf3azHbEj1+YWWOGp1whaaKks81siaTfSrpX0nmFrBsAABQHQQ0AAEBh/EFSg6RPS/q9pDMlfT71ohDCI5July9/+pOkDkmnhRB6ClMmAAAopppiFwAAADBOPBBC+GD0jplNl3S2pE9luPYKSddL6pH06hDChsKUCAAAio2gBgAAIAMzq5JUm8u1IYSuHC77Ycr7d0h6q5lNCiHsTDm3X/zx8RDC3bnUAAAAKgNLnwAAADI7TlJnLoeZzcjhfi+lvL89/jg1edDM3iDpMknPSzrCzI7K9wMAAADlhxk1AAAAmT0j6awcr23L4ZpYlnH7vze8efD/SLpbvh33SkkXSPp/OdYBAADKHEENAABABvGtsn9ZqNczs4ny5sHtkk4PIbSY2U8lfczMLgwhrC1ULQAAoHhY+gQAAFBkZmaSfi1pkXyHp03xU9+Vz7j5SLFqAwAAhUVQAwAAUHyXSDpV0odDCPdFgyGE1ZKuk/QBM2sqUm0AAKCACGoAAACK682SPi/pByGEn2c4f4W84fCZhSwKAAAUh4UQil0DAAAAAAAAxIwaAAAAAACAkkFQAwAAAAAAUCIIagAAAAAAAEoEQQ0AAAAAAECJIKgBAAAAAAAoEQQ1AAAAAAAAJYKgBgAAAAAAoEQQ1AAAAAAAAJQIghoAAAAAAIASQVADAAAAAABQIghqAAAAAAAASgRBDQAAAAAAQIkgqAEAAAAAACgRBDUAAAAAAAAlgqAGAAAAAACgRBDUAAAAAAAAlAiCGgAAAAAAgBJBUAMAAAAAAFAiCGoAAAAAAABKBEENAAAAAABAiSCogSTJzG43sy4z2xU/bip2TQAAAAAAjDc1xS4AJeXMEMLVxS4CAAAAAIDxihk1AAAAAAAAJYKgpoSY2Vwz+5qZ/cPM2swsmNnxg1xfZ2ZfN7P1ZtZpZvea2WtGUMJ3zWyLmd1qZgeP4D4AAAAAACAPBDWlZR9Jn5I0X9JjOVz/S0kXSPqNpI9J6pd0k5kdk8drf1LSnpIWSLpV0o1m1pzHfQAAAAAAQJ4IasaQmU03s1MHOf8+M6tNGnpQ0owQwhJJ3xji3kdJeqekT4YQPhlC+LGkEyS9JOnrSdfdHp+Zk+n4RHRdCOH+EMKuEEJnCOFySbskHZXHhw0AAAAAAPJEUDO2zpN0jZmdnHrCzC6Uz4g5NRoLIbSFELbleO/TJfVK+mnS87sk/UzSsWY2Nz52fAjBshzfHOT+/TnWAQAAAAAARglBzdi6TL6M6BozOzYaNLP3S7pc0n+FEH6f570Pk/RMCGFXyvj9kkzSobneyMymmNmJ8Z43tWZ2gaSpkh7IszYAAAAAAJAHtuceQyGEXjM7XdJtkpaZ2XGSFkv6sbyvzPkjuP1cSesyjG+IP84bxr0mSPqqpH0l9Uh6WNIbQghtI6gPAAAAAAAME0HNGAshdMSXPt0hD2wmS7pZ0lkhhDCCWzdI6s4w3pV0Ptcat0haOoJaAAAAAADAKGDpUwGEELZL+oykWfJw7PwQQt8Ib9spqS7DeH3SeQAAAAAAUEYIagrAzPaR9HNJj0raKulPZjZthLfdIF/+lCoaWz/C+wMAAAAAgAIjqBljZjZf0l8lbZf0OkmvlzRf0l/MrGkEt35E0r5m1pwyfnT88dER3BsAAAAAABQBQc0YMrPp8pCmWtKJIYTNIYRHJJ0i6RBJ15lZbZ63v1beBPjfk16vTtJZku4KITCjBgAAAACAMkMz4bF1nqTZkl4ZQlgdDYYQ7jCzMyT9SdKpkv5vi24z+1z8zf3ij++Jb+3dGkL4XtI97jOzayRdbmZzJa2Q9D5Je0g6c6w+IAAAAAAAMHZsZBsPYTBmNkHSkhDCU1nOHxqfYZM8lu0PZHUIYWHKtfWSLpX0bklTJT0m6bMhhNtGWDoAAAAAACgCghoAAAAAAIASQY8aAAAAAACAEkFQAwAAAAAAUCJoJjzKZsyYERYuXFjsMgAAADAOvfCCPy5eXNw6AABDe/DBB7eGEGamjhPUjLKFCxdq+fLlxS4DAAAA49App/jjsmXFrQMAMDQzW51pnKVPAAAAAAAAJYIZNQAAAECFOOmkYlcAABgpghoAAACgQpx3XrErAACMFEufAAAAAAAASgRBDQAAAFAhXnghsfMTAKA8sfQJAAAAqBAXXOCP7PoEAOWLGTUAAAAAAAAlgqAGAAAAAACgRLD0CQAAAEDJC2F0HvMZG+zt4ZzL5/2Rjg32GoPdY6j7j/R8tmvG4rpsBrs+n3sP589ktJ8zGs/NVa5/HqP1vFyuy/fPZzivPxavLU3ImMkQ1AAAAAAVJAQpFvPH/n5/HOzt5GOw8WxH6nNTx7ONDfZ6yeeijwm5M8v8OTPL/375nBvta4Yr13uOxedltF8rXyN5vXJ87mgY7usnXz+c5+7YIUlVGVc5EdQAAAAAYywWGxhupL6fevT1JY7o/Vgs+xHdc/Nmf71bbx3d+qMfPswGHtnGUscz3aOqSqqpGXgu+XzqcwCgkmSOaBxBDQAAAJBBNDMlW0jS3y/19Ei9vYmjr8/HYrHEY1/f8F87CjKqqhJvJwcc0du1tQMDkbo6f/7MmaP7uQAAFA5BDQAAACpaCANnqCQfPT1Sd7c/Jr8dhS5DqaqSqqs9JKmuToQrVVVSY2Pi7UL5z/8s3GsBAMYGQQ0AAADKTjRTJXk2S2+v1NkpdXX50d2dCF6yiYKWKGSprvZZKVHIUm52373YFQAARoqgBgAAACUjBA9colkt0SyXjg4/Ojv9SJ7tEkJi6U91tfc9icKX5mZ/BACgXBDUAAAAoGCivi7RTJeuLqm9Xdq1KxHEJO/0EwUwEyZ4AFNTI02aRPiSze9+54/veEdx6wAA5I+gBgAAAKOqry+x9KirS2pr8yBm1y4fSw5iqqo8hJkwwRvjNjayw89I3HuvPxLUAED5IqgBAADAsPX3J4KYzk5p504/ojAmeVvlmhoPYRoapIkTi1s3AACljqAGAAAAWfX3J8KYjg6ptTURyPT3+zXR0qS6OqmpSZo8uaglAwBQ1ghqAAAAIMmb90ZNe1tbpe3bE4FMtEyprs5nx0yfzhIlAADGAkENAADAONTT44FMW5vU0uJHd3fifG2thzLTphHIAABQSAQ1AAAAFS4WS+ystG2btHVroqlvNEumocF3UwIAAMVFUAMAAFBhuro8lGltlbZskXbsSIQyUVNfQpnKNH9+sSsAAIwUQQ0AAECZ6+jwYGbrVmnzZm/8ayZVV/t21zNmsHxpvPj4x4tdAYothPzOjfY1+cj3viOpZzQ/lrH6vIymsaxxrD/+Qnx+C/ln2N4uZfvfmaAGAACgzHR1+c5LW7Z4MBMtY6qr82CGLbCRjxAGHkONZXo79TnJ9852fabXybWW5PtEu5ANVWfqa2Y6P9TzMr2f7TFVttfJdv98x4diNvhzhzo/3OuGe210vZTfc4b7vLG6x2j94D8aNRXyvtleYyxeZ6zvn+k1RuN1tm+XpAkZMxmCGgAAgBLX2+tNf7dulTZs8Bk0Zr6MqamJZUzlKgoBol21Uh+Heru/3/sPRW+HkP5+9HbqWPK5TGFEMST/IJT6Q1H0fq7jQ40N9lpD1WeWvY7h3jPba+R6L2bKAeVr167s5whqAAAASkwIPiV6+3YPZlpafGzCBA9mmpuLXeH4kxyMpAYiyUcsJvX1+RG9nTwePS96zFdqaBAd//3fPn7eef5+VdXA51RV+ddR8lim4AEAUDwENQAAACUgFvOmv5s3ezjT1eU/VNNjZnRE4UpycJJ89PX5luVRyNLbm3i7ry/3GSdVVYngI3o7eay2duD50VZd7Y+NjaN/bwBAYRDUAAAAFElPj+/MtH69BzSxmP8g39zMcqahJM9QiR5jMe/X09ubeOzt9c9zLDb4/aqq0o/qap99EgUtAAAUAkENAABAAXV3+1Kmdeu850wIvl321KljM8OinIQwcBZLNLOlu9uPri4PXXp6Mi8bimaqVFcngpaaGg9bopkmAACUOoIaAACAMRaFM2vXStu2+dh4W9IULT2KlhdFAUxnpwcwUQiTugtO8uyWKHSpqyPUAgBULoIaAACAMdDX5+HMmjW+rMms8sOZKIDp6fHHjg4/uro8kEnt81JV5eFLTY0v+WpoqNzPDQAAuSKoAQAAGCX9/d4QeN06P2Ix36Vp5szKCSCiprs9PR7