PortOpt.Opt.MaxSharpe.MinVol.Real.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Packages and Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import scipy.optimize as sco\n",
    "\n",
    "#load csv containing return data on assets\n",
    "assets = pd.read_csv('/home/Portfolio_2.csv',header='infer',index_col='Date') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-04-01</th>\n",
       "      <td>549.489990</td>\n",
       "      <td>81.669998</td>\n",
       "      <td>59.017143</td>\n",
       "      <td>370.260010</td>\n",
       "      <td>73.779182</td>\n",
       "      <td>139.591400</td>\n",
       "      <td>81.300003</td>\n",
       "      <td>31.535204</td>\n",
       "      <td>68.523880</td>\n",
       "      <td>87.257195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-02</th>\n",
       "      <td>541.309998</td>\n",
       "      <td>81.559998</td>\n",
       "      <td>59.154285</td>\n",
       "      <td>372.250000</td>\n",
       "      <td>74.233482</td>\n",
       "      <td>140.882874</td>\n",
       "      <td>81.120003</td>\n",
       "      <td>32.055969</td>\n",
       "      <td>67.968102</td>\n",
       "      <td>87.807785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-06</th>\n",
       "      <td>543.950012</td>\n",
       "      <td>82.440002</td>\n",
       "      <td>60.330002</td>\n",
       "      <td>377.040009</td>\n",
       "      <td>74.900414</td>\n",
       "      <td>141.691223</td>\n",
       "      <td>80.980003</td>\n",
       "      <td>32.287418</td>\n",
       "      <td>69.050911</td>\n",
       "      <td>88.532707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-07</th>\n",
       "      <td>544.859985</td>\n",
       "      <td>82.320000</td>\n",
       "      <td>60.494286</td>\n",
       "      <td>374.410004</td>\n",
       "      <td>74.136803</td>\n",
       "      <td>141.022232</td>\n",
       "      <td>80.580002</td>\n",
       "      <td>32.104183</td>\n",
       "      <td>67.824371</td>\n",
       "      <td>88.284943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-08</th>\n",
       "      <td>548.840027</td>\n",
       "      <td>82.279999</td>\n",
       "      <td>63.049999</td>\n",
       "      <td>381.200012</td>\n",
       "      <td>75.084068</td>\n",
       "      <td>141.226639</td>\n",
       "      <td>83.529999</td>\n",
       "      <td>32.046318</td>\n",
       "      <td>67.345238</td>\n",
       "      <td>88.119774</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 GOOGL         FB       NFLX        AMZN       BBBY  \\\n",
       "Date                                                                  \n",
       "2015-04-01  549.489990  81.669998  59.017143  370.260010  73.779182   \n",
       "2015-04-02  541.309998  81.559998  59.154285  372.250000  74.233482   \n",
       "2015-04-06  543.950012  82.440002  60.330002  377.040009  74.900414   \n",
       "2015-04-07  544.859985  82.320000  60.494286  374.410004  74.136803   \n",
       "2015-04-08  548.840027  82.279999  63.049999  381.200012  75.084068   \n",
       "\n",
       "                  COST       DLTR        FOX       Gold        PEP  \n",
       "Date                                                                \n",
       "2015-04-01  139.591400  81.300003  31.535204  68.523880  87.257195  \n",
       "2015-04-02  140.882874  81.120003  32.055969  67.968102  87.807785  \n",
       "2015-04-06  141.691223  80.980003  32.287418  69.050911  88.532707  \n",
       "2015-04-07  141.022232  80.580002  32.104183  67.824371  88.284943  \n",
       "2015-04-08  141.226639  83.529999  32.046318  67.345238  88.119774  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assets.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-23</th>\n",
       "      <td>1026.550049</td>\n",
       "      <td>159.389999</td>\n",
       "      <td>300.940002</td>\n",
       "      <td>1495.560059</td>\n",
       "      <td>21.299999</td>\n",
       "      <td>180.839996</td>\n",
       "      <td>91.949997</td>\n",
       "      <td>35.450001</td>\n",
       "      <td>83.919998</td>\n",
       "      <td>106.150002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-26</th>\n",
       "      <td>1054.089966</td>\n",
       "      <td>160.059998</td>\n",
       "      <td>320.350006</td>\n",
       "      <td>1555.859985</td>\n",
       "      <td>21.070000</td>\n",
       "      <td>187.220001</td>\n",
       "      <td>95.209999</td>\n",
       "      <td>36.580002</td>\n",
       "      <td>85.220001</td>\n",
       "      <td>106.809998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-27</th>\n",
       "      <td>1006.940002</td>\n",
       "      <td>152.220001</td>\n",
       "      <td>300.690002</td>\n",
       "      <td>1497.050049</td>\n",
       "      <td>20.250000</td>\n",
       "      <td>183.149994</td>\n",
       "      <td>93.629997</td>\n",
       "      <td>36.080002</td>\n",
       "      <td>83.660004</td>\n",
       "      <td>107.639999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-28</th>\n",
       "      <td>1005.179993</td>\n",
       "      <td>153.029999</td>\n",
       "      <td>285.769989</td>\n",
       "      <td>1431.420044</td>\n",
       "      <td>20.610001</td>\n",
       "      <td>183.610001</td>\n",
       "      <td>93.910004</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>82.320000</td>\n",
       "      <td>109.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-29</th>\n",
       "      <td>1037.140015</td>\n",
       "      <td>159.789993</td>\n",
       "      <td>295.350006</td>\n",
       "      <td>1447.339966</td>\n",
       "      <td>20.990000</td>\n",
       "      <td>188.429993</td>\n",
       "      <td>94.900002</td>\n",
       "      <td>36.369999</td>\n",
       "      <td>83.239998</td>\n",
       "      <td>109.150002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                  GOOGL          FB        NFLX         AMZN       BBBY  \\\n",
       "Date                                                                      \n",
       "2018-03-23  1026.550049  159.389999  300.940002  1495.560059  21.299999   \n",
       "2018-03-26  1054.089966  160.059998  320.350006  1555.859985  21.070000   \n",
       "2018-03-27  1006.940002  152.220001  300.690002  1497.050049  20.250000   \n",
       "2018-03-28  1005.179993  153.029999  285.769989  1431.420044  20.610001   \n",
       "2018-03-29  1037.140015  159.789993  295.350006  1447.339966  20.990000   \n",
       "\n",
       "                  COST       DLTR        FOX       Gold         PEP  \n",
       "Date                                                                 \n",
       "2018-03-23  180.839996  91.949997  35.450001  83.919998  106.150002  \n",
       "2018-03-26  187.220001  95.209999  36.580002  85.220001  106.809998  \n",
       "2018-03-27  183.149994  93.629997  36.080002  83.660004  107.639999  \n",
       "2018-03-28  183.610001  93.910004  35.500000  82.320000  109.180000  \n",
       "2018-03-29  188.429993  94.900002  36.369999  83.239998  109.150002  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "assets.tail(5) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate Daily Returns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-02</th>\n",
       "      <td>-0.014887</td>\n",
       "      <td>-0.001347</td>\n",
       "      <td>0.002324</td>\n",
       "      <td>0.005375</td>\n",
       "      <td>0.006158</td>\n",
       "      <td>0.009252</td>\n",
       "      <td>-0.002214</td>\n",
       "      <td>0.016514</td>\n",
       "      <td>-0.008111</td>\n",
       "      <td>0.006310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-06</th>\n",
       "      <td>0.004877</td>\n",
       "      <td>0.010790</td>\n",
       "      <td>0.019875</td>\n",
       "      <td>0.012868</td>\n",
       "      <td>0.008984</td>\n",
       "      <td>0.005738</td>\n",
       "      <td>-0.001726</td>\n",
       "      <td>0.007220</td>\n",
       "      <td>0.015931</td>\n",
       "      <td>0.008256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-07</th>\n",
       "      <td>0.001673</td>\n",
       "      <td>-0.001456</td>\n",
       "      <td>0.002723</td>\n",
       "      <td>-0.006975</td>\n",
       "      <td>-0.010195</td>\n",
       "      <td>-0.004721</td>\n",
       "      <td>-0.004940</td>\n",
       "      <td>-0.005675</td>\n",
       "      <td>-0.017763</td>\n",
       "      <td>-0.002799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-08</th>\n",
       "      <td>0.007305</td>\n",
       "      <td>-0.000486</td>\n",
       "      <td>0.042247</td>\n",
       "      <td>0.018135</td>\n",
       "      <td>0.012777</td>\n",
       "      <td>0.001449</td>\n",
       "      <td>0.036610</td>\n",
       "      <td>-0.001802</td>\n",
       "      <td>-0.007064</td>\n",
       "      <td>-0.001871</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "               GOOGL        FB      NFLX      AMZN      BBBY      COST  \\\n",
       "Date                                                                     \n",
       "2015-04-01       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2015-04-02 -0.014887 -0.001347  0.002324  0.005375  0.006158  0.009252   \n",
       "2015-04-06  0.004877  0.010790  0.019875  0.012868  0.008984  0.005738   \n",
       "2015-04-07  0.001673 -0.001456  0.002723 -0.006975 -0.010195 -0.004721   \n",
       "2015-04-08  0.007305 -0.000486  0.042247  0.018135  0.012777  0.001449   \n",
       "\n",
       "                DLTR       FOX      Gold       PEP  \n",
       "Date                                                \n",
       "2015-04-01       NaN       NaN       NaN       NaN  \n",
       "2015-04-02 -0.002214  0.016514 -0.008111  0.006310  \n",
       "2015-04-06 -0.001726  0.007220  0.015931  0.008256  \n",
       "2015-04-07 -0.004940 -0.005675 -0.017763 -0.002799  \n",
       "2015-04-08  0.036610 -0.001802 -0.007064 -0.001871  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns = (assets/assets.shift(1))-1\n",
    "returns.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check Distribution of Returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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p1i1lLVqM89It8WpEZZ6ajnEnz+gecsgh1m7z589v+zSalUfZ6PCT7kaKcZHj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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3339410470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns.hist(bins=100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate Log Returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "log_returns = np.log((assets/assets.shift(1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-02</th>\n",
       "      <td>-0.014998</td>\n",
       "      <td>-0.001348</td>\n",
       "      <td>0.002321</td>\n",
       "      <td>0.005360</td>\n",
       "      <td>0.006139</td>\n",
       "      <td>0.009209</td>\n",
       "      <td>-0.002216</td>\n",
       "      <td>0.016379</td>\n",
       "      <td>-0.008144</td>\n",
       "      <td>0.006290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-06</th>\n",
       "      <td>0.004865</td>\n",
       "      <td>0.010732</td>\n",
       "      <td>0.019680</td>\n",
       "      <td>0.012786</td>\n",
       "      <td>0.008944</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>-0.001727</td>\n",
       "      <td>0.007194</td>\n",
       "      <td>0.015806</td>\n",
       "      <td>0.008222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-07</th>\n",
       "      <td>0.001672</td>\n",
       "      <td>-0.001457</td>\n",
       "      <td>0.002719</td>\n",
       "      <td>-0.007000</td>\n",
       "      <td>-0.010247</td>\n",
       "      <td>-0.004733</td>\n",
       "      <td>-0.004952</td>\n",
       "      <td>-0.005691</td>\n",
       "      <td>-0.017922</td>\n",
       "      <td>-0.002802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-08</th>\n",
       "      <td>0.007278</td>\n",
       "      <td>-0.000486</td>\n",
       "      <td>0.041379</td>\n",
       "      <td>0.017973</td>\n",
       "      <td>0.012696</td>\n",
       "      <td>0.001448</td>\n",
       "      <td>0.035955</td>\n",
       "      <td>-0.001804</td>\n",
       "      <td>-0.007089</td>\n",
       "      <td>-0.001873</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               GOOGL        FB      NFLX      AMZN      BBBY      COST  \\\n",
       "Date                                                                     \n",
       "2015-04-01       NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "2015-04-02 -0.014998 -0.001348  0.002321  0.005360  0.006139  0.009209   \n",
       "2015-04-06  0.004865  0.010732  0.019680  0.012786  0.008944  0.005721   \n",
       "2015-04-07  0.001672 -0.001457  0.002719 -0.007000 -0.010247 -0.004733   \n",
       "2015-04-08  0.007278 -0.000486  0.041379  0.017973  0.012696  0.001448   \n",
       "\n",
       "                DLTR       FOX      Gold       PEP  \n",
       "Date                                                \n",
       "2015-04-01       NaN       NaN       NaN       NaN  \n",
       "2015-04-02 -0.002216  0.016379 -0.008144  0.006290  \n",
       "2015-04-06 -0.001727  0.007194  0.015806  0.008222  \n",
       "2015-04-07 -0.004952 -0.005691 -0.017922 -0.002802  \n",
       "2015-04-08  0.035955 -0.001804 -0.007089 -0.001873  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_returns.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GOOGL    0.212306\n",
       "FB       0.224318\n",
       "NFLX     0.538202\n",
       "AMZN     0.455631\n",
       "BBBY    -0.420122\n",
       "COST     0.100268\n",
       "DLTR     0.051696\n",
       "FOX      0.047673\n",
       "Gold     0.065021\n",
       "PEP      0.074819\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_returns_means= log_returns.mean()*252\n",
    "log_returns_means"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Covariance Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GOOGL</th>\n",
       "      <td>0.051703</td>\n",
       "      <td>0.037923</td>\n",
       "      <td>0.040084</td>\n",
       "      <td>0.037761</td>\n",
       "      <td>0.006759</td>\n",
       "      <td>0.014809</td>\n",
       "      <td>0.017474</td>\n",
       "      <td>0.016526</td>\n",
       "      <td>0.003415</td>\n",
       "      <td>0.011622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>0.037923</td>\n",
       "      <td>0.063865</td>\n",
       "      <td>0.041359</td>\n",
       "      <td>0.041199</td>\n",
       "      <td>0.006268</td>\n",
       "      <td>0.012379</td>\n",
       "      <td>0.015795</td>\n",
       "      <td>0.018267</td>\n",
       "      <td>0.004893</td>\n",
       "      <td>0.011475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>0.040084</td>\n",
       "      <td>0.041359</td>\n",
       "      <td>0.174764</td>\n",
       "      <td>0.048329</td>\n",
       "      <td>0.011944</td>\n",
       "      <td>0.016129</td>\n",
       "      <td>0.022053</td>\n",
       "      <td>0.023956</td>\n",
       "      <td>0.009260</td>\n",
       "      <td>0.011262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>0.037761</td>\n",
       "      <td>0.041199</td>\n",
       "      <td>0.048329</td>\n",
       "      <td>0.077447</td>\n",
       "      <td>0.004387</td>\n",
       "      <td>0.013007</td>\n",
       "      <td>0.015140</td>\n",
       "      <td>0.020239</td>\n",
       "      <td>0.005545</td>\n",
       "      <td>0.010551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBBY</th>\n",
       "      <td>0.006759</td>\n",
       "      <td>0.006268</td>\n",
       "      <td>0.011944</td>\n",
       "      <td>0.004387</td>\n",
       "      <td>0.099406</td>\n",
       "      <td>0.016719</td>\n",
       "      <td>0.031556</td>\n",
       "      <td>0.020358</td>\n",
       "      <td>0.002565</td>\n",
       "      <td>0.004672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COST</th>\n",
       "      <td>0.014809</td>\n",
       "      <td>0.012379</td>\n",
       "      <td>0.016129</td>\n",
       "      <td>0.013007</td>\n",
       "      <td>0.016719</td>\n",
       "      <td>0.034535</td>\n",
       "      <td>0.021681</td>\n",
       "      <td>0.011282</td>\n",
       "      <td>-0.002043</td>\n",
       "      <td>0.010648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DLTR</th>\n",
       "      <td>0.017474</td>\n",
       "      <td>0.015795</td>\n",
       "      <td>0.022053</td>\n",
       "      <td>0.015140</td>\n",
       "      <td>0.031556</td>\n",
       "      <td>0.021681</td>\n",
       "      <td>0.079864</td>\n",
       "      <td>0.018325</td>\n",
       "      <td>-0.000960</td>\n",
       "      <td>0.010233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FOX</th>\n",
       "      <td>0.016526</td>\n",
       "      <td>0.018267</td>\n",
       "      <td>0.023956</td>\n",
       "      <td>0.020239</td>\n",
       "      <td>0.020358</td>\n",
       "      <td>0.011282</td>\n",
       "      <td>0.018325</td>\n",
       "      <td>0.060808</td>\n",
       "      <td>0.000715</td>\n",
       "      <td>0.008245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold</th>\n",
       "      <td>0.003415</td>\n",
       "      <td>0.004893</td>\n",
       "      <td>0.009260</td>\n",
       "      <td>0.005545</td>\n",
       "      <td>0.002565</td>\n",
       "      <td>-0.002043</td>\n",
       "      <td>-0.000960</td>\n",
       "      <td>0.000715</td>\n",
       "      <td>0.127163</td>\n",
       "      <td>0.006395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP</th>\n",
       "      <td>0.011622</td>\n",
       "      <td>0.011475</td>\n",
       "      <td>0.011262</td>\n",
       "      <td>0.010551</td>\n",
       "      <td>0.004672</td>\n",
       "      <td>0.010648</td>\n",
       "      <td>0.010233</td>\n",
       "      <td>0.008245</td>\n",
       "      <td>0.006395</td>\n",
       "      <td>0.017353</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          GOOGL        FB      NFLX      AMZN      BBBY      COST      DLTR  \\\n",
       "GOOGL  0.051703  0.037923  0.040084  0.037761  0.006759  0.014809  0.017474   \n",
       "FB     0.037923  0.063865  0.041359  0.041199  0.006268  0.012379  0.015795   \n",
       "NFLX   0.040084  0.041359  0.174764  0.048329  0.011944  0.016129  0.022053   \n",
       "AMZN   0.037761  0.041199  0.048329  0.077447  0.004387  0.013007  0.015140   \n",
       "BBBY   0.006759  0.006268  0.011944  0.004387  0.099406  0.016719  0.031556   \n",
       "COST   0.014809  0.012379  0.016129  0.013007  0.016719  0.034535  0.021681   \n",
       "DLTR   0.017474  0.015795  0.022053  0.015140  0.031556  0.021681  0.079864   \n",
       "FOX    0.016526  0.018267  0.023956  0.020239  0.020358  0.011282  0.018325   \n",
       "Gold   0.003415  0.004893  0.009260  0.005545  0.002565 -0.002043 -0.000960   \n",
       "PEP    0.011622  0.011475  0.011262  0.010551  0.004672  0.010648  0.010233   \n",
       "\n",
       "            FOX      Gold       PEP  \n",
       "GOOGL  0.016526  0.003415  0.011622  \n",
       "FB     0.018267  0.004893  0.011475  \n",
       "NFLX   0.023956  0.009260  0.011262  \n",
       "AMZN   0.020239  0.005545  0.010551  \n",
       "BBBY   0.020358  0.002565  0.004672  \n",
       "COST   0.011282 -0.002043  0.010648  \n",
       "DLTR   0.018325 -0.000960  0.010233  \n",
       "FOX    0.060808  0.000715  0.008245  \n",
       "Gold   0.000715  0.127163  0.006395  \n",
       "PEP    0.008245  0.006395  0.017353  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cov_mat = log_returns.cov()*252\n",
    "cov_mat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Correlation Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>FB</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BBBY</th>\n",
       "      <th>COST</th>\n",
       "      <th>DLTR</th>\n",
       "      <th>FOX</th>\n",
       "      <th>Gold</th>\n",
       "      <th>PEP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GOOGL</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.659948</td>\n",
       "      <td>0.421682</td>\n",
       "      <td>0.596727</td>\n",
       "      <td>0.094283</td>\n",
       "      <td>0.350461</td>\n",
       "      <td>0.271933</td>\n",
       "      <td>0.294732</td>\n",
       "      <td>0.042117</td>\n",
       "      <td>0.388017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>0.659948</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.391481</td>\n",
       "      <td>0.585806</td>\n",
       "      <td>0.078667</td>\n",
       "      <td>0.263593</td>\n",
       "      <td>0.221170</td>\n",
       "      <td>0.293131</td>\n",
       "      <td>0.054295</td>\n",
       "      <td>0.344700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>0.421682</td>\n",
       "      <td>0.391481</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.415408</td>\n",
       "      <td>0.090621</td>\n",
       "      <td>0.207611</td>\n",
       "      <td>0.186670</td>\n",
       "      <td>0.232387</td>\n",
       "      <td>0.062117</td>\n",
       "      <td>0.204512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>0.596727</td>\n",
       "      <td>0.585806</td>\n",
       "      <td>0.415408</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.050001</td>\n",
       "      <td>0.251497</td>\n",
       "      <td>0.192502</td>\n",
       "      <td>0.294913</td>\n",
       "      <td>0.055871</td>\n",
       "      <td>0.287823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBBY</th>\n",
       "      <td>0.094283</td>\n",
       "      <td>0.078667</td>\n",
       "      <td>0.090621</td>\n",
       "      <td>0.050001</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.285347</td>\n",
       "      <td>0.354165</td>\n",
       "      <td>0.261850</td>\n",
       "      <td>0.022818</td>\n",
       "      <td>0.112488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COST</th>\n",
       "      <td>0.350461</td>\n",
       "      <td>0.263593</td>\n",
       "      <td>0.207611</td>\n",
       "      <td>0.251497</td>\n",
       "      <td>0.285347</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.412833</td>\n",
       "      <td>0.246201</td>\n",
       "      <td>-0.030832</td>\n",
       "      <td>0.434950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DLTR</th>\n",
       "      <td>0.271933</td>\n",
       "      <td>0.221170</td>\n",
       "      <td>0.186670</td>\n",
       "      <td>0.192502</td>\n",
       "      <td>0.354165</td>\n",
       "      <td>0.412833</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.262965</td>\n",
       "      <td>-0.009527</td>\n",
       "      <td>0.274878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FOX</th>\n",
       "      <td>0.294732</td>\n",
       "      <td>0.293131</td>\n",
       "      <td>0.232387</td>\n",
       "      <td>0.294913</td>\n",
       "      <td>0.261850</td>\n",
       "      <td>0.246201</td>\n",
       "      <td>0.262965</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.008136</td>\n",
       "      <td>0.253833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gold</th>\n",
       "      <td>0.042117</td>\n",
       "      <td>0.054295</td>\n",
       "      <td>0.062117</td>\n",
       "      <td>0.055871</td>\n",
       "      <td>0.022818</td>\n",
       "      <td>-0.030832</td>\n",
       "      <td>-0.009527</td>\n",
       "      <td>0.008136</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.136136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP</th>\n",
       "      <td>0.388017</td>\n",
       "      <td>0.344700</td>\n",
       "      <td>0.204512</td>\n",
       "      <td>0.287823</td>\n",
       "      <td>0.112488</td>\n",
       "      <td>0.434950</td>\n",
       "      <td>0.274878</td>\n",
       "      <td>0.253833</td>\n",
       "      <td>0.136136</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          GOOGL        FB      NFLX      AMZN      BBBY      COST      DLTR  \\\n",
       "GOOGL  1.000000  0.659948  0.421682  0.596727  0.094283  0.350461  0.271933   \n",
       "FB     0.659948  1.000000  0.391481  0.585806  0.078667  0.263593  0.221170   \n",
       "NFLX   0.421682  0.391481  1.000000  0.415408  0.090621  0.207611  0.186670   \n",
       "AMZN   0.596727  0.585806  0.415408  1.000000  0.050001  0.251497  0.192502   \n",
       "BBBY   0.094283  0.078667  0.090621  0.050001  1.000000  0.285347  0.354165   \n",
       "COST   0.350461  0.263593  0.207611  0.251497  0.285347  1.000000  0.412833   \n",
       "DLTR   0.271933  0.221170  0.186670  0.192502  0.354165  0.412833  1.000000   \n",
       "FOX    0.294732  0.293131  0.232387  0.294913  0.261850  0.246201  0.262965   \n",
       "Gold   0.042117  0.054295  0.062117  0.055871  0.022818 -0.030832 -0.009527   \n",
       "PEP    0.388017  0.344700  0.204512  0.287823  0.112488  0.434950  0.274878   \n",
       "\n",
       "            FOX      Gold       PEP  \n",
       "GOOGL  0.294732  0.042117  0.388017  \n",
       "FB     0.293131  0.054295  0.344700  \n",
       "NFLX   0.232387  0.062117  0.204512  \n",
       "AMZN   0.294913  0.055871  0.287823  \n",
       "BBBY   0.261850  0.022818  0.112488  \n",
       "COST   0.246201 -0.030832  0.434950  \n",
       "DLTR   0.262965 -0.009527  0.274878  \n",
       "FOX    1.000000  0.008136  0.253833  \n",
       "Gold   0.008136  1.000000  0.136136  \n",
       "PEP    0.253833  0.136136  1.000000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_mat = log_returns.corr()\n",
    "corr_mat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Weights via Monte Carlo Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[0.14365897, 0.15598001, 0.14344649, ..., 0.14458544, 0.14830179,\n",
       "         0.1608611 ],\n",
       "        [0.1212781 , 0.08015034, 0.1584359 , ..., 0.10973662, 0.13775662,\n",
       "         0.04444071],\n",
       "        [0.73979439, 0.41768393, 0.99992615, ..., 0.65522935, 0.82774875,\n",
       "         0.18301947]]),\n",
       " [array([0.00721621, 0.1210429 , 0.08125156, 0.06874213, 0.06607656,\n",
       "         0.13043946, 0.10162401, 0.10270595, 0.19745913, 0.1234421 ]),\n",
       "  array([0.10234308, 0.17324074, 0.00838424, 0.16372678, 0.19519414,\n",
       "         0.02965192, 0.05669804, 0.07715214, 0.16458669, 0.02902221]),\n",
       "  array([0.09760999, 0.09178964, 0.03994588, 0.1488204 , 0.04112386,\n",
       "         0.25612967, 0.082804  , 0.07000565, 0.10793936, 0.06383157]),\n",
       "  array([0.05441003, 0.05208831, 0.1625174 , 0.06908703, 0.15078714,\n",
       "         0.04346037, 0.12887574, 0.15568779, 0.1525968 , 0.0304894 ]),\n",
       "  array([0.28232219, 0.06249611, 0.02806029, 0.14362898, 0.04100347,\n",
       "         0.11996605, 0.06673545, 0.06829318, 0.10376066, 0.08373361]),\n",
       "  array([0.12256615, 0.10490512, 0.13007964, 0.07806077, 0.06503524,\n",
       "         0.17295642, 0.14980317, 0.02860224, 0.03543308, 0.11255816]),\n",
       "  array([0.06165406, 0.11759675, 0.08684291, 0.13245863, 0.05943195,\n",
       "         0.1192101 , 0.11527545, 0.12542492, 0.04929849, 0.13280675]),\n",
       "  array([0.12386571, 0.22115881, 0.05792254, 0.07591058, 0.04249459,\n",
       "         0.03944539, 0.16204745, 0.01089908, 0.12608865, 0.1401672 ]),\n",
       "  array([0.01593915, 0.13732625, 0.04669554, 0.05997904, 0.15887493,\n",
       "         0.2232863 , 0.16248405, 0.0613116 , 0.00653173, 0.12757141]),\n",
       "  array([0.04182724, 0.14186693, 0.1376097 , 0.12513465, 0.10182029,\n",
       "         0.05889362, 0.14478338, 0.07739366, 0.12357518, 0.04709536]),\n",
       "  array([0.00614991, 0.00262089, 0.07457587, 0.06806562, 0.13827453,\n",
       "         0.11824555, 0.17290891, 0.18853127, 0.03206694, 0.19856051]),\n",
       "  array([0.01600184, 0.17491002, 0.16486056, 0.14912463, 0.04523383,\n",
       "         0.07068355, 0.15044554, 0.11289053, 0.10096127, 0.01488823]),\n",
       "  array([0.0581662 , 0.03531015, 0.14383138, 0.13548446, 0.05485149,\n",
       "         0.04002241, 0.19052564, 0.11384949, 0.12376824, 0.10419053]),\n",
       "  array([0.1430193 , 0.14035257, 0.04664323, 0.03184013, 0.16371438,\n",
       "         0.08908088, 0.04128457, 0.09524862, 0.195577  , 0.05323932]),\n",
       "  array([0.01630914, 0.07141605, 0.06610353, 0.02177127, 0.17177865,\n",
       "         0.13986685, 0.03297641, 0.14998491, 0.2116191 , 0.11817409]),\n",
       "  array([0.02386902, 0.09165102, 0.15277154, 0.16441381, 0.08369932,\n",
       "         0.17666914, 0.10667273, 0.12164546, 0.01346897, 0.06513898]),\n",
       "  array([0.11698122, 0.16271431, 0.12675393, 0.00321406, 0.12131459,\n",
       "         0.18760304, 0.11191485, 0.10082023, 0.00310858, 0.06557517]),\n",
       "  array([0.16860327, 0.04787555, 0.00487229, 0.13560091, 0.04702223,\n",
       "         0.14413677, 0.14511014, 0.06552751, 0.12747509, 0.11377624]),\n",
       "  array([0.04065377, 0.17536322, 0.04082299, 0.17556951, 0.20492343,\n",
       "         0.0288798 , 0.11931402, 0.12187837, 0.06168949, 0.03090542]),\n",
       "  array([0.07480479, 0.15579284, 0.07197231, 0.10477768, 0.09668558,\n",
       "         0.13313287, 0.03203138, 0.08699076, 0.19177004, 0.05204176]),\n",
       "  array([0.21724479, 0.05415276, 0.00820745, 0.2103113 , 0.00811104,\n",
       "         0.1303565 , 0.06967433, 0.04012711, 0.13587828, 0.12593644]),\n",
       "  array([0.07158954, 0.2589618 , 0.19756791, 0.01178969, 0.05626563,\n",
       "         0.00821684, 0.1012959 , 0.08245041, 0.14048561, 0.07137666]),\n",
       "  array([0.18827664, 0.17842729, 0.01348127, 0.00107864, 0.17724666,\n",
       "         0.06475709, 0.17396823, 0.04306441, 0.06069362, 0.09900616]),\n",
       "  array([0.05059406, 0.23911893, 0.00429186, 0.11406703, 0.09583399,\n",
       "         0.06316359, 0.1458417 , 0.04437208, 0.00616406, 0.23655272]),\n",
       "  array([0.17799365, 0.03973534, 0.03307093, 0.15077069, 0.07531753,\n",
       "         0.13712355, 0.02412477, 0.18175599, 0.12429349, 0.05581407]),\n",
       "  array([0.11056946, 0.05954211, 0.07584381, 0.13605808, 0.17750851,\n",
       "         0.15312561, 0.05891442, 0.13013543, 0.09423051, 0.00407205]),\n",
       "  array([0.08020807, 0.04721655, 0.07097269, 0.16771496, 0.10069517,\n",
       "         0.1347218 , 0.14576518, 0.02188217, 0.16816721, 0.0626562 ]),\n",
       "  array([0.11211601, 0.11030074, 0.04516493, 0.10536574, 0.13336575,\n",
       "         0.06462384, 0.09778873, 0.15044498, 0.03282285, 0.14800643]),\n",
       "  array([0.11832061, 0.10236875, 0.12253405, 0.07335012, 0.09055823,\n",
       "         0.08465676, 0.0883795 , 0.1104052 , 0.09127079, 0.118156  ]),\n",
       "  array([0.08668451, 0.16426197, 0.02095462, 0.07688304, 0.05185055,\n",
       "         0.29897284, 0.07352274, 0.02794834, 0.13242892, 0.06649248]),\n",
       "  array([0.0752549 , 0.11390303, 0.16227236, 0.17019054, 0.09858472,\n",
       "         0.10078584, 0.02799106, 0.07348466, 0.04645809, 0.13107479]),\n",
       "  array([0.06503365, 0.1169725 , 0.18357485, 0.09694167, 0.06373718,\n",
       "         0.0505232 , 0.10001927, 0.13827535, 0.07380649, 0.11111585]),\n",
       "  array([0.07980073, 0.13538766, 0.0346275 , 0.11009599, 0.14134784,\n",
       "         0.12460158, 0.06232971, 0.1332027 , 0.17835877, 0.00024751]),\n",
       "  array([0.09488579, 0.11333843, 0.00794527, 0.01742407, 0.1554139 ,\n",
       "         0.15513185, 0.14268116, 0.0941379 , 0.10361177, 0.11542985]),\n",
       "  array([0.13479177, 0.0628845 , 0.06562507, 0.12636884, 0.11121338,\n",
       "         0.05771918, 0.13258995, 0.13410711, 0.07404769, 0.10065251]),\n",
       "  array([0.16268018, 0.1526362 , 0.01890683, 0.16894384, 0.04040138,\n",
       "         0.0013575 , 0.03060566, 0.12637126, 0.14470943, 0.15338771]),\n",
       "  array([0.17651908, 0.21011143, 0.02919384, 0.08187466, 0.03927222,\n",
       "         0.17728349, 0.1739064 , 0.0153043 , 0.05671481, 0.03981977]),\n",
       "  array([0.17785584, 0.25449851, 0.00280998, 0.07995112, 0.0556836 ,\n",
       "         0.01877951, 0.12603557, 0.07874871, 0.06375628, 0.14188087]),\n",
       "  array([1.52320421e-01, 7.09455539e-02, 2.91056192e-02, 1.56092435e-01,\n",
       "         1.81237298e-01, 5.00394609e-05, 8.83256817e-02, 7.38641173e-02,\n",
       "         1.93401430e-01, 5.46574050e-02]),\n",
       "  array([0.06530835, 0.15439898, 0.09027456, 0.1594189 , 0.08356212,\n",
       "         0.10679348, 0.03080204, 0.11752293, 0.1312919 , 0.06062675]),\n",
       "  array([0.02484113, 0.07432913, 0.11080786, 0.08530733, 0.04779522,\n",
       "         0.14087518, 0.12573886, 0.14224792, 0.11295189, 0.13510549]),\n",
       "  array([0.01017158, 0.18237183, 0.16194621, 0.09892498, 0.08202338,\n",
       "         0.03949728, 0.0903207 , 0.16147668, 0.13863014, 0.03463721]),\n",
       "  array([0.0532874 , 0.16598886, 0.16763118, 0.10253212, 0.02494263,\n",
       "         0.14376966, 0.01479832, 0.0036536 , 0.18389576, 0.13950047]),\n",
       "  array([0.0235075 , 0.00649204, 0.04580962, 0.14768465, 0.11009441,\n",
       "         0.09179705, 0.16280945, 0.06574682, 0.1673909 , 0.17866757]),\n",
       "  array([0.07976449, 0.12689583, 0.01811859, 0.15662603, 0.12167329,\n",
       "         0.04551737, 0.13164439, 0.03025005, 0.15800939, 0.13150056]),\n",
       "  array([0.1788469 , 0.18592697, 0.14128357, 0.01788103, 0.07552497,\n",
       "         0.0707303 , 0.07017063, 0.01377197, 0.09548108, 0.15038257]),\n",
       "  array([0.13164247, 0.09317406, 0.02407525, 0.125289  , 0.02388521,\n",
       "         0.1710688 , 0.02163144, 0.17014573, 0.13627038, 0.10281765]),\n",
       "  array([0.07599513, 0.10928223, 0.11470867, 0.14312718, 0.13496574,\n",
       "         0.00651222, 0.14891098, 0.04352156, 0.12378742, 0.09918888]),\n",
       "  array([0.07617693, 0.04876117, 0.12131251, 0.18504628, 0.12751563,\n",
       "         0.13747858, 0.09212841, 0.01131228, 0.12370851, 0.0765597 ]),\n",
       "  array([0.1073387 , 0.1495701 , 0.04780379, 0.00224639, 0.10618673,\n",
       "         0.08640075, 0.15723141, 0.11982231, 0.08735676, 0.13604307]),\n",
       "  array([0.09102969, 0.07158165, 0.0364971 , 0.3079337 , 0.07789897,\n",
       "         0.19773382, 0.00985656, 0.0694333 , 0.12867339, 0.00936183]),\n",
       "  array([0.1620465 , 0.18020131, 0.08349623, 0.18075904, 0.01815355,\n",
