Char2Mel_generation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Char2Mel Generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/var/Sources/experiments/core/tts/Alternative', '/home/kaz/anaconda3/envs/core/lib/python37.zip', '/home/kaz/anaconda3/envs/core/lib/python3.7', '/home/kaz/anaconda3/envs/core/lib/python3.7/lib-dynload', '', '/home/kaz/.local/lib/python3.7/site-packages', '/home/kaz/anaconda3/envs/core/lib/python3.7/site-packages', '/home/kaz/anaconda3/envs/core/lib/python3.7/site-packages/Mako-1.0.7-py3.7.egg', '/home/kaz/anaconda3/envs/core/lib/python3.7/site-packages/IPython/extensions', '/home/kaz/.ipython', '../../']\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.append('../../')\n",
    "print(sys.path)\n",
    "import numpy as np\n",
    "import torch\n",
    "import pandas as pd\n",
    "import seaborn as sns; sns.set()\n",
    "from matplotlib.pyplot import figure\n",
    "import matplotlib.pyplot as plt\n",
    "from models.mlmodeldic import best_model_path_and_settings\n",
    "from tts.Alternative.neuravoice import CharToMel\n",
    "from models.mlmodeldic import best_model_path_and_settings\n",
    "from models.phoneme import Phoneme43\n",
    "from tts.duration.phoneme_duration import PhonemeDuration\n",
    "from nlp.kana.kana import text_to_kana\n",
    "from tools.libaudio.utils import load\n",
    "from tools.libaudio.display import show_spec, show_mel\n",
    "from tools.libaudio.feature import melspectrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "device = 'cuda:3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_name = 'char2mel_512_512_32_ver9'\n",
    "#model_name = 'char2mel512_512_16_ver9'\n",
    "#model_name = 'char2mel_256_16_ver9'\n",
    "#model_name = 'char2mel256_16_ver8'\n",
    "#model_name = 'char2mel512_512_16_ver8'\n",
    "#model_name = 'char2mel_16_ver6'\n",
    "#model_name = 'char2mel_24_ver6'\n",
    "#model_name = 'char2mel_16_ver6_single5'\n",
    "#model_name = 'char2mel_1_ver5'\n",
    "#model_name = 'char2mel_16_ver1'\n",
    "#model_name = 'char2mel_24_ver1'\n",
    "#model_name = 'char2mel3'\n",
    "#model_name = 'char2mel'  # oldest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "code = model_name.replace('_single5','')[-1]\n",
    "version = 1 if code == 'l' or code =='1' else int(code)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Char2Mel Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('/diskB/6/out/models/char2mel/char2mel_512_512_32_ver9_epoch100_lr0.001_loss0-375_1',\n",
       " {'lr': 0.001,\n",
       "  'n_epoch': 100,\n",
       "  'encode_type': 'onehot',\n",
       "  'hidden_size': 512,\n",
       "  'K': 10,\n",
       "  'out_size': 512})"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_path, settings = best_model_path_and_settings(model_name, 'loss_ave', is_lower_better=True)\n",
    "model_path, settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model version 9\n",
      "Trainable Parameters: 5.600 million\n"
     ]
    }
   ],
   "source": [
    "if model_path: model = CharToMel.init_from_settings(settings, model_path, device=device, **{'version':version})\n",
    "else:          model = CharToMel(encode_type='onehot', K=20, hidden_size=256, out_size=278, device=device, version=version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CharToMel(\n",
      "  (H1): GRUCell(171, 512)\n",
      "  (H2): GRUCell(683, 512)\n",
      "  (H3): GRUCell(683, 512)\n",
      "  (window): AttentionKGaussianWindow(\n",
      "    (Wh1p): Linear(in_features=512, out_features=30, bias=True)\n",
      "  )\n",
      "  (Wh1y): Linear(in_features=512, out_features=512, bias=True)\n",
      "  (Wh2y): Linear(in_features=512, out_features=512, bias=True)\n",
      "  (Wh3y): Linear(in_features=512, out_features=512, bias=True)\n",
      "  (Y): Linear(in_features=512, out_features=128, bias=True)\n",
      "  (mse_loss): MSELoss()\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "print(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for n, p in model.named_parameters():\n",
    "#    print(n, p.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load Duration Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('/diskB/6/out/models/phoneme_duration/phoneme_duration_hid100_rnnnum1_embeddim20_directbi_batchnormrnnoff_batchnormfullyoff_lr0.01_loss1655.643_acc0.729_index40',\n",
       " {'lr': 0.01,\n",
       "  'epoch': 3,\n",
       "  'iter': 29000,\n",
       "  'rnn_type': 2,\n",
       "  'is_bidirectional': True,\n",
       "  'n_layers': 1,\n",
       "  'batchnorm_rnn': False,\n",
       "  'batchnorm_fully': False,\n",
       "  'hidden_size': 100,\n",
       "  'embedding_dim': 20,\n",
       "  'annealing_rate': 0.9,\n",
       "  'annealing_interval': 1000,\n",
       "  'last_lr': 0.000471012869724625})"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration_model_path, duration_settings = best_model_path_and_settings('phoneme_duration', 'loss_average', is_lower_better=True)\n",
    "duration_model_path, duration_settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PhonemeDuration(\n",
       "  (embeds): Embedding(43, 20)\n",
       "  (rnns): Sequential(\n",
       "    (rnn_0): [0] GRU (bidirectional) (\n",
       "    rnn_input_size=20,\n",
       "    rnn_hidden_size=100,\n",
       "    device=None)\n",
       "    \n",
       "  )\n",
       "  (dropout): Dropout(p=0)\n",
       "  (fully_connected): FullyConnected(\n",
       "    (fully_connected): DataParallel(\n",
       "      (module): Linear(in_features=100, out_features=12, bias=False)\n",
       "    )\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration_model = PhonemeDuration.init_from_settings(\n",
    "    duration_settings,\n",
    "    duration_model_path,\n",
    "    device=device,\n",
    "    **{\n",
    "        'disable_cuda':False,\n",
    "        'cuda_device_ids':None,\n",
    "        'cuda_output_device':None,\n",
    "        'verbose':False\n",
    "    })\n",
    "duration_model.eval()  # without droput\n",
    "duration_model.cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for n, p in duration_model.named_parameters():\n",
    "#    print(n, p.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predict Duration & Genarate Mel Spectrogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 15.3 µs\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'ケツアツハケンコウノバロメータートシテジュウヨウデアル'"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time\n",
    "text = 'ケツアツハケンコウノバロメータートシテジュウヨウデアル'\n",
    "#text = '本当にそうなることが'\n",
    "#text = 'それです'\n",
    "#text = 'しました'\n",
    "#text = '水をマレーシアから買わなくてはならないのです。'\n",
    "#text = '木曜日、停戦会談は、何の進展もないまま終了しました。'\n",
    "#text = '上院議員は私がデータをゆがめたと告発した。'\n",
    "#text = 'むかし、むかし、ひとりの老人が住んでいた。'\n",
    "#text = 'これとそれは'\n",
    "#text = '週に四回、フランスの授業があります'\n",
    "#text = '許可書がなければここへは入れない'\n",
    "#text = '許可書'\n",
    "#text = '大声で泣きながら、女の子は母親を探していた'\n",
    "#text = '無罪の人々は、もちろん放免された。'\n",
    "#text = '末期試験に備えて、本当に気合いを入れて勉強しなきゃ'\n",
    "#text = '疲労やら、飢えやらで、彼は目眩を感じた'\n",
    "#text = 'むしろロン毛のほうが禿げやすいって聞いたぞ'\n",
    "#text = '容姿端麗、頭脳明晰、運動神経抜群、家は金持ちで、ついでに学生会の副会長をしてたりもする、いわゆる、パーフェクトな奴だ'\n",
    "#text = '分析においては、クルツによって最初に分析された、権威的行動の類型に負っている部分が大きい。'\n",
    "#text = 'さよならを言わなければなりません。'\n",
    "#text = 'センセイガクは科学的な根拠もないのに、とても人気があって、センセイガクは信じている人が多いようです。'\n",
    "#text = '案の定、あの業者、今日になって泣きついてきたよ。'\n",
    "#text = 'スマートフォンからフィーチャーフォンまでマルチデバイスに対応'\n",
    "kana_text = text_to_kana(text)\n",
    "kana_text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 19.6 µs\n"
     ]
    },
    {
     "data": {
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       "  'u'],\n",
       " 42)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time\n",
    "phonemes = Phoneme43.text_to_indices(kana_text)\n",
    "phoneme_names = Phoneme43.to_phoneme_names(phonemes)\n",
    "phonemes, phoneme_names, len(phonemes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 9.78 µs\n"
     ]
    },
    {
     "data": {
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     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "%time\n",
    "score, durations = duration_model.predict(phonemes)\n",
    "score, durations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     },
     "execution_count": 90,
     "metadata": {},
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   ],
   "source": [
    "list(zip(phoneme_names, durations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "sum(durations), (sum(duration_model.predict(phonemes)[1])/1000)*24000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "scrolled": false
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   "outputs": [
    {
     "name": "stdout",
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      "Wall time: 11.4 µs\n"
     ]
    },
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       "        ...,\n",
       "        [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
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       "        [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
       "         0.        ],\n",
       "        [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
       "         0.        ]], dtype=float32),\n",
       " (229, 43))"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time\n",
    "mel_generated, phi, w = model.generate(phonemes, duration_model)\n",
    "mel_generated, mel_generated.shape, phi, phi.shape, w, w.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
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       "      <th>t</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.142317e-24</td>\n",
       "      <td>1.127732e-05</td>\n",
       "      <td>2.085932e-03</td>\n",