AdHT4DlUdHYk+MCH4x1tTk5gJM2kSs2AAAMgFQQ0AAMAItbdLmzZJq1d7eFFXJ02bVt7BRHIY096eOHp6Bm4NHS1HamqiD0wpOPHEYlcAABgpghoAAIA8xGLeDHjVKl/iVFUlTZ5cfrs19fV5GNPdLe3aJbW1+WNys94ojGlo8B2pULoOPrjYFQAARoqgBgAAYBja23077VWrPORoapJmzSp2VbmJdk/q6JB27vRQpqsrMUMm6hXT3MzsGAAAioWgBgAAYAj9/dL27dKLL0pbtiR6rtSU8HdSyT1kWls9mOnt9XNVVR7I1NZ6g2NUjsce80dm1gBA+Srhby8AAACKq7dX2rhReuEFDz0aG0tz9kwslghlduzwYKa722fKmCUCGWbJVL5bb/VHghoAKF8ENQAAACk6Onxb7dWrfTbNpEml1Xumr89rbGvzmT5tbYmtr2trvZlxU1Nxa0Rlib6+QkjfZj15LNP5TNek3jfT6+QyPtRYrvVkuibTucGuy/b+UDXnes/BDPb6+dxvOM8djfrH4vmjbSR/HqOt1D43hVJpH/fmzVK2ubkENQAAAHE7d3rvmbVr/VunKVNKYxZKb6/3xmlrk7Zt85BG8iVM9fXexLhStv8ej/r7Ez+ARG8P9n7yY3Quuq6nxx83bEg/l/zc1HOpdaSeK8cfkLL9nch1fLh/p3K9fjTvW05/70fj4x6rj7dYn8dy+vPD6PN/k6syfhUQ1AAAgHEtBF8qtGKF/3arrs6XNxXzG+hoxszOnb6zVGowM3Vq8Wobj6LQIjpSw48o9AjBl6H19Q28PhbL/HZqCDMS0TK37m5/v6UlMZ76mCmQMPNQMts5AMDoGuzfVoIaAAAwLoXgP8w+/7w/NjZKs2cXr5bOTg9mtm3zx/5+/8GZYGZkojAlFksEKakhSl+fP0ZH6vvJW5UPJQo2qqoSbyeHHWa+1Xn0flXV6H680QwwmkQDQPkiqAEAAONKFNA8+6zPpGlqKk5A09cn7drltWzd6subqqp8Rg9LmTKLgpbkACV6u7fXP6e9vYmwpbd34PKdTJJDleRwparKl78xowQAUGgENQAAYFwIwRvvPvOMBzTNzYUPaLq6vM/M5s2+O1MIPrtiPO/IFM14SZ3F0t2dCF+6u/2xry/zPZLDleSjoWH0Z6wAADDWCGoAAEDFa22VnnvOZ64UMqAJIbFl9ubN3hDYzJczTZlS+TM1kpcWRUFMd7c3vO3pSQQwqTNeknumRH1T6usJXXLx7ncXuwIAwEgR1AAAgIrV1uY9aDZuLNwSpyic2b7dX7e7OzG7Y9q0sX/9QurvTyw1ima/dHX5Ec2ISVVVlQhg6uo8gKn0wAoAgOEgqAEAABWns1NauVJ66SUPAwoR0HR0eL+Z5HCmqcmPcpbc76W3NxHCdHb6rJhkZt7XJQphGhqKUzMAAOWMoAYAAFSM3l5p9WrphRc8MJg5c2xna3R1+bKqjRt9WVN1tfebKcdwJgpiojCms9PDp9RZMVEQM2GCz4ZBabnxRn984xuLWwcAIH8ENQAAoOz193tY8vTTPvtj2rSxa87b1+c9ZzZu9JCm3JY19fUlesR0dCQCmeQtqKurPZBhVkz5aWkpdgWVI+qdFMLAPkrJ48mPg41lumaw1xzNc/k8t5Cvlet9R1uhX2+0lGvdY6lcPyeD/XtNUAMAAMra9u3SU095eDJ1qlRbO/qvEYLPmNm82Y++Pp85M3Vq6fZXCSERyHR1ef3t7QN3Tqqp8aOxkUa95SraNSs6YjEfb2tLjEXXZHvM9vZg10XhQ66HNHCr9Fyuz/WawR7zOVeuP/QBKC+dndnPEdQAAICy1NnpjYLXrh27nZx6e/03XuvX+6yTCRP8tUptK+2oqW/UO6atzR+jWTJVVYmlSgQyoyuExJbiqVuMR+8nj2caiwKW5LAl17ejYCaycaM/Xn994T8XAIDRQVCThZkdKekLkl4uaYKkFZKuCCH8sohlAQAw7sViHs4884yHDrNmjf6sll27pE2bfPZMf7/3nCmlpU3R1tYdHV5r8tKlqH8Ms2Qyi3aoio7kRsnR26mP0dvJ48lBCzMwAACjiaAmAzN7g6TrJd0u6WJJvZL2lrR7EcsCAGDca2mRnnjCw4np033ZzmiJxXwZ1bp1fv8JE6RJk4ofdvT3J5YvtbX5ETX4rarypV7jLZTp6/Ogqrs7sbyrp8c/L8nvZzqXvPQLAIBSRFCTwswmS/qlpB+EED5W5HIAAID8B/Lnn/cdnSZNGt1lTj09PnNm3Tr/Ib7Ys2disYFLmKJeI5KHR5XW4DeEgdt+R4/JbyePdXen70QFjJVott5Qj7mOpc7+G2w24FAzBfN97nDPFaOOXM6XunKtv1zrHktj9TlpbZXWrMl8jqAm3b9JmiLpEkkys4mSdoXApFYAAAotBO8P89RT/v7s2aP3DVNHh/fz2LjR7zlxYnF6z/T3J7bD3rHDG/7293tN5byEKYRE4NTV5Z/v6ONMPZjlMjJVVf61W1UlTZmS+Ho287GqqsTb2R6zvZ3tuuQj+vpMHU89omuS75Hr87K9RjQWSR5PPjecYCVbqAIAo+nFF6XHHst8jqAm3WslPSPpjWZ2uaT5klrN7EeSLgohxAZ9NgAAGBXt7R7QbNniM1wmTBid+7a1eY+blhZfOjV5cuGDkCjA2LFD2rkzEcyU0zKm3l4PX6LdpFLf7uhIb3RbqaqrE1uaR28nv588njqWHLKkPg41Fr1NoAAAlYWgJt1ieS+aX0q6XNLDkt4k6VOS6iWdn/oEMztH0jmStGDBggKVCQBAZerv9yVOzzzjuxSNxjKnEDwUWbPGH+vrC7u1dizmwczOnT7VOVq6U8rBTCzmocuuXR5uRY9RENPdXewK8xMFYhMm+BFtUR69XVubPpbt2ih8KcU/PwBA+SKoSdcsaaqkT4cQvh4fu87MmiV92My+HELYmvyEEMKPJf1YkpYuXcoSKQAA8tTW5tOAd+70WTQjbRYcgjcIfuklDxoaG70JcSFEuzK1tvrHFYJ/PKXUYyYW88/Lzp2JfjhRIJO8k1SpiZoo19X5EQUvdXX+WFub+YgCl0qegbJtmz8W6uscADD6CGrSdcYf/zdl/LeSzpB0lKQbC1oRAAAVLhbzWTTPPuthyqxZI7tfckDT3u4Ngsf6B9cQvAfLrl2+rKqry8dra6Xm5uKGA729HsZES62ix+RGxcVUXe3hVV2dz3ZKfoyO5Pdrays7bBmJm27yx3e/u7h1AADyR1CTboOkAyRtShmP3p9a2HIAAKhs0SyaHTukGTNG1tA3U0Azljs4hZBY0tTS4oGImYcJkyaN3etm09/vn8/t2xNH1KC4GCZM8ACmocGDlsZGf4zGooPgBQCABIKadA/KGwrvJmll0vj8+OOWglcEAEAF6u/3QOWppzxQGUkvmqgHzapVPqOluXnsAprkcGbbNt+xqKoqEToUSk9PIoxpbU2EMoXaQamqyoOXxkb/82tqSn+7trYwtQAAUEkIatJdI28cfLakiyTJzEzSv0tql3Rv8UoDAKAydHRITzzhQcf06SPrRdPW5sumWlvHdolTV5cHIdu2+cyZKKgoRCPZvj7/+LZu9dffts2DorFWX+/bPDc3D3xsavJzNNEFAGD0EdSkCCE8aGa/lvQZM5sl6SFJJ0s6SdInQwgF+LYIAIDKFIK0YYP0+OO+LGYkvWg6OnxGztatPpNlLAKanh4PgrZu9aCmEDNnotlByaFMa+vY9ZKpr/ctyidNSgQxUSgzWluiAwCA3BHUZPYBSS9Jel/8WCnpQyGEHxW1KgAAylhvr/T0075F9vTp+YcA3d3SunUe+EyYMPoBTSzmIdC2bR6YjHXPmVjM+9ts3ixt2eLHaG99beazYCZPToQy0WNd3ei+FipXCH4Mdj71usGuz/S8bOeGGhvqmqGek889Jf+7NZzxXOX6/HxeJ+oHNZL6Uu8VGY17jpVK74NVyp/7UjXSr4mRfs57erKfI6jJIITQI+ni+AEAAEaotVV65BH/pmT27Py+OerrkzZt8lk0ZtKUKaO79KarK7G8KBbz/ioTJ47+N/e9vR7GRMFM1OdmtNTVSVOn+jFlij9OmjTyrc4xcqlBR39/5rFs10bjyY+poq+lsVgaZ5b4+xC9nfz3w2zg38nkazJdmzoWjae+Vrb3sz0v0/