       "         0.07737539, 0.03899299, 0.08469042, 0.11168556, 0.062599  ]),\n",
       "  array([0.02884863, 0.12343558, 0.11317447, 0.12116275, 0.11956581,\n",
       "         0.12831364, 0.11992422, 0.1285258 , 0.06319652, 0.05385258]),\n",
       "  array([0.1485622 , 0.16154043, 0.0823278 , 0.17090949, 0.04135582,\n",
       "         0.0268792 , 0.08036434, 0.19813419, 0.00399694, 0.08592959]),\n",
       "  array([0.06842291, 0.18034984, 0.17828297, 0.0193262 , 0.06914914,\n",
       "         0.13650314, 0.0489997 , 0.07454526, 0.11844531, 0.10597551]),\n",
       "  array([0.11803017, 0.08520992, 0.10082263, 0.06520284, 0.01001263,\n",
       "         0.20396548, 0.02237394, 0.03713832, 0.19391188, 0.16333221]),\n",
       "  array([0.03042965, 0.07518542, 0.01339874, 0.19067273, 0.07423514,\n",
       "         0.08877264, 0.00203923, 0.19479936, 0.16644727, 0.16401981]),\n",
       "  array([0.20013972, 0.09033599, 0.16535928, 0.17892144, 0.00931291,\n",
       "         0.07649601, 0.08000467, 0.16024494, 0.01919571, 0.01998933]),\n",
       "  array([0.11128578, 0.16548201, 0.10093021, 0.16308855, 0.07483258,\n",
       "         0.11031833, 0.10391798, 0.00402349, 0.15187151, 0.01424955]),\n",
       "  array([0.18841389, 0.08605248, 0.04453624, 0.03054169, 0.05241609,\n",
       "         0.13697155, 0.15363986, 0.02717881, 0.17716147, 0.10308793]),\n",
       "  array([0.01608753, 0.09993471, 0.07377352, 0.09517536, 0.07917167,\n",
       "         0.14156975, 0.11691015, 0.1628997 , 0.15465281, 0.05982481]),\n",
       "  array([0.14518513, 0.16902058, 0.1003634 , 0.00076036, 0.02900176,\n",
       "         0.1717836 , 0.17803284, 0.08496038, 0.01563466, 0.10525727]),\n",
       "  array([0.04862745, 0.1829593 , 0.16331742, 0.05808651, 0.02915883,\n",
       "         0.11286858, 0.11923391, 0.08041244, 0.01284219, 0.19249335]),\n",
       "  array([0.17693838, 0.14039372, 0.06323462, 0.01732134, 0.03722614,\n",
       "         0.04881481, 0.22111947, 0.00487173, 0.06430286, 0.22577694]),\n",
       "  array([0.08453597, 0.18512758, 0.01971912, 0.09157153, 0.03203881,\n",
       "         0.04475238, 0.20224528, 0.18051389, 0.12862724, 0.03086819]),\n",
       "  array([0.04902595, 0.161554  , 0.01102835, 0.16954   , 0.01960798,\n",
       "         0.02747682, 0.15465156, 0.16857796, 0.02111373, 0.21742366]),\n",
       "  array([0.02211924, 0.00994988, 0.12701391, 0.10858533, 0.18532808,\n",
       "         0.07175255, 0.17341319, 0.16034593, 0.05929815, 0.08219374]),\n",
       "  array([0.18003633, 0.07834801, 0.05357431, 0.05608474, 0.08756357,\n",
       "         0.11496392, 0.14480958, 0.17492728, 0.10584751, 0.00384474]),\n",
       "  array([0.09989835, 0.11409385, 0.11606223, 0.18030709, 0.06626407,\n",
       "         0.06845031, 0.1407784 , 0.00120424, 0.13366017, 0.07928128]),\n",
       "  array([0.09645937, 0.08918027, 0.16967654, 0.06966045, 0.14607231,\n",
       "         0.05643052, 0.19177334, 0.12363499, 0.02673153, 0.03038069]),\n",
       "  array([0.12696829, 0.01716408, 0.15034101, 0.0184797 , 0.08348874,\n",
       "         0.09138305, 0.17159968, 0.07711273, 0.13142609, 0.13203663]),\n",
       "  array([0.02951593, 0.07482641, 0.15115141, 0.10115735, 0.15549624,\n",
       "         0.14894433, 0.11641653, 0.01870057, 0.16373403, 0.0400572 ]),\n",
       "  array([0.09115751, 0.01161215, 0.01012606, 0.1779299 , 0.09033388,\n",
       "         0.04154033, 0.15303868, 0.18506796, 0.06424526, 0.17494827]),\n",
       "  array([0.1532762 , 0.11758622, 0.02309791, 0.00100417, 0.0130126 ,\n",
       "         0.10160722, 0.2257417 , 0.15465359, 0.04517823, 0.16484216]),\n",
       "  array([0.16140832, 0.10087617, 0.14779277, 0.02378656, 0.06719247,\n",
       "         0.13719431, 0.16622133, 0.07267011, 0.04179441, 0.08106356]),\n",
       "  array([0.02354928, 0.11056045, 0.13952321, 0.14180657, 0.06309961,\n",
       "         0.121177  , 0.08619281, 0.18595993, 0.04859722, 0.07953391]),\n",
       "  array([0.13913191, 0.14774313, 0.04483639, 0.13173202, 0.10702957,\n",
       "         0.15395164, 0.07048448, 0.12465573, 0.04838769, 0.03204744]),\n",
       "  array([0.07578157, 0.13016648, 0.15534724, 0.05594866, 0.1562034 ,\n",
       "         0.03210341, 0.07415868, 0.16017693, 0.12804076, 0.03207287]),\n",
       "  array([0.10927542, 0.10668027, 0.1047998 , 0.08674795, 0.05766446,\n",
       "         0.12439395, 0.12811247, 0.09936019, 0.02546731, 0.15749818]),\n",
       "  array([0.08044463, 0.09960925, 0.04313706, 0.12855259, 0.06764678,\n",
       "         0.14381296, 0.10246904, 0.06594179, 0.14035298, 0.12803292]),\n",
       "  array([0.08591288, 0.13570182, 0.09379963, 0.00052028, 0.18308833,\n",
       "         0.18412044, 0.15987781, 0.05288952, 0.02546185, 0.07862743]),\n",
       "  array([0.09310776, 0.04609515, 0.17030986, 0.01047167, 0.11940984,\n",
       "         0.07515755, 0.16076089, 0.13542228, 0.12758651, 0.06167849]),\n",
       "  array([0.00596246, 0.03247569, 0.00989337, 0.12872618, 0.16816294,\n",
       "         0.11116973, 0.18473111, 0.02299522, 0.17479626, 0.16108703]),\n",
       "  array([0.15658209, 0.15444239, 0.00179271, 0.16846696, 0.16371338,\n",
       "         0.21708208, 0.01715542, 0.03878723, 0.02855914, 0.0534186 ]),\n",
       "  array([0.08981102, 0.17355334, 0.10770003, 0.06581057, 0.00672937,\n",
       "         0.17873046, 0.02167821, 0.02918695, 0.13436651, 0.19243356]),\n",
       "  array([0.09328298, 0.04777371, 0.17479767, 0.14536524, 0.05629058,\n",
       "         0.15806485, 0.14912468, 0.07769453, 0.03174744, 0.06585831]),\n",
       "  array([0.11670252, 0.20515624, 0.00260074, 0.08783527, 0.03125879,\n",
       "         0.14337335, 0.07589818, 0.1724377 , 0.14958131, 0.0151559 ]),\n",
       "  array([0.02686933, 0.14567478, 0.11708095, 0.06836328, 0.08111878,\n",
       "         0.17532636, 0.02945545, 0.14738493, 0.20292816, 0.00579798]),\n",
       "  array([0.21340466, 0.11690297, 0.07242347, 0.06866288, 0.06015851,\n",
       "         0.05186954, 0.08590126, 0.07356758, 0.12486649, 0.13224265]),\n",
       "  array([0.20076174, 0.02913354, 0.1059194 , 0.07257117, 0.1208684 ,\n",
       "         0.03123658, 0.0933441 , 0.07546706, 0.12719265, 0.14350537]),\n",
       "  array([0.08630013, 0.10933246, 0.0652995 , 0.14827649, 0.0875253 ,\n",
       "         0.15368697, 0.06082347, 0.12939039, 0.15296069, 0.0064046 ]),\n",
       "  array([0.13398786, 0.11418034, 0.13915757, 0.06199354, 0.1197328 ,\n",
       "         0.02876861, 0.10581975, 0.12391827, 0.09041443, 0.08202683]),\n",
       "  array([0.13722778, 0.10560936, 0.1625208 , 0.08830493, 0.08369629,\n",
       "         0.04741006, 0.1228887 , 0.14012337, 0.04250368, 0.06971504]),\n",
       "  array([0.08203808, 0.11252529, 0.01845531, 0.22372016, 0.15382572,\n",
       "         0.07872926, 0.08893874, 0.11104726, 0.08518171, 0.04553848]),\n",
       "  array([0.15652803, 0.16157328, 0.08778152, 0.10056858, 0.03136527,\n",
       "         0.02634205, 0.01239734, 0.1390222 , 0.17754916, 0.10687256]),\n",
       "  array([0.01230613, 0.14893063, 0.0263222 , 0.1836685 , 0.0468187 ,\n",
       "         0.01486872, 0.08941714, 0.1880766 , 0.17287394, 0.11671745]),\n",
       "  array([0.08020942, 0.01040839, 0.19778108, 0.15038374, 0.12883865,\n",
       "         0.03375086, 0.1161979 , 0.13508415, 0.08997932, 0.0573665 ]),\n",
       "  array([0.16242385, 0.07140086, 0.10130526, 0.01178639, 0.17545854,\n",
       "         0.02724985, 0.13219982, 0.0719222 , 0.02974048, 0.21651275]),\n",
       "  array([0.07893944, 0.00406561, 0.06441272, 0.13425395, 0.13632717,\n",
       "         0.19042906, 0.03994065, 0.02190073, 0.21154836, 0.11818232]),\n",
       "  array([0.19111174, 0.10113051, 0.1836687 , 0.03384647, 0.15409772,\n",
       "         0.12652427, 0.05659826, 0.08846955, 0.05029222, 0.01426055]),\n",
       "  array([0.03028416, 0.11847618, 0.08234492, 0.1731891 , 0.07217692,\n",
       "         0.16861129, 0.09572145, 0.05890273, 0.17215871, 0.02813455]),\n",
       "  array([0.02421806, 0.13510108, 0.21483026, 0.04807092, 0.12364675,\n",
       "         0.11361702, 0.19592917, 0.01558273, 0.02221982, 0.10678419]),\n",
       "  array([0.1142642 , 0.109993  , 0.10898649, 0.02612799, 0.14103515,\n",
       "         0.14473298, 0.14660513, 0.0817882 , 0.02740101, 0.09906586]),\n",
       "  array([0.04143117, 0.07827826, 0.15791587, 0.13401737, 0.1825703 ,\n",
       "         0.10162032, 0.01324379, 0.14936864, 0.039692  , 0.10186228]),\n",
       "  array([0.08124041, 0.01203758, 0.14835506, 0.15368966, 0.08857454,\n",
       "         0.01890768, 0.12457463, 0.05734474, 0.12237866, 0.19289703]),\n",
       "  array([0.03234011, 0.08860558, 0.03410318, 0.13766199, 0.25487013,\n",
       "         0.0595622 , 0.12139637, 0.06325894, 0.04938504, 0.15881645]),\n",
       "  array([0.00064749, 0.1496266 , 0.08450976, 0.14975785, 0.07365857,\n",
       "         0.05803971, 0.12509975, 0.19524586, 0.15720517, 0.00620925]),\n",
       "  array([0.14669866, 0.15041906, 0.01003467, 0.15424721, 0.10293453,\n",
       "         0.06432806, 0.09576233, 0.17572694, 0.02283594, 0.07701259]),\n",
       "  array([0.10327005, 0.13622656, 0.17941133, 0.00607087, 0.05627328,\n",
       "         0.05845936, 0.24199617, 0.05482466, 0.0079684 , 0.15549933]),\n",
       "  array([0.18235043, 0.09260898, 0.06082582, 0.13988953, 0.01261648,\n",
       "         0.11546901, 0.10149145, 0.05856456, 0.09687963, 0.13930411]),\n",
       "  array([0.07758567, 0.09396237, 0.17705781, 0.00955738, 0.05371996,\n",
       "         0.1780874 , 0.14774825, 0.18981663, 0.03020516, 0.04225937]),\n",
       "  array([0.12627399, 0.02729201, 0.06479702, 0.10888133, 0.08471922,\n",
       "         0.15175964, 0.02813469, 0.17229795, 0.17291446, 0.06292968]),\n",
       "  array([0.16646454, 0.00945752, 0.08528176, 0.04156762, 0.16795677,\n",
       "         0.10584377, 0.10284151, 0.13443367, 0.08093669, 0.10521615]),\n",
       "  array([0.20963438, 0.02189024, 0.09805462, 0.04845558, 0.03641744,\n",
       "         0.00052833, 0.09331348, 0.17137037, 0.16210654, 0.15822901]),\n",
       "  array([0.21431055, 0.03192109, 0.0935754 , 0.10546667, 0.15629797,\n",
       "         0.07534892, 0.17888863, 0.12971723, 0.00112407, 0.01334946]),\n",
       "  array([0.13611923, 0.03596911, 0.15380198, 0.00492117, 0.03081544,\n",
       "         0.11511005, 0.17438569, 0.17184072, 0.1394687 , 0.03756791]),\n",
       "  array([0.07893647, 0.14100962, 0.16532634, 0.14709046, 0.04342488,\n",
       "         0.00794889, 0.15307196, 0.12040376, 0.05687272, 0.08591491]),\n",
       "  array([0.14539438, 0.13012354, 0.09171003, 0.09650113, 0.09106867,\n",
       "         0.14772538, 0.04445348, 0.12481803, 0.0974762 , 0.03072918]),\n",
       "  array([0.02546651, 0.0489606 , 0.14277463, 0.09044568, 0.14469882,\n",
       "         0.07301374, 0.15157364, 0.07207304, 0.0903469 , 0.16064644]),\n",
       "  array([0.11670739, 0.15201889, 0.07681171, 0.10121638, 0.07752745,\n",
       "         0.16033209, 0.16439819, 0.05174645, 0.06895458, 0.03028686]),\n",
       "  array([0.12625409, 0.13347492, 0.12765376, 0.09044182, 0.09399093,\n",
       "         0.04839957, 0.10926919, 0.02470164, 0.16853498, 0.07727911]),\n",
       "  array([0.05256894, 0.0611699 , 0.14104301, 0.11950107, 0.15109323,\n",
       "         0.15028339, 0.13409621, 0.00138414, 0.02179066, 0.16706945]),\n",
       "  array([0.17611368, 0.02391837, 0.04763186, 0.19459423, 0.19563786,\n",
       "         0.04340442, 0.12669667, 0.04640072, 0.06392231, 0.08167989]),\n",
       "  array([0.01787855, 0.0409772 , 0.16179336, 0.14545719, 0.06057466,\n",
       "         0.12107414, 0.07379885, 0.06692109, 0.14864994, 0.16287502]),\n",
       "  array([0.12881026, 0.13831347, 0.14684019, 0.15485821, 0.05576535,\n",
       "         0.13032419, 0.01764004, 0.09942144, 0.07223405, 0.05579279]),\n",
       "  array([0.20184962, 0.13268238, 0.17665844, 0.16990102, 0.10483942,\n",
       "         0.08119771, 0.01032821, 0.05691975, 0.02585425, 0.03976922]),\n",
       "  array([0.14139238, 0.14735675, 0.07258316, 0.10664737, 0.14262763,\n",
       "         0.0297591 , 0.06479933, 0.10481349, 0.06953423, 0.12048656]),\n",
       "  array([0.13480753, 0.03939518, 0.10149846, 0.10955291, 0.15939911,\n",
       "         0.04881257, 0.05449526, 0.134916  , 0.1311426 , 0.08598037]),\n",
       "  array([0.03689668, 0.02467949, 0.18962489, 0.0313969 , 0.03085317,\n",
       "         0.00904209, 0.26174818, 0.05925238, 0.06229933, 0.29420689]),\n",
       "  array([0.13927034, 0.06371891, 0.02814393, 0.08925801, 0.01831997,\n",
       "         0.15496442, 0.08622716, 0.22273129, 0.0040146 , 0.19335136]),\n",
       "  array([0.17248587, 0.04683859, 0.18641318, 0.15157409, 0.07606742,\n",
       "         0.00671497, 0.0980344 , 0.00396586, 0.16022742, 0.09767819]),\n",
       "  array([0.07035319, 0.11810253, 0.12171531, 0.11632847, 0.15316686,\n",
       "         0.17409603, 0.00387812, 0.00998439, 0.07180548, 0.16056963]),\n",
       "  array([0.08473296, 0.17321372, 0.15439892, 0.07410816, 0.00770348,\n",
       "         0.17144773, 0.15311925, 0.03909158, 0.12217349, 0.0200107 ]),\n",
       "  array([0.02215558, 0.10437519, 0.14602536, 0.0502921 , 0.18264558,\n",
       "         0.08096538, 0.13942133, 0.20865005, 0.01536319, 0.05010623]),\n",
       "  array([0.11204987, 0.11198461, 0.08356027, 0.15530014, 0.12108205,\n",
       "         0.10931033, 0.01626843, 0.14139027, 0.09983532, 0.04921872]),\n",
       "  array([0.13436864, 0.01794693, 0.04968689, 0.08795705, 0.17702718,\n",
       "         0.0854697 , 0.09912734, 0.13183852, 0.10478355, 0.1117942 ]),\n",
       "  array([0.13348201, 0.1718042 , 0.16924699, 0.08600308, 0.04150586,\n",
       "         0.04474056, 0.05732297, 0.13700475, 0.1453547 , 0.01353489]),\n",
       "  array([0.06290896, 0.12037849, 0.11886484, 0.13520309, 0.13317591,\n",
       "         0.13066124, 0.01135323, 0.07398675, 0.07283983, 0.14062767]),\n",
       "  array([0.16029808, 0.02231749, 0.09526153, 0.09188564, 0.07246832,\n",
       "         0.13409506, 0.0837751 , 0.08702669, 0.10315978, 0.14971231]),\n",
       "  array([0.11256702, 0.15880657, 0.12001854, 0.03280566, 0.0621459 ,\n",
       "         0.1474032 , 0.09335402, 0.04687841, 0.14281592, 0.08320476]),\n",
       "  array([0.08747827, 0.15541745, 0.10205821, 0.081031  , 0.13885283,\n",
       "         0.15134598, 0.17378087, 0.03528444, 0.02846375, 0.0462872 ]),\n",
       "  array([0.11719657, 0.11609713, 0.04139252, 0.0765453 , 0.10356324,\n",
       "         0.14579477, 0.11632373, 0.06638176, 0.08254614, 0.13415885]),\n",
       "  array([0.02750501, 0.13027895, 0.10442044, 0.01724012, 0.14589144,\n",
       "         0.08228993, 0.1228499 , 0.11149965, 0.14016556, 0.117859  ]),\n",
       "  array([0.13140996, 0.14512041, 0.05764873, 0.14906823, 0.13555741,\n",
       "         0.07205712, 0.05880376, 0.03158418, 0.08974292, 0.12900728]),\n",
       "  array([0.05826421, 0.03432628, 0.10343997, 0.08992329, 0.10638968,\n",
       "         0.07205903, 0.1196158 , 0.1574808 , 0.1707254 , 0.08777554]),\n",
       "  array([0.02063857, 0.17839744, 0.02392316, 0.00191013, 0.22154552,\n",
       "         0.09327836, 0.22739825, 0.05098365, 0.0089138 , 0.17301113]),\n",
       "  array([0.06040581, 0.08339409, 0.11000862, 0.07743995, 0.00813478,\n",
       "         0.12484857, 0.18101456, 0.07639   , 0.11642448, 0.16193915]),\n",
       "  array([0.06662874, 0.06897886, 0.19376284, 0.12266705, 0.16076215,\n",
       "         0.08632282, 0.07873592, 0.02677566, 0.18066738, 0.01469857]),\n",
       "  array([0.01095503, 0.11355731, 0.09050867, 0.11197844, 0.11123677,\n",
       "         0.15584116, 0.03634165, 0.15854989, 0.07721787, 0.1338132 ]),\n",
       "  array([0.14003239, 0.04603543, 0.04417284, 0.01910992, 0.00637655,\n",
       "         0.19541336, 0.15493243, 0.15388859, 0.06530029, 0.17473819]),\n",
       "  array([0.0025131 , 0.15742301, 0.00211143, 0.16734329, 0.17619675,\n",
       "         0.09119827, 0.12824116, 0.20469873, 0.06721566, 0.00305858]),\n",
       "  array([0.13317541, 0.14112572, 0.19261462, 0.07058705, 0.11140111,\n",
       "         0.08699196, 0.0603642 , 0.12921631, 0.0511406 , 0.02338303]),\n",
       "  array([0.09352557, 0.13421051, 0.03689607, 0.14542875, 0.09134256,\n",
       "         0.18021643, 0.06932607, 0.0009139 , 0.1685298 , 0.07961035]),\n",
       "  array([0.09687741, 0.01152733, 0.12378723, 0.147026  , 0.1559548 ,\n",
       "         0.05233157, 0.14752609, 0.02728997, 0.14021856, 0.09746104]),\n",
       "  array([0.07797952, 0.12776992, 0.15674249, 0.03490335, 0.0527825 ,\n",
       "         0.13636472, 0.0831078 , 0.09900156, 0.13595382, 0.09539432]),\n",
       "  array([0.14966055, 0.10949843, 0.03765574, 0.01555745, 0.08746049,\n",
       "         0.08849837, 0.09389861, 0.13418803, 0.13200615, 0.15157618]),\n",
       "  array([0.04949022, 0.09655376, 0.05505461, 0.0953639 , 0.10325976,\n",
       "         0.03570684, 0.11919533, 0.160395  , 0.15330517, 0.13167541]),\n",
       "  array([0.07623449, 0.02500918, 0.11628388, 0.09504995, 0.35053938,\n",
       "         0.01928794, 0.08701589, 0.05430568, 0.02466278, 0.15161085]),\n",
       "  array([0.00073821, 0.01486091, 0.0335114 , 0.15247907, 0.09196887,\n",
       "         0.06369062, 0.19431375, 0.15470072, 0.08058849, 0.21314796]),\n",
       "  array([0.16390395, 0.21710141, 0.00244843, 0.1404394 , 0.00142769,\n",
       "         0.03971603, 0.22842548, 0.04170644, 0.02495184, 0.13987933]),\n",
       "  array([0.07082013, 0.06007083, 0.0318651 , 0.09921013, 0.14852602,\n",
       "         0.11592204, 0.14186663, 0.10903596, 0.14950917, 0.07317399]),\n",
       "  array([0.22839151, 0.00816539, 0.17691081, 0.11617185, 0.02113311,\n",
       "         0.03877662, 0.15869678, 0.07927639, 0.11931406, 0.05316347]),\n",
       "  array([0.01825808, 0.12377799, 0.11851051, 0.04762905, 0.14406931,\n",
       "         0.05966108, 0.14838685, 0.12577562, 0.09050056, 0.12343094]),\n",
       "  array([0.15534065, 0.14122177, 0.03344978, 0.13819895, 0.15209149,\n",
       "         0.04194744, 0.04143314, 0.11472298, 0.04683431, 0.1347595 ]),\n",
       "  array([0.06903986, 0.16982565, 0.17082437, 0.12200505, 0.05966329,\n",
       "         0.05404216, 0.21306455, 0.02078764, 0.00251385, 0.11823357]),\n",
       "  array([0.12205821, 0.15688091, 0.08254295, 0.12974426, 0.04780592,\n",
       "         0.03738673, 0.08142383, 0.0848878 , 0.05159551, 0.20567387]),\n",
       "  array([0.12819072, 0.12136698, 0.05191128, 0.11063014, 0.13455412,\n",
       "         0.11575855, 0.10064942, 0.04880482, 0.11208171, 0.07605226]),\n",
       "  array([0.150549  , 0.14397257, 0.04903001, 0.146619  , 0.13688942,\n",
       "         0.02933593, 0.09329556, 0.13236418, 0.02482456, 0.09311976]),\n",
       "  array([0.06567136, 0.07069096, 0.09860435, 0.09223618, 0.08816377,\n",
       "         0.01948662, 0.15550807, 0.16185834, 0.09804221, 0.14973815]),\n",
       "  array([0.12943138, 0.09179558, 0.09195228, 0.07321241, 0.0305151 ,\n",
       "         0.15424975, 0.16687656, 0.02718345, 0.20735721, 0.02742629]),\n",
       "  array([0.06982534, 0.1022692 , 0.05091445, 0.11002318, 0.07146102,\n",
       "         0.12557877, 0.11225943, 0.13893132, 0.12241571, 0.09632159]),\n",
       "  array([0.10047726, 0.11467385, 0.14906434, 0.13549375, 0.05617779,\n",
       "         0.02943365, 0.04302039, 0.05967401, 0.1621887 , 0.14979627]),\n",
       "  array([0.09789063, 0.08974615, 0.11640507, 0.08977098, 0.01229849,\n",
       "         0.09574519, 0.12740348, 0.13491775, 0.14390211, 0.09192013]),\n",
       "  array([0.02176702, 0.05369413, 0.0982376 , 0.00711604, 0.0955377 ,\n",
       "         0.10400326, 0.16867365, 0.0207266 , 0.20702551, 0.2232185 ]),\n",
       "  array([0.10048474, 0.1289029 , 0.11705313, 0.1375964 , 0.02543213,\n",
       "         0.1268299 , 0.01053341, 0.12817569, 0.10245785, 0.12253385]),\n",
       "  array([0.12599851, 0.0923749 , 0.08274579, 0.08375163, 0.13277448,\n",
       "         0.0679965 , 0.11851472, 0.09707944, 0.09218106, 0.10658298]),\n",
       "  array([0.11710775, 0.11553125, 0.12212325, 0.11558057, 0.06516111,\n",
       "         0.07665683, 0.08403785, 0.11718556, 0.12524696, 0.06136886]),\n",
       "  array([0.03476069, 0.13102564, 0.03175957, 0.18623309, 0.12649681,\n",
       "         0.12402392, 0.08336932, 0.10481883, 0.15065363, 0.0268585 ]),\n",
       "  array([0.08634504, 0.14530897, 0.15478028, 0.16976271, 0.09692356,\n",
       "         0.13119961, 0.0284523 , 0.06117868, 0.09697695, 0.02907191]),\n",
       "  array([0.13653   , 0.14540636, 0.12243449, 0.08353121, 0.02997968,\n",
       "         0.13074082, 0.04549382, 0.15523725, 0.13670279, 0.01394358]),\n",
       "  array([0.11174513, 0.07462986, 0.13509115, 0.06969163, 0.09062568,\n",
       "         0.01634127, 0.08495626, 0.16099017, 0.13568513, 0.12024372]),\n",
       "  array([0.10010159, 0.14494493, 0.08835479, 0.07662879, 0.05809067,\n",
       "         0.17046504, 0.1321635 , 0.03833243, 0.1296824 , 0.06123586]),\n",
       "  array([0.02960399, 0.14348391, 0.07203765, 0.11593897, 0.0375713 ,\n",
       "         0.11494607, 0.09319287, 0.13550024, 0.14089232, 0.11683267]),\n",
       "  array([0.08765996, 0.03661454, 0.04994415, 0.04630527, 0.12283934,\n",
       "         0.15287755, 0.1370895 , 0.06246132, 0.15177497, 0.1524334 ]),\n",
       "  array([0.1347805 , 0.01775244, 0.11290157, 0.08930424, 0.07219738,\n",
       "         0.10782187, 0.06973308, 0.11905197, 0.13370129, 0.14275566]),\n",
       "  array([0.02382826, 0.14783385, 0.01121771, 0.11503482, 0.11943361,\n",
       "         0.16170332, 0.01598379, 0.16964691, 0.15837667, 0.07694105]),\n",
       "  array([0.08642456, 0.07838999, 0.11196579, 0.06056323, 0.16894454,\n",
       "         0.10786558, 0.08489318, 0.10168143, 0.12043682, 0.07883488]),\n",
       "  array([0.00166923, 0.0607001 , 0.21050436, 0.03964903, 0.06514147,\n",
       "         0.15215797, 0.02315006, 0.08037796, 0.14119756, 0.22545226]),\n",
       "  array([0.11060706, 0.16727789, 0.06874002, 0.13192069, 0.04829055,\n",
       "         0.15986191, 0.17210879, 0.12935282, 0.00493939, 0.00690088]),\n",
       "  array([0.00934886, 0.16666276, 0.11488257, 0.16153158, 0.17683274,\n",
       "         0.08494073, 0.08250103, 0.03096813, 0.05021657, 0.12211503]),\n",
       "  array([0.13006403, 0.06814157, 0.14738438, 0.0047778 , 0.10175684,\n",
       "         0.0335312 , 0.16909985, 0.07336263, 0.1660971 , 0.10578461]),\n",
       "  array([0.00454626, 0.12175793, 0.18498295, 0.18246422, 0.18439819,\n",
       "         0.03326354, 0.12222987, 0.06770012, 0.07098068, 0.02767624]),\n",
       "  array([0.22233527, 0.14079571, 0.0800673 , 0.07748653, 0.00488235,\n",
       "         0.12377184, 0.00600031, 0.04716689, 0.14105249, 0.15644132]),\n",
       "  array([0.17246888, 0.10509433, 0.14090969, 0.00612419, 0.16988269,\n",
       "         0.03357592, 0.06739641, 0.02731848, 0.17425625, 0.10297316]),\n",
       "  array([0.14117649, 0.14571989, 0.07524375, 0.06252694, 0.05948557,\n",
       "         0.04578058, 0.15504373, 0.07038344, 0.11834386, 0.12629575]),\n",
       "  array([0.0540903 , 0.05991863, 0.10739785, 0.06588823, 0.13131312,\n",
       "         0.11396287, 0.13571082, 0.1125093 , 0.13950014, 0.07970875]),\n",
       "  array([0.04799772, 0.08758162, 0.06225968, 0.07544783, 0.15587589,\n",
       "         0.15686085, 0.10867039, 0.12985904, 0.13990132, 0.03554565]),\n",
       "  array([0.19404405, 0.07952926, 0.04062085, 0.06804475, 0.14193997,\n",
       "         0.08081266, 0.16068531, 0.0070794 , 0.10122321, 0.12602054]),\n",
       "  array([0.01607894, 0.09483529, 0.18659502, 0.16376138, 0.09517822,\n",
       "         0.10139333, 0.00575609, 0.13206716, 0.04111498, 0.16321959]),\n",
       "  array([0.01758569, 0.09725755, 0.1398388 , 0.0601413 , 0.08699194,\n",
       "         0.14117361, 0.1297877 , 0.09335075, 0.10642315, 0.12744952]),\n",
       "  array([0.09990474, 0.05249147, 0.10774312, 0.14126532, 0.16738322,\n",
       "         0.10390969, 0.04647849, 0.11975961, 0.06795603, 0.09310829]),\n",
       "  array([0.14033491, 0.110584  , 0.10866606, 0.06799096, 0.0919253 ,\n",
       "         0.11062166, 0.10741953, 0.10146952, 0.12724149, 0.03374658]),\n",
       "  array([0.09770072, 0.11349246, 0.11131721, 0.0988482 , 0.08268421,\n",
       "         0.11874371, 0.1102091 , 0.18616069, 0.0222142 , 0.05862949]),\n",
       "  array([0.10013572, 0.07505803, 0.09958267, 0.12971122, 0.15647742,\n",
       "         0.15150781, 0.02755347, 0.11521993, 0.08890177, 0.05585197]),\n",
       "  array([2.94327909e-02, 1.10376469e-01, 4.36787013e-02, 1.51990162e-04,\n",
       "         1.69085354e-01, 1.39062724e-01, 1.78918659e-01, 5.43573946e-02,\n",
       "         1.97530802e-01, 7.74051149e-02]),\n",
       "  array([5.50542465e-06, 2.31746370e-02, 1.61129679e-01, 7.13293669e-02,\n",
       "         2.86469547e-02, 2.43903262e-01, 4.34532960e-02, 2.75505840e-02,\n",
       "         1.87399382e-01, 2.13407333e-01]),\n",
       "  array([0.17478029, 0.05649027, 0.04630034, 0.07293399, 0.12823359,\n",
       "         0.09574989, 0.0651598 , 0.15689485, 0.10632924, 0.09712776]),\n",
       "  array([0.06196086, 0.13138198, 0.03338947, 0.16037631, 0.002548  ,\n",
       "         0.16008768, 0.0994578 , 0.01081026, 0.21486686, 0.12512077]),\n",
       "  array([0.10522746, 0.00940741, 0.14595462, 0.05947531, 0.17675153,\n",
       "         0.06537292, 0.10903466, 0.02038416, 0.21164062, 0.09675132]),\n",
       "  array([0.15598046, 0.02163799, 0.10902403, 0.15124534, 0.16013049,\n",
       "         0.06771734, 0.00870728, 0.00497943, 0.18141912, 0.13915853]),\n",
       "  array([0.13335105, 0.02356106, 0.16106289, 0.12020829, 0.01208573,\n",
       "         0.15842429, 0.0787279 , 0.13889905, 0.09790962, 0.07577013]),\n",
       "  array([0.08180007, 0.02512047, 0.00907266, 0.11853408, 0.04932217,\n",
       "         0.16565148, 0.10646735, 0.21185731, 0.03191346, 0.20026094]),\n",
       "  array([0.06927503, 0.09670459, 0.12201845, 0.08720702, 0.05222757,\n",
       "         0.19330807, 0.08443635, 0.11186447, 0.08082624, 0.10213221]),\n",
       "  array([0.08946231, 0.03275966, 0.03400637, 0.05676725, 0.11731582,\n",
       "         0.16354115, 0.13046913, 0.17234767, 0.12294382, 0.08038683]),\n",
       "  array([0.08252777, 0.21497662, 0.08177038, 0.00845728, 0.16323975,\n",
       "         0.06070215, 0.20699268, 0.07748383, 0.05832621, 0.04552334]),\n",
       "  array([0.06153111, 0.1745969 , 0.01111607, 0.18866723, 0.11357121,\n",
       "         0.11635349, 0.00100388, 0.11465878, 0.11832859, 0.10017274]),\n",
       "  array([0.15345028, 0.00680571, 0.03920291, 0.05921701, 0.1567479 ,\n",
       "         0.1345109 , 0.15154175, 0.07184724, 0.20433357, 0.02234274]),\n",
       "  array([0.04899308, 0.13874167, 0.10571799, 0.12850634, 0.09998604,\n",
       "         0.09887059, 0.05123538, 0.12911448, 0.14343363, 0.0554008 ]),\n",
       "  array([0.24447035, 0.04741977, 0.24292123, 0.00389695, 0.2118027 ,\n",
       "         0.01138849, 0.16592156, 0.04813872, 0.00722173, 0.0168185 ]),\n",
       "  array([0.12977557, 0.13585887, 0.00771254, 0.12140753, 0.01625736,\n",
       "         0.00974254, 0.16325398, 0.12608463, 0.10903604, 0.18087095]),\n",
       "  array([0.14404473, 0.10768237, 0.12194234, 0.13046142, 0.13472376,\n",
       "         0.02596745, 0.03233779, 0.16342962, 0.05149234, 0.08791818]),\n",
       "  array([0.09886619, 0.13743339, 0.16392167, 0.04255652, 0.0474458 ,\n",
       "         0.12917493, 0.01354905, 0.13105195, 0.11019428, 0.12580623]),\n",
       "  array([0.07112428, 0.02568266, 0.09653266, 0.02529944, 0.08664494,\n",
       "         0.14793015, 0.17363536, 0.18739861, 0.03903227, 0.14671964]),\n",
       "  array([0.10542952, 0.10458654, 0.16384678, 0.13534026, 0.08185879,\n",
       "         0.05033068, 0.00787144, 0.07710703, 0.12853844, 0.14509052]),\n",
       "  array([0.00418671, 0.12199542, 0.11761375, 0.15810989, 0.15947177,\n",
       "         0.13928354, 0.07486731, 0.05837259, 0.12548454, 0.04061449]),\n",
       "  array([0.15646043, 0.00850316, 0.12019379, 0.11079441, 0.17179949,\n",
       "         0.08599939, 0.08391294, 0.16692347, 0.08046557, 0.01494734]),\n",
       "  array([0.1676966 , 0.08542308, 0.10165975, 0.05697236, 0.03583805,\n",
       "         0.12726584, 0.13326613, 0.1379732 , 0.06290433, 0.09100068]),\n",
       "  array([0.14731537, 0.04285482, 0.11347365, 0.02559067, 0.13606148,\n",
       "         0.12677848, 0.15877897, 0.03629326, 0.10008777, 0.11276553]),\n",
       "  array([0.16695601, 0.16367807, 0.07926819, 0.05506889, 0.00847338,\n",
       "         0.13035317, 0.00551524, 0.06395211, 0.20082849, 0.12590647]),\n",
       "  array([0.14107298, 0.23684292, 0.06827199, 0.19189877, 0.0516753 ,\n",
       "         0.02431169, 0.07988613, 0.04178488, 0.1540614 , 0.01019393]),\n",
       "  array([0.06311545, 0.15224748, 0.01197097, 0.06442365, 0.26246769,\n",
       "         0.11193115, 0.10279061, 0.04596947, 0.13601283, 0.04907069]),\n",
       "  array([0.20843118, 0.0268187 , 0.11448461, 0.10190148, 0.05526752,\n",
       "         0.05265284, 0.03073567, 0.00817761, 0.13312745, 0.26840293]),\n",
       "  array([0.11694258, 0.11263617, 0.09898888, 0.16522565, 0.16887909,\n",
       "         0.05422235, 0.13497663, 0.06612824, 0.05367043, 0.02832998]),\n",
       "  array([0.0961575 , 0.10682692, 0.11061004, 0.11440689, 0.09380403,\n",
       "         0.11866634, 0.06714769, 0.16517036, 0.04315316, 0.08405707]),\n",
       "  array([0.07089098, 0.01502426, 0.12982137, 0.07242866, 0.01688295,\n",
       "         0.15438132, 0.19403784, 0.03911522, 0.11668156, 0.19073584]),\n",
       "  array([0.00772492, 0.17165162, 0.01078403, 0.10818462, 0.19031132,\n",
       "         0.08834337, 0.0714661 , 0.05979065, 0.12363624, 0.16810713]),\n",
       "  array([0.17801284, 0.12747724, 0.09454444, 0.02508284, 0.01412536,\n",
       "         0.14753671, 0.18896689, 0.0770885 , 0.13115855, 0.01600665]),\n",
       "  array([0.16581495, 0.08136783, 0.04618859, 0.15066345, 0.12990603,\n",
       "         0.041719  , 0.19307763, 0.11980602, 0.06563565, 0.00582085]),\n",
       "  array([0.14497815, 0.0125744 , 0.14748061, 0.17107987, 0.03876223,\n",
       "         0.09067547, 0.05828457, 0.08331474, 0.07906621, 0.17378375]),\n",
       "  array([0.08395313, 0.10997748, 0.03929723, 0.0112971 , 0.21590222,\n",
       "         0.02793984, 0.10605041, 0.1457561 , 0.09819819, 0.1616283 ]),\n",
       "  array([0.09242536, 0.04574407, 0.21830563, 0.01842192, 0.14500656,\n",
       "         0.03596711, 0.20309097, 0.04729242, 0.05390334, 0.13984262]),\n",
       "  array([0.09598449, 0.13441339, 0.06683623, 0.08499679, 0.046176  ,\n",
       "         0.16620092, 0.1746984 , 0.06176668, 0.07191797, 0.09700914]),\n",
       "  array([0.14628271, 0.04873824, 0.0943117 , 0.11475148, 0.11125093,\n",
       "         0.18679444, 0.11919423, 0.01780785, 0.00585428, 0.15501414]),\n",
       "  array([0.10563543, 0.07052455, 0.0517846 , 0.14977424, 0.05110199,\n",
       "         0.07264836, 0.18625896, 0.10561947, 0.16738937, 0.03926302]),\n",
       "  array([0.12087086, 0.13829553, 0.01583047, 0.07422134, 0.11465968,\n",
       "         0.07825314, 0.12290481, 0.08817411, 0.1316584 , 0.11513166]),\n",
       "  array([0.13902292, 0.05297998, 0.00038958, 0.15833038, 0.09147721,\n",
       "         0.07289884, 0.17774545, 0.06533802, 0.14286375, 0.09895385]),\n",
       "  array([0.14542857, 0.01609565, 0.03908855, 0.15013498, 0.05145049,\n",
       "         0.20963682, 0.08058375, 0.21319593, 0.00304045, 0.09134482]),\n",
       "  array([0.10363879, 0.01020305, 0.04105809, 0.10497117, 0.13194252,\n",
       "         0.05392295, 0.16716667, 0.08725456, 0.15630806, 0.14353415]),\n",
       "  array([0.12937803, 0.05332618, 0.0106814 , 0.2468856 , 0.14564778,\n",
       "         0.06586676, 0.18770929, 0.07595489, 0.03483094, 0.04971914]),\n",
       "  array([0.20771718, 0.20057881, 0.02905644, 0.15678292, 0.04156138,\n",
       "         0.04884719, 0.11541885, 0.03645433, 0.08298757, 0.08059534]),\n",
       "  array([0.03502198, 0.03467924, 0.07524127, 0.13730214, 0.16878462,\n",
       "         0.16444229, 0.16448456, 0.07982672, 0.11437723, 0.02583996]),\n",
       "  array([0.00451852, 0.09467421, 0.13996861, 0.03356258, 0.02027975,\n",
       "         0.13548109, 0.14860872, 0.1272369 , 0.15324996, 0.14241967]),\n",
       "  array([0.15019692, 0.05071918, 0.00985463, 0.11781906, 0.06885141,\n",
       "         0.19114812, 0.07854214, 0.1062349 , 0.07349013, 0.15314351]),\n",
       "  array([0.12661694, 0.14971742, 0.06720107, 0.07813487, 0.03182484,\n",
       "         0.15752543, 0.19337608, 0.00629822, 0.07173362, 0.11757151]),\n",
       "  array([0.18789786, 0.11592545, 0.15241815, 0.07460564, 0.09258912,\n",
       "         0.01855145, 0.08187672, 0.14332931, 0.08562204, 0.04718427]),\n",
       "  array([0.03183592, 0.06782027, 0.16815285, 0.14934532, 0.17349541,\n",
       "         0.00290179, 0.16303075, 0.00243023, 0.08134063, 0.15964683]),\n",
       "  array([0.041073  , 0.23833982, 0.11264896, 0.16556412, 0.10085209,\n",
       "         0.11954034, 0.00829216, 0.02278322, 0.00332391, 0.18758238]),\n",
       "  array([0.15542018, 0.06684717, 0.17951795, 0.05032024, 0.07888263,\n",
       "         0.04334081, 0.08373736, 0.10773921, 0.10059554, 0.1335989 ]),\n",
       "  array([0.03242566, 0.08429665, 0.14007062, 0.11982232, 0.13502564,\n",
       "         0.03711927, 0.08471575, 0.05329   , 0.15826202, 0.15497207]),\n",
       "  array([0.07663845, 0.13461129, 0.09877936, 0.00667859, 0.06503652,\n",
       "         0.01926537, 0.18307193, 0.13509163, 0.16611875, 0.1147081 ]),\n",
       "  array([0.12558885, 0.19822359, 0.12683021, 0.09821151, 0.0253823 ,\n",
       "         0.00230278, 0.07072603, 0.1051845 , 0.13256456, 0.11498569]),\n",
       "  array([0.05465334, 0.04451731, 0.01722313, 0.16669008, 0.20471607,\n",
       "         0.00402144, 0.04075913, 0.13610238, 0.12252909, 0.20878802]),\n",
       "  array([0.02324594, 0.13908258, 0.04415597, 0.05357606, 0.16814283,\n",
       "         0.00957779, 0.19450795, 0.11151377, 0.06064234, 0.19555478]),\n",
       "  array([0.20386228, 0.13031788, 0.15033352, 0.00301774, 0.2086163 ,\n",
       "         0.06575884, 0.07104555, 0.05105822, 0.05268248, 0.06330719]),\n",
       "  array([0.08498707, 0.06004494, 0.00683739, 0.17706983, 0.04679066,\n",
       "         0.11076074, 0.2024622 , 0.11568157, 0.18960475, 0.00576085]),\n",
       "  array([0.13418409, 0.12627452, 0.12355924, 0.06831029, 0.06670498,\n",
       "         0.15662099, 0.05584626, 0.04180518, 0.07830814, 0.14838631]),\n",
       "  array([0.08981702, 0.09954033, 0.09485316, 0.14809548, 0.13501927,\n",
       "         0.13981806, 0.12376247, 0.02839407, 0.07699547, 0.06370467]),\n",
       "  array([0.14089671, 0.18566801, 0.06468802, 0.05612637, 0.19286571,\n",
       "         0.2091821 , 0.07657036, 0.00682507, 0.0226371 , 0.04454054]),\n",
       "  array([0.02971947, 0.05322631, 0.12011087, 0.0704477 , 0.06292499,\n",
       "         0.07508758, 0.17354176, 0.11366413, 0.13442857, 0.16684862]),\n",
       "  array([0.00963264, 0.14859313, 0.04060791, 0.07968462, 0.16231746,\n",
       "         0.00939089, 0.12188818, 0.18363928, 0.10529332, 0.13895258]),\n",
       "  array([0.03907422, 0.19145394, 0.16724148, 0.16940124, 0.11468407,\n",
       "         0.12669578, 0.00186849, 0.00090207, 0.00468762, 0.18399109]),\n",
       "  array([0.12882675, 0.18096274, 0.12819095, 0.0128627 , 0.14903374,\n",
       "         0.06844132, 0.00514529, 0.16203108, 0.09794365, 0.06656179]),\n",
       "  array([0.15741288, 0.04017856, 0.12724318, 0.00967903, 0.13536903,\n",
       "         0.10824129, 0.04290054, 0.15156595, 0.13978535, 0.08762419]),\n",
       "  array([0.02242799, 0.20557878, 0.09280492, 0.15377534, 0.06127643,\n",
       "         0.20512827, 0.13621883, 0.11048727, 0.00704269, 0.00525947]),\n",
       "  array([0.06067024, 0.14201385, 0.09713764, 0.07431657, 0.10006963,\n",
       "         0.14686724, 0.13857034, 0.02255733, 0.08789731, 0.12989985]),\n",
       "  array([0.07001837, 0.10773424, 0.0353995 , 0.19042442, 0.11984835,\n",
       "         0.05713907, 0.05986999, 0.15726126, 0.17789495, 0.02440985]),\n",
       "  array([0.04334074, 0.10304705, 0.0497075 , 0.07327949, 0.04558526,\n",
       "         0.15576101, 0.12457852, 0.10568908, 0.15026931, 0.14874205]),\n",
       "  array([0.05434025, 0.11530603, 0.15777714, 0.14724771, 0.15628612,\n",
       "         0.04316993, 0.05081261, 0.11014241, 0.05242741, 0.11249039]),\n",
       "  array([0.02292777, 0.05257834, 0.20568551, 0.02037302, 0.07542635,\n",
       "         0.04928858, 0.12331922, 0.1628459 , 0.08754982, 0.20000549]),\n",
       "  array([0.02369641, 0.12554558, 0.0520228 , 0.06999952, 0.11460896,\n",
       "         0.14907838, 0.13790365, 0.12235905, 0.19242971, 0.01235592]),\n",
       "  array([0.1629042 , 0.13772749, 0.1521032 , 0.08242148, 0.0301304 ,\n",
       "         0.03426248, 0.09216323, 0.05919829, 0.16313491, 0.08595431]),\n",
       "  array([0.06003129, 0.13650011, 0.12763765, 0.1646674 , 0.06522379,\n",
       "         0.15999926, 0.00217169, 0.05669199, 0.19839577, 0.02868105]),\n",
       "  array([0.04422204, 0.1631974 , 0.10000851, 0.05496459, 0.12482419,\n",
       "         0.02821075, 0.14495219, 0.13621491, 0.12094751, 0.08245792]),\n",
       "  array([0.11484055, 0.09726063, 0.11582265, 0.03575351, 0.20019836,\n",
       "         0.11183069, 0.08784195, 0.07605364, 0.14689442, 0.01350361]),\n",
       "  array([0.02904739, 0.17362576, 0.28180589, 0.03616437, 0.09692364,\n",
       "         0.04114915, 0.06112508, 0.12545231, 0.00873047, 0.14597593]),\n",
       "  array([0.0886313 , 0.14613895, 0.05808128, 0.06862403, 0.07276967,\n",
       "         0.12748999, 0.05847743, 0.12037495, 0.13778052, 0.12163189]),\n",
       "  array([0.11065411, 0.06084662, 0.15784176, 0.03238756, 0.19980678,\n",
       "         0.15768266, 0.06360453, 0.02702806, 0.04682031, 0.14332762]),\n",
       "  array([0.0583628 , 0.15690703, 0.00986951, 0.08020202, 0.13672901,\n",
       "         0.02150416, 0.07437926, 0.14404516, 0.17427652, 0.14372453]),\n",
       "  array([0.07163039, 0.16567316, 0.03232219, 0.19227106, 0.17353432,\n",
       "         0.12799407, 0.01788914, 0.0345046 , 0.17507692, 0.00910415]),\n",
       "  array([0.13660634, 0.04289346, 0.10660253, 0.11469184, 0.09423401,\n",
       "         0.00721184, 0.20240045, 0.18790258, 0.08286627, 0.02459069]),\n",
       "  array([0.02863402, 0.03524916, 0.22972168, 0.02382347, 0.06247472,\n",
       "         0.05449351, 0.0979357 , 0.06574627, 0.1365381 , 0.26538336]),\n",
       "  array([0.06998429, 0.03086413, 0.14189298, 0.00300193, 0.01363626,\n",
       "         0.13775517, 0.12621326, 0.17438569, 0.11126791, 0.19099837]),\n",
       "  array([0.09841153, 0.15201143, 0.01157111, 0.07245651, 0.13477177,\n",
       "         0.17005821, 0.05196469, 0.01966911, 0.16944915, 0.1196365 ]),\n",
       "  array([0.14609994, 0.05536522, 0.13378812, 0.13475833, 0.08340632,\n",
       "         0.15778324, 0.00452263, 0.04882144, 0.14471145, 0.09074332]),\n",
       "  array([0.15320739, 0.07384125, 0.07010875, 0.00216933, 0.04215989,\n",
       "         0.15521314, 0.14570515, 0.15388709, 0.17358961, 0.03011841]),\n",
       "  array([0.1625694 , 0.12380875, 0.13779476, 0.03912719, 0.09428462,\n",
       "         0.14862932, 0.04031801, 0.05380272, 0.12641882, 0.0732464 ]),\n",
       "  array([0.04863639, 0.16610626, 0.17329877, 0.11726846, 0.07126607,\n",
       "         0.0314479 , 0.1412403 , 0.00876486, 0.12208447, 0.11988651]),\n",
       "  array([0.15565173, 0.16266637, 0.04987137, 0.02260496, 0.03248734,\n",
       "         0.13165385, 0.15584096, 0.15614028, 0.07316426, 0.05991886]),\n",
       "  array([0.02290052, 0.05419184, 0.18836228, 0.16150223, 0.21333491,\n",
       "         0.03283634, 0.01678613, 0.20339656, 0.09527003, 0.01141915]),\n",
       "  array([0.150617  , 0.17576224, 0.1416108 , 0.07043978, 0.0445844 ,\n",
       "         0.18810046, 0.01214898, 0.1190472 , 0.07795792, 0.01973122]),\n",
       "  array([0.09808791, 0.13743262, 0.10289772, 0.10704639, 0.11508474,\n",
       "         0.03634827, 0.23047512, 0.06039724, 0.04296037, 0.06926962]),\n",
       "  array([0.13615239, 0.04207426, 0.12558614, 0.09161697, 0.07772573,\n",
       "         0.09172129, 0.06286157, 0.10672778, 0.16369298, 0.10184088]),\n",
       "  array([0.13103431, 0.12840407, 0.09128117, 0.00921127, 0.06910902,\n",
       "         0.09289981, 0.13105193, 0.12564968, 0.10363809, 0.11772066]),\n",
       "  array([0.16954098, 0.11327271, 0.17555918, 0.1417776 , 0.0203009 ,\n",
       "         0.10419341, 0.15479945, 0.01431966, 0.07173829, 0.03449783]),\n",
       "  array([0.09303748, 0.04784843, 0.11019327, 0.07391179, 0.14082651,\n",
       "         0.13352887, 0.14320417, 0.06276997, 0.15374069, 0.04093883]),\n",
       "  array([0.10222096, 0.10875282, 0.11510207, 0.08773054, 0.10618423,\n",
       "         0.06018529, 0.09574248, 0.08646586, 0.11832609, 0.11928966]),\n",
       "  array([0.01610116, 0.13715186, 0.15930463, 0.10739893, 0.13523375,\n",
       "         0.01399598, 0.16593488, 0.1558344 , 0.06232353, 0.04672087]),\n",
       "  array([0.10299427, 0.13656379, 0.1250966 , 0.00143297, 0.12718158,\n",
       "         0.02327695, 0.08910658, 0.1507792 , 0.07925617, 0.16431188]),\n",
       "  array([0.01751944, 0.15283557, 0.07776045, 0.18160564, 0.0050926 ,\n",
       "         0.02123299, 0.10731332, 0.08623592, 0.19984518, 0.15055889]),\n",
       "  array([0.07542124, 0.21172396, 0.01232391, 0.06843129, 0.12354003,\n",
       "         0.05439346, 0.19098146, 0.17984579, 0.03263104, 0.05070783]),\n",
       "  array([0.10756431, 0.16678108, 0.15693998, 0.01090794, 0.06249691,\n",
       "         0.05654641, 0.09103878, 0.1978143 , 0.13856099, 0.01134929]),\n",
       "  array([0.20580647, 0.1174555 , 0.19036915, 0.07083571, 0.17657323,\n",
       "         0.06495675, 0.0109644 , 0.04685694, 0.08682601, 0.02935585]),\n",
       "  array([0.21709851, 0.00805005, 0.12611306, 0.16338087, 0.06083891,\n",
       "         0.03759835, 0.08195037, 0.20449919, 0.08923191, 0.01123876]),\n",
       "  array([3.83917255e-02, 1.32105538e-01, 7.97178911e-02, 2.18156383e-01,\n",
       "         5.26364217e-02, 7.33722287e-05, 1.16840461e-01, 7.96113865e-02,\n",
       "         5.90277674e-02, 2.23439055e-01]),\n",
       "  array([0.04928173, 0.17010228, 0.12569118, 0.04671966, 0.16182592,\n",
       "         0.02373215, 0.14487868, 0.13919929, 0.1087803 , 0.02978882]),\n",
       "  array([0.04098756, 0.16204234, 0.06585862, 0.14289495, 0.12998402,\n",
       "         0.08076659, 0.15608704, 0.06452236, 0.03098007, 0.12587646]),\n",
       "  array([0.08238577, 0.11727254, 0.11146226, 0.03070612, 0.06506816,\n",
       "         0.01843434, 0.16197627, 0.12413091, 0.082933  , 0.20563063]),\n",
       "  array([0.02593396, 0.01490954, 0.0451522 , 0.22236808, 0.05784123,\n",
       "         0.02001479, 0.14908624, 0.20166597, 0.13364688, 0.12938112]),\n",
       "  array([0.05880337, 0.15816746, 0.06733666, 0.14568444, 0.10564088,\n",
       "         0.06260052, 0.00929975, 0.16788717, 0.16296946, 0.06161029]),\n",
       "  array([0.00368809, 0.03850738, 0.02866778, 0.26848756, 0.0979048 ,\n",
       "         0.06034247, 0.00161471, 0.19702026, 0.1488068 , 0.15496015]),\n",
       "  array([0.03205937, 0.12508576, 0.14616758, 0.09089767, 0.05609773,\n",
       "         0.09511614, 0.16555916, 0.16694378, 0.09223683, 0.02983599]),\n",
       "  array([0.16833334, 0.19820419, 0.17453378, 0.09267778, 0.03618594,\n",
       "         0.06017567, 0.21014779, 0.03722855, 0.01485885, 0.00765411]),\n",
       "  array([0.07723057, 0.16270065, 0.05933943, 0.17590523, 0.03216007,\n",
       "         0.1116416 , 0.01448863, 0.15507118, 0.04222521, 0.16923744]),\n",
       "  array([0.08146325, 0.10407398, 0.12478365, 0.09507772, 0.0998647 ,\n",
       "         0.05348539, 0.12620809, 0.12261867, 0.09292358, 0.09950097]),\n",
       "  array([0.16590015, 0.1369581 , 0.0949277 , 0.14915526, 0.15333672,\n",
       "         0.06580168, 0.04123334, 0.12331383, 0.03491891, 0.03445432]),\n",
       "  array([0.0805076 , 0.16959026, 0.15600305, 0.08397177, 0.13448967,\n",
       "         0.06972289, 0.00216289, 0.13423511, 0.09801398, 0.07130276]),\n",
       "  array([0.11558099, 0.03459084, 0.09045088, 0.16589447, 0.04625406,\n",
       "         0.00227213, 0.1896403 , 0.09433069, 0.09595894, 0.16502669]),\n",
       "  array([0.0027095 , 0.14701853, 0.02366976, 0.10397478, 0.17346121,\n",
       "         0.1354953 , 0.10004769, 0.07992346, 0.12850782, 0.10519195]),\n",
       "  array([0.06743632, 0.29138227, 0.13121665, 0.04700186, 0.14250627,\n",
       "         0.00679967, 0.07978399, 0.0315246 , 0.19111823, 0.01123016]),\n",
       "  array([0.09242855, 0.10917207, 0.16483114, 0.15351797, 0.1151385 ,\n",
       "         0.13537689, 0.00930245, 0.08496547, 0.09845748, 0.03680947]),\n",
       "  array([0.10936267, 0.02857719, 0.06196192, 0.11666746, 0.13911251,\n",
       "         0.18328851, 0.00816225, 0.10145407, 0.06889483, 0.18251858]),\n",
       "  array([0.04112085, 0.13622354, 0.05769524, 0.08510375, 0.07881196,\n",
       "         0.16466979, 0.03033975, 0.06426085, 0.25985565, 0.08191861]),\n",
       "  array([0.05351633, 0.07634967, 0.0624326 , 0.06670435, 0.02147355,\n",
       "         0.2017732 , 0.17420342, 0.1815239 , 0.08558965, 0.07643334]),\n",
       "  array([0.15520598, 0.17035056, 0.07271523, 0.08289761, 0.03241662,\n",
       "         0.17849465, 0.10761094, 0.05903146, 0.01674011, 0.12453685]),\n",
       "  array([0.06739833, 0.05437786, 0.16475196, 0.05678575, 0.0799593 ,\n",
       "         0.17402094, 0.0558555 , 0.04760398, 0.1579159 , 0.14133048]),\n",
       "  array([0.23502892, 0.17787394, 0.22900226, 0.01755904, 0.04521252,\n",
       "         0.11317313, 0.03141899, 0.0256237 , 0.04143701, 0.0836705 ]),\n",
       "  array([0.18887339, 0.17425509, 0.02968907, 0.08965112, 0.02924192,\n",
       "         0.01604811, 0.04187026, 0.15528516, 0.11721017, 0.15787573]),\n",
       "  array([0.24202636, 0.01310759, 0.02117683, 0.19012922, 0.18045679,\n",
       "         0.06717393, 0.13206849, 0.02328969, 0.0182781 , 0.11229301]),\n",
       "  array([0.10623577, 0.151754  , 0.04420284, 0.13792301, 0.06814645,\n",
       "         0.09908199, 0.14578161, 0.08210872, 0.04651715, 0.11824845]),\n",
       "  array([0.04355144, 0.05902047, 0.02655474, 0.17316068, 0.19437565,\n",
       "         0.06679336, 0.10109497, 0.13101599, 0.04341331, 0.16101939]),\n",
       "  array([0.16675586, 0.20725612, 0.03670206, 0.20464132, 0.04023849,\n",
       "         0.02563922, 0.02339719, 0.03023691, 0.22989265, 0.03524018]),\n",
       "  array([0.19169218, 0.08101688, 0.08587485, 0.01366055, 0.00443723,\n",
       "         0.20164533, 0.10040033, 0.04111712, 0.15105224, 0.12910328]),\n",
       "  array([0.11391572, 0.16882023, 0.17349497, 0.07479903, 0.05009883,\n",
       "         0.09250268, 0.18808148, 0.0173183 , 0.10878367, 0.01218509]),\n",
       "  array([0.04140166, 0.33206805, 0.25056898, 0.084672  , 0.04057774,\n",
       "         0.00716721, 0.06758249, 0.00165073, 0.16414129, 0.01016985]),\n",
       "  array([0.17671984, 0.17367935, 0.01326598, 0.08373543, 0.09240022,\n",
       "         0.12371165, 0.03907539, 0.16094061, 0.10718946, 0.02928208]),\n",
       "  array([0.13657584, 0.12586613, 0.14022484, 0.0325123 , 0.06067799,\n",
       "         0.15792743, 0.11701888, 0.06947504, 0.11776327, 0.04195829]),\n",
       "  array([0.18217508, 0.0942335 , 0.15529454, 0.051557  , 0.05219363,\n",
       "         0.11055491, 0.02822635, 0.14484793, 0.05297213, 0.12794491]),\n",
       "  array([0.10250847, 0.12230971, 0.08898954, 0.19269544, 0.19586109,\n",
       "         0.12787277, 0.05340977, 0.07550177, 0.03483292, 0.00601852]),\n",
       "  array([0.1437753 , 0.12203758, 0.17833805, 0.02227394, 0.05594383,\n",
       "         0.0957785 , 0.01061343, 0.13749667, 0.10930116, 0.12444154]),\n",
       "  array([0.11387898, 0.13088417, 0.05945788, 0.08353038, 0.00480016,\n",
       "         0.15786981, 0.10675728, 0.0933267 , 0.15887165, 0.09062299]),\n",
       "  array([0.01117455, 0.14618166, 0.22040816, 0.11704948, 0.15928759,\n",
       "         0.02961951, 0.14706095, 0.0084942 , 0.09654107, 0.06418283]),\n",
       "  array([0.12243902, 0.0674636 , 0.14561691, 0.14198407, 0.13435179,\n",
       "         0.08506038, 0.1260326 , 0.0221532 , 0.12859832, 0.02630012]),\n",
       "  array([0.08458243, 0.00588984, 0.20365485, 0.04764047, 0.06626172,\n",
       "         0.18393898, 0.11169211, 0.16347907, 0.03998997, 0.09287055]),\n",
       "  array([0.01748899, 0.08018024, 0.09729445, 0.10829238, 0.15731416,\n",
       "         0.12118579, 0.03703775, 0.09624846, 0.15387508, 0.13108269]),\n",
       "  array([0.0336795 , 0.11002664, 0.12625639, 0.14211285, 0.10942991,\n",
       "         0.12071176, 0.14517866, 0.03554257, 0.04094242, 0.1361193 ]),\n",
       "  array([0.12211695, 0.09906817, 0.07475202, 0.03956177, 0.11971312,\n",
       "         0.1360716 , 0.16496109, 0.06740795, 0.01260774, 0.1637396 ]),\n",
       "  array([0.10946704, 0.00518451, 0.06718566, 0.27006639, 0.00097618,\n",
       "         0.17154458, 0.13542716, 0.0720302 , 0.0909156 , 0.07720268]),\n",
       "  array([0.07660827, 0.14413428, 0.12323318, 0.09975355, 0.08905677,\n",
       "         0.10003864, 0.08236552, 0.13711048, 0.05821452, 0.08948478]),\n",
       "  array([0.02162597, 0.02199091, 0.223708  , 0.22847957, 0.11171931,\n",
       "         0.19249276, 0.02706574, 0.13043124, 0.02055331, 0.02193319]),\n",
       "  array([0.04163761, 0.096537  , 0.0947264 , 0.10921716, 0.11028455,\n",
       "         0.17148059, 0.10123902, 0.05321253, 0.15471417, 0.06695099]),\n",
       "  array([0.11394344, 0.15577199, 0.11609655, 0.12370237, 0.05281837,\n",
       "         0.04625434, 0.12414634, 0.16251541, 0.02688296, 0.07786822]),\n",
       "  array([0.15282212, 0.1616019 , 0.07365415, 0.03382748, 0.07575446,\n",
       "         0.1230425 , 0.07338917, 0.08121295, 0.11188502, 0.11281023]),\n",
       "  array([0.11138348, 0.15914791, 0.07455153, 0.13136169, 0.13785479,\n",
       "         0.00710771, 0.01295072, 0.09084772, 0.13222694, 0.14256751]),\n",
       "  array([0.12890555, 0.01220173, 0.09774058, 0.2227513 , 0.02252643,\n",
       "         0.11493784, 0.12463359, 0.01357988, 0.14675578, 0.11596731]),\n",
       "  array([0.17663   , 0.17622514, 0.05707326, 0.06979548, 0.18305015,\n",
       "         0.0410072 , 0.08013242, 0.12876756, 0.07223164, 0.01508714]),\n",
       "  array([0.0193645 , 0.23555658, 0.1792975 , 0.0286856 , 0.10953971,\n",
       "         0.09094272, 0.05701645, 0.08099163, 0.13863427, 0.05997104]),\n",
       "  array([0.04342257, 0.04387963, 0.03011258, 0.14425719, 0.00619937,\n",
       "         0.20762319, 0.07073944, 0.05396057, 0.23150219, 0.16830328]),\n",
       "  array([0.15024262, 0.0894112 , 0.04415273, 0.09878878, 0.00423211,\n",
       "         0.12095046, 0.09080933, 0.16031238, 0.07668216, 0.16441824]),\n",
       "  array([0.14414783, 0.09259237, 0.15276061, 0.02994204, 0.00932372,\n",
       "         0.12248388, 0.11594249, 0.16076716, 0.11416286, 0.05787704]),\n",
       "  array([0.1015384 , 0.05839661, 0.10824777, 0.1737906 , 0.154747  ,\n",
       "         0.10927721, 0.00442378, 0.0939464 , 0.11450267, 0.08112955]),\n",
       "  array([0.04251397, 0.12277106, 0.13525983, 0.14191376, 0.11133494,\n",
       "         0.03155869, 0.1021064 , 0.08489879, 0.13059486, 0.0970477 ]),\n",
       "  array([0.05035223, 0.07736823, 0.07135075, 0.07685875, 0.10825227,\n",
       "         0.16036577, 0.1197099 , 0.16173255, 0.03904924, 0.13496032]),\n",
       "  array([0.11747306, 0.14782878, 0.00519234, 0.07539366, 0.06548785,\n",
       "         0.05927139, 0.12095636, 0.1069239 , 0.15057001, 0.15090267]),\n",
       "  array([0.01673673, 0.07275313, 0.09691293, 0.10426502, 0.12711179,\n",
       "         0.16439005, 0.12082133, 0.04438784, 0.14537078, 0.1072504 ]),\n",
       "  array([0.04851633, 0.04342886, 0.14113441, 0.1753047 , 0.08902378,\n",
       "         0.06643805, 0.18629061, 0.09121316, 0.04014608, 0.11850402]),\n",
       "  array([0.12687091, 0.09206471, 0.16284139, 0.17005097, 0.16253402,\n",
       "         0.1758001 , 0.01590122, 0.00999665, 0.06031838, 0.02362164]),\n",
       "  array([0.1256635 , 0.06070717, 0.13110178, 0.14791671, 0.0689993 ,\n",
       "         0.16178576, 0.08505059, 0.10331661, 0.06534597, 0.05011261]),\n",
       "  array([0.0960358 , 0.10144443, 0.13951984, 0.15704428, 0.04492184,\n",
       "         0.13851787, 0.01632529, 0.08833719, 0.17056987, 0.04728359]),\n",
       "  array([0.06739024, 0.01272173, 0.0453939 , 0.03978203, 0.17025146,\n",
       "         0.16668552, 0.04927559, 0.11704462, 0.17813881, 0.1533161 ]),\n",
       "  array([0.18529933, 0.11111074, 0.00726852, 0.11454323, 0.171141  ,\n",
       "         0.1057152 , 0.01418389, 0.15153238, 0.03577466, 0.10343106]),\n",
       "  array([0.14529431, 0.12667839, 0.11185606, 0.08612146, 0.00032755,\n",
       "         0.15784109, 0.08068885, 0.17878485, 0.10190136, 0.01050608]),\n",
       "  array([0.13269793, 0.1446806 , 0.0801586 , 0.08440264, 0.12304489,\n",
       "         0.15265123, 0.11874449, 0.02068961, 0.06777938, 0.07515061]),\n",
       "  array([0.08527258, 0.12936799, 0.11440464, 0.12195386, 0.11482734,\n",
       "         0.15266606, 0.09010051, 0.03192136, 0.09053552, 0.06895015]),\n",
       "  array([0.00558318, 0.00281399, 0.14901905, 0.16283512, 0.01604181,\n",
       "         0.19741182, 0.17151251, 0.11664591, 0.14388394, 0.03425267]),\n",
       "  array([0.12513963, 0.11131547, 0.11994237, 0.0657334 , 0.14885755,\n",
       "         0.16920811, 0.12808574, 0.0728998 , 0.01786019, 0.04095774]),\n",
       "  array([0.01892478, 0.17309093, 0.04630803, 0.15255639, 0.09074405,\n",
       "         0.05066181, 0.15744303, 0.161501  , 0.08001091, 0.06875906]),\n",
       "  array([0.08373563, 0.03680793, 0.12821999, 0.1607226 , 0.14989279,\n",
       "         0.04714182, 0.12090956, 0.09588236, 0.10484155, 0.07184578]),\n",
       "  array([0.07051748, 0.18045746, 0.02378219, 0.03767586, 0.17371601,\n",
       "         0.12358395, 0.00888325, 0.12099573, 0.12209127, 0.13829682]),\n",
       "  array([0.02482757, 0.02860292, 0.19210585, 0.15450856, 0.13462657,\n",
       "         0.00429412, 0.15764293, 0.01252958, 0.17671495, 0.11414695]),\n",
       "  array([0.16234545, 0.16635349, 0.03380469, 0.03412887, 0.12901849,\n",
       "         0.02017587, 0.17300751, 0.13844719, 0.02564906, 0.11706938]),\n",
       "  array([0.12174687, 0.14286849, 0.02226666, 0.06244815, 0.02271498,\n",
       "         0.15039445, 0.04237939, 0.15017316, 0.15045114, 0.1345567 ]),\n",
       "  array([0.08180726, 0.12746504, 0.02436574, 0.15362195, 0.12262053,\n",
       "         0.02709229, 0.15936762, 0.11507096, 0.06956184, 0.11902677]),\n",
       "  array([0.03355254, 0.01507453, 0.09806207, 0.12427635, 0.01504304,\n",
       "         0.15971611, 0.1910822 , 0.17498309, 0.03209397, 0.1561161 ]),\n",
       "  array([0.16651675, 0.05199997, 0.10259817, 0.10920954, 0.15039786,\n",
       "         0.03714363, 0.14511979, 0.05289398, 0.09214828, 0.09197203]),\n",
       "  array([0.09981082, 0.03512385, 0.19142634, 0.14261351, 0.19343419,\n",
       "         0.02068336, 0.09116607, 0.07599517, 0.08529952, 0.06444717]),\n",
       "  array([0.13569701, 0.10879529, 0.00545981, 0.09448722, 0.09426322,\n",
       "         0.15959174, 0.14794307, 0.09716525, 0.13025773, 0.02633965]),\n",
       "  array([0.10301812, 0.14756545, 0.12549881, 0.05462691, 0.04238579,\n",
       "         0.10247906, 0.14089627, 0.01025689, 0.0794552 , 0.1938175 ]),\n",
       "  array([0.2106681 , 0.05083177, 0.05007646, 0.07604975, 0.14776854,\n",
       "         0.16387606, 0.04954619, 0.06538252, 0.0941818 , 0.09161883]),\n",
       "  array([0.1322336 , 0.13143293, 0.02771765, 0.11407511, 0.20170517,\n",
       "         0.00288849, 0.19145714, 0.01626736, 0.06556932, 0.11665322]),\n",
       "  array([0.13659367, 0.02892703, 0.0862354 , 0.15137453, 0.13605771,\n",
       "         0.01672203, 0.13520292, 0.1967149 , 0.03972775, 0.07244404]),\n",
       "  array([0.18536747, 0.10494431, 0.12622061, 0.20365906, 0.01287574,\n",
       "         0.01529243, 0.0376192 , 0.093979  , 0.12624326, 0.09379892]),\n",
       "  array([0.1980352 , 0.14301003, 0.03520703, 0.10116121, 0.06393063,\n",
       "         0.02475372, 0.07931023, 0.12684615, 0.18626513, 0.04148066]),\n",
       "  array([0.16522535, 0.09551773, 0.09635548, 0.10611386, 0.0714841 ,\n",
       "         0.07298709, 0.16478837, 0.08815315, 0.11996039, 0.01941448]),\n",
       "  array([0.15204821, 0.06315945, 0.04957481, 0.02240913, 0.24924571,\n",
       "         0.10583287, 0.12164417, 0.16389985, 0.05327121, 0.0189146 ]),\n",
       "  array([0.09325201, 0.15711553, 0.20896757, 0.02551753, 0.20985326,\n",
       "         0.12141914, 0.0222056 , 0.03396048, 0.03962962, 0.08807926]),\n",
       "  array([0.11554273, 0.02940489, 0.19311732, 0.14710463, 0.10478723,\n",
       "         0.0521579 , 0.03837035, 0.14609958, 0.01625662, 0.15715875]),\n",
       "  array([0.12823662, 0.09469973, 0.16297194, 0.02853962, 0.15738064,\n",
       "         0.01805259, 0.04159426, 0.11150391, 0.16962685, 0.08739384]),\n",
       "  array([0.08516487, 0.10569046, 0.16887903, 0.00578097, 0.04883843,\n",
       "         0.1062225 , 0.1308247 , 0.09571742, 0.08620401, 0.16667762]),\n",
       "  array([0.03968078, 0.11732612, 0.02642907, 0.16860613, 0.127519  ,\n",
       "         0.18015889, 0.15312122, 0.00865361, 0.16095015, 0.01755504]),\n",
       "  array([0.17552059, 0.11148307, 0.09557115, 0.11713773, 0.06579875,\n",
       "         0.04601539, 0.0871074 , 0.01903009, 0.11378665, 0.16854919]),\n",
       "  array([0.02518672, 0.05678657, 0.03810333, 0.06595002, 0.12029133,\n",
       "         0.13507302, 0.14106426, 0.14157914, 0.1209139 , 0.15505172]),\n",
       "  array([0.16709726, 0.03537701, 0.04691828, 0.03239882, 0.13851386,\n",
       "         0.14539998, 0.14040448, 0.1353129 , 0.00453227, 0.15404514]),\n",
       "  array([0.03553764, 0.09254104, 0.07667761, 0.15458815, 0.05147365,\n",
       "         0.16234546, 0.11561892, 0.05694575, 0.15208722, 0.10218456]),\n",
       "  array([0.08365808, 0.18386381, 0.13405613, 0.06112641, 0.06236799,\n",
       "         0.19663542, 0.06559895, 0.03103031, 0.08864424, 0.09301865]),\n",
       "  array([0.04441131, 0.20443371, 0.06744674, 0.18509412, 0.01364297,\n",
       "         0.05776699, 0.07672063, 0.12183304, 0.05243839, 0.17621209]),\n",
       "  array([0.11404666, 0.09980807, 0.07581863, 0.20661306, 0.05653526,\n",
       "         0.19747214, 0.07619199, 0.09016698, 0.00600024, 0.07734698]),\n",
       "  array([0.07543689, 0.19245221, 0.04057141, 0.12139127, 0.16627432,\n",
       "         0.04114094, 0.04490675, 0.19677724, 0.01203315, 0.10901581]),\n",
       "  array([0.1211566 , 0.06666568, 0.00292185, 0.11312868, 0.23576805,\n",
       "         0.11905614, 0.13985115, 0.13719286, 0.02655738, 0.03770162]),\n",
       "  array([0.11365806, 0.05552955, 0.06371591, 0.12655638, 0.17951923,\n",
       "         0.08434706, 0.10799874, 0.06257707, 0.16188636, 0.04421164]),\n",
       "  array([0.04610084, 0.03219493, 0.21798186, 0.09772346, 0.04131562,\n",
       "         0.14848123, 0.13162519, 0.061112  , 0.01810259, 0.20536226]),\n",
       "  array([0.16305603, 0.08224439, 0.00807525, 0.00700843, 0.0698547 ,\n",
       "         0.09261829, 0.12337133, 0.17775984, 0.10270561, 0.17330614]),\n",
       "  array([0.10748963, 0.11156895, 0.10296564, 0.04362511, 0.13734907,\n",
       "         0.06213465, 0.05845439, 0.12914979, 0.08924012, 0.15802264]),\n",
       "  array([0.12930884, 0.12533655, 0.2181186 , 0.06035348, 0.12104861,\n",
       "         0.11491634, 0.03191103, 0.06241343, 0.03050195, 0.10609119]),\n",
       "  array([0.02650921, 0.14030845, 0.13275978, 0.03274195, 0.16815111,\n",
       "         0.13795493, 0.14409963, 0.11115767, 0.08898821, 0.01732907]),\n",
       "  array([0.02556282, 0.04715249, 0.1351801 , 0.16386679, 0.16629178,\n",
       "         0.11328147, 0.08851299, 0.05582192, 0.03312251, 0.17120712]),\n",
       "  array([1.59558750e-01, 4.78995993e-02, 1.48518636e-01, 7.65516224e-02,\n",
       "         3.63826467e-02, 2.19730772e-01, 9.25015419e-02, 1.21115177e-04,\n",
       "         4.58673340e-02, 1.72867983e-01]),\n",
       "  array([0.00446572, 0.08386061, 0.13374748, 0.03377673, 0.17478478,\n",
       "         0.1414315 , 0.17991769, 0.11557461, 0.0283198 , 0.10412109]),\n",
       "  array([0.18129258, 0.08726087, 0.21716725, 0.0027633 , 0.00924303,\n",
       "         0.08115039, 0.20131226, 0.02006265, 0.06478393, 0.13496374]),\n",
       "  array([0.17787592, 0.03770969, 0.00098351, 0.21635846, 0.12286118,\n",
       "         0.0079312 , 0.05242351, 0.16534782, 0.19405755, 0.02445116]),\n",
       "  array([0.11231082, 0.05745662, 0.14784362, 0.09549856, 0.14198969,\n",
       "         0.01851494, 0.06746827, 0.12560284, 0.12250654, 0.1108081 ]),\n",
       "  array([0.10019811, 0.03824276, 0.08535271, 0.12156042, 0.08150019,\n",
       "         0.07933685, 0.07642783, 0.16419039, 0.14245733, 0.11073341]),\n",
       "  array([0.16811998, 0.03448418, 0.0402141 , 0.1174241 , 0.03248998,\n",
       "         0.0752486 , 0.1385761 , 0.09223177, 0.13145973, 0.16975146]),\n",
       "  array([0.06753206, 0.10594144, 0.21125072, 0.13256051, 0.06150163,\n",
       "         0.18210765, 0.01056506, 0.10616015, 0.06392651, 0.05845428]),\n",
       "  array([0.06970256, 0.16207474, 0.07813283, 0.07921193, 0.1487138 ,\n",
       "         0.10536067, 0.13652164, 0.05636194, 0.04701439, 0.1169055 ]),\n",
       "  array([0.06061116, 0.14955251, 0.03714376, 0.00403989, 0.16038955,\n",
       "         0.14977182, 0.12724945, 0.13789122, 0.1027454 , 0.07060524]),\n",
       "  array([0.1118122 , 0.05581511, 0.15288492, 0.0567175 , 0.0248984 ,\n",
       "         0.04391006, 0.04740691, 0.06035147, 0.17574724, 0.2704562 ]),\n",
       "  array([0.09780007, 0.14249011, 0.01259891, 0.18401375, 0.12963313,\n",
       "         0.07510118, 0.01048455, 0.15419852, 0.05142009, 0.1422597 ]),\n",
       "  array([0.15242181, 0.1608935 , 0.02122724, 0.00832224, 0.08408848,\n",
       "         0.17238821, 0.12597284, 0.11358684, 0.00701622, 0.15408261]),\n",
       "  array([0.12363825, 0.12160058, 0.00991967, 0.08522622, 0.0731745 ,\n",
       "         0.11890257, 0.10649817, 0.12555221, 0.12737279, 0.10811504]),\n",
       "  array([0.0459761 , 0.0874329 , 0.1826487 , 0.11559723, 0.03864547,\n",
       "         0.19229344, 0.00697291, 0.17295836, 0.0363565 , 0.12111839]),\n",
       "  array([0.11146774, 0.00409233, 0.1480882 , 0.18227431, 0.10753493,\n",
       "         0.10768352, 0.08966343, 0.03450432, 0.13616438, 0.07852684]),\n",
       "  array([0.09866652, 0.15402174, 0.249621  , 0.1325663 , 0.03110682,\n",
       "         0.02009689, 0.11642932, 0.09970125, 0.09061827, 0.00717189]),\n",
       "  array([0.07805157, 0.01618405, 0.06257414, 0.15996302, 0.06216978,\n",
       "         0.11148104, 0.19667828, 0.09115737, 0.03888917, 0.18285158]),\n",
       "  array([0.11816041, 0.01636813, 0.10421618, 0.05425211, 0.04210054,\n",
       "         0.12482452, 0.1908917 , 0.14615916, 0.17101727, 0.03200998]),\n",
       "  array([0.00179455, 0.02204053, 0.17509968, 0.22151766, 0.12757104,\n",
       "         0.0133181 , 0.01955604, 0.17489504, 0.0119176 , 0.23228977]),\n",
       "  array([0.16191488, 0.03453577, 0.03007955, 0.18710926, 0.09205037,\n",
       "         0.11941003, 0.05560985, 0.16091031, 0.01172033, 0.14665964]),\n",
       "  array([0.13905976, 0.08421147, 0.09748305, 0.15056564, 0.00671124,\n",
       "         0.02242624, 0.21717955, 0.09919516, 0.0135994 , 0.16956849]),\n",
       "  array([0.12617513, 0.10129066, 0.01505988, 0.08319479, 0.14400209,\n",
       "         0.13951344, 0.12631321, 0.07065752, 0.13787046, 0.05592282]),\n",
       "  array([0.04171506, 0.01628476, 0.15933741, 0.00267813, 0.07780458,\n",
       "         0.22448324, 0.01565678, 0.0922547 , 0.22386808, 0.14591727]),\n",
       "  array([0.03995949, 0.00064954, 0.21285922, 0.10176799, 0.09854597,\n",
       "         0.21372595, 0.19975547, 0.01251943, 0.05351487, 0.06670207]),\n",
       "  array([0.01530582, 0.24493768, 0.0757972 , 0.09074463, 0.20857867,\n",
       "         0.02242327, 0.03002345, 0.20487733, 0.04520874, 0.06210324]),\n",
       "  array([0.12839901, 0.06138685, 0.12795013, 0.01013453, 0.12710213,\n",
       "         0.11537756, 0.14958403, 0.06244961, 0.11243113, 0.10518501]),\n",
       "  array([0.05106556, 0.12737044, 0.06891031, 0.07733952, 0.13986466,\n",
       "         0.13435923, 0.13847673, 0.08562835, 0.0739808 , 0.10300438]),\n",
       "  array([0.17500356, 0.14970197, 0.16070594, 0.10496789, 0.04444137,\n",
       "         0.07050358, 0.13927727, 0.08713472, 0.05078752, 0.01747618]),\n",
       "  array([0.10252566, 0.07568379, 0.12081081, 0.14818207, 0.03783659,\n",
       "         0.00918791, 0.24669018, 0.04579415, 0.03035813, 0.18293071]),\n",
       "  array([0.02455984, 0.11003039, 0.09144332, 0.13336293, 0.15746069,\n",
       "         0.08635246, 0.03247298, 0.0503023 , 0.17156722, 0.14244786]),\n",
       "  array([0.02087772, 0.10199256, 0.0105466 , 0.16298397, 0.08906969,\n",
       "         0.04656989, 0.10857331, 0.17578513, 0.14411942, 0.13948171]),\n",
       "  array([0.11850645, 0.08325517, 0.00345631, 0.13008174, 0.10290716,\n",
       "         0.15039367, 0.09140268, 0.15063998, 0.04820154, 0.1211553 ]),\n",
       "  array([0.15151878, 0.00845966, 0.03998507, 0.14960294, 0.15341791,\n",
       "         0.11327603, 0.13684165, 0.05214459, 0.15401494, 0.04073842]),\n",
       "  array([0.03420105, 0.13066791, 0.14178494, 0.10081514, 0.08181786,\n",
       "         0.10472703, 0.04489204, 0.10886909, 0.11973267, 0.13249226]),\n",
       "  array([0.1863143 , 0.13190854, 0.02868871, 0.06540303, 0.01162474,\n",
       "         0.07592517, 0.07280766, 0.16189398, 0.19016541, 0.07526846]),\n",
       "  array([0.04695616, 0.17811269, 0.17098283, 0.11358864, 0.13412935,\n",
       "         0.02212626, 0.06144956, 0.05351704, 0.14269884, 0.07643862]),\n",
       "  array([0.1625342 , 0.106257  , 0.18136693, 0.00077982, 0.11864125,\n",
       "         0.06598928, 0.06254226, 0.015154  , 0.18313499, 0.10360026]),\n",
       "  array([0.15905804, 0.12139168, 0.05191052, 0.05326783, 0.0474552 ,\n",
       "         0.14518603, 0.02246966, 0.14066276, 0.18727391, 0.07132435]),\n",
       "  array([0.02150949, 0.2063089 , 0.17015926, 0.12940253, 0.17834528,\n",
       "         0.11687494, 0.03858264, 0.01341489, 0.00991421, 0.11548784]),\n",
       "  array([0.04782614, 0.12162136, 0.17336049, 0.14764397, 0.1306823 ,\n",
       "         0.07171024, 0.10163631, 0.05876093, 0.1060846 , 0.04067365]),\n",
       "  array([0.13652458, 0.13134221, 0.13679007, 0.09184675, 0.00123632,\n",
       "         0.05832726, 0.15209043, 0.06541303, 0.14528238, 0.08114696]),\n",
       "  array([0.01459084, 0.00180247, 0.05696077, 0.05682759, 0.31469564,\n",
       "         0.12463256, 0.01988789, 0.01671632, 0.2327772 , 0.16110872]),\n",
       "  array([0.05382613, 0.07237621, 0.11691496, 0.07297636, 0.02840685,\n",
       "         0.08634634, 0.16486351, 0.08984217, 0.20102934, 0.11341813]),\n",
       "  array([0.0895725 , 0.15549869, 0.10880281, 0.13693477, 0.07917307,\n",
       "         0.07598481, 0.00291618, 0.07756789, 0.14409978, 0.12944949]),\n",
       "  array([0.14218206, 0.10333804, 0.04330673, 0.06877161, 0.15336173,\n",
       "         0.14962541, 0.01543126, 0.11280278, 0.07011891, 0.14106147]),\n",
       "  array([0.11578959, 0.18811032, 0.04703016, 0.12126788, 0.16783616,\n",
       "         0.18000359, 0.06235596, 0.03278251, 0.02468804, 0.06013579]),\n",
       "  array([0.12813885, 0.04850466, 0.14747789, 0.02091581, 0.08888521,\n",
       "         0.0185626 , 0.20428491, 0.09357601, 0.20857684, 0.04107722]),\n",
       "  array([0.05718849, 0.02644163, 0.21242438, 0.05392378, 0.15452648,\n",
       "         0.04365977, 0.05938435, 0.1176523 , 0.02980806, 0.24499075]),\n",
       "  array([0.12116687, 0.11559723, 0.1352679 , 0.12648305, 0.08606304,\n",