       "      <td>1.804180e-16</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.340309e-41</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.090024e-17</td>\n",
       "      <td>3.262273e-03</td>\n",
       "      <td>4.708068e-06</td>\n",
       "      <td>3.841672e-24</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.797295e-16</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.216742e-40</td>\n",
       "      <td>1.135288e-10</td>\n",
       "      <td>2.056582e-02</td>\n",
       "      <td>2.467782e-10</td>\n",
       "      <td>1.790759e-33</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>o</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.264996e-04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.879522e-29</td>\n",
       "      <td>3.156876e-06</td>\n",
       "      <td>2.825418e-03</td>\n",
       "      <td>3.003944e-16</td>\n",
       "      <td>1.821688e-44</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.050992e-04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.232330e-20</td>\n",
       "      <td>1.739413e-03</td>\n",
       "      <td>8.459228e-06</td>\n",
       "      <td>8.491782e-24</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.792711e-18</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.714013e-13</td>\n",
       "      <td>1.899075e-02</td>\n",
       "      <td>5.519371e-10</td>\n",
       "      <td>5.574760e-33</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.802597e-45</td>\n",
       "      <td>9.567013e-36</td>\n",
       "      <td>8.655678e-08</td>\n",
       "      <td>4.108428e-03</td>\n",
       "      <td>7.848027e-16</td>\n",
       "      <td>8.547921e-44</td>\n",
       "      <td>5.525129e-39</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>o</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.160302e-25</td>\n",
       "      <td>2.825744e-04</td>\n",
       "      <td>1.761180e-05</td>\n",
       "      <td>2.431878e-23</td>\n",
       "      <td>5.149772e-42</td>\n",
       "      <td>1.729105e-27</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.015890e-16</td>\n",
       "      <td>1.292226e-02</td>\n",
       "      <td>1.495979e-09</td>\n",
       "      <td>1.642572e-32</td>\n",
       "      <td>1.480261e-32</td>\n",
       "      <td>3.910673e-18</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.122586e-09</td>\n",
       "      <td>8.277852e-03</td>\n",
       "      <td>2.517923e-15</td>\n",
       "      <td>2.726335e-31</td>\n",
       "      <td>7.323351e-22</td>\n",
       "      <td>6.391920e-11</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>o</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.016649e-43</td>\n",
       "      <td>2.480771e-34</td>\n",
       "      <td>3.176972e-05</td>\n",
       "      <td>7.427980e-05</td>\n",
       "      <td>8.397720e-23</td>\n",
       "      <td>1.809258e-26</td>\n",
       "      <td>1.786657e-13</td>\n",
       "      <td>7.550239e-06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>k</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.288641e-16</td>\n",
       "      <td>1.084886e-22</td>\n",
       "      <td>6.835914e-03</td>\n",
       "      <td>9.336781e-09</td>\n",
       "      <td>2.738897e-23</td>\n",
       "      <td>6.280114e-17</td>\n",
       "      <td>2.149291e-07</td>\n",
       "      <td>6.445264e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>1.899446e-40</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.786421e-04</td>\n",
       "      <td>1.092735e-13</td>\n",
       "      <td>1.118329e-02</td>\n",
       "      <td>1.643988e-14</td>\n",
       "      <td>1.857561e-19</td>\n",
       "      <td>1.365237e-09</td>\n",
       "      <td>1.274893e-03</td>\n",
       "      <td>3.999923e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>6.427109e-33</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.105491e-04</td>\n",
       "      <td>2.535001e-07</td>\n",
       "      <td>1.391018e-04</td>\n",
       "      <td>9.279834e-17</td>\n",
       "      <td>1.681603e-12</td>\n",
       "      <td>9.483249e-05</td>\n",
       "      <td>3.765364e-02</td>\n",
       "      <td>1.719145e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>k</th>\n",
       "      <td>3.607292e-26</td>\n",
       "      <td>8.276664e-39</td>\n",
       "      <td>3.687946e-19</td>\n",
       "      <td>1.354490e-03</td>\n",
       "      <td>1.315483e-08</td>\n",
       "      <td>1.398346e-13</td>\n",
       "      <td>2.167519e-06</td>\n",
       "      <td>2.171860e-02</td>\n",
       "      <td>1.927279e-02</td>\n",
       "      <td>1.441798e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>3.433776e-20</td>\n",
       "      <td>4.316478e-30</td>\n",
       "      <td>7.602674e-16</td>\n",
       "      <td>1.666890e-02</td>\n",
       "      <td>5.074903e-12</td>\n",
       "      <td>5.238531e-08</td>\n",
       "      <td>7.096599e-03</td>\n",
       "      <td>2.522853e-02</td>\n",
       "      <td>1.376270e-02</td>\n",
       "      <td>2.892432e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>5.751894e-15</td>\n",
       "      <td>1.509809e-22</td>\n",
       "      <td>9.573204e-08</td>\n",
       "      <td>4.724675e-04</td>\n",
       "      <td>1.104449e-07</td>\n",
       "      <td>3.521602e-03</td>\n",
       "      <td>3.519534e-02</td>\n",
       "      <td>1.333545e-02</td>\n",
       "      <td>2.694699e-02</td>\n",
       "      <td>3.413733e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <td>1.767359e-10</td>\n",
       "      <td>2.808705e-11</td>\n",
       "      <td>2.617093e-03</td>\n",
       "      <td>2.837345e-07</td>\n",
       "      <td>5.359295e-03</td>\n",
       "      <td>3.453209e-02</td>\n",
       "      <td>1.403445e-02</td>\n",
       "      <td>2.475571e-02</td>\n",
       "      <td>3.073584e-03</td>\n",
       "      <td>2.881915e-04</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ts</th>\n",
       "      <td>1.001765e-06</td>\n",
       "      <td>3.605714e-03</td>\n",
       "      <td>1.553344e-02</td>\n",
       "      <td>8.018154e-03</td>\n",
       "      <td>1.671363e-02</td>\n",
       "      <td>1.747773e-02</td>\n",
       "      <td>2.240720e-02</td>\n",
       "      <td>3.600875e-03</td>\n",
       "      <td>4.821350e-03</td>\n",
       "      <td>1.176099e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>9.832393e-04</td>\n",
       "      <td>5.050012e-03</td>\n",
       "      <td>1.458337e-02</td>\n",
       "      <td>7.416185e-03</td>\n",
       "      <td>2.811838e-02</td>\n",
       "      <td>2.358448e-02</td>\n",
       "      <td>1.294165e-02</td>\n",
       "      <td>1.748260e-02</td>\n",
       "      <td>1.679744e-02</td>\n",
       "      <td>1.250502e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <td>1.503478e-01</td>\n",
       "      <td>6.892006e-02</td>\n",
       "      <td>1.590109e-02</td>\n",
       "      <td>5.841862e-02</td>\n",
       "      <td>3.792340e-02</td>\n",
       "      <td>3.164599e-02</td>\n",
       "      <td>3.239371e-02</td>\n",
       "      <td>3.681683e-02</td>\n",
       "      <td>4.426009e-02</td>\n",
       "      <td>5.117250e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ts</th>\n",
       "      <td>3.244644e+00</td>\n",
       "      <td>1.512579e-01</td>\n",
       "      <td>1.426479e-01</td>\n",
       "      <td>6.628504e-02</td>\n",
       "      <td>6.071615e-02</td>\n",
       "      <td>6.573392e-02</td>\n",
       "      <td>6.771031e-02</td>\n",
       "      <td>6.719652e-02</td>\n",
       "      <td>6.612789e-02</td>\n",
       "      <td>6.303129e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>9.291076e+00</td>\n",
       "      <td>2.616327e-01</td>\n",
       "      <td>6.372570e-02</td>\n",
       "      <td>4.156128e-02</td>\n",
       "      <td>4.022356e-02</td>\n",
       "      <td>4.003968e-02</td>\n",
       "      <td>3.884883e-02</td>\n",
       "      <td>3.658211e-02</td>\n",
       "      <td>3.431142e-02</td>\n",
       "      <td>3.081538e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>k</th>\n",
       "      <td>3.487881e+00</td>\n",
       "      <td>1.600285e-02</td>\n",
       "      <td>1.055647e-02</td>\n",
       "      <td>1.059084e-02</td>\n",
       "      <td>1.226547e-02</td>\n",
       "      <td>1.248631e-02</td>\n",
       "      <td>1.169951e-02</td>\n",
       "      <td>1.034816e-02</td>\n",
       "      <td>8.699845e-03</td>\n",
       "      <td>6.865812e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>42 rows × 229 columns</p>\n",
       "</div>"
      ],
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       "\n",
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       "k   9.336781e-09  2.738897e-23  6.280114e-17  2.149291e-07  6.445264e-03  ...   \n",
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       "e   9.279834e-17  1.681603e-12  9.483249e-05  3.765364e-02  1.719145e-02  ...   \n",
       "k   1.398346e-13  2.167519e-06  2.171860e-02  1.927279e-02  1.441798e-02  ...   \n",
       "a   5.238531e-08  7.096599e-03  2.522853e-02  1.376270e-02  2.892432e-02  ...   \n",
       "h   3.521602e-03  3.519534e-02  1.333545e-02  2.694699e-02  3.413733e-03  ...   \n",
       "u   3.453209e-02  1.403445e-02  2.475571e-02  3.073584e-03  2.881915e-04  ...   \n",
       "ts  1.747773e-02  2.240720e-02  3.600875e-03  4.821350e-03  1.176099e-02  ...   \n",
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       "e   4.003968e-02  3.884883e-02  3.658211e-02  3.431142e-02  3.081538e-02  ...   \n",
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       "\n",
       "    219  220  221  222  223  224  225  226  227  228  \n",
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       "k   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