nBrhns73ima4b7b8JI/w0ZzvNLOYwo5dpQWcoltPJflPRm/A6A/7IBAMCYCcEb/D79tIce+cx+CcHDjFWrfKbJ5Mkj2xkqWSzmzYe3bvXHseg7E4t5/Rs3+iygbdtGbxnTpEmJUCYKZhob+YEoH8lBSCyWeDsKU6JrhppVMpgobKiq8sfq6vRHyc9H12Qbj75GU4ON977XH6Pm3EMFK9nOJY8nXwsAGB1NTVK2/1EIagAAwJjo7vaGwZs25b/t9q5d0osv+hKkqIntaNXW2uozWmKx0V3aFILfe8MGD2e2bPFZNCPV2OhB1/Tp/vmcNo1dlaREcNLfnzhSx3JRVeVfo8mhSXRE51KvSQ1eUo9oPLp/IcKOiRPH/jUAAGOLoAYAAIy61lbpoYf8h+R8tt3u6ZHWrpXWrx+9RsEheO+ZLVu8vqoqD35GY/ZMb6+HMuvWec0dHSO7X02NhzEzZiTCmcbGkddZ6vr7PTiLZrXkEraY+eerujrzY01NYiZK8myU5JkshQpRAADIRUUENWa2r6RLJB0vaYak14cQ/m5mMyR9S9IPQwj3FLFEAADGhRC8h8yTT/oMleHujtTf70HKiy/6+9OmjfwH6FjMd27atMn70EyY4LWN9L47dyaCmc2bE8tl8lFf7ztgzZzpj1OmjN7yrmKKZrb09SUClyiAySQKViZM8GAqejsKW6JZLdHbycuC4G691R9PPLG4dQAA8lf2QY2ZHS7pn5LaJN0h6fToXAhhq5ktkfQfkghqAAAYQ729HtCsX+8zQIbbvHbXLmnFCn8cjea3fX0+c2bTJn+7vn5ky5tCkLZv9yBqzRpfjpWvpiafaTRrlh9j0bR4rPX3Dx3ARLNdamv9819b60c04yUKXKIgptw+B6Xoscf8kaAGAMpX2Qc1kr4uaY2koyXVSToj5fxfJb270EUBADCe7NrlS526uoa/1Kmvz5c5rV3rM3CmTRtZLd3dHqhs3uzvNzbmv2woBG80vGaNBzS7duV3n7o6/7zMmeNHOQQzURDT15c5hKmu9tClsdEf6+oyLzkq9Y8TAIBSUwlBzTGSPhdCaDOzTC311kqaV+CaAAAYNzZtkh5+ePi9ZEKQWlp8Fk1/v+9aNJJ+Md3dHqps3Tqy/jPJu0y99FJ+/Waqq32mzNy5HsxMnVp6gUW0JCkWS8yMiUQzYerrpeZmf4yWICX3gAEAAKOvEoKamKTB+vnPldReoFoAABg3+vs9ZHnuueHvQNTV5UHI1q0+u2Qkuxd1dXlfm5YWD2aam/MLaHbu9N44q1Z5T5vhamyU5s2TdtvNw5kJE4Z/j7EQi/mytExhTF2d193QkJgRE/WFGc0tygEAQO4qIai5X9LbJP1X6gkza5D0PnnvGgAAMEp6eqTHH/fZNLNm5f5DfQgeqqxc6UHBSHZz6uz05U2trR4u5LOcqLPTg5lVq3wWzXDNmOHBzG67FX/WTBTI9PYOXKZUW+tBTENDYmZMNDum1Gb5AACAyghqPi/pH2b2J0lXx8cOMLP5kj4hX/Z0epbnAgCAYcq3H01Xl8/A2b5dmjw5/2bBXV0eEOUb0PT3+25NK1b4Y7YdiDIx84959939KMaW2VHvmN7egTtNRf1impp8dkwUyLBECWMh+nsT7ew11DWDjWV73mBvD/acoc7l+nd+qI8rHyN57ljfO9O/o2NZL0Yml//3SvnPj18U+JLtbMo+qAkh3G1mJ0v6b0n/Ex/+TvxxpaQ3hRAeKUZtAABUmi1bPKSpr899NkwIPvNlxQoPDvKdRdPd7fdpackvoGlr8xpWrhxe35nqag9nFiyQ5s/3j71Q+vt99lLyLJmo/86UKQN3UiKQKW39/enhRrQULXo/9fxg72czebI/bt8++h9DMrPE37/o7eSxbOPDeU7y9cnnM90n9fxQ5zLdM9P9h/u8XM5lk8vrDOee/CCMQhvrYGg071+IEGuo15gyRRr4K5eEsg9qJCmEcJuZ7SPpEElLJFVJWiHpoRDCYP1rAABADkKQVq/27benTvUZG7no6vJgpKXFvyHJJ0xIbhJcXT28gCYW84bAK1ZIGzfm/prRzJk99/SZMyPpoZOr/v7E0qXoB/iaGg9lZs5MLFuqreUHsNEShSchJL5VTh5LfnuwmSO5qKpKP8wS25Qnv2+WeD/Tc5J300oNPPbfP3tAMli4kS0cyRayAABGxnvZxTLmFRUR1EhSCCFIeiR+AACAURKLSc8+6412Z87MLWyJtrVescJ/qMxnFk1fn99j06bhNwnu6JCef96Prq7cX3PaNGnhQj/GellTX5/Plunr8/ejmTLTp3soU1dXmICoHEXbhUeP/f0Dj6GWwURBQ1VVYhvx6uqBO1olj0djycFJFGCkhiepb0fvAwCQq7IPaszsbElvDCGcluX8tZL+HEL4ZUELAwCgAvT0SI8+6o12Z8/O7Tfpvb0e6mzenF8vmljMl21s2ODv5xrQRI2Kn31WWrNm4A5Hg2lq8pkze+6ZWDYy2kLwz0tPT6Ku+nqfZRRtfz0eZ8rEYolwJRYb+H42UfARNUROfYyOKFCJApbkmSvJYQsAAKWm7IMaSedKunuQ8+sknSfplwWpBgCACtHeLj34oC89mjkzt+fs2OHbdcdiPjtlOD8Ih+BbZK9b56FGrgFNX5/v2vTcc77EKhdVVd5vZvFi30p7tGc8RMFMd3diBkdjo++Q1dTkwUy+zZRLWXLoEm0HHs16SRZCYjZLtJwran6c3HMneaZL8vsELNldcIE/XnFFcesAAOSvEr5FWCLph4Ocf1LSmYUpBQCAytDaKj3wgP/gPG3a0NfHYtLatT6TpbnZj+Fob5fWr/fHaCvpoXR3ezjz7LO5L2+aNMnDmT33zO01hqOnZ+CMmeZm/9w1NnowU87NfqNlRlEAE4UwycuIJA9SoqCludkfox2okpcWJS8lAgAAA1VCUNMnadYg54excSgAANi0yWfSTJ6c2w5HnZ0emOza5Y2GhzM7pbvbX6+lxX+gz2Xp0a5d0tNPe/+bqL/LYKqqfMemvff2mUGjFQ7093tAFNVQX+8zZqKlTOUUzEQBTPJjNAsm6rMShS4TJ/pjNCso9QAAACNTCf+d3ivpTDO7MoSwK/mEmU2Sz6a5vxiFAQBQblavlp54whva+m4Eg9uyRXrhhdxn3kRiMe97s2GDBymTJg0doGzbJj31lO/ilMvuOw0N0pIlPoNmtBoD9/QkljPV1HiwNGmSv1Yun69iiWbE9PYmZsRE41H/lvp6D2GiGUDRUqSo9wuzXwAAKIxKCGq+JOl2SQ+Z2RXypU6SdKCkCyTNl/S+4pQGAEB5CMGXEK1YIc2YMfTMiKgvzMaNw28YvHOnL5PKtQ/N5s3S448nmgsPZeZMaZ99fFvtkc5q6e9PLGmSPJCZNy/RZ6bUwosojIkCmUg0I6apyT+GpqaBvWGYCQMAQOko+/+WQwj3mNlbJP1A0vclRb9jM0mrJZ0aQrizWPUBAFDqYjHpySe9ie+sWUMHJ+3tvtSpq2t4DYO7uz1saW0dug9NCL4k6vHH/XEoVVXSHntI++6b31bgyZKXNJn5jJm5c32mSalslx1t7d3bO3A76iiMmTbNH6N+MbW1bBGN0pQ8Oy6Xtwd7frZrc7lmMMN5/XyvyedaIF+l8EuGYtRQqNfM9XUGW75d9kGNJIUQbjazRZIOl7RXfHiFpIdDCDluzgkAwPjT2+vbb2/dmlv/li1bpOef9x4lU6bk9hqxmPegWb8+sVwomxB8ls7jj/tMmqFMmOBLm/bd14OJfCWHM1VV/rFNmeLhTDF7zUQzZHp6/O1IXZ1/vNGyq6h/DDNjSl8Igx/RNckBXLZrUsckD0Ql/7taDpL/zYn6IWV6O9O1w3kc6Vi2a4ZzPpOhrst2Pp8fOAv1nFI2FkFYIcK1fF9jNGsrhRAx1xpGUmshg9UZM6SB/7snVMx/5/FAZnn8AAAAQ+jq8qbB7e1Db7/d1+e9YdavH95Sp/Z2X+bU2en9T7LN6ogCmscey+0HzIYGD2cWL/aAIh+p4cy0af6xNTQUJ5yJxfyH7GjnKLNE/54ZMzyYqasjkBlN0XbiUQ+f5IAkeozeTg5OBpO6E1aqKICIthuPjuTtx6Ox6Gsg+cg0lnx87GP+OocdNvD1UgOQbIFILkFJvo/ZxgBg/Oqr7KDGzPaXz6aZKl/2NEAI4dcFLwoAgBLV3u7bb8diQy8V6uqSnnnGw5ZclzrFYh68bNnivVwGm0WzZYv0yCO5LXGaNEnaf3/fXjufMCWERBhi5rNmpk4t/MyZ1FBG8gBm0qTELJn6ep8pww+0CVFgEosl3k59fzi/4UzdLjzq1xONZ3rMFJokhyfJY6nnk8OPsfJv/za29wcAjL2yD2riS55+I+koZQho4oIkghoAAOTNfO+/338oHWr50vbt3mS4pib3pU47d0pr1vgPzYPNomlt9YBm7dqh7zl5snTQQb7Ndj69VpJ3a5o0yRsCNzcXJpwJwV+/qysxwXnCBK9jt90SuyyVSv+bsRbNXom2AY+ClujtwVRVJZogR42Qk4/aWv9azTRDJTlkid4GAKAUlX1QI+lHkg6SdL6kOyRtL2o1AACUsJYWn0nT2Dj4ltUheHPhVas8bMklROjt9WbBLS2JvimZtLX5EqdVq4ae/TBligc0u+8+/B+s+/uljg5/rK/3UCTXj2UkotkyUa8QyV83ev36ej8qRRS0RMFLtP13tj9bM589VFvrYVkUukRbgqfOYEk+CFeGdvPN/vj61xe3DgBA/iohqHmFpK+GEL5b7EIAAChlmzdLy5f77JTBgoK+PumFF7zB8JQpuc062bHDZ9FEM1YyLe/o6vImwS+8kK11XsLUqYmAZrhLRaKQpKrKl3VFTYHHSizmH1tPj3/81dX+mvPnJ7bDLmZD4nz19/vXQrTVd19f5hkvVVWJ8Cn5iHrppB7l+LkoJ9//vj8S1ABA+aqEoGabmEUDAMCg1q3zZUbTpg0+o6Sz0/vRdHfnts118iyaxkafEZEqFvPtvB9/3MOMwUyeLB1yyPADmuTZM83Nvp32WC1tipoQR0upamo8WJo2zT8HDQ2l31cmBP+zi45MM2Cqq/3jaW72jylaopW81CgKXwAAwOiphP9afyTp3Wb23yGEIX4/BwDA+LNqlfTkk75z0GA/VLe2ekgzYcLgzX8jQ82iCcH7zzz0kC93GkxTk3Twwd4keDjLW3p6PFyqrvadq6ZOzX8XqMF0d/vr9PcnZswsWJCYMVOKwUxfn39+eno8jElmlghhosdoOVJyrxcAAFB4lfBf8BOSTpX0kJn9TNIaSWmBTQjhhgLXBQBAUYXgy4yee85DjGyzS6KtsVesyK2HSyzm23Rv25Z9Fs327b7198aNg9+rvl464ABpyZLcg4HkbbUbGqSFC73u0Zw9Ey1nivrMNDdLe+zhgVRjY+n0Sunr8xqjmTHJ6ur88zJzZqI3Tm2tj0+YUJrhEgAAqIyg5g9Jb1+Z5ZogiRXRAIBxIwSfHbNypTRrVvZgIRaTXnzRA5Vc+tG0t0urV/vzMs2i6e72JVYvvDB4o+AJE3yb7X33zRz0ZNLf768fgi8zmj59dHvPRLNzYjEPjaZP96Opqbg7MkW7RkU7V0V9YqKmvJMne5A0aZK/H/WHKZUwCQAADE8lBDWvLnYBAACUkv5+6amnpJdekmbPzj5zoqfHZ9vs3OnBx2AzLGIxb0a8aZPPYmloGHg+BJ+R8/DDA3c7SmUmLVrkfWhS75FNFKDU1PjHM3Xq6AUnyUuaGhq8AXDUfLgYQUdv78D+N5J/zpqbPTSaPNmDo6hhL415AQCoPGUf1IQQ/lnsGgAAKBWxmPTEE948eNas7OFLe7v09NMeUEydOvg9u7p8Fk1Xly+hSQ0wWlqk++/3XaIGM2eOdMQRQ79e8uv29HggMZrLm7q6PJwJwe+5554egOQaHI2G/n7/2KKPMfpzamjwz8/UqYn+N/X1zI4BAGA8KfugJmJmkyUdLWmmpNtCCJvi41UhhAybSQIAUFn6+qRHH/WZL7NnZ79u+3YPaerrPQzIJgS/ds0aX540adLA8z090mOPSc8+O/gyp4kTpcMP99kqQ/VFCcFDlL4+n0Wy++5e40j7qSSHM5Mney3RUqGx1t/vM2SivjrRFt6TJvnHN3lyYrcoGvhipJYtK3YFAICRqohvB8zsYkmfltQg70dzoqRNZjZd0ktm9skQwveLWSMAAGOpt9d7w7S0+EyaTJKbBk+aNHhvmL4+n5WzfXv6LJoQfCephx7y8COb2lrpoIOkvfceeiZM8vbaU6Z4A9yR9p9JXtY0caI3LC5EOBO9brQVeRTKLFw4MJRhlgwAAMik7IMaM/uIpC9K+qGkW5XUXDiEsM3M/ijpdEkENQCAitTT46HJzp2+BXcmsZgvX1q/fuimwckNg1O36d61S7rvPmnDhsFr2nNP6bDDhg5bkgOaGTP8GEmQEot5jbGYz8TZc0//eOvr87/nYPr7PZSJAiEzf91587zvT1NTae0SBQAASl/ZBzWSzpV0dQjhw/EZNKkekfSawpYEAEBhdHdLy5d72DE90/+C8tk2zz/vs2MGaxocgveZWbcuvWFwf78vcXr0UZ9tk83kydJRRw2+9Cq6X7SD08yZXnu+AU0U9vT0+Cyh3XZLhCSjLRbzUKary1+3utpfK9q6u7k5912sgLFw/vn+eOWVxawCADASlRDULJT0rUHO75SUY9tCAADKR1eX9OCD/jhtWvZrnnlm8GskD1/WrpVaW9OXOm3fLt17r7RtW/bn19T4Mqd99x18tk5qQDNjRv47OHV3e0Aj+b1mzcrc7HgkohCoqyvRW2bGDGnxYg9mmpqYLYPSsmJFsSsAAIxUJQQ1WyTNG+T8oZLWFKYUAAAKo6vLd1rq7fWlPZns2iU9+aSHC6lLmJJ1dHjPmdSlTn19voPUU095YJHNggW+m9NgM1iSlziNJKBJXdq0ZIl//KM1iyUE/9y2tydmzCQHM83NI29sDAAAMJhKCGr+JOk/zOwXktqTT5jZqyS9X9IVRagLAIAx0dnpIU0slj2kaWnxnZ2amrIvKQrBZ8msW+c9XJKXOm3bJt19t7RjR/Y6mpqkI4/0HZSyCcEDmljMA4+ZM/MLaLq7PTyprvZtvmfOHL2lTX19Hv5E22RPmeIzg6ZMGf0ZOgAAAEOphKDmEknHS3pM0j/luz593Mw+J+k4SY9L+krRqgMAYBR1dHhIE20zncmGDUPv7BSL+VKn1F2dYjGfRfPkk9ln0Zj5Tk6HHDJ46NLR4SHItGm+LGm4PWiiZVI9PT6TZZ99PDwZjS2sOzsTs2bq6rz578yZ/jmlxwwAACimsg9qQgjbzexoSR+XdJqkLkknSFoh6cuSLg8hdBSxRAAARkVHh++4ZOYhTKr+fumllzyAGWxnp85O39Wpt3dg2NPa6rNoWlqy1zB5svSyl3mokU1Xl8+AmTLFmwonz9TJRW+vz3Ax8+fPmuVBzUhES6+injbRrJlp01jOBAAASkvZBzWSFA9iLo0fAABUnPZ2n0lj5jNgUvX1SStXSps3S1OnZl+u09rqIU1tbSL86O/3ZVKPPeYzajKprpb231868MDsAVBPj4dAjY3eO2a4S5Oipr11ddJee/lOUCOZ3RKL+eetq8s/HzNn+qycqVNHtgU4AADAWKqIoAYAgEo2VEjT2+tbZ7e1Zd+iOxaTNm6UtmzxgCYKW9rafBbNli3ZX3/aNOnlL8/eD6e/32fATJgg7bmnz/bJdYZKtLwpmt2zaJE/P9++MFGz4e7uRD+befNGb8kUUOpOOqnYFQAARqrsvmUxs5/n8bQQQjh71IsBAGCMRSFNVVXm5T9dXb4r02C7P/X0SGvWeIARhSghSM8/Lz30kM/GyaSqSjrggOyzaKLlRJK0224+U2WwrbmTxWIeEvX3+/KmOXPyX94UBUVdXf768+ZJc+cOvvwLqFTnnVfsCgAAI1V2QY28/0xIGWuUFK2W3x5/nBp/3KKU3aAAACgHUeNgs8whxq5dHtJUVWXuWSN50LNqlb8dXdPVJd1zj+/2lM3kyT6LJtsMnc5OD4dmzPAeMrkuUerr84CmqsrDnVmzfMep4QrBP7aODr/X3Ll+P8IZAABQ7souqAkhLEx+38z2l/RXSZdJujKEsDU+PkPSBZLeK+nkApcJAMCIJDcOzrTcqbXVQ5qGhsxBRwjeFHjNGr8m2p1p/XoPaTo7M7+umTfZPeSQzEuFoj40EydKCxd6P5pc9PQMXB41c2Z+S5G6ujzoCcFDnv3286VZLGsC3Asv+OPixcWtAwCQv0r4tua7km4KIXwueTAe2FxkZrPi17y2GMUBADBcnZ0+k0bKHNJs3eo9aZqaMjfFjcU8kNm2LbH1dl+f9Oij3jQ4m+Zm6ZhjfClSqqiXTE3N8PrQdHf78+rqvMHw9OnDn/HS1yft2OEf16RJvhRr5kwaAgOZXHCBPy5bVtw6AAD5q4Sg5mWSrh3k/EOS/l+BagEAYES6ujykCSHzcqYNG6QVK3xpUqZZJN3dvkV3R0ciTNmxQ7rzTmn79vTrI0uWSIcfnnkJU0eHhyVz5vhSp1yCliigaWjwnZamTRteg+AQfOZMV5fPBtprr5H1sQEAACgXlRDUtEg6SdIPspx/g6TWglUDAECeurulBx7wUCS1MXAIHsCsWZO9D0tqP5oQpOeeG7xhcF2d9LKXSbvvnn6utzcR+Oy2W24zWJIDmn33HXyr8GzP37nTa58zR1qwYPj3AAAAKGeVENT8SNKXzOwP8iVO8ZW5WiLpI/L+NJ8vUm0AAOSku1tavtx7uaSGNP39HsCsX589tNi2TVq71vvV1Nb6TJR77/WxbObO9aVOqX1mot2cqqpyX+YUBTT19cMPaELwcKa722vZf39ffsXSJgAAMB6VfVATQviymdVJulDSqSmn+yR9LYTw5YIXBgBAjnp6pAcf9HAlNaSJxbw56JYtvnwoNTCJxaSNG/181I9m0ybprrsSW2enqq6WDj3UA5XU+3V3ex2zZnlYMtQyp95eD1nq64e/xKm315dl9ff7ltoLFvjHn0vvGwAAgEpV9kGNJIUQLjaz78gbBu8RH14t6bZoFygAAEpRb6/08MM+G2XatIHn+vp86dKOHZm3ye7t9eVQu3Ylljo9/rj02GP+diaTJ0uveEX6a/X3+33q66W99x56N6dYzAOaCRP8+uE0Cd61y0OkKNyZMye/LboBAAAqUUUENdL/7fJ0dbHrAAAgV3190iOPZA5ient9h6aOjvRZNpLvDPXiix6wTJrk7991l8+uyWbJEumII9KbEEfNgufN8zoGmxETi3mTX7PhbbPd3+8fZ2+vv8YBBwy/wTAAAMB4UHZBjZktkKQQwkvJ7w8luh4AgFIQi/l22S0tvpNSsu5uD2m6u30GTKqdOz2kqa31Lbo3bPCQpqsr82tlaxgci/nslokTpfnzB+8JE/WR6e/3+8yZk3mHqFR9fVJrqz9/wQJ/bqYtxwGMjiuuKHYFAICRKrugRtIqScHMGkIIPdH7OTwvxwnZAACMrVjMlydt2eIzUpJ1dUlPPunXpG7PHYK0dau0bp0HNFVVPiPnySezL3WaNUs69tj0pUzt7YnwZOrUwfvCtLd7aDRnju/+lMsypa6uxNKoJUty3zUKwMgsXlzsCgAAI1WOQc375cFMb8r7AACUvP5+D1Y2bvQQJVlHh58zS591Eov5rk/btvm5aKnT5s2ZX8dMOvBA6aCDBi4v6uvz4GXKFN/1abDwpLvbZ9xMmybtt5+HQ0Pp6PDnNDZKhxziH2MuS6MAAADgyu5bpxDCLwd7HwCAUtXfLz31lM+ISQ1p2tulJ57wUCN19ktq0+BoqVN3d+bXaWiQXv5yD2IiIXiIEoK0cKEvqco2i6avz/vJNDZ62JOpR06qqEHw5MnS0qVD97oBMDa+9z1/PO+84tYBAMhf2QU1qczss5KuDiGsLHYtAABkE4L0zDMeuKSGNLt2eUhTW+shS7KuLu9HE4tJzc3e1+aJJ7K/zpw5vqtT8n16ez1EmTrVGwZn6y3T3+/Llcx8udLMmYOHLSF4Y+HOTr/24IPZXhsotltu8UeCGgAoX2Uf1Ej6kqRLzexh+a5P14QQVhe5JgAA/k8I0rPPSqtWeUiTHGTs3OnBS2Nj+jKk9nZp5UqfZVNdLf3jHz6bJhMzD0oOOGBguLJrV2KHpkyNiZNfq6vLmwrvttvgjYJD8Bk3PT3S7NnS4YcPfm8AAADkrhKCmvmSzogfX5f0dTN7QInQZt1wbmZmSyVdJOlwSbMk7ZD0iKQvhRDuHsW6AQDjQAjS889LK1Z4qJEc0rS2ek+apqb0kGb7dp99U1/vYc4dd3iYkkljo8+imT07MRb1ohlqFk1Pj8+KmTJl6D40yQHNvHnSXnuxgxMAAMBoK/ugJoSwUdJ3JX3XzOZKeruk0yV9S9I3zeweSb8LIXwvx1sukn9efiJpg6Qpkt4l6V9m9oYQwq2j/CEAACrYypUe1KTOpGlp8S24m5t9yVMkBG8QvGGDn3vhBemhh3zpUybz5nk/muSdmKIdnQbrRROLeUBTU+MBzbRp2ZcspQY0ixZ5bQAAABh9ZR/UJAshbJD0HUnfMbN58oDlc5KOkZRTUBNC+J2k3yWPmdkPJK2U9DFJBDUAgJysWuV9aVJ7vWzd6uOTJg2c6ZK8s1N9vXTPPX6PTKKlTgcemAhYYjFf6jRligcqyQFQsl27vBHxggV+3WC7Mu3Y4UuiooCGGTQAAABjq6KCGkkys2pJJ8pn1pwqaaKkTSO5Zwihw8y2yGfXAAAwpJde8mVNM2d6f5nI5s3Sc8/5TJfkgCQWk1av9lkuknTrrb40KpO6OunYYwfu6tTR4fdYsMCXO2WaHRMtc5o61XvZpO4ulaytze85Z460eLGHSgAAABh7FRHUmFmVpNfIw5m3Spomaat8ZszvJf0zj3tOlFQnabqk90k6UN64GACAQa1bJz3+uDRjxsCQZuNGX8o0ZcrA8e5unzkTBSl33eVvZzJjhvTKVyZ6yfT3+wyZ5mZvBJza6ya6ZufO3JY5tbf7/WbOlA47jCbBQLlZtKjYFQAARspCCMWuYUTM7EfycGa6pO2SrpOHM38PIfSP4L7XSjot/m6PpJ9LOj+E0J3h2nMknSNJCxYsOGL1ajadAoDxasMG7ykzY8bAGTPr1vk226khTWenj/f3e1jzyCPeEyaTvfeWjjgi8fyuLg955s/38CXTVtodHf4a8+f7kW2ZU1eXhzmTJiXCHAAAAIwdM3swhLA0bbwCgpoWSX+Sz565LYSQpd3isO97kKQ58l2l3iNplaSPhhB2Dfa8pUuXhuXLl49GCQCAMrNpk/Tgg9L06YlAJAQPaVatSg9pdu3ykMbMw51sOX9NjXTUUb7LkpSYRVNf70udGhrSn9PX5/1lJk3y52Vr/tvb6ztMNTR4QJPa9BgAAABjI1tQU5ZLn8xsf0lrQghtkmaHEHoHuXY3SUeEEG4YzmuEEB6X9Hj8Hr+RtFzSL+U7SgEAMMCWLR62TJs2MKR56SVpzRrvC5M846W11YOZWMybBre0ZL7vxInSccf58yVfEtXZ6Vtxz5o1MPiJXrOtzR+XLElvZByJxfw1a2qkgw7yfjep9wIAAEDhlWVQIw9Q3iPpf0IIvWY2VdKzkt4WQrgz5drjJf1aUt7ffsZf43pJnzOzhhBCZ773AgBUnpYWafly7+cS7eIUgs+WWb9+YEgTgoc669f7sqS77vJlR5nMnetNg+vq/Hnt7R6mLF6ceYZMd7fPtJk1S9pjj8z9akLwkKivz++zxx4Dd54CUN5OOcUfly0rbh0AgPyVa1CTOim7StIMSVk2Ih0VDfHXnSiJoAYAIMlDjwce8CVGUTDS3y+tXOnNg5Mb9/b3ew+bzZv93EMP+Vgm++8vHXqoBzzRtttTp0q77ZbeZyZqFjxhgu/mFM2+SRXt5LRggTcczbRkCgAAAMVVrkHNmDGzmSGELSljkySdIV9utbk4lQEASs3OndJ99/nslvp6H4vFpBUrPIxJDmliMV8C1dIiPfus7/6USU2NdPTR0p57+vudnd5HZo89vMdNav+Yjg6fkbPbbtmbBXd1eb+amTOlww9nq20AAIBSRlCT7ndm1iXpbkkbJe0u6Sx5U+F3FrMwAEDpaGvzkKaxcWBI8/zzHsZMn564trfXmwlv3+6zaLZsyXhLNTV5P5rp0xMNgxsafPZL6jKmWMzDl6Ym6ZBDMi+F6uvzWhobpSOP9J2oaBQMAABQ2ghq0v1G0nslfVTSVEmtku6V9J4Qwj+LWBcAoES0t3tIU1fnIYjkochzz3l4krz0qLvbl0Ft3Srdf7/PgMlk5kwPaRoaPNjp6PBeM7Nnpzf5bW/3psJ77inNmZPeLLi/3wOaqipfCrXbbjQKBgAAKBflHNTsbmYHx9+eEn/cy8y2ply3YDg3DSH8XNLPR1gbAKBCdXR4SDNhgs9mkTykeeYZnwEzZUri2vZ2D2nWrpUefthnwWSyZIm0dKmHKR0dHrTstVf6EqVYzHviTJ3qAUymHjM7d/pSpz339CNTQ2EAAACUrnIOai6LH8l+lOE6kxTGvhwAQKXr7PRZMVVViaVGvb0e0rS3+65PkR07PKR57jk/Mqmq8oBm7709nNmxw7fj3n13qTalPX5bmwc1S5b4TJvUJUxdXR7izJrl95w4cdQ+bAAAABRQuQY1ZxW7AADA+NLV5bs79fcnApmeHumpp/xcckizbZs3FH7kEWnTpsz3q6+XXvlKX9rU0+Mh0Ny5vgQqeSlTX58HONOm+SybqB9O8vnt233mzJFH+vPpQwOMX+eeW+wKAAAjVZZBTQjhV8WuAQAwfnR3S8uX++yZaGlTd7f09NMeskQhTQi+7fbzz0sPPuhLoTKZNk161at86VTUs2bx4vSGwG1tHgztvXd6ABOCz6Dp65P22ce33KYPDYDXv77YFQAARqosgxoAAAqlp8dDmu7uREjT1SU9+aQvRYqWGMVi0vr10uOPS48+6gFKJgsXSi97mc+a2bHD+9DMnz9wqVPUiybbLJqODu9Fs/vuvhQqU68aAAAAlCeCGgAAsujp8ZkxnZ2JnZw6Oz2kkQaGNKtWeaCTrR+NmXTYYdJ++/nMnPb2zEuddu3ykCfTLJpou+2JE6VjjvEgBwCS3XyzPzKzBgDKF0ENAAAZ9PZKDz3kwUkUiHR0eEhTVZXYlru725c63X139n40tbXSscdK8+ZlX+qUvKPTokUDZ9FEy5xiMWn//X0mTeqW3AAgSd//vj8S1ABA+SKoAQAgRRTS7NwpTZ/uY7t2SU884dtyRyFNZ6cvdbrrruz9aCZP9n40zc1+v2hXpwkTEte0t3vgs2iRNxdODmE6O/158+f7LJvUZVAAAACoLAQ1AAAk6e2VHn7Y+8dEIU1bm8+kqatLBCXt7dI99/hOUNn60cyfL7385Yl7pC51imbRTJzoM2WiACg619Li/Wde9jKWOQEAAIwXBDUAAMRFIU1rayKkaW31LbgbGz2okXw77L//3cObbFthH3SQdPDBvtTJzJv+NjUlznd2+rmFCz3ASd6xaccOn2Gzzz7SHnuwmxMAAMB4QlADAIB8VswjjwwMaVpaPKRpbvaQJtp++8YbfYenTCFNTY03+t19d1+yNHmyz6yJljr19/t4XZ106KED+9T09HgINHOmdPTRA4MdAAAAjA8ENQCAca+vz2fSbN+eCGm2bJGefda3z54wwQOWFSukv/zFlzFl0tzs/WiamvyaefMG7tzU3e29bObP96Mm/r9wCB4KmXl4M3du9pk6AAAAqGwENQCAcS3TcqeNG6UXXpCmTPFlR7GYb9N9223+diZz5vjOTrGYBz/JS51C8OVMEyb4kqjJkxPP6+z0c3vs4c+JllcBAABgfCKoAQCMW6khTQjSunXSiy/6NtnV1X7N3/4m3Xdf9i2x991XOuQQ7zmTutSpp8dn18yZ42FM8hKobdu8OfExx9AsGMDoWLas2BUAAEaKoAYAMC5lCmlWr5bWrk2ENB0d0nXX+eyaTA19q6ulo47yfjQdHb5kadasxLKltjYPZPbbLzFbR/LlTx0d0uLF0p57JpZAAQAAAHxrCAAYd3p7pYceSmzB3d8vrVzpS56mTvWZM1u2SFdf7b1jMoU0jY3Sccf5Y+pSp2jb7RkzPIiJljP19fksmilTpFe8wvvfAAAAAMkIagAA40pPj/ebaWvzkKavz2fMbN3qy4/MpOee85k0PT2ZlzvNmOH9aPr7pYYGn1ETLWnatcvvuffeAxsJt7b6+IEH+tKobMuoAGAkzj/fH6+8sphVAABGgqAGADBudHdLy5d7A9/p031mzbPPJkKbEKS77vKmwVVVmXdeWrzY+9H09PhSp5kz/dpoFs2UKX5NfX3iNVtbvUfNfvt5sAMAY2XFimJXAAAYKYIaAMC4EIU0XV2+vKm7W3r6aX9/yhQPXm64QXr88cw9Y6qqpKVLpd1280AnealTR4ffZ6+9PJCpqvJrtm3zex1xxMDeNQAAAEA2BDUAgIrX1SU98ICHMVOm+IyaJ5/0pUuTJ0vbt3s/mo0bM4c09fXeU6apyXvSREud+vu9z01jo8+yaW726zs7pZ07pYULfXZNbW0hP1oAAACUM4IaAEBF6+jwkCYW85Bm1y7piSc8aJk40fvTXHuthzmZQppp03z77Koqny0TLXXq7vZ7zZ/vwU11tb9GS4svbzrmGJ+5AwAAAAwHQQ0AoGLt2uUhjVli5szTT/sMmNpa6V//kv7xD782085OCxdKBx3koc7ChT6jJgSfRVNTIx18cGLnpmjL7SVL/Fq23AYAAEA++DYSAFCRdu6U7rvPA5nmZmnzZt/NaeJED1t+9zsPbaqr03vHVFVJhx3mzYInT/ZZMxMm+NKptjafWROFMX19PotmyhTp8MP9/gAAAEC+CGoAABWnpcVn0jQ2+jKktWulVas8TGlp8ZBmy5bMs14aG6Wjj/bAZbfdfDcoMw9+QpD239+XQ0m+m1Nvr3TAAWy5DaA0nHRSsSsAAIwUQQ0AoKJs2iQ9+KDPhKmtlV58UVq/3kOaZ5+Vrr8+ez+aWbN8Vkxzs7THHh7a9PX5UqcZM6Q995Tq6nxmTUtLYsvtxsaCf5gAkNF55xW7AgDASBHUAAAqxksv+fba0SyYZ5/1QGXyZOnvf5fuvttnxWQKafbdV1q0yAOZ3XbzJVFtbd4geJ99fFzyLberqnzL7dmz2XIbAAAAo4ugBgBQ9kKQnn/ejxkzfBbMM8/4zJnqauk3v/GlT2bpTYMnTPB+NHPmSAsW+Myb/v5E35lFi3x77s5On1mzxx7eMLiurggfKAAM4YUX/HHx4uLWAQDIH0ENAKCs9fVJTz7py5tmzZLa26WnnvJAZvNm6YYbvL9MpqbBkyb5UqcopKmr892bens9oJk920ObLVsSW25H/WkAoBRdcIE/LltW3DoAAPkjqAEAlK3ubunhh32my6xZiZ2dGhqke+7xo7c381Kn+fOlAw+Udt9dmjnTx7Zt81k0Bx7o92hr85k0ixd7fxq23AYAAMBY41tOAEBZ2rVLWr7ce8hMm+ZLm9au9XPXXuvv9/enhytVVd4AeO+9fYvt5mafhdPT44HMrFl+z02bpKlTvRcNW24DAACgUAhqAABlZ+tW39mpvt53XHr6ae8ps2GDdOutvtQpUz+axkbvR7NokTcMNkvMojngAL9fa6v3vDn4YGnePLbcBgAAQGER1AAAykYIvrPTk096uNLbKz32mM+Iuftu703T3Z25H83s2d6PZtEif257uz8/mkXT3e1Lp+bP99k29fXF+AgBAAAw3hHUAADKQizm222/+KLv7NTS4v1otmyR/vY3nxkTi6UvdTLzrbcPPdT70VRX+3OnTvXQZsIEf25Dg3T00b61NwAAAFAsBDUAgJLX1SU9+qgHLNOn+6ya1aulxx+XHnrIG/5K6SFNQ4P3mDngAA93du3yWTl77+0NhHfs8IbBe+/t226nLpUCAAAACo2gBgBQ0nbs8H40IXhT3yeflFaskO66y5cq9fRkXuo0b5501FG+tKmmRtq+3cOahQv9/KZNvhxqv/2kpqaCf1gAMCauuKLYFQAARoqgBgBQstat85k0kyZJHR3S/ff7Tk9PPOGzbDItdaqpkQ45xGfSRLNoens9kJk82ZsF19ZKRx7ps2pSAx4AKGeLFxe7AgDASBHUAABKTl+f95958UXvJbN+vXTffdI99/jMmK4u340pNaSZNk16xSt8KVNVlYcyc+dKCxZ40NPSIi1Z4rNqUp8LAAAAlAK+TQUAlJT2dumRR3wmzMSJ/vbf/y49/7wHNH19mUOWAw6QXvlK39Gprc370xx8sM+eaWnxnZ1Y5gSg0n3ve/543nnFrQMAkD+CGgBAyVi/3rfbrqvzZU3XXSfde6+HN5kaBofgy5le9SoPYbq7PeDZc09vOrxjh1935JG+DIplTgAq3S23+CNBDQCUL4IaAEDR9fb61turV/ssmscek5YtkzZu9PCltzfzLJqDD/aQpr7eA5qZM30L7q4uf3+//RJbcgMAAADlgKAGAFBUra3eMLi722e8/OpXvstTLJZ5Fk1/v8+Wee1rvddMR4f3oznoID/f1ubje+3lAQ4AAABQTghqAABFEYtJK1d675m6Ot/R6cYbfSZMT4/PoknedjsEf/vII6XjjvPn9/T4DicNDR7qzJrl5ydOLO7HBgAAAOSLoAYAUHBtbb68accOafNm6eqrpbVr/VxXlz8mz6KJxaR586STTvJmwT090m67+S5PnZ0e9Bx6qO8QBQAAAJQzghoAQMHEYt6H5tlnPZC5/npp+XKfKdPT4+dTA5r6eunEE6X99/dZNlOnSrNn+1Kp6mpp6VLvTUOjYAAAAFQCghoAQEHs2CE9/ri0aZN0113SP/7hwUu0hKmqKhHShOC9aA48UDr+eA9hGht9Vk1fn197+OG+1KmqqqgfFgCUlEWLil0BAGCkCGoAAGOqt1dascJn0TzwgHTrrb7ddgg+K0YaGNDEYtLcudIJJ/iW2lFAI0kTJkgHHCDNmcNOTgCQyZVXFrsCAMBIEdQAAMZECN5/5rHHfAbN3/8utbT4eDSTJnmZU1+fNGmSb7e9cKE3CJ43zwOZ+npp7709wCGgAQAAQCUjqAEAjLq2Nl/mdNNNHtJs2eLBTCzmgUx1dSKk6euTamulV77St9hubvYeNDU1UlOTBzTMoAEAAMB4QVADABg1PT3Sk09K11wj3Xmn1NrqQUx/v8+iMRsY0FRXS4cc4g2Bp0/3njM1NdLkyR7QzJxJQAMAw3HKKf64bFlx6wAAHp83hgAAEXFJREFU5I+gBgAwYrGY9NRT/7+9ew+2q6oPOP79BUwChBtDopDwJoCkdhwQkkixoT5GtFJLC1RbpQZfHcX6GAcfIIKijjI40CpVRAsThaJYQVBxBCwW5WWQpxV5yCNIEh8EyPOG5P76x9qHezi5Se7NTc7eJ/l+Zvbsc9be597fyazcs89vr/Vb8M1vlgTNsmUlMdOZoMkcLAY8YwbMnFmW2X7+88tUp8mTYf/9y95VnCRJkrQtMlEjSdpkmaVA8Lx5cOutZURNa5ntNWvWTdBElETMrFmlDk1fX5netPvu5fnEiXW/I0mSJKleJmokSSP2zDNw7bVwySVlJE1rie3OBM3AwOAImv32g9mz4YADSnJm4sTSNm1aGU0jSZIkyUSNJGkEFiyAyy+HH/6wFAhes6YkbdasKUmaVoKmvWjwQQcNjqCZOLEUCt53X+vPSJIkSUMxUSNJ2qAVK+CGG+DKK+H222HVqpKcaS2xPTBQEjTbbTeYoHne80qCZvbskqCZNKkkZ6ZNg513rvsdSZIkSc1lokaStI5Vq2D+fPjJT+DGG2HJEujvHxw9s2ZNOS+ibJklSbPjjmWJ7VmzYM89Ya+9yjZ58uBqT5IkSZLWz8tmSRIAS5fCL38JN99ckjNPPVVWb2pP0LRGz7SSMwMDpf7MlClw6KFw+OGwxx6l9swLX2jtGUnqtpNOqjsCSdJomaiRpG1UJjz0UBk5M39+KQrc31+SMytXlsftxYFhMEEDMHZsmc50+OFw2GGlSPCuu8KECS6tLUl1ee1r645AkjRaJmokaRuRWYoB33MP3H132T/xRBkts2JF2Vr1Z9aufe5r2+vQTJkCM2fCnDlw8MGlKHBfn8kZSZIkaXMwUSNJW6nly+GBB+D+++G+++BXv4Knny5Jl/bkzMqV5fnAwOBomZaIMrWprw9e8hJ45StLgmbKlLLEtskZSWqWH/2o7B1ZI0m9y0SNJPW4zLJU9qOPlu3BB0uC5vHHB89ZswZWry6JmeXLy8iZVs2Z1s9oJV3GjCkjZ/r6yoiZ17wGjjyyrNw0blzX354kaQTOO6/sTdRIUu8yUSNJPSCz1I5ZtAgWLy77xx4riZkFC0ripd3atSUxs3LlYGJm9erBKU3tI2fGjCnLaY8dC1Onlnozr3pVWVrbKU2SJElSd5moGUJEjAM+BZwATALuBE7NzOtqDUzSVmn1anjyybIEduf+iSdKYmbx4jIaZigDAyUB098/OJ2pv7/83NZ0plYR4NZUprFjy9bXV5bTPuKIsk2fbmJGkiRJqpOJmqFdBBwLnAs8AMwFro6IIzPzpvrCklSXzJIMaa2C1Bqx0t+//q11vDXdaNmyoff9/cOPoVVfpjVaplUAuD0pA4NLaI8ZU6YrjR1blsru64MXvxhe+tKyzZhRjkmSJElqBhM1HSJiFvAm4IOZeW7VNg+4B/g8MGdDr1+4ED71qfUf7yzUOdLjG7M5fn4TYhjt6+t+D6P9/d34Hb3wHrrRV1qjUdoTMEM9b9Vy2dLa43nmmcGkz8qVz60r04qnlYxpJWTGjy9b6/Fee5VkzEEHwYEHliW0t/cvvyRJktRYXq6v6zjgGeBrrYbMXBURXwc+ExFTM3Ph+l68fDn84hddiFJS42U+dyROewKmtbVPUWqNiGnfWtOQWgmZHXYYTMKMHVseb789TJgA++wDe+9dkjPTp5dtp51q/SeQJEmSNEImatZ1CHBvZi7raL8VCOBgYL2Jmv2fuo2rvm+BB0mSJHXfVa0HXo5KUs8yUbOuqcDvhmhvJWemdR6IiHcB7yrPtlsT7LZ4SwWnrd2ynWDC8rqj2HqNuExuPGf37GSq9rEvAwlZjYcZyMGxMWsHYGDtYNuz526GSWVDmgL8cQv9bG3d7DsaDfuPNpV9R5vKvqPRaFr/2XuoRhM169oBGKq056q248+RmV8FvgoQEfMzHztsy4WnrVnpP0/afzRipe+kfUcjZt/RaNh/tKnsO9pU9h2NRq/0nzF1B9BAK4FxQ7SPbzsuSZIkSZK02ZmoWddCyvSnTq22x7sYiyRJkiRJ2oaYqFnXHcBBETGho312tb9zI6//6maPSNsS+482lX1Hm8q+o9Gw/2hT2Xe0qew7Go2e6D+RW6yuZW+KiNnAzcAHM/Pcqm0ccA+wODNfXmN4kiRJkiRpK2Yx4Q6ZeUtEXAacFRFTgQeBt1KqMc+tMzZJkiRJkrR1c0TNECJiPHAm8BZgEnAXcEpmXltrYJIkSZIkaatmokaSJEmSJKkhLCa8GUTEuIj4fEQ8HhErI+LmiHhV3XGp+SLisIi4PCIeqfrOooj4UUT8Rd2xqTdExMyI+EFELImIZRFxZ0TMrTsuNVtEvCwirqv6zFMRcUVETK87LjVLREyNiM9FxP9ExNKIyIj4q45zJkfEyRFxQ0T8ISKejIibIuL4eqJWEwyn71TnPVwd69w+1/2o1RQj6D/jI+KUiPh1RKyIiAURcUlEHNj9qFW36pr4vIj4v4hYHhGPRsSlEbF/x3lvjIhvRsR9Vd+6vqaQN8gaNZvHRcCxwLnAA5RaNldHxJGZeVN9YakHTKf8P7yAsjT884E3A/8bEa/LzGtqjE0NFxGvA74HXA+cBjwDHAjsWWNYariImAn8FHgYOJ1y0+Y9wA0RcUhmLq4xPDXLi4CPUK5t7gKGuolwOPAZ4IfAp4E1lGuib0fEJzLzzC7FqmYZTt9puY1yDd3uni0TlnrEcPvPN4BjKKv43A7sAZwEHBURMzLz91s+VDXIR4AjgMso/WY34L3A7RExKzN/XZ33buBQYD4wuY5Ah8OpT6MUEbOAW3juKlHjKR8wj2fmnBrDUw+KiB2B3wLzM/PouuNRM0XEROA+4NLMfH/d8ah3RMTVwEzggMxcUrVNpfSnr2fmB2oMTw0SETsDYzPzTxFxDHA58IrMvL7tnH2Bgcx8pK0tgGspSZzJmbmyq4GrdsPpO9V5DwN3ZOYx3Y5RzTXMvz27AouAszPz5Lb2o4GrgLdl5oVdDVy1qmYkzM/M1W1tBwB3U66X51Zte1K+p6+NiDuAJzPzr7of8YY59Wn0jqPcxf5aqyEzVwFfB15eXfxKw5aZK4A/UEbXSOvzT5Q+8gkoFzXVlyNpY44AftxK0gBk5kLKKJt/qC0qNU5mLs3MP23knIfakzRVWwJXADsA+2yxANVYw+k77aoyAjtuyZjUO4bZf/qqfeco0EXV3gTxNiYzb2xP0lRt9wO/Ama0tS3IzLXdjm+kTNSM3iHAvZm5rKP9ViCAg7sekXpO9SV7SkS8KCI+C/w5cF3dcanRXg3cC/x1RCwAngaeqOZ0b1dvaGq4cQx9AbsCmOoNBm0mu1X7P9YahXrBa4DlwPKIeDAi3lV3QOoJDwELgA9FxN9ExB4R8TLg34BfU6aGaxtX3cTclR78LLJGzehNBX43RPvCaj+ti7God11ImdMPsBr4CvDZ+sJRD9ifUovmIuAsytzsoynzc8cDH6grMDXeb4DDI2JMZg4ARMRYYHZ1fBqDn2HSiEXELsA7gOsz8w91x6NGuwu4gTL18gXAO4HzI2KXzLSgsNYrM9dExHHAJcCVbYduBuY45VKVNwO7A6fWHchImagZvR2A/iHaV7Udlzbmk8D5lCJoJ1DueD+PofuWBDABmAR8NDM/X7V9NyImAO+JiE9nZs/dPVBX/AfwZeCCiPgCZXTtxyk3HsDPLY1CRIwBLgYmAu+rORw1XGa+of15RFwI/Aw4LSK+nJlP1ROZesQSyo2qb1Nqhu4PfAz4TkQclZleR2/DIuIg4DzK35Rv1BzOiDn1afRWUr5UdxrfdlzaoMy8OzOvqYqeHUWpRH5RvVGp4Vp/W/6ro/1iSpJvVnfDUa/IzNaIvRMo87bvpqxAd1Z1SudUXmkkvkj5HDsxM++uOxj1lqpuxLnAjpRi1NKQqkUVbgB+lpmnZOb3MvMLlBHqRwL/XGuAqlVE7Ab8gJLMO741griXmKgZvYUM3oVs12p7vIuxaCuQmc9Q5tX+fUR4Z1vr05qa0llEr/V8UhdjUY/JzFMpc7b/EnhJZs6kXBMk8GCdsal3RcTplKXeP5yZnUlkabgWVPtdao1CTXcs5XOsfdoTmflTSt2+I+oISvWrknhXU0Z2HpWZizbykkYyUTN6dwAHVdMN2rXm+t/Z3XC0ldiBUox657oDUWPdVu1372jfo9pbF0IblJlLMvNnbaMeXg3cmplL64xLvSkiTgLOAM7JzLNrDke9bb9q7+eYNmTXav+cBRSq4rHbYYmPbVJEjKcsz34gcHRm/qbmkDaZiZrR+w5lmsE7Wg0RMQ44Efh5ZjqiRusVES8Yoq0POB5YkJm/735U6hGXVfu3txqqi5N3UFbPuLmOoNSbIuKNwEzKlANpRKr+8++UqZcfqjkc9YiI2KWqadTeNh44GVgK3FRLYOoV91X7N3W0vwHYiVK7RtuQatXTb1GmTR6fmT19LWymcZQy85aIuAw4q1rS9EHgrcDewNw6Y1NP+FZErAJuBBZRVvE5kTIqovODR3pWZt4WEfOAj0XEC4FfAq+n1Ib4cGY+XWuAaqyIeCVwCvBj4E+UC5q5wMWZeWmNoamBIuLj1cMZ1f6EiHg58GRmfikiZgHzKH3pOuDNJWf8rGsys3OKprYBG+s7lC/Up0bEd4CHgcmUa+gDgXdnpvWytmHD6D9XUeqsfTIi9qUUEz4AeC9lRd4Luxyy6vcFyt+Vq4BdIuItbceWZeYVABExB5hTte8KTGzrb1dm5l1dineDIjPrjqHnVdn/M4G3UOpC3AWckpnX1hqYGi8i3kYpdvZnlL7zJGUkxNnVHFtpvaollU+jXNjuBvyWMu3g/FoDU6NFxAGUVRAOoUyvvB+4APhSLxbb05YVEeu7UHwkM/eJiLls+AvRKzLz+s0emBpvGH3nUMp0uUMoS3P3U246nJ2Z3+9OlGqqjfWf6pxJlOug11Nuki8FrgE+lpmPdCNONUdEXE8pJD2U9n5zBnD6es47MTMv2tyxbQoTNZIkSZIkSQ1hjRpJkiRJkqSGMFEjSZIkSZLUECZqJEmSJEmSGsJEjSRJkiRJUkOYqJEkSZIkSWoIEzWSJEmSJEkNYaJGkiRJkiSpIUzUSJIkbSYRcUZEZN1xSJKk3mWiRpIkqSEi4syIWBsR+3W0R0RcERH9EXFEXfFJkqQtz0SNJElSc5wHrAHe19F+GvC3wPsy8+ddj0qSJHWNiRpJkqSGyMxFwKXA2yKiDyAiXg+cAVyQmefXGJ4kSeoCEzWSJElbUKtuTUTsGxHzIuKparswInYc4iXnADsDb4+IA4CLgZuB93YzbkmSVA8TNZIkSd3x38AOwEeBbwNzgdM7T8rMO4DrKdOfrgBWAMdm5uruhClJkuq0fd0BSJIkbSN+kZn/0noSEZOBtwMfGeLcc4DvAauBV2Tmwu6EKEmS6maiRpIkaQgRMQYYO5xzM3PVME77SsfzG4C/i4i+zHy649iMan93Zt44nBgkSdLWwalPkiRJQ5sDrBzOFhFThvHzHu14vqTaT2pvjIjXAZ8F7gcOjYhZm/oGJElS73FEjSRJ0tDuBU4c5rlLh3HO2vW0x7MPSvHgS4AbKctx/xb4IPCPw4xDkiT1OBM1kiRJQ6iWyr6oW78vInamFA9eDhyXmU9ExNeA90fEyZn5WLdikSRJ9XHqkyRJUs0iIoB5wHTKCk+Lq0NfpIy4+de6YpMkSd1lokaSJKl+nwCOAd6Tmbe0GjPzEeC7wDsjYqeaYpMkSV1kokaSJKlebwBOB76cmf85xPFzKAWH53YzKEmSVI/IzLpjkCRJkiRJEo6okSRJkiRJagwTNZIkSZIkSQ1hokaSJEmSJKkhTNRIkiRJkiQ1hIkaSZIkSZKkhjBRI0mSJEmS1BAmaiRJkiRJkhrCRI0kSZIkSVJDmKiRJEmSJElqiP8HNVavr7308DEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x1152 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from dynesty import plotting as dyplot\n",
    "\n",
    "lnz_truth = ndim * -np.log(2 * 10.)  # analytic evidence solution\n",
    "fig, axes = dyplot.runplot(res, lnz_truth=lnz_truth)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not eval(overwrite):\n",
    "    fig.savefig(diagnosis_plot, format = 'png', dpi = 384, bbox_inches = 'tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figband = plt.figure(figsize = (12, 9))\n",
    "plt.plot(timesrd_final_tsh,gwdatanew_re_tsh, \"green\", alpha=0.9, lw=3, label=r'$res_{240}$')\n",
    "plt.plot(timesrd_final_tsh,dict[model](vars_ml).real,'bo', alpha=0.9, lw=3, label=r'$fit$')\n",
    "onesig_bounds = np.array([np.percentile(samps[:, i], [16, 84]) for i in range(len(samps[0]))]).T\n",
    "samples_1sigma = filter(lambda sample: np.all(onesig_bounds[0] <= sample) and np.all(sample <= onesig_bounds[1]), samps)\n",
    "samples_1sigma_down = list(samples_1sigma)[::downfactor]\n",
    "for sample in samples_1sigma_down:\n",
    "    plt.plot(timesrd_final_tsh, dict[model](sample).real, \"r-\", alpha=0.1, lw=1)\n",
    "plt.title(r'Comparison of the MC fit data and the $1-\\sigma$ error band')\n",
    "plt.legend()\n",
    "plt.xlabel('t')\n",
    "plt.ylabel('h')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not eval(overwrite):\n",
    "    figband.savefig(fit_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not eval(overwrite):\n",
    "    with open(samples_file,'w') as file:\n",
    "        writer = csv.writer(file)\n",
    "        writer.writerow(labels)\n",
    "        writer.writerows(samps[::downfactor])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}