       "         0.10542948, 0.07552478, 0.11261875, 0.00916063, 0.11268826]),\n",
       "  array([0.0036786 , 0.2075205 , 0.01010309, 0.11580937, 0.10328017,\n",
       "         0.09517112, 0.0396123 , 0.17003204, 0.15190494, 0.10288786]),\n",
       "  array([0.12198129, 0.14982138, 0.11149573, 0.01805089, 0.11593206,\n",
       "         0.13652423, 0.12340816, 0.04889279, 0.03562425, 0.13826923]),\n",
       "  array([0.02373352, 0.11389983, 0.06659726, 0.09496059, 0.25595589,\n",
       "         0.00416831, 0.07042681, 0.04368379, 0.05541242, 0.27116157]),\n",
       "  array([0.05710744, 0.1014688 , 0.00639918, 0.0718269 , 0.17859752,\n",
       "         0.09617081, 0.19588751, 0.00457457, 0.14970521, 0.13826206]),\n",
       "  array([0.11802903, 0.12680325, 0.01987486, 0.03150521, 0.20554933,\n",
       "         0.08387024, 0.09204918, 0.0280074 , 0.20146673, 0.09284477]),\n",
       "  array([0.0083039 , 0.16942586, 0.16993805, 0.00202527, 0.14235156,\n",
       "         0.07617937, 0.03372533, 0.11281785, 0.11009392, 0.17513889]),\n",
       "  array([0.00797768, 0.14235806, 0.14625144, 0.08181777, 0.03729263,\n",
       "         0.16320562, 0.01901375, 0.06990579, 0.15719226, 0.17498501]),\n",
       "  array([0.16768628, 0.07887068, 0.00085257, 0.14089635, 0.14301075,\n",
       "         0.08049697, 0.01694838, 0.18026823, 0.10007517, 0.09089463]),\n",
       "  array([0.08006728, 0.10997024, 0.04021349, 0.12277965, 0.14645991,\n",
       "         0.08712283, 0.08792812, 0.11016306, 0.10747142, 0.107824  ]),\n",
       "  array([0.11125523, 0.17260992, 0.03458004, 0.2158992 , 0.03600948,\n",
       "         0.05715081, 0.02020265, 0.24681434, 0.10131835, 0.00415998]),\n",
       "  array([0.03891756, 0.03001358, 0.12439857, 0.08405539, 0.0502428 ,\n",
       "         0.11822355, 0.1875972 , 0.11645744, 0.1456577 , 0.10443622]),\n",
       "  array([0.16257565, 0.01675032, 0.11573571, 0.17352652, 0.01466934,\n",
       "         0.13317594, 0.03020098, 0.05828492, 0.15029948, 0.14478113]),\n",
       "  array([0.04676553, 0.19123304, 0.08654044, 0.127008  , 0.07100279,\n",
       "         0.07398938, 0.03658429, 0.05939683, 0.2117467 , 0.095733  ]),\n",
       "  array([0.04298731, 0.10652279, 0.15695957, 0.16839659, 0.07066083,\n",
       "         0.12588318, 0.15231321, 0.07210992, 0.02541022, 0.07875639]),\n",
       "  array([0.11946994, 0.02964859, 0.13642517, 0.03809785, 0.10822246,\n",
       "         0.17983314, 0.06832511, 0.10477567, 0.19191899, 0.02328307]),\n",
       "  array([0.15230598, 0.1188822 , 0.1214838 , 0.04871954, 0.1566807 ,\n",
       "         0.0575269 , 0.01393857, 0.16337259, 0.11370398, 0.05338575]),\n",
       "  array([0.02687248, 0.13384431, 0.1491195 , 0.0470807 , 0.13767186,\n",
       "         0.08149053, 0.08421457, 0.14620022, 0.06045166, 0.13305418]),\n",
       "  array([0.02171169, 0.13574871, 0.02741611, 0.17504946, 0.05893109,\n",
       "         0.03529137, 0.17028805, 0.11716117, 0.12376836, 0.13463399]),\n",
       "  array([0.01315905, 0.24154217, 0.05512348, 0.09622432, 0.03834045,\n",
       "         0.05720636, 0.05899072, 0.13877622, 0.08726278, 0.21337444]),\n",
       "  array([0.06358043, 0.09308077, 0.12318749, 0.07449326, 0.16472039,\n",
       "         0.09270638, 0.08869161, 0.04412325, 0.15919505, 0.09622137]),\n",
       "  array([0.031663  , 0.09306438, 0.14240786, 0.03506905, 0.04127584,\n",
       "         0.14833862, 0.1516346 , 0.21416406, 0.02838335, 0.11399924]),\n",
       "  array([0.12269022, 0.11479248, 0.07486262, 0.00031465, 0.03091153,\n",
       "         0.21169459, 0.12970754, 0.03646297, 0.1319763 , 0.14658709]),\n",
       "  array([0.16442938, 0.11013144, 0.13437632, 0.05013511, 0.06048303,\n",
       "         0.12226722, 0.09752332, 0.00712099, 0.14093013, 0.11260306]),\n",
       "  array([0.08625208, 0.15684694, 0.08114835, 0.12216334, 0.03512157,\n",
       "         0.20412129, 0.19765643, 0.01239447, 0.01195709, 0.09233845]),\n",
       "  array([0.03974053, 0.13309554, 0.09964101, 0.12941294, 0.11421908,\n",
       "         0.16559796, 0.12833218, 0.03706334, 0.03064971, 0.12224773]),\n",
       "  array([0.06736207, 0.12837422, 0.0618158 , 0.15753623, 0.14642668,\n",
       "         0.15361791, 0.1484987 , 0.07379193, 0.00972948, 0.05284699]),\n",
       "  array([0.02545152, 0.05759512, 0.07493748, 0.04161154, 0.01162916,\n",
       "         0.08240911, 0.15008984, 0.08512286, 0.22579766, 0.24535571]),\n",
       "  array([0.08562999, 0.12086252, 0.07895278, 0.0914156 , 0.18012756,\n",
       "         0.06728297, 0.0375951 , 0.17249856, 0.00031168, 0.16532325]),\n",
       "  array([0.08255214, 0.13689212, 0.13013976, 0.06727363, 0.10228707,\n",
       "         0.06374795, 0.14619274, 0.06451374, 0.07728993, 0.12911091]),\n",
       "  array([0.0954492 , 0.1261211 , 0.07295809, 0.07886687, 0.09358311,\n",
       "         0.05012614, 0.17657965, 0.06201163, 0.19027953, 0.0540247 ]),\n",
       "  array([0.10154943, 0.02377506, 0.06434317, 0.17512783, 0.0181586 ,\n",
       "         0.15608884, 0.14154722, 0.02040924, 0.13667707, 0.16232354]),\n",
       "  array([0.07301964, 0.09627589, 0.0190067 , 0.18325376, 0.138785  ,\n",
       "         0.05618597, 0.00749727, 0.17757762, 0.18283081, 0.06556733]),\n",
       "  array([0.15980949, 0.12150848, 0.02282734, 0.04594403, 0.08883498,\n",
       "         0.17387187, 0.17492912, 0.02860411, 0.00976803, 0.17390256]),\n",
       "  array([0.07865952, 0.02852931, 0.03145642, 0.1180794 , 0.13215211,\n",
       "         0.15445181, 0.15034464, 0.08774782, 0.15642603, 0.06215292]),\n",
       "  array([0.02192763, 0.02483466, 0.06944766, 0.23632561, 0.12563552,\n",
       "         0.00083705, 0.02403265, 0.21010762, 0.08180548, 0.20504613]),\n",
       "  array([0.11988095, 0.14730801, 0.05110711, 0.15997913, 0.02705575,\n",
       "         0.0971952 , 0.06374747, 0.1477642 , 0.0675792 , 0.11838299]),\n",
       "  array([0.07291513, 0.12659472, 0.1460144 , 0.11716155, 0.12099157,\n",
       "         0.03527306, 0.01801459, 0.13004185, 0.12239008, 0.11060304]),\n",
       "  array([0.00432611, 0.07451161, 0.13753003, 0.02672681, 0.19732914,\n",
       "         0.05393341, 0.16727477, 0.12585415, 0.08038301, 0.13213095]),\n",
       "  array([0.02345037, 0.16265037, 0.01197723, 0.17699609, 0.24297791,\n",
       "         0.09243292, 0.01385701, 0.03492927, 0.05940433, 0.1813245 ]),\n",
       "  array([0.11774716, 0.15425397, 0.1173127 , 0.11964395, 0.11786119,\n",
       "         0.06824891, 0.0530701 , 0.03984541, 0.03792419, 0.17409241]),\n",
       "  array([0.12918818, 0.12041872, 0.02264049, 0.17680391, 0.13294199,\n",
       "         0.02881087, 0.10093133, 0.06064027, 0.03554478, 0.19207947]),\n",
       "  array([0.06150667, 0.10580111, 0.01118347, 0.04911803, 0.01153548,\n",
       "         0.21727199, 0.15144084, 0.21726444, 0.09126349, 0.08361448]),\n",
       "  array([0.16770435, 0.14238374, 0.12509444, 0.15328148, 0.03289472,\n",
       "         0.10985748, 0.02010351, 0.0230029 , 0.03294542, 0.19273196]),\n",
       "  array([0.2210285 , 0.03148538, 0.0560105 , 0.03331152, 0.03163628,\n",
       "         0.07777741, 0.09203584, 0.09997941, 0.18941965, 0.16731551]),\n",
       "  array([0.02972785, 0.14333751, 0.08620537, 0.05569734, 0.03863221,\n",
       "         0.09388421, 0.15019613, 0.14640243, 0.15166507, 0.10425188]),\n",
       "  array([0.13422181, 0.11193928, 0.13603988, 0.13527821, 0.15829748,\n",
       "         0.07231129, 0.02281631, 0.0394937 , 0.08056166, 0.10904038]),\n",
       "  array([0.16316754, 0.07902003, 0.03144362, 0.15199932, 0.02967975,\n",
       "         0.10209077, 0.11524918, 0.0894274 , 0.1544578 , 0.08346458]),\n",
       "  array([0.0327382 , 0.03261033, 0.17912572, 0.17550991, 0.13944327,\n",
       "         0.07677321, 0.14393127, 0.00098274, 0.1772649 , 0.04162046]),\n",
       "  array([0.15686458, 0.08974136, 0.1337037 , 0.13060043, 0.092856  ,\n",
       "         0.12727723, 0.1489765 , 0.05430186, 0.04356446, 0.02211386]),\n",
       "  array([0.14976408, 0.15986365, 0.00130891, 0.00580224, 0.10852371,\n",
       "         0.02174632, 0.17472349, 0.12587916, 0.13803356, 0.11435489]),\n",
       "  array([0.14886192, 0.09089426, 0.06925289, 0.08908822, 0.0123724 ,\n",
       "         0.11587316, 0.15549278, 0.19497209, 0.10846426, 0.01472802]),\n",
       "  array([0.13500706, 0.07309883, 0.01661718, 0.07367351, 0.11701153,\n",
       "         0.05493727, 0.06422572, 0.11866546, 0.17792228, 0.16884117]),\n",
       "  array([0.13603451, 0.11434884, 0.15635709, 0.08120988, 0.1169551 ,\n",
       "         0.04014658, 0.10570546, 0.03144245, 0.03855965, 0.17924043]),\n",
       "  array([0.194648  , 0.06163447, 0.13451973, 0.1353767 , 0.01431034,\n",
       "         0.00561131, 0.02847146, 0.17010769, 0.20194032, 0.05337997]),\n",
       "  array([0.14302516, 0.14926751, 0.06436185, 0.14890403, 0.14372096,\n",
       "         0.02563941, 0.02101505, 0.1491311 , 0.06343541, 0.09149953]),\n",
       "  array([0.12102602, 0.09634352, 0.10474121, 0.07191375, 0.16276698,\n",
       "         0.13975906, 0.02701149, 0.1311356 , 0.06910906, 0.07619332]),\n",
       "  array([0.0412481 , 0.06090987, 0.00073717, 0.0366744 , 0.19721812,\n",
       "         0.26260669, 0.02797052, 0.14081933, 0.21554946, 0.01626635]),\n",
       "  array([0.13105029, 0.14652794, 0.05193048, 0.08564619, 0.09277171,\n",
       "         0.12547332, 0.09785615, 0.11734372, 0.04209629, 0.10930391]),\n",
       "  array([0.17259185, 0.13991659, 0.14539393, 0.00903463, 0.21438971,\n",
       "         0.09242831, 0.05581375, 0.014015  , 0.15505708, 0.00135914]),\n",
       "  array([0.12034466, 0.15307276, 0.13967009, 0.09043006, 0.13393748,\n",
       "         0.06904623, 0.02177725, 0.11295174, 0.03925399, 0.11951574]),\n",
       "  array([0.00875515, 0.08506162, 0.13185544, 0.14300447, 0.09330482,\n",
       "         0.10860978, 0.06878886, 0.15289398, 0.11135369, 0.0963722 ]),\n",
       "  array([0.10702418, 0.01495511, 0.11819056, 0.1185342 , 0.13603588,\n",
       "         0.16434905, 0.08673586, 0.14334759, 0.08538496, 0.0254426 ]),\n",
       "  array([0.04272432, 0.10079204, 0.17684295, 0.08891434, 0.00130989,\n",
       "         0.13522425, 0.13997412, 0.19794624, 0.08334878, 0.03292307]),\n",
       "  array([0.13643479, 0.08660927, 0.16461236, 0.11161221, 0.09110537,\n",
       "         0.1156244 , 0.09208815, 0.13443414, 0.02687761, 0.04060171]),\n",
       "  array([0.12917855, 0.03362799, 0.04562158, 0.16086322, 0.11212232,\n",
       "         0.02387962, 0.09632589, 0.10808984, 0.15756465, 0.13272635]),\n",
       "  array([0.08616327, 0.1827834 , 0.10800946, 0.05826288, 0.08834898,\n",
       "         0.10343419, 0.19474379, 0.00097208, 0.05642347, 0.12085848]),\n",
       "  array([0.0653932 , 0.05641442, 0.08067199, 0.1459556 , 0.11406746,\n",
       "         0.090856  , 0.1378822 , 0.16979247, 0.1269526 , 0.01201406]),\n",
       "  array([0.052726  , 0.14739269, 0.08736166, 0.03682992, 0.10363168,\n",
       "         0.15372009, 0.10493724, 0.1180815 , 0.14061967, 0.05469955]),\n",
       "  array([0.16650514, 0.04782274, 0.17744635, 0.07992662, 0.15536406,\n",
       "         0.02999173, 0.08177894, 0.14367669, 0.10245062, 0.0150371 ]),\n",
       "  array([1.85596658e-01, 1.27020466e-01, 7.75496723e-02, 1.69322902e-01,\n",
       "         1.17697257e-01, 1.19986299e-04, 5.86872745e-02, 1.16666814e-01,\n",
       "         1.41684867e-01, 5.65410138e-03]),\n",
       "  array([0.02697788, 0.0238142 , 0.16818182, 0.17022405, 0.22552242,\n",
       "         0.06751446, 0.04775263, 0.11959265, 0.07196232, 0.07845757]),\n",
       "  array([0.04151268, 0.12685483, 0.1168773 , 0.06447485, 0.1295816 ,\n",
       "         0.19411709, 0.12040356, 0.07656265, 0.05363619, 0.07597925]),\n",
       "  array([0.15356545, 0.00109892, 0.12748706, 0.10193002, 0.06852534,\n",
       "         0.12001292, 0.17912687, 0.00961761, 0.15679931, 0.0818365 ]),\n",
       "  array([0.18022559, 0.12647873, 0.10799758, 0.14916716, 0.1327458 ,\n",
       "         0.18328148, 0.01754535, 0.05796479, 0.00310419, 0.04148934]),\n",
       "  array([0.11263636, 0.10271121, 0.11129871, 0.01971904, 0.03419286,\n",
       "         0.11412672, 0.1724811 , 0.11493425, 0.14044295, 0.07745679]),\n",
       "  array([0.00240174, 0.22696985, 0.0096639 , 0.10609825, 0.04705721,\n",
       "         0.13787189, 0.07450147, 0.14661249, 0.18885271, 0.0599705 ]),\n",
       "  array([0.09112032, 0.11713359, 0.05990104, 0.02888921, 0.23659835,\n",
       "         0.07419455, 0.06920574, 0.21049309, 0.07263197, 0.03983216]),\n",
       "  array([0.13405695, 0.04563055, 0.00372691, 0.19169859, 0.11310469,\n",
       "         0.0115525 , 0.02653399, 0.11407726, 0.14979353, 0.20982502]),\n",
       "  array([0.09805338, 0.00843172, 0.25913485, 0.14419966, 0.00660712,\n",
       "         0.11347163, 0.21709348, 0.00838216, 0.03056895, 0.11405704]),\n",
       "  array([0.14006515, 0.12710756, 0.14239747, 0.16140423, 0.00863155,\n",
       "         0.06005839, 0.02481471, 0.03114733, 0.14961958, 0.15475403]),\n",
       "  array([0.13097472, 0.08094772, 0.14921643, 0.14939189, 0.13336308,\n",
       "         0.12574614, 0.02893277, 0.08488601, 0.08221052, 0.03433071]),\n",
       "  array([0.13240002, 0.08376211, 0.10534376, 0.00741821, 0.13253186,\n",
       "         0.0608418 , 0.1451602 , 0.12450245, 0.10283464, 0.10520495]),\n",
       "  array([0.10779793, 0.14937937, 0.05382914, 0.16590352, 0.03206401,\n",
       "         0.06765899, 0.02524332, 0.14667273, 0.15427261, 0.09717836]),\n",
       "  array([0.06568511, 0.11295981, 0.14938509, 0.06006473, 0.13638372,\n",
       "         0.07169518, 0.07405756, 0.14764363, 0.07786203, 0.10426314]),\n",
       "  array([0.1768465 , 0.00663298, 0.11547475, 0.05056932, 0.13551658,\n",
       "         0.12205008, 0.01749376, 0.08564551, 0.17858646, 0.11118406]),\n",
       "  array([0.16005344, 0.0926175 , 0.08001215, 0.12338052, 0.14109766,\n",
       "         0.059569  , 0.1678896 , 0.00952066, 0.12507087, 0.04078861]),\n",
       "  array([0.11017411, 0.07925423, 0.17845963, 0.12135217, 0.05823008,\n",
       "         0.11966573, 0.09065806, 0.02660483, 0.1219941 , 0.09360705]),\n",
       "  array([0.12681708, 0.12298607, 0.1352462 , 0.03501002, 0.02284067,\n",
       "         0.08336154, 0.1495115 , 0.09153662, 0.16806459, 0.06462571]),\n",
       "  array([0.26811737, 0.00057058, 0.01472741, 0.0608871 , 0.11936427,\n",
       "         0.02031036, 0.27239297, 0.09103215, 0.02802368, 0.1245741 ]),\n",
       "  array([0.10915019, 0.13195931, 0.07781219, 0.08043466, 0.15652397,\n",
       "         0.10082601, 0.0767292 , 0.08928774, 0.09730608, 0.07997065]),\n",
       "  array([0.06657107, 0.09698371, 0.24839183, 0.09855828, 0.21291411,\n",
       "         0.00250398, 0.00509475, 0.11638313, 0.06653203, 0.08606711]),\n",
       "  array([0.04721415, 0.03919494, 0.16584411, 0.01173243, 0.15227784,\n",
       "         0.14933074, 0.14925749, 0.14854819, 0.11977588, 0.01682422]),\n",
       "  array([0.0557399 , 0.16033797, 0.120806  , 0.15274625, 0.1156098 ,\n",
       "         0.01765283, 0.08564269, 0.11145864, 0.14133061, 0.03867531]),\n",
       "  array([0.08765706, 0.0651097 , 0.08611232, 0.00941362, 0.10427456,\n",
       "         0.13509719, 0.15032011, 0.16559898, 0.02208483, 0.17433165]),\n",
       "  array([0.14362765, 0.12486579, 0.01899582, 0.08904943, 0.03082058,\n",
       "         0.05095823, 0.13921712, 0.1493964 , 0.12648727, 0.12658172]),\n",
       "  array([0.03074717, 0.02127903, 0.12660707, 0.1532818 , 0.09251529,\n",
       "         0.01626677, 0.12897316, 0.14300171, 0.17833915, 0.10898884]),\n",
       "  array([0.06867012, 0.14601149, 0.07421858, 0.06728866, 0.06158078,\n",
       "         0.17457115, 0.19382524, 0.09015587, 0.06017971, 0.0634984 ]),\n",
       "  array([0.17836982, 0.08657965, 0.0934966 , 0.02550429, 0.1364209 ,\n",
       "         0.04737176, 0.0320668 , 0.2207144 , 0.05770738, 0.12176841]),\n",
       "  array([0.01953394, 0.14853824, 0.01329529, 0.14226757, 0.112177  ,\n",
       "         0.17112341, 0.0863861 , 0.05102929, 0.11522666, 0.1404225 ]),\n",
       "  array([0.09314916, 0.16647958, 0.10285567, 0.11777296, 0.02450222,\n",
       "         0.08692752, 0.08756761, 0.1695439 , 0.12236996, 0.02883142]),\n",
       "  array([0.16589846, 0.16301456, 0.04064587, 0.02514389, 0.06406549,\n",
       "         0.16371406, 0.1540346 , 0.13127501, 0.04608009, 0.04612797]),\n",
       "  array([0.09808916, 0.14648037, 0.01153589, 0.1495497 , 0.13036468,\n",
       "         0.15117961, 0.03243799, 0.00299316, 0.1393232 , 0.13804622]),\n",
       "  array([0.20978909, 0.00534032, 0.11656019, 0.10792953, 0.03846039,\n",
       "         0.17872053, 0.10029026, 0.09798841, 0.05189433, 0.09302696]),\n",
       "  array([0.09866236, 0.13720549, 0.13447524, 0.06518251, 0.04995547,\n",
       "         0.0925219 , 0.05731472, 0.10386456, 0.11657067, 0.14424708]),\n",
       "  array([0.10119807, 0.12238699, 0.10181688, 0.12135201, 0.07135674,\n",
       "         0.01926602, 0.15766034, 0.14089074, 0.15601742, 0.0080548 ]),\n",
       "  array([0.02653207, 0.02247631, 0.06927504, 0.03470707, 0.16941069,\n",
       "         0.07101951, 0.11672547, 0.19672369, 0.09308943, 0.20004073]),\n",
       "  array([0.13589103, 0.01905373, 0.08357328, 0.04332725, 0.12906941,\n",
       "         0.12789532, 0.12783788, 0.1254241 , 0.10549939, 0.10242862]),\n",
       "  array([0.108713  , 0.02091841, 0.14824969, 0.02835369, 0.23403176,\n",
       "         0.01867542, 0.21506834, 0.11487991, 0.09318957, 0.0179202 ]),\n",
       "  array([0.17590536, 0.13055367, 0.03044451, 0.17900103, 0.04384017,\n",
       "         0.07832981, 0.1047654 , 0.15269846, 0.05697097, 0.04749063]),\n",
       "  array([0.04694279, 0.06337922, 0.06345942, 0.15340318, 0.09496586,\n",
       "         0.09709896, 0.09675785, 0.14172732, 0.15400179, 0.08826362]),\n",
       "  array([0.03284553, 0.13521131, 0.06176697, 0.09241851, 0.13905579,\n",
       "         0.10138528, 0.08221446, 0.07443946, 0.13923715, 0.14142555]),\n",
       "  array([0.012366  , 0.09558033, 0.03724678, 0.01304671, 0.12755311,\n",
       "         0.21177484, 0.08601656, 0.20044262, 0.05513681, 0.16083624]),\n",
       "  array([0.15736783, 0.00903244, 0.16199988, 0.16430658, 0.07218711,\n",
       "         0.11327022, 0.10655198, 0.13203031, 0.06308501, 0.02016866]),\n",
       "  array([0.01961602, 0.23608662, 0.09554636, 0.03851027, 0.1581038 ,\n",
       "         0.05423786, 0.17767131, 0.05274312, 0.13600106, 0.03148357]),\n",
       "  array([0.1441953 , 0.1470023 , 0.14044004, 0.02042994, 0.09119428,\n",
       "         0.08066119, 0.13783778, 0.08961853, 0.12105525, 0.0275654 ]),\n",
       "  array([0.08846622, 0.06854097, 0.12942173, 0.19514061, 0.18070605,\n",
       "         0.09834463, 0.03709627, 0.02452953, 0.1609682 , 0.01678581]),\n",
       "  array([0.10266803, 0.0412561 , 0.1476881 , 0.1389152 , 0.11412586,\n",
       "         0.07990301, 0.04461929, 0.08968906, 0.12341016, 0.11772517]),\n",
       "  array([0.0043257 , 0.16021713, 0.01508122, 0.0287315 , 0.19370569,\n",
       "         0.18281027, 0.09852831, 0.01146745, 0.12331688, 0.18181586]),\n",
       "  array([0.03851026, 0.10586435, 0.05784259, 0.09401379, 0.14034467,\n",
       "         0.13925708, 0.19938597, 0.08840622, 0.10873634, 0.02763874]),\n",
       "  array([0.18004698, 0.06209502, 0.03748744, 0.18440799, 0.07623159,\n",
       "         0.07016421, 0.01215875, 0.13563891, 0.07333333, 0.16843577]),\n",
       "  array([0.07446134, 0.07860808, 0.04639687, 0.2020029 , 0.01829315,\n",
       "         0.20367059, 0.15434928, 0.03343448, 0.02588941, 0.16289391]),\n",
       "  array([0.09269002, 0.05769219, 0.07792602, 0.06760805, 0.11586168,\n",
       "         0.04916236, 0.12710302, 0.19213042, 0.13182365, 0.08800259]),\n",
       "  array([0.09515004, 0.13983753, 0.14780997, 0.06777344, 0.00083961,\n",
       "         0.10654123, 0.11344767, 0.09596856, 0.07648838, 0.15614356]),\n",
       "  array([0.07102878, 0.12793378, 0.05959127, 0.11254311, 0.1253724 ,\n",
       "         0.05600785, 0.03212806, 0.13168438, 0.15263004, 0.13108033]),\n",
       "  array([0.06451706, 0.13620797, 0.0357021 , 0.13235209, 0.03855635,\n",
       "         0.05325578, 0.16067795, 0.17011391, 0.03131079, 0.17730599]),\n",
       "  array([0.16748027, 0.00027871, 0.17367114, 0.20469174, 0.1775109 ,\n",
       "         0.06144117, 0.06758742, 0.07942806, 0.04223837, 0.02567222]),\n",
       "  array([0.00072511, 0.11227694, 0.06119232, 0.16990757, 0.16359832,\n",
       "         0.06675401, 0.09599276, 0.09332857, 0.0495862 , 0.18663821]),\n",
       "  array([0.07590036, 0.12220786, 0.15527246, 0.07664695, 0.13746094,\n",
       "         0.10531869, 0.09233271, 0.11504389, 0.10185876, 0.01795739]),\n",
       "  array([0.05867485, 0.17419223, 0.10865772, 0.16153785, 0.08278927,\n",
       "         0.0991263 , 0.11905872, 0.06539457, 0.01868498, 0.11188353]),\n",
       "  array([0.11984792, 0.03206069, 0.05818926, 0.13320835, 0.00863787,\n",
       "         0.03951439, 0.13593415, 0.11301925, 0.17730988, 0.18227822]),\n",
       "  array([0.02225898, 0.12739017, 0.16228091, 0.05170721, 0.03569738,\n",
       "         0.18043637, 0.16829079, 0.07930581, 0.05122383, 0.12140854]),\n",
       "  array([0.04785   , 0.17288757, 0.08321826, 0.08477615, 0.02608189,\n",
       "         0.1951501 , 0.07425409, 0.04708991, 0.18237834, 0.08631369]),\n",
       "  array([0.00945668, 0.02758478, 0.03741334, 0.0830135 , 0.2361525 ,\n",
       "         0.22672594, 0.06379292, 0.23024579, 0.04958554, 0.036029  ]),\n",
       "  array([0.09996738, 0.17216968, 0.14952084, 0.08711245, 0.14483366,\n",
       "         0.04268266, 0.07542087, 0.14309256, 0.0834947 , 0.00170519]),\n",
       "  array([0.11779466, 0.04205185, 0.00633611, 0.00788259, 0.13409777,\n",
       "         0.19021843, 0.2101886 , 0.15053759, 0.13244738, 0.00844502]),\n",
       "  array([0.13877549, 0.12891823, 0.08971818, 0.07960678, 0.04690812,\n",
       "         0.08875416, 0.14996354, 0.08281123, 0.02826616, 0.16627811]),\n",
       "  array([0.13263028, 0.10071139, 0.12451581, 0.13879645, 0.00657565,\n",
       "         0.1576529 , 0.07287459, 0.0610171 , 0.08461563, 0.12061021]),\n",
       "  array([0.16939367, 0.00786998, 0.03210474, 0.18151573, 0.08571058,\n",
       "         0.08939533, 0.03167134, 0.13680278, 0.19707376, 0.0684621 ]),\n",
       "  array([0.05332517, 0.0483339 , 0.23046664, 0.15355633, 0.05869239,\n",
       "         0.00050354, 0.02288127, 0.21519931, 0.04339687, 0.17364456]),\n",
       "  array([0.15855453, 0.14742634, 0.00916306, 0.01998384, 0.0992371 ,\n",
       "         0.14595559, 0.15026717, 0.02941661, 0.12241998, 0.1175758 ]),\n",
       "  array([0.14760241, 0.10478724, 0.03968077, 0.03942704, 0.03644311,\n",
       "         0.15933929, 0.146088  , 0.11655077, 0.07535858, 0.13472277]),\n",
       "  array([0.1720983 , 0.14660915, 0.07646751, 0.06798177, 0.06994537,\n",
       "         0.08965343, 0.10583804, 0.14959393, 0.00739844, 0.11441407]),\n",
       "  array([0.04861707, 0.14915627, 0.12876159, 0.14869672, 0.1377002 ,\n",
       "         0.07751347, 0.14899741, 0.00065037, 0.12951189, 0.03039501]),\n",
       "  array([0.10261299, 0.08196956, 0.14552229, 0.16307852, 0.12527102,\n",
       "         0.06384585, 0.03560862, 0.05192768, 0.10879998, 0.12136349]),\n",
       "  array([0.05814095, 0.06880822, 0.06046943, 0.10348595, 0.12262088,\n",
       "         0.01127901, 0.1506841 , 0.1394063 , 0.14662435, 0.13848081]),\n",
       "  array([0.00190449, 0.03352779, 0.13976869, 0.1042498 , 0.17054148,\n",
       "         0.06428302, 0.09692132, 0.1368223 , 0.17088888, 0.08109224]),\n",
       "  array([0.08099011, 0.16738772, 0.12506203, 0.11026616, 0.00510331,\n",
       "         0.186503  , 0.14885364, 0.06929691, 0.09542718, 0.01110995]),\n",
       "  array([0.05116488, 0.07041539, 0.01256595, 0.15168809, 0.17574585,\n",
       "         0.08415341, 0.10738783, 0.1711898 , 0.02532165, 0.15036716]),\n",
       "  array([0.15069412, 0.02150294, 0.06907992, 0.09264134, 0.13549015,\n",
       "         0.16171994, 0.16620844, 0.12102857, 0.05140734, 0.03022725]),\n",
       "  array([0.0572091 , 0.05165454, 0.15571193, 0.11543534, 0.00054173,\n",
       "         0.12546192, 0.16609626, 0.13051289, 0.00912377, 0.18825252]),\n",
       "  array([0.11019626, 0.0483409 , 0.08331084, 0.04179279, 0.08269098,\n",
       "         0.14916098, 0.12617845, 0.04111927, 0.15130334, 0.16590619]),\n",
       "  array([0.02550929, 0.10038764, 0.0401471 , 0.1332928 , 0.20145694,\n",
       "         0.1537368 , 0.13762315, 0.02630882, 0.05544833, 0.12608914]),\n",
       "  array([0.10611541, 0.12618945, 0.04802655, 0.18410007, 0.06251604,\n",
       "         0.13762059, 0.02049595, 0.13318413, 0.13450597, 0.04724584]),\n",
       "  array([0.06310957, 0.1489196 , 0.17957457, 0.03039005, 0.18930426,\n",
       "         0.00796478, 0.01396096, 0.17734444, 0.05520166, 0.13423012]),\n",
       "  array([0.15878464, 0.13111349, 0.14194092, 0.11139344, 0.06265254,\n",
       "         0.12514207, 0.10757558, 0.05162647, 0.0655746 , 0.04419625]),\n",
       "  array([0.01492359, 0.22269444, 0.06437414, 0.00450226, 0.1562964 ,\n",
       "         0.02012302, 0.12399553, 0.07460943, 0.1910898 , 0.12739139]),\n",
       "  array([0.10917572, 0.11979875, 0.10414705, 0.00118056, 0.0838051 ,\n",
       "         0.17795668, 0.08853907, 0.03382751, 0.09186481, 0.18970475]),\n",
       "  array([0.11851658, 0.06167496, 0.17684111, 0.09493006, 0.01371953,\n",
       "         0.08063755, 0.15907405, 0.07076601, 0.13730107, 0.08653909]),\n",
       "  array([0.17181201, 0.08222616, 0.01830653, 0.12669051, 0.15860902,\n",
       "         0.04614031, 0.03665283, 0.05987498, 0.14876203, 0.15092562]),\n",
       "  array([0.09988311, 0.02683735, 0.157987  , 0.15831118, 0.07202471,\n",
       "         0.1690015 , 0.00294284, 0.01742799, 0.1347342 , 0.16085012]),\n",
       "  array([0.05352137, 0.04174275, 0.1164531 , 0.0130522 , 0.15424692,\n",
       "         0.12702745, 0.0372104 , 0.18603298, 0.06048225, 0.21023059]),\n",
       "  array([0.16018899, 0.11967422, 0.12152447, 0.08970285, 0.13503032,\n",
       "         0.00470364, 0.06635195, 0.14732369, 0.13560789, 0.01989198]),\n",
       "  array([0.06100824, 0.16467513, 0.15643805, 0.14962008, 0.02746443,\n",
       "         0.17048426, 0.04363342, 0.04606328, 0.06263185, 0.11798125]),\n",
       "  array([0.14970176, 0.02284238, 0.1047321 , 0.15806384, 0.10845174,\n",
       "         0.07807976, 0.15185304, 0.04021928, 0.1031823 , 0.0828738 ]),\n",
       "  array([0.07055968, 0.18144794, 0.0142027 , 0.11624805, 0.16694649,\n",
       "         0.01851688, 0.12902537, 0.11493024, 0.17628237, 0.01184029]),\n",
       "  array([0.10153814, 0.14172703, 0.11280339, 0.13785428, 0.07178485,\n",
       "         0.09336556, 0.08101989, 0.0359682 , 0.12620341, 0.09773526]),\n",
       "  array([0.11951468, 0.02377563, 0.06703616, 0.09967956, 0.15464199,\n",
       "         0.11500945, 0.0825427 , 0.09311733, 0.11768529, 0.12699722]),\n",
       "  array([0.1302458 , 0.12125716, 0.13958975, 0.06084945, 0.15706707,\n",
       "         0.03814511, 0.02704957, 0.15054165, 0.15908764, 0.01616678]),\n",
       "  array([0.01016341, 0.18472532, 0.14275778, 0.19038985, 0.05560193,\n",
       "         0.0231901 , 0.12252606, 0.13466181, 0.07008443, 0.06589931]),\n",
       "  array([0.13268046, 0.04329164, 0.16508616, 0.12575261, 0.00784201,\n",
       "         0.09202934, 0.0124523 , 0.12417723, 0.11816806, 0.17852018]),\n",
       "  array([0.08403582, 0.11185646, 0.17289154, 0.21329972, 0.17057596,\n",
       "         0.02222087, 0.03740153, 0.04332007, 0.10112721, 0.04327082]),\n",
       "  array([0.05469775, 0.17150574, 0.10660193, 0.12611202, 0.11309028,\n",
       "         0.18265733, 0.03065629, 0.17564352, 0.00839726, 0.03063788]),\n",
       "  array([0.02688618, 0.16156212, 0.02022567, 0.13667385, 0.16901796,\n",
       "         0.07996448, 0.15963992, 0.11406388, 0.05921288, 0.07275307]),\n",
       "  array([0.13117433, 0.1868302 , 0.04253271, 0.11040184, 0.09193924,\n",
       "         0.04428424, 0.01103139, 0.16084021, 0.09853929, 0.12242655]),\n",
       "  array([0.16858746, 0.08782674, 0.10314056, 0.18226526, 0.04149698,\n",
       "         0.12253642, 0.06454761, 0.01448683, 0.07076004, 0.1443521 ]),\n",
       "  array([0.14049481, 0.06601601, 0.0872951 , 0.14408734, 0.12766843,\n",
       "         0.02389943, 0.0074492 , 0.12904802, 0.08736214, 0.18667952]),\n",
       "  array([0.10304035, 0.17419457, 0.07174694, 0.09096873, 0.04921074,\n",
       "         0.06006071, 0.13312692, 0.07830219, 0.1320738 , 0.10727504]),\n",
       "  array([0.022162  , 0.14916022, 0.13859107, 0.16981202, 0.09579199,\n",
       "         0.05561186, 0.13833164, 0.17687544, 0.02067605, 0.03298771]),\n",
       "  array([0.16184878, 0.13314819, 0.11581967, 0.06580312, 0.13780611,\n",
       "         0.07433029, 0.13220429, 0.0981145 , 0.00894311, 0.07198194]),\n",
       "  array([0.00339501, 0.12991574, 0.20746604, 0.23330925, 0.09430917,\n",
       "         0.0578681 , 0.06897015, 0.08907286, 0.06958523, 0.04610846]),\n",
       "  array([0.00996998, 0.03528443, 0.05007773, 0.07501067, 0.13618795,\n",
       "         0.12193391, 0.14455421, 0.15379925, 0.06656843, 0.20661344]),\n",
       "  array([0.09159318, 0.0654302 , 0.03915715, 0.01444984, 0.08204731,\n",
       "         0.17754315, 0.17427862, 0.09643358, 0.09936011, 0.15970686]),\n",
       "  array([0.03302606, 0.09203196, 0.11806916, 0.13568109, 0.05043264,\n",
       "         0.0917273 , 0.09496588, 0.14474242, 0.01353223, 0.22579126]),\n",
       "  array([0.08869979, 0.01013704, 0.13904203, 0.13575947, 0.11802575,\n",
       "         0.14646813, 0.07817679, 0.12470354, 0.1190481 , 0.03993937]),\n",
       "  array([0.0578426 , 0.12707854, 0.12390238, 0.05439221, 0.04171137,\n",
       "         0.14929402, 0.14143728, 0.09481221, 0.07687238, 0.13265701]),\n",
       "  array([0.07220791, 0.14551907, 0.06652103, 0.07976872, 0.02217763,\n",
       "         0.12683759, 0.29451317, 0.02821456, 0.0017687 , 0.16247161]),\n",
       "  array([0.13987266, 0.1188734 , 0.17501547, 0.05321212, 0.09265512,\n",
       "         0.00877514, 0.09648751, 0.11938603, 0.10170246, 0.09402008]),\n",
       "  array([0.11767899, 0.06851958, 0.0996278 , 0.17915202, 0.16810328,\n",
       "         0.01423883, 0.14516883, 0.00773295, 0.04002106, 0.15975666]),\n",
       "  array([0.11247795, 0.1065873 , 0.11803361, 0.15099731, 0.14106758,\n",
       "         0.16624259, 0.01149986, 0.07487396, 0.01981567, 0.09840418]),\n",
       "  array([0.03858007, 0.00486608, 0.13136725, 0.16965676, 0.05911246,\n",
       "         0.17840047, 0.18828357, 0.049665  , 0.09962043, 0.08044791]),\n",
       "  array([0.09109457, 0.02100291, 0.00837125, 0.20427803, 0.03942574,\n",
       "         0.02468094, 0.17949119, 0.22662622, 0.09528986, 0.10973929]),\n",
       "  array([0.02090891, 0.0933339 , 0.12415998, 0.24877744, 0.14049776,\n",
       "         0.01068206, 0.06919001, 0.12572327, 0.1305156 , 0.03621107]),\n",
       "  array([0.12940591, 0.08602057, 0.05153345, 0.06215816, 0.16232743,\n",
       "         0.10533466, 0.04105693, 0.15738148, 0.14848184, 0.05629957]),\n",
       "  array([0.00353713, 0.05510204, 0.19941189, 0.21118111, 0.08220253,\n",
       "         0.08706307, 0.13321239, 0.03279128, 0.0354017 , 0.16009687]),\n",
       "  array([0.10858655, 0.02801187, 0.04104846, 0.05063127, 0.1708449 ,\n",
       "         0.10405821, 0.17001226, 0.06181869, 0.16404284, 0.10094495]),\n",
       "  array([0.09775578, 0.06111842, 0.06758083, 0.14396823, 0.04319761,\n",
       "         0.11291461, 0.06090209, 0.11732644, 0.13927188, 0.15596411]),\n",
       "  array([0.1782899 , 0.16763666, 0.02057991, 0.02462005, 0.04418773,\n",
       "         0.16333402, 0.05509713, 0.18041911, 0.14402322, 0.02181227]),\n",
       "  array([0.26374459, 0.02287912, 0.16925911, 0.10508258, 0.25074089,\n",
       "         0.02093486, 0.0903604 , 0.01944416, 0.04103507, 0.01651922]),\n",
       "  array([0.09756906, 0.16194911, 0.06370941, 0.10009486, 0.15250376,\n",
       "         0.13700107, 0.09486577, 0.05351951, 0.04852834, 0.09025911]),\n",
       "  array([0.00436506, 0.14230208, 0.079142  , 0.1397895 , 0.09565555,\n",
       "         0.0539347 , 0.15027457, 0.04964762, 0.19260783, 0.0922811 ]),\n",
       "  array([0.02029476, 0.12118564, 0.10441283, 0.19198809, 0.05552632,\n",
       "         0.19183015, 0.1531165 , 0.07348007, 0.02840309, 0.05976256]),\n",
       "  array([0.14247495, 0.072367  , 0.129134  , 0.1507719 , 0.03987875,\n",
       "         0.06986509, 0.13709743, 0.11852489, 0.12162194, 0.01826405]),\n",
       "  array([0.12024046, 0.1256045 , 0.07323476, 0.04901857, 0.08128407,\n",
       "         0.13381832, 0.04780054, 0.14039807, 0.09033295, 0.13826773]),\n",
       "  array([0.15138618, 0.00698515, 0.06539921, 0.18505965, 0.19079321,\n",
       "         0.16021652, 0.00781984, 0.12573677, 0.10130869, 0.00529477]),\n",
       "  array([0.19186182, 0.02916977, 0.01863696, 0.17777306, 0.16301039,\n",
       "         0.09776845, 0.12678929, 0.08340725, 0.05053592, 0.06104709]),\n",
       "  array([0.11076181, 0.08799192, 0.1580621 , 0.10685931, 0.06280551,\n",
       "         0.08900987, 0.13991048, 0.13701016, 0.06478805, 0.0428008 ]),\n",
       "  array([0.04496758, 0.0789804 , 0.15953789, 0.08907433, 0.09957785,\n",
       "         0.0230306 , 0.03967257, 0.15341694, 0.15263556, 0.15910627]),\n",
       "  array([0.10093165, 0.18301966, 0.11664044, 0.06890618, 0.10781831,\n",
       "         0.14983552, 0.06690388, 0.00510698, 0.01059769, 0.19023969]),\n",
       "  array([0.00526064, 0.13168463, 0.14467655, 0.11928473, 0.00081911,\n",
       "         0.15859135, 0.2223657 , 0.0446995 , 0.1555003 , 0.01711751]),\n",
       "  array([0.00600304, 0.1427526 , 0.17431853, 0.16256676, 0.04668346,\n",
       "         0.1512229 , 0.01790617, 0.02581086, 0.14133483, 0.13140086]),\n",
       "  array([0.1231721 , 0.03884472, 0.1622713 , 0.03633036, 0.12336549,\n",
       "         0.14346664, 0.08745603, 0.042726  , 0.13460954, 0.10775781]),\n",
       "  array([0.07385321, 0.1718142 , 0.20780633, 0.02015489, 0.00732543,\n",