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       "e   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
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       "a   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "h   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "u   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "ts  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "a   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "u   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "ts  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "e   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "k   0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "\n",
       "[42 rows x 229 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phi_frame = pd.DataFrame(phi.T, index=phoneme_names).iloc[::-1]  # reverse by row\n",
    "phi_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'φ(t, u)')"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(16, 10), dpi=80)\n",
    "sns.heatmap(phi_frame, cmap=\"plasma\")\n",
    "plt.suptitle('φ(t, u)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>219</th>\n",
       "      <th>220</th>\n",
       "      <th>221</th>\n",
       "      <th>222</th>\n",
       "      <th>223</th>\n",
       "      <th>224</th>\n",
       "      <th>225</th>\n",
       "      <th>226</th>\n",
       "      <th>227</th>\n",
       "      <th>228</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>silE</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>silB</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sp</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>q</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>r</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.050992e-04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.926736e-19</td>\n",
       "      <td>1.739413e-03</td>\n",
       "      <td>8.459228e-06</td>\n",
       "      <td>8.491782e-24</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>5.751894e-15</td>\n",
       "      <td>1.509809e-22</td>\n",
       "      <td>9.573204e-08</td>\n",
       "      <td>4.724675e-04</td>\n",
       "      <td>1.104449e-07</td>\n",
       "      <td>3.521602e-03</td>\n",
       "      <td>3.519534e-02</td>\n",
       "      <td>1.333545e-02</td>\n",
       "      <td>2.694699e-02</td>\n",
       "      <td>3.413733e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sh</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.485195e-22</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.890978e-32</td>\n",
       "      <td>3.667285e-09</td>\n",
       "      <td>2.218750e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>s</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.015890e-16</td>\n",
       "      <td>1.292226e-02</td>\n",
       "      <td>1.495979e-09</td>\n",
       "      <td>1.642572e-32</td>\n",
       "      <td>1.480261e-32</td>\n",
       "      <td>3.910673e-18</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.797295e-16</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.216742e-40</td>\n",
       "      <td>1.135288e-10</td>\n",
       "      <td>2.056582e-02</td>\n",
       "      <td>2.467782e-10</td>\n",
       "      <td>1.790759e-33</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>z</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.629388e-10</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.802597e-45</td>\n",
       "      <td>9.567013e-36</td>\n",
       "      <td>8.655678e-08</td>\n",
       "      <td>4.108428e-03</td>\n",
       "      <td>7.848027e-16</td>\n",
       "      <td>8.547921e-44</td>\n",
       "      <td>5.525129e-39</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ch</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ts</th>\n",
       "      <td>3.244645e+00</td>\n",
       "      <td>1.548637e-01</td>\n",
       "      <td>1.581813e-01</td>\n",
       "      <td>7.430319e-02</td>\n",
       "      <td>7.742978e-02</td>\n",
       "      <td>8.321165e-02</td>\n",
       "      <td>9.011751e-02</td>\n",
       "      <td>7.079739e-02</td>\n",
       "      <td>7.094924e-02</td>\n",
       "      <td>7.479228e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>k</th>\n",
       "      <td>3.487881e+00</td>\n",
       "      <td>1.600285e-02</td>\n",
       "      <td>1.055647e-02</td>\n",
       "      <td>1.194533e-02</td>\n",
       "      <td>1.910139e-02</td>\n",
       "      <td>1.248632e-02</td>\n",
       "      <td>1.170167e-02</td>\n",
       "      <td>3.206676e-02</td>\n",
       "      <td>2.797285e-02</td>\n",
       "      <td>2.772905e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.079035e-03</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.142317e-24</td>\n",
       "      <td>1.127732e-05</td>\n",
       "      <td>7.214302e-03</td>\n",
       "      <td>3.125764e-05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>py</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ry</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hy</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ny</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gy</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>by</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dy</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ky</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>my</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.275156e-29</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4.614616e-41</td>\n",
       "      <td>7.592653e-15</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.270697e-41</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>w</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>1.899446e-40</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.786421e-04</td>\n",
       "      <td>1.092735e-13</td>\n",
       "      <td>1.118329e-02</td>\n",
       "      <td>1.643988e-14</td>\n",
       "      <td>1.857561e-19</td>\n",
       "      <td>1.365237e-09</td>\n",
       "      <td>1.274893e-03</td>\n",
       "      <td>3.999923e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.340309e-41</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.090024e-17</td>\n",
       "      <td>3.262273e-03</td>\n",
       "      <td>4.708068e-06</td>\n",
       "      <td>3.841672e-24</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>aH</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.196099e-34</td>\n",
       "      <td>8.495774e-10</td>\n",
       "      <td>2.146243e-02</td>\n",
       "      <td>1.854892e-10</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>o</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.016649e-43</td>\n",
       "      <td>6.264996e-04</td>\n",
       "      <td>3.176972e-05</td>\n",
       "      <td>3.568542e-04</td>\n",
       "      <td>2.076867e-05</td>\n",
       "      <td>2.825418e-03</td>\n",
       "      <td>2.845779e-05</td>\n",
       "      <td>2.064546e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>9.291076e+00</td>\n",
       "      <td>2.616327e-01</td>\n",
       "      <td>6.383625e-02</td>\n",
       "      <td>4.156154e-02</td>\n",
       "      <td>4.036266e-02</td>\n",
       "      <td>4.859649e-02</td>\n",
       "      <td>3.884883e-02</td>\n",
       "      <td>3.667694e-02</td>\n",
       "      <td>7.196506e-02</td>\n",
       "      <td>4.800684e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>u</th>\n",
       "      <td>1.503478e-01</td>\n",
       "      <td>6.892006e-02</td>\n",
       "      <td>1.851818e-02</td>\n",
       "      <td>5.841891e-02</td>\n",
       "      <td>4.328270e-02</td>\n",
       "      <td>7.445593e-02</td>\n",
       "      <td>4.642816e-02</td>\n",
       "      <td>6.157254e-02</td>\n",
       "      <td>4.733368e-02</td>\n",
       "      <td>5.146069e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.005168e-06</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.614129e-43</td>\n",
       "      <td>1.097511e-14</td>\n",
       "      <td>5.239162e-03</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>9.832393e-04</td>\n",
       "      <td>5.050012e-03</td>\n",
       "      <td>1.458337e-02</td>\n",
       "      <td>2.408509e-02</td>\n",
       "      <td>2.811838e-02</td>\n",
       "      <td>2.359479e-02</td>\n",
       "      <td>3.902900e-02</td>\n",
       "      <td>4.271113e-02</td>\n",
       "      <td>3.056015e-02</td>\n",
       "      <td>4.142934e-02</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>43 rows × 229 columns</p>\n",
       "</div>"
      ],
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       "\n",
       "               5             6             7             8             9    \\\n",
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       "b     8.655678e-08  4.108428e-03  7.848027e-16  8.547921e-44  5.525129e-39   \n",
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       "w     0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "N     1.643988e-14  1.857561e-19  1.365237e-09  1.274893e-03  3.999923e-02   \n",
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       "iH    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "aH    0.000000e+00  3.196099e-34  8.495774e-10  2.146243e-02  1.854892e-10   \n",
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       "e     4.859649e-02  3.884883e-02  3.667694e-02  7.196506e-02  4.800684e-02   \n",
       "u     7.445593e-02  4.642816e-02  6.157254e-02  4.733368e-02  5.146069e-02   \n",
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       "\n",