       "         0.19282879, 0.02588727, 0.1210172 , 0.11527066, 0.06404201]),\n",
       "  array([0.12120224, 0.02103393, 0.0172064 , 0.06509443, 0.19045111,\n",
       "         0.18879805, 0.18153697, 0.08359739, 0.00211945, 0.12896003]),\n",
       "  array([0.12950132, 0.18835644, 0.06334494, 0.07670402, 0.18187466,\n",
       "         0.01656457, 0.07011365, 0.03372733, 0.05400111, 0.18581196]),\n",
       "  array([0.03467507, 0.16978178, 0.1738901 , 0.08573475, 0.14150749,\n",
       "         0.11436942, 0.14231722, 0.01574532, 0.01046844, 0.11151041]),\n",
       "  array([0.18169991, 0.06776439, 0.0180679 , 0.07109222, 0.21702545,\n",
       "         0.06358142, 0.17270844, 0.01069406, 0.16588008, 0.03148612]),\n",
       "  array([0.1178397 , 0.13654049, 0.06729124, 0.14160638, 0.12515926,\n",
       "         0.0924015 , 0.01359454, 0.07058532, 0.10479976, 0.13018181]),\n",
       "  array([0.13469963, 0.19378683, 0.06977785, 0.007973  , 0.07669804,\n",
       "         0.18879039, 0.00068162, 0.10228437, 0.16992526, 0.05538301]),\n",
       "  array([0.05324695, 0.18049708, 0.18344844, 0.02563514, 0.15921702,\n",
       "         0.05232419, 0.15085529, 0.06017922, 0.08449313, 0.05010354]),\n",
       "  array([0.16353089, 0.04696213, 0.11076863, 0.00452927, 0.04794772,\n",
       "         0.13703501, 0.11599537, 0.07562927, 0.14377106, 0.15383065]),\n",
       "  array([0.07650243, 0.22691294, 0.00621449, 0.08415819, 0.09187654,\n",
       "         0.09964633, 0.08041996, 0.10578853, 0.04551979, 0.18296079]),\n",
       "  array([0.149896  , 0.06443477, 0.07674739, 0.16651203, 0.06156198,\n",
       "         0.01970587, 0.08024778, 0.15832182, 0.06587412, 0.15669823]),\n",
       "  array([0.15667166, 0.11286086, 0.01947261, 0.1503527 , 0.08489279,\n",
       "         0.06527658, 0.07367433, 0.15386181, 0.15097666, 0.03196   ]),\n",
       "  array([0.05262902, 0.11710009, 0.03029509, 0.17593226, 0.15022941,\n",
       "         0.08561823, 0.10592024, 0.01187093, 0.08054941, 0.18985532]),\n",
       "  array([0.12103336, 0.01601203, 0.20699766, 0.09753419, 0.12796634,\n",
       "         0.06357615, 0.12946467, 0.0975015 , 0.1279906 , 0.01192352]),\n",
       "  array([0.00746639, 0.14731264, 0.04108352, 0.09013904, 0.16269373,\n",
       "         0.16158806, 0.16140092, 0.02070472, 0.07388146, 0.13372952]),\n",
       "  array([0.06384419, 0.13433605, 0.17842344, 0.06134249, 0.10703929,\n",
       "         0.11771158, 0.15779707, 0.08801556, 0.05202635, 0.03946399]),\n",
       "  array([0.26258595, 0.10014316, 0.02233096, 0.07558049, 0.10963374,\n",
       "         0.0119829 , 0.11697987, 0.15163118, 0.11331898, 0.03581277]),\n",
       "  array([0.18310889, 0.15458461, 0.02438159, 0.01188154, 0.04783814,\n",
       "         0.19057954, 0.15565944, 0.07545444, 0.00529098, 0.15122083]),\n",
       "  array([0.12807097, 0.07857055, 0.08611407, 0.05353233, 0.146276  ,\n",
       "         0.12852406, 0.09966382, 0.05544675, 0.09644832, 0.12735312]),\n",
       "  array([0.07876169, 0.04380398, 0.06784283, 0.12270181, 0.04944437,\n",
       "         0.06851756, 0.19359243, 0.20019095, 0.09046436, 0.08468004]),\n",
       "  array([0.13390788, 0.05732704, 0.02594704, 0.00778845, 0.20189919,\n",
       "         0.14832296, 0.21349162, 0.15409398, 0.04456918, 0.01265267]),\n",
       "  array([0.05639623, 0.23093798, 0.09033103, 0.13927056, 0.00524645,\n",
       "         0.13385203, 0.01023073, 0.06811567, 0.1645366 , 0.10108272]),\n",
       "  array([0.04532124, 0.05352053, 0.15477632, 0.14997542, 0.01175589,\n",
       "         0.18338979, 0.12298062, 0.07613138, 0.17171739, 0.03043141]),\n",
       "  array([0.14330048, 0.03567365, 0.0997895 , 0.04789903, 0.11241179,\n",
       "         0.12852593, 0.14788386, 0.08303456, 0.14521705, 0.05626415]),\n",
       "  array([0.04731162, 0.08145544, 0.03443229, 0.09699112, 0.05114512,\n",
       "         0.11894371, 0.10306735, 0.14659957, 0.12019355, 0.19986023]),\n",
       "  array([0.07213491, 0.13087767, 0.15619639, 0.13695108, 0.09114572,\n",
       "         0.15648255, 0.07597081, 0.06510277, 0.01501071, 0.10012738]),\n",
       "  array([0.12301813, 0.11750728, 0.10791973, 0.09796709, 0.08917313,\n",
       "         0.05723663, 0.10620341, 0.14484004, 0.13172548, 0.02440909]),\n",
       "  array([0.11964682, 0.09213564, 0.06266281, 0.13406147, 0.13352572,\n",
       "         0.06968311, 0.04014401, 0.08061262, 0.12504724, 0.14248056]),\n",
       "  array([0.16551879, 0.15770698, 0.17179948, 0.01965736, 0.09464951,\n",
       "         0.03058369, 0.17362636, 0.15253276, 0.02075682, 0.01316826]),\n",
       "  array([0.10461462, 0.0613447 , 0.04313894, 0.17019317, 0.01451389,\n",
       "         0.1163818 , 0.15773846, 0.17476774, 0.06889941, 0.08840726]),\n",
       "  array([0.0918087 , 0.1459784 , 0.06371121, 0.1449181 , 0.13916353,\n",
       "         0.06334747, 0.08023073, 0.00889303, 0.1515596 , 0.11038924]),\n",
       "  array([0.13756673, 0.01109459, 0.0622817 , 0.05799014, 0.15071063,\n",
       "         0.14884946, 0.05779361, 0.12446449, 0.11967424, 0.1295744 ]),\n",
       "  array([0.13691783, 0.11822314, 0.13873898, 0.08543895, 0.08134897,\n",
       "         0.00924257, 0.06854729, 0.14707678, 0.11574907, 0.09871642]),\n",
       "  array([0.0511616 , 0.03714647, 0.02422776, 0.16623628, 0.09184838,\n",
       "         0.19034941, 0.14567611, 0.09183912, 0.07700563, 0.12450925]),\n",
       "  array([0.18724895, 0.0212026 , 0.01356875, 0.11331996, 0.15840351,\n",
       "         0.00683545, 0.16136033, 0.02305294, 0.0910661 , 0.22394141]),\n",
       "  array([0.01815932, 0.15408252, 0.02444792, 0.00970104, 0.13616173,\n",
       "         0.09753278, 0.15118016, 0.13373454, 0.13779146, 0.13720853]),\n",
       "  array([0.0960362 , 0.15693559, 0.01851057, 0.18267373, 0.13726303,\n",
       "         0.08625443, 0.15398698, 0.15748132, 0.00823447, 0.00262367]),\n",
       "  array([0.12673648, 0.06335646, 0.06289303, 0.11308007, 0.05347521,\n",
       "         0.1261261 , 0.14148322, 0.09705752, 0.11038339, 0.10540852]),\n",
       "  array([0.0195056 , 0.07166684, 0.07006038, 0.04919391, 0.17012594,\n",
       "         0.17261414, 0.03331301, 0.19221453, 0.15238276, 0.06892288]),\n",
       "  array([0.1226662 , 0.01071487, 0.03148394, 0.09159448, 0.16868407,\n",
       "         0.09901165, 0.09455398, 0.11677137, 0.14111404, 0.12340539]),\n",
       "  array([0.07259733, 0.16224968, 0.05541964, 0.1035862 , 0.08831197,\n",
       "         0.00885522, 0.1422981 , 0.09812596, 0.10888752, 0.15966837]),\n",
       "  array([0.12164792, 0.07260676, 0.09830631, 0.08227607, 0.08633521,\n",
       "         0.09123014, 0.03657271, 0.08600224, 0.16187434, 0.16314832]),\n",
       "  array([0.10767648, 0.06875816, 0.1559126 , 0.19406053, 0.10480962,\n",
       "         0.22385456, 0.03755388, 0.01881915, 0.04627746, 0.04227756]),\n",
       "  array([0.10348192, 0.07950288, 0.13441825, 0.13607311, 0.0300414 ,\n",
       "         0.1057696 , 0.07304158, 0.17885078, 0.04649395, 0.11232654]),\n",
       "  array([0.14978459, 0.08595303, 0.11899214, 0.107623  , 0.01969504,\n",
       "         0.16497743, 0.14400084, 0.0684507 , 0.06894875, 0.07157448]),\n",
       "  array([0.14047531, 0.01749469, 0.11942864, 0.10312259, 0.15094597,\n",
       "         0.01577177, 0.09128363, 0.14167859, 0.1807284 , 0.03907041]),\n",
       "  array([0.02077583, 0.1364276 , 0.02137704, 0.11987112, 0.04854289,\n",
       "         0.1152201 , 0.06568535, 0.13963155, 0.14642963, 0.18603889]),\n",
       "  array([0.05162051, 0.13174568, 0.15427671, 0.1364713 , 0.00318967,\n",
       "         0.20644461, 0.0100142 , 0.14375285, 0.08656097, 0.07592349]),\n",
       "  array([0.17976634, 0.12233922, 0.06841314, 0.08121049, 0.00568912,\n",
       "         0.16376015, 0.13149338, 0.00296658, 0.17224446, 0.07211712]),\n",
       "  array([0.06681918, 0.19571479, 0.01989947, 0.02292806, 0.02145691,\n",
       "         0.1157468 , 0.1983031 , 0.12567077, 0.07888477, 0.15457616]),\n",
       "  array([0.13313919, 0.08131147, 0.11048476, 0.15439986, 0.15211293,\n",
       "         0.15077501, 0.09765454, 0.06310531, 0.04373586, 0.01328106]),\n",
       "  array([0.03690604, 0.00415413, 0.12983417, 0.13461925, 0.14267952,\n",
       "         0.14499478, 0.10983056, 0.12161933, 0.12476601, 0.05059622]),\n",
       "  array([0.10413536, 0.07953962, 0.09758707, 0.16023175, 0.10043929,\n",
       "         0.10076655, 0.04313313, 0.08049867, 0.15320908, 0.08045949]),\n",
       "  array([0.00507968, 0.14139221, 0.04969208, 0.10900755, 0.13175498,\n",
       "         0.11947509, 0.07964803, 0.13700078, 0.11372276, 0.11322684]),\n",
       "  array([0.04388478, 0.08165515, 0.15619595, 0.03697707, 0.17875034,\n",
       "         0.12000057, 0.1067239 , 0.06647119, 0.16341911, 0.04592194]),\n",
       "  array([0.16576411, 0.18391771, 0.17751894, 0.00932969, 0.03912778,\n",
       "         0.02860063, 0.10212529, 0.01163601, 0.10787284, 0.17410701]),\n",
       "  array([0.16526034, 0.05746292, 0.15355913, 0.03058465, 0.08865226,\n",
       "         0.0295184 , 0.07182499, 0.04393608, 0.16464793, 0.1945533 ]),\n",
       "  array([0.04124615, 0.1663179 , 0.15251751, 0.08837304, 0.10145408,\n",
       "         0.01508211, 0.03458317, 0.19158235, 0.19075455, 0.01808913]),\n",
       "  array([0.16545599, 0.1140318 , 0.0135738 , 0.10101312, 0.20361195,\n",
       "         0.07342178, 0.03723074, 0.09609227, 0.07082104, 0.12474752]),\n",
       "  array([0.02630951, 0.13589556, 0.15642509, 0.13619761, 0.09624878,\n",
       "         0.1618342 , 0.01596152, 0.04948197, 0.11966783, 0.10197793]),\n",
       "  array([0.0422125 , 0.06837117, 0.17690728, 0.01924258, 0.29004209,\n",
       "         0.05996953, 0.10020013, 0.19138393, 0.04152422, 0.01014657]),\n",
       "  array([0.13796956, 0.01519275, 0.17265343, 0.05659652, 0.15220386,\n",
       "         0.01282589, 0.08230943, 0.1570073 , 0.04160101, 0.17164025]),\n",
       "  array([0.0280867 , 0.00866443, 0.01487412, 0.16413922, 0.10376154,\n",
       "         0.00416715, 0.09856368, 0.33094348, 0.21311802, 0.03368165]),\n",
       "  array([0.02294026, 0.12265516, 0.03171811, 0.19380945, 0.0841931 ,\n",
       "         0.10144284, 0.125714  , 0.02077112, 0.18102214, 0.11573382]),\n",
       "  array([0.13062674, 0.05146891, 0.09373892, 0.15309791, 0.05972106,\n",
       "         0.13431601, 0.06790616, 0.10355166, 0.11597264, 0.08959999]),\n",
       "  array([0.04044311, 0.1089725 , 0.14021489, 0.18341092, 0.0290452 ,\n",
       "         0.052765  , 0.08263783, 0.08989438, 0.20477513, 0.06784102]),\n",
       "  array([0.0088502 , 0.11517403, 0.16427327, 0.16163252, 0.03950424,\n",
       "         0.02309009, 0.03573394, 0.14110102, 0.16434093, 0.14629976]),\n",
       "  array([0.0312883 , 0.04358886, 0.15897631, 0.0949108 , 0.16860943,\n",
       "         0.12823488, 0.07592289, 0.09209551, 0.12651976, 0.07985325]),\n",
       "  array([0.19303589, 0.12912856, 0.03230082, 0.15143283, 0.16283072,\n",
       "         0.08663353, 0.02213469, 0.02736128, 0.13919978, 0.0559419 ]),\n",
       "  array([0.04570113, 0.02053267, 0.19504361, 0.00330056, 0.13114357,\n",
       "         0.20511749, 0.15120241, 0.13942089, 0.07392975, 0.03460793]),\n",
       "  array([0.06075813, 0.0335444 , 0.12979792, 0.13078847, 0.14271702,\n",
       "         0.0802395 , 0.11389255, 0.12006847, 0.06723864, 0.12095491]),\n",
       "  array([0.14490717, 0.07506978, 0.17803587, 0.17401025, 0.00124335,\n",
       "         0.00290885, 0.08109384, 0.15077717, 0.07666728, 0.11528645]),\n",
       "  array([0.06209884, 0.06127685, 0.19699875, 0.15464941, 0.18387479,\n",
       "         0.14557548, 0.01282853, 0.0509681 , 0.0656498 , 0.06607944]),\n",
       "  array([0.10119684, 0.00157172, 0.18379809, 0.14940539, 0.135057  ,\n",
       "         0.03084417, 0.08050792, 0.1611476 , 0.05496825, 0.10150301]),\n",
       "  array([0.08692704, 0.14882677, 0.15031635, 0.04411285, 0.09890031,\n",
       "         0.06598555, 0.05857658, 0.12656274, 0.08562718, 0.13416464]),\n",
       "  array([0.14151159, 0.04760012, 0.15687151, 0.11699444, 0.07851351,\n",
       "         0.01752976, 0.09879815, 0.14653167, 0.06002678, 0.13562248]),\n",
       "  array([0.07110729, 0.09339284, 0.11551303, 0.05189261, 0.17685168,\n",
       "         0.11006201, 0.00153393, 0.08535364, 0.1354052 , 0.15888778]),\n",
       "  array([0.16430163, 0.18030312, 0.09205102, 0.03309299, 0.13170747,\n",
       "         0.02547488, 0.03866952, 0.02461065, 0.1530983 , 0.15669042]),\n",
       "  array([0.04036119, 0.05650698, 0.20701191, 0.17526703, 0.00923478,\n",
       "         0.16873838, 0.04174724, 0.01776583, 0.26922112, 0.01414554]),\n",
       "  array([0.09375212, 0.1334938 , 0.11634718, 0.08333758, 0.09721851,\n",
       "         0.07664141, 0.09455038, 0.12390384, 0.10129711, 0.07945806]),\n",
       "  array([0.18187413, 0.03148934, 0.13124929, 0.10900423, 0.05023529,\n",
       "         0.1430068 , 0.00140602, 0.05720101, 0.10022247, 0.1943114 ]),\n",
       "  array([0.14231841, 0.1074456 , 0.15968833, 0.07350562, 0.07950433,\n",
       "         0.10054417, 0.06911243, 0.10932223, 0.06033406, 0.09822481]),\n",
       "  array([0.04233263, 0.07512813, 0.0297497 , 0.11193869, 0.06994916,\n",
       "         0.17053329, 0.20543104, 0.14518102, 0.12729905, 0.02245729]),\n",
       "  array([0.13987137, 0.0405467 , 0.19799588, 0.16105388, 0.05320023,\n",
       "         0.09422987, 0.0084697 , 0.12379976, 0.05826341, 0.1225692 ]),\n",
       "  array([0.10852661, 0.07131092, 0.07048537, 0.19064251, 0.12579198,\n",
       "         0.03138973, 0.06610955, 0.0490225 , 0.07810735, 0.20861348]),\n",
       "  array([0.0089216 , 0.1348598 , 0.13048576, 0.10625856, 0.18506544,\n",
       "         0.11715454, 0.00474641, 0.12289349, 0.1370262 , 0.05258819]),\n",
       "  array([0.16764097, 0.11361311, 0.08188401, 0.12697582, 0.13313181,\n",
       "         0.01724651, 0.14072312, 0.18172606, 0.02686646, 0.01019213]),\n",
       "  array([0.0772767 , 0.08113771, 0.09082102, 0.10316169, 0.16044712,\n",
       "         0.04896706, 0.15379445, 0.14291052, 0.13615878, 0.00532495]),\n",
       "  array([0.03847989, 0.0664881 , 0.11493994, 0.16594711, 0.03637144,\n",
       "         0.18261981, 0.16448465, 0.15353932, 0.02361092, 0.05351881]),\n",
       "  array([0.05274011, 0.10093289, 0.11211396, 0.14645333, 0.05234386,\n",
       "         0.11522946, 0.01633676, 0.17158877, 0.19271898, 0.03954187]),\n",
       "  array([0.12991871, 0.04707341, 0.14102877, 0.18507417, 0.10564151,\n",
       "         0.05937113, 0.03204132, 0.05147943, 0.15737856, 0.09099299]),\n",
       "  array([0.06373884, 0.05533302, 0.02719932, 0.06594727, 0.16150079,\n",
       "         0.09269466, 0.15348982, 0.15674865, 0.14683851, 0.07650912]),\n",
       "  array([0.03035393, 0.14176949, 0.04103938, 0.23972243, 0.01884436,\n",
       "         0.25129702, 0.03160383, 0.11335375, 0.05621692, 0.07579889]),\n",
       "  array([0.0961009 , 0.07002377, 0.08165698, 0.13949613, 0.17363022,\n",
       "         0.11944698, 0.1269016 , 0.02167839, 0.08860806, 0.08245698]),\n",
       "  array([0.04416921, 0.08566764, 0.09921724, 0.04937382, 0.10426989,\n",
       "         0.13551701, 0.24674535, 0.04809317, 0.0639189 , 0.12302775]),\n",
       "  array([0.07399224, 0.14213702, 0.18026361, 0.00193759, 0.11461109,\n",
       "         0.01486776, 0.14156118, 0.06984693, 0.04030581, 0.22047678]),\n",
       "  array([0.15862497, 0.07585635, 0.16222316, 0.09474813, 0.16887268,\n",
       "         0.05975185, 0.16726739, 0.00576574, 0.05275652, 0.0541332 ]),\n",
       "  array([0.17569024, 0.15146864, 0.10925873, 0.02581093, 0.09754222,\n",
       "         0.03839565, 0.09345979, 0.04934011, 0.15264848, 0.10638522]),\n",
       "  array([0.18937381, 0.0730461 , 0.149078  , 0.01546493, 0.17846028,\n",
       "         0.03856861, 0.06717317, 0.08709326, 0.02575668, 0.17598518]),\n",
       "  array([0.13340916, 0.09097255, 0.11591968, 0.1097998 , 0.13358817,\n",
       "         0.06760296, 0.1273181 , 0.00273952, 0.09598329, 0.12266679]),\n",
       "  array([0.12138287, 0.16398093, 0.10539929, 0.04306869, 0.03633879,\n",
       "         0.1373261 , 0.03500083, 0.15475989, 0.11964146, 0.08310114]),\n",
       "  array([0.11893125, 0.12647521, 0.0563997 , 0.05794639, 0.11938008,\n",
       "         0.12254868, 0.11623267, 0.12577563, 0.14772982, 0.00858057]),\n",
       "  array([0.20023814, 0.16686672, 0.08895822, 0.05114855, 0.03795844,\n",
       "         0.07278379, 0.06616707, 0.05776912, 0.14773002, 0.11037993]),\n",
       "  array([0.01108629, 0.1338855 , 0.14149619, 0.10502245, 0.01043908,\n",
       "         0.11982598, 0.13879096, 0.14302628, 0.13674023, 0.05968704]),\n",
       "  array([0.16040685, 0.19069085, 0.15373949, 0.01921712, 0.05437482,\n",
       "         0.09795496, 0.0562282 , 0.01888419, 0.15791192, 0.0905916 ]),\n",
       "  array([0.15176603, 0.22943846, 0.00919857, 0.13652209, 0.03055786,\n",
       "         0.04294271, 0.01065127, 0.01523859, 0.23463763, 0.13904678]),\n",
       "  array([0.11663477, 0.09715302, 0.01612147, 0.02865761, 0.08084861,\n",
       "         0.09750597, 0.22949268, 0.18918002, 0.02154497, 0.12286088]),\n",
       "  array([0.12378378, 0.02464   , 0.07478894, 0.09555645, 0.11118844,\n",
       "         0.13380293, 0.03652341, 0.14403152, 0.10990082, 0.14578371]),\n",
       "  array([0.1771525 , 0.1816257 , 0.0426399 , 0.00125149, 0.10820188,\n",
       "         0.10816184, 0.23947773, 0.09672003, 0.00056707, 0.04420185]),\n",
       "  array([0.12330707, 0.12513775, 0.05775751, 0.08769442, 0.12814636,\n",
       "         0.14871622, 0.0509098 , 0.04703641, 0.16857633, 0.06271813]),\n",
       "  array([0.04138504, 0.04230213, 0.01216683, 0.09157687, 0.10774379,\n",
       "         0.14805453, 0.10780322, 0.14935601, 0.15759447, 0.14201712]),\n",
       "  array([0.03131848, 0.09694322, 0.03255604, 0.0650853 , 0.11756998,\n",
       "         0.13911494, 0.08586762, 0.17525612, 0.12198897, 0.13429934]),\n",
       "  array([0.00442463, 0.10169374, 0.08467065, 0.11698478, 0.1559653 ,\n",
       "         0.12686819, 0.07028466, 0.06375121, 0.16389954, 0.1114573 ]),\n",
       "  array([0.04333432, 0.12033306, 0.05462806, 0.10236602, 0.18682933,\n",
       "         0.06588561, 0.00893447, 0.18825517, 0.01772876, 0.21170521]),\n",
       "  array([0.15032919, 0.05852878, 0.13504937, 0.15913913, 0.13764134,\n",
       "         0.10258662, 0.00511793, 0.03581472, 0.18000643, 0.03578649]),\n",
       "  array([0.13342943, 0.001721  , 0.075459  , 0.13122528, 0.04221826,\n",
       "         0.05510908, 0.17082265, 0.09399853, 0.18246808, 0.11354868]),\n",
       "  array([0.08798935, 0.14140946, 0.07228302, 0.04215772, 0.13159742,\n",
       "         0.163885  , 0.11392096, 0.07931256, 0.03044228, 0.13700223]),\n",
       "  array([0.0718125 , 0.14730946, 0.07697109, 0.07844156, 0.16086562,\n",
       "         0.15369331, 0.0296805 , 0.12722464, 0.1167427 , 0.03725862]),\n",
       "  array([0.20469506, 0.05057586, 0.0819641 , 0.10373021, 0.21427138,\n",
       "         0.09290253, 0.16633804, 0.02241049, 0.02615899, 0.03695332]),\n",
       "  array([0.20480406, 0.02008918, 0.0596873 , 0.04531638, 0.02352731,\n",
       "         0.03607437, 0.27483406, 0.13723331, 0.07861375, 0.11982028]),\n",
       "  array([0.04434505, 0.07459389, 0.13806417, 0.09376553, 0.16003277,\n",
       "         0.14345366, 0.05456585, 0.03270162, 0.08724707, 0.17123039]),\n",
       "  array([0.03118845, 0.01863279, 0.07087997, 0.13944822, 0.01849477,\n",
       "         0.04347178, 0.15342157, 0.15907072, 0.12407968, 0.24131206]),\n",
       "  array([0.01128012, 0.10877532, 0.05679822, 0.16308566, 0.11108018,\n",
       "         0.05640478, 0.10576246, 0.06133291, 0.17930473, 0.14617563]),\n",
       "  array([0.08119596, 0.14483946, 0.142187  , 0.10901208, 0.16290891,\n",
       "         0.0870295 , 0.03520034, 0.03185771, 0.13040585, 0.07536319]),\n",
       "  array([0.09358629, 0.15436693, 0.11618304, 0.03447499, 0.11679107,\n",
       "         0.06508714, 0.06116059, 0.14308005, 0.05419717, 0.16107272]),\n",
       "  array([0.06514248, 0.16018847, 0.14971973, 0.03805839, 0.09977029,\n",
       "         0.11753405, 0.12767426, 0.09817808, 0.04281652, 0.10091774]),\n",
       "  array([0.17665459, 0.14541112, 0.17159749, 0.01043376, 0.1238982 ,\n",
       "         0.00914129, 0.1318901 , 0.05196879, 0.0585296 , 0.12047506]),\n",
       "  array([0.13644039, 0.02599732, 0.04919425, 0.08094922, 0.14105614,\n",
       "         0.14835844, 0.17044329, 0.04581859, 0.03916401, 0.16257834]),\n",
       "  array([0.10874979, 0.12056741, 0.01280922, 0.10785061, 0.16270474,\n",
       "         0.03125394, 0.14087118, 0.04237535, 0.10090058, 0.17191717]),\n",
       "  array([0.13644078, 0.04411969, 0.1089665 , 0.16083553, 0.07030265,\n",
       "         0.03697899, 0.11194734, 0.13981198, 0.14482703, 0.04576952]),\n",
       "  array([0.10913773, 0.13489482, 0.14364025, 0.09701548, 0.04843329,\n",
       "         0.15882053, 0.17656769, 0.02952141, 0.06615176, 0.03581704]),\n",
       "  array([0.10804382, 0.15868469, 0.1147758 , 0.03818226, 0.08561939,\n",
       "         0.09095489, 0.13498407, 0.06183055, 0.07809655, 0.128828  ]),\n",
       "  array([0.00261866, 0.13875184, 0.15283147, 0.13715495, 0.09958233,\n",
       "         0.03106769, 0.03617264, 0.14515067, 0.15685085, 0.09981888]),\n",
       "  array([0.14923017, 0.17593323, 0.09959566, 0.04571053, 0.06624523,\n",
       "         0.13193193, 0.17280666, 0.05398396, 0.06772173, 0.0368409 ]),\n",
       "  array([0.10420308, 0.08573382, 0.01021256, 0.03670971, 0.12014607,\n",
       "         0.17376012, 0.20742278, 0.11873179, 0.03383663, 0.10924344]),\n",
       "  array([0.15395682, 0.13102826, 0.06634921, 0.11612608, 0.12202329,\n",
       "         0.00051936, 0.15454449, 0.16630826, 0.0751509 , 0.01399335]),\n",
       "  array([0.02774523, 0.11748632, 0.16222152, 0.05647169, 0.13787954,\n",
       "         0.0500828 , 0.0358729 , 0.1550049 , 0.17578453, 0.08145058]),\n",
       "  array([0.17361532, 0.0134666 , 0.04059591, 0.26590985, 0.24671769,\n",
       "         0.0035652 , 0.04069086, 0.0173011 , 0.09201519, 0.10612227]),\n",
       "  array([0.0853728 , 0.01851274, 0.11635326, 0.04374769, 0.14856687,\n",
       "         0.17214753, 0.15603359, 0.04349589, 0.17044588, 0.04532376]),\n",
       "  array([0.08400551, 0.18474426, 0.03763823, 0.1398949 , 0.00241794,\n",
       "         0.12729613, 0.05376648, 0.12810703, 0.13637554, 0.10575398]),\n",
       "  array([0.00722016, 0.23310499, 0.20794653, 0.03558665, 0.19091851,\n",
       "         0.01354732, 0.05703953, 0.05897825, 0.18596243, 0.00969563]),\n",
       "  array([0.02391095, 0.19000611, 0.03649518, 0.12683054, 0.17448008,\n",
       "         0.13206714, 0.1096692 , 0.12368806, 0.02818345, 0.0546693 ]),\n",
       "  array([0.11573523, 0.01288065, 0.21802896, 0.25158366, 0.08876657,\n",
       "         0.272991  , 0.00067109, 0.00604205, 0.01638166, 0.01691914]),\n",
       "  array([0.12123868, 0.03841583, 0.04087315, 0.23137955, 0.03173843,\n",
       "         0.13417184, 0.11703469, 0.12763412, 0.08927106, 0.06824266]),\n",
       "  array([0.09529021, 0.07364945, 0.17048133, 0.0708011 , 0.10726737,\n",
       "         0.08436135, 0.10212304, 0.13731382, 0.04330856, 0.11540379]),\n",
       "  array([0.18336293, 0.15463988, 0.01349932, 0.00528886, 0.08473732,\n",
       "         0.08128347, 0.18429145, 0.05527191, 0.20299044, 0.03463442]),\n",
       "  array([0.09404829, 0.13005583, 0.19090709, 0.06470991, 0.07906041,\n",
       "         0.01042096, 0.114306  , 0.01071455, 0.11174322, 0.19403375]),\n",
       "  array([0.15536141, 0.12602984, 0.06795842, 0.08260923, 0.13667551,\n",
       "         0.09612204, 0.05934512, 0.01577107, 0.12071231, 0.13941504]),\n",
       "  array([0.01090732, 0.15202534, 0.09256244, 0.14207439, 0.17939508,\n",
       "         0.08545693, 0.17299801, 0.07626195, 0.05413795, 0.03418058]),\n",
       "  array([0.12396663, 0.01684857, 0.16254904, 0.04485194, 0.19921336,\n",
       "         0.11613393, 0.03280123, 0.04014345, 0.14193462, 0.12155725]),\n",
       "  array([0.1087997 , 0.15601293, 0.0767442 , 0.04181207, 0.171532  ,\n",
       "         0.06337102, 0.00328153, 0.07521354, 0.09934174, 0.20389127]),\n",
       "  array([0.16391067, 0.10235921, 0.03642246, 0.08167934, 0.00664756,\n",
       "         0.15876717, 0.04092943, 0.14712698, 0.08807251, 0.17408467]),\n",
       "  array([0.08614889, 0.08393569, 0.15004608, 0.0080863 , 0.1510332 ,\n",
       "         0.17229873, 0.14609602, 0.10670151, 0.05772567, 0.03792791]),\n",
       "  array([0.13359597, 0.13363677, 0.01267569, 0.18370769, 0.05489572,\n",
       "         0.14381506, 0.07589347, 0.01821747, 0.115771  , 0.12779115]),\n",
       "  array([0.10872251, 0.20931748, 0.16544845, 0.09679936, 0.02378595,\n",
       "         0.0034971 , 0.02205293, 0.14961091, 0.05860793, 0.16215738]),\n",
       "  array([0.11298052, 0.04960062, 0.09742485, 0.05721611, 0.04338344,\n",
       "         0.11470249, 0.07608155, 0.11887069, 0.16660946, 0.16313027]),\n",
       "  array([0.1593136 , 0.21496033, 0.00734227, 0.07276602, 0.03548458,\n",
       "         0.13577357, 0.03621132, 0.18654717, 0.09666166, 0.05493948]),\n",
       "  array([0.02829291, 0.05207108, 0.06136008, 0.14152012, 0.21179794,\n",
       "         0.07747533, 0.11401553, 0.20395497, 0.06323714, 0.04627489]),\n",
       "  array([0.16990149, 0.17266227, 0.09550327, 0.08220498, 0.00240218,\n",
       "         0.16392541, 0.00695481, 0.1490313 , 0.01064271, 0.14677157]),\n",
       "  array([0.0341864 , 0.10764117, 0.09435042, 0.18606278, 0.14222736,\n",
       "         0.01776893, 0.01703468, 0.16288916, 0.05199678, 0.18584232]),\n",
       "  array([0.02021175, 0.13134615, 0.12344736, 0.10884238, 0.04325021,\n",
       "         0.14992391, 0.12955065, 0.09549994, 0.05251648, 0.14541117]),\n",
       "  array([0.12154934, 0.13357703, 0.0729828 , 0.03072638, 0.21501641,\n",
       "         0.03242616, 0.08861302, 0.14442743, 0.04437975, 0.11630169]),\n",
       "  array([0.01116585, 0.08740032, 0.05147315, 0.17515381, 0.16907688,\n",
       "         0.18463619, 0.10404409, 0.04874479, 0.16280576, 0.00549917]),\n",
       "  array([0.15530083, 0.00018076, 0.15301225, 0.07391948, 0.13465842,\n",
       "         0.08925893, 0.12557086, 0.12226087, 0.078972  , 0.0668656 ]),\n",
       "  array([0.12222975, 0.12504393, 0.22586461, 0.0212016 , 0.04753918,\n",
       "         0.00710981, 0.21146778, 0.09507359, 0.10887632, 0.03559344]),\n",
       "  array([0.03547803, 0.0433517 , 0.08357094, 0.03200265, 0.20359822,\n",
       "         0.15026654, 0.04652959, 0.15404171, 0.11090855, 0.14025208]),\n",
       "  array([0.09302844, 0.1317438 , 0.00203736, 0.04749754, 0.02671916,\n",
       "         0.09998832, 0.15934127, 0.19531514, 0.2358246 , 0.00850435]),\n",
       "  array([0.16438408, 0.049426  , 0.11497397, 0.12252347, 0.00095147,\n",
       "         0.28598478, 0.03629954, 0.03544137, 0.15700537, 0.03300995]),\n",
       "  array([0.05165437, 0.02048369, 0.18332565, 0.14023968, 0.02635064,\n",
       "         0.14279264, 0.08713024, 0.01611279, 0.1618106 , 0.1700997 ]),\n",
       "  array([0.01424211, 0.08276315, 0.20703375, 0.07097159, 0.11845651,\n",
       "         0.17098367, 0.0394836 , 0.1691791 , 0.1034303 , 0.02345621]),\n",
       "  array([0.09696645, 0.13467799, 0.11673433, 0.09035401, 0.13186381,\n",
       "         0.08249644, 0.0916004 , 0.10043557, 0.01861863, 0.13625236]),\n",
       "  array([0.13561488, 0.13650312, 0.12858977, 0.03359181, 0.1410825 ,\n",
       "         0.12423559, 0.11638568, 0.07097998, 0.0435998 , 0.06941687]),\n",
       "  array([0.19775639, 0.04878728, 0.15683925, 0.18210171, 0.02738542,\n",
       "         0.03894462, 0.03372894, 0.08392262, 0.08628432, 0.14424947]),\n",
       "  array([0.0796292 , 0.04356084, 0.29587658, 0.23450248, 0.09037806,\n",
       "         0.00491256, 0.0360135 , 0.04880039, 0.07551449, 0.0908119 ]),\n",
       "  array([0.09545164, 0.14204029, 0.08111663, 0.06813404, 0.00327525,\n",
       "         0.19420179, 0.05929783, 0.16462544, 0.14609619, 0.04576091]),\n",
       "  array([0.08834413, 0.17372537, 0.1035059 , 0.06833975, 0.1097966 ,\n",
       "         0.16767588, 0.11716396, 0.04192435, 0.11495664, 0.0145674 ]),\n",
       "  array([0.02060794, 0.18242054, 0.17384026, 0.11998415, 0.0049505 ,\n",
       "         0.11421918, 0.0353199 , 0.14030049, 0.11467863, 0.09367841]),\n",
       "  array([0.00391521, 0.06304941, 0.1470877 , 0.06501654, 0.07768475,\n",
       "         0.0772022 , 0.23310998, 0.05490265, 0.04050866, 0.23752291]),\n",
       "  array([0.20464904, 0.11815116, 0.06094961, 0.02262491, 0.10910219,\n",
       "         0.1329738 , 0.00065145, 0.0842647 , 0.10391317, 0.16271997]),\n",
       "  array([0.05761736, 0.04723869, 0.1038405 , 0.1343677 , 0.07096941,\n",
       "         0.19578749, 0.18597092, 0.05896145, 0.11314392, 0.03210255]),\n",
       "  array([0.20014074, 0.05040687, 0.03597163, 0.14345051, 0.01991258,\n",
       "         0.1959929 , 0.07998681, 0.10227164, 0.1285541 , 0.04331222]),\n",
       "  array([0.03457419, 0.21488062, 0.07701194, 0.05013965, 0.19809825,\n",
       "         0.0517085 , 0.09689493, 0.19232181, 0.07783471, 0.0065354 ]),\n",
       "  array([0.06134382, 0.18215587, 0.00735283, 0.07286757, 0.17925603,\n",
       "         0.16640619, 0.14730068, 0.04102664, 0.00760201, 0.13468836]),\n",
       "  array([0.14157903, 0.051736  , 0.21254996, 0.05668821, 0.01489894,\n",
       "         0.03096662, 0.04707517, 0.06630976, 0.18792942, 0.19026688]),\n",
       "  array([0.07838933, 0.04843883, 0.1372783 , 0.19143274, 0.03657041,\n",
       "         0.07850829, 0.15102698, 0.04715934, 0.0145041 , 0.21669169]),\n",
       "  array([0.06491755, 0.05039229, 0.047301  , 0.236307  , 0.04757301,\n",
       "         0.15281912, 0.15957905, 0.09276388, 0.07080461, 0.0775425 ]),\n",
       "  array([0.08177771, 0.07574137, 0.14091575, 0.07720218, 0.20188322,\n",
       "         0.00696575, 0.12855215, 0.12316419, 0.06624143, 0.09755625]),\n",
       "  array([0.10305985, 0.11551424, 0.14899483, 0.09878414, 0.03077981,\n",
       "         0.00233882, 0.16919228, 0.06947905, 0.09466688, 0.1671901 ]),\n",
       "  array([0.0813976 , 0.20537345, 0.06553126, 0.11278214, 0.00216689,\n",
       "         0.03649655, 0.17481893, 0.06716488, 0.19551196, 0.05875634]),\n",
       "  array([0.01038504, 0.07096909, 0.16291806, 0.02443056, 0.06398588,\n",
       "         0.2559574 , 0.09552092, 0.03533303, 0.09560728, 0.18489275]),\n",
       "  array([0.12915725, 0.06103803, 0.10032891, 0.11022182, 0.00523533,\n",
       "         0.15554329, 0.15554532, 0.12304792, 0.00650534, 0.15337679]),\n",
       "  array([0.14022184, 0.15402688, 0.02480064, 0.08212104, 0.01855554,\n",
       "         0.12360916, 0.16255285, 0.15846399, 0.12912391, 0.00652415]),\n",
       "  array([0.04145302, 0.10739829, 0.16225577, 0.04621875, 0.03423823,\n",
       "         0.10052308, 0.0926647 , 0.1555047 , 0.11532485, 0.14441859]),\n",
       "  array([0.12869722, 0.02020472, 0.15269358, 0.22077028, 0.11876581,\n",
       "         0.22520468, 0.03990981, 0.03718659, 0.03467057, 0.02189674]),\n",
       "  array([0.00093555, 0.06945682, 0.1941239 , 0.08493868, 0.04737168,\n",
       "         0.09980353, 0.04587149, 0.18520862, 0.1867536 , 0.08553614]),\n",
       "  array([0.16196186, 0.12254269, 0.22681725, 0.04802528, 0.00968954,\n",
       "         0.08244489, 0.06365669, 0.09765377, 0.07212216, 0.11508587]),\n",
       "  array([0.03719477, 0.13000717, 0.09706399, 0.11094447, 0.09486652,\n",
       "         0.08606244, 0.18007163, 0.1463427 , 0.03587721, 0.0815691 ]),\n",
       "  array([0.03138289, 0.00531604, 0.12626921, 0.07038311, 0.09435754,\n",
       "         0.16772941, 0.12358046, 0.18792558, 0.16182766, 0.03122808]),\n",
       "  array([0.04455499, 0.13935983, 0.06342869, 0.00260519, 0.08308709,\n",
       "         0.18091677, 0.16356969, 0.166397  , 0.07820941, 0.07787134]),\n",
       "  array([0.02459637, 0.12212152, 0.13882532, 0.10535469, 0.16626223,\n",
       "         0.01406622, 0.03887381, 0.17672817, 0.02096746, 0.19220421]),\n",
       "  array([0.05379878, 0.08479784, 0.07710799, 0.12546633, 0.0797388 ,\n",
       "         0.12019295, 0.12123037, 0.14644346, 0.0509179 , 0.14030559]),\n",
       "  array([0.06346714, 0.03712553, 0.17796322, 0.09441766, 0.15393344,\n",
       "         0.18712491, 0.0111378 , 0.00554757, 0.05769751, 0.21158522]),\n",
       "  array([0.0840669 , 0.08714494, 0.14893164, 0.07353451, 0.02284587,\n",
       "         0.13359009, 0.0889033 , 0.15169385, 0.15837011, 0.05091879]),\n",
       "  array([0.17341109, 0.16384562, 0.11731007, 0.15832206, 0.00927388,\n",
       "         0.01164918, 0.13193903, 0.18093944, 0.02045803, 0.03285159]),\n",
       "  array([0.11770625, 0.02756801, 0.11394237, 0.12561831, 0.12523014,\n",
       "         0.01350589, 0.12741299, 0.13702042, 0.15020104, 0.06179458]),\n",
       "  array([0.00450155, 0.0329501 , 0.06867777, 0.17375646, 0.13035881,\n",
       "         0.14316226, 0.17953962, 0.05205437, 0.15139933, 0.06359973]),\n",
       "  array([0.12814717, 0.15745721, 0.1741086 , 0.01676341, 0.06518689,\n",
       "         0.15528645, 0.04908099, 0.05672318, 0.10490218, 0.09234391]),\n",
       "  array([0.13823077, 0.14092767, 0.02102148, 0.13284315, 0.01057633,\n",
       "         0.07812915, 0.07637691, 0.10820472, 0.13188546, 0.16180437]),\n",
       "  array([0.02161255, 0.09511541, 0.14093003, 0.06607825, 0.16946199,\n",
       "         0.20485467, 0.11042633, 0.07941699, 0.07901374, 0.03309005]),\n",
       "  array([0.17103498, 0.09183495, 0.08089293, 0.17451812, 0.08804034,\n",
       "         0.1176377 , 0.12236283, 0.00221816, 0.00725306, 0.14420694]),\n",
       "  array([0.18193996, 0.05008015, 0.00244279, 0.05316305, 0.17928398,\n",
       "         0.16819807, 0.11799376, 0.05921513, 0.14880244, 0.03888067]),\n",
       "  array([0.00184165, 0.00818181, 0.16416432, 0.18746912, 0.1324877 ,\n",
       "         0.03005116, 0.01541714, 0.0795485 , 0.16103392, 0.21980467]),\n",
       "  array([0.09096492, 0.06984909, 0.02485121, 0.09022844, 0.16779661,\n",
       "         0.22014157, 0.02982754, 0.08739968, 0.19120513, 0.0277358 ]),\n",
       "  array([0.06128509, 0.16262033, 0.14844432, 0.18451873, 0.07516555,\n",
       "         0.07932676, 0.13711668, 0.08053495, 0.02619705, 0.04479055]),\n",
       "  array([0.05722552, 0.09202547, 0.0994924 , 0.10420945, 0.13397556,\n",
       "         0.05374091, 0.13673593, 0.14421827, 0.11461859, 0.0637579 ]),\n",
       "  array([0.05225561, 0.18535612, 0.11910922, 0.13998321, 0.04829561,\n",
       "         0.1680097 , 0.04184845, 0.11166093, 0.10020273, 0.03327842]),\n",
       "  array([0.07571928, 0.03466063, 0.1511778 , 0.15002148, 0.1520926 ,\n",
       "         0.0664761 , 0.11105266, 0.06341843, 0.04034045, 0.15504057]),\n",
       "  array([0.12359494, 0.03016271, 0.14180164, 0.15589459, 0.12313362,\n",
       "         0.04387062, 0.0738565 , 0.0445635 , 0.13925699, 0.12386489]),\n",
       "  array([0.1709834 , 0.12282852, 0.00664566, 0.2177447 , 0.05039092,\n",
       "         0.15959669, 0.04120229, 0.08911483, 0.11328805, 0.02820493]),\n",
       "  array([0.15565602, 0.00415969, 0.1610695 , 0.17938402, 0.1411878 ,\n",
       "         0.03143356, 0.12983197, 0.13503387, 0.04174868, 0.02049489]),\n",
       "  array([0.01362781, 0.17283695, 0.01298261, 0.1677952 , 0.04814325,\n",
       "         0.10246153, 0.15579736, 0.17516928, 0.04618443, 0.10500157]),\n",
       "  array([0.19053739, 0.15352946, 0.08958597, 0.09179755, 0.00713731,\n",
       "         0.05799473, 0.01188754, 0.12261544, 0.11550911, 0.1594055 ]),\n",
       "  array([0.10551989, 0.16597099, 0.16101719, 0.15423145, 0.06817884,\n",
       "         0.05248533, 0.01132102, 0.05919918, 0.0698212 , 0.15225489]),\n",
       "  array([0.17323068, 0.09469533, 0.12142414, 0.0988852 , 0.06397783,\n",
       "         0.18120174, 0.03552494, 0.07653636, 0.11116865, 0.04335512]),\n",
       "  array([0.08643844, 0.12484408, 0.09345401, 0.01233306, 0.03926801,\n",
       "         0.14998625, 0.10161655, 0.1532838 , 0.05994412, 0.17883167]),\n",
       "  array([0.12238906, 0.1054232 , 0.00921566, 0.06637074, 0.12103565,\n",
       "         0.09341438, 0.17283156, 0.04497807, 0.17131577, 0.09302591]),\n",
       "  array([0.08548564, 0.05863347, 0.17116433, 0.04769155, 0.19677596,\n",
       "         0.08350533, 0.15873597, 0.03613625, 0.07482695, 0.08704456]),\n",
       "  array([0.13899202, 0.0689666 , 0.14120244, 0.11166438, 0.11522607,\n",
       "         0.01626201, 0.07253344, 0.12239367, 0.06846162, 0.14429776]),\n",
       "  array([0.12059983, 0.02238752, 0.15269087, 0.14882438, 0.08361003,\n",
       "         0.10110302, 0.04573403, 0.1632496 , 0.00574834, 0.15605237]),\n",
       "  array([0.06354797, 0.15917898, 0.12173796, 0.02922759, 0.08553379,\n",
       "         0.09008308, 0.13884444, 0.15717428, 0.02580921, 0.12886269]),\n",
       "  array([0.15826486, 0.09866017, 0.0875892 , 0.1171166 , 0.13042563,\n",
       "         0.0072141 , 0.12808021, 0.11718814, 0.05275918, 0.10270191]),\n",
       "  array([0.01111141, 0.08669406, 0.01844244, 0.18431304, 0.10949344,\n",
       "         0.20830149, 0.11370526, 0.09467743, 0.10552872, 0.06773271]),\n",
       "  array([0.14422741, 0.16855283, 0.09132139, 0.02932213, 0.03174803,\n",
       "         0.19841926, 0.17370176, 0.06501256, 0.0518529 , 0.04584173]),\n",
       "  array([0.08828723, 0.17139588, 0.05866302, 0.01273473, 0.13680439,\n",
       "         0.09922699, 0.19100129, 0.01926406, 0.1942047 , 0.0284177 ]),\n",
       "  array([0.01030694, 0.16592483, 0.0453421 , 0.15453393, 0.02094933,\n",
       "         0.16027364, 0.15950635, 0.10040749, 0.07853189, 0.10422351]),\n",
       "  array([0.16769624, 0.24821184, 0.13318884, 0.01529491, 0.14735081,\n",
       "         0.001325  , 0.00409831, 0.13489816, 0.14074756, 0.00718835]),\n",
       "  array([0.17601036, 0.01233587, 0.04562159, 0.17268878, 0.0294159 ,\n",
       "         0.12246421, 0.14712697, 0.15395061, 0.10838673, 0.03199897]),\n",
       "  array([0.04821335, 0.15256083, 0.10541293, 0.03913129, 0.11258219,\n",
       "         0.06873675, 0.142526  , 0.18155628, 0.01093903, 0.13834134]),\n",
       "  array([0.21323431, 0.05829953, 0.19491985, 0.08775652, 0.01096889,\n",
       "         0.0121968 , 0.10049191, 0.18635472, 0.04637766, 0.0893998 ]),\n",
       "  array([0.18084342, 0.01531634, 0.11700155, 0.00980963, 0.12935608,\n",
       "         0.1084728 , 0.16465622, 0.15931483, 0.10500723, 0.01022189]),\n",
       "  array([0.18217085, 0.01054827, 0.17545644, 0.11673187, 0.12011282,\n",
       "         0.06740919, 0.12449346, 0.08116339, 0.00725569, 0.11465803]),\n",
       "  array([0.25558114, 0.16005126, 0.0351755 , 0.11716415, 0.09296201,\n",
       "         0.05241595, 0.06782466, 0.02882028, 0.00513018, 0.18487487]),\n",
       "  array([0.17866776, 0.03725448, 0.13476633, 0.1406295 , 0.19311746,\n",
       "         0.09657738, 0.07829468, 0.02482297, 0.09285965, 0.02300979]),\n",
       "  array([0.05469794, 0.11185323, 0.15229814, 0.1182524 , 0.03393173,\n",
       "         0.08447292, 0.02211322, 0.1478366 , 0.15666219, 0.11788164]),\n",
       "  array([0.20485943, 0.037932  , 0.03179393, 0.12861953, 0.09436224,\n",
       "         0.14023043, 0.00651804, 0.03909547, 0.18811406, 0.12847486]),\n",
       "  array([0.11373155, 0.16514064, 0.11267349, 0.01111252, 0.10469415,\n",
       "         0.0680973 , 0.17196459, 0.094864  , 0.03896331, 0.11875845]),\n",
       "  array([0.07451006, 0.10612945, 0.04760325, 0.03191719, 0.16124312,\n",
       "         0.05130616, 0.14348061, 0.14207844, 0.06039007, 0.18134166]),\n",
       "  array([0.08678193, 0.16405867, 0.00711133, 0.12406191, 0.13282726,\n",
       "         0.05212918, 0.07482039, 0.15407259, 0.05481787, 0.14931889]),\n",
       "  array([0.17109833, 0.04961803, 0.02089413, 0.0761797 , 0.02671954,\n",
       "         0.14508052, 0.13284526, 0.15569619, 0.05306937, 0.16879893]),\n",
       "  array([0.04132129, 0.11011551, 0.14449747, 0.12789965, 0.16203963,\n",
       "         0.00985717, 0.07692267, 0.14591718, 0.06454798, 0.11688145]),\n",
       "  array([0.02709857, 0.10501085, 0.07900816, 0.13837497, 0.03327491,\n",
       "         0.1688705 , 0.05861381, 0.1843428 , 0.17271109, 0.03269434]),\n",
       "  array([0.19009332, 0.05265951, 0.13045178, 0.01375346, 0.08174481,\n",
       "         0.06033619, 0.19065492, 0.1310321 , 0.09570433, 0.05356959]),\n",
       "  array([0.17431643, 0.10827034, 0.17958351, 0.04354991, 0.17881418,\n",
       "         0.02820848, 0.0984047 , 0.06243497, 0.03663482, 0.08978265]),\n",
       "  array([0.02559706, 0.11453335, 0.01519244, 0.14723653, 0.12452282,\n",
       "         0.15254935, 0.0055397 , 0.13288804, 0.12668364, 0.15525706]),\n",
       "  array([0.10794993, 0.01652404, 0.02459562, 0.10510014, 0.18639997,\n",
       "         0.11610261, 0.16468388, 0.01414721, 0.16915579, 0.09534082]),\n",
       "  array([0.00246817, 0.12586399, 0.21630199, 0.06671084, 0.13288544,\n",
       "         0.0055992 , 0.10550459, 0.1031519 , 0.08294561, 0.15856826]),\n",
       "  array([0.05494329, 0.19614101, 0.22760015, 0.01629745, 0.04308616,\n",
       "         0.17863822, 0.05461068, 0.01535941, 0.10868462, 0.104639  ]),\n",
       "  array([0.06538286, 0.15446892, 0.14056003, 0.01030605, 0.18111848,\n",
       "         0.11336031, 0.1446684 , 0.12287524, 0.05870889, 0.00855083]),\n",
       "  array([0.01465805, 0.18045164, 0.18456722, 0.10549984, 0.06648088,\n",
       "         0.07853002, 0.19548417, 0.02840443, 0.14151915, 0.00440461]),\n",
       "  array([0.1340934 , 0.09857616, 0.18943314, 0.12214076, 0.05332166,\n",
       "         0.05239469, 0.13872235, 0.0331421 , 0.02385813, 0.15431761]),\n",
       "  array([0.07797305, 0.14267823, 0.14419712, 0.1010941 , 0.11953126,\n",
       "         0.03754721, 0.0038741 , 0.05186056, 0.22614704, 0.09509733]),\n",
       "  array([0.17645809, 0.0690575 , 0.03108424, 0.05070166, 0.03337201,\n",
       "         0.0954589 , 0.14493383, 0.14882511, 0.2025763 , 0.04753236]),\n",
       "  array([0.12936392, 0.05872755, 0.12455744, 0.0936437 , 0.12305644,\n",
       "         0.13270048, 0.05959047, 0.10595395, 0.04897952, 0.12342653]),\n",
       "  array([0.0841279 , 0.11423286, 0.02418887, 0.09592404, 0.10236484,\n",
       "         0.10591897, 0.16692178, 0.04300236, 0.14086455, 0.12245382]),\n",
       "  array([0.08833364, 0.0927477 , 0.14916551, 0.15738666, 0.01542564,\n",
       "         0.10858473, 0.14464993, 0.1152233 , 0.11829815, 0.01018475]),\n",
       "  array([0.11589737, 0.00781403, 0.00750522, 0.1522039 , 0.13896155,\n",
       "         0.15102605, 0.08344973, 0.13776778, 0.13116347, 0.07421089]),\n",
       "  array([0.10983777, 0.11829077, 0.13866346, 0.02648537, 0.00453153,\n",
       "         0.16822739, 0.12862823, 0.0348992 , 0.20262756, 0.06780872]),\n",
       "  array([0.15181022, 0.09323981, 0.170544  , 0.01853312, 0.17805016,\n",
       "         0.06853808, 0.04235512, 0.01262092, 0.17185556, 0.09245301]),\n",
       "  array([1.64953716e-01, 1.90873412e-01, 1.06574974e-04, 3.98013880e-03,\n",
       "         8.86738523e-02, 2.38050759e-01, 4.88574176e-03, 2.33166210e-01,\n",
       "         2.25364168e-02, 5.27731788e-02]),\n",
       "  array([0.00395326, 0.0881402 , 0.03741094, 0.07666926, 0.0696539 ,\n",
       "         0.08275892, 0.16967833, 0.17478523, 0.17079624, 0.12615372]),\n",
       "  array([0.03531529, 0.11664355, 0.03513399, 0.06484236, 0.1506378 ,\n",
       "         0.01077521, 0.13092267, 0.14056352, 0.17696534, 0.13820028]),\n",
       "  array([0.14316375, 0.01532794, 0.0832607 , 0.12964097, 0.12222655,\n",
       "         0.11286999, 0.14250349, 0.03209382, 0.09226243, 0.12665036]),\n",
       "  array([0.08451629, 0.11540364, 0.05520054, 0.10606425, 0.05372598,\n",
       "         0.00965994, 0.15668624, 0.15403229, 0.10847533, 0.1562355 ]),\n",
       "  array([0.13780382, 0.13451044, 0.02025485, 0.13874527, 0.15807333,\n",
       "         0.05590489, 0.03647011, 0.09145491, 0.1084345 , 0.11834789]),\n",
       "  array([0.04678254, 0.08501236, 0.05075969, 0.16725875, 0.1236572 ,\n",
       "         0.1009111 , 0.00159288, 0.02619061, 0.19905331, 0.19878156]),\n",
       "  array([0.11155638, 0.05647811, 0.1158769 , 0.11931287, 0.1697776 ,\n",
       "         0.08518192, 0.19184025, 0.1093078 , 0.00836325, 0.03230493]),\n",
       "  array([0.19186053, 0.09044691, 0.03548495, 0.15438165, 0.17645   ,\n",
       "         0.07173303, 0.00144406, 0.02632447, 0.10973395, 0.14214045]),\n",
       "  array([0.06267345, 0.15576047, 0.04763074, 0.13018616, 0.05531776,\n",
       "         0.0112007 , 0.17689239, 0.0021719 , 0.17996634, 0.17820009]),\n",
       "  array([0.08409018, 0.00561239, 0.10033118, 0.08954145, 0.06536282,\n",
       "         0.06592096, 0.14713297, 0.15423766, 0.15606872, 0.13170166]),\n",
       "  array([0.16535247, 0.06693312, 0.09583734, 0.06868185, 0.06376625,\n",
       "         0.10142641, 0.01348243, 0.17336709, 0.05465195, 0.19650109]),\n",
       "  array([0.18222757, 0.04604125, 0.13937637, 0.00181643, 0.04636979,\n",
       "         0.1431317 , 0.08352766, 0.16638391, 0.16470413, 0.02642118]),\n",
       "  array([0.20759664, 0.10318996, 0.14437318, 0.00153668, 0.13192291,\n",
       "         0.04450091, 0.05754869, 0.05522436, 0.14888608, 0.10522058]),\n",
       "  array([0.12063368, 0.12449786, 0.18473222, 0.132115  , 0.1714339 ,\n",
       "         0.11274651, 0.04941458, 0.04300001, 0.02654252, 0.03488372]),\n",
       "  array([0.13670028, 0.11981673, 0.04954569, 0.06235241, 0.04249178,\n",
       "         0.04432536, 0.0792099 , 0.17189239, 0.18488557, 0.10877988]),\n",
       "  array([0.0052904 , 0.0687146 , 0.15741252, 0.12522455, 0.1480048 ,\n",
       "         0.0942357 , 0.14196717, 0.1306195 , 0.00535582, 0.12317495]),\n",
       "  array([0.14649788, 0.14585687, 0.03420978, 0.04946841, 0.06283472,\n",
       "         0.10257779, 0.09243968, 0.12594614, 0.1411642 , 0.09900453]),\n",
       "  array([0.05622334, 0.00243648, 0.13144417, 0.10690451, 0.16692221,\n",
       "         0.16049311, 0.13170968, 0.09023873, 0.10873094, 0.04489684]),\n",
       "  array([0.13227732, 0.11323541, 0.0723008 , 0.02606157, 0.15455196,\n",
       "         0.07661428, 0.14572296, 0.04948988, 0.18663005, 0.04311578]),\n",
       "  array([0.13948739, 0.02382285, 0.10376829, 0.05398243, 0.09813079,\n",
       "         0.03700858, 0.18541715, 0.04315651, 0.17850752, 0.13671848]),\n",
       "  array([0.10905316, 0.07852891, 0.01461768, 0.01968229, 0.13007897,\n",
       "         0.05593072, 0.16881881, 0.15538188, 0.14754618, 0.1203614 ]),\n",
       "  array([0.17696909, 0.00691735, 0.20615344, 0.15672133, 0.15140178,\n",
       "         0.04865053, 0.0345249 , 0.00590242, 0.02739261, 0.18536657]),\n",
       "  array([0.14042816, 0.04889373, 0.09493065, 0.04326792, 0.07754424,\n",
       "         0.15217186, 0.19098058, 0.12865277, 0.01669547, 0.10643464]),\n",
       "  array([0.01558708, 0.10279952, 0.07025234, 0.16593497, 0.0214641 ,\n",
       "         0.05475168, 0.14608688, 0.18592205, 0.13337878, 0.10382259]),\n",
       "  array([0.16987505, 0.0787186 , 0.18185074, 0.00889731, 0.22094808,\n",
       "         0.09567615, 0.01185454, 0.11609493, 0.10830389, 0.00778071]),\n",
       "  array([0.1624777 , 0.0407787 , 0.13428177, 0.15867581, 0.11750585,\n",
       "         0.12568631, 0.02110866, 0.14227316, 0.07656854, 0.0206435 ]),\n",
       "  array([0.04907604, 0.15106167, 0.01736232, 0.18924981, 0.17791786,\n",
       "         0.11318508, 0.03194402, 0.02166581, 0.11251217, 0.13602524]),\n",
       "  array([0.01406416, 0.09376468, 0.19221183, 0.0643647 , 0.15434257,\n",
       "         0.14485943, 0.13288639, 0.03724747, 0.08746668, 0.0787921 ]),\n",
       "  array([0.0922495 , 0.00428849, 0.09805901, 0.06732334, 0.202352  ,\n",
       "         0.09246199, 0.16375345, 0.11057068, 0.14420297, 0.02473857]),\n",
       "  array([0.16799648, 0.07147752, 0.00632314, 0.09985541, 0.15852442,\n",
       "         0.03611381, 0.10246027, 0.19079898, 0.05260444, 0.11384554]),\n",
       "  array([0.11022659, 0.00564455, 0.18321353, 0.17849662, 0.07392299,\n",
       "         0.20316059, 0.03897384, 0.09837106, 0.00064598, 0.10734424]),\n",
       "  array([0.20509087, 0.07843359, 0.14263926, 0.02354766, 0.05290036,\n",
       "         0.16375955, 0.10111938, 0.10620559, 0.10085835, 0.02544539]),\n",
       "  array([0.14652227, 0.13632645, 0.06657642, 0.17187011, 0.12949372,\n",
       "         0.15251211, 0.00988741, 0.03318292, 0.02977214, 0.12385646]),\n",
       "  array([0.02638758, 0.11491186, 0.13767136, 0.05791448, 0.1363802 ,\n",
       "         0.12740337, 0.10811469, 0.10236888, 0.09372318, 0.0951244 ]),\n",
       "  array([0.02476369, 0.09313117, 0.07724799, 0.10605613, 0.10441385,\n",
       "         0.04058551, 0.17830957, 0.0876468 , 0.1164281 , 0.17141718]),\n",
       "  array([0.03135659, 0.13074268, 0.11625298, 0.03528752, 0.11040392,\n",
       "         0.06898597, 0.12686117, 0.1148045 , 0.10473239, 0.16057227]),\n",
       "  array([0.17749605, 0.12023795, 0.19481185, 0.22089279, 0.01781004,\n",
       "         0.05753799, 0.01976775, 0.00909795, 0.03219062, 0.150157  ]),\n",
       "  array([0.19100132, 0.17676192, 0.02268892, 0.04050949, 0.16742623,\n",
       "         0.06531871, 0.06027632, 0.17016865, 0.07467832, 0.03117012]),\n",
       "  array([0.00456929, 0.08996042, 0.00837456, 0.05542808, 0.04423269,\n",
       "         0.17968295, 0.20054057, 0.21634663, 0.08638043, 0.11448437]),\n",
       "  array([0.0065602 , 0.00335797, 0.1364931 , 0.13509822, 0.11680957,\n",
       "         0.04544636, 0.20138423, 0.05321872, 0.2048429 , 0.09678873]),\n",
       "  array([0.00888117, 0.06977789, 0.14355272, 0.04068438, 0.2006082 ,\n",
       "         0.13580031, 0.03962016, 0.09478016, 0.01762805, 0.24866696]),\n",
       "  array([1.60981081e-01, 4.77946083e-02, 6.72867535e-02, 1.45019929e-01,\n",
       "         1.41662203e-04, 1.46436634e-01, 7.48956466e-02, 9.46331685e-02,\n",
       "         7.91049789e-02, 1.83705538e-01]),\n",
       "  array([0.00606513, 0.14365662, 0.20308967, 0.22269123, 0.03908114,\n",
       "         0.12672761, 0.04717374, 0.05340889, 0.10496805, 0.05313792]),\n",
       "  array([0.05299615, 0.04920596, 0.08828868, 0.08384212, 0.09939781,\n",
       "         0.13258954, 0.10357191, 0.00861616, 0.19782116, 0.18367052]),\n",
       "  array([0.02567479, 0.06601139, 0.04794084, 0.12286512, 0.05400727,\n",
       "         0.03537507, 0.13833499, 0.22264399, 0.03464051, 0.25250603]),\n",
       "  ...])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "number_ports = 25000\n",
    "number_assets = len(assets.columns)\n",
    "Rf = .015\n",
    "weight_log=[]\n",
    "port_info = np.zeros((3,25000))\n",
    "for x in range(number_ports):   \n",
    "    weights = np.random.random(number_assets)\n",
    "    weights /= np.sum(weights)\n",
    "    #Save Weights\n",
    "    weight_log.append(weights)\n",
    "    #Expected Returns\n",
    "    pret = np.sum(weights*log_returns.mean())*252\n",
    "    #Save Expected Returns\n",
    "    port_info[1,x] = pret\n",
    "    #Expected Volatility\n",
    "    pvol = np.sqrt(np.dot(weights.T,np.dot(log_returns.cov()*252, weights)))\n",
    "    #Save Expected Volatility\n",
    "    port_info[0,x] = pvol\n",
    "    #Save Sharpe Ratio\n",
    "    port_info[2,x] =(pret - Rf)/pvol\n",
    "    \n",
    "port_info,weight_log "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(                       GOOGL    FB  NFLX   AMZN  BBBY   COST  DLTR   FOX  \\\n",
       " Max_Sharpe_Allocation   3.06  1.87  24.7  26.07  1.08  12.29  5.43  2.92   \n",
       " \n",
       "                        Gold    PEP  \n",
       " Max_Sharpe_Allocation  5.29  17.29  ,\n",
       "                     GOOGL    FB  NFLX  AMZN  BBBY   COST  DLTR   FOX   Gold  \\\n",
       " Min_Vol_Allocation  13.48  0.43  0.05  5.81  5.71  26.73  3.45  5.59  12.31   \n",
       " \n",
       "                       PEP  \n",
       " Min_Vol_Allocation  26.46  )"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_sharpe_idx = np.argmax(port_info[2])#Provides index location of Max Sharpe Ratio\n",
    "sdp, rp = port_info[0,max_sharpe_idx], port_info[1,max_sharpe_idx]\n",
    "max_sharpe_allocation = pd.DataFrame(weight_log[max_sharpe_idx],index=returns.columns,columns=['Max_Sharpe_Allocation'])\n",
    "max_sharpe_allocation.Max_Sharpe_Allocation = [round(i*100,2)for i in max_sharpe_allocation.Max_Sharpe_Allocation]\n",
    "max_sharpe_allocation = max_sharpe_allocation.T\n",
    "\n",
    "min_vol_idx = np.argmin(port_info[0])\n",
    "sdp_min, rp_min = port_info[0,min_vol_idx], port_info[1,min_vol_idx]\n",
    "min_vol_allocation = pd.DataFrame(weight_log[min_vol_idx],index=returns.columns,columns=['Min_Vol_Allocation'])\n",
    "min_vol_allocation.Min_Vol_Allocation = [round(i*100,2)for i in min_vol_allocation.Min_Vol_Allocation]\n",
    "min_vol_allocation = min_vol_allocation.T\n",
    "\n",
    "max_sharpe_allocation,min_vol_allocation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ZizmIepF4BSI1i2/QoyAliIYRSVA3DJqfegPxEBIPou3dFp8lPZzM0Sqadk1X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Y1/YTGlCkkSo90WGvaw968jlaqrkBB2CS69MNYnH7ZxBGEbM7uEbTdIdjd+7YAr2rxDfO86EhQo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PkDb7BEtVvJkSSaPH5jfeQSiJTnJmPnUYt1ZCFfoopxrgzZZZ+OIpolstvLkS4YHJfMa9kI4i\nWL53hUPa7ONUfVToEvfa6CibEq4ppngPyPsprdfXf9iX8WEjM8b8L/d78JRwfQyQ95PbwnqdSjj0\n8tJZjpCShS9/gt7FmzRfusTCv/0kupfR6lyhemKFtBsz/7lTyJKHKgf0zm3gztdILmzQvbZjSVVu\ny0F5lCGMIEsyJrIKDaAEJi0qRFqQG1BSonM9iuEZVIckxd8IZkiYTEFIxi0ARuuPt/TGBF5GjLUD\nxaCjCZh9pxonIIrrcZWtbJEPC1hGj9a0+xbGpRP9U4NG2vZp8ZgGg4wjh3lL/ERBumQpRPcSjB60\nYocMzV5/LkAJpHIw2lA+uoTONX1tz5W0IrKrDYQr0UYjpbX/MEicmRCnFJD3UxAuSbOLv1zFO1JC\nIIgbPeROH+U76DgnT3Oqq3OUT6zQeu06/fUW3kxI5fQBSDXRVpus2ceUA27+wZv4y3VmP3mI8PA8\nnUvbJNtdnEpAf73FrT94E+EKOme3cMs+M0+v4c1YsjROmLJWBAa8+TLJbo+8GzP3ueN03rqFt1il\n/rj19vEXKvjvoql6P6ieWmH7uxdJW32CpRpO9YPz1JpiigcFD0pLUQgxV9z8f4QQfw34v4B4sN0Y\ns3Mv60wJ1484+td2aLx4AWMM5YeWqT9xe2CvdBTlh5bpnF3Hnakw94XTkGiia9t4c1WizQ5ps8fG\nH71B1optNQrNwhcfQaea/s1dUsAIg8k0ebsPUhHMVdHKsWampgi8TqEQXNmTa8gzA0baRpcG4wg7\nsZdTVMTExLTXgGzpYVlrJDYHQBhLkoYtTIbbhlWpYWVspKWya489MUW70BgQ2tgJzIFL6aAVacbW\nxeqShiOMZuArNnYCPfkmNIjzMUW7UgymJlVx/bpoa45Vw6QxKNfDWaoy++RhOm+v0z1rK4kmMyTN\nCBW4xZScgztTpnJghniri05S3FqIjlJ615sIV5H3c9JuSrhSJ720A55C1QOEgbQV0XpjHeV7uHNl\nVOBRPjbP3KePkbVjFherIKB15hb+co3oRoPtNEfHGQe+8gku/dZ3yaKU3mvX0UlG4411SgfruAsV\n4p0O/kKVrJtQf3SF8lGr3XJnSqBkobmCYLlGsFwjXP7wsgNLh2ZxawE6pCeO9gAAIABJREFUzXFn\nSnecCp5iiin2hwpd6o89MC3FF5kU8v6tsW0GeP9O81N89NF6/QpOLUQ4it65W1ROrKBC77b9Ko8e\nIlibBwSq7JNsNAmPLbP9J2esRUSU0fr2OaQjcaoBWScmODhL79IWSTMiyzQm1hjhgNYYBP2Lu9hg\nP8ZYhrRcq2jBIQcVMDEiMZph69FiMnJnmEkoR7YOljgVOwhlCcqQXRWkSMgxz6sR7Zlwqh+0Gce6\nmkARvD24cBAK0AKDGVbWhBQYIVBKgK/Q7WS0vpFWwyQoSJRlXkJKDIXRqxTW1bxjLTsortdIMJke\nGFJgXBdnvoKSLk6tRPXRNVpnNu3EoskxqSYnAyQycFCzFaL1NsluD3e2RN5N8VdqZN2MrJeQdWOy\nXoJbCqmcXKZ9Zh2nHFiH+M+eQKc5zdeusfjFU+gsp3+tQdqMWfziSZTv0L20zVDjJqwQXkiJTnOU\n7xLdaqHKLibRZL0YVQ3I2xHttzcAgVsL2Xn+Ct5CBbfi49YClr98ini3i1sN8edv11z1rjXYfema\ndXr/7BG8+v7JC+8H7g9gzSmmeFCQ91MabzwYU4rGmHubqrkLpn/W/YhDhT55L0ZHCfF2h61vn6V9\n9uakpgmrPcoTG5DbeOES7kyFmSePsPClx3CqJaTjgIGk3ae/3iLZ7tJ86RLSc6idWsWfqyMqJYTv\ngnRs21ADuQAUCAekiwxccFwM1vjUZlorTC5ACmQ9BOWQa4XBkpGB5msgMrfO7gKDU9gtDKwc7O2B\nUF9r6wg/zPQq9GFW0zX6Z1uBsqi6CbQW6FxgcoHOJPieJUUKG04sBcL3iqDi4ldkUJWSElEpgeOj\njcQoBUbZc2Vg0kIHVpzPIBElt6ikKUsWNfZ5cRyMKvRXKLRQBWmEtJOSxxnRlV2irZ597FrbcxiG\nE4/B8iy9S7tksd0fBKXD84Srs/hLVdxaQOnIAu5cCacaECzUKJ9Y4cCfeYryiWUQAqfksfDjJxFK\n0r/aoHpqhaTRZ/uFy2w+d4Gk2SdYqhBttPCXqsx/9ggycNn61nmcio9QEiEV7kIJ5bt0zm7QOb9F\n0opACKSnLHHNRhpTtx5SObqwL9nK44yt71yyU4txxs73Ln+gvzNTTDHFBwQjPph/d4EQ4meFEG8L\nIc4JIf72Ptv/CyHEm0KIV4UQXxdCHBnblgshXi7+ffV+HqYQ4tNCiJWx7/+CEOL3hBD/41i78a6Y\nVrh+xDHzqWM0X7lMtN6w3lja0Hz5Km4lIBjTzeg4Y/dPzyF8l6wVsfvSZRY+f5LaY2ukzR67371A\neGyR5ouXQKdQDoh3ImQ1Q8cpyW4Pk2hrppmnloC4RVUn0YjAxWQaowWy7KPKHsmtDqrkgOuSd2JU\naH2W8kQXBaBBVI8YVqWEUJZAKYrK2VjgtbAastFE4ECkbuxaRYHKrimHpHMw8WgGE4fjthJA3skR\njq3gqKpvdUNC0b/RxHStJ5RwhK14ZZBFmrwVQ15Uwsa5rbLxODgSoYuGYmbQGUBeTCxKlJC45QC5\nEiCVpHt+y54jB7Qk7+YkpZTtV6+TdRK0KzFtW72TJR8RuKhKQJakSFehSiHxRo94q8vs04cpH55n\n9ulDtN/ZsJUpV7L++2+i04zS6gxO2Sfa7tF88xbhwRqnfu3LxFsddG5wqwHxbp/o1jXKx+bpXdul\n/thBFr7wkCVXQlD/xCppO8ZbLLPz3YukzQh/rkx4sEbnSoP66RW615tsfecSlSOzzD5zBLd2bxUl\noy37lq4CY8jT9zwMNMUUU/yAoQKX+mMfXLTVnSCEUMD/BPw0cA14XgjxVWPMm2O7vQQ8Y4zpCSH+\nKvDfA3++2NY3xjz1Pi/j14GfKq7ni8A/AP5z4CngN4A/ey+LTAnXjyh0lpN3E5J2n7yfY1A4YYAK\nPfJObEXTe/Y3mcaZ9dCOJO/YwICsHREemifvJeQvZqh6ybauMoP0PVTJJ+8muIt18mYfGTiIMCDb\n7mCwH4oidAnmy+g0t35P0iHe6GKSDCMlMkuRnosqh8Rb25CNSNOg2zisTknGCJVChgrdSZic/hs8\nqkE/cKSzGnYZh9OQDCcPZcXDOBp66aTnlgCTgfQDdAYqCMmTnCzJ7bUWFhjKlzbUe3cUtjBwqJdK\nYgbZkI5C+i4m19bOIs4xtviEBhzfAd/FPzSLiXOydjzUeLllD2+lTrrbJ9rqkzX6BYk0GAFePcRd\nLiMSgz9fwVuo0L/WwGSa8olFVOCRdhNk6OIv1+mvt3FKLqoasPSlh1GhQ55kbDx3HrShemKJeLdL\n1o1xKj699TY7L19Hhg4zjx3ErQYgBEmjNxFh49VDpKtItnr4y3UO/sKTVE8skLZixB+fs/YO11uE\na/PIio83X75nk1An9Kg/ukLzzZsIJZn/saP3dNwUU0zx4SHrpzRev/lhnOozwDljzAUAIcS/AH4R\nGBIuY8wfje3/HeCXP+BrUGPC+D8P/IYx5neB3xVC3HOu9JRw/Qgij1K2vvkOSaNH5+wt6p9YwxhD\ntNFE+g4qdPH3jMirkkd4ZIHe5S2EEMx8+hjxVofNb75D3kvoXtpCeg7Vxw6RbraJNtoEh+bwF+s4\nlYDy0QU2//AMWTemtFDDeXSVzrkNnJJDeHge4TjEt9pop0fe7CM8F+G7mCRDpxq3VqJ/tVG0xKyu\nSwx4VyG7Gui1xEAPb3K0tkTDDLIXx/yuJh3kgSKGUJQ8a4+Q6glPrLydFhODEoFBj3t2CWEd9XNJ\ncGSO+FabvGft6oUsRP5pIWwfXOtAdeUIG49YiPtVPcSth2Sd2AaCm9y2J40BKQgOzyOVwCkHZCQQ\nZajAJ89zKieXkIFLstMja0TDqCBrsyHJUoPqaMLDswQHqlRPLpHs9MnaMf6BMnknpnxoju7VJjsv\nXSc8WCftpXCrgwodvIUKuy9dpX+jRbrbRx/McSs+aEP36g7khtLaLPFuj6ybEN1qgRDMPT1pNurW\nAuY+fYTrv/8mKMHGNy9w6xvn0UlOeW2GaKONWwuon162GrJ2TNLos/XdK+gkZ+6Tq5RW6+hMk0cp\nTsmbIGT1xw5QOb6AUDZCZ4oppvjo4UOaUlwFro59fw347Lvs/58A/3rs+0AI8QL2E+IfGGP+7/u4\nBiWEcIwxGfBvAX95bNs9v0FN38k+YujfbFrjyVpI7fTKvsG40c0maTvCmymjo4ysG+PPV3FLAXM/\ndgynHCD9yR+tEIKZTx6hcnIZoSRO2Wf35SvWCym1ppjlk0t0zm0QPrpKsNaje6VB/1qL4NAs3m6f\nla88QdqK2HzuHK23b6EcByNcWmc2UYFL7/IuQhh0pkEZnEqITq0bfX6tgc7M8DfUFNOBSDHmh1pM\nO+aWVRkhimgbCb6EOB9mKg66g8DQ22uwnhpqqLCO7WbyjWGoExuW1+ypSQza5PSvt+jfbA+9tawm\ny2Ym2rifIUuzh2ZiOI0IkHcStO/hVkKcsk/v8g5aW2JmBwEMWgtEO0N3U7JuRvn4AjgSb8HG06Sd\n68VjL8hnkU0pHIWq+Egp2HllnZ2XbpDFKcpRxK/cwKn4qIpPvtujc26brBWTJxnGQDBfIu0lCKVY\n/IkT7H7vKlk/Zf5zB/EXK0SbXfI4w6n4OKFH9fgCwYE6vWsNutdaePNl1Bj5SZoRwVIV6SnWv/4O\n0nNxAoet9assfv4o3mzFZiFKKB+etWQrzpCeYvNPL7PyUyfY/PYVsk6MP1di6YvHJtZX4aQvVh5l\nbH73Csl2l/BAjaQZYdKcuWfWKB2YpoxNMcWHCRW6zDz+gbUUFwpSNMBvGGN+470uIoT4ZeAZ4Etj\ndx8xxlwXQhwH/lAI8Zox5vx7XPqfA98QQmwBfeBPivOdAJr3usiUcH2EkLYjtr99Hif0iNbtz3Dm\nidXb9rOxOhokuLMhWTtG+S5znz2ON/fuWXADHU3zzXV2nr9K98oWTtklTzWy5FM5ucLiTzzM9ncu\nkndtLEvajHDqZZZ/5gnO/fo3yVNDutvHVAJ0JybvJIigEJkrifJd0BqdaFAuWZoMzUEZqwwBhZjc\nWH06wladBDavUA4k61ZYqYfHCQoOhHQVJrJETFCsn2kQ1pMKbP4gqR4eOyJHo+sYTUYqmhd3kbke\n7isG9hPSXoNQWNJlDMKTtoqWY/VsucFkxgY7dyJU4EHoIfo5SIm3VKb80BLdc9tIV9Lb7WMyjVsP\nUYFDtN1Fui7OTMkSs04yHApQwrqom1zTudK0rd6aj5QKHAW5IN6JuPEHZ5h9ahV/sYwBOpca1E4v\nUjmxROudTbJegtruM/PkKkJJVn/2UVTgUn1kicqJRdrntxFKoio+7bNbuLWAzgV7vXNPjV6PTskt\nyJzBpAYZStJWRNrN6FzYpXJsjoVnj+DWA9yKT57kKN+x2iwd0z67Q9roE65UiTa6RDc7lA/f2eC0\neeYW0UYbf7bE9d9/i/rpRfy5EpvPXebQLz5q151iiik+FOT9lMZrH5jx6ZYx5pk7bLsOHBr7fq24\nbwJCiJ8C/g7wJWPMuEfW9eLrBSHEHwNPA++JcBlj/hshxNeBA8C/MaOpNInVct0TpoTrIwQd22A+\np2JNGLN2f9/9gpU6tcdW6V/fZemnH6O0NocKnH3tIMZhcusobkXzV5Elj6yTkHUTSgfrYAz1J9fw\nF6tkUUrz7Cb69Zs4NZ/a4wfI+wnxeptweYa8nZA0+7YllBtoR6ANTtlDKIfaJ5bZefEaed+Ky7Ue\nD7YuKjYDCwVHgivR0Vh2YCHI0lIgy65t50k99CU1CIQR5Jm9bQ+xt7RUSEfhlKz+yJmr0ru8jYky\ne245sjewXMqSLekAUloSmdp8IWPM0LJCOg5SKZuHmGTopBBmCW07lxmWKDoSR0i8WkjWz1B+iHFz\nsm6CUw5IGzFpNyE5F5P3UlTZoXu1iVP2mP/cMbJWbD20EOA5CEAFHl49QMca6bjkcYIKPeKtLjKw\nIdRSuZSOziGEQ/30AZTvoQKHpBFROjBDst0lutVm/tNrtM5sMLc6w9IXHxo6rLslj/qjB8ijHKcS\nsPPiDYQncas+ynfIusnE66lydI54t8/Gc5fx5iskO13i7R7eXIhwFcl2b0i2kmZEsFih9fYGTuji\nL5a5/Duv0r3aoHZ6ieqxWYTz7kPTOtVIJRFKYPIc4So7AdmKbTVwahQ/xRQfMu5Nl/k+8TxwUghx\nDEu0/l3g35+4CiGexgrbf9YYszF2/yzQM8bEQogF4PNYQf17hjHmO/vc9857WWNKuD5CcGdCvNkS\n0UYbBNQ/eWjf/YQU1B49+J5zrHa+f5XOhS3SVszuS1esL1QnITw8iztXYeapw3izJRvs+/YmOslJ\ndvuk7Zid19ZZ/vIpwkMzRLfaOPUQVfXpXWngzlUwaYpODKVjc6jAxVuuER6s0720MyQuY4/AEp0i\n0Fl6Dt5MQBolZDv9wrEea26qBOVD80TbXUTiWdPV1LYbcw2iqESNOoMCnVjiJysBJssRjiRcmaF3\nrYHJcmsBUdjJG2NAgqp4+Ct14ustjNGWjJlCbwagBbqvEb5AOQqkwlsqkcUpWaMQ0WsDrrVIyLoZ\nbjlEhh7RbhehJSbRdK+20LFGpxpyjfQV5SOLxDs94nZK+50tln78GCbJ2H5N2ee/GSMcRfX/Z++9\nYmTN7zO95//lULmqczw5TDwcThCDOAwSRXElcS3KC2EXkAEvDGPXC/hiYcO+8IWvjDXsK8PrNYyF\nYSxWG2xJu5JIimEoDeMMJ3PSmZM7VldVV/5y+Pvi6zmTzpmZI3Iocaaeq0b11xW/qnr7F9735Bz2\nYhmtYrH/rUtE/SnJJEVNwGhY6CULu+UiNAXV1ameW8DfGbDw6AnSaYy/O6J0rIHVKiNPSer3r6C/\nzWE9j1KctRqD59oMX2yTTCP6SxXc9Srrv3sPqZ+gOYWyed0s1FmsUD01x8FfXUUqCtPrA9Iwx12t\nFOfQKGTvm5eRWQaKSuuRDXa+fhGhKjgrVSavdJn7+Cr2Yvldz9/KmTnCgwlhx6P5yDp5mBH2fGr3\nLKJas4+yGTN+kRQtxcX3PvBnREqZCiH+K+AvKMx7/qWU8iUhxP8IPCWl/I/A/wyUgH9/lFCyJaX8\nbeAc8C+EEEdhc/xPb9tu/IUy+5T6W4SiqbR+9RTJMEC1NLSS9XO7bikl/o0+UoK/MyAZR+gVi6Dn\noZQt4sEOaZhjtVzctRp5nCF0jVyAiDI6f3kZf2tEFkSkkwDVMUCoZFJBTXJARStrlM8tkfkpo58e\nFO1BVQWRItTX429eH+ICmUmEo2Gt1An3R4WvlWKSH63+CUWglyyyTKC6DqqZobkmaZgSHfjFvBcC\nxaCIHcoFr0cJpqkkaE8xmy5CqATDiBwNqakICVmUoSBBUZBCYM3VSEYxWSJRTAUU9Y3qWy4RWuH/\nIKUkniYoUqCWFZRchVwtHpV2VOHLJYqpEx0GgEDRDJJxgGKo5HFKNAwpnWgi04xkFDLdGZKOQhTT\noPfkDjKHE3/wMZIwZ3K1j1ADknFANAhoPrjGdGdEPAyJh0lhZeGa6CWHxoUlop6Pkguu/qvnQYJZ\nczjxBxfQaxbe9oDh8/uE3Qlmq4Q1XyKL0mLT9GhgvXyqxe7XXmV8qYdqazfnxfy9CRf/j59g1Cxq\ndy1gVEwqZ5oE7SlCV0jjFJlLjJqNZnnIuKgQJuOoEMNZjr1QLoTlIEBIidAUrIZNPIpAU8nC9KaY\nuxVG1WL5S2fJ4wzV1sjjjDzJ0dxZaWvGjF80WZAw+OnBL+S2pJRfA772tsv+hzf9/IXb/N0PgXs+\n2Hv3/pkJrr9lKJp6y/w4b2tA/9kdVEOj9YnN9+W8LbOcZBKhGBqao5Nnkt0/fQmZ5WRRintqjizO\nMOoO6TQ+avWUj9o8i3SeuEHqpQghkHHM8MU2RtUi8WMUr4h30Ss2qZdgLZeo3bXM8NldtIpNFmSg\nimKAO8mQcUae5YjXo3NUgTbnomoKiqmTRDmKECiOgfTiwvldhXSc4kVjjLJR2FS4OqgpaTUjm8TF\n0L2hkIfxkW2XgsgkMpNkeYbMJf7elHQUF1WlN41vSUU5mvsSZEGGMHWEphfZk2bhK1b4OCiorkaW\n5GTj+KhtCVHHR1gaqmOiaArxuLDoUHQVwqy4XIDIFFI1QbMN0nFAPI4J9iZodat47J2IbJph2KDX\nXGQO7maTLMqIOh7CKIKZtYpDNIzJxglG3SUeRcgkJ53GREJBmDrl4020qsX2f3gFd6VK4kXc+OOX\nqJ2fJzzwyHNofnyZ8maD3k92md4YYlRNFj5zDN01cNdqrPzmWcaX+uRJQtQLSLNCcNlLFUavdIgG\nAa0Hljn43nVKmzX6L7TRLAOhQuYnKKqC0bDJwqOZLbMQpFHfJwszzJbD8m+c5tofvsDwpS7mvEt4\nGND+q2usfPHUu9pHKJqCctR69HfH9J7aQzFUFj+9gdl07uzNNmPGjJ+NX9Ca4oeFmeD6JSALEw5/\nsoVescjClMMnt1j6tTNvOSYeBnjbQ/SSibtRR+aS7g+uER5MQFFY+MxxUFXMZgm9YRPsjfC2RmRe\nijaJSSbFcHYWJAhFoJRt3I0W8WCPXBa+8RwZr8ukqCwUeYASYWgYVRdzqcL41R7+7oTYiyit19BL\nJkmYg0yQSeE3JShMRDM/I5c5iTchi0DqOXLwun+YRJh6cTuRJAxTUEIUVUGxNVRNR5QVFKHQfGSF\n4U87xJOILMrIg4R8UszDxaND9IZ9VFF7w0oCoRRVtzSDXBZbiVlhnyHRUDQFVRekUQKpIA0kWZAW\nTvMCFF0pnO69BKlpZGFG+VQLq1kCXRAfBvh7Y8rnFlBsjeEzu2RZjrANTNsgjQV5L4Isx1mrMH6l\nS9QNEc2iyrT/2FWiwwDVNci8BExB88IqWZIghSD1ElRHJ/NTpBQYDZvej3cwqhaVs3PIVCIslXQa\nM3q5S55InOUScS+g/dh1ovtCvGsD7KUS0aHP+NUezQeKFrW7VuPkf/4A1/7wecJegFAUFEMlSzKy\nMMPfHTMwNYyyCYqC6hg0H1whGUVEhz6KqlLaqGHWbYyGjWpqLH3+BEF7gtGwcVeKzMS7/umnufbv\nXsReLCMUQdCeFluSR9uJaZAwvTFCUQWlzdpbhuKzMKX35G4h7KKMzhM7rP3m6Xd5D6WIN4m1GTNm\n/Gyotk7tng++pfhhYia4fgmQUt5sayn6ke3Cm0j9mPZjlwtX7jgji1PMpkvQnmAvlAkPPfa+cRHF\n0tAbdlH98TMqdy2QDEOEplA6Podiaii6QvWBdQ6f2sZdb+JtjQrT1KTwkpJZcT+0kk4WZGSRRHMM\nlJJN74c7RTSNoZF1JgRdD0VRScdpEWmDWgzLKyrCUFAMg3SakHlRYckQF49LWAokOblXtCI1Syu8\nr2JJluTFlqGSobsGK791jjyUmEsx0fiANCwG65UcMIAY0knE6/NaQlcglai2hlAVMrVwj8/iovol\nw5Q8AaoGCqBZJpmfkIV5scmYSbKj1qIwFAQqimNgzTmc+i8eJtydMLrYQaQQ9gIGL3WwF0vU719F\n6IKo7+PvTiFKyTLIgwTUEL1qQQ56w6V0Zp5L/+dTJMMQo2niLpRRdRXN0QmuTwvRZ+hYZasQhV6C\nomnYy1WiQcjghQOq9ywQdTyScUTzoRW6P97FKJsEnSlGo7CHUAB7sVSYtb6tqlQ+3qR6fonWI5sE\nnSn737xENIwwWw7WSpl4EFLarJFMY+JByMEPtgnaUxr3LmDOlcgTydKvnUQ9siex5lysubfG+Ci6\nSvV0i9HFHghwlio3Z7FkLmn/5XWiYYjMJUHXZ+ETb8w0FukCFBXO133SbvXeySW9p/YYX+6jOjpL\nn9nErP/8WvUzZnxUKVqKvxDj0w8NM8H1S4BmG1TOLzB66QBFV2i9zXk7nUTkaYY9XyaZRkSdKc5S\nhTxK2P32JYbP72POl5j/lQ2clQZmy8FerGI0HSavdoj9GG9riKLr2PfXkErxJS6zDHuhjExTkijD\nWa5iVCyErWM3bXpP7hRh165J7qekfsp0Z4RRN0ExyGOJYokiDijNi5xBIRG2KBzWkwDCom0nj3y0\nBBKyogohj/zCMATZOCLPJAoCtWagGCrucolgz2dybUDYnYJUEWRIVRTty5iipJWKI0d4gUwK0VW9\nZ4UszZhcOiQLoyODVEke5ghdJY1SRJyjuAZ5UMwnkVNYXxhFpmMe5wgpUBJZGIYulGnev4xWMWk/\nfp1cUZEixz/w0aoO9/7TT3Lwoy32v32VoONhVUySMCEZRehli9q5eTRH5/DH25hNB9VQCPYmVI81\n2fj9u1GEQjSMUPQEd72O357SeHANIXO8GyPCno9aMrEbVUqnGsx/YhN/d0wyiYtsxiRHZpLUT/D3\nPUqrZaKej9lyqJxtveWcKoKyJaqpYc+XWPzcCeJBiKIKhKURDUIUTUcrFd5g8SAk81P8tsfab5w6\n2sh8Y2s2mcZEhz6aa2C13mj9NR9Yxl4uQy6xF0scDbyShWmxXblQQmY5/s6IN2+Ga7ZO88Iih8+2\nUXSVhU+v3/K9Ew0CRpf62ItFC3bw4gGLn9645bEzZsy4E8TNDfEZ74+Z4PoloXbXEuUTLYSqvMNv\nSK8WkT7BQWHWWbtrEb1iITQNf3uMYmqITBJ2p5RPtFj7yt2ML3YZPL+LXrNIJjHls3OUNhvsffMS\nRs1GaApGs0RroYxQFfy9CQufPkaeFM7g9nKZLMhxVqscPrWDtzPCbLmoB1PiXoAQCtZCFVUXeDtj\nsjApKikq5ElWDKHrCpkfAxKRH+UiQtEOs3WEFCR+Bn5RqRBSgFkMV5stB71RVEyMqkl4MCWNC+8v\nKYuPAamCah3ZQwDJNEUxFKQAf3+Ku1EjC3PyBISivOFyr4ojcahAWvQhhUqxFakIBCpauZiJE0hU\n10CxdMz5EpprFC7zfko6TlBMBZlJ/O0xoysDVNukcn4eb/cKsZ/QemgVoSok4wjNNdDKBvEoQlFV\nnI06etnm5D/8ONaCS++pfbzdMcH+BGelUoSBGxqrXzzJ5FqfS//yOdLAp7RRZfRyl3gpwtsakE4T\n3LUKaZgS7CdoCDI/obReY/3vnrspct6Mvz8h9lKmT+9TWquw+punMes2k8t99v/qOrXz8yiqQtTz\ncdZrkOeEbY/UT5huj6iead6sbqVezM43rpBHhS3H0qMbuCuFUalQxM2f34xqaZhzDv7+BCkl1dOt\ndxxTPTNH+XijeE3UW7cKhRCFm1peiOL3sp6YMWPG+0O1NeqzluIdMRNcv0S87pd0q8uXPn+SqOuh\n2jrWfDF0r1csnNUqWZAQHkyJuj5LX2gU4cNn53FWqyCh84Mbhdu8lCSjgPKJJoquMr02xD3WoHbX\nHNbWiKjnk6c51lKZ6dYEqapEPZ/SiWJQW6/YxdyRrRENQ8Kuh+boKKZWBBDnEpmBREHRBCIRKJZO\n5h9F7gDCUBEUFgp5ylHuz1F4tKYWbu9a4eslpUp4GJAmOWE/KNqCOSAVcopYnjwUoEmEWhipqpaB\n6mqEhyFR/wDF1UmDo/wfFVRXIw3TIlvR0UinadG2ovD5UjUNmedFhrZabB1mcU4wjtn604soqkoy\nCbEXKwxf7RH2fDTXxJwz2fn6FSqn6mi2SeXcPGmQ0HuqjeaalI9V8Q88OCiMUMPuFFcps/n37sJZ\nLnPlD1+k/2ybPM2JhxHGXPH8ZEFK50c7KLrK6pdPM7ncZ/hSD3e9irtWYfhSl8RLqJ1rFs/lUdZj\nnkrSKC/yHt+WZhD2fDo/3MFZKKGoCrXzc7jLhSiqnZ+j/1IXvWSALITR3ANL7H/nGua8S2OlwtKv\nblA+Xr/ZpowGIVmU4iyWiEch3vbkliLrzQhFsPirm3g7YxRNwV25tWXEe5mdmg2b5v1LDF7qYNQs\nGvcsvOvxM2bMeH9kQcrghV/MluKHhZng+pCgOQbaxluNT1sPrzMafI+XAAAgAElEQVS+0se7MaR8\nqsnKb5ym+cAbTuH6kcFq6+E1uj+8QeYlzH1yk7DjMb42IA8zjKrF+LVDlj57jLgfIEyVw2fa6K5B\n7dw8Yddj/SvnyPyE8Ws9jLrJweNbJNMMmeXoJZXymQVGLx+QpjEIiVQFqmOh6kphP6GopK+HbUuB\nzPIjQ/qi6gUg4xwlA6zCVT3oBcSjBMVQSEYhimOSRhFSvr6JWKRgK6ZGFmdYDRtp66iGhmqq1O9Z\nYPTaIUiJNeeSBgnWgoNRsxlfGpBmMYpUCgN5W0fRFNJpjHO8DmlOMk0IhxG6peFs1EiGxWYlhkbU\nC2g+sEQ0jo7WphWSSUKW5nSf3Edzj7ZG06NtyjDB255gNEzCA7+YiTM03PUaC59YJx5HhL0Ao2Gj\nmCpJULTbjIpF/e55wl5AFmXoFYP6hUWEqWLPlfD3JghDoXFiHn9vyuKn14ukAVG05PovdkiDhPpd\n88w9uFzEFkmJvzch9VLsRQ29ZJCG2c1zRqgKrQuLHD7TBilpPbhM9VST+U+skfkpZsN+hyeWXi5y\nEqN+QBqmWC2bPMtJRhGqrd0ckn87qqFSOV7/674lblK7a47aXXM/8/XMmDHjDV5PwJjx/pkJrg8x\n1pzL2X/0CPEoLL7ENYX+823iYUjlTPNm1cKs26x++SxQtO687SFplGFUTLRS4UavmjrVc2XyLOfw\nmX1kLplcH+Lvjqme79O8b4H5T26gV0wOvrd7MytxdH2Eu1JFrzjFZRRVCb1q0bx3gcnVAZPrIxQE\nybSYpRKaisgphuhf7wAJFUXTioKXppEMImIiZJojTKUo3uSimP866pApKqi6hsxh/tObWE0XVEnv\niT3Muk39nnmSYYQwFFRTY+5jSwwuHqJZOr1n9kmjwtZeCqWYAVMUon5xm2kQo5kaKAqZlyIzibc3\nQTFUhKOx+9h1Dp9tF15UIx/F0FC2JxhlA6NikaU56TjGWangt6dMbwyxQ5fEK4SnVjbx9z3ypFgO\nsOcc+u0p0U6IQNK8f4n+8x0GL/VwFl2aDy7x6r94Fn9vQu38PGmYMrkywKha1M7PYy+UqN09TzxN\nSCcRftvD35mAEEyvj3GWSpTWqxw+d8Dhcx3G14YEhx61Uw2qJxtvOa+ctSqTrTFhLyTqR+Rpjlmz\n4TapPEbVYuULx5hujzHrNs5qmb3v3iBs+6AJVj6/iT03s3SYMeOXCc3RqN87qxjfCTPB9SFH0VWs\nVjHrdPjsPsOXe2glnfbjW6x/+dQ7nMaFIiht1Fn9zdMcPH6D8GBK+UQDvWoy3R7T/dEO8ThmfHlA\n2PFpXFhi+GIHq2kzuTLg8r/+KcOXOmRJiiIKIRRPIqonG0yuD1F1BdXRkKhoFYfyeQOv7RONY2Sq\nFpuQMUcxLUoRzWNpKKqCvezi3Rjjdz3Ii2igPCxmvHg9C1F9k/WDoZKlOUbJJOyHGFWLyZUJUtEI\neyHzn1otgq1ziWqptB5cIQd2v3GlcKMXEmOpRNgLkQnU726hlwy86yOMkkWuCLJpRDyKMZoO42tj\nysdrxB2f1E/JE0kWp2RRhlAUokGIu1xm6dFjhD0f5WGV/ceuIRBUz7ao3T1P0J6ShylGzSrsElQV\n1VTZ+MoZqmeaTK4MyJIcs2GT0yUex5gNl4Mf7JJn0LiwyOCnXbK0RmmzzuCVHsNLh9RON3n1/3qB\nZByhmsVroJVNzLrN9NoIv+3hrlYYvtLDXS3jLLkMXu6hN1yCXoBRtxCKIOz6XP1/X6X/Uo/SeqXw\n1WraVE++sxI1ujJgfHmIPW/TuGee1tGWYnDgEbQ9nKVSMcj+cg/7M7ceev9Fk6c5k+sj8jinvFl5\nVyPWGTM+yqR+Sv/5WUvxTpgJro8Q8TBEK+noZZPUT8nC9B2C63Xs+RLVuxeI+wHlkw3IJQff30K1\nNKw5B29vSvlkE3e5jN+e0v3JLruPXWf4So88leRRYVxqNB2SUUIaZKz8+knGl/oEhz5hx2fnm9dQ\n9KMlACmK0AZJMbuVU3g8qQpmw0ZmxexSFuUIVyefxGQZxXwXR0UtWYRQC0NgVG1Kx+oohobdstHK\nBrvf3SGdxrgbFdAV3JUqtTNNrJaN6ujkcU7YD7n2x6+huQaJn5D5EqGo5FmGt+2h6gEoYFRMogMf\nkauUT8/ht6fI/EhY9UPicUSWFDYdCBV0rYgbslTCjkft7nlq55roFYPek3tUz7Tw21Pq9yyQTGLM\nqsncQyuoZjGjZFQt5h9ZpXqmxY0/ucj2N68SHATY8w47370BUpKHCfaSQxpmZEHK1l9cIx5E+Ach\n3r6PQFA+XiPseoUIzyTxMMScc7BaDkIRmHWbqF+0KP0DD7cX4O9OkVlO/XyLwSuHIMCsmSTjGL1s\nFBmgbyPo+hz8cBejYtJ/oYdqatTPF4PviqkCgtRPSP2E0mb1fZ2/0SgiGUWYTRv9A3KX7z3dZvBK\nH0UTjC4PWP/N4zPvrhkzbstsS/FOmAmujxCVM03aj2+R+ilW08ao3d6PaPBKj8On2yiWhrc7ZenR\nDfo/7SKFJOwW0SzxKCSZxtTOtRhd7BP1IrJYomgqek0lDVKErSHCnOn25MjnS6V8vIG3cwPVUImn\nKTLJUS2d3EtABUUVyCRHcVREJtDKJkbZxD+YkCOQo6PQaOSRpQRHM18gMpC5ysoXT6CaGv6BRxrl\njLcPyeOUZBLTfaqYQauf7+PvezQ/tsjWn1+h/