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       "w     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "N     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "oH    ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "eH    ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "uH    ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "iH    ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "aH    ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "o     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "e     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "u     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "i     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "a     ...  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  \n",
       "\n",
       "[43 rows x 229 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phoneme43_names = [Phoneme43(i).name for i in range(len(Phoneme43))]\n",
    "w_frame = pd.DataFrame(w.T, index=phoneme43_names).iloc[::-1]  # reverse by row\n",
    "w_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'w(t)')"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(16, 10), dpi=80)\n",
    "sns.heatmap(w_frame, cmap=\"plasma\")\n",
    "plt.suptitle('w(t)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2ahjdkxqphPKolozQShKjvDNjGy2tZKE7Yzw1mAN0SZIkSdJ4kgrmoPe6M+fXNmuSJEmSJNWAEfQmsGeIwBR3qSC5ReJqyFR5aTIWiau/E+/72szlb/rhaTPf9kLSoD8A6iwH6JIkSZKk8VTRZq1DKe4O0JugO8fjzkqvDllzRtClQuRFpYuMrPcLatlT1HrUPY0qRFdgqojfHOoj7xi8z57VndfuWGzQ50Kd5QBdkiRJkjSWXpKkheLKlHTngrUD9AZInIMutZeZEeVzCmIrNSpirJlp+xz0XguyavZaU12ew7ZBu48PtYMDdEmSJEnSeKpos9bvzgQW4wiSJEmSJNWAEXSpKfpeT5OK0Kw2a81PZ1V71XFaQdtT3Oto0qnIu89Vd167ZaFBfwDUWQ7QJUmSJEnjGSTprextdoQD9CbIuzJpG7JusZiYVIwSAihFRb4L7D6lGpk08rxSsdjenAfJKCPo9be2wrnE//XTyjYtjc0BuiRJkiRpPElSfqCwQ23WnIghSZIkSVINGEFvgu5cMJKkmcstEmc++cw0qTCfmm3B2X+1N19h8ct3XnVa5vJX/+oflbwnUj4H6JIkSZKk8Qwq6IPeodpbDtAbYKXiMOoQi8RJxSilSFxB6+l7/h9XHVt+VWnQ0ffDInHjmbQ1WpHmKywSJzWBA3RJkiRJ0niSpPyrPB0qEucAvQm80LizDqW47MT5sVIhemajSK21wwj6zGzY989y7rlyovXMVTgHXWoCB+iSJEmSpPEkFcxBr3JeRsmsqypJkiRJUg0YQW+AZKHqPZAkSUXpagG3MiwWlD3drzINu6aBwv12my9kPaa4SytzgC5JkiRJGs8gSW9lb7MjHKA3wMRTLrpaRK3t+s5IkQqRF7wssHhcUe3RekaapInsGJidMCvr1hTz3q6xfaS0IgfokiRJkqTxDJLyA4JG0FUnyWLVeyBJLVLDZBRbv62e87oFsL3lEfQqs2rmCnpre3RnoCVNwwG6JEmSJGk8tlmbqRrGESRJkiRJ6h4j6A1gm7UZalJBvTJSYC1EJ9VKr93ZuuVo0Gm+SElHU/53mD09M0V9Q5izSJy0IgfokiRJkqSx9AYVpLg3Kai2Sg7QG2BgkTip+SwCVhtlFGSzPZpUjTv8zlQbg5yCff0aFonznK06cYAuSZIkSRpPkqS3srfZEU44lSRJkiSpBoygN0CyYGqsMEVaxet5jXYnLf+MnfRLJ+fcc0Wp+yFIWtKrOy+FuUrbFuu3T21R1AzgvunkzZckFbRZ685x47czSZIkSZJqwAh6Ayzu8GqwJBWmQZemewW2IzpgXbujD22JSmt17hi0+ziv0kJB7+2cEXRpRQ7QJUmSJEnjsc3aTDlAb4Add7T819ShOSWSaqCUNmsz38TE9pjrzpcbddftC8Wsx7Zbd7ZtsZj3xPdWWlnLR36SJEmSpMIkCZQ9naRDAb0GzcSTJEmSJKm9jKA3wPbtc1Xvguqg7/U0laTl7ca6am2BBedUH72cz2tXJzRsXfA4n5Vrt91RyHr8E9MCgwrarHWoAKTf+CVJkiRJqgEj6A1w0227Zy6/Z8n7IUlt0GvQpekiiynNW5hJHbC9oEJmurNP3fRXOfc8c6L1WCROWpkDdEmSJEnSeGyzNlMNiiNIkiRJktReRtAb4LDPvCNz+YC3lLwnqpRVVaTZKvAz1qthQbb5Gu5TkyTdCd402oB2H+eFTdGp8Hjum+LefElSftsz26xJkiRJkqQyGUEvW4eu/kgag5kR5evoez7X8qhVk/68Nmlfm2atLUlrzyJx0socoEuSJEmSxpNU0Ae9Q1c2HaCrer0Jo1kdquIoSUVZ083EAc1QHb8vr/NAl9RwDtAlSZIkSeMZJOmt7G12hBN1JEmSJEmqASPoTdb2VO+2v75JdbSwlVS4Bn2WCmuphIWZ1A3r5opZj63AZsfoYAskgwrmoNd7XBBC+ACwJcZ4ymrX5QBdkiRJktRaIYRfBN4FHAX8IvArMcYtyx5zOvBC0jHy+4GXxhh3TLGtg4AfArcNF20FLgKOizHetKvnexFLkiSg1+9l3qZaVy/JvFVpTS/JvEltsm4u+6b6qOP5UZ0wAD4JHJ11ZwjhecAzSAfwBwMPBk5a5Tb3jzGuB+4P7AecPs6TjKBLkiRJksYzqKDN2rBI3DnnnHPIpk2bsh5xTYzxmrynxxh/BLwDIISQ9ZCNwFtijJcPH3P68PGvy3pwCOHRwJnAgcCFwNoVtn1zCGEz8Pt5jxllBF3FGgyyb5KkSvVybm0xSHqZN3XL2n4v86b66PeSzJs0js2bN18AfDXj9oJVrvpQ4BsjP18C3CuEsM/yB4YQ9gM+AmwC9gU+A2zIW/Hw8UcDXxhnR4ygS5IkSZLGU2GbtQ0bNhxz2WWXbcl4RG70fEzrgZtHfl6aK77XsuUATwa+G2N87/Dn80IIx2es89phtH5vYAvw7HF2xAG6JEmSJKn2Nm7cuGXjxo1fW+kxIYRjSAvCAVwRY3zgGKu+lXQgvWQpcn5LxmPvAVy5bNkVGY+7e4xxWwhhd+BU4BOkc9tX5AC9hXqmlLdTkf2WpA7r6kfJFNL6mDT1ftpihV20tt/u47xJ568k51dRx4JwddynehtU0PZs/O3FGC8ALphwA5cChwOfH/58BHBVjHF59BzgatK556MOJE2Lz9qfrSGEc4FXhBD2jzHesNKOOECXJEmSJLVaCGHdyI9rhz/fEWNMgHOBE0MIHydtj3YS8J6cVX0MODOE8CzgQ8AzgcOAzTnbXUua3n4tcOOu9rNB1+EkSeqWXj/7No1+L/smtcl8P/s2qV4v/yapsbYOb5AWhNsK3Gf489mkg+2vAt8njYZntkWLMd4IPJV0EP8T4PHARzMeekMI4VbgOuBhwFOGFwNWZARdkiRJkjSeARUUiVv9KmKMuZfYhgPnkxiz93mM8WLgATn3Xc4qGqUYQZckSZIkqQaMoEv6ub7X7NQBJeSo1rGQUw+LIHVJUkIP+DK2Malp0tlVLgtWtsBgkN7K3mZHeBqTJEmSJKkGjKBLTWE1J2m2Wv4Za/nLq2U0V+Wbq+Fh8JpfOjlz+Z9//9SS96QeLLTXAklS/hz0vL59LWQEXZIkSZKkGjCCLknqlraHknPkzkEvOwoio/0zNF/D+c333XOx6l2Q1CAO0CVJkiRJ4xkkFRSJq9/Ft1kxxV2SJEmSpBowgq5u61DLhlXp0FVLqa1sbaQuKKpIXK9f3Odl7/kJv2tUGT4rYdtFvreqiEXiZsoIuiRJkiRJNWAEXcUy0ipJ9Aq6/N0rMOrd0dp4mqGZF7ub4nNUx0yR3eeKKxJX5DmhKnX8HUl14gBdkiRJkjSeZJDeyt5mRzhAl5qi74yU2mvL76jtmTCGkltp0ILWZSfe97U593xv5tt+1f1Ozlz+xh+cOvNtF6moOehF2q3fnYGFpNVzgC5JkiRJGs+ggiJxbQ8ejGhJuEeSJEmSpGYzgi5JErQ+9b1Hd6IPo+o4bTEvHT/sVdzOTlpM7BfWteP4mCuoAFmRhczmbSu2kzYUuuu8hArarJW7uSoZQZckSZIkqQaMoKt56hgOkaTVKOFyeZWtjYyYjWef+eLacU1qzzWT/22tY2G+Okae5mtYJC7vq1RRLSKhhDZ8Uks5QJckSZIkjWcwSG9lb7Mj6nihUZIkSZKkzjGCrmJ1qAVC6VpewKqz/L2Wr4T3PD+lu7rfd6/lh1qT0mnz9nXdXHURonUtKWRWx1PqXK87kb9xOOWlBWyzNlNG0CVJkiRJqgEj6JI0qb7XNtU8/S71qGmo3SosJtaWVmB1bCdYVOu3upo0e6Xt2TydkFQQQU/a/Tka5bdMSZIkSZJqwAh6G3XoCpPUGHWMutdxsmYJeg163VO1POrQPL22qTKKPc22k0H9PktFfbyLnCc9V+Dvtcg2aJLqyQG6JEmSJGk8g6SCNmvdufjsdThJkiRJkmrACLqkXSv7KqlUhQalvk+j3/JCVU06S+Xt63yFReLaUsisjh9j26ztrN+SgoSdliTlT6nt0BReI+iSJEmSJNWAEXQVy0jr7NSxyJikTHUs5GRro/qrMtI6TQS9QwGtVSmySJxUC7ZZm6kafoWQJEmSJKl7KoughxDuCkTgezHGhw6XHQqcDTwI+AHwohjjv4885xXAS4C7Ap8Fnh9jvHbk/gcBbwUeAmwFzooxvrqUF6TC9RKj8ZKk9kmS7HSGKueBtyVi06OY97DINmttr/+QJ+84L/K9ldqoyvPxm4FvLf0QQpgHNgMXAvsCm4CPhBD2Hd5/DPAi4DHAAcB1wPtGnr8fcBFwHrA/cB/gA2W8EEmSJEnqhEFSza0jKhmghxAeBfwS8Hcjix8F7AG8KcZ4R4zxfOCHwFOH9x8NvDvG+IMY4zbgVODRIYT7De//E+DiGON5McZtMcbbY4zfLOHlSJIkSZK0aqWnuIcQdgPOBJ4JHDly16HAt2KMo3nNlwyXQ3oxYTRXZun/h5Gmwz8M+HYI4fPALw+f+7IY47cLfxGSpOaqYx+mEvQLSv2tq7x02joa5KW4V1hMbJr0+rzXoZ2Z0q3WSZLyC0NbJG6mXgV8Ksb4rWXL1wM3L1t2E7DX8P8fB54bQjg4hLAHcAqQkEbdAe4N/CFwPHAP4D+AfxqmzkuSJEmSVGulRtBDCAcDzwYOz7j7VmDvZcv2AW4Z/v8c4F7Ap4HdSeew3wJcNbz/duDCGOOXhts6DXglaTTdKHpZOnR1q3QdjfpJKoZRvPqrMsthmkJmdcxaqOOfyiqL/9VRHVs+1vFYrrUq5oQ7B31mHg7cE7g8hHADcAZw5PD/PwAOCyGM7tMRwKUAMcZBjPH1Mcb7xhjvDnwUmFu6H/gmtDx/T5IkSZLUWmXPQf8QcPHIz08jjahvAH4EbANOCCG8Dfg94H6kVd0ZVnPfH/gecBBwFvCWGONPhut6N2lK+5mkg/VXAZeTtnKTJEmSJKnWSh2gxxhvJ01FByCE8BNge4zxquHPG0j7oJ9KGlE/Osb44+HD9yONmh8I/GT4uNePrPtfQwgnAv9Emhr/leHzF2b9uqTWc+qCuqDI3NgKi311VZMKltWxP3SlqeF1zEsvUKF90D23qA5McZ+p0qu4j4oxngucO/Lzt4Bfz3ns94FDdrG+s0kH7pIkSZIkNUqlA3RpKkW2dSi7RYSk6rU8Wpenoy8baniazwsEVdlmbRpNylqYVJGFzLpaoLHNx0fnJRVE0DuUzVlFmzVJkiRJkrSMEXSpKXolXE+rY+8TSRpDk9ok5e1rv1dcuH/Svxi9KRrhNOk9r1Khc9BboNewTBGpbA7QJUmSJEljSSoqEteVS4KmuEuSJEmSVANG0FWsDrVAkArR9zqpVlBgKmhXC1UVJSmyPmlOHKhpv6NFU9zH4uwxtU5C+UXbmnV6XBW/GUqSJEmSVANG0NvI1mGr53u4MzMjpIkYMStfk05TeYGnKqMm07Thq2MbrToeBxZF21nTMkWUwTZrM2UEXZIkSZKkGjCCLjXFNOENSXdW5WepjuG9IlX4+prU8isv8ty0yOLioDnv+aT6BUa9u9pmLWnx8SHNkgN0SZIkSdJ4Kmqz1hWmuEuSJEmSVANG0CVJkkrUlvZki8ls4zy9KaajJDkt7KrUtKkL0i4ZQZ8pI+iSJEmSJNWAEXRJ6qq+12hbqUNRhlGDGkZO8+RFnptWTCy3SJynlp10NYKe1xXLNpQtYJu1mfIUKkmSJElSDThAlyRJkiSpBkxxl5qiynTkjqbMqmPMu2y0vOzHZFDufoxjISc1vGmp0DsG9Yvz+OdKmr1kQAVF4srdXJXqd2aVJEmSJKmDjKBLUpWmaCOk+ut5+bt0gwa1LluYcXuysmwfzFW9C3dSxxZ2RSbnmOijWrBI3Ey14y+EJEmSJEkNZwRdxSrjapoTzCRJDbYjrz1ZgcqYrrltsX5xnqK+IhRZD6Df7+b3lrysll5H349WGVQQQe/Q9//6nVklSZIkSeogB+iSJEmSJNWAKe6qXFJl+7Am8X2SpFwDmlM9646c9mT9hrVZ+8n2+n2NrGOROKl1THG/kxDCB4AtMcZTVruu+p1ZJUmSJEkqSAjhScArgcMRsc4+AAAgAElEQVSA7cBngONjjD8aeczpwAtJx8jvB14aY9wxxbYOAn4I3DZctBW4CDguxnjTrp7vAL2NBmWUhpGkhupoa7uk5ZHFWXfgKfL9u32hHRlRz/r6GzOXb330M0rek59bqGGQrciCc03S9nNOtyUVtD1b9fb2ATYBnwV6wDuBc4EnAoQQngc8AziKdGD9z8BJwOtWsc39Y4zbQgj7AB8ETgdesqsnOUCXJEmSJNXeOeecc8imTZuy7romxnhN3vNijO8b/TmE8DbSKPqSjcBbYoyXD+8/HXgHOQP0EMKjgTOBA4ELgbUrbPvmEMJm4PfzHjPKAbrUFFVG/czKkKpRQjuutlhMmhOVvnH7XNW70FrOQa+/rmYUtEkyoJxejqOG29u8efMFOY94PXDKBGt8JHDpyM+HAt8Y+fkS4F4hhH1ijDePPjGEsB/wEeDFpKnwxwDvBr6ZtaHh448GvjDOjjlAlyRJkiTV3oYNG4657LLLtmTclRs9Xy6EcBTwGuBJI4vXA6MD8aW54nstWw7wZOC7Mcb3Dn8+L4RwfMamrg0hAOwNbAGePc7+OUCXJEmSJNXexo0bt2zcuPFrKz0mhHAM8K7hj1fEGB84ct+DSOeXPy/G+LmRp91KOpBess/w31syNnEP4Mply67IeNzdh3PQdwdOBT4BPHilfQcH6JJUrToWLKvjPjVNDbOta96hZtVyX18NZ+j88bdPz1z+pAOfV/KetM+OGh7nvY6eUgdON2ivARW0WRv/oTHGC4A7pcKHEA4FPg2cEGP8h2V3XwocDnx++PMRwFXL09uHriadez7qQNK0+Kz92RpCOBd4RQhh/xjjDSvtvwN0SZIkSVJrhRAeCFwMvGo4gF/uXODEEMLHSau4nwS8J2d1HwPODCE8C/gQ8EzS9m2bc7a9ljS9/Vrgxl3tqwP0Jiu9vYGkqRmVVsWqbHnUKyGjwGidABYsrCjNXpKUH0Ff/bjnFcDdgDNCCGcsLYwxrh/+92zgPsBXgXnS4m+Z6U4xxhtDCE8F3kaaSn8h8NGMh94wnIO+QFqA7ikxxl2+EAfokiRJkqTWijFuJG2llnd/Qho1P2nM9V0MPCDnvstJe61PpYaz5CRJkiRJ6h4j6Oq2JvX37ns9TQUz7b5TBtNfzG+EpAWvr8hiYlVOaajSQg1n//X6NdypEjTpGGzSvtZBlX3Qu8Bv/JIkSZIk1YARdEmSWiTpUJRh1GILImBtqf1aRlHAPC15C1uho6eibmhmkbjGMIIuSZIkSVINGEFX8zRp3rgk1UTbgw9lB3PapmfseSdF1gOQWsc56DNlBF2SJEmSpBpwgC5JkiRJUg2Y4i41RQn5dklOKzcz/WbIPMpWqrJIVp5BGUXUKkxBzCsS1/bU/lab4nM0V8NTaq/XzYMwr3VZHc+PmtAgISl5XlGvQ/OY/IhIkiRJklQDRtAlSd3S0ayFQctzYRZa0GatFDlBqH5LorzzLXkdUq0llJ8x1aGPthF0SZIkSZJqwAi6JEmSJGk8CeVHtDsUQXeALklSB7S9WFpekbiiJIN2p9D3W/Ly1pobWhulFKYswXuPeHXm8mdf8oaS90Rd4WlMkiRJkqQaMIIuNUVOCzTNzu/s92dV74JUmLZEs/LMOoKuZtitX79UkTrWpcxtdVZg4a+8NmtNc5e1C1XvQu0kFbRZwzZrkiRJkiSpTEbQVT0jw6qpE35le9W7oIaqY8QsaXmbtTZE0KvMcui1pALT2n7ZvZ9apsCvZE0KePZWaM+3x9xiiXvSELZZmylHRpIkSZIk1YARdEmSJEnSWJJBeitVh5JjHKBLUo6915aQ4l7lFA+nl6hFFjr05W0W+iuk+DbJfA2LxKnZdpvz5KJy+e1MkiRJkqQaMIIuZRnU8GppgdHOy5/83MLW1Wbr1lgYRu1RacGm3KhmcUXRdrSgSFyV6ljYcBpG0MuXl+rcljZrayw8eGcWiZspI+iSJEmSJNWAEXSp4W54xh9kLt//A+fnPmff/W+f1e60yto1C1XvgkrU65cQ7cnbRgnh7SpbeJVhx6D5r68tEccqwz/zNZxL3yswqt9rUGhtkJMh06TXADBvBP1OLBI3Ww37iEiSJEmS1E4O0CVJkiRJqgFT3NU8dSzgVqF1+06ehj2/vn4pgHW0Zk2Bx5otzWqjnFT22W9CO1vMSQ8vPQ2zbAUda/2WVGAyHbk+knYcUsz1PKbuZED5Kecd+jX4FUKSJEmSpBowgi41RU7Ub273KVa1bpX70hF9IzGqWJHR36TAlmZ1tN2P66r0a1hcbRpzLXkdbbCQtCMOOGfrvjtJkgoyJDr0a2jHJ0eSJEmSpIYzgi5JkiRJGk9Sfn2PLiXHOECXGq6/2+Rpq70pntNFvTLepjIKlkkdsKMFPcSL7FXfm/DbbCnnuyLlTfvq0rf4mmtLkbi2TP9Qc5jiLkmSJElSDRhBb7K8dmODllzps53aWHprp4igr8l5jq3AdjI35zEoNcX2xdmuvy3RwDyVtlkrMJNoTQ0Lek