f0dZJIhBcx/co3OD/cIegFCEyiGQjSIisqQq+Md\nBCiaSvlYlXgckyUZqqHj7U9BgDXnEHR9slGG7uoIITAaDug6fi/E7AYYdY+lz23irlfpPrGPt+eD\npjK+PELmOV4n5PjvnsZdeiN5IB6FeN2AydaUsO0xeK2PZmmUViukYcL02pjKiRrxICIdx7hrhano\n9MaY0lqZaBCSBhlzH18ii1KCvSnlzRqJl3Dtjy+hl3WcleK42ulCjMbjiKDrUwc0V0O1dBRDJewF\n1O5qUdp8Zy8xizJAoLs6WZQST5KbvzNrFoufXGHw6iGVkw0a72O+Kuj6bH/zOuSgmiprXzqGUX73\nsPa/DtPtCfaCi6Ir+G2PLEhRPoDbmTHjlx3N0WnMWop3xExwfYRwlyusf/kU2VHL6nYbXlmUMXy5\nhxRgNW2C9pTJtSHWgkOwP2VyZYB7rI5TsdHLJkuf3aTz432ctTJBd0oySSivVgl7IekgQdEVsiRH\nr1p4+x7pzpRknCJqgjyVmA0bvWwweLmLXjIxGhbetRGKUJEKKLaFtVJivDNFaEphwioFxrxdOORH\neZGrmIHQVTTLoPtsD9VUMMoGWZyRDCOypBBmRZyPZLI9oqLVufh/v8Dg+S5ZLpF5Dpmk/b1dhBBo\nVZP4MES1VMgz9LKF2bDI/LTYfJRFRctsWCx8YqVoXdZNzIpJlkqyaZnSZoXBi4c071vAb/scvtBj\nfHVE+XgNmefkqWR0eYAqBJMbE8KuD6rC5NqEoONx4b95GL1kMLw04PqfXOLwpz2ifoQwNfJJRBxL\nUBUUXefMP7yfxr1zbH/tCl7bK4byg4ylR9cob1SZbo1Y/cImC7+ygqIp5FlO1A/Z+vo1rKaN3/Zo\n3NVi7uNLbH/9Gv6+hwTmHixEVePuuaKNWLcob1aon2/d8jyy52zMhoV/4KGoCtWTbxVl5WM1ysdq\n5ElO/6UeyTShdraB3bp1ZNV0e4KiKlgLNt6eVywR3EYIJdOYaBhhVM07FmXlY1X6P+2BIrCaFqoz\n+4icMeNWpH7C4ayleEfMPk0+Yuhl87ZtRCg8sna/fZ3pzpTJ1QHhsYDK8SrxJGJ0cVhUoEwdo2QQ\nDUKsBZfptRFaycBZdDEqJuOrI7IoJ8tCFF1DaALd1tErNoafUT1ZI5kmaLZK2A+JvZwsi0DVUW2L\naBCjlgyyKCdPcsZXh2husWFo1h1kRRIOfRRNo3yiRDyOCnPPSYLQVbJMEvSCwgJB9bGbNu7xOsHu\nBH9/il43kank8Pke061pIXrynGSSFjGPbjEzNvfQAuPLI0ZRhuEapFFGGmWE18bojo4951A720Rz\nNWScM3h1iGppBL0YoxzizLvox2tkYYqzVELmRTyQaqoYFYvx1RHD1/pFoS5KUUwV/8An81L0ukn9\nVJ3wICAaRXSebHP9z64w3ZmiqpJ4HKFaGnq5eCyKInA2Khz8aJ/RpSGtj81z7r+8QOeHu1RO1jjx\ne2dv+borqkKe5MXjPmpf7v9gl9HVEbUzdcyqieboWM1CCKmmxuInV9/zPFNNjbVf3yQexWiOdttZ\nqN5zHfqvHKJZGtPtCZu/cwL9FseadYsszIgGISDRS7e+vngUcePr18njDEVTWPvSJtYdOMu3Lixg\nzzlkSUZppYxyG3+vGTNmzKIU75SZ4PoIkAYp21+/yuC1PvW75tj40rHbzqXE45hoENK8Zw67ZZNL\nSfX8HC//78+SBBkyy9AqJtVTdRIvQWaw970d8kwyuDhAdTWErpJ0QpAKWklHKILqmTqKAs6CS2mz\nQtAO0Cs67R/uIzSV6DDGarnojo7MwVqzGb3WRxgKMoewG6BXTOyGzbQX4pYtjEYhNionSmRRynRr\nRNjxC3+oJEcxNJIgI+8VwnD1N04wvPwc/mGMDDP0IMeac3BaLnrJ4PDZDmkqESUN3TXJI4lAMH9h\nCXveofdch8iL0YUCmig8zxZdNFNDdTSiacroyhC9ZFA/Uz8SKZLDFw8pnWiglSzKJxSCg4DEj+m/\ndEjiJ8RegkglqqmSS9BrBukkwdv3aNw3RzJJmGxP0Ksm2eUBxrxDabOKYii4i2Wiw4DqmQbxOMZd\nLaO5Or1nOpz8e2fZ/Dsnb762iZ+w//09gm5A7WSNuY/No+gKmq2hWBrT7THevocz76CaGr1nOhz7\nnZMY1dsL9HejWNh495D1oBtgVE10R7/ZwruV4CpvVsizZcJOQGm9fNutRr/tk8cZzpKLf+Dj73p3\nJLiEIiitv7tH2IwZM4qWYvO+WUvxTpgJro8AnSf22Ht8G71ssPONq5gVneXbbIVp7tF8zmFALiWN\nu1qMXu2jWhrVBaeoHEmIRwl+12d4cQ93rYSqq5BDFsviSy/NixgfTaN1YZ57/skFNMeg88Qe+z/e\nwzlWYfTaEGvBRdVURqOIsB+imRq6q6OYapGdeDSAH41i6ne3iIYxrfsXyOKMqBdSPlXGqJvsPrZN\nMM4QugG5JBzH6I5AMxRKy2XSOKXzTBtrwSGexiRZjGZpeAc+7kqZ5c8skqcwvDYiCwXT0ZTqyTrL\nn1tHMTU0QyHNcna+vUM8CkGAahqUVitEw5C9v9pluj0mT3K8fQ+tpLPw4BJmw0LRFOJhjL/ncewr\np6idrbP73W0Onu6SehmZn6FqAqkIFFWjerpO2PNp3DPP3f/4Y3g7U/I8p7JZYfDTHtEgwp4v07yn\nRflYBWfBwahbXPujy0zbHqXlUuG8/rZ51t4zHbzdKaNrI/Z/sMfo8pDlR1fZ+8udIiRc0QqD1Fyi\nGIWP2dtzO3/e1M7UaX9/l2QUYc85txV3QghqJ+twi23IN6OXDWQmiUYRMs7Rqx/clmHQDRi8OsAo\n69TO1EmmCaqlfiCzZTNm/G0j9RMOn+v8Td+NXypmgusjQDSKQAiMiknmZwTd8LbHapbG6hc2GF4a\nYpR1qqcbxKNtyutVxlsjvO0prY8vMNmaMrzYR1Fh+NIhqq2z8ugqaZqTpRJ73mG6W6z+uytldr+7\nw9qvbxJNEvJUMni5z+TqCM1Wb7rRp9MEr+1TOVNHtQ1U10TJJKmXkAuF8CAimoa07m8RdELSICUe\nJ/idgGk7QB4FYGuODmlW+HhZGoqt4e0GxF58ZLQqUEwFa9HFqlqc+P1zBB2fOM4RQsGo6WSBil7S\nOf57Z9FsjSxMCUYxWXi9CN8WgmAQcOWPriDTnGQaI3NBMonRSwZ5lJPL4r5HoxirZSOGCuPrI9AE\nnZ8coJd1Ei9ByVWspo27XibqB4SHEfZShXv+0f1MtyYcPNlmem2CvWBTPlbDXnSobFRIvJTlT69i\nVE1u/Pl19LLJ4OVDgj2fu//xve+oYmZxRjyOkEmOWTGIhhHdpw4AgbtcYrI1xp6r4O1MCNo+lePV\nDyToOYsz/LaPoivFbdRMsijDatk/80agu+yy/Ogq3s4U54JLabVMFmX0X+6TRRn1s3XM2l+vYvdm\nEj9h65tbKJrCcJqw+709jCOD19XPr1JaKb33lcyY8UvOLEvxzpgJro8A8w8v0X2yzeTGBKtp0frY\n/LsebzZsFh5+oxU0/+BS0eZbcHCXS1RPNfB2PfI0x14oIZUA1dCwl8uMLw9p3NXCqluolsHcg4uU\nVsv0Xuhy+L88zd73d4lHMVmYoVoKTtOBXCIMnSyISWRK/Gyfyukyqq6iVjXSKCX3U6QCaZATjxKS\nUUzlRB21rHHw9RvINEemxVB8To4z72LNW0T9iMHFIfE4xWqZxOMAZ9HBmXMorVZYfnSNwxcO6T3b\nJepH+AcBZpKj2zreQcjFP3yV479zgsp6Batm4cy7+B2PPJbkEUxujNFdHb1mFAP9Wc7CJ5eon26g\nqArzDy/SeeqA6fUxaZIRTVLGW1NUS8NZKJHHkmgYkWeCLMxZ/NQapcUSeZwTTWL6LxziLLqYVYtc\n5rTum+fw+R7d57rIDFY/n6DZGmE/RDVVVNcgHMYEhyGlN8XhBN2A6Y5XCI84p3G+UeQVNmzC/oDR\ntRG953okfsriI4vUzzXQS/otcxZvRZ7k5FmOZr37R0qe5Wx9a4uwEyKlZP7BeVr3vDMn8WehcqxK\n5dgbVhPtJ9uMr4xRDIXJ1oTjXzmOarx7JNB7kfopMs0x52zSIGWyPWH9C+vEk7hoIc8E14wPOaqt\n07zv3b9LZryVmeD6COAulrjw3z2CtzfFbJjYrXfOv0hZzBpNrk9wV1zm7p+7mYWnlw1Wv7CBlJKd\n72zh7U6x6uaRP5aktF7h5H9yGqNmUDlWZXJjjBCi8GhKcg5f7LHz2A4ykyReQngYInRBFgmiQUR5\ns0I0TpCqgm6qCF0QDYtYIUUtBqbtORdnzqF+volRNSgfq+Hte7R/3CYLcxCFs73u6FRP14n6Eek0\nx6jZmDXJYDpE1VWMuoOzWGHl86tUNipUT1R58Z+/QBKkBN0YoavEkwx73kV3dUaXxlz8Vxe58F9f\nYP6hRaZ7U67/6TWyOMOetzHLJjKXxP2QhUeWcBYcFE0lj3MWPr2Eu1Tiwn/7IJf/7UXiUYJqa/Rf\nPqR6vMpka1KYjzZtVh5dI/FTMj9FLxsML40YvDpAHuUfylyimSpzH5tn7/v7KIZGabXE/g/bnPjq\nCZxFh6t/fAW9pFM7XePw+UOa55somoKUku3HttFLBquf22B4qU/1RI3qsQqNe1rYLYtL//4yrQst\nyusV+q8MaNzdfN9iy9v32PnuDnkiad3bZO7C7W0ekklC2AtxV9xiG/a14c9dcL2doB1gtSxUQ8Vr\ne4XY/xkFl1k1MZtHW7dhivN6q3qSUF69de7jjBkfJrJg1lK8U2aC6yNC8UV8+/kXb9ej85MOVtOi\n92wXs2K8Y5VfCMHyr64y2Rqz9OkVTknY//4eYS+k/9oIRVcw3KKqZdVMzJrJdG/Klf/vCuWNKkHH\nIx7HRbRPSUOzNJyVEtN9n/GOTzJOye3CRb159IWvmgqrn11lcn1CluSojsrWt3YYXxkBAs1WMMo6\nWaKiGpLmfS3mH1pgen1C0PFJvITqqSrjaxPiUYxeNcjSwrxrcn0CEpxll8nWhDzMsBcd4knC4PKE\nJAS7aWI4OuOtMc6Cy8aXjxEOY0aXB4SHCUJLad7Vwl5yqZ+osvipJYQQ+Ac+ez9ok3rbLP7KIrUz\nTYJOgGIpjK+MQYC96NK6f47uUx3iaYJVNYlyye53dxC6gl7WqZ2qMLpWOJ8vPLJEluS4yyX0is5k\na8ro+pS5j89TO9+gcXkIqihm7MYxWZwXLTpZxCQZZQPVUimvVzn2228YetbPNZi7MEcapGRxhhDi\npth+P7SfOECzNbSGRvf5HtVTNYy3bRFKKem9cMjg4hBvz0MIgcwktTO3yQP6OVI7W6PzVAeBwF12\nb7vheCcousL6r68TdAM0SyPxE/ov9Sktl2jd/8EKyBkz/jYgJeSzNcU7Yia4ZgDFJqNQRLGxZqgk\n/jvdw6EIFK4dDS6H/RCkoHK8yva3t6lsVnAXXQYvDTj5e8V2XO1kndrJGmbVZOc7hXeSXtHRXYPS\nWhlhKPQvjrBqJqquIinmv6yGQ+VYmeqJKoqh0XtxgFAVxi8NSaYxeZIjUwmqhmabZH6Eu1Ji8RPL\n7H9vF6Gp6CUT1dQ4/tsnWfviOk//s2cJOiHhcErvhT6qIajfVad6okYyTRlfn5BEGXkCVtPC35+S\nRRkyk1z9k2s4Cy5ChbCfMG3HxIOQ6oklomFM5UQN7yBk//F9Nr60wcETHaJBxPDKmIOnu5z+/VOg\nQDKIOf7VE7hLLjf+/AbRJEGxVPIop3FXA7Nhs/2tLcobFeJJRPeFogU43Z6CqjLd9Wjd2+Liv7lE\nNIyw5yye/V+fZ+5CE6vpEHQDhldHVNYrbH1rm2Nf3kDRFBYeXqD94zYAiw8vvmNWavlTy+x+f5cs\nyFj+zDKKqhD2Q/SS/p7VIFVXSLyEXM8LsXYLrebt+XSe6mLN2WgVE9VWaZxrUD/zs4dTvxfNu5s4\n8w55kuMsOHckJt8N1VBvtg6tpkV5bVbZmvHRQXN0WvfPWop3wkxwfYiJRhGjq8WMUfVE5V09hUor\nJYyqgd/2UG2NyuZ7r8bLXBJP48LhXYhijifJjzbc3mDl0VX2f7TPia+epHa2TnmtTND1QQh2Htuh\n80QXoQqyLEezdZr3togGIcM0o3q6xov/4kXyJMdqWQTdgLAXk4YSzVIwSgbVUzVAIJEkfkIuBc2T\nFZIgRWAQjRMu//E1QKV2qsboyhi/7VNaLeEuuSw+tMjyp5dZ/JVFXv1/LhJPE5x5m+GVEe6CQ57n\nxEFKtaRz+PIhw0tDNF2Bskk4irFqJpqjoZc0Jnse8shAdXRlhFHRUVTB6PKYM3//FOQUM1fDEP8w\nIuj4CE2w/JkVlj65TOIl2AsO4SAi6gcohkoW5lh1q2jJThJKG2XqZ+sYJZ3B5RFilGK3HKJBBLqC\n7hpM9z2CXsDypxbRbB1nweXkV08iEGi3MPM06ybHf+s4UMwnXf3T68TjGN3V2PjSxjsqVm9m6RNL\n7PzVLvE4YelTi7eM3cmTDARopopZMakcr9K8u/me59jPAyEEzsIsHHvGjJ8nqZ/Qm7UU74iZ4PqQ\nkoYp17++RR7nZElOPIlZeOD2/41ojsbmlzdJJjGaq6NZGnmWIzN52wpHMAjxOyGHP+2jGipWy0Ko\nguVPLb/lOKtpcezvHHvrZY1i+02ogs5zPYavDrAbNrVzNaonqwTtgMpmmcGrQ6JxUlg9DEYYNY0s\nzpBCkiWS8lqJhYcXEcDFP7zE5PoUzdXJJWRRMTP22r+5hFpSyeKcNMzRHI3KiQqNs4Wxp7fvIxTB\n2ufWKK2VuP61G/Rf7GM3bErrJXovDJjemBIPE8prLs6iSx5lROMJXjugvOYS9SM6T/fQXJ0rf3Kd\n1gPztJ/sEA1iKidrBL2Q9hMdmucbyExy5Y+uMbo+wW97aLbO1T+7wcKDC+iuzuaXNwl7AVmcs/f9\nfWQmmW5NMaoGpbUSuqsxd6FF5+kuaZCiOQppmBbVJQlBL0CvGESjmMGlEaPXxuRpTvVkhca5OuOt\nYgbPWbi1R9Z4Z4LX9iitlImGEeNrY1r33F4cmXWTE185ftvfAziLDtbRzJNmq9RPffCtxBkzZnyQ\niCIDd8b7Zia4PqQk05QsynAXXdIgxdv14YF3/xvVUFGPHMWDbsCNb++QRRlz97WYv/DOuZTBKyPm\nLsyjaAK/E3DyK8ewmre3EUjDjN0ftPHbPs1zdeYuNKmdqPGpf/YJpjuFoNh5fI+tb+ygWyr2YlGV\nsFoWqZ+QDXOEqqGWTDB1NFOjef88mqEx3hpDLqidaZClGXkKVsumfs6i85MumqXjLhWDzXMPzLH8\nyWXmPtak89wh42tjkNC8u8HSIwtU1iqMd6bs/eiA7nNdaufq2HWTsB+y8pllWvc1ef5/ewm9bGA1\nHab7IZE/IJ0mrH2uXgxPjxMe/O8fYPfxPQ5fGRZO6jsekxtT6mdr5LkkHid47QC7IRlfnzC6Nqa6\nWabzTJd4lNC6v8nqZ1cYXBzSPF+jvF6htOwSjxNqp2u4Sw5ZkOEd+MSTBGfB5vo3dsjinMqcheHo\njC6NyHPJZN+n8/wh5fUudsNC5pKNL61RXnbf8hpJKem/OODg6UMGlya4izaa/bN/TGiWxrEvbxBP\nEnRHu+lqP2PGjF9eZrYQd8ZMcH1IMSo6RsVguudBJll85M4cgfef6KBoCmbNpP1Eh+lRFWjhgRbO\nXCHK7JbF4OIQ3dHQTOU9v5gPX+ozuTHFmbc4eKaHu+TgLjmYFRPzfLHtN77moTk6wlDxDgKMikme\nSJwll+b5BnGQ0n22TxJmZHaG1wk4/5+dofN0j+HVCUZFx++luEvFtqBmq6iWShZmrP/6GllYhCon\nQYZq6kyuTyitFrE7g4tDFh+eB0XQ/nGHyfUJQTciHMa0ztVpnG9QPVbFappMd3x6L/bRXJ2t7+yS\np2M0S0P/SZe5e5o3nzvF1An7MYiYymaZJEpAFg72iqkgpUAYKtGgGHJv/6TD6OoEvaSz/Z1dTn/1\nONVjRXs38RKufW2baBgx3fGonKiw+OAciw8tIKXktX93BWfRJh6WmNzwOPcPThFPEq78xxtFjNJh\nRJ7mtO5qEPRC/HbwDsEVTxKCw4ja6Sr+gQ+KoHLs5zObpGgKVv1n98CaMWPG3zyao9G6/72D52e8\nwUxwfUhRDZXNL67jtX1UU8VdvrMZFqEUW2QylwwuDUEpVn0xPXkAACAASURBVOFv/MUOp//Twsdo\n4eNzqIZCMk0orZcZb08xSjqlFfeW15nFGYouioFtUXgy3fxdkpNMYqJRwni7cKrvXxxx+veOs/zJ\nRab7PvaiS//xPewlG3EYoZUMpts+w9fGLDwwx8FTXQ5fHmBWDTa+uE6e5lz815eRQlA5XkE1VdpP\n9oo4G0ulcryMWTPxD3xkBu6ygxCFeel4Z8pkx6NyrIwzSTAqOosPznH9WzvkcU75eIWDZ3pM26PC\nVyyVxJOEg6cy1j+7QuNcncmOx8Ezh2iOznTPo/PcIUsPzdO8twkUrdR4OUa1NOx5C7tlMt2aopd0\njJJOPE5Io+zmVt1k1yOaJKRhxmTXw2yY7PzlPmmQ4S45pGGO3TRZfGQBvxuw8PF5onHC1rd2US2V\nxYdaHL40xO8EZEmOM//OaqRQBMOrY+JJQhZLmi3rA88TTPyUne+1Cbohc/fUmbvvFzPbNWPGjL8+\nqZ/Sfbb7N303fqmYCa4PMZqjUT3+/nLh4kmCoombVaqlX1lg+7EdosOocItfdFB0BW8/II/zov1o\nqCx8fJ7ES7j8H26QBRl5Jln77BL1U9V33EbzfIPJtsd0z6eyUVxnluRsP7bPeGeKXTeJJzGarZJM\nC8d6RVOwWyadZ/tYDQujbpFveSimjqIUQmqy59M8X8eoWiw8sAAKhIcRlWNl7AWHuQstsjDjxmO7\nJJOUaBQRjRL0ks75f3CSya6Pogoa5+pIKdl/qou3HzC6PmW667H6q8u07m1w5c+2GV6ekEYZRknn\nwj85z/Zju/RfGaKXNcgk9pzNyqeW0CyVw5cHTG6Mi7gaWTynm7+2imqqLD40j2qp7Dy+j6Ip6K6G\nVTVp3d9k+zvFAHp5o/SWipBua8g0Jx4nIIrXqvt8n8RLMasG7qqD3w4QwOKD8yhaYZmx+VvrXPva\nDp2fjpi/r0nzngbuokNp6RZ+bJnEalqopoZQQFE++PDm7nOHeHs+VtOk/ZMu7rJzs4o6Y8aMGR8W\nZoJrBvtPdum+0EeogvXPLlHdLGPVTU797gmkLFptuz/sQC6pn6miuW89baJhXMyLLTtE45jx1vSW\ngsusGhz70hqTbQ+rVWQM9i+NGG9NKa047DzeZrTt4e8FVE+UUbIcb98nDTOMsk55o0RlvYxm6vQv\nDVE1hcm2x9IjC8TTFNVSqR4rKm3Xv7mLPW8xvDpB0RSEEJg1E83WiqgjRbD74y5Wy+b83z9xczEg\nizN2v3+A3w3RK0VUy+aX11B0hef++StIKVEUhemuz/7TPc7/wWn6l8aMLo1RHZXG6Rp6qXh+8ihn\n7kKLsBuhOxpLD82/ZXapdXcD1VKJRzG1ExX0ko5e0jn91eOkUYZVNxFKkWfo7QegClr31em/PAIg\n9ovHXD9bJQ0ykHDy726y83ib/Se69F4eEk9T/G6Aoits/Noq0TAqqpC3EFsAmqXiLjgoK4I0zCmt\n3rpa+fMki16vfAqgqKzOmDHjbzeao72ryfGMdzITXB9x4mlC9/k+7rJDFmXsP9GluvnGzI4QgsbZ\nOs6ig0wlVsN8hwO5UTEQqoJ3UFS/5u5t3PK20jDj2jd2iUYxUsLG55eIxjHDqxPCYfT/t3fnQXJd\n92Hvv+cuva+z7zNYSQBcQBIAF4nURopSJJGULVGLrSVPLsX1nisVp/yelfKrJOVXrlLs5CnP5cSJ\nEie2vMmyYsm0RVGiKFqiRNEiuJMgQeyYfe+e3vsu5/1xmyCWGQANzI7fRzViL/d2/+Zi0PPD+Z3z\nOxTGKrTuzqJ8hVvyyF6XZvD+vmAi+cuz5I4UAOi+o51Yd4z8qSLV2WA7nkhLmHAqRO7YAsM/maQ6\nW8epeiR7g+9r6P19dN7ezrG/O83kwVmcsotCMfLUBG03ZuneF3xw1AoOM6/OUxwr4xRdlKU49p0R\nwnGb1FCS0R9PYNgGHbe04td8tA8HvnQLxx89BT5s+1D/mbYI2eszVOZqJAdtYh1RIi3nzl9ShiLS\nEiF3rEg1P0f3gXbCKftM4gVB641TT4yzcLrIwnAJFGSGkmz/hS2E0zYnvz9Kbb6OW/HIbE3y8h8f\n4di3TxNtj4Dvs/WD/YQSNrkjBXrusKgv1PHdpRMaM2wy9IE+pl+cw4qadNy68k082/e2UpqoUJ6o\nkt6SINYho1tCrHdu2WXq+Zm1DmNDkYTrGmdYBspSuFUPt+ISToUWPS5ykQ1/Q0mbbR8ZYOFUkVDa\nPidhO1t1vkZtoU6iN05posKpJyfwXR/f00y+MIdS0LYry8zLedy6S+5UielX5+m8pY3+u7tp2ZFB\nGcG/rCb+/avU5uuEkiFKU1XqRYetH+rnzW+dpF5wKc9UCWdsfNcn0hql+44OwqkQid4YxZEyC8Ml\nkn0xnIpHLV8/E2M975DoT1CerUHVJ5SyqUxVKbkVBu/rRSkojpbpvK2NcCqEHbOIZMLc/Cu7zvle\nS1MVnJJL200txLuiJLpjFzQb9V2fE4+NokyFX/c5/eQ4Ox4cOOcYp+xSGCkS64gy/WoO01aEsyEm\nDs6y5zPb2PaRAXJH8oTSIcywyfCPJgmlw7g1n/JEGd/xibZFCKdtiuNlYu0R0peYBB9rjzJ4X+9F\nj1lOkWyYHR/bgl/3sGLWZW8pJIRYO7rxJS6fJFzXOCtiMvi+HsaemSacCdH/zq6mX0NrTe5kkdzx\nIqn+OKkBjTIv/KUZStgYpsHCqSJjP58m1hamMldny/t76TrQTnG0hO9oot0R8BWhdIjTT04y9L5e\n4l1Rom3hM6W/rgPtuE4wn6kwXCF3vEh5ssLoMzMYpkG97FHN1zEjJome6JnGneFEiG0PDHD0W6eo\n5R2SPXE6zpqkXS85+C4owHc1GihOVWjfnaUyWaXtxla2PTBItDVMdlvqgh5lTtmlOl/jxPdGUaaB\nW/EYeE9o0V5mXt3Hq3rEu6P4ng5WMy7y5xOK21RmK7glh0hPHLfiYUaD14u2Rog2WnHMvhGUWX3P\nxy26JPviGCET7Whu+xd7iLZEsKLmsnVaX06mbWDaKz9fTAixPOyYRYeUFJsiCdc1xim7VGZrhJI2\nkUwwmpUaSJAaSFzxay6cLjH2zAzxzgiTL8wSyYRo2RlM1s8dL1CarJIciJHsidH/7i6OPTaC9hWe\nVni1YDVirDPK4Ht7aNuTwan7TD47g9KQ6I4ycyjHob8+ie9o+u/uoOdAG517Wzj698PBxPC0zeH/\ndZKOm7KYIYPCRIVYRwSn7BLviJPenub0jyZovyFLrD3CwLu7yWxJUluok9mWJJQIrkM1V2f8mRm6\n72gHfIwjRWKdUUJxm879bfQeaMewDexFOrUDzB7OM/LUFJXZKm7VpXt/O9X5GqWJKq3XnXtsvRi0\nX0j0x1k4VQz2qbzzwg8vwzLY8oE+Zg7liHfFqM4Hiwr67z43MfbqHlMvzxNK2+TeXCA1lOD2L91I\n266gwehSo0bzRxcYf26WcCpE/z2dhOLNfSRUc3WGn5rELbn03NFOeujKf46EEBuHU3aZfF5WKTZD\nEq5rSL3k8ua3h4P5Swq2f7iPRNfVz5dxq16wwjFiBvvqVYJ9GPOnihz//hhuzaP6/TqZwQRe3Wfm\njWDPwpCj8T3oubODtt0Z4t1RlFLsfGiQer4OShHJhjj63VFqeQcralAvOLTsSBFK2nTubSPaFsJz\nPU49PoFT9cAwcCoenqdJdMeZO1nitb88QedNWfKnS+x6eAg7apHekkSft/OqW/XQGhIdUdpubMUI\nhxh6XxfFiQrRljDh9OLlVghG+UZ/OkW0PUwoZXHq8XHynUUMQ12QhNQWHI787Wncqo9WmoF7uoh3\nRpbsURXOhOi9a+ldArSvKY5XqOcddn50kPJUhVh7lPbdF9+nsLbgcPKHE8RawxQnKow9M83Q+7ov\nes75hp+apJarY8VMTj4xzu5Pb8E+qx9bNVdn+rUcVtig/cYsVpMNT52yi/Y0oeTVbzi9nJyyS73g\nEMkuPnopxKankU7zTZKE6xpSnqrilhySvTHKM1XmjxeuOOHSviZ/uoTvamLtEcKZEMXxCnbMItOY\nI1SeDuZW5U+WKE1WmXo5z55PDmJYimhbhEhLsM9hcapGx17zzChMsjfG3n92PdW5GlrB7OHDRDKh\noC3FRCVYcZgO0XlLlpGfTjHzRtBN/eQPxylP1ui7u4vc0QUqs3WUqShPVJiP2aS3xBn56RT502VA\nU56rg6/Z8eE+2ndniLWFSXRHKY6WsUImQ+/tpDJTI9Ufp33PpTdZtqLmmU3Au/a30f+uTiLZEL6j\nmT9WINEdxY5ZlKcqOFWPVG+M0lSVWsGh9foLV3WezSm7jD8/h1/36NzbQrQxAb86X+fYY6OUp6uU\nJiuYMQuvrol3X/rP1at7KMCMGNiOiVNafMPyi75G1cOKmlhhk6pfx3c0NN7ac3yOfmcU3/Hw6z61\nXJ2he3su/oJnmT9W4NSTE2hf03lLCz37V34C/+WozNY4+vfDeI4mnLLZ/pG+c5JMIa4FdtxalUU1\nm4l8SlxD7LiF1sEvabfiEW1ZesTmUsYPzjJ2cBbDUETbw2z/cB9u2cNOWGdGMVJ9ccpTteC9WkNU\n5h0q83WS3XGquRrFsSrxzija1Rx7bIw9nxo802Qz2hom2hrGrXm07koz9fI8znSVgfd2EckGcbfu\nyjD+/ByGZaAx6NqdZvbwAqmBGE7JQdl17JiJV/OYPZwnNRBj7s0Cid4Yr/7ZMXwXYm1hfv4fX+e+\nr+wjFLfZ+sFeqnNB2e5yR1U8x2f61XmsmE1ltko4abP9gX4SXUE59NSPplAGhFMhrvuFYNVgsDdk\njcJYGc/TeHWf7n2ti44A1YsOz/3nNynNVMluS1Icq7DrE0OYtsH4szP4jk9mSwK36mLHTNr3pGm/\n4eIJotbBqFF2R4rp1+apzDsMvacL3/UvmNx/MT13tHHy8XGq83Xab8wQSr79keJWPJyyS7Inilf3\nKYxXL/pa5+/dOfqzaSItIUzLYPLFOdr3ZJYs566muTcXgpHQ7iiFkTKliSqZLVJKFdcWp+QyKasU\nm7L2n15i1cQ7Imy5v4fc8QLxziytOy8+qnIxc0eC0TEzbFIcK+PVgy7n57xfV5RdDw9y9LtjhNON\nLW60pm1Pmu7bWzn0F6dI9kZRhmL2zQK5UyUyg/FzOpubIYMdD/bTcWMWM2bSvvvtTY9rCw6GqUgP\nJZk5lCN3qkzP7W103NxC3zs7yZ8scuyxMbQBTtFj/IV5TNsk0haiXgyatHqOTy3vMH0oR+/+dgzL\nWLQD+8WMPz/L5PNz2HEb34NoZ5SJF+Zp2+Uxd6xItCVEKGFTGCtTna+T6Iqy9f5epg/l0CdK2BGT\n6dfyaB8G7r6wdHj8++PMvpnHilnkjhfJbglKs6ZtoEwVlEY1RNJh+u/uJNYWxK91kMiZIeOcOVz1\nksuxx0apzNZJb41hxWyiymDq5Xk0MPDOpcuX50v1J9j96a34jn9BghpKWKR6YywMl9Boeg4s/a/h\n0mSFY98bx615dN/aQvdtrUED3JKLHw5K1UGfrrUXSlk4FY96yUVrjRWRkqK4NmlZptgUSbiuMZmh\nBJllmNicGogz1WhTYCfsJUceuve1EeuIUJmvk+qNE2t7Oynrv7uD0WemyZ0o4ftw/HvjZLclGXpP\nB1Ov5MmPlCmMljAMg+zWBEMHWs9JxmJtYUJJm/JsjdJMnbhtEEqG6b4tOK62t4XCWBUzZDD9eh4r\nFGzpM/7zOVqvSzH6sxlC6RDpwTizry3Quz+YtO45PoapzlnN51Rc8qdKzBxewDAUnTdnSQ8ETUHL\nk1WMkEl5psqJJycJxS16D7SycLpEdkeCwkgZp+RihAzCqSApSQ8lsGIW+eEK4UwYZTpU52oXXD/t\na3KnS2S3JcmPlCiMVRh8dyd2LPgl372/jcpcndJUla7bWs4kW27N4/jj4xTHKsS7omy7v/vM6NnU\nK/PUcg6JnijTLy/gux7te7J4dZ/8yRK8s7mfBStiwiJJhzIUQ/d1U5qoYFgG8a6lE9nhn05j2AaJ\nTIjxg3O07Egx+J4uhn88hVf3GLqve93MlWptNJotjFYYeFcnicso3wqx2Vgxi04pKTZFEi5xAd/z\nmXgxR2m6Stt1KbKLlEv67mwj2hrCq/tktyUXXdKvtWb2zQUWRipkBs9NtgA6b8qS7o/z8p8dJ9UX\nw7BNcseLnPA0hx8Zpppz8T2f6x/qY/ZogdadKdKDb3c+tyImOx/s59Wvn2T7h3tJ9cVZGClTnqmT\n6IwQilm070ozfShHveCSui6J60KyK8Kuhwc4+AdvYoYMIukQ4WwomPj+j7NMvjRPKGmz/YM9RLMh\nvLrHm4+MMvrsLMWxCl23ZimMV7nhk4OEUzaR1hDPfOUwhfEy2tf039nG/LEirdenadmeItkdpV50\nyW5LnpOYWlGD0lSVsYOzpPtj3PTZredcn1rBYeqVHKXxKgsjZaItNtd/tJtt9/ecGbGyYybbPtiD\nFTHPKQXmThQpDJdJ9cdZGC6RO16kbVcwouk5PhOv5Kj8qI4dMei8MRs0VfU0nbct3rT2Spm2Qar/\n0t3qta8pT1bwW8NBTw4F0ZYwOx/qX9Z4loNhGnTva6N731pHIsTaccsuk8/Nrsp7KaU+APx/gAn8\nd631l897Pgx8DbgNmAU+obU+2XjuXwFfADzgn2utv7cqQS9iTROuq7mIYuVMvZpn5JkZwhmbo98b\nZ8/HB4idVy40LOOc8t5icidLHH9iklDSZvZwAStqkuo9d0uZSDZEdmuShdEKhqUIpyxO/mgKrRWG\nrcifDhqIuhUPt+Zd8B52zKJlR4qZQwvUSy5KKaxwkHgoQ7H1/m5ar0+R7I9x4olJlGUQzYaYPbTA\nzZ/dyumfTBGK2wzc00llts7Ei/Mke6JU5uqMPjvL9vd3U5l3qObr2FGTaFuYWt4hnLRxKh7hlE15\nuhb0CIsZ5E4UOfXTGQxTYUZMYu1h7IHFE46JF3PE28MkuqJU5mvUSy71okMoYTP681nGnptl5OkZ\neu9qpW13mtJkle0f6jsz8lbN1znynVHqRZdUX5yt93WdSXyVqdBaB18QrNyse5ghk1rBZfrVHJ7j\nY0ctht7bRdctWSzbJD208lv5nM+teVTzDpOv5vHqHjf+0hbC62xVohDiQqtRUVRKmcB/Au4DRoBn\nlVKPaK0PnXXYF4B5rfV2pdQngX8HfEIptRv4JLAH6AF+oJTaqbW+8JfJKlizhOtqLuLqR3ttqczV\nCCUtIukQ9YIbrF5rXbrT/Fucikut4BLJ2Fghk+p8HdMOEhyn5FJbcGCRBuZD7+1k8qV5vLpPx00Z\nFkbL1BbqWBETO2kx8XIO0zY48eQkZsQkc14C07u/Fe1qyrM1tt7beaa/GIAZMmnZkSLWHqEy75Ie\niOHVfRZGKwy+q5PstmBFZWm6yuyRAnMnC7iOTyhm8VZBMZSwMG2DUMpi/niRcNwi2RMl1hpqPG9j\nhkxiYcXUKx6hjE3LUIJa0SV/ukzbdYtvIO6UXOy4jRU1GH56GpQi2hJm2/1djL8wR6I7Sqw9zOTz\nOQbubifREz1nJHH6tTxOxSfZE2xzVBgLRhIhKB237Egxf6KAV/cZfmaa8Rfm2XZ/F7V8ncyWBInu\nKOWpKuXZGm3XXfl8vqtVmQ22G7ruoX6q+Tr+mnwUCiGaYcUsOm9blZLiAeCo1vo4gFLq68CDwNm5\nwoPAv23c/ibwByooAzwIfF1rXQNOKKWONl7vZ6sR+PnWcoTrii+i1jJVbyW1XZ9m7miRhdEy0WyI\n+GVMIi/P1Tj8SNBzK5y2uf6BXtKDccaen2NhtIwVNkn2LD7XxY5a9N3xdtPPbR/o5cQTE7hVj+t/\noZ/5Y8XGykOP0X+cvSDhsiImQ+/pvGh8oWSQJC2MlEFD3x1vf1BMvprj+A8nGX9+DrfqsXCqQvue\nNLt/sT8YfcnVGXx3J8XxCoN3d5IeiBHviJwp4fW/o538qRKTr+ToujVLrC1COGmj/WBj5qV03dLC\n0UdHmXm9iJ20ad2ZojRTY+F0CdM28Go+LTtSwdY+bWH67mg7Z16ZETLQro/n+GjNOZPKTdtg633d\nVOZbePXrp0n2RnHKLiM/m6X3QBujz8wyf7RIJGvTf9eFH5paBxPxV6MrfShhoQxFZbYWbId0/eIJ\nqhBi/QhKisu2SrFNKXXwrPtf1Vp/tXG7Fxg+67kR4Pbzzj9zjNbaVUrlgdbG48+cd+7q7Vt2nrVM\nuK7mIspa1BWU7I6y5+EB6kWXWFv4sppVzh4t4rs+qZ4oueFysBH19iRD7+lk4qUcmYHYZbdZ6Lwx\nQ2YwjtYawzLIny7jNlaFpZZI2goTFSrzdTzHxyl7pHqi5yRmhmmw45/0UBitYIYMkr1vv87kSznC\nKYtwwiYUt+jZ14IdszAjJoe+NUI1V6cyW6f3QCu9+1qIZs9tp2FHLW75wnZ812f057O8+LUT1Esu\nfXe0nRlBW0yiM8INnxoid6LEsR+MUy+5eDWPWFuEre+PM/zTGZJdEW74xMCZvlvnXKcbMlRn6xTG\nK/Tsa100oTVDwVY+nuPjVn1iLTYt25Lc869vZGG4RLwjQrLn3DJvabrK0cfGcSoe/Xe10XnDxUvH\nVyucstn5kV5m3lggkg3RccPajbYJIS6PBvzlG/qY0Vpv+lmRm2LSvFLqi8AXAQYGBi5xtLgckXSI\nyEU6q58vnLBwq0FShK+xoybVBYfjP5zCMGF4LFjJ133T5f3yfms1H8C2e7sY+fksye4IvXe0cuKp\naaZey9G2M8nAXe2Upqq88Xdj1Ap1Jl/JM3BnG2OGYvdDfeckaL6ryY0ELSysmEmskcTYCZPj351m\n/miBcMKidadL994spckq1fk6vqeZemOB8lydhZEyNzw8sOgWOIZl0H9XOz37WnAqXpC0XWJ/QCti\n0rYrBaZm/liJjhvStGxP4vuabe/vxo6bWEuszrMiJtvuv3hn+FDcYuv7Ojn99DThlM3gPcFIYqw1\nfMG8vLec+vEUWiniHWGGfzpDdih+Zi/KlZLoii7LrgdCiNVhxyy6VqekOAqcvXqmr/HYYseMKKUs\nIE0w7/tyzl01a5lwXc1FPEdj6PGrAPv27ZNy4xpouy5JveSyMFJm6D0dQflutILvaZJdUaq5YCTm\nchOus2W3JshuDVZKHv7uGC/+2UlMWzH2wjzaBztqYsdMtG+jlMJzNE7VZWG8ck7CdeyHkxTGq5iW\nojBe4aZPDWJaBhjBPLPogRbwYdu9nbTvTlOeCdo0zJ8qYViKzGDsTInxYnsOmiGz6RYGbTvTtDX6\nouWHS/zkP7xBJefQdXOGff/b1qaS3/O1bE8S64iQHylTLbiE0/aSeyuW52qc+skMtYJLxw0p7LC5\nLL12StNVnIpHoiuyZAIphNg4nLLLxPKVFC/mWWCHUmoLQU7wSeDT5x3zCPA5grlZHwN+qLXWSqlH\ngL9QSv2/BJPmdwA/X42gF7OWCdcVX8RVjVJcFsM06NvfCvtbzzwWaw0RTljkR8poH/rvuvr+XzNv\nFginbOJtYQoTVQrjFQbuamP8xXl816dWdDn10ynMsEm0NUTnnjR2o0dUcbJKoj2EMhWFsWrQFNQy\n0J6mc0+acMpiYbRCoivY0zHeHmH7/d2ox8eZM4Lv0Y5ZZzrdXy7P9Zk7XsR3NS1bE2fiWcqr3xyh\nknNIdkUYeyHH5Kt5Bt9x4cbWF7MwXsEpeyS7I6Dh0LdGcCoevuuz/d5O2pfYSujUU9NktsYZf36O\nV/7qNIP3dLAwWl7y+Msxc6TAsccnUIYi3h7m+gd6LznyJ4RY79Sq7KXYmE70a8D3CDoa/A+t9WtK\nqd8GDmqtHwH+CPjTxqT4OYJ8gsZx3yCYG+4C/8darVCENUy4ruYiio3Bjlrs/mgfxckqdtQ8pw+X\n5/iMvThPed6h+8Y0qUbzSLfmUZyqYcdM4ouUvDpuSDP9+gKzRwtE0ja9B1pp3ZbE+LCiNFPDSpjU\nci6p3ijVvEN5tka6N4ZT9TCjBiefniHZHaXn5gx2NEh8+u9o5fCj49RGK3TsTp+z5VHL1gTZL25n\nYaRCreiQ6o0RanJ7mRM/nmbqUB5lKKbfWGD3Q30YS0xG91yf8nwNt+bje+A7Hma4uQ+16cMLHPvB\nJBgQSdv0396KU/FIN67J/MnSkgmU9iGaDRNKhmjblabjhjQnfjxNdkui6Y2n3zL1ao5oNkQoYbEw\nFsy1SzQWYjgVl5NPTVOeq9NzS5b2JVZ0CiHWFztm0rWv9dIHLgOt9aPAo+c99q/Pul0FPr7Eub8D\n/M6KBniZ1nQO19VcRLExhOIW4bTN698Zwyl79N2WpX9/K8PPzjL2Yo5QwmL+VIm9nxzAChu89sgo\npemglLfz/i7azpt0vvVdHaS6I5Sma7TtSJ0pGWYHE2QHE6AUhx8dY+LQAnbUIBQPkoTj/zBJNe+S\n6IpiRy0G72l/e7Psrih7f3kQr+4TilsXlNvmT5eYfG2BRHv4TIf36oJDabpGJB2MtkGwsm/+VJla\nwSHRGcF3NZGUxezRAum+GIapyI9WcKveokmb72vefGwCLEV5vo5Tdbnun/TQsiWB7+slk7TzzR4p\nEMnYhFM2C6MVtA62SCqMV3DrPl17ly7rDryjjTcfHaNacGjdniQcs3ArF/6DsDRTY/LV4M+v++bs\nRUesEl0Rxl/I4dY8DFOdU44d/vkscydKRLM2x344SaIjcsGiBCHE+uOUPMaeXZ3Gp5vFppg0L9a3\nk08Hdf5kV4Thg3O0bk9Smq4RzdiEkzb5xtY3Tin4RZ7pj1FdcJh6feGChMu0DDov0nA11R2lXvbw\nnWDifmnOIZoJkxsO5nMZpgrmljkazpoHboUWn5xenqvxxqPjRJI2cyeKKFPRui3BK98cOdOO4YaH\nekl1R5l4Jc/xH0+hPc3EoTxdezI4FQ9lasqzdSJpUsU3ogAAHpFJREFUm2RXZMm99+oFh/xwib5b\nWmjfmaQ4WUWZBi99Y5iWLXF23Nd1ztZGS4l3Rpg/UcKpehiWItUdZfdDveROl4mkrEV3DnhLoiPC\n3s8MMfSudk78KBh52vrujnNGt5yKy+uPBNMtnaqHU/HZcvfbJc962cUw1Zlzeve1YtoG1bxD5w2Z\ncxKuetEjFDOxoxZQx6v7l/z+hBBiI5KES6w4pXh7/XDjP503pDny/QkquWA0KNYaDhIEU1Geq1Mr\nurRuX7qlwlJqRZdMf4x0X4ziVJXSVJW2rQk696QYez6H5/okOiOXvRFyveShCEpzvq8pzdQJJ2t4\ndS94j+kq8ydLpLqjzJ0sEWsJUSu6VBdcXMdj/OV50n2xoFfY3W307WtdcqTKiprYMYvidBW35uOU\nPCIZRbovxtyJMqXpGslLrOSbOJRn5Ll5ygWH3i1x+u9oIxS3CMWtM6syL8UwDVq2JMkOJYL+XufF\nWy95uDWfdF+UetmlOFE989zIwVmGn53DsAx2vr+T7GAC0zboXaL00Htblje+M0Z+tEzL1jixNhnd\nEmIjsOMW3ftkL8VmSMIlVtzQXW288dg4hckqA3e2EsuGgq9PhKiXPRIdYUzbwLQNdn+kl4lX80Sz\nNj03Z5t+r0R7GMM2yI2UAUW20Xl94I42opkQh747TnGuzit/M8KeB3sJRS/+VyDREbRPyI9WUAq6\n9qQwbQOtoTRdwyl7xDuCRKZlKM7xH09RL7mYlkE156AhiMFQJDqiF50wb4VMdn2kh4mXc1hRi1rB\nYe5YsbGlkca4xETzetnlxI+nSXSECSctamXvTLkTwK17VOYdwknrsuahKaVYbDFjJGOT6AyTHy6j\ngS3v6jjz/sMH50h2R/FqXjD36zMXXyiR7Iqy95eGcKvBNkmXWzYVQqwtp+QydlBKis2QhEusuFhL\nmFs+NXjBaEmsJUzsvL2SU93RMxPor0Q0E+Kmj/c3SpahMwmHYSjqFZdIwiLVE2X+dJnccIWOnRcf\nRbPCJnse6qU0UycUN4k22jPsfqCH3Kky8c4IrY2WFV03pgmnbGoFh+33djL5Wh7f9UEH86/ilzF6\nE2sJs/XdQdd8p+Liu5ryTI0t93QsuojgHDr4P6WCUUV9VldCp+Lyyt+OUs05mLbBDQ/1Xvr1lmBa\nBtd/uIfiRBUzbJLsDCbAK0NhGEbQZLXmn1mUcCl2xLzkyk0hxPqiYVlaxlxLJOESq2Kp0ZKVEE2H\nziRGZ7NjFq7j41Q8tK+xI5fXmsAKmaTP6+Ke6YuT6Tt3iyGlFC1nbf7cf1srhckq5bkaiY7IJUt6\nvq+ZPlLAKXu0bU8QSdpc94GLNzYFKM3V8F1NvC3M0F3tnPrZDGbI4PoPvn3uwniVylydTH9Qap06\nvMCWu5prNXE2K3ThnpZ2xGT7fZ2cfGoaK2yy7b0X325JCLFxBbtyrM4qxc1CEi5xzejYmaQyX2d+\nuMzQO9rI9McufdJVSnZGzowAXcrpZ+c4/ewspm0w8VqevR/vv2QrhrGXcxz/yTQAHbtS7Hh3Bx27\nU43RprczXDsaNDCtFV2cik/4MrdZuhStNfmxCl7dJ90bpXVLgtaLTMoXQmwO9ZLLqKxSbIokXOKa\nYZgGW+5qZ8taB7KEuVMlkh0R7KhJfqxCZcGhNFtk/nSF7ECUzutSKKXQWjN7okh1weX4T6ZJdUcx\nbcXUGwUGD7QSXqQLfqo7yvb3dDB9uED/gRa6di9Pv6uRF+Y5+fQMylAkuyLc+GDvBSsptdaMv5Jn\n9mSJlsE4PTell+x0L4QQm5UkXGLTq+TrHH5ikmrBZcudrXTuXPnmmr4fjPygId0Tuax2Du3bEhx/\negbTUkQzIap5h8OPTxLN2EwdXiAUtWgZjDP+Wp4jT05hhgwm31hAKUU4aWFHDKzQ0u/TtTtN1+7l\n3Rh68vWFoNVF2CQ/WqFacIllzi3nzp8uc/RHU8RaQxz78RThpEnb1uZXoAoh1g87btGzX0qKzZCE\nS2x6R5+appSrE0nZHH5iknR3lMgyldSWcvzpGUZfygGajutS7Lq365Ln9N6SDdpjVFyyA3Fmjxcx\nbINoJljNWc7VaRmMM3eqTKwlRCRl41RcYq0hoimbgf0tq75lTqY3ysShBUzbwI6ZhGIXlkBrRRfD\nUkSSNrWCS63grmqMQojl50hJsWmScIlNz6n52BETq9HOwfdWdmmN72vGX82T7YuCgukjBbbf3Y59\niflYhqFoPWvSfaY/hhUyyI1WsGyDlsYk9ZahOEd+WKS6EDR1vfGB3qa3G1ouW97RHiSEFY/OXalF\nm8dm+4PtkPKjFayIec7CAiHExiWLFJsjCZfY9Lbe2cZrj45TzVfpvSlDNL2yo1uGoUh1RchPVFGG\nItYSuqKRp1gmxK0P91Oed4hlbcIJm3rFxal6tG1LkOyK0L49uWbJFhA0Nd178X5pkZTN3of7qeQc\nohn7kr3PhBDrnx236JWSYlPkk09sepmeKLd/dhDP0YtOKF8Ju97fxchLObSv6b0pc8UNPcOJINGC\nYPL5oe9NkB+vAODUfQZubbnY6etGKGpJoiXEJuKUXEZ/LiXFZsgnoLgmBHslLu9r+p7PqRfmmT9d\npnNnkp49b6++C8Ustt555dteaK2ZOVmiOFujbTBOsj3YDDs/XiXTG/QEmx+t4Lk+prW687aEEAKk\npNgsSbiEuEKTbxY4/rNZEm1h3nhyklg2RLZ3eXp7Tb65wKHHJ7HCBqefn2f/JwaIpUO0bUswdaQA\nWtN5XUqSLSHEmpCSYvMk4RJrqrzg4Dk+8Wxow+2jVy24WBGDcMKiPG9QL3vL9tq5sSqRpE28JcT8\nSJnyfJ1YOsT17+2gY3vQWLRl4OLJnVP1GH5xHqfq0XtThsRlbl4thBCXUi+5jMgqxaZIwiXWzMTR\nAq/9YAKtNd3Xpdj9ns4N1RCzfXuC0dfy5EbLRNP2mVLfcmgZjDP2Wp562cUKmyQa+x6alkH71svr\n5H74R1NMHy9ihQ1mT5U48OkhrFVuGyGE2LxkL8XmSMIl1syxn88Qz9rYUZOxwwtsua2F2CJ7IK5X\niZYwBz45QGXBJZaxL9n2oRkdWxPc+gv9VBbqV9w3bGGiQrIjghUymB8p41S8dZtwlebrjB3KY0dN\n+m5IL9peQgixfoTiFn0HpKTYDEm4xJqJpUPkxip4rsayjUvuG7gereTqu0xPlEzPhaNm1ZLL4R9P\nUc7V2bK/la7ti3dt770pw7GnZ0FB62CccGJ9/nV36x4vPDKC72icmkcl77DrPWuz8XW14PD6ExOU\ncg5bD7TSs8yd+YXYLOollxFZpdiU9fkJLK4Ju97VwZGnp6mVPHa9u4NQZOMlXGvhyNPTzI2UiaZs\nXntignRHhGjqwhGwgb1ZMt1RPFeT7oqs2zly9bKHU/HI9sZwah65scqaxXL06RkK03ViWZvDP5oi\n0xvdUKOuQqwmf60D2GAk4RJrJpKwufH9PWsdxrrh1DzKeYdoyr5o8lkruoRiFnbURM9pXGfxjz2l\nFOmu5ZtXtpTZkRKzp8ukOyN0bmt+j8RI0iLVGWVuuIzWmu13XXk7javl1jysiIEZMkCD78okFSEW\nE4pb9EtJsSmScAmxDlRLLge/PUyl4BCKWux/qG/JkZUt+1t4+bvjVBbqdO9MEc+u3QhMfrLCC4+M\nYkdMTj4/z94PQceW5pIuwzS4+UPd5MYqmCGTTHdkhaK9tC23t/Hyd0bJjVbo2ZMm3iKjW0Ispl5y\nGZaSYlMk4RJiHZgdLlFecGjtizE/XmHyWIEtty7+r8fWvjjv+OUh3LpPNGWv6crOct4BpYLGrJNV\nCtN1OrY0/zpWyKRt6PJWX66kdGeEOz+zBa/uE4qZG2rVrBBifZOES4h1IByz0J6mVnJxa94ltyAK\nJuuvUnAXkeqIYNoGcyNllILWS/QG2wgs21i3qzmFWC+kpNg8SbiEWAda+2Ncd3cHU8cK7Lizna4d\nqYsePzdWZvi1HIlsmMGbs2uWIMQzIQ58rJ/iTI1YJkSyTZqrCnEtqJdcTktJsSmScAmxDiil6Nqe\nJNESIp65eNf98oLDc383gh21GH+zgO9pdty+dhPN45kg5uXkOj4TRxbwHE3XjiThmHxUCbGeaGQv\nxWbJp5gQi/B9jef62KvUgLO8UOeZbw1Tr7iYlsEdHx0g2br4aFGt5KI1JLIhDFOxMF1dlRhX0xtP\nTTH6eh7DVIy9ucDtvziwbttaCHEtCsUtBqSk2BRJuIQ4T36mysFHR6iVPbbd0sJ1t7ev+HvOjVWo\nl11a++LMT1SYPFFYMuFKtgalu9mRMgDX3bXy8a22qeNFWnpjGKZibrRMveIRucS8NiHE6qmXXE5J\nSbEp8gkmxHne+Nk0CmjpinLs+Tl6dqRIrvDGz9Gkje9rSrk6Ts27aInOCpnsf6CP/FSNcMzclJtS\nd+1IcvqVHEpBtjtKKCpNcYVYb6Sk2BxJuIQ4j2EqfB9Ao9GsRmeA1t4Ye9/fw+TxIltvbaHrEg1E\nrZBJa9/GXxG4lOvf2U5rXwzP9WkfSkg5UYh1JhS3GJSSYlMk4RLiPLvubOe5x0bJTdXYdVcHiezq\njCD17EjRc4nViavJ9zUnXppjfrxC944UvasYm2EaV9S1XgixOuoll5NSUmyKJFxCnCeRDfOuT23F\n93VTIyuTpwrMjlVo643RMbD2TTyv1sgbeV7/6TSJrM1Lj48RS9pkV2GrICGE2Iwk4RJiCc0kW9Mj\nJf7xOyOEoxZHnp/hnR8dorVn5Up+1ZLDydfmARi6oYXICrRNKOXqhGMmsVSI8oJLteQu+3sIITYm\njWxe3SxJuIRYBvmZKpZlkG6L4I75LMzVVizh0lpz8LFR8jM1lIKZ0Qrv/Ojgsr9Pz44Upw/lmR0t\nE0vZtHTL6JYQIhCOWwzJHK6mSMIlxDJo643zhp5mZrSEYShaVzA58T1NbqZKa3eQ0M2OlfFcH9Na\n3m7z6fYId39iiErBIdkSJhSRlYJCiEBN5nA1TRIuIZZBpj3CPR/fQmGuRqo1THIFJ9qblkHfzjSn\nD+UAGNidWfZk6y2xpE0saa/IawshNrb10BZCKdUC/BUwBJwEHtZaz593zF7gD4EU4AG/o7X+q8Zz\nfwy8C8g3Dv+81vrFlYhVEi4hlkmqJUxqlXpi3XhPJz2NVXxtffFVeU8hhHjLOiopfgl4Qmv9ZaXU\nlxr3f/O8Y8rAZ7XWR5RSPcBzSqnvaa1zjef/T631N1c6UEm4hNiATNPYFCshhRAb0zoqKT4IvLtx\n+0+Af+C8hEtr/eZZt8eUUlNAO5BjFa1MHUIIIYQQm5q/TF9Am1Lq4FlfX2wijE6t9Xjj9gTQebGD\nlVIHgBBw7KyHf0cp9bJS6itKqRUrU8gIlxBCCCGaEopbbFm+kuKM1nrfUk8qpX4AdC3y1G+dfUdr\nrZVSS04tU0p1A38KfE5r/VZXi39FkKiFgK8SjI79dnPhXx5JuIQQQgjRlHrJ5cQqlRS11vcu9ZxS\nalIp1a21Hm8kVFNLHJcCvgP8ltb6mbNe+63RsZpS6n8Cv7GMoZ9DSopCCCGEaJpepq+r9Ajwucbt\nzwF/e/4BSqkQ8C3ga+dPjm8kaSilFPAQ8OrVh7Q4GeESQgghRFNCcYut62OV4peBbyilvgCcAh4G\nUErtA35Va/0rjcfuAVqVUp9vnPdW+4c/V0q1Awp4EfjVlQpUEi4hhBBCNKVWcjm2DlYpaq1ngfct\n8vhB4Fcat/8M+LMlzn/vigZ4Fkm4hBBCCNG09dD4dCORhEsIsSStNYdfmGH42ALdgwl23daOacrU\nTyGudeH1U1LcMCThEkIsafxUkVd+NkmmI8qhZ6dJpsMMXpdZ67CEEGssKCnOrHUYG4okXEKIJdWr\nLoapiEQtLNugVnHXOiQhxDohJcXmSMIlhFhS10CSRCbMzFiJSNSid2tqrUMSQqwD4bjJNikpNkUS\nLiHEkiIxi/f94lZKC3WiCZtQ2FzrkIQQ60Ct5K2LVYobiSRcQoiLsmyDdGtkrcMQQqwry9S29Boi\nCZcQQgghmhKOW2w70LbWYWwoknAJIYQQoinVkssRWaXYFGmoI4QQQgixwmSESwghhBBNicQttktJ\nsSmScAkhhBCiKVJSbJ4kXEIIIYRompZVik2RhEsIIYQQTQnHLXZISbEpknAJIYQQoim1ksubUlJs\niiRcQgghhGiaFBSbIwmXEEIIIZoSjlvslJJiUyThEkIIIURTqiWXw1JSbIokXEIIIYRonlrrADYW\nSbiEEEII0ZRI3GLnfikpNkMSLiGEEEI0pVpyeeNZKSk2QxIuIYQQQlwBWafYDEm4hBBCCNGUSNzi\nuv3tax3GhiIJlxBCCCGaEpQUp9c6jA1FEi4hhBBCNEUjeyk2SxIuIYQQQjQlGre4XkqKTZGESwgh\nhBBNqZRcXpeSYlMk4RJCCCFE86TxaVPWJOFSSrUAfwUMASeBh7XW84sc9xhwB/ATrfWHVzNGIYQQ\nQiwuIiXFpq3VCNeXgCe01l9WSn2pcf83Fznu94AY8M9WMzghhBBCLK1acjkkJcWmGGv0vg8Cf9K4\n/SfAQ4sdpLV+AiisVlBCCCGEuFx6mb6uDWs1wtWptR5v3J4AOtcoDiGEEEI0KRK32CUlxaasWMKl\nlPoB0LXIU7919h2ttVZKXVWKq5T6IvBFgIGBgat5KSGEEEJcgpQUm7diCZfW+t6lnlNKTSqlurXW\n40qpbmDqKt/rq8BXAfbt23ftjE8KIYQQa0Cj8a+hcuByWKuS4iPA54AvN/77t2sUhxBCCCGaFI3b\n7N7fsdZhbChrlXB9GfiGUuoLwCngYQCl1D7gV7XWv9K4/xRwPZBQSo0AX9Baf2+NYhZCCCEEUCk5\nHHr2qopTy6KJNlMe8Erj7mmt9QONx7cAXwdageeAz2it6ysR65qsUtRaz2qt36e13qG1vldrPdd4\n/OBbyVbj/t1a63atdVRr3SfJlhBCCLFerItVim+1mdoBPNG4v5iK1npv4+uBsx7/d8BXtNbbgXng\nC1cb0FKk07wQQgghmrKOSooPAu9u3P4T4B9YvK/nBZRSCngv8Omzzv+3wB8uZ4BvkYRLCCGEEE2p\nlBxeXb6SYptS6uBZ97/aWAx3OS63zVSk8R4u8GWt9bcJyog5rbXbOGYE6G0y9ssmCZcQQgghmraM\naxRntNb7lnpymdpMDWqtR5VSW4EfKqVeAfJXHPEVkIRLCCGEEE2JxG32rFJJcTnaTGmtRxv/Pa6U\n+gfgFuB/ARmllNUY5eoDRpf9G2iQhEsIIYQQTVnmkuLVuGSbKaVUFihrrWtKqTbgHcDvNkbEngQ+\nRrBScUXbVK3VXopCCCHEspibq/D3j7zJt//mDSYnimsdzjVDL9P/rtKXgfuUUkeAexv3UUrtU0r9\n98Yxu4CDSqmXgCcJ5nAdajz3m8C/VEodJZjT9UdXG9BSZIRLCCHEhvaD7x/Hc31MS/H494/zqV+6\nAdOU8YSVt/ad5rXWs8D7Fnn8IPArjdtPAzcucf5x4MBKxvgWSbiEEEJsWFprymWH1pYohqEoFEq4\nri8J1wqLxi1u2L/UgkCxGEm4hBBCbFhKKW6/o5enfzKMBm65tYtwWH61rbRKyeXlZyfXOowNRX4q\nhRBCbGi7drfT159Ca0ilwmsdjhCLkoRLCCHEhpdMSqK1mqJxixulpNgUSbiEEEII0ZSgpDix1mFs\nKJJwCSGEEKIpGvDXOogNRhIuIYQQQjQlFre4SUqKTZGESwghhBBNKcsqxaZJwiWEEEKIJmn8ddD4\ndCORhEsIIYQQTYnGbW7e37XWYWwoknAJIYQQoimVksOLz46vdRgbiiRcQgghhGiKZj3spLixSMIl\nhBBCiKbE4jZ7paTYFEm4hBBCCNGUcsnhBWl82hRJuIQQQgjRNK2kqNgMSbiEEEII0RQpKTZPEi4h\nhBBCNKVccnheVik2RRIuIYQQQjRF9lJsniRcQgghhGhKLG5z6/7utQ5jQ5GESwghhBBNKZccnnt2\nbK3D2FAk4RJCCCFEU2Jxm9tkhKspSuvNtaxTKTUNnLrEYW3AzCqEI94m13z1yTVfXXK9V59c87cN\naq3bV+vNlFKPEVz/5TCjtf7AMr3WurXpEq7LoZQ6qLXet9ZxXEvkmq8+uearS6736pNrLjYSY60D\nEEIIIYTY7CThEkIIIYRYYddqwvXVtQ7gGiTXfPXJNV9dcr1Xn1xzsWFck3O4hBBCCCFW07U6wiWE\nEEIIsWo2XcKllPqAUuqwUuqoUupLizx/j1LqeaWUq5T62FmP71VK/Uwp9ZpS6mWl1CdWN/KN60qv\n+VnPp5RSI0qpP1idiDe2q7neSqkBpdT3lVKvK6UOKaWGVivujewqr/nvNj5XXldK/b5SSq1e5BvT\nZVzvf9n4+X1ZKfWEUmrwrOc+p5Q60vj63OpGLsTSNlXCpZQygf8EfBDYDXxKKbX7vMNOA58H/uK8\nx8vAZ7XWe4APAP9RKZVZ2Yg3vqu85m/5f4Afr1SMm8kyXO+vAb+ntd4FHACmVi7azeFqrrlS6i7g\nHcBNwA3AfuBdKxzyhnaZ1/sFYJ/W+ibgm8DvNs5tAf4NcDvBz/e/UUplVyt2IS5mUyVcBH/Bjmqt\nj2ut68DXgQfPPkBrfVJr/TLn7buptX5Ta32kcXuM4BfRqjWR28Cu+JoDKKVuAzqB769GsJvAFV/v\nxi8tS2v9eOO4ota6vEpxb2RX8zOugQgQAsKADUyufMgb2uVc7yfP+tl9Buhr3L4feFxrPae1ngce\nJ/gHtBBrbrMlXL3A8Fn3RxqPNUUpdYDgA/LYMsW1mV3xNVdKGcB/AH5jBeLarK7mZ3wnkFNK/Y1S\n6gWl1O81RhPExV3xNdda/wx4EhhvfH1Pa/36ske4uTR7vb8AfPcKzxVi1Wy2hOuqKaW6gT8F/qnW\n+oIRGbGs/nfgUa31yFoHco2wgLsJEtz9wFaCMphYIUqp7cAughGYXuC9Sqm71zaqzUMp9cvAPuD3\n1joWIS5lsyVco0D/Wff7Go9dFqVUCvgO8Fta62eWObbN6mqu+Z3ArymlTgL/HvisUurLyxvepnM1\n13sEeLFRqnGBbwO3LnN8m9HVXPOPAs80yrdFgpGYO5c5vs3msq63Uupe4LeAB7TWtWbOFWItbLaE\n61lgh1Jqi1IqBHwSeORyTmwc/y3ga1rrb65gjJvNFV9zrfUvaa0HtNZDBKMuX9NaX7AiSZzjiq93\n49yMUuqtuYnvBQ6tQIybzdVc89PAu5RSllLKJpgwLyXFi7vk9VZK3QL8V4Jk6+yFH98D3q+UyjYm\ny7+/8ZgQa25TJVyNf7X/GsFfsNeBb2itX1NK/bZS6gEApdR+pdQI8HHgvyqlXmuc/jBwD/B5pdSL\nja+9a/BtbChXec1Fk67memutPYLE9gml1CuAAv7bWnwfG8lV/ox/k2Au6CvAS8BLWuu/W/VvYgO5\nnOtNUEJMAH/d+Kx+pHHuHMGq52cbX7/deEyINSed5oUQQgghVtimGuESQgghhFiPJOESQgghhFhh\nknAJIYQQQqwwSbiEEEIIIVaYJFxCCCGEECtMEi4hrkFKqSeVUvef99i/UEr94RLHDymlXr3Eaw4p\npT591v19Sqnfb9z+vFLqDxq3f1Up9dmzHu+52u9HCCHWO0m4hLg2/SVBQ8mzfbLx+JUaAs4kXFrr\ng1rrf37+QVrr/6K1/lrj7ucBSbiEEJueJFxCXJu+CXyo0ckbpdQQQeLzVGNT61eVUq8opT5x/omN\nkaynlFLPN77uajz1ZeDuRiPKX1dKvVsp9feLnP9vlVK/oZT6GME+eH/eOOdDSqlvn3XcfUqpby3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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7dc5f86710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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73v6+hngWaJk5uv37w8KFcMYZXvn4LaGkxOu/cKE3XhMYNGgQy5YtY9KkSRxz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0sFabngxrqG6Q7C9FhjnlKSpKA6WeOsBXDHyoUbf9vK+olqxYUhYz8z/1EMyp0dONNTt2HB3RPT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\nzf4fV3SVEgnu/QsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7dc46bbda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "plt.scatter(port_info[0,:],port_info[1,:],c=port_info[2,:],cmap='plasma', marker='o', s=10, alpha=0.3)\n",
    "plt.colorbar(label='Sharpe Ratio')\n",
    "plt.xlabel('Volatility')\n",
    "plt.ylabel('Returns')\n",
    "plt.scatter(sdp,rp,marker='*',color='r',s=500, label='Maximum Sharpe ratio')\n",
    "plt.scatter(sdp_min,rp_min,marker='*',color='b',s=500, label='Minimum volatility')\n",
    "plt.show()\n",
    "\n",
    "#\n",
    "plt.figure(figsize=(10, 7))\n",
    "#Assign data to axis, Vol,Returns, C= Sharpe Ratio, Cmap = 'Style'\n",
    "plt.scatter(port_info[0,:],port_info[1,:],c=port_info[2,:],cmap='plasma')\n",
    "#Label Colorbar\n",
    "plt.colorbar(label='Sharpe Ratio')\n",
    "#Label Maximum Sharpe and Minimum Vol\n",
    "plt.scatter(sdp,rp,marker='*',color='b',s=500, label='Maximum Sharpe ratio')\n",
    "plt.scatter(sdp_min,rp_min,marker='*',color='r',s=500, label='Minimum volatility')\n",
    "#Provide a title\n",
    "plt.title('Portfolio Optimization - Efficient Frontier')\n",
    "plt.grid(True)\n",
    "#Label X and Y Access\n",
    "plt.xlabel('Volatility')\n",
    "plt.ylabel('Returns')\n",
    "plt.legend(labelspacing=0.8)\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimization - Maximum Sharpe Ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     fun: -1.7127920851531224\n",
       "     jac: array([ 0.11540911,  0.13836393, -0.05567932, -0.05621485,  1.72263229,\n",
       "       -0.04763238,  0.20887129,  0.32444508, -0.05409127, -0.02379861])\n",
       " message: 'Optimization terminated successfully.'\n",
       "    nfev: 62\n",
       "     nit: 5\n",
       "    njev: 5\n",
       "  status: 0\n",
       " success: True\n",
       "       x: array([0.00000000e+00, 2.99973863e-16, 2.67967210e-01, 7.21511770e-01,\n",
       "       0.00000000e+00, 2.40231153e-16, 3.80254917e-16, 3.40411189e-17,\n",
       "       1.05210201e-02, 2.47228194e-16])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def optim_info(weights, returns, cov_mat):\n",
    "    pvol = np.sqrt(np.dot(weights.T,np.dot(cov_mat, weights)))\n",
    "    pret = np.sum(weights*log_returns.mean())*252\n",
    "    return np.array([pret,pvol,(pret-Rf)/pvol])\n",
    "    \n",
    "def neg_sharpe_ratio(weights, returns):\n",
    "    return -optim_info(weights,returns, cov_mat)[2]\n",
    "\n",
    "\n",
    "args = (log_returns.mean(), cov_mat, Rf)\n",
    "constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "bound = (0.0,1.0)\n",
    "bounds = tuple(bound for x in range(number_assets))\n",
    "optimized = sco.minimize(neg_sharpe_ratio, weights, args=log_returns.mean(),\n",
    "                        method='SLSQP', bounds=bounds, constraints=constraints)\n",
    "optimized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        GOOGL   FB   NFLX   AMZN  BBBY  COST  DLTR  FOX  \\\n",
      "Max_Sharpe_Opt_Weights    0.0  0.0  0.268  0.722   0.0   0.0   0.0  0.0   \n",
      "\n",
      "                         Gold  PEP  \n",
      "Max_Sharpe_Opt_Weights  0.011  0.0  \n",
      "Expected return, volatility and Sharpe ratio: [0.47364764 0.26777777 1.71279209]\n"
     ]
    }
   ],
   "source": [
    "Max_Sharpe_Opt_Weights = pd.DataFrame(optimized['x'].round(3),returns.columns, columns=['Max_Sharpe_Opt_Weights'])\n",
    "print(Max_Sharpe_Opt_Weights.T)\n",
    "print(\"Expected return, volatility and Sharpe ratio:\",optim_info(optimized['x'], returns, cov_mat))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Optimization - Minimum Volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     fun: 0.11677811988473649\n",
       "     jac: array([0.1163002 , 0.11686035, 0.12823888, 0.11702894, 0.11676697,\n",
       "       0.11678104, 0.11672872, 0.11697163, 0.11677704, 0.1167593 ])\n",
       " message: 'Optimization terminated successfully.'\n",
       "    nfev: 120\n",
       "     nit: 10\n",
       "    njev: 10\n",
       "  status: 0\n",
       " success: True\n",
       "       x: array([2.31577338e-02, 1.98342299e-02, 2.46655994e-18, 2.30710584e-02,\n",
       "       6.39532523e-02, 1.37796023e-01, 4.20950184e-03, 7.77675190e-02,\n",
       "       7.65168192e-02, 5.73693862e-01])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def portfolio_volatility(weights, mean_returns, cov_mat):\n",
    "    return optim_info(weights, mean_returns, cov_mat)[1]\n",
    "\n",
    "\n",
    "args = (log_returns.mean(), cov_mat)\n",
    "constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "bound = (0.0,1.0)\n",
    "bounds = tuple(bound for asset in range(number_assets))\n",
    "optimized1 = sco.minimize(portfolio_volatility, number_assets*[1./number_assets,], args=args,\n",
    "                        method='SLSQP', bounds=bounds, constraints=constraints)\n",
    "optimized1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     GOOGL    FB  NFLX   AMZN   BBBY   COST   DLTR    FOX  \\\n",
      "Min_Vol_Opt_Weights  0.023  0.02   0.0  0.023  0.064  0.138  0.004  0.078   \n",
      "\n",
      "                      Gold    PEP  \n",
      "Min_Vol_Opt_Weights  0.077  0.574  \n",
      "Expected return, volatility and Sharpe ratio: [0.05864926 0.11677812 0.37377944]\n"
     ]
    }
   ],
   "source": [
    "Min_Vol_Opt_Weights = pd.DataFrame(optimized1['x'].round(3),returns.columns, columns=['Min_Vol_Opt_Weights'])\n",
    "print(Min_Vol_Opt_Weights.T)\n",
    "\n",
    "print(\"Expected return, volatility and Sharpe ratio:\",optim_info(optimized1['x'],returns, cov_mat))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimize Portfolios for a Target Return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                             GOOGL     FB   NFLX   AMZN   BBBY   COST   DLTR  \\\n",
      "Efficient_Portfolio_Weights   0.02  0.016  0.003  0.058  0.029  0.153  0.009   \n",
      "\n",
      "                               FOX   Gold    PEP  \n",
      "Efficient_Portfolio_Weights  0.075  0.077  0.559  \n",
      "Expected return, volatility and Sharpe ratio: [0.09       0.11764915 0.63748869]\n"
     ]
    }
   ],
   "source": [
    "def efficient_return(mean_returns, cov_matrix, target):\n",
    "    num_assets = len(mean_returns)\n",
    "    args = (mean_returns, cov_matrix)\n",
    "\n",
    "    def portfolio_return(weights):\n",
    "        return optim_info(weights, mean_returns, cov_mat)[0]\n",
    "\n",
    "    constraints = ({'type': 'eq', 'fun': lambda x: portfolio_return(x) - target},\n",
    "                   {'type': 'eq', 'fun': lambda x: np.sum(x) - 1})\n",
    "    bounds = tuple((0,1) for asset in range(num_assets))\n",
    "    eff_port_return = sco.minimize(portfolio_volatility, weights, args=args, method='SLSQP', bounds=bounds, constraints=constraints)\n",
    "    return eff_port_return\n",
    "\n",
    "\n",
    "Target_Portfolio = efficient_return(log_returns.mean(),cov_mat, .09) #Adjust Last Param for Target Vol\n",
    "Efficient_Portfolio_Weights = pd.DataFrame(Target_Portfolio['x'].round(3),returns.columns, columns=['Efficient_Portfolio_Weights'])\n",
    "print(Efficient_Portfolio_Weights.T)\n",
    "print(\"Expected return, volatility and Sharpe ratio:\",optim_info(Target_Portfolio['x'],returns, cov_mat))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimized Portfolios within a Range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def efficient_frontier(mean_returns, cov_matrix, returns_range):\n",
    "    efficients = []\n",
    "    for ret in returns_range:\n",
    "        efficients.append(efficient_return(mean_returns, cov_matrix, ret))\n",
    "    return efficients\n",
    "\n",
    "returnsRange = np.linspace(0.0,0.5,50) \n",
    "eff_RangePorts=efficient_frontier(log_returns.mean(),cov_mat,returnsRange)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7dc41e09e8>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lrZ9E0h6ewDXCEAZCiGmisxM2bLCf19dDVxdUVOQ3pmMUDHhYMUma6iaaJE5i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\noz/i3HPP5eSTT2bt2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uAP/mCPthyqUqnEJZdcwt13382//uu/snr16nG5rjHGmP2xVN20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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7dc437de48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 7))\n",
    "plt.scatter(port_info[0,:],port_info[1,:],c=port_info[2,:],cmap='YlGnBu', marker='o', s=10, alpha=0.3)\n",
    "plt.colorbar()\n",
    "plt.scatter(sdp,rp,marker='*',color='r',s=500, label='Maximum Sharpe ratio')\n",
    "plt.scatter(sdp_min,rp_min,marker='*',color='g',s=500, label='Minimum volatility')\n",
    "\n",
    "target = np.linspace(rp_min, 0.32, 250)\n",
    "efficient_portfolios = efficient_frontier(log_returns_means, cov_mat, target)\n",
    "plt.plot([p['fun'] for p in efficient_portfolios], target, linestyle='-.', color='black', label='efficient frontier')\n",
    "plt.title('Calculated Portfolio Optimization based on Efficient Frontier')\n",
    "plt.xlabel('annualised volatility')\n",
    "plt.ylabel('annualised returns')\n",
    "plt.legend(labelspacing=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7dc4475588>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XaN++PaGhoXzyyScAxMXFERkZSb9+/bj99tsZNGgQWmvef/99jh8/TpcuXejSpUuR4k1O\nTqZ58+YMGTKE1q1bc+TIEWJjYwkJCaF169a8/PLLzrJBQUFMmjSJsLAwOnTowKlTp/j5559ZuXIl\nL730EuHh4Rw8eJDo6Ghnq15CQgL33HMP7dq1o1u3bpw4cQIwEsmxY8cSERHBP//5z1J7/YUQQghv\nVD6aMMpYZGRkoWWioqIYP368s3x0dDTR0dGcPXs2T6tRXFxcoedLT08nPDzcuf3KK6/w5JNPsnnz\n5hwtUUFBQSQmJgIQExPjLD9o0CAmTpxI3759ycjIICsri9Onry71+sUXX1C1alW2bdvGlStX6NSp\nE/fffz8Av/32G0lJSdSrV49OnTrx008/MXr0aN59911++OEHty1v2df09/cHYP369QDs37+fuXPn\n0qFDB44fP87LL79MQkIC1atX5/7772f58uX06dOHtLQ0OnTowJQpU5gwYQKfffYZkydPplevXm5b\n3qxWK88//zwrVqygVq1afPXVV0yaNInZs2cDkJmZKWvWCiGEEFTQ5M0T/P39nUlZcaWkpHDs2DH6\n9u0LGBPE5vbvf/+bHTt2OFuxLl68yP79+/H19eWOO+4gODgYgPDwcJKTk7n77rsLve7ChQtzdJum\npKRwyy230KFDBwC2bdtGZGQk2ataDBo0iE2bNtGnTx98fX2JiooCoF27dqxdu7bAa/3+++/s2rWL\n++67DzBaEuvWres8PmDAgELjFUIIISqCCpm8FaWlLL/yNWvWLHb9sqC15oMPPqBbt2459sfFxVGp\nUiXnttlsxmazlfg6gYGBRSpnsVic02kU5Zpaa1q1asUvv/xyTdcVQgghbnQy5s0LVK5cmeDgYJYv\nXw7AlStX8jwl2q1bN2bNmoXVagVg3759pKWlFXrelJSUEsd1xx13sHHjRs6ePYvdbic2NpZ77rmn\nRNds3rw5Z86ccSZvVquVpKSkEscmhBDCPZs9i0sZVuxZN9YDixWJJG9lJHvMW/bXxIkTi1V//vz5\nvP/++4SGhtKxY0dOnjyZ4/iTTz5Jy5Ytadu2La1bt+bpp58utLVrxIgRdO/evcgPLORWt25dpk6d\nSpcuXQgLC6Ndu3b07t27wDoDBw7knXfeoU2bNhw8eNC539fXlyVLlvDyyy8TFhZGeHg4P//8c4ni\nEkIIkdMVm51lvx3l/hkbaTp5De3+spbbJq2m24yNLPvtKFds9nzrKqUYN26cc3v69OnOMdkxMTHU\nr18/z2dbZGRknnHKS5cu5d5773Vub968mfDw8GvqDaqoZKoQIUpI3ldCCG+QeOQC0bO3YrVnkZaZ\nN0kL9DVjMZuYO+wOwhpUy3Pcz8+PunXrsm3bNmrWrMn06dNJTU0lJiaGmJgYgoKCnA/4Zctvuqke\nPXrw+OOP079/f9q1a8fHH39Mx44dS/eGvYxMFSKEEEIIp+1HLvDop1u4kG51m7gBpGXauZBuZeCn\nW9h+5EKe4z4+PowYMYIZM2ZcczwffvghkydPJiYmhvbt21f4xK2kJHkTQgghbkBXbHaGzt5KujX/\nLlFX6VajvLsu1FGjRrFw4UIuXryY59iMGTOc3abff/99gde49dZbGTBgAB9++CHTpk0r2o2IPCR5\nK4ibFRGEEEIIb7B65wms9qxi1bHas1iz82Se/VWqVGHIkCG8//77eY698MILJCYmkpiYmGfGg9zs\ndjtr164lKCiIw4cPFys2cZUkb/k5cQJq1zb+FUIIIbzMrLiD+XaV5ict086suANuj40dO5Yvvvii\n0JkMCvLRRx8REhLCF198wahRo7jRxt2XFUne8rNsGaSng2N6DiGEEMJb2LM0+0+XrPdo3+lUt9OI\n1KhRg0ceeYQvvviiROc9efIk7777Lm+//Tbdu3enfv36fP755yU6V0UnyVt+vvwy579CCCGEl0jL\ntOFjUiWq62NSpGW6n75j3LhxnD17tkjnefDBBwkODiY4OJj+/fvz4osvMmHCBOeqPO+99x5Tpkzh\n/PnzJYqzIquQKywU6swZ2LHD+H77djh7FvJZ/1MIIYQobwJ9fbCVcBJeW5Ym0PdqepDqMv67Tp06\nOSaJd12D21VRViJq0KABycnJJYqxopOWN3dWrACLxfjeYjG2hRBCCC9hNima1g4qUd1mtYMwl7DV\nTpQNSd7cmTMHsgdkpqUZ20IIIYQXeSayCYG+5mLVCfQ180zkbdcpIlFaJHnL7cIF2LYt576tW439\n10ApxeOPP+7cttls1KpVi6ioqBKdb+XKlUydOvWaYroWq1atok2bNoSFhdGyZUs++eQTAKKjo1my\nZInH4iqq5ORkFi1a5NyOj49n9OjRHoxICCFKV4+QuljMxfuYt5hNPBBy83WKSJSWijfm7ddfYcOG\n/I/v2QO+vpCZeXWfry+MHw+3355/va5doW3bfA8HBgaya9cu0tPT8ff3Z+3atdSvX78EN2Do1asX\nvXr1KnH9a2G1WhkxYgRbt24lODiYK1eulMq4Ba01WmtMptL5m8Jms+Hj4/4tnp28PfbYYwBERETk\nWcZFCCG8WSUfM3OH3cHAT7cUaaJef4tRvpJP8VrrRNmreC1vx4/Dq6/ChAnwyit5v+bNyzs5b2oq\nzJ3rvvyECcb5jh8v9NI9evTgu+++AyA2NpZHH33UeWzr1q3cddddtGnTho4dO/L7778DxszVw4YN\nA2Dnzp20bt2ay5cvM2fOHJ577jnAaO165pln6NChA7feeitxcXEMGzaMFi1aEB0d7bxGUNDV8Q9L\nlixxHitq/WwpKSnYbDZuuukmACpVqkTz5s2dxzdt2kTHjh259dZbna1wqamp3HvvvbRt25aQkBBW\nOMYRJicn07x5c4YMGULr1q05cuQIQUFBvPDCC7Rq1Yp7772XM2fOAHDw4EG6d+9Ou3bt6Ny5M3v3\n7s0TW0xMDIMHD6ZTp04MHjyY5ORkOnfuTNu2bWnbtq1zsfuJEyfy448/Eh4ezowZM4iLi3O2gp4/\nf54+ffoQGhpKhw4d2JH98IoQQniZsAbVWDyiA9X8Lfl2oQb6mqnmb2HxiA5u1zYV5VB2a8eN8tWu\nXTud2+7du3PuSErS+tZbtfb31xpK/uXvb5wnKSnPNXMLDAzU27dv1w8//LBOT0/XYWFh+ocfftAP\nPvig1lrrixcvaqvVqrXWeu3atfqhhx7SWmttt9t1586d9dKlS3W7du305s2btdZaf/nll3rUqFFa\na62HDh2qBwwYoLOysvTy5ct15cqV9Y4dO7Tdbtdt27bVv/32mzOGbN98840eOnRoseq7Gj58uK5V\nq5YeOHCgXrBggbbb7c5z9evXT9vtdp2UlKSbNGmitdbaarXqixcvaq21PnPmjG7SpInOysrSf/zx\nh1ZK6V9++cV5bkAvWLBAa631m2++6bzPrl276n379mmttd6yZYvu0qVLnrjeeOMN3bZtW3358mWt\ntdZpaWk6PT1da631vn37dPb7w/W1z7393HPP6ZiYGK211uvXr9dhYWFuf6Z53ldCCFFOZVhtetmv\nR/X978bpRhNX6dte/U43mrhK3//uRr3s16M6w2rzdIgVFhCvi5nrVLxuU4CWLSEpCZ5/HhYtApfH\nnossIAAeeww++AD8/IpUJTQ0lOTkZGJjY+nRo0eOYxcvXmTo0KHs378fpRRWqxUAk8nEnDlzCA0N\n5emnn6ZTp05uz92zZ0+UUoSEhFCnTh1CQkIAaNWqFcnJyYSHhxcYW3Hrf/755+zcuZN169Yxffp0\n1q5dyxzHgx19+vTBZDLRsmVLTp06BRh/JLz66qts2rQJk8nEsWPHnMduueUWOnTo4Dy3yWRiwIAB\nADz++OM89NBDpKam8vPPP9O/f39nuStXrri9l169euHv7w8YXbzPPfcciYmJmM1m9u3bV+DrALB5\n82b+9a9/AdC1a1fOnTvHpUuXqFKlSqF1hRCiPKrkY6ZPm/r0aVMfe5YmLdNGoK+PPFXqpSpm8gZG\nwvXZZxAVBYMHG6sp2NxPSpiDj4+RuM2fDyUYc9arVy/Gjx9PXFwc586dc+5/7bXX6NKlC8uWLSM5\nOZnIyEjnsf379xMUFMTxArpmK1WqBBiJT/b32ds2x30pdfWXNCMjo9j1cwsJCSEkJITBgwfTuHFj\nZ/LmWl87lj5ZuHAhZ86cISEhAYvFQqNGjZwxBAYG5ntf2XFnZWVRrVo1EhMTCyyb+3wzZsygTp06\nbN++naysLPyKmGgLIcSNymxSVPGzeDoMcQ0q3pi33Hr3ht27ITwcCkkiCAyENm2M8iV8WGDYsGG8\n8cYbzpatbBcvXnQ+wDDHZWqSixcvMnr0aDZt2sS5c+eu6UnOOnXqsGfPHrKysli2bFmJz5Oamppj\nAsbExERuueWWAutcvHiR2rVrY7FY+OGHHwpckDgrK8t5n4sWLeLuu++mSpUqNG7cmG+++QYwksLt\n27cXGuvFixepW7cuJpOJ+fPnY7cbg3YrV65MSkqK2zqdO3dm4cKFgDHRZM2aNaXVTQghRLkhyRtA\ncDBMmgSFPeVoMhnlruEp0eDgYLdTUkyYMIFXXnmFNm3a5GjpeuGFFxg1ahTNmjXjiy++YOLEiZw+\nfbpE1546dSpRUVF07NiRunXrlvgetNa8/fbbNG/enPDwcN54440cCac7gwYNIj4+npCQEObNm8ft\nBTy5GxgYyNatW2ndujUbNmzg9ddfB4zWuy+++IKwsDBatWrlfOihIM8++yxz584lLCyMvXv3Olvl\nQkNDMZvNhIWFMWPGjBx1YmJiSEhIIDQ0lIkTJzJ37txCryOEEEKUFZXdrXWjiIiI0PHx8Tn27dmz\nhxYtWhRc8aGHjMXoC/Pww+AF85h5s6CgoBzLsZRXRXpfCSGEEAVQSiVorYs1V5W0vIExp9v33+fd\n7zJ2y2nNmpxzwAkhhBBClCFJ3gDWrzceRMimlPFQwvDhxr8uA/3x8Sl4kl9xzbyh1U0IIYTwFEne\nABYsgOzB6/7+0KQJJCSQOmMaxMcb246pJ0hJMcoLIYQQQniAJG82G6xcaUy7GxAAQ4bAzp2cqF+V\n2u/U5kRwNdi505hOJCDAKLdiRdGmFRFCCCGEKGWSvG3caCx/VaUKfPUVfPwx+PmxbO8y0m3pLN+7\n3JgT7pNPYPFio1xqKmza5OnIhRBCCFEBSfKWmAgdOxoL0jvWtgT4MvHLHP8C0LOnMcdbx47w229l\nHakQQgghRAVeYSHbuHHGl4szaWfYccpYjHz7qe2cvXyWmgE1jYP168NPP5V1lEIIIYQQgLS8ubXi\n9xVYTMbSIRaThRV7C58MVgghhBCiLEjy5sacxDmkWdMASLOmMSdxjmcDEkJ4LZs9i0sZVuxZN9aE\n6EIIz5HkLZcLGRfYdnxbjn1bj2/lQsaFazqvUorHH3/cuW2z2ahVqxZRjnF2K1euZOrUqQWe4/jx\n4/Tr1++a4ihL0dHRha7FOmfOHI4fP+7cfvLJJ9m9ezcAjRo14uzZswB07NgRgOTkZBYtWnSdIhai\ndFyx2Vn221Hun7GRppPX0O4va7lt0mq6zdjIst+OcsVmL7D+8uXLUUqxd+9ewHjfK6WYPHmys8zZ\ns2exWCw899xzAHTr1o3w8HDnV7169bjzzjsB43exfv36XLlyxVm3UaNG1+HOhRBlocKNefv1xK9s\n+CP/SXb3nNmDr9mXTPvVVRR8zb6M//d4bq+Z/3qcXRt3pW3dtvkeDwwMZNeuXaSnp+Pv78/atWud\nC9ED9OrVi16FLHZfr169a1qYvjyaM2cOrVu3pl69egB8/vnnbsv9/PPPwNXk7bHHHiuzGIUojsQj\nF4ievRWrPYu0TCNJs9qNVrffT6Uyedku3ly5m7nD7iCsQTW354iNjeXuu+8mNjaWN998E4DGjRvz\n3Xff8de//hWAb775hlatWjnrfO+ySkxaWhrt2rVzlgUwm83Mnj2bZ555pnRvWAhR5ipc8nb80nFe\nXf8qtiwbZpPZbRlbVs453FIzU5m73f3i5PYsOz4mH5Y+srTA5A2gR48efPfdd/Tr14/Y2FgeffRR\nfvzxR8BIYuLj4/nwww+Jjo6mSpUqxMfHc/LkSd5++2369etHcnIyUVFR7Nq1izlz5rB8+XLS0tLY\nv38/48ePJzMzk/nz51OpUiVWr15NjRo1iIyMZPr06URERHD27FkiIiJITk4ucv1sFy9eJDQ0lD/+\n+AOTyURaWhq33347hw4dIimjcifLAAAgAElEQVQpiZEjR3L58mWaNGnC7NmzqV69eo57f+utt/j2\n229JT0+nY8eOfPLJJ/zrX/8iPj6eQYMG4e/vzy+//MIDDzzgjNdV9nqnEydOZM+ePYSHhzN06FCW\nLVvG+++/T3h4OAB33303M2fOJCwsrMCfhRDXw/YjF3j00y2kW/NvWTMSOjsDP93C4hEd8iRwqamp\nbN68mR9++IGePXs6k7eAgABatGhBfHw8ERERfPXVVzzyyCM5Wq6zjRkzhh49enDfffc5940dO5YZ\nM2bw1FNPlc7NCiE8psJ1m0Y1jyJxZCKNqzfGYrJgy7Ll+XLHXTmLyULj6o1JHJlIVPMot/VcDRw4\nkMWLF5ORkcGOHTucXRrunDhxgs2bN7Nq1SomTpzotsyuXbtYunQp27ZtY9KkSQQEBPDbb79x1113\nMW/evELjKU79qlWrEh4ezsaNGwFYtWoV3bp1w2KxMGTIEKZNm8aOHTsICQlxfti4eu6559i2bZuz\n9XHVqlX069ePiIgIFi5cSGJiIv7Zq1gUYOrUqXTu3JnExEReeOEFhg8fzpw5cwDYt28fGRkZkrgJ\nj7hiszN09tYCEzdX6VajfO4u1BUrVtC9e3eaNWvGTTfdREJCgvNY9v8hR44cwWw2O1usXS1dupT4\n+Hj+/ve/59jfsGFD7r77bubPn1+CuxNClCcVLnkDaFmrJUnPJjEodBABloASnSPAJ4BBoYNIejaJ\nlrVaFqlOaGgoycnJxMbG0qNHjwLL9unTB5PJRMuWLTl16pTbMl26dKFy5crUqlWLqlWr0rNnTwBC\nQkJITk4uNJ7i1h8wYABfffUVAIsXL2bAgAFcvHiRCxcucM899wAwdOhQNrmZwPiHH37gzjvvJCQk\nhA0bNpCUlFRofEXRv39/Vq1ahdVqZfbs2URHR5fKeYUortU7T2C1ZxWrjtWexZqdJ3Psi42NZeDA\ngYCRrMXGxjqPde/enbVr1zp//3I7duwYY8aMYdGiRVSqVCnP8VdeeYV33nmHrKzixSmEKF8qXLdp\nNj8fPz7r+RlRTaMYvGww6bb0fFvdXPmYfAjwCWD+Q/Pp1bzgMWru9OrVi/HjxxMXF8e5c+fyLef6\nH6/W7p9Scy1jMpmc2yaTCZtj+S4fHx/nf9QZGRnFrp879ldffZXz58+TkJBA165di7SIfEZGBs8+\n+yzx8fE0aNCAmJiYPLGUVEBAAPfddx8rVqzg66+/ztFKIURZmhV30DnGrajSMu3MijtAnzbG+Nfz\n58+zYcMGdu7ciVIKu92OUopRo0YB4OvrS7t27fjHP/7B7t27WblypfNcWmuGDh3KxIkTadnS/R+U\nTZs2JTw8nK+//rqEdymEKA8qZMubq96392b3qN2E3xxOoCWwwLKBlkDa3NyG3aN2lyhxAxg2bBhv\nvPEGISEhJapfXI0aNXImNNf6sENQUBDt27dnzJgxREVFYTabqVq1KtWrV3eO3Zs/f76zFS5bdqJW\ns2ZNUlNTc8RRuXJlUlJSihyDu/JPPvkko0ePpn379nnG2glRFuxZmv2nC/9Dxp19p1Od04gsWbKE\nwYMHc/jwYZKTkzly5AiNGzfmyJEjzvLjxo1j2rRpOcakAkyfPh0/Pz9nopefSZMmMX369BLFKoQo\nHyp88gYQXCWYSZ0nYVIFvxwmZWJS50nUr1K/wHIFXis4mNGjR5e4fnGNHz+eWbNm0aZNG+e0G9di\nwIABLFiwIEeXzdy5c3nppZcIDQ0lMTGR119/PUedatWq8dRTT9G6dWu6detG+/btnceio6MZOXIk\n4eHhpKenF3r90NBQzGYzYWFhzJgxA4B27dpRpUoVnnjiiWu+PyFKIi3Tho9Jlaiuj0mRlmm0dMfG\nxtK3b98cxx9++OEc49datWrF0KFD85xn8uTJzod5sr+6dOmSp1yrVq1o27bgh6uEEOWbyq9LzltF\nRETo+Pj4HPv27NlDixYtCqz30FcPsWzvskLP/3CLh1nyyI01XYe3O378OJGRkezduxeTqez+HinK\n+0pUDPYszW2TVlOS/06VggNTemAuYfInhPBuSqkErXVE4SWvkpY3INOeyfcHvs+zv5I574DfNQfW\n5JgDTnjWvHnzuPPOO5kyZUqZJm5CuDKbFE1rB5WobrPaQZK4CSGKRT7tgPWH1uNjvvrshkIRYAlg\neNvhBFgCUFz9j9XH5FPgJL+ibA0ZMoQjR47Qv39/T4ciKrhnIpsQ6Ot+7sj8BPqaeSbytusUkRDi\nRlVhkreCuocX7FhAyhVjELy/jz9NajQhYUQCM3vMJP6peJrUaIK/jzEHWcqVFBbsWFAmMYvy60Yb\nbiCuXY+QuljMxfsv1WI28UDIzdcpIiHEjapCJG9+fn6cO3fO7QeuLcvGyn0r0WgCfAIYEjaEnc/s\ndC6F1aJWC3Y+s5PBYYMJsASg0az4fUWRphURNyatNefOncPPz8/ToYhypJKPmbnD7sDfUrTWN3+L\nUb6ST/Fa64QQokLM8xYcHMzRo0c5c+ZMnmO/nPqF1MxUAn0CeafDO0TWi+SP/X/kKTe2yVjC/MOY\nsGUCqZmpzN80nw51OpRF+KIc8vPzIzg42NNhiHImrEE1Fo/owNBca5u6CvQ1YzGbClzbVAghClIh\nkjeLxULjxo3dHlv9v9V0bNCRb/p/Q73KeZeacdWiRQt6t+/NI0se4bzveXnSUAiRR1iDavxn0r2s\n2XmSWXEH2Hc6FR+TwpalaVa7Ms9ENuGBkJulxU0IUWIVYqoQIYTwFHuWJi3TRqCvjzxVKoTIoyRT\nhVSIljchhPAUs0lRxc/i6TCEEDeQCvHAghBCCCHEjUKSNyGEEEIILyLJmxBCCCGEF5HkTQghhBDC\ni0jyJoQQQgjhRSR5E0IIIYTwIh5N3pRS3ZVSvyulDiilJhZQ7mGllFZKFWseFCGEEEKIG43Hkjel\nlBmYCTwAtAQeVUq1dFOuMjAG+E/ZRiiEEEIIUf54suXtDuCA1vqQ1joTWAz0dlPuL8A0IKMsgxNC\nCCGEKI88mbzVB464bB917HNSSrUFGmitvyvoREqpEUqpeKVUvLvF54UQQgghbhTl9oEFpZQJeBcY\nV1hZrfWnWusIrXVErVq1rn9wQgghhBAe4snk7RjQwGU72LEvW2WgNRCnlEoGOgAr5aEFIYQQQlRk\nnkzetgFNlVKNlVK+wEBgZfZBrfVFrXVNrXUjrXUjYAvQS2sd75lwhRBCCCE8z2PJm9baBjwHfA/s\nAb7WWicppd5SSvXyVFxCCCGEEOWZjycvrrVeDazOte/1fMpGlkVMQgghhBDlWbl9YEEIIYQQQuQl\nyZsQQgghhBeR5E0IIYQQwotI8iaEEEII4UUkeRNCCCGE8CKSvAkhhBBCeBFJ3oQQQgghvIgkb0II\nIYQQXkSSNyGEEEIILyLJmxBCCCGEF5HkTQghhBDCi0jyJoQQQgjhRSR5E0IIIYTwIpK8CSGEEEJ4\nEUnehBBCCCG8iCRvQgghhBBeRJI3IYQQQggvIsmbEEIIIYQXkeRNCCGEEMKLSPImhBBCCOFFJHkT\nQgghhPAikrwJIYQQQngRSd6EEEIIIbyIJG9CCCGEEF5EkjchhBBCCC8iyZsQQgghhBeR5E0IIYQQ\nwotI8iaEEEII4UUkeRNCCCFExZSa6ukISkSSNyGEEEJUPCdOQO3axr9eRpI3IYQQQlQ8y5ZBejos\nX+7pSIpNkjchhBBCVDxffpnzXy8iyZsQQgghKpYzZ2DHDuP77dvh7FnPxlNMkrwJIYQQomJZsQIs\nFuN7i8XY9iKSvAkhhBCiYpkzB9LSjO/T0oxtLyLJmxBCCCEqjgsXYNu2nPu2bjX2ewkfTwcghBBC\nCFFqfv0VNmzI//iePeDrC5mZV/f5+sL48XD77fnX69oV2rYtvTivgSRvQgghhLhxHD8Or74KNhuY\nze7L2Gw5t1NTYe5c92XtdvDxgaVLy03yJt2mQgghhLhxREVBYiI0bmw8jGCz5f1yx105i8U4T2Ki\ncd5yQpI3IUrg3LlzLFmyxNNhCCGEcKdlS0hKgkGDICCgZOcICDDqJyUZ5ytHJHkTopi+//57QkJC\nGDJkCKdPn/Z0OEIIIdzx84PPPoNFi6ByZaPrsyh8fKBKFYiNNer7+V3fOEtAkjchiig9PZ0xY8bQ\nvXt3qlevzk8//UTt2rU9HZYQQoiC9O4Nu3dDeDgEBhZcNjAQ2rQxyvfqVTbxlYAkb0IUwc6dO2nf\nvj3vv/8+o0ePJj4+njZt2ng6LCGEEEURHAyTJoGpkLTHZDLK1a9fNnGVkCRvQhRAa80HH3xA+/bt\nOXv2LGvWrOGf//wn/v7+ng5NCCFEccybBykpBZdJSYH588smnmsgU4UIkY/U1FQee+wxvv32Wx58\n8EFmz54t3aRCCOGNMjPh++/z7q9UCa5cyblvzRqjvK9v2cRWAtLyJkQ+AgICyMrK4r333uPbb7+V\nxE0IIbzV+vU5H1hQyniadPhw41+lrh7z8Sl4kt9yQJI3IVxkZWUxffp0jh07hslk4ttvv2XMmDEo\n119sIYQQ3mXBgqtdpv7+0KQJJCTAzJkQH29sZw+HSUkxypdjkrwJ4eLw4cPExMQwb948AEnabiA2\nexaXMqzYs7SnQxFClCWbDVauBK2NVrYhQ2DnzqtLYbVoYWwPHmwc1xpWrMh/Mt9yQMa8CQHs37+f\n2267jcaNG5OYmEiTJk08HZIoBVdsdlbvPMGsuIPsP52Kj0lhy9I0qx3EyMgm9AipSyUf98vnmM1m\nQkJCnNvLly8nOTmZ3r1707hxY7KysqhduzaLFi2SLnUhyrONG43lr6pUgYUL3a+U4OcHn3xiHHv8\ncbh0CTZtMtYzLYek5U1UaFprPvzwQ1q2bMl8xxNGt912m7S43QASj1zgzinrmbxsF/tOpaI1WO0a\nreH3U6lMXraLO6esZ/uRC27r+/v7k5iY6Pxq1KgRAJ07dyYxMZEdO3bQvn17Zs6cWYZ3JYQotsRE\n6NjRWJC+sCWuevY05njr2BF++61s4isBSd5EhXX58mWGDBnC888/T/fu3enZs6enQxKlZPuRCzz6\n6RYupFtJy7S7LZOWaedCupWBn27JN4EriNaalJQUqlevfq3hCiGup3Hj4KefoF69opWvX98oP27c\n9Y3rGkjyJiqkw4cP06lTJxYuXMhbb73FihUr5EO4jFzvsWdXbHaGzt5KutV90pZbutUof8WWs3x6\nejrh4eGEh4fTt29f5/4ff/yR8PBwGjZsyLp16xg2bFipxi+EEIWRMW+iwomLi6N///5YrVZWrVpF\njx49PB3SDe9axp4BnDp1ihdeeIEtW7ZQvXp1fH19mTBhAn379mXz5s28+OKLXLp0CYAu/Z7Aagpz\n1k1J/D8ubVsOgKmSP9W7PolfcCsAdJadCz8u4MS+n7h9UTWq+lvo378/kyZNwt/fnwMHDpCampoj\nls6dO7Nq1SoApk2bxoQJE/j4449L9fUSQoiCSMubqFA+/vhj7rvvPmrWrMnWrVslcSsD1zr2TGtN\nnz59+NOf/sShQ4dISEhg8eLFHD16lJMnT/LYY4/x8ccfs3fvXjZv3szCubM5s2cLAJcPbCU1cQ03\nD5pG/ac+psb9ozi7cjr21P8BcGHTfOyp57n5iQ9pNvIjfvzxR6xWa5HvrVevXmzatOnaXyQhhCgG\nSd5EhfH3v/+dZ555hvvvv58tW7bQrFkzT4d0wyuNsWcbNmzA19eXkSNHOvfdcsstPP/888ycOZPo\n6Gjatm0LQPUaNxFw9xAubfkGgEv/WUK1LsMwB1QFoNLNtxHUuispv64iy5pB6vbvqfHnp1E+vuw7\nnUpAYBAxMTFFvr/NmzfLk8lCiDIn3aaiwujXrx+XL18mJiYGszn/LjpROko69uw/k+7N0YWalJTk\nTM5yS0pKYujQoc7ttEwbAfWacebsfwGwnv0vlW6+LUcd37pNSd21Htv/TmCuUgtTpQAAfEyKtEwb\nVfwsBcaZPeZNa03VqlX5/PPPi3R/QghRWiR5Eze0o0ePMnv2bF577TWaNm3KX/7yF0+HVGGs3nkC\nqz2rWHWs9izW7DxJnzb18y0zatQoNm/ejK+vLw0aNMhxLNDXp8QPQvwv8d/8qcOrnDt3jp9//pnU\n1FSCgoJylImMjOTixYslOr8QQpQW6TYVN7TFixczffp0Dh065OlQKpxZcQfz7SrNT1qmnVlxB3Ls\na9WqFb/++qtze+bMmaxfv54zZ87QsmVLEhISnMfMJkWtK8ew1GwIgOWmhlw5mfN8mScP4HtTQ3yq\n18V+6QxZVy4D0O7PfUlMTKRq1arY7cWLWwghypIkb+KGlJGRAcC4cePYtWuXjEsqY/Yszf7TqYUX\ndGPf6dQcrWddu3YlIyODWbNmOfddvmwkXKNGjWLOnDkkJiYCcO7cOS5snEPtTv0BqHLnw1yIm4M9\n3XgSNfPUIVJ3rieo7YOYLH4Ehd7H+XUf42+y80zkbdjtdjIzM0sUtxBClBVJ3sQNZ/ny5TRt2pTf\nf/8dpRQNGzb0dEgVTlqmDR9TyVapyB57lk0pxfLly9m4cSONGzfmjjvuYOjQoUybNo26deuyYMEC\nnnrqKW6//XY6duzImGdGUKNFRwACmt5JUOh9nFzwEsc+G8m5//uAmj3H4RNUA4BqfxqCObAGhz4e\nScwTUXTu3JmhQ4dSzzGZ5+XLlwkODnZ+vfvuu9f4ygghxLVTWntukWalVHfgn4AZ+FxrPTXX8ReB\nJwEbcAYYprU+XNA5IyIidHx8/HWKWJR38+bN44knnqB9+/Z899133HTTTZ4OqUKyZ2lum7Sakvz3\nohQcmNIDcwmTPzCech346ZYiPSzhbzGzeEQHwhpUK/H1hBCipJRSCVrriOLU8VjLm1LKDMwEHgBa\nAo8qpVrmKvYbEKG1DgWWAG+XbZTCm3z00UcMHTqUrl27sm7dOkncPMhsUjStHVR4QTea1Q66psQN\nIKxBNRaP6EA1fwuBvu6fLA70NVPN3yKJmxDC63iy2/QO4IDW+pDWOhNYDPR2LaC1/kFrfdmxuQUI\nLuMYhZd49913GTVqFL169WLVqlV5nhIUZe+ZyCb5Jk75CfQ180zkbYUXLIKwBtX4z6R7mdI3hOZ1\nglAKLGaFUtC8TmWm9A3hP5PulcRNCOF1PDlVSH3giMv2UeDOAsoPB9Zc14iEV3rnnXeYMGEC/fr1\nY9GiRVgsBc/TJcpGj5C6vLlyN1D0JzctZhMPhNxcajFU8jHTp019+rSpjz1Lk5ZpI9DX55pb9oQQ\nwpO84oEFpdTjQATwTj7HRyil4pVS8WfOnCnb4IRH/eMf/2DChAk88sgjxMbGSuJWjlTyMTN32B34\nW4rW+uZvMcoXtMbptTCbFFX8LJK4CSG8XrGSN6WUSSlVpZSufQxwnWEz2LEv9zX/DEwCemmtr7g7\nkdb6U611hNY6olatWqUUnijvtmzZwvjx4+nfvz8LFy7Ex0fmnC5vZOyZEEKUvkKfNlVKLQJGYvR9\nbAOqAP/UWrttBSvyhZXyAfYB92IkbduAx7TWSS5l2mA8qNBda72/KOeVp00rliVLltC7d29pcSvn\nrtjsrNl5kllxB9h3OhUfk8KWpWlWuzLPRDbhgZCbr1uLmxBClGcledq0KMlbotY6XCk1CGgLTAQS\nHE+AXhOlVA/gPYypQmZrracopd4C4rXWK5VS64AQ4ISjyn+11r0KOqckbze+lStXcssttxAWFubp\nUEQJyNgzIYS4qiTJW1H6mSxKKQvQB/hQa21VSpXK5HBa69XA6lz7Xnf5/s+lcR1x48jMzOTFF1+k\nefPmfPfdd54OR5RA9tgzIYQQJVOU5O0TIBnYDmxSSt0CXLqeQQmRH19fX+Li4ggICPB0KEIIIYRH\nFPrAgtb6fa11fa11D204DHQpg9iEcDp58iRvvvkmdrud4OBgatSo4emQhBBCCI8otOVNKVUJeBho\nlKv8W9cpJiFySE9Pp3fv3uzatYuBAwfSvHlzT4ckhBBCeExRuk1XABeBBMDtVB1CXC9aa0aMGMHW\nrVtZunSpJG5CCCEqvKIkb8Fa6+7XPRIh3Hj//fdZsGABb775Jn379vV0OEIIIYTHFWWS3p+VUiHX\nPRIhcvn5558ZP348vXv3ZvLkyZ4ORwghhCgXitLydjcQrZT6A6PbVAG6NOZ5EyI/586dY8CAATRs\n2JA5c+ZgMnnFSm5CCCHEdVeU5O2B6x6FEC601gwfPpxTp07xyy+/UK2aLJkkhBBCZCsweVNKmYHv\ntda3l1E8QjB37lxWrFjB9OnTadeunafDEUIIIcqVAvuitNZ24HelVMMyikcIevTowRtvvMELL7zg\n6VCEEEKIcqco3abVgSSl1FYgLXtnYWuMClFcWmu01tSuXZuYmBhPhyOEEEKUS0VJ3l677lHcoFIz\nUwnyDfJ0GF4jNjaWmTNnsnz5cmrVquXpcIQQQohyqdDkTWu9sSwCudGcSDlBk/ebcHD0QepWruvp\ncLyCj48P1apVk6WvhBBCiAIUOv+CUipFKXXJ8ZWhlLIrpWRh+kIs27uMdFs6y/cu93QoXuORRx7h\nu+++w2w2ezoUIYQQotwqysL0lbXWVbTWVQB/jHVOP7rukXm5LxO/zPGvyN/hw4f56KOPsFqtng5F\nCCGEKPeKNfOpNiwHul2neG4IZ9LOsOPUDgC2n9rO2ctnPRxR+fbGG28wbtw4Tp8+7elQhBBCiHKv\n0DFvSqmHXDZNQASQcd0iugGs+H0FFpOFTHsmFpOFFXtXMLztcE+HVS7t37+f+fPnM3bsWOrXr+/p\ncIQQQohyrygtbz1dvroBKUDv6xmUt5uTOIc0qzGrSpo1jTmJczwbUDk2bdo0fH19mTBhgqdDEUII\nIbxCUaYK+Vxr/ZPrDqVUJ0D6uNy4kHGBbce35di39fhWLmRcoJqfLPPk6tSpU8yfP5/hw4dTp04d\nT4cjhBBCeIWiJG8fAG2LsK9C+PXEr2z4Y0O+x/ec2YOv2ZdMe6Zzn6/Zl/H/Hs/tNfNfZaxr4660\nrVuxXtJPP/2UzMxMxo4d6+lQhBBCCK+Rb/KmlLoL6AjUUkq96HKoClBh53I4fuk4r65/FVuWDbPJ\n/ctgy7Ll2E7NTGXu9rluy9qz7PiYfFj6yNIKlbzZ7XY+++wz7rvvPpo1a+bpcIQQQgivUdCYN18g\nCCPBq+zydQnod/1DK5+imkeRODKRxtUbYzFZsGXZ8ny5466cxWShcfXGJI5MJKp5VBnfiWfFxcVx\n5MgRhg+XBzmKw2bP4lKGFXuW9nQoQgghPCTfljfHygoblVJztNaHlVIBWuvLZRhbudWyVkuSnk3i\n+TXPs2jnIi5bi/+yBPgE8FjoY3zwwAf4+fhdhyjLt9jYWCpXrkyvXrJEbmGu2Oys3nmCWXEH2X86\nFR+TwpalaVY7iJGRTegRUpdKPu5bgU+ePMnYsWPZtm0b1apVo06dOrz33ntYrVaef/55jh07RlZW\nFkOGDGHy5MkopTh16hTDhw/nyJEjWK1WGjVqxLRp0xg8eDAA//3vf6latSpVq1alZs2arFu3rixf\nDiGEqPCU1gX/Be/oPv0CCNJaN1RKhQFPa62fLYsAiysiIkLHx8eX2fVW7F3B4GWDSbel59vq5srH\n5EOATwDzH5pPr+YVN3FZtmwZhw8flvFuhUg8coHo2Vux2rNIy7TnOR7oa8ZiNjF32B2ENcj5QIzW\nmo4dOzJ06FBGjhwJwPbt27l06RLR0dHMmjWL+++/n8uXL/Pwww8TFRXFqFGjePrpp2nZsiVjxowB\nYMeOHYSGhjrPGx0dTVRUFP36VdgGeCGEKDVKqQStdURx6hRlqpD3MKYIOQegtd4O/Kn44d2Yet/e\nm92jdhN+cziBlsACywZaAmlzcxt2j9pdoRM3gL59+0riVojtRy7w6KdbuJBudZu4AaRl2rmQbmXg\np1vYfuRCjmM//PADFovFmbgBhIWFsW/fPjp16sT9998PQEBAAB9++CFTp04F4MSJEwQHBzvruCZu\nQgghPK9IKyxorY/k2uX+k6SCCq4SzKTOkzCpgl9OkzIxqfMk6leRyWhFwa7Y7AydvZV0a9F+1dKt\nRvkrtqvld+3aRbt27fKUTUpKyrO/SZMmpKamcunSJUaNGsXw4cPp0qULU6ZM4fjx49d2M0IIIUpV\nUZK3I0qpjoBWSlmUUuOBPdc5Lq8zb/s8UjJTCiyTkpnC/B3zyygi4c1W7zyB1Z5VrDpWexZrdp68\n5mt369aNQ4cO8dRTT7F3717atGnDmTNnrvm8QgghSkdRkreRwCigPnAMCHdsC4dMeybfH/g+z/5K\n5kp59q05sCbHHHBCuDMr7mC+XaX5Scu0MyvugHO7VatWJCQk5CnXsmXLPPsPHTpEUFAQVapUAaBG\njRo89thjzJ8/n/bt27Np06YS3IUQQojrodDkTWt9Vms9SGtdR2tdW2v9OLK2aQ7rD63Hx3z1wV2F\nIsASwPC2wwmwBKBQzmM+Jp8CJ/kVwp6l2X86tUR1951OdU4j0rVrV65cucKnn37qPL5jxw6aN2/O\n5s2bnU+JpqenM3r0aOcSZRs2bODyZeMJ6pSUFA4ePEjDhg2v5ZaEEEKUogKTN6VUfaVUhFLK17Fd\nWyn1N2B/mUTnJRbsWEDKFaPL1N/HnyY1mpAwIoGZPWYS/1Q8TWo0wd/HH4CUKyks2LHAk+GKci4t\n04aPSRVe0A0fkyIt03jqWSnFsmXLWLduHU2aNKFVq1a88sor3HzzzaxYsYK//vWvNG/enJCQENq3\nb89zzz0HQEJCAhEREYSGhnLXXXfx5JNP0r59+1K7PyGEENcm36lClFJjgUnAAaAS8BEwDZgHvK21\nPlFWQRZHWU8VYsuyUX1adVIzUwnwCWBw2GDe6/5ejrnbMmwZjPm/MSzYsYDL1ssE+Qbxv5f/h4+p\nKKuTCVc2exaXrXYCfSjrQjwAACAASURBVH0wlzDBKe/sWZrbJq2mkFl83FIKDkzpccO+NkIIcaMp\nyVQhBWUPI4DmWuvzSqmGwD6gk9Y67yCaCmxj8kZSM1OpUqkKCx9aSFSzvCsl+Pn48UnUJ0Q1jeLx\nZY9z6colNh3eRNfGXT0Qsfe5lklqzWYzISEh2Gw2WrRowdy5cwkICHDuzzZw4EAmTpxIZGQkJ06c\nwM/Pj6CgIGbPnk3z5s3L6laNmE2KprWD2Heq+F2nzWoHSeImhBA3uIK6TTO01ucBtNb/BX6XxC2v\nxJOJdGzQkT2j9rhN3Fz1bN6T3c/upmODjvx24rcyitC7JR65wJ1T1jN52S72nUpFa7DaNVrD76dS\nmbxsF3dOWZ9njrNs/v7+JCb+f3t3H+fXfOd9/PXJJEPETdxW1l2IWJdsZMSgsWSjtNXaklotoYR2\n69G4Lar0waroRhVX22srl5tLl7SXlquIjSW2lkbQViWVIErQpqQNuakWJWQmn+uP+c1kEnPzm8n8\nZubMvJ6Pxzzmd875/s75/HLMeM/3fM/3LODZZ5+lurqaG264Yb31jV8XX3xx03tuu+02Fi5cyOTJ\nk7nwwgu75XNuaMqEEQyp7tgjhIdUVzFlwp4VqkiS1Fu0Fd52joh/a/wChm2wLOCCgy/g8c8/zt9s\n8Tdltd9py514/POPc8HBF1S4suLb2ElqN3TooYfy0ksvtdmmufHjx3eofVf65OhhDKoqaxrGJoOq\nBvCJ0TtWqCKpOHwGsPq6tv7vcCEwv9nXhstSxXTFJLXN1dXVMXv27KZLpe+++y41NTVNX3fccccH\n3nPvvfeud2m1O20ysIoZnz+QwYPK630bPKihfWuXj6W+7r26emY+tZSPfecRRl46m/2/8SB7XnI/\nH//OI8x8ammrvxsAXn/9dU488UT22GMP9t9/f8aNG8fMmTNbbT9nzhz+8R9bvtIyfPhwVq5cudGf\nR2pLWw+mn9GdhUjNbcwktRP3W/cEi8aQBg09b1/4wheAdZdNW3LSSScxePBghg8fzve+971OfoKN\nN2aXodx++oeZ3Mlnm0r9RUvPAF5T39Dr1ji8Yuqs51p9BvDEiROZPHkyP/rRjwD4/e9/z6xZs7r3\nQ0gd4O2O6pU2ZpLa5uGtrZDWmttuu43a2g7d+FMxY3YZyhOXHM7sZ17j+jkvsXi9Gza2YMqEEXxi\n9I72uKnfahxe0VYvfcPvknpOuOmX3H76h9cLcA8//DDV1dXrPQN4t9124+yzz2b16tVMmTKFefPm\nMXDgQL797W9z2GGHrbfvVatWMWnSJP7whz8wbtw4WpvBQepKhjf1Ol0xSW1fuuNyk4FVTNxvJybu\ntxP1a5O/vl/Xp6dKkcrV2eEVT1xyeNMfPIsWLWLs2LEttp8+fToRwTPPPMPzzz/Pxz72MRYvXrxe\nm6lTp3LIIYdw2WWXcd999/H9739/4z6UVAbDm3qdxklqGy97dETjJLVbbjqozXbNL6cCHHnkkVx1\n1VUdPl53qxoQ7X429X79Yb7C7tBVwyuaO/PMM3nssceorq5m55135uyzzwZg7733ZrfddvtAeJs7\ndy533303AEcddRRbb711Jz6J1DGthreI+B7Q6v89M/OcilSkfm9I9UDqOnmXWN3aZEj1uv+s3367\n5R68+vqW/1KfM2dOp46r3qE3h6KumK9wzZo1DBw4kFNOOYXzzjuPAQMGMGfOHK699lr+8z//s6n9\n0UcfzSuvvMLbb7/NihUr2H333QG48cYbueCCC1ixYgWbbropm2yyCTfffDP77rtvt/wbdLWuGF4x\natQo7rrrrqbt06dPZ+XKldTW1rLzzjt3ab1SV2nrbtN5NNxVuikwloZHYr1Iw4Ppqytfmvqrxklq\nO8NJavufjbnLsKqqar27jpcsWQLAY489xoEHHsjee+/N3nvvvd7zYc855xyuuOKKpuVp06Zx5pln\ntlljV81XuGjRIh588EFmz57N1KlTWz3erFmzWLBgATfccAOHHXZY03yGBx10EAB33HEHCxcu5Itf\n/CIXXXRRm7X3Vl35DODVq1dz/fXXN21vfLbvoYceym233dbwnsWLeeWVVz4waff48eObbnSYPXs2\nb7zxRqdqkjqi3btNI2IKcEhm1pWWbwAe7Z7y1F9NmTCCS2c+26G/qp2ktv/ZmLsMoeUbWl577TVO\nPPFE7rnnHsaOHcvKlSv5+Mc/zk477cRRRx3Fv/7rv1JTU8PnPvc5AG6++Waeeqr1Sbc3dkD9hnbY\nYQduuukmDjjgAC6//PJW25Vj3LhxPXpH9cboquEVEcE999zDeeedx9VXX83222/PkCFD+Na3vsUx\nxxzDlClTGD16NAMHDuTWW29lk002WW9fX//615k0aRKjRo3i4IMPZtddd+2qjyi1qpwxb1sDWwJ/\nKi1vXlonVcwnRw9j6qzngPLDm5PU9i9dHYoaTZ8+nVNPPbVpEPt2223H1VdfzeWXX85RRx3Flltu\nybRp0zjrrLMAuOKKKxg6tOX9dsWA+pbsscce1NfXs3z58rL225oHHniAiRMnbtQ+ekpXDq8YNmwY\nt99+e4ttb7nllg+smzBhAhMmTABg22235ac//Wmn6pA6q5wp3K8CnoqIWyNiBvBr4MrKlqX+zklq\n1ZaumsS5+WTNn/70p4GGuw/333//9drV1tayaNGipuVJkybxxhtv8Oabb3LyySe3etyNGVBfSccf\nfzzDhw/nmmuuYcqUKRU9VqU4vEL9WbvhLTNvAQ4CZgJ3A+OcwFfdoXGS2qGDB7X6nM8h1VUMHTyo\n7F4V9Q1dFYqaP+O2rRn1N7R06VKWLVvGH//4x1ZvioGNG1Dflt/+9rdUVVWxww47dGjfje644w5+\n97vfMWnSJM4999xO7aM38BnA6q/aDW8REcARwJjM/A+gOiIOrHhlEusmqZ326dH87Yc2JwIGVQUR\n8Lcf2oJpnx7NE5ccbnDrZyoVigD22Wcf5s9f/wmA8+fPZ9SoUU3L5557LlOnTuWzn/1sqzcOdNWA\n+g2tWLGCL33pS5x11lk0/HrunIjgyiuvZO7cubz44oud3k9P8hnA6q/KGfP2v4G1wEeAK4C3gLuA\nAypYl9TESWrVXKUncT7zzDM56KCDOPbYY6mpqWHVqlVcdNFFXHbZZUDDHYXLly/nlFNO4Z133mHf\nfffltNNOY5999llvP105X2Hj5d3GqUJOPvlkzj///Kb2Dz300HrTWvzkJz9h3Lhx7R5ns80247zz\nzuPaa6/lxhtv7HCdPa1xeMUJ7Yx9bOTwCvUV0d6jPCLi15k5NiKeysz9SusWZuaYbqmwg2pra3Pe\nvHk9XYakCnlz9Rr2/8aDnQpFg6qC+f/y0aZQtPnmm7d42XPu3LlccMEFvPXWW2QmX/7yl5kyZQqr\nV69mzJgx3HnnnYwePRqAu+++m+uuu46HH354vX3Ur032vOR+OvO0pAh4adon/QOlTAtf/bPPAFZh\nRcT8zOzQMxnL6XlbExFVlCbsjYjtaeiJk6Ru1x2TOI8fP54nn3zyA+s33XRTXnjhhfXWHXvssRx7\n7LEfaNs4oH7x6x3vJXRAfcf4DGD1N+WEt3+j4WaFHSJiGnAccGlFq5KkVhQpFDlfYfdxeIX6k3Lu\nNr0N+CrwTWAZMDEzf1LpwiSpNUW5y9AB9T2j8RnABjf1VeXcbfp9YNPMnJ6Z12XmbyLi8sqXJkkt\nK0oocr5CSZVQzm+/jwMzIuKUZuuOrlA9ktSuIoUi5yuU1NXKCW/LgfHAZyJiekQMBOyLltSjihSK\nnK9QUlcqZ6qQ5lOEXE7DhL1/k5l7VL68jnOqEKl/ea+uvnB3GTqgXlKjSk0VMqvxRWZeHhHzgfM6\nWpwkVUIR7zJsHFAvSZ1Rzt2mX99g+d7M/EjlSpKkzvEuQ0n9Qas9bxHxWGYeEhFvUZqgt3ETkJm5\nZcWrkyRJ0npaDW+ZeUjp+xbdV44kSZLa0lbP2zZtvTEz/9T15UiSJKktbd2wMJ+Gy6UtDR5JoFfe\nbSpJktSXtXXZdPdKHzwijgT+F1AF3JyZV22wfRPgB8D+wCrg+MxcUum6JEmSeqtypgohIrYGRgKb\nNq7LzLkbc+CIqAKmAx8FlgJPRsSszHyuWbMvAG9k5p4RcQLwLeD4jTmuJElSkZXzbNN/BuYC/wVM\nLX2/vAuOfSDwUmb+NjPfB24HjtmgzTHAjNLrO4HDI8I5ACRJUr9VzuOxzgUOAH6fmYcB+wF/7oJj\n7wS82mx5aWldi20ysw74C7DthjuKiNMjYl5EzFuxYkUXlCZJktQ7lRPeVmfmamgYg5aZzwN/W9my\nOiYzb8rM2sys3X777Xu6HEmSpIopZ8zb0ogYCtwDPBgRbwC/74Jj/wHYpdnyzqV1LbVZGhEDga1o\nuHFBkiSpX2o3vGXmp0svL4+In9EQoB7ogmM/CYyMiN1pCGknACdu0GYWMBn4BXAc8HBmJpIkSf1U\nu+EtInZttvi70vcdgVc25sCZWRcRZ9FwA0QV8O+ZuSgirgDmZeYs4PvADyPiJeBPNAQ8SZKkfquc\ny6b3sW6y3k2B3YEXgFEbe/DMvB+4f4N1lzV7vRr4zMYeR5Ikqa8o57Lp6ObLETEWOKNiFUmSJKlV\n5dxtup7M/DVwUAVqkSRJUjvKGfN2frPFAcBY4I8Vq0iSJEmtKmfM2xbNXtfRMAbursqUI0mSpLaU\nM+ZtancUIkmSpPaVc9l0L+ArwPDm7TPzI5UrS5IkSS0p57LpT4AbgJuB+sqWI0mSpLaUE97qMvP6\nilciSZKkdpUzVci9EXFGRAyLiG0avypemSRJkj6gnJ63yaXvFzZbl8AeXV+OJEmS2lLO3aa7d0ch\nkiRJal85PW9ExMF88G7TH1SoJkmSJLWinKlCfgiMABaw7m7TBAxvkiRJ3aycnrdaYJ/MzEoXI0mS\npLaVc7fps8COlS5EkiRJ7Sun52074LmI+BXwXuPKzDy6YlVJkiSpReWEt8srXYQkSZLKU85UIY80\nX46IQ4BJwCMtv0OSJEmVUu5UIfsBJwKfAX4H3FXJoiRJktSyVsNbROxFQw/bJGAlcAcQmXlYN9Um\nSZKkDbTV8/Y88Cjwj5n5EkBEnNctVUmSJKlFbU0VciywDPhZRPyfiDgciO4pS5IkSS1pNbxl5j2Z\neQKwN/Az4MvADhFxfUR8rLsKlCRJ0jrtTtKbmX/NzB9l5qeAnYGngIsqXpkkSZI+oJwnLDTJzDcy\n86bMPLxSBUmSJKl1HQpvkiRJ6lmGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElS\ngRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmS\nCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmS\nVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mS\npAIxvEmSJBVIj4S3iNgmIh6MiBdL37duoU1NRPwiIhZFxNMRcXxP1CpJktSb9FTP28XAQ5k5Enio\ntLyhd4BTMnMUcCTw3YgY2o01SpIk9To9Fd6OAWaUXs8AJm7YIDMXZ+aLpdd/BJYD23dbhZIkSb1Q\nT4W3D2XmstLr14APtdU4Ig4EqoGXK12YJElSbzawUjuOiP8Gdmxh0yXNFzIzIyLb2M8w4IfA5Mxc\n20qb04HTAXbddddO1yxJktTbVSy8ZeYRrW2LiNcjYlhmLiuFs+WttNsSuA+4JDN/2caxbgJuAqit\nrW01CEqSJBVdT102nQVMLr2eDPzHhg0iohqYCfwgM+/sxtokSZJ6rZ4Kb1cBH42IF4EjSstERG1E\n3Fxq81lgPHBqRCwofdX0TLmSJEm9Q2T2rauMtbW1OW/evJ4uQ5IkqV0RMT8zazvyHp+wIEmSVCCG\nN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIx\nvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI\n4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlA\nDG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkF\nYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkq\nEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkFYniTJEkqEMObJElS\ngRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlADG+SJEkF0iPhLSK2iYgHI+LF0vet22i7\nZUQsjYjrurNGSZKk3qinet4uBh7KzJHAQ6Xl1nwDmNstVUmSJPVyPRXejgFmlF7PACa21Cgi9gc+\nBPy0m+qSpH6trn4tb65eQ/3a7OlSJLWip8LbhzJzWen1azQEtPVExADgfwJfaW9nEXF6RMyLiHkr\nVqzo2kolqY97r66emU8t5WPfeYSRl85m/288yJ6X3M/Hv/MIM59aynt19a2+t6qqipqaGsaMGcPY\nsWP5+c9/DsCSJUsYPHhw07aDDz6YF154AYA5c+aw1VZbUVNTw7777ssRRxzB8uXLWbRoEXvttRfv\nvvtu0/6POuoofvzjH1f2H0AqmIqFt4j474h4toWvY5q3y8wEWvoT7wzg/sxc2t6xMvOmzKzNzNrt\nt9++iz6BJPV9C179MwdNe4hLZz7L4tffJhPW1CeZ8MLrb3PpzGc5aNpDLHz1zy2+f/DgwSxYsICF\nCxfyzW9+k6997WtN20aMGNG0bfLkyVx55ZVN2w499FAWLFjA008/zQEHHMD06dMZNWoUxx57LNOm\nTQPgnnvuYc2aNUyaNKmy/whSwQys1I4z84jWtkXE6xExLDOXRcQwYHkLzcYBh0bEGcDmQHVEvJ2Z\nbY2PkySVaeGrf2bSTb/k3TWt96z99f16oJ4Tbvolt5/+YcbsMrTVtm+++SZbb93y/WetbctM3nrr\nLfbcc08ALrvsMvbbbz+OO+44Lr74Yu69996OfSipH6hYeGvHLGAycFXp+39s2CAzT2p8HRGnArUG\nN0nqGu/V1TP533/VZnBr7t01De2fuORwNhlYtW79u+9SU1PD6tWrWbZsGQ8//HDTtpdffpmamhre\neust3nnnHZ544ommbY8++ig1NTWsWrWKIUOGNPXKbbbZZlx77bWMHz+e888/n5EjR3bRJ5b6jp4a\n83YV8NGIeBE4orRMRNRGxM09VJMk9Rv3P7OMNfVrO/SeNfVrmf3Ma+uta7xs+vzzz/PAAw9wyimn\n0DAaZt1l05dffpnvfve7nH766U3va7xs+uqrr3Laaafx1a9+tWnbpz71KYYOHcoZZ5yxEZ9Q6rt6\nJLxl5qrMPDwzR2bmEZn5p9L6eZn5zy20vzUzz+r+SiWpb7p+zsulS6Ll++v79Vw/56VWt48bN46V\nK1fS0o1jRx99NHPntjzrU0vbBgwYwIABziMvtcSfDEnqZ+rXJi8uf7tT7128/O1WpxF5/vnnqa+v\nZ9ttt/3Atscee4wRI0a0+L62tkn6oJ4a8yZJ6iF/fb+OgQOCNfUdn8tt4IDgr+/XseWmg4B1Y96g\n4eaDGTNmUFXVMCauccxbZlJdXc3NN68bFdM45i0z2WqrrdbbJqlthjdJ6meGVA+krpOT8NatTYZU\nr/tfR319y5dehw8fvt58bc1NmDCBv/zlL20eZ8mSJZ2qT+oPvGwqSf1M1YBg5A6bd+q9e+2wOVUD\noosrktQRhjdJ6oemTBjBkOqq9hs2M6S6iikT9qxQRZLKZXiTpH7ok6OHMaiqY/8LGFQ1gE+M3rFC\nFUkql+FNkvqhTQZWMePzBzJ4UHm9b4MHNbRvPkGvpJ5heJOkfmrMLkO5/fQPM3TwoFYvoQ6prmLo\n4EHtPhpLUvfxblNJ6sfG7DKUJy45nNnPvMb1c15i8fK3GTggqFub7LXDFkyZMIJPjN7RHjepFzG8\nSVI/t8nAKibutxMT99uJ+rXJX9+vY0j1QO8qlXopw5skqUnVgGiagFdS7+SYN0mSpAIxvEmSJBWI\n4U2SJKlADG+SJEkFYniTJEkqEMObJElSgRjeJEmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlA\nDG+SJEkFYniTJEkqEMObJElSgURm9nQNXSoiVgC/7+k6+pDtgJU9XYS6nOe1b/K89k2e175rO2BI\nZm7fkTf1ufCmrhUR8zKztqfrUNfyvPZNnte+yfPad3X23HrZVJIkqUAMb5IkSQVieFN7burpAlQR\nnte+yfPaN3le+65OnVvHvEmSJBWIPW+SJEkFYniTJEkqEMObiIgjI+KFiHgpIi5uYfv4iPh1RNRF\nxHE9UaM6p4xze35EPBcRT0fEQxGxW0/UqY4p47x+KSKeiYgFEfFYROzTE3WqY9o7r83a/VNEZEQ4\nfUgBlPHzempErCj9vC6IiH9ud5+OeevfIqIKWAx8FFgKPAlMysznmrUZDmwJfAWYlZl3dn+l6qgy\nz+1hwBOZ+U5ETAEmZObxPVKwylLmed0yM98svT4aOCMzj+yJelWecs5rqd0WwH1ANXBWZs7r7lpV\nvjJ/Xk8FajPzrHL3a8+bDgReyszfZub7wO3AMc0bZOaSzHwaWNsTBarTyjm3P8vMd0qLvwR27uYa\n1XHlnNc3my0OAfwrvfdr97yWfAP4FrC6O4tTp5V7XjvE8KadgFebLS8trVPxdfTcfgGYXdGK1BXK\nOq8RcWZEvAxcDZzTTbWp89o9rxExFtglM+/rzsK0Ucr9PfxPpeErd0bELu3t1PAmiYj4HFALXNPT\ntahrZOb0zBwBXARc2tP1aONExADg28AFPV2Luty9wPDM3Bd4EJjR3hsMb/oD0Dzl71xap+Ir69xG\nxBHAJcDRmfleN9Wmzuvoz+ztwMSKVqSu0N553QL4O2BORCwBPgzM8qaFXq/dn9fMXNXsd+/NwP7t\n7dTwpieBkRGxe0RUAycAs3q4JnWNds9tROwH3EhDcFveAzWq48o5ryObLR4FvNiN9alz2jyvmfmX\nzNwuM4dn5nAaxqge7Q0LvV45P6/Dmi0eDfymvZ0O7NISVTiZWRcRZwH/BVQB/56ZiyLiCmBeZs6K\niAOAmcDWwKciYmpmjurBslWGcs4tDZdJNwd+EhEAr2Tm0T1WtNpV5nk9q9SjugZ4A5jccxWrHGWe\nVxVMmef1nNJd4XXAn4BT29uvU4VIkiQViJdNJUmSCsTwJkmSVCCGN0mSpAIxvEmSJBWI4U2SJKlA\nDG+SKi4iJkZERsTePXDsJRGxXen1z7tgf6dGxHUbrBseEUtLs+A3X78gIg5qY1+XR8RX2jnexIjY\np9nyFaVpQIiIOY2TtEbE/RExtPR1Rmc+m6RiMLxJ6g6TgMdK33tMZh5cof0uAV4BDm1cVwqqW2Tm\nExu5+4lAU3jLzMsy879bqOGTmflnYChgeJP6MMObpIqKiM2BQ2h48P0JzdZPKPUc3RkRz0fEbVGa\nKbjUWzY1In4dEc809tht2FMVEc9GxPDS63siYn5ELIqI01up5e3S9ytKvWILIuIPEXFLaf3nIuJX\npfU3RkRVaf1pEbE4In4F/H0rH/XHzT9f6fXtpfcPj4iHSw+efigidm2hti9GxJMRsTAi7oqIzSLi\nYBpmXL+mVNOIiLg1Io5r4f2NPYxXASNK7a+JiB9ExMRm7W6LiGNa+QySCsDwJqnSjgEeyMzFwKqI\naP7cvv2AL9PQs7QH6wejlZk5FrgeaPPSYsnnM3N/oJaGGcu3ba1hqfeqBphAw4zm10XE/wCOB/6+\ntK0eOKn06JqppdoOoVkv2Ab+HzAxIhqfXHM8DYEO4HvAjNKDp28D/q2F99+dmQdk5hgaHo/zhcz8\nOQ2P0rkwM2sy8+Uy/h0uBl4utb8Q+D6lGdsjYivgYOC+MvYjqZcyvEmqtEmUeqBK35tfOv1VZi7N\nzLXAAmB4s213l77P32B9a86JiIU0PPNxF2BkW41LvXz/F/h2Zs4HDqfhgdBPRsSC0vIewEHAnMxc\nkZnvA3e0tL/MfB14Fjg8ImqAusx8trR5HPCj0usf0hACN/R3EfFoRDwDnAR0ySPoMvMRGp6tuD0N\n//Z3ZWZdV+xbUs/w2aaSKiYitgE+AoyOiKTh2X4ZEReWmrzXrHk96/9Oeq+F9XWs/0fnpqXjTACO\nAMZl5jsRMadxWxsuB5Zm5i2N5dLQO/a1DT7DxA3f2IbGS6evs67XrVy3AhMzc2FEnEpDr2BX+QHw\nuVJtp3XhfiX1AHveJFXSccAPM3O3zByembsAv6PZwP4OWgKMBYiIscDupfVbAW+UgtvewIfb2klE\nfIqGsHdOs9UPAcdFxA6lNttExG7AE8A/RMS2ETEI+Ewbu74b+CQNl0xvb7b+56wbD3cS8GgL790C\nWFY6xknN1r9V2laultrfSsPlaTLzuQ7sS1IvZHiTVEmTgJkbrLuLzt91ehewTUQsAs4CFpfWPwAM\njIjf0DBg/5ft7Od8YCeg8eaEK0qh5lLgpxHxNPAgMCwzl9HQS/cL4HEaxqO1qHS35y+A1zPzt802\nnQ2cVtrvycC5Lbz9X2gIio8DzzdbfztwYUQ8FREj2vlcZOYq4PHSzRzXlNa9Xqr7ljbfLKkQIjN7\nugZJUgVFxGbAM8DYzPxLT9cjaePY8yZJfVhpQt/fAN8zuEl9gz1vkiRJBWLPmyRJUoEY3iRJkgrE\n8CZJklQghjdJBt0ergAAABBJREFUkqQCMbxJkiQVyP8HhyzTTmGzbWwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7dc45422e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sdp, rp, cmp = optim_info(optimized['x'], returns, cov_mat)\n",
    "sdp_min, rp_min, cmpmin = optim_info(optimized1['x'],returns, cov_mat)\n",
    "\n",
    "an_vol = np.std(log_returns) * np.sqrt(252)\n",
    "an_rt = log_returns.mean() * 252\n",
    "fig, ax = plt.subplots(figsize=(10, 7))\n",
    "ax.scatter(an_vol,an_rt,marker='o',s=200)\n",
    "for i, txt in enumerate(returns.columns):\n",
    "        ax.annotate(txt, (an_vol[i],an_rt[i]), xytext=(10,0), textcoords='offset points')\n",
    "ax.scatter(sdp,rp,marker='*',color='r',s=500, label='Maximum Sharpe ratio')\n",
    "ax.scatter(sdp_min,rp_min,marker='*',color='g',s=500, label='Minimum volatility')\n",
    "target = np.linspace(rp_min, rp, 50)\n",
    "efficient_portfolios = efficient_frontier(log_returns.mean(), cov_mat, target)\n",
    "ax.plot([p['fun'] for p in efficient_portfolios], target, linestyle='-.', color='black', label='Efficient Frontier')\n",
    "ax.set_title('Portfolio Optimization with Individual Stocks')\n",
    "ax.set_xlabel('Annualized Volatility')\n",
    "ax.set_ylabel('Annualized Returns')\n",
    "ax.legend(labelspacing=0.8)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}