2azdAWRWaEVKmrv78V2WZtpvw2LkmSJElSDRhBlxouNxpe8HO6qHFzMlUbvRpe/m5LclWeO1oQXUlaEnGs0lyvBQdCSyy25Hi2rsGdJRUUiWt7FtOoGn6FkCRJkiSpe4ygS5IkSZLGkiTlR7S7FEF3gC41RV4BtzVTJMJM85wO6k1abMiceKky2xb9/I2a9Cxfy0JYUxSPMx25PhaTdnzXsM2aytaOT44kSZIkSQ1nBF1quN7cFEXivDQ3llpGlIpUYGsjqWpbF5v/ea2yvFlbTgdzNWyz1lVtKRLX+u8C0xj00lvZ2+wIv6ZLkiRJklQDRtClpptmPvmc1+bGUcqU8jqGrUyxaKU6HmpFum2HUS5BH4+DulhoScTTOeh3Zpu12fJbmCRJkiRJNWAEXZIkSZI0liTpkZRcY6Ds7VXJAbqK1fYcyjqa5j339zSWidusaWx/88DXZi5/2bdPm/3G847/QYG/b/PTSvfTHVWWWCtGlV9A21IIq6gicbU9/xd1binhHLUj53hu2rFmB1WVza8QkiRJkiTVgBF0ddugQRGXfvb1tJ4R9Jkp9Cq/7/lOnnCP67Pv+Ha5+6H2+OmO7dl3FHSab1p6ZdOilEWp4+tuUt3NIvd1+6BBL1yTGZRfJK7SPpQl85MjSZIkSVINGEGXJEmSJI3FNmuz5QBdjdNrUlp6GUydnpkmpSU2zfo9tlW9C2qZrclC1bvQaG3p9dyW19EG2xab80d0pakRtS0YqNZygC5JkiRJGott1mbLAbrUdFNE0CcuLJdToK7tjKDPztrdFqvehfbKaRfXY/ZRoKTIVnUT2r3X/K80gw59AZ2VOhaJ66pbFtrxR9SsDJWtHZ8cSZIkSZIarvmXm6Wus83azJQSielodsKa+RpG0P1cNNpea+ar3oVamTTq15bIczfPqPX0g1s9p7ZVMuiRDEpOcS95e1XyPCZJkiRJUg0YQZckSZIkjSVJym97Zps1Sc1hWu7MWCRudubm2/2Xto7HTpWFjnolnKb2WDM3+43MWJeqFM9KW1L12+Avf3ha5vLXPPKZJe/J6nhMqWw1/AohSZIkSVL3GEGXmiIvBFVkaKqjBcsmZtbCqvVbHkFX+fZY4+dStsSSymLGz+z4bVySJEmSpBowgq7qGbVdlZ5t1manbyRmVnr+9RlLkXPZ2/6xXzfjKehltPgZFHjKmXTebFv+EpcxX/iEg16bufzNl2fPuVazOQf9zmyzNlttOR9LkiRJktRoxjAkSZIkSWOxzdqdhRA+AGyJMZ6y2nU5QG+yInPhtLPBoOo9GF/b81YrVEZrqEpV2Aus0jZkeZ8Zz6mNtrb5XdZUgDKKxB2yd3XfEerYwlFqghDCQ4G/Be4D9ICvAMfHGL898pjTgReSjpHfD7w0xrhjim0dBPwQuG24aCtwEXBcjPGmXT3fj7kkSZIkqc2+D/wOcFdgf+CjwIeW7gwhPA94BnAUcDDwYOCkVW5z/xjjeuD+wH7A6eM8yQi61HRG0GfGSMXs9Noe7cw5dvKOqaSEgFyPdmcIrGlByksZbYuSlmeKlHEY7LVmsg9sk/6WTPP+lXH+qlILTi2FS5Je6W3WlrZ3zjnnHLJp06ash1wTY7wm7/kxxuuX/h9C6AMJcP8QQi/GmAAbgbfEGC8fPuZ04B3A67LWF0J4NHAmcCBwIbB2hW3fHELYDPz+Ci/xZxygS5IkSZJqb/PmzRfk3PV64JSVnhtC2Ae4AtiLNM391OHgHOBQ4BsjD78EuFcIYZ8Y483L1rMf8BHgxaSp8McA7wa+mbPd/YCjgS+stH9LHKBLkiRJksaSJD0GZbdZG0bQN2zYcMxll122JeMhudHzJcOB9l1CCHsBzwX+a+Tu9cDoQHxprvhey5YDPBn4bozxvcOfzwshHJ+xyWtDCAB7A1uAZ+9qH8EBuopmuvXMJDn94n3HZ6jItMS8HMeOfmaalPLZFmUUz6rSfL/5r29Q4Rm9Lb2eeyUcB+vmWp7T3UGmsTfHxo0bt2zcuPFrKz0mhHAM8K7hj1fEGB84en+M8ZYQwpnADSGEX44xXgfcSjqQXrLP8N9bMjZxD+DKZcuuyHjc3WOM20IIuwOnAp8gndu+Ir8iSZIkSZLGstRmrezbuGKMF8QY1w9vD8x5WB/YA7jn8OdLgcNH7j8CuGp5evvQ1aRzz0ct/3l0f7YC5wK/GkLYf1f7bwRdarqORmDL0JYo79cf9ZKqd+HOWvLeqj7mZnwqrHsP3uWqzJjotfzv0nxLsg2kLgkhPAX4AfAd0kj5G4Hrhz9DOoA+MYTwcdL2aCcB78lZ3ceAM0MIzyKtBP9M4DBgc86215Kmt18L3LirffUrkiRJkiSpzX6BtLDbLaRzz+8FPCHGuG14/9mkg+2vkrZku4SctmgxxhuBp5IO4n8CPJ60bdtyN4QQbgWuAx4GPGWkKF0uI+hS0+XMTdfqtWVO2l33ur3qXbiTtmQnNElbjuc8a3JeX5NaQDUtSl9HRWUOrDQnf77foINKq9ZvQX2LolXZZm1aMcazSQfhefcnpAPusXqfxxgvBh6Qc9/lrKJMlF+RJEmSJEmqgVIj6CGE3YC3A48F9ietfvfnMcb3De8/lPTKxoNI5wi8KMb47xnrOYW0afwTY4yfHFn3W0nTDdYCXwZeHGP87oxfliRJkiR1Qlq0rewIeqmbq1TZKe5rSKvePRa4HPgN4GMhhB8CXyGdWP8u4JHA04CPhBB+Kcb4k6UVhBB+mXQQvrzX3Z8AjyCtuHcD8FfAe4GHzvD1SGqzluQYrdt9R9W7cGcteW9VH21P4dd4ymgX14YaeE4zkuqr1AF6jPE24OSRRf8RQvgc6UB9PWmp+zfFGAfA+SGEl5MOxt898px3AicAZy1b/f2AT8QYrwEIIfwdaQN6SZIkSVIBEnoMyo6gTz+lu3EqLRIXQtgTOAr4G+BQ4FvDwfmSS4bLlx5/LHB9jPGiEMLy1Z0NvDWEcC/SCPpG4OOz23upJtpwKb+m2hJhWDO/WPUu3Enb2zDV8fX1aXd+4OzbrM3+d1r2F15NZ842a5JmqLIBegihRxoZ/xLwaeAhwPJG8DcB+wwff1fS6Psjcla5hTRt/r+BRdI57I8rer8lSZIkSZqFSgbow8H53wL3Bv53jDEZ9ojbe9lD9yHtVQfwJuCMGOPVOat9J7AXcDfSgf0fAf8aQnhgjLF+PYbaqoxJgF2qEjEqr51aDSN1qpc1u9XwM1PHw9bP0k7e+oDXZi4//rLTSt6T8bTh1zco8IPR1Tn5ZcxB71WYjdLV36vqJRn0SAYlp7iXvL0qlZ7AORycvx14MGkV9tuGd10KHBZCGN2nI4bLAR4DvDaEcEMI4QbSwf0HQwhLDeQPA86NMV4fY9wRY3wXcAA5/ekkSZIkSaqTKiLoZ5JWVn9sjPGnI8s/C2wDTgghvA34PdLCbxcO738oO+/vF4BXAR8d/vxF4A9DCP+PNFX+2OHy7xX/EiRJkiSpe9I2a+VvsyvK7oN+H+A44A7gv0cKvb0hxviGEMIG0mJvp5LOIT86xvhjgBjjtcvWtQjcEGNcmrd+Imkf9O8A64DvAk+NMd4021clqbUmzDFK8qYhsEJGdwl5uf35Dv1VU67+hKm/B+6xfUZ7Is1OGSngk36Wyki7L0xLiqMWqVG/P7VC2W3WrmCF76kxxm8Bvz7mug5a9vOPgT9czf5JkiRJklSVStusSSrANOGCgVeDx9GWNmu9Op7pW/Lezly/us/q+jX1a8+3kjYcUl1K4WyyNhQkLFIZLQhVL4Ok/D7oXWpD2Ya/Z5IkSZIkNV4d4yqSJEmSpFrqVZA50Z0IugP0JhsMqt4Dqd1akmPUm5vwCeZvttKks2HWzTUrxX3WBiX04O1SCues9CucFqLm8rhRnThAlyRJkiSNZZCUf0GxS+WTHKBLTbdCay+tTq/ISHKFUek6Fokr9L2toxa8vLVzJWRpFfg+tSGnLCnwDelVGBFMKvwmXVRLrJUyTnp0aKQgqXR+s5ckSZIkqQZqGFdRoxnNnZ0i39su5QmtRguioLBCu7i2R7GbpMrfRc625/vNiknP+rRWRgs0T82SmiBJyi8S16V2fo6mJEmSJEmqASPokiRJkqSxJJRf96NLCUYO0KWmmyI1Nq+AT3eSh8bUkhyj3hp/szvJ+8y0PL+4P+HXm7les1Lc2/Dbs83a6k3aTlCS6sYBuiRJkiRpLM5Bny0H6JKUozWtwOr4MlqSndBmc9O06aow6L7YrIB/ptw2a3X8DEuSZsKvSJIkSZIk1YARdKnpponytnyubWHKuISZ2wOtwE04B72xqpxPO5fTZu2ouzx/hWfdOpudGcMdM46gl5FeuVjgNvq9bp7ne9NkfsxYCaf5wkyzr8nAvzFdM0h6pdfM6FKNjgadMiRJkiRJai8j6JIkSZKksSRUUCSuQ8U4HKCrWG0pqpXUL0WuUKa4j6ctx7O5UvXRoBZveYfNb+//iys867uz2JWxbF3MXt6k03kNDwNl6NJAQVL5HKBLkiRJksaSJOVfUGzSxdbVcoAuNV1/ivDopP2IBi3oXzSFJhX2WVFbMgGapMpjp6CPa16RuL3n6/kt6apbZ3uealqRuK7qFVQcr47F5gAzomakqONGKoIfc0mSJEmSasAIuiRJkiRpLElSQZG4DmUYOUCXmqLANOUkJxO0O6e+MbUkNbw1qfpalUlTOPMev8fc5KmgZRyD51/355nL38EzZr/xgix06Atok1nMT9IsOUCXJEmSJI1lAAxKDut0qRqSA3RVryVRyspM8/4tdOk0t2vfftyLsu/o31rujsyKnzFNoZ8TQV83RQS9DQYlRLd3DKr7rHYpfXS1yjgWJHWXA3RJkiRJ0liSpPy2Z7ZZk6ZlpK4RkoUOneXGsM+eWzOXt2butp9LMXmEtJfz8PmOtiNKSohuLyTFnXS62jYq77gtUmLFFkkz1Javn5IkSZIkNZoRdEmSJEnSWJKkV3othi7VyXCALnVQsr2bqY95dlu3kHNPgX8M+tUlLLUmVV+l6vWzzxPzOcu1elsXu/MFtMkmbrPW8s9Ml+YGS2VwgC5JkiRJGsuAXgVt1rpzAdMBujqtl2S3G2vUxeApCoAN7mjUK5y5NWtz2s71WnKKLKNqklonr83aXEeLj5URJbxlobp0l0qbb04cks6Xl/kx8XpWOM4X25xqa8aVVDk/hpIkSZIk1UBLwkOSJEmSpFlLqKAPermbq5QD9CYb5CSk2fNYu7B4W9V7UC9zu3X0s5RXuC7v3NJ2Nfx9V1ngLy/Ft6tF4sqoWPy9W+p3DOrOZp7i3tFTsKSUA3RJkiRJ0lhsszZbDtDVPJ2N7hUXStt6U/ZHf/fCttAs/fm8O0r4Y9CWbaj2iqqA290icbP/HL31itMyl/8Fz5z5trv05Xe1FnyvWmelWqq2kVPZHKBLkiRJksaS0CMpue1Z2durkgN0qemmmKR6wAfPz1y++MZHrXJnmqk/l3dHS/4YtOV1NEivhu/5pFGgvDnoazoaQVczrNQerSg7BvX7fEtqD9usSZIkSZJUA0bQJUmSJEljGSTprextdoUDdBWrwEJmUll6bT8T1jDd2jZC9ZdXNKmrReLKrli8WmWkenfVQuJ3HUmz0/avpZIkSZKkgiRJ+Rctu1RN3wG61HR1jI42TF4EvY6FvqRpFfVlqqsR9La3IWtahkCeKeqmTuz2hck2slILrzZo+2dDKpsDdEmSJEnSWGyzNlsO0OvE+dtSNfI+ei2JoJsJ0C1JTiWdwYRfbvr97PWseDi1OLi+2PIooVHQna0Uib95wgi6ms3PhsrmGUaSJEmSpBowgi5JkiRJGott1mbLAbqkzuvNtTx9rYYp7nlp2JqdxcFkx0Fem665Xjd75LWliJpW78vXd/MzIKkcDtAlSZIkSWMqv0gcFomTVDt5FWvKKC7Y9mhnUUXiLPSoGiuqyJlt1tqp7af5Ip1/3Z9XvQuSWswBuiRJkiRpLM5Bny3DPZIkSZIk1cBEEfQQwsnA52KMn1m2fE/ghBjjqUXunCSVIbdPeA2Lq02ljq+jyhpLeZfhy3ifcrbRy+k5XqTFZLJr8r3cj0WHwhgjJi2yV1s5n722pPCv1L9cP5f3+e6qFc/BbfnsqzEmPY2dAnwshPDKZcvXA68rZI8kSZIkSbU0oMcgKflW8yJxIYQPhBBOKWJd08xBfxrw9hDCkcBzYoy3F7EjUq0MbKHSKZNeqswtBre42j2RZmZHQVGgrhaJK6rInlRnZiCoC4YD6dcBT4wxfnJk+enAC0nHyO8HXhpj3DHF+g8CfgjcNly0FbgIOC7GeNOunj/Nx/CLwFHA3YAvhhDuO8U6JEmSJEkNlJR8K0oI4ZeBpwLXLFv+POAZpOPcg4EHAyetcnP7xxjXA/cH9gNOH+dJk0bQE4AY43UhhMcAbwW+AvzJhOuR1CR1nMNcpDLmoFfZgi339eXsUxkZJN0MwlZqx2DCOeg5czIbNwe9oMyBhQnn8DdN3dNHm8yodLMNnINeK+ecc84hmzZtyrrrmhjjNVl3LPNO4ATgrGXLNwJviTFeDj+Lpr+DnGncIYRHA2cCBwIXAmvzNhhjvDmEsBn4/TH2b+II+s+O0BjjYozxj4GXk+68JEmSJKnFSp9/PrwBbN68+QLgqxm3F+xqv0MIxwLXxxgvyrj7UOAbIz9fAtwrhLBPxnr2Az4CbAL2BT4DbFhhu/sBRwNf2NU+wuQR9EcDPx5dEGP8uxDC14AjJ1yXJEmSJElj2bBhwzGXXXbZloy7VoyehxDuCpwMPCLnIeuBm0d+Xporvtey5QBPBr4bY3zv8OfzQgjHZ6zz2hACwN7AFuDZK+3jkrEG6CGEvxv58bnDDWU5b5z1SSpQ29PPS9D69MMaHiNJXquztqjhMXX7YjE71dUicQsTThFomqQlv9ZeR4/PKiWmgKtEGzdu3LJx48avrfSYEMIxwLuGP14RY3wg8CbgjBjj1TlPu5V0IL1kKXJ+S8Zj7wFcuWzZFRmPu3uMcVsIYXfgVOATpHPbVzTuX5vFZbenA3tkLJckSZIktdSgotu4YowXxBjXD28PHC5+DPDaEMINIYQbgHsDHxzONQe4FDh8ZDVHAFfFGJdHzwGuJp17Pmr5z6P7sxU4F/jVEML+u9r/sSLoMcaNoz+HEH4f+NMY4w/Geb4k1VpehLlnVGBm7GQ4ngKDtjdun2xWW14ksqsRykmL7DXNwDZyktrtoew89v0C8Crgo8OfzwVODCF8nLQ92knAe3LW9THgzBDCs4APAc8EDgM2Zz04hLCWNL39WuDGXe3oNH3QJUmSJEldlEBS9kW9VV4bjjFeO/pzCGERuGEkQn42cB/SgnPzpH3QM9uixRhvDCE8FXgbaSr9hfx8oD/qhuHU8AXSAnRPiTHu8pU4QJeaoso2XW2XE0Hv5SxvXPywhpkAiRH02cl5b1/4rez2q8/jOROtfi6n/VrbbStoDn9d2WZNUpfEGA9a9nNCGjUfq/d5jPFi4AE5910O059U2/3XRpIkSZKkhhi3ivupyxatBV4eQvjJ6MIY48lF7ZgkSZIkqV4mLdpW1Da7YtwU9/+17OfPkzZzH9XNnDftbDDFx8fU7dXx/Vu1StusdfX316W/tC3T72iRuNsX56reBY2h9W0zVbq2tCBUc4xbxf3Rs94RSZIkSVK9DZL0VvY2u8IicZKUV0Qtr/1aw+QVu6uSReJqJK9IYm73wQ59Sxrxo23t/spklFBd8J7DX5Nzz5Wl7oe0knb/tZEkSZIkFahHUnrnh/oFG2bFmTqSJEmSJNWAEfQ26mrRKWlaNUwBb7tkseo90LTmVkhxTyadJNigP1fHXZrdR74tBonnwZkp4Th/Q3ht5vJXx9Nmv/EG2X/tQtW7IO2SA3RJkiRJ0lgsEjdbDtClpisj+tvVrIy2RNZr+DoSgxi11+tnfxvqapu1tit/PumM5By3bbff2ua87qTCbI091/jHR/XnAF2SJEmSNJakgiJxrbmIOAYH6FJTdDWKXYYaRpjbblDlHPS8PDmPg7F0tc1a23UpfbSNdp+rrndlk1r07TbF+1RlxF/d5ABdkiRJkjSWhPIv6jXoOtCqGZKTJEmSJKkGjKCrWObIqYnyUpvbkvJcw9eRLNRvn8rQy7ksXsczZ14q+9w0RbgMB9Sebdaabfe5Op5F6mdNv7qpANK4HKBLkiRJksZim7XZcoCu+rIo2njyQnJFqmEEVgWo8Pe6uMNjqqny2q+p2dpSIbnXjpcxsTU9I8PjmDeCrgZwgC5JkiRJGott1mbLAbqkzuu1PUOghq9vYcdc1bugXchLzunbZq0RJm0N1aX00bKVkeg2b2bLWOamyDSwzZrK5gBdkiRJkjSWpII56EmHrkE5yXE1XSMAACAASURBVFeSJEmSpBowgq5iNS1HbpCT6pS3vO26+rpz26x5DXNWtt9hivvMzPg0nNd+Tc3WpfmdjZbzZ3qNn8uxTNUmUiqZA3RJkiRJ0lgG5F4rmuk2u8IButR0ZRQAq2GRMU2ghpkAt96+rupd0JSMoLdT0xLgtLO5oj6XU/y5aFIRtTnbrKkBHKBLkiRJksaSJL3SL8w06ULQatUvrCJJkiRJUgcZQZeawjTz2cktElfge+7vbyffvXnvqndBu5DXu7nnodxKgxpGp6bpH15Gz/E6KizFveU6enioYRygS5IkSZLGklB+0bYuXYJygK5idbVNl6SJPOVLf1ndxsuohtXijIn+FG2KuhrVbJIuffltIyPo45mmyGUds0vUbg7QJUmSJEljGSTld37oUqcJB+iSdq3tk05bHO0E2v/6VCrbrDVDlyoe110Zf0L7fi7HYps1NYEDdEmSJEnSWBLKnxbTpUtQzgqTJEmSJKkGjKC3Ub/C6y5Jl65v1USVv++2KKPNmtQweansbZ/xUobH3+WEzOUX3fTmkvfk51pTCKujfxItEjcepwKoCRygS5IkSZLGMqD8i3pdqh7gAL1OjNZJqgOzMjStGn6DSmq4Tw8/YM/M5RfdVPKOjKjh26QJTBwZ7uhpPi8DyOKXqhMH6JIkSZKksXlJY3YcoKtYXWpS2CVtj6i2fVKt2Tn10YJjrdf3PL9ad5n3PVSxWnBqKYXnLzWBA3RJkiRJ0lgGSfkxuS7FAFseFpMkSZIkqRmMoKtYXbq8Vba8NPO2p59XqYycQdPP68Pz1056OaeWIosp9Tp6/O8+N/tjbdIKy0lL2qzlHbdtkdfNtu+M4JlJBu34bKg5HKBLkiRJksYyoPzOD13qNOEAXdVr++Vu1V5Xo3j52ReLpe5G2ZKcSHmlR0GDjkGLUa3eurkufdVUGSZus9ZRvk9qAgfokiRJkqTxJPnTLWa5za4wdClJkiRJUg0YQVexBqbttVKD0m8l1Y9p8TvbzV7M3VJCOMzP2HiKLHLZZQN6DEqeGFb29qpU+gA9hPAS4FjgMODCGOMzRu47FDgbeBDwA+BFMcZ/H973JOCVw+dtBz4DHB9j/FHGNv4FeBSwe4xx2yxfjyRJkiRJRagixf1q4HTgrNGFIYR5YDNwIbAvsAn4SAhh3+FD9hkuuydwP9IqRucuX3kI4dgZ7bfGMUiyb00zGGTf6qjfy75pfG1/D3u97Js0hV4/yb1pPPP9JPNWpGTQy7ypnfokmTdJzVN6BD3G+GGAEMIRwP4jdz0K2AN4U4xxAJwfQng58FTg3THG942uJ4TwNtIo+uiyuwKvBo4BvjSr1yBJkiRJXZRUUCSu9KJ0FarTHPRDgW8NB+dLLhkuz/JI4NJly94M/DVwffG7p7GUES3PbQ0lFcxjTQ2U10ZuYkbEZ2bOebAz09XkIOdWj8f3SU1QpwH6euDmZctuIk1t30kI4SjgNcCTRpY9CngA8EfAgTPbS0mSJEnqqAQoe+Jnly6t1Ck8dCuw97Jl+wC3jC4IITwI+GfgeTHGzw2XrQXeDhy3LAIvSZIkSVIj1GmAfilwWAhhdJ+OYCSNfVjl/dPACTHGfxh53D2AQ4BPhhBuAL42XH5VCOGJs91t7aQtReK6qknF8YrU9iJxUoF6vST3pvHM95LMW5X8nTabf8bGM03N1KX51stvXZb3dX/Wt66oos3amuF21wD9EMI60orsnwW2AScMC8D9Hmm19guHz3sgcDHwqhjjBctW+9/AfUZ+vhfwBeDXgf+Z2YuRJEmSJKkgVcxBPwl43cjPTwPOizEeG0LYQNoH/VTSPuhHxxh/PHzcK4C7AWeEEM5YenKMcX2McRG4amnZ8CIAwP90sg96hRVSksWGRVsbdDku6WUnvPTKKGTmZXhJDZUk9Tt/lVEkrusRvll606+8NnP5id85reQ9+TmzHVanq8UFVU9VtFk7BTgl575vkUa9s+7bCGwccxuXA37UJEmSJKlACeUXbevSJag6zUGXJEmSJKmz6tRmTW3QoJRx6WfansJvP3cVKGe2jSbQNx250Q5YO9l0Pj8zO0sqnA3Z7/vZK0JC+V/5u/Sb85QhSZIkSVINOECXJEmSJKkGTHGXJEmSJI2lil7wXepM4QBdxVpoWJs1aSVtn5suFazKuaVNUkabtcGE7eVak1JZwgvZc83i7DeSI+8zVmVdg7wWb5tCdjs6+P7sdkZqAQfokiRJkqSxDIa3srfZFa25YCpJkiRJUpMZQVehElPcy9czDXvVbEMmjc2WUavn7Jlm262Grbry0swnXk+BB+e995j9VIDn3+OkzOVnXX16YduYdLpIFyRJBW3W6vex20kIYRNw9xjjsatdlwN0SZIkSVJrhRAOAn4I3Day+PwY4wtHHvMS4FXA3sDHgefHGH865fYS4HbSFu7bgc8Dx8UYr9zVc70OLkmSJEnqgv1jjOuHt9HB+eOB1wFPAu4J7AacscptHRljXD9c3/XAO8Z5khH0OmlD3qAp7u1kCrjapMo8OXObBcz1Zv+3Mpm0inuFVcBzrfR5KTu/dsTafv2+69Txr3QZ1e5/cY/JXnneVIBeDact1FkyvJW9TYBzzjnnkE2bNmU95JoY4zWr2MSxwDkxxksAQgivBb4cQnhRjPH25Q8OITwIeDdwCPBvwFV5K44xbg0h/D1w5jg7UsfPsyRJkiRJO9m8efMFwFczbi8YcxXfCyFcHUL4QAjh3iPLDwW+MfLzpcAccPDyFYQQ5oGPABcC+wF/Azw7b4MhhD2BpwNfGGcHHaBLkiRJksYySKq5AWzYsOEY4MiM27t2sds3/P/27jxekqq8//i3l7vPwgwowyKKokcQAijBJfklEDEuUWJcEVAYo4kxRo0/RY1gVFBx/cW4RCMKiigQlwTXaNziFhVFUJGjhk2UnWFm7t5L/f7oO3oZzlPTp6a6urr78+bFSzndXefU2l23nuc5kn5f0n0kHaZOLvqnnXO1ldfXSNq6483e+0TSNklrA8t6uKQZSWd77xve+y9K+s/A+77nnLtzZTmPlNRV9UJC3JGrpJFf2FdihPwTIIrcEXYM3A0TRPQOl5zBVi9hOHReVdzzNFlAKsBMvffrHZsugt7avHnzVZs3b/5h2nuccyfpdzfs13nvH+S9n5V06Urb7c6550vars4T8qskzapTHG61dSvv2dm+kn7tvV99kF8naY+d3ne09/6qlSfuz5f0JefcA0Ih86vxBB0AAAAA0JVElb782y3v/QWrCsE9yFyNzr87FvwTSYfveNE5d6iklqRfBD77G0n7OedW30sfkDKehqRz1CkWd8iuxs8TdAAAAADA0HLOPVSdEPafq/Nk/M2Sfrny35J0nqQLnHMXqDMd25mSLjKedn9HnSnUTnPOvU3SH0t6jKSLjb5rkjZLWpB09a7Gyg06cpUs9r5iZyHa5avQalZSp8J67xCHCtxNrqG0BVy+khJezisF1D9uj2hYrjUhzkePfGWw/cTL3hjdR72AKvzDYKLW++00xk8gdO++kl4vaW91wta/Kenx3vuWJHnvv+ScO1PSF/S7edD/LrQg733DOfdEdZ6Kny7p65LOV2dqttV+sDIfeluSl/QX3vs7djVQbtABAAAAAF1JVhVtK7LP3eG9/5ikj+3iPe9Ul3Ofr0zHdlTK65n/SsrfnQAAAAAAKAGeoAMAAAAAutJW8U/QRymxhBv0QVbC3OP2wiidPhga5JoDKFC1gCmxYqeGGvar4IbxZm7Lit5/Bfxcix2TlaufpzFjmrU860LUIg/cLNNHjmo9B/QPN+gAAAAAgK7smJ+s6D5HRfkewQIAAAAAMIJ4go5cNbf3ewQA7oYQfqBUsoTZYvdM1fKbBrZWQIpCrFynP4zuO9xeN0Lc81TN6blqP7cfsDNu0AEAAAAAXRnEadYGCSHuAAAAAACUAE/Qh1DSx+ru87eP9a3vkZXj/q60jXC0YQ+R7me8aT9nYyDOFhkUUf0Zu485Ve5qIscQ9yKq8JsGaMfWKwM02BSxMyKMgmTln6L7HBV8zQIAAAAAUALcoAMAAAAAUAKEuCNX97z4/H4PAQCAUsur8nQawnLvaizHiuJlzA7qa9i9oYzV7rMYjkD9fLX7UCSu6P76iSfoAAAAAACUAE/QAQAAAABdG6EH2oXjBh0ALP2ssI7eGfY4uX7GYxILWhrtUQ1xNy7beYZbF5GiMAxq1fJtp4oxJmanQJlwgw4AAAAA6Ao56L3F34sAAAAAACgBbtABAAAAACgBQtzRf+T5dsfaTtURzTPME8cgyoqc7qEUPSVWjpeoZESPqTzzocs4pVk/p36z8rprxtR2eU4B2FbvV5wpC+8uSTr/Ft3nqOBXKQAAAAAAJcATdAAAAABAVxIVH+A1Qg/QuUEHgtojGgMIAAPqtfc/w3jlfwsdR+GMNCfCcu+qUsKw9GFXxDZvFbBbR3bKQvQNN+gAAAAAgK601Ydp1ortrq/IQQcAAAAAoAR4go7RRih7d4a9Uvywrx/Kr+hHEbsjQzXsIqrv7jkxONuwiIrbg3RIFcGqKD4srErq/VQbkhB30kVQNG7QAQAAAABdYZq13iLEHQAAAACAEuAJOsqravz9qIjYQGCYEMJ/V/2M/WVf9Mya2gg9XulCbFjusG+9PJ9I8TOkO1UjxD1p57cBGzllLlRSDhDSRe6ureKLtg13kspd8QQdAAAAAIAS4Ak6AAAAAKA7fchBH/own1W4QS9aWpwMoY/IwkoFAIARMj7kVbpjtRX3m6I95JWqKzlWFI+9MUkLnw4uP+W3YlLCw9zatkVUzl/OMVze0kr4nYViccQBAAAAAFACPEEHAAAAAHSFInG9xRN0AAAAAABKgCfog4zcYyAfVv0H6kKgz8qYb1pWEwM0zVq1gGpHsXnSw3KoxeZ7o3eKmI4ur2nW0hReDG0AJEmipOANU3R//cRlDAAAAACAEuAJOgAAAACgK0mSPjFVr/ocFdygDyNC34dTEft1lK5+GF1F/6pAIcZynEZrGDQjp4ZKhnyatWqOx0cZp6TLc/1iWaHstVrv489bBfxuiT2XgN3FEQcAAAAAQAnwBB0AAAAA0JVk5d+i+xwV3KBjtA1DOsAwrAPKZVSPKULfu1JEZeYsxqrDUoc8H7GRv41+hm0XcO5V8gxxV0lPgpKxtnmeUemVnPZF2vHRbI/odyL6hht0AAAAAEBX2ir+b9qj9CdY/iQEAAAAAEAJ8AQdCKgko/R3OoxsSDdKr58TK1SM06Ksl8exKikKq7WsytPG/mu0Cdvu1jBPeJLk+Fg0z7QCy3S99300CHFHwbhBBwAAAAB0hXnQe4s/CQEAAAAAUAI8QcfASQhHLp4V6zqqBm17cM7cFdXaC1dEWHytgHDavBQR+tuMDFmfbXKdWC3tmCXk+a4qRnpJrdb743wm8k4my7m32GJ/76wzzVqx19zBucLvPo44AAAAAABKgCfoAAAAAICutPuQgz5KwW/coAODrkLl3d1WNbah1Y6BZlUpZm/3QY7nWK1S0vLyfdK0qrgb/PbhDqqs5phWsNiq5basYWaFkydJfuf92nrvz/s7lsd63gew2nBfjQEAAAAAGBA8QQcAAAAAdCVJip/2jGnWAAAAAABAoXiCXrRRqnCwu5gaCsCoi5wqq9+KmE7NMlYdnBz0IspbNCKPnbdcc2aPRjJ8tjYG/+ezda5mOTStXPNqAdOsFZGDftJlb+h5H4MmUaJ24dOsjc49FHdAAAAAAACUwOD/CRAAAAAAUAhy0HuLG3T0X3twwhLLKMkzFcDaF0w3hmFipRoVkYIUeS71M2R80NRynEar16yQYPP9Ga7B88ZUYIUcU0N+3D71B2f3ewh3E3tM5dq38TOkiGnWpmtDfrBhJBHiDgAAAABACfAEHQAAAADQlbaKD5QZpVgJbtDLhKrlSNPP42NUj00rbi9P/UzxGNX9WkQoe0595BkKOuxq1cEJcS/CV24eC7Y/tuBxlEWln6fSiF5qrW2eZy7xZK2V38KAkuAGHQAAAADQpURJ4VXbRuePsCP6Nz0AAAAAAMqFJ+iDjOrnu28YqpP3MUy5+eZnBdvrp3244JH0yDAcH9LwrEdeWuFrZ1JE6LvBqqzdavRx31mXlpJ+9YxVSzqwPnn3r84Mtr+5dULBI9kNWc7JMj56ijw006r2V/JK5bDGlOE0srLBqkaF9XY7PMNAFrGzN5A2lI92Uky22M59jooyXsYAAAAAABg53KADAAAAAFAChLhj4FQI7S9ePRyOVr3vXgUPpEdGKW4KSprh/V3Js+BNTpepVrN/f0c3JzHIMKQiJkSoDVCIe6vdvzBbK52ir30UUGyqZoRbDxzjXKpEhnrnye47fJznOdbYEPd2ixD3PLSVqF1w0bai+4vlnLtQ0lXe+9fs7rK4QQcAAAAADDXn3EZJ/0/S8er8uetS7/0jV71+lqTnqXOP/DFJL/TeNzL0cx9J10iaW2lakPQlSc/33t+5q88T4g4AAAAA6E7SCXwp8t+cHqB/UtJWSQdK2lPSy3e84Jx7jqQTJB0l6f6SHizp9N3sby/v/RpJB0naKOmsbj7EE3QAAAAAQOmde+65Dzz77LNDL93ovb/R+pxz7jh1bswf6b1vrTRfuuotmyW93Xt/7cr7z5L0Hkn/aCzvWEnvknSApE9JGrf69t5vdc5dIukp1ntW4wZ9GPVx2q1M+jleM/d4gHLVith+1pQva6d633cR8qprMGjn3oiyctDLaHkpw3RE/TwM+3jprA9QDvp4vbXrN/VIEfUA+smaomxsrH/bPDonP8M+qtfjOikg7b8QsdMrMs1aPvqZg37JJZdcYLzltZJek7KIh0vykj7knHuspF9J+kfv/X+svH6opMtXvf9HkvZ3zq333m9dvaCVUPn/kPS36oTCnyTpA5KuCHW88v4nSvpOyvh+ixt0AAAAAEDpHX/88SddeeWVVwVeMp+er7iXpEdJeq46T8uPk/QJ59wR3vufS1qjTvj7Djtyxdfu1C5Jj5f0C+/9+Sv//SHn3IsDfd7knJOkdZKukvTMXYxREjfoAAAAAIABsHnz5qs2b978w7T3OOdOkvS+lf+8znv/IEnzkq713p+z0v5559y31Llp/7mkWXVupHdYv/K/2wNd7Cvp+p3argu8b5P3ftE5NyXpdZI+r05ueypu0IuWFkobGx477OG0RayftT+qGcJKe62f+9uKiRyWY9BajzynXxukqdyslIYhkSz3LxTaCr+1TrHYsNU8VYzDIMuRbIX45hluPTHezG9hPTY1FjnWAbvU5rZfc7wW1XI8l77zf14Ubr99XbBd7V/k1relWos7M63zOwtrfxeRTjHXjLuV6ed0dMPkt4XbCu6zW977CyTtHAp/hTrV2y0/kXS4pG+v/PcRkm7YObx9xW/UyT1f7QB1wuJD41lwzp0n6aXOub2897eljZ8bdAAAAADAMPuUpLc4506VdL6kP1EnL/1vVl4/T9LLnHOfU2d6tNMlfdBY1mclvcs5d6KkiyU9Q9Jhki4Jvdk5N65OePtNkm7f1UAH7G+yAAAAAIB+SfS7QnFF/bu7D+y991skPUHSiyRtk/R2SU/33v9y5S3nqHOz/QNJ/6vO0/DgtGje+9slPUmdm/gt6oTJfzrw1tucc7OSblHnjwFP8N7vclV4go6BkwxLWHVe+hmOPOSh0NHyqgZflFE9l4rYTTlt2tiw1UJkWTdjm0dXt05RHaDQ1bHYEPcc5bnNB0kRoc2Hr5/veR+DpIgQ97/2V0a9P8/Qfgwe7/23JR1pvJaoc8Pd1dzn3vv/knSI8dq1kjIfbSP66wwAAAAAgHLhCToAAAAAoCvtJFG74CpxRffXT9ygDzLCi1EUKyayXsJq90WwQsOzhIwPUnX3IVGpG9fOPu4L6xRbXBjrfefWeluHcytlUcZrRYRVLzdG9HoUa8hD3BPjeI4NbU4Lz374N94RbL/0j/8u/IEc41XNiukDlOKRJPn9fr1my+dyWxZQFtygAwAAAAC6kqz8U3Sfo4IcdAAAAAAASoAn6Oi/MlaSJuz4rqyYuvECwm+x+0iHKT/jmvPrO9dGL6qS0/62TvtqSiR5ayncXkTq4HIrPLAiKknHajT69/OriHSD3PrI8bs49hjMsg7jNeNDBWzz2BB+a3tkWe/Yz/QzHL9S5fddHjrTrBXf56go4dcWAAAAAACjhxt0AAAAAABKgBB3AAAAAEBX2krULjjovOj++okb9EFmTo0zYPmmgzbesikih9/aRxPjve+7n4pI1iwCNRXuImka2yPP7RR76Bjvt6ZzKkKmXNQ+HmrWlbDdLHQYXVnqZw56CS8H1rGWdgz2urZA2lRgnz76tGB7rbq9V8PJXT+/3qq1/A7CdzzojGD7i356Zm59AEXjBh0AAAAA0JVEiZKC/9rHNGsAAAAAAKBQPEEvWp7hyM0Sxu1hsFnHp9U+7NOsmfNMWe0Z0jXa/YwzHJz0ki3PPDHYvuH8j0YvK2n1/q/wSWS4fOz7c12W9f4Mh2a7ET43iphWqV5rBdvbrfI9i4jetGkfiFy9pFnAeV/ENGvG9cuaZjB6GrK2/YG9JxeD7ePGMZgnKzS9nTLeKBn2nfVVmRibI8/rwT6T+fwWTktpwN11plkr+gn66CjftxYAAAAAACOIG3QAAAAAAEqAEPdBNuyVmY0w4ko/Q4L7yYrPq+V4Glt9GPsiGRuSEPd+HlNFnMexoewFzAyw9KpnhNtvDm+PyXvlF36YLBsv5LkvjNBOM/w8x0Mw6WP2U6sR3k8161KR4zavVcPLaizXcusjL9uWJvrWt7WP+irDeRFbhTy2nlXa+9dNWBcRY1kFfMVEh41nqJxvMs69pIBj7Wk/eGMuyynjbA9lxjRrvcUTdAAAAAAASqBUT9Cdc+dJOlHS6j9NHuK9v37l9TMlPVHSwZLe6r1/xarPPkzSayUdtdL0P5Je7L3/RQFDBwAAAIChl6w8Qy+6z1FRqhv0FW9ffeO9k19KOk3ScwOvbZD0QUlPk7Qg6UxJl6hzM18eaaG00WGoceHIpRU53iTP9bP2R718IZF9ZW2nQTvWLNZ6FBGXWITYavQFqK0PxzyPL4VDR6sz+X1d3fq/08H2/Q7KrYv+ij1sjVjeLFPcWmG2dlh1fiGL9XrvK2jnZbaRY3pQ7IwBZaxWXUCqT7UW18fykn3NmRiLi4e2qplnYpzfrWbk9TzHy7+VHWdWdy/hV2vaefHVR/zfYPux335br4aDEVfGG3ST9/5DkuSce3rgtc+v/m/n3Nskneac29N7f3tBQwQAAACAoZX0IQc9IQe9r/7KOXeHc+5y59yzd2M5fyzpJm7OAQAAAACDoGxP0P9Z0kslbZH0fyR93Dm31Xv/iZiFOOfuI+mdkl6Y+wh3V1oY17BXZTckVgyUodIanDDGQhQRpjzsqQBWuogZGj4k6SUWK14xzy7WhatYF/GldI/7z4dfqK/NrQ+zWrv1/lZ+1/92I+79STPcd8U4vdPCdednx4PtE5NGSHCO33t3zk0F29dPL+bWR16O+85b+9Z3dCj0gLHOvaSd33XtzvnJYPuGNQv5dJAhBLxWzyluPMfwczPlpdm/3w7Wdkqrgn/dXHh/A71Sqht07/0PV/3n15xz75b0VEld36A75/aX9GVJb/LeX5zzEAEAAABgZLVV/LRnJSxd0DNl/zNqW1LXf/J0zu0n6auS3u+9/389GxUAAAAAADkr1RN059xTJX1B0pykR0h6gaS/W/X6mKTajn+dc5OSmt77pnNuX0lfk/QR7/3ZRY8dAAAAAIZde+WfovscFaW6QVfnZvz96tyAXy/pDO/9hatef7+kU1b990vVmfv8NepMvXaQpJc551626j2/nUd96DTipvkYOFbe83JkgmWmvgeoHkDs9Hx5Ggvnmw4ca39XI6eXi6ynUBhrTps+5sxX1kbm9C3nV3ti8dbweo/fN78v/yQ8W5x5rJnvz9J37FeDNSZjk6ctv9EI/6wwc9BzPAS3LYWvR3N5TmnWJ1adAEmqjMd9Bywv9T7/N/YYtNYvrZZDxQiwrBjfic1G3MHWSMmTHjem9KtZ3xl5sqYui50+zxhqkuGczDIlY79YtQiSlIDdtWPUPkKxSnWD7r3/o128fqqkU43XXqvOzToAAAAAAAOnVDfoAAAAAIDyStRWUik25DwhxB0908zx4LJCwMsaZpuXRgEh7v0MG+8nK07NDAEfkmOtWUD42iAdU0Xs1wkj7HhuKdye4/ZrFBDia4Zum1NAFdC3werbmmYtdVnWpaLW+xjYlhHiu+dE+aZZy1XksbO83PuffnmFPFvh6ukfCjfHHoNLKdtpoh6O4U+bqisvg/QTr90y0hD6+HXYNkLc06apO3Tjll4NBwjiBh0AAAAA0JWk8wy98D5HxQD9HQ4AAAAAgOHFE/SCpVckjTRIlcbzNDff7xGUS57hyFbahBUDWy8gVLgIVhil0Z4YMYaVLPuin6HvVpxhESHu4+Gvn8qE8bVUy29MVtiltS+uffxfBtvv85kP5DUks2J6JrHh8jl+l1iHVG3Min3P7/ifrIU34sTYEMx4kuMpObfc+9k3olM28kzxMDOyIkPcm/ZP5Htu2B5sbzbz2VFpvxUtses3qo/orFkMZibsi3B0hfwR0FbSh2nWRue+Z0RPTwAAAAAAyoUbdAAAAAAASoAQ96I1coxjtMKRh4W1flffVOw4ysIIO7bCrTNZNirkz4cra+fadz9ZId15Vne3+hiWSvixxoyvn8h0gyw2feLDwfbWseFQ9o2b5qL7ME8Nq4p7jlHYVaNAfvRyjEjo9rL9mcnJ8DWkOha+nleq+aXJrJkID2x6OmXAI2h2Oe4AOdudYb72Cn9msD16t2a4DFrnmBWNXK3F/Wa6bnbGfG3/UM2UcQAAIABJREFUfcJVvZOFnE6+lKFasytY1cnN5VjbL8efllYfldhw/BSXHfOCYPuRX3tXsL3RCH/3VGvGDCKSJicKmD1owCQrQe5F9zkqRvSXIQAAAAAA5cITdAAAAABAV5JKonal4CfoldEpEscNetGaOR7Mw1JB22KEuFc3/0t+fVixXKMadrywGG6/5c5w+7BsJyt8uhlbFbekVdxjrztFjMm6flnVi/s4a0VeIeOSpCS8Hs3F/M6lSo+/2dOWPzYeTgsxt2GOx5pVaTk2tLmMKjlup3ZkRepj9t5mv+iN9hJ+NcRmZN20aJ/4Zui2cQORZ9i4FeVrzk5hsGZcaGdJtzHC663tkWHeItP0eFz4+c1G6sKe+86an5kYH4KZIDBQuEEHAAAAAHSlvfJP0X2OihL+jRMAAAAAgNHDDToAAAAAACVAiHvBkmV72qbojJwhyUGvGMlZueZsWYxptIZm+rBYt4VzzaunvCfY3rzzuF6OpjhWfvPW+XB7llxzK+FvLM8EZ4N1nBvrUUAGujQe/vqxrpF55uCajOPAyp/+2iNeYi6qUr8x2J4YdQ0aeeagG9Ojmcyp7Yzmur0vxqfjctArKcuKNTMZnk6tPj4EYZEph4d1TFn2XhM3beBkLT7/NvortIBdVK3FbafnXvF687WnPfgZwfZWy1jxHNevbaRcN5txG90oh2G2p2k1rPoP4YXZuenxpo3z3vKw/35HsH3bQeF9KkmTM+GNfuGDXxlsP+GHb4wa0yBK+hDizjRrAAAAAACgUDxBBwAAAAB0JVFS+BPtREyzhl4pIkyzkNjwIWFM5TZQ04flONbq8W/uW999tRgOkWtevTXYbq512vltbatCplmzU2uCitivsTGwBWynxAhxbxqZDve/5x32soywY6t9+7ap9MH1UuwUdhl2RTU27D6Des1Kj+h9330VeXqvXbMU9f6ZyGmsJEXHZ1rnXtq6VcYjpxWr5/fj3prSbHk5/LO6HbmP0rSWwn0vLsWlS5k/FY0p07Isqzbd+xuqajWfPtJ+Oluh+qMQyo7+4AYdAAAAANCVtlpqx/51MIc+R8Ww/10ZAAAAAICBwBP0glXqOf5NJDYsccBY1d1z7WMuHLua7LVXz/seCvXhuIQsfP2mYPvMuy8Mtjf//knxnVhh40Vsw4W4KreFhLjHzkJRRCqAYfttk8H2tGrHiVH4OlkOX9fmlnOMAc/p0mlWzk/76jHCTStj4WUVkZFlVZgeFu3FuN8CtXrcRq9VM+ykyI8kjfA6tBftz1SsrBBjc7Qb+V3XrBD3pUb4er60PfI6n7JLm8vh9ahH7lerGnyWc7KxFF6/8XXh7548007GJ+JnGQhZ2G6nCMxsDK/HNY97TrD9wM+dk8uYMLqG49c1AAAAAKDnKBLXW4S4AwAAAABQAjxBL9pUSpVNq6J4Tu+ff+EJ5mvT/xwO5S1E7HrnacGInxuW6uS9VhmO0FErlD1aluMmNtQ7i2bkbAVFnJNG32Ya0Hj/vq72+/fzgu0/OObvzM9sbBrXFqPGzWFffk/kqGztyIwGq7K8vXz7/UkzfE2o1Ht/rbCqWG+d62OF/AJYocqW+kTvz28rxcNkDKm1YH/EuiJYFeFbOYa4WybGwit+553TUctJOycbS739zsgSfr59diLYPrOncTHKqfK6lN/PEKsCvyStqYbXY2oq8mI7RJJKW+1KwU/QC+6vn7gLAQAAAACgBHiCDgAAAADoSlvtPkyzNjpP0LlBL1hlMsdNvrAU9faJQ9bm1/ewMKq491P74heH280P9PGClSGku/X+vw621577vt0dTblZFbFrvQ9xT1pxx0hSRIqHsT2SRvgLvzKdY5XznDzka+80X5t14ZSiqhF+e8nvvzzYfvz33xQ9rmbsZc34jWWFCje324vKszpzLKuK9UFf+JeCR9IDKadwcy4uxrcdGX4+NRUZQy+pFffzxKwc3ly0D6gJayYba1nL+V1r6+PhTqyQ59m5cAi4Ja2S+vbZ8KwSt83HpXJY6SiNxfjtdNAX3h8e0wknB9vHJvO7sZufy+e7YX7RXs7GaviiWh8bnRtGFIsQdwAAAAAASoAn6AAAAACAriRq92GatdGJWOAJOgAAAAAAJcAT9IDP/tGfa3m/B9+l7T6f+UA+C89zSiUr/8pIAqyMFTCdUxZNIxepiDzY5di5YApwwKZwez9zzS0Z9lHl8Pv2YCADrJDjvI/nmMXq2xprAVP6mVO8ZWDlzo5tDF+3H7LfzeEFfT++75/6vaPe35oPj8nKJ7/p+nXmsjbuORdsnzCm+qtY32MZTE7E50oPCqsegCQlSdy50WzE/RaoZpgSK8lpt1ZraQuKW+9GAdOsWTnJGzbGFYZop+Tw3/8//zVqWZbtW8J58Qspudix9rrwI8H2O046Mbc+7pjt3zSKRUxZWFZJ0lY7KbZIXJJWnGHI8AQdAAAAAIAS4AYdAAAAAIASIMQ9YNOjJ6Ut03dt/ExOC08L54sNN711W7jdCgHZf8+45fdbs4Dw81vuDLcvh6dKKcT6uOnwKq3wdmq997nmZ2rPC0+JUoh14fVrf/wlwfbqU97ey9EUp25cbgtIXUjmw6G/vQ8aj1eZGgu/0M9w/AwWZ8P7e3o8fL6uu8dibn0//BvviHp/ayHcXjcuRWkhtjf8+anB9jVJOGY3Wc7v+Lemnyqjax//l8F2M50uJZJ0YbtxzhiWFuN++l16vZF2laOKMaT6TMpvprYxVaPx06GWGi4fx9rmYxPhHTWxPtx+05OfFWyfuzW/sVou8PcKtr/8qjOjl3XZMS8Ith/5tXcF2xtL+d1+/HpuJpflPPBL7zVf23avZwTb69OjE3K9M4rE9dZg/eIBAAAAAGBI8QQdAAAAANCVzhP0govEjdATdG7QQ2YmpeZdq0Je87jnBN964OfOiVt2WtXwalzAafUvw+E4rauPilpO3xkh2kWonvKeYHvrxj8oeCS/k0wZYZpWWVwjbaKQqv0ZwrMTI9S7su9euzuawlhpBanbw6pCXkTo9ngJZ3CoGWNaPx1uz7HC+tIrwuGKVh83PyUchrr3xz9s9jE+GT5GkqXw+VrPJ0ozk6pRtLk6EZ8Esf9/nBdsXzjwhGB7nlXc86puncUvHxNOKbppdk2wfd16o2q/Ia2K+z6f/FDUsm7YYlfhD/mz77056v2S1I6smF6phY+1SiWler2xTVpGBfSx8fxuJjZ9Inzubz01fG2xZkSwvhZ+dcseZt+/On5zsL3ZDF9Trd+pWULZLZs2bo96f9q1M9aNi3EpHpY3PfAM87Wk/ctg+9j68A68+CGvDLbv4faJHxhGEjfoAAAAAICuJGqrTQ76XTjnLpR0lff+Nbu7LG7QAQAAAABDyzn3D5L+YVVTVdKUpId473+48p6zJD1PnXvkj0l6ofc+XGk3va/7SLpG0txK04KkL0l6vvfeqFD9O9ygd+lefxLeNwsPCIftTf3ThcH2ZMHex5VmPuFXlSUjvmsp+viK1v73lwbbq098q/0ha72LqOJuafSxivuEEeJubQ9jrO2t+VWFNrVyzD+qlzAM25LTuSrJjHHc8swTg+0bzv9odBfVPcNh472vE5yBFcqeYyh0bS8jpttw4+1xMytI0sy94sZbncmvpn5sSH7buNxVJvNLK2gbXz/1yfzW+1t/+OJg+x98859yWf5tJ5xsvja1ZzjE955L4fZq5OWuNWe/ZlXOt9INNq1NWVhOrFkMTFlOb+NhWm0q3L7w63Ao9FWPel6wPa2qt6U2ZaScGft7eTn8wt7r7ZDxRiO8bTfcYz59cD0Umz5ghenf65Jzo/v+i0OvDbY/54q45Tz78GvM15YXwvtp0sjBrhmpGVY7iuG9f4OkN+z4b+fc30h6yaqb8+dIOkHSUercWH9G0umS/nE3ut3Le7/onFsv6SJJZ0kKT3uwCjfoAAAAAICuJEr6MM1a5w8c55577gPPPvvs0Ftu9N7fGLHIZ0ta/VehzZLe7r2/Vvrt0/T3yLhBd84dK+ldkg6Q9ClJ5l//vfdbnXOXSHpKNwNjmjUAAAAAQOldcsklF0j6QeDfv+52Gc65QyU9WNLq0LJDJV2+6r9/JGn/laffO39+o6T/kHS2pA2Svizp+JT+Nkp6oqTvdDM+nqCHNFt3D2G1witj/8SRVqm9kVMIuhUKnaHidrS97MqjlsqyEV+5UECItqEy179QMfMYsbaTEW5df8l5+YwnTZY0BOs4tKp6l5GVAmGV6k2RGFXc1/2BUdb7/OgupHHjUl/ENSGWNda0GTAiVdYbaSSGe++/Jdh+7eP/MqUT4xpifZXkGE6+Zu/w8Xn7iScF2yt1K80oPhzzR8f+bbB9eVt4G9am8jsG77f3HcH2vMJpqzV7rFYIc20i3D5/W9zPr+Vt9vGxYf+478paynrEOu/wVwXbG43fRC2nvRg+1hbusL8Xpqrh49aalWD9XuHt9OtfxlW1l+xzSUbIc2sh/O7JqfDvvmrNPvf2/+h5wXYrBePGJ50SbJ+dCx+cWWZDsM6NW58eHlOS5Hc9X5zPp4r7NTduNF/btH422D4zG77OP/nS4NNdHdk6Uj/U8+MHV0JJ0lKSFDzN2kp/xx9//ElXXnnlVYG3xD49/6L3/oZVbWskbV313ztyxdfu1C5Jj5f0C+/9jl9lH3LOhfKsbnLOSdI6SVdJemY3g+MGHQAAAABQeps3b75q8+bNP0x7j3PuJEnvW/nP67z3D1r12pikkyXt/BflWXVupHfY8eQ8VBRiX0nX79R2XeB9m1Zy0KckvU7S59V5cp+KG3QAAAAAQFfaKxOtFd1nt7z3F0i6wHj58ZJqki7Zqf0nkg6X9O2V/z5C0g3e+52fnkvSb9TJPV/tAHXC4kPjWXDOnSfppc65vbz3t6WNnxt0AAAAAMAo2CzpAu/9ztNenSfpZc65z6lTxf10SR80lvFZSe9yzp0o6WJJz5B0mO5+0y9Jcs6NqxPefpOk23c1QG7QQ1rtu+X1Jq24XLzPP/Rl4Rfa4Tw8SdJi3NRe258bnuLNnAKqgGnWNJ4hF2jJWO+8cvKz2B7ON7K0v3RGsL36qDPzGI0kqdIK52yZOfxFyNB3pY95z1Yu3j6f/FDcgpatOaNS8uiTuGtIZb0xV1AWVg2NMuagjxnXkDxz0CfDX33WNJhT+4S3U20spVaFsckTY1+0F8N9WNPt3XyTnTebNMNTrM7sH/5uWL4tXPfCGmua+x0U/t2xPBc+N9o5lhpJkvB63LbNqOcQqZrhF5M15Ves+qR9rtYiV2/dxriNfv4R/2C+9qcH/SrYbl3urCnhWkbNmeVFe6NPLIWPZ2tKv1YjfHw87L/fYfZhsXLErdTqttH3dTdtCLbfd3/79/vVj31OsL1hfC9ZU6Dd/5PxueYW69yrj4eP2ztvD0/9mcUvbrFzx2Mc/d//bL5mTV1pHWsoL+fc3pIeK+n3Ay+fI+ne6hScG1NnHvSzQsvx3t/unHuSpH9WJ5T+U5I+HXjrbSs56E11CtA9wXu/yy9XbtABAAAAAF1qKTGKIvayz93lvb9ZnZvv0GuJOk/NT+9yWf8l6RDjtWslpVQGT8c0awAAAAAAlABP0EPml6Ttdw23at4cjmNpzoUXccdyhlDvlhF+eEY4xDGxpsCxwlYn4sd0/ROeHWw/4NNWSkYG1lRdxvRThYhMN9DafEIoJdnrbYVV9zEVoJJkCJG2xmsc/3na++nGNICfjFtOxThm4wOCU4zleHk2wsP7mW5gHufWNGsLOV4PjL4rNaN9LPxH8NqUvcdjT432QnhZY9Ph9r03bbMXZmyqSi28Hu2W9Uf++CPammlw+7bw1HYTa40v0Qyq1fB495iOC+n+oDF1WKtxrfkZc4ZFo33MCFm3pqlLTVk0jrVPHvVy4wPhsHTLMQfYMxeNT4WvLY2lcErD2rU7p3yuMLZTrZ5yIkVeElqNuA986w9DMyZ1bN0SKuosrVkTXj9zGrLF8Hlxn5Y91vUbwnO2bd0SzqeYMKZy+/Ejw9N9Hfbl95h9W5rL4f09NhE+Pg783DnRfXz26NOC7futDaf05Mlaj8b86D7nTJQoyfIbcDf7HBWje2QBAAAAAFAiPEEHAAAAAHSlvfJP0X2OCm7QA9qzy9LWu4bEXX/l+uB799orXO37oXvfGl54PSVowaiYW79vuO/2LUal8chq0WmiQ9ljQ8MlqWGEuOcZ4htrLhxCZspzrFbYsdVuhb6naP3rXwXba38VWdU1S4i0NctAESkNa3MqqWyF6ee5DmnXikjJcnibV3K8VuSmZlTCz3F7qGqEdBvtlXp8iHvFWJZVGT0xLp1VIzPJqiItyQx5jpYh66RiXArNMPocd6sVDr1uj/D1/JrHhath1+u/CbanbXOrendlPNzeNt6/94bw97pVBVyS2svhcT3p0jcF229/wEnmskKs1IE0YxPhg6c6Fl6WlSJQqcT3be2LWBum7NSIxaXwiVmvhdd7ek34BD9wXThUfimlev3UTHhZb7piU7D9dQ+/PthuVV7PYm4ufKCvS0tRCHjLweEZcSTpgLXhNI/pqd7PZGMdn4tzGdJZgS4Q4g4AAAAAQAnwBB0AAAAA0JUkaSlJip1mrej++okb9ID2HctKbrlrJU73xfOC7735Kc8Kts9MWyE3EykdG6FcM+HPbPlhODRqz2ONkKI5o3pqnm7ZEv+Zuflw+/q1webWe58bbK9MhUONqqfEVySNVs8zxN04DlpG3F6G6ueVjWuiP5ObAqq1m8ZyCkcz9lElbd2sdAAzpNtoz2LJOHb6WcXdUkSqQ04h7la7ZIeyW+Hn7cjTwq68LlWtMPqG0d6OC8e3QsM7nwmHaI+NGWkWeWYuGJWyq8bleXIyLj2oZoRnS/b+qxr721rvyZnwmNLCkdtLcWHg1v42lx/5fil+v1rFoLOkFViZO5XIUP1my74GrzNmBrA+s2yErNeMA2TrXLi6uySNjYcPtvf9+qxg+xmNU4Ptv56bNvuIdctceCabteviZlC4nxG+L0kLjfA2tLZHnqzrbaOR4/c0sAo36AAAAACALiVKCi/aVsK6OT1CDjoAAAAAACXAE/SAh577n7rsssu6eq8VSlU3wvlUSQkVs6pbj4d30z0u+kiwvf33Z4fbbzWqvktqvumZwfb6y883PxNSfcrbo94vSdo6F25fGw6ZqhywZ/j9VkhpFrHhxcb7m289xf7ISz8UfsEKO7aOD6s9zUw4fK759lOD7fWXnBdeTpZtHhvqnScrtDlW04itzDMsPcftkcyHw2Yr5owBBfyV2urbCnHPMxbaug5bx4dVQb6S4elB5OpZob9ZtHMqdjyzJiVdyhhvPbKacxZWKHtqxfsAs3J4Soi0FW5tbXNrf1fHwtupuWAf/62luOualQpg2TZvh1uvWR8+Fqwq9dWakS5ibNu0cHyrsn2lns/1K+0yODkRvqZaIc8LC+Eq5612eL9edttGs+8/NsLrT7/fq4Pt7fYNwfbHfvctZh+xllvh9WhGhoDvPWlfW7Y3jDTGDLMMxGo1w+uXZZYBoBvcoAMAAAAAupIkbSV5/gW5yz5HBSHuAAAAAACUAE/QAQAAAABdSdRWooKnWSu8KF3/cIO+m2pGXt3YZIaDyEp4is1rNfJj6y8+1+764heHF/Xm8DRy9dM+HDemFO3r7wi2V/e/Z/gDU0Y+XJZcbEtOucrVAzbEf8jMC45sTzMZzoerbpiKX1Ys6zgfpNlKrOITafvCyK0288DzypeXlCxF1i8oYvq1Mk7xlidr9SLj1qxc5bSUfOvwjJ5C1ioXkSGfPPYzHzz8VcH2Z1/++ui+LU0jr9TKaW037I1u5aJa+dBWpKZVHqFt5PhKUmLtcENsOYd3X7WX+dpZe28Ntls5u1XrODC2eTNlm1urPT4VPtBjp5erpeQ2p5UTCrnTyOOfGAv/XjvpsjeYy7p6U3iaw7P+93XB9r909rSIeZkx1mNxMW5q07Xj9tSH120J/z6JnT4vi9hjB9hd3KADAAAAALpCDnpvkYMOAAAAAEAJ8AR9N03MhEOpKpHTukiSWlYYamRojbWcNFbI895r4pcVyQq9b/9PeLo4M/Q3x5Dg3Kyxp6cxtcKhYhVrv2aZEsuawmsyLhwtU5hy7PRaecpr+rDYqfAk+2pbwHq358PjrVnrERkyiwiRp4wVSptleh9rKrDYKd7S+s7rAccf7XNL+IXL7c+YfRuXu2Yz/ELNmIasuWSfqzVjerRKIy7E3WKFjEvxp2u7Ffdd+Z4bzjRfOzM5KdhuTa9lpTpUjAN9fj7820Syp8+rjy8E29sFhCknSbiPq2fDv6UeuEc4RSDNcjPup3urgPWuGVNOzi/H/aao1+zv0BMve2Ow/Y5DTozqIwvrHLOmyQN2FzfoAAAAAICuJEnShxD30Xl4wJ9+AAAAAAAoAZ6gd+max4WrYFYnZoPtsVVSJdnhtw0jLtGSpZp53RjwTIYQ7WFghB3Pv+CEuOWMRYaMS/ZxsGxUN83yF0wrHaA25H+zy6vSv7UcK3VAkqxQuAKqmSdGmK2ZDmMcg7edcHKwfa8LP5JhUJF/Cc/zL/VmFf7YMaW8FHnZtlSMb+ks3zHRIevW+1P6tl6zKqNb1swsBdv/6+EvNT+TtH9jtIff3zQqo1shwbVF+yfTZNW4Phth8VYotHVoNlKqmTdbcVNgxIa4p7FC763q3WPjRoV1Y8W3Lti/QW6Ynw62P3xN+DhISxMIvj8lNNzaT9bMAE++NJyyd9kxL4gakyQtGqkZ/WQdz9uXwykKnz36NGM523MbU56s9cvzXBo0idpqFzzt2ShNszbkv8YBAAAAABgMPEEHAAAAAHQlUR+mWRuhJ+jcoHdpz01zwfZqnpFGVnjlohE6Z8kSxmuF5k7bFVR7Ljb0N68K3SkmHhAOqTNlqCxfWV4Ov9DMKWY2TWxF8QLCs3OVZYaDEGu9syzfOkZyPJ7N71DrWmG0r7t/jvvb6ruIY6pp9FHENo9dPeuUTAkZt76X2pGHpxkSn3aZsELcjcroVh91oyr6vdbaIbDRYeNG2okVMl5L2eYTk+Hrc9MIgbWq88sIq04LY19cikulig31TtNYDo9rqRH+eTllhOpb++7yLevNvk+9/PXB9psPeFaw3Qq7tyy27J/ILSM9ohGZbrDUjv8RuRzZh7Vt8zRvVJbf3ghv840T4RSWdoaxWutnhdH/2ffeHN1HyziPqeKOXuHIAgAAAACgBHiCDgAAAADoSpK0lSQ5RSVG9DkquEHv0tgecaGPeVXwlaRkezgUyJRXGK+UXpW61yLDb3MNjTWWVVk7EbeceobtZ+2/2Gr+RchysexnWPxyTtvQrH6edkm1jmcjkCnP89jSMNJnjFDv6voMsxJYYlM28kxhsY6DyD6SlPdbv1us7warWrslLb3KXJY1JiusNMdtXo1ev/B1YmYq8vtQUtvY5lZ46p1L4dSuNUZYbhornLxWjwv5t6qDS9KCEU5ujskIz86iYVQUt8Y0vRxuXzLarTD21DEZYfTbF+O+v5dTtpOVNtGKDNGei9x3Wfoowp1GtfatjfDxscdEOJWvVrV/H7zivmcE25P2NcH2fafnzWXFahvXCitNBthd3KADAAAAALqSqF140bZRKhLHn34AAAAAACgBnqADAAAAALqTJMXnhFu5JUOIG/QuVaeM6VsaxsGS5Zg1cnNbty7GLceaQihN7PRaRbBycK380QxTmpms3MtJIwfXyqtOnY/IsGzkBVvtWeSVW5oln7yA6fBMSzltQ6sOQi0lr9o6x6z2PKf8soZl1nMI912ZzPErw1o/Mwk3v5z8xLpGWl/+GfaFtRrtRvg6VatH9pFyaTGn8IpkbY4sv8kqlbjvSuvSOWZMvyZJbWMqpNjpUG8zctAPHIs/Bu2p3/Jpl6TFyGm38mTlxlu5uctGTvKWhcncxmTlC99q9PGyA8O5zY22ncOcZT+FPPI7b4t6vyQt9XF/W757R3jbPnRj+PfrrDH92h4pdR7OvvrMYPtLjnpmsH1irPd1e4qYwg6jqYR3ZQAAAAAAjB6eoAMAAAAAutKZZq3gInFMs4adVafDIUXt2XDIWyIjRDQtDNsIdb3++zPpg9tZXlNJ9ZsV0rpghEBZ4ed5mrBC3I3wzSxh99bUV1Z7lqnczPjbyItflrDjyL6XXvGMYPvE2R+L73s+PLVLNDPNIiUoyZqy0PpMjiHdbSuyP/ZaMZ5jaKU5VZ11fOSYGrEUmSZj9Z12uhivtYwQ9+pEZB9pfee0m6xTNfU3UmTIurUs6/3W9GuS1DamxapU4q5rtyyFr/PVasq0epGHZ9I2QqSt4yZlOqdWEhcMmWcapzUuK8S9aYRn37oYDpF+72Gnm30/78dnhcdkHAdWOPmFD35lsD2R/f1thTabqRw5ut2Y0sySduzk5XW/fF2w/Vt/+OJg+yt+HL7+v/f3438zWedSESHCRWxbjCZu0AEAAAAAXUmU9GGatdEpEseffgAAAAAAKAGeoAd8/QmPUfv3Dr5LW2XMCJ2rG389SgmFi3XQF94f94FGhhD3yNDO2b8+Idi+5n0XBttvP/Eks+s9P3pB+AUrpHv7Qrh9vIDD2Qonz1LN3GJWcc8QVm0xK2hHHrfGejdef7L9GSt02+i7tjG/1IXECm2OZYVnZwlLbxrnXhEh7tZ6WPIqDy7Fz0qQZxX3ZWNZxnUwS6h39GeyhJPHigyrNseUUrk4er0jL19ph6BVUdwKi68a4ci3Lhkhsynf63Z4ffgzsRXy0w6DJaNvi7X//umQcDXzF18Zrp4tSS2rmrkRHm69/8++9+Zg+2ePPs3s2xL7NTZTD18P0rJqrDD6Iqp6/3hrOMT90A3h31nWNi/CRC28bb+x9Z3B9uXmC6L7aBvXtTzTDdrGNuznpDT9Rg56b/EEHQCUwNX1AAAYr0lEQVQAAACAEuAGHQAAAACAEiDEPWByk3S3OgR1q6SssRAzzM+Oh0mt8B6jgCrukwdPRb1/zb0zhKUY69G+aXuwvbp+Or4Pi7UvxoxTJjZUOI2VomC1T8ZVdJVkh+Q34/ZTxVhO7T4b7A9ZocpGe2U6xxD3+ciwaot1jlmV2qX4NIhWfqFczQXjQmWmTRghg3ldo6SUKu7GNTLH7aGG0bcVP22MKUm51JohzFZIcGSYeTvlklMxLlNm+HQrckwpYtc7ssB6pr6t8POaEQJbMw6DPENmY0OkU9MKUqqNxyzrgOn4WS5iq7jHVr2eNEKks4zJMlGNPwjzrIQf6zW/CFdMt1IUWu07ejmcVNY5ZtkaWaFeskPc82RdI2NnUBgmhLj31ugeWQAAAAAAlAhP0AEAAAAAXUqUXr6yV32OBm7QA6rTNWntTpsmz9DOHstUqdqsBG5Uv107EWzf/txwdffqdIZgDSPcuv7y84Pt7Y+/JL6PWEVUcV80wgxzrGJthhHHpkdYcX4z4eNDUkoFdKPv8ZSw8UhJI6f9ZO2LtBkUrGuIde7luL9bRnVrc7xpofp5sdIprHMpx9Sd9mK4j0rdCC9uWrHTdh+JVZ3fer8Znm18ICWs00qlssPrjXYz9D2lb2O9zeruxqKyRDK2jdBmKyyyZoQ233vaSLdJ2aVWmK1V+d2u4h7/W2O2GXe+WuH1e08uRfdtHVMNYz1akeuXJcTdqrhtscKw01IHGq3wNo/tO08bxsPbyko3KKNbl8oZ4h6bNgHsLo44AAAAAABKgCfoAAAAAICuJOpDkbjCQ+r7hyfoAAAAAACUAE/QAyoTNWmyy01j5JWaf1RKm5sjrzz3yKmyMpkMT301fVh4qrNkMUP+aPS0VDnmaEfm5Jv5winT6pmsvGCzj0zJmkZ75Hit5Uyk5JEtGTn2xv6r1HL8O2Je54Y15VeWvHHrvM/xPF5aNK5ni8a0c1P55fTd+KRTwi9YOeXGMZUs53d+J8vW8W+st3XqpQwpbVqs4PutnPVa+Jy0pv2RpKqVg26m/ec5zVrksgood2CNycpBX1vP8bvEYE+nFr8sK9/bsmzkrFczTCNn5ZQvGjnasfnQrQw53c3IPsaM48Bahyx9FGG6Fl6PQcpB/8GW+GlVY6+1WVi1BWJrKgyXpA9PtEenSNzgnLUAAAAAAAwxnqADAAAAALqSJH3IQS+4v37iBj1krHb3qZ1iw02tt2cJeY6UKRQ0dlqlejj4omJMv5ZpTFYYsSXP0H4rdDt2mrUsFxNrmrU8GeHk0VP0Weudlq5hnQN5TiMX6bYTTg6273XhR8IfsMaaFo5vxa5aaTI5Hs9mOK1xXlbGjTDzDNevNXsaUzeZ0+0Z6x17PUiRNIwQcKPdup63jQwBSWobp1LFCCO2QtZjw9V39Vr4/Va4dXz4phlGb0ztVa3nt1+t6cPGxuKmTZuph3dexZgyTZLaxlSG1jRrFmubW8eNJD31B2dH9bFshG6vGU85oA1tYyqyrY1wH3tOxAVupn2VXPyQVwbbl5vbo/qwQtyX2/bvosVm+Oeztaw8/fvvvzzcdyXcdxHh+K+636uD7a1kS9RyDpiO/47p59R2NeP8Pu/wVwXbNz5gn14OB0OEEHcAAAAAAEqAJ+gAAAAAgC61ZVZQ7Wmfo4Eb9JBKpfuK6lb4oRWlkxa2asXbRaoY4eep7PK+4faJuEqble1GmGufLb3iGeEXrCruFaM9zwryS0aYoRlenyFtIq9UC2s5ZhV82eHhVlXvPBnnxtoDI/u2zuNqynFgnUvWeZ9jSPeW2fDsCvsuLYY/YM1ikaHEdH2t8YK1DY3jwJoJ4pzfC4cSStJzrnh9sL1trLb53W8czmblddmhylWjKnurEe6kNhF/HFiXKesyH7tb00K9Y8WG42fp2wozrxlVr6eNEPc01jaMHa+VbpBnuONcI/z9vW4i/D390SPDoeSSlCSzwfYf3Rn+vtq72xlyVmxZtn9rjBvh5FuXU2YRCS3HOA5uXLBD3KeMtMAxIz0oTxPGek8a69EsoNL4pslw30splfBD7jsT/1vRPGcyzEoQq2pUFT9o7XywfWbG+vIB7oobdAAAAABAVygS11vkoAMAAAAAUAI8QQ+o1Cp3q8acWHkWkcW70yozxwYhbXnmieE+5sJVwJdeZYRzS3YVdytW0gphNpaTpfpztAxVwKvrjVPACkceM96/lGOIu3WMRKYVpPdhVHGfjawgb22nNFYsaMMIbTZCvRdfekKwffKtF5pdV8aMMOI94i6F1nlcSQtxN8PijXMpxyrua4zQVStsvLLWqmaeIbx4wriyWaHs1nobMww87airzb6fc0W43aq+3l4yQiUnwuvdWLTDN63DvDYWfqFphLiPFxCealb5N7MyMlRatsJQrdPCOiWzTFJiVIqvLIfXY7JmVX0vYBaWuIkEMvnN/GSwfdO6cLj6dEql/bqxA9927ZnB9rHqGbsY3V357eGZYSTp0HXhcOErt4VTeizjxv5+0qVvMj/ztUe8JNhexDGyaWoh2N4yzmMr5N+qgv+0H7wxekz3mg5fVBcjQ9z3NtYtTcu4ttSNkP8srGvk1Fj4e2neqPJfMULiB1NbxeeE8wQdAAAAAAAUiBt0AAAAAABKgBD3kFrVrPa8Myt0O7GKwKaFrUaW0l17mBFCsy4cEjZ7ebiqpCRtsEJXG0YsaGwV9+kM4dndVtLfDbVNa8IvWBXT68YpY4RnZ1oH6zPW8ZEhtN8KVa7sEQ59NKvdW9LW26rWblUzN8Kwa+vjQuck+zhMlsPb8JNHvTy8oNYdxnJSOjdC9SvWtsoxLWR6OjywZME4dqzrVJYxmRXQjT4a4TG1Z8PtVvi5JN1+4knGK+FlzW8NHx9Ta8PXwfk5u1r09Ex4m1shsI2GdTyH+7ayjySpYlymrLBxK/zcCnGvp2zz2Bo+rWZ4RepT4fO+bbxfsium161K+MZXohUam2WiFauCvBUya0/qYK/3Bw8Pz2Tw7MvDsxhYodu/On5zsH2vCfvCNl6P+/6pR27El/4sHCqfp5qVZ5Fiz6lweP1YhmWF/PiRzzdfG6+FrwlWiLtlo5H6lOY841h74vfDx5r1fsualGPtyw//v8H2hUY4LH7DmvAJ/qEj/iHYfsqP3mD2vdgMX5/XTYa34XI7/P7xlPN44CRJ/AU/jz5HxBAdKQAAAAAADC6eoAMAAAAAupKs/FN0n6OCJ+gAAAAAAJQAT9BDalU7B3ln1jQ0Vt5l2nRcRm7utmeH83+r+6wN97E1nBs1tTGl70kjl3LcyB3fuj3cPhXOf69MZchBXzTy3w3tLfHTc2jGmMLFyrW18oW3G8mMxvZIkywYOacbjHz5LBaMPC9rvc302Lh9lMrIPTanApvKcPmycu+NmhPH/d71xpjCufqV8ZRpt4w8d+uYstY7i+kNxv42kpLNaREz5KDPXRtev/X7xeW/L98Wn+s2Nh03PeamT3w42G7lsh/w6Q+afd/05GcF26186KaR49g0pn5rLNnH//jauOkSrTzpdit8XlRqacemlc8ebp+bD18jp/YIT/ll5W5Ldi6xlfdvrffMuFGzIeXwX1wKf8eNT8RN2dYwpts77MvvMfv+6XF/Yw8sgrU9Gil5s9YrX3joy4LtE7W5YPtZ/5s6tJ5aNs69NOunw7+zFozjIFZaLrZVa8E6xybr+X2X3HsmvN6WU406CJaxMft36pwxddlcI7zN7zkWvh7sNxU5naykVhI+0qu18L449ttvC7YfuXCkfqgXRvdfTkyz1ks8QQcAAAAAoAS4QQcAAAAAoAQIcQ9ptO4Wbm5OCWSEvFkzD7S22KFG1bXhEO11H/xY+AN2dGW09pMfGH7h9m3h9unIkHgrvFdS803PNJYVd3hu+354uov2RS+yP7QmHKqsCWP9liOnnUsJcW9/MjxliDlt2qIRljWW4TS2Qvu3hEP1K3UjrNQa65IdQpbMGdNPbZgOtxvTBqYdUyYjBD2ZDY/JOveabz0lvJyUaRQbN4SPz7H9rbms8vv76bpzLgy2z/7NCcF2a1qxLGPaeMFHg+3Nh5wabE/mwn2v+ZfwOsy/MLwOkrS0Nby/J9aGj51bn35ysL1qTLuVpm6EV1ohkdsXw8f513+yd7B9zAhzlaQ/3/PqYHtjMbz/9vnkh8xlhdxx0onma9ZUbpdevynY/mffe3Ow/c5Twn1su3MqfXABrUb4+rV2r3C47vyv1gXb08Lrf7llj2D7kWtuDrZvmQ1f78Zr8de1LJ8J+dnNewXbKymFmW6YDadePea7bwm2X3bMC+IHFunKRz0v2H7Il94bbD/iq+8Otn/1EcZ3tKRKJTzV5uyyPfVijLSw+6mJ8DVyfCrcvrwcPik/d+2+0eNaNNJe8jI1aafNHf/98PSA1v6uj4fPi+O+89bocf16Lny+7rsx/Bv5LQefEWy/54Hh6+BASpLipz0r+TRrzrmzJW3y3p+6u8sauht059wekv5V0mMlbZP0eu+9nbwFAAAAABhqzrkXSHqJpHtIulrSy733X9jp9VdKWifpc5Ke6703nlbusq9E0rw6j3OXJX1b0vO99+ECR6sMY4j7u9T5w8O+kh4v6Uzn3LH9HRIAAAAADL5Ev5tqrbh/do9z7uGS3iTpBHVuwM+S9Ann3MaV1x8l6R8l/Zmk/SRNSHrnbnb7EO/9mpXl3Sqpq4fGQ/UE3Tk3I+mpko703m+XdJlz7jxJz5b01S4WMSlJLa2XkruG+iaT4XDF1ppweyMJb9o/+uLnzM7/51l/Gmw/8sgjg+3ffe5jgu0Pff8Xgu0XHf00s2+NGxXC99kz2Jz8OhzeVZkKV5ZvG5WLJalyoBF23Ap/xtoeEw+8V7C9ucX+O1R9fTgsUQvGqbHGCK+shCvT6nY71PshZ34l2P7dzY8Ottc714+7M6rdW9tJkpL2+nD7mnCY7UM/ED5uf/AnR4c7qKdUsr3HTLjd6Puos40UD8NtLz3dfK1l5J7U9g2HJS6+7eXB9mS9Uf28ZX99POLrnw+2f+9vHxdsv/p74XMybb/GWl53v2D7RDiaT8lCOGRw/o3h7SRJf3DxF4PtrUo4dLuyRziMeMsrXhVsb47b15bjvhG+Fn7iYU8Otm86LDw7xR98IrwOafvilrWHmq+FnLLlovALGf6MfkgjXHX+nvcMX6du/vtXB9sf87VPB9sfeeXPzL4vPvqpwfbTG/8W1feyEU3+pCvCY0rzjYeFv1vn7wxfc552S7iPjx/4FLOPV/7i4+EXcqpOnnasbTjsnsH2f5kI/w7811+9P9h+1LHh6+DsNjtV6wnf+vdguzXe9QeHQ3y/e++3B9vvMW3MkCLpyf/ziWD7mgfsFx7TbXHXzgOPMH4fSNreuEew/Tm/Cp/HsdftE279nvnaZ/7wicH2x34zvC++8ujwd8yj9w+n+B1Zt8d69B+Fj4VfHPGGYPs6o9r9tvlw31uNWSAkexs2DrhvsH1uMtx3lu/QI44Ofx8/7ttXBNvfe/Thwfbpe/82fcbIrxwcBx9spMYW0Oe55577wLPPPjv0lhu99zemLOK+kn7qvd9xgv2bc+6DK+13SDpV0rne+x9JknPuDEnfd879jff+bhcj59zvSfqApAdK+m9JN1gde+8XnHP/ps6D5F2qJCWP54/hnDtS0ne99+Or2p4p6SXe+27OyBMlXdCr8QEAAAAYaSdJChdoKb8DJP1MkvGn/N5qNBqNRz3qUWM33hi8D3+t9/411mdX0qC/Jun5kr4r6emS3ijpgSs30JdLerP3/oKV91fUCU0/ynt/+U7LGpP0c0nvl/QWScdK+ndJF+/IQV8JcT/Ye3/VykPk90iqe+/Df0VfZaieoEtao07e+Wp3Sgo/1r27/1TnpLlWUtxkjwAAAAAQNinpPurcbwyq6yUdLClcVbLHLrroouqNN95ohc6lPT2XOveIF6tzk16VtCDpyd77HVW610jauuPN3vvEObdN4fvIh0uakXS2974t6YvOudB+/Z5zrr2yjBslPWoXY5Q0fDfos+rkFKy2XlI4bvHubtfg/kULAAAAQHl9u98DyMH1K/8W7uSTT9bJJ4dnXFnNOXeSpPet/Od13vsHSXruyr9HSLpK0sMkfco59+iVsPbQfeQ6he8j95X065Wb8x2uk7RzbszRK0/Qx9R5cv8l59wDQiHzqw1bkbifS0qccwevajtC0k/6NB4AAAAAQEG89xd479es/PuglebDJH3We3+l977tvf+2pEslHbfy+k8k/baAgHPuUEktSb8IdPEbSfs551bfSx+QMp6GpHPUKRZ3yK7GP1Q36N77OUkfV6dy+1rn3OFaSfjv68AAAAAAAP3yXUmPc849QJKcc0dLeoSkHfnl50na7Jz7PefcWklnSrrIeNr9HXWmUDvNOTfmnDtOUrh6d6evmqTN6oTVX72rgQ7VDfqKv1Wn+v+Nkj4v6dXe+3C5bAAAAADAsPuIpA+pky++XZ205td6778kSSv/e6akL6hzH9mQ9HehBa08EX+ipKdI2iLp7yWdH3jrD5xzsyvvOUXSX3jvw1NhrTJUVdwBAAAAABhUw/gEHQAAAACAgcMNOgAAAAAAJcANOgAAAAAAJcANOgAAAAAAJcANOgAAAAAAJVDv9wDKwjm3h6R/lfRYSdskvd57/57+jgpFidn/zrlEnbkPd0yB8A3v/WMLGSj6zjn3AkmnSjpM0qe89yf0d0QoSsy+5zox2pxzE5LeLemRkvaSdL063ysf7evAUIjY/c/1AsBq3KD/zrvU2R77SjpI0n85537mvf9qf4eFgsTu/4d4768qbHQok99IOkvScer88MLoiN33XCdGV12d4+WRkq6V9AhJn3XOXeO9/04/B4ZCZNn/XC8ASOIGXZLknJuR9FRJR3rvt0u6zDl3nqRnS+IGfcix/xHDe/9JSXLOHSFu0EcK+x7d8t7PSXr1qqZvOue+pc6NGjfoQ479D2B3kIPe8QBJFe/9lavafiTp0D6NB8XKsv+/4py72Tn3Wefcg3o7PAADiusEJP32D8FHSfpJv8eC4nW5/7leAJDEDfoOa9TJO17tTklr+zAWFC92/x8j6T7qhMJfJumLzrl1vRocgIF0jLhOQJJzriLpA5K+J+mLfR4OCtbl/j9GXC8ArCDEvWNW0s4XwvWStvdhLChe1P733n995f8uSzrdOfdMdcLWvtCzEQIYKFwnIP325uxfJN1L0p9675NdfARDpNv9z/UCwGo8Qe/4uaTEOXfwqrYjRCjaqNjd/d+WVMl9VACGCdeJEbNyc/ZuSQ+W9NiVvGSMiN3c/1wvgBHGE3R1ink45z4u6Uzn3GZJ91VnKp2n9XVgKETM/l/JC5uQdIWkcUmnSZoSRV9GhnOurs61sy6p6pyblNTy3jf6OzL0Wrf7nusEVrxL0sMkPdJ7v3MaFYZfV/uf6wWAnfEE/Xf+Vp35J2+U9HlJr/bef6W/Q0KBzP3vnJt1zv2flffdU9JHJW1VZ17Th0l6tPf+zuKHjD45XdKCpFepU/1/QdL7+zoiFMXc91wnsJpz7t6Sni/pEEm/Wjk+Zp1z/9DnoaEAu9r/XC8ApKkkCelQAAAAAAD0G0/QAQAAAAAoAW7QAQAAAAAoAW7QAQAAAAAoAW7QAQAAAAAoAW7QAQAAAAAoAW7QAQAAAAAoAW7QAQAAAAAoAW7QAQAwOOde45z7Zr/HAQAARkMlSZJ+jwEAgMI553b1BXispEsljXvv7yhgSAAAYMTV+z0AAAD6ZJ9V///lkh4q6Umr2u7w3i8XOyQAADDKuEEHAIwk7/1NO/6/c25O0vLqtpX210g6znv/hyv//TVJ35e0h6QTJN0u6fmSrpB0nqSHS/qRpBO999etWs4LJb1Y0iZJP5X0Mu/913qzZgAAYFCRgw4AQJy/kvQTSQ+W9FlJ50s6R9I/SXqIpIqkt+94s3Pu2ZJepM6N/KGSPizpc865+xQ6agAAUHrcoAMAEOdb3vt3eO9/IelMSRsl/Zf3/jPe+6sk/bOkY1a9/3RJL/Lef8F7f7X3/p2Svinp5KIHDgAAyo0QdwAA4vx41f+/eeV/f7pT20bnXE3SlKQDJV20U1G6CUk39HSUAABg4HCDDgBAnMaO/+O9T5xzd2mTtONGvCJpZuX/n6i73sRL0vZeDRAAAAwmbtABAOidWyTdJOkA7/1/9HswAACg3LhBBwCgR1aesL9B0pnOuVlJ/y1pg6TjJH3Pe/+Vvg4QAACUCkXiAADooZWicKet/PszSZ+WdLSkX/dzXAAAoHwqSZLs+l0AAAAAAKCneIIOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJcIMOAAAAAEAJ/H/B//wQ7BvmOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1280x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_mel(mel_generated)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ground Truth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "key = 'BASIC5000_0005'\n",
    "wav_005 = load(f'/diskB/6/Datasets/VoiceData/jsut_ver1.1/basic5000/wav/{key}.wav', sample_rate=24000)\n",
    "mel = melspectrogram(wav_005, sample_rate=24000, n_fft=2048, hop_length=300, power=2.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_mel